8253 results for "canc*"

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• Sequencing data for the manuscript "Multi-focal sampling of de novo metastatic prostate cancer reveals complex polyclonality and enables accurate clinical genotyping"

  This submission includes targeted and whole exome paired-end fastq files.

  Dataset EGAD00001009651

• ATAC-seq of metastatic prostate tumors

  This dataset includes Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data, in FASTQ format, from 70 metastatic castration-resistant prostate cancer tumor samples from the SU2C/PCF West Coast Dream Team (WCDT) project. The sequencing data is paired-end, 150 bp sequencing data from an Illumina NovaSeq 6000 machine. ATAC-seq libraries were prepared following the protocol described in Buenrostro et al. Nature Methods. 2013 (PMID: 24097267) and Corces et al. Nature Methods. 2017 (PMID: 28846090).

  Dataset EGAD00001009654

• Nanopore low-pass WGS of human brain tumors

  Nanopore low-pass WGS of human brain tumors for evaluation of DNA methylation-based classification of cancer

  Dataset EGAD00001009663

• 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

• The University of Hong Kong Colon Cancer Ganciclovir Study WGS Data

  Human clonal intestinal organoids were treated with 1µM MMF (Roche), 20 μM GCV (Hainan Poly Pharm Co Ltd), or in combinations (1 µM MMF + 20 μM GCV or 1 µM MMF + 40 μM GCV) continuously for 4-6 weeks. DNA was extracted after drug treatment. WGS was performed with 150 bp PE sequencing at 30X using an Illumina Novaseq sequencer.

  Dataset EGAD00001009667

• Tumour sample for patient SA1058

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1058

  Dataset EGAD00001009673

• Normal sample for patient SA1058

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1058

  Dataset EGAD00001009672

• Tumour sample for patient SA998

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA998

  Dataset EGAD00001009674

• Variants from germline WES data of pediatric cancer patients

  This dataset contains germline variants (in .vcf format) from six pediatric cancer patients (sample IDs D1 - D6). WES data of the children and their parents was mapped to hg38. A consensus of four variant callers was used to obtain germline variants of the children.

  Dataset EGAD00001009678

• META-PRISM

  A pan-cancer cohort of 1031 patients resistant to systemic therapies or with no approved therapeutic options. It includes whole-exome sequencing of 571 tumor and matched-normal samples, and transcriptome sequencing of 947 tumor samples. Biopsies were taken at entry into precision medicine trials, often after diagnosed resistance. Comprehensive clinical information is available for all patients and include patient age at biospy, tumor primary site and histological subtype, biopsy site, treatments received prior to biopsy, blood assessment results at biopsy, metastatic sites at biopsy, and survival time from the biopsy date.

  Dataset EGAD00001009684

• CRUK Accelerator: Pancreatic neuroendocrine tumours (panNETs) whole exome and RNAseq raw sequencing data

  Whole exome and RNASeq raw sequencing data for an individual with multiple pancreatic neuroendocrine tumours (panNETs). Age at diagnosis was 51. Tumour tissue and PBMCs were used for sequencing. This data was generated as part of a study funded by a Cancer Research UK Centres Network Accelerator Award Grant (A21998).

  Dataset EGAD00001009685

• Cancers of Unknow Primary

  genetic data of 14 rigorously selected CUP samples

  Dataset EGAD00001009426

• Single Cell Genome Sequence for DLP+ library A110660A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA610 passage 3 on DLP+ library A110660A

  Dataset EGAD00001009430

• 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

• Single Cell Genome Sequence for DLP+ library A95670B

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 6 on DLP+ library A95670B

  Dataset EGAD00001009449

• Single Cell Genome Sequence for DLP+ library A95722A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 6 on DLP+ library A95722A

  Dataset EGAD00001009451

• Single Cell Genome Sequence for DLP+ library A96109A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 2 on DLP+ library A96109A

  Dataset EGAD00001009452

• Single Cell Genome Sequence for DLP+ library A96130A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA609 passage 8 on DLP+ library A96130A

