7342 results for "canc*"

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• 18 plasma samples and their paired 18 urinary cfDNA samples without cancer

  18 plasma samples and their paired 18 urinary cfDNA samples without cancer

  Dataset EGAD00001009839

• whole genome sequence of liver cancer

  There are six samples with three blood samples and three organids

  Dataset EGAD00001009841

• ChIPseq sequence of liver cancer

  There are 61 samples

  Dataset EGAD00001009842

• RNA sequencing

  RNAseq of 45 high-grade serous ovarian cancer tumour samples. Libraries were generated using the NEB Ultra II Directional RNA library Prep kit with polyA enrichment. Libraries were sequenced as paired-end 50 or 100bp on an Illumina NextSeq or NovaSeq.

  Dataset EGAD00001009844

• Sequencing of longitudinal glioma pairs

  Clonal evolution drives cancer progression and therapeutic resistance. Recent studies revealed divergent longitudinal trajectories in gliomas, but early molecular traits steering post-treatment cancer evolution remain unclear. We analyzed sequencing data of 544 initial-recurrent adult diffuse glioma pairs to identify genomic and transcriptomic early predictors of tumor evolution in each molecular subtype.

  Dataset EGAD00001009845

• WES and RNAseq of Simultaneous Bilateral Breast Cancer

  This dataset includes NGS profiling of 13 women with simultaneous bilateral breast cancer. Seven women have WES of untreated surgical resections and matched healthy tissue. The six other women have WES of healthy tissue, WES+RNAseq of pre-neoadjuvant tumor biopsies, and when residual disease was present (6 tumors in 4 patients), WES+RNAseq of residual disease from post-neoadjuvant therapy surgery. One patient from the WES+RNAseq cohort had multifocal bilateral disease at diagnosis so there are 2 pre-neoadjuvant biopsy samples from each breast.

  Dataset EGAD00001009987

• PELICAN45 RNAseq Dataset

  RNAseq in cryostat-microdissected metastatic and primary prostate cancer tissues and matched noncancerous tissues from the same study subjects.

  Dataset EGAD00001009997

• TGL49_HBC CHARM panel

  Targeted panel sequencing of hereditary cancer syndrome-associated genes (TP53, BRCA1, BRCA2, PALB2, MLH1, MSH2, MSH6, PMS2, EPCAM, and APC) in plasma and buffy coat samples from healthy control patients.

  Dataset EGAD00001010001

• TGL49 LFS CHARM panel

  Targeted panel sequencing of hereditary cancer syndrome-associated genes (TP53, BRCA1, BRCA2, PALB2, MLH1, MSH2, MSH6, PMS2, EPCAM, and APC) in plasma and buffy coat samples from patients with Li-Fraumeni syndrome.

  Dataset EGAD00001010011

• Single-cell RNA-sequencing of CD19 Chimeric Antigen Receptor (CAR) T-cells (CD19 CAR T-cells) from a Phase I clinical study in paediatric ALL: CARPALL

  Chimeric antigen receptor (CAR)-modified T-cells have become established as an effective treatment of haematological cancers. In the context of relapsed and refractory childhood pre-B cell acute lymphoblastic leukaemia (B ALL), CD19 targeting CAR T-cells often induce durable remissions. Previously, we generated a novel low-affinity CAR incorporating a CD19-specific single-chain variable fragment (scFV) called CAT, displaying a faster off-rate of interaction than the FMC63 CD19 binder used in prior clinical studies. Here, we systematically analysed CD19 CAR T-cells of ten children with relapsed or refractory B ALL enrolled in the CARPALL trial (NCT02443831). To characterize persisting CD19 CAR T-cells, we performed high throughput single-cell gene expression and T-cell receptor (TCR) sequencing of infusion products and serial blood and bone marrow samples up to five years post-infusion. We isolated CAR T-cells from peripheral blood or bone marrow by flow cytometry for CD3 and CAR expression, prior to single cell sequencing (Chromium 10X) platform.

  Dataset EGAD00001010018

• Treated and control Patient Derived Xenografts of colorectal cancer (CRC) samples

  Bank of treateed and control PDXs metastastic colorectal cancer sample RNAseq

  Dataset EGAD00001010022

• Bulk BCR NGS data from metastatic breast tumours from donors with therapy-resistant lethal metastatic breast cancer.

