381 results for "cancer rna-seq"

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• Genomic and Transcriptomic Profiling of Patients with Malignant Pleural and Peritoneal Mesothelioma: The NCI Cohort

  Malignant mesothelioma is an aggressive cancer with limited treatment options and poor prognosis. Better understanding of mesothelioma genomics and transcriptomics could advance novel therapies. We performed whole-exome sequencing (WXS) of germline and tumors of 122 patients, and RNA-sequencing (RNA-Seq) of tumor samples of 100 patients with pleural, peritoneal, and tunica-vaginalis mesothelioma.The biospecimens used in this study were collected as a part of the Mesothelioma Natural History Protocol (https://clinicaltrials.gov/ct2/show/NCT01950572), wherein, samples were collected from subjects with malignant mesothelioma as listed in the eligibility criteria below and written consent from each participant was obtained before sample acquisition.

  Study phs002207

• The UC San Diego Chronic Lymphocytic Leukemia (CLL) Study

  The UC San Diego Chronic Lymphocytic Leukemia Study is designed to identify genetic, epigenetic, and transcriptional changes important for CLL. This data release consists of samples collected to 1) identify genomic changes associated with CLL progression using serially collected tumor samples; 2) characterize the transcriptional consequences of SF3B1 mutation through RNA-seq; and 3) characterize the expression profiles of ROR1+ vs. ROR1- tumors. The samples were collected from participants at the University of California, San Diego Moores Cancer Center and the data was generated at UC San Diego or in collaboration with the BC Cancer Agency Genome Sciences Centre.

  Study phs000767

• Resistance studies in Lung Cancer

  The purpose of the study was to compare gene expression profiles from a cohort of crizotinib-resistant ALK-rearranged lung tumors and a cohort of treatment-naive ALK-rearranged lung tumors. Expression profiles were generated by RNA-seq. In parallel, gene expression profiles were obtained from ALK-rearranged lung cancer cell lines in the presence or absence of the ALK inhibitor TAE684. Gene expression profiles were also obtained from ALK-rearranged cells ectopically expressing genes associated with ALK inhibitor resistance that were identified from a functional genetic study.

  Study phs000855

• Gene signature for predicting homologous recombination deficiency in triple-negative breast cancer

  We developed a gene expression-based classifier for homologous recombination deficiency (HRD) in breast cancer patients using WES and RNA-seq data obtained from 94 TNBC samples from a Malaysian hospital-based cohort (MyBrCa). This classifier was able to predict for high levels of a mutational signature associated with HRD in an additional MyBrCa TNBC validation cohort (this EGA study) as well as in TNBCs from TCGA. We also validated the classifier on a NanoString platform with both fresh frozen and FFPE tissue.

  Study EGAS00001006518

• March 2017 data update (bam/fastq) (containing H3K27ac for CEMT_87, RNA-Seq for CEMT_141, CEMT_142, CEMT_145, CEMT_146, H3K27me3, H3K9me3, H3K4me3, H3K4me1, ChIP-Seq Input for CEMT_88, CEMT_90 and CEMT_91) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  March 2017 data update (bam/fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001003272

• Clinical Cancer Genomic Profiling by Three-Platform Sequencing of Whole Genome, Whole Exome and Transcriptome

  To evaluate the potential of an integrated clinical test to detect diverse classes of somatic and germline mutations relevant to pediatric oncology, we performed three-platform whole-genome (WGS), whole exome (WES) and transcriptome (RNA-Seq) sequencing of tumors and normal tissue from 78 pediatric cancer patients in a CLIA-certified, CAP-accredited laboratory. Our analysis pipeline achieves high accuracy by cross-validating variants between sequencing types, thereby removing the need for confirmatory testing, and facilitates comprehensive reporting in a clinically-relevant timeframe. Three-platform sequencing has a positive predictive value of 97-99%, 99% and 91% for somatic SNVs, indels and structural variations, respectively, based on independent experimental verification of 15,225 variants. We report 240 pathogenic variants across all cases, including 84 of 86 known from previous diagnostic testing (98% sensitivity). Combined WES and RNA-Seq, the current standard for precision oncology, achieved only 78% sensitivity. These results emphasize the critical need for incorporating WGS in pediatric oncology testing.

  Study EGAS00001002217

• 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

• Metastases of a cancer of unknown primary (CUP)

  RNA seq analysis of 6 CUP metastases (each in triplicate), analysed by paired sequencing with NextSeq 500. Whole exome sequencing of 15 CUP metastases, analysed by paired sequencing with NextSeq 500.

