15041 results for "cancer studies using rna-seq"

in 51.16 milliseconds.

• Single-Cell Sequencing Reveals Distinct Microenvironment Cell Types Associated with Response to High Dose Melphalan and Autologous Stem Cell Transplant in Multiple Myeloma

  The aim of this study is to understand the transcriptome of microenvironment cells in pre- and post- autologous stem cell transplantation (ASCT) samples between patients with complete response and partial response to transplant. Here, we studied immune cells from 40 multiple myeloma patients who have undergone ASCT. Samples were collected from 40 multiple myeloma patients before and after ASCT. Samples were sorted using magnetic activated cell sorting (MACS) and the non-tumor CD138- fraction underwent 3' single cell RNA-sequencing (scRNA-seq) or 5' scRNA-seq + 5' T cell receptor sequencing (TCRseq), to determine the scRNA transcriptome and TCR repertoire. This study includes 24 samples with 3' scRNA-seq, 56 samples with 5' scRNA-seq, and 56 samples with 5' TCRseq data.

  Study phs003219

• Spatial Transcriptomics on prostate cancer heterogeneity

  Intratumor heterogeneity is one of the biggest challenges in cancer treatment today. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal prostate cancer using the spatial transcriptomics (ST) technology. Utilizing a novel approach for deconvolution, we analyze the transcriptomes of nearly 6750 tissue regions and extract distinct expression profiles for the different tissue components, such as stroma, normal and PIN glands, immune cells and cancer. We distinguish healthy and diseased areas and thereby provide insight into gene expression changes during the progression of prostate cancer. Compared to pathologist annotations, we delineate the extent of cancer foci more accurately, interestingly without link to histological changes. We identify gene expression gradients in stroma adjacent to tumor regions that allow for re-stratification of the tumor microenvironment. The establishment of these profiles is the first step towards an unbiased view of prostate cancer and can serve as a dictionary for future studies.

  Study EGAS00001003001

• Identification_of_cardiovascular_biomarkers_through_an_integrative_omics_approach

  Recent GWAS studies have made extensive use of large eQTL data sets to functionallyannotate index SNPs. With a large number of association signals located outside codingregions there has been an intense search among sequence variants affecting geneexpression at the transcriptional level. However, little progress has been made in mappingregulatory variants that affect protein levels at the translational or post-translational level. It isnow possible to undertake a protein QTL scan for focused sets of e.g. oxidized proteins bymass spectrometry. We have established a collaboration with a longitudinal, family-basedstudy in France, the Stanislas cohort, which comprises circa 1000 nuclear families (4,295individuals) and has follow up data for 10 years (three visits). We have undertaken a pilotstudy in a focus set of 257 subjects from 79 families with the aim to integrate GWAS,transcriptomic and DNA methylation data with proteomic data on a set of 100 proteinsmeasured in PBMCs. We have already generated GWAS data using Illumina's core-exomechip as well as DNA methylation profiles with the 450K array. We propose to use RNA seq togenerate transcriptomic data of the corresponding PBMCs.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000711

• Single-cell RNA sequencing of control and Notch inhibitor treated HCC PDX model

  We generated single-cell RNA-seq data for anti-Notch2 (n=3), anti-JAG1 (n=1) and anti-gD (n=4) treated LIV78 tumors. NCR nude mice bearing similarly sized LIV78 tumors (volumes between 300-900mm3) were injected intravenously with 30mg/kg body weight of either anti-Notch2, anti-Jag1 or anti-gD control antibody 72hrs prior to tumor harvest and tumor cell isolation. Following the depletion of CD45+ and Ter119+ cells, the samples were processed for single-cell RNA-seq (scRNAseq) as described previously (Long et al., 2019) using the Chromium Single Cell 3’ Library and Gel bead kit v2, following the manufacturer’s manual. cDNAs and libraries were prepared following the manufacturer’s manual (10X Genomics). Libraries were profiled by Bioanalyzer High Sensitivity DNA kit (Agilent Technologies) and quantified using Kapa Library Quantification Kit (Kapa Biosystems, Wilmington, MA). Each library was sequenced in one lane of HiSeq 2500 (Illumina) following the manufacturer’s sequencing specification (10X Genomics) to produce the resulting FASTQ files.

  Dataset EGAD50000000738

• Phenotype information

  This study explores the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft (PDTX) model. Blood plasma samples (n=171) derived from a DLBCL PDTX model in-cluding 27 humanized (HIS) PDTX, 8 HIS non-PDTX and 21 non-HIS PDTX non-obese diabetic (NOD)-scid IL2Rgnull (NSG) mice were collected during humanization, xenografting, treatment, and sacrifice. The mice were treated with either rituximab, cyclophosphamide, doxorubicin, vincris-tine, and prednisone (R-CHOP), CD20-targeted human IFNα2-based AcTaferon combined with CHOP (huCD20-Fc-AFN-CHOP), or phosphate-buffered saline (PBS). RNA was extracted using the miRNeasy serum/plasma kit and sequenced on the NovaSeq 6000 platform using the using the SMARTer Stranded Total RNA-Seq Kit v3.

  Dataset EGAD50000000806

• Single cell RNA-seq of 24 samples from 13 individual human embryonic meninges of PCW 5.0-13.0 using 10X chromium technology

  A total of 24 samples of meninges from 13 normal human embryos of post-conceptional week (PCW) 5.0-13.0 were dissected and subject to 10Xgenomics chromium single cell RNA sequencing with the purpose of identifying cell types and gene expression programs for normal meninges development. All libraries were sequenced on an Illumina NovaSeq 6000 using S4 to a target sequencing depth of 100,000 reads/cell. Final data after processing with STARSolo 2.7.10a, using human genome GRCh38.p12 and transcript annotations from ENSEMBL release 93 from reference package GRCh38-3.0.0 as available from 10Xgenomics, consists of 24 BAM files.

  Dataset EGAD50000001434

• Breast Cancer Genome Guided Therapy Study (BEAUTY)

  The Breast Cancer Genome Guided Therapy Study (BEAUTY) is a prospective neoadjuvant clinical study enrolling 140 women with Stage I-III breast cancer. The goals of this study were to 1) perform comprehensive sequencing of germline and tumor tissues (exome and RNA seq), 2) identify genomic alterations and perturbed pathways associated with response/resistance to standard chemotherapy, and 3) develop patient-derived xenograft (PDX) for testing of therapeutic regimens chosen on the basis of alterations identified by genetic sequencing.

  Study phs001050

• Identification of potential blood biomarkers for early diagnosis of Alzheimer���s disease through immune landscape analysis

  Mild cognitive impairment (MCI) is a clinical precursor of Alzheimer���s disease (AD). Recent genetic studies have reported on associations between AD risk genes and immunity. Here, we obtained samples and data from 317 AD, 432 MCI, and 107 cognitively normal (CN) subjects and investigated immune-cell type composition and immune clonal diversity of T-cell receptor (TRA, TRB, TRG, and TRD) and B-cell receptor (IGH, IGK, and IGL) repertoires through bulk RNA sequencing. Our prognosis prediction model using the potential blood-based biomarkers for early AD diagnosis, which combined two immune repertoires (IGK and TRA), WDR37, and clinical information, successfully classified MCI patients into two groups, low and high, in terms of risk of MCI-to-AD conversion.

  Study JGAS000532

• Characterization of a New Case of XMLV (Bxv1) Contamination in the Human Cell Line Hep2 (Clone 2B) Using High-Throughput DNA- and RNA-Seq

  We have sequenced DNA and RNA from the Hep2 (clone 2B) cell line (Sigma-Aldrich catalog number: 85011412-1VL) using short read Illumina sequencing. We show that this cell line is indistinguishable from the HeLa cell line (as mentioned on the Sigma-Aldrich website) by mapping integrations of the human papillomavirus 18. We also show that the cell line is contaminated by the Bxv1 xenotropic murine leukemia virus. This contamination has to be taken into account when using the cell line in future experiments.

  Study phs001944

• Transcriptomic Profiling of Oropharyngeal Squamous Cell Carcinoma

  The study is a retrospective transcriptomic profiling of oropharyngeal squamous cell carcinoma. The pathologic database was queried for squamous cell carcinoma tumors originating from the anatomic oropharynx (tonsil or tongue base) with available samples from surgical archives. This retrospective RNA sequencing cohort included cases dating prior to the routine implementation of p16 immunohistochemistry (IHC) testing at our institution, therefore, p16 status was not required for inclusion in this study. Formalin-fixed paraffin-embedded (FFPE) tissue samples were sent to the UNC Lineberger Comprehensive Cancer Center (LCCC) Translational Genomics Lab (TGL) for RNA isolation using the Maxwell 16 MDx Instrument (Promega AS3000) and the Maxwell 16 LEV RNA FFPE Kit (Promega AS1260) following the manufacturer's protocol (Promega 9FB167). After a pathology review of a hematoxylin and eosin (H&E) stained slides to identify tumor area, RNA was extracted from unstained slides using macrodissection. Total RNA quality was measured using a NanoDrop spectrophotometer (Thermo Scientific ND-2000C) and a TapeStation 4200 (Agilent G2991AA). Total RNA concentration was quantified using a Qubit 3.0 fluorometer (Life Technologies Q33216). Libraries were prepared with Illumina TruSeq Stranded Total RNA with Ribo-Zero protocol. Libraries were sequenced on an Illumina HiSeq2500 sequencer. Paired end read data, with read lengths of 75 were collected.

