7297 results for "canc*"

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• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

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

  Dataset EGAD00001010984

• Genome sequence data from a metastatic paraganglioma patient

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

  Dataset EGAD00001010985

• Genome and transcriptome sequence data from a metastatic papillary renal cell ca patient

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

  Dataset EGAD00001010986

• Genome and transcriptome sequence data from a lung adenocarcinoma patient

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

  Dataset EGAD00001010987

• Genome and transcriptome sequence data from a prostate adenocarcinoma patient

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

  Dataset EGAD00001010988

• Genome and transcriptome sequence data from a unknown - likely pancreatobiliary / intrahepatic cholangiocarcinoma in liver patient

  Genome and transcriptome sequence data from a unknown - likely pancreatobiliary / intrahepatic cholangiocarcinoma in liver patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010989

• Genome and transcriptome sequence data from a metastatic thymic carcinoma patient

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

  Dataset EGAD00001010990

• Genome and transcriptome sequence data from a colorectal cancer patient

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

  Dataset EGAD00001010991

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

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

  Dataset EGAD00001010992

• Genome and transcriptome sequence data from a metastatic lymphoepithelial carcinoma of the parotid gland patient

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

  Dataset EGAD00001010993

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

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

  Dataset EGAD00001010994

• Genome and transcriptome sequence data from a primary unknown patient

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

  Dataset EGAD00001010995

• Genome and transcriptome sequence data from a metastatic duodenal carcinoma patient

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

  Dataset EGAD00001010996

• Genome and transcriptome sequence data from a hepatic cholangiocarcinoma patient

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

  Dataset EGAD00001010997

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

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

  Dataset EGAD00001010998

• Genome and transcriptome sequence data from a breast invasive ductal adenocarcinoma patient

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

  Dataset EGAD00001010999

• Genome and transcriptome sequence data from a melanoma patient

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

  Dataset EGAD00001011000

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

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

  Dataset EGAD00001011001

• Genome and transcriptome sequence data from a metastatic breast carcinoma (er positive) patient

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

  Dataset EGAD00001011002

• Genome and transcriptome sequence data from a paget disease of the vulva patient

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

  Dataset EGAD00001011003

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

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

  Dataset EGAD00001011004

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

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

  Dataset EGAD00001011005

• Genome and transcriptome sequence data from a poorly differentiated adenocarcinoma of the pancreas patient

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

  Dataset EGAD00001011006

• Genome and transcriptome sequence data from a inflammatory myofibroblastic lung tumor patient

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

  Dataset EGAD00001011007

• Genome and transcriptome sequence data from a colorectal adenocarcinoma patient

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

  Dataset EGAD00001011008

• Genome and transcriptome sequence data from a metastatic pancreatic neuroendocrine tumour patient

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

  Dataset EGAD00001011009

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

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

  Dataset EGAD00001011010

• Genome and transcriptome sequence data from a metastatic pancreatic neuroendocrine adenocarcinoma patient

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

  Dataset EGAD00001011011

• Genome and transcriptome sequence data from a metastatic cholangiocarcinoma patient

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

  Dataset EGAD00001011012

• Genome and transcriptome sequence data from a metastatic colorectal carcinoma patient

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

  Dataset EGAD00001011013

• Genome and transcriptome sequence data from a metastatic esophageal adenocarcinoma patient

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

  Dataset EGAD00001011014

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

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

  Dataset EGAD00001011015

• Genome and transcriptome sequence data from a metastatic thymic carcinoma patient

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

  Dataset EGAD00001011016

• Genome and transcriptome sequence data from a metastatic nasopharyngeal carcinoma patient

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

  Dataset EGAD00001011017

• Genome and transcriptome sequence data from a metastatic melanoma patient

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

  Dataset EGAD00001011018

• Genome and transcriptome sequence data from a metastatic pancreatic neuroendocrine tumour patient

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

  Dataset EGAD00001011019

• Genome and transcriptome sequence data from a metastatic carcinoma of unknown primary patient

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

  Dataset EGAD00001011020

• Genome and transcriptome sequence data from a metastatic breast ductal carcinoma patient

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

  Dataset EGAD00001011021

• Total RNA sequencing data from the Triple Negative Trial (TNT)

  BAM files from total RNA sequencing of samples from breast cancer patients in the TNT trial. Data includes 186 primary tumour samples and 13 matched recurrence samples.

  Dataset EGAD00001011141

• Exome sequencing data from two small cell prostate cancer patients

  Exome sequencing data from two small cell prostate cancer patients - 4 cancer samples (FFPE) from Patient 1 collected at 3 different time points and 2 cancer samples (FFPE) from Patient 2 collected at 1 time point. Exonic DNA was enriched using the TruSeq Exome Kit (Illumina) and sequenced on the Illumina NextSeq 500 as 75bp paired end reads (total read length 150bp).