  Bulk B Cell Receptor high-throughput sequencing data across 27 metastatic breast tumours obtained from 8 donors with therapy-resistant lethal metastatic breast cancer at the time of a warm autopsy. The 35 samples were sequenced on an Illumina MiSeq instrument and their raw FastQ files deposited here.

  Dataset EGAD00001010023

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 5)

  Whole genome sequencing data of 19 high-grade serous carcinoma (HGSC) patients (47 samples) sequenced with HiSeq X Ten.

  Dataset EGAD00001010029

• Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA dataset

  Whole-exome sequencing of tumour regions and deep targeted sequencing of plasma samples.

  Dataset EGAD00001010031

• CCMA-RNA

  This dataset has the raw RNA sequencing data for the cancer models in CCMA.

  Dataset EGAD00001010034

• CCMA-WGSraw

  This dataset has the mapped bam files from WGS for the cancer models in CCMA.

  Dataset EGAD00001010035

• Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations WGS

  Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations WGS

  Dataset EGAD00001010042

• Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations WXS

  Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations WXS

  Dataset EGAD00001010043

• Dataset_for_linked_WES_and_WGS_data_from_EGAS00001004813 which belong also to EGAS00001005537 for germline controls of rare cancers

  WES/WGS sequencing data of 37 germline runs, which were uploaded to umbrella studies. The sequencing was always paired. The WGS sequencing was on HiSeq X Ten using the Illumina TruSeq DNA Nano Kit. The WES Sequencing was on HiSeq4000 with Agilent Sureselect V5+UTR.

  Dataset EGAD00001010046

• Germline variants in patients with rare cancers - control samples WGS and WES

  The control samples (mostly blood) of 351 samples (paired WGS and WES sequencing) are in this dataset. The WGS was in nearly all cases at an Illumina HighSeq X Ten with the Illumina TruSeq Nano DNA Kit. The WES mostly on Illumina HighSeq 4000 with the Agilent SureSelect V5 plus UTRs Kit.

  Dataset EGAD00001010047

• BCG Molecular Subtyping

  Dataset for the paper: Non-muscle Invasive Bladder Cancer Molecular Subtypes Predict Differential Response to Intravesical Bacillus Calmette-Guérin

  Dataset EGAD00001010065

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 4)

  Whole genome sequencing data of 7 high-grade serous carcinoma (HGSC) patients (32 samples) sequenced with HiSeq X Ten.

  Dataset EGAD00001010066

• Somatic L1 retrotransposition in normal colorectal epthelium

  Throughout an individual’s lifetime, genomic alterations accumulate in somatic cells. However, the mutational landscape induced by retrotransposition of long interspersed nuclear element-1 (L1), a widespread mobile element in the human genome, is poorly understood in normal cells. Here, we explored the whole-genome sequences of 406 normal colorectal clones, 12 MUTYH-associated adenomatous clones, and 19 matched colorectal cancer tissues. In addition, we analyzed promoter DNA methylation status of retrotransposition-competent L1 (in 139 clones) and read-through RNA expression profiles (in 116 clones) to investigate the epigenetic regulation of L1 activity.

  Dataset EGAD00001010183

• CRUK-ICGC Prostate DNA Methylation Sequencing Dataset (Prostatectomy Batches 1-6)

  This dataset includes Illumina EPIC Capture Sequencing Data of 376 samples from 188 men with prostate cancer. Samples were taken from primary tissue obtained at prostatectomy, with matched pathologically assessed non-cancer control material. This DNA methylation data includes donors and samples included in previously published WGS datasets (from CRUK-ICGC batches 1 to 3 [EGAD00001001116] and batches 4 to 6 [EGAD00001003225]; including the majority of donors used in Wedge et al, Nature Genetics 2018 [PMID: 29662167]). The targeted DNA methylation sequencing data in this EGA dataset were generated using the Illumina TruSeq methyl capture method (EPICseq), covering over 3.3 million CpGs in the human genome, representing a total targeted hybridisation capture panel of 107Mbp. According to the EPICseq protocol, DNA samples extracted from prostatectomy tissue samples were enriched for target regions using hybridisation capture, prior to bisulfite conversion, amplification and sequencing in pools of 12 samples (150 single end reads over two Illumina HiSeq4000 lanes). This approach generated DNA methylation profiles from prostate cancer and control samples at base-pair resolution across millions of CpGs in the human genome.

