12040 results for "cancer rna-seq"

in 22.42 milliseconds.

• scRNA transcriptome and TCR sequencing data modeling treatment responses in eight renal cell carcinoma patient

  Single cell RNA sequencing and coupled TCR sequencing data generated following immunological treatments in patient-derived ex vivo tumor models. Dataset consist of 46 sequencing samples originating from eight individual patient-derived ex vivo models. Single cell RNA and TCR sequencing data is generated using 10X Genomics platform with 5´ sequencing. The submission contains 46 Fastq files where each patient-derived ex vivo model and it's transcriptomic response to specified treatment is a unique sequencing run. TCR sequencing runs are submitted as one file per individual model, gathering all the treatment conditions.

  Dataset EGAD50000001934

• Multi-modal single-cell analysis of salivary glands from patients with Sjogren's syndrome

  Sjogren's syndrome (SS) is an autoimmune disease that causes salivary gland dysfunction due to immune-mediated destruction. In this study, we apply multi-modal single-cell technologies - single-cell RNA sequencing and T-cell receptor sequencing - to salivary gland lesions, aiming to uncover transcriptional signatures and TCR sequence linked to autoantibody profiles.

  Study JGAS000808

• Investigation of relapse prediction in infants with MLL-rearranged Acute Lymphoblastic Leukemia

  In infants with ALL, accurate relapse prediction would enable treatment strategies that take relapse risk into account, with potential benefits for both low- and high-risk patients. Through analysis of bone marrow biopsies taken at initial diagnosis, we show that single-cell RNA sequencing can predict future relapse occurrence.

  Study EGAS00001003986

• TTV018_RORC_IBD_associated_genotype_effects_on_RORgT_expression_and_function_in_ex_vivo_T_cells

  RNA sequencing of peripheral immune cells from patients +/- an IBD risk variant. Peripheral immune cells +/- in vitro test compound treatment.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 EGAS00001001590

• Multiomics analyses of Parkinson's disease midbrains

  Understanding the key pathological mechanisms underlying Parkinson's Disease pathology is fundamental for the development of novel and more effective therapeutic strategies. In this study, post-mortem human midbrain tissue from a cohort of 13 PD patients and 10 controls was analyzed with a set of multi-omics technologies including small RNA sequencing, transcriptomics and proteomics profiling.

  Study EGAS00001004966

• B-ALL bone marrow and CNS xenograft RNA sequencing

  This dataset includes TruSeq paired-end, total RNA sequencing data from primary B-precursor acute lymphoblastic leukaemia (B-ALL) xenografts. It comprises 43 pairs of matched bone marrow (BM) and central nervous system (CNS) human leukaemia cells from individual immunodeficient mice. Xenografts were generated from 6 patients with B-ALL and include samples taken at diagnosis and relapse from 3 of 6 patients.

  Dataset EGAD00001008183

• IG-MYC ALL - DNA and RNA sequencing

  The dataset is composed by the raw RNA sequencing (n=6), targeted DNA sequencing (n=18) and whole exome sequencing (n=17) from 19 patients with IG-MYC-rearrangements.

  Dataset EGAD00001008705

• HuBMAP: Single-Cell Multiplex Chromatin and RNA Interactions in Aging Human Brain

  The study employs the Multi-Nucleic Acid Interaction Mapping in Single Cell (MUSIC) technique to concurrently profile multiplex chromatin interactions, gene expression, and RNA-chromatin associations within individual nuclei, revealing dynamically organized chromatin complexes in human frontal cortex samples from elderly donors. The MUSIC technique allows for the exploration of chromatin architecture and transcription at cellular resolution in complex tissues. The study includes 14 human cortex tissues and employs MUSIC to delineate diverse cortical cell types and states, revealing that nuclei with fewer short-range chromatin interactions correlate with an "older" transcriptomic signature and Alzheimer's pathology. Additionally, the study elucidates that specific cell types, characterized by chromatin contacts between cis expression quantitative trait loci (cis eQTLs) and a promoter, are particularly susceptible to the regulatory impact of these cis eQTLs on target gene expression. Furthermore, the female cortical cells exhibit highly heterogeneous interactions between the X-inactive specific transcript (XIST) non-coding RNA and Chromosome X, along with diverse spatial organizations of the X chromosomes. MUSIC presents a potent tool for exploring chromatin architecture and transcription at cellular resolution in complex tissues.

