11754 results for "cancer rna-seq"

in 30.16 milliseconds.

• Comprehensive Deep Sequencing Atlas in HCC tumors

  Establishment of a comprehensive deep sequencing atlas focused on Hepatocellular Carcinoma (HCC) tumors, employing Whole Genome Sequencing (WGS), RNA Sequencing (RNAseq), and Whole Exome Sequencing (WES). The atlas aims to unravel the intricate genetic landscape of HCC, providing a detailed characterization of genomic alterations, transcriptomic profiles, and key mutations associated with this liver cancer. The integration of WGS, RNAseq, and WES data offers a holistic perspective, facilitating a deeper understanding of the molecular mechanisms driving HCC pathogenesis. The resulting atlas serves as a valuable resource for researchers, clinicians, and the broader scientific community, contributing to advancements in HCC diagnostics, prognostics, and therapeutic interventions.

  Study EGAS00001007694

• Comprehensive molecular portrait reveals genetic diversity and distinct molecular subtypes of small intestinal neuroendocrine tumors

  This study aims to characterize neuroendocrine tumors of the small intestine (siNETs) from genomic, transcriptomic, epigenomic, and clinical perspectives. Involving 122 patients and 219 samples, we generated whole-genome sequencing data, RNA sequencing data, genotyping arrays, and methylation arrays to conduct an integrative analysis of this rare tumor type. Our findings identify distinct molecular subtypes that correlate with siNET clinical features.

  Study EGAS50000000642

• Single-cell RNA sequencing on 11,138 single T cells from 12 colon and rectal cancer (CRC) patients

  Deep single-cell RNA sequencing data for 11,138 T cells from tumour, adjacent normal tissue and peripheral blood of treatment-naive CRC patients. The DATA ACCESS AGREEMENT is provided at https://github.com/zhangyybio/single-T-cell-data-access. Applicants can request access to the data by directly downloading it or by sending an email to cancerpku@pku.edu.cn. The process that is used to approve an application includes verifying the institution, participants and research purposes of the application. In general this process will take about two weeks. In principal, any academic research institutions complying with the laws and bioethic regulation policies of China will be approved.

  Dataset EGAD00001003910

• Whole exome and RNA sequencing data from urothelial bladder cancer patients treated with anti-PD-(L)1

  We have generated and analyzed genomic data from a cohort of metastatic urothelial carcinoma patients treated with ICI such as anti-PD-(L)1 monoclonal antibodies. The dataset contains whole exome sequencing data of 27 whole blood samples and 27 FFPE tumor samples. Further, it includes RNA sequencing data from 21 tumor samples. Following the RECIST criteria, 10 patients were classified as non-responders to the treatment, and 17 were responders. The dataset also contains a merged vcf file containing somatic mutations called by Strelka2 and Mutect2 following the gatk best practice pipeline.

  Dataset EGAD00001010324

• WES of precancerous lesions from 10 lynch patients and 3 sporadics

  Raw sequencing data of WES that were obtained from precancerous samples as adenoma and MMR-deficient crypts and paired healthy tissue from MSI CRC patients of which 10 are diagnosed with lynch syndrome and 3 had sporadic cancer. These data were analyzed in order to evaluate microsatellite instability though tumorigenesis and associated to splicing deregulation in MSI tumors RNA.

  Dataset EGAD50000000644

• Characterization of four subtypes in morphologically normal tissue excised proximal and distal to breast cancer

  RNA sequencing data from breast cancers (n=18) and their matched HN tissues (n=36), healthy breast from cosmetic reduction mammoplasty (RM; n=5), and risk reducing mastectomies (RR, n=5), with peritumoral samples excised proximal to (TP, less than 2 cm) and distal from (TD, 5-10 cm) the primary tumor.

  Dataset EGAD00001006291

• lymphoma plasma cfRNA

  Dataset contains total RNA sequencing data from plasma of 65 different human donors: 30 diffuse large B-cell lymphoma (DLBCL) and 13 primary mediastinal large B-cell lymphoma (PMBCL) patients, and 22 cancer-free controls. Samples were sequenced on a NovaSeq 6000 and are provided in FASTQ format.

  Dataset EGAD00001010259

• RNAseq of ribosomal footprints

  Cancer genes can affect ribosomal RNA processing and this can underlie their essentiality to cells, making them cell-essential in the same way as ribosomal genes themselves. We want to confirm this, in order to understand the results of our CRISPR drop-out screens.NOTE FROM BESPOKE TEAM: Run a single read 1 (forward read) of 30 bases, then an index 1 read as normal. This would fit a 50cycle kit

  Dataset EGAD00001001930

• Differential expression in clear cell renal cell carcinoma

  To investigate the levels of gene expression in clear cell renal cell carcinoma (ccRCC), we performed an RNA-seq analysis in 786-O, A-498, UM-RC-2 clear cell renal carcinoma cell lines, as well as HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq files and csv files with the differential expression results. Differential expression was calculated by the RNAflow pipeline (DEseq2), and log fold changes are calculated with respect to the normal cell line (HK-2), with separate results between normoxic and hypoxic datasets.

  Dataset EGAD50000001883

• Unravelling the contribution of HIF pathway and its therapeutic potential in human AML leukemia-initiating cells

  We performed single cell RNA sequencing (scRNA-seq) from bone marrow on 11 pediatric (0-14 years-old) and adolescent and young adult (AYA) (15-39 years-old) de novo AML samples (Dx) (4 inv(16), 3 t(8;21) and 4 rMLL). In addition, for some patients also relapse sample was sequenced (2 inv(16), 2 t(8;21) and 3 rMLL). Cells were sorted into CD34+/CD38- and CD34-/CD38+ and sequenced separately.