  Dataset EGAD00001010184

• RCRF release 1

  Transcriptome sequencing from the Rare Cancer Research Foundation: leiomyosarcoma, large cell neuroendocrine carcinoma, clear cell carcinoma

  Dataset EGAD00001010198

• RCRF release 1

  Rare Cancer Research Foundation: leiomyosarcoma, large cell neuroendorcrine carcinoma, clear cell carcinoma

  Dataset EGAD00001010199

• WGS of peripheral blood leukocytes from patients with Li-Fraumeni syndrome

  We performed whole genome sequencing on 84 LFS family members from 47 families: 22 with wildtype TP53 and 62 with variant TP53. The variant TP53 cohort consists of 49 individuals who developed cancer and 13 individuals who remain cancer-free; 34 were from 13 families with 2-4 individuals sequenced within a given family and the remaining 28 had no family members sequenced. The wildtype cohort consists of 14 individuals who developed cancer and 8 individuals who are cancer-free, from 6 families.

  Dataset EGAD00001010200

• RNAseq of GEPARSIXTO

  294 formalin-fixed paraffin-embedded (FFPE) tissue samples were sent to the UNC Lineberger Comprehensive Cancer Center Translational Genomics Lab (TGL) for RNA isolation using the Maxwell 16 MDx Instrument (Promega AS3000) and the Maxwell 16 LEV RNA FFPE Kit (Promega AS1260) following the manufacturer’s protocol (Promega 9FB167). 279 total RNA sequencing libraries were prepared at TGL using a Bravo Automated Liquid-Handling Platform (Agilent G5562A) and the TruSeq Stranded Total RNA Library Prep Gold Kit (Illumina 20020599) following the manufacturer’s protocol (Illumina 1000000040499). RNAseq library quality and quantity were measured using a TapeStation 4200 (Agilent G2991AA) and Qubit 3.0 fluorometer (Life Technologies Q33216), pooled at equal molar ratios, and denatured following the manufacturer’s protocol (Illumina 1000000106351). 271 total RNA sequencing libraries were sequenced at TGL on NovaSeq 6000 (Illumina 20012850) S4 flow cells (Illumina 20028313) following the manufacturer’s protocol (Illumina 1000000019358) using a 2x50 bp paired-end configuration and pool sizes of 91 libraries to target a read depth of 110 million clusters per library on average.

  Dataset EGAD00001010201

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 6)

  Whole genome sequencing data of 31 high-grade serous carcinoma (HGSC) patients (101 samples) sequenced with HiSeq X Ten and BGISEQ-500

  Dataset EGAD00001010202

• Spatial TCR sequencing in breast cancer

  Spatial characterization by TCR sequencing in tumor core and matched stroma in seven cases of triple negative breast cancer.

  Dataset EGAD00001010203

• Mutation analysis of 77 genes in cfDNA from metastatic CRC patients

  Aligned NGS data (BAM) of 77 frequently mutated genes in cancer using the AVENIO Expanded platform.

  Dataset EGAD00001010294

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (normal data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010295

• Enhanced Detection of Landmark Minimal Residual Disease in Lung Cancer using Cell-Free DNA Fragmentomics

  The circulating tumor DNA (ctDNA) mutation-based approach shows limited performance in minimal residual disease (MRD) detection, especially for landmark MRD detection at an early-stage cancer after surgery. Here, A total of 87 NSCLC patients, who received curative surgical resections (23 patients relapsed during follow-up), enrolled in this study. A total of 163 plasma samples, collected at 7 days and 6 months postsurgical, were used for high-throughput sequencing.

  Dataset EGAD00001010300

• Genome and transcriptome sequence data from a breast cancer patient

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

  Dataset EGAD00001010315

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

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

  Dataset EGAD00001010316

• Genome and transcriptome sequence data from a pancreatic ductal adenocarcinoma patient

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

  Dataset EGAD00001010317

• 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 EGAD00001010318

• Processed bam files for the whole exome sequencing of primary lung adenocarcinoma samples

  We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas and dynamics during lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

  Dataset EGAD00001010320

• IL1R1+ cancer-associated fibroblasts drive tumor development and immunosuppression in colorectal cancer

  180502: RNA-Sequencing data of cocultured matched CRC patient (P4) derived normal fibroblasts (NFs), cancer associated fibroblasts (CAFs) and tumor spheroids. 200503_coculture: RNA-Sequencing data of cocultured CRC patient derived normal fibroblasts (NFs) or cancer associated fibroblasts (CAFs) (P16, P19, P22, P32, P41, P42) and tumor spheroids (HT29). 200503_il1b: RNA-Sequencing data of IL-1β stimulated fibroblasts (NFs and CAFs) Cole: scRNA-sequencing of matched CRC tumour samples and normal tissue counterparts derived from 3 patients. 220501: RNA-Sequencing of FACS sorted IL1R1 high and IL1R1 low CT5.3 CAFs

