495 results for "cancer rna-seq"

in 18.07 milliseconds.

• Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas

  Spitzoid melanoma is a specific morphologic variant of melanoma that most commonly affects children and adolescents and ranges on the spectrum of malignancy from low-grade to overtly malignant. These tumors are generally driven by fusions of ALK, RET, NTRK1/3, MET, ROS1 and BRAF. However, in approximately 50% of cases, no genetic driver has been established. Clinical whole genome and transcriptome sequencing (RNA-Seq) of a spitzoid tumor from an adolescent revealed a novel gene fusion of MAP3K8, encoding a serine−threonine kinase that activates MEK. The patient who had exhausted all other therapeutic options was treated with a MEK inhibitor and underwent a transient clinical response. We subsequently analyzed spitzoid tumors from 49 patients by RNA-Seq and found in-frame fusions or C-terminal truncations in 33% of cases. The fusion transcripts and truncated genes all contained MAP3K8 exons 1-8 but lacked the autoinhibitory final exon. Data mining of RNA-Seq from the Cancer Genome Atlas (TCGA) uncovered analogous MAP3K8 rearrangements in 1.5% of adult melanomas. Thus, MAP3K8 rearrangements - uncovered by comprehensive clinical sequencing of a single case - are the most common genetic event in spitzoid melanoma, are present in adult melanomas, and could be amenable to MEK inhibition.

  Study EGAS00001003430

• Comprehensive RNA repository of tissue and plasma from patients with esophageal cancer or precursor lesions

  A comprehensive RNA repository (both coding and non-coding) from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were collected. This dataset includes both mRNA and small RNA sequencing data (fastq.gz files) of all tissue and plasma samples. In total,102 RNA-seq libraries from 51 samples (17 plasma and 34 tissue samples) were sequenced (plasma mRNA libraries were sequenced twice).

  Dataset EGAD00001006857

• Wellcome LEAP TNBC cohort raw sequencing data

  This study contains controlled-access raw sequencing data from the retrospective Wellcome LEAP triple-negative breast cancer cohort. The data include human patient-derived single-nucleus RNA-seq and 10x Visium spatial transcriptomics generated from pre- and post-treatment tumour samples. The first dataset linked to this study supports the Victori et al. Cell Reports Medicine manuscript and includes raw FASTQ files from the relevant sequencing runs. Because some snRNA-seq libraries were generated from multiplexed pools, some raw FASTQ files may include additional co-multiplexed LEAP samples beyond those directly analysed in that manuscript. Access is controlled through the appropriate LEAP Data Access Committee and policy.

  Study EGAS50000001956

• Hereditary Gastric Cancer Syndromes: An Integrated Genomic and Clinicopathologic Study of the Predisposition to Gastric Cancer

  Gastric cancers are cancers of the stomach. Hereditary cancers are passed from parent to child. Researchers want to gather data about hereditary gastric cancers. Bulk RNA sequencing (RNA-seq) of signet ring cells (SRCs) and adjacent non-SRC epithelium (NEP) was performed on laser-capture microdissected (LCM) regions of interest found in risk-reducing total gastrectomy specimens from hereditary diffuse gastric cancer (HDGC) patients (Clinicaltrials.gov ID: NCT03030404). Twenty patients (6 male, 14 female) with confirmed HDGC were identified. Analysis of differentially expressed genes (DEGs) demonstrated upregulation of certain individual epithelial–mesenchymal transition (EMT) and proliferation genes. SRC regions had significant enrichment in pathways involved in T cell signaling. CIBERSORTx predicted significant increases in the presence of regulatory T cells (Tregs) specific to SRC regions.

