Biology subjects

Freeman, M.

Publications and source records attributed to Freeman, M..

9 recordsLinked to original sources

bioRxiv2018

Modeling cellular response in large-scale radiogenomic databases to advance precision radiotherapy

Radiotherapy is integral to the care of a majority of cancer patients. Despite differences in tumor responses to radiation (radioresponse), dose prescriptions are not currently tailored to individual patients. Recent large-scale cancer cell line databases hold the promise of unravelling the complex molecular arrangements underlying cellular response to radiation, which is critical to novel predictive biomarker discovery. Here, we present RadioGx, a computational platform for integrative analyses of radioresponse using radiogenomic databases. We first used RadioGx to investigate the robustness of radioresponse assays and indicators. We then combined radioresponse and genome-wide molecular data with established radiobiological models to predict molecular pathways that are relevant for individual tissue types and conditions. We also applied RadioGx to pharmacogenomic data to identify several classes of drugs whose effects correlate with radioresponse. RadioGx provides a unique computational toolbox to advance preclinical research for radiation oncology and precision medicine.

bioinformatics↗

bioRxiv2018

Quantitative Proteomic Analysis of Prostate Tissue Specimens Identifies Deregulated ProteinComplexes in Primary Prostate Cancer

Prostate cancer (PCa) is the most frequently diagnosed non-skin cancer and a leading cause of mortality among males in developed countries. However, our understanding of the global changes of protein complexes within PCa tissue specimens remains very limited, although it has been well recognized that protein complexes carry out essentially all major processes in living organisms and that their deregulation drives the pathogenesis and progression of various diseases. By coupling tandem mass tagging-synchronous precursor selection-mass spectrometry/mass spectrometry/mass spectrometry (TMT-SPSMS3) with differential expression and co-regulation analyses, the present study compared the differences between protein complexes in normal prostate, low-grade PCa, and high-grade PCa tissue specimens. Globally, a large downregulated putative protein-protein interaction (PPI) network was detected in both low-grade and high-grade PCa, yet a large upregulated putative PPI network was only detected in high-grade but not low-grade PCa, compared with normal controls. To identify specific protein complexes that are deregulated in PCa, quantified proteins were mapped to protein complexes in CORUM, a collection of experimentally verified mammalian protein complexes. Differential expression analysis suggested that mitochondrial ribosomes and the fibrillin-associated protein complex were significantly overexpressed, whereas the ITGA6-ITGB4-Laminin10/12 and the P2X7 receptor signaling complexes were significantly downregulated, in PCa compared with normal prostate. Moreover, differential co-regulation analysis indicated that the assembly levels of some nuclear protein complexes involved in RNA synthesis and processing were significantly increased in low-grade PCa, and those of mitochondrial complex I and its subcomplexes were significantly increased in high-grade PCa, compared with normal prostate. In summary, the study represents the first global and quantitative comparison of protein complexes in prostate tissue specimens. It is expected to enhance our understanding of the molecular mechanisms underlying PCa development and progression in human patients, as well as lead to the discovery of novel biomarkers and therapeutic targets for precision management of PCa.

cancer biology↗

bioRxiv2018

MeCP2-E1 isoform is a dynamically expressed, weakly DNA-bound protein with different protein and DNA interactions compared to MeCP2-E2

MeCP2 - a chromatin-binding protein associated with Rett syndrome - has two main isoforms, MeCP2-E1 and MeCP2-E2, with 96% amino acid identity differing in a few N-terminal amino acid residues. Previous studies have shown brain region-specific expression of these isoforms which, in addition to their different cellular localization and differential expression during brain development, suggest they may also have non-overlapping molecular mechanisms. However, differential functions of MeCP2-E1 and E2 remain largely unexplored. Here, we show that the N-terminal domains (NTD) of MeCP2-E1 and E2 modulate the ability of the methyl binding domain (MBD) to interact with DNA as well as influencing the turnover rates, binding dynamics, response to nuclear depolarization, and circadian oscillations of the two isoforms. Our proteomics data indicate that both isoforms exhibit unique interacting protein partners. Moreover, genome-wide analysis using ChIP-seq provide evidence for a shared as well as a specific regulation of different sets of genes. Our findings provide insight into the functional complexity of MeCP2 by dissecting differential aspects of its two isoforms.\n\nSignificanceWhether the two E1 and E2 isoforms of MeCP2 have different structural and/or functional implications has been highly controversial and is not well known. Here we show that the relatively short N-terminal sequence variation between the two isoforms impinges them with an important DNA binding difference. Moreover, MeCP2-E1 and E2 exhibit a different cellular dynamic behavior and have some distinctive interacting partners. In addition, while sharing genome occupancy they specifically bind to several distinctive genes.

