7073 results for "canc*"

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• Cancer Alliance RNA-Seq PolyA

  PolyA selection transcriptome profiling by high-throughput for individualized cancer interpretation

  Dataset EGAD00001006234

• RNAseq analysis on primary sites Colorectal Cancer xenografts (PRX) samples

  Bank of primary sites (PRs) colorectal cancer of Patient Derived Xenografts (PDXs)

  Dataset EGAD00001010101

• Tracking the evolution of esophageal squamous cell carcinoma under dynamic immune selection by multi-omics sequencing

  Intratumoral heterogeneity (ITH) has been linked to decreased efficacy of clinical treatments. However, although genomic ITH has been characterized in genetic, transcriptomic and epigenetic alterations are hallmarks of esophageal squamous cell carcinoma (ESCC), the extent to which these are heterogeneous in ESCC has not been explored in a unified framework. Further, the extent to which tumor-infiltrated T lymphocytes (TILs) are directed against cancer cells, but how the immune infiltration acts as a selective force to shape the clonal evolution of ESCC is unclear. In this study, we perform multi-omic sequencing on 186 samples from 36 primary ESCC patients. Through multi-omics analyses, it is discovered that genomic, epigenomic, and transcriptomic ITH are underpinned by ongoing chromosomal instability. Based on the RNA-seq data, we observe diverse levels of immune infiltrate across different tumor sites from the same tumor. We reveal genetic mechanisms of neoantigen evasion under distinct selection pressure from the diverse immune microenvironment. Overall, our work offers an avenue of dissecting the complex contribution of the multi-omics level to the ITH in ESCC and thereby enhances the development of clinical therapy.

  Dataset EGAD00001009482

• The polarity and specificity of antiviral T lymphocyte responses determine susceptibility to SARS-CoV-2 infection in cancer patients and healthy individuals

  We monitored patient's anti SARS-CoV-2 immune responses using an in vitro cross presentation assay. The goal of this study was to identify immune correlates of clinical protection against SARS-CoV-2 infection. Briefly, peripheral blood mononuclear cells of patient were divided into a monocyte and lymphocyte. Monocyte were differentiated into monocyte derived dendritic (mo-DC)cells using GM-CSF and Interferon alpha. Mo-DC were then loaded with SARS-CoV-2 culture lysates , or VeroE86 lysates. SARS-CoV-2 loaded mo-DC were then used to stimulates their autologous lymphocytes and T cell cytokine secretion was monitored in the supernatant. We discriminated patients producing IL-2 and patients producing IL-5. RNA sequencing was performed for 18 patients, to identify gene profile associated with IL-2 or IL-5 production.

  Dataset EGAD00001008538

• Somatic mutations in facial skin from countries of contrasting skin cancer risk

  The incidence of non-melanoma skin cancer is 17-fold lower in Singapore compared to the UK1, despite Singapore receiving 2-3 times more year-round ultraviolet radiation (UV)2,3. The ageing epidermis of the skin comprises competing somatic mutant clones4,5, from which such cancers develop. We question if differences in keratinocyte skin cancer incidence are reflected in the mutational landscape by comparing ageing facial epidermis from donors of Singapore and the UK. We find UK skin to be a highly competitive, densely mutated landscape with 4-fold greater mutation burden compared to Singaporean skin and differences in clonal selection by country. We disproportionately observe multiple features common to keratinocyte skin cancers6,7,8 in UK skin, such as UV mutagenesis, copy number aberration and hotspot mutations (in particular TP53 R248W). We conclude that keratinocyte skin cancer incidence is reflected in the somatic clones of non-cancerous epidermis. Finally, we re-analyse squamous cell carcinoma exomes from Korea9 to show, even in low incidence populations, carcinogenesis is driven by UV damage.

  Dataset EGAD00001009666

• Spatial transcriptome sequence data from cross section of cancer containing prostates

  Spatial transcriptome sequence data from two tumour containing prostates. Entire cross section of organ divided into cubes to fit spatial transcriptomics arrays. The dataset contains paired-end sequences from 21 sections of 1k array sections and 9 sections of 10x Visium sections for patient 1 as well as 28 sections of 10x Visium sections for patient 2.

  Dataset EGAD00001008644

• Fastq and reference alignment of 19 samples for defining structural variation associated with breast cancer susceptibility by long-read genome sequencing

  Long-read genome sequencing performed on the Oxford Nanopore Technologies' PromethION to resolve variants underlying breast cancer susceptibility in sixteen individuals with pathogenic germline SVs in BRCA1, BRCA2, CHEK2 or PALB2.

