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• BarcUVa-Seq (Biology of Colorectal Cancer Risk Enhancers)

  This study was designed to generate a cohort of normal colon mucosal biopsies from the "average risk" population. Its primary aims included the development of an RNA-seq dataset of normal colon mucosal biopsies across three colon regions (ascending, transverse and descending). Further, we aimed to provide plausible prioritization to genetic components of colorectal cancer risk by employing methods such as expression quantitative trait loci analysis. In doing so, we provide a novel reference dataset for the study of colon cancer risk in the healthy colon epithelium. RNA-seq was performed in batches on an Illumina HiSeq 2500 (batch 1-7) or NovaSeq 6000 (batch 8) on a total of 463 samples. Matched genotyping data was generated on the Illumina OncoArray BeadChip. Phasing was carried out using Minimac 3 and imputation was performed using The Haplotype Reference Consortium panel on the Michigan Imputation Server.Genotype and RNA-seq data will be made available in dbGaP.

  Study phs003338

• Whole Exome Sequencing of 60 tumor/normal matched liver Cancers (HCC)

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 60 whole exome tumor/normal pairs with matched RNA-seq. Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Study EGAS00001003063

• Single_cell_analysis_of_cytokine_induced_T_cell_states

  We isolated T cells from healthy platelet donors and cultured them in resting and stimulated conditions with addition of a range of cytokines. We performed scRNA sequencing to assess the variability of polarization in different cytokines treated cells. Cytokines affect T cell responses by polarising them to different phenotypes. Given that the inflammation and and autoimmune tissue distruction is driven by the local production of cytokines, we investigated cytokine induced changes in T cells by using a combination of immunological and genomics approaches. To characterize, the efficacy of cytokine induced porization, here we stimulated naive and memory CD4+ T cells in the presence of cytokine polarizing coctails and profiled single cell transcriptome five days following polarization. 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 EGAS00001003215

• RNA-seq of Liver Cancer

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 161 RNA-seq samples from tumors with matched WES or WGS. Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Study EGAS00001002879

• Whole Genome Sequencing of HCC

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 24 whole genome sequencing (12 Tumoral/Non-tumoral pairs). Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Study EGAS00001002888

• Renal Cell Carcinoma Tumors From S-TRAC trial (NCT00375674) Whole Transcriptome Sequencing

  We report a comprehensive genomic and transcriptomic analysis of tumor samples from 171 patients at high risk for recurrent renal cell carcinoma post nephrectomy from the S-TRAC trial (NCT00375674). We identify gene expression signatures, including STRAC11 (derived from the sunitinib-treated population). The overlap in key elements captured in these gene expression signatures, which include genes representative of the tumor stroma microenvironment, regulatory T cell, and myeloid cells, suggests they are likely to be both prognostic and predictive of the anti-angiogenic effect in the adjuvant setting. These signatures also point to the identification of potential therapeutic targets for development in adjuvant renal cell carcinoma, such as MERTK and TDO2. Finally, our findings suggest that while anti-angiogenic adjuvant therapy might be important, it may not be sufficient to prevent recurrence and other factors such as immune response and that tumor environment may be of greater importance.

  Study EGAS00001006528

• Renal Cell Carcinoma Tumors From S-TRAC trial (NCT00375674) Exome Sequencing

  We report a comprehensive genomic and transcriptomic analysis of tumor samples from 171 patients at high risk for recurrent renal cell carcinoma post nephrectomy from the S-TRAC trial (NCT00375674). We identify gene expression signatures, including STRAC11 (derived from the sunitinib-treated population). The overlap in key elements captured in these gene expression signatures, which include genes representative of the tumor stroma microenvironment, regulatory T cell, and myeloid cells, suggests they are likely to be both prognostic and predictive of the anti-angiogenic effect in the adjuvant setting. These signatures also point to the identification of potential therapeutic targets for development in adjuvant renal cell carcinoma, such as MERTK and TDO2. Finally, our findings suggest that while anti-angiogenic adjuvant therapy might be important, it may not be sufficient to prevent recurrence and other factors such as immune response and that tumor environment may be of greater importance.

