5624 results for "canc*"

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• Cancer Team Data Access Committee

  Dac EGAC00001003407

• Genotype data for African Esophageal squamous cell cancer cases and controls from South Africa

  This dataset contains the cleaned genotype data from 2173 African eosphageal squamous cell cancer cases and population controls. The genotype data was generated using the H3Africa Illumina Custom microarray.

  Dataset EGAD00010002575

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 9 part 1)

  Whole genome sequencing data of 6 high-grade serous carcinoma (HGSC) patients (11 samples) sequenced with MGISEQ-2000

  Dataset EGAD00001011353

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 7a)

  Whole genome sequencing data of 36 high-grade serous carcinoma (HGSC) patients (89 samples) sequenced with HiSeq X Ten.

  Dataset EGAD00001010845

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 7b)

  Whole genome sequencing data of 21 high-grade serous carcinoma (HGSC) patients (59 samples) sequenced with MGISEQ-2000.

  Dataset EGAD00001011086

• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - RNA-Seq

  This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.

  Dataset EGAD00001011192

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 8a)

  Whole genome sequencing data of 26 high-grade serous carcinoma (HGSC) patients (87 samples) sequenced with MGISEQ-2000 and HiSeq X Ten.

  Dataset EGAD00001011304

• Lymphoctye_colony_WGS

  We study lymphocyte somatic evolution through the sequencing of normal healthy lymphocytes. We perform whole-genome sequencing of single-cell derived T and B cell colonies to identify somatic mutations, and perform targeted deep-sequencing of these mutations. The lineages of T and B cells, and the frequencies of these mutations reveals the neutral and non-neutral evolutionary processes underlying lymphocyte growth and function.

  Study EGAS00001002948

• neoALTTO

  RNAseq fastq files for 254 samples for the neoALTTO study of lapatinib, trastuzumab or combination in HER2+ breast cancer patients. Those are pre-treatment baseline samples.

  Dataset EGAD00001011354

• Tumor-derived cell lines as pharmacogenomic models to predict therapeutic vulnerabilities in hepatocellular carcinoma

  Hepatocellular carcinoma (HCC) is a heterogeneous aggressive malignancy with low efficacy of current therapies at advanced stages. We integrated molecular and pharmacological profiling of a large panel of liver cancer cell lines (LCCL) to assess their clinical relevance as HCC preclinical models and identify new effective therapies and biomarkers of response. Here, we performed multi-omic analysis including whole-exome, RNA and microRNA sequencing in a series 34 LCCL. Molecular profiles of LCCL and primary HCC were compared and we searched for molecular features associated with drug response. Our panel of LCCL faithfully recapitulated the most aggressive molecular “proliferation class” of HCC.

  Dataset EGAD00001004938

• Integrated genomic analysis identifies driver genes and cisplatin-resistant progenitor phenotype in pediatric liver cancer

  Dataset EGAD00001007858

• FunGeST - Functional Genomics from cancer research to personalized medicine

  Dac EGAC00001002924

• Whole Genome Sequencing of Liver Cancers

  Genomic alterations driving tumorigenesis result from the interaction of environmental exposures and endogeneous cellular processes. With a diversity of risk factors including viral infection, carcinogenic exposures and metabolic diseases, liver cancer is an ideal model to study these interactions. Whole genome sequencing of liver tumors identified 10 mutational signatures showing distinct relationships with environmental exposures, replication and transcription. Transcription-coupled damage was specifically associated with the liver-specific signature 16 and alcohol intake. Flood of indels were identified in very highly expressed hepato-specific genes, likely resulting from replication-transcription collisions. Reconstruction of sub-clonal architecture revealed mutational signature evolution during tumor development exemplified by the vanishing of aflatoxin-B1 signature in African migrants. These findings shed new light on the natural history of liver cancers.

  Dataset EGAD00001003281

• RNA-seq of Liver Cancer

  The present series corresponds to 161 RNA-seq samples from tumors with matched WES or WGS. Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Dataset EGAD00001003993

• Whole Genome Sequencing of HCC

  The present series corresponds to 24 whole genome sequencing (12 Tumoral/Non-tumoral pairs). Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Dataset EGAD00001003994

• Whole Exome Sequencing of 60 tumor/normal matched liver Cancers (HCC)

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 60 whole exome tumor/normal pairs with matched RNA-seq.

  Dataset EGAD00001004180

• Hepatocellular adenomas samples

  Whole exome sequencing data from 30 donors (46 tumors and 30 non-tumoral whole exome sequencing, paired-end, HiSeq 2000, Illumina) collected by the Inserm U674, PI Jessica Zucman-Rossi - Institut National du Cancer (INCa), PI Fabien Calvo, France.

