ORCID Profile
0000-0002-0428-6195
Current Organisations
New Mexico State University
,
Children's Cancer Institute Australia
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Publisher: IOP Publishing
Date: 11-2021
Abstract: A zombie idea is one that has been repeatedly refuted by analysis and evidence, and should have died, but clings to life for reasons that are difficult to understand without further investigation. The perception that investments in modern irrigation systems automatically save water constitutes a zombie idea. On face value, most would accept that modernizing irrigation systems makes sense: agriculture represents 70% of global water withdrawals while physical irrigation efficiencies range between 25% and 50% worldwide—that is, most of the water entering the irrigation system never makes it to the targeted crop. However, the impacts of modern irrigation systems are complex, and as we show, usually have the opposite effect to that intended through altered cropping and water application decisions by farmers, that aggravate water scarcity. This paper investigates how this zombie idea forms why it persists, even when proven wrong by scientific evidence and how to overcome it.
Publisher: American Society of Hematology
Date: 09-10-2020
DOI: 10.1182/BLOODADVANCES.2020002708
Abstract: A novel KMT2A-rearrangement, MLL-TFE3, was identified in an infant leukemia patient. MLL-TFE3 expression produces aggressive leukemia in a mouse model.
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: Cold Spring Harbor Laboratory
Date: 08-2021
DOI: 10.1101/2021.08.01.454393
Abstract: B-cell acute lymphoblastic leukemia (B-ALL) is the most common childhood cancer. Subtypes within B-ALL are distinguished by characteristic structural variants and mutations, which in some instances strongly correlate with responses to treatment. The World Health Organisation (WHO) recognises seven distinct classifications, or subtypes , as of 2016. However, recent studies have demonstrated that B-ALL can be segmented into 23 subtypes based on a combination of genomic features and gene expression profiles. A method to identify a patient’s subtype would have clear clinical utility. Despite this, no publically available classification methods using RNA-Seq exist for this purpose. Here we present ALLSorts: a publicly available method that uses RNA-Seq data to classify B-ALL s les to 18 known subtypes and five meta-subtypes. ALLSorts is the result of a hierarchical supervised machine learning algorithm applied to a training set of 1223 B-ALL s les aggregated from multiple cohorts. Validation revealed that ALLSorts can accurately attribute s les to subtypes and can attribute multiple subtypes to a s le. Furthermore, when applied to both paediatric and adult cohorts, ALLSorts was able to classify previously undefined s les into subtypes. ALLSorts is available and documented on GitHub ( github.com/Oshlack/AllSorts/ ). ALLSorts is a gene expression classifier for B-cell acute lymphoblastic leukemia, which predicts 18 distinct genomic subtypes - including those designated by the World Health Organisation (WHO) and provisional entities. Trained and validated on over 2300 B-ALL s les, representing each subtype and a variety of clinical features. Correctly identified subtypes in 91% of cases in a held-out dataset and between 82-93% across a newly combined cohort of paediatric and adult s les. ALLSorts assigned subtypes to s les with previously unknown driver events. ALLsorts is an accurate, comprehensive and freely available classification tool that distinguishes subtypes of B-cell acute lymphoblastic leukemia from RNA-sequencing.
Publisher: American Society of Hematology
Date: 16-02-2022
Publisher: Cold Spring Harbor Laboratory
Date: 31-10-2022
DOI: 10.1101/2022.10.27.514132
Abstract: Cancer is driven by mutations of the genome that can result in the activation of oncogenes or repression of tumour suppressor genes. In acute lymphoblastic leukemia (ALL) focal deletions in IKAROS family zinc finger 1 (IKZF1) result in the loss of zinc-finger DNA-binding domains and a dominant negative isoform that is associated with higher rates of relapse and poorer patient outcomes. Clinically, the presence of IKZF1 deletions informs prognosis and treatment options. In this work we developed a method for detecting exon deletions in genes using RNA-seq with application to IKZF1. We developed a pipeline that first uses a custom transcriptome reference consisting of transcripts with exon deletions. Next, RNA-seq reads are mapped using a pseudoalignment algorithm to identify reads that uniquely support deletions. These are then evaluated for evidence of the deletion with respect to gene expression and other s les. We applied the algorithm, named Toblerone, to a cohort of 99 B-ALL paediatric s les including validated IKZF1 deletions. Furthermore, we developed a graphical desktop app for non-bioinformatics users that can quickly and easily identify and report deletions in IKZF1 from RNA-seq data with informative graphical outputs.
Publisher: F1000 Research Ltd
Date: 03-02-2023
DOI: 10.12688/F1000RESEARCH.129490.1
Abstract: Cancer is driven by mutations of the genome that can result in the activation of oncogenes or repression of tumour suppressor genes. In acute lymphoblastic leukemia (ALL) focal deletions in IKAROS family zinc finger 1 (IKZF1) result in the loss of zinc-finger DNA-binding domains and a dominant negative isoform that is associated with higher rates of relapse and poorer patient outcomes. Clinically, the presence of IKZF1 deletions informs prognosis and treatment options. In this work we developed a method for detecting exon deletions in genes using RNA-seq with application to IKZF1. We developed a pipeline that first uses a custom transcriptome reference consisting of transcripts with exon deletions. Next, RNA-seq reads are mapped using a pseudoalignment algorithm to identify reads that uniquely support deletions. These are then evaluated for evidence of the deletion with respect to gene expression and other s les. We applied the algorithm, named Toblerone, to a cohort of 99 B-ALL paediatric s les including validated IKZF1 deletions. Furthermore, we developed a graphical desktop app for non-bioinformatics users that can quickly and easily identify and report deletions in IKZF1 from RNA-seq data with informative graphical outputs.
Publisher: American Society of Hematology
Date: 30-10-2023
Publisher: Springer Science and Business Media LLC
Date: 21-02-2023
Publisher: Springer Science and Business Media LLC
Date: 14-10-2017
DOI: 10.1038/LEU.2016.279
Abstract: Enforced expression of microRNA-155 (miR-155) in myeloid cells has been shown to have both oncogenic or tumour-suppressor functions in acute myeloid leukaemia (AML). We sought to resolve these contrasting effects of miR-155 overexpression using murine models of AML and human paediatric AML data sets. We show that the highest miR-155 expression levels inhibited proliferation in murine AML models. Over time, enforced miR-155 expression in AML in vitro and in vivo, however, favours selection of intermediate miR-155 expression levels that results in increased tumour burden in mice, without accelerating the onset of disease. Strikingly, we show that intermediate and high miR-155 expression also regulate very different subsets of miR-155 targets and have contrasting downstream effects on the transcriptional environments of AML cells, including genes involved in haematopoiesis and leukaemia. Furthermore, we show that elevated miR-155 expression detected in paediatric AML correlates with intermediate and not high miR-155 expression identified in our experimental models. These findings collectively describe a novel dose-dependent role for miR-155 in the regulation of AML, which may have important therapeutic implications.
Publisher: American Society of Hematology
Date: 15-07-2022
Publisher: Springer Science and Business Media LLC
Date: 21-03-2019
No related grants have been discovered for Hansen Kosasih.