7084 results for "canc*"

in 12.58 milliseconds.

• RNA-seq data from 121 tumor samples with muscle invasive bladder cancer.

  In this study, a total of 300 patients with MIBC receiving chemotherapy were included; 62 received NAC before cystectomy and 245 received first-line chemotherapy upon detection of locally-advanced (T4b) or metastatic disease. Treatment response, defined as pathological downstaging (< pTa,CIS,N0) after NAC or complete or partial response after first-line treatment (RECIST criteria). RNA-seq was performed using the QuantSeq kit FWD HT kit (Lexogen) using 500 ng input RNA from 121 tumor samples. Data provided here consist of 780 fastq files for RNA-seq.

  Study EGAS00001004505

• Chromosomal copy number heterogeneity predicts survival rates across cancers

  Survival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis1,2. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing3. Here, we introduce a scalable measure of chromosomal copy number heterogeneity that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 35 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

  Study EGAS00001004702

• Super enhancers define regulatory subtypes and cell identity in neuroblastoma

  Half of the children diagnosed with neuroblastoma have high-risk disease, disproportionately contributing to overall childhood cancer-related deaths. In addition to recurrent gene mutations, there is increasing evidence supporting the role of epigenetic deregulation in disease pathogenesis. Yet, comprehensive cis-regulatory network descriptions from neuroblastoma tissues are lacking. Here, using genome-wide H3K27ac profiles across 60 neuroblastomas, covering the different clinical and molecular subtypes, we identified four major super enhancer-driven epigenetic subtypes and their underlying master regulatory networks. Three of these subtypes recapitulated known clinical groups, namely MYCN amplified, MYCN non-amplified high-risk and MYCN non-amplified low-risk neuroblastomas. The fourth subtype, exhibiting mesenchymal characteristics, shared features with multipotent Schwann cell precursors, was induced by RAS activation and enriched in relapsed disease. Notably, CCND1, a disease essential gene, was regulated by both mesenchymal and adrenergic regulatory networks converging on distinct super-enhancer modules. Together, this reveals subtype-specific super-enhancer regulation in neuroblastoma.

  Study EGAS00001004551

• Angiosarcoma_follow_up_study

  A bespoke targeted pulldown experiment will be performed on patients with Angiosarcoma. the resulting products will be sequenced to determine the prevalence of previously found mutations in these patients.

  Study EGAS00001000405

• Mutational signatures in head and neck cancer (H019)

  Genomic alterations are a driving force in the multistep process of head and neck cancer (HNC) and result from the interaction of exogenous environmental exposures and endogenous cellular processes. Each of these processes leaves a characteristic pattern of mutations on the tumor genome providing the unique opportunity to decipher specific signatures of mutational processes operative during HNC pathogenesis and to address their prognostic value. Computational analysis of whole exome sequencing data of the HIPO-HNC (n=83) and TCGA-HNSC (n=506) cohorts revealed five common mutational signatures (COSMIC signature 1, 2, 3, 13 and 16), and demonstrated their significant association with etiological risk factors (tobacco, alcohol and HPV16).

  Study EGAS00001004588

• Molecular sub-classification of hormone receptor-positive breast cancer

  Patients with estrogen and/or progesterone receptor-positive breast cancer benefit from hormonal treatment, yet high global death burdens due to high prevalence and long-term recurrence risk call for biomarkers to guide additional treatment approaches. From a prospective, observational study of postmenopausal early breast cancer patients treated with tamoxifen or aromatase inhibitors gene expression analyses of 612 tumors was performed using the NanoString® Breast Cancer 360 panel. We identified novel gene expression signatures, i.e. BRCAness and Tumor Inflammation Signature (associated with high tumor lymphocyte infiltration), that may aid to select high-risk patients in order to improve adjuvant treatment by targeting DNA repair deficiency or immune-checkpoints in addition to standard chemo-endocrine treatment. The overall goal is to foster novel concepts for a stratified early breast cancer management.