  Dataset EGAD00001008690

• Clonal somatic copy number altered driver events inform drug sensitivity in high-grade serous ovarian cancer.

  This dataset consists of shallow whole genome sequencing data and amplicon sequencing data for 26 ovarian cancer patients (21 high-grade serous ovarian cancer, 4 low-grade serous ovarian cancer and 1 clear cell ovarian cancer). The data are provided as single end FASTQ files for the shallow whole genome sequencing data (31 libraries) and paired end FASTQ files for the amplicon sequencing data (98 libraries).

  Dataset EGAD00001008716

• 133 CRC RNA-seq fastq

  This dataset contain 133 pairs of colorectal tumor and adjacent normal tissue. For each sample paired RNA-seq fastq were generated using an Illuma Myseq-2000. Those colorectal cancer comprise 101 MSI and 32 MSS tumors.

  Dataset EGAD00001006667

• RNA-seq derived from metastatic Castration-Resistant Prostate Cancer

  Patients with progressive, metastatic castration-resistant prostate cancer (mCRPC) underwent metastatic tumor biopsy. 118 total samples including 14 paired samples (baseline and later progression). Various organ sites including soft tissue & bone were present. Published in DOI: 10.1200/JCO.2017.77.6880 Journal of Clinical Oncology 36, no. 24 (August 20, 2018) 2492-2503.

  Dataset EGAD00001008991

• Normal sample for patient SA225

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA225

  Dataset EGAD00001009549

• Plasma whole genome sequencing from patients with stage IV colorectal cancer and microsatellite instability

  This dataset contains plasma WGS data from patients with stage IV colorectal cancer (CRC, n = 16) and healthy individuals (n = 21) used in the Pointy manuscript. Patients with CRC provided written consent and samples were collected as performed as described previously (Clinical-Trials.gov number NCT01876511; Georgiadis et al., 2019, Le et al., 2017). Plasma samples from 21 healthy control individuals were procured through BioIVT. Cell-free DNA (cfDNA) was extracted from plasma using the QIAamp Circulating Nucleic Acid Kit. Libraries were prepared with 5 to 250 ng of cfDNA using the NEBNext DNA Library Prep Kit. Libraries were sequenced on HiSeq2000/2500.

  Dataset EGAD00001008999

• Differential methylation positions

  This dataset includes an analyzed DMP file that provide the information about differential methylation positions based on Illumina Infinium MethylationEPIC BeadChip. All samples (5 lung cancer cases vs. 5 benign lung disease controls) were obtained from bronchial washings at the site of the lesion under bronchoscopy manipulation. Of the five lung cancer cases, 3 are adenocarcinoma and 2 are squamous carcinoma.

  Dataset EGAD00001010147

• Normal sample for patient SA1026

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1026

  Dataset EGAD00001009587

• Detection of cancer cell transcriptomes

  Single cell transcriptomes, generated using chromium 10X 3' sequencing, for two tumour types (AT/RT, and Ewing's sarcoma). For each individual, tumour and normal whole genome sequencing was also obtained using Illumina short read sequencing to an average depth of 30X. These data were used to validate the accuracy of a method for identifying cancer cell transcriptomes based on the allelic shift produced by copy number changes.

  Dataset EGAD00001009005

• RNA and whole-exome sequencing of 22 patients with non-small cell lung cancer

  Whole exome sequencing from pre-treatment samples and matched blood normals from 22 patients. Of these individuals, on-treatment samples are available for a subset of 18 patients. RNA sequencing from pre-treatment samples from 21 patients. Of these individuals, on-treatment samples are available for a subset of 15 patients.

  Dataset EGAD00001008733

• Tumour sample for patient SA1028

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1028

  Dataset EGAD00001009614

• Tumour sample for patient SA600

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA600

  Dataset EGAD00001009204

• Tumour sample for patient SA592

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA592

  Dataset EGAD00001009198

• Single Cell Genome Sequence for DLP+ library A95670A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 5 on DLP+ library A95670A

