ORCID Profile
0000-0003-4864-7033
Current Organisations
Wageningen University & Research
,
Wageningen University
,
University of Adelaide
,
Walter and Eliza Hall Institute of Medical Research
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Publisher: Springer Science and Business Media LLC
Date: 14-04-2021
DOI: 10.1186/S13073-021-00871-5
Abstract: Aberrant changes in epigenetic mechanisms such as histone modifications play an important role in cancer progression. PRMT1 which triggers asymmetric dimethylation of histone H4 on arginine 3 (H4R3me2a) is upregulated in human colorectal cancer (CRC) and is essential for cell proliferation. However, how this dysregulated modification might contribute to malignant transitions of CRC remains poorly understood. In this study, we integrated biochemical assays including protein interaction studies and chromatin immunoprecipitation (ChIP), cellular analysis including cell viability, proliferation, colony formation, and migration assays, clinical s le analysis, microarray experiments, and ChIP-Seq data to investigate the potential genomic recognition pattern of H4R3me2s in CRC cells and its effect on CRC progression. We show that PRMT1 and SMARCA4, an ATPase subunit of the SWI/SNF chromatin remodeling complex, act cooperatively to promote colorectal cancer (CRC) progression. We find that SMARCA4 is a novel effector molecule of PRMT1-mediated H4R3me2a. Mechanistically, we show that H4R3me2a directly recruited SMARCA4 to promote the proliferative, colony-formative, and migratory abilities of CRC cells by enhancing EGFR signaling. We found that EGFR and TNS4 were major direct downstream transcriptional targets of PRMT1 and SMARCA4 in colon cells, and acted in a PRMT1 methyltransferase activity-dependent manner to promote CRC cell proliferation. In vivo, knockdown or inhibition of PRMT1 profoundly attenuated the growth of CRC cells in the C57BL/6 J-Apc Min/+ CRC mice model. Importantly, elevated expression of PRMT1 or SMARCA4 in CRC patients were positively correlated with expression of EGFR and TNS4, and CRC patients had shorter overall survival. These findings reveal a critical interplay between epigenetic and transcriptional control during CRC progression, suggesting that SMARCA4 is a novel key epigenetic modulator of CRC. Our findings thus highlight PRMT1/SMARCA4 inhibition as a potential therapeutic intervention strategy for CRC. PRMT1-mediated H4R3me2a recruits SMARCA4, which promotes colorectal cancer progression by enhancing EGFR signaling.
Publisher: Springer Science and Business Media LLC
Date: 10-11-2015
Publisher: Springer Science and Business Media LLC
Date: 04-10-2021
Publisher: Springer Science and Business Media LLC
Date: 21-06-2021
DOI: 10.1186/S13073-021-00920-Z
Abstract: Medulloblastoma (MB) is the most common malignant paediatric brain tumour and a leading cause of cancer-related mortality and morbidity. Existing treatment protocols are aggressive in nature resulting in significant neurological, intellectual and physical disabilities for the children undergoing treatment. Thus, there is an urgent need for improved, targeted therapies that minimize these harmful side effects. We identified candidate drugs for MB using a network-based systems-pharmacogenomics approach: based on results from a functional genomics screen, we identified a network of interactions implicated in human MB growth regulation. We then integrated drugs and their known mechanisms of action, along with gene expression data from a large collection of medulloblastoma patients to identify drugs with potential to treat MB. Our analyses identified drugs targeting CDK4, CDK6 and AURKA as strong candidates for MB all of these genes are well validated as drug targets in other tumour types. We also identified non-WNT MB as a novel indication for drugs targeting TUBB, CAD, SNRPA, SLC1A5, PTPRS, P4HB and CHEK2. Based upon these analyses, we subsequently demonstrated that one of these drugs, the new microtubule stabilizing agent, ixabepilone, blocked tumour growth in vivo in mice bearing patient-derived xenograft tumours of the Sonic Hedgehog and Group 3 subtype, providing the first demonstration of its efficacy in MB. Our findings confirm that this data-driven systems pharmacogenomics strategy is a powerful approach for the discovery and validation of novel therapeutic candidates relevant to MB treatment, and along with data validating ixabepilone in PDX models of the two most aggressive subtypes of medulloblastoma, we present the network analysis framework as a resource for the field.
Publisher: Life Science Alliance, LLC
Date: 03-08-2023
Abstract: Epithelial–mesenchymal transition is essential for tissue patterning and organization. It involves both regulation of cell motility and alterations in the composition and organization of the ECM—a complex environment of proteoglycans and fibrous proteins essential for tissue homeostasis, signaling in response to chemical and biomechanical stimuli, and is often dysregulated under conditions such as cancer, fibrosis, and chronic wounds. Here, we demonstrate that basonuclin-2 (BNC2), a mesenchymal-expressed gene, that is, strongly associated with cancer and developmental defects across genome-wide association studies, is a novel regulator of ECM composition and degradation. We find that at endogenous levels, BNC2 controls the expression of specific collagens, matrix metalloproteases, and other matrisomal components in breast cancer cells, and in fibroblasts that are primarily responsible for the production and processing of the ECM within the tumour microenvironment. In so doing, BNC2 modulates the motile and invasive properties of cancers, which likely explains the association of high BNC2 expression with increasing cancer grade and poor patient prognosis.
Publisher: Impact Journals, LLC
Date: 16-08-2016
Publisher: Elsevier BV
Date: 03-2020
DOI: 10.1016/J.SCITOTENV.2019.136281
Abstract: Urban rivers often function as sinks for various contaminants potentially placing the benthic communities at risk of exposure. We performed a comprehensive biological survey of the benthic macroinvertebrate and bacterial community compositions in six rivers from the suburb to the central urban area of Guangzhou city (South China), and evaluated their correlations with emerging organic contaminants, heavy metals and nutrients. Overall, the benthic macroinvertebrate community shifted from molluscs to oligochaete from the suburban to the central urban rivers that receive treated and untreated sewage. An exception was the site in the Sha River where chironomids were most abundant. The differences in macroinvertebrate community assemblages were significantly associated with chromium, total phosphorus, galaxolide, triclosan and sand content in the sediment. There was no significant difference in benthic macroinvertebrate composition between the dry and wet season. As assessed by double constrained ordination, sexual reproduction was the only trait of benthic macroinvertebrates that showed a significant correlation with pollution variables, as it was significantly positively correlated with chromium and total phosphorus. This suggests that r-strategist occurs in polluted s ling sites. The benthic bacterial community composition showed a significant difference between seasons and among the Liuxi River, Zhujiang River and central urban rivers. The differences in community composition of the benthic bacteria were significantly correlated with galaxolide, total phosphorus, lead and triclosan. These results suggest that input of treated and untreated sewage significantly altered the benthic macroinvertebrate and bacterial community compositions in urban rivers.
Publisher: PeerJ
Date: 25-05-2021
DOI: 10.7717/PEERJ.11298
Abstract: Protein phosphorylation is one of the best known post-translational mechanisms playing a key role in the regulation of cellular processes. Over 100,000 distinct phosphorylation sites have been discovered through constant improvement of mass spectrometry based phosphoproteomics in the last decade. However, data saturation is occurring and the bottleneck of assigning biologically relevant functionality to phosphosites needs to be addressed. There has been finite success in using data-driven approaches to reveal phosphosite functionality due to a range of limitations. The alternate, more suitable approach is making use of prior knowledge from literature-derived databases. Here, we analysed seven widely used databases to shed light on their suitability to provide functional insights into phosphoproteomics data. We first determined the global coverage of each database at both the protein and phosphosite level. We also determined how consistent each database was in its phosphorylation annotations compared to a global standard. Finally, we looked in detail at the coverage of each database over six experimental datasets. Our analysis highlights the relative strengths and weaknesses of each database, providing a guide in how each can be best used to identify biological mechanisms in phosphoproteomic data.
Publisher: Wiley
Date: 2006
DOI: 10.1002/DVDY.20740
Abstract: The term "secretome" has been defined as a set of secreted proteins (Grimmond et al. [2003] Genome Res 13:1350-1359). The term "secreted protein" encompasses all proteins exported from the cell including growth factors, extracellular proteinases, morphogens, and extracellular matrix molecules. Defining the genes encoding secreted proteins that change in expression during organogenesis, the dynamic secretome, is likely to point to key drivers of morphogenesis. Such secreted proteins are involved in the reciprocal interactions between the ureteric bud (UB) and the metanephric mesenchyme (MM) that occur during organogenesis of the metanephros. Some key metanephric secreted proteins have been identified, but many remain to be determined. In this study, microarray expression profiling of E10.5, E11.5, and E13.5 kidney and consensus bioinformatic analysis were used to define a dynamic secretome of early metanephric development. In situ hybridisation was used to confirm microarray results and clarify spatial expression patterns for these genes. Forty-one secreted factors were dynamically expressed between the E10.5 and E13.5 timeframe profiled, and 25 of these factors had not previously been implicated in kidney development. A text-based anatomical ontology was used to spatially annotate the expression pattern of these genes in cultured metanephric explants.
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22526523
Abstract: Sox9 immunostaining pattern in a variety of Shh-MB genetic mouse models
Publisher: Elsevier BV
Date: 09-2018
DOI: 10.1016/J.AQUATOX.2018.07.008
Abstract: Triclosan (TCS) is an antibacterial agent that is commonly used in personal care products. Because of its sediment-binding properties, TCS exposure presents a potential threat to sediment-dwelling aquatic organisms. Currently our knowledge of the fate and effects of sediment-associated TCS in aquatic systems is limited. To understand the impact of sediment-associated TCS, we used microcosms to assess effects of TCS exposure on a erse range of organisms selected to mimic a subtropical community, with an exposure period of 28 days. We included the oligochaete freshwater worm Limnodrilus hoffmeisteri to evaluate the interaction between sediment-associated TCS and sediment-dwelling organisms, including potential loss of TCS from the sediment due to biological activity and bioaccumulation. Benthic macroinvertebrate presence significantly increased the TCS levels from 0.013 ± 0.007 μg/L to 0.613 ± 0.030 μg/L in the overlying water through biological activity, posing a potential additional risk to pelagic species, but it did not result in a significant reduction of the sediment concentration. Furthermore, worms accumulated TCS with estimated Biota-Sediment-Accumulation-Factors (BSAFs) ranging between 0.38-3.55. Other than for algae, TCS at environmental concentrations did not affect the survival of the introduced organisms, including the L. hoffmeisteri. Our results demonstrate that, although TCS at currently detected maximum concentration may not have observable toxic effects on the benthic macroinvertebrates in the short term, it can lead to bioaccumulation in worms.
Publisher: American Association for Cancer Research (AACR)
Date: 10-2017
DOI: 10.1158/1078-0432.CCR-16-2943
Abstract: Purpose: Bioinformatics analysis followed by in vivo studies in patient-derived xenograft (PDX) models were used to identify and validate CDK 4/6 inhibition as an effective therapeutic strategy for medulloblastoma, particularly group 3 MYC- lified tumors that have the worst clinical prognosis. Experimental Design: A protein interaction network derived from a Sleeping Beauty mutagenesis model of medulloblastoma was used to identify potential novel therapeutic targets. The top hit from this analysis was validated in vivo using PDX models of medulloblastoma implanted subcutaneously in the flank and orthotopically in the cerebellum of mice. Results: Informatics analysis identified the CDK4/6/CYCLIN D/RB pathway as a novel “druggable” pathway for multiple subgroups of medulloblastoma. Palbociclib, a highly specific inhibitor of CDK4/6, was found to inhibit RB phosphorylation and cause G1 arrest in PDX models of medulloblastoma. The drug caused rapid regression of Sonic hedgehog (SHH) and MYC- lified group 3 medulloblastoma subcutaneous tumors and provided a highly significant survival advantage to mice bearing MYC- lified intracranial tumors. Conclusions: Inhibition of CDK4/6 is potentially a highly effective strategy for the treatment of SHH and MYC- lified group 3 medulloblastoma. Clin Cancer Res 23(19) 5802–13. ©2017 AACR.
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22526517
Abstract: GFAPCre:Sox9lox/lox mice are not viable
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22526514
Abstract: Medulloblastoma and granule cell precursor Gli1 target genes
Publisher: Rockefeller University Press
Date: 27-03-2020
Publisher: Frontiers Media SA
Date: 25-09-2023
Publisher: Cold Spring Harbor Laboratory
Date: 08-12-2017
DOI: 10.1101/231217
Abstract: Gene set scoring provides a useful approach for quantifying concordance between s le transcriptomes and selected molecular signatures. Most methods use information from all s les to score an in idual s le, leading to unstable scores in small data sets and introducing biases from s le composition across a data set (e.g. varying numbers of s les for different cancer subtypes). To address these issues we have developed a truly single s le scoring method, and associated R/Bioconductor package singscore . We have developed a rank-based single s le scoring method, implemented as a Bioconductor package. We use multiple cancer data sets to compare it against widely-used scoring methods, including GSVA, z-scores, PLAGE, and ssGSEA. Our approach does not depend upon background s les and thus the scores are stable regardless of the composition and number of s les in the gene expression data set. In contrast, scores obtained by GSVA, z -score, PLAGE and ssGSEA can be unstable when less data are available ( n s les 25). We show that the computational time for singscore is faster than current implementations of GSVA and ssGSEA, and is comparable with that of z-score and PLAGE. The singscore package also produces visualisations and interactive plots that enable exploration of molecular phenotypes. The single s le scoring method described here is independent of s le composition in gene expression data and thus it provides stable scores that are less likely to be influenced by unwanted variation across s les. These scores can be used for dimensional reduction of transcriptomic data and the phenotypic landscapes obtained by scoring s les against multiple molecular signatures may provide insights for s le stratification.
Publisher: Cold Spring Harbor Laboratory
Date: 15-03-2023
DOI: 10.1101/2023.03.15.532733
Abstract: Spatial molecular technologies have revolutionised the study of disease microenvironments by providing spatial context to tissue heterogeneity. Recent spatial technologies are increasing the throughput and spatial resolution of measurements, resulting in larger datasets. The added spatial dimension and volume of measurements poses an analytics challenge that has, in the short-term, been addressed by adopting methods designed for the analysis of single-cell RNA-seq data. Though these methods work well in some cases, not all necessarily translate appropriately to spatial technologies. A common assumption is that total sequencing depth, also known as library size, represents technical variation in single-cell RNA-seq technologies, and this is often normalised out during analysis. Through analysis of several different spatial datasets, we noted that this assumption does not necessarily hold in spatial molecular data. To formally assess this, we explore the relationship between library size and independently annotated spatial regions, across 23 s les from 4 different spatial technologies with varying throughput and spatial resolution. We found that library size confounded biology across all technologies, regardless of the tissue being investigated. Statistical modelling of binned total transcripts shows that tissue region is strongly associated with library size across all technologies, even after accounting for cell density of the bins. Through a benchmarking experiment, we show that normalising out library size leads to sub-optimal spatial domain identification using common graph-based clustering algorithms. On average, better clustering was achieved when library size effects were not normalised out explicitly, especially with data from the newer sub-cellular localised technologies. Taking these results into consideration, we recommend that spatial data should not be specifically corrected for library size prior to analysis unless strongly motivated. We also emphasise that spatial data are different to single-cell RNA-seq and care should be taken when adopting algorithms designed for single cell data.
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22526529.V1
Abstract: S3. Sox9 expression quantification
Publisher: Public Library of Science (PLoS)
Date: 28-04-2006
Publisher: American Association for the Advancement of Science (AAAS)
Date: 09-07-2021
Abstract: Optical barcoding reveals enhanced TNFα activation and polyclonality in lung, but not liver, metastases from breast cancer.
Publisher: The Company of Biologists
Date: 2020
DOI: 10.1242/JCS.235622
Abstract: Cell extrusion is a morphogenetic process that is implicated in epithelial homeostasis and elicited by stimuli ranging from apoptosis to oncogenic transformation. To explore if the morphogenetic transcription factor, Snail (SNAI1), induces extrusion, we inducibly expressed a stabilized Snail6SA transgene in confluent MCF-7 monolayers. When expressed in small clusters (& cells) within otherwise wild-type confluent monolayers, Snail6SA expression induced apical cell extrusion. In contrast, larger clusters or homogenous cultures of Snail6SA cells did not show enhanced apical extrusion, but eventually displayed sporadic basal delamination. Transcriptomic profiling revealed that Snail6SA did not substantively alter the balance of epithelial: mesenchymal genes. However, we identified a transcriptional network that led to upregulated RhoA signalling and cortical contractility in Snail6SA expressing cells. Enhanced contractility was necessary, but not sufficient, to drive extrusion, suggesting that it collaborates with other factors. Indeed, we found that the transcriptional downregulation of cell-matrix adhesion cooperates with contractility to mediate basal delamination. This provides a pathway for Snail to influence epithelial morphogenesis independently of classic Epithelial to Mesenchymal Transition.