  Study phs002935

• Single-Cell ATAC and RNA Sequencing of Human Breast Cancer Reveals Salient Cancer-Specific Enhancers

  Matched single-cell chromatin accessibility sequencing (scATAC-seq) and single-cell transcriptomic sequencing (scRNA-seq) were performed for 12 human breast tumor samples, 4 normal human mammary reduction samples, and 4 human breast cancer cell lines (HCC1143, SUM149PT, MCF7, and T47D). Both scATAC-seq and scRNA-seq assays resolved the underlying cellular heterogeneity in chromatin accessibility and transcriptional output for each patient sample. In this work, we quantitatively linked variation in chromatin accessibility to gene expression across malignant and non-malignant cell types from patient samples. We then showed that our findings were recapitulated in the breast cancer cell line samples. These data will serve as an important resource for the single-cell genomics and breast cancer research communities.

  Study phs003253

• FAM50A_Disruption_in_TOV21G_Cells___RNAseq

  In this project we aimed to assess the transcriptional consequences of disrupting FAM50A in TOV21G cells in vivo. To do this we generated a dox inducible FAM50A gRNA allele such that we could conditionally inactivate FAM50A by feeding mice a diet containing doxycycline. Tumour masses were harvested from mice when they reached the ethical limit and RNA was extracted for RNA-Seq analysis.

  Study EGAS00001004156

• RNA Sequencing Analysis of Patient-Derived Xenograft Tissue PIM-084 Treated with L-NMMA+Alpelisib vs Vehicle Control

  This dataset contains RNA-seq analysis of vehicle control compared to L-NMMA+alpelisib treated metaplastic breast cancer PDX PIM084 tumors (RNA sequencing and analysis performed by Novogene). The submitted data contains the gene ID, gene name, normalized read counts from all samples from control group and combination treatment group, log2-fold change derived from DESeq2 R/EdgeR package, p-value, adjusted p-value, read counts from each group, and gene FPKM from the each sample in the group. Due to patient privacy, we are submitting only the processed and desensitized RNA sequencing analysis to this repository.

  Study phs003814

• TenK10K Phase 1:  Single Cell

  Understanding the genetic basis of gene expression can shed light on the regulatory mechanisms underlying complex traits and diseases. Single-cell resolved measures of RNA levels and single-cell expression quantitative trait loci (sc-eQTLs) have revealed genetic regulation that drives sub-tissue cell states and types across diverse human tissues. Here, we describe the first phase of TenK10K, the largest- to-date dataset of matched whole-genome sequencing (WGS) and single-cell RNA-sequencing (scRNA-seq). We leverage scRNA-seq data from over 5 million cells across 28 immune cell types and matched WGS from 1,925 individuals. This provides power to detect associations between rare and low-frequency genetic variants that have largely been uncharacterised in their impact on cell-specific gene expression. We map the effects of both common and rare variants in a cell type specific manner using SAIGE-QTL.

  Study EGAS50000001653

• RNA-Seq of Myeloid Cells in Dendritic Cell Therapy Response

  RNA libraries were prepared from 100 ng of total RNA using the Illumina Stranded Total RNA Prep with Ribo-Zero Plus kit, then sequenced (2×150 bp) on the Illumina NextSeq550. Transcript-level quantification was done with kallisto, followed by gene-level summarization (tximport) and differential expression analysis (DESeq2). Quality control included PCA, hierarchical clustering, and deconvolution with CIBERSORTx to exclude non-myeloid genes. Final analyses identified transcriptomic differences among healthy donors and three patient subgroups based on response to dendritic cell therapy.

  Dataset EGAD50000001681

• RNA-Seq Profiles from the CheckMate-577 Clinical Trial

  The dataset contains RNAseq profiles of 386 patients from the CheckMate-577 (CA209-577) clinical trial whose ICF allows data deposition into a public repository. The Allprep DNA/RNA FFPE kit was used to simultaneously purify genomic DNA and total RNA from formalin-fixed, paraffin embedded (FFPE) tissue sections. RNA was analyzed using the Illumina TruSeq RNA Access method for library preparation, followed by sequencing on the Illumina NovaSeq platform with a 50bp paired-end strategy and a target read depth of 50M per sample. Fastq files are included.

  Dataset EGAD50000002394

• Dataset for cancer_of_unknown_primary-RNA

  Rare cancer sequencing data of 58 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008857

• CGP CORE CELL LINES - RNA-seq

  Genomic characterisation of a large series of cancer cell lines.

  Dataset EGAD00001001357

• The characterization of gene expression pattern of anticancer agent-resistant cancer stem cells using RNA sequencing analysis.

  Slow cycling cancer stem cells persist and contribute to tumor regrowth after chemotherapy.To investigate this mechanism, we developed stemness- and cell cycle-visualized colon cancer organoids from patient tissues, and perfomed comparative transcriptome analysis using sorted rapid cycling stem cells (LGR5+p27-) and slow cycling stem cells (LGR5+p27+). In addition, we analyzed the changes in the gene expression patterns in the slow cycling stem cells and all of tumor cells after chemotherapy (camptothecin) treatment. Gene ontology analysis and gene set enrichment analysis using these transcriptome data revealed cell adhesion signal and YAP siganling pathway were important to maintain the dormancy and resume propagation after chemotherapy. In each experiments, total RNA was extracted from organoids and sequenced with HiSeq X Ten (Illumina).

  Study JGAS000350

• FOXM1 is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer that is detectable using metabolic imaging (RNA-seq data)

  PIK3CA, encoding the PI3Kα isoform, is the most frequently mutated oncogene in estrogen receptor-positive breast cancer. Isoform-selective PI3K inhibitors are used clinically but intrinsic and acquired resistance limits their utility. Improved selection of patients that will benefit from these drugs requires novel predictive biomarkers. We show here that persistent FOXM1 expression following drug treatment is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer. Since the transcription factor drives expression of lactate dehydrogenase (LDH) but not hexokinase 2 (HK-II), changes in FOXM1 expression can be detected using magnetic resonance imaging of LDH-catalyzed hyperpolarized 13C label exchange between pyruvate and lactate but not by PET measurements of HK-II-mediated trapping of the glucose analog 2-deoxy-2-[18F]fluorodeoxyglucose.

  Study EGAS00001004452

• 99 Cases of Small Cell Lung Cancer Study

  Small cell lung cancer (SCLC) is an aggressive disease with poor survival. A few sequencing studies performed on limited number of samples have revealed potential disease-driving genes in SCLC, however, much still remains unknown, particularly in the Asian patient population. Here we conducted whole exome sequencing (WES) and transcriptomic sequencing of primary tumors from 99 Chinese SCLC patients. Dysregulation of tumor suppressor genes TP53 and RB1 was observed in 82% and 62% of SCLC patients, respectively, and more than half of the SCLC patients (62%) harbored TP53 and RB1 mutation and/or copy number loss. Additionally, Serine/Arginine Splicing Factor 1 (SRSF1) DNA copy number gain and mRNA over-expression was strongly associated with poor survival using both discovery and validation patient cohorts. Functional studies in vitro and in vivo demonstrate that SRSF1 is important for tumorigenicity of SCLC and may play a key role in DNA repair and chemo-sensitivity. These results strongly support SRSF1 as a prognostic biomarker in SCLC and provide a rationale for personalized therapy in SCLC. The manuscript has been accepted by Plos Genetics.

  Study phs001083

• Assessment of candidate high-grade serous ovarian carcinoma predisposition genes through integrated germline and tumour sequencing

  High-grade serous ovarian carcinoma (HGSOC) has a significant hereditary component, only half of which is explained. Previously, we performed germline exome sequencing on BRCA1 and BRCA2-negative HGSOC patients, revealing three proposed and 43 novel candidate genes enriched with rare loss-of-function variants. For validation, we undertook case-control analyses using genomic data from disease-free controls. This confirms enrichment for nearly all previously identified genes. Additionally, one-hundred-and-eleven HGSOC tumours from variant carriers were sequenced alongside other complementary studies, seeking evidence of biallelic inactivation as supportive evidence. PALB2 and ATM validate as HGSOC predisposition genes, with 6/8 germline carrier tumours exhibiting biallelic inactivation accompanied by characteristic mutational signatures. Among candidate genes, only LLGL2 consistently shows biallelic inactivation and protein expression loss, supporting it as a novel HGSOC susceptibility gene. The remaining candidate genes fail to validate. Integrating case-control analyses with tumour sequencing is thus crucial for accurate gene discovery in familial cancer studies.

  Study EGAS50000000770

• Covacta RNAseq counts

  RNA-seq data from PAXgene extracted whole blood of patients enrolled in the COVACTA trial. This dataset includes read counts per gene. Read counts were generated for the Gencode v27 annotation using the summarize Overlaps method from bioC in mode “IntersectionStrict”

  Dataset EGAD00001011164

• SU2C-MARK Lung Cancer Consortium - Checkpoint Blockade Response Project

  Immune checkpoint inhibitors have become a critical part of the armamentarium against advanced Non-Small Cell Lung Cancer (NSCLC). While early studies have identified Tumor Mutation Burden (TMB) and PD-L1 staining as important biomarkers of response, they remain imperfect predictors. Here we describe a multi-institutional effort as part of the SU2C-MARK Lung Cancer Consortium in which Whole Exome Sequencing (WES) - and in select cases, RNA sequencing – was performed on a large collection of NSCLC samples prior to immune checkpoint blockade therapy, along with matched clinical response data following therapy. (Profiling of a small number of on- or post-treatment samples was also performed.) We anticipate this dataset to be of high value for the development of a deep understanding of the molecular determinants of immune checkpoint blockade response as well as the discovery of novel biomarkers.

  Study phs002822

• Raw RNA-seq data for clinical efficacy and biomarker analysis of neoadjuvant atezolizumab in operable urothelial carcinoma in the ABACUS trial

  ABACUS is a single arm phase 2 study that investigated 2 cycles of atezolizumab (1200mg Q3) prior to cystectomy in 95 patients with muscle invasive transitional cell cancer (T2-4N0M0). Pathological complete response (pCR) occurring in ≥20% of patients was the primary endpoint. Biomarker analysis on sequential tissue was a co-primary endpoint. This dataset includes the raw RNA-seq data.