  Study EGAS00001006529

• T2D-GENES Consortium: San Antonio Mexican American Family Studies (SAMAFS)

  The Type 2 Diabetes (T2D) Genetic Exploration by Next-generation sequencing in Ethnic Samples (T2D-GENES) Consortium is a collaborative international effort to identify genes influencing susceptibility to type 2 diabetes in multiple ethnic groups using next generation sequencing. To fulfill this objective, T2D-GENES Consortium undertook two large sequencing studies, called T2D-GENES Projects 1 and 2. Project 1 has carried out whole exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 non-diabetic controls, equally divided among five continental ancestry groups: Europeans, East Asians, South Asians, Hispanic Americans, and African Americans. The goal of Project 1 is to identify all genetic variants in the complete coding regions of the genomes (i.e., whole exome) by sequencing, including rare variants. Project 2 (i.e., SAMAFS substudy 2) is a pedigree-based study designed to identify low frequency or rare variants influencing susceptibility to T2D, using whole genome sequence information from approximately 600 individuals in 20 Mexican American T2D-enriched pedigrees from San Antonio, Texas, augmented with family-based imputation into approximately 440 additional family members. The major objectives of Project 2 are to identify low frequency or rare variants in and around known common variant signals for T2D, as well as to find novel low frequency or rare variants influencing susceptibility to T2D. Both T2D-GENES Projects 1 and 2 involve the San Antonio Mexican American Family Studies (SAMAFS), which are composed of four San Antonio, Texas-based family studies: the San Antonio Family Heart Study (SAFHS), San Antonio Family Diabetes/Gallbladder Study (SAFDGS), Veterans Administration Genetic Epidemiology Study (VAGES), and Family Investigation of Nephropathy and Diabetes - San Antonio (FIND-SA) Component and its extension called the Extended FIND [E-FIND]. The SAFHS and SAFDGS began in 1991 and have followed participants with extensive clinical phenotyping related to T2D for over 20 years. The VAGES was initiated in 1994 and a large battery of T2D-related phenotypic data has been obtained from its participants. The FIND-SA began in 2000, a part of the multicenter FIND study which was designed to identify genetic determinants of diabetic kidney disease; data from its participants related to T2D were used for this project. Non-overlapping subsets of SAMAFS participants are part of the T2D-GENES Projects 1 and 2, henceforth referred to as SAMAFS substudies 1 and 2, respectively. The SAMAFS substudies 1 and 2 are part of one of the five awards funded by NIDDK under a cooperative agreement award mechanism, which is governed by the Steering Committee of the T2D-GENES Consortium. Since Project 1 relies on population based subsets of cases and controls, 491 unrelated participants are drawn from the four SAMAFS as part of the T2D-GENES Project 1 Mexican American sample (i.e., SAMAFS substudy 1). The whole exome sequencing was performed at the Broad Institute. For Project 2, 1048 individuals are drawn from two SAMAFS (SAFHS and SAFDGS), representing 20 large families for substudy 2. The substudy 2 strategy is to sequence approximately 600 individuals at an average of 50x coverage across the entire genome, then impute genome wide genotypes for about 440 additional family members. The 600 sequenced individuals are specifically chosen for their value in imputing sequence information into other family members. By studying large pedigrees, we expect to find multiple individuals carrying each genetic variant, even if this variant is very rare in the population at large. Thus, a pedigree-based approach provides an excellent opportunity for identifying rare novel variants influencing risk of T2D and quantitative variation in T2D-related phenotypes. The whole genome sequencing has been done commercially by Complete Genomics, Inc. (CGI). The available sample of 1,048 includes 5 sequenced individuals who do not belong to any of the 20 large pedigrees. The final family data of 1,043 individuals includes whole genome sequence data for 607 individuals. After quality control, 590 sequenced individuals provide data for family based imputation using Merlin linkage analysis software into approximately 440 additional family members for whom chip based genotypes are available to indicate which parental haplotype is transmitted. The complete SAMAFS data including phenotype, genotype, sequence, other T2D-related trait data utilized for Projects 1 and 2 are available. These data can readily be viewed by clicking on the substudy title shown below or in the box: "Substudies", located on the right hand side of this parent or top study page phs000847.v1.p1, titled T2D-GENES Consortium: San Antonio Mexican American Family Studies (SAMAFS). phs000849 T2D-GENES Project 1: San Antonio Mexican American Family Studies (SAMAFS), Substudy 1: Whole Exome Sequencing phs000462 T2D-GENES Project 2: San Antonio Mexican American Family Studies (SAMAFS), Substudy 2: Whole Genome Sequencing in Pedigrees