Publisher: Oxford University Press (OUP)
Date: 23-07-2020
Abstract: Methylation is a common posttranslational modification of arginine and lysine in eukaryotic proteins. Methylproteomes are best characterized for higher eukaryotes, where they are functionally expanded and evolved complex regulation. However, this is not the case for protist species evolved from the earliest eukaryotic lineages. Here, we integrated bioinformatic, proteomic, and drug-screening data sets to comprehensively explore the methylproteome of Giardia duodenalis—a deeply branching parasitic protist. We demonstrate that Giardia and related diplomonads lack arginine-methyltransferases and have remodeled conserved RGG/RG motifs targeted by these enzymes. We also provide experimental evidence for methylarginine absence in proteomes of Giardia but readily detect methyllysine. We bioinformatically infer 11 lysine-methyltransferases in Giardia, including highly erged Su(var)3-9, Enhancer-of-zeste and Trithorax proteins with reduced domain architectures, and novel annotations demonstrating conserved methyllysine regulation of eukaryotic elongation factor 1 alpha. Using mass spectrometry, we identify more than 200 methyllysine sites in Giardia, including in species-specific gene families involved in cytoskeletal regulation, enriched in coiled-coil features. Finally, we use known methylation inhibitors to show that methylation plays key roles in replication and cyst formation in this parasite. This study highlights reduced methylation enzymes, sites, and functions early in eukaryote evolution, including absent methylarginine networks in the Diplomonadida. These results challenge the view that arginine methylation is eukaryote conserved and demonstrate that functional compensation of methylarginine was possible preceding expansion and ersification of these key networks in higher eukaryotes.
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22526535.V1
Abstract: S1. Sox 9 and Sox 2 immunoreactivity in the developing cerebellum
Publisher: EMBO
Date: 13-06-2022
Publisher: F1000 Research Ltd
Date: 03-06-2019
DOI: 10.12688/F1000RESEARCH.19236.1
Abstract: Advances in RNA sequencing (RNA-seq) technologies that measure the transcriptome of biological s les have revolutionised our ability to understand transcriptional regulatory programs that underpin diseases such as cancer. We recently published singscore - a single s le, rank-based gene set scoring method which quantifies how concordant the transcriptional profile of in idual s les are relative to specific gene sets of interest. Here we demonstrate the application of singscore to investigate transcriptional profiles associated with specific mutations or genetic lesions in acute myeloid leukemia. Using matched genomic and transcriptomic data available through the TCGA we show that scoring of appropriate signatures can distinguish s les with corresponding mutations, reflecting the ability of these mutations to drive aberrant transcriptional programs involved in leukemogenesis. We believe the singscore method is particularly useful for studying heterogeneity within a specific subsets of cancers, and as demonstrated, we show the ability of singscore to identify where alternative mutations appear to drive similar transcriptional programs.
Publisher: F1000 Research Ltd
Date: 14-10-2019
DOI: 10.12688/F1000RESEARCH.19236.3
Abstract: Advances in RNA sequencing (RNA-seq) technologies that measure the transcriptome of biological s les have revolutionised our ability to understand transcriptional regulatory programs that underpin diseases such as cancer. We recently published singscore - a single s le, rank-based gene set scoring method which quantifies how concordant the transcriptional profile of in idual s les are relative to specific gene sets of interest. Here we demonstrate the application of singscore to investigate transcriptional profiles associated with specific mutations or genetic lesions in acute myeloid leukemia. Using matched genomic and transcriptomic data available through the TCGA we show that scoring of appropriate signatures can distinguish s les with corresponding mutations, reflecting the ability of these mutations to drive aberrant transcriptional programs involved in leukemogenesis. We believe the singscore method is particularly useful for studying heterogeneity within a specific subsets of cancers, and as demonstrated, we show the ability of singscore to identify where alternative mutations appear to drive similar transcriptional programs.
Publisher: Cold Spring Harbor Laboratory
Date: 05-05-2020
DOI: 10.1101/2020.05.04.077859
Abstract: Transcriptomic signatures are useful in defining the molecular phenotypes of cells, tissues, and patient s les. Their most successful and widespread clinical application is the stratification of breast cancer patients into molecular (PAM50) subtypes. In most cases, gene expression signatures are developed using transcriptome-wide measurements, thus methods that match signatures to s les typically require a similar degree of measurements. The cost and relatively large amounts of fresh starting material required for whole-transcriptome sequencing has limited clinical applications, and accordingly thousands of existing gene signatures are unexplored in a clinical context. Genes in a molecular signature can provide information about molecular phenotypes and their underlying transcriptional programs from tissue s les, however determining the transcriptional state of these genes typically requires the measurement of all genes across multiple s les to allow for comparison. An efficient assay and scoring method should quantify the relative abundance of signature genes with a minimal number of additional measurements. We identified genes with stable expression across a range of abundances, and with a preserved relative ordering across large numbers (thousands) of s les, allowing signature scoring, and supporting general data normalisation for transcriptomic data. Based on singscore, we have developed a new method, stingscore , which quantifies and summarises relative expression levels of signature genes from in idual s les through the inclusion of these “stably-expressed genes”. We show that our proposed list of stable genes has better stability across cancer and normal tissue data than previously proposed stable or housekeeping genes. Additionally, we show that signature scores computed from whole-transcriptome data are comparable to those calculated using only values for signature genes and our panel of stable genes. This new approach to gene expression signature analysis may facilitate the development of panel-type tests for gene expression signatures, thus supporting clinical translation of the powerful insights gained from cancer transcriptomic studies.
Publisher: F1000 Research Ltd
Date: 15-08-2019
DOI: 10.12688/F1000RESEARCH.19236.2
Abstract: Advances in RNA sequencing (RNA-seq) technologies that measure the transcriptome of biological s les have revolutionised our ability to understand transcriptional regulatory programs that underpin diseases such as cancer. We recently published singscore - a single s le, rank-based gene set scoring method which quantifies how concordant the transcriptional profile of in idual s les are relative to specific gene sets of interest. Here we demonstrate the application of singscore to investigate transcriptional profiles associated with specific mutations or genetic lesions in acute myeloid leukemia. Using matched genomic and transcriptomic data available through the TCGA we show that scoring of appropriate signatures can distinguish s les with corresponding mutations, reflecting the ability of these mutations to drive aberrant transcriptional programs involved in leukemogenesis. We believe the singscore method is particularly useful for studying heterogeneity within a specific subsets of cancers, and as demonstrated, we show the ability of singscore to identify where alternative mutations appear to drive similar transcriptional programs.
Publisher: ClinTransMed, AB
Date: 2012
Publisher: Frontiers Media SA
Date: 31-01-2020
Publisher: American Society of Hematology
Date: 20-08-2020
Abstract: Modulators of epithelial-to-mesenchymal transition (EMT) have recently emerged as novel players in the field of leukemia biology. The mechanisms by which EMT modulators contribute to leukemia pathogenesis, however, remain to be elucidated. Here we show that overexpression of SNAI1, a key modulator of EMT, is a pathologically relevant event in human acute myeloid leukemia (AML) that contributes to impaired differentiation, enhanced self-renewal, and proliferation of immature myeloid cells. We demonstrate that ectopic expression of Snai1 in hematopoietic cells predisposes mice to AML development. This effect is mediated by interaction with the histone demethylase KDM1A/LSD1. Our data shed new light on the role of SNAI1 in leukemia development and identify a novel mechanism of LSD1 corruption in cancer. This is particularly pertinent given the current interest surrounding the use of LSD1 inhibitors in the treatment of multiple different malignancies, including AML.
Publisher: Mary Ann Liebert Inc
Date: 15-06-2016
Publisher: Elsevier BV
Date: 09-2020
Publisher: Oxford University Press (OUP)
Date: 14-08-2013
DOI: 10.1093/BIB/BBT058
Publisher: American Chemical Society (ACS)
Date: 02-09-2016
DOI: 10.1021/ACS.JPROTEOME.5B01035
Abstract: Lipid rafts are dynamic membrane microdomains that orchestrate molecular interactions and are implicated in cancer development. To understand the functions of lipid rafts in cancer, we performed an integrated analysis of quantitative lipid raft proteomics data sets modeling progression in breast cancer, melanoma, and renal cell carcinoma. This analysis revealed that cancer development is associated with increased membrane raft-cytoskeleton interactions, with ∼40% of elevated lipid raft proteins being cytoskeletal components. Previous studies suggest a potential functional role for the raft-cytoskeleton in the action of the putative tumor suppressors PTRF/Cavin-1 and Merlin. To extend the observation, we examined lipid raft proteome modulation by an unrelated tumor suppressor opioid binding protein cell-adhesion molecule (OPCML) in ovarian cancer SKOV3 cells. In agreement with the other model systems, quantitative proteomics revealed that 39% of OPCML-depleted lipid raft proteins are cytoskeletal components, with microfilaments and intermediate filaments specifically down-regulated. Furthermore, protein-protein interaction network and simulation analysis showed significantly higher interactions among cancer raft proteins compared with general human raft proteins. Collectively, these results suggest increased cytoskeleton-mediated stabilization of lipid raft domains with greater molecular interactions as a common, functional, and reversible feature of cancer cells.
Publisher: Oxford University Press (OUP)
Date: 30-09-2020
DOI: 10.1093/NAR/GKAA802
Abstract: Gene expression signatures have been critical in defining the molecular phenotypes of cells, tissues, and patient s les. Their most notable and widespread clinical application is stratification of breast cancer patients into molecular (PAM50) subtypes. The cost and relatively large amounts of fresh starting material required for whole-transcriptome sequencing has limited clinical application of thousands of existing gene signatures captured in repositories such as the Molecular Signature Database. We identified genes with stable expression across a range of abundances, and with a preserved relative ordering across thousands of s les, allowing signature scoring and supporting general data normalisation for transcriptomic data. Our new method, stingscore, quantifies and summarises relative expression levels of signature genes from in idual s les through the inclusion of these ‘stably-expressed genes’. We show that our list of stable genes has better stability across cancer and normal tissue data than previously proposed gene sets. Additionally, we show that signature scores computed from targeted transcript measurements using stingscore can predict docetaxel response in breast cancer patients. This new approach to gene expression signature analysis will facilitate the development of panel-type tests for gene expression signatures, thus supporting clinical translation of the powerful insights gained from cancer transcriptomic studies.
Publisher: S. Karger AG
Date: 26-04-2022
DOI: 10.1159/000515289
Abstract: The epithelial-mesenchymal (E/M) hybrid state has emerged as an important mediator of elements of cancer progression, facilitated by epithelial mesenchymal plasticity (EMP). We review here evidence for the presence, prognostic significance, and therapeutic potential of the E/M hybrid state in carcinoma. We further assess modelling predictions and validation studies to demonstrate stabilised E/M hybrid states along the spectrum of EMP, as well as computational approaches for characterising and quantifying EMP phenotypes, with particular attention to the emerging realm of single-cell approaches through RNA sequencing and protein-based techniques.
Publisher: Wiley
Date: 09-2023
DOI: 10.1002/CTM2.1356
Publisher: Elsevier BV
Date: 10-2020
Publisher: Springer Science and Business Media LLC
Date: 24-11-2014
Publisher: Springer Science and Business Media LLC
Date: 20-07-2020
DOI: 10.1186/S12302-020-00375-W
Abstract: The Partnership for Chemicals Risk Assessment (PARC) is currently under development as a joint research and innovation programme to strengthen the scientific basis for chemical risk assessment in the EU. The plan is to bring chemical risk assessors and managers together with scientists to accelerate method development and the production of necessary data and knowledge, and to facilitate the transition to next-generation evidence-based risk assessment, a non-toxic environment and the European Green Deal. The NORMAN Network is an independent, well-established and competent network of more than 80 organisations in the field of emerging substances and has enormous potential to contribute to the implementation of the PARC partnership. NORMAN stands ready to provide expert advice to PARC, drawing on its long experience in the development, harmonisation and testing of advanced tools in relation to chemicals of emerging concern and in support of a European Early Warning System to unravel the risks of contaminants of emerging concern (CECs) and close the gap between research and innovation and regulatory processes. In this commentary we highlight the tools developed by NORMAN that we consider most relevant to supporting the PARC initiative: (i) joint data space and cutting-edge research tools for risk assessment of contaminants of emerging concern (ii) collaborative European framework to improve data quality and comparability (iii) advanced data analysis tools for a European early warning system and (iv) support to national and European chemical risk assessment thanks to harnessing, combining and sharing evidence and expertise on CECs. By combining the extensive knowledge and experience of the NORMAN network with the financial and policy-related strengths of the PARC initiative, a large step towards the goal of a non-toxic environment can be taken.
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22526532.V1
Abstract: S2. Math1CrePtchlox/Ptchlox Math1 GFP mice display GFP expression in the majority of tumour cells
Publisher: Cold Spring Harbor Laboratory
Date: 06-2003
DOI: 10.1101/GR.978703
Abstract: A general overview of the protein sequence set for the mouse transcriptome produced during the FANTOM2 sequencing project is presented here. We applied different algorithms to characterize protein sequences derived from a nonredundant representative protein set (RPS) and a variant protein set (VPS) of the mouse transcriptome. The functional characterization and assignment of Gene Ontology terms was done by analysis of the proteome using InterPro. The Superfamily database analyses gave a detailed structural classification according to SCOP and provide additional evidence for the functional characterization of the proteome data. The MDS database analysis revealed new domains which are not presented in existing protein domain databases. Thus the transcriptome gives us a unique source of data for the detection of new functional groups. The data obtained for the RPS and VPS sets facilitated the comparison of different patterns of protein expression. A comparison of other existing mouse and human protein sequence sets (e.g., the International Protein Index) demonstrates the common patterns in mammalian proteomes. The analysis of the membrane organization within the transcriptome of multiple eukaryotes provides valuable statistics about the distribution of secretory and transmembrane proteins
Publisher: American Chemical Society (ACS)
Date: 30-03-2006
DOI: 10.1021/PR050397B
Abstract: In this study, we propose a novel method to predict the solvent accessible surface areas of transmembrane residues. For both transmembrane alpha-helix and beta-barrel residues, the correlation coefficients between the predicted and observed accessible surface areas are around 0.65. On the basis of predicted accessible surface areas, residues exposed to the lipid environment or buried inside a protein can be identified by using certain cutoff thresholds. We have extensively examined our approach based on different definitions of accessible surface areas and a variety of sets of control parameters. Given that experimentally determining the structures of membrane proteins is very difficult and membrane proteins are actually abundant in nature, our approach is useful for theoretically modeling membrane protein tertiary structures, particularly for modeling the assembly of transmembrane domains. This approach can be used to annotate the membrane proteins in proteomes to provide extra structural and functional information.
Publisher: American Chemical Society (ACS)
Date: 21-04-2010
DOI: 10.1021/CI900461J
Abstract: A wide range of data on sequences, structures, pathways, and networks of genes and gene products is available for hypothesis testing and discovery in biological and biomedical research. However, data describing the physical, chemical, and biological properties of small molecules have not been well-integrated with these resources. Semantically rich representations of chemical data, combined with Semantic Web technologies, have the potential to enable the integration of small molecule and biomolecular data resources, expanding the scope and power of biomedical and pharmacological research. We employed the Semantic Web technologies Resource Description Framework (RDF) and Web Ontology Language (OWL) to generate a Small Molecule Ontology (SMO) that represents concepts and provides unique identifiers for biologically relevant properties of small molecules and their interactions with biomolecules, such as proteins. We instanced SMO using data from three public data sources, i.e., DrugBank, PubChem and UniProt, and converted to RDF triples. Evaluation of SMO by use of predetermined competency questions implemented as SPARQL queries demonstrated that data from chemical and biomolecular data sources were effectively represented and that useful knowledge can be extracted. These results illustrate the potential of Semantic Web technologies in chemical, biological, and pharmacological research and in drug discovery.
Publisher: Springer Science and Business Media LLC
Date: 26-02-2011
DOI: 10.1007/S12672-011-0069-3
Abstract: Granulosa cell tumors of the ovary (GCT) represent ~5% of malignant ovarian tumors. The adult form is defined by a mutation in the FOXL2 gene. GCT exhibit many of the features of normal proliferating granulosa cells. We have profiled the expression of the 48 human nuclear receptors (NR) by quantitative RT-PCR in a panel of GCT and in two GCT-derived cell lines, COV434 and KGN. The highest level of expression is seen for COUP-TF2 with abundant expression of PPARγ, SF-1, and TR-α. Estrogen receptor (ER)-β is the most abundant of the steroid receptors with relatively high expression also of AR, ER-α, and PR. The concordance of expression for each NR across the tumors is remarkably high with same discordance between the cell lines and the tumors, particularly the COV434 line. No significant differences were observed with respect to tumor stage for NR expression. These findings provide a full profile of NR expression in GCT which will enable full characterization of their roles and potential as therapeutic targets.