  Dataset EGAD00001006205

• SYSCOL Human colorectal cancer project pilot RNA-seq and germline genotyping

  Genotyping by array and Transcriptome profiling by high-throughput sequencing

  Dataset EGAD00001000880

• RNA-Seq of kidney cancer organoid biobank

  Dataset EGAD00001005318

• Effects of Metformin on Transcriptomic and Metabolomic Profiles in Breast Cancer Survivors Enrolled in the Randomized Placebo-Controlled MetBreCS Trial

  RNA from snap-frozen breast tissue biopsies were purified after lysing by tissuelyser (Qiagen) and using RNA Purification Plus Kit (Norgen biotek CORP, 47700) with additional on-column DNase-I treatment (Qiagen, 79254) at 27 °C. RNA purity and integrity (RIN) were quantified using RNA 6000 Nano kit (Agilent Technologies, 5067-1511) on the 4200 TapeStation (Agilent, Santa Clara, USA). Library preparation and 2x75bp paired-end of 160 ng total RNA input was performed using Illumina Stranded Total RNA Prep Ligation kit and Illumina HiSeq4000 system (Illumina, Sand Diego, CA, USA). RNA sequencing data from HiSeq4000 were quality checked and aligned to GRCh38 (GCA_000001405.15) reference genome using HISAT2 2.0.5 and submitted to subread v.1.5.2 for feature counts calculation. Finally, 36 paired biopsies samples (metformin n=26 and placebo n=12) were sequenced and included in the final analyses.

  Dataset EGAD50000001274

• RNA-seq data from the MESOMICS project (French project of molecular characterization of malignant pleural mesothelioma)

  The dataset includes fastq files from 109 tumor samples as well as RNA-seq gene expression R data, RNA-seq transcript expression R data, RNA-seq gene counts matrix, RNA-seq transcript counts matrix, RNA-seq gene FPKM matrix RNA-seq transcript FPKM matrix for the 109 samples. The sequencing was done with HiSeq 2000 instrument.

  Dataset EGAD00001007024

• Hyperdiploid Acute Lymphoblastic Leukemia RNA-Seq

  Few genetic drivers of children with hyperdiploid precursor B-cell acute lymphoblastic leukemia (ALL) have been identified to date. In an effort to detect novel genomic rearrangements that could be promoting leukemogenesis in this subset of patients, we sequenced ribosomal RNA-depleted transcriptomes isolated from 5 hyperdiploid acute lymphoblastic leukemia samples. In addition to looking for novel genomic rearrangements, we also sought to identify transcripts that could be created as a result of a novel posttranscriptional process. Surprisingly, we identified transcripts created as the result of exon circularization. The results of our studies are present in the paper "Circular RNAs Are the Predominant Transcript Isoform from Hundreds of Human Genes in Diverse Cell Types" published in PLoS ONE (PMID: 22319583).

  Study phs000522

• RNA-Seq profiles from the CheckMate-649 Clinical Trial

  This dataset contains RNA sequencing (RNAseq) data of 814 patients from the CheckMate 649 clinical trial whose ICF allows data deposition into a public repository. Gene expression profiling was performed retrospectively using RNAseq on a subset of baseline tumor samples. Paired-end FASTQ files were processed on Seven Bridges platform (Seven Bridges Genomics).

  Dataset EGAD50000001105

• Characterizing Immune Profiles in Extrapulmonary Tuberculosis via RNA Sequencing

  This dataset provides insight into the immune response in extrapulmonary tuberculosis (EPTB), using bulk RNA-seq data to analyze different disease severities. Hierarchical clustering identified three distinct levels of severity, revealing disease progression driven by interferon and IL-1β-mediated signaling. Additionally, the dataset helped develop a diagnostic gene expression signature for both EPTB and pulmonary TB.

  Dataset EGAD50000000943

• SCLC study MGH - RNAseq dataset

  RNA-seq analyses were performed on cDNA libraries prepared from PolyA+ RNA using the Illumina TruSeq protocol for mRNA. The final libraries were sequenced with a paired-end 2×75 bp protocol aiming at 8.5 Gb per sample for a 30x mean coverage of the annotated transcriptome. All sequencing reactions were conducted on an Illumina HiSeq instrument (Illumina, San Diego, CA, USA).

  Dataset EGAD00001003969

• LongRNA_Monocytes

  This dataset consists of bulk RNA sequencing profiles generated from monocytes isolated from peripheral blood mononuclear cells (PBMCs) collected from 315 patients enrolled in the ImmunAID consortium. Each sample corresponds to a unique patient, providing a resource to investigate transcriptional variation in circulating monocytes across the cohort. PBMCs were isolated from whole blood, and monocytes were subsequently enriched using standard immunological protocols. Total RNA was extracted and libraries were prepared using the SMART-Seq mRNA Library Preparation Kit with Unique Molecular Identifiers (UMIs). Sequencing was performed on an Illumina NovaSeq 6000 platform following manufacturer-recommended protocols.

  Dataset EGAD50000002341

• snRNA-seq schizophrenia control Prefrontal cortex

  In this study, we performed RNA sequencing of single nuclei from the prefrontal cortex of donors with and without schizophrenia using the 10x Genomics Chromium Single Cell protocol. The project rationale is to determine cell type specific transcriptomic changes between the two groups and linking them to the risk for schizophrenia.

  Study EGAS50000001703

• Genomic and Transcriptomic Data from Advanced Rare Cancer Patients Treated with Pembrolizumab

  This dataset comprises whole exome sequencing data and RNA-seq data of advanced rare cancer patients.

  Dataset EGAD50000002182

• Proteogenomic Landscape of Curable Prostate Cancer

  Aligned RNA-seq sequences in this dataset are from the Proteogenomic Landscape of Curable Prostate Cancer study

  Dataset EGAD00001004875

• Disease-Linked Regulatory DNA Variants and Homeostatic Transcription Factors in Epidermis

  The role of non-coding variants in polygenic skin disease and their connection to homeostatic transcription factors (TFs) in epidermis was investigated. Homeostatic TFs were identified by perturb-seq in differentiating keratinocytes, using either 10x or split-pool approaches to sequencing, with follow-up validation by siRNA and RNA-seq. TF binding events were profiled by population sampling Cleavage Under Targets & Release Using Nuclease (CUT&RUN), in which a random population of neonatal foreskin keratinocytes were assayed by CUT&RUN for homeostatic TFs under progenitor growth and differentiation conditions. Heterozygous alleles were identified from the TF binding data and examined for allele specific binding events (ASBs). ASBs were then compared with non-coding variants linked to skin disease. Variants with potentially pathogenic effects were identified. Promoters and high TF occupancy genomic regions were found to be "buffered" against variants causing ASBs.

  Study phs003977

• Deregulation of FOXF1/FENDRR from t(14;16)(q32;q24) defines a subtype of high risk lineage ambiguous leukemia

  Despite great progress in understanding the genomic basis of immature T-cell acute lymphoblastic leukemia/lymphoblastic lymphoma (T-ALL) and acute leukemias of ambiguous lineage (ALAL), there are still cases that lack defining genetic markers, complicating risk stratification and limiting targeted therapeutic options. Here, we describe a subtype of leukemia defined by the t(14;16)(q32;q24) translocation, which places the FOXF1 gene and its antisense long noncoding RNA gene FENDRR under the regulatory control of the BCL11B enhancer, leading to their ectopic transcriptional activation. Analysis of different high-throughput sequencing data, including WGS, RNA-seq, scDNA-seq, scRNA-seq, ChIP-seq, ATAC-seq, and HiChIP-seq, identified BCL11B-enhancer mediated deregulation of FOXF1/FENDRR as a hallmark of a subtype of high-risk lineage ambiguous leukemia that is potentially amenable to targeted therapeutic intervention.

  Study EGAS50000001255

• Detection and characterization of lung cancer using cell-free DNA fragmentomes

  Lung cancer remains the leading cause of cancer death world-wide, largely due to its late diagnosis. Non-invasive approaches for assessment of cell-free DNA (cfDNA) provide an opportunity for detection and intervention that may have broader accessibility than current imaging approaches. Using a machine learning model for detecting tumor-derived cfDNA through genome-wide analyses of cfDNA fragmentation, we examined a prospective study of 365 individuals at risk for lung cancer (Lung Cancer Diagnostic Study, LUCAS), including 129 individuals ultimately diagnosed with lung cancer and 236 individuals determined to not have lung cancer. We externally validated the cancer detection model using an independent cohort of 385 non-cancer individuals and 46 predominantly early stage lung cancer patients. Combining fragmentation features with clinical risk factors and CEA levels followed by CT imaging detected 94% of patients with cancer across stages and subtypes, including 91% of stage I/II and 96% of stage III/IV, at 80% specificity. Genome-wide fragmentation profiles across ~13,000 ASCL1 transcription factor binding sites could be used to distinguish individuals with small cell lung cancer (SCLC) from those with non-small cell lung cancer (NSCLC) with high accuracy (AUC=0.98). Among individuals with lung cancer, a higher cfDNA fragmentation score was associated with tumor size and invasion, and represented an independent prognostic indicator of survival. These studies provide a facile approach for non-invasive detection of lung cancer and clinical management of this disease.

