12214 results for "cancer rna-seq"

in 70.01 milliseconds.

• LICA-CN project - 116 liver cancer cases

  LICA-CN project - 116 liver cancer cases

  Study EGAS00001002300

• PROstate Cancer Medically Optimized Genome Enhanced ThErapy (PROMOTE) of Castration Resistant Prostate Cancer (CRPC) Patients Treated with Abiraterone Acetate

  The Prostate Cancer Medically Optimized Genome-Enhanced Therapy (PROMOTE) study uses genetic clues in castration-resistant prostate cancer that may identify an individualized treatment approach for men with the disease. Understanding the molecular biology behind castration-resistant prostate cancer has led to more treatment options, but there are still no definite conclusions about which specific drug best treats patients - maximum suppression of cancer growth while minimizing side effects. The PROMOTE study explores the genetic characteristics of each tumor to predict these treatment paradigms for the future, resulting in more effective and less toxic options for patients. Our long-term goal is to improve treatments for men with advanced prostate cancer by using genomic sequencing to increase life span and quality of life. We also will uncover novel vulnerable targets in the cancer genome that may provide new drug therapies. PARTICIPATION Eligible participants are men: With castration-resistant prostate cancer or prostate cancer not responding to hormone treatments About to begin abiraterone acetate therapy Agreeable to undergoing two tumor biopsies During the study, participants travel to Mayo Clinic for an initial biopsy (before beginning abiraterone acetate) and a second biopsy approximately three months later. The cell tissue collected is analyzed to identify gene alterations in the tumor that could eventually be targeted with treatments. Tissue is preserved for future research. Participants can continue to be treated by their local cancer care team during this period and beyond. In addition, the Mayo team carefully monitors participants' cancer via follow-up studies and the genetic signature of tumors that were biopsied so that patients may benefit from future treatments.

  Study phs001141

• The International Consortium for Prostate Cancer Genetics Genome Wide Association Study of Familial Prostate Cancer

  Initially, the ICPCG focused largely on high-risk prostate cancer pedigrees using linkage analysis. However, association studies have also been informative to find prostate cancer susceptibility variants in the genome. We hypothesize that genome-wide (GW) association studies of familial cases of prostate cancer will have the power to identify rarer and perhaps less penetrant risk variants associated with prostate cancer than have been identified to date. Our approach will be to examine evidence for association in selected, independent cases from high-risk pedigrees; we hypothesize that they represent a more homogeneous set of cases with potentially different associations. Use of the 5M plus exome SNP platform will allow us to include in our search more rare variants in our search than have ever been investigated for prostate cancer. Aim 1. Identify a set of independent prostate cancer cases selected from ICPCG high-risk prostate cancer pedigrees that have 3 or more related prostate cancer cases and have an average age at diagnosis ≤ 75 years. Identify appropriate matched controls from participating ICPCG groups/ populations. Aim 2. Perform GW SNP genotyping with the Illumina 5M plus exome SNP set on the set of independent prostate cancer cases and controls described in Aim 1. Aim 3. Perform association analyses appropriately matching controls for different ICPCG populations and groups. There will be a two-stage design for confirmation. Aim 4. Test reported associations using the extensive sample set available to us by collaboration with the PRACTICAL consortium that has access to 50 000 DNA samples from 34 groups internationally (over 7,000 of whom are positive for prostate cancer family history).

  Study phs000733

• Single-cell ATAC-seq analysis for COVID19 patients

  While SARS-CoV-2 infection causes mild respiratory disease in most individuals, a small group of patients develops severe COVID-19. Dysfunctional innate immune responses have been identified to contribute to differences in COVID-19 severity, but the key regulators are still unknown. Here, we present an integrative single-cell epigenetics, transcriptomic, and genetics analysis of peripheral blood mononuclear cells from hospitalized and convalescent COVID-19 patients. In classical monocytes, we identified 41.3% of significantly up-regulated genes in hospitalized COVID-19 patients potentially induced by differential chromatin accessibility. Sub-clustering and motif-enrichment analyses of monocytes reveal disease condition-specific regulation by transcription factors, such as C/EBPs and SPI1, and their targets, including a long-noncoding RNA LUCAT1, which further regulates interferon responses and is associated with the need for oxygen supply of COVID-19 patients. The interaction between C/EBPs and LUCAT1 was validated through loss-of-function experiments. Finally, we investigated genetic risk variants that exhibit allele-specific open chromatin (ASoC) in promoters/enhancers of COVID-19 patients. Integrating our data with publicly available expression quantitative trait loci and chromosomal interactions indicates that ASoC SNP rs6800484-C is associated with lower expression of CCR2, which may contributeto higher viral loads in lungs and higher risk of COVID-19 hospitalization. Altogether, our study highlights the diverse genetic and epigenetic regulators that contribute to the innate immune responses of different COVID-19 patients.

  Study EGAS00001006559

• Multidimensional Proteomics analysis of intractable cancers with prospective observational cohort for precision medicine

  Multi-omics project of Non small cell Lung Cancer. Exome and RNAseq datasets were generated from normal-tumor pairs of Non small cell Lung Cancer patients from the retrospective cohort.

  Study EGAS50000000592

• germline variants in children with hematological cancer

  Trio parent-child whole exome sequencing has been used to identify cancer predisposing syndrome (CPS) in our pediatric patients with hematological cancer, and it was identified in 3.8% of the total number of patients(131).

  Study EGAS00001006907

• 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

• AVENIO Expanded ctDNA panel sequence alignments (BAMs) from plasma DNA of lung cancer patients from the OSCILLATE trial

  The AVENIO ctDNA Expanded Kit is a next-generation sequencing (NGS) liquid biopsy assay with a 77 gene panel (192 kb) containing genes in U.S. National Comprehensive Cancer Network (NCCN) Guidelines and emerging cancer biomarkers. This pan-cancer assay was applied to 100 plasma samples from patients with lung cancer undergoing treatment in the OSCILLATE trial. After 150 bp paired-end sequencing, reads were aligned to the human genome reference with the AVENIO Oncology Analysis Software. These files are the sorted non-deduplicated alignments generated by the analysis software used for subsequent variant, indel and CNV calling.

