Search Results - EGA European Genome-Phenome Archive

Specific BRCA and immune configurations determine optimal response to platinum-based chemotherapy in triple negative breast and ovarian carcinomas (COH_TNBC_RNAseq)

To determine the trascriptional profiles of Triple Negative Breast Cancers (COH cohort)

Study EGAS00001006002

Systematic Growth Factor Profiling Platform for 3D Tumor Models Reveals EstradiolResponsive Cellular Mechanisms of Immunotherapy Resistance

Epithelial ovarian cancer (EOC) exhibits significant molecular heterogeneity, which is thought to be influenced by the tumor microenvironment (TME). However, the specific factors driving this heterogeneity remain poorly understood. In this study, we integrated growth factoromics and genomic data to identify TME factors contributing to EOC heterogeneity and immunosuppression. Our analysis revealed distinct subgroups of EOC samples with differential responsiveness to specific growth factors, particularly estradiol and R-spondin. Notably, samples with high responsiveness to estradiol and Wnt (C1 cluster) were enriched in the Mesenchymal (MES) molecular subtype, while samples with high responsiveness to R-spondin (C2 cluster) were associated with the Differentiated (DIF) and Immunoreactive (IMR) subtypes. We discovered that the G protein-coupled estrogen receptor (GPER), rather than the classical estrogen receptor alpha (ERα), was the key mediator of estrogen responsiveness and a determinant of molecular subtype classification. Single-cell sequencing analysis identified subsets of estrogen-responsive malignant cell (MAL.PDCD5) and cancer-associated fibroblast (FB.TNFSF10), which were associated with immunosuppressive patterns in the TCGA cohort. Importantly, the interaction between these cell populations significantly increased upon estrogen treatment, suggesting a potential mechanism by which estrogen signaling may contribute to the development of an immunosuppressive TME. Our findings highlight the critical role of estrogen signaling in shaping the molecular heterogeneity and immunosuppressive TME of EOC and provide novel insights into potential therapeutic targets for overcoming immunosuppression in this malignancy.

Study EGAS50000000422

A genotype-phenotype study of tumors from patients with inherited mutations in DNA repair genes

This study investigated the genomic landscape of tumors from patients with inherited mutations in DNA repair genes. The aim of this study was to determine the relationship between locus-specific loss of heterozygosity (LOH) and genomic signatures of homologous recombination-based DNA repair (HR) deficiency in tumors associated with pathogenic germline variants in DNA repair genes. Cohorts of pathogenic germline variant (PGV) carriers with different cancer types were identified via a cancer genetics registry and clinical practice at Penn Medicine and through our collaborator network. Tumors were analyzed with next generation sequencing (whole exome and/or targeted panel sequencing) with or without transcriptomic analyses. Sub-study #1 "Non-breast/ovarian tumors in germline BRCA1/2 carriers". This study investigated primary non-breast/ovarian tumors that arise in individuals with BRCA1/BRCA2 pathogenic germline variants (PGVs). Whole exome sequencing (WES) using Agilent All-Exon Kit v7 hybrid capture probes was performed on matched tumor and blood germline normal DNA on an Illumina HiSeq. Individual WES data from DNA samples from tumor and normal are available. Sub-study #2: "Breast tumors in germline CHEK2 carriers". This study investigated primary breast tumors that arise in individuals with CHEK2 pathogenic germline variants (PGVs). Whole exome sequencing (WES) using Agilent All-Exon Kit v7 hybrid capture probes was performed on matched tumor and blood germline normal DNA on an Illumina HiSeq. Whole transcriptome RNAseq was performed on tumors. Individual WES data from DNA samples from tumor and normal and RNAseq data from tumor are available. Sub-study #3: "Breast tumors in germline TP53 carriers". This study investigated primary breast tumors that arise in individuals with TP53 pathogenic germline variants (PGVs). Whole genome sequencing (WGS) and/or custom panel targeted sequencing was performed on matched tumor and blood germline normal DNA on an Illumina HiSeq. Whole transcriptome RNAseq was performed on tumors and normal breast tissue. Individual WGS or targeted data from DNA samples from tumor and normal and RNASeq data from tumor and normal are available. Sub-study #4: "Prostate tumors in germline DNA repair carriers". This study investigated prostate tumors that arise in individuals with a variety of pathogenic germline variants (PGVs). Whole genome sequencing (WGS) and/or custom panel targeted sequencing was performed on matched tumor and blood germline normal DNA on an Illumina HiSeq. Whole transcriptome RNAseq was performed on tumors and normal prostate tissue. Individual WGS or targeted data from DNA samples from tumor and normal and RNASeq data from tumor and normal are available.