  Dataset EGAD00001005963

• 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

• Whole Genome Sequencing of HCC

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 24 whole genome sequencing (12 Tumoral/Non-tumoral pairs). Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Study EGAS00001002888

• Breast Cancer - immune clusters - RNA-seq

  In this study we use expression data from breast cancer tumors to define immune clusters in breast cancer. Immune clusters have gradual levels of immune infiltration. In the intermediate immune infiltration cluster, we found a worse prognosis which is independent of known clinicopathological features. We also found the immune clusters associated with treatment response. Further using gene expression data and deconvolution algorithms to dissect the immune contexture of the clusters.

  Dataset EGAD00001004985

• Whole exome sequencing of advanced gastric cancer

  To define the cellular characteristics of malignant ascites of advanced gastric cancer patients and search for therapeutic strategies, we obtained 5 malignant ascites and 1 cerebrospinal fluid from five patients with gastric cancer. We analyzed single-cell RNA-seq data of 180 cells from 4 malignant ascites and 1 cerebrospinal fluid metastasis using Fluidigm® C1™ System. Whole exome sequencing data was also generated from blood or tumor tissue.

  Dataset EGAD00001005740

• A Personalized Neoantigen Vaccine Generates Anti-Tumor Immunity in High-Risk Renal Cell Carcinoma

  Personalized cancer vaccines (PCVs) can generate circulating immune responses against predicted neoantigens. However, whether such responses can target cancer driver mutations, lead to immune recognition of a patient's tumor, and result in clinical activity are largely unknown, particularly in patients with lower mutation burden tumors. We conducted a phase I trial testing a neoantigen-targeting PCV in patients with high-risk, fully resected clear cell renal cell carcinoma (RCC; stage III or IV), with or without ipilimumab administered adjacent to the vaccine. At a median follow-up of 40.2 months from surgery, none of the 9 initial participants experienced a recurrence of RCC. No dose-limiting toxicities were observed. All patients generated T cell immune responses against PCV antigens, including RCC driver mutations in VHL, PBRM1, BAP1, KDM5C, and PIK3CA. Following vaccination, there was a durable expansion of peripheral T cell clones, and T cell reactivity against autologous tumor was detected in 7 of the 9 patients. Our results demonstrate that neoantigen-targeting PCVs in high-risk RCC are highly immunogenic, capable of targeting key driver mutations, and induce anti-tumor immunity. These observations, in conjunction with the absence of recurrence in all 9 vaccinated patients, highlights the promise of PCV as effective adjuvant therapy in RCC. We are submitting whole exome sequencing (WES) data from whole blood samples and tumor FFPE samples, and RNA-Seq data from tumor FFPE samples. We are also submitting RNA-Seq data from purified tumor samples. Single-cell RNA sequencing (scRNA-seq) data will be submitted for skin samples (vaccine site biopsies at weeks 0, 4, and 13), tumor samples (including resected metastatic tumor samples for two patients), and normal kidney samples. Bulk T-cell receptor sequencing (TCR-seq) data will be submitted for blood samples.

  Study phs003710

• WES and RNA-seq data of 11 cancer patients with multiple cancer types

  This dataset includes WES and RNAseq from 11 patients with metastatic melanoma, lung, kidney, and stomach cancers, enrolled in phase I clinical trials of TIL ACT (NCT03475134 & NCT04643574). WES was performed on matched cancer and healthy samples, whereas RNAseq was performed on cancer tissues, using Illumina HiSeq 2500/4000 and Illumina NextSeq 550 systems. Paired-end reads are provided in fastq format.

  Dataset EGAD00001010169

• Integrative Analysis for Multi-Omics Data in Non-Small-Cell Lung Cancer

  We conducted epigenetic and transcriptomic mapping of primary non-small cell lung tumors and non-neoplastic tissues. 20 non-neoplastic lung tissues and 18 non-small cell lung tumors were obtained from Biorepository and Tissue Technology Shared Resource at Moores Cancer Center, UC San Diego. All tumor samples were in pathological stages I and II. 8 pairs of samples were "matched", meaning that the tumor and normal tissues came from the same patient. Microfluidic oscillatory washing–based chromatin immunoprecipitation followed by sequencing (MOWChIP-seq) was used to profile the binding of H3K4me1, H3K4me3, H3K9me3, H3K27ac and H3K27me3. SmartSeq-2 was used to map mRNA expression. We identified a large number of differentially modified regions for both epigenetic and transcriptomic markers between tumors and normal tissues. Deep learning model showed extensive transcription factor network rewiring. Raw sequencing data of the ChIP-seq and RNA-seq libraries are available through this dbGaP submission.