  Dataset EGAD00001009448

• WGS of high grade serous ovarian tumours and matched blood normals

  FASTQ reads for 81 matched tumour-normal WGS pairs for high grade serous ovarian cancer patients. Scottish HGSOC samples were collected via local Bioresource facilities at Edinburgh, Glasgow, Dundee and Aberdeen and stored in liquid Nitrogen until required. HGSOC patients were determined from pathology records and were included in the study where there was matched tumour and whole blood samples. Tumour samples were divided into two for DNA and RNA extraction and slivers of tissue were taken, fixed in formalin and embedded in paraffin wax (FFPE). Samples were only included if they were confirmed as HGSOC and there was greater than 40% tumour cellularity throughout the tumour, determined using H&E staining of the FFPE sections and pathology review. Somatic DNA was extracted from the tumour and germline DNA was extracted from whole blood. Somatic DNA was extracted using the Qiagen DNeasy Blood and tissue kit (cat no 69504). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including RNase digestion step). Germline DNA was extracted from 1-3ml whole blood using the Qiagen FlexiGene kit (cat no 51206) following the manufacturers recommended protocol. The resulting DNA underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as surrogate measures of DNA purity. A260/280 had to be 1.8 or greater and A260/230 had to be 2.0 or greater. Then, DNA was quantified using LifeTechnologies Qubit dsDNA BR kit (cat no Q32850) and we required a minimum of 50ul at 25ng/ul for WGS. Thirdly, DNA was diluted to 25ng/ul and a representative sample was loaded onto a 0.8% TAE gel, ran at 100v for 60mins and then imaged using a BioRad ChemiDoc imaging system to visualise the DNA quality.

  Dataset EGAD00001009049

• Targeted amplicon sequencing on 218 samples from Stage 1 epithelial ovarian cancer biopises

  BAM files (aligned against the hg38 genome) from a targeted amplicon sequencing (139 genes) experiment (median depth 1000X) on 218 samples from Stage 1 epithelial ovarian cancer biopises. Samples labeled "bis" or "tris" with the same ID are relapses; "left" or "right" samples indicate, in the case of bilateral tumor, from which ovary the sample was taken.

  Dataset EGAD00001006873

• PAMELA - 142 patients with HER2+ breast cancer

  RNA sequencing data of 141 samples from 141 patients with HER2+ breast cancer treated withletrozole or tamoxifen (SOLTI-1114 PAMELA trial)

  Dataset EGAD00001009054

• Garvan/St Vincent’s Prostate Cancer Tissue and Data

  The cohort (n=53) consists of prostate cancer patients from Australia. For each patient, a pair of blood and tumour samples were collected. The sequencing data was mapped to hg38 reference. Blood BAMs are named with “-B” as suffix and tumour BAMs are named with “-T” as suffix.

  Dataset EGAD00001009066

• Whole genome sequencing of retinoblastoma reveals the diversity of rearrangements disrupting RB1 and uncovers a treatment related mutational signature

  Background: The development of retinoblastoma is thought to require pathological genetic changes in both alleles of the RB1 gene. However, cases exist where RB1 mutations are undetectable suggesting alternative pathways to malignancy. Methods: We applied comprehensive whole genome sequencing (WGS) and transcriptomics to sporadic retinoblastomas derived from twenty patients attending our clinic, contrasting these results to that obtained through customary clinical testing. We sought RB1 and other driver mutations, investigated mutation burden, mutational signatures and phylogenetic relatedness in one case of bilateral retinoblastoma. Results: At least one RB1 mutation was identified in all retinoblastomas. We confirmed RB1 mutations previously identified by clinical screening, identified three new RB1 mutations and provided clarity to the mechanism behind a further six mutations. Eight tumours carried structural rearrangements involving RB1 ranging from relatively simple to extremely complex rearrangement patterns, including a chromothripsis-like pattern in one tumour. Potential driver mutations included mutations in BCOR (5/20) and amplification of MYCN (2/20) and MDM4 (1/20). We show that RB1 mutations are not mutually exclusive of MYCN amplifications, and further reveal that all tumours demonstrate increased MYCN expression suggesting a universal role in retinoblastoma tumorigenesis.  Bilateral tumours obtained from one patient harboured conserved germline but divergent somatic RB1 mutations, indicating independent evolution. In-keeping with previous WGS of paediatric cancers, the mutation burden in retinoblastomas was extremely low. Mutational signature analysis showed a predominance of signatures associated with cell division and an absence of ultraviolet-related DNA damage. In a tumour exposed to chemotherapy prior to enucleation, a profound platinum-related mutational signature was observed. Conclusions: WGS provides a complete picture of the genomic landscape of retinoblastomas, allowing the discovery of mutations otherwise undetected by conventional clinical screening approaches. The presence of at least one RB1 mutation in all retinoblastomas and the relative paucity of driver mutations in other genes suggests mutations beyond RB1, MYCN and BCOR are rare. Whilst most RB1 mutations are identifiable by clinical screening, the increased resolution and ability to detect otherwise elusive rearrangements of RB1 by WGS, confirming whether they are somatic or germline, has important repercussions on clinical management and advice on recurrence risks.

  Dataset EGAD00001006431

• RNAseq of breast cancer bone metastases PDX resistant of responder to IACS-010759 treatment

  Fastq files from RNAseq of breast cancer bone metastases PDX after treatment with IACS-010759. Five PDX are resistants to treatment and 6 are responders.