  Study EGAS00001005340

• The Natural History of Human Prostate Cancer

  Whole genome DNA sequencing was used to decrypt the phylogeny of multiple samples from distinct areas of cancer and morphologically normal tissue taken from the prostates of 3 men. For each of three different prostates, multiple tumour samples (4, 5, and 3 depending on the case) and one normal tissue sample were whole genome sequenced with a matched blood sample using the Illumiuna HiSeq platform. Tumour samples were sequenced to a target depth of 50X and normals and blood to a target depth of 30X. As of September 2020, some of the studies using these data include: Cooper et al, Nature Genetics 2015 (PMID: 25730763) Wedge et al, Nature Genetics 2018 (PMID: 29662167) Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)

  Dataset EGAD00001000689

• Single-Cell Transcriptomic Characterization of Microscopic Colitis

  Patients with microscopic colitis (MC), chronic diarrhea without histological signs of MC, or unaffected controls were profiled using single-cell RNA sequencing (scRNA-seq; inDrops and 10X Genomics were used). One profiled patient without clinical symptoms was found to have histological signs of MC (asymptomatic MC). Some of the subjects from dbGaP study phs003418 are controls in this study. T-Cell Receptor sequencing (TCR-Seq) was also performed on a subset of patients. Individual transcriptomes were analyzed to characterize the cellular profile associated with MC and search for mediators of disease pathology. Raw reads and processed count matrices will be available through dbGaP.

  Study phs003876

• Ghana Breast Health Study

  The Ghana Breast Health Study (GBHS) was a multi-disciplinary, population-based case-control study conducted in Accra and Kumasi, Ghana that was designed to investigate breast cancer etiology in the West Africa region. The study enrolled 1,126 invasive breast cancer cases and 2,106 frequency matched population-based controls using census-based sampling. GHBS participants were between the ages of 18 to 74 years of age. Breast cancer cases were recruited at the time they presented with lesions suspicious of breast cancer at three hospitals: Korle Bu Teaching Hospital (Accra), Komfo Anoyke Teaching Hospital (Kumasi) and Peace and Love Hospital (Kumasi). These hospitals are the primary providers of treatment for breast cancer in Ghana, allowing for cases in our study to represent most breast cancers diagnosed in these areas during the study period. The following publications describe the GBHS in detail: 1) Brinton LA et al. Design considerations for identifying breast cancer risk factors in a population-based study in Africa. Int J Cancer 2017;140:2667-2677 (PMID:28295287). 2) Nyante SJ et al. Recruiting population controls for case-control studies in sub-Saharan Africa: The Ghana Breast Health Study. PloS one 2019;14:e0215347 (PMID:30990841)Among subjects with an available source of germline DNA genotyping was performed using the Infinium Global Screening Array-24 per the manufacturer’s guidelines using the Infinium automated protocol. We excluded probable duplicates and close relatives, and samples with a call rate < 95% or samples with extreme heterozygosity. Female sex was verified by Identifiler using X chromosome heterozygosity and the X chromosome inbreeding coefficient F statistics. The GLU genetics’ ld.tagzilla module was used to confirm African ancestry. To resolve more detailed population substructure, principal components analysis was conducted among all unrelated subjects using the EIGENSOFT v7.2.1. Imputation was performed using the Michigan imputation server Minimac3 with 1K genomes phase3 as reference panel.

  Study phs002387

• Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses

  Background Single-cell RNA sequencing (scRNAseq) is a powerful tool for studying complex biological systems, such as tumour heterogeneity and tissue microenvironments. However, the sources of technical and biological variation in primary solid tumour tissues and patient-derived mouse xenografts for scRNAseq, are not well understood. Here, we used low temperature (6°C) protease and collagenase (37°C) to identify the transcriptional signatures associated with tissue dissociation across a diverse scRNAseq dataset comprising 128,481 cells from patient cancer tissues, patient-derived breast cancer xenografts and cancer cell lines.Results We observe substantial variation in standard quality control (QC) metrics of cell viability across conditions and tissues. From FACS sorted populations gated for cell viability, we identify a sub-population of dead cells that would pass standard data filtering practices, and quantify the extent to which their transcriptomes differ from live cells. We identify a further subpopulation of transcriptomically “dying” cells that exhibit up-regulation of MHC class I transcripts, in contrast with live and fully dead cells. From the contrast between tissue protease dissociation at 37°C or 6°C, we observe that collagenase digestion results in a stress response. We derive a core gene set of 512 heat shock and stress response genes, including FOS and JUN, induced by collagenase (37°C), which are minimized by dissociation with a cold active protease (6°C). While induction of these genes was highly conserved across all cell types, cell type-specific responses to collagenase digestion were observed in patient tissues. We observe that the yield of cancer and non-cancer cell types varies between tissues and dissociation methods.Conclusions The method and conditions of tumour dissociation influence cell yield and transcriptome state and are both tissue and cell type dependent. Interpretation of stress pathway expression differences in cancer single cell studies, including components of surface immune recognition such as MHC class I, may be especially confounded. We define a core set of 512 genes that can assist with identification of such effects in dissociated scRNA-seq experiments.

  Study EGAS00001003753

• Discovery of Non-ETS Gene Fusions in Human Prostate Cancer using Next Generation RNA Sequencing

  Half of prostate cancers harbor gene fusions between TMPRSS2 and members of the ETS transcription factor family. To date little is known about the presence of non-ETS fusion events in prostate cancer. We employed next-generation transcriptome sequencing (RNA-Seq) in order to explore the whole transcriptome of 25 human prostate cancer samples for the presence of chimeric fusion transcripts. We generated more than 1 billion sequence reads and used a novel computational approach (FusionSeq) in order to identify novel gene fusion candidates with high confidence. In total, we discovered and characterized seven new cancer-specific gene fusions, two involving the ETS genes ETV1 and ERG, and five involving non-ETS genes such as CDKN1A (p21), CD9 and IKBKB (IKK-beta), genes known to exhibit key biological roles in cellular homeostasis or assumed to be critical in tumorigenesis of other tumor entities, as well as the oncogene PIGU and the tumor suppressor gene RSRC2. The novel gene fusions are found to be of low frequency but interestingly, the non-ETS fusions were all present in prostate cancer harboring the TMPRSS2-ERG gene fusion. Future work will focus on determining if the ETS rearrangements in prostate cancer are associated or directly predispose to a rearrangement prone phenotype.

  Study phs000310

• Genomic profiling of BRCA- mutant breast cancer tumors

  This data set contains whole exome sequencing (WXS) and RNA-Seq on germline BRCA- mutant tumors from 18 patients. BAM files are provided for WXS on tumor and germline samples. FASTQ files are provided for the RNA-Seq samples. Sequencing was done on an Illumina Hi-Seq 2500.

  Dataset EGAD00001008276

• ICGC Breast Cancer Project, RNA seq

  A comprehensive characterisation and analysis of human breast cancers through genome-wide approaches through transcriptomics.

  Dataset EGAD00001001323

• Comparison of good PDX responders and bad PDX responders

  RNA-Seq raw data of untreated breast cancer xenografts known as good or bad acetalax responders.

  Dataset EGAD50000000876

• Single cell RNA sequencing of PBMC samples from CRC patients

  This data contains scRNA-seq on 14 PBMC samples from colorectal cancer patients.

  Dataset EGAD50000000841

• RNA sequencing in primary human macrophages overexpressing ETS2

  This dataset consists of RNA sequencing data from an ETS2 overexpression experiment in M0 macrophages. Controlled overexpression of ETS2 mRNA or control mRNA (an equivalent amount of mRNA encoding the reverse complement of ETS2 – thereby controlling for the quantity, length and purine/pyrimidine composition of the transfected RNA but with a transcript that would not be translated) was induced in resting, non-activated (M0) macrophages by transfecting predefined amounts of in vitro transcribed mRNA. To minimise non-specific activation due to the transfected RNA, in vitro transcription was performed using co-transcriptional capping (to minimise uncapped products), and incorporating modified, minimally immunogenic nucleotides (replacing uridine with N1-methyl-pseudouridine and cytidine with methylcytidine). After 18 hours, transfected cells were were activated with low dose LPS and harvested for RNA-sequencing 6 hours later. Sequencing libraries were prepared from 10ng RNA using the SMARTer Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian (Takara) following the manufacturer’s instructions. The quality and molarity of all libraries was assessed using a BioAnalyzer 2100 and the libraries were sequenced on a NovaSeq6000. Raw data are provided as 100 bp paired-end Illumina reads from n = 8 donors.

  Dataset EGAD00001011341

• Genomic Profiling of Pediatric Tumors by Cell Free DNA Sequencing

  BACKGROUND Analysis of cell-free DNA (cfDNA) from peripheral blood has been studied extensively for detection and monitoring therapy response in adult cancers, but utility in pediatric tumors is unclear. METHODS We studied 233 children with hematologic, solid and brain tumors. cfDNA was extracted from 1 mL of plasma collected at diagnosis. Circulating tumor DNA (ctDNA) in cfDNA was quantified and diverse classes of somatic genomic variants were detected using PeCan-Seq. PeCan-Seq findings were compared with matched tumor whole-genome and whole-exome sequencing data. Minimal residual disease (MRD) status was evaluated by cfDNA PeCan-Seq in 14 patients with B-cell acute lymphoblastic leukemia. RESULTS Plasma cfDNA yields at diagnosis were higher for hematologic malignancies than for solid and brain tumors. Patients with hematologic malignancy were 100% ctDNA-positive, the median ctDNA fraction in cfDNA was 0.77. We detected 97% variants that were present in tumors and covered by the capture panel, and 50 subclonal variants that were present in cfDNA only. Our approach enabled detection of sequence and structural variants in B-ALL ctDNA at varying levels of MRD. Nineteen of 38 patients with solid tumors were ctDNA-positive, with high prevalence in Ewing Sarcoma, liver tumors and osteosarcoma. One of 19 brain tumor patients was ct-DNA positive, indicating lack of utility for plasma-derived cfDNA in this disease. Notably, cfDNA analysis of a single plasma sample identified genomic features in ctDNA derived from B-ALL, concurrent primary neuroblastoma, and a later neuroblastoma relapse, indicating that genomic variations from multiple tumors could be detected simultaneously. CONCLUSIONS Pediatric patients with hematologic malignancy had an abundance of plasma ctDNA at diagnosis. Plasma ctDNA levels varied between different solid tumor types, more studies are needed to determine utility. Panel-based cfDNA sequencing could serve as a non-invasive approach for pediatric cancer diagnosis and disease monitoring.