  Study phs003422

• Regulatory Changes in Glioblastoma Brain Tumors and Xenografts Wave 1

  Non-coding elements in our genomes that play critical roles in complex disease are frequently marked by highly unstable RNA species. Sequencing nascent RNAs attached to an actively transcribing RNA polymerase complex can identify unstable RNAs, including those templated from gene-distal enhancers (eRNAs). However, nascent RNA sequencing techniques remain challenging to apply in some cell lines and especially to intact tissues, limiting broad applications in fields such as cancer genomics and personalized medicine. Here we report the development of chromatin run-on and sequencing (ChRO-seq), a novel run-on technology that maps the location of RNA polymerase using virtually any frozen tissue sample, including samples with degraded RNA that are intractable to conventional RNA-seq. We used ChRO-seq to develop the first maps of nascent transcription in 23 human glioblastoma (GBM) brain tumors and patient derived xenografts. Remarkably, >90,000 distal enhancers discovered using the signature of eRNA biogenesis within primary GBMs closely resemble those found in the normal human brain, and diverge substantially from GBM cell models. Despite extensive overall similarity, 12% of enhancers in each GBM distinguish normal and malignant brain tissue. These enhancers drive regulatory programs similar to the developing nervous system and are enriched for transcription factor binding sites that specify a stem-like cell fate. These results demonstrate that GBMs largely retain the enhancer landscape associated with their tissue of origin, but selectively adopt regulatory programs that are responsible for driving stem-like cell properties. We also identified enhancers and their associated transcription factors that regulate genes characteristic of each known GBM subtype, and discovered a core group of transcription factors that control the expression of genes associated with clinical outcomes. This study uncovers new insights into the molecular etiology of GBM and introduces ChRO-seq which can now be used to map regulatory programs contributing to a variety of complex diseases.

  Study phs001646

• Expressed Pseudogenes in the Transcriptional Landscape of Human Cancers

  In this study, we describe a systematic analysis of pseudogene 'transcription' from an RNA-Seq resource of 293 samples, from 13 cancer and normal tissue types. We observed a highly prevalent, genome-wide expression of pseudogenes that could be categorized as universally expressed or lineage- and/or cancer-specific. We also explored disease subtype specificity and functions of selected expressed pseudogenes. We provide evidence that transcribed pseudogenes are a significant contributor to the transcriptional landscape of cells and are positioned to play significant roles in cellular differentiation and cancer progression. Our work provides a transcriptome resource that enables high-throughput analyses of pseudogene expression.

  Study phs000525

• OncoCis: Annotation of cis-regulatory mutations in cancer

  RNA-seq dataset used for the validation of CDK6 cis-regulatory mutation annotated by OncoCis. NB bam files for manuscript A_Proteomic_Chronology_of_Gene_Expression_through_the_Cell_Cycle_in_Human_Myeloid_Leukemia_Cells are now available at the following link:http://www.ebi.ac.uk/ena/data/view/ERP008483

  Dataset EGAD00001001019

• Single-cell RNA-seq data from metastatic ovarian cancer for quality control study

  This study includes treatment-naïve fresh tissue sample from 4 HGSOC patients.

  Dataset EGAD00001006984

• 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

• Multi-omics datasets (WES, RNA-seq) of mesothelioma MIST4 study, a phase II PD-L1/VEGF blockage clinical trial

  This study comprises 26 mesothelioma patients with whole exome and RNA sequencing, designed to examine the efficacy and correlates of response to dual inhibition of programmed death-ligand 1 and vascular endothelial growth factor inhibition.

  Study EGAS50000001818

• 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

• RNA sequencing data from glioblastoma primary cell lines treated with indisulam

  This study aimed to develop NovumRNA, a bioinformatics pipeline designed to predict non-canonical tumor-specific antigens (ncTSAs) from human tumor RNA-sequencing data, potentially broadening the target pool for cancer neo-epitope-based immunotherapies. The splicing-modulating drug indisulam was investigated for its potential to induce aberrant transcriptomes, potentially increasing ncTSAs, subsequently predicted by NovumRNA. Four glioblastoma primary cell lines were derived from patient Cavitron Ultrasonic Aspirator (CUSA) material, cultured as neurospheres, and treated with indisulam or vehicle control. RNA was extracted at 6 and 16 hours post-treatment and sequenced using the NovaSeq platform. The resulting RNA-seq data was analyzed with NovumRNA, using healthy brain GTEx samples as controls, to identify and validate ncTSAs induced by indisulam treatment. NovumRNA is available at: https://github.com/ComputationalBiomedicineGroup/NovumRNA.

