ORCID Profile
0000-0002-5053-4540
Current Organisations
oNKo-innate Pty Ltd
,
Monash University
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Oxford University Press (OUP)
Date: 05-05-2015
Publisher: IEEE
Date: 08-2010
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.22543860.V1
Abstract: List of the tools and packages used in the manuscript
Publisher: Physiome Incorporated
Date: 27-08-2020
DOI: 10.36903/PHYSIOME.12871070
Abstract: The Na+/K+ATPase is an essential component of cardiac electrophysiology, maintaining physiological Na+ and K+ concentrations over successive heart beats. Terkildsen et al. (2007) developed a model of the ventricular myocyte Na+/K+ ATPase to study extracellular potassium accumulation during ischaemia, demonstrating the ability to recapitulate a wide range of experimental data, but unfortunately there was no archived code associated with the original manuscript. Here we detail an updated version of the model and provide CellML and MATLAB code to ensure reproducibility and reusability. We note some errors within the original formulation which have been corrected to ensure that the model is thermodynamically consistent, and although this required some reparameterisation, the resulting model still provides a good fit to experimental measurements that demonstrate the dependence of Na+/K+ ATPase pumping rate upon membrane voltage and metabolite concentrations. To demonstrate thermodynamic consistency we also developed a bond graph version of the model. We hope that these models will be useful for community efforts to assemble a whole-cell cardiomyocyte model which facilitates the investigation of cellular energetics.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.22543863.V1
Abstract: Supplementary data containing 25 Supp. figures that support the results of the paper.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.C.6549990
Abstract: 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 i singscore /i 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 i IL15 /i . 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 Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.22542600.V1
Abstract: Supplementary Figures 1-9, & Supplementary Table 2.
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: 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: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.22543857.V1
Abstract: Table S2 is the list of studies identifying genes associated with Exh/Res programs. Table S3 is a list of signatures used for scoring tumour data and performing survival analysis
Publisher: American Association for Cancer Research (AACR)
Date: 19-08-2021
DOI: 10.1158/2326-6066.CIR-21-0137
Abstract: Immunotherapy success in colorectal cancer is mainly limited to patients whose tumors exhibit high microsatellite instability (MSI). However, there is variability in treatment outcomes within this group, which is in part driven by the frequency and characteristics of tumor-infiltrating immune cells. Indeed, the presence of specific infiltrating immune-cell subsets has been shown to correlate with immunotherapy response and is in many cases prognostic of treatment outcome. Tumor-infiltrating lymphocytes (TIL) can undergo distinct differentiation programs, acquiring features of tissue-residency or exhaustion, a process during which T cells upregulate inhibitory receptors, such as PD-1, and lose functionality. Although residency and exhaustion programs of CD8+ T cells are relatively well studied, these programs have only recently been appreciated in CD4+ T cells and remain largely unknown in tumor-infiltrating natural killer (NK) cells. In this study, we used single-cell RNA sequencing (RNA-seq) data to identify signatures of residency and exhaustion in colorectal cancer–infiltrating lymphocytes, including CD8+, CD4+, and NK cells. We then tested these signatures in independent single-cell data from tumor and normal tissue–infiltrating immune cells. Furthermore, we used versions of these signatures designed for bulk RNA-seq data to explore tumor-intrinsic mutations associated with residency and exhaustion from TCGA data. Finally, using two independent transcriptomic datasets from patients with colon adenocarcinoma, we showed that combinations of these signatures, in particular combinations of NK-cell activity signatures, together with tumor-associated signatures, such as TGFβ signaling, were associated with distinct survival outcomes in patients with colon adenocarcinoma.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.22542597
Abstract: Official gene symbols (HGNC) for our 20 NK signature genes and a subset of the results leading to their inclusion during curation, in particular bulk RNA-seq differential expression results and comparison to T cells for single-cell RNA-seq data from Tirosh et al (2016). For further details please refer to the Materials and Methods. LM22: CIBERSORT LM22 lists LM7: Tosolini et al LM7 list.
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: 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: 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: Physiome Incorporated
Date: 27-08-2020
DOI: 10.36903/PHYSIOME.12871070.V1
Abstract: The Na+/K+ATPase is an essential component of cardiac electrophysiology, maintaining physiological Na+ and K+ concentrations over successive heart beats. Terkildsen et al. (2007) developed a model of the ventricular myocyte Na+/K+ ATPase to study extracellular potassium accumulation during ischaemia, demonstrating the ability to recapitulate a wide range of experimental data, but unfortunately there was no archived code associated with the original manuscript. Here we detail an updated version of the model and provide CellML and MATLAB code to ensure reproducibility and reusability. We note some errors within the original formulation which have been corrected to ensure that the model is thermodynamically consistent, and although this required some reparameterisation, the resulting model still provides a good fit to experimental measurements that demonstrate the dependence of Na+/K+ ATPase pumping rate upon membrane voltage and metabolite concentrations. To demonstrate thermodynamic consistency we also developed a bond graph version of the model. We hope that these models will be useful for community efforts to assemble a whole-cell cardiomyocyte model which facilitates the investigation of cellular energetics.