  Study EGAS50000000072

• RNA-seq of longitudinal human blood and nose swab samples from a controlled human infection experiment with SARS-CoV-2 virus

  Controlled human infection experiments enable longitudinal profiling of immune responses to a pathogen. 36 healthy volunteers aged 18-29 years, with no evidence of previous infection or vaccination, were inoculated with SARS-CoV-2 virus and quarantined for 14 days. Blood samples (n=374) for RNA sequencing were collected into PAXgene tubes before virus challenge, 6 hours after challenge, daily thereafter for 14 days and on day 28. Mid-turbinate nose swabs (n=96) for RNA sequencing were collected before virus challenge, and on days 1, 3, 5, 7, 10 and 14 after challenge, preserved in RNAprotect. 18 of 36 participants developed a replicative SARS-CoV-2 infection as evidenced by consecutive PCR-positive swabs for the virus. For every participant, blood RNA from selected days were extracted and depleted for genomic DNA and globin mRNA, before cDNA libraries were constructed using KAPA RNA HyperPrep with RiboErase kits. Libraries were sequenced on the Illumina NovaSeq 6000 platform using NovaSeq 6000 S4 Reagent Kits (200 cycles). Nose swab RNA samples were extracted and depleted for genomic DNA before cDNA libraries were constructed using KAPA mRNA HyperPrep Kits. Libraries were sequenced on the Illumina NextSeq platform the using the NextSeq 500/550 High Output Kit (75 cycles).

  Dataset EGAD50000000942

• RNA-Seq analysis of cocaine use disorder in Brodmann Area 9

  We aimed to identify cocaine use disorder associated changes in gene expression in the Brodmann Area 9 subregion of the human prefrontal cortex. RNA-sequencing was performed in N=13 individuals with and N=12 individuals without CUD. The individuals are originating from a cohort of N=42 individuals where DNA methylation (DNAm) levels were previously analyzed using the EPIC array.

  Study EGAS50000000150

• RNA-Seq of human longitudinal whole blood samples from PCR-positive and PCR-negative adults following controlled inoculation with Influenza A H3N2 virus.

  Understanding of the transcriptomic profile of individuals in early influenza infection is limited. To investigate this, longitudinal whole-blood samples (n=178) were taken from adult participants following controlled inoculation with Influenza A H3N2 virus (sampling at baseline (0) and days 1, 2, 3, 7, 10 and 14 post-challenge). Most participants became influenza PCR-positive; a minority remained PCR-negative. Total RNA was extracted from PAXgene tubes before undergoing globin and rRNA depletion. DNA libraries were constructed using the NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina. All samples were then sequenced using Illumina NovaSeq 6000.

  Dataset EGAD50000000956

• CMML Collection of WES, WGS, RNA-Seq and ERRBS data

  We first performed a comprehensive analysis of the genome of 66 chronic myelomonocytic leukemia cases using whole exome (N=49) or whole genome (N=17) sequencing for paired leukemic-control DNA. Then, we realized serial analysis of whole exome sequence in 17 cases, completed with serial RNA sequencing and DNA methylation analysis in 9 cases, including patients treated or not with hypomethylating agents.

  Study EGAS00001001264

• Human normal brain single-cell

  We profiled two human fetal brainstem specimens at 17 and 19 post-conception weeks by single-cell RNA-seq using 10X Chromium Single Cell 3'. The BAM files are provided.

  Dataset EGAD00001005128

• TenK10K Phase 1: scRNA-seq AnnData objects

  Single cell RNA-sequencing data for PBMCs from the Tenk10k Phase 1 cohort (1925 individuals post-QC). Libraries were prepared using the 10x Genomics 3’ Chromium Next GEM Single Cell HT V3.1 kit and sequenced on the NovaSeq 6000 platform. Reads were mapped to the GRCh38 reference genome with Cellranger, and count matrices were preprocessed using Scanpy.

  Dataset EGAD50000002379

• RNA-seq of human iPSC-derived neurons to explore cellular phenotypes associated with schizophrenia.

  This dataset contains high-throughput RNA-sequencing of 12 samples, each sample comprising neural precursor cells derived from human induced pluripotent stem cells from individuals with and without the 16p13.11 microduplication (a copy number variant associated with a range of neurodevelopmental disorders). 4 samples derive from patients carrying the 16p13.11 microduplication, and 8 derive from unaffected family controls. RNA samples were processed to deplete rRNA using the TruSeq Stranded Total RNA with Ribo-Gold kit. Libraries were then sequenced using the NextSeq 500/550 High-Output v2 Kit on the Illumina NextSeq 550 platform, to produce 75 base pair paired-end sequencing reads at an average depth of around 100 million reads per sample. Raw sequencing reads data are stored in two FASTQ files per sample for these paired-end reads.

  Dataset EGAD00001004064

• Cell type-specific transcriptomics of esophageal adenocarcinoma

  3' mRNA-Seq obtained from distinct isolated cell types (epithelia cells,immune cells, fibroblasts) of endoscopically obtained esophageal adenocarcinoma tissue as well as normal esophageal mucosa. Libraries for RNA-sequencing were prepared using the QuantSeq 3' mRNA-Seq Library Prep Kit FWD for Illumina according to the low input protocol. Libraries were sequenced on a HiSeq 4000 (Illumina) by 1x 50 bases.

  Dataset EGAD00001005508

• MethylBERT enables read-level DNA methylation pattern identification and tumour deconvolution using a Transformer-based model

  DNA methylation (DNAm) is a key epigenetic mark that shows profound alterations in cancer. Read-level methylomes enable more in-depth DNAm analysis due to the broad coverage and preservation of rare cell-type signals, compared to array-based data such as 450K/EPIC array. Here, we propose MethylBERT, a novel Transformer-based model for read-level methylation pattern classification. MethylBERT identifies tumour-derived sequence reads based on their methylation patterns and genomic sequence and the method estimates tumour cell fractions within bulk samples. In our evaluation, MethylBERT outperforms existing deconvolution methods and demonstrates high accuracy regardless of methylation pattern complexity, read length and read coverage. Moreover, we show its applicability to cell-type deconvolution as well as non-invasive early cancer diagnostics using liquid biopsy samples. MethylBERT represents a significant advancement in read-level methylome analysis and enables accurate tumour purity estimation. The broad applicability of MethylBERT will enhance studies on both tumour and non-cancerous bulk methylomes.

  Study EGAS50000000806

• Natural variation of circulating RNAs in human serum

  The Janus Serum Bank (JSB) is a population-based cancer research biobank. This dataset contains small RNA sequencing (RNA-seq) data of 520 JSB samples from cancer-free individuals. Sequencing libraries were indexed and 12 samples were sequenced per lane on a HiSeq 2500 (Illumina) to an average depth of 18 million reads per sample. The dataset files are raw FASTQ files from the sequencing machine (50bp, single-end sequencing)

  Dataset EGAD00001003968

• Systematic comparative analysis of single-nucleotide variant detection methods from single-cell RNA sequencing data

  In this study, we performed systematic comparative analysis of seven widely-used SNV-calling methods, including SAMtools, the GATK Best Practices pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, on both simulated and real single-cell RNA-seq datasets. We generated SMART-seq2 data for 70 CD45- single cells, which were derived from two colorectal cancer patients (P0411 and P0413). The average sequencing depths of these cells were 1.4 million reads per cell. We also generated tumor and adjacent normal bulk WES data, as well as tumor bulk RNA-seq data for these patients.

  Dataset EGAD00001005373

• Single-cell RNA-seq of immune cells from human tumor fragments after 48 hour culture ex vivo (Kaptein et al., 2024)

  Single-cell RNA-seq profiling of immune cells from human ovarian carcinoma, renal carcinoma and melanoma samples after 48h of ex vivo culture using the patient-derived tumor fragment platform (5 samples total). Samples were cultured in various conditions, including: untreated, CD8-IL2v-treated, CD8-IL2v + LCKi -treated, aPD1-treated, CD8-IL2v + aPD1 -treated, Untargeted IL2-treated, aCD3-treated and aCD3 + CD8-IL2-treated . FASTQ files contain gene expression data, feature barcode antibody capture or TCR data on immune cells from all conditions combined per patient.

  Dataset EGAD50000000377

• Finding structural variation from the human skin fibroblast at the single-cell level

  Somatic structural variants (SVs) are widespread in cancer, but their impact on disease evolution is understudied due to a lack of methods to directly characterize their molecular consequences. We present a computational method, scNOVA, that integrates haplotype-resolved SV discovery with nucleosome occupancy analysis using Strand-seq, to functionally characterize SVs in single cells.