  Study phs000847

• Combined Metabolic Activators Reduces Liver Fat in Nonalcoholic Fatty Liver Disease Patients

  Nonalcoholic fatty liver disease (NAFLD) refers to excess fat accumulation in the liver. In animal experiments and human kinetic study, we found that administration of combined metabolic activators (CMA) promotes the oxidation of fat, attenuates the resulting oxidative stress, activates mitochondria and eventually removes excess fat from the liver. Here, we tested the safety and efficacy of CMA in NAFLD patients in a placebo-controlled 10-week study. We found that CMA significantly decreased hepatic steatosis and levels of aspartate aminotransferase, alanine aminotransferase, uric acid, and creatinine, whereas found no differences on these variables in the placebo group after adjustment for weight loss. By integrating clinical data with plasma metabolomics and inflammatory proteomics as well as oral and gut metagenomics data, we revealed the underlying molecular mechanisms associated with the reduced hepatic fat and inflammation in NAFLD patients and identified the key players involved in the host-microbiome interactions. In conclusion, we showed that CMA can be used to develop a pharmacological treatment strategy in NAFLD patients.

  Study EGAS00001005616

• Robust detection of translocations in lymphoma FFPE samples using Targeted Locus Capture-based sequencing

  Chromosomal translocations with immunoglobin (IG) loci are the classic drivers in a large subset of B-cell lymphomas. Detection of these translocations is important for confirmation of diagnosis and for prognosis and therapy decisions. Currently, molecular diagnosis of translocations in lymphomas is not addressed well by Next Generation Sequencing (NGS). The standard method for detection of translocations is Fluorescence In Situ Hybridization (FISH), which is labor-intensive, and can be difficult to interpret. There is a need for a robust technology that can be standardized. Targeted Locus Capture (TLC) selectively enriches and sequences entire genes based on the crosslinking of physically proximal sequences, and thereby enables complete sequencing of genes of interest, including detection of large structural variants. Because the technology is based on the crosslinking and fragmenting of DNA, it has particular advantages in the analysis of Formalin-Fixed, Paraffin-Embedded (FFPE) samples, in which DNA is inherently crosslinked and fragmented. In order to validate the FFPE-TLC technology as a novel approach for translocation detection in lymphoma samples, we have developed a panel assay containing genes with frequent translocations (MYC, BCL2, BCL6, IG loci). With this assay we have analyzed >140 lymphoma and control FFPE samples of variable input amounts and qualities that had previously been analyzed with FISH, and a subset also with standard targeted NGS. Good concordance with FISH results was observed for both translocation positive and negative samples. In 10 cases for which FFPE-TLC detected a relevant fusion and FISH had been called negative, discordance could be explained by higher sensitivity of FFPE-TLC or by inconclusive FISH results. In a specific case, FFPE-TLC detected a small-distance rearrangement on chromosome 3 that caused a BCL6 fusion but led to insufficient and therefore undetectable break-apart with FISH. Secondly, the FFPE-TLC approach was tested on a set of 19 B-cell lymphoma FFPE samples that had previously been analyzed using standard targeted NGS and FISH and was enriched for discordant results between these methods. FFPE-TLC-based NGS enables more robust translocation calling as the detection relies on broad sequencing coverage across the translocation partner rather than on breakpoint sequences only. In 3 cases, FFPE-TLC could proof false negative calls in standard targeted NGS due to breakpoints located in regions difficult to capture or to sequence. In 1 case, standard targeted NGS had made a false positive call on a breakpoint sequence that was shown to be caused by a small insertion rather than a genuine translocation. This study shows that FFPE-TLC promises to be a robust alternative for FISH analysis and standard targeted NGS procedures in lymphoma diagnostics and possibly in other cancers with frequent structural variants. The FFPE-TLC approach enables a single, DNA-based NGS test detecting both small mutations and translocations.

