8213 results for "canc*"

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• RPPA analysis + clinical data

  RPPA analysis from FAIRLANE Trial of Neoadjuvant Ipatasertib Plus Paclitaxel for Triple-Negative Breast Cancer.

  Dataset EGAD00001008507

• Targeted Myeloid DNA-Panelsequencing, MLL

  Sequencing data from a targeted myeloid DNA-Panelsequnencing at the MLL Dx, Munich lab. Targeted sequencing was performed using the Nextera DNA Flex library preparation kit, starting with 100ng of genomic DNA (Illumina, San Diego, CA, USA). The target regions were enriched by a custom xGen Lockdown panel using a hybridization capture workflow (IDT Integrated DNA Technologies, Coralville, IA, USA). All libraries were sequenced with 100bp paired-end reads on a NovaSeq6000 (Illumina) with a mean coverage of 3206x. Somatic variant calling was performed with Pisces and a sensitivity cut off of 2%. Large deletions and medium-sized insertions, as they are for example found in CALR and FLT3, were called with Pindel. Variant annotation considered the publicly available data bases Cosmic (v91), ClinVar (2020-03), gnomAd (non-cancer, v2.1.1), dbNSFP (v3.5) and UMD TP53 (2017_R2). Variants that are described as somatic, protein truncating or affecting splice sites were considered as mutations while variants with no or discrepant data base information were considered as variant of uncertain significance.

  Dataset EGAD00001008485

• RNA-seq data from 224 advanced prostate tumors generated by the West Coast Dream Team

  224 pairs of FASTQ files from metastatic Castration-Resistant Prostate Cancer (mCRPC) sequenced on HiSeq 4000 instruments. Patients were enrolled in the West Coast Dream Team study. Biopsies include various tissue sites including bone, soft tissue, and lymph node.

  Dataset EGAD00001008487

• CRUK Accelerator: oesophageal adenocarcinoma whole exome and RNA-seq raw sequencing data

  Whole exome and RNASeq raw sequencing data for a cohort of 7 male patients with oesophageal adenocarcinoma. Median age at diagnosis was 68. Tumour tissue and PBMCs were used for whole exome sequencing and RNA sequencing. This data was generated as part of a study funded by a Cancer Research UK Centres Network Accelerator Award Grant (A21998).

  Dataset EGAD00001008489

• Bulk RNA sequencing of Singapore colorectal cancer patients (SG-BULK)

  RNA-seq libraries were prepared using the KAPA Stranded RNA-Seq Kit with RiboErase (Kapa Biosystems, Wilmington, MA) and sequenced to a target depth of 200-M reads on the Illumina HiSeq platform (Illumina, San Diego, CA).

  Dataset EGAD00001008512

• Target pilot trial

  In vitro and in vivo drug screens of tumor cells identify novel therapies for high-risk child cancer

  Dataset EGAD00001008358

• Mutation analysis of core biopsies from localized breast cancer patients

  Targeted next-generation sequencing (NGS) of 93 frequently mutated genes in breast cancer using the QIAseq Human Breast Cancer Targeted Panel (QIAGEN), which uses digital sequencing by incorporating unique molecular barcodes (UMI).

  Dataset EGAD00001008396

• sWGS of core biopsies from localized breast cancer patients

  Paired end shallow whole genome sequencing (sWGS) data for the identification of genomewide somatic copy number alterations (SCNA) and the estimation of tumor fractions.

  Dataset EGAD00001008397

• small RNA next generation sequencing in head and neck cancer

  small RNA next generation sequencing in head and neck cancer

  Dataset EGAD00001008402

• The genomic VCF data of the Integrative proteogenomic characterization of early esophageal cancer project

  The genomic VCF data of the Integrative proteogenomic characterization of early esophageal cancer project ,this dataset contains 90 VCF files.

  Dataset EGAD00001008672

• Integrated single-cell profiling dissects cell-state-specific enhancer landscapes of human tumor infiltrating T cells.

  Despite extensive studies on the chromatin landscape of exhausted T cells, the transcriptional wiring underlying functional and dysfunctional states of human tumor infiltrating lymphocytes (TILs) is incompletely understood. Here, we identify tissue-specific and general gene-regulatory landscapes in the wide breadth of CD8+ TIL functional states covering four cancer entities using single-cell chromatin profiling. We map enhancer-promoter interactions in human TILs by integrating single-cell chromatin accessibility with single-cell RNA-seq data from tumor entity-matching samples and prioritize key elements by super enhancer analysis. Our analysis reveals a human core chromatin trajectory to TIL dysfunction and identifies key enhancers, transcriptional regulators, and deregulated target genes involved in this process. Finally, we validate enhancer regulation at loci encoding PD1, TCF1, and TIM3 by targeting non-coding regulatory elements with potent CRISPR activators and repressors. In summary, our study advances the understanding of molecular regulation of TIL (dys-)function and provides a framework for modulating immunotherapeutic relevant TIL genes via their enhancers.

