3331 results for "ovarian cancer"

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• Long-read sequencing of diagnosis and post-therapy medulloblastoma reveals complex rearrangement patterns and epigenetic signatures

  Cancer genomes harbor a broad spectrum of structural variants (SV) driving tumorigenesis, a relevant subset of which are likely to escape discovery in short reads. We employed Oxford Nanopore Technologies (ONT) sequencing in a paired diagnostic and post-therapy medulloblastoma to unravel the haplotype-resolved somatic genetic and epigenetic landscape. We assemble complex rearrangements and such associated with telomeric sequences, including a 1.55 Megabasepair chromothripsis event. We uncover a complex SV pattern termed "templated insertion thread", characterized by short (mostly less than 1kb) insertions showing prevalent self-concatenation into highly amplified structures of up to 50kbp in size. Templated insertion threads occur in 3% of cancers, with a prevalence ranging to 74% in liposarcoma, and frequent colocalization with chromothripsis. We also perform long-read based methylome profiling and discover allele-specific methylation (ASM) effects, complex rearrangements exhibiting differential methylation, and differential promoter methylation in seven cancer-driver genes. Our study shows the potential of long-read sequencing in cancer.

  Study EGAS00001006576

• Analysis of four key cell types (epithelial, fbroblast, myeloid and T cells)

  Alterations of the normal prostate epithelial cell genome trigger the emergence of carcinoma, however cancer-only analyses of genomic aberrations have resulted in little clinical translation. A deep understanding of the tumor microenvironment is likely to inform on key drivers of disease progression and novel therapeutic opportunities. We investigated the role of key cell types along disease progression, profiling the RNA abundance of 52 samples from 13 patients enriched for one of four key cell types, spanning a wide CAPRA-S risk score range. Using a novel differential transcription Bayes method, TABI, we avoided a priori patient stratification, and mapped transcriptional alteration events to specific risk scores. The developmental and cell-type resolution yielded a landscape of concurrent transcriptional alterations from the tumour microenvironment, including key hallmarks. These transcriptional signatures permitted the identification of a “high survival” patient cluster in an independent prostate cancer dataset. Most importantly, together with our integrated transcriptional analysis, differential tissue composition analysis provided evidence for a key role for monocytes and macrophages in prostate cancer progression and disease recurrence.

  Study EGAS00001003579

• Sequencing of an organoid biobank for childhood kidney cancers that captures disease and tissue heterogeneity.

  Kidney tumors are among the most common solid tumors in children, comprising several distinct subtypes differing in many aspects, including cell-of-origin, genetics, and pathology. Pre-clinical cell models capturing the disease heterogeneity are currently lacking. Here, we describe the first pediatric cancer organoid biobank. It contains tumor and matching normal organoids from over 50 children with different subtypes of kidney cancer, including Wilms tumors, malignant rhabdoid tumors, renal cell carcinomas, and congenital mesoblastic nephromas. The malignant rhabdoid tumor organoids represent the first organoid model for tumors of non-epithelial origin. The tumor organoids retain key properties of native tumors, useful for revealing patient specific drug vulnerabilities. We further demonstrate that organoid cultures derived from Wilms tumors consist of multiple different cell types, including epithelial, stromal and blastemal-like. Our organoid biobank captures the cellular heterogeneity of pediatric kidney tumors, providing a representative collection of well-characterized models for basic cancer research, drug-screening, and personalized medicine.

  Study EGAS00001003853

• Dissecting intratumor heterogeneity of nodal B cell lymphoma on the transcriptional, genetic, and drug response level

  Tumor heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is well-known to affect the efficacy of anti-cancer, most personalized treatment approaches do not account for intratumor heterogeneity. We addressed this issue by studying the heterogeneity of lymph node-derived B cell non-Hodgkin lymphoma (B-NHL) by single cell RNA-sequencing (scRNA-seq) and transcriptome-informed flow cytometry. We identified transcriptionally distinct malignant subclones and compared their drug response and genomic profiles. Malignant subclones of the same patient responded strikingly different to anti-cancer drugs ex vivo, which recapitulated subclone-specific drug sensitivity during in vivo treatment. Tumor infiltrating T cells represented the majority of non-malignant cells, whose gene expression signatures were similar across all donors, whereas the frequencies of T cell subsets varied significantly between the donors. Our data provide new insights into the heterogeneity of B-NHL and highlight the relevance of intratumor heterogeneity for personalized cancer therapies.

  Study EGAS00001004335

• Pheno-Seq, linking 3D phenotypes of clonal tumor spheroids to gene expression

  3D-culture systems have advanced cancer modeling by reflecting physiological characteristics of in-vivo tissues, but our understanding of functional intratumor heterogeneity including visual phenotypes and underlying gene expression is still limited. Transcriptional heterogeneity can be dissected by single-cell RNA-sequencing, but these technologies suffer from low RNA-input and fail to directly correlate gene expression with contextual cellular phenotypes. Here we present pheno-seq for integrated high-throughput imaging and transcriptomic profiling of clonal tumor spheroids derived from 3D models of breast and colorectal cancer. Specifically, we identify characteristic expression signatures that are associated with heterogeneous invasive and proliferative behavior including a rare cell subtype. Furthermore, we identify functionally relevant transcriptional regulators missed by single-cell RNA-seq, link visual phenotypes defined by heterogenous expression to inhibitor response and infer single-cell regulatory states by deconvolution. We anticipate that directly linking molecular features with patho-phenotypes of cancer cells will improve the understanding of intratumor heterogeneity and consequently prove to be useful for translational research.