  Study EGAS50000000680

• 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

• Comprehensive peripheral blood immunoprofiling reveals five immunotypes with immunotherapy response characteristics in cancer patients

  The lack of comprehensive diagnostics and consensus analytical models for evaluating the status of a patient’s immune system has hindered a wider adoption of immunoprofiling for treatment monitoring and response prediction in cancer patients. To address this unmet need, we developed an immunoprofiling platform that uses multiparameter flow cytometry and RNA-seq to characterize immune cell heterogeneity in the peripheral blood of healthy donors and patients with advanced cancers. Using unsupervised clustering, we identified five immunotypes with unique distributions of different cell types, and gene expression profiles.

  Study EGAS50000000286

• 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

• CASCADE tumour transcriptome data

  RNA-Seq data from 20 fresh-frozen postmortem samples from three patients who participated in the CASCADE rapid autopsy program and died of metastatic castration resistant prostate cancer.

  Dataset EGAD00001009492

• Single Cell Transcriptomic Analysis of Cellular Heterogeneity in Human Colorectal Tumours

  1,591 single cells from 11 colorectal cancer patients were profiled using Fluidigm based single cell RNA-seq protocol to characterized cellular heterogeneity of colorectal cancer. 630 single cells from 7 cell lines were profiled similarly to benchmark de novo cell type identification algorithms.

  Dataset EGAD00001002727

• June 2016 data update 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.

  June 2016 data update (bam/fastq for CEMT0062, CEMT0068, CEMT0072, CEMT0086, CEMT0087 ChIP-Seq and RNA-Seq) 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 EGAD00001002239

• 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

• RNA-seq analysis of TGF-β-induced transcriptional changes in 19TT cancer-associated fibroblasts

  The dataset contains 6 samples, three biological replicates for vehicle-treated 19TT cells, and three biological replicates for TGF-β-treated 19TT cells. The dataset was generated by the next generation high throughput sequencing. Strand specific transcriptome library construction is completed by enriching mRNA from total RNA, sequenced by DNBSEQ high throughput platform.

  Dataset EGAD50000001350

• 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

• 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

• Pooled Mutant KRAS-Targeted Long Peptide Vaccine Combined with Nivolumab and Ipilimumab for Patients with Resected MMR-p Colorectal and Pancreatic Cancer

  We developed INtraCEllular Reverse Transcription with Sorting and sequencing (INCERTS), an approach to combine molecular indexing of receptor repertoires within intact cells and fluorescence-activated cell sorting (FACS). We demonstrate that INCERTS enables efficient processing of millions of cells from pooled human peripheral blood mononuclear cell (PBMC) samples while retaining robust association between T cell receptor (TCR) sequences and cellular phenotypes. We used INCERTS to discover antigen-specific TCRs from patients with cancer immunized with a novel mutant KRAS peptide vaccine. After ex vivo stimulation, 28 uniquely barcoded samples were pooled prior to FACS into peptide-reactive and non-reactive CD4+ and CD8+ populations. Combining complementary patient-matched single-cell RNA sequencing (scRNA-seq) data enabled retrieval of full-length, paired TCR alpha and beta chain sequences for future validation of therapeutic utility. Data available through dbGaP include scRNA-seq with matched TCR-seq.

  Study phs003425

• RNA-Seq dataset for Genomic rearrangements in Pediatric Cancer

  RNA-Seq data for systematic gene fusion detection in Pediatric Cancer

  Dataset EGAD00001008152

• 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

• 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

• Small-RNA sequencing of pheochromocytoma and paraganglioma arising from germline SDHB mutations

  Single-end 75 basepair small-RNA sequencing of 90 SDHB-deficient non-metastatic and metastatic pheochromocytoma and paraganglioma. Samples were prepared using the NEXTFLEX® Small RNA-Seq Kit v3 (Bioo Scientific ). Samples were sequenced at the molecular genomics core (Peter MacCallum Cancer Centre) using 50bp single end sequencing on the Illumina NextSeq 500 (Illumina, USA). This dataset contains raw sequencing reads in FASTQ format.

