3428 results for "ovarian cancer"

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• Paired Biopsy Project: West Coast Dream Team

  This project aims to analyze the paired metastatic biopsy samples from patients with metastatic castration-resistant prostate cancer (mCRPC), collected before the initiation of the first-line androgen receptor signaling inhibitor (ARSI) for mCRPC and after radiographic disease progression on that ARSI, to understand the resistance mechanisms. We generated both whole genome sequencing (WGS) and RNA-seq data on these samples. A majority of these samples have been deposited in the public domain along with prior publications, and this project contains the 16 WGS samples that have not yet been deposited.

  Study EGAS50000000327

• Diversity of the immune microenvironment and response to checkpoint inhibitor immunotherapy in mucosal melanoma

  Mucosal melanoma (MucM) is a rare cancer with a poor prognosis and low response rate to immune checkpoint inhibition (ICI) compared to cutaneous melanoma (CM). To explore the immune microenvironment and potential drivers of MucM’s relative resistance to ICI drugs, we characterized 101 MucM tumors (43 head and neck, 31 female urogenital, 13 male urogenital, 11 anorectal, and 3 other gastro-intestinal) using bulk RNA-sequencing (RNAseq). The original publication is written by JL Vos, JJH Traets, et al. and published in JCI Insight in 2024.

  Study EGAS50000000631

• MIBC NAC2020 cohort RNA sequencing

  The dataset contains RNA sequencing data from N=48 transurethral resections of bladder tumours (TURBTs) from N=48 patients with muscle-invasive bladder cancer. All TURBTs originate from formalin-fixed paraffin embedded tissue. We used the Illumina TruSeq RNA exome kit, previously known as the TruSeq RNA Access Library Prep Kit. This kit converts total RNA into template molecules of known strand origin, followed by sequence-specific capture of coding RNA. All samples were run in an Illumina NovaSeq6000 instrument. Paired FASTQ files from all 48 patients are provided.

  Study EGAS50000000741

• Pediatric tumor in a single child of three large nuclear families

  We identify three nuclear families in which a pediatric tumor had been diagnosed in a single child and neither parent had been diagnosed with cancer. These families had 4, 5, and 7 children, respectively. Diagnoses included Wilms tumor, low-grade astrocytoma, and Burkitt’s lymphoma, respectively. We used whole-genome sequencing to profile normal cells from each family member and a linked-read technology for genomic phasing, which enabled us to identify compound-heterozygous and de novo variants in addition to simple-heterozygous and homozygous-alternate variants.

  Study EGAS00001005321

• MutWP5__CRUK_Mutographs_of_Cancer__Lung__PD43291_Novaseq__Exome_

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutaiton burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs.

  Study EGAS00001003503

• Gene expression-based prediction of pazopanib efficacy in sarcoma (HIPO, H021)

  The multi-receptor tyrosine kinase (RTK) inhibitor pazopanib is approved for the treatment of advanced non-adipocytic soft-tissue sarcoma and has also shown activity in other sarcoma subtypes. However, its clinical efficacy is highly variable, and no reliable predictors exist to date to select patients who are most likely to benefit from this drug. We analyzed the molecular profiles and clinical outcomes of pazopanib-treated sarcoma patients enrolled in a prospective observational study by the German Cancer Consortium, DKTK MASTER, that employs whole-genome/exome sequencing (WGS/WES) and transcriptome sequencing to inform the care of adults with advanced cancer across histologies who are younger than 51 and patients with rare tumors, including rare subtypes of more common entities, regardless of age.​ Among a total of 109 patients with available WGS/WES data, there was no correlation between clinical parameters, specific genetic alterations, or mutational signatures and clinical outcome. In contrast, analysis of a subcohort of 62 patients who underwent molecular analysis before pazopanib treatment and had transcriptome sequencing data available showed that mRNA levels of NTRK3 (hazard ratio [HR]=0.53, p=0.021), IGF1R (HR=1.82, p=0.027), and KDR (HR=0.50, p=0.011) were independently associated with progression-free survival (PFS). Based on the expression of these RTK genes, i.e., the features NTRK3-high, IGF1R-low, and KDR-high, we developed a pazopanib efficacy predictor (PEP) that stratified patients into three groups with significantly different PFS (p<0.0001). Application of the PEP to an independent cohort of pazopanib-treated sarcoma patients from DKTK MASTER (n=43) confirmed its potential to separate patient groups with significantly different PFS (p=0.02), whereas no such association was observed in sarcoma patients from DKTK MASTER (n=77) or The Cancer Genome Atlas sarcoma cohort (n=256) who were not treated with pazopanib. A score based on the combined expression of NTRK3, IGF1R, and KDR allows identification of sarcoma patients with good, intermediate, and poor outcome following pazopanib therapy and warrants investigation as a predictive tool in prospective studies to optimize the use of this drug in the clinic.