  Dataset EGAD00001008514

• ScRNA-seq of PBMC and whole blood samples reveales a dysregulated myeloid cell compartment in severe COVID-19

  In a dual-center, two-cohort study, we performed single-cell RNA-sequencing of whole blood and peripheral blood mononuclear cells to determine changes in immune cell composition and activation in mild vs. severe COVID-19 over time. This study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in the myeloid cell compartment associated with severe COVID-19.

  Dataset EGAD00001006550

• RNAseq of blood, fat and muscle samples from 45,X, 46,XX, 46,XY and 47,XXY

  Samples of blood, muscle and fat were collected from individuals with TS (n = 33) and KS (n = 22) and from male (n = 16) and female (n = 44) controls. The RNA-seq libraries were multiplexed paired-end sequenced on an Illumina Novaseq 6000 (100 bp) and subjected to initial quality control using FastQC (BAbraham Bioinformatics). In addition to trimming of low-quality ends, adaptor removal was conducted using Trim Galore with default settings (BAbraham Bioinformatics).

  Dataset EGAD00001010052

• G-SAM: Transcriptional Evolution of Glioblastomas Treated With Standard of Care

  Collection of mostly matching primary and recurrent glioblastoma RNA-seq sample pairs, also matching with an earlier DNA sequencing study

  Dataset EGAD00001007860

• Whole genome sequencing of multiple myeloma patient samples.

  Tumor (CD138+ plasma cells) and non-tumor (peripheral blood white cells or stem cell harvest) DNA from patients with a plasma cell dyscrasias were sequenced. Whole genome sequencing using high molecular weight DNA was performed using the 10X Genomics Chromium platform on either a HiSeq4000 or NovaSeq (Illumina) using 100 to 150 bp paired-end reads. The dataset consists of 111 patients, and 223 samples in total (matched tumor and control per patient; one patient had 2 tumor samples sequenced). Diseases consisted of 2 MGUS patients, 8 SMM patients, 91 newly diagnosed myeloma patients, 1 previously treated patient, 4 relapsed MM patients, and 5 PCL patients. Paired RNA-seq data are available for 81 of the samples under study EGAS00001003411.

  Dataset EGAD00001004452

• ATAC-seq dataset of Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  In this study, we demonstrate that primary AML cells harboring the chromosomal translocation t(8;21) are critically dependent on the corresponding fusion gene, RUNX1::RUNX1T1, to suppress differentiation and maintain stemness. Silencing RUNX1::RUNX1T1 expression using siRNA-loaded lipid nanoparticles induces significant changes in chromatin accessibility, redirecting the leukemia-associated transcriptional network towards a myeloid differentiation program. Single-cell analyses reveal that this transcriptional reprogramming is associated with the depletion of immature stem and progenitor-like cell populations, accompanied by an expansion of granulocytic and eosinophilic/mast cell-like populations with impaired self-renewal capacity.

  Dataset EGAD00001015509

• scRNA-seq dataset of Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  In this study, we demonstrate that primary AML cells harboring the chromosomal translocation t(8;21) are critically dependent on the corresponding fusion gene, RUNX1::RUNX1T1, to suppress differentiation and maintain stemness. Silencing RUNX1::RUNX1T1 expression using siRNA-loaded lipid nanoparticles induces significant changes in chromatin accessibility, redirecting the leukemia-associated transcriptional network towards a myeloid differentiation program. Single-cell analyses reveal that this transcriptional reprogramming is associated with the depletion of immature stem and progenitor-like cell populations, accompanied by an expansion of granulocytic and eosinophilic/mast cell-like populations with impaired self-renewal capacity.

  Dataset EGAD00001015510

• mRNA capture sequencing and RT-qPCR for the detection of pathognomonic, novel and secondary fusion transcripts in formalin-fixed paraffin-embedded tissue: a sarcoma showcase

  RNA sequencing is widely used to study gene abundance patterns, but less frequently to assess structural alterations such as fusion transcripts. In this study, we assess the performance of messenger RNA (mRNA) capture sequencing to identify fusion transcripts in formalin-fixed paraffin-embedded (FFPE) tissue of different types of sarcoma, followed by orthogonal confirmation using RT-qPCR. To validate our workflow, we used the TruSight RNA Pan-Cancer Panel to analyze a first cohort of 6 positive control tumors for which the diagnostic workup demonstrated the presence of a specific chromosomal rearrangement. Fusion transcript calling by FusionCatcher confirmed all known aberrations and enabled the identification of both fusion gene partners and breakpoints. Next, whole transcriptome TruSeq RNA Exome sequencing was applied to a second cohort of 17 patients, diagnosed with fusion gene-negative alveolar rhabdomyosarcoma (ARMS) or undifferentiated round cell sarcoma (URCS), for whom fluorescence in situ hybridization (FISH) did not identify the classical pathognomonic rearrangements. Remarkably, for 6 out of 17 patients, mRNA capture sequencing readily detected a pathognomonic fusion transcript, i.e. PAX3-FOXO1 in 2 ARMS patients, and EWSR1-FLI1, EWSR1-ERG or EWSR1-NFATC2 in 4 URCS patients. These data show that RNA capture sequencing may enhance the detection rate of pathognomonic fusion genes in sarcoma. For the 11 patients with no known pathognomonic fusion transcript, 11 newly identified fusion transcripts were confirmed by RT-qPCR, including COPS3-TOM1L2, NCOA1-DTNB, WWTR1-LINC01986, PLAA-MOB3B, AP1B1-CHEK2 and BRD4-LEUTX fusion transcripts in ARMS patients. Additionally, recurrently detected secondary fusion transcripts in two patients diagnosed with EWSR1-NFATC2-positive sarcoma were confirmed (COPS4-TBC1D9, PICALM-SYTL2, SMG6-VPS53 and UBE2F-ALS2). Our results provide new insights into the underlying genetic causes of these malignancies.