  Study phs003113

• Genomic profiling of subcutaneous patient derived xenograft models of solid childhood cancer

  The pediatric cancer cohort in this study included 70 PDX models from 65 different individuals. This cohort included a total of 16 different pediatric solid tumor subtypes, including fourteen Wilms tumors, thirteen hepatoblastomas, thirteen osteosarcomas, ten germ cell tumors, four neuroblastomas, three clear cell sarcomas, two adrenal cortical carcinomas, two leydig cell tumors, two medulloblastomas, one embryonal rhabdomyosarcoma (ERMS), one Ewing sarcoma, one pleomorphic sarcoma, one adenocarcinoma, one glioblastoma, one mesothelioma and one ovarian tumor. Notably, we have five samples with multiple PDX models from same patient, including two cases with duplicates (564 and 564-Dup, 1796 and 1796-Dup), one case with two different metastasis (560-SM, 560-LM), one case with two blocks from same tumor (1939 and 1939-Dup), and one case with different primary tumor from same patient (2264 and 1932). We have a total of 353 sequencing data, including 82 RNA sequencing data (RNA-seq), 138 whole-exome sequencing (WES) and 135 low-pass whole-genome sequencing (WGS). For RNA-seq data, we have 61 PDXs and 21 PTs; for WES, we have 67 PDXs, 30 PTs and 40 matched normal germlines; for WGS, we have 64 PDXs, 30 PTs and 40 matched normal germlines. Of which, 19 PT-PDX paired RNA-seq, 28 paired PT-PDX paired WES and WGS were included.

  Dataset EGAD00001009863

• RNA-seq dataset

  HTG EdgeSeq fastq files of bulk baseline tumors from IMbassdor250: a randomised phase 3 trial comparing atezolizumab with enzalutamide vs enzalutamide alone in patients with metastatic castration-resistant prostate cancer.

  Dataset EGAD00001007685

• Childhood Cancer Data Initiative (CCDI): NCI-COG Pediatric MATCH Precision Medicine Clinical Trial

  The National Cancer Institute-Children's Oncology Group (NCI-COG) Pediatric Molecular Analysis for Therapy Choice (MATCH) trial provides a framework for biomarker-driven early phase trials of targeted therapies in pediatric and young adult cancer patients across the United States. Pediatric MATCH enrolled more than 1,300 patients with treatment-refractory cancers, offering access to molecular screening and investigational targeted therapies. To further advance this, matched diagnostic, refractory tumor, and normal samples from Pediatric MATCH cases were molecularly characterized, creating one of the largest comprehensive data sets available for childhood cancers. This analysis has the potential to provide novel insights into the genetics of refractory pediatric, adolescent, and young adult cancers, as well as inform potential therapeutic strategies. The following molecular characterization assays were performed: Tumor whole exome sequencing (WES) Tumor whole genome sequencing (WGS) Tumor RNA sequencing (RNA-seq) Blood whole exome sequencing (WES) Blood whole genome sequencing (WGS)

  Study phs002883

• WES, sWGS and RNA-seq of Asian breast cancer

  The dataset contains a full genomics characterization of 527 Asian breast tumours. This includes whole-exome sequencing of tumour tissue at 80X, whole-exome sequencing of matched normal (blood) tissue at 40X, shallow-whole genome sequencing at 0.1X for copy number analyses, and RNA-seq of tumour tissue at 40X coverage (>15 million reads). Whole-exome libraries were prepared using the Nextera Rapid Capture Exome Kit; exome capture was performed in pools of 3 and subjected to paired end 75 sequencing on a HiSEQ4000 platform. RNA libraries were prepared using the TruSeq Stranded Total RNA HT kit with Ribo-Zero Gold as per manufacturer’s instructions and also subjected to paired end 75 sequencing on a HiSEQ4000 platform. Uploaded bam files have been mapped to the hs37d5 human genome and processed using the standard GATK pipelines. Paired clinical, demographic, genotyping, and overall survival data for these patients are available from the associated publications or by request.