  Study phs003568

• Ontario Institute for Cancer Research; Biliary Tract Cancer

  Next Generation Sequencing data from Biliary Tract cancers

  Study EGAS50000000972

• SNP array datas of 'Matched' cancer/PNE

  SNP array data of 31 Matched cancer/PNE samples

  Study EGAS00001003331

• Sequencing data for oesophageal and related samples - OACs release 2 (RNA)

  Dataset EGAD00001003839

• Sequencing data for oesophageal and related samples - OACs release 1 (RNA)

  Dataset EGAD00001002259

• Single-nucleus RNA-sequencing of normal adrenal cortex and adrenocortical tumors

  CellRanger counts processed with the Cell Ranger software v3.1.0.

  Dataset EGAD50000000836

• High-throughput 3D engineered paediatric tumour models for precision medicine

  Paired fastqs for DNA and RNA from Illumina TSO500 targeted sequencing from PDX.

  Dataset EGAD00001015753

• Carcinoid study - RNASeq dataset

  Fernandez-Cuesta et al, 2014, Nature Communication, RNA Sequencing data set

  Dataset EGAD00001000795

• SNF_RNAseq_CD138p_20

  TPM matrices of counts from RNA sequencing (RNAseq) from baseline CD138+ enriched BM fractions.

  Dataset EGAD00001011148

• TXT_CD138P_15

  TPM matrices of counts from RNA sequencing (RNAseq) from longitudinal CD138+ enriched BM fractions.

  Dataset EGAD00001011144

• TCELL PILOT ATAC-SEQ

  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/

  Dataset EGAD00001001317

• scRNA-seq

  This dataset gather scRNAseq data performed for MM.1S cell line in control and dex conditions at 4h and 24h

  Dataset EGAD00001011139

• San Francisco Bay Area Latina Breast Cancer Study

  The genome-wide association study (GWAS) includes participants enrolled into two different studies. The first study, the San Francisco Bay Area Cancer Study (SFBCS) is a population-based case-control study of breast cancer conducted in the San Francisco Bay Area and included women ages 35-79 years from three racial/ethnic groups: Non-Hispanic whites, African Americans, and Hispanics/Latinas. For the GWAS, only Hispanic/Latina women were included. Women diagnosed with invasive breast cancer between 1995 and 2002 were identified through the Greater Bay Area Cancer Registry. Controls were identified by random digit dialing and were frequency-matched to cases by age in 5 year increments and by race/ethnicity. Hispanic/Latina ethnicity was assessed by self-report. 175 Hispanic/Latina cases and 307 Hispanic/Latina controls from the SFBCS had given adequate consent and provided biospecimens that were used in the GWAS to be included in this data submission. The second study is the Northern California site of the Breast Cancer Family Registry (NC-BCFR). This population-based family study recruited breast cancer cases ages 18-64 years diagnosed from 1995-2009 that were identified through the Greater Bay Area Cancer Registry. Cases included all women at increased genetic susceptibility for breast cancer who met one or more of the following criteria: (a) being diagnosed with breast cancer at age <35 years; b) having a personal history of ovarian cancer or childhood cancer; (c) being diagnosed with two different breast cancers (bilateral breast cancers), with the first one diagnosed at age <50 years; and d) having one or more first-degree relatives with breast cancer, ovarian cancer or childhood cancer. Cases not meeting these criteria were randomly sampled and racial/ethnic minorities were oversampled. Controls were recruited by random digit dialing and were matched by 5-year age increments and by race/ethnicity. For the current GWAS only Latina/Hispanic cases and controls were included. Latina/Hispanic ethnicity was assessed by self-report. 631 Hispanic/Latina cases and 61 Hispanic/Latina controls from the NC-BCFR had given adequate consent and provided biospecimens that were used in the GWAS to be included in this data submission.