  Study EGAS00001005202

• Interactions between the tumor and the systemic response of breast cancer patients

  Breast cancer (BC) research has largely focused on the molecular properties of the tumor proper. However, to understand how cancer progresses and ultimately modulates patient outcome, we also require an understanding of the molecular changes in the patient systemic response (SR). Toward this end, we generated and analyzed RNA profiles from tumor and matched blood samples in 173 BC patients. We designed a system (MIxT) to explore and link tightly co-expressed gene sets (modules) across matched tissues. The gene composition of modules, and their expression, largely vary across tissues. Distinct patterns of expression in the SR are predominantly detected in highly immunogenic BC subtypes. We also find that the expression pattern of a module in one tissue is correlated to the expression pattern of a module in the other tissue in a fashion that depends on subtype. For example, systemic immunosuppression is detected in basalL patients in a fashion that is proportional to the level of expression of several tumor modules highlighting immune evasion mechanisms active in these particular cancers.

  Study EGAS00001001804

• MethCORR: DNA Methylation-based Characterization, Classification and Prognostication of Colorectal Cancer using Archival Formalin-fixed, Paraffin-embedded Tissue

  Transcriptional characterization and classification has potential to resolve the inter-tumor heterogeneity of colorectal cancer (CRC) and improve patient management. Yet, robust transcriptional profiling is difficult using formalin-fixed, paraffin-embedded (FFPE) samples, which complicates testing in clinical and archival material. We present MethCORR, an approach that allows uniform molecular characterization and classification of fresh-frozen and FFPE samples. MethCORR identifies genome-wide correlations between RNA expression and DNA methylation in fresh-frozen samples. This information is used to infer gene expression information in FFPE samples from their DNA methylation profiles. MethCORR was applied to methylation profiles from 877 fresh-frozen and FFPE samples and comparative analysis identified the same two major subtypes in four independent cohorts. Furthermore, subtype-specific prognostic biomarkers that better predicted relapse-free survival (HR=2.66, 95% CI [1.67-4.22], P<0.001) than TNM staging and MSI status were identified and validated using DNA methylation-specific PCR assays. The MethCORR approach is general, and may be similarly successful for other cancer types.

  Study EGAS00001004293

• Genomic Characterization CS-MATCH-0007 Arm N

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing, RNA sequencing and if possible, whole-genome, methylation and miRNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH clinical trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm N is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with PTEN mutation, or deletion with PTEN expression on IHC, are treated with the drug GSK2636771. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002151

• Analysis of genes related to the oncogenesis, progression or effectiveness of drug therapies of urological tumors .

  To clarify the oncogenesis and the progression mechanism of urological tumors, we continuously collect tumor samples of our patients with high quality. Then we used them to comprehensive analyses such as genome sequencing or epi-genome sequencing. Through these analyses, we aim for elucidating the oncogenesis or for developing newly treatment strategies of each cancer.

  Study JGAS000303

• DynaTag for efficient profiling of transcription factors in small samples and single cells

  Systematic discovery of transcription factor (TF) landscapes in low-input samples and at single cell level is a major challenge in the fields of molecular biology, genetics, and epigenetics. To address this, we present here cleavage under Dynamic targets and Tagmentation (DynaTag), which allows robust mapping of specific TF-DNA interactions via the use of a physiological salt solution during sample preparation. Using this method, we revealed occupancy alterations for 15 different TFs in stem cell and cancer tissue models. Of note, we showcased for NANOG, MYC, and OCT4 differentially occupied genomic loci during stem cell differentiation, both in bulk and at single-cell resolution. DynaTag demonstrated superior signal-to-background ratio and occupancy resolution in comparison to CUT&RUN and ChIP-seq. In addition, a model for small cell lung cancer chemotherapy treatment in vivo showed increased chromatin occupancies of the gain-of-function mutant P53 p.R248Q, FOXA1, and MYC at altered gene pathways, such as epithelial-mesenchymal-transition. Altogether, these results highlight the technical advancement of DynaTag to uncover TF landscapes in cell models and in tissues of a complex disease model.