Publisher: Frontiers Media SA
Date: 03-04-2023
DOI: 10.3389/FIMMU.2023.1135489
Abstract: Mucosal head and neck squamous cell carcinoma (HNSCC) are the seventh most common cancer, with approximately 50% of patients living beyond 5 years. Immune checkpoint inhibitors (ICIs) have shown promising results in patients with recurrent or metastatic (R/M) disease, however, only a subset of patients benefit from immunotherapy. Studies have implicated the tumor microenvironment (TME) of HNSCC as a major factor in therapy response, highlighting the need to better understand the TME, particularly by spatially resolved means to determine cellular and molecular components. Here, we employed targeted spatial profiling of proteins on a cohort of pre-treatment tissues from patients with R/M disease to identify novel biomarkers of response within the tumor and stromal margins. By grouping patient outcome categories into response or non-response, based on Response Evaluation Criteria in Solid Tumors (RECIST) we show that immune checkpoint molecules, including PD-L1, B7-H3, and VISTA, were differentially expressed. Patient responders possessed significantly higher tumor expression of PD-L1 and B7-H3, but lower expression of VISTA. Analysis of response subgroups indicated that tumor necrosis factor receptor (TNFR) superfamily members including OX40L, CD27, 4-1BB, CD40, and CD95/Fas, were associated with immunotherapy outcome. CD40 expression was higher in patient-responders than non responders, while CD95/Fas expression was lower in patients with partial response (PR) relative to those with stable disease (SD) and progressive disease (PD). Furthermore, we found that high 4-1BB expression in the tumor compartment, but not in the stroma, was associated with better overall survival (OS) (HR= 0.28, p-adjusted= 0.040). Moreover, high CD40 expression in tumor regions (HR= 0.27, p-adjusted= 0.035), and high CD27 expression in the stroma (HR= 0.2, p-adjusted=0.032) were associated with better survival outcomes. Taken together, this study supports the role of immune checkpoint molecules and implicates the TNFR superfamily as key players in immunotherapy response in our cohort of HNSCC. Validation of these findings in a prospective study is required to determine the robustness of these tissue signatures.
Publisher: Elsevier BV
Date: 06-2006
DOI: 10.1016/J.MODGEP.2005.10.008
Abstract: In many instances, kidney dysgenesis results as a secondary consequence to defects in the development of the ureter. Through the use of mouse genetics a number of genes associated with such malformations have been identified, however, the cause of many other abnormalities remain unknown. In order to identify novel genes involved in ureter development we compared gene expression in embryonic day (E) 12.5, E15.5 and postnatal day (P) 75 ureters using the Compugen mouse long oligo microarrays. A total of 248 genes were dynamically upregulated and 208 downregulated between E12.5 and P75. At E12.5, when the mouse ureter is comprised of a simple cuboidal epithelium surrounded by ureteric mesenchyme, genes previously reported to be expressed in the ureteric mesenchyme, foxC1 and foxC2 were upregulated. By E15.5 the epithelial layer develops into urothelium, impermeable to urine, and smooth muscle develops for the peristaltic movement of urine towards the bladder. The development of these two cell types coincided with the upregulation of UPIIIa, RAB27b and PPARgamma reported to be expressed in the urothelium, and several muscle genes, Acta1, Tnnt2, Myocd, and Tpm2. In situ hybridization identified several novel genes with spatial expression within the smooth muscle, Acta1 ureteric mesenchyme and smooth muscle, Thbs2 and Col5a2 and urothelium, Kcnj8 and Adh1. This study marks the first known report defining global gene expression of the developing mouse ureter and will provide insight into the molecular mechanisms underlying kidney and lower urinary tract malformations.
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22526517.V1
Abstract: GFAPCre:Sox9lox/lox mice are not viable
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22430400.V1
Abstract: Supplementary tables
Publisher: Springer New York
Date: 15-12-2016
DOI: 10.1007/978-1-4939-6740-7_15
Abstract: Network analysis methods are increasing in popularity. An approach commonly applied to analyze proteomics data involves the use of protein-protein interaction (PPI) networks to explore the systems-level cooperation between proteins identified in a study. In this context, protein interaction networks can be used alongside the statistical analysis of proteomics data and traditional functional enrichment or pathway enrichment analyses. In network analysis it is possible to adjust for some of the complexities that arise due to the known, explicit interdependence between the measured quantities, in particular, differences in the number of interactions between proteins. Here we describe a method for calculating robust empirical p-values for protein interaction networks. We also provide a worked ex le with python code demonstrating the implementation of this methodology.
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22526523.V1
Abstract: Sox9 immunostaining pattern in a variety of Shh-MB genetic mouse models
Publisher: Wiley
Date: 27-09-2023
DOI: 10.1111/IMM.13577
Abstract: The severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is known to present with pulmonary and extra‐pulmonary organ complications. In comparison with the 2009 pandemic (pH1N1), SARS‐CoV‐2 infection is likely to lead to more severe disease, with multi‐organ effects, including cardiovascular disease. SARS‐CoV‐2 has been associated with acute and long‐term cardiovascular disease, but the molecular changes that govern this remain unknown. In this study, we investigated the host transcriptome landscape of cardiac tissues collected at rapid autopsy from seven SARS‐CoV‐2, two pH1N1, and six control patients using targeted spatial transcriptomics approaches. Although SARS‐CoV‐2 was not detected in cardiac tissue, host transcriptomics showed upregulation of genes associated with DNA damage and repair, heat shock, and M1‐like macrophage infiltration in the cardiac tissues of COVID‐19 patients. The DNA damage present in the SARS‐CoV‐2 patient s les, were further confirmed by γ‐H2Ax immunohistochemistry. In comparison, pH1N1 showed upregulation of interferon‐stimulated genes, in particular interferon and complement pathways, when compared with COVID‐19 patients. These data demonstrate the emergence of distinct transcriptomic profiles in cardiac tissues of SARS‐CoV‐2 and pH1N1 influenza infection supporting the need for a greater understanding of the effects on extra‐pulmonary organs, including the cardiovascular system of COVID‐19 patients, to delineate the immunopathobiology of SARS‐CoV‐2 infection, and long term impact on health.
Publisher: BMJ
Date: 04-2022
Abstract: Patients with BRAF -mutant and wild-type melanoma have different response rates to immune checkpoint blockade therapy. However, the reasons for this remain unknown. To address this issue, we investigated the precise immune composition resulting from BRAF mutation in treatment-naive melanoma to determine whether this may be a driver for different response to immunotherapy. In this study, we characterized the treatment-naive immune context in patients with BRAF -mutant and BRAF wild-type ( BRAF -wt) melanoma using data from single-cell RNA sequencing, bulk RNA sequencing, flow cytometry and immunohistochemistry (IHC). In single-cell data, BRAF -mutant melanoma displayed a significantly reduced infiltration of CD8 + T cells and macrophages but also increased B cells, natural killer (NK) cells and NKT cells. We then validated this finding using bulk RNA-seq data from the skin cutaneous melanoma cohort in The Cancer Genome Atlas and deconvoluted the data using seven different algorithms. Interestingly, BRAF -mutant tumors had more CD4 + T cells than BRAF -wt s les in both primary and metastatic cohorts. In the metastatic cohort, BRAF -mutant melanoma demonstrated more B cells but less CD8 + T cell infiltration when compared with BRAF -wt s les. In addition, we further investigated the immune cell infiltrate using flow cytometry and multiplex IHC techniques. We confirmed that BRAF -mutant melanoma metastases were enriched for CD4 + T cells and B cells and had a co-existing decrease in CD8 + T cells. Furthermore, we then identified B cells were associated with a trend for improved survival (p=0.078) in the BRAF -mutant s les and Th2 cells were associated with prolonged survival in the BRAF -wt s les. In conclusion, treatment-naive BRAF -mutant melanoma has a distinct immune context compared with BRAF -wt melanoma, with significantly decreased CD8 + T cells and increased B cells and CD4 + T cells in the tumor microenvironment. These findings indicate that further mechanistic studies are warranted to reveal how this difference in immune context leads to improved outcome to combination immune checkpoint blockade in BRAF -mutant melanoma.
Publisher: Elsevier BV
Date: 07-2018
DOI: 10.1016/J.CELS.2018.05.019
Abstract: MicroRNAs (miRNAs) are important post-transcriptional regulators of gene expression, functioning in part by facilitating the degradation of target mRNAs. They have an established role in controlling epithelial-mesenchymal transition (EMT), a reversible phenotypic program underlying normal and pathological processes. Many studies demonstrate the role of in idual miRNAs using overexpression at levels greatly exceeding physiological abundance. This can influence transcripts with relatively poor targeting and may in part explain why over 130 different miRNAs are directly implicated as EMT regulators. Analyzing a human mammary cell model of EMT we found evidence that a set of miRNAs, including the miR-200 and miR-182/183 family members, co-operate in post-transcriptional regulation, both reinforcing and buffering transcriptional output. Investigating this, we demonstrate that combinatorial treatment altered cellular phenotype with miRNA concentrations much closer to endogenous levels and with less off-target effects. This suggests that co-operative targeting by miRNAs is important for their physiological function and future work classifying miRNAs should consider such combinatorial effects.
Publisher: Proceedings of the National Academy of Sciences
Date: 28-10-2013
Abstract: Medulloblastoma is a common malignant pediatric brain tumor. Gene expression data have indicated that the tumors fall into four molecular subgroups, “Wnt,” “Hedgehog,” “group 3,” and “group 4.” With the exception of the Hedgehog subgroup, few functional data exist defining key molecular pathways driving tumor growth. Using a transposon mutagenesis approach, we identified genes that functionally cooperate with Hedgehog signalling to promote tumorigenesis in a Ptch1 mouse model of medulloblastoma. Surprisingly, the genes we identified were able to accurately define all four human molecular subtypes, not just Hedgehog, when used to interrogate published expression data. Thus, we have functionally defined key regulatory networks that illustrate both the differences and commonalities between tumor subgroups indicating a number of therapeutic strategies.
Publisher: Springer Science and Business Media LLC
Date: 23-09-2016
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.22545717
Abstract: Supplementary Figure from TGFβ and CIS Inhibition Overcomes NK-cell Suppression to Restore Antitumor Immunity
Publisher: Springer Science and Business Media LLC
Date: 10-2004
DOI: 10.1007/S00244-003-3212-5
Abstract: In Australia, water-quality trigger values for toxicants are derived using protective concentration values based on species-sensitivity distribution (SSD) curves. SSD curves are generally derived from laboratory data with an emphasis on using local or site-specific data. In this study, Australian and non-Australian laboratory-species based SSD curves were compared and the concept of species protection confirmed by comparison of laboratory-based SSD curves with local mesocosm experiments and field monitoring data. Acute LC50 data for the organochlorine pesticide endosulfan were used for these comparisons SSD curves were fitted using the Burr type III distribution. SSD curves indicated that the sensitivities of Australian fish and arthropods were not significantly different from those of corresponding non-Australian taxa. Arthropod taxa in the mesocosm were less sensitive than taxa in laboratory tests, which suggests that laboratory-generated single-species data may be used to predict concentrations protective of semifield (mesocosm) systems. SSDs based on laboratory data were also protective of field populations.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Cold Spring Harbor Laboratory
Date: 29-10-2018
DOI: 10.1101/454801
Abstract: Natural killer (NK) cells are innate lymphocytes that play a major role in immunosurveillance against tumor initiation and metastasis spread. Signals and checkpoints that regulate NK cell fitness and function in the tumor microenvironment are not well defined. Transforming grow factor (TGF)-β is a recognized suppressor of NK cells that inhibits IL-15 dependent signaling events and induces cellular transdifferentiation, however the role of other SMAD signaling pathways in NK cells is unknown. In this report, we show that NK cells express the type I Activin receptor, ALK4, which upon binding its ligand Activin-A, phosphorylates SMAD2/3 to efficiently suppress IL-15-mediated NK cell metabolism. Activin-A impairs human and mouse NK cell proliferation and downregulates intracellular granzyme B levels to impair tumor killing. Similar to TGF-β, Activin-A also induced SMAD2/3 phosphorylation and drove NK cells to upregulate several ILC1-like surface markers including CD69, TRAIL and CD49a. Activin-A also induced these changes on TGF-β receptor deficient NK cells, highlighting that Activin-A and TGF-β are independent pathways that drive SMAD2/3-mediated NK cell suppression. Finally, therapeutic inhibition of Activin-A by Follistatin significantly slowed orthotopic melanoma growth in mice. These data highlight independent SMAD2/3 pathways target NK cell fitness and function and identify a novel therapeutic axis to promote tumor immunity. One Sentence Summary: Activin-A can directly inhibit NK cell effector functions, promote NK cells transdifferentiation into ILC1-like cells and suppress anti-melanoma immunity.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.C.6551013.V1
Abstract: Abstract Antibodies targeting “immune checkpoints” have revolutionized cancer therapy by reactivating tumor-resident cytotoxic lymphocytes, primarily CD8 sup + /sup T cells. Interest in targeting analogous pathways in other cytotoxic lymphocytes is growing. Natural killer (NK) cells are key to cancer immunosurveillance by eradicating metastases and driving solid tumor inflammation. NK-cell antitumor function is dependent on the cytokine IL15. Ablation of the IL15 signaling inhibitor CIS ( i Cish /i ) enhances NK-cell antitumor immunity by increasing NK-cell metabolism and persistence within the tumor microenvironment (TME). The TME has also been shown to impair NK-cell fitness via the production of immunosuppressive transforming growth factor β (TGFβ), a suppression which occurs even in the presence of high IL15 signaling. Here, we identified an unexpected interaction between CIS and the TGFβ signaling pathway in NK cells. Independently, i Cish /i - and i Tgfbr2 /i -deficient NK cells are both hyperresponsive to IL15 and hyporesponsive to TGFβ, with dramatically enhanced antitumor immunity. Remarkably, when both these immunosuppressive genes are simultaneously deleted in NK cells, mice are largely resistant to tumor development, suggesting that combining suppression of these two pathways might represent a novel therapeutic strategy to enhance innate anticancer immunity. /
Publisher: Elsevier BV
Date: 05-2019
DOI: 10.1016/J.ECOENV.2019.01.098
Abstract: Personal care products (PCPs) are ubiquitous in the environment due to their wide use in daily life. However, there are insufficient sediment toxicity data of PCPs under ecologically relevant conditions. Here we used Fourier transform infrared spectroscopy (FTIR) to investigate the sediment toxicity of triclosan (TCS) and galaxolide (HHCB) to two freshwater benthic macroinvertebrates, Limnodrilus hoffmeisteri and Branchiura sowerbyi, in microcosms containing a erse biological community. Exposure to 8 µg TCS/g and 100 µg HHCB/g dry weight (dw) sediment induced significant biochemical alterations in the L. hoffmeisteri tissue. 8 µg TCS/g primarily affected proteins and nucleic acid while 100 µg HHCB/g mainly affected proteins and lipids of L. hoffmeisteri. However, 0.8 µg TCS/g and 30 µg HHCB/g did not cause significant subcellular toxicity to L. hoffmeisteri. In contrast, exposure of B. sowerbyi to 30 µg HHCB/g led to significant biochemical changes, including proteins, polysaccharides and lipids. Therefore, B. sowerbyi was more sensitive to sediment-associated HHCB than L. hoffmeisteri. Such effects were significantly enhanced when the HHCB concentration increased to 100 µg/g dw where death of B. sowerbyi occurred. These results demonstrate the application of FTIR spectroscopy to sediment toxicity testing of chemicals to benthic invertebrates with biochemical alterations as endpoints that are more sensitive than standard toxic endpoints (e.g., survival and growth).
Publisher: Springer Science and Business Media LLC
Date: 02-05-2019
Publisher: American Chemical Society (ACS)
Date: 30-04-2014
DOI: 10.1021/JF500232F
Abstract: Nanopesticides or nano plant protection products represent an emerging technological development that, in relation to pesticide use, could offer a range of benefits including increased efficacy, durability, and a reduction in the amounts of active ingredients that need to be used. A number of formulation types have been suggested including emulsions (e.g., nanoemulsions), nanocapsules (e.g., with polymers), and products containing pristine engineered nanoparticles, such as metals, metal oxides, and nanoclays. The increasing interest in the use of nanopesticides raises questions as to how to assess the environmental risk of these materials for regulatory purposes. Here, the current approaches for environmental risk assessment of pesticides are reviewed and the question of whether these approaches are fit for purpose for use on nanopesticides is addressed. Potential adaptations to existing environmental risk assessment tests and procedures for use with nanopesticides are discussed, addressing aspects such as analysis and characterization, environmental fate and exposure assessment, uptake by biota, ecotoxicity, and risk assessment of nanopesticides in aquatic and terrestrial ecosystems. Throughout, the main focus is on assessing whether the presence of the nanoformulation introduces potential differences relative to the conventional active ingredients. The proposed changes in the test methodology, research priorities, and recommendations would facilitate the development of regulatory approaches and a regulatory framework for nanopesticides.