  Study phs000912

• Whole-genome cfDNA TAPS sequencing data from 91 people with various types of cancer and from non-cancer controls

  TAPS data in the form of BAM files from 214 samples: plasma (at 80x) and matched germline (at 30x) pairs from 61 cancer and 30 non-cancer subjects, fresh-frozen matched tumour biopsies (at 80x) from 16 subjects, as well as several follow-up plasma samples (at 80x) from 10 subjects with colorectal cancer.

  Dataset EGAD50000000996

• Metastatic_Breast_Cancer_Whole_Genome

  We propose to definitively characterise the somatic genetics of Metastatic breast cancer through generation of comprehensive catalogues of somatic mutations in Metastatic breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000902

• Breast_Cancer_FRT_RNA_seq

  We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000420

• Triple_Negative_Breast_Cancer_RNA_Sequencing

  We propose to definitively characterise the somatic genetics of triple negative breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000377

• Lineage Plasticity and Immune Cell Heterogeneity Are Coordinately Dysregulated Through Changes in FOXA1 Expression in Bladder Cancers with Squamous Differentiation

  We performed whole exome sequencing (WES) of paired, macrodissected regions of urothelial carcinoma (UC), not otherwise specified (NOS-UC) and squamous differentiation (SqD) from 21 bladder tumors in which distinct and separable NOS-UC and SqD regions were present (total 42 exomes, in addition to matched normal exomes). Mean tumor mutational burden (TMB) was higher in the SqD versus the NOS-UC regions. Consistent with the higher TMB, the SqD regions also had a higher neoantigen burden than the patient-matched NOS-UC regions. The SqD regions also exhibited higher karyotypic complexity with a higher median ploidy relative to the paired NOS-UC regions. Phylogenetic analysis of the WES data confirmed that the morphologically distinct regions of all 21 tumors arose from a shared precursor with a median of 68 (range 16 – 852) non-synonymous mutations shared between the NOS-UC and SqD regions, and the overall data were indicative of early branched evolution. As whole exome sequencing did not identify a shared mutational alteration or genomic signature unique to the SqD or NOS-UC components, we therefore performed expression profiling of separable SqD and NOS-UC regions of 12 bladder tumors from the WES cohort with RNA quality sufficient for whole transcriptome RNA-sequencing (RNAseq, total of 24 regions). Based on centroid clustering analysis of expression data, all 12 regions of SqD were basal-squamous subtype based on the TCGA molecular classification schema. Notably, 8 of the NOS-UC regions were also basal-squamous subtype, with only four pairs exhibiting discordant transcriptional subtypes (three NOS-UC regions were luminal-infiltrated, one luminal-papillary). To better quantify differences in the transcriptional profiles of the paired NOS-UC and SqD regions, we used single sample gene set enrichment analysis (ssGSEA) to assess for enrichment of luminal or basal-squamous gene expression. ssGSEA analysis revealed that the SqD regions expressed higher levels of basal-squamous genes based on the BASE47 gene set and UPK/KRT gene sets; whereas the matched NOS-UC regions expressed higher levels of luminal genes. These differences in the levels of expression of basal and luminal genes were observed even in cases in which both the NOS-UC and SqD regions were basal-squamous subtype based the TCGA molecular classification schema. Exomes from eight patients in this study have previously been deposited in dbGaP: accession number phs001783 as part of the study "Exome Recapture and Sequencing of Prospectively Characterized Clinical Specimens From Cancer Patients".

  Study phs002357

• The impact of CCR8+ regulatory T cells on cytotoxic T cell function in human lung cancer

  Regulatory T cells (Tregs) suppress the host immune response and maintain immune homeostasis. Tregs also promote cancer progression and are involved in resistance to immune checkpoint inhibitor treatments. Recent studies identified selective CCR8 expression on tumor-infiltrating Tregs; CCR8+ Tregs have been indicated as a possible new target of cancer immunotherapy. Here, we investigated the features of CCR8+ Tregs in lung cancer patients. CCR8+ Tregs were highly activated and infiltration of CCR8+ Tregs in tumors was associated with poor prognosis in lung cancer patients. We also investigated their immune suppressive function, especially the influence on cytotoxic T lymphocyte cell function. The Cancer Genome Analysis revealed that CD8 T cell activities were suppressed in high CCR8-expressing tumors. Additionally, depletion of CCR8+ cells enhanced CD8 T cell function in an ex vivo culture of lung tumor-infiltrating cells. Moreover, CCR8+ Tregs, but not CCR8��� Tregs, induced from human PBMCs markedly suppressed CD8 T cell cytotoxicity. Finally, we demonstrated the therapeutic effect of targeting CCR8 in a murine model of lung cancer. These findings reveal the significance of CCR8+ Tregs for immunosuppression in lung cancer, especially via cytotoxic T lymphocyte cell suppression, and suggest the potential value of CCR8-targeted therapy for cancer treatment.