  Study EGAS50000001074

• Recurrent epimutations activate gene body promoters in primary glioblastoma

  Aberrant DNA hypomethylation may play an important role in the growth rate of glioblastoma (GBM), but the functional impact on transcription remains poorly understood. We assayed the GBM methylome with MeDIP-seq and MRE-seq, adjusting for copy number differences, in a small set of non-glioma CpG island methylator phenotype (non-G-CIMP) primary tumors. Recurrent hypomethylated loci were enriched within a region of chromosome 5p15 that is specified as a cancer amplicon and also encompasses TERT, encoding telomerase reverse transcriptase, which plays a critical role in tumorigenesis. Overall, 76 gene body promoters were recurrently hypomethylated, including TERT and the oncogenes GLI3 and TP73. Recurring hypomethylation also affected previously unannotated alternative promoters, and luciferase reporter assays for three of four of these promoters confirmed strong promoter activity in GBM cells. Histone H3 lysine 4 trimethylation (H3K4me3) ChIP-seq on tissue from the GBMs uncovered peaks that coincide precisely with tumor-specific decrease of DNA methylation at 200 loci, 133 of which are in gene bodies. Detailed investigation of TP73 and TERT gene body hypomethylation demonstrated increased expression of corresponding alternate transcripts, which in TP73 encodes a truncated p73 protein with oncogenic function and in TERT encodes a putative reverse transcriptase-null protein. Our findings suggest that recurring gene body promoter hypomethylation events, along with histone H3K4 trimethylation, alter the transcriptional landscape of GBM through the activation of a limited number of normally silenced promoters within gene bodies, in at least one case leading to expression of an oncogenic protein.

  Study EGAS00001000685

• Tracking the evolution of esophageal squamous cell carcinoma under dynamic immune selection by multi-omics sequencing

  Intratumoral heterogeneity (ITH) has been linked to decreased efficacy of clinical treatments. However, although genomic ITH has been characterized in genetic, transcriptomic and epigenetic alterations are hallmarks of esophageal squamous cell carcinoma (ESCC), the extent to which these are heterogeneous in ESCC has not been explored in a unified framework. Further, the extent to which tumor-infiltrated T lymphocytes (TILs) are directed against cancer cells, but how the immune infiltration acts as a selective force to shape the clonal evolution of ESCC is unclear. In this study, we perform multi-omic sequencing on 186 samples from 36 primary ESCC patients. Through multi-omics analyses, it is discovered that genomic, epigenomic, and transcriptomic ITH are underpinned by ongoing chromosomal instability. Based on the RNA-seq data, we observe diverse levels of immune infiltrate across different tumor sites from the same tumor. We reveal genetic mechanisms of neoantigen evasion under distinct selection pressure from the diverse immune microenvironment. Overall, our work offers an avenue of dissecting the complex contribution of the multi-omics level to the ITH in ESCC and thereby enhances the development of clinical therapy.

  Dataset EGAD00001009482

• 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

• BCSA_Exome+SmartSeq3

  Multiple regions were cut out of each tumor extracted form breast cancer patients and two experiments were run: - Whole exome sequencing on each of the regions plus an adjacent normal tissue sample - Smart-Seq3 Single cell RNA sequencing on EPCAM+ CD45- sorted cells from different tumor regions

  Dataset EGAD00001009781

• RNA sequencing of high-risk paediatric cancers for identifying T-cell infiltration signatures

  Transcriptome profiling of 121 high-risk paediatric cancer samples for identifying T-cell infiltration signatures using poly-A capture by Truseq and sequenced on NextSeq 500

  Dataset EGAD00001010920

• Single-cell RNA-seq of bronchoalveolar lavage (BAL) fluid in severe COVID-19 and SARS-CoV-2 stimulated classical blood monocytes

  We analyzed pulmonary monocyte and macrophage responses as well as and pulmonary pathology in two cohorts of patients with COVID-19 associated ARDS. Monocyte-derived macrophages accumulated in the lung during ARDS and acquired a profibrotic signature, characterized by high expression of known fibrogenic factors like TGFB1, SPP1 and LGMN. COVID-19 associated macrophages showed highly significant transcriptional similarity with profibrotic macrophage populations identified in idiopathic pulmonary fibrosis (IPF). Notably, overnight exposure to SARS-CoV-2, but not influenza A virus or viral RNA analogues, induced a similar phenotype in human monocytes from healthy volunteers in vitro. Patients with severe COVID-19 associated ARDS showed clear clinical, radiographic and histopathological features of scarring and fibrotic tissue remodeling. In conclusion, SARS-CoV-2 triggers profibrotic macrophage responses, fibroproliferative ARDS, and lung fibrosis

  Study EGAS00001004928

• Single-cell RNA-Seq of human lymphoma reveals malignant B cell diversity and patterns of T cell immune checkpoint co-expression

  Follicular lymphoma (FL) is a generally incurable B-cell malignancy which has the potential to transform into highly aggressive lymphomas. Genomic studies indicate it is often a small subpopulation rather than the dominant population in the FL that gives rise to the more aggressive subtype. To resolve the underlying transcriptional networks of follicular B-cell lymphomas at single molecule and cell resolution, we leveraged droplet-based barcoding technology for highly parallel single cell RNA-Seq. We analyzed the transcriptomes from tens of thousands of cells derived from five primary FL tumors. Simultaneously, we conducted multi-dimensional flow cell sorting to validate our characterizing of cellular lineages and critical expressed proteins. For each tumor, we identified multiple cellular subpopulations, matching known hematopoietic lineages. Comparison of gene expression by matched malignant and normal B cells from the same patient revealed tumor-specific features. Malignant B cells exhibited restricted immunoglobulin light chain expression (either Ig Kappa or Ig Lambda), as well the expected upregulation of the BCL2 gene, but also down-regulation of the FCER2, CD52 and MHC class II genes. By leveraging the single-cell resolution on large numbers of cells per patient, we were able to examine tumor-resident T cells. We identified pairs of immune checkpoint molecules that were co-expressed, providing a potentially useful strategy for selection of patient-tailored combination immunotherapies. In summary, massively parallel measurement of single-cell expression in thousands of tumor cells and tumor-resident lymphocytes can be used to obtain a systems-level view of the tumor microenvironment and identify new avenues for therapeutic development.