  Study EGAS50000000103

• 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

• Comprehensive molecular profiling for breast cancer patients and high-risk individuals.

  Although germ-line mutations in BRCA1 and BRCA2 gene are responsible for familial breast and ovarian cancer, the detailed mechanism of tumorigenesis is yet unknown. Here, we performed next-generation sequencing to determine the genomic profiles of familial breast cancer tumorigenesis. Target-capture sequencing of fresh-frozen or formalin-fixed-paraffin-embedded (FFPE) samples of breast cancer or normal breast tissue were performed.

  Study JGAS000368

• The landscape of somatic mutations in epigenetic regulators across 1000 pediatric cancer genomes

  To define the frequency and pattern of somatic mutations in epigenetic regulators in pediatric cancer, we sequenced 633 genes, encoding the majority of proteins involved in patterning the epigenome, in 1000 pediatric tumors spanning 21 different cancer subtypes. This analysis establishes an epigenetic landscape of pediatric cancer, which expands the knowledge for potential therapeutic targets and for developing personalized therapy.

  Study EGAS00001000449

• 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

• 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

• MPNST study - scRNA

  10X single nucleus RNA data of one MPNST patient, including one primary and five recurrence regions

  Dataset EGAD50000002565

• Multi-omics RNA profiling of glioblastoma patient tissues

  Multi-omics profiling of paired primary and recurrent glioblastoma patient tissues

  Dataset EGAD00010001895

• 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

• Pan Prostate Cancer Group Germany BAM files

  German early-onset prostate cancer whole-genome sequencing samples of the Pan-Prostate Cancer Genome (PPCG) project. Whole Genome Sequencing Illumina data from men with prostate cancer. Samples were taken from primary tissue obtained at prostatectomy with matched blood control.

  Dataset EGAD00001005997

• Clonal Lineage Tracing of Primary Human Cortical Progenitors, Cell Type Profiles in the Brain Vasculature and Genotyping Data for 22q11DS and Control iPS Lines

  We sought to characterize the cell types produced by individual human cortical progenitors and describe their lineage relationships. We labeled individual human cortical cells with a massively complex lentivirus library encoding a GFP reporter gene and a molecular barcode that could be captured by standard 3' scRNA-seq methodologies. We then cultured the labeled human cells for 6 weeks in either a 1) mouse cortical astrocyte co-culture system or 2) in the mouse cortex as a xenograft. In a separate experiment, we maintained human cortical tissue slices in organotypic slice culture for 12 days. GFP+ cells were then isolated by FACS and then captured on the 10x chromium scRNA-seq platform. An additional sample was labeled by lentivirus and briefly cultured for 3 days prior to being mixed with mouse 3T3 cells in order to perform a cell mixing experiment ("barnyard") to benchmark our methodologies. We found that human individual cortical progenitors gave rise to both excitatory and inhibitory neurons as well as glia.We also sought to characterize the adult brain vasculature in both vascular malformations and non-malformed tissue. We use the 10x chromium scRNA-seq platform across 10 individuals (5 control and 5 arteriovenous malformations). We find broad disregulation across multiple cell types including the immune cells and find a specific monocyte subtype to contribute to a rupture phenotype. We also find a novel population of fibromyocytes in both conditions.Finally, we confirmed the genotype status of iPS lines that were derived from either karyotypically normal control individuals or from DiGeorge Syndrome patients carrying the 22q11.2 deletion using the Illumina Infinium Global Screening Array v3.0.

  Study phs002624

• 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

• scRNA-seq analysis of HGSC tumors, including immune TME, before and after NACT

  Gene expression profiles of single cells from 26 tumor and ascites samples samples from 17 patients

  Dataset EGAD50000000862

• Targeted MCC-seq

  The capture panel targets the functional methylome in human whole blood. Regions incorporated in the panel design included hypomethylated windows generated from merged WGBS data.

  Dataset EGAD50000000286

• SCNA-Seq of tumor DNA samples

  Low coverage whole genome sequencing for the identification of somatic copy number alterations (SCNA) and focal amplification mapping of corresponding tumor material

  Dataset EGAD00001002150

• Bulk exome sequencing of primary GBM - SF 10360

  We performed bulk exome-seq on a primary GBM and a blood sample from SF10360

  Dataset EGAD00001002274

• ChIP sequencing from a collection of PFA tumors

  ChIP data from PFA (n = 10). Raw data provided as FASTQ. Data generated on Illumina NovaSeq 6000 PE50.

  Dataset EGAD00001009045

• Paired-end Whole Exome-seq analysis of the 3D spatially mapped GBM samples.

  Dataset contains 50 paired-end Whole Exome sequencing samples from 3 patients. 3 normal blood samples are also included.

  Dataset EGAD00001010289

• NiCOL Study Target-seq dataset

  10 samples sequenced in Target-sequencing of a panel of 571 genes (Illumina NovaSeq 6000) - Raw FASTQ data - Annotated VCF

  Dataset EGAD00001010911

• H3K27ac ChIPseq of cohesin-mutated and wildtype adult AMLs

  ChIP-seq targeting the H3K27ac histone modification in cohesin-mutated (STAG2 or RAD21 mutation) and cohesin wildtype (CTRL-AMLs) AMLs.