  Study JGAS000454

• Targeted sequencing of breast cancer susceptibility genes for 1,995 Japanese breast cancer patients

  In this study, we investigated pathogenic germline variants in 11 genes implicated in hereditary breast cancer, including BRCA1, BRCA2, TP53, PTEN, CDH1, STK11, NF1, PALB2, ATM, CHEK2, NBN1, in a total of 1,995 unselected Japanese women with breast cancer using targeted-capture sequencing of pooled DNA (n = 106).

  Study EGAS00001004630

• Germline genome sequencing samples from the Hereditary Cancer Syndromes (ICCon) Cancer Flagship

  A prospective study of individuals with suspicion of a hereditary cancer syndrome for whom previous clinical targeted genetic testing was either not informative or was not available. To identify pathogenic disease-causing variants explaining participant presentation, germline whole-genome sequencing and a comprehensive cancer virtual gene panel analysis were undertaken.

  Study EGAS00001007045

• Highlights from 2025: Our top 10 requested studies

  In 2025, as in previous years, EGA has facilitated the reuse of numerous datasets spanning a broad range of research and healthcare topics. To reflect on this activity, we would like to highlight the top 10 studies behind the most requested datasets of last year. Notably, the vast majority of these highly requested datasets are cancer-focused, particularly involving the study of immune checkpoint inhibitor therapies. Immune checkpoint inhibitors (ICIs) have become one of the most transformative advances in modern cancer therapy. These monoclonal antibodies enhance antitumor immune responses by targeting inhibitory immune checkpoint molecules. While ICIs have led to remarkably favorable and durable responses in some patients, treatment outcomes vary widely. This variability has fueled intense research efforts aimed at understanding resistance mechanisms, exploring combination therapies, and discovering predictive biomarkers to better stratify patients and guide treatment decisions. Study Title Disease 1 EGAS00001005503 Integrated genomic analyses reveal molecular correlates of clinical response and resistance to atezolizumab in combination with bevacizumab in advanced hepatocellular carcinoma Liver Cancer 2 EGAS00001005013 Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer Lung Cancer 3 EGAS00001004809 BIOKEY: A single-cell catalogue of the dynamic changes underlying Checkpoint Immunotherapy response in Early Breast Cancer Breast Cancer 4 EGAS50000000138 BIOKEY: Immune heterogeneity in small cell lung cancer and vulnerability to immune checkpoint blockade Lung Cancer 5 EGAS50000000497 Bladder cancer subtyping study across 4 atezo clinical trials Bladder Cancer 6 EGAS50000000689 MOSAIC - Multi-Omics Spatial Atlas In Cancer Cancer Atlas 7 EGAS00000000083 METABRIC (Breast cancer - genome and transcriptome) Breast Cancer 8 EGAS00001005702 Human genomic and phenotypic synthetic data for the study of rare diseases Synthetic data 9 EGAS00001002556 TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells Bladder Cancer 10 EGAS00001004353 Molecular subsets in renal cancer determine outcome to checkpoint and angiogenesis blockade Renal Cancer The most requested dataset of the year was EGAD00001008128. It belongs to a study that analyzed 358 liver cancer patients enrolled in clinical trials and treated with the combination of atezolizumab (anti–PD-L1) and bevacizumab (anti-VEGF), atezolizumab alone, or sorafenib. The study highlights how bevacizumab enhances anti-PD-L1 effect and identifies candidate biomarkers to predict treatment response. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and the third leading cause of cancer-related death worldwide [1]. Because symptoms often appear late, many patients are diagnosed at advanced stages, when curative options are no longer viable. For many years, sorafenib—a multikinase inhibitor approved in 2007—was the only systemic treatment available. Although numerous clinical trials followed, it was not until a decade later that additional therapies showed meaningful clinical benefit. Among these advances, immunotherapy emerged as a promising first-line option [2]. In particular, the combination of atezolizumab and bevacizumab demonstrated improved survival in patients with advanced HCC, reshaping the treatment landscape. However, treatment efficacy remains limited by the complex and diverse hepatic microenvironments that influence immune responses, as well as by high intratumoral heterogeneity. Identifying robust predictors of treatment response is critical to enable effective patient stratification and maximize the benefits of these therapies [2]. The continued demand for these datasets highlights the interest and critical role of data reuse in deepening our understanding of cancer, accelerating the development of more effective therapies, and improving patient outcomes. By providing secure access to high-quality genomic and clinical data, EGA acts as a catalyst for biomedical progress. References Sung, Hyuna, et al. "Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries."CA: a cancer journal for clinicians 71.3 (2021): 209-249. Ladd, Alexandra D, et al.“Mechanisms of drug resistance in HCC.” Hepatology 79(4) (2024): 926-940