  Study EGAS00001002999

• Combined hereditary and somatic mutations of replication error repair genes result in rapid onset of ultra-hypermutated cancers

  DNA replication-associated mutations are repaired by two components: polymerase proofreading and mismatch repair. The mutational consequences of disruption to both repair components in humans are not well studied. We sequenced cancer genomes from children with inherited biallelic mismatch repair deficiency (bMMRD). High-grade bMMRD brain tumors exhibited massive numbers of substitution mutations (>250/Mb) – higher than all childhood and most cancers (>7000 analyzed). All ultra-hypermutated bMMRD cancers acquired early somatic driver mutations in DNA polymerases epsilon or delta. The ensuing mutation signatures and numbers are unique and diagnostic of childhood germline bMMRD (p<10e-13). Sequential tumor biopsy analysis revealed that bMMRD/polymerase mutant cancers rapidly amass an excess of simultaneous mutations (~600 mutations/cell division), reaching but not exceeding ~20,000 exonic mutations in <6 months. Thus implying a threshold compatible with cancer cell survival. We suggest a new mechanism of cancer progression in which mutations develop in a rapid burst after ablation of replication repair.

  Study EGAS00001001112

• National Cancer Institute Genome-Wide Association Study of Renal Cell Carcinoma

  The National Cancer Institute (NCI) genome-wide association study (GWAS) of renal cell carcinoma (RCC) was conducted to investigate common genetic variants associated with RCC risk. The GWAS includes 1,453 RCC cases and 3,531 controls of European background from 4 studies (3 cohort, 1 case-control), scanned using the Illumina InfiniumHumanHap 550, 610 and 660W chips. This project was supported by the Intramural Research Program of the National Institutes of Health and NCI. Data from this GWAS were pooled with those from another GWAS of RCC (2,639 cases and 5,392 controls) conducted in Europe by the International Agency for Research on Cancer and the Centre National de Gènotypage. Findings from this collaboration are described in an upcoming report (Purdue et al. Nature Genetics 2011;43(1):60-65; PMID: 21131975). Only data from the NCI scan are included in this dbGaP submission.

  Study phs000351

• SU2C-MARK Lung Cancer Consortium - Checkpoint Blockade Response Project

  Immune checkpoint inhibitors have become a critical part of the armamentarium against advanced Non-Small Cell Lung Cancer (NSCLC). While early studies have identified Tumor Mutation Burden (TMB) and PD-L1 staining as important biomarkers of response, they remain imperfect predictors. Here we describe a multi-institutional effort as part of the SU2C-MARK Lung Cancer Consortium in which Whole Exome Sequencing (WES) - and in select cases, RNA sequencing – was performed on a large collection of NSCLC samples prior to immune checkpoint blockade therapy, along with matched clinical response data following therapy. (Profiling of a small number of on- or post-treatment samples was also performed.) We anticipate this dataset to be of high value for the development of a deep understanding of the molecular determinants of immune checkpoint blockade response as well as the discovery of novel biomarkers.

  Study phs002822

• A Pilot Study of Neoadjuvant Nivolumab, Ipilimumab and Intralesional Oncolytic Virotherapy for HER2-Negative Breast Cancer

  This study was a single arm phase 1 trial that assessed the regimen safety and feasibility as well as tumor response in patients with localized HER2-negative breast cancer treated with talimogene laherparepvec (T-VEC) in combination with nivolumab and ipilimumab. The primary objective was to evaluate the safety and adverse event profile of this treatment combination. Six patients were enrolled, four having relapses after prior neoadjuvant chemotherapy, and two who were previously untreated. One patient had a pathological complete response, three patients had pathological partial responses, one showed no significant response, and one had disease progression. Biopsies demonstrated increased immune cell infiltration in samples from patients who responded to therapy. In this study, the checkpoint blockade immunotherapy combined with T-VEC provided responses in patients with advanced or relapsed HER2-negative breast cancer at the expense of long-term toxicities.

  Study phs003316

• Whole-genome sequencing of BRCA-mutant breast cancer patient samples from tumour, germline tissue and plasma

  The use of circulating tumor DNA (ctDNA) to profile mutational signatures presents a non-invasive opportunity for understanding cancer mutational processes. In this study we developed MisMatchFinder, a liquid biopsy approach for mutational signature detection using low- coverage whole-genome sequencing of ctDNA. Through analysis of plasma samples across multiple different cancers, we demonstrated that MisMatchFinder accurately infers single-base and doublet-base substitutions as well as indels to enhance detection of ctDNA and clinically relevant mutational signatures. This study contains fastq files from whole-genome sequencing of temporally matched tumour (fresh frozen biopsies), blood germline and plasma samples collected from a BRCA1-mutant breast cancer patient to directly compare mutation signature analysis using gold-standard tumour-germline paired variant calling with our novel ctDNA-based method (MisMatchFinder).

  Study EGAS50000000569