biochemistry↗

bioRxiv2018

Necroptosis and apoptosis contribute to cisplatin and aminoglycoside ototoxicity

Ototoxic side effects of cisplatin and aminoglycosides have been extensively studied, but no therapy is available to date. Sensory hair cells, upon exposure to cisplatin or aminoglycosides, undergo apoptotic and necrotic cell death. Blocking these cell death pathways has therapeutic potential in theory, but incomplete protection and lack of therapeutic targets in the case of necrosis, has hampered the development of clinically applicable drugs. Over the past decade, a novel form of necrosis, termed necroptosis, was established as an alternative cell death pathway. Necroptosis is distinguished from passive necrotic cell death, in that it follows a cellular program, involving the receptor-interacting protein kinases 1 and 3 (RIPK1 and 3). In this study, we used pharmacological and genetic intervention to test the relative contributions of necroptosis and caspase-8-mediated apoptosis towards cisplatin and aminoglycoside ototoxicity. We find that ex vivo, only apoptosis contributes to cisplatin and aminoglycoside ototoxicity, while in vivo, both necroptosis and apoptosis are involved. Inhibition of necroptosis and apoptosis using pharmacological compounds is thus a viable strategy to ameliorate aminoglycoside and cisplatin ototoxicity.\n\nSignificance statementThe clinical application of cisplatin and aminoglycosides is limited due to ototoxic side effects. Here, using pharmaceutical and genetic intervention, we present evidence that two types of programmed cell death, apoptosis and necroptosis, contribute to aminoglycoside and cisplatin ototoxicity. Key molecular factors mediating necroptosis are well characterized and druggable, presenting new avenues for pharmaceutical intervention.

neuroscience↗

bioRxiv2018

FRMD8 promotes inflammatory and growth factor signalling by stabilising the iRhom/ADAM17 sheddase complex

Many intercellular signals are synthesised as transmembrane precursors that are released by proteolytic cleavage ( shedding) from the cell surface. ADAM17, a membrane-tethered metalloprotease, is the primary shedding enzyme responsible for the release of the inflammatory cytokine TNF and several EGF receptor ligands. ADAM17 exists in complex with the rhomboid-like iRhom proteins, which act as cofactors that regulate ADAM17 substrate shedding. Here we report that the poorly characterised FERM domain-containing protein FRMD8 is a new component of iRhom2/ADAM17 sheddase complex. FRMD8 binds to the cytoplasmic N-terminus of iRhoms, and is necessary to stabilise the iRhoms and ADAM17 beyond the Golgi. In the absence of FRMD8, iRhom2 and ADAM17 are degraded via the endolysosomal pathway, resulting in the reduction of ADAM17-mediated shedding. We have confirmed the pathophysiological significance of FRMD8 in iPSC-derived human macrophages and mouse tissues, thus demonstrating its role in the regulated release of multiple cytokine and growth factor signals.

biochemistry↗

bioRxiv2017

In vivo clonal analysis reveals spatiotemporal regulation of thalamic nucleogenesis

The thalamus, a crucial regulator of cortical functions, is composed of many nuclei arranged in a spatially complex pattern. Thalamic neurogenesis occurs over a short period during mammalian embryonic development. These features have hampered the effort to understand how regionalization, cell divisions and fate specification are coordinated and produce a wide array of nuclei that exhibit distinct patterns of gene expression and functions. Here, we performed in vivo clonal analysis to track the divisions of individual progenitor cells and spatial allocation of their progeny in the developing mouse thalamus. Quantitative analysis of clone compositions revealed evidence for sequential generation of distinct sets of thalamic nuclei based on the location of the founder progenitor cells. Furthermore, we identified intermediate progenitor cells that produced neurons populating more than one thalamic nuclei, indicating a prolonged specification of nuclear fate. Our study reveals an organizational principle that governs the spatial and temporal progression of cell divisions and fate specification, and provides a framework for studying cellular heterogeneity and connectivity in the mammalian thalamus.

neuroscience↗

bioRxiv2017

PharmacoDB: an integrative database for mining in vitro anticancer drug screening studies