  Dataset EGAD00001011149

• Cell-free DNA sequencing data of healthy control, atrophic gastritis, and gastric cancer patients’ blood

  Sample cohort (n=48) is consisted of healthy, atrophic gastritis and gastric cancer patients. Some of the gastric cancer patients samples are collected at the separate time points: -1 before the operation; -2 after the operation; -3 during the control visit. For the hybridisation capture of the genes unique 15 gastric cancer-related gene panel was developed and very deep sequencing using TruSight Oncology Unique Molecular Identifier (UMI) Reagents (Illumina) was used.

  Dataset EGAD00001011153

• RNASeq data from one small cell prostate cancer patient (4 samples from 3 time points)

  RNASeq data from one small cell prostate cancer patient - 4 cancer samples (FFPE) from Patient 1 collected at 3 different time points. mRNA was selected using the Magnetic mRNA Isolation Module (NEB) and sequenced on the Illumina NextSeq 500 as 75bp paired end reads (total read length 150bp).

  Dataset EGAD00001011154

• Colorectal cancer organoid-stroma biobank cohort

  In colorectal cancers (CRC) the tumor microenvironment plays a key role for prognosis and therapy efficacy. Patient-derived tumor organoids (PDTOs) show enormous potential for preclinical testing, however, purely epithelial cultures features including the ‘consensus molecular subtypes’ (CMS) are largely eradicated. To better reflect the cell type heterogeneity, we established the CRC organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAFs) from 30 patients. Whole exome sequencing and transcriptome analysis in various in vitro and in vivo contexts was performed to study the influence of the TME on the CRC phenotype.

  Dataset EGAD00001011173

• Intra-prostatic tumour evolution, steps in metastatic spread and histogenomic associations revealed by integration of multi-region whole genome sequencing with histopathological features

  We performed whole genome sequencing on 42 prostate cancer samples from the prostate, seminal vesicles and regional lymph nodes of five treatment-naive patients with locally advanced disease who underwent radical prostatectomy. Whole genome sequencing was performed as 150bp paired end reads on the Illumina NovaSeq 6000 platform.

  Dataset EGAD00001011174

• cfDNA methylation profiling in Metastatic Cancer and Cancer of Unknown Primary

  This study contains methyl-binding domain sequencing and shallow whole genome sequencing from circulating cell-free DNA (cfDNA) for 143 patients with metastatic cancer of known type, 41 patients with Cancer of Unknown Primary (CUP) and 27 non-cancer controls.

  Dataset EGAD00001011178

• Cancer treatment re-shapes the somatic mutational landscape of normal esophagus - wgs

  Ageing epithelial tissues, including the esophagus, are progressively colonized by somatic mutant clones, some carrying mutations linked to cancer. However, whether normal epithelial mutational landscapes that evolve over decades can be altered by short term interventions such as cancer treatment is not known. Here we sequenced normal esophageal epithelium removed from patients after 5-8 weeks of therapy for esophageal cancer. Some patients had no prior treatment (NT), while others had 8 weeks of 5 Fluorouracil (5-FU) containing chemotherapy (FLOT) or 4 weeks of chemotherapy and radiation directed at the tumor (CROSS). Despite the brief duration of therapy, we observed treatment specific differences in the selection of mutant clones. The median size of mutant TP53 and PPM1D clones in the CROSS group was double that in the other groups. Mutants of the tumor suppressor SPOP were selected in CROSS but not FLOT or NT patients. In FLOT patients we found positive selection of activating MTOR mutations, consistent with the hypothesis that these mutants confer 5-FU resistance. Sequencing densely mutated normal epithelia after cancer reveals treatment specific selection of mutations with potential therapeutic impact.

  Dataset EGAD00001011181

• Cancer treatment re-shapes the somatic mutational landscape of normal esophagus - 0.25mm punches targeted

  Ageing epithelial tissues, including the esophagus, are progressively colonized by somatic mutant clones, some carrying mutations linked to cancer. However, whether normal epithelial mutational landscapes that evolve over decades can be altered by short term interventions such as cancer treatment is not known. Here we sequenced normal esophageal epithelium removed from patients after 5-8 weeks of therapy for esophageal cancer. Some patients had no prior treatment (NT), while others had 8 weeks of 5 Fluorouracil (5-FU) containing chemotherapy (FLOT) or 4 weeks of chemotherapy and radiation directed at the tumor (CROSS). Despite the brief duration of therapy, we observed treatment specific differences in the selection of mutant clones. The median size of mutant TP53 and PPM1D clones in the CROSS group was double that in the other groups. Mutants of the tumor suppressor SPOP were selected in CROSS but not FLOT or NT patients. In FLOT patients we found positive selection of activating MTOR mutations, consistent with the hypothesis that these mutants confer 5-FU resistance. Sequencing densely mutated normal epithelia after cancer reveals treatment specific selection of mutations with potential therapeutic impact.

