8252 results for "canc*"

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• Bam files for a metastatic bladder cancer patient with BAP1 variants

  This dataset consists of three bam files (two cell-free DNA and one germline DNA) from a metastatic bladder cancer patient with BAP1 variants. Bam files were generated from targeted Illumina sequencing data.

  Dataset EGAD00001005520

• Heterogeneous metabolic signatures are linked to cancer cell differentiation in colorectal cancer

  Colorectal cancer (CRC) is characterized by functional intratumor heterogeneity that shares many similarites with the hierarchical organization of the normal intestinal epithelium. In order to relate transcriptional subtypes to functional tumor cell heterogeneity we applied scRNA-seq to 12 patient-derived CRC spheroid cultures. We identified shared expression programs that relate to intestinal lineages and revealed metabolic signatures that are linked to cancer cell differentiation. In addition, we validated and complemented sequencing results by quantitative microscopy using live-dyes and multiplexed RNA fluorescence in situ hybridization, thereby revealing metabolic compartmentalization and potential cell-cell interactions. Finally, we demonstrate functional differences between metabolically distinct lineage subtypes that might have strong implications for future treatment strategies of CRC.

  Dataset EGAD00001005524

• Ovarian cancer organoid biobank - followup

  WGS of more samples in the ovarian cancer organoid biobank dataset.

  Dataset EGAD00001005707

• Neoantigen study samples for prostate cancer

  Whole exome sequencing and RNA sequencing data from 30 patients with prostate cancer.

  Dataset EGAD00001005713

• pancreatic ductal adenocarcinoma exomes in study: Pro-immunogenic Impact of MEK inhibition combined with an anti-CD40 immunostimulatory antibody

  This dataset contains 3 pairs of exomes, germline (from whole blood) and patient-derived xenograft (PDX), from human pancreatic durctal adenocarcinoma patients. The data is referred to in the publication: "Pro-immunogenic impact of MEK inhibition synergizes with agonist anti-CD40 immunostimulatory antibodies in tumor therapy" (Nature Communications, 2020) Abstract: Cancer types with lower mutational load and a non-permissive tumor microenvironment are intrinsically resistant to immune checkpoint blockade. While the combination of cytostatic drugs and immunostimulatory antibodies constitutes an attractive concept for overcoming this refractoriness, suppression of immune cell function by cytostatic drugs may limit therapeutic efficacy. Here we show that targeted inhibition of mitogen-activated protein kinase (MAPK) kinase (MEK) does not impair dendritic cell-mediated T-cell priming and activation. Accordingly, combining MEK inhibitors (MEKi) with agonist antibodies (Abs) targeting the immunostimulatory CD40 receptor resulted in potent synergistic anti-tumor efficacy. Detailed analysis of the mechanism of action of MEKi GDC-0623 by means of flow cytometric analysis of the tumor immune infiltrate and whole tumor transcriptomics showed that, in addition to its cytostatic impact on tumor cells, this drug exerts multiple pro-immunogenic effects, including the suppression of M2-type macrophages, myeloid derived suppressor cells and CD4+ T-regulatory cells. In addition, MEKi was found to induce tumor-cell intrinsic interferon signaling, which contributed to antigen presentation by tumor cells. Finally, the tumoridical impact of MEKi involves the activation of multiple pro-inflammatory pathways involved in immune cell effector function in the tumor microenvironment. Our data therefore indicate that the combination of MEK inhibition with agonist anti-CD40 Ab is a promising therapeutic concept, especially for the treatment of mutant Kras-driven tumors such as pancreatic ductal adenocarcinoma.

  Dataset EGAD00001005938

• PCa mtDNA data

  50 paired benign/cancer samples from prostate tissue generated in 2 different runs - on 3 plates on the IonTorrent Proton. Total of 200 fastq.gz single end runs. Read length ~300 bp. %GC 44 Sequences per file approx 1 Mio.

  Dataset EGAD00001005945

• Ovarian cancer sample size analysis

  The dataset contains exome sequencing fastq from 5 ovarian cancer patients, paired with tumor normal blood samples. Three tumor samples were sequenced from each patient: a biopsy sample ("-1" suffix in the file name), a local sample (multiple regions around the biopsy pooled together, with the "-2" suffix in the file name), and a global sample (multiple regions from the tumor pooled together, with a "-3" suffix in the file name).

  Dataset EGAD00001005947

• Organoid Derivation Project WGS: Release 2

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients.

  Dataset EGAD00001005955

• WES_localized non-small cell lung cancer (540 samples)_MDACC

  Whole exome sequencing of tumors and paired adjacent uninvolved tissues from 222 early stage NSCLC patients, in order to identify genomic drivers present in early-stage non-small cell lung cancer and determine the overall tumor mutational burden in early-stage non-small cell lung cancer.