  Dataset EGAD00001000737

• Analysis of the Elements Involved in the Enrichment of a Panel of Genomic Regions by Nanopore Sequencing Using Adaptive Sampling

  DNA sequencing using nanopore technologies with the affordable MinION device is useful for the identification and characterization of structural variants, long haplotypes, sequencing of repetitive regions and identification of epigenetic modifications. The main limitation of this approach is the low coverage obtained, which might be avoided by adaptive sampling, a computationally controlled method of enrichment for targeted genomic regions. This study dissects the factors involved in the enrichment by adaptive sampling of a panel of 18 human genome regions containing 20 genes implicated in breast cancer sequenced in 16 patients with familial breast cancer negative for NGS screening. An average coverage of 2.0x was obtained for the whole genome and 5.1x for selected regions. Sequencing time was the main factor improving coverage. The selection of long reads (>1 Kb) did not improve the enrichment. The length of the selected region, which in our study ranged from 126 to 565 Kb, did not play a significant role in enrichment. However, the region containing PMS2 showed significantly lower coverage, which could be explained by the high number of PMS2 pseudogenes (N = 14), which were also enriched. Our study shows new evidence of enrichment obtained by adaptive sampling in a panel of genomic regions and shows parameters, the relevance of sequencing time and the role of pseudogenes, that improve the enrichment yield with no library reloading or GPU use, data useful for a more efficient application of this procedure in future studies.

  Study EGAS00001007375

• Familial breast cancer targeted sequencing with ONT

  A large cohort of 600 cases with familial breast cancer as classified by the Spanish Society of Medical Oncology (SEOM) Clinical Guidelines Update that were recruited during 6 years at Hospital Universitario Morales Meseguer (Murcia, Spain) were retrospectively evaluated to select 16 cases with no positive finding in NGS analysis of 20 genes implicated in this disease. These 16 cases were selected for further investigation using nanopore sequencing. This method involved the use of adaptive sampling enrichment, targeting a panel of 18 human genome regions, which contained the 20 genes (PTEN, ATM, BRCA2, PALB2, CDH1, TP53, NF1, RAD51D, BRCA1, RAD51C ,BRIP1, STK11, CHEK2, EPCAM, MSH2, MSH6, BARD1, MLH1, PMS2, NBN). In 5 samples (P1, P2, P4, P15 and P16) no selection of long reads was performed. Additionally, in 3 samples (P7, P9 and P10), both procedures were performed in two independent runs, and for the second run of P7, the DNA was previously fragmented using g-TUBE Covaris® (ref 520079) according to the protocol for 6 kb fragments.

  Dataset EGAD00001011106

• Sequence data from stage I of the CCTG BR.36 ctDNA-directed, multi-center phase II study of molecular response adaptive immunotherapy in non-small cell lung cancer

  The dataset for the study "Early ctDNA molecular response captures therapeutic response in the first stage of CCTG BR.36 ctDNA-directed, multi-center phase II study of molecular response adaptive immunotherapy in non-small cell lung cancer", includes 134 bam files from hybrid capture targeted error-correction next-generation sequencing (PGDx Elio plasma resolve) from plasma cell-free DNA and matched white blood cell DNA from 35 individuals with non-small cell lung cancer on the BR.36 trial, alongside 11 bam files from targeted next generation sequencing (PGDx Elio tissue complete) of tumor DNA from 11 individuals with non-small cell lung cancer on the BR.36 trial.

  Dataset EGAD00001011359

• Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations

  Molecular characterization of 20 tumors of 18 children with Lynch syndrome to investigate causality. This characterization includes the investigation of second hits, tumor mutational load, mutational signatures and MMR protein expression.

  Study EGAS00001006992

• Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations WXS

  Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations WXS

  Dataset EGAD00001010043

• Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations WGS

  Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations WGS

  Dataset EGAD00001010042

• PELICAN45 and GP21 prostate cancer studies Data Access Committee

  Dac EGAC00001001309

• Low-coverage whole-genome sequencing of cancer and healthy plasma circulating DNA

  Plasma samples from patients with melanoma (stage II/III/IV) and breast cancer (stage IV) as well as healthy individuals were subjected to low-coverage whole-genome sequencing (less than 10x average depth). This dataset contains raw fastq files from 39 breast cancer, 127 melanoma and 42 healthy control plasma samples.

  Dataset EGAD00001011817