Publisher: American Association for Cancer Research (AACR)
Date: 07-2019
DOI: 10.1158/2326-6066.CIR-18-0500
Abstract: Natural killer (NK) cell activity is essential for initiating antitumor responses and may be linked to immunotherapy success. NK cells and other innate immune components could be exploitable for cancer treatment, which drives the need for tools and methods that identify therapeutic avenues. Here, we extend our gene-set scoring method singscore to investigate NK cell infiltration by applying RNA-seq analysis to s les from bulk tumors. Computational methods have been developed for the deconvolution of immune cell types within solid tumors. We have taken the NK cell gene signatures from several such tools, then curated the gene list using a comparative analysis of tumors and immune cell types. Using a gene-set scoring method to investigate RNA-seq data from The Cancer Genome Atlas (TCGA), we show that patients with metastatic cutaneous melanoma have an improved survival rate if their tumor shows evidence of NK cell infiltration. Furthermore, these survival effects are enhanced in tumors that show higher expression of genes that encode NK cell stimuli such as the cytokine IL15. Using this signature, we then examine transcriptomic data to identify tumor and stromal components that may influence the penetrance of NK cells into solid tumors. Our results provide evidence that NK cells play a role in the regulation of human tumors and highlight potential survival effects associated with increased NK cell activity. Our computational analysis identifies putative gene targets that may be of therapeutic value for boosting NK cell antitumor immunity.
Publisher: American Society of Hematology
Date: 07-04-2022
DOI: 10.1182/BLOODADVANCES.2021006076
Abstract: Philadelphia-like (Ph-like) acute lymphoblastic leukemia (ALL) is a high-risk subtype of B-cell ALL characterized by a gene expression profile resembling Philadelphia chromosome–positive ALL (Ph+ ALL) in the absence of BCR-ABL1. Tyrosine kinase–activating fusions, some involving ABL1, are recurrent drivers of Ph-like ALL and are targetable with tyrosine kinase inhibitors (TKIs). We identified a rare instance of SFPQ-ABL1 in a child with Ph-like ALL. SFPQ-ABL1 expressed in cytokine-dependent cell lines was sufficient to transform cells and these cells were sensitive to ABL1-targeting TKIs. In contrast to BCR-ABL1, SFPQ-ABL1 localized to the nuclear compartment and was a weaker driver of cellular proliferation. Phosphoproteomics analysis showed upregulation of cell cycle, DNA replication, and spliceosome pathways, and downregulation of signal transduction pathways, including ErbB, NF-κB, vascular endothelial growth factor (VEGF), and MAPK signaling in SFPQ-ABL1–expressing cells compared with BCR-ABL1–expressing cells. SFPQ-ABL1 expression did not activate phosphatidylinositol 3-kinase rotein kinase B (PI3K/AKT) signaling and was associated with phosphorylation of G2/M cell cycle proteins. SFPQ-ABL1 was sensitive to navitoclax and S-63845 and promotes cell survival by maintaining expression of Mcl-1 and Bcl-xL. SFPQ-ABL1 has functionally distinct mechanisms by which it drives ALL, including subcellular localization, proliferative capacity, and activation of cellular pathways. These findings highlight the role that fusion partners have in mediating the function of ABL1 fusions.
Publisher: Rockefeller University Press
Date: 29-05-2015
DOI: 10.1084/JEM.20181778
Abstract: Interleukin (IL)-17–producing CD8+ T (Tc17) cells have emerged as key players in host-microbiota interactions, infection, and cancer. The factors that drive their development, in contrast to interferon (IFN)-γ–producing effector CD8+ T cells, are not clear. Here we demonstrate that the transcription factor TCF-1 (Tcf7) regulates CD8+ T cell fate decisions in double-positive (DP) thymocytes through the sequential suppression of MAF and RORγt, in parallel with TCF-1–driven modulation of chromatin state. Ablation of TCF-1 resulted in enhanced Tc17 cell development and exposed a gene set signature to drive tissue repair and lipid metabolism, which was distinct from other CD8+ T cell subsets. IL-17–producing CD8+ T cells isolated from healthy humans were also distinct from CD8+IL-17− T cells and enriched in pathways driven by MAF and RORγt. Overall, our study reveals how TCF-1 exerts central control of T cell differentiation in the thymus by normally repressing Tc17 differentiation and promoting an effector fate outcome.
Publisher: Cold Spring Harbor Laboratory
Date: 03-12-2019
DOI: 10.1101/861542
Abstract: B-cell development is initiated by the stepwise differentiation of hematopoietic stem cells into lineage committed progenitors, ultimately generating the mature B-cells that mediate protective immunity. This highly regulated process also generates clonal immunological ersity via recombination of immunoglobulin genes. While several transcription factors that control B-cell development and V(D)J recombination have been defined, how these processes are initiated and coordinated into a precise regulatory network remains poorly understood. Here, we show that the transcription factor ETS Related Gene ( Erg ) is essential for the earliest steps in B-cell differentiation. Erg initiates a transcriptional network involving the B-cell lineage defining genes, Ebf1 and Pax5 , that directly promotes the expression of key genes involved in V(D)J recombination and formation of the B-cell receptor. Complementation of the Erg-deficiency with a productively rearranged immunoglobulin gene rescued B-cell development, demonstrating that Erg is an essential and exquisitely stage specific regulator of the gene regulatory network controlling B-lymphopoiesis.
Publisher: Elsevier BV
Date: 02-2012
Publisher: Springer Science and Business Media LLC
Date: 14-11-2019
DOI: 10.1186/S13059-019-1851-8
Abstract: Elucidation of regulatory networks, including identification of regulatory mechanisms specific to a given biological context, is a key aim in systems biology. This has motivated the move from co-expression to differential co-expression analysis and numerous methods have been developed subsequently to address this task however, evaluation of methods and interpretation of the resulting networks has been hindered by the lack of known context-specific regulatory interactions. In this study, we develop a simulator based on dynamical systems modelling capable of simulating differential co-expression patterns. With the simulator and an evaluation framework, we benchmark and characterise the performance of inference methods. Defining three different levels of “true” networks for each simulation, we show that accurate inference of causation is difficult for all methods, compared to inference of associations. We show that a z -score-based method has the best general performance. Further, analysis of simulation parameters reveals five network and simulation properties that explained the performance of methods. The evaluation framework and inference methods used in this study are available in the dcanr R/Bioconductor package. Our analysis of networks inferred from simulated data show that hub nodes are more likely to be differentially regulated targets than transcription factors. Based on this observation, we propose an interpretation of the inferred differential network that can reconstruct a putative causal network.
Publisher: Cold Spring Harbor Laboratory
Date: 13-08-2020
DOI: 10.1101/2020.08.12.248963
Abstract: Recent developments in mass spectrometry (MS) instruments and data acquisition modes have aided multiplexed, fast, reproducible and quantitative analysis of proteome profiles, yet missing values remain a formidable challenge for proteomics data analysis. The stochastic nature of s ling in Data Dependent Acquisition (DDA), suboptimal preprocessing of Data Independent Acquisition (DIA) runs and dynamic range limitation of MS instruments impedes the reproducibility and accuracy of peptide quantification and can introduce systematic patterns of missingness that impact downstream analyses. Thus, imputation of missing values becomes an important element of data analysis. We introduce msIm pute , an imputation method based on low-rank approximation, and compare it to six alternative imputation methods using public DDA and DIA datasets. We evaluate the performance of methods by determining the error of imputed values and accuracy of detection of differential expression. We also measure the post-imputation preservation of structures in the data at different levels of granularity. We develop a visual diagnostic to determine the nature of missingness in datasets based on peptides with high biological dropout rate and introduce a method to identify such peptides. Our findings demonstrate that msImpute performs well when data are missing at random and highlights the importance of prior knowledge about nature of missing values in a dataset when selecting an imputation technique.
Publisher: Springer Science and Business Media LLC
Date: 05-2023
Publisher: Elsevier BV
Date: 04-2015
DOI: 10.1016/J.SCITOTENV.2014.12.057
Abstract: Environmental quality monitoring of water resources is challenged with providing the basis for safeguarding the environment against adverse biological effects of anthropogenic chemical contamination from diffuse and point sources. While current regulatory efforts focus on monitoring and assessing a few legacy chemicals, many more anthropogenic chemicals can be detected simultaneously in our aquatic resources. However, exposure to chemical mixtures does not necessarily translate into adverse biological effects nor clearly shows whether mitigation measures are needed. Thus, the question which mixtures are present and which have associated combined effects becomes central for defining adequate monitoring and assessment strategies. Here we describe the vision of the international, EU-funded project SOLUTIONS, where three routes are explored to link the occurrence of chemical mixtures at specific sites to the assessment of adverse biological combination effects. First of all, multi-residue target and non-target screening techniques covering a broader range of anticipated chemicals co-occurring in the environment are being developed. By improving sensitivity and detection limits for known bioactive compounds of concern, new analytical chemistry data for multiple components can be obtained and used to characterise priority mixtures. This information on chemical occurrence will be used to predict mixture toxicity and to derive combined effect estimates suitable for advancing environmental quality standards. Secondly, bioanalytical tools will be explored to provide aggregate bioactivity measures integrating all components that produce common (adverse) outcomes even for mixtures of varying compositions. The ambition is to provide comprehensive arrays of effect-based tools and trait-based field observations that link multiple chemical exposures to various environmental protection goals more directly and to provide improved in situ observations for impact assessment of mixtures. Thirdly, effect-directed analysis (EDA) will be applied to identify major drivers of mixture toxicity. Refinements of EDA include the use of statistical approaches with monitoring information for guidance of experimental EDA studies. These three approaches will be explored using case studies at the Danube and Rhine river basins as well as rivers of the Iberian Peninsula. The synthesis of findings will be organised to provide guidance for future solution-oriented environmental monitoring and explore more systematic ways to assess mixture exposures and combination effects in future water quality monitoring.
Publisher: Elsevier BV
Date: 2020
DOI: 10.2139/SSRN.3512977
Publisher: Cold Spring Harbor Laboratory
Date: 06-11-2020
DOI: 10.1101/2020.11.04.20225557
Abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that emerged in late 2019 has spread globally, causing a pandemic of respiratory illness designated coronavirus disease 2019 (COVID-19). Robust blood biomarkers that reflect tissue damage are urgently needed to better stratify and triage infected patients. Here, we use spatial transcriptomics to generate an in-depth picture of the pulmonary transcriptional landscape of COVID-19 (10 patients), pandemic H1N1 (pH1N1) influenza (5) and uninfected control patients (4). Host transcriptomics showed a significant upregulation of genes associated with inflammation, type I interferon production, coagulation and angiogenesis in the lungs of COVID-19 patients compared to non-infected controls. SARS-CoV-2 was non-uniformly distributed in lungs with few areas of high viral load and these were largely only associated with an increased type I interferon response. A very limited number of genes were differentially expressed between the lungs of influenza and COVID-19 patients. Specific interferon-associated genes (including IFI27 ) were identified as candidate novel biomarkers for COVID-19 differentiating this COVID-19 from influenza. Collectively, these data demonstrate that spatial transcriptomics is a powerful tool to identify novel gene signatures within tissues, offering new insights into the pathogenesis of SARS-COV-2 to aid in patient triage and treatment.
Publisher: MDPI AG
Date: 23-03-2023
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.C.6545124.V1
Abstract: Abstract Medulloblastoma is the most common malignant pediatric brain tumor and there is an urgent need for molecularly targeted and subgroup-specific therapies. The stem cell factor SOX9, has been proposed as a potential therapeutic target for the treatment of Sonic Hedgehog medulloblastoma (SHH-MB) subgroup tumors, given its role as a downstream target of Hedgehog signaling and in functionally promoting SHH-MB metastasis and treatment resistance. However, the functional requirement for SOX9 in the genesis of medulloblastoma remains to be determined. Here we report a previously undocumented level of SOX9 expression exclusively in proliferating granule cell precursors (GCP) of the postnatal mouse cerebellum, which function as the medulloblastoma-initiating cells of SHH-MBs. Wild-type GCPs express comparatively lower levels of SOX9 than neural stem cells and mature astroglia and SOX9 sup low /sup GCP-like tumor cells constitute the bulk of both infant (Math1Cre: i Ptch1 sup lox/lox /sup /i ) and adult ( i Ptch1 sup LacZ/+ /sup /i ) SHH-MB mouse models. Human medulloblastoma single-cell RNA data analyses reveal three distinct i SOX9 /i populations present in SHH-MB and noticeably absent in other medulloblastoma subgroups: i SOX9 /i sup + /sup i MATH1 /i sup + /sup (GCP), i SOX9 /i sup + /sup i GFAP /i sup + /sup (astrocytes) and i SOX9 /i sup + /sup i MATH1 /i sup + /sup i GFAP /i sup + /sup (potential tumor-derived astrocytes). To functionally address whether SOX9 is required as a downstream effector of Hedgehog signaling in medulloblastoma tumor cells, we ablated i Sox9 /i using a Math1Cre model system. Surprisingly, targeted ablation of i Sox9 /i in GCPs (Math1Cre: i Sox9 sup lox/lox /sup /i ) revealed no overt phenotype and loss of i Sox9 /i in SHH-MB (Math1Cre: i Ptch1 sup lox/lox /sup Sox9 sup lox/lox /sup /i ) does not affect tumor formation. Implications: Despite preclinical data indicating SOX9 plays a key role in SHH-MB biology, our data argue against SOX9 as a viable therapeutic target. /
Publisher: Oxford University Press (OUP)
Date: 21-05-2013
DOI: 10.1093/BIB/BBT034
Publisher: CSIRO Publishing
Date: 2016
DOI: 10.1071/MF15330
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22526526.V1
Abstract: S4. Single cell sequencing data analysis
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.C.6551013
Abstract: Abstract Antibodies targeting “immune checkpoints” have revolutionized cancer therapy by reactivating tumor-resident cytotoxic lymphocytes, primarily CD8 sup + /sup T cells. Interest in targeting analogous pathways in other cytotoxic lymphocytes is growing. Natural killer (NK) cells are key to cancer immunosurveillance by eradicating metastases and driving solid tumor inflammation. NK-cell antitumor function is dependent on the cytokine IL15. Ablation of the IL15 signaling inhibitor CIS ( i Cish /i ) enhances NK-cell antitumor immunity by increasing NK-cell metabolism and persistence within the tumor microenvironment (TME). The TME has also been shown to impair NK-cell fitness via the production of immunosuppressive transforming growth factor β (TGFβ), a suppression which occurs even in the presence of high IL15 signaling. Here, we identified an unexpected interaction between CIS and the TGFβ signaling pathway in NK cells. Independently, i Cish /i - and i Tgfbr2 /i -deficient NK cells are both hyperresponsive to IL15 and hyporesponsive to TGFβ, with dramatically enhanced antitumor immunity. Remarkably, when both these immunosuppressive genes are simultaneously deleted in NK cells, mice are largely resistant to tumor development, suggesting that combining suppression of these two pathways might represent a novel therapeutic strategy to enhance innate anticancer immunity. /
Publisher: American Association for Cancer Research (AACR)
Date: 27-06-2022
DOI: 10.1158/2326-6066.CIR-21-1052
Abstract: Antibodies targeting “immune checkpoints” have revolutionized cancer therapy by reactivating tumor-resident cytotoxic lymphocytes, primarily CD8+ T cells. Interest in targeting analogous pathways in other cytotoxic lymphocytes is growing. Natural killer (NK) cells are key to cancer immunosurveillance by eradicating metastases and driving solid tumor inflammation. NK-cell antitumor function is dependent on the cytokine IL15. Ablation of the IL15 signaling inhibitor CIS (Cish) enhances NK-cell antitumor immunity by increasing NK-cell metabolism and persistence within the tumor microenvironment (TME). The TME has also been shown to impair NK-cell fitness via the production of immunosuppressive transforming growth factor β (TGFβ), a suppression which occurs even in the presence of high IL15 signaling. Here, we identified an unexpected interaction between CIS and the TGFβ signaling pathway in NK cells. Independently, Cish- and Tgfbr2-deficient NK cells are both hyperresponsive to IL15 and hyporesponsive to TGFβ, with dramatically enhanced antitumor immunity. Remarkably, when both these immunosuppressive genes are simultaneously deleted in NK cells, mice are largely resistant to tumor development, suggesting that combining suppression of these two pathways might represent a novel therapeutic strategy to enhance innate anticancer immunity.
Publisher: Springer Science and Business Media LLC
Date: 20-11-2017
DOI: 10.1038/S41467-017-01560-X
Abstract: The mammary epithelium comprises two primary cellular lineages, but the degree of heterogeneity within these compartments and their lineage relationships during development remain an open question. Here we report single-cell RNA profiling of mouse mammary epithelial cells spanning four developmental stages in the post-natal gland. Notably, the epithelium undergoes a large-scale shift in gene expression from a relatively homogeneous basal-like program in pre-puberty to distinct lineage-restricted programs in puberty. Interrogation of single-cell transcriptomes reveals different levels of ersity within the luminal and basal compartments, and identifies an early progenitor subset marked by CD55. Moreover, we uncover a luminal transit population and a rare mixed-lineage cluster amongst basal cells in the adult mammary gland. Together these findings point to a developmental hierarchy in which a basal-like gene expression program prevails in the early post-natal gland prior to the specification of distinct lineage signatures, and the presence of cellular intermediates that may serve as transit or lineage-primed cells.
