24 research outputs found

    Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin

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    Recent genomic analyses of pathologically-defined tumor types identify “within-a-tissue” disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head & neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multi-platform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All datasets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies

    Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

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    Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

    Preclinical Testing of Chronic ICA-1S Exposure: A Potent Protein Kinase C-ι Inhibitor as a Potential Carcinoma Therapeutic

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    Protein kinase C-iota (PKC-ι) is an oncogene overexpressed in many cancer cells including prostate, breast, ovarian, melanoma, and glioma cells. Previous in vitro studies have shown that 5-amino-1-((1R,2S,3R,4R)-2-3-dihydroxy-4-(hydroxymethyl)cyclopentyl)-1H-imidazole-4-carboxamide (ICA-1S), a PKC-ι-specific inhibitor, has low toxicity in both acute and sub-acute mouse model toxicological testing and is an effective therapeutic against several cancer cell lines showing significant reductions in tumor growth when treating athymic nude mice with xenografted carcinoma cell lines. To further assess ICA-1S as a possible therapeutic agent, chronic mouse model toxicological testing was performed in vivo to provide inferences concerning the long-term effects and possible health hazards from repeated exposure over a substantial part of the animal’s lifespan. Subjects survived well after 30, 60, and 90 days of doses ranging from 50 mg/kg to 100 mg/kg. Heart, liver, kidney, and brain tissues were then analyzed for accumulations of ICA-1S including the measured assessment of aspartate transaminase (AST), alkaline phosphatase (ALK-P), gamma-glutamyl transferase (GGT), troponin, and C-reactive protein (CRP) serum levels to assess organ function. Predictive in vitro/in silico methods were used to predict compound-induced direct hepatocyte toxicity or renal proximal tubular cell (PTC) toxicity in humans based on the high-content imaging (HCI) of compound-treated cells in combination with phenotypic profiling. In conclusion, ICA-1S shows low toxicity in both acute and chronic toxicology studies, and shows promise as a potential therapeutic

    Identification of Nephrotoxic Compounds with Embryonic Stem-Cell-Derived Human Renal Proximal Tubular-Like Cells

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    The kidney is a major target for drug-induced toxicity, and the renal proximal tubule is frequently affected. Nephrotoxicity is typically detected only late during drug development, and the nephrotoxic potential of newly approved drugs is often underestimated. A central problem is the lack of preclinical models with high predictivity. Validated in vitro models for the prediction of nephrotoxicity are not available. Major problems are related to the identification of appropriate cell models and end points. As drug-induced kidney injury is associated with inflammatory reactions, we explored the expression of inflammatory markers as end point for renal in vitro models. In parallel, we developed a new cell model. Here, we combined these approaches and developed an in vitro model with embryonic stem-cell-derived human renal proximal tubular-like cells that uses the expression of interleukin (IL)-6 and IL-8 as end points. The predictivity of the model was evaluated with 41 well-characterized compounds. The results revealed that the model predicts proximal tubular toxicity in humans with high accuracy. In contrast, the predictivity was low when well-established standard in vitro assays were used. Together, the results show that high predictivity can be obtained with in vitro models employing pluripotent stem cell-derived human renal proximal tubular-like cells

    Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

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    The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts.The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that -80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAFPeer reviewe

    Sex differences in oncogenic mutational processes

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    Sex differences have been observed in multiple facets of cancer epidemiology, treatment and biology, and in most cancers outside the sex organs. Efforts to link these clinical differences to specific molecular features have focused on somatic mutations within the coding regions of the genome. Here we report a pan-cancer analysis of sex differences in whole genomes of 1983 tumours of 28 subtypes as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We both confirm the results of exome studies, and also uncover previously undescribed sex differences. These include sex-biases in coding and non-coding cancer drivers, mutation prevalence and strikingly, in mutational signatures related to underlying mutational processes. These results underline the pervasiveness of molecular sex differences and strengthen the call for increased consideration of sex in molecular cancer research.Sex differences have been observed in multiple facets of cancer epidemiology, treatment and biology, and in most cancers outside the sex organs. Efforts to link these clinical differences to specific molecular features have focused on somatic mutations within the coding regions of the genome. Here we report a pan-cancer analysis of sex differences in whole genomes of 1983 tumours of 28 subtypes as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We both confirm the results of exome studies, and also uncover previously undescribed sex differences. These include sex-biases in coding and non-coding cancer drivers, mutation prevalence and strikingly, in mutational signatures related to underlying mutational processes. These results underline the pervasiveness of molecular sex differences and strengthen the call for increased consideration of sex in molecular cancer research.Peer reviewe
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