  Dataset EGAD00001009454

• Single Cell Genome Sequence for DLP+ library A96154A

  Single Cell Genome Sequence for triple negative breast cancer patient SA1135, patient SA1162SA on DLP+ library A96154A

  Dataset EGAD00001009456

• Single Cell Genome Sequence for DLP+ library A96161A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 8 on DLP+ library A96161A

  Dataset EGAD00001009457

• Single Cell Genome Sequence for DLP+ library A96171A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 2, patient-derived xenograft SA611 passage 3 on DLP+ library A96171A

  Dataset EGAD00001009458

• Single Cell Genome Sequence for DLP+ library A96173A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 15 on DLP+ library A96173A

  Dataset EGAD00001009459

• Single Cell Genome Sequence for DLP+ library A96174A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 11 on DLP+ library A96174A

  Dataset EGAD00001009460

• Single Cell Genome Sequence for DLP+ library A96175A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 7 on DLP+ library A96175A

  Dataset EGAD00001009461

• Single Cell Genome Sequence for DLP+ library A96177C

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 6 on DLP+ library A96177C

  Dataset EGAD00001009462

• Single Cell Genome Sequence for DLP+ library A96180A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 6 on DLP+ library A96180A

  Dataset EGAD00001009463

• Single Cell Genome Sequence for DLP+ library A96187A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 11, patient-derived xenograft SA609 passage 7 on DLP+ library A96187A

  Dataset EGAD00001009464

• Single Cell Genome Sequence for DLP+ library A96212B

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 7 on DLP+ library A96212B

  Dataset EGAD00001009476

• Single Cell Genome Sequence for DLP+ library A96213A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 6, cell line SA1090 on DLP+ library A96213A

  Dataset EGAD00001009477

• Single Cell Genome Sequence for DLP+ library A98181A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA919 passage 7, patient-derived xenograft SA1050A passage 1 on DLP+ library A98181A

  Dataset EGAD00001009479

• Single Cell Genome Sequence for DLP+ library A98240A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA530 passage 3 on DLP+ library A98240A

  Dataset EGAD00001009480

• 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

• Single Cell Genome Sequence for DLP+ library A95621B

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 2 on DLP+ library A95621B

  Dataset EGAD00001009487

• KiCS cancer panel academic only data

  This data set contains KiCS cancer panel data for academic and for-profit use.

  Dataset EGAD00001009733

• TRACERx Reduced-representation bisulfite sequencing (RRBS)

  RRBS data from TRACERx non-small cell lung cancer (NSCLC) tumours and matched normal adjacent tissue. TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC).

  Dataset EGAD00001009707

• Human primary and metastatic colorectal cancer (CRC) samples

  Bank of human both primary and metastastic colorectal cancer sample RNAseq

  Dataset EGAD00001009712

• pan-cancer plasma cfRNA

  Dataset contains mRNA capture sequencing data from plasma of 266 different human donors. The first, pan-cancer, cohort covers 25 high-grade to metastatic cancer types (8 cancer patients per type) and a control group (8 healthy donors). The validation cohort comprises additional plasma samples from ovarian, prostate and uterine cancer patients (12 per type) as well as additional samples from controls (22 new and 8 repeated). Samples were sequenced on a NovaSeq 6000 and are provided in FASTQ format.

  Dataset EGAD00001009713

• 2 paired WGS samples of peritumour regions of colorectal cancer

  2 paired WGS samples of peritumour regions of colorectal cancer (2 patients). The library was prepared using the Illumina TruSeq Nano FFPE kit and the sequencing was done on NovaSeq6000.

  Dataset EGAD00001009714

• PGDx elio™ plasma resolve assay: targeted sequencing analyses of WBC DNA

  The dataset "PGDx elio™ plasma resolve assay: targeted sequencing analyses of WBC DNA" includes paired end FASTQ reads of 49 white blood cell (WBC) genomic DNA samples from metastatic colorectal cancer patients. Sequencing was performed using a panel consisting of 33 genes, covering over 237,000 bp, targeting 25,000x depth across the targeted regions.