Publisher: Elsevier BV
Date: 10-2023
Publisher: Cold Spring Harbor Laboratory
Date: 24-04-2023
DOI: 10.1101/2023.04.23.538017
Abstract: To gain a better understanding of the complexity of gene expression in normal and diseased tissues it is important to account for the spatial context and identity of cell in situ . State-of-the-art spatial profiling technologies, such as the Nanostring GeoMx Digital Spatial Profiler (DSP), now allow quantitative spatially resolved measurement of the transcriptome in tissues. However, the bioinformatics pipelines currently used to analyse GeoMx data often fail to successfully account for the technical variability within the data and the complexity of experimental designs, thus limiting the accuracy and reliability of subsequent analysis. Carefully designed quality control workflows, that include in-depth experiment-specific investigations into technical variation and appropriate adjustment for such variation can address this issue. Here we present standR , a R/Bioconductor package that enables an end-to-end analysis of GeoMx DSP data. With four case studies from previously published experiments, we demonstrate how the standR workflow can enhance the statistical power of GeoMx DSP data analysis and how application of standR enables scientists to develop in-depth insights into the biology of interest.
Publisher: Cold Spring Harbor Laboratory
Date: 31-03-2022
DOI: 10.1101/2022.03.24.22272732
Abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is known to present with pulmonary and extra-pulmonary organ complications. In comparison with the 2009 pandemic (pH1N1), SARS-CoV-2 infection is likely to lead to more severe disease, with multi-organ effects, including cardiovascular disease. SARS-CoV-2 has been associated with acute and long-term cardiovascular disease, but the molecular changes govern this remain unknown. In this study, we investigated the landscape of cardiac tissues collected at rapid autopsy from SARS-CoV-2, pH1N1, and control patients using targeted spatial transcriptomics approaches. Although SARS-CoV-2 was not detected in cardiac tissue, host transcriptomics showed upregulation of genes associated with DNA damage and repair, heat shock, and M1-like macrophage infiltration in the cardiac tissues of COVID-19 patients. The DNA damage present in the SARS-CoV-2 patient s les, were further confirmed by γ−H2Ax immunohistochemistry. In comparison, pH1N1 showed upregulation of Interferon-stimulated genes (ISGs), in particular interferon and complement pathways, when compared with COVID-19 patients. These data demonstrate the emergence of distinct transcriptomic profiles in cardiac tissues of SARS-CoV-2 and pH1N1 influenza infection supporting the need for a greater understanding of the effects on extra-pulmonary organs, including the cardiovascular system of COVID-19 patients, to delineate the immunopathobiology of SARS-CoV-2 infection, and long term impact on health.
Publisher: American Society of Hematology
Date: 22-06-2020
DOI: 10.1182/BLOODADVANCES.2019001416
Abstract: Improving survival outcomes in adult B-cell acute lymphoblastic leukemia (B-ALL) remains a clinical challenge. Relapsed disease has a poor prognosis despite the use of tyrosine kinase inhibitors (TKIs) for Philadelphia chromosome positive (Ph+ ALL) cases and immunotherapeutic approaches, including blinatumomab and chimeric antigen receptor T cells. Targeting aberrant cell survival pathways with selective small molecule BH3-mimetic inhibitors of BCL-2 (venetoclax, S55746), BCL-XL (A1331852), or MCL1 (S63845) is an emerging therapeutic option. We report that combined targeting of BCL-2 and MCL1 is synergistic in B-ALL in vitro. The combination demonstrated greater efficacy than standard chemotherapeutics and TKIs in primary s les from adult B-ALL with Ph+ ALL, Ph-like ALL, and other B-ALL. Moreover, combined BCL-2 or MCL1 inhibition with dasatinib showed potent killing in primary Ph+ B-ALL cases, but the BH3-mimetic combination appeared superior in vitro in a variety of Ph-like ALL s les. In PDX models, combined BCL-2 and MCL1 targeting eradicated ALL from Ph− and Ph+ B-ALL cases, although fatal tumor lysis was observed in some instances of high tumor burden. We conclude that a dual BH3-mimetic approach is highly effective in erse models of high-risk human B-ALL and warrants assessment in clinical trials that incorporate tumor lysis precautions.
Publisher: Oxford University Press (OUP)
Date: 09-05-2023
DOI: 10.1093/NAR/GKAD337
Abstract: Gene-set analysis (GSA) dominates the functional interpretation of omics data and downstream hypothesis generation. Despite its ability to summarise thousands of measurements into semantically interpretable components, GSA often results in hundreds of significantly enriched gene-sets. However, summarisation and effective visualisation of GSA results to facilitate hypothesis generation is still lacking. While some webservers provide gene-set visualization tools, there is still a need for tools that can effectively summarize and guide exploration of GSA results. To enable versatility, webservers accept gene lists as input, however, none provide end-to-end solutions for emerging data types such as single-cell and spatial omics. Here, we present vissE.Cloud, a webserver for end-to-end gene-set analysis, offering gene-set summarisation and highly interactive visualisation. vissE.Cloud uses algorithms from our earlier R package vissE to summarise GSA results by identifying biological themes. We maintain versatility by allowing analysis of gene lists, as well as, analysis of raw single-cell and spatial omics data, including CosMx and Xenium data, making vissE.Cloud the first webserver to provide end-to-end gene-set analysis of sub-cellular localised spatial data. Structuring the results hierarchically allows swift interactive investigations of results at the gene, gene-set, and clusters level. vissE.Cloud is freely available at www.vissE.Cloud.
Publisher: Elsevier BV
Date: 12-2003
DOI: 10.1016/J.BBRC.2003.11.069
Abstract: Signal peptides and transmembrane helices both contain a stretch of hydrophobic amino acids. This common feature makes it difficult for signal peptide and transmembrane helix predictors to correctly assign identity to stretches of hydrophobic residues near the N-terminal methionine of a protein sequence. The inability to reliably distinguish between N-terminal transmembrane helix and signal peptide is an error with serious consequences for the prediction of protein secretory status or transmembrane topology. In this study, we report a new method for differentiating protein N-terminal signal peptides and transmembrane helices. Based on the sequence features extracted from hydrophobic regions (amino acid frequency, hydrophobicity, and the start position), we set up discriminant functions and examined them on non-redundant datasets with jackknife tests. This method can incorporate other signal peptide prediction methods and achieve higher prediction accuracy. For Gram-negative bacterial proteins, 95.7% of N-terminal signal peptides and transmembrane helices can be correctly predicted (coefficient 0.90). Given a sensitivity of 90%, transmembrane helices can be identified from signal peptides with a precision of 99% (coefficient 0.92). For eukaryotic proteins, 94.2% of N-terminal signal peptides and transmembrane helices can be correctly predicted with coefficient 0.83. Given a sensitivity of 90%, transmembrane helices can be identified from signal peptides with a precision of 87% (coefficient 0.85). The method can be used to complement current transmembrane protein prediction and signal peptide prediction methods to improve their prediction accuracies.
Publisher: American Chemical Society (ACS)
Date: 16-07-2018
Abstract: Personal care products are widely used in our daily life in considerable quantities and discharged via the down-the-drain route to aquatic environments, resulting in potential risks to aquatic organisms. We investigated bioaccumulation and biotransformation of two widely used personal care products, triclosan (TCS) and galaxolide (HHCB) spiked to sediment, in the oligochaete worm Limnodrilus hoffmeisteri in water/sediment microcosms. After 7 days of sediment exposure to 3.1 μg of TCS or HHCB/g of dry weight sediment, the accumulation of TCS and HHCB in L. hoffmeisteri reached equilibrium, at which point the biota-sediment accumulation factors (BSAFs) were 2.07 and 2.50 for TCS and HHCB, respectively. The presence of L. hoffmeisteri significantly accelerated the dissipation of the levels of TCS and HHCB in the microcosms, with approximately 9.03 and 2.90% of TCS and HHCB, respectively, eliminated from the water/sediment systems after exposure for 14 days in the presence of worms. Two biotransformation products, methyl triclosan and triclosan O-sulfate, were identified for TCS in worm tissue, whereas only methyl triclosan was identified in the sediment. Unlike TCS, no evidence of biotransformation products was found for HHCB in either worm tissue or sediment. These experiments demonstrate that L. hoffmeisteri biotransformed TCS through methylation and sulfation, whereas HHCB biotransformation was undetectable.
Publisher: Cold Spring Harbor Laboratory
Date: 21-03-2022
DOI: 10.1101/2022.03.21.22269988
Abstract: Cancer cells invoke phenotypic plasticity programs to drive disease progression and evade chemotherapeutic insults, yet until now there have been no validated clinical therapies targeting this process. Here, we identify a phenotypic plasticity signature associated with poor survival in basal/triple-negative breast cancer, in which androgen signalling is prominent. We establish that anti-androgen therapies block cancer stem cell function and prevent chemotherapy-induced emergence of new cancer stem cells. In particular, the anti-androgen agent seviteronel synergizes with chemotherapy to improve chemotherapeutic inhibition of primary and metastatic tumour growth and prevent the emergence of chemotherapy-resistant disease. We validate cytoplasmic AR expression as a clinical phenotypic plasticity biomarker that predicts poor survival and poor response to chemotherapy, and positive response to seviteronel plus chemotherapy. This new targeted combination therapy validates modulating phenotypic plasticity as an effective strategy to prevent and treat chemotherapy-resistant cancers with transformative clinical potential. There are currently no curative therapies for patients with chemotherapy-resistant cancer. We demonstrate that modulating phenotypic plasticity prevents the emergence of chemotherapy-resistant disease in triple-negative breast cancer. This represents the first known validated clinical therapy leveraging phenotypic plasticity. Moreover, we identify a highly effective anti-androgen drug and a biomarker to select and treat patients best-suited to this new therapy. A clinical trial is underway ( NCT04947189 ). Blocking phenotypic plasticity is an effective targeted therapeutic strategy to treat cance
Publisher: European Respiratory Society (ERS)
Date: 21-10-2022
DOI: 10.1183/13993003.01881-2021
Abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which emerged in late 2019 has spread globally, causing a pandemic of respiratory illness designated coronavirus disease 2019 (COVID-19). A better definition of the pulmonary host response to SARS-CoV-2 infection is required to understand viral pathogenesis and to validate putative COVID-19 biomarkers that have been proposed in clinical studies. Here, we use targeted transcriptomics of formalin-fixed paraffin-embedded tissue using the NanoString GeoMX platform to generate an in-depth picture of the pulmonary transcriptional landscape of COVID-19, pandemic H1N1 influenza and uninfected control patients. Host transcriptomics showed a significant upregulation of genes associated with inflammation, type I interferon production, coagulation and angiogenesis in the lungs of COVID-19 patients compared to non-infected controls. SARS-CoV-2 was non-uniformly distributed in lungs (emphasising the advantages of spatial transcriptomics) with the areas of high viral load associated with an increased type I interferon response. Once the dominant cell type present in the s le, within patient correlations and patient–patient variation, had been controlled for, only a very limited number of genes were differentially expressed between the lungs of fatal influenza and COVID-19 patients. Strikingly, the interferon-associated gene IFI27 , previously identified as a useful blood biomarker to differentiate bacterial and viral lung infections, was significantly upregulated in the lungs of COVID-19 patients compared to patients with influenza. Collectively, these data demonstrate that spatial transcriptomics is a powerful tool to identify novel gene signatures within tissues, offering new insights into the pathogenesis of SARS-COV-2 to aid in patient triage and treatment.
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22430403
Abstract: Supplementary Methods and Data- Changes are unmarked
Publisher: Springer Science and Business Media LLC
Date: 08-06-2012
Abstract: The half-life of a protein is regulated by a range of system properties, including the abundance of components of the degradative machinery and protein modifiers. It is also influenced by protein-specific properties, such as a protein’s structural make-up and interaction partners. New experimental techniques coupled with powerful data integration methods now enable us to not only investigate what features govern protein stability in general, but also to build models that identify what properties determine each protein’s metabolic stability. In this work we present five groups of features useful for predicting protein stability: (1) post-translational modifications, (2) domain types, (3) structural disorder, (4) the identity of a protein’s N-terminal residue and (5) amino acid sequence. We incorporate these features into a predictive model with promising accuracy. At a 20% false positive rate, the model exhibits an 80% true positive rate, outperforming the only previously proposed stability predictor. We also investigate the impact of N-terminal protein tagging as used to generate the data set, in particular the impact it may have on the measurements for secreted and transmembrane proteins we train and test our model on a subset of the data with those proteins removed, and show that the model sustains high accuracy. Finally, we estimate system-wide metabolic stability by surveying the whole human proteome. We describe a variety of protein features that are significantly over- or under-represented in stable and unstable proteins, including phosphorylation, acetylation and destabilizing N-terminal residues. Bayesian networks are ideal for combining these features into a predictive model with superior accuracy and transparency compared to the only other proposed stability predictor. Furthermore, our stability predictions of the human proteome will find application in the analysis of functionally related proteins, shedding new light on regulation by protein synthesis and degradation.
Publisher: Frontiers Media SA
Date: 05-01-2023
DOI: 10.3389/FIMMU.2022.1060438
Abstract: Robust biomarkers that predict disease outcomes amongst COVID-19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID-19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness. We conducted a multi-cohort observational study to investigate the biology and the prognostic role of interferon alpha-inducible protein 27 ( IFI27 ) in COVID-19 patients. We show that IFI27 is expressed in the respiratory tract of COVID-19 patients and elevated IFI27 expression in the lower respiratory tract is associated with the presence of a high viral load. We further demonstrate that the systemic host response, as measured by blood IFI27 expression, is associated with COVID-19 infection. For clinical outcome prediction (e.g., respiratory failure), IFI27 expression displays a high sensitivity (0.95) and specificity (0.83), outperforming other known predictors of COVID-19 outcomes. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For ex le, in the pandemic H1N1/09 influenza virus infection, IFI27- like genes were highly upregulated in the blood s les of severely infected patients. These data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet-to-be discovered respiratory virus.
Publisher: Springer Science and Business Media LLC
Date: 13-11-2012
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22430400
Abstract: Supplementary tables
Publisher: Cold Spring Harbor Laboratory
Date: 07-03-2022
DOI: 10.1101/2022.03.06.483195
Abstract: Functional analysis of high throughput experiments using pathway analysis is now ubiquitous. Though powerful, these methods often produce thousands of redundant results owing to knowledgebase redundancies upstream. This scale of results hinders extensive exploration by biologists and often leads to investigator biases due to previous knowledge and expectations. To address this issue, we present vissE, a flexible network-based analysis method that summarises redundancies into biological themes and provides various analytical modules to characterise and visualise them with respect to the underlying data, thus providing a comprehensive view of the biological system. We demonstrate vissE’s versatility by applying it to three different technologies: bulk, single-cell and spatial transcriptomics. Applying vissE to a factor analysis of a breast cancer spatial transcriptomic data, we identified stromal phenotypes that support tumour dissemination. Its adaptability allows vissE to enhance all existing gene-set enrichment and pathway analysis workflows, removing investigator bias from molecular discovery.
Publisher: MDPI AG
Date: 02-2021
Abstract: Chronic inflammation of the gastrointestinal (GI) tract contributes to colorectal cancer (CRC) progression. While the role of adaptive T cells in CRC is now well established, the role of innate immune cells, specifically innate lymphoid cells (ILCs), is not well understood. To define the role of ILCs in CRC we employed complementary heterotopic and chemically-induced CRC mouse models. We discovered that ILCs were abundant in CRC tumours and contributed to anti-tumour immunity. We focused on ILC2 and showed that ILC2-deficient mice developed a higher tumour burden compared with littermate wild-type controls. We generated an ILC2 gene signature and using machine learning models revealed that CRC patients with a high intratumor ILC2 gene signature had a favourable clinical prognosis. Collectively, our results highlight a critical role for ILC2 in CRC, suggesting a potential new avenue to improve clinical outcomes through ILC2-agonist based therapeutic approaches.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.22545717.V1
Abstract: Supplementary Figure from TGFβ and CIS Inhibition Overcomes NK-cell Suppression to Restore Antitumor Immunity
Publisher: American Association for Cancer Research (AACR)
Date: 05-2017
DOI: 10.1158/1541-7786.MCR-16-0313
Abstract: Most cancer deaths are due to metastasis, and epithelial-to-mesenchymal transition (EMT) plays a central role in driving cancer cell metastasis. EMT is induced by different stimuli, leading to different signaling patterns and therapeutic responses. TGFβ is one of the best-studied drivers of EMT, and many drugs are available to target this signaling pathway. A comprehensive bioinformatics approach was employed to derive a signature for TGFβ-induced EMT which can be used to score TGFβ-driven EMT in cells and clinical specimens. Considering this signature in pan-cancer cell and tumor datasets, a number of cell lines (including basal B breast cancer and cancers of the central nervous system) show evidence for TGFβ-driven EMT and carry a low mutational burden across the TGFβ signaling pathway. Furthermore, significant variation is observed in the response of high scoring cell lines to some common cancer drugs. Finally, this signature was applied to pan-cancer data from The Cancer Genome Atlas to identify tumor types with evidence of TGFβ-induced EMT. Tumor types with high scores showed significantly lower survival rates than those with low scores and also carry a lower mutational burden in the TGFβ pathway. The current transcriptomic signature demonstrates reproducible results across independent cell line and cancer datasets and identifies s les with strong mesenchymal phenotypes likely to be driven by TGFβ. Implications: The TGFβ-induced EMT signature may be useful to identify patients with mesenchymal-like tumors who could benefit from targeted therapeutics to inhibit promesenchymal TGFβ signaling and disrupt the metastatic cascade. Mol Cancer Res 15(5) 619–31. ©2017 AACR.
