7201 results for "canc*"

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• miRNA expression data from primary tumors, metastasis and matched normals.

  MicroRNAs (miRs) have been recognized as promising biomarkers. It is unknown to what extent tumor-derived miRs are differentially expressed between primary colorectal cancers (pCRCs) and metastatic lesions, and to what extent the expression profiles of tumor tissue differ from the surrounding normal tissue. Next-generation sequencing (NGS) of 220 fresh-frozen samples, including paired primary and metastatic tumor tissue and non-tumorous tissue from 38 patients, revealed expression of 2245 known unique mature miRs and 515 novel candidate miRs. Unsupervised clustering of miR expression profiles of pCRC tissue with paired metastases did not separate the two entities, whereas unsupervised clustering of miR expression profiles of pCRC with normal colorectal mucosa demonstrated complete separation of the tumor samples from their paired normal mucosa. Two hundred and twenty-two miRs differentiated both pCRC and metastases from normal tissue samples (false discovery rate (FDR) <0.05). The highest expressed tumor-specific miRs were miR-21 and miR-92a, both previously described to be involved in CRC with potential as circulating biomarker for early detection. Only eight miRs, 0.5% of the analysed miR transcriptome, were differentially expressed between pCRC and the corresponding metastases (FDR <0.1), consisting of five known miRs (miR-320b, miR-320d, miR-3117, miR-1246 and miR-663b) and three novel candidate miRs (chr 1-2552-5p, chr 8-20656-5p and chr 10-25333-3p). These results indicate that previously unrecognized candidate miRs expressed in advanced CRC were identified using NGS. In addition, miR expression profiles of pCRC and metastatic lesions are highly comparable and may be of similar predictive value for prognosis or response to treatment in patients with advanced CRC.

  Dataset EGAD00001001644

• BASIS BC WGS Dataset

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001337

• Whole genome sequencing of RIKEN liver cancers

  RIKEN collection of WGS reads of 530 liver cancer and matched blood samples from 260 donors.

  Dataset EGAD00001001642

• Complete DNA/RNA sequencing dataset for Australian ICGC ovarian cancer sequencing project 2014-07-07

  Complete WGS and RNA-Seq dataset for Australian ICGC ovarian cancer sequencing project 2014-07-07, representing 93 donors. Sequencing was performed on Illumina HiSeq. Alignment of the lane-level fastq data was performed with bwa (WGS data) and RSEM (transcriptome data). For this dataset lane-level .bam files have been merged and de-duplicated to create a single bam file for each sample type (tumour/normal) for each donor. This dataset supersedes all previous datasets for this study. 2016-08-08 updated with 14 outstanding RNA-seq samples & corresponding RSEM bams 2016-12-07 updated with 7 outstanding RNA-seq controls and corresponding RSEM bams

  Dataset EGAD00001000877

• Bulk RNASeq on CD8+CD69+CD103+ and CD8+CD69+CD103- T cells form breast cancer.

  CD8+CD69+CD103+ and CD8+CD69+CD103- T cells were flow sorted from 1 primary triple negative breast cancer, 1 primary HER2 amplified breast cancer, and 1 triple negative liver metastasis. Prior to flow sorting, fresh tumor samples were digested to produce single cell homogenates on the day of surgery. Following RNA extraction, RNASeq was performed using polyA selection.

  Dataset EGAD00001003964

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the lung patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004680

• 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

• Genome and transcriptome sequence data from a metastatic pancreatic cancer patient

  Genome and transcriptome sequence data from a metastatic pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004715

• TRACERx100 metastatic samples

  Whole exome sequencing of 10 metastatic biopsies from four TRACERx100 patients (see EGA dataset EGAS00001002247), collected either after relapse or death. The data from these samples are initially published with Abbosh, C. et al. Phylogenetic ctDNA analysis depicts early stage lung cancer evolution. Nature, http://dx.doi.org/10.1038/nature22364 (2017). Abstract: Earlier detection of relapse following primary surgery for non-small cell lung cancer and the characterization of emerging subclones seeding metastatic sites might offer new therapeutic approaches to limit tumor recurrence. The potential to non-invasively track tumor evolutionary dynamics in ctDNA of early-stage lung cancer is not established. Here we conduct a patient-specific approach to ctDNA profiling in the first 100 lung TRACERx (TRAcking Cancer Evolution through therapy (Rx)) study participants, including one patient co-recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release in early-stage non-small cell lung cancer and perform tumor volume limit of detection analyses. Through blinded profiling of post-operative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients destined to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastases, providing a new approach for ctDNA driven therapeutic studies.

  Dataset EGAD00001003301

• TCR- and BCR-sequencing data for The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

  Each tumor sample was cut into three pieces, yielding two end-pieces for cryovials and a middle portion placed in 10% buffered formalin. End pieces were homogenized manually and with a paddle blender (Stomacher). All paraffin-embedded blocks, including formalin-fixed tumor samples and molecular-fixed fallopian tubes, were sectioned and stained with hematoxylin and eosin prior to expert histopathological review to confirm the presence of high grade serous carcinoma. Homogenized end pieces were then flash frozen, and RNA was extracted using the miRNeasy Mini kit. Nanodrop was used to assess quality (260/280) and quantity. Total RNA samples were also QC checked using the Caliper HT RNA HiSens assay. Samples ranging from 60-255ng RNA were re-arrayed into a 96-well plate. 5'-RACE PCR was carried out as described in "The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer" (Zhang et al.). Briefly, this involved first round and nested PCR with TRB (TCR beta chain) and IGH (immunoglobulin heavy chain) gene-specific primers. The indexed libraries were sequenced on the Illumina HiSeq platform with paired-end 250bp reads using v2 chemistry reagents.

  Dataset EGAD00001003985