Search Results - EGA European Genome-Phenome Archive

Integrating Genomic and Transcriptomic Data to Identify Breast Cancer Susceptibility Genes

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

Study phs003535

NHLBI TOPMed: Lung Tissue Research Consortium (LTRC)

Chronic obstructive pulmonary disease (COPD), a disease state characterized by airflow limitation that is not fully reversible, is the third leading cause of death in the U.S. COPD is a heterogeneous syndrome, with affected individuals demonstrating marked differences in lung structure (emphysema vs. airway disease); physiology (airflow obstruction); and other clinical features (e.g., exacerbations, co-morbid illnesses). Multiple genomic regions influencing COPD susceptibility have been identified by genome-wide association studies (GWAS), and rare coding variants can also influence risk for COPD. However, only a small percentage of the estimated heritability for COPD risk can be explained by known genetic loci. Like most complex diseases, COPD is influenced by multiple genetic determinants (each with modest individual effects). Emerging evidence supports the paradigm that complex disease genetic determinants are part of a network of interacting genes and proteins; perturbations of this network can increase disease risk. To identify this network, multiple Omics data will need to be analyzed with methods to account for nonlinear relationships and interactions between key genes and proteins. Our overall hypothesis is that integrated network analysis of genetic, transcriptomic, proteomic, and epigenetic data from biospecimens ranging from lung tissue to nasal epithelial cells to blood in highly phenotyped subjects will provide insights into COPD pathogenesis and heterogeneity. We will leverage the well-phenotyped, NHLBI-funded Lung Tissue Research Consortium (LTRC) to address these questions. We will perform multi-omics analysis in 1548 lung tissue and blood samples from the LTRC. With these multi-omics data, we will utilize a systems biology approach to understand relationships between multiple genetic determinants and multiple types of Omics data. We will begin by performing single Omics analyses in COPD vs. control lung, nasal, and blood samples. Next, we will integrate single Omics data with genetic variants identified by WGS to assist in fine mapping genetic determinants of COPD. We will then perform integrated network analysis of COPD with genetic and multiple Omics data using correlation-based, gene regulatory, and Bayesian networks. Subjects were recruited from Mayo Clinic, Universities of Colorado, Michigan, and Pittsburgh, and Temple University.

Study phs001662

METSIM (METabolic Syndrome In Men) Study

The METSIM Study includes 10,197 men, aged from 45 to 73 years, randomly selected from the population register of the town of Kuopio, Eastern Finland, and examined in 2005-2010. The aim of the study is to investigate genetic and non-genetic factors associated with the risk of type 2 diabetes (T2D), cardiovascular disease (CVD), and insulin resistance-related traits in a cross-sectional and longitudinal setting. Study protocol includes collection of data on CVD risk factors (smoking, exercise, diet, history of chronic diseases including coronary heart disease, stroke, cardiac failure, medication, history of diabetes or early onset coronary heart disease in the family), questionnaire on the FINDRISC Score, measurement of height, weight, waist, hip, blood pressure, and bioimpedance for the evaluation of fat percentage. July 2016 - The first study release (v1) included phenotype and whole exome sequencing (WES) data of n=982 participants in substudy: Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Project 1: Metabolic Syndrome in Men Study (METSIM) - phs001100.v2.p1. The second study release (v2) included phenotype data for the entire METSIM cohort and made two additional substudies available, phs000919.v1.p1 and phs000752.v1.p1. The third study release (v3) made three subcutaneous adipose biopsy substudies available, phs003385.v1.p1, phs003386.v1.p1, and phs003387.v1.p1.The fourth study release (v4) added phenotype data for the subcutaneous adipose biopsies, made two additional substudies available, phs01579.v1.p1 and phs004033.v1.p1, and is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" section of this top-level study page phs000743 METSIM Study. phs000752 METSIM FinMetSeq Exome Sequencing phs000919 METSIM GWAS and Exome Chip phs001100 METSIM T2D-GENES Exome Sequencingphs001579 METSIM CCDG Whole Genome Sequencingphs003385 METSIM Subcutaneous Adipose Needle Biopsy RNA-Seq phs003386 METSIM Subcutaneous Adipose Needle Biopsy ATAC-Seq phs003387 METSIM Subcutaneous Adipose Surgical Biopsy RNA-Seqphs004033 METSIM Metabolomics

Study phs000743

Upcycling and merging data to challenge the dogma and identify new therapeutic targets for Glioblastoma

