5707 results for "canc*"

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• 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