  Dataset EGAD00001009072

• Genome and transcriptome sequence data from an adnexal tumor probable of Wolffian origin patient

  Genome and transcriptome sequence data from an adnexal tumor probable of Wolffian origin patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002600

• Transcriptome sequencing of replication repair deficient brain cancers

  Hypermutant tumors which harbor many somatic mutations may obscure the interpretation of targetable genomic events. This dataset contains transcriptome sequencing from 21 replication repair deficient brain tumor samples as well as healthy controls.

  Dataset EGAD00001006921

• Sequence of breast cancer bone metastases PDX before and after palbociclib treatment resistance

  RNAseq sequencing of 10 breast cancer bone metastasis PDX. Samples were obtained from 5 PDX that acquired palbociclib resistance (palboR) and 5 from the parentale PDX (palboS).

  Dataset EGAD00001009068

• Tumour sample for patient SA1017

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1017

  Dataset EGAD00001009609

• Normal sample for patient SA239

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA239

  Dataset EGAD00001009364

• Normal sample for patient SA674

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA674

  Dataset EGAD00001009374

• Enhancer profiling to identify identifies epigenetic markers of endocrine resistance in metastatic castration resistant prostate cancer patients

  ChIP-seq and matched input data of AR, FOXA1 and H3K27ac for mCRPC patient samples taken prior to and after treatment with AR targeted therapy

  Dataset EGAD00001008688

• cfMeDIP data for 72 VPC samples for validation

  We analyzed the cell free DNA methylomes using 72 plasma samples from patients with mCRPC prostate cancer in the VPC project for validation. Methylation was profiled using the methylated DNA immunoprecipitation coupled to next generation sequencing (MeDIP) technology. Files from multiple lanes exists per sample.

  Dataset EGAD00001008737

• 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

• Whole-exome sequencing data from a head and neck cancer patient

  This dataset contains paired-end whole-exome sequencing data (2x50 bp) from the normal sample, three synchronous primary tumors and the recurrence of a head and neck cancer patient.

  Dataset EGAD00001006653

• 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

• WGS files for Zhang GenomePaint paper

  WGS files for GenomePaint paper titled "Exploration of coding and non-coding variants in cancer using GenomePaint."

  Dataset EGAD00001006679

• 10x Genomics Single Cell Gene Expression for SA535X6XB03099

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 6

  Dataset EGAD00001009116

• 10x Genomics Single Cell Gene Expression for SA535X4XB05462

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 4

  Dataset EGAD00001009115

• 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 EGAD00001002555

• Cholangiocarcinoma

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting two datasets that contain NGS files from gastrointestinal rare cancers (n=119): - Dataset 2 (87 patients): Intra-hepatic cholangiocarcinoma (n=47), Extra-hepatic, cholangiocarcinoma (n=16), Not specified Cholangiocarcinoma (n=9), Small bowel adenocarcinoma (n=6) and other rare GI cancer (n=9)

  Dataset EGAD00001008968

• Genome and transcriptome sequence data from a lung cancer patient

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

  Dataset EGAD00001002548

• Genome and transcriptome sequence data from an ovarian cancer patient

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

  Dataset EGAD00001002556

• NECC WXS

  Whole exome sequencing of neuroendocrine cervical cancer

  Dataset EGAD00001006391

• 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 EGAD00001002557

• 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 EGAD00001002558

• Exome Sequencing of Gastric Cancer Samples

  We perform whole exome sequencing on 50 pairs of gastric cancer and matched normal samples.

  Dataset EGAD00001006957

• 10x Genomics Single Cell Gene Expression for SA604X8XB02164

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 8

  Dataset EGAD00001009118

• 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 EGAD00001002570

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

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

  Dataset EGAD00001002571

• 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 EGAD00001002578

• Genome and transcriptome sequence data from a carcinoma of left lower outer quadrant patient

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

  Dataset EGAD00001002579

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

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

  Dataset EGAD00001002582

• 10x Genomics Single Cell Gene Expression for SA604X7XB02089

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 7

  Dataset EGAD00001009119

• 10x Genomics Single Cell Gene Expression for SA609X6XB01899

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA609 passage 6

  Dataset EGAD00001009120

• 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 EGAD00001002585

• 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 EGAD00001002603

• RBtargetedSeq

  Retinoblastoma is a rare childhood cancer of the retina. We studied retinoblastoma by Targeted Sequencing.