  Dataset EGAD00001005956

• Organoid Derivation Project TGS: Release 3

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients.

  Dataset EGAD00001005958

• Metastases of a cancer of unknown primary (CUP)

  RNA seq analysis of 6 CUP metastases (each in triplicate), analysed by paired sequencing with NextSeq 500. Whole exome sequencing of 15 CUP metastases, analysed by paired sequencing with NextSeq 500.

  Dataset EGAD00001005963

• ATAC-seq

  ATAC-seq data for 26 CLL samples (7 controls, 19 tumor) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005967

• single-cell ATAC-seq

  Single-cell ATAC-seq data for 5 CLL samples (2 controls, 3 tumor) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005965

• T-WGBS for Naive B Cell

  Tagged-WGBS for 3 Naive B Cell samples of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005966

• WGBS for T-Cell and B-Cell, control and tumor

  WGBS data for 75 paired fastq, spread over 31 samples (4 healthy T-cell, 7 healthy B-cell, 20 B-cell CLL tumors) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005970

• combined ChIPseq (H3, modifications and TF)

  ChIPseq data for 31 CLL samples (12 controls, 19 tumor) of the CancerEpiSys-PRECiSe project; containing histone H3, histone modifications and transcription factor binding sites (CTCF, EBF1).

  Dataset EGAD00001005969

• long RNA data

  long RNA data for 27 CLL samples (8 controls, 19 tumor) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005968

• Single MII oocyte mRNA expression from women

  This dataset contains 14 paired-end FASTQ sequences from mRNA-Seq on single human M-II stage oocytes that were collected from ovarian tissue from unstimulated patients undergoing fertility preservation treatments due to cancer diagnoses, which did not influence ovarian function. Cumulus-oocyte-complexes were matured in vitro according Gruhn et al (Science 365: 1466-1469) and short term flash frozen prior to lysis, RNA extraction, full length cDNA preparation and amplification using the Ultra-low-input SMART-Seq2 v4 kit from Takara Clonetech. Further, these cDNA were used to prepare libraries for sequencing according the Nextera XT DNA library preparation kit from Illumina

  Dataset EGAD00001005971

• CYPTAM - PacBio SMRT sequencing

  Dataset contains CYP2D6 sequencing data of 566 individuals who used tamoxifen as adjuvant breast cancer therapy. Phenotype data consists of the ratio between the metabolites endoxifen and desmethyltamoxifen (Metabolic ratio (MR)) as a proxy for CYP2D6 enzyme activity. Each sample is linked to one bam-file containing the CYP2D6 sequence.

  Dataset EGAD00001005972

• Long-read sequencing of prostate adenocarcinoma metastatic to left axillary lymph node. Data used to support Figure 6 in Pubmed ID 32025007 "Pan-Cancer Analysis of Whole Genomes Consortium." Nature 2020 578:8293.

  Oxford Nanopore long-read sequencing of A17-LAxillaryLN2Met-23312 PELICAN sample, identified as D051965 un Pan-Cancer Analysis of Whole Genomes study, and identified as PD13412a by prior Gundem et al whole genome sequencing study (PMID 25830880). Data used to support Figure 6 in Pubmed ID 32025007 "Pan-Cancer Analysis of Whole Genomes Consortium." Nature 2020 578:8293.

  Dataset EGAD00001005974

• NanoString gene expression of PBMC from bladder cancer and RCC patients

  This dataset contains NanoString gene expression of PBMC from patients from IMvigor210, IMvigor211 and IMmotion150 cohorts

  Dataset EGAD00001005976

• Single Cell RNAseq of blood and tumor from renal cancer patients

  Single Cell RNAseq of blood and tumor from renal cancer patients

  Dataset EGAD00001005977

• Omics data of advanced bladder cancer

  To identify the therapeutic targets in a treatment-refractory cancer patient, we performed single-cell RNA sequencing for 3,115 cells from primary bladder cancer (BC159-T#3) and patient-derived xenografts (BC159-T#3-PDX-vehicle and BC159-T#3-PDX-tipifarnib). Matched time-series bulk tumor tissues were also sequenced using whole exome target probe (WES) and whole transcriptome target probe (WTS).

  Dataset EGAD00001005978

• MutWP5: CRUK Mutographs of Cancer: Lung: PD37920 (WG) (2020-02-20)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005990

• MutWP5: CRUK Mutographs of Cancer: Lung: PD38234 (WG) (2020-02-20)

  Sequencing of LCM-derived microbiopsies from explanted lung from pulmonary fibrosis patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005991