Glioblastoma is the most common brain tumour. Characterised by a poor prognosis and its recurrence after multimodal treatments, the search for preventable risk factors has been mainly inconclusive up to date. Recently, the data merge from datasetsdeposited at the EGA allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. Challenges in glioblastoma research As for virtually all cancer types, many efforts have been made to unveil the molecular features responsible of the disease, and several cellular pathways have indeed been identified as being frequently mutated in glioblastoma. Nonetheless, targeted therapies based on identified genes have so far failed to improve outcome, thus survival mostly relies on a standard treatment unchanged since 2005. This is a frustrating situation for both the scientific and medical communities, and above all for the patients, still facing a dreadful path. Some researchers hypothesised that this may be due to the inability to efficiently target cancer stem cells, the originators of the other cell types, thus inducing cancer relapse. In 2019 Charles P. Couturier and colleagues sequenced RNA from single cells of freshly excised glioblastomas of 16 patients, and demonstrated that glioblastoma cells replicate normal brain cell development with a conserved neural cancer cell hierarchy centered around glial progenitor-like cells. In this way, they helped identify the possible target cells to improve efficacy and durability of treatment. Data upcycling at the EGA: the glioblastoma case study Single cell RNA sequencing is generated with a laborious and expensive protocol. The quality of the starting material is crucial (cells sample freshly extracted from the patients) and often several attempts are needed before producing reliable quality sequencing results. Collecting big numbers of patients is also challenging. The sequencing data produced by Kevin Petrecca’s group in Montreal, Canada and deposited at the EGA (EGAS00001004422) was recently upcycled by Lin Wang in San Francisco, California and pooled with their freshly produced ones, and then deposited at the EGA as Dataset EGAS00001004909 The data merge allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. They profiled 86 primary-recurrent patient-matched paired glioblastoma samples with single-nucleus RNA, among other techniques. These very comprehensive results lead the team to challenge the findings from several other cancer fields where chemotherapy standard chemo-radiation therapy selection pressure at the level of genomic alterations; this is indeed not the case for glioblastoma, where the pressure results in phenotypic transition between cellular states. Several technical controls were made to ensure that the merge of the data was not introducing a bias in the results, and an Inter-table analysis demonstrated nearly equal contribution to overall variance from each of the studies included, indicating that the findings were not due to inter-laboratory technical effect. A novel principal-component analysis showed that the largest contribution to variation in primary glioblastoma neoplastic cells was an axis between MES (mesenchymal) and proneural expression programs. In summary, treating glioblastoma often makes a MES, as commented by Lucy Stead about this remarkable work. Check Aaron Diaz’s team Nature Cancer paper, with strong technical tools, state of the art analysis and data from different sources converging to the same outcomes that made possible a significant step toward a better handling of a frightful cancer. References Couturier, C.P., Ayyadhury, S., Le, P.U. et al. Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy. Nat Commun 11, 3406 (2020). Stead, L.F. Treating glioblastoma often makes a MES. Nat Cancer 3, 1446–1448 (2022). Wang, L., Jung, J., Babikir, H. et al. A single-cell atlas of glioblastoma evolution under therapy reveals cell-intrinsic and cell-extrinsic therapeutic targets. Nat Cancer 3, 1534–1552 (2022). Related links: Kevin Petrecca’s group dataset deposited at the EGA: EGAS00001004422 Lin Wang dataset deposited at the EGA: EGAS00001004909

Blog upcycling-and-merging-data-to-challenge-glioblastoma

Chromatin profiles classify castration-resistant prostate cancers suggesting therapeutic targets