  Dataset EGAD00001011204

• 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

• 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

• FFPE_Normal_Panel_V3_Cancer_Panel

  FFPE normal panel generation for use with V3 cancer panel 0618521

  Study EGAS00001000836

• 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

• 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

• RNA-sequençing of 21 inflammatory hepatocellular adenomas and 1 non-tumoral sample

  Dataset EGAD00001005284

• Carcinoid study - RNASeq dataset

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

  Dataset EGAD00001000795

• 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

• SNP array datas of 'Matched' cancer/PNE

  SNP array data of 31 Matched cancer/PNE samples

  Study EGAS00001003331

• 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

• Fibroblast heterogeneity drives metastatic spread in breast cancer through distinct mechanisms

  The major cause of death among breast cancer patients is metastatic dissemination, suggesting that understanding the mechanisms driving this process remains an unmet medical need. Here, by concomitantly using 5 markers, we identify 4 Carcinoma-Associated Fibroblasts (CAF) subsets in primary tumors and corresponding metastatic lymph nodes (LN). Two CAF subsets, called CAF-S1 and CAF-S4, correlate with the proportion of cancer cells in invaded LN and exert distinct functions in tumor cell spread. CAF-S1 promote cancer cell migration and initiates an epithelial to mesenchymal transition through a CXCL12 / TGFb positive loop. For their part, the highly contractile CAF-S4 foster cancer cell motility and invasion in 3-dimensional matrix via Notch pathway activation. Finally, CAF-S1 and CAF-S4 accumulation in LN is a new prognostic factor at diagnostic, independent of breast cancer subtypes and LN status, strengthening the validity of our findings in human breast cancer pathophysiology.

  Study EGAS00001003238

• Mapping the Evolution of T Cell States During Response and Resistance to Adoptive Cellular Therapy

  We investigated single T cell transcriptional states that define donor lymphocyte infusion (DLI) response and resistance from cryopreserved bone marrow mononuclear cells from 15 patients with relapsed chronic myeloid leukemia (CML) after allogeneic hematopoietic stem cell transplant. By integrating bulk ATAC-seq data from sorted T cell populations from these bone marrow samples, we also defined gene regulatory networks that underlay these clusters.

  Study phs002877

• DAC for a single-cell multi-omic atlas of nodal B-cell non-Hodgkin lymphomas

  Nodal B-cell non-Hodgkin lymphomas (B-NHL) are a clinically diverse set of cancers thought to originate from distinct stages of B-cell maturation. To characterize intratumor heterogeneity across B-NHL entities, we performed CITE-Seq (cellular indexing of transcriptomes and epitopes) on 51 lymph node samples including mantle cell lymphoma (MCL, n = 8), follicular lymphoma (FL, n = 12), germinal center (GCB, n = 5) or activated B-cell (non-GCB/ABC, n = 7) diffuse large B-cell lymphoma (DLBCL) and marginal zone lymphoma (MZL, n = 11) tumors, in addition to non-malignant reactive lymph nodes (rLN, n = 8). We also performed 5 prime scRNA-seq with immune receptor profiling for 11 of these samples (2 rLN, 2 MCL, 3 FL, 2 DLBCL, and 2 MZL).

  Dac EGAC50000000226

• Modeling glioblastoma invasion using human brain organoids and single-cell transcriptomics

  We performed scRNA-seq of patient-derived glioblastoma cells alone or after co-culture with human iPSC-derived cerebral organoid cells. Transcriptional changes implicated in the invasion process that are coherent across patient samples indicate that GBM cells reactively upregulate genes required for their dispersion. Potential interactions between GBM and organoid cells identified by an in silico receptor-ligand pairing screen suggest functional therapeutic targets.

  Study EGAS00001003852

• ATAC_SEQ_MAIN___PHASE_1

  This is a study to test ATAC-seq protocols. CD4+ and CD8+ cells have been obtained from three different anatomical compartments. We aim to assay open-chromatin regions across these cells and perform comparative analyses.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 EGAS00001000947

• Investigation of chromatin accessibility in clear cell renal cell carcinoma using ATAC-seq

  To identify regions of open and accessible chromatin in clear cell renal cell carcinoma (ccRCC), we performed ATAC-seq on the 786-O, A-498, UM-RC-2 ccRCC 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 and processed narrowPeak fomats. Data were processed using the nf-core atacseq pipeline.

  Dataset EGAD50000001885

• cfMeDIP-seq for 18 patients with pleural mesothelioma

  The dataset contains cfMeDIP-sequencing data (bam files) for 18 plasma samples from pleural mesothelioma patients. The libraries were prepared according to the published protocol (Shen, S. Y., Burgener, J. M., Bratman, S. V. & De Carvalho, D. D. Preparation of cfMeDIP- seq libraries for methylome profiling of plasma cell-free DNA. Nat. Protoc. 14, 2749–2780 (2019)). Whole genome sequencing (WGS) was performed for pre-made libraries on NovaSeq X Plus with a 150 paired-end strategy. Low-quality reads and adapters were removed with Trim Galore version 0.6.6 (https://www.bioinformatics.babraham.ac.uk/projects/trim_galore). The trimmed reads were aligned to hg38 with Bowtie2 version 2.3.4.3. SAMTools version 1.9 was used to convert the SAM alignment files to BAM files, sort and index reads, and remove duplicates.

  Dataset EGAD50000002126

• DOGMA-seq data and analysis

  Data and analysis of DOGMA-seq assay of Lin- sorted live cells from bone marrow tissue of 12 patients with MDS or AML (before treatment with 5-azacytidine). Data files are paired-end reads in FASTQ format from the Illumina NovaSeq 6000 sequencer. Analysis files are outputs from Cellranger ARC: .h5 peaks and genes matrix file, atac_fragments.tsv.gz file and its index. Samples with ADT assay have analysis files from kallisto, bustools, and kite: ADT_features.txt, ADT_barcodes.txt, ADT_matrix.mtx.