  Dataset EGAD00001011182

• Cancer treatment re-shapes the somatic mutational landscape of normal esophagus - nanoseq

  Ageing epithelial tissues, including the esophagus, are progressively colonized by somatic mutant clones, some carrying mutations linked to cancer. However, whether normal epithelial mutational landscapes that evolve over decades can be altered by short term interventions such as cancer treatment is not known. Here we sequenced normal esophageal epithelium removed from patients after 5-8 weeks of therapy for esophageal cancer. Some patients had no prior treatment (NT), while others had 8 weeks of 5 Fluorouracil (5-FU) containing chemotherapy (FLOT) or 4 weeks of chemotherapy and radiation directed at the tumor (CROSS). Despite the brief duration of therapy, we observed treatment specific differences in the selection of mutant clones. The median size of mutant TP53 and PPM1D clones in the CROSS group was double that in the other groups. Mutants of the tumor suppressor SPOP were selected in CROSS but not FLOT or NT patients. In FLOT patients we found positive selection of activating MTOR mutations, consistent with the hypothesis that these mutants confer 5-FU resistance. Sequencing densely mutated normal epithelia after cancer reveals treatment specific selection of mutations with potential therapeutic impact.

  Dataset EGAD00001011183

• Cancer treatment re-shapes the somatic mutational landscape of normal esophagus - 2mm targeted

  Ageing epithelial tissues, including the esophagus, are progressively colonized by somatic mutant clones, some carrying mutations linked to cancer. However, whether normal epithelial mutational landscapes that evolve over decades can be altered by short term interventions such as cancer treatment is not known. Here we sequenced normal esophageal epithelium removed from patients after 5-8 weeks of therapy for esophageal cancer. Some patients had no prior treatment (NT), while others had 8 weeks of 5 Fluorouracil (5-FU) containing chemotherapy (FLOT) or 4 weeks of chemotherapy and radiation directed at the tumor (CROSS). Despite the brief duration of therapy, we observed treatment specific differences in the selection of mutant clones. The median size of mutant TP53 and PPM1D clones in the CROSS group was double that in the other groups. Mutants of the tumor suppressor SPOP were selected in CROSS but not FLOT or NT patients. In FLOT patients we found positive selection of activating MTOR mutations, consistent with the hypothesis that these mutants confer 5-FU resistance. Sequencing densely mutated normal epithelia after cancer reveals treatment specific selection of mutations with potential therapeutic impact.

  Dataset EGAD00001011184

• HiSeq Colorectal Cancer Dataset

  Set of 19 patients afflicted with colorectal cancer with matching preoperative and postoperative blood plasma, PBMC, and tumor biopsy sequencing data. Originally referenced by Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring. Nat Med. 2020, Zviran et. al.

  Dataset EGAD00001011186

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0079_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0079_002 for Triple negative breast cancer patient-derived xenograft SA1035X6XB03211

  Dataset EGAD00001011242

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0142_004

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0142_004 for Triple negative breast cancer sample SA1035X6XB03209

  Dataset EGAD00001011243

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0145_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0145_001 for Triple negative breast cancer patient-derived xenograft SA1035X7XB03338

  Dataset EGAD00001011244

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0145_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0145_002 for Triple negative breast cancer patient-derived xenograft SA1035X7XB03340

  Dataset EGAD00001011245

• Germline genome sequencing samples from the Hereditary Cancer Syndromes (ICCon) Cancer Flagship

  A prospective study of individuals with suspicion of a hereditary cancer syndrome for whom previous clinical targeted genetic testing was either not informative or was not available. To identify pathogenic disease-causing variants explaining participant presentation, germline whole-genome sequencing and a comprehensive cancer virtual gene panel analysis were undertaken.