Publisher: The Royal Society
Date: 12-2015
Abstract: The bond graph approach to modelling biochemical networks is extended to allow hierarchical construction of complex models from simpler components. This is made possible by representing the simpler components as thermodynamically open systems exchanging mass and energy via ports. A key feature of this approach is that the resultant models are robustly thermodynamically compliant: the thermodynamic compliance is not dependent on precise numerical values of parameters. Moreover, the models are reusable owing to the well-defined interface provided by the energy ports. To extract bond graph model parameters from parameters found in the literature, general and compact formulae are developed to relate free-energy constants and equilibrium constants. The existence and uniqueness of solutions is considered in terms of fundamental properties of stoichiometric matrices. The approach is illustrated by building a hierarchical bond graph model of glycogenolysis in skeletal muscle.
Publisher: Public Library of Science (PLoS)
Date: 13-10-2021
DOI: 10.1371/JOURNAL.PCBI.1009513
Abstract: It is widely acknowledged that the construction of large-scale dynamic models in systems biology requires complex modelling problems to be broken up into more manageable pieces. To this end, both modelling and software frameworks are required to enable modular modelling. While there has been consistent progress in the development of software tools to enhance model reusability, there has been a relative lack of consideration for how underlying biophysical principles can be applied to this space. Bond graphs combine the aspects of both modularity and physics-based modelling. In this paper, we argue that bond graphs are compatible with recent developments in modularity and abstraction in systems biology, and are thus a desirable framework for constructing large-scale models. We use two ex les to illustrate the utility of bond graphs in this context: a model of a mitogen-activated protein kinase (MAPK) cascade to illustrate the reusability of modules and a model of glycolysis to illustrate the ability to modify the model granularity.
Publisher: Springer Science and Business Media LLC
Date: 15-05-2015
Publisher: Cold Spring Harbor Laboratory
Date: 26-07-2021
DOI: 10.1101/2021.07.26.453900
Abstract: It is widely acknowledged that the construction of large-scale dynamic models in systems biology requires complex modelling problems to be broken up into more manageable pieces. To this end, both modelling and software frameworks are required to enable modular modelling. While there has been consistent progress in the development of software tools to enhance model reusability, there has been a relative lack of consideration for how underlying biophysical principles can be applied to this space. Bond graphs combine the aspects of both modularity and physics-based modelling. In this paper, we argue that bond graphs are compatible with recent developments in modularity and abstraction in systems biology, and are thus a desirable framework for constructing large-scale models. We use two ex les to illustrate the utility of bond graphs in this context: a model of a mitogen-activated protein kinase (MAPK) cascade to illustrate the reusability of modules and a model of glycolysis to illustrate the ability to modify the model granularity. The biochemistry within a cell is complex, being composed of numerous biomolecules and reactions. In order to develop fully detailed mathematical models of cells, smaller submodels need to be constructed and connected together. Software and standards can assist in this endeavour, but challenges remain in ensuring submodels are both consistent with each other and consistent with the fundamental conservation laws of physics. In this paper, we propose a new approach using bond graphs from engineering. In this approach, connections between models are defined using physical conservation laws. We show that this approach is compatible with current software approaches in the field, and can therefore be readily used to incorporate physical consistency into existing model integration methodologies. We illustrate the utility of this approach in streamlining the development of models for a signalling network (the MAPK cascade) and a metabolic network (the glycolysis pathway). The advantage of this approach is that models can be developed in a scalable manner while also ensuring consistency with the laws of physics, enhancing the range of data available to train models. This approach can be used to quickly construct detailed and accurate models of cells, facilitating future advances in biotechnology and personalised medicine.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.22542597.V1
Abstract: Official gene symbols (HGNC) for our 20 NK signature genes and a subset of the results leading to their inclusion during curation, in particular bulk RNA-seq differential expression results and comparison to T cells for single-cell RNA-seq data from Tirosh et al (2016). For further details please refer to the Materials and Methods. LM22: CIBERSORT LM22 lists LM7: Tosolini et al LM7 list.
