Single cell genome variation induced by mutational processes in cancer - HGSOC Trios study
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PROVIDER: PRJNA871024 | ENA |
REPOSITORIES: ENA
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Project description:Single cell genome variation induced by mutational processes in cancer - HGSOC Trios study
| PRJNA871025 | ENA
Project description:High-grade serous ovarian cancer (HGSOC) is an archetypal cancer of genomic instability patterned by distinct mutational processes, tumour heterogeneity and intraperitoneal spread. Immunotherapies have had limited efficacy in HGSOC, highlighting an unmet need to assess how mutational processes and the anatomical sites of tumour foci determine the immunological states of the tumour microenvironment. Here we carried out an integrative analysis of whole-genome sequencing, single-cell RNA sequencing, digital histopathology and multiplexed immunofluorescence of 160 tumour sites from 42 treatment-naive patients with HGSOC. Homologous recombination-deficient HRD-Dup (BRCA1 mutant-like) and HRD-Del (BRCA2 mutant-like) tumours harboured inflammatory signalling and ongoing immunoediting, reflected in loss of HLA diversity and tumour infiltration with highly differentiated dysfunctional CD8+ T cells. By contrast, foldback inversion-bearing tumours exhibited elevated immunosuppressive TGFβ signalling and immune exclusion, with predominantly naive/stem-like and memory T cells. Phenotypic state associations were specific to anatomical sites, highlighting compositional, topological and functional differences between adnexal tumours and distal peritoneal foci. Our findings implicate anatomical sites and mutational processes as determinants of evolutionary phenotypic divergence and immune resistance mechanisms in HGSOC. Our study provides a multi-omic cellular phenotype data substrate from which to develop and interpret future personalized immunotherapeutic approaches and early detection research.
2022-12-14 | GSE180661 | GEO
Project description:Transcript abundance was measured in whole-body virgin male Drosophila serrata from 41 inbred lines that had diverged through 27 generations of mutation accumulation. Pleiotropic mutations are the ultimate source of genetic variation in complex traits, including many human diseases. However, the nature and extent of mutational pleiotropy remain largely unknown. Here, we investigate the variation in 11,604 gene expression traits among 41 mutation accumulation lines of Drosophila serrata, which had diverged for 27 generations. We detected significant mutational variance in 4.6% of ESTs, but 70% of ESTs were invariant among lines, allowing us to reject a null hypothesis of phenome-wide universal pleiotropy. Mutational covariance among ESTs was detected at a frequency of only 1 in 193 random pairs of variable EST, bu t was detected among random combinations of five ESTs in 1 in 5 cases, revealing that mutational covariance among multiple ESTs was common. The observed frequency of significant multivariate covariance among random ESTs implied that a substantial number of ESTs (>70) must be pleiotropically affected by at least some mutations. We measured gene expression of male Drosophila serrata from 41 mutation accumulation lines (whole-body). Data from two replicates for each line are presented.
2013-09-01 | E-GEOD-49815 | biostudies-arrayexpress
Project description:Transcript abundance was measured in whole-body virgin male Drosophila serrata from 41 inbred lines that had diverged through 27 generations of mutation accumulation. Pleiotropic mutations are the ultimate source of genetic variation in complex traits, including many human diseases. However, the nature and extent of mutational pleiotropy remain largely unknown. Here, we investigate the variation in 11,604 gene expression traits among 41 mutation accumulation lines of Drosophila serrata, which had diverged for 27 generations. We detected significant mutational variance in 4.6% of ESTs, but 70% of ESTs were invariant among lines, allowing us to reject a null hypothesis of phenome-wide universal pleiotropy. Mutational covariance among ESTs was detected at a frequency of only 1 in 193 random pairs of variable EST, bu t was detected among random combinations of five ESTs in 1 in 5 cases, revealing that mutational covariance among multiple ESTs was common. The observed frequency of significant multivariate covariance among random ESTs implied that a substantial number of ESTs (>70) must be pleiotropically affected by at least some mutations.