Study phs003348

Low and variable tumor reactivity of the intratumoral TCR repertoire in human cancers

Infiltration of human cancers by T cells is generally interpreted as a sign of immune recognition, and there is a growing effort to reactivate dysfunctional T cells at such tumor sites. However, these efforts only have value if the intratumoral T cell receptor (TCR) repertoire of such cells is intrinsically tumor-reactive, and this has not been established in an unbiased manner for most human cancers. To address this issue, we analyzed the intrinsic tumor-reactivity of the intratumoral TCR repertoire of CD8+ T cells in ovarian and colorectal cancer – two tumor types for which T cell infiltrates form a positive prognostic marker. Data obtained demonstrate that a capacity to recognize autologous tumor is limited to approximately 10% of intratumoral CD8+ T cells. Furthermore, in two out of four patient samples tested, no tumor-reactive TCRs were identified, despite infiltration of their tumors by T cells. These data indicate that the intrinsic capacity of intratumoral T cells to recognize adjacent tumor tissue can be rare and variable, and suggest that clinical efforts to reactivate intratumoral T cells will benefit from approaches that simultaneously increase the quality of the intratumoral TCR repertoire.

Study EGAS00001003119

Prediction of homologous recombination deficiency identifies colorectal tumors sensitive to PARP inhibition

BRCAness is a well-established feature in breast, ovarian, prostate and pancreatic carcinomas, our recent findings indicate that up to 15% of colorectal cancers (CRC) also harbor defects in the HR pathway, presenting promising opportunities for innovative therapeutic strategies in CRC patients. We developed a new tool called HRDirect, which builds upon the HRDetect algorithm and is able to predict HRD from reference-free tumor samples. We validated HRDirect using matched breast cancer and CRC patient samples. Subsequently, we assessed its efficacy in predicting response to the PARP inhibitor olaparib by comparing it with two other commercial assays: AmoyDx HRD by Amoy Diagnostics and the TruSight Oncology (TSO) _500 HRD panel by Illumina NGS technology. While all three approaches successfully identified the most PARPi-sensitive CRC models, HRDirect demonstrated superior precision in distinguishing resistant models compared to AmoyDX and TSO500-HRD, which exhibited overlapping scores between sensitive and resistant cells. Furthermore, we propose integrating HRDirect scoring with ATM immunohistochemical analysis as part of our "composite biomarker approach" to enhance the identification of HRD tumors, with an immediate translational and clinical impact for CRC personalized treatment.

Study EGAS50000000426

National Cancer Institute (NCI) Prostate Cancer Genome-Wide Association Study for Uncommon Susceptibility Loci (PEGASUS)

This genome-wide association study was funded by the National Cancer Institute (NCI) to identify uncommon susceptibility loci for prostate cancer. A total of 4,600 prostate cancer cases and 2,840 controls of European ancestry from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial were genotyped using the Illumina HumanOmni2.5 and passed rigorous quality control filters. Additional genotype data (available in dbGap under other accession numbers) from 101 independent controls of European ancestry scanned with the HumanOmni2.5 were also included, resulting in a total of 4,600 cases and 2,941 controls for the published analysis. SNPs from the most promising regions, as determined by rank p-value, under multiple different models as well as select candidate genes were taken forward for replication using a custom Iselect chip in 6,575 cases and 6,392 controls of European ancestry. Results from the primary scan after imputation were then meta-analyzed with the Iselect results as well as results from previous GWAS. In a combined meta-analysis of the primary scan together with the custom Iselect replication and a previous GWAS, thirteen loci reached genome-wide significance (P < 5 x 10-8) for prostate cancer overall; however, each of them confirmed a previously reported locus. Although they did not reach genome-wide significance, we found evidence for two new suggestive loci at chromosome 16q22.2 (PKD1L3, rs12597458, P = 9.67 x 10-8) and 6p22.3 (CDKAL1, rs12198220, P = 2.13 x 10-7). In a combined case-only analysis of 12,518 prostate cancer cases, we identified two loci associated with Gleason score, a pathological measure of disease aggressiveness: rs35148638 at 5q14.3 (RASA1, P=6.49x10-9) and rs78943174 at 3q26.31 (NAALADL2, P=4.18x10-8). In a stratified case-control analysis, the SNP at 5q14.3 appears specific for aggressive prostate cancer (P=8.85x10-5) with no association for non-aggressive prostate cancer compared to controls (P=0.57). Only the cases and controls genotyped on the HumanOmni2.5 specifically for this study are included under this accession number. Controls (n=101) genotyped with the HumanOmni2.5 for another study are posted under a different accession number. Please note that the majority of prostate cancer cases and controls genotyped in CGEMS (and posted under a different accession number) are included in this study.