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: Springer Science and Business Media LLC
Date: 25-11-2016
Publisher: Springer Science and Business Media LLC
Date: 24-11-2014
Publisher: Cold Spring Harbor Laboratory
Date: 26-08-2021
DOI: 10.1101/2021.08.25.457323
Abstract: The advent of next-generation sequencing revealed extensive transcription beyond protein-coding genes, identifying tens of thousands of long non-coding RNAs (lncRNAs). Selected functional ex les raised the possibility that lncRNAs, as a class, may maintain broad regulatory roles. Compellingly, lncRNA expression is strongly linked with adjacent protein-coding gene expression, suggesting a potential cis -regulatory function. Evidence for these regulatory roles may be obtained through careful examination of the precise timing of lncRNA expression relative to adjacent protein-coding genes. Where causal cis -regulatory relationships exist, lncRNA activation is expected to precede changes in adjacent target gene expression. Using an RNA-seq time course of uniquely high temporal resolution, we profiled the expression dynamics of several thousand lncRNAs and protein-coding genes in synchronized, transitioning human cells. Our findings reveal lncRNAs are expressed synchronously with adjacent protein-coding genes. Analysis of lipopolysaccharide-activated mouse dendritic cells revealed the same temporal relationship observed in transitioning human cells. Our findings suggest broad-scale cis -regulatory roles for lncRNAs are not common. The strong association between lncRNAs and adjacent genes may instead indicate an origin as transcriptional by-products from active protein-coding gene promoters and enhancers.
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: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.22542600
Abstract: Supplementary Figures 1-9, & Supplementary Table 2.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.22543854
Abstract: An excel file with several sheets, representing supp. tables S4-S10 in the paper.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.C.6549990.V1
Abstract: 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 i singscore /i 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 i IL15 /i . 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 Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.22543857
Abstract: Table S2 is the list of studies identifying genes associated with Exh/Res programs. Table S3 is a list of signatures used for scoring tumour data and performing survival analysis
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.C.6550434.V1
Abstract: Abstract Immunotherapy success in colorectal cancer is mainly limited to patients whose tumors exhibit high microsatellite instability (MSI). However, there is variability in treatment outcomes within this group, which is in part driven by the frequency and characteristics of tumor-infiltrating immune cells. Indeed, the presence of specific infiltrating immune-cell subsets has been shown to correlate with immunotherapy response and is in many cases prognostic of treatment outcome. Tumor-infiltrating lymphocytes (TIL) can undergo distinct differentiation programs, acquiring features of tissue-residency or exhaustion, a process during which T cells upregulate inhibitory receptors, such as PD-1, and lose functionality. Although residency and exhaustion programs of CD8 sup + /sup T cells are relatively well studied, these programs have only recently been appreciated in CD4 sup + /sup T cells and remain largely unknown in tumor-infiltrating natural killer (NK) cells. In this study, we used single-cell RNA sequencing (RNA-seq) data to identify signatures of residency and exhaustion in colorectal cancer–infiltrating lymphocytes, including CD8 sup + /sup , CD4 sup + /sup , and NK cells. We then tested these signatures in independent single-cell data from tumor and normal tissue–infiltrating immune cells. Furthermore, we used versions of these signatures designed for bulk RNA-seq data to explore tumor-intrinsic mutations associated with residency and exhaustion from TCGA data. Finally, using two independent transcriptomic datasets from patients with colon adenocarcinoma, we showed that combinations of these signatures, in particular combinations of NK-cell activity signatures, together with tumor-associated signatures, such as TGFβ signaling, were associated with distinct survival outcomes in patients with colon adenocarcinoma. /
Publisher: Springer Science and Business Media LLC
Date: 29-04-2023
DOI: 10.1186/S13148-023-01482-0
Abstract: Epigenetic silencing of tumor suppressor genes (TSGs) is a key feature of oncogenesis in hepatocellular carcinoma (HCC). Liver-targeted delivery of CRISPR-activation (CRISPRa) systems makes it possible to exploit chromatin plasticity, by reprogramming transcriptional dysregulation. Using The Cancer Genome Atlas HCC data, we identify 12 putative TSGs with negative associations between promoter DNA methylation and transcript abundance, with limited genetic alterations. All HCC s les harbor at least one silenced TSG, suggesting that combining a specific panel of genomic targets could maximize efficacy, and potentially improve outcomes as a personalized treatment strategy for HCC patients. Unlike epigenetic modifying drugs lacking locus selectivity, CRISPRa systems enable potent and precise reactivation of at least 4 TSGs tailored to representative HCC lines. Concerted reactivation of HHIP , MT1M , PZP , and TTC36 in Hep3B cells inhibits multiple facets of HCC pathogenesis, such as cell viability, proliferation, and migration. By combining multiple effector domains, we demonstrate the utility of a CRISPRa toolbox of epigenetic effectors and gRNAs for patient-specific treatment of aggressive HCC.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.C.6550434