  Study EGAS00001004760

• THAP11 mutations in a patient with a cblX-like phenotype implicates THAP11 in the regulation of cobalamin metabolism and early vertebrate development

  Mutations in HCFC1 are associated with cblX (MIM309541), an X-linked recessive disorder, characterized by defects in cobalamin metabolism and other developmental defects. HCFC1 is a transcriptional co-regulator, which interacts with transcription factors to regulate the expression of a myriad of genes. Notably, HCFC1 regulates cobalamin metabolism via the regulation of MMACHC expression through its interaction with THAP11, a THAP domain-containing transcription factor. In addition, the HCFC1/THAP11 complex potentially regulates genes involved in diverse cellular functions including cell cycle, proliferation, and transcription. Thus, it is likely that mutations in THAP11 may also result in biochemical and other phenotypes similar to those observed in patients with cblX. We report a patient who presented with phenotypic features that overlap cblX, but did not have any mutations in either MMACHC or HCFC1. We sequenced THAP11 by Sanger sequencing and discovered a potentially pathogenic, homozygous variant in THAP11, c.240C>G (p.Phe80Leu). Functional analysis in the developing zebrafish embryo, demonstrate that both THAP11 and HCFC1 regulate the proliferation and differentiation of neural precursors, suggesting important roles in normal brain development. Further, the loss of THAP11 in zebrafish embryos, results in craniofacial abnormalities including the complete loss of Meckel’s cartilage, the ceratohyal, and all of the ceratobranchial cartilages. These data are consistent with our previous work which demonstrated a role for HCFC1 in vertebrate craniofacial development. Furthermore, our high throughput RNA-sequencing analysis reveals several overlapping gene targets of HCFC1 and THAP11 that likely contribute to the phenotypes associated with cblX and related disorders. Thus, both HCFC1 and THAP11 play important roles in the regulation of cobalamin metabolism as well as other pathways involved in early vertebrate development.

  Study EGAS00001002201

• Precision Medicine for Dilated Cardiomyopathy in European and African Ancestry

  The DCM Precision Medicine Study is a multi-site consortium-based cross-sectional study of families with an embedded open-label randomized controlled trial. The aims of the study are to test the hypothesis that dilated cardiomyopathy (DCM) has a substantial genetic basis and to evaluate the effectiveness of a family communication intervention in improving the uptake of preventive screening and surveillance in at-risk first-degree relatives. The Study goal was to recruit 1,300 individuals (600 non-Hispanic African ancestry, 600 non-Hispanic European ancestry, and 100 Hispanic; 50% female) meeting rigorous diagnostic criteria for idiopathic DCM (probands) and 2,600 of their relatives. The probands were inpatients or outpatients identified by heart failure and cardiac transplant cardiovascular physicians and clinical research personnel in heart failure/heart transplant programs at sites in the DCM Consortium. The DCM phenotype was selected for this study because of its prevalence and its prior inclusion in the development of virtually all pharmacotherapy for non-ischemic heart failure from reduced ejection fraction. Study procedures included obtaining family history, cardiac history, medical record review, surveys, and blood sample collection. Exome data from 1219 idiopathic DCM probands and 127 idiopathic DCM relatives are included in dbGaP.