Untreated prostate cancers rely on androgen receptor (AR) signaling for growth and survival, forming the basis for the initial efficacy of androgen deprivation therapy (ADT). Yet, the disease can relapse and progress to a lethal stage termed castration-resistant prostate cancer (CRPC). Reactivation of AR signaling represents the most common driver of CRPC growth and next generation AR signaling inhibitors (ARSIs) are now used in combination with ADT as a first line therapy. However, ARSIs can result in selective pressure generating AR-independent tumors. The transition from AR-dependence frequently accompanies a change in phenotype resembling developmental trans-differentiation or ‘lineage plasticity’. Neuroendocrine prostate cancer, which lacks a defined pathologic classification, is the most studied type of lineage plasticity. However, most AR-null tumors do not exhibit neuroendocrine features and are classified as ‘double-negative prostate cancer’, the drivers of which are poorly defined. Lineage plasticity studies in CRPC are limited by the lack of genetically defined patient-derived models that recapitulate the disease spectrum. To address this, we developed a biobank of organoids generated from patient biopsies to study the landscape of metastatic CRPC and allow for functional validation assays. Proteins called transcription factors (TFs) are drivers of tumor lineage plasticity. To identify the key TFs that drive the growth of AR-independent tumors, we integrated epigenetic and transcriptomic data generated from CRPC models. By presenting a map of the chromatin accessibility and transcriptomic landscape of CRPC using a diverse biobank of organoids, PDXs and cell lines that recapitulate the heterogeneity of metastatic prostate cancer, we validate CRPC-AR and CRPC-NE subtypes and reveal two subtypes of AR-negative/low samples as well as their respective masterTFs. Additional analysis revealed a model in which YAP, TAZ, TEAD and AP-1 function together and drive oncogenic growth in CRPC-SCL samples. Overall, we show here how an approach to stratify CRPC patients into four subtypes using their transcriptomic signatures can potentially inform upon appropriate clinical decisions.

Study EGAS00001006059

Scottish High Grade Serous Ovarian Cancer

Scottish HGSOC samples were collected via local Bioresource facilities at Edinburgh, Glasgow, Dundee and Aberdeen and stored in liquid Nitrogen until required. HGSOC patients were determined from pathology records and were included in the study where there was matched tumour and whole blood samples. On receipt of tumour material the tumour was processed as follows: firstly, the tumour sample was divided into two for DNA and RNA extraction. Slivers of tissue were cut from the front and rear faces of the DNA sample, then fixed in formalin and embedded in paraffin wax. Sections from the front and rear tissues from all samples were examined by H&E staining supplemented by WT1/p53 immunohistochemistry if required. Following pathology review, samples were only included if they met the following criteria: they were confirmed as HGSOC and there was greater than 40% tumour cellularity throughout the tumour, determined using the H&E sections. Somatic DNA was extracted using the Qiagen DNeasy Blood and tissue kit (cat no 69504). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including RNase digestion step). Germline DNA was extracted from 1-3ml whole blood using the Qiagen FlexiGene kit (cat no 51206) following the manufacturers recommended protocol. The resulting DNA underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as surrogate measures of DNA purity. A260/280 had to be 1.8 or greater and A260/230 had to be 2.0 or greater. Then, DNA was quantified using LifeTechnologies Qubit dsDNA BR kit (cat no Q32850) and we required a minimum of 50ul at 25ng/ul for WGS. Thirdly, DNA was diluted to 25ng/ul and a representative sample was loaded onto a 0.8% TAE gel, ran at 100v for 60mins and then imaged using a BioRad ChemiDoc imaging system to visualise the DNA quality. Only when all 4 quality control requirements were satisfied was the DNA sequenced. The DNA was sequenced at the Glasgow Precision Oncology Laboratories.

Study EGAS00001004410

Evolution and clinical impact of genetic epistasis within EGFR-mutant lung cancers

The current understanding of tumorigenesis is largely centered on a monogenic driver oncogene model. This paradigm is incompatible with the prevailing clinical experience in most solid malignancies: monotherapy with a drug directed against an individual oncogenic driver typically results in incomplete clinical responses and eventual tumor progression1-7. By profiling the somatic genetic alterations present in over 2,000 cases of lung cancer, the leading cause of cancer mortality worldwide, we show that combinations of functional genetic alterations, i.e. genetic collectives dominate the landscape of advanced-stage disease. We highlight this polygenic landscape and evolution of advanced-stage non-small cell lung cancer (NSCLC) through the spatial-temporal genomic profiling of 7 distinct tumor biopsy specimens and 6 plasma specimens obtained from an EGFR-mutant NSCLC patient at (1) initial diagnosis of early-stage disease, (2) metastatic progression, (3) sequential treatment and resistance to 2 EGFR inhibitors, (4) death. The comprehensive genomic analysis of this case, coupled with circulating free (cf) tumor DNA profiling of additional advanced-stage EGFR-mutant NSCLC clinical cohorts with associated treatment responses uncovered features of evolutionary selection for multiple concurrent gene alterations: including the presence of EGFR inhibitor-sensitive (EGFRL858R;EGFRexon19del) or inhibitor-resistant (EGFRT790M;EGFRC797S) forms of oncogenic EGFR along with cell cycle gene alterations (e.g. in CDK4/6, CCNE1, RB1) and activating alterations in WNT/β-catenin and PI3K pathway genes, which our data suggest can cooperatively impart non-redundant functions to limit EGFR targeted therapy response and/or promote tumor progression. Moreover, evidence of an unanticipated parallel evolution of both EGFR T790M and two distinct forms of oncogenic PIK3CA was observed. Our study provides a large-scale clinical and genetic dataset of advanced-stage EGFR-mutant NSCLC, a rationale for specific polytherapy strategies such as EGFR and CDK4/6 inhibitor co-treatment to potentially enhance clinical outcomes, and prompts a re-evaluation of the prevailing paradigm of monogenic-based molecular stratification for targeted therapy. Instead, our findings highlight an alternative model of genetic collectives that operate through epistasis to drive lung cancer progression and therapy resistance.