  Dataset EGAD50000000501

• 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

• ovarian cancer sample RNA-seq

  Tissue samples were collected from 18 ovarian cancer patients. After mechanical and enzymatic dissociation, a part of these tissues underwent growth factoromics analysis. For four cases, single-cell sequencing analysis was conducted under conditions with or without estradiol. Additionally, the remains of the tissues were frozen and subsequently subjected to bulk RNA-sequencing on 17 of these samples. Sixteen cases were diagnosed as HGSOC, while two samples were clear cell or mucinous type (Extended Data Table 1). All cases were grade 3, and none had received neoadjuvant chemotherapy. - Group C1, Epithelial Ovarian Cancer(EOC) patients with estrogen responsiveness : 6 samples - Group C2, Epithelial Ovarian Cancer(EOC) patients with estrogen non-responsiveness : 10 samples - non-classified 1-sample

  Dataset EGAD50000000613

• 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

• 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 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. 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 TCR-seq data will be submitted for blood samples.

  Study phs003710

• Comprehensive genomic characterization of early stage bladder cancer - Total RNA-seq data

  This study looks at the non muscle invasive bladder cancer subtypes based on totRNAseq data of 414 bladder cancer samples collected in different European centers within the UROMOL project. All samples were sequenced using paired reads on Illumina platforms. The reads are mapped to hg38.

  Study EGAS50000000512

• 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

• 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

• CGP CORE CELL LINES - RNA-seq

  Genomic characterisation of a large series of cancer cell lines.

  Dataset EGAD00001001357

• 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

• Single-Cell RNA-Sequencing of Human Prostatectomy Tissue

  The tissue microenvironment in prostate cancer is profoundly altered. How prostate cancer cells and their precursors mediate those changes is unclear, in part due to the inability to longitudinally study the disease evolution in human tissues. To overcome this limitation, we performed extensive single-cell RNA-sequencing (scRNA-seq) to assess the transcriptional profiles of the tissue microenvironment in prostate tissues from prostatectomies from men diagnosed with prostate cancer. For each subject, benign-enriched and tumor-enriched tissues were collected from the peripheral zone of the prostate. Our studies of human tissues revealed that cancer cell-intrinsic activation of MYC signaling was the top up-regulated pathway in human cancers, representing a common denominator across the well-known molecular and pathological heterogeneity of human prostate cancer. Numerous non-malignant cell states in the tumor microenvironment (TME), including non-cancerous epithelial, immune, and fibroblast cell compartments, were conserved across individuals, suggesting that these cell types may be a sequelae of the convergent MYC activation in the cancer cells.

  Study phs003480

• 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

• 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

• SMARCB1 loss activates patient-specific distal oncogenic enhancers in malignant rhabdoid tumors

  Malignant rhabdoid tumor (MRT) is a highly malignant and often lethal childhood cancer. MRTs are genetically defined by bi-allelic inactivating mutations in SMARCB1, a member of the BRG1/BRM-associated factors (BAF) chromatin remodeling complex. Mutations in BAF complex members are common in human cancer, yet their contribution to tumorigenesis remains in many cases poorly understood. Here, we studied derailed regulatory landscapes as a consequence of SMARCB1 loss in the context of MRT. Our multi-omics approach on patient-derived MRT organoids revealed a dramatic reshaping of the regulatory landscape upon SMARCB1 reconstitution. Chromosome conformation capture experiments subsequently revealed patient-specific looping of distal enhancer regions with the promoter of the MYC oncogene. This intertumoral heterogeneity in MYC enhancer utilization is also present in patient MRT tissues as shown by combined single-cell RNA-seq and ATAC-seq. We show that loss of SMARCB1 drives patient-specific epigenetic reprogramming underlying MRT tumorigenesis.