  Dataset EGAD00001011260

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0162_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0162_002 for Triple negative breast cancer sample SA1035X7XB03502

  Dataset EGAD00001011246

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0151_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0151_001 for Triple negative breast cancer patient-derived xenograft SA1035X8XB03425

  Dataset EGAD00001011247

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0162_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0162_001 for Triple negative breast cancer sample SA1035X8XB03420

  Dataset EGAD00001011248

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0175_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0175_002 for Triple negative breast cancer patient-derived xenograft SA1035X8XB03631

  Dataset EGAD00001011249

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0164_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0164_002 for Triple negative breast cancer sample SA530X3XB03295

  Dataset EGAD00001011250

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0014_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0014_001 for Triple negative breast cancer patient-derived xenograft SA604X6XB01979

  Dataset EGAD00001011251

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0015_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0015_001 for Triple negative breast cancer patient-derived xenograft SA604X6XB01979

  Dataset EGAD00001011252

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0019_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0019_001 for Triple negative breast cancer patient-derived xenograft SA604X7XB02089

  Dataset EGAD00001011253

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0020_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0020_002 for Triple negative breast cancer patient-derived xenograft SA604X8XB02164

  Dataset EGAD00001011254

• WGS of a Li-Fraumeni patient's HSPCs

  WGS data of clonally expanded HSPCs from a Li-Fraumeni patient at the time of second cancer (Burkitt lymphoma and <5% t-MN) after primary osteosarcoma diagnosis and a reference MSC bulk.

  Dataset EGAD00001011257

• 10x Single Cell Gene Expression Library TENX063

  10x Single Cell Gene Expression library TENX063 for Triple negative breast cancer patient-derived xenograft SA609X3XB01584

  Dataset EGAD00001011268

• Whole-exome sequencing data from head and neck cancer patients

  This dataset contains paired-end whole-exome sequencing data (2x50 bp) from the normal samples, the primary tumors and the recurrences/metastases of 8 head and neck cancer patients.

  Dataset EGAD00001011278

• RNA-seq data from the tumor samples of head and neck cancer patients

  This dataset contains paired-end RNA sequencing data (2x50 bp) from the primary tumors and the recurrences/metastases of 6 head and neck cancer patients.

  Dataset EGAD00001011279

• Clinical and genetic factors associated with tumor response to neoadjuvant (chemo)radiotherapy, survival and recurrence risk in rectal cancer

  Dataset consists of 216 samples, with each sample having a BAM, BAI and VCF file.

  Dataset EGAD00001011297

• Neoantigen Immunogenicity Landscapes and Evolution of Tumor Ecosystems During Immunotherapy with Nivolumab

  We performed Whole Exome (WXS) and RNASeq sequencing on samples obtained from the same site before and during therapy from our prospective clinical trial (CA209-153, NCT02066636) of nivolumab in advanced Non-small cell lung cancer (NSCLC) patients that progressed on chemotherapy. There are 58 pre and 42 on therapy WXS samples and 24 pre and 12 on therapy RNASeq samples. All WXS tumor samples have matching normal samples.

  Dataset EGAD00001011302

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 8a)

  Whole genome sequencing data of 26 high-grade serous carcinoma (HGSC) patients (87 samples) sequenced with MGISEQ-2000 and HiSeq X Ten.

  Dataset EGAD00001011304

• INSPIRE multi-timepoint cfMeDIP dataset

  This dataset contains raw sequencing data from multi-timepoint cell-free methylated DNA immunoprecipitation and sequencing (cfMeDIP-seq) of plasma samples from the INSPIRE study (NCT02644369). Details about the study, including inclusion/exclusion criteria and interventions are available at https://clinicaltrials.gov/study/NCT02644369. Briefly, five cohorts were included, INS-A (head & neck squamous cell carcinoma), INS-B (triple-negative breast cancer), INS-C (high-grade serous ovarian cancer), INS-D (melanoma), and INS-E (mixed solid tumors). All patients in the study were diagnosed with advanced cancer and received treatment with pembrolizumab. Plasma samples were collected at baseline and every 3 cycles until disease progression, death, loss of follow-up, or completion of the study. Plasma samples were first processed for cell-free DNA mutations and remaining samples were then processed by cfMeDIP-seq, prioritizing baseline and post-cycle 3 samples. In total, data from 204 timepoints from 87 distinct patients are deposited.

  Dataset EGAD00001011312

• Machine Learning Guided Signal Enrichment for Plasma Tumor-burden Monitoring Dataset

  Includes 4 Datasets: 1. 35 Control Plasma WGS samples sequenced on NovaSeq V1.0 Chemistry at the New York Genome Center. Denoted by CTRL-2XX naming scheme. 2. Plasma WGS from 17 patients with Small Cell Lung Cancer. Samples extracted at either Pretreatment or Postoperative at weeks 2 or 3. Denoted by SCLC-XX naming scheme. 3. Plasma WGS from a synthetic mixing study of a high-burden melanoma plasma sample with plasma bag, at estimated tumor concentrations of 10e-3, 10e-4, 10e-5, and 10e-6 for 2 replicates. Denoted by SM-repX naming scheme. 4. Assorted Plasma, Tumor, and Normal WGS from patients with NSCLC expressing high-burden for use in model training. Denoted by NSCLC-2XX naming scheme.