  Dataset EGAD50000001377

• SUM-seq data for Primary T-cells differentiated to helper subtypes

  Briefly, naive CD4+ T cells were isolated from PBMCs obtained from buffy coats from three healthy human donors, and differentiated into Th0, iTreg, Th2, Th1, Th17, and IFN-β-activated subsets. This allowed us to study the differentiation of naive CD4+ T cells into distinct helper subsets under the influence of a specific cytokine environment. Following 5 days of differentiation, T cells were left unstimulated or re-stimulated with phorbol 12-myristate 13-acetate (PMA) and ionomycin to assess their functional responses. Thus, this SUM-seq experiment consisted of 36 multiplexed conditions (3 donors x 6 stimulations x with/without re-stimulation). Single-cell chromatin accessibility and gene expression data is provided as demultiplexed fastq files.

  Dataset EGAD50000001204

• GEX CITE-Seq performance dataset

  To understand the impact of enzymatic treatments on gene expression and epitope preservation on major immune cell populations, skin dissociation (SkinD) and solid soft tumor dissociation (TumorD) were tested on three healthy PBMC samples in triplicate (D1, D2, D3), against an untreated control. CITE-seq performance was assessed on a solid biopsy cohort of 11 samples (5 healthy skin samples, 3 primary melanoma samples, 3 melanoma metastasis samples) as well as on a liquid biopsy PBMC cohort consisting of three healthy donors and three immunotherapy-treated melanoma patients. This dataset contains the GEX data for each sample. Data is provided in the form of pooled BAM files. Linkage between samples, BAM files and hashtags is provided in a separate linkage file.

  Dataset EGAD00001008418

• ADT/SPEX CITE-Seq performance dataset

  To understand the impact of enzymatic treatments on gene expression and epitope preservation on major immune cell populations, skin dissociation (SkinD) and solid soft tumor dissociation (TumorD) were tested on three healthy PBMC samples in triplicate (D1, D2, D3), against an untreated control. CITE-seq performance was assessed on a solid biopsy cohort of 11 samples (5 healthy skin samples, 3 primary melanoma samples, 3 melanoma metastasis samples) as well as on a liquid biopsy PBMC cohort consisting of three healthy donors and three immunotherapy-treated melanoma patients. This dataset contains the ADT/SPEX data for each sample. Data is provided in the form of pooled BAM files. Linkage between samples, BAM files and hashtags is provided in a separate linkage file.

  Dataset EGAD00001008419

• 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

• Target bisulfite sequencing of endometrial cancer

  This study aims to investigate epigenetic alterations in the HLA-A locus in endometrial cancer. Targeted bisulfite sequencing was performed to evaluate DNA methylation status of the HLA-A region in a cohort of endometrial cancer samples. The resulting data were used to assess the association between HLA-A methylation and tumor immune microenvironment. These findings contribute to understanding the role of epigenetic regulation of antigen presentation in endometrial cancer.

  Study JGAS000897

• 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

• Study of pediatric hepatocellular carcinoma caused by bile salt export pump deficiency

  Hepatocellular carcinoma (HCC) is almost invariably associated with an underlying inflammatory state, whose direct contribution to the acquisition of critical genomic changes is unclear. We mapped the acquired genomic alterations in human and mouse HCCs induced by defects in hepatocyte biliary transporters, which expose hepatocytes to bile salts and cause the onset of chronic inflammation that develops into cancer. In both human and mouse cancer genomes we found few somatic point mutations with no impairment of cancer genes, but instead massive gene amplification and rearrangements. This genomic landscape differs greatly from that of virus- and alcohol-associated liver cancer. Copy number gains preferentially occurred at late stages of cancer development and frequently targeted the MAPK signaling pathway, and in particular direct regulators of JNK. The pharmacological inhibition of JNK retarded cancer progression in the mouse. Our study demonstrates that intrahepatic cholestasis leading to hepatocyte exposure to bile acids and inflammation promotes cancer through genomic modifications that can be clearly distinguished from those determined by other etiological factors.

  Study EGAS00001000749

• This study explored and validated the clinical application of targeted NGS of circulating tumor DNA in identifying tumor-specific mutations and uncovering clinical actionable targets in a variety of solid tumors in large patient cohorts.

  Cancer is a disease of genetic alterations. Comprehensive genetic diagnosis is needed to match each patient to appropriate cancer therapy. However, acquisition of representative tumor samples is invasive and often infeasible. Circulating tumor DNA (ctDNA) is a promising non-invasive biomarker for cancer mutational profiling. Here we implemented targeted next generation sequencing (NGS) with a customized pan-cancer gene panel on 605 clinical ctDNA samples in multiple cancer types. Overall, tumor-specific mutations were identified in 87% of ctDNA samples, with mutation spectra highly concordant with their matched tumor tissues. 71% of patients have at least one clinical actionable mutation with 76% of which have suggested drugs approved or in clinical trials. In particular, our study reveals a unique mutation spectrum in Chinese lung cancer patients, which could be used to guide treatment decision and monitor the appearance of drug-resistant mutations. Taken together, our study demonstrated the clinical utility of target NGS-based ctDNA mutational profiling to guide cancer treatment decision.

  Study EGAS00001002251

• 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

• 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

• Chugai_colorectal_organoid_sequencing

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

  Study EGAS00001000872

• Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci

  Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n=17) and DNA methylation (whole-genome bisulphite sequencing, n=10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis.

  Study EGAS00001002592

• Single-Cell RNA-Sequencing Analysis of Responses to Pembrolizumab in Sezary Syndrome

  This phase 2 single arm clinical trial assessed the efficacy of pembrolizumab in patients with previously treated mycosis fungoides or Sezary syndrome. Pembrolizumab was found to have a 38% overall response rate, and a 27% overall response rate in subjects with Sezary syndrome. We performed single-cell RNA-sequencing on samples collected before the first treatment and after 3 weeks of pembrolizumab treatment. Sequencing was performed on cryopreserved peripheral blood T-lymphocytes isolated from 6 trial participants, including 3 patients who responded to pembrolizumab treatment and 3 patients who did not respond. A total of 118,961 peripheral blood T-cells are included in this data set.