  Study EGAS00001004594

• whole genome sequence data of multifocal hepatocellular carcinoma

  Background & Aims: The differentiation of distinct multifocal hepatocellular carcinoma (HCC): multicentric disease vs. intrahepatic metastases, in which the management and prognosis varies substantively, remains problematic. We aim to stratify multifocal HCC and identify novel diagnostic and prognostic biomarkers by performing whole genome and transcriptome sequencing, as part of a multi-omics strategy Methods: A complete collection of tumour and somatic specimens (intrahepatic HCC lesions, matched non-cancerous liver tissue and blood) were obtained from representative patientswith multifocal HCC exhibiting two distinct postsurgical courses. Whole-genome and transcriptome sequencing with genotyping were performed for each tissue specimen to con-trast genomic alterations, including hepatitis B virus integrations, somatic mutations, copy number variations, and structural variations. We then constructed a phylogenetic tree to visualise individual tumour evolution and performed functional enrichment analyses on select differentially expressed genes to elucidate biological processes involved in multifocal HCC development. Multi-omics data were integrated with detailed clinicopathological information to identify HCC biomarkers, which were further validated using a large cohort of HCC patients (n = 174).Results: The multi-omics pro?ling and tumour biomarkers could successfully distinguish the two multifocal HCC types, while accurately predicting clonality and aggressiveness. The dual speci?city protein kinase TTK, which is a key mitotic checkpoint regulator with links to p53 signaling, was further shown to be a promising overall prognostic marker for HCC in the large patient cohort.Conclusions: Comprehensive multi-omics characterisation of multifocal tumour evolution may improve clinical decision-making, facilitate personalised medicine, and expedite identi?cation of novel biomarkers and therapeutic targets in HCC.

  Study EGAS00001002338

• In this study, we performed exon sequencing (WXS) of 80 paired Brain cancer tumors and adjacent normal tissues to identify novel potential biomarkers. We extracted mutational signatures which induce somatic mutations . Our study covers a comprehensive genetic framework that can be used in clinical trials and treatment modalities in Brain cancer.

  In this study, we performed exon sequencing (WXS) of 80 paired Brain cancer tumors and adjacent normal tissues to identify novel potential biomarkers. We extracted mutational signatures which induce somatic mutations . Our study covers a comprehensive genetic framework that can be used in clinical trials and treatment modalities in Brain cancer.

  Study EGAS00001002352

• CEHM

  Study of the genetic and epigenetic clonal evolution of blood cancers.

  Study EGAS00001002366

• Genomic analysis of patient-derived xenograft models reveals intratumor-heterogeneity in endometrial cancer and can predict tumor growth inhibition with talazoparib

  Background: Endometrial cancer (EC) is a major gynecological cancer with increasing incidence. It comprised of four molecular subtypes with differing etiology, prognoses, and response to chemotherapy. In the future, clinical trials testing new single agents or combination therapies will be targeted to the molecular subtype most likely to respond. Pre-clinical models that faithfully represent the molecular subtypes of EC are urgently needed, we sought to develop and characterize a panel of novel EC patient-derived xenograft (PDX) models. Methods: Here, we report whole exome or whole genome sequencing of 11 PDX models and the matched primary tumor. Analysis of multiple PDX lineages and passages was performed to study tumor heterogeneity across lineages and/or passages. Based on recent reports of frequent defects in the homologous recombination (HR) pathway in EC, we assessed mutational signatures and HR deficiency scores and correlated these with in vivo responses to the PARP inhibitor (PARPi) talazoparib in six PDXs representing the copy number high/p53-mutant and mismatch-repair deficient molecular subtypes of EC. Results: PDX models were successfully generated with similar histomorphology from all four molecular subtypes of EC and uterine carcinosarcomas. We also observed a wide range of inter-tumor and intra-tumor heterogeneity across different PDX lineages, however one arm of most PDX models recapitulated the molecular landscape of the primary tumor without major genomic drift. An in vivo response to talazoparib was detected in four copy number high models. Two models (carcinosarcomas) showed a response consistent with stable disease and two models (one copy number high serous EC and another carcinosarcoma) showed significant tumor growth inhibition, albeit one consistent with progressive disease, however all lacked the HR deficiency genomic signature. Conclusions: EC PDX models represent the four molecular subtypes of disease and can capture intra-tumoral heterogeneity of the original primary tumor. PDXs of the copy number high molecular subtype showed sensitivity to PARPi, however, deeper and more durable responses will likely require combination of PARPi with other agents.

  Study EGAS00001004666