  Dataset EGAD00001010322

• Whole exome and RNA sequencing data from urothelial bladder cancer patients treated with anti-PD-(L)1

  We have generated and analyzed genomic data from a cohort of metastatic urothelial carcinoma patients treated with ICI such as anti-PD-(L)1 monoclonal antibodies. The dataset contains whole exome sequencing data of 27 whole blood samples and 27 FFPE tumor samples. Further, it includes RNA sequencing data from 21 tumor samples. Following the RECIST criteria, 10 patients were classified as non-responders to the treatment, and 17 were responders. The dataset also contains a merged vcf file containing somatic mutations called by Strelka2 and Mutect2 following the gatk best practice pipeline.

  Dataset EGAD00001010324

• WGS short read and 10X linked read sequencing of HR Deficient breast cancers

  A set of tumor/normal paired sequencing experiments, performed in short read WGS and 10X linked read whole genomes. BAM files aligned to hg19 are provided. Sample Alias number and Subject ID reflects patient of origin. T/N distinction discriminates between tumor and normal (peripheral blood) tissue.

  Dataset EGAD00001010326

• Bulk RNAseq of Neuroblastoma patient's tumors

  This dataset contains 9 bulk RNAseq of neuroblastoma patient's tumors used to compare with derived PDXs and/or single-cell data in the Thirant C et al, Nature Communications, 2023. They were intially produced for the Berlanga P., Cancer Discovery, 2022.

  Dataset EGAD00001010287

• Genomic data used in "ACT-Discover: identifying karyotype heterogeneity in pancreatic cancer evolution using ctDNA"

  Genomic data used in "ACT-Discover: identifying karyotype heterogeneity in pancreatic cancer evolution using ctDNA"

  Dataset EGAD00001010250

• lymphoma plasma cfRNA

  Dataset contains total RNA sequencing data from plasma of 65 different human donors: 30 diffuse large B-cell lymphoma (DLBCL) and 13 primary mediastinal large B-cell lymphoma (PMBCL) patients, and 22 cancer-free controls. Samples were sequenced on a NovaSeq 6000 and are provided in FASTQ format.

  Dataset EGAD00001010259

• Evaluation of triple negative breast cancer with heterogeneous immune infiltration

  This dataset contains the raw RNA-seq data (FASTQ files) of the samples used in the study title: "Evaluation of triple negative breast cancer with heterogeneous immune infiltration". The dataset is composed of 3 patients with 6 samples per patient (3 with high TILs and 3 with low TILs).

  Dataset EGAD00001010280

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (tumour data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010274

• UCSF-CASCADE analysis of metastatic prostate cancer

  Targeted cancer therapy inevitably selects for tumor cells that harbor some form of therapy resistance. This phenomenon is a principle reason why advanced prostate cancer, which can be treated with agents targeting androgen signaling dependency and DNA repair failure, is a lethal condition. The influence of a patient's clinical history and disease evolution on how their disseminated tumors develop resistance has been difficulty to study, because few autopsy studies have been performed in heavily treated patients with DNA-repair deficient metastatic castration-resistant prostate cancer (mCRPC). Here, we assessed how resistance to targeted cancer therapies evolved in an autopsy cohort of 54 mCRPC tumors from six men. This dataset includes targeted sequencing, exome sequencing, and RNA-seq conducted on these biopsies.

  Dataset EGAD00001010275

• Epigenetic characterization of glioblastoma stem cells

  Chromatin accessibility discriminates stem from mature cell populations, enabling the identification of primitive stem-like cells in primary tumors, such as glioblastoma (GBM) where self-renewing cells driving cancer progression and recurrence are prime targets for therapeutic intervention. We show, using single-cell chromatin accessibility, that primary human GBMs harbor a heterogeneous self-renewing population whose diversity is captured in patient-derived glioblastoma stem cells (GSCs). In-depth characterization of chromatin accessibility in GSCs identifies three GSC states: Reactive, Constructive, and Invasive, each governed by uniquely essential transcription factors and present within GBMs in varying proportions. Orthotopic xenografts reveal that GSC states associate with survival, and identify an invasive GSC signature predictive of low patient survival, in line with the higher invasive properties of Invasive state GSCs compared to Reactive and Constructive GSCs as shown by in vitro and in vivo assays. Our chromatin-driven characterization of GSC states improves prognostic precision and identifies dependencies to guide combination therapies.