  Study phs002933

• Long-read single-cell RNA sequencing uncovers cell-type specific transcript regulation in COVID-19

  SARS-CoV-2 infection leads to extensive host transcriptomic changes, but the role of alternative splicing in shaping the immune response remains underexplored. Here, we present the first application of long-read single-cell RNA sequencing on nasopharyngeal swabs from COVID-19 patients and healthy controls to resolve transcript-level changes across cell types. Leveraging the strengths of long-read sequencing, we characterize alterations in both gene and isoform expression within cell populations of the upper respiratory tract—the primary site of SARS-CoV-2 entry. This approach provides new insights into how transcriptional regulation and splicing shape host immune responses to viral infection.

  Study EGAS50000001290

• Integrative single-cell and cell-free plasma RNA transcriptomics elucidates placental cellular dynamics

  The human placenta is a dynamic and cellular heterogeneous organ, which is critical in fetomaternal homeostasis and the development of preeclampsia. Previous work has shown that placenta-derived cell-free RNA increases during pregnancy. We applied large-scale microfluidic single-cell transcriptomic technology to comprehensively characterize cellular heterogeneity of the human placentas and identified multiple placental cell-type–specific gene signatures. Analysis of the cellular signature expression in maternal plasma enabled noninvasive delineation of the cellular dynamics of the placenta during pregnancy and the elucidation of extravillous trophoblastic dysfunction in early preeclampsia.

  Study EGAS00001002449

• RNA sequencing in primary inflammatory (TPP) macrophages treated with a MEK1/2 inhibitor

  By investigating an intergenic haplotype on chr21q22, independently linked to inflammatory bowel disease (IBD), ankylosing spondylitis, primary sclerosing cholangitis and Takayasu’s arteritis, we discover that the causal gene, ETS2, is a master regulator of inflammatory responses in human macrophages and delineate how the risk haplotype increases ETS2 expression. Using a database of cellular signatures, we identified drugs that could modulate this pathway. To validate the anti-inflammatory activity of one class of small molecules in vitro, we treated TPP macrophages with vehicle control or a selective, non-ATP competitive MEK inhibitor (PD-0325901) at 2 doses (100nM and 500nM) and performed RNA sequencing.

  Study EGAS00001007552

• Single-cell RNA sequencing of SI-NET

  Small intestinal neuroendocrine tumors (SI-NETs) arise from hormone-producing cells in the gut, yet the molecular changes driving malignant transformation remain poorly understood. Bulk tissue-based analyses make it challenging to distinguish signals derived from normal cells from those of normal hormone-producing cells. In this study, we analyzed SI-NETs at single-cell resolution and directly compared tumor cells with their corresponding normal hormone-producing counterparts using single-cell RNA sequencing. Tissue samples were obtained from two patients undergoing tumor resection surgery. Cells from corresponding normal intestinal mucosa and SI-NET tumors were isolated using specific markers and analyzed for direct comparison.

  Study EGAS50000001584

• Detroit Research on Cancer Survivors (ROCS) and Disparities and Cancer Epidemiology - Colorectal Cancer (DANCE)

  The goals for this study were as follows:1. Enroll a total of 5,060 African Americans newly diagnosed with cancer into the Detroit Research on Cancer Survivors (Detroit ROCS) Cohort. These population-based cases will be ascertained through the Detroit Metropolitan Detroit Cancer Surveillance System (MDCSS), a founding member of the NCI SEER Program. Participation at baseline will include a written, web-based, or telephone interview, saliva and/or blood collection, and tumor block retrieval, with detailed cancer-related information coming from the MDCSS registry and medical records.2. Enroll a subgroup of colorectal cancer patients identified through the Louisiana Tumor Registry (LTR). An additional 500 colorectal cancer patients, approximately half non-Hispanic white and half African American, will be identified through the LTR and enrolled into the ROCS protocol. The survey is the same survey administered to the ROCS cohort. The Louisiana (“DANCE-CRC”) cohort will not be followed beyond baseline, and blood will not be collected (tumor tissue, however, will be collected, deidentified, and sent for processing through Dr. Rozek's laboratory at Georgetown University).The proposed cohorts will provide for a broad research agenda evaluating cancer outcomes in African Americans across a variety of factors from individual, provider, health care system and community perspectives. These factors include tumor characteristics driving individualized treatment planning, quality of life after a diagnosis and recurrence. Utilizing the MDCSS registry, we will enroll a large population-based sample of African-American cases with lung, breast, colorectal, and prostate cancers and their caregivers resulting in a cohort that will provide substantial benefit to the cancer research community. KCI has a strong history of research in the African-American community and the faculty represents a breadth of experience that includes clinical oncology, genetic epidemiology, environmental exposures, quality of life, treatment decision making, racism/discrimination, and health behaviors. Drs. Schwartz and Beebe-Dimmer have been and will continue to be generous collaborators with other institutions to ensure that this resource will be extensively utilized. The proposed overall cohort will be the only one of its kind, to our knowledge, filling a substantial gap in our understanding of the determinants driving cancer outcomes in African Americans. In addition to registry data detailing cancer specifics, yearly surveys have collected information about individualized treatment experiences, heath histories, family histories, quality of life after a diagnosis, recurrence and caregiving. Population: Adult cancer survivors (see inclusion criteria in next section) Molecular Technologies: Genotyping: Infinium Expanded Multi-Ethnic Genotyping Array (MEGAEX) DNA Sequencing: Illumina NovaSeq X Plus using XLEAP-SBS (sequencing by synthesis) Whole genome sequencingPrincipal Findings: The preliminary data collected reinforces differences by race in factors affecting cancer outcomes. Variants in DNA damage repair genes and HOXB13 may be important cancer risk factors for Black men diagnosed with prostate cancer, and are more frequently observed in men with a family history of cancer. ROCS participants reported high rates of a family history of cancer. The high rate of eligibility for Cancer genetic counseling among ROCS participants supports the need for interventions to increase referrals and uptake of genetic counseling among African Americans 60% of ROCS participants reported participating in regular physical activity (PA), with 24% reporting ≥150 min/wk. There were no differences by sex, but prostate cancer survivors were the most likely to report participating in regular PA, whereas lung cancer survivors were the least likely. Survivors who reported participating in regular PA reported higher health-related quality of life and lower depression. More African American than White survivors reported financial hardship and limiting care. More White than African American survivors reported utilizing assets, while more African American survivors reported cancer-related debt. Data available in dbGaP: Individual phenotype data Individual genotype data Individual sequencing dataSample types: Germline DNA