  Dataset EGAD00001009721

• PGDx elio plasma resolve analytical validation

  This dataset consists of 39 noncancerous donor and 62 cancer patient plasma samples (including 29 patients with CRC across a total of 13 tumor types) that were analyzed with the PGDx elio plasma resolve assay. The PGDx elio plasma resolve assay is a hybrid capture approach targeting 33 genes with sequencing performed using the Illumina NextSeq with 150bp paired-end reads. The bam files provided have been adapter masked and contain duplicate reads.

  Dataset EGAD00001009718

• PGDx elio™ plasma resolve assay: targeted sequencing analyses of plasma cfDNA

  The dataset "PGDx elio™ plasma resolve assay: targeted sequencing analyses of plasma cfDNA" includes paired end FASTQ reads of 183 cfDNA samples from metastatic colorectal cancer patients. Sequencing was performed using a panel consisting of 33 genes, covering over 237,000 bp, targeting 25,000x depth across the targeted regions.

  Dataset EGAD00001009719

• PGDx elio™ tissue complete assay: targeted sequencing analyses of tissue DNA

  The dataset "PGDx elio™ tissue complete assay: targeted sequencing analyses of tissue DNA" includes paired end FASTQ reads of 28 tissue samples from metastatic colorectal cancer patients. Sequencing was performed using a panel consisting of 505 genes, targeting 2,500x depth across the targeted regions.

  Dataset EGAD00001009720

• KiCS cancer panel data for academic and for-profit use

  This data set contains KiCS cancer panel data for academic and for-profit use.

  Dataset EGAD00001009734

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 0)

  Whole genome sequencing data of 5 High-grade serous carcinoma (HGSC) patients (6 samples) sequenced with BGI.

  Dataset EGAD00001009738

• Whole genome sequencing

  Whole genome sequencing of high-grade serous ovarian cancer (HGSC) tumours and matched normals from 15 patients with homologous recombination deficiencies. The dataset includes fastq files from 56 HGSC tumours (1 primary, 1 relapse, 54 end-stage) and 15 matched normals. Sequence libraries were generated from tumour and matched normal genomic DNA using the KAPA HyperPrep PCR-free library preparation kit (Roche), or the Illumina TruSeq DNA Nano kit according to manufacturer’s instructions. Sequencing was carried out by the Kinghorn Centre for Clinical Genomics Sequencing Laboratory (Sydney, Australia) on the HiSeq X Ten System (Illumina) or by the Australian Genome Research Facility (Melbourne, Australia) on an Illumina NovaSeq to a minimum base coverage of 30-fold for normal DNA and 60-fold for tumour DNA samples.

  Dataset EGAD00001009746

• Targeted DNA sequencing

  Targeted DNA sequencing of high-grade serous ovarian cancer (HGSC) tumour and normal samples from 15 patients with homologous recombination deficiencies. The dataset includes fastq files from 243 HGSC tumours (15 primary, 3 relapse, 225 end-stage) and 15 normals from 15 HGSC patients. Following target hybrid capture of 63 genes involved in DNA repair and response to treatment with an Agilent SureSelect XT panel, sequencing libraries were generated using the SureSelect XT Low Input Target Enrichment System (Agilent) as per the manufacturer's protocol. Libraries were sequenced on an Illumina NextSeq 500 at the Peter MacCallum Cancer Centre (Melbourne, Australia).

  Dataset EGAD00001009747

• GELATO clinical trial whole exome sequencing data (metastatic lesions)

  Paired-end whole exome sequencing of 19 lobular breast cancer metastatic tumors and matched normal samples obtained from 19 unique patients from the GELATO clinical trial. The included raw sequencing data in fastq format was generated using Illumina NovaSeq 6000 from fresh frozen material.

  Dataset EGAD00001009837

• 15 Healthy controls, 25 conlonrectal cancer patients without liver metastasis and 24 conlonrectal cancer patients with liver metastasis (target capture)

  15 Healthy controls, 25 conlonrectal cancer patients without liver metastasis and 24 conlonrectal cancer patients with liver metastasis (target capture)

  Dataset EGAD00001009838

• 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