  Study EGAS00001006498

• Multimodal Epigenetic Sequencing Analysis (MESA) of Cell-free DNA for Non-invasive Cancer Detection

  Multimodal characterization of cell-free DNA (cfDNA) in the blood can enable the sensitive and non-invasive detection of human cancers but remains technically challenging and costly. Here, we developed Multimodal Epigenetic Sequencing Analysis (MESA), a flexible and sensitive method of capturing and integrating multimodal epigenetic information of cfDNA using a single experimental assay, i.e., non-disruptive bisulfite-free methylation sequencing, such as Enzymatic Methyl-seq (EM-seq) and TET-assisted pyridine borane sequencing (TAPS). MESA can simultaneously infer cfDNA methylation, nucleosome occupancy, nucleosome fuzziness, and fragmentation profile for regions surrounding the promoters and polyadenylation sites (PASs). MESA’s integrated analysis of multimodal epigenetic features significantly improved the performance of cancer detection models compared to the usage of any single modality alone. MESA captures additional and highly complementary epigenetic information from cfDNA without additional experimental assays, highlighting the importance and clinical prospect of using multimodal epigenetic features for non-invasive cancer detection

  Study EGAS00001006462

• Transdisciplinary Research Into Cancer of the Lung (TRICL) - Exome Plus Targeted Sequencing

  The study was conducted under the auspices of the Transdisciplinary Research In Cancer of the Lung (TRICL) Research Team, which is a part of the Genetic Associations and MEchanisms in ONcology (GAME-ON) consortium, and associated with the International Lung Cancer Consortium (ILCCO). Ethics All participants provided written informed consent. All studies were reviewed and approved by institutional ethics review committees at the involved institutions. Sequencing data are derived from four sub-studies. The sub-studies that contributed include Harvard, Liverpool, Toronto, and IARC. The IARC and Toronto studies are described above. A description of the Harvard and Liverpool studies is provided below. Liverpool Lung Project: The Liverpool Lung Project (LLP)1 is a case control and cohort study, which has over 11,500 individuals, with detailed epidemiological, clinical and outcome data with associated specimens (i.e. tumour tissue, blood, plasma, sputum, bronchial lavage, EBUS and oral brushings). The participants have completed a detailed lifestyle questionnaire and updated data on clinical outcome and hospital events are collected through the Office of National Statistics, Cancer Registry and from Health Episode Statistics. The project is registered on the UK National Institute for Health Research (NIHR) lung cancer portfolio and has all the required ethical approvals and sponsorship arrangements in place. The LLP has detailed standard operating procedures (SOP) for all aspects of the recruitment, data, specimen collection as well as the data storage. The LLP Cohort study has 8,224 participants with blood and 7,761 with plasma samples. The LLP case-control samples have been incorporated into in a large number of international GWAS and molecular studies 2,3, methylation 4-7, microRNA 8and next generation studies 9-11, resulting in high ranking publications, as well as forming the basis for the LLP risk prediction model 12-14 which has been utilised in the UK lung cancer screening trial (UKLS) 15-17 Patient and control DNAs were derived from EDTA-venous blood samples. Harvard Samples. David Christiani at the Harvard University School of Public Health has been directing research studies to investigate etiological factors influencing lung cancer development since 1983 and has amassed a collection of 2000 controls and 5055 lung cancer cases. He has been actively collecting and storing snap frozen tumor samples since 1992. Around 1500 tumor samples have been collected and the average wet tumor yield is about 30 grams of tumor, of which 631 cases have completely annotated clinical and survival information. Pathology confirmation is provided by two pathologists. At the time of surgery, a minimum of 30 grams of wet lung tumor tissue and 30 grams of non-involved tissue from the same lobe is sectioned, flash frozen and sent to Dr. Christiani's lab for logging and storage. A blood sample for DNA and serum is collected. A structured interview by trained research staff is conducted on each case, and clinical outcomes and treatments is extracted and entered into the molecular epidemiology data base at Harvard. Fresh frozen samples have been collected from 1451 lung cancer and are available for study. Samples from this collaborative study have played key roles in major studies, including the initial finding describing EGFR mutations in lung cancer 22. Participants in this study are patients, > 18 years of age, with newly diagnosed histologically confirmed lung cancer. Samples that are included in the analysis have the following histologies: Adenocarcinoma: 8140/3, 8250/3, 8260/3, 8310/3, 8480/3 8560/3; LCC: 8012/3, 8031/3; squamous carcinoma: 8070/3, 8071/3, 8072/3, 8074/3; and other NSCLC: 8010/3, 8020/3, 8021/3, 8032/3, 8230/3. The Toronto Study: The Toronto study was conducted in the Great Toronto Area between 1997 and 2014. Cases were recruited at the hospitals in the network of University of Toronto and Lunenfeld- Tanenbaum Research Institute. At the time of recruitment in the clinical setting, provisional diagnoses of lung carcinoma were first assigned based on clinical criteria. Diagnoses for all cases included were histologically confirmed by the reference pathologist who is a specialist in pulmonary pathology, based on review of pathology reports from surgery, biopsy or cytology samples in 100% of cases. Diagnostic classification was done initially according to ICD-9, ICD-10, and ICD for oncology-2, and subsequently converted to ICD-O-3. Tumors were grouped into the major categories included in this analysis according to primary cancer type based on the ICD-3 definitions. Controls were randomly selected from individual visiting family medicine clinics and Ministry of Finance Municipal Tax Tapes. All subjects were interviewed using a standard questionnaire and information on lifestyle risk factors, occupational history, medical and family history was collected. Blood samples were collected from more than 85% of the subjects. IARC: The IARC data are derived from case-control studies conducted in Russia and include samples that have available tissue samples. Patient and control DNAs were derived from EDTA-venous blood samples. The lung cancer patients were classified according to ICD-O-3; SQ: 8070/3, 8071/3, 8072/3, 8074/3; AD: 8140/3, 8250/3, 8260/3, 8310/3, 8480/3, 8560/3, 8251/3, 8490/3, 8570/3, 8574/3; with tumous with overlapping histologies classified as mixed. The Lung Cancer Transdisciplinary Research Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" section of this top-level study page phs000876 Lung Cancer Transdisciplinary Research Cohort. phs000877 Meta Analysis phs000878 CIDR Lung Cancer phs001681 Affy Axiom Array

  Study phs000876

• Semibulk RNA-seq analysis as a convenient method for measuring gene expression statuses in a local cellular environment

  For two cases of breast cancers, semibulk RNA-seq and single cell RNA-seq were performed.

  Study JGAS000387

• Genome and transcriptome sequencing of cancer of unknown primary tumours

  Genome and transcriptome sequencing of cancer of unknown primary tumours was used to determine yield of clinical biomarkers for a molecular guided trial or for resolving cancer type of origin. This study includes profiling of germline DNA and tumour DNA by whole genome sequencing of tissue and cfDNA biopsies, as well as targeted genome sequencing using two panels, including Comprehensive cancer panel (CCP) and TruSight Oncology 500 (TSO500). This study also includes profiling of tumour RNA by whole transcriptome sequencing.

  Study EGAS50000000452

• Dataset for synovial_sarcoma-RNA

  Rare cancer sequencing data of 23 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008844

• Spatial heterogeneity, stromal phenotypes, and therapeutic vulnerabilities in colorectal cancer peritoneal metastasis

  Peritoneal metastases (PM) in colorectal cancer (CRC) portend a poor prognosis. We sought to elucidate molecular features differentiating primary tumors (PTs) from PMs and actionable targets facilitating transcoelomic dissemination and progression. We performed multi-omic profiling of 217 samples from 136 patients, including 56 primary tumor (PT) and 120 PMs comprising 25 matched PT-PM pairs. Whole exome, and bulk RNA-seq analysis was conducted to identify underlying genomic aberrations and transcriptomic differences between primary and peritoneal lesions.

  Study EGAS50000000813

• Epigenetic profiling of colorectal cancer initiating cells (CC-ICs) to identify bivalently marked genes (H3K4me3 and H3K27me3 ChIP-seq), and investigation of changes in transcriptome following EZH2 inhibition using RNA-seq.

  Epigenetic regulation of transcription plays a crucial role in lineage commitment of embryonic stem cells. Promoters of key lineage-specific differentiation genes are found in a repressed bivalent state, having both activating H3K4me3 and repressive H3K27me3 histone marks, making them poised for transcription upon loss of H3K27me3 in response to environmental cues. Whether the tumour-initiating, self-renewing, cancer-initiating cells (C-ICs) have similar epigenetic regulatory mechanism that prevent lineage commitment is unknown. In order to investigate bivalently marked and repressed promoters, we used a patient-derived CC-IC enriched model to identify the changes in transcriptome following inhibition of EZH2, the H3K27 methyltransferase. We also performed ChIP-seq for H3K27me3 and H3K4me3 at baseline in order to identify repressed and bivalently marked promoters.

  Study EGAS00001003003

• Diversity of U1 small nuclear RNAs and Evaluation of Diagnostic Methods for their Mutations

  U1 small nuclear RNA (snRNA) mutations are recurrent non-coding alterations found in various malignancies, including medulloblastoma, yet their identification has proven challenging due to their repetitive nature. To establish a robust DNA-based, and RNA-based method for detecting U1 snRNA mutations, we performed targeted DNA sequencing using our original gene panel for medulloblastoma and RNA-sequencing. As an RNA-based method, we developed a random forest classifier employing splicing patterns which were massively altered as a result of U1 snRNA mutations. By using both methods, we successfully detected U1 snRNA mutation in five DNA samples and four RNA samples.

  Study EGAS50000000693

• Single cell RNAseq and TCRseq data from tumor and blood samples from 4 patients with muscle invasive bladder cancer

  For this dataset we performed single cell RNAseq paired with single cell TCR-seq on tumor and blood samples from 4 patients. This dataset contains 4 tumor samples as well as 4 blood samples. Each sample is made up of 2 sets of paired fastq files. The first pair contains reads corresponding to RNA transcripts (_Transcripts in file name), while the second pair contain reads corresponding to TCRs (_VDJ in file name). Sequenced on the Illumina NovaSeq6000 platform in a paired-end run using an SP flow cell (v1.5, 300 cycles).