  Study EGAS50000001804

• POETIC clinical Trial Ki67 Bookend Breast Cancer Targeted Exome and RNAseq Project

  Using RNAseq, we compare the 15% of poorest responders (PRs, n=177) as measured by proportional Ki67 changes after 2 weeks of neoadjuvant aromatase inhibitors to good responders (GRs, n=190) selected from the top 50% responders in the POETIC trial and matched for baseline Ki67 categories. In the POETIC trial, 4,480 postmenopausal women with primary ER+ BC were randomised 2:1 to receive either treatment with a non-steroidal AI (letrozole or anastrozole) for 2 weeks before and 2 weeks after surgery or to no perisurgical treatment. Only AI-treated patients with HER2- tumors, paired baseline and surgery Ki67 available, and baseline Ki67 immunohistochemistry (IHC) >10% (to minimise imprecision in proportional Ki67 falls) were included for selection. Data is baseline RNAseq and targeted exome DNA sequencing analysis of POETIC Good/Poor Responders to aromatase inhibitors based on change in Ki67.

  Dataset EGAD00001010919

• RNA sequencing of high-risk paediatric cancers for identifying T-cell infiltration signatures

  Transcriptome profiling of 121 high-risk paediatric cancer samples for identifying T-cell infiltration signatures using poly-A capture by Truseq and sequenced on NextSeq 500

  Dataset EGAD00001010920

• RNAseq of primary mesothelioma cell lines

  Mesothelioma is an aggressive cancer associated with previous exposure to asbestos and dismal prognosis. Since a pemetrexed/cisplatin combination was introduced for treatment of mesothelioma, no new first- or second-line therapies have been discovered. Thus, to better understand what drives mesothelioma carcinogenesis and to identify potential targets for therapy, in this project we aim at performing RNAseq analysis of a panel of mesothelioma cells lines.

  Dataset EGAD00001010924

• Cancerous Adaptive Dosing Melanoma WGS Dataset

  Illumina NovaSeq 6000 30x WGS of 26 samples, each with up to 5 matched timepoints. Timepoints A,B,C,D,and E correspond to Pretreatment, Week 3, Week 6, Week 9, and Week 12 after treatment, respectively. Additional sample metadata (sample recurrence, treatment course, age, sex, comorbidities, etc.) are present in sample description.

  Dataset EGAD00001010926

• The dataset for Detecting Liver Cancer Using Cell-Free DNA Fragmentomes

  The dataset for Detecting Liver Cancer Using Cell-Free DNA Fragmentomes includes 444 BAM files from whole genome next-generation sequencing on the Illumina NovaSeq 6000. The samples analyzed include plasma samples from individuals with and without cancer.

  Dataset EGAD00001010931

• 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 EGAD00001010940

• Genome and transcriptome sequence data from a pancreatic cancer patient

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

  Dataset EGAD00001010945

• Genome and transcriptome sequence data from a myoepithelioma patient

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

  Dataset EGAD00001010938

• Genome and transcriptome sequence data from a leiomyosarcoma patient

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

  Dataset EGAD00001010939

• Genome and transcriptome sequence data from a squamous cell carcinoma patient

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

  Dataset EGAD00001010941

• Genome and transcriptome sequence data from a non-small cell lung carcinoma patient

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

  Dataset EGAD00001010942

• 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 EGAD00001010943

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

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

  Dataset EGAD00001010944

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

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

  Dataset EGAD00001010946

• Genome and transcriptome sequence data from a cervical cancer patient

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

  Dataset EGAD00001010947

• Genome and transcriptome sequence data from a pancreatic cancer patient

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

  Dataset EGAD00001010948

• Genome and transcriptome sequence data from a endometrial adenocarcinoma patient

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

  Dataset EGAD00001010949

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

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

  Dataset EGAD00001010950

• 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 EGAD00001010951

• Genome and transcriptome sequence data from a chromophobe renal cell carcinoma patient

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

  Dataset EGAD00001010952

• Genome and transcriptome sequence data from a unknown primary adenocarcinoma patient