  Study phs003116

• 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

• Intra-prostatic tumour evolution, steps in metastatic spread and histogenomic associations revealed by integration of multi-region whole genome sequencing with histopathological features

  We performed whole genome sequencing on 42 prostate cancer samples from the prostate, seminal vesicles and regional lymph nodes of five treatment-naive patients with locally advanced disease who underwent radical prostatectomy. Using cancer cell fractions computed from single nucleotide variants and copy number alterations, we reconstructed the tumour phylogenies, which in turn allowed us to infer key molecular steps in the progression of prostate cancer in these individuals. We mapped the clonal composition of cancer sampled across the prostate in each individual and inferred the routes of spread of cancer cells within the prostate and to seminal vesicles and lymph nodes.

  Study EGAS00001007438

• DNA Methylation Markers and Pancreatic Cancer Risk in 3 Cohort Studies (NHS, PHS, HPFS)

  Pancreatic cancer is the 4th leading cause of cancer deaths in the US. Due to the lack of early symptoms, pancreatic cancer is difficult to identify at early stages and no screening is available for the general population. Identifying pancreatic cancer at earlier stages could significantly improve survival with increased opportunities for surgery. New high-dimensional arrays designed to measure DNA methylation levels at hundreds of thousands of CpG sites throughout the genome have opened opportunities to examine the role of DNA methylation in cancer risk using blood samples. Using this method, archived samples from prospective studies can be used to examine early changes in the DNA methylation levels in individuals who develop cancer months or years later, providing new opportunities to better understand biological mechanisms and, perhaps, identify biomarkers for early detection. Pancreatic cancer cases and matched controls were obtained from 3 large cohort studies, the Nurses' Health Study (NHS), the Physician's Health Study (PHS), and the Health Professionals Follow-up Study (HPFS), to measure DNA methylation in stored buffy coats using a nested case-control study design.

  Study phs001917

• Genetic Epidemiology of Ovarian Cancer Histotypes

  Epithelial ovarian cancer is a highly fatal malignancy with known genetic etiology; however, it is estimated that a substantial portion of narrow sense heritability remains to be discovered. The goal of this research was to use genetic information from distantly related ovarian cancer cases to identify regions of the genome that may harbor rare risk variants for epithelial ovarian cancer. The study was conducted in the setting of the Utah Population Database, a statewide data resource in which extensive ancestry data are linked to Utah Cancer Registry records. Focusing on families with a statistically significant excess risk of epithelial ovarian cancer, we used the Infinium Global Screening Array v.3.0 to generate germline genotyping data for distantly related cases. We then applied Shared Genomic Segment Analysis to each set of related cases to identify genomic regions that may harbor ovarian cancer risk variants. Eleven regions were identified. Genotype data are available through dbGaP for one case from each pedigree. Genotype data from other ovarian cancer cases within the high-risk pedigrees as well as the pedigrees' corresponding structures can be requested and made available with approval from the Utah Resource for Genetic and Epidemiologic Research (RGE).

  Study phs003140

• noninvasive lung cancer subtyping

  Accurate diagnosis of lung cancer is important for treatment decision-making. Currently, the gold standard for diagnosing histological subtypes of lung cancer relies on tumor biopsies. Recently, liquid biopsy, particularly cell-free DNA (cfDNA), has shown promising results in cancer detection and classification. In this study, we investigated the potential of cfDNA methylome for the noninvasive classification of lung cancer histological subtypes. Specifically, we focused on the two most prevalent lung cancer subtypes, lung adenocarcinoma and lung squamous cell carcinoma. Using a fragment-based marker discovery approach, we identified robust subtype-specific methylation markers from tumor samples. These markers were successfully validated in independent cohorts and associated with subtype-specific transcription activity. Leveraging these markers, we constructed a subtype classification model using cfDNA methylation profiles, achieving an AUC of 0.808 in the cross-validation and an AUC of 0.747 in the independent validation. Additionally, tumor copy number variations inferred from cfDNA methylome analysis revealed potential implications for treatment selection. In summary, our study demonstrates the potential of cfDNA methylome analysis for noninvasively lung cancer subtyping, offering insights for cancer monitoring and early detection.