  Blog top-10-studies-2025

• Chugai_colorectal_organoid_sequencing

  Genomic and transcriptomic characterization of drug-resistant colon cancer stem cell lines.

  Study EGAS00001000872

• Germline Whole-Exome Sequencing of Lung Cancer in EAGLE

  EAGLE is a large population-based case-control study designed and conducted to investigate the genetic and environmental determinants of lung cancer and smoking persistence using an integrative approach that allows combined analysis of genetic, environmental, clinical, and behavioral data. Here, we applied whole exome sequencing (WES) to EAGLE study, in a group of 2,777 Italian subjects (including 1,461 lung cancer cases and 1,316 healthy controls). We derived gene-level burden tests to explore the cumulative effect of deleterious rare variants within protein-coding genes and the lung cancer risk. Additionally, at this site we include WES datasets of 1259 healthy controls from 1054 PLCO (The Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial) subjects and 205 ACS (The American Cancer Society study) subjects.

  Study phs002496

• The Cancer Dependency Map (DepMap)

  The Cancer Dependency Map (DepMap) aims to accelerate precision cancer medicine by creating a comprehensive map of tumor vulnerabilities. The DepMap project genomically profiles a wide range of cancer models and characterizes them for their sensitivity to genetic and compound perturbations. The data is computationally analyzed to create a systematic overview of the genetic dependencies and compound sensitivities of cancer types and the predictive biomarkers that point to patient populations most likely to benefit from targeting of these vulnerabilities. The DepMap public portal has become a comprehensive resource to identify cancer vulnerabilities by providing datasets at scale, cutting-edge computational tools, and sophisticated visualization tools that together have accelerated the discovery of novel targets and biomarkers. Please visit Depmap.org to access the public portal.

  Study phs003444

• Genetic Alterations in Benign Breast Biopsies of Subsequent Breast Cancer Patients

  Fibrocystic changes are associated with an increased risk of breast cancer (approximately 1.5-2 times that of the general population). Although the relative risk seems low, because of the high frequency of such changes, the absolute risk is significant. Genetic alterations have been found in fibrocystic changes with or without epithelial changes, suggesting that critical oncogenic events are occurring at an early stage. We investigated a unique collective of 17 breast cancer patients who, prior to the diagnosis of invasive breast cancer, underwent open surgical biopsy showing fibrocystic changes of the breast. Massive parallel sequencing targeting genes frequently mutated in breast cancer was performed on the fibrocystic breast tissue as well as the ensuing cancer tissue.