2013-09-01 | GSE49815 | GEO
Project description:Ovarian cancer mutational processes drive site-specific immune evasion
| PRJNA749041 | ENA
Project description:High-grade serous ovarian carcinoma (HGSOC) is the most genomically complex cancer, characterised by ubiquitous TP53 mutation, profound structural variation and heterogeneity. Multiple mutational processes driving chromosomal instability can be distinguished by specific copy number signatures. To develop clinically relevant models of these mutational processes we derived 15 continuous HGSOC patient-derived organoids (PDOs) and provide detailed transcriptomic and genomic profiles using shallow whole genome sequencing single cell and bulk analysis. We show that PDOs comprise communities of different clonal populations and represent models of CCNE1 amplification, chromothripsis, tandem-duplicator phenotype and whole genome duplication. PDOs can also be used as exploratory tools to study transcriptional effects of copy number alterations as well as compound-sensitivity tests. In summary, HGSOC PDO cultures provide a genomic tool for studies of specific mutational processes and precision therapeutics.
2022-07-17 | GSE208216 | GEO
Project description:High-grade serous ovarian carcinoma (HGSOC) is the most genomically complex cancer, characterized by ubiquitous TP53 mutation, profound chromosomal instability and heterogeneity. The mutational processes driving chromosomal instability in HGSOC can be distinguished by specific copy number signatures. To develop clinically relevant models of these mutational processes we derived 15 continuous HGSOC patient-derived organoids (PDOs) and characterized them using bulk transcriptomic, bulk genomic, single cell genomic, and drug sensitivity assays. We show that HGSOC PDOs comprise communities of different clonal populations and represent models of different causes of chromosomal instability including homologous recombination deficiency, chromothripsis, tandem-duplicator phenotype and whole genome duplication. We also show that these PDOs can be used as exploratory tools to study transcriptional effects of copy number alterations as well as compound-sensitivity tests. In summary, HGSOC PDO cultures provide validated genomic models for studies of specific mutational processes and precision therapeutics.
| EGAS00001007189 | EGA
Project description:Transcript abundance was measured in whole-body virgin male Drosophila serrata from 41 inbred lines that had diverged through 27 generations of mutation accumulation that were sexually selected Sexual selection is predicted to have widespread effects on the genetic variation generated by new mutations as a consequence of the genic capture of condition by male sexual traits. We manipulated the opportunity for sexual selection on males during 27 generations of mutation accumulation in inbred lines of Drosophila serrata, and used a microarray platform to investigate the effect of sexual selection on the expression of 2685 genes, representing a broad coverage of biological function. Sexual selection had little effect on mean gene expression levels, with only 4 genes diverging significantly at a false discovery rate of 5% . In contrast, sexual selection impacted on both the magnitude and nature of mutational variance accumulating in these genes. The magnitude of mutational variance increased under sexual selection by an average of 29%. Mutational variance was less commonly generated by extreme phenotypes less commonly under sexual selection. Furthermore, analysis of random sets of five genes revealed that the mutational variance that accumulated under sexual selection was less pleiotropic in nature than that found in the absence of sexual selection. The generation of greater mutational variance without a general concomitant change in mean expression under sexual selection suggested that gene expression traits were be under apparent rather than direct sexual selection. We discuss two main explanations for the broad-based increase in mutational variance under sexual selection that both require extensive pleiotropy between traits affecting male mating success, standard metric traits represented here by gene expression traits, and general fitness. We measured gene expression of male Drosophila serrata from 41 mutation accumulation lines (whole-body) that were sexually selected. Data from two replicates for each line are presented.
2014-03-01 | E-GEOD-54777 | biostudies-arrayexpress
Project description:Stratification of a retrospective cohort of HGSOC based on its tissues of origin.
2020-09-29 | E-MTAB-9605 | biostudies-arrayexpress
Project description:Finding gene associations in rare diseases is frequently hampered by the reduced numbers of patients accessible. Conventional gene-based association tests rely on the availability of large cohorts, which constitutes a serious limitation for its application in this scenario. To overcome this problem we have used here a combined strategy in which a functional association study (pathway-based analysis) has been conducted to prioritize candidate genes in a Spanish cohort of 53 trios of short-segment Hirschsprung's disease that have been further validated in a larger population of 146 trios. The study revealed a strong association of 10 gene ontology (GO) modules related to signal transduction and its regulation, enteric nervous system (ENS) formation and other HSCR-related processes to the disease. A total of 10 new loci among the preselected candidates were found to be significantly associated to HSCR. This approach, based on the study of functionally-related gene sets, requires of lower sample sizes and opens new opportunities for the study of rare diseases.
2012-03-18 | GSE33732 | GEO