  Study EGAS00001007717

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

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

  Dataset EGAD50000000836

• Genetic Epidemiology of Lung Cancer Consortium GWAS of Familial Lung Cancer

  Familial lung cancer cases were collected by the Genetic Epidemiology of Lung Cancer Consortium (GELCC) recruitment sites: University of Cincinnati, Karmanos Cancer Institute at Wayne State University, Louisiana State University Health Sciences Center-New Orleans, Mayo Clinic, and Medical College of Ohio. Familial cases for this study came from three sources: 1) one case each from families (at least 3 affected lung cancer cases in the family) included in the linkage analysis; 2) one case from linkage-eligible families (at least 3 affected lung cancer cases in the family) but where there were insufficient biospecimens available to make them informative for linkage analysis; and 3) one case from families not eligible for the linkage study with a family history of at least one first or second degree relative affected with lung cancer. Unrelated controls were selected from 1) among the spouses of family members, thus matching on socio-economic status (SES) and ethnicity (typically) of the cases or 2) from case-control studies of lung cancer conducted in the same location in which the linkage families were collected and matched on age, sex, and race. All cases and controls self-reported as European American. Biospecimens used for normal DNA extraction included blood, saliva or mouthwash. Some samples underwent whole genome amplication.

  Study phs000629

• Discovery of Colorectal Cancer Susceptibility Genes in High-Risk Families

  Colorectal cancer remains one of the most common cancers in the US with 146,970 new diagnoses and 49,920 deaths estimated for 2009. Colon cancer is also one of the most familial of cancers. Individuals with a first-degree relative with colon cancer have a 2- to 3-fold increased risk, and those with more than one first-degree relative with colon cancer, or a single first-degree relative affected at age 50 years, have a 3- to 6-fold greater risk than those with no family history. The most prominent high-risk colorectal cancer susceptibility genes, APC, MLH1, MSH2, MSH6, and PTEN, were all discovered more than a decade ago. Currently, mutation screening of these genes, plus a short list of additional genes that are responsible for a very small fraction of colorectal cancer, plays an important role in the clinical management of individuals with a strong family history of the disease or syndromic evidence for the presence of a gene mutation. At the other end of the risk spectrum, genome-wide association studies have identified a number of common alleles with very modest effects on colorectal cancer risk; their clinical utility has yet to be established. However, taken together, the known spectrum of genetic effects only explain about one quarter of the overall familial excess of colorectal cancer. It should be emphasized that, at present, the vast majority of individuals seen at familial cancer clinics are counseled on the basis of their family history alone because they do not have mutations in the known susceptibility genes. Accordingly, the long-term objective of this project is to identify the majority of genes responsible for the unexplained component of inherited colorectal cancer risk. Nextgen DNA sequencing is well suited for application to research questions in genetic susceptibility for which linkage analysis is confounded by extensive genetic heterogeneity. Taking advantage of unparalleled familial cancer genetics resources available through the Utah Population Database, candidate genes have been identified by sequencing all of the gene exons in the human genome from a series of colorectal cancer cases with a very strong family history of colorectal cancer not explained by one of the currently known high-risk susceptibility genes.

  Study phs001787

• RNAseq_Pulldown_

  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. In this experiment cDNA derived form Breast Cancer Cell lines was used in an Agilent whole exome pulldown experiment.

  Study EGAS00001000230

• Automated system for scoring hematoxylin and eosin-stained ovarian cancer sections by identifying single cells uncovered that stromal cell ratio is a significant predictor for overall survival and progression-free survival.

  Concerted efforts in genomic studies have revealed profound insights in prognostic ovarian cancer subtypes. On the other hand, abundant histology slides have been generated to date, yet their uses remain very limited and largely qualitative. Our goal is to develop automated histology analysis as an alternative subtyping technology for ovarian cancer that is cost-efficient and do not rely on DNA quality. We develop an automated system for scoring hematoxylin and eosin-stained (H&E) primary tumour sections of 91 late-stage ovarian cancer to identify single cells including cancer and stromal cells. We demonstrated high accuracy of our system based on expert pathologists’ scores (cancer=97.1%, stromal=89.1%) as well as compared to immunohistochemistry scoring (correlation=0.87). Quantitative stromal cell ratio is significantly associated with poor overall survival after controlling for clinical parameters including debulking status and age (multivariate analysis p=0.0021, HR=2.54, CI=1.40-4.60) and progression-free survival (multivariate analysis p=0.022, HR=1.75, CI=1.09–2.82). We demonstrate how automated image analysis enables objective quantification of microenvironmental composition of ovarian tumours. Our analysis reveals a strong effect of the tumour microenvironment on ovarian cancer progression and highlights the potential of therapeutic interventions that target the stromal compartment or cancer-stroma signalling in the stroma-high, late-stage ovarian cancer subset.

  Study EGAS00001001694

• 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

• Ontario Institute for Cancer Research; Biliary Tract Cancer

  Next Generation Sequencing data from Biliary Tract cancers

  Study EGAS50000000972

• 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

• IACS treatment on breast cancer bone metastases

  Off-target effect of IACS on breast cancer bone metastases.

  Study EGAS00001006908

• β-catenin ChIP sequencing in HCC models.

  This dataset contains ChIP sequencing data for β-catenin, H3K27ac and H3K27me3 from three HCC cell lines and five tumour organoids under normal conditions and oleic acid treatment.

  Dataset EGAD50000001816

• Primary human hepatocyte ATAC-seq

  Profiling the chromatin accessibility landscape of cultured primary human hepatocytes (PHH) from three female and three male adult, non-diabetic donors.

  Dataset EGAD50000001751

• Centroblast Cohort

  miRNA-seq Cohort of 15 Benign Centroblasts

  Dataset EGAD00001001075

• Bulk exome sequencing of primary GBM - SF 10282

  We performed bulk exome-seq on a primary GBM and a blood sample from SF10282

  Dataset EGAD00001002275

• Bulk exome sequencing of primary GBM - SF 10345

  We performed bulk exome-seq on a primary GBM and a blood sample from SF10345

  Dataset EGAD00001002273

• ChIP-Seq of human stimulated and cultured CD4+ Treg cells

  This dataset includes whole genome sequence data for ChIPmentation assays (18 H3K4me3, 20 H3K27ac and 3 input samples) of human stimulated and cultured CD4+ Treg cells.