Abstract: Abstract Immunotherapy success in colorectal cancer is mainly limited to patients whose tumors exhibit high microsatellite instability (MSI). However, there is variability in treatment outcomes within this group, which is in part driven by the frequency and characteristics of tumor-infiltrating immune cells. Indeed, the presence of specific infiltrating immune-cell subsets has been shown to correlate with immunotherapy response and is in many cases prognostic of treatment outcome. Tumor-infiltrating lymphocytes (TIL) can undergo distinct differentiation programs, acquiring features of tissue-residency or exhaustion, a process during which T cells upregulate inhibitory receptors, such as PD-1, and lose functionality. Although residency and exhaustion programs of CD8 sup + /sup T cells are relatively well studied, these programs have only recently been appreciated in CD4 sup + /sup T cells and remain largely unknown in tumor-infiltrating natural killer (NK) cells. In this study, we used single-cell RNA sequencing (RNA-seq) data to identify signatures of residency and exhaustion in colorectal cancer–infiltrating lymphocytes, including CD8 sup + /sup , CD4 sup + /sup , and NK cells. We then tested these signatures in independent single-cell data from tumor and normal tissue–infiltrating immune cells. Furthermore, we used versions of these signatures designed for bulk RNA-seq data to explore tumor-intrinsic mutations associated with residency and exhaustion from TCGA data. Finally, using two independent transcriptomic datasets from patients with colon adenocarcinoma, we showed that combinations of these signatures, in particular combinations of NK-cell activity signatures, together with tumor-associated signatures, such as TGFβ signaling, were associated with distinct survival outcomes in patients with colon adenocarcinoma. /
Publisher: Cold Spring Harbor Laboratory
Date: 27-06-2022
Abstract: The advent of massively parallel sequencing revealed extensive transcription beyond protein-coding genes, identifying tens of thousands of long noncoding RNAs (lncRNAs). Selected functional ex les raised the possibility that lncRNAs, as a class, may maintain broad regulatory roles. Expression of lncRNAs is strongly linked with adjacent protein-coding gene expression, suggesting potential cis -regulatory functions. A more detailed understanding of these regulatory roles may be obtained through careful examination of the precise timing of lncRNA expression relative to adjacent protein-coding genes. Despite the ersity of reported lncRNA regulatory mechanisms, where causal cis -regulatory relationships exist, lncRNA transcription is expected to precede changes in target gene expression. Using a high temporal resolution RNA-seq time course, we profiled the expression dynamics of several thousand lncRNAs and protein-coding genes in synchronized, transitioning human cells. Our findings reveal that lncRNAs are expressed synchronously with adjacent protein-coding genes. Analysis of lipopolysaccharide-activated mouse dendritic cells revealed the same temporal relationship observed in transitioning human cells. Our findings suggest broad-scale cis -regulatory roles for lncRNAs are not common. The strong association between lncRNAs and adjacent genes may instead indicate an origin as transcriptional by-products from active protein-coding gene promoters and enhancers.
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: Springer Science and Business Media LLC
Date: 06-11-2018
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: MDPI AG
Date: 20-01-2023
Abstract: Rich intercultural music engagement (RIME) is an embodied form of engagement whereby in iduals immerse themselves in foreign musical practice, for ex le, by learning a traditional instrument from that culture. The present investigation evaluated whether RIME with Chinese or Middle Eastern music can nurture intercultural understanding. White Australian participants were randomly assigned to one of two plucked-string groups: Chinese pipa (n = 29) or Middle Eastern oud (n = 29). Before and after the RIME intervention, participants completed measures of ethnocultural empathy, tolerance, social connectedness, explicit and implicit attitudes towards ethnocultural groups, and open-ended questions about their experience. Following RIME, White Australian participants reported a significant increase in ethnocultural empathy, tolerance, feelings of social connection, and improved explicit and implicit attitudes towards Chinese and Middle Eastern people. However, these benefits differed between groups. Participants who learned Chinese pipa reported reduced bias and increased social connectedness towards Chinese people, but not towards Middle Eastern people. Conversely, participants who learned Middle Eastern oud reported a significant increase in social connectedness towards Middle Eastern people, but not towards Chinese people. This is the first experimental evidence that participatory RIME is an effective tool for understanding a culture other than one’s own, with the added potential to reduce cultural bias.