  Dataset EGAD50000001381

• Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in HGSOC

  Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Long-read single-cell RNA sequencing (scRNA-seq), capturing full-length transcripts, lacked the depth to provide this information so far. Here, we increased the PacBio sequencing depth to 12,000 reads per cell, leveraging multiple strategies, including artifact removal and transcript concatenation, and applied the technology to samples from three human ovarian cancer patients. Our approach captured 152,000 isoforms, of which over 52,000 were novel, detected cell type- and cell-specific isoform usage, and revealed differential isoform expression in tumor and mesothelial cells. Furthermore, we identified gene fusions, including a novel scDNA sequencing-validated IGF2BP2::TESPA1 fusion, which was misclassified as high TESPA1 expression in matched short-read data, and called somatic and germline mutations, confirming targeted NGS cancer gene panel results. With multiple new opportunities, especially for cancer biology, we envision long-read scRNA-seq to become increasingly relevant in oncology and personalized medicine.

  Study EGAS00001006807

• The Mood and Methylation Study (MMS)

  The Mood Methylation Study (MMS) is an observational study designed to understand epigenetic mechanisms underlying major depression symptoms (MDD) using a co-twin control design. Twins enrolled in the MMS were monozygotic (MZ) twin pairs discordant on lifetime history of MDD. All twins were members of the Washington State Twin Registry (WSTR), a community-based twin registry consisting of over 10,000 twin pairs. Lifetime and current MDD diagnoses were determined using the Structured Clinical Interview for DSM-IV Research Version (SCID-4-RV). DNA methylation in blood monocytes was measured using the Infinium HumanMethylationEPIC BeadChip. Monocyte gene expression was quantified by paired end RNA-seq (50 PE). Zygosity of the twin pairs included in the MMS was self-reported and confirmed using the polymorphic SNPs included in the DNA methylation array.

  Study phs002858

• Comprehensive Genomic Data Deposition for Pancreatic Cancer Precision Medicine Studies: Clinical Trials NCT02451982 and NCT02648282

  This submission includes specimens from 89 pancreatic cancer patients at Johns Hopkins Hospital, comprising 41 surgically resectable and 48 locally advanced pancreatic cancer (LAPC) cases. These samples originate from two clinical studies, NCT02451982 and NCT02648282, following the Johns Hopkins Medical Institution Institutional Review Board-approved registry protocol at the Pancreatic Cancer Precision Medicine Center of Excellence Program. Written consent for specimen use, obtained from participants in the original studies, covers additional research, including this one. Biopsy specimens collected through endoscopic ultrasound-guided fine needle core biopsies or surgically resected tumors are included. NCT02451982 is a platform trial evaluating immunotherapy combinations for surgically resectable pancreatic ductal adenocarcinoma in the neo-adjuvant and adjuvant settings. It investigates the GVAX pancreatic cancer vaccine with immune-boosting cyclophosphamide, exploring immune cell trafficking and the impact of PD-1 blocking. NCT02648282 focuses on the efficacy and safety of combining cyclophosphamide, pembrolizumab, GVAX, and stereotactic body radiotherapy (SBRT) in locally advanced pancreatic cancer, with an emphasis on anti-tumor activity. Both studies provide valuable insights into innovative pancreatic cancer treatment approaches.

  Study phs003600

• De novo modeling of chromoplectic Ewing sarcoma tumors from patient-derived mesenchymal stem cells

  Ewing sarcoma is characterized by pathognomonic translocations fusing most frequently EWSR1 with FLI1 (EF1). In addition, Ewing sarcoma can also display alterations in STAG2, TP53 and CDKN2A (SPC). Starting from Ewing sarcoma derived human mesenchymal stem cells (MSCpat), we recapitulated this translocation and SPC alterations using a CRISPR/cas9 approach and generated a bona fide Ewing sarcoma model (EWIma1) displaying transcriptomic (RNA-seq) and epigenetic (ChIP-seq) hallmarks of EwS.

  Dataset EGAD50000001673

• Single-cell RNA sequencing dissects gene-environment interactions on gene expression and regulation in immune cells.

  This study aims to dissect gene-environment interactions on gene expression and regulation in immune cells using scRNA-seq data from 120 donors being stimulated with 3 pathogens, for 2 different timepoints. More specifically, we identified context- and cell-type-specific eQTLs and co-expression QTLs in PBMCs.

  Study EGAS00001005376

• DNTR sequencing data of paediatric acute lymphoblastic leukemia

  This study used the DNTR-seq method in leukaemia samples to profile the whole-genome and mRNA jointly in single cells. Direct tagmentation is used in a collection of single-cell whole genome sequencing (scWGS) methods, including DNTR-seq, which provide high quality data at ultra-low to low coverage. The overall goal was to characterize the genetic and transcriptional heterogeneity of cancer samples. To infer clonal structure and evolutionary history, copy number analysis based workflows were implemented. Bone marrow mononuclear cells from pediatric acute lymphoblastic leukemia samples were FACS sorted into 384 plates to generate the DNA and RNA profiles.

  Study EGAS50000001247

• The Normal Human Tissue Sequencing Project: Non-Diseased, Non-Malignant Tissues

  The Normal Human Tissue Sequencing Project provides RNA expression and DNA methylation data from normal (non-diseased) human tissues. This data set from a variety of source tissue is a valuable resource for human disease studies.

  Study phs000819

• Comprehensive molecular and clinicopathological profiling of desmoid tumors

  Previous studies have not clearly identified a prognostic factor for desmoid tumors (DT). Whole-exome sequencing and/or RNA sequencing were performed in 64 cases of DT to investigate the molecular profiles in combination with the clinicopathological characteristics.

  Study JGAS000270

• T cell and Antibody Responses in Rituximab-Treated Lymphoma Patients After SARS-CoV-2 Vaccination

  This dataset contains T cell receptor (TCR) sequencing data from 51 RNA samples, each processed into three independent libraries (tot 153 FASTQ files). Sequencing was performed on an Illumina NextSeq 500 platform using the NextSeq 500/550 Mid Output Kit v2.5 (300 Cycles), generating paired-end FASTQ files with dual 10 bp barcodes and 5% PhiX as internal control. Libraries were quantified with the Qubit HS dsDNA kit and assessed for fragment size distribution using the Agilent Tapestation D1000 system before isochoric pooling to 4 nM and sequencing in two independent runs. The resulting dataset enables analysis of TCR β-chain CDR3 sequences for clonal expansion and diversity studies.

  Dataset EGAD50000001714

• Metabolic Biomarkers in Thoracic Cancers

  Here we present RNA sequencing (RNA-Seq) of non-small cell lung cancer (NSCLC) and adjacent lung tissue. These samples were acquired from primarily untreated, surgically resected primary tumors. The first analysis published with this data was to determine the metabolic signatures between primary tumors and adjacent lung tissue.The associated clinical trial (NCT02095808) includes patients with many kinds of thoracic cancers, including NSCLC and other diseases, such as thymoma and esophageal adenocarcinoma. However, the current dbGaP data is focused on the NSCLCs described in the associated paper.

  Study phs003880

• Single nuclei RNA-Seq from 5 regions of the human fetal brain

  Data generated through single nuclei RNA sequencing on 5 regions of the brain (frontal cortex, ganglionic eminence, hippocampus, thalamus and cerebellum) from 3 fetuses (two of 14 and one of 15 post-conception weeks, all female). Tissue was acquired from the MRC-Wellcome Trust Human Developmental Biology Resource (HDBR) with ethical approval. snRNA-seq libraries were prepared from ∼10,000 nuclei from each sample using Chromium Single Cell 3ʹ (v3) reagents (10X Genomics). Quality control of libraries was performed using the Agilent 5200 Fragment Analyzer before sequencing on an Illumina NovaSeq 6000 to a depth of at least 865 million (median = 1.01 billion) read pairs per library. Raw sequencing data were converted into FASTQ files. For a full description of data generation, please see Cameron et al, Biological Psychiatry 2022, https://doi.org/10.1016/j.biopsych.2022.06.033.

  Dataset EGAD00001009303

• Single-cell RNA-sequencing reveals that glioblastoma recapitulates a normal neurodevetlopmental hierarchy

  We discovered a conserved neural tri- lineage cancer hierarchy centered around glial progenitor-like cells. We also found that this progenitor population contains the majority of the cancer’s cycling cells, and, using RNA velocity, is often the originator of the other cell types. Finally, we show that this hierarchal map can be used to identify therapeutic targets specific to progenitor cancer stem cells. Our analyses show that normal brain development reconciles glioblastoma development, suggests a possible origin for glioblastoma hierarchy, and helps to identify cancer stem cell-specific targets.

  Study EGAS00001004422

• Molecular Characterization of Prostate Cancer Specimens by Bulk and Single Cell Analysis

  Version 1: We performed single-cell RNA-sequencing (scRNA-seq) of fresh biopsies from metastatic castration resistant prostate cancer. Additionally, where available, we performed matched bulk whole exome sequencing (WXS; tumor and normal paired) and whole transcriptome sequencing for the same individuals. We also performed bulk whole exome (WXS) and RNA-sequencing (RNA-Seq) from FFPE pre-treatment biopsies from patients with clinically localized high-risk prostate cancer.Version 2: We added data from a randomized phase 2 trial of radium-223 with or without pembrolizumab in patients with Metastatic Castration-Resistant Prostate Cancer (mCRPC) to bone. After enrollment, study participants underwent bone biopsy and were randomized 2:1 to receive radium-223 at 55 kBq/kg every 4 weeks + pembrolizumab at 200 mg every 3 weeks (Arm A, R223+P) or radium-223 at 55 kBq/kg every 4 weeks alone (Arm B, R223). Stratification factors were alkaline phosphatase ≥220 vs. Data generated includes bulk whole exome sequencing (WXS), ultra-low pass whole genome sequencing (WGS) at 0.1X coverage, and targeted-capture sequencing. The ultra-low pass sequencing was used as part of the selection criteria for the target capture sequencing. Note: Two subjects in this study are linked to phs001577 and phs000915 respectively.