Publisher: Springer Science and Business Media LLC
Date: 31-03-2022
Publisher: American Association for Cancer Research (AACR)
Date: 31-05-2018
DOI: 10.1158/0008-5472.CAN-17-1869
Abstract: Posttreatment recurrence of colorectal cancer, the third most lethal cancer worldwide, is often driven by a subpopulation of cancer stem cells (CSC). The tight junction (TJ) protein claudin-2 is overexpressed in human colorectal cancer, where it enhances cell proliferation, colony formation, and chemoresistance in vitro. While several of these biological processes are features of the CSC phenotype, a role for claudin-2 in the regulation of these has not been identified. Here, we report that elevated claudin-2 expression in stage II/III colorectal tumors is associated with poor recurrence-free survival following 5-fluorouracil–based chemotherapy, an outcome in which CSCs play an instrumental role. In patient-derived organoids, primary cells, and cell lines, claudin-2 promoted colorectal cancer self-renewal in vitro and in multiple mouse xenograft models. Claudin-2 enhanced self-renewal of ALDHHigh CSCs and increased their proportion in colorectal cancer cell populations, limiting their differentiation and promoting the phenotypic transition of non-CSCs toward the ALDHHigh phenotype. Next-generation sequencing in ALDHHigh cells revealed that claudin-2 regulated expression of nine miRNAs known to control stem cell signaling. Among these, miR-222-3p was instrumental for the regulation of self-renewal by claudin-2, and enhancement of this self-renewal required activation of YAP, most likely upstream from miR-222-3p. Taken together, our results indicate that overexpression of claudin-2 promotes self-renewal within colorectal cancer stem-like cells, suggesting a potential role for this protein as a therapeutic target in colorectal cancer. Significance: Claudin-2-mediated regulation of YAP activity and miR-222-3p expression drives CSC renewal in colorectal cancer, making it a potential target for therapy. Cancer Res 78(11) 2925–38. ©2018 AACR.
Publisher: Cold Spring Harbor Laboratory
Date: 23-07-2018
DOI: 10.1101/375253
Abstract: Animal models have demonstrated that natural killer (NK) cells can limit the metastatic dissemination of tumors, however their ability to combat established human tumors has been difficult to investigate. A number of computational methods have been developed for the deconvolution of immune cell types within solid tumors. We have taken the NK cell gene signatures from several tools, then curated and expanded this list using recent reports from the literature. Using a gene set scoring method to investigate RNA-seq data from The Cancer Genome Atlas (TCGA) we show that patients with metastatic cutaneous melanoma have an improved survival rate if their tumor shows evidence of greater NK cell infiltration. Furthermore, these survival effects are enhanced in tumors which have a higher expression of NK cell stimuli such as IL-15, suggesting NK cells are part of a coordinated immune response within these patients. Using this signature we then examine transcriptomic data to identify tumor and stromal components which may influence the penetrance of NK cells into solid tumors. These data support a role for NK cells in the regulation of human tumors and highlight potential survival effects associated with increased NK cell activity. Furthermore, our computational analysis identifies a number of potential targets which may help to unleash the anti-tumor potential of NK cells as we enter the age of immunotherapy.
Publisher: Springer Science and Business Media LLC
Date: 11-07-2022
DOI: 10.1038/S41389-022-00413-7
Abstract: MiR-21 was identified as a gene whose expression correlated with the extent of metastasis of murine mammary tumours. Since miR-21 is recognised as being associated with poor prognosis in cancer, we investigated its contribution to mammary tumour growth and metastasis in tumours with capacity for spontaneous metastasis. Unexpectedly, we found that suppression of miR-21 activity in highly metastatic tumours resulted in regression of primary tumour growth in immunocompetent mice but did not impede growth in immunocompromised mice. Analysis of the immune infiltrate of the primary tumours at the time when the tumours started to regress revealed an influx of both CD4 + and CD8 + activated T cells and a reduction in PD-L1 + infiltrating monocytes, providing an explanation for the observed tumour regression. Loss of anti-tumour immune suppression caused by decreased miR-21 activity was confirmed by transcriptomic analysis of primary tumours. This analysis also revealed reduced expression of genes associated with cell cycle progression upon loss of miR-21 activity. A second activity of miR-21 was the promotion of metastasis as shown by the loss of metastatic capacity of miR-21 knockdown tumours established in immunocompromised mice, despite no impact on primary tumour growth. A proteomic analysis of tumour cells with altered miR-21 activity revealed deregulation of proteins known to be associated with tumour progression. The development of therapies targeting miR-21, possibly via targeted delivery to tumour cells, could be an effective therapy to combat primary tumour growth and suppress the development of metastatic disease.
Publisher: Oxford University Press (OUP)
Date: 07-2021
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22526514.V1
Abstract: Medulloblastoma and granule cell precursor Gli1 target genes
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.22430403.V1
Abstract: Supplementary Methods and Data- Changes are unmarked
Publisher: Cold Spring Harbor Laboratory
Date: 11-2021
DOI: 10.1101/2021.10.29.21265555
Abstract: Robust biomarkers that predict disease outcomes amongst COVID-19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID-19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness. We conducted a multi-cohort observational study to investigate the biology and the prognostic role of interferon alpha-inducible protein 27 ( IFI27 ) in COVID-19 patients. We show that IFI27 is expressed in the respiratory tract of COVID-19 patients and elevated IFI27 expression is associated with the presence of a high viral load. We further demonstrate that systemic host response, as measured by blood IFI27 expression, is associated with COVID-19 severity. For clinical outcome prediction (e.g. respiratory failure), IFI27 expression displays a high positive (0.83) and negative (0.95) predictive value, outperforming all other known predictors of COVID-19 severity. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For ex le, in the pandemic H1N1/09 swine influenza virus infection, IFI27- like genes were highly upregulated in the blood s les of severely infected patients. These data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet-to-be discovered respiratory virus. We searched the scientific literature using PubMed to identify studies that used the IFI27 biomarker to predict outcomes in COVID-19 patients. We used the search terms “ IFI27 ”, “COVID-19, “gene expression” and “outcome prediction”. We did not identify any study that investigated the role of IFI27 biomarker in outcome prediction. Although ten studies were identified using the general terms of “gene expression” and “COVID-19”, IFI27 was only mentioned in passing as one of the identified genes. All these studies addressed the broader question of the host response to COVID-19 none focused solely on using IFI27 to improve the risk stratification of infected patients in a pandemic. Here, we present the findings of a multi-cohort study of the IFI27 biomarker in COVID-19 patients. Our findings show that the host response, as reflected by blood IFI27 gene expression, accurately predicts COVID-19 disease progression (positive and negative predictive values 0.83 and 0.95, respectively), outperforming age, comorbidity, C-reactive protein and all other known risk factors. The strong association of IFI27 with disease severity occurs not only in SARS-CoV-2 infection, but also in other respiratory viruses with pandemic potential, such as the influenza virus. These findings suggest that host response biomarkers, such as IFI27 , could help identify high-risk COVID-19 patients - those who are more likely to develop infection complications - and therefore may help improve patient triage in a pandemic. This is the first systemic study of the clinical role of IFI27 in the current COVID-19 pandemic and its possible future application in other respiratory virus pandemics. The findings not only could help improve the current management of COVID-19 patients but may also improve future pandemic preparedness.
Publisher: American Association for Cancer Research (AACR)
Date: 24-08-2021
DOI: 10.1158/0008-5472.CAN-21-0839
Abstract: These findings demonstrate antitumor activities of eosinophils in the metastatic tumor microenvironment, suggesting that harnessing eosinophil activity may be a viable clinical strategy in patients with cancer.
Publisher: Wiley
Date: 22-05-2023
Abstract: Epithelial‐mesenchymal transition (EMT) is a reversible transcriptional program invoked by cancer cells to drive cancer progression. Transcription factor ZEB1 is a master regulator of EMT, driving disease recurrence in poor‐outcome triple negative breast cancers (TNBCs). Here, this work silences ZEB1 in TNBC models by CRISPR/dCas9‐mediated epigenetic editing, resulting in highly‐specific and nearly complete suppression of ZEB1 in vivo, accompanied by long‐lasting tumor inhibition. Integrated “omic” changes promoted by dCas9 linked to the KRAB domain (dCas9‐KRAB) enabled the discovery of a ZEB1‐dependent‐signature of 26 genes differentially‐expressed and ‐methylated, including the reactivation and enhanced chromatin accessibility in cell adhesion loci, outlining epigenetic reprogramming toward a more epithelial state. In the ZEB1 locus transcriptional silencing is associated with induction of locally‐spread heterochromatin, significant changes in DNA methylation at specific CpGs, gain of H3K9me3, and a near complete erasure of H3K4me3 in the ZEB1 promoter. Epigenetic shifts induced by ZEB1 ‐silencing are enriched in a subset of human breast tumors, illuminating a clinically‐relevant hybrid‐like state. Thus, the synthetic epi‐silencing of ZEB1 induces stable “lock‐in” epigenetic reprogramming of mesenchymal tumors associated with a distinct and stable epigenetic landscape. This work outlines epigenome‐engineering approaches for reversing EMT and customizable precision molecular oncology approaches for targeting poor outcome breast cancers.
Publisher: Springer Science and Business Media LLC
Date: 10-2013
Publisher: Springer Science and Business Media LLC
Date: 15-05-2015
Publisher: Cold Spring Harbor Laboratory
Date: 12-09-2023
Publisher: Cold Spring Harbor Laboratory
Date: 15-05-2018
DOI: 10.1101/321984
Abstract: Motivation: Post-translational modifications (PTMs) regulate many key cellular processes. Numerous studies have linked the topology of protein-protein interaction (PPI) networks to many biological phenomena such as key regulatory processes and disease. However, these methods fail to give insight in the functional nature of these interactions. On the other hand, pathways are commonly used to gain biological insight into the function of PPIs in the context of cascading interactions, sacrificing the coverage of networks for rich functional annotations on each PPI. We present a machine learning approach that uses Gene Ontology, InterPro and Pfam annotations to infer the edge functions in PPI networks, allowing us to combine the high coverage of networks with the information richness of pathways. Results: An ensemble method with a combination Logistic Regression and Random Forest classifiers trained on a high-quality set of annotated interactions, with a total of 18 unique labels, achieves high a average F1 score 0.88 despite not taking advantage of multi-label dependencies. When applied to the human interactome, our method confidently classifies 62% of interactions at a probability of 0.7 or higher. Availability: Software and data are available at github.com/DavisLaboratory yPPI Contact: davis.m@wehi.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.
Publisher: Royal Society of Chemistry (RSC)
Date: 2012
DOI: 10.1039/C2MB25050K
Abstract: Transcriptomics continues to provide ever-more evidence that in morphologically complex eukaryotes, each protein-coding genetic locus can give rise to multiple transcripts that differ in length, exon content and/or other sequence features. In humans, more than 60% of loci give rise to multiple transcripts in this way. Motifs that mediate protein-protein interactions can be present or absent in these transcripts. Analysis of protein interaction networks has been a valuable development in systems biology. Interactions are typically recorded for representative proteins or even genes, although exploratory transcriptomics has revealed great spatiotemporal ersity in the output of genes at both the transcript and protein-isoform levels. The increasing availability of high-resolution protein structures has made it possible to identify the domain-domain interactions that underpin many protein interactions. To explore the impact of transcript and isoform ersity we use full-length human cDNAs to interrogate the protein-coding transcriptional output of genes, identifying variation in the inclusion of protein interaction domains. We map these data to a set of high-quality protein interactions, and characterise the variation in network connectivity likely to result. We find strong evidence for altered interaction potential in nearly 20% of genes, suggesting that transcriptional variation can significantly rewire the human interactome.
Publisher: American Association for the Advancement of Science (AAAS)
Date: 27-08-2019
DOI: 10.1126/SCISIGNAL.AAT7527
Abstract: Activin-A inhibits NK cell effector functions and suppresses antimelanoma immunity.
Publisher: Elsevier BV
Date: 10-2023
Publisher: Wiley
Date: 17-04-2018
DOI: 10.1111/IMCB.12045
Abstract: Natural Killer (NK) cells have long been considered an important part of the anti-tumor immune response due to their potent cytolytic and cytokine-secreting abilities. To date, a clear demonstration of the role NK cells play in human cancer is lacking, and there are still very few ex les of therapies that efficiently exploit or enhance the spontaneous ability of NK cells to destroy the autologous cancer cells. Given the paradigm shift toward cancer immunotherapy over the past decade, there is a renewed push to understand how NK cell homeostasis and function are regulated in order to therapeutically harness these cells to treat cancer. This review will highlight recent advancements in our understanding of how growth factors impact on NK cell development, differentiation, survival and function with an emphasis on how these pathways may influence NK cell activity in the tumor microenvironment and control of cancer metastasis.
Publisher: Wiley
Date: 06-2013
DOI: 10.1111/MEC.12309
Abstract: Recent advances in molecular technologies have opened up unprecedented opportunities for molecular ecologists to better understand the molecular basis of traits of ecological and evolutionary importance in almost any organism. Nevertheless, reliable and systematic inference of functionally relevant information from these masses of data remains challenging. The aim of this review is to highlight how the Gene Ontology (GO) database can be of use in resolving this challenge. The GO provides a largely species-neutral source of information on the molecular function, biological role and cellular location of tens of thousands of gene products. As it is designed to be species-neutral, the GO is well suited for cross-species use, meaning that, functional annotation derived from model organisms can be transferred to inferred orthologues in newly sequenced species. In other words, the GO can provide gene annotation information for species with nonannotated genomes. In this review, we describe the GO database, how functional information is linked with genes/gene products in model organisms, and how molecular ecologists can utilize this information to annotate their own data. Then, we outline various applications of GO for enhancing the understanding of molecular basis of traits in ecologically relevant species. We also highlight potential pitfalls, provide step-by-step recommendations for conducting a sound study in nonmodel organisms, suggest avenues for future research and outline a strategy for maximizing the benefits of a more ecological and evolutionary genomics-oriented ontology by ensuring its compatibility with the GO.
Publisher: Springer Science and Business Media LLC
Date: 07-06-2021
Publisher: Cold Spring Harbor Laboratory
Date: 16-05-2017
DOI: 10.1101/138024
Abstract: Epithelial-mesenchymal transition (EMT) is a process whereby cells undergo reversible phenotypic change, losing epithelial characteristics and acquiring mesenchymal attributes. While EMT underlies normal, physiological programs in embryonic tissue development and adult wound healing, it also contributes to cancer progression by facilitating metastasis and altering drug sensitivity. Using a cell model of EMT (human mammary epithelial (HMLE) cells), we show that miRNAs act as an additional regulatory layer over and above the activity of the transcription factors with which they are closely associated. In this context, miRNAs serve to both enhance expression changes for genes with EMT function, whilst simultaneously reducing transcriptional noise in non-EMT genes. We find that members of the polycistronic miR-200c~141 and miR-183~182 clusters (which are decreased during HMLE cell EMT and are associated with epithelial gene expression in breast cancer patients) co-regulate common targets and pathways to enforce an epithelial phenotype. We demonstrate their combinatorial effects are apparent much closer to endogenous expression levels (and orders of magnitude lower than used in most studies). Importantly, the low levels of combinatorial miRNAs that are required to exert biological function ameliorate the “off-target” effects on gene expression that are a characteristic of supra-physiologic miRNA manipulation. We argue that high levels of over-expression characteristic of many miRNA functional studies have led to an over-estimation of the effect of many miRNAs in EMT regulation, with over 130 in idual miRNAs directly implicated as drivers of EMT. We propose that the functional effects of co-regulated miRNAs that we demonstrate here more-accurately reflects the endogenous post-transcriptional regulation of pathways, networks and processes, and illustrates that the post-transcriptional miRNA regulatory network is fundamentally cooperative.