  Study EGAS00001007590

• single cell RNA-seq of small cell lung cancer tumors

  This study investigated the transcriptomic profile of small cell lung cancer from 10 patients. Tumors were rapidly dissociated after the surgical procedure. Libraries were constructed using the VDJ NextGEM v1.1 10x Genomics Chromium kit. Samples were sequenced on a NextSeq 550 sequencer (Illumina).

  Study EGAS50000001400

• RNAseq from 6 organotypic co-cultures (OC cells bulk/OCSC with or without TME)

  The dataset contains samples of 6 organotypic co-cultures, assembled with patient-derived material from ovarian cancer (OC) patients. Tumor cells, both as bulk and as cancer stem cells-enriched (OCSC) populations, are cultured or not with in vitro peritoneal TME (for details see Battistini C et al, Tumor microenvironment-induced FOXM1 regulates ovarian cancer stemness, CDDis 2024). Dataset is composed by fastq file (paired end) type from bulk RNA-Seq.

  Dataset EGAD50000000523

• Ongoing Replication Stress Tolerance and Clonal T Cell Responses Distinguish Liver and Lung Recurrence and Patient Outcomes in Pancreatic Ductal Adenocarcinoma

  Patients with metastatic pancreatic ductal adenocarcinoma (PDAC) survive longer when disease spreads to the lung but not to the liver. We generated overlapping, multi-omic datasets to identify molecular and cellular features that distinguish patients whose disease develops liver metastasis (liver cohort) from those whose disease progression results in lung metastasis without liver metastases (lung cohort). Lung cohort patients generally survived longer than liver cohort patients, independent of tumor subtype. We developed a pORG gene signature that distinguishes primary tumors in the liver and lung cohorts. We identified ongoing replication stress (RS) response pathways in high pORG/liver cohort tumors, while low pORG/lung cohort tumors had greater densities of lymphocytes and shared T cell clonal responses. Our study demonstrates that liver-avid PDAC is associated with tolerance to ongoing RS, limited tumor immunity, and less favorable outcomes; whereas low RS, lung-avid/liver-averse tumors are associated with active tumor immunity that may account for favorable outcomes. As expected, we found high frequencies of KRAS, TP53, CDKN2A, and SMAD4 gene alterations in our tumor samples. High pORG activity (GSVA scores) in our primary tumors appear to be positively correlated with alteration frequencies in both TP53 and CDKN2A. We did not see a correlation with alterations in KRAS as almost all the tumor samples have KRAS alterations. From a de-identified dataset of 1,873 patients diagnosed with and/or treated for PDAC at our institution between 2004 and 2020, we identified 422 patients for which we had specimens with sequencing data (N=374) and/or specific evidence of disease metastasis site(s) from the OHSU cancer registry or disease-relevant computed tomography (CT) scans to allow cohort classification. Note that our study includes RNA-Seq, DNA-Seq panel, and TCR-Seq (T-cell Receptor Sequencing) data, but that this dbGaP submission just includes the patients/samples with RNA-Seq and/or DNA-Seq panel data. Therefore, this submission includes 290 samples from 278 patients. TCR sequence data is available on the Adaptive Biotechnologies platform. Clinical course timepoints, patient demographics, stage, grade, nodal involvement, resection margins, and angiolymphatic invasion were provided as deidentified data by the OHSU cancer registry with quality control data verification in a subset by pathologists (BB and TM). We reviewed all available computed tomography (CT) scans for all patients with primary tumor resection dates recorded by the cancer registrar, with tumor samples analyzed by RNA-seq, DNA-seq, or TCR-seq, and/or with additional information indicating metastatic spread (e.g., metastatic samples received for related studies). We abstracted the site of all lesions proven to be metastatic by biopsy and/or that clearly increased in size during progression or decreased in size during treatment as long as a radiologist described the lesion as “likely”, “suspicious for”, “concerning for”, or “favor” metastasis. Clinical imaging was reviewed by a radiologist (AG) to validate patient assignments to the liver, lung, and neither liver nor lung (other recurrence site) cohorts. Time to recurrence was calculated from the earliest of either the recurrence date provided by the OHSU cancer registry, or the date of earliest lesion abstracted from CT reports. The subject attributes reported in this submission were up to date at the time of our data freeze, which occurred July 2021.