  Study phs001988

• The evolutionary dynamics of human colorectal cancer using single-gland spatial multi-omic profiling of DNA, RNA and chromatin.

  Deciphering the mechanisms of colorectal cancer growth, progression and dissemination in each individual patient.

  Study EGAS00001005230

• BrainSpan Atlas of the Human Brain

  The NIH-funded BrainSpan (www.brainspan.org) and PsychENCODE (www.psychencode.org). Consortia sought to generate and analyze multi-dimensional genomics data from the developing and adult human brain in healthy and disease states. One of the main goals has been to perform large-scale and integrated analysis of the genome, transcriptome, and epigenome of the human brain to broaden our understanding of human neurodevelopment. This dataset consists of sixteen regions, including eleven neocortical areas, of human donors of both sexes and various ethnic groups. In the first stage of this project, we provide the genome-wide exon-level transcriptome data generated using the Affymetrix GeneChip Human Exon 1.0 ST Arrays, and the genome-wide genotyping data for 2.5 million markers using the Illumina Human Omni 2.5-Quad Bead Chips. In the second stage of this project, we provide whole-genome sequencing data, transcriptome data by mRNA-Seq, small RNA data by smRNA-seq, DNA cytosine methylation by Infinium HumanMethylation450 BeadChip, and epigenomic/epigenetic data by ChIP-Seq for H3K4me3, H3K27me3, H3K27ac and CTCF.

  Study phs000755

• miRNAseq of paired FL and tFL samples

  This dataset contains miRNA-seq of paired FL and tFL samples (n=10 pairs) sequenced by Illumina NextSeq500. Libraries used in this miRNA-seq dataset were prepared with NEBNext Multiplex Small RNA Library Prep Set for Illumina (NEB,Catalog number: E7560S). RNAs used for library preparation were isolated from FFPE tissues using High Pure miRNA Isolation Kit (Roche,Catalog number: 05080576001). Data are uploaded as FASTQ format.

  Dataset EGAD50000001385

• 10Xchromium 3' RNA-seq of 21 samples from human embryonic heart

  21 samples were taken from human embryonic heart of PCW 5.5-14 of a total of 13 fetuses. Samples were subject to 10Xgenomics chromium single cell 3' sequencing version 2 or 3. Data was analyzed using STARSolo version 2.7.10a, using human genome GRCh38.p12 and transcript annotations from ENSEMBL release 93 from reference package GRCh38-3.0.0 as available from 10Xgenomics.

  Dataset EGAD50000001499

• Cellular composition of spheres derived from lymph nodes of lung cancer patients

  To decipher the cell type composition within single spheres we performed RNA-Seq of 25 selected spheres of 4 different categories (including 8 signature-/balanced, 9 signature+/balanced, 1 signature-/aberrant, 7 signature+/aberrant). To track the individual cell types within single spheres we performed deconvolution analysis.

  Study EGAS00001007369

• National Cancer Institute Genome-Wide Association Study of Renal Cell Carcinoma

  The National Cancer Institute (NCI) genome-wide association study (GWAS) of renal cell carcinoma (RCC) was conducted to investigate common genetic variants associated with RCC risk. The GWAS includes 1,453 RCC cases and 3,531 controls of European background from 4 studies (3 cohort, 1 case-control), scanned using the Illumina InfiniumHumanHap 550, 610 and 660W chips. This project was supported by the Intramural Research Program of the National Institutes of Health and NCI. Data from this GWAS were pooled with those from another GWAS of RCC (2,639 cases and 5,392 controls) conducted in Europe by the International Agency for Research on Cancer and the Centre National de Gènotypage. Findings from this collaboration are described in an upcoming report (Purdue et al. Nature Genetics 2011;43(1):60-65; PMID: 21131975). Only data from the NCI scan are included in this dbGaP submission.

  Study phs000351

• Application of high-throughput, high-depth, targeted single-nucleus DNA sequencing in pancreatic cancer

  Despite insights gained by bulk DNA sequencing of cancer it remains challenging to resolve the admixture of normal and tumor cells, and/or of distinct tumor subclones; high throughput single-cell DNA sequencing circumvents these and brings cancer genomic studies to higher resolution. However, its application has been limited to liquid tumors or a small batch of solid tumors, mainly because of the lack of a scalable workflow to process solid tumor samples. Here we optimized a highly automated nuclei extraction workflow that achieved fast and reliable targeted single-nucleus DNA library preparation of 38 samples from 16 pancreatic ductal adenocarcinoma (PDAC) patients, with an average library yield per sample of 2867 single nuclei. We demonstrate that this workflow not only performs well using low cellularity or low tumor purity samples but reveals novel genomic evolution patterns of PDAC as well.

  Study EGAS00001006024

• Genome-wide expression profiles to compare array-based, RNAseq and NanoString technologies in patients with resected pancreatic ductal carcinoma.

  Using formalin-fixed paraffin embedded (FFPE) tissues collected prospectively in patients with resected pancreatic ductal carcinoma (PDC) we generated genome-wide expression profiles to compare array-based, RNAseq and NanoString technologies. Samples included in the study were collected 17 patients. After careful selection by the pathologist of 17 malignant cells-enriched, 7 stroma-enriched, and 6 normal (normal pancreas in 4 cases and normal duodenum in 2 cases) regions, sections were macrodissected, and total RNA extracted. Two additional FFPE-frozen matched-paired PDAC from our local Biobank were included. Our study represents the most extensive work comparing three technologies to generate gene expression profiles from FFPE samples, and provides technical guidance for future biomarker studies in samples collected prospectively in the context of clinical trials.

  Study EGAS00001002501

• Rio Dataset

  Homologous recombination DNA repair deficiency and PARP inhibition activity in primary triple negative breast cancer. RNA-Seq data for paired baseline and end of treatment samples

  Dataset EGAD00001006120

• Bladder cancer subtyping study across 4 atezo clinical trials

  Checkpoint inhibitors targeting the PD-1/PD-L1 interaction have revolutionized cancer therapy across many indications. In urothelial carcinoma (UC), several PD-1/PD-L1 inhibitors have been approved for treatment in localized and metastatic disease. While these agents provide durable clinical benefit in a number of patients, the majority do not respond. A better understanding of the molecular mechanisms underlying response and resistance is needed to tailor existing treatments and develop new therapeutics in UC. We profiled tumors from 2803 patients from four late-stage randomized clinical trials evaluating the PD-L1 inhibitor atezolizumab in metastatic UC and muscle-invasive bladder cancer by RNA-seq, a targeted DNA panel, immunohistochemistry, and digital pathology. A machine learning algorithm identified four UC transcriptional subtypes, representing luminal desert, stromal, immune, and basal tumors. Overall survival benefit from atezolizumab over standard-of-care was observed in immune and basal tumors (45% of patients). Digital pathology showed enrichment of human interpretable features in specific molecular subtypes, and a self-supervised approach could classify molecular subtypes from H&E slides with high accuracy, suggesting that machine-based image interpretation could accelerate tumor molecular profiling. Somatic alterations showed limited capacity to identify responders. Finally, mechanisms of benefit with PD-L1 blockade appeared different in immune and basal tumors, with immune tumors benefiting from B/plasma cell enrichment, while basal tumors benefited from granulocyte enrichment. This study represents the largest integration of UC molecular and curated clinical data in randomized clinical trials to date, paving the way for prospective clinical studies tailoring treatment regimens to specific tumor molecular subtypes in UC and other indications.

  Study EGAS50000000497

• A New High-Throughput Sequencing-Based Technology to Study Heterochromatin Structure

  In this study we report epigenomic and transcriptomics datasets for normal control fibroblasts. The following cell lines were obtained from the NIGMS Human Genetic Cell Repository at the Coriell Institute for Medical Research: AG08498, AG07095, originally collected as part of the NIA Aging Cell Repository study. We applied a high-throughput sequencing-based technique, named Sequential Analysis of MacroMolecules accessibilitY (SAMMY-seq), for the genome-wide mapping of chromatin regions separated by differential accessibility. The method is based on the sequential extraction of multiple chromatin fractions, corresponding to increasingly compacted and less accessible chromatin regions, which are mapped along the genome using high-throughput sequencing. Additionally we carried out ChIP-seq for the H3K9me3 and H3K27me3 histone modifications and RNA-seq for the characterization of transcriptome in control fibroblasts.

  Study phs002202

• Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer

  Inhibitors of the programmed cell death-1 (PD-1/PD-L1) signaling axis are approved to treat non-small cell lung cancer (NSCLC) patients, based on their significant overall survival (OS) benefit. Using transcriptomic analysis of 891 NSCLC tumors from patients treated with either the PD-L1 inhibitor atezolizumab or chemotherapy from two large randomized clinical trials, we found a significant B cell association with extended OS with PD-L1 blockade, independent of CD8+ T cell signals. We then derived gene signatures corresponding to the dominant B cell subsets present in NSCLC from single-cell RNA-seq data. Importantly, we found increased plasma cell signatures to be predictive of OS in patients treated with atezolizumab, but not chemotherapy. B cells were also associated with the presence of tertiary lymphoid structures and organized lymphoid aggregates. Our results suggest an important contribution of B and plasma cells to PD-L1 blockade efficacy in NSCLC.

  Study EGAS00001005013

• BCAC TIIC Data

  Data on spatially-resolved tissue infiltrating immune cells (TIICs) from 17,265 breast cancer patients of European descent, from studies participating in the Breast Cancer Association Consortium, together with linked clinical data.

  Study EGAS50000001477

• GBM-ZEB1: RNA sequencing of parental tumors used for cell line generation

  This dataset contains RNA sequencing raw data from four parental tumors that were used for classification of gene expression subtypes (Verhaak, Cancer Cell 2010) using ssGSEA.

  Dataset EGAD00001001627