Study EGAS00001002604

Identifying transcriptional programs underlying anti-EGFR small molecule response and resistance with TraCe-seq

Genetic and non-genetic heterogeneity within cancer cell populations represents a major challenge to anti-cancer therapies. We currently lack robust methods to determine how pre-existing and adaptive features affect cellular responses to therapies. Here, by conducting clonal fitness mapping and transcriptional characterization using expressed barcodes and single-cell RNA-sequencing, we have developed TraCe-seq, a method that captures at clonal resolution the origin, fate, and differential early adaptive transcriptional programs of cells in a complex population in response to distinct treatments. We used TraCe-seq to benchmark how next-generation dual EGFR inhibitors-degraders compare to standard EGFR kinase inhibitors in EGFR-mutant lung cancer cells. To QC the TraCe-seq strategy, single-cell RNA-seq libraries were generated from a variety of human cancer cell lines transduced with the TraCe-seq library to validate the TraCe-seq strategy. Specifically, 5 different cell lines (PC9, MCF-10A, MDA-MB-231, NCI-H358, and NCI-H1373) were each transduced with a unique TraCe-seq barcode. The transduced cells were selected with puromycin only, dissociated to single cell suspensions, and then mixed together. The complex mixture of the 5 cell lines was profiled by 10X scRNA-seq. Furthermore, transduced NCI-H1373 cells were sorted by FACS to enrich for the top 50% of eGFP positive cells, and sorted cells were cultured briefly and used to construct scRNA-seq libraries and profiled by 10x scRNA-seq. To carry out the full TraCe-seq experiment, ~600 PC9 cells carrying unique TraCe-seq barcodes were expanded over 12 doublings to establish the barcoded population. A subset of the barcoded PC9 population was used to generate scRNA-seq libraries and profiled by 10x scRNA-seq prior to treatment to establish a baseline transcription profile for each barcoded clone. The rest of the cells were then treated for four days with 1 µM erlotinib, 1 µM GNE-069, or 1 µM GNE-104 respectively. scRNA-seq libraries were then generated form the treated cells and profiled by 10x scRNA-seq.

Study EGAS00001005405

Expression Quantitative Trait Locus Mapping Studies in Mid-Secretory Phase Endometrial Cells Identifies HLA-F and TAP2 as Fecundability-Associated Genes

We performed an unbiased genome-wide expression quantitative trait locus (eQTL) mapping study to identify common regulatory (expression) single nucleotide polymorphisms (eSNPs) in mid-secretory endometrium, corresponding to the luteal phase of the ovarian cycle. Biopsies were collected from 58 women with two or more early pregnancy losses and 53 of these samples passed all quality control. RNA was extracted from endometrial biopsies and DNA was extracted for sequencing from blood. Gene expression data can be found at NCBI GEO Series GSE77688.

Study phs001146

Accurate Genome-Wide Germline DNA Profiling from Decade-Old Archival Tissue Specimens

We evaluate the validity of repurposing archival tissue specimens for germline genetic studies. We performed lc-WGS and imputed genotypes on 10 pairs of matching blood and tumor tissue and benchmarked the accuracy of genome-wide genotypes, HLA haplotypes, and several polygenic risk scores (PRSs). The reported results indicate the high accuracy of germline genotypes and haplotypes obtained from archival tissue DNA. Using this methodology, we estimate breast cancer PRS in 36 Ductal carcinoma in situ (DCIS) patients and demonstrate its association with breast cancer subsequent event (BCSE).  