  Study EGAS00001005836

• METABRIC

  The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (CNVs, SNPs) and acquired somatic copy number aberrations (CNAs) were associated with expression in 40% of genes, although the landscape was dominated by cis and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP, and MAP2K4. Unsupervised analysis of paired DNA/RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, ER-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration 0152hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the 0152CNA-devoid sub-group and a Basal-specific chromosome 5 deletion-driven mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic copy number aberrations on the transcriptome.

  Study EGAS00000000083

• Exploiting New Patterns of Genome Damage in Triple Negative Breast Cancer

  Genomic instability, a feature of triple negative breast cancers (TNBC), represents an opportunity for discovery of biologic and clinically relevant subgroups of patients. Owing to TP53 mutation in the majority of cases, DNA repair deficiency through loss of BRCA1 and BRCA2, and by expression features patterning a basal cell of origin, TNBC represents a molecularly and clinically distinct group of breast cancer patients. Unfortunately, targetable molecular features of TNBC remain elusive and TNBC patients suffer the poorest outcomes amongst clinical subgroups. Within TNBC patients, responses to treatment vary and although gene expression patterns within TNBC have been identified, little progress has been made in developing biomarkers; effective stratification as a route to directing patients to more targeted therapy is lacking. In this study, we exploit mutational processes in TNBC as a new opportunity to stratify patients and to understand the evolutionary progression of TNBC cells harboring specific DNA repair properties.

  Study phs003038

• Nasopharynx Cancer Whole Exome Sequencing

  Nasopharyngeal carcinoma (NPC) is an aggressive head and neck cancer characterized by Epstein-Barr virus (EBV) infection and dense lymphocyte infiltration. The scarcity of NPC genomic data hinders the understanding of NPC biology, disease progression, and rational therapy design. Here, we performed whole-exome sequencing (WES) on 111 micro-dissected EBV-positive NPCs, with 15 cases subjected to further whole-genome sequencing (WGS), to determine its mutational landscape. We identified enrichment for genomic aberrations of multiple negative regulators of the NF-kB pathway in a total of 41% of cases including CYLD, TRAF3, NFKBIA and NLRC5. Functional analysis confirmed novel inactivating CYLD mutations as drivers for NPC cell growth. The EBV oncoprotein latent member protein 1 (LMP1) functions to constitutively activate NF-kB signaling, and we observed mutual exclusivity among somatic NF-kB pathway aberrations and LMP1-overexpression, suggesting that NF-kB activation is selected for by both somatic and viral events during NPC pathogenesis.

  Study phs001244

• Integrative Analysis for Multi-Omics Data in Non-Small-Cell Lung Cancer

  We conducted epigenetic and transcriptomic mapping of primary non-small cell lung tumors and non-neoplastic tissues. 20 non-neoplastic lung tissues and 18 non-small cell lung tumors were obtained from Biorepository and Tissue Technology Shared Resource at Moores Cancer Center, UC San Diego. All tumor samples were in pathological stages I and II. 8 pairs of samples were "matched", meaning that the tumor and normal tissues came from the same patient. Microfluidic oscillatory washing–based chromatin immunoprecipitation followed by sequencing (MOWChIP-seq) was used to profile the binding of H3K4me1, H3K4me3, H3K9me3, H3K27ac and H3K27me3. SmartSeq-2 was used to map mRNA expression. We identified a large number of differentially modified regions for both epigenetic and transcriptomic markers between tumors and normal tissues. Deep learning model showed extensive transcription factor network rewiring. Raw sequencing data of the ChIP-seq and RNA-seq libraries are available through this dbGaP submission.

  Study phs003113