  Dataset EGAD00001005816

• Breast Cancer Family Registry

  The Breast Cancer Family Registry (BCFR) is a multi-center prospective cohort, comprised of over 30,000 women and men from nearly 12,000 families from the United States, Canada, and Australia. Our BCFR resource has been used, and continues to be used, by breast cancer researchers around the world in order to find new ways to prevent, diagnose, and treat cancer. The BCFR provides an extensive and diverse range of resources, expertise, and specialized skills, and has several unique strengths: 1) the collection of a large number of individuals and families across a wide spectrum of breast cancer risk, including both affected and unaffected individuals; 2) the large collection of families with early-onset breast cancer; 3) the large collection of racial/ethnic minority families not replicated elsewhere; 4) the extensive molecular characterization performed to date; and 5) active follow-up of both probands and family members. Thus, the BCFR comprises a unique cohort of probands and family members at familial/genetic risk of breast cancer that will continue to facilitate a wide range of research studies, such as gene discovery, examination of cancer-related outcomes and risk factors in high-risk subjects, investigation of novel behavioral interventions, and cancer prevention trials among at-risk family members. Consequently, the BCFR Cohort, as one of the few cohorts available worldwide with biospecimens and extensive molecular and genetic characterization, combined with epidemiologic data and long-term follow up, will be an invaluable resource for translational research in the genetic epidemiology of breast cancer.

  Study phs002835

• Colon Cancer Family Registry (Colon CFR)

  The Colon Cancer Family Registry Cohort (CCFRC www.coloncfr.org) is a cohort of families recruited through six study sites located in the USA, Canada, Australia, and New Zealand. The CCFRC was formed as a resource to support studies on the etiology, prevention, and clinical management of colorectal cancer. Recruitment protocols fall broadly into two main categories: population-based and clinic-based ascertainment. Between 1998 and 2013, the CCFR recruited and interviewed probands who were either recently diagnosed with colorectal cancer that was reported to state or regional population cancer registries in the United States (Washington, California, Arizona, Minnesota, Colorado, New Hampshire, North Carolina, and Hawaii), Australia (Victoria), and Canada (Ontario) or were from multiple-case families referred to family-cancer clinics in the United States (Mayo Clinic in Rochester, Minnesota, and Cleveland Clinic in Cleveland, Ohio), Australia (Melbourne, Adelaide, Perth, Brisbane, and Sydney), New Zealand (Auckland), and Canada. Cases with known familial adenomatous polyposis were excluded. Once recruited, probands were asked for permission to contact their relatives for recruitment. Collectively, we have enrolled 42,49874 participants in 15,048 families who participated in standardized protocols used to collect information regarding family cancer history and colorectal cancer risk factors and biospecimens. All participants of population-based case families (excluding control-families) and clinic-based families are asked to provide updates on their personal and family history of cancer as well as their history of surgery, cancer screening, and some risk factors every 4-5 years either by telephone interview or by self-completed questionnaire via mail or online (PMID: 17982118).

  Study phs002733

• Spatial transcriptome analysis of aging of healthy skin samples

  Previous studies have revealed that skin T cells accumulate and maintain immune responses in the elderly. However, we questioned why these functional T cells fail to recognize and eliminate malignant cells, making elderly skin more prone to developing malignant tumors. To address this question, we examined the overall skin microenvironment in aging using Xenium digital spatial RNA sequencing.

  Study JGAS000771

• Whole blood transcriptomics analysis in Antiphospholipid syndrome in patients with Systemic Lupus Erythematosus

  We analyzed whole-blood RNA-sequencing data from 299 SLE patients (108 SLE-aPL-positive, including 67 SLE-APS; 191 SLE-aPL-negative) and 72 matched healthy controls (HC). Pathway enrichment analysis, unsupervised WGCNA analysis and machine learning were applied to distinguish disease endotypes. Deconvolution analysis was performed to characterize the peripheral blood immune cell profile.

  Study EGAS00001007750

• CLUSTER consortium RNAseq CD19 B cell dataset of UK JIA patients.

  This study examines B cell transcriptomic profiles in Juvenile Idiopathic Arthritis (JIA) patients to investigate molecular mechanisms underlying disease heterogeneity. CD19+ B cells were isolated from peripheral blood samples and subjected to RNA sequencing to characterise gene expression patterns. The dataset includes patients with documented uveitis status to enable investigation of B cell contributions to the common JIA comorbidity.

  Study EGAS50000001123

• Defective homologous recombination in HCC

  Backgrounds and Aims: We performed an in-depth examination of pathogenic germline (PGVs) and somatic variants in DNA damage response (DDR) genes in hepatocellular carcinoma (HCC) to explore their clinical and genomic impacts. Approach and Results: We used a merged whole exome or RNA sequencing dataset derived from in-house (n=230) and TCGA (n=362) databases of multiethnic HCC samples.

  Study EGAS00001006599

• The Berlin (BLN) panel of glioblastoma cell lines: RNAseq of human gliomasphere cell lines and matched parental tumors

  We generated a panel of nine glioma stem-like cell lines under serum-free cell culture conditions from human glioblastoma samples. In addition to clinical annotation, MR imaging and histological characterization of the parental tumor, as well as xenograft studies of tumorigenecity, transcriptomic profiling of tumor/cell line pairs by RNA sequencing has been performed.

  Study EGAS00001001167

• Determining off-target effects of splice-switching antisense oligonucleotides using short read RNAseq in neuronally differentiated human induced pluripotent stem cells

  Splice-switching antisense oligonucleotides (AONs) are designed to modulate pre-mRNA splicing, thereby for instance restoring protein expression or modifying the eventual protein to restore its function or reduce its toxicity. To determine off-target effects, RNA from neuronally differentiated human induced pluripotent stem cells transfected with splice-switching AONs was sequenced.

  Study EGAS50000001222