  Dataset EGAD00001008662

• cfDNA and CDX/PDX methylation profiling in Small Cell Lung Cancer

  This study contains methyl-binding domain sequencing and shallow whole genome sequencing from circulating free DNA (cfDNA) for 79 patients with small cell lung cancer (SCLC) and 78 non-cancer controls. We also sequence genomic DNA (both methyl-binding domain sequencing and shallow whole genome sequencing) from 30 circulating-tumour-cell derived explant models (CDXs, from 23 unique patients with SCLC), 20 patient derived explant models (PDXs, from 10 unique patients with SCLC) and 13 lung tissue samples.

  Dataset EGAD00001008673

• Lung cancer and non-cancerous plasma cfDNA samples

  The dataset contains 90 lung cancer and 5 non-cancerous lung lesion plasma cfDNA samples collected in EDTA blood collection tubes. Shallow WGS was performed on an Illumina Novaseq S4 PE150bp. Samples are provided as raw reads without any prior processing.

  Dataset EGAD00001008666

• 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

• Myeloma Genome Project Targeted Panel Validation dataset

  372 samples consisting of 185 patient paired CD138+ tumor and non-involved DNA pairs, plus 5 Horizon Diagnostic known mutation standards (HD). Samples were processed using the KAPA HyperCap protocol and hybridized onto a targeted panel for multiple myeloma and associated diseases. Reference Sudha et al Clinical Cancer Research, 2022.

  Dataset EGAD00001008689

• 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

• Characterization of Cell Free Plasma Methyl-DNA From Xenografted Tumors to Guide the Selection of Diagnostic Markers for Early-Stage Cancers

  Circulating cell-free methyl-DNA (mcfDNA) contains promising cancer markers but its low abundance and possibly diverse origin pose challenges toward the accurate diagnosis of early stage cancers. By whole-genome bisulfite sequencing (WGBS) of cell-free DNA (cfDNA) from about 0.5 mL plasma of mice xenografted with human tumors, we obtained and aligned the reads to the human genome, filtered out the mouse and carrier bacterial sequences, and confirmed the tumor origin of methyl-cfDNA (mctDNA) by methylation-sensitive restriction enzyme digestion prior to species-specific PCR. We estimated that human tumor-specific reads (ctDNA) or mctDNA comprised about 0.29 or 0.01%, respectively of the xenograft mouse cfDNA, and about 0.029 or 0.001% of the cfDNA of human early stage cancer patients. Similar WGBS of early stage (0-II, node- and metastasis-free) breast, lung or colorectal cancer samples identified hundreds of specific DMRs (differentially methylated regions) compared to healthy controls. Their association with tumourigenesis was supported by stage-dependent methylation, tumor suppressor or oncogene clusters, and genes also identified in the xenograft samples. Using 20 three-cancer-common and 17 colorectal cancer-specific DMRs in combination (top 0.0018% of the WGBS methylation clusters) was sufficient to distinguish the stage I colorectal cancers from breast and lung cancers and healthy controls. Our data thus confirmed the tumor origin of mctDNA by sequence specificity, and provide a selection threshold for authentic tumor mctDNA markers toward precise diagnosis of early stage cancers solely by top DMRs in combination.

  Dataset EGAD00001008696

• cfMeDIP data for 67 VPC samples

  We analyzed the cell free DNA methylomes using 67 plasma samples from patients with mCRPC prostate cancer in the VPC project. Methylation was profiled using the methylated DNA immunoprecipitation coupled to next generation sequencing (MeDIP) technology.

  Dataset EGAD00001008711

• cfMeDIP data for 22 WCDT samples

  We analyzed the cell free DNA methylomes using 22 plasma samples from patients with mCRPC prostate cancer in the WCDT project. Methylation was profiled using the methylated DNA immunoprecipitation coupled to next generation sequencing (MeDIP) technology.