Publisher: Oxford University Press (OUP)
Date: 21-09-2014
DOI: 10.1093/BIOINFORMATICS/BTU612
Abstract: Summary : The wide variety of published approaches for the problem of regulatory network inference makes using multiple inference algorithms complex and time-consuming. Network Analysis and Inference Library (NAIL) is a set of software tools to simplify the range of computational activities involved in regulatory network inference. It uses a modular approach to connect different network inference algorithms to the same visualization and network-based analyses. NAIL is technology-independent and includes an interface layer to allow easy integration of components into other applications. Availability and implementation : NAIL is implemented in MATLAB, runs on Windows, Linux and OSX, and is available from SourceForge at rojects/nailsystemsbiology/ for all researchers to use. Contact : daniel.hurley@unimelb.edu.au Supplementary information : Supplementary data are available at Bioinformatics online.
Publisher: Springer Science and Business Media LLC
Date: 24-06-2020
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 Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.22543863
Abstract: Supplementary data containing 25 Supp. figures that support the results of the paper.
Publisher: Springer Science and Business Media LLC
Date: 26-03-2021
DOI: 10.1038/S41467-021-22101-7
Abstract: Adipogenesis associated Mth938 domain containing (AAMDC) represents an uncharacterized oncogene lified in aggressive estrogen receptor-positive breast cancers. We uncover that AAMDC regulates the expression of several metabolic enzymes involved in the one-carbon folate and methionine cycles, and lipid metabolism. We show that AAMDC controls PI3K-AKT-mTOR signaling, regulating the translation of ATF4 and MYC and modulating the transcriptional activity of AAMDC -dependent promoters. High AAMDC expression is associated with sensitization to dactolisib and everolimus, and these PI3K-mTOR inhibitors exhibit synergistic interactions with anti-estrogens in IntClust2 models. Ectopic AAMDC expression is sufficient to activate AKT signaling, resulting in estrogen-independent tumor growth. Thus, AAMDC -overexpressing tumors may be sensitive to PI3K-mTORC1 blockers in combination with anti-estrogens. Lastly, we provide evidence that AAMDC can interact with the RabGTPase-activating protein RabGAP1L, and that AAMDC, RabGAP1L, and Rab7a colocalize in endolysosomes. The discovery of the RabGAP1L-AAMDC assembly platform provides insights for the design of selective blockers to target malignancies having the AAMDC lification.
Publisher: Springer Science and Business Media LLC
Date: 16-11-2016
Publisher: The Royal Society
Date: 06-2018
Abstract: Mathematical models of cardiac action potentials have become increasingly important in the study of heart disease and pharmacology, but concerns linger over their robustness during long periods of simulation, in particular due to issues such as model drift and non-unique steady states. Previous studies have linked these to violation of conservation laws, but only explored those issues with respect to charge conservation in specific models. Here, we propose a general and systematic method of identifying conservation laws hidden in models of cardiac electrophysiology by using bond graphs, and develop a bond graph model of the cardiac action potential to study long-term behaviour. Bond graphs provide an explicit energy-based framework for modelling physical systems, which makes them well suited for examining conservation within electrophysiological models. We find that the charge conservation laws derived in previous studies are ex les of the more general concept of a ‘conserved moiety’. Conserved moieties explain model drift and non-unique steady states, generalizing the results from previous studies. The bond graph approach provides a rigorous method to check for drift and non-unique steady states in a wide range of cardiac action potential models, and can be extended to examine behaviours of other excitable systems.
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.22543860
Abstract: List of the tools and packages used in the manuscript
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2016
Publisher: Elsevier BV
Date: 11-2019
DOI: 10.1016/J.JTBI.2018.09.034
Abstract: Membrane transporters contribute to the regulation of the internal environment of cells by translocating substrates across cell membranes. Like all physical systems, the behaviour of membrane transporters is constrained by the laws of thermodynamics. However, many mathematical models of transporters, especially those incorporated into whole-cell models, are not thermodynamically consistent, leading to unrealistic behaviour. In this paper we use a physics-based modelling framework, in which the transfer of energy is explicitly accounted for, to develop thermodynamically consistent models of transporters. We then apply this methodology to model two specific transporters: the cardiac sarcoplasmic/endoplasmic Ca
Publisher: Oxford University Press (OUP)
Date: 12-2015
Publisher: Springer Science and Business Media LLC
Date: 25-07-2015
Publisher: American Association for Cancer Research (AACR)
Date: 04-04-2023
DOI: 10.1158/2326-6066.22543854.V1
Abstract: An excel file with several sheets, representing supp. tables S4-S10 in the paper.
Location: Australia
Location: Australia
No related grants have been discovered for Joseph Cursons.