  Study phs001378

• Childhood Cancer Data Initiative (CCDI): Identification and Targeting of Treatment Resistant Progenitor Populations in T-cell Acute Lymphoblastic Leukemia

  Our goal with this study was to identify the mechanisms of treatment resistance in T-cell acute lymphoblastic leukemia (ALL) using single-cell genomics. We profiled 40 T-ALL cases from the Children's Oncology Group AALL0434 clinical trial using CITE-seq/snATAC-seq, capturing a breadth of immunophenotypes, including early T-cell precursor (ETP) and near-ETP/non-ETP subtypes. By integrating analyses of T-ALL cells with the normal T-cell developmental trajectory, the study identified a specific subgroup of leukemia cells resembling bone marrow progenitors (BMP-like cells). These BMP-like cells were associated with treatment failure and poor overall survival in T-ALL patients. Overall, this study reveals comprehensive multiomic signatures for rapidly assessing risk and tailoring targeted treatment for high-risk T-ALL patients.

  Study phs003432

• Randomized Phase II 2 x 2 Factorial Trial of the Addition of Carboplatin +/- Bevacizumab to Neoadjuvant Weekly Paclitaxel Followed by Dose-Dense AC in Hormone Receptor-Poor/HER2-Negative Resectable Breast Cancer: DNA Sequencing

  This randomized phase II trial studies how well paclitaxel with or without carboplatin and/or bevacizumab followed by doxorubicin and cyclophosphamide works in treating patients with breast cancer that can be removed by surgery. Drugs used in chemotherapy, such as paclitaxel, carboplatin, doxorubicin, and cyclophosphamide, work in different ways to stop the growth of tumor cells, either by killing the cells or by stopping them from dividing. Bevacizumab may stop the growth of tumor cells by blocking blood flow to the tumor. Giving chemotherapy together with bevacizumab before surgery may make the tumor smaller and reduce the amount of normal tissue that needs to be removed. All participants in this study were female. RNA sequencing data from the same patients were published under phs001863. Subject aliases are the same in the two datasets.

  Study phs003801

• The impact of mutational clonality in predicting the response to anti-PD-L1/PD-L1 in advanced urothelial cancer

  The advent of immune checkpoint inhibitors (ICI) has radically changed the management and therapeutic treatment landscape for patients with cancer. It has been shown that the use of these inhibitors can result in long-term complete remissions even in cases with advanced stages of the disease. However, only a small fraction of patients respond to the treatment. A better understanding of which factors could drive this clinical benefit is fundamental to building more accurate predictive biomarkers and developing alternative therapeutic options for patients who are unlikely to benefit. In order to address this issue, we have generated and analyzed whole exome sequencing (WES) and RNA sequencing (RNASeq) data from a cohort of metastatic urothelial carcinoma patients (N = 27) treated with ICI such as anti-PD-(L)1 monoclonal antibodies.

  Study EGAS00001007086

• ecDNA copy number heterogeneity

  Neuroblastoma exhibits significant inter- and intra-tumour genetic heterogeneity and varying clinical outcomes. Here, we used DNA and RNA sequencing from the same single cells in cell lines and neuroblastoma patients to investigate these effects. We reveal extensive intercellular ecDNA copy number heterogeneity. We also provide direct evidence of how this heterogeneity influences the expression of cargo genes, including MYCN and its downstream targets, and the overall transcriptional state of neuroblastoma cells.

  Study EGAS50000000509

• Integrating Genomic and Transcriptomic Data to Identify Breast Cancer Susceptibility Genes

  Genetic factors play an important role in the etiology of both sporadic and familial breast cancer. Since 2007, common genetic variants in ~200 loci have been identified in genome-wide association studies (GWAS) in relation to breast cancer risk. However, it is often difficult to translate GWAS findings to disease prevention and treatment since causal genes in the large majority of GWAS-identified loci are unknown. Furthermore, a large fraction of breast cancer heritability remains unexplained. Recent studies suggest that nearly 80% of disease heritability can be explained by genetic variants regulating gene expression. Herein, we propose three well-powered transcriptome-wide association studies (TWAS) to systematically investigate the association of breast cancer risk with gene expression across the transcriptome of African, Asian and European descendants. In Aim 1, we will perform RNA sequencing and high-density genotyping assays using normal breast tissue samples, and build race-specific gene expression prediction models using data from 1000 women of African, Asian and European descent. These models will be applied to the GWAS data generated from approximately 320,000 breast cancer patients and controls to impute gene expression for association analyses of predicted gene expression with risk of breast cancer overall, and by estrogen receptor and HER2 status. In Aim 2, we will select the top 50 genes identified in Aim 1 for in vitro functional assays to assess their influence on major cell functions related to cancer biology. In Aim 3, we will evaluate whether TWAS-identified genes may express differently in normal breast tissues and breast cancer tissues collected from African, Asian, and European descendants to assess whether these genes may contribute to racial differences in breast cancer risk by molecular subtypes. With strong methodology and a large sample size, we believe that this proposed study should be able to identify and characterize a large number of novel genes related to breast cancer risk. Uncovering breast cancer susceptibility genes will greatly improve the understanding of the genetic and biological basis for breast cancer and accelerate the translation of genetic findings to disease prevention and patient care.

