6049 results for "canc*"

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• Whole Exome Sequencing of Mixed Histology Lung Cancer

  We conducted whole-exome sequencing (WES) and microarray profiling on 19 micro-dissected tumor regions of different histologic subtypes from 9 patients with lung cancers of mixed histologic patterns including 6 LUAD, 6 LCNEC, 3 SCLC, 3 LUSC, and one poorly differentiated NSCLC-NOS.

  Dataset EGAD00001007076

• Single cells of colorectal cancer organoids

  458 single cell samples of multiple colorectal cancer organoids

  Dataset EGAD00001007305

• A life history of colorectal cancer metastases

  Multiple metastatic sites were sampled at autopsy from four patients diagnosed with metastatic colorectal cancer and subjected to whole-genome sequencing using the Illumina HiSeq X Ten platform to identify somatic variants, structural rearrangements and mutational signatures. The number of tumour samples per patient ranged from 6 to 66.

  Dataset EGAD00001007503

• Breast Cancer Single-Cell RNA-Seq Dataset

  Single-cell RNA-Sequencing of 26 primary breast cancers from Wu et al. (2021) study. Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq 500 platform.

  Dataset EGAD00001007495

• sWGS on cfDNA and matching tumor DNA in pediatric cancer

  This dataset contains shallow whole genome sequencing data from paired cfDNA - tumor DNA samples of various pediatric cancer entities (total 215 samples). Files are provided in fastq format. Samples were sequenced on an Ion Proton sequencer (Thermo Fisher Scientific) or a Hiseq3000 (Illumina). Data analysis is available at https://github.com/rmvpaeme/sWGS_pediatric_cancer.

  Dataset EGAD00001007508

• Somatic copy-number alterations in plasma circulating tumor DNA from advanced EGFR-mutated lung adenocarcinoma patients

  This is the raw data obtained from shallow whole-genome sequencing of plasma DNA (plasma-seq) for calling of somatic copy number alterations as well as focal amplifications from patients with lung cancer.

  Dataset EGAD00001007505

• November 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  November 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001007529

• 252 human breast cancer samples in WGS and WES

  We analyzed chromothripsis in 252 human breast cancers from two patient cohorts (149 metastatic breast cancers, 63 untreated primary tumors, 29 local relapses, 11 longitudinal pairs) using whole-genome and whole-exome (paired) sequencing. A lot of the WGS samples were sequenced on Illumina HiSeq X-Ten using Illumina TruSeq Nano DNA. For exome sequencing Agilent_SureSelect_V5+UTRs has been used (sequencing on Hiseq2000, Hiseq2500 and Hiseq4000). For exome sequencing Agilent_SureSelect_V5+UTRs has been used (sequencing on Hiseq2000, Hiseq2500 and Hiseq4000).

  Dataset EGAD00001007563

• Comparison of sequencing assays for sensitive detection of circulating tumour DNA in stage IA-IV breast cancer

  This study compared different assays for the detection of circulating tumour DNA (ctDNA) in serial plasma from stage IA-IV breast cancer patients, targeting structural variants (SVs), single nucleotide variants (SNVs) and/or somatic copy-number aberrations (SCNAs). SV-multiplex PCR, SNV-/SV-hybrid capture, and different depths of whole-genome sequencing (WGS) were used to evaluate ctDNA levels, demonstrating concordant results. SNV-hybrid capture targeting 1,347-7,491 mutations was the most sensitive assay, detecting 67% (36/54) of samples down to an allele fraction (AF) of 0.00024%. SV-multiplex PCR, targeting 21-47 mutations, detected 63% (34/54) of samples down to 0.00047% AF and has potential as a clinical assay.

  Dataset EGAD00001008589

• Evolutionary trajectories and clonal migration underlying tumor progression and lymph node metastasis in resectable lung cancer

  In this prospective study, targeted deep sequencing was performed on a total of 160 primary tumors (474 regions) and 112 lymph nodes from 125 patients with stage I-III lung cancer (LuCaTH). Progressive evolution at clonal divergence scale was observed while specific driver events were positively selected for clonal sweeps during tumor development. Between-region genetic divergence (BRGD) of tumors were assessed and positively correlated with tumor differentiation. A machine learning algorithm was employed to evaluate clinicopathological and molecular parameters of primary tumors underlying lymph node metastasis. By analyzing clonal lineages and metastatic trajectories across multiple nodal stations, we unraveled a common sequential LNM seeding pattern but with divergent modes of clonal spread.

  Dataset EGAD00001007587