  Study EGAS00001003563

• Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) - OncoArray Genotypes

  Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) was one of five projects funded in 2010 as part of the NCI's Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (http://epi.grants.cancer.gov/gameon/). GAME-ON's overall goal was to foster an intra-disciplinary and collaborative approach to the translation of promising research leads deriving from the initial wave of cancer GWAS. Specific goals included replication of previous GWAS findings and identification of new susceptibility loci through meta analyses of existing GWAS data and fine mapping of identified loci to better pinpoint causal variants; and identify germline variants that are associated with risk of multiple cancers. The other four funded GAME-ON projects were: the ColoRectal TransdisciplinaryStudy (CORECT), Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE), Follow-up of Ovarian Cancer Genetic Association and Interaction Study (FOCI), and Transdisciplinary Research in Cancer of the Lung (TRICL). To identify additional cancer risk loci, improve the precision of fine-mapping, and facilitate cross-cancer analyses, the GAME-ON projects and other consortia formed the OncoArray network (http://epi.grants.cancer.gov/oncoarray/), which developed and genotyped a new custom genotyping array (the "OncoArray") in large numbers of cancer cases and controls (over 400,000 samples). The OncoArray is a custom array manufactured by Illumina. The array includes a backbone of approximately 260,000 SNPs that provide genome-wide coverage of most common variants, together with markers of interest for each of the five GAME-ON cancers identified through genome-wide association studies (GWAS), fine-mapping of known susceptibility regions, sequencing studies, and other approaches. The array also includes loci of interest identified through studies of other cancer types, and other loci of interest to multiple cancer types (including loci associated with cancer related phenotypes, drug metabolism and radiation response). Additionally, SNPs relating to quantitative phenotypes such as body mass index (BMI), height, and breast density that correlate with common cancer risks are also included. The DRIVE data included under this dbGAP submission include OncoArray data from 60,015 breast cancer cases and controls genotyped at the Center for Inherited Disease Research (CIDR), University of Cambridge, National Cancer Institute, University of Copenhagen, University of Southern California and Mayo Clinic. Details on an additional approx. 80,000 breast cancer cases and controls genotyped at other centers can be found at http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/.

  Study phs001265

• Plasma mutation profile of precursor lesions and colorectal cancer using the Oncomine Colon cfDNA Assay

  Colorectal cancer (CRC) is the second leading cause of cancer death worldwide. Early detection of precursor lesions or early-stage cancer could hamper cancer development or improve survival rates. Liquid biopsy, which detects tumor biomarkers, such as mutations, in blood, is a promising avenue for cancer screening. To assess the presence of genetic variants in plasma cell-free tumor DNA from patients with precursor lesions and colorectal cancer using the commercial Oncomine Colon cfDNA Assay. Cell-free DNA (cfDNA) samples from the blood plasma of 52 Brazilian patients were analyzed. Eight patients did not have any significant lesions (five normal colonoscopies and three hyperplastic polyps), 24 exhibited precursor lesions (13 nonadvanced adenomas, ten advanced adenomas, and one sessile serrated lesion), and 20 patients with cancer (CRC). The mutation profile of 14 CRC-associated genes were determined by next-generation sequencing (NGS) using the Oncomine Colon cfDNA Assay in the Ion Torrent PGM/S5 sequencer.

  Dataset EGAD50000000679

• ctDNA multigenic panel for non-small cell lung cancer

  Detection of actionable mutations in liquid biopsies constitute an important tool for management of non-small cell lung cancer (NSCLC) patients in the era of oncology precision medicine. We aimed to evaluate the actionable alterations using a commercial multi-gene panel in circulating tumor DNA (ctDNA) derived from plasma samples of treatment naïve and prior-treated non-small cell lung cancer (NSCLC) patients. For this, we analyze plasma samples of 30 subjects with non-small cell lung cancer.

  Study EGAS50000000643

• Longitudinal Studies of Patients with Familial Platelet Disorder with Associated Myeloid Malignancy (FPDMM)