Study phs000882

Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) - OncoArray Genotypes

Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) was one of five projects funded in 2010 as part of the NCI's Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (http://epi.grants.cancer.gov/gameon/). GAME-ON's overall goal was to foster an intra-disciplinary and collaborative approach to the translation of promising research leads deriving from the initial wave of cancer GWAS. Specific goals included replication of previous GWAS findings and identification of new susceptibility loci through meta analyses of existing GWAS data and fine mapping of identified loci to better pinpoint causal variants; and identify germline variants that are associated with risk of multiple cancers. The other four funded GAME-ON projects were: the ColoRectal TransdisciplinaryStudy (CORECT), Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE), Follow-up of Ovarian Cancer Genetic Association and Interaction Study (FOCI), and Transdisciplinary Research in Cancer of the Lung (TRICL). To identify additional cancer risk loci, improve the precision of fine-mapping, and facilitate cross-cancer analyses, the GAME-ON projects and other consortia formed the OncoArray network (http://epi.grants.cancer.gov/oncoarray/), which developed and genotyped a new custom genotyping array (the "OncoArray") in large numbers of cancer cases and controls (over 400,000 samples). The OncoArray is a custom array manufactured by Illumina. The array includes a backbone of approximately 260,000 SNPs that provide genome-wide coverage of most common variants, together with markers of interest for each of the five GAME-ON cancers identified through genome-wide association studies (GWAS), fine-mapping of known susceptibility regions, sequencing studies, and other approaches. The array also includes loci of interest identified through studies of other cancer types, and other loci of interest to multiple cancer types (including loci associated with cancer related phenotypes, drug metabolism and radiation response). Additionally, SNPs relating to quantitative phenotypes such as body mass index (BMI), height, and breast density that correlate with common cancer risks are also included. The DRIVE data included under this dbGAP submission include OncoArray data from 60,015 breast cancer cases and controls genotyped at the Center for Inherited Disease Research (CIDR), University of Cambridge, National Cancer Institute, University of Copenhagen, University of Southern California and Mayo Clinic. Details on an additional approx. 80,000 breast cancer cases and controls genotyped at other centers can be found at http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/.

Study phs001265

High-grade serous ovarian cancer refined with single-cell RNA-sequencing

We performed single-cell RNA-sequencing of 18,403 cells unbiasedly collected from 7 treatment-naive HGSOC tumours. For each phenotypic cluster of tumour or stromal cells, we identified specific transcriptomic markers. Next, we explored which phenotypic clusters correlate with overall survival based on expression of these transcriptomic markers in 1467 bulk RNA-seq tumours. By evaluating molecular subtype signatures in single cells, we assessed to what extent a phenotypic cluster of tumour or stromal cells contributes to each molecular subtype.

Study EGAS00001004987

RNA sequencing data of 66 matched primary and recurrent high grade serous ovarian cancer

Gene expression profiles of matched primary and recurrent fresh frozen tumor tissues from 66 HGSOC patients were obtained by RNA sequencing. RNA libraries were created using the Illumina TruSeq RNA sample preparation kit V2 according to the manufacturer’s instructions and sequenced on a HiSeq2000 (Illumina, California, USA) using a V3 flowcell generating 1 x 50 bp reads. Raw sequencing reads were mapped to the transcriptome and the human reference genome (NCBI37/hg19) using TopHat 2.0 and Bowtie 2.0.

Study EGAS00001002660

National Institutes of Health The Cancer Genome Atlas (TCGA)

The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to accelerate our understanding of the molecular basis of cancer through the application of genome analysis technologies, including large-scale genome sequencing. TCGA is a joint effort of the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI), which are both part of the National Institutes of Health, U.S. Department of Health and Human Services. TCGA projects are organized by cancer type or subtype. Click here for a current list of cancer types selected for study in TCGA. Data from TCGA (e.g., gene expression, copy number variation and clinical information), are available via the Genomic Data Commons (GDC). Data from TCGA projects are organized into two tiers: Open Access and Controlled Access. Open Access data tier contains data that cannot be attributed to an individual research participant. The Open Access data tier does not require user certification. Data in Open Access tier are available in the TCGA Data Portal. Controlled Access data tier contains individual-level genotype data that are unique to an individual. Access to data in the Controlled Access data tier requires user certification through dbGaP Authorized Access. Controlled Access data types consist of the following: Individual germline variant data (SNP .cel files) Primary sequence data (.bam files), which are available at GDC Clinical free text fields Exon Array files (for Glioblastoma and Ovarian projects only) NOTE: TCGA strives to release most data in the open access tier. Individual genotype or sequence files are prominent exceptions. Commonly requested files such as descriptions of somatic mutations or clinical data are open access. Please go to this page: https://tcga-data.nci.nih.gov/docs/publications/ to access all data associated with TCGA tumor specific publications. The TCGA study is utilized in the following dbGaP substudies. To view genotypes and other molecular data collected in these substudies, please click on the following substudies below or in the "Substudies" section of this top-level study page phs000178 TCGA study. phs000854 Genome-wide Analysis of Noncoding Regulatory Mutations in Cancer

Study phs000178

3423 results for "ovarian cancer"

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