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

  Dataset EGAD00001010953

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

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

  Dataset EGAD00001010954

• Genome and transcriptome sequence data from a merkel cell carcinoma patient

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

  Dataset EGAD00001010955

• Genome and transcriptome sequence data from a uveal melanoma patient

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

  Dataset EGAD00001010956

• Genome and transcriptome sequence data from a leiomyosarcoma patient

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

  Dataset EGAD00001010957

• 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 EGAD00001010958

• Genome and transcriptome sequence data from a metastatic cancer to the breast patient

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

  Dataset EGAD00001010959

• Genome and transcriptome sequence data from a metastatic adenocarcinoma patient

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

  Dataset EGAD00001010960

• Genome and transcriptome sequence data from a ovarian serous carcinoma patient

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

  Dataset EGAD00001010961

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

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

  Dataset EGAD00001010962

• Genome and transcriptome sequence data from a pancreas adenocarcinoma patient

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

  Dataset EGAD00001010963

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

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

  Dataset EGAD00001010964

• Genome and transcriptome sequence data from a leiomyosarcoma patient

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

  Dataset EGAD00001010965

• Genome and transcriptome sequence data from a metastatic chondrosarcoma patient

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

  Dataset EGAD00001010966

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

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

  Dataset EGAD00001010967

• 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 EGAD00001010968

• Genome and transcriptome sequence data from a metastatic pleomorphic sarcoma patient

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

  Dataset EGAD00001010969

• Ovarian cancer cfDNA dataset

  The dataset contains 23 ovarian cancer and 2 healthy control urine cfDNA samples. Shallow WGS was performed on an Illumina Novaseq S4 PE150bp. Samples are provided as raw reads without any prior processing.

  Dataset EGAD00001010848

• Sequence of breast cancer bone metastases PDX from 2 targeted panels

  Sequence of breast cancer bone metastases PDX obtained by 2 targeted panels

  Dataset EGAD00001010856

• Sequence of breast cancer bone metastases PDX from 2 targeted panels

  Sequence of breast cancer bone metastases PDX obtained by 2 targeted panels

  Dataset EGAD00001010860

• Melanoma PEACE Dataset

  Dataset for the initial melanoma PEACE paper in Cancer Discovery, March 2023.

  Dataset EGAD00001010877

• Molecular risk stratification in patients with T1 colorectal cancer_WES

  The introduction of bowel cancer screening has led to a significant increase in the proportion of patients being diagnosed with asymptomatic, early-stage colorectal cancer (CRC). Although the majority of these patients are successfully treated with surgery alone, a small proportion of patients have 'born-to-be-bad' aggressive lesions with early dissemination leading to distant metastases. Current standard of care histological assessment is unable to distinguish between these aggressive versus non-aggressive early lesions which is essential to provide appropriate clinical management decisions. This study aims to carry out molecular and histological profiling of approximately 300 T1 CRCs in order to develop a molecular stratifier based on the risk of relapse in early-invasive CRC. This novel T1 cohort will represent the world's largest molecularly characterised T1 cohort of samples, with digital pathology assessment alongside whole exome sequencing, copy number variation analysis and 3' RNA-seq. This data will be used to generate a robust panel of molecular and/or histological markers applicable to formalin-fixed paraffin embedded (FFPE) archival tissue which discriminates between T1 lesions based on risk of relapse, which will ultimately be used to inform clinical management of CRC at the earliest stages of the disease.

  Dataset EGAD00001010890

• The dataset for Single molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer

  The dataset for Single molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer includes 57 BAM files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from individuals with and without cancer.

  Dataset EGAD00001010891

• Clonal selection after gene therapy in sickle cell disease

  While gene therapy (GT) provides a potentially curative treatment option for patients with sickle cell disease (SCD), the occurrence of myeloid malignancies in clinical trials has prompted concern. To interrogate potential mechanisms underlying increased cancer risk, we used hematopoietic stem cell (HSC) clonal tracking by whole genome sequencing (WGS) to map the somatic mutation and clonal landscape of 2,592 gene modified as well as unmodified single stem and progenitor cells from six SCD patients undergoing gene therapy (7-26 years old, average 12.7× depth). Pre-GT phylogenetic trees in SCD were highly polyclonal and mutation burdens per cell were elevated in some, but not all, patients. Post-GT, no clonal expansions were identified. However, an increased frequency of driver mutations associated with myeloid neoplasms or clonal hematopoiesis (DNMT3A- and EZH2-mutated clones in particular) were seen in both genetically modified and unmodified cells suggested positive selection of mutant clones during gene therapy. This work sheds light on the mutation landscape and HSC clonal dynamics in gene therapy for SCD and highlights enhanced fitness of some HSCs harboring pre-existing driver mutations following gene therapy. Future studies should define the long-term fate of mutant clones including any contribution to expansions associated with myeloid neoplasms.