  Study phs003535

• Count Me In (CMI): The Metastatic Breast Cancer (MBC) Project (CMI-MBCproject)

  Count Me In - The Metastatic Breast Cancer Project: A Patient-Driven Research Initiative to Accelerate Metastatic Breast Cancer Research The Metastatic Breast Cancer Project is a research study that directly engages patients with metastatic breast cancer via social media and advocacy groups and empowers them to accelerate cancer research by sharing their samples and clinical information. Our goal is to create a publicly available dataset of genomic, molecular, clinical, and patient-reported data to enable research. Patients in the US or Canada may register online. Registered patients are sent an online consent form that asks for permission to obtain and analyze their medical records, tumor tissue, saliva, and blood samples. Once enrolled, patients are sent a saliva kit and asked to mail back a saliva sample, which is used to extract germline DNA. Study staff contact participants' medical providers and obtain medical records and a portion of their stored tumor biopsies. Patients may be asked to mail in a blood sample, which is used to extract cell free DNA (cfDNA). Whole exome sequencing (WES) is performed on tumor DNA, germline DNA, and cfDNA; transcriptome sequencing is performed on tumor RNA. Clinically annotated genomic data are used to study specific patient cohorts (including outliers) and to identify mechanisms of response and resistance to therapies. All de-identified data, including genomic, clinical, and patient-reported data, are shared via public databases on a pre-publication and recurring basis as it is generated. The latest data release in cBioPortal is available here. Study updates are shared with participants regularly.

  Study phs001709

• Bulk RNA sequencing of metastatic colorectal cancer patient-derived xenografts with known response to irinotecan

  Chemotherapy is the standard-of-care treatment for metastatic colorectal cancer (mCRC) and benefits some patients, but what distinguishes responders from non-responders is unclear. In this study, we expand a pre-existing collection (https://doi.org/10.1158/2159-8290.CD-24-0556) of molecularly annotated patient-derived xenografts to uncover functional predictors of response to 5-FU and irinotecan combination therapy (FOLFIRI) in mCRC. We complemented previous expression profiles with bulk RNAseq for 38 xenografts with known response to irinotecan.

  Study EGAS50000001485

• TK-EPN862 - Patient-dervied xenograft model of Posterior Fossa A Ependymoma - RNAseq

  Ependymomas (EPN) are the third most common malignant brain cancer in children. Treatment strategies for pediatric EPN have remained unchanged over recent decades, with 10-year survival rates stagnating at just 67% for children aged 0-14 years. Moreover, patients who survive treatment for the most common subtype of pediatric EPN (posterior fossa A (PFA)), often suffer long-term neurological side effects as a result of therapy. It is evident that there is a need for safer, more effective treatments for pediatric EPN patients. There are ten distinct subgroups of EPN, each with their own molecular and prognostic features. To identify and facilitate the testing of new treatments for EPN, in vivo laboratory models representative of the diverse molecular subtypes are required. Here, we describe the establishment of a patient-derived orthotopic xenograft (PDOX) model of PFA EPN, derived from a metastatic cranial lesion. Patient and PDOX tumors were analyzed using immunohistochemistry, DNA methylation profiling, whole genome sequencing (WGS) and RNA sequencing. Both patient and PDOX tumors classified as PFA EPN by methylation profiling, and shared similar histological features consistent with this molecular subgroup. RNA sequencing revealed that gene expression patterns were maintained across the primary and metastatic tumors, as well as the PDOX. Copy number profiling revealed gains of chromosomes 7, 8 and 19, and loss of chromosomes 2q and 6q in the PDOX and matched patient tumor. No clinically significant single nucleotide variants were identified, consistent with the low mutation rates observed in PFA EPN. Overexpression of EZHIP RNA and protein, a common feature of PFA EPN, was also observed. Despite the aggressive nature of the tumor in the patient, this PDOX was unable to be maintained past two passages in vivo. Others who have successfully developed PDOX models report some of the lowest success rates for EPN compared to other pediatric brain cancer types attempted, with loss of tumorigenicity not uncommon, highlighting the challenge in propagating these tumors in the laboratory. Here, we discuss our collective experiences with PFA EPN PDOX model generation and propose potential approaches to improve future success in establishing preclinical EPN models

  Study EGAS00001006844

• Genomic Analysis of Head and Neck Cancers

  These aggregate studies focus on specimens from head and neck squamous cell carcinoma (HNSCC) patients who were treated with standard of care or window of opportunity clinical trial approaches. Specimens were interrogated with exome and RNA-Seq analysis. Patient derived xenografts (PDXs) represent a robust platform for performing co-clinical trial approaches. In the first study we generated a large panel of PDXs and compared genomic profiles between the primary tumor and matched PDX with the patients blood serving as a source of somatic variants. In the second study, we performed a window of opportunity clinical trial in oral cavity squamous cell carcinoma patients using the MEK inhibitor trametinib. In addition, PDX models were generated from these specimens also and analyzed as in the first study. Finally, the third approach used pembrolizumab, an anti-PD1 blocking antibody, in a window of opportunity setting in HNSCC patients. For the latter two studies genomic matched sample analysis was performed to define response and resistance mechanisms. Together, these genomic data will inform several therapeutic approaches for HNSCC patients.