  Dataset EGAD00001008004

• Genetic vulnerability of knockout cancer lines (2019-04-01)

  Genome-wide CRISPR/Cas9 library screen was performed in isogenic cell lines. Three biological replicates were used. Cells were harvested at initiation of screen and at specific time points following cell culture. Using this approach we aim to identify genes specifically important in cell survival in engineered cell lines. Please perform 72, instead of 36, PCR reactions as the screen performed at 200x coverage. . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004881

• Unraveling the transcriptomic profile of utero-tubal lavage fluid of ovarian cancer patients

  mRNA capture seq of uterotubal lavage samples

  Dataset EGAD00001007933

• Genome and transcriptome sequence data from an adenocarcinoma of unknown primary cancer patient

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

  Dataset EGAD00001002611

• Genome and transcriptome sequence data from an esophageal adenocarcinoma patient

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

  Dataset EGAD00001002612

• 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 EGAD00001005823

• 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 EGAD00001005832

• 10x Genomics Single Cell Gene Expression for SA605X3XB01966

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA605 passage 3

  Dataset EGAD00001009142

• 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 EGAD00001005833

• 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 EGAD00001005834

• Dataset for Ewing_sarcoma_PNET-RNA

  Rare cancer sequencing data of 28 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008845

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

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

  Dataset EGAD00001005840

• 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 EGAD00001005842

• Genome and transcriptome sequence data from a metastatic gastrointestinal stromal tumor patient

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

  Dataset EGAD00001005843

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

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

  Dataset EGAD00001005844

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

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

  Dataset EGAD00001005845

• 10x Genomics Single Cell Gene Expression for SA1035X8XB03425

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 8

  Dataset EGAD00001009148

• 10x Genomics Single Cell Gene Expression for SA535X6XB03101

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 6

  Dataset EGAD00001009149

• 10x Genomics Single Cell Gene Expression for SA1035X6XB03211

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 6

  Dataset EGAD00001009150

• 10x Genomics Single Cell Gene Expression for SA1035X7XB03502

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 7

  Dataset EGAD00001009151

• 10x Genomics Single Cell Gene Expression for SA535X4XB02498

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 4

  Dataset EGAD00001009152

• 10x Genomics Single Cell Gene Expression for SA1035X6XB03216

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 6

  Dataset EGAD00001009154

• Tumour sample for patient SA276

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA276

  Dataset EGAD00001009182

• 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 EGAD00001005854

• 10x Genomics Single Cell Gene Expression for SA535X5XB02891

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 5

  Dataset EGAD00001009155

• 10x Genomics Single Cell Gene Expression for SA535X5XB02895

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 5

  Dataset EGAD00001009156

• Genome and transcriptome sequence data from a cervical adenocarcinoma patient

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

  Dataset EGAD00001005856

• 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 EGAD00001005860

• Normal sample for patient SA530

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA530

  Dataset EGAD00001009234

• 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 EGAD00001005861

• 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 EGAD00001005875

• Tumour sample for patient SA1073

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1073

  Dataset EGAD00001009611

• 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 EGAD00001005876

• Genome and transcriptome sequence data from a malignant choroid melanoma patient

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

  Dataset EGAD00001005883

• 10x Genomics Single Cell Gene Expression for SA604X9XB02425

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 9

  Dataset EGAD00001009159

• 10x Genomics Single Cell Gene Expression for SA610X3XB03802

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA610 passage 3

  Dataset EGAD00001009160

• MESA colorectal cancer cfDNA EM-seq dataset

  This dataset contains the methylation sequencing data of 60 nonCancer and 70 colorectal cancer cfDNA samples. The methylation library is constructed by using NEBNext Enzymatic-seq Kit.

  Dataset EGAD00001009165

• scRNA-seq using 10X Genomics platform

  Matrices of counts from single-cell RNA-seq data for 15 samples from patients with ovarian cancer, 5 samples for each of the 3 tumor immune phenotypes (Infiltrated, Excluded and Desert). Dissociated cells from each tumor sample have been sorted to isolate live cells from the 3 compartments: tumor, immune and stromal. Each of the compartments has been analyzed separately by scRNAseq, excluding some desert tumors for which cells from the stromal and immune compartments have been pooled. Sequencing was performed using 10X Genomics Chromium Single Cell platform (v2 Chemistry).

  Dataset EGAD00001006974

• 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 EGAD00001005886

• 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 EGAD00001005890

• Breast Cancer TNBC Single-Cell RNA-Seq Dataset

  Single-cell RNA-Sequencing of five TNBC primary breast cancers from Wu et al. (2020) EMBO J study. Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq 500 platform.

  Dataset EGAD00001006981

• Genome and transcriptome sequence data from a thyroid hurthle cell carcinoma patient

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

  Dataset EGAD00001005891