Study phs002865

Characterization of CNS Metastases

Metastatic disease to the central nervous system (CNS) is devastating, with a poor prognosis. There are limited treatment options for patients with CNS metastases, and in particular with leptomeningeal carcinomatosis (LMD). In this study, we evaluated the molecular and cellular features of parenchymal brain metastases and LMD. We used single-cell RNA and cell-free DNA profiling of CSF from patients with LMD receiving immunotherapy to demonstrate shifts in the liquid LMD tumor microenvironment. We also characterize the tumor microenvironment of parenchymal brain metastases using single cell sequencing, before and after treatment with immunotherapy.

Study phs002416

Organoid Profiling Identifies Common Responders to Chemotherapy in Pancreatic Cancer

We generated a collection of patient-derived pancreatic normal and cancer organoids. We performed whole genome sequencing, targeted exome sequencing, and RNA sequencing on organoids as well as matched tumor and normal tissue if available. This dataset is a valuable resource for pancreas cancer researchers, and those looking to compare primary tissue to organoid culture. In our linked publication, we show that pancreatic cancer organoids recapitulate the mutational spectrum of pancreatic cancer. Furthermore, RNA sequencing of organoids demonstrates the presence of both transcriptional subtypes of pancreas cancer.

Study phs001611

Differential Mutations in Matched Primary and Metastatic Colorectal Cancers

This study compares DNA mutations detected in matched primary and metastatic colorectal cancer samples from 18 individuals across 1,321 genes. We found many more mutations were shared between tumor pairs (avg. 33.3 mutations/tumor) than were discordant (avg. 2.3 mutations / tumor). Nearly all tumors showed at least one discordance, and these were observed in genes known to be involved in colorectal cancer progression. Therefore, although primary and metastatic colorectal tumors are highly genetically concordant, evidence exists for discordance, which has clinical implications especially in situations of chemotherapy resistance or insensitivity.

Study phs001084

Breakpoint detection using long insert whole genome sequencing

In this study, we hypothesize that shallow long insert whole genome sequencing (LI-WGS) increases our power for detecting breakpoints compared to shallow short insert WGS. We performed a priori analyses to demonstrate the benefits of LI-WGS, developed a long insert library preparation protocol based off Illumina's protocol, and compared LI-WGS against short insert WGS on test samples. We then used long insert WGS to identify translocations and copy number changes in tumor and germline samples collected from cancer patients with different malignancies.

Study phs000646

Pharmacogenomic Analysis of Microtubule Targeting Agent Response and Toxicity

Microtubule targeting agents are commonly prescribed for early and metastatic breast cancer and other solid tumors. However, interindividual variability in microtubule targeting drug response and toxicity can cause limited therapeutic benefit and impact quality of life. In the present study, genome-wide analyses were performed to investigate how genetic factors can be used to increase prediction of treatment response and toxicity, identify genes or gene pathways associated with chemotherapy-induced neurotoxicity, and inform further in vitro studies that may help isolate differences in response and toxicity of microtubule targeting agents.

Study phs002060

Genome Wide Association Study of Subjects with Myalgic Encephalomyelitis (ME)/Chronic Fatigue Syndrome (CFS)

Myalgic encephalomyelitis, also known as chronic fatigue syndrome or ME/CFS, is a complex and heterogeneous disease that severely impacts the health and quality of life of those afflicted. Several lines of evidence support the possibility that ME/CFS development may involve a heritable component. In this pilot study, 42 cases that meet the diagnostic criteria of ME/CFS and 38 healthy controls were consented into this study. The goal of this study was to identify candidate polymorphisms that can be used for a large multi-center screening study.

Study phs001015

Nivolumab and Ipilimumab and Radiation Therapy in Microsatellite Stable (MSS) and Microsatellite Instable (MSI) High Colorectal and Pancreatic Cancer

This is a single-arm, non-randomized, phase 2 trial (NCT03104439) combining radiation, ipilimumab and nivolumab in patients with metastatic MSS Colorectal Cancer (CRC; n=40) and Pancreatic Ductal Adenocarcinoma Cancer (PDAC; n=25). Patients were previously treated population, and the primary endpoint was disease control rate. Pre- and post-treatment samples were subjected to RNA sequencing and whole exome sequencing. The primary data is shared via GEO and dbGaP at National Center for Biotechnology Information (NCBI), National Institutes of Health (NIH).