  Dataset EGAD00001011352

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 9 part 1)

  Whole genome sequencing data of 6 high-grade serous carcinoma (HGSC) patients (11 samples) sequenced with MGISEQ-2000

  Dataset EGAD00001011353

• 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

• Sequence data from stage I of the CCTG BR.36 ctDNA-directed, multi-center phase II study of molecular response adaptive immunotherapy in non-small cell lung cancer

  The dataset for the study "Early ctDNA molecular response captures therapeutic response in the first stage of CCTG BR.36 ctDNA-directed, multi-center phase II study of molecular response adaptive immunotherapy in non-small cell lung cancer", includes 134 bam files from hybrid capture targeted error-correction next-generation sequencing (PGDx Elio plasma resolve) from plasma cell-free DNA and matched white blood cell DNA from 35 individuals with non-small cell lung cancer on the BR.36 trial, alongside 11 bam files from targeted next generation sequencing (PGDx Elio tissue complete) of tumor DNA from 11 individuals with non-small cell lung cancer on the BR.36 trial.

  Dataset EGAD00001011359

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0150_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0150_002 for Triple negative breast cancer sample SA609X5XB03231

  Dataset EGAD00001011213

• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - RNA-Seq

  This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.

  Dataset EGAD00001011192

• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - Ribo-Seq

  This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.

  Dataset EGAD00001011193

• 10x Single Cell Gene Expression Library TENX069

  10x Single Cell Gene Expression library TENX069 for Triple negative breast cancer patient-derived xenograft SA609X4XB03083

  Dataset EGAD00001011211

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0150_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0150_001 for Triple negative breast cancer sample SA609X5XB03230

  Dataset EGAD00001011212

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0063_000

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0063_000 for Triple negative breast cancer patient-derived xenograft SA609X3XB01584

  Dataset EGAD00001011209

• 10x Single Cell Gene Expression Library TENX068

  10x Single Cell Gene Expression library TENX068 for Triple negative breast cancer patient-derived xenograft SA609X4XB03080

  Dataset EGAD00001011210

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0146_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0146_002 for Triple negative breast cancer patient-derived xenograft SA609X5XB03223

  Dataset EGAD00001011214

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0152_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0152_001 for Triple negative breast cancer patient-derived xenograft SA609X6XB03401

  Dataset EGAD00001011215

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0152_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0152_002 for Triple negative breast cancer sample SA609X6XB03404

  Dataset EGAD00001011216

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0172_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0172_001 for Triple negative breast cancer sample SA609X6XB03447

  Dataset EGAD00001011217

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0163_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0163_002 for Triple negative breast cancer sample SA609X7XB03510

  Dataset EGAD00001011218

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0163_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0163_001 for Triple negative breast cancer patient-derived xenograft SA609X7XB03505

  Dataset EGAD00001011219

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0172_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0172_002 for Triple negative breast cancer sample SA609X7XB03554

  Dataset EGAD00001011220

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0148_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0148_001 for Triple negative breast cancer patient-derived xenograft SA535X4XB02498

  Dataset EGAD00001011221

• 10x Single Cell Gene Expression Library TENX048

  10x Single Cell Gene Expression library TENX048 for Triple negative breast cancer sample SA535X5XB02895

  Dataset EGAD00001011222

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0146_006

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0146_006 for Triple negative breast cancer sample SA535X6XB03099

  Dataset EGAD00001011223

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0175_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0175_001 for Triple negative breast cancer patient-derived xenograft SA535X6XB03101

  Dataset EGAD00001011224

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0182_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0182_001 for Triple negative breast cancer patient-derived xenograft SA535X7XB03304

  Dataset EGAD00001011225

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0189_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0189_001 for Triple negative breast cancer patient-derived xenograft SA535X7XB03448

  Dataset EGAD00001011226

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0184_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0184_001 for Triple negative breast cancer sample SA535X7XB03305

  Dataset EGAD00001011227

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0146_004

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0146_004 for Triple negative breast cancer sample SA535X7XB03305

  Dataset EGAD00001011228

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0189_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0189_002 for Triple negative breast cancer patient-derived xenograft SA535X8XB03663

  Dataset EGAD00001011229

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0182_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0182_002 for Triple negative breast cancer sample SA535X8XB03431

  Dataset EGAD00001011230