  FPDMM (OMIM #601399) is a rare autosomal dominant disease characterized by defective megakaryocytic development, thrombocytopenia, platelet functional defects, and a life-long risk of developing hematological malignancies. FPDMM is caused by germline mutations in the RUNX1 gene, which encodes a master regulator of hematopoiesis. The overall lifetime risk of hematological malignancies in FPDMM patients is 35 - 45%. It is hypothesized that mutations in other genes cooperate with the germline RUNX1 mutations for leukemia development. However, it is not clear which genes need to be mutated for leukemia to develop and which biomarkers or clinical tests can be used to predict which patients will progress to leukemia. Likewise, there are no treatments and/or preventative measures that can reduce or stop disease progression except for stem cell transplantation, which is not available for all patients and may be associated with significant complications. To address these questions, we launched a longitudinal natural history study of patients associated with RUNX1 germline mutations at the NIH Clinical Center in early 2019 (Trial Registration ID: NCT03854318). The goals of this study are to: (1) perform comprehensive longitudinal phenotyping of FPDMM patients to document the full spectrum of both hematopoietic and non-hematopoietic manifestations of the disease; and (2) perform extensive genomic analyses of FPDMM patient samples to identify cooperating genomic variants, which may confer growth advantage that leads to clonal expansion of affected hematopoietic cells that may serve as the precursor to malignancies. The data available through dbGaP include exome sequencing and RNA-seq data from these patients. Diverse germline mutation types were identified in the RUNX1 gene, including splice site mutations and large deletions, in addition to nucleotide substitutions and small indels. Somatic mutations, especially in genes associated with clonal hematopoiesis of indeterminate potential (CHIP), were found in a substantial proportion of FPDMM patients who were leukemia-free. The findings suggest that the genomes in these patients are prone to somatic mutations and monitoring the dynamic changes of these somatic mutations prospectively may provide a way to predict progression to malignancies.

  Study phs003075

• Detection of brain cancer using genome-wide cell-free DNA fragmentomes

  Diagnostic delays in patients with brain cancer are common and can impact patient outcome. Development of a blood-based assay for detection of brain cancers could accelerate brain cancer detection. In this study, we analyzed genome-wide cell-free (cfDNA) fragmentomes, including fragmentation profiles and repeat landscapes, from the plasma of individuals with (n=148) and without (n=357) brain cancer. Machine learning analyses of cfDNA fragmentome features detected brain cancer across all grade gliomas (AUC=0.90, 95% CI: 0.87-0.93) and these results were validated in an independent prospectively collected cohort. cfDNA fragmentome changes in patients with gliomas represented a combination of fragmentation profiles from glioma cells and altered white blood cell populations in the circulation. These analyses reveal the properties of cfDNA in patients with brain cancer and open new avenues for noninvasive detection of these individuals.

  Study EGAS50000000986

• 15 Healthy controls, 25 conlonrectal cancer patients without liver metastasis and 24 conlonrectal cancer patients with liver metastasis (target capture)

  15 Healthy controls, 25 conlonrectal cancer patients without liver metastasis and 24 conlonrectal cancer patients with liver metastasis (target capture)

  Dataset EGAD00001009838

• Large Cancer Fingerprint Screening for Detection of Minimal Residual Disease.

  We describe an approach for large cancer fingerprint screening and its application to cell-free DNA from patients with cancer. Our approach involves tracking somatic mutations identified from patients' tumor biopsies, in the cell-free DNA from a blood draw.

  Study phs001977

• exploration of biomarkers in colorectal cancer

  Targeted therapies based on the molecular and histological features of cancer types are becoming standard practice. To understand the molecular basis of colorectal cancer, we performed CAGE (Cap Analysis of Gene Expression) to quantify promoter activities on 45 colorectal cancers.

  Study JGAS000489

• Genome and transcriptome sequence data from a sigmoid cancer and an ampullary cancer patient

  Genome and transcriptome sequence data from a sigmoid cancer and an ampullary cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003046

• Target sequencing of 27 cancer-predisposing genes in Japanese colorectal cancer patients

  Background: National Comprehensive Cancer Network (NCCN) recently recommended germline genetic testing for all pancreatic cancer patients. However, the genes targeted by genetic testing and the feasibility of selecting patients likely to carry pathogenic variants have not been sufficiently verified. The purpose of this study was to genetically characterize Japanese patients and examine whether the current guideline is applicable in this population. Methods: Using targeted sequencing, we analyzed the coding regions of 27 cancer-predisposing genes in 1,005 pancreatic cancer patients and 23,705 controls in Japan. We compared the pathogenic variant frequency between cases and controls and documented the demographic and clinical characteristics of carrier patients. We then examined if it was possible to use machine learning to predict carrier status based on those characteristics. Findings: We identified 205 pathogenic variants across the 27 genes. Pathogenic variants in BRCA2, ATM, and BRCA1 were significantly associated with pancreatic cancer. Characteristics associated with carrier status were inconsistent with previous investigations. Machine learning classifiers had a low performance in determining the carrier status of pancreatic cancer patients, while the same classifiers, when applied to breast cancer data as a positive control, had a higher performance that was comparable to that of the NCCN guideline. Interpretation: Our findings support the clinical significance of multigene panel testing for pancreatic cancer and indicate that at least 3.4% of Japanese patients may respond to poly (ADP ribose) polymerase inhibitor treatments. The difficulty in predicting carrier status suggests that offering germline genetic testing for all pancreatic cancer patients is reasonable.