  Dataset EGAD00001006399

• Control samples, breast cancer clinical samples and matched patient-derived tumour xenografts (PDTXs) to develop and test a computational approach to discriminate human and mouse sequences in PDTXs

  Patient-Derived Tumour Xenografts (PDTXs) have emerged as the pre-clinical models that best represent clinical tumour diversity and intra-tumour heterogeneity. The molecular characterization of PDTXs using High-Throughput Sequencing (HTS) is essential; however, the presence of mouse stroma is challenging for HTS data analysis. Indeed, the high homology between the two genomes results in a proportion of mouse reads being mapped as human. In this study we generated Whole Exome Sequencing (WES) and RNA sequencing (RNA-seq) data from samples with known mixtures of mouse and human DNA or RNA.

  Study EGAS00001002445

• Sequencing of Rare Pancreatic Tumors That Respond to PD-1 Blockade

  Pancreatic cancer is nearly always refractory to immunotherapy, except in a rare subset of patients whose tumors have a high mutational burden (TMB), usually due to mismatch-repair deficiency. We collected tumors and matched blood from patients with pancreatic cancer, some of whom had high-TMB disease. We performed single-cell RNA-seq analyses of those samples to understand the correlates in the pancreatic tumor microenvironment of productive responses to immunotherapy. We found that different T cell populations responded to PD-1 blockade in TMB-high vs TMB-low tumors. This dataset consists of Illumina NovaSeq sequencing output (as FASTQ files) for blood and tumor libraries prepared using 10X Genomics Single Cell 5' Immune Profiling kits. FASTQs are provided for GEX, TCR, and (for multiplexed samples) HTO libraries.

  Study phs004257

• Single cell RNA sequencing of colorectal cancer patients (KUL3/KUL5)

  Libraries for scRNA-seq were generated using the Chromium Single Cell 3′ or 5′ library and Gel Bead & Multiplex Kit from 10x Genomics. Aimed to profile 5000 cells per library (if sufficient cells were retained during dissociation).

  Study EGAS00001006049

• Lung Adenocarcinoma Promotion by Air Pollutants

  A complete understanding of how environmental carcinogenic exposures promote cancer formation is lacking. Over 70 years ago, tumour formation was proposed to occur in a two step process: an initiating step which induces mutations in normal tissue, followed by a promoter step which triggers cancer development. Recent evidence has revealed healthy human tissue contains a patchwork of clones harbouring oncogenic mutations.This led us to hypothesise that environmental particulate matter measuring PM2.5, known to be associated with lung cancer risk, might promote lung cancer by acting on pre-existing cells harbouring oncogenic mutations in normal lung tissue. Here we use a combination of WGS and RNA-seq of mouse tumours from pollution-exposed mice to examine the impact of particulate matter on mutagenesis and gene expression respectively.

  Study EGAS00001006951

• Heterogeneous metabolic signatures are linked to cancer cell differentiation in colorectal cancer

  Colorectal cancer (CRC) is characterized by functional intratumor heterogeneity that shares many similarites with the hierarchical organization of the normal intestinal epithelium. In order to relate transcriptional subtypes to functional tumor cell heterogeneity we applied scRNA-seq to 12 patient-derived CRC spheroid cultures. We identified shared expression programs that relate to intestinal lineages and revealed metabolic signatures that are linked to cancer cell differentiation. In addition, we validated and complemented sequencing results by quantitative microscopy using live-dyes and multiplexed RNA fluorescence in situ hybridization, thereby revealing metabolic compartmentalization and potential cell-cell interactions. FInally, we demonstrate functional differences between metabolically distinct lineage subtypes that might have strong implications for future treatment strategies of CRC.

  Study EGAS00001004064

• Dendritic Cell Redundancy Enables Priming of Anti-Tumor CD4 T Cells in Pancreatic Cancer

  Pancreatic ductal adenocarcinoma (PDAC) is resistant to current immunotherapies. Using mouse models, we achieved durable remissions and immunological memory after administration of anti-CTLA-4 and anti-PD-1. The mechanism of action involves activation of cDC2 cells and CD4 T cells. To validate these findings in humans, we collected tumor samples from patients with pancreatic cancer. We performed single-cell RNA-seq analyses to assess the abundance of cDC2 cells before and after treatment. This dataset consists of Illumina NovaSeq sequencing output (FASTQ files) from blood and tumor libraries prepared using the 10x Genomics Single Cell 5′ Immune Profiling kit. FASTQ files are provided for gene expression (GEX), TCR, and, for multiplexed samples, HTO libraries.

  Study phs004508