Study phs002545

Single Nucleus Transcriptomes from the Ventral Midbrain of Opioid Overdose Cases and Controls

We generated ventral midbrain single nuclei RNA-seq libraries for 95 brain donors, including 45 subjects with documented histories of opioid abuse and overdose, and 50 demographically-matched, opioid-free control subjects, collected from two geographically distinct regions within the U.S. (greater Detroit area, Michigan and Miami, Florida). Each sample included both substantia nigra and the adjacent ventral tegmental area. Nuclei were processed in pools of 3-4 brains using the 10X Chromium system followed by Illumina sequencing, read alignment and processing by 10X Cellranger.

Study phs003260

Transcriptional Profiling of PD-1+ and PD-1- Teff and Treg Cells in Glioblastoma and Health

PD-1 is an important immune checkpoint inhibitor that shows great promise in the clinic, particularly for melanoma and lung cancers. Since PD-1 is also expressed on infiltrating CD4+ Treg and Teffector cells in glioblastoma, we sought to better understand the role of PD-1 on these infiltrating CD4+ Treg and Teffector cells. To this end, we performed functional and transcriptional profiling using CD4+ Treg and Teffector cells isolated from healthy donors and glioblastoma patients (from both tumors and blood).

Study phs001079

Molecular Characterization of Response to Rectal Chemoradiation

Pre-operative chemoradiation (CRT) followed by resection is the standard of care option for patients with locally advanced rectal adenocarcinoma. Pathologic downstaging after CRT is associated with improved outcomes, but molecular predictors of response are poorly understood. We performed whole exome sequencing, gene expression profiling, and immune infiltrate analysis on rectal adenocarcinoma tumors prior to neoadjuvant CRT (pre-CRT) and at the time of resection (post-CRT) in 17 patients to identify somatic mutations and derive molecular biomarkers distinguishing complete and excellent partial responders versus non-responders.

Study phs001829

Novel Approach to High-Throughput Identification and Characterization of Neoantigens

This study focuses on the development of novel approach for the screening, identification and characterization of neoantigen-specific T-cell receptors (TCRs). The developed method consists of collecting targeted RNA-Seq from a T-cell specific gene panel via 3' end Illumina sequencing combined to Oxford Nanopore based full-length TCR sequencing post T-cell activation. The data generated during this study demonstrates feasibility of the approach on a Jurkat control cell line as well as T-cells isolated from the blood of 3 independent healthy donors.

Study phs002372

Cellular and Molecular Investigations of Human Hearts

We aim to discover gene regulatory networks that govern heart morphogenesis in the early fetal heart. To this end, we have performed single-nucleus ATAC-seq on cells derived from 2 human hearts at 15 weeks post conception to define the chromatin profiles and genomic regulatory networks for these in vivo specific cardiomyocyte lineages during development, from which the FASTQ files are available through dbGAP. This information will help us understand the process of heart morphogenesis early in development and may further our understanding of how congenital heart disease impacts development.

Study phs003473

A Prospective Study of Lifestyle, the Gut Microbiome, and Diverticulitis

By leveraging a large-scale collection of stool specimens (Micro-N) within the Nurses' Health Study II, we performed shotgun metagenomic sequencing and untargeted metabolomics profiling among 121 case women with a diagnosis of diverticulitis requiring antibiotics or hospitalization, with each matched to a control woman without diverticulitis during the same time period accounting for age, race, and month of stool collection (total N=242). We found microbiome and metabolomic profiles differed in diverticulitis cases compared to controls. Data deposited include metagenomic sequencing data (after removing the human sequences) and metabolomics data.

Study phs003531

Genetics of Antinuclear Antibodies

Antinuclear antibodies (ANA) are antibodies that react against self-antigens in the cell. While it has been reported that 12 to 20% of the general population have a positive ANA test, the genetics of ANA positivity is unknown. We performed a genome wide-association study for positive ANA tests among individuals without an ANA related autoimmune disease in the Vanderbilt University Medical Center (VUMC) DNA biobank linked to the de-identified electronic health record (EHR) system. The study is funded by the National Institute of Arthritis and Musculoskeletal and Skin diseases (NIAMS) grant R01AR076516.

Study phs003189

The Study of Somatic LINE1 Activity in Cancers

This study focuses exclusively on the quantification of LINE1 mobilization. We analyzed a recent whole genome sequencing data release from multiple Cancer Genome Atlas (TCGA) sub-projects. In addition to the somatic LINE1 insertions (present in tumor and having no support in the matched normal) there are "pseudo-germline" non-reference LINE1 elements identified in tumor tissue and having some support in the matched normal. This dataset reports such "pseudo-germline" LINE1 retrotranspositions. Individual level data for TCGA can be accessed by requesting access to phs000178.

Study phs003888

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