Publisher: SAGE Publications
Date: 2014
DOI: 10.4137/CIN.S13630
Abstract: The emergence of transcriptomics, fuelled by high-throughput sequencing technologies, has changed the nature of cancer research and resulted in a massive accumulation of data. Computational analysis, integration, and data visualization are now major bottlenecks in cancer biology and translational research. Although many tools have been brought to bear on these problems, their use remains unnecessarily restricted to computational biologists, as many tools require scripting skills, data infrastructure, and powerful computational facilities. New user-friendly, integrative, and automated analytical approaches are required to make computational methods more generally useful to the research community. Here we present INsPeCT (INtegrative Platform for Cancer Transcriptomics), which allows users with basic computer skills to perform comprehensive in-silico analyses of microarray, ChlPseq, and RNA-seq data. INsPeCT supports the selection of interesting genes for advanced functional analysis. Included in its automated workflows are (i) a novel analytical framework, RMaNI (regulatory module network inference), which supports the inference of cancer subtype-specific transcriptional module networks and the analysis of modules and (ii) WGCNA (weighted gene co-expression network analysis), which infers modules of highly correlated genes across microarray s les, associated with s le traits, eg survival time. INsPeCT is available free of cost from Bioinformatics Resource Australia-EMBL and can be accessed at inspect.braembl.org.au .
Publisher: Wiley
Date: 27-04-2022
DOI: 10.1111/ELE.14013
Abstract: Predicting the impacts of multiple stressors is important for informing ecosystem management but is impeded by a lack of a general framework for predicting whether stressors interact synergistically, additively or antagonistically. Here, we use process‐based models to study how interactions generalise across three levels of biological organisation (physiological, population and consumer‐resource) for a two‐stressor experiment on a seagrass model system. We found that the same underlying processes could result in synergistic, additive or antagonistic interactions, with interaction type depending on initial conditions, experiment duration, stressor dynamics and consumer presence. Our results help explain why meta‐analyses of multiple stressor experimental results have struggled to identify predictors of consistently non‐additive interactions in the natural environment. Experiments run over extended temporal scales, with treatments across gradients of stressor magnitude, are needed to identify the processes that underpin how stressors interact and provide useful predictions to management.
Publisher: Elsevier BV
Date: 03-2019
DOI: 10.1016/J.ECOENV.2018.11.092
Abstract: Galaxolide (HHCB) is used as a fragrance ingredient in household and personal care products, and has been ubiquitously detected in the environment. Here we investigated the fate of HHCB in subtropical freshwater microcosms, and evaluated effects of sediment-associated HHCB on a biological community consisting of algae, Daphnia, benthic macroinvertebrates and bacteria. The concentrations of sediment-associated HHCB did not change significantly during a 28 days exposure period, but HHCB accumulated in worms with biota-sediment accumulation-factor (BSAF) values in the range of 0.29-0.66 for Branchiura sowerbyi and 0.94-2.11 for Limnodrilus hoffmeisteri. There was no significant effects of HHCB (30 μg/g dry weight (dw) sediment) on chlorophyll-a content, sediment bacterial community composition, and survival and growth of benthic macroinvertebrates. However, the presence of benthic macroinvertebrates altered the sediment bacterial community structure relative to microcosms without introduced organisms. The findings of this study suggest that a single high-dose of HHCB, over 28 days, at environmentally relevant concentrations would not impose direct toxicological risks to aquatic organisms such as benthic macroinvertebrates.
Publisher: Springer Science and Business Media LLC
Date: 11-05-2021
DOI: 10.1038/S41467-021-22888-5
Abstract: Intellectual disability (ID) and autism spectrum disorder (ASD) are the most common neurodevelopmental disorders and are characterized by substantial impairment in intellectual and adaptive functioning, with their genetic and molecular basis remaining largely unknown. Here, we identify biallelic variants in the gene encoding one of the Elongator complex subunits, ELP2, in patients with ID and ASD. Modelling the variants in mice recapitulates the patient features, with brain imaging and tractography analysis revealing microcephaly, loss of white matter tract integrity and an aberrant functional connectome. We show that the Elp2 mutations negatively impact the activity of the complex and its function in translation via tRNA modification. Further, we elucidate that the mutations perturb protein homeostasis leading to impaired neurogenesis, myelin loss and neurodegeneration. Collectively, our data demonstrate an unexpected role for tRNA modification in the pathogenesis of monogenic ID and ASD and define Elp2 as a key regulator of brain development.
Publisher: Rockefeller University Press
Date: 25-02-2020
DOI: 10.1084/JEM.20191421
Abstract: Despite increasing recognition of the importance of GM-CSF in autoimmune disease, it remains unclear how GM-CSF is regulated at sites of tissue inflammation. Using GM-CSF fate reporter mice, we show that synovial NK cells produce GM-CSF in autoantibody-mediated inflammatory arthritis. Synovial NK cells promote a neutrophilic inflammatory cell infiltrate, and persistent arthritis, via GM-CSF production, as deletion of NK cells, or specific ablation of GM-CSF production in NK cells, abrogated disease. Synovial NK cell production of GM-CSF is IL-18–dependent. Furthermore, we show that cytokine-inducible SH2-containing protein (CIS) is crucial in limiting GM-CSF signaling not only during inflammatory arthritis but also in experimental allergic encephalomyelitis (EAE), a murine model of multiple sclerosis. Thus, a cellular cascade of synovial macrophages, NK cells, and neutrophils mediates persistent joint inflammation via production of IL-18 and GM-CSF. Endogenous CIS provides a key brake on signaling through the GM-CSF receptor. These findings shed new light on GM-CSF biology in sterile tissue inflammation and identify several potential therapeutic targets.
Publisher: Wiley
Date: 12-2009
Abstract: Protein-protein interactions (PPIs) underpin key biological processes in cells. Describing and interpreting this network of interactions is a key focus of computational systems biology. While mouse is commonly used as a model system for mammalian biology, the description of mouse PPIs available in public interaction databases is remarkably poor. Collectively, public resources such as BIND, IntACT and MINT contain only a few thousand mouse PPIs, far behind the many tens or hundreds of thousands likely to exist. To supplement this lack and to take advantage of other high-throughput omic data sets in mouse, here we identify that portion of the human interactome with orthologs in mouse, and from that infer a mouse interolog network. By inferring interactions in mouse based on only the most closely related species with abundant PPI data (human), we create a view of mouse interactions enriched for shared mammalian biological processes. We also demonstrate that available methods for determining orthologs between even closely related species produce distinctly different results, and we propose an integrated view of mouse-human orthology from which to infer a broader interolog network.
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/0008-5472.C.6513609.V1
Abstract: Abstract The recognition of the immune system as a key component of the tumor microenvironment (TME) led to promising therapeutics. Because such therapies benefit only subsets of patients, understanding the activities of immune cells in the TME is required. Eosinophils are an integral part of the TME especially in mucosal tumors. Nonetheless, their role in the TME and the environmental cues that direct their activities are largely unknown. We report that breast cancer lung metastases are characterized by resident and recruited eosinophils. Eosinophil recruitment to the metastatic sites in the lung was regulated by G protein–coupled receptor signaling but independent of CCR3. Functionally, eosinophils promoted lymphocyte-mediated antitumor immunity. Transcriptome and proteomic analyses identified the TME rather than intrinsic differences between eosinophil subsets as a key instructing factor directing antitumorigenic eosinophil activities. Specifically, TNFα/IFNγ–activated eosinophils facilitated CD4 sup + /sup and CD8 sup + /sup T-cell infiltration and promoted antitumor immunity. Collectively, we identify a mechanism by which the TME trains eosinophils to adopt antitumorigenic properties, which may lead to the development of eosinophil-targeted therapeutics. Significance: These findings demonstrate antitumor activities of eosinophils in the metastatic tumor microenvironment, suggesting that harnessing eosinophil activity may be a viable clinical strategy in patients with cancer. /
Publisher: Frontiers Media SA
Date: 27-09-2016
Publisher: Springer Science and Business Media LLC
Date: 06-11-2018
Publisher: Wiley
Date: 16-03-2006
DOI: 10.1111/J.1600-0854.2006.00407.X
Abstract: Application of a computational membrane organization prediction pipeline, MemO, identified putative type II membrane proteins as proteins predicted to encode a single alpha-helical transmembrane domain (TMD) and no signal peptides. MemO was applied to RIKEN's mouse isoform protein set to identify 1436 non-overlapping genomic regions or transcriptional units (TUs), which encode exclusively type II membrane proteins. Proteins with overlapping predicted InterPro and TMDs were reviewed to discard false positive predictions resulting in a dataset comprised of 1831 transcripts in 1408 TUs. This dataset was used to develop a systematic protocol to document subcellular localization of type II membrane proteins. This approach combines mining of published literature to identify subcellular localization data and a high-throughput, polymerase chain reaction (PCR)-based approach to experimentally characterize subcellular localization. These approaches have provided localization data for 244 and 169 proteins. Type II membrane proteins are localized to all major organelle compartments however, some biases were observed towards the early secretory pathway and punctate structures. Collectively, this study reports the subcellular localization of 26% of the defined dataset. All reported localization data are presented in the LOCATE database (www.locate.imb.uq.edu.au).
Publisher: Springer Science and Business Media LLC
Date: 07-10-2010
Abstract: The use of ontologies to control vocabulary and structure annotation has added value to genome-scale data, and contributed to the capture and re-use of knowledge across research domains. Gene Ontology (GO) is widely used to capture detailed expert knowledge in genomic-scale datasets and as a consequence has grown to contain many terms, making it unwieldy for many applications. To increase its ease of manipulation and efficiency of use, subsets called GO slims are often created by collapsing terms upward into more general, high-level terms relevant to a particular context. Creation of a GO slim currently requires manipulation and editing of GO by an expert (or community) familiar with both the ontology and the biological context. Decisions about which terms to include are necessarily subjective, and the creation process itself and subsequent curation are time-consuming and largely manual. Here we present an objective framework for generating customised ontology slims for specific annotated datasets, exploiting information latent in the structure of the ontology graph and in the annotation data. This framework combines ontology engineering approaches, and a data-driven algorithm that draws on graph and information theory. We illustrate this method by application to GO, generating GO slims at different information thresholds, characterising their depth of semantics and demonstrating the resulting gains in statistical power. Our GO slim creation pipeline is available for use in conjunction with any GO-annotated dataset, and creates dataset-specific, objectively defined slims. This method is fast and scalable for application to other biomedical ontologies.
Publisher: Elsevier BV
Date: 07-2012
Publisher: MDPI AG
Date: 13-05-2022
Abstract: The development of therapies that target specific disease subtypes has dramatically improved outcomes for patients with breast cancer. However, survival gains have not been uniform across patients, even within a given molecular subtype. Large collections of publicly available drug screening data matched with transcriptomic measurements have facilitated the development of computational models that predict response to therapy. Here, we generated a series of predictive gene signatures to estimate the sensitivity of breast cancer s les to 90 drugs, comprising FDA-approved drugs or compounds in early development. To achieve this, we used a cell line-based drug screen with matched transcriptomic data to derive in silico models that we validated in large independent datasets obtained from cell lines and patient-derived xenograft (PDX) models. Robust computational signatures were obtained for 28 drugs and used to predict drug efficacy in a set of PDX models. We found that our signature for cisplatin can be used to identify tumors that are likely to respond to this drug, even in absence of the BRCA-1 mutation routinely used to select patients for platinum-based therapies. This clinically relevant observation was confirmed in multiple PDXs. Our study foreshadows an effective delivery approach for precision medicine.
Publisher: Elsevier BV
Date: 09-2019
DOI: 10.1016/J.SCITOTENV.2019.02.455
Abstract: A workshop was held in Wageningen, The Netherlands, in September 2017 to collate data and literature on three aquatic ecosystem types (agricultural drainage ditches, urban floodplains, and urban estuaries), and develop a general framework for the assessment of multiple stressors on the structure and functioning of these systems. An assessment framework considering multiple stressors is crucial for our understanding of ecosystem responses within a multiply stressed environment, and to inform appropriate environmental management strategies. The framework consists of two components: (i) problem identification and (ii) impact assessment. Both assessments together proceed through the following steps: 1) ecosystem selection 2) identification of stressors and quantification of their intensity 3) identification of receptors or sensitive groups for each stressor 4) identification of stressor-response relationships and their potential interactions 5) construction of an ecological model that includes relevant functional groups and endpoints 6) prediction of impacts of multiple stressors, 7) confirmation of these predictions with experimental and monitoring data, and 8) potential adjustment of the ecological model. Steps 7 and 8 allow the assessment to be adaptive and can be repeated until a satisfactory match between model predictions and experimental and monitoring data has been obtained. This paper is the preface of the MAEGA (Making Aquatic Ecosystems Great Again) special section that includes three associated papers which are also published in this volume, which present applications of the framework for each of the three aquatic systems.
Publisher: Cold Spring Harbor Laboratory
Date: 07-12-2021
DOI: 10.1101/2021.12.05.471338
Abstract: Peptide identity propagation (PIP) can substantially reduce missing values in label-free mass spectrometry quantification by transferring peptides identified by tandem mass (MS/MS) spectra in one run to experimentally related runs where the peptides are not identified by MS/MS. The existing frameworks for matching identifications between runs perform peak tracing and propagation based on similarity of precursor features using only a limited number of dimensions available in MS1 data. These approaches do not produce accompanying confidence estimates and hence cannot filter probable false positive identity transfers. We introduce an embedding based PIP that uses a higher dimensional representation of MS1 measurements that is optimized to capture peptide identities using deep neural networks. We developed a propagation framework that works entirely on MaxQuant results. Current PIP workflows typically perform propagation mainly using two feature dimensions, and rely on deterministic tolerances for identification transfer. Our framework overcomes both these limitations while additionally assigning probabilities to each transferred identity. The proposed embedding approach enables quantification of the empirical false discovery rate (FDR) for peptide identification, while also increasing depth of coverage through coembedding the runs from the experiment with experimental libraries. In published datasets with technical and biological variability, we demonstrate that our method reduces missing values in MaxQuant results, maintains high quantification precision and accuracy, and low false transfer rate.
Publisher: American Association for Cancer Research (AACR)
Date: 30-07-2021
DOI: 10.1158/1541-7786.MCR-21-0117
Abstract: Despite preclinical data indicating SOX9 plays a key role in SHH-MB biology, our data argue against SOX9 as a viable therapeutic target.
Publisher: Oxford University Press (OUP)
Date: 02-08-2019
DOI: 10.1093/NAR/GKZ664
Abstract: Epithelial–mesenchymal transition (EMT) has been a subject of intense scrutiny as it facilitates metastasis and alters drug sensitivity. Although EMT-regulatory roles for numerous miRNAs and transcription factors are known, their functions can be difficult to disentangle, in part due to the difficulty in identifying direct miRNA targets from complex datasets and in deciding how to incorporate ‘indirect’ miRNA effects that may, or may not, represent biologically relevant information. To better understand how miRNAs exert effects throughout the transcriptome during EMT, we employed Exon–Intron Split Analysis (EISA), a bioinformatic technique that separates transcriptional and post-transcriptional effects through the separate analysis of RNA-Seq reads mapping to exons and introns. We find that in response to the manipulation of miRNAs, a major effect on gene expression is transcriptional. We also find extensive co-ordination of transcriptional and post-transcriptional regulatory mechanisms during both EMT and mesenchymal to epithelial transition (MET) in response to TGF-β or miR-200c respectively. The prominent transcriptional influence of miRNAs was also observed in other datasets where miRNA levels were perturbed. This work cautions against a narrow approach that is limited to the analysis of direct targets, and demonstrates the utility of EISA to examine complex regulatory networks involving both transcriptional and post-transcriptional mechanisms.
Publisher: Royal Society of Chemistry (RSC)
Date: 2013
DOI: 10.1039/C2MB25300C
Abstract: Membrane microdomains such as lipid rafts and caveolae regulate a myriad of cellular functions including cell signalling, protein trafficking, cell viability, and cell movement. They have been implicated in diseases such as cancer, diabetes and Alzheimer's disease, highlighting the essential role they play in cell processes. Despite much research and debate on the size, composition and dynamics of membrane microdomains, the molecular mechanism(s) of their action remain poorly understood. Most studies have dealt solely with the content and properties of the membrane microdomain as an entity in itself. However, recent work shows that membrane microdomain disruption has wide ranging effects on other subcellular compartments, and the cell as a whole. Hence we propose that a systems approach incorporating many cellular attributes such as subcellular localisation is required in order to understand the global impact of microdomains on cell function. Although analysis of sub-proteome changes already provides additional insight, we further propose biological network analysis of functional proteomics data to capture effects at the systems level. In this review, we highlight the use of protein-protein interactions networks and mixed networks to portray and visualize the relationships between proteins within and between subcellular fractions. Such a systems analysis will be required to improve our understanding of the full cellular function of membrane microdomains.
Publisher: Cold Spring Harbor Laboratory
Date: 06-2003
DOI: 10.1101/GR.983703
Abstract: We have developed a computational strategy to identify the set of soluble proteins secreted into the extracellular environment of a cell. Within the protein sequences predominantly derived from the RIKEN representative transcript and protein set, we identified 2033 unique soluble proteins that are potentially secreted from the cell. These proteins contain a signal peptide required for entry into the secretory pathway and lack any transmembrane domains or intracellular localization signals. This class of proteins, which we have termed the mouse secretome, included novel proteins and 92 proteins amino acids in length. Functional analysis of the secretome included identification of human orthologs, functional units based on InterPro and SCOP Superfamily predictions, and expression of the proteins within the RIKEN READ microarray database. To highlight the utility of this information, we discuss the CUB domain-containing protein family.