Recent pharmacogenomic studies profiled large panels of cancer cell lines against hundreds of approved drugs and experimental chemical compounds. The overarching goal of these screens is to measure sensitivity of cell lines to chemical perturbation, correlate these measures to genomic features, and thereby develop novel predictors of drug response. However, leveraging this valuable data is challenging due to the lack of standards for annotating cell lines and chemical compounds, and quantifying drug response. Moreover, it has been recently shown that the complexity and complementarity of the experimental protocols used in the field result in high levels of technical and biological variation in the in vitro pharmacological profiles. There is therefore a need for new tools to facilitate rigorous comparison and integrative analysis of large-scale drug screening datasets. To address this issue, we have developed PharmacoDB (pharmacodb.pmgenomics.ca), a database integrating the largest pharmacogenomic studies published to date. Here, we describe how the curation of cell line and chemical compound identifiers maximizes the overlap between datasets and how users can leverage such data to compare and extract robust drug phenotypes. PharmacoDB provides a unique resource to mine a compendium of curated pharmacogenomic datasets that are otherwise disparate and difficult to integrate.\n\nKey pointsO_LICuration of cell line and drug identifiers in the largest pharmacogenomic studies published to date\nC_LIO_LIUniform processing of drug sensitivity data to reduce heterogeneity across studies\nC_LIO_LIMultiple drug response summary metrics enabling visual comparison and integrative analysis\nC_LI

bioinformatics↗

bioRxiv2016

Genome-wide association study in Collaborative Cross mice revealed a skeletal role for Rhbdf2

Osteoporosis, the most common bone disease, is characterized by a low bone mass and increased risk of fractures. Importantly, individuals with the same bone mineral density (BMD), as measured on two dimensional (2D) radiographs, have different risks for fracture, suggesting that microstructural architecture is an important determinant of skeletal strength. Here we took advantage of the rich phenotypic and genetic diversity of the Collaborative Cross (CC) mice. Using microcomputed tomography, we examined key structural parameters in the femoral cortical and trabecular compartments of male and female mice from 34 CC lines. These traits included the trabecular bone volume fraction, number, thickness, connectivity, and spacing, as well as structural morphometric index. In the mid-diaphyseal cortex, we recorded cortical thickness and volumetric BMD.\n\nThe broad-sense heritability of these traits ranged between 50 to 60%. We conducted a genome-wide association study to unravel 5 quantitative trait loci (QTL) significantly associated with 6 of the traits. We refined each locus by combining information obtained from the known ancestry of the mice and RNA-Seq data from publicly available sources, to shortlist potential candidate genes. We found strong evidence for new candidate genes, including Rhbdf2, which association to trabecular bone volume fraction and number was strongly suggested by our analyses. We then examined knockout mice, and validated the causal action of Rhbdf2 on bone mass accrual and microarchitecture.\n\nOur approach revealed new genome-wide QTLs and a series of genes that have never been associated with bone microarchitecture. This study demonstrates for the first time the skeletal role of Rhbdf2 on the physiological remodeling of both the cortical and trabecular bone. This newly assigned function for Rhbdf2 can prove useful in deciphering the predisposing factors of osteoporosis and propose new investigative avenues toward targeted therapeutic solutions.\n\nAuthor summaryIn this study, we used the novel mouse reference population, the Collaborative Cross (CC), to identify new causal genes in the regulation of bone microarchitecture, a critical determinant of bone strength. This approach provides a clear advantage in terms of resolution and dimensionality of the morphometric features (versus humans) and rich allelic diversity (versus classical mouse populations), over current practices of bone-related genome-wide association studies.\n\nOur genome-wide study revealed 5 loci significantly associated with microstructural traits in the cortical and trabecular bone. We found strong evidence for new candidate genes, in particular, Rhbdf2. We then validated the specific role of Rhbdf2 on bone mass accrual and microarchitecture using knockout mice. Importantly, this study is the first demonstration of a physiological role for Rhbdf2.

genetics↗

bioRxiv2016

Tissue specificity of in vitro drug sensitivity

Research in oncology traditionally focuses on specific tissue type from which the cancer develops. However, advances in high-throughput molecular profiling technologies have enabled the comprehensive characterization of molecular aberrations in multiple cancer types. It was hoped that these large-scale datasets would provide the foundation for a paradigm shift in oncology which would see tumors being classified by their molecular profiles rather than tissue types, but tumors with similar genomic aberrations may respond differently to targeted therapies depending on their tissue of origin. There is therefore a need to reassess the potential association between pharmacological response and tissue of origin for therapeutic drugs, and to test how these associations translate from preclinical to clinical settings.\n\nIn this paper, we investigate the tissue specificity of drug sensitivities in large-scale pharmacological studies and compare these associations to those found in clinical trial descriptions. Our meta-analysis of the four largest in vitro drug screening datasets indicates that tissue of origin is strongly associated with drug response. We identify novel tissue-drug associations, which may present exciting new avenues for drug repurposing. One caveat is that the vast majority of the significant associations found in preclinical settings do not concur with clinical observations. Accordingly, our results call for more testing to find the root cause of the discrepancies between preclinical and clinical observations.

bioinformatics↗