  Study phs001623

• Characterization of Immune Evasion in Merkel Cell Carcinoma

  Merkel cell carcinoma (MCC) is a rare, neuroendocrine skin carcinoma that is caused by the Merkel cell polyomavirus (MCPyV) in 80% of cases and by ultraviolet (UV) damage in 20% of cases. MCC should theoretically elicit a strong cytotoxic T cell response due to the high neoantigen and viral antigen burden in MCPyV- and MCPyV+ MCC, respectively. However, MCC often escapes immune recognition and is associated with very poor prognosis at advanced stages. To systemically identify mechanisms of immune evasion in MCC, we established 11 robust MCC lines from either primary tumors or patient-derived xenografts (7 MCPyV+ and 4 MCPyV-). We then characterized these tumors and cell lines by whole exome sequencing (WES), RNA-sequencing, scRNA-sequencing, ATAC-seq, and whole genome bisulfite sequencing (WGBS). We also studied MCC transcriptional subtypes, utilizing bulk and scRNA-sequencing datasets of patient-derived tumors and cell lines to investigate profiles of neuroendocrine gene expression. The genes linked below define either a neuroendocrine or a non-neuroendocrine phenotype presence within MCC tumors.

  Study phs002260

• Altered Interactions between Circulating and Tissue-Resident CD8 T Cells with the Colonic Mucosa Define Checkpoint Inhibitor Colitis

  Therapeutic immune checkpoint blockade has revolutionized oncology, but treatments are limited by immune-related adverse events, including checkpoint inhibitor colitis (irColitis). To define molecular drivers of irColitis, we profiled ~300,000 cells from the colonic mucosa and blood of 29 patients and controls. Patients with irColitis showed expanded mucosal Tregs (regulatory T cells), CD8 tissue-resident memory T cells expressing CXCL13 and Th17 gene programs, and recirculating ITGB2 CD8 T cells. Cytotoxic CD4 T cells, recirculating CD8 T cells, and endothelial cells expressing hypoxia gene programs were further expanded in colitis associated with anti-PD-1/CTLA-4 compared to in the presence of anti-PD-1 therapy. Luminal epithelial cells in irColitis patients expressed PCSK9, PD-L1, and interferon-induced signatures associated with apoptosis, increased cell turnover, and malabsorption.Raw data files from both colon and PBMCs from irColitis patients and controls have been provided to dbGaP. Count matrices derived from raw RNA-Seq data will be available through GEO accession GSE206301.

  Study phs003418

• Multi-Omic Profiling of Glioma Patient Tumors and Patient-Derived Model Systems

  We have created a resource of transcriptomic (RNAseq), genomic (whole-exome seq), and lipidomic (untargeted shotgun) profiling data from over 175 molecularly diverse glioma tumors and derivative models in orthotopic mouse xenografts and gliomasphere cultures from over 110 unique patient tumor lines. Provided in this dataset are matched bulk RNA and whole-exome paired-end sequencing data from resected gliomas and derived model systems performed on Illumina HiSeq and NovaSeq sequencing instruments. This comprehensive dataset powers multiple studies aiming to derive molecular signatures of intertumoral heterogeneity and perturbation responses in glioma. Through integrative multi-omic analyses in Minami, et al., 2023, PMID: 37236196, we identified that CDKN2A deletion remodels the GBM lipidome and consequently primes CDKN2A-deleted tumors for ferroptosis. Lipidomics data related to this study are publicly available here. In another study, we used a combination of molecular profiling and functional profiling of apoptotic potential to stratify patients into groups with differential vulnerability to the current standard-of-care in gliomas, and in combination with drugs targeting intrinsic apoptosis, largely informed but not limited to TP53 mutation status.

  Study phs003286

• Immuno-genomic Profiling of Biopsy Specimens Predicts Neoadjuvant Chemotherapy Response in Esophageal Squamous Cell Carcinoma

  Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive cancers and is primarily treated with platinum-based neoadjuvant chemotherapy (NAC). Some ESCCs respond well to NAC. However, biomarkers to predict NAC sensitivity and their response mechanism in ESCC remain unclear. We introduce a model by machine learning and validated its potential to predict the NAC response in ESCC. To create this model, we performed whole genome sequencing and RNA-seq analysis on totally 141 ESCC biopsy specimens before NAC treatment and analyzed their immuno-genomic features and association with NAC response. Neutrophils infiltration could play an important role in ESCC response to NAC. We also demonstrated that specific copy number alterations and copy number signatures in the ESCC genome were significantly associated with NAC response. The interactions between the tumor genome and immune features of ESCC are likely to be a new indicator of therapeutic capability and a new therapeutic target for ESCC, and machine learning prediction for NAC response is useful.

  Study JGAS000535

• Myasthenia gravis-specific aberrant neuromuscular gene expression by medullary thymic epithelial cells in thymoma

  Myasthenia gravis (MG) is a neurological disease caused by autoantibodies against neuromuscular-associated proteins. While MG is frequently developed in thymoma patients, the etiologic factors for MG are not well understood. Here, by constructing a comprehensive atlas of thymoma using bulk and single-cell RNA-seq, we identified ectopic expression of neuromuscular molecules in MG-associated thymoma (MG-thymoma). These molecules were originated from a distinct subpopulation of medullary thymic epithelial cells (mTECs), which we named neuromuscular mTECs (nmTECs). MG-thymoma also exhibited microenvironments dedicated to autoantibody production, including ectopic germinal center formation, T follicular helper cell accumulation, and type 2 conventional dendritic cell migration. Cell-cell interaction analysis also predicted the interaction between nmTECs and T/B cells via CXCL12-CXCR4. The enrichment of nmTECs presenting neuromuscular molecules within MG-thymoma was further confirmed by immunohistochemically and by cellular composition estimation from MG-thymoma transcriptome. Altogether, this study suggests that nmTECs play a significant role in MG pathogenesis via ectopic expression of neuromuscular molecules.