  Dataset EGAD00001010913

• Clonal selection after gene therapy in sickle cell disease

  While gene therapy (GT) provides a potentially curative treatment option for patients with sickle cell disease (SCD), the occurrence of myeloid malignancies in clinical trials has prompted concern. To interrogate potential mechanisms underlying increased cancer risk, we used hematopoietic stem cell (HSC) clonal tracking by whole genome sequencing (WGS) to map the somatic mutation and clonal landscape of 2,592 gene modified as well as unmodified single stem and progenitor cells from six SCD patients undergoing gene therapy (7-26 years old, average 12.7× depth). Pre-GT phylogenetic trees in SCD were highly polyclonal and mutation burdens per cell were elevated in some, but not all, patients. Post-GT, no clonal expansions were identified. However, an increased frequency of driver mutations associated with myeloid neoplasms or clonal hematopoiesis (DNMT3A- and EZH2-mutated clones in particular) were seen in both genetically modified and unmodified cells suggested positive selection of mutant clones during gene therapy. This work sheds light on the mutation landscape and HSC clonal dynamics in gene therapy for SCD and highlights enhanced fitness of some HSCs harboring pre-existing driver mutations following gene therapy. Future studies should define the long-term fate of mutant clones including any contribution to expansions associated with myeloid neoplasms.

  Dataset EGAD00001010914

• Whole genome sequencing of breast cancer and related clones

  Paired WGA (whole-genome amplificated) samples from 65 single cell-derived organoids and six fresh single cell-derived organoid samples both of which were established from normal mammary epithelial cells, 84 FFPE LCM (laser-capture microdissection) samples of breast cancer and related clones, 79 fresh-frozen LCM samples of non-cancer lobules of breast cancer patients, and 36 matched germline controls were subjected to whole genome sequencing using NovaSeq 6000 system (Illumina) or DNBSEQ-G400RS (MGI Tech).

  Dataset EGAD00001010833

• RNAseq

  RNAseq of pancreatic cancer organoids.

  Dataset EGAD00001010834

• WGS

  Whole-genome sequencing of pancreatic cancer organoids and matched germline controls.

  Dataset EGAD00001010835

• pilot

  Pilot study for genome-wide sequencing of cell-free DNA from nipple aspirate fluid and plasma of breast cancer patient

  Dataset EGAD00001010836

• Transcriptomic analyses of a large cohort of adult B cell acute lyphoblastic leukemia

  Total mononuclear cells (MNC) were isolated from peripheral blood (PB) or bone marrow (BM) samples of 105 Ph-/-/- (B-cell acute lymphoblastic leukemia [B-ALL] triple negative) and 31 Ph+ B-ALL adult patients using Lymphosep (Biowest, Nuaillé, France). A total of 15 samples from healthy subjects were processed including hematopoietic stem-progenitor cells (CD34+) from bone marrow specimens (n = 3), and bone marrow mononuclear cell samples (n = 3) from STEMCELL Technologies (Vancouver, Canada). PB MNC samples (n=5) and cord blood samples (n = 4). CD34+ cells were enriched from cord blood samples by immunomagnetic separation (CD34 MicroBead Kit, Miltenyi Biotec, Bergisch Gladbach, Germany).Libraries were prepared using the TruSight RNA Pan-Cancer Panel Kit (Illumina, San Diego, California, USA), following the manufacturer’s protocol. Sequencing was performed using the Illumina MiSeq instrument.

  Dataset EGAD00001010837

• Digital tEchnology For Lung Cancer Treatment

  DEFLeCT metadata: 1) A table containing the mutational profile for all human genes across the cohort of the 81 PROMOLE lung cancer samples. 2) A table containing the expression levels for all human genes across the cohort of the 81 PROMOLE lung cancer samples. 3) A table containing the clinical, histology data and follow-ups of the cohort of 81 PROMOLE lung cancer patients.

  Dataset EGAD00001010838

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 7a)

  Whole genome sequencing data of 36 high-grade serous carcinoma (HGSC) patients (89 samples) sequenced with HiSeq X Ten.

  Dataset EGAD00001010845