7361 results for "canc*"

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• Somatic_mutation_in_skin_epidermis__SMS_

  We aim to assess the range and depth of mutations in genes linked with cancer in skin epidermis surrounding lesions which are undergoing surgical removal. Patient history will be collected to provide a detailed outline of tumour type (including histology), skin type, and sunlight exposure. We will perform ultra-deep targeted sequencing using genes implicated in cancer to try and understand the background of mutations surrounding these lesions

  Study EGAS00001002165

• Whole-exome sequencing of ovarian clear cell carcinoma in clinical outliers

  Whole-exome sequencing dataset for the Australian Ovarian Cancer Study (AOCS) and The Jikei University School of Medicine (JIKEI) ovarian clear cell carcinoma (OCCC) clinical outliers project, representing 10 donors. Although OCCC are commonly resistant to platinum based chemotherapy, good clinical outcomes are observed in a subset of patients. Exome sequencing was performed in 10 patients who had either unusually long survival (N=5) or had a very short time to progression (N=5).

  Study EGAS00001004248

• Hereditary Cancer Diagnostics with I2HCP gene panel

  This dataset contains targetted DNA sequencing data generated in the context of genetic diagnostics of hereditary cancer. Target enrichment was performed with the I2HCP, a custom hereditary cancer gene panel based in Agilent SureSelect and developed by the Germans Trias i Pujol Research Institute (IGTP, Badalona, Catalonia, Spain) and the Catalan Institute of Oncology (ICO, L'Hospitalet de Llobregat, Catalonia, Spain). After the enrichment, 108 samples were sequenced in Illumina HiSeq machines and 130 in MiSeq machines. Some of the samples were sequenced on both platforms. The dataset also includes MLPA validation data for all identified copy-number alterations, annotated with exon resolution and information about negative MLPA results. All this data was generated in the context of routine diagnostics and compiled together with MPLA validation data for a genetic diagnostics oriented benchmark of germline CNV calling tools.

  Study EGAS00001004316

• TSG_knock_out_in_hiPSCs

  We will perform RNAseq to evaluate the effects of the loss of a list of TSGs on the transcriptome.

  Study EGAS00001002262

• Molecular origins of mpMRI visibility

  Multiparametric magnetic resonance imaging (mpMRI) has transformed the landscape of prostate cancer (PCa) management. Prostate Imaging Reporting and Data System (PI-RADSv2) scores reflect function and correlate phenotypic features with tumor aggressiveness, is an independent predictor of biochemical recurrence, and may distinguish low-risk tumors requiring no treatment from high-risk tumors requiring aggressive management. We hypothesize that differences in functional mpMRI of prostate tumors reflect the genetic and epigenetic heterogeneity of PCa. We profiled the genomes and transcriptomes of 40 Gleason score 3+4 tumors, of which 20 tumors were mpMRI invisible (not PI-RADSv2 3-5) and 20 tumors were visible (PI-RADSv2 5). Genomes of visible tumors were more unstable than those of invisible tumors. We identified 62 enriched transcripts, including numerous snoRNAs, Relaxin 1 and SCHLAP1, in visible tumors. These data suggest a confluence of aggressive pathological and microenvironmental phenomenon in PI-RADSv2 5 tumors reminiscent of nimbosus, while linking the molecular profiles of tumor aggressiveness with their functional features on mpMRI.

  Study EGAS00001003179

• Coding and non-coding drivers of mantle cell lymphoma identified through exome and genome sequencing

  Mantle cell lymphoma (MCL) is an uncommon B-cell non-Hodgkin lymphoma (NHL) that is incurable with standard therapies. The genetic drivers of this cancer have not been firmly established and the features that contribute to differences in clinical course remain limited. To extend our understanding of the biological pathways involved in this malignancy, we performed a large-scale genomic analysis of MCL using data from 51 exomes and 34 genomes alongside previously published exome cohorts. To confirm our findings, we re-sequenced the genes identified in the exome cohort in 191 MCL tumors, each having clinical follow-up data. We confirmed the prognostic association of TP53 and NOTCH1 mutations. Our sequencing revealed novel recurrent non-coding mutations surrounding a single exon of the HNRNPH1 gene. In RNA-seq data from 103 of these cases, MCL tumors with these mutations had a distinct imbalance of HNRNPH1 isoforms. This altered splicing of HNRNPH1 was associated with inferior outcomes in MCL and showed a significant increase in protein expression by immunohistochemistry. We describe a functional role for these recurrent non-coding mutations in disrupting an auto-regulatory feedback mechanism, thereby deregulating HNRNPH1 protein expression. Taken together, these data strongly implicate a role for aberrant regulation of mRNA processing in MCL pathobiology.

  Study EGAS00001004289

• MethCORR: DNA Methylation-based Characterization, Classification and Prognostication of Colorectal Cancer using Archival Formalin-fixed, Paraffin-embedded Tissue

  Transcriptional characterization and classification has potential to resolve the inter-tumor heterogeneity of colorectal cancer (CRC) and improve patient management. Yet, robust transcriptional profiling is difficult using formalin-fixed, paraffin-embedded (FFPE) samples, which complicates testing in clinical and archival material. We present MethCORR, an approach that allows uniform molecular characterization and classification of fresh-frozen and FFPE samples. MethCORR identifies genome-wide correlations between RNA expression and DNA methylation in fresh-frozen samples. This information is used to infer gene expression information in FFPE samples from their DNA methylation profiles. MethCORR was applied to methylation profiles from 877 fresh-frozen and FFPE samples and comparative analysis identified the same two major subtypes in four independent cohorts. Furthermore, subtype-specific prognostic biomarkers that better predicted relapse-free survival (HR=2.66, 95% CI [1.67-4.22], P<0.001) than TNM staging and MSI status were identified and validated using DNA methylation-specific PCR assays. The MethCORR approach is general, and may be similarly successful for other cancer types.

  Study EGAS00001004293

• The Landscape of Genetic Alterations in Hepatocellular Carcinoma, 88 matched HCC tumour/normal pairs WGS belongs to ICGC LICA-CN project

  Hepatocellular carcinoma (HCC) is the most common malignancy of the liver. Genomic analysis is conducted to identify genetic alterations in driver genes which are all druggable targets for cancer therapy. Whole genome shotgun sequencing (WGS) and the landscaple of somatic mutations in 88 paired samples from HCC patients including tumors and matched adjacent normal tissues using Illumina HiSeq 2000 platform were performed.

  Study EGAS00001002218

• WGS_of_AML_during_PARPi_therapy

  We will require WGS on Illumina X10 machines of three samples, along with storage and computational power to perform the relevant analysis.

  Study EGAS00001002274

• Oesophageal_Adenocarcinoma_Organoid_10x

  10x Sequencing of 6 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical rescetion of the tumour. All model derivations took place with the CGaP facility in Sanger. This 10x data will be combined with other sequencing data in order to generate accurate reference cancer genomes.

  Study EGAS00001003191