  Study JGAS000346

• Target sequencing of 27 cancer-predisposing genes in Japanese pancreatic cancer patients

  Background: National Comprehensive Cancer Network (NCCN) recently recommended germline genetic testing for all pancreatic cancer patients. However, the genes targeted by genetic testing and the feasibility of selecting patients likely to carry pathogenic variants have not been sufficiently verified. The purpose of this study was to genetically characterize Japanese patients and examine whether the current guideline is applicable in this population. Methods: Using targeted sequencing, we analyzed the coding regions of 27 cancer-predisposing genes in 1,005 pancreatic cancer patients and 23,705 controls in Japan. We compared the pathogenic variant frequency between cases and controls and documented the demographic and clinical characteristics of carrier patients. We then examined if it was possible to use machine learning to predict carrier status based on those characteristics. Findings: We identified 205 pathogenic variants across the 27 genes. Pathogenic variants in BRCA2, ATM, and BRCA1 were significantly associated with pancreatic cancer. Characteristics associated with carrier status were inconsistent with previous investigations. Machine learning classifiers had a low performance in determining the carrier status of pancreatic cancer patients, while the same classifiers, when applied to breast cancer data as a positive control, had a higher performance that was comparable to that of the NCCN guideline. Interpretation: Our findings support the clinical significance of multigene panel testing for pancreatic cancer and indicate that at least 3.4% of Japanese patients may respond to poly (ADP ribose) polymerase inhibitor treatments. The difficulty in predicting carrier status suggests that offering germline genetic testing for all pancreatic cancer patients is reasonable.

  Study JGAS000327

• The MD Anderson Colorectal Cancer Case Control Study

  Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the US. Driven by common disease common variants hypothesis, genome-wide association studies only identified a number of common susceptibility loci that explained a small portion of CRC heritability. We conducted a case-control study using whole exome sequencing to identify rare genetic variants with intermediate effect size that predispose individuals to colorectal cancer.

  Study phs002691

• Project for Development of Innovative Research on Cancer Therapeutics;Shuttle system between petient-derived xenograft and ex vivo culture for innovative platform of evaluating drug sensitivity.

  We developed CTOS (cancer tissue-originated spheroid) panel covering diversity among patients for colorectal cancer, lung cancer and cervical small cell carcinoma. We then carried out exome sequence analysis of tumor tissues, cell lines and CTOS derived from patients to validate qualitative changes in preparation, culture, cell line, transplantation and passage of CTOS pathologically, biochemically, molecular biologically.

  Study JGAS000089

• Whole-genome sequencing identifies ADGRG6 enhancer mutations and FRS2 duplications as angiogenesis-related drivers in bladder cancer

  Bladder cancer is one of the most common and highly vascularized cancers. To better understand its genomic structure and underlying etiology, we conducted whole-genome sequencing in 65 urothelial bladder carcinomas (the most common type of bladder cancer) and identified recurrent genetic alterations in a set of angiogenesis genes, facilitating the understanding of molecular mechanisms underlying pathological angiogenesis in this type of cancer.

  Study EGAS00001003388

• Cancer Genomics, ICR, summary data

  DAC for summary level data from the Cancer Genomics group, Division of Genetics and Epidemiology at the Institute of Cancer Research, Sutton, UK.

  Dac EGAC50000000050

• GIST_SSGXVIII_trial_targeted_gene_sequencing

  Targeted cancer gene sequencing of samples enrolled in the SSGXVIII trial from Finland.

  Study EGAS00001001054

• The_genetic_evolution_of_precursor_lesions_in_pancreatic_cancer

  Mapping genetic evolution of pancreatic cancer precursor lesions such as IPMNs and PanINs.

  Study EGAS00001001573