  Study phs003597

• Paediatric MN1::ZNF341-associated cancer scRNA-seq

  A lethal round-cell malignancy with an MN1::ZNF341 fusion has recently been reported. Here, using single-cell RNA sequencing data derived from monozygotic twins, we find the tumour to be transcriptionally distinct from neuroblastoma. Instead, it exhibits steroidogenic differentiation. These data, in combination with the clinical, radiological, histopathological and additional molecular findings, corroborate suggestions that this tumour is a distinct and aggressive childhood cancer.

  Dataset EGAD00001016421

• Pathogenesis and Immunity in Endemic Burkitt Lymphoma

  This genomic landscape of Burkitt lymphoma represents a multimodal sequencing of tumors and control tissues and individuals to better understand the etiology, and molecular pathogenesis of Burkitt lymphoma including the roles of the associated Plasmodium falciparum malaria and EBV infections. Comprehensive sequencing set includes genomic, transcriptomic, and epigenomic datasets in concert with variable clinical phenotypes and outcome information such as anatomical presentation site, in-hospital survival rates, and EBV genome type. This deposit includes additional small RNA-seq data from endemic BL (eBL) tumors and RNA-sequencing data from sorted NK cell subsets from the peripheral blood of eBL patients. The additional small RNA-seq data are from tumor specimens from 17 eBL cases, of the previously deposited polyA RNA-seq data from 28 eBL cases (phs1282.V1). The additional RNAseq data from Fluorescence-activated cell sorting (FACS) of NK cell subsets, isolated from the peripheral blood of 7 eBL cases. The additional RNAseq data are from eBL tumor samples of 5 eBL cases, BL cell lines established from these tumor samples and also NSG mouse tumors created by implanting the established BL cell lines into NSG mice. The dataset also includes RNAseq data of the NSG mouse tumors after treatment with Rituximab (RIT) and Phosphate buffered saline (PBS). The fifth batch of data includes mRNA-seq from different passages of a single eBL cell line that have variable EBV phenotypes (low passage with lytic EBV and high passage with latent EBV). This batch also includes lytic and latent lymphoblastoid cell line (LCL) clones from a single blood donor generated through infection with the strain of EBV isolated from the aforementioned eBL cell line. For initial transcriptome analysis see: Kaymaz et al. "Comprehensive Transcriptome and Mutational Profiling of Endemic Burkitt Lymphoma Reveals EBV Type-specific Difference." Molecular Cancer Research, 2017, PMID: 28465297. For initial microRNA analysis see: Oduor et al. "Human and Epstein-Barr Virus miRNA Profiling as Predictive Biomarkers for Endemic Burkitt Lymphoma." Frontiers in Microbiology 8, 2017, PMID: 28400759. For initial NK subsets RNA expression analysis see: Forconi et al. "A new hope for CD56negCD16pos NK cells as unconventional cytotoxic mediators: an adaptation to chronic diseases." Frontiers in Cellular and Infection Microbiology, 2020, PMID: 32373555.For initial eBL cell line and mouse avatar RNA expression analysis see: Saikumar et al. "Endemic Burkitt lymphoma avatar mouse models for exploring inter-patient tumor variation and testing targeted therapies." Life Science Alliance, 2023, PMID: 36878637. For general overview of cohort study see: Buckle et al. "Factors influencing survival among Kenyan children diagnosed with endemic Burkitt lymphoma between 2003 and 2011: A historical cohort study." Int J Cancer. 15:1231, 2016, PMID: 27136063.

  Study phs001282