  Study JGAS000482

• Single-cell analysis of airway samples identifies immune cell activation correlating with COVID-19 disease severity

  To investigate the immune response and mechanisms associated with severe COVID-19, we performed single-cell RNA-seq on nasopharyngeal and bronchial samples from 19 clinically well-characterized patients with moderate or critical disease and from 5 healthy controls. We identified airway epithelial cell types and states vulnerable to SARS-CoV-2 infection. In COVID-19 patients, epithelial cells showed an average threefold increase in expression of the SARS-CoV-2 entry receptor ACE2, which correlated with interferon signals by immune cells. Compared with moderate cases, critical cases exhibited stronger interactions between epithelial and immune cells, as indicated by ligand–receptor expression profiles, and activated immune cells , including inflammatory macrophages expressing CCL2, CCL3, CCL20, CXCL1, CXCL3, CXCL10, IL8, IL1B and TNF . The transcriptional differences in critical cases compared with moderate cases likely contribute to clinical observations of heightened inflammatory tissue damage, lung injury and respiratory failure. Our data suggest that pharmacologic inhibition of the CCR1 and/or CCR5 pathways may suppress immune hyperactivation in critical COVID-19.

  Study EGAS00001004481

• Next gen seq of eye cancers (2019-08-14)

  Retinoblastoma (RB), the commonest eye cancer in children was the first cancer for which a genetic cause was identified: the Rb1 gene is a tumour suppressor gene that is mutated in RB. The Rb1 gene defect alone does not predict the clinical outcome. We propose to study other possible mechanisms: 1. Stepwise further mutations occur in RB, increasing its carcinogenesis. We will sequence the whole genome in RB tissue, and relate the different genes expressed to the treatments used. 2. Extracellular matric proteins contribute to a tumour permissive environment for RB to continue to grow. This includes Samll Leucine Rich Proteoglycans (SLRP), a family of 15 secreted extracellular matrix proteins involved in eye development. 3. Cancer stem cells (CSC), a subpopulation of treatment resistant cells, drive RB tumours, and whether these stem cells can be manipulated for new therapies. The aim of this study is to assist finding targeted diagnostic techniques and treatments for RB. . This dataset contains all the data available for this study on 2019-08-14.

  Dataset EGAD00001005251

• Whole blood RNAseq from a large ALS case-control study at Univ of Michigan

  This dataset consists of 694 bulk RNA-seq data (sorted aligned BAM files) from whole blood of ALS participants meeting the Gold Coast definition of ALS during their clinical visit (n=422) and healthy controls (n=272) at the University of Michigan (UM). Samples were collected as part of the UM Pranger ALS Clinic between 2011-2021, and prepared either using poly-A selection of rRNA depletion (see Experiments). RNAseq was performed on the NovSeq 6000 S4 at the UM Advanced Genomics Core, resulting in 150bp paired-end reads. Raw reads were trimmed using Cutadapt (v2.3) and aligned to hg38 using STAR (v2.5.3a). Age provided is the age at blood sample collection date.

  Dataset EGAD50000001488

• RNA-seq data in hMPC, MSC_Pat and EWIma

  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 and epigenetic hallmarks of EwS.

  Study EGAS50000001173

• Oropharynx cancers sequencing study (RNA-seq from FFPE)

  This is a study of transcriptomics in HPV-associated oropharynx tumors. The goals of this study were to characterize HPV+ oropharynx tumor subtypes and to examine HPV integration events and their downstream effects. HPV-host fusion transcripts and recurrent HPV integration genes were identified. Various alternative isoforms and splicing events of HPV genes were also studied. Multiple potential biomarkers of prognosis were associated with clinical outcomes.

  Study EGAS50000000893

• Transcriptomic response of miRNAs of monocytes to bacterial and viral stimuli assessed by RNA-seq in Africans and Europeans

  Leveraging the miRNA transcriptome of 977 samples, the study aims to define the levels of miRNA and isomiR diversity across individuals and populations, explore the genetic sources of miRNA expression variability and miRNA-environment interactions, evaluate the effects of immune challenges upon miRNA and isomiR expression dynamics, and quantify the relative impact of transcription and miRNA-mediated degradation on gene expression variability.

  Study EGAS00001004192

• Cell line data (RNAseq, ATACseq, ChIPseq)

  Content: 2 GB RTK I cell lines (LN229, ZH487) in two conditions (NT control and shSOX10). RNAseq: single replicates per condition, polyA+ RNA sequencing, SE. ATACseq: biological replicates per condition, SE. ChIPseq (histone H3 modifications, LN229 only): all marks for each condition were pooled and sequenced on two lanes for each pool. ChIPseq (BRD4 and SOX10): SOX10 libraries were sequenced on single lanes. BRD4 samples were multiplexed and sequenced in two lanes. ChIPseq input samples are also included. Data type and technology: RNAseq: SE 50bp sequenced on HiSeq2000/4000. ATACseq: SE 50bp sequenced on HiSeq2000/4000. ChIPseq: SE 50bp sequenced on HiSeq2000/4000.

  Dataset EGAD00001005493