  Dataset EGAD00001008713

• Precise reconstruction of the tumor microenvironment using bulk RNA-seq and a unique machine learning-based algorithm trained on artificial transcriptomes

  Cellular deconvolution algorithms virtually reconstruct tissue composition by analyzing the gene expression of complex tissues. Here, we present the decision tree machine learning algorithm, Kassandra, trained on a broad collection of > 9,400 tissue and blood sorted cell RNA profiles to accurately reconstruct the tumor microenvironment (TME). Bioinformatic correction for technical and biological variability, aberrant cancer cell expression inclusion, and the accurate quantification and normalization of transcript expression increased the stability and robustness of Kassandra. Performance was validated on over 4,000 H&E tissue slides and more than 1,000 normal and tumor tissues by comparison with cytometric, immunohistochemical or single-cell RNA-seq measurements. Kassandra accurately deconvolved stromal and immune elements of blood and tumors, revealing the role of the TME in tumor pathogenesis. Digital TME reconstruction revealed that the presence of PD1-positive CD8+ T cells strongly correlated with immunotherapy response and increased the predictive potential of established biomarkers, indicating that Kassandra could potentially be utilized in future clinical applications.

  Dataset EGAD00001008776

• WCDT deep RNA-seq

  This dataset includes fastq files for total RNAseq of 104 patient biopsies with metastatic castration resistant prostate cancer. The RNAseq libraries were rRNA depleted and sequenced at 150bp paired-end on Illumina Novaseq.

  Dataset EGAD00001008799

• low pass WGS of patient from the CN300 cohort

  We copy number profiled 688 tumor regions from 300 patients presenting with advanced prostate cancer and prospectively followed-up (median, 7 years) in the control group of the STAMPEDE trial. Patients were categorised into four metastatic states, namely high-risk non-metastatic (with or without local lymph node involvement) or metastatic (low or high volume).

  Dataset EGAD00001008800

• whole genome sequencing of breast cancer cell lines and patient derived xenograft models

  whole genome sequencing of six commonly used breast cancer cell lines and six patient derived xenograft models

  Dataset EGAD00001008802

• Dataset for head_and_neck_cancer-EXON

  Rare cancer sequencing data of 86 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008880

• Dataset for hematopoietic_malignancy-WHOLE_GENOME

  Rare cancer sequencing data of 49 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008881

• Dataset for hematopoietic_malignancy-EXON

  Rare cancer sequencing data of 91 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008882

• Dataset for hepatopancreaticobiliary_malignancy-EXON

  Rare cancer sequencing data of 162 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008883

• Dataset for hepatopancreaticobiliary_malignancy-WHOLE_GENOME

  Rare cancer sequencing data of 83 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008884

• Dataset for leiomyosarcoma-EXON

  Rare cancer sequencing data of 96 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008885

• Dataset for liposarcoma-EXON

  Rare cancer sequencing data of 29 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008886

• Dataset for leiomyosarcoma-WHOLE_GENOME

  Rare cancer sequencing data of 66 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008887

• Dataset for liposarcoma-WHOLE_GENOME

  Rare cancer sequencing data of 48 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008888

• Dataset for melanoma-WHOLE_GENOME

  Rare cancer sequencing data of 22 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008889

• Dataset for melanoma-EXON

  Rare cancer sequencing data of 76 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008890

• Dataset for neuroendocrine_adrenal_tumor-EXON

  Rare cancer sequencing data of 164 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008891

• Dataset for NSCLC-EXON

  Rare cancer sequencing data of 42 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008892

• Dataset for NSCLC-WHOLE_GENOME

  Rare cancer sequencing data of 34 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008894

• Dataset for neuroendocrine_adrenal_tumor-WHOLE_GENOME

  Rare cancer sequencing data of 112 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008893

• Dataset for other_cancer-WHOLE_GENOME

  Rare cancer sequencing data of 49 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008895

• Dataset for other_cancer-EXON

  Rare cancer sequencing data of 137 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008896

• Dataset for soft_tissue_tumor-EXON

  Rare cancer sequencing data of 246 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008897

• Dataset for synovial_sarcoma-WHOLE_GENOME

  Rare cancer sequencing data of 6 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008899

• Dataset for synovial_sarcoma-EXON

  Rare cancer sequencing data of 34 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008898

• 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 EGAD00001008927

• Dataset for soft_tissue_tumor-WHOLE_GENOME

  Rare cancer sequencing data of 142 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008900

• Dataset for upper_gastrointestinal_tumor-WHOLE_GENOME

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

  Dataset EGAD00001008901

• Dataset for upper_gastrointestinal_tumor-EXON

  Rare cancer sequencing data of 85 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008902

• Dataset for urologic_cancer-WHOLE_GENOME

  Rare cancer sequencing data of 36 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008903

• Dataset for urologic_cancer-EXON

  Rare cancer sequencing data of 112 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008904

• 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 EGAD00001008928