Publisher: Research Square Platform LLC
Date: 02-11-2022
DOI: 10.21203/RS.3.RS-2196744/V1
Abstract: Ikaros family transcription factors regulate lymphocyte biology and are targets of the immunomodulatory imide drugs (IMiDs) for hematological maligancies. Ikaros (Ikzf1/IKZF1) is the most broadly expressed family member in lymphocytes, yet its role in innate lymphopoiesis was unknown. Here we used conditional gene inactivation to reveal that Ikaros is required for normal NK cell development. Ikzf1-null NK cells had impaired IL-15 signaling, manifesting in reduced proliferation and enhanced apoptosis. Cish and Socs2, known negative regulators of IL-15 signaling are increased in Ikzf1-null NK cells and are direct targets of Ikaros-mediated repression. Ikzf1-null NK cells have extensive transcriptional alterations with a striking reduction in expression of genes encoding AP-1 transcriptional complexes as well as a compensatory increase in Ikaros-family members, Ikzf2 and Ikzf3. Deletion of both Ikzf1 and Ikzf3 in NK cells further reduced AP-1 gene expression culminating in a complete loss of peripheral NK cells in mice. Inactivation of Ikaros-family members in human NK cells also impaired their fitness and function, while genetic screens revealed a co-dependency on IKZF1 and in idual AP-1 genes in hematopoietic cell survival, suggesting that IMiDs induce apoptosis of malignant IKZF1/3-dependent cells by ablating AP-1 transcriptional activity. Collectively we show the Ikaros-family are novel regulators of cytokine responsiveness and essential for promoting AP-1 transcriptional activity required for NK cell development.
Publisher: Mary Ann Liebert Inc
Date: 06-2014
Abstract: Nuclear receptors (NRs) play a key role in endocrine signaling and metabolism and are important therapeutic targets in a number of hormone-dependent malignancies. Studies on the role of NRs in thyroid cancer are limited. The objective of the study was to examine systematically the expression of the 48 human NRs in a series of benign and malignant thyroid tissues. Within the papillary carcinoma cohort, we sought to determine if NR expression differed significantly by BRAF mutation status. RNA was isolated from multinodular goiter (MNG n=6), papillary carcinoma (PTC, n=14), follicular carcinoma (FC n=5), and Hürthle cell carcinoma (HCC n=7). The 48 human NRs were profiled in this panel by quantitative real time polymerase chain reaction. Protein expression for selected NRs (Rev-erbα and LXR-β) was examined by immunohistochemistry (IHC) on tissue microarrays comprising benign and malignant thyroid tissues. Across all groups of benign and malignant thyroid tissue, there was prominent expression of LXR-β and ROR-γ. Key findings in PTC were marked overexpression of RXR-γ and Rev-erbα compared to MNG. Within the PTC cohort, when BRAF(V600E) tumors were compared with wild type BRAF, there was relative upregulation of RXR-γ and Rev-erbα and downregulation of AR, ERR-γ, and ROR-γ. In FC, EAR-2 was overexpressed, while PPAR-α and PPAR-δ were underexpressed compared to MNG. The NR expression profile of HCC was distinct, characterized by significant downregulation of a wide range of NRs. IHC for Rev-erbα and LXR-β localized protein expression to the tumor cells. Moderate to strong Rev-erbα immunostaining was seen in 22 out of 23 PTC, and, overall, staining was stronger than in the benign group. These results represent the first systematic examination of NR expression in thyroid cancer. Our finding of tumor-specific patterns of NR expression, as well as significant differences in NR expression between BRAF(V600E) and wild type BRAF PTC, provides a basis for further mechanistic studies and highlights potential novel therapeutic targets for this malignancy.
Publisher: Cold Spring Harbor Laboratory
Date: 29-04-2019
DOI: 10.1101/621698
Abstract: Cell extrusion is a morphogenetic process that is implicated in epithelial homeostasis and highly dependent on the cellular insult and context. Minorities of cells expressing HRas V12 or undergoing apoptosis are typically extruded apically in vertebrate cells. However, basal extrusion (delamination) predominates when mammalian cells express oncogenic KRas and during development in Drosophila. To explore if the morphogenetic transcription factor, Snail, induces extrusion, we inducibly expressed a metabolically stabilized Snail 6SA transgene mosaically in confluent MCF-7 monolayers. We found that the morphogenetic impact of Snail 6SA was critically influenced by the proportion of cells in which it was expressed. When expressed in small clusters ( cells) within confluent monolayers, Snail 6SA expression induced apical cell extrusion. In contrast, confluent cultures of Snail 6SA expressing cells were retained in the monolayer to eventually undergo basal extrusion (delamination). Transcriptomic profiling revealed that Snail 6SA did not substantively alter the balance of epithelial:mesenchymal genes. However, we identified a gene transcriptional network that led to the upregulation of RhoA signalling, actomyosin contractility and reduced basal adhesion in Snail 6SA expressing cells. We show that this was necessary to drive both apical extrusion and basal delamination. Thus, contractile upregulation by RhoA along with weakened basal adhesion provides a pathway for Snail to influence epithelial morphogenesis independently of classic Epithelial to Mesenchymal Transition (EMT).
Publisher: F1000 Research Ltd
Date: 16-05-2022
DOI: 10.12688/OPENRESEUROPE.14283.2
Abstract: By 2050, the global population is predicted to reach nine billion, with almost three quarters living in cities. The road to 2050 will be marked by changes in land use, climate, and the management of water and food across the world. These global changes (GCs) will likely affect the emissions, transport, and fate of chemicals, and thus the exposure of the natural environment to chemicals. ECORISK2050 is a Marie Skłodowska-Curie Innovative Training Network that brings together an interdisciplinary consortium of academic, industry and governmental partners to deliver a new generation of scientists, with the skills required to study and manage the effects of GCs on chemical risks to the aquatic environment. The research and training goals are to: (1) assess how inputs and behaviour of chemicals from agriculture and urban environments are affected by different environmental conditions, and how different GC scenarios will drive changes in chemical risks to human and ecosystem health (2) identify short-to-medium term adaptation and mitigation strategies, to abate unacceptable increases to risks, and (3) develop tools for use by industry and policymakers for the assessment and management of the impacts of GC-related drivers on chemical risks. This project will deliver the next generation of scientists, consultants, and industry and governmental decision-makers who have the knowledge and skillsets required to address the changing pressures associated with chemicals emitted by agricultural and urban activities, on aquatic systems on the path to 2050 and beyond.
Publisher: Springer Science and Business Media LLC
Date: 04-01-2022
DOI: 10.1186/S12859-021-04504-X
Abstract: Protein-protein interactions (PPIs) are critical to normal cellular function and are related to many disease pathways. A range of protein functions are mediated and regulated by protein interactions through post-translational modifications (PTM). However, only 4% of PPIs are annotated with PTMs in biological knowledge databases such as IntAct, mainly performed through manual curation, which is neither time- nor cost-effective. Here we aim to facilitate annotation by extracting PPIs along with their pairwise PTM from the literature by using distantly supervised training data using deep learning to aid human curation. We use the IntAct PPI database to create a distant supervised dataset annotated with interacting protein pairs, their corresponding PTM type, and associated abstracts from the PubMed database. We train an ensemble of BioBERT models—dubbed PPI-BioBERT-x10—to improve confidence calibration. We extend the use of ensemble average confidence approach with confidence variation to counteract the effects of class imbalance to extract high confidence predictions. The PPI-BioBERT-x10 model evaluated on the test set resulted in a modest F1-micro 41.3 (P =5 8.1, R = 32.1). However, by combining high confidence and low variation to identify high quality predictions, tuning the predictions for precision, we retained 19% of the test predictions with 100% precision. We evaluated PPI-BioBERT-x10 on 18 million PubMed abstracts and extracted 1.6 million (546507 unique PTM-PPI triplets) PTM-PPI predictions, and filter $$\\approx 5700$$ ≈ 5700 (4584 unique) high confidence predictions. Of the 5700, human evaluation on a small randomly s led subset shows that the precision drops to 33.7% despite confidence calibration and highlights the challenges of generalisability beyond the test set even with confidence calibration. We circumvent the problem by only including predictions associated with multiple papers, improving the precision to 58.8%. In this work, we highlight the benefits and challenges of deep learning-based text mining in practice, and the need for increased emphasis on confidence calibration to facilitate human curation efforts.
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22526535
Abstract: S1. Sox 9 and Sox 2 immunoreactivity in the developing cerebellum
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22526532
Abstract: S2. Math1CrePtchlox/Ptchlox Math1 GFP mice display GFP expression in the majority of tumour cells
Publisher: Elsevier BV
Date: 08-2023
Publisher: Oxford University Press (OUP)
Date: 11-11-2014
DOI: 10.1093/NAR/GKU1131
Publisher: Oxford University Press (OUP)
Date: 04-11-2012
DOI: 10.1093/BIOINFORMATICS/BTR610
Abstract: Motivation: Protein–protein interactions (PPIs) are pivotal for many biological processes and similarity in Gene Ontology (GO) annotation has been found to be one of the strongest indicators for PPI. Most GO-driven algorithms for PPI inference combine machine learning and semantic similarity techniques. We introduce the concept of inducers as a method to integrate both approaches more effectively, leading to superior prediction accuracies. Results: An inducer (ULCA) in combination with a Random Forest classifier compares favorably to several sequence-based methods, semantic similarity measures and multi-kernel approaches. On a newly created set of high-quality interaction data, the proposed method achieves high cross-species prediction accuracies (Area under the ROC curve ≤ 0.88), rendering it a valuable companion to sequence-based methods. Availability: Software and datasets are available at bioinformatics.org.au/go2ppi/ Contact: m.ragan@uq.edu.au
Publisher: Springer Science and Business Media LLC
Date: 2012
DOI: 10.1186/GM340
Publisher: Elsevier BV
Date: 09-2019
DOI: 10.1016/J.SCITOTENV.2019.03.497
Abstract: In September 2017, a workshop was held at Wageningen University and Research to determine the current state of knowledge of multiple stressor effects on aquatic ecosystems and to assess how to improve prediction of these effects. We developed a theoretical framework that integrates species-level responses to stressors to predict how these effects propagate through higher levels of biological organisation. Here, we present the application of the framework for drainage ditch ecosystems in the Netherlands. We used food webs to assess single and multiple stressor effects of common stressors on ditch communities. We reviewed the literature for the effects of targeted stressors (nutrients, pesticides, dredging and mowing, salinization, and siltation) on each functional group present in the food web and qualitatively assessed the relative sensitivity of groups. Using this information, we created a stressor-response matrix of positive and negative direct effects of each stressor-functional group combination. Fungicides, salinization, and sedimentation were identified as particularly detrimental to most groups, although destructive management practices, such as dredging with almost complete community removal, would take precedence depending on frequency. Using the stressor-response matrix we built, first, a series of conceptual null models of single stressor effects on food web structure and, second, a series of additive null models to illustrate potential paired-stressor effects. We compared these additive null models with published studies of the same pairs of combined single stressors to explore more complex interactions. Our approach serves as a first-step to considering multiple stressor scenarios in systems that are understudied or data-poor and as a baseline from which more complex models that include indirect effects and quantitative data may be developed. We make specific suggestions for appropriate management strategies that could be taken to support the bio ersity of these systems for in idual stressors and their combined impacts.
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22526526
Abstract: S4. Single cell sequencing data analysis
Publisher: Elsevier BV
Date: 05-2014
Publisher: Springer Science and Business Media LLC
Date: 25-02-2009
Abstract: Many biological processes are mediated by dynamic interactions between and among proteins. In order to interact, two proteins must co-occur spatially and temporally. As protein-protein interactions (PPIs) and subcellular location (SCL) are discovered via separate empirical approaches, PPI and SCL annotations are independent and might complement each other in helping us to understand the role of in idual proteins in cellular networks. We expect reliable PPI annotations to show that proteins interacting in vivo are co-located in the same cellular compartment. Our goal here is to evaluate the potential of using PPI annotation in determining SCL of proteins in human, mouse, fly and yeast, and to identify and quantify the factors that contribute to this complementarity. Using publicly available data, we evaluate the hypothesis that interacting proteins must be co-located within the same subcellular compartment. Based on a large, manually curated PPI dataset, we demonstrate that a substantial proportion of interacting proteins are in fact co-located. We develop an approach to predict the SCL of a protein based on the SCL of its interaction partners, given sufficient confidence in the interaction itself. The frequency of false positive PPIs can be reduced by use of six lines of supporting evidence, three based on type of recorded evidence (empirical approach, multiplicity of databases, and multiplicity of literature citations) and three based on type of biological evidence (inferred biological process, domain-domain interactions, and orthology relationships), with biological evidence more-effective than recorded evidence. Our approach performs better than four existing prediction methods in identifying the SCL of membrane proteins, and as well as or better for soluble proteins. Understanding cellular systems requires knowledge of the SCL of interacting proteins. We show how PPI data can be used more effectively to yield reliable SCL predictions for both soluble and membrane proteins. Scope exists for further improvement in our understanding of cellular function through consideration of the biological context of molecular interactions.
Publisher: Elsevier BV
Date: 10-2006
DOI: 10.1016/J.MODGEP.2006.02.001
Abstract: The E11.5 mouse metanephros is comprised of a T-stage ureteric epithelial tubule sub- ided into tip and trunk cells surrounded by metanephric mesenchyme (MM). Tip cells are induced to undergo branching morphogenesis by the MM. In contrast, signals within the mesenchyme surrounding the trunk prevent ectopic branching of this region. In order to identify novel genes involved in the molecular regulation of branching morphogenesis we compared the gene expression profiles of isolated tip, trunk and MM cells using Compugen mouse long oligo microarrays. We identified genes enriched in the tip epithelium, sim-1, Arg2, Tacstd1, Crlf-1 and BMP7 genes enriched in the trunk epithelium, Innp1, Itm2b, Mkrn1, SPARC, Emu2 and Gsta3 and genes spatially restricted to the mesenchyme surrounding the trunk, CSPG2 and CV-2, with overlapping and complimentary expression to BMP4, respectively. This study has identified genes spatially expressed in regions of the developing kidney involved in branching morphogenesis, nephrogenesis and the development of the collecting duct system, calyces, renal pelvis and ureter.
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/1541-7786.22526529
Abstract: S3. Sox9 expression quantification
Publisher: Springer Science and Business Media LLC
Date: 03-06-2019
DOI: 10.1038/S41598-019-44489-5
Abstract: RNA secondary structure may influence many cellular processes, including RNA processing, stability, localization, and translation. Single-nucleotide variations (SNVs) that alter RNA secondary structure, referred to as riboSNitches, are potentially causative of human diseases, especially in untranslated regions (UTRs) and noncoding RNAs (ncRNAs). The functions of somatic mutations that act as riboSNitches in cancer development remain poorly understood. In this study, we developed a computational pipeline called SNIPER (riboSNitch-enriched or depleted elements in cancer genomes), which employs MeanDiff and EucDiff to detect riboSNitches and then identifies riboSNitch-enriched or riboSNitch-depleted non-coding elements across tumors. SNIPER is available at github: uzhixi/SNIPER/ . We found that riboSNitches were more likely to be pathogenic. Moreover, we predicted several UTRs and lncRNAs (long non-coding RNA) that significantly enriched or depleted riboSNitches in cancer genomes, indicative of potential cancer driver or essential noncoding elements. Our study highlights the possibly neglected importance of RNA secondary structure in cancer genomes and provides a new strategy to identify new cancer-associated genes.
Publisher: Springer Science and Business Media LLC
Date: 15-06-2020
DOI: 10.1038/S41467-020-16828-Y
Abstract: B lymphoid development is initiated by the differentiation of hematopoietic stem cells into lineage committed progenitors, ultimately generating mature B cells. This highly regulated process generates clonal immunological ersity via recombination of immunoglobulin V, D and J gene segments. While several transcription factors that control B cell development and V(D)J recombination have been defined, how these processes are initiated and coordinated into a precise regulatory network remains poorly understood. Here, we show that the transcription factor ETS Related Gene ( Erg ) is essential for early B lymphoid differentiation. Erg initiates a transcriptional network involving the B cell lineage defining genes, Ebf1 and Pax5 , which directly promotes expression of key genes involved in V(D)J recombination and formation of the B cell receptor. Complementation of Erg deficiency with a productively rearranged immunoglobulin gene rescued B lineage development, demonstrating that Erg is an essential and stage-specific regulator of the gene regulatory network controlling B lymphopoiesis.
Publisher: University of Queensland Library
Date: 2022
DOI: 10.14264/40C2222
Publisher: Springer Science and Business Media LLC
Date: 2013
DOI: 10.1186/GM468
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 09-2004
Location: Australia
Location: Australia
No related grants have been discovered for Melissa Davis.