  Study phs002641

• Developing Allelic Imbalance Analysis from Single-Nucleus RNA-Seq Data

  Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool for understanding gene function across diverse cells. Recently, this has included the use of allele-specific expression (ASE) analysis to better understand how variation in the human genome affects RNA expression at the single-cell level. We reasoned that, because intronic reads are more prevalent in single-nucleus RNA-Seq (snRNA-Seq) and introns are under lower purifying selection, and are thus enriched for genetic variants, that snRNA-seq should facilitate single-cell analysis of ASE. Here we demonstrate how experimental and computational choices can improve the results of allelic imbalance analysis. We explore how experimental choices, such as RNA source, read length, sequencing depth, genotyping, etc., impact the power of ASE-based methods. We developed a new suite of computational tools to process and analyze scRNA-seq and snRNA-seq for ASE. As hypothesized, we extracted more ASE information from reads in intronic regions than those in exonic regions and show how read length can be set to increase power. Additionally, hybrid selection improved our power to detect allelic imbalance in genes of interest. We also explored methods to recover allele-specific isoform expression levels from both long- and short-read snRNA-seq. Overall, we provide an end-to-end experimental and computational approach for future studies.

  Study phs003749

• NIH Roadmap Epigenomics Program - Broad Institute

  For the NIH Roadmap Epigenomics project, we applied ChlP-Seq, HTBS and WGBS pipelines to generate comprehensive high-resolution maps of chromatin state and DNA methylation for 100 diverse cell types. Cell types were selected for their biological and medical importance, and for their potential to maximize the comprehensiveness of acquired epigenomic data. They include human ES cells, ES-derived cells, mesenchymal stem cells, reprogrammed stem cells and primary tissues. Comprehensive characterization of epigenetic marks ("the epigenome") is a critical step towards a global understanding of the human genome in health and disease. In this study we provide unprecedented views of the human epigenetic landscape and its variation across cell states, which offer fundamental insight into the functions and interrelationships of epigenetic marks, and provide a framework for future studies of normal and diseased epigenomes. The Roadmap Epigenomics Broad cohort is utilized in the following dbGaP sub-study. To view molecular data and derived variables collected in this sub-study, please click on the following sub-study below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000700 the Roadmap Epigenomics Broad cohort. phs000610 RM_Epigenomics_Broad_Alz

  Study phs000700

• Virtual Growing Child 5-Dimensional Functional Models for Treating Respiratory Anomalies (dMRI-VGC)

  Objectives We are sharing a database of dynamic magnetic resonance imaging (dMRI) scans of normal children, which can serve as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The database can also be useful to advance future AI-based research on image-based object segmentation and analysis. Background In pediatric patients with respiratory abnormalities, it is important to understand the alterations in regional dynamics of the lungs and other thoracoabdominal components, which in turn requires a quantitative understanding of what is considered as normal in healthy children. Currently, such a normative database of regional respiratory structure and function in healthy children does not exist. Participants 200 normal children (ages 6-18 years) participated in our research study related to this dataset. DesignThe shared open-source normative database is from our ongoing virtual growing child (VGC) project, which includes 4D dMRI images representing one breathing cycle for each normal child and also segmentations of 10 objects at end expiration (EE) and end inspiration (EI) phases of the respiratory cycle in the 4D image. The lung volumes at EE and EI as well as the excursion volumes of chest wall and diaphragm from EE to EI, left and right sides separately, are also reported. The database has thus 4,000 3D segmentations from 200 normal children in total. The database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for normal children. All dMRI scans are acquired from normal children during free-breathing. The dMRI acquisition protocol was as follows: 3T MRI scanner (Verio, Siemens, Erlangen, Germany), true-FISP bright-blood sequence, TR=3.82 ms, TE=1.91 ms, voxel size ~1×1×6 mm3, 320×320 matrix, bandwidth 258 Hz, and flip angle 76o. With recent advances, for each sagittal location across the thorax and abdomen, we acquired 40 2D slices over several tidal breathing cycles at ~480 ms/slice. On average, 35 sagittal locations are imaged, yielding a total of ~1400 2D MRI slices, with a resulting total scan time of 11-13 minutes for any particular study participant.The collected dMRI scan data then went through the procedure of 4D image construction, image processing, object segmentation, and volumetric measurements from segmentations. 4D image construction: For the acquired dMRI scans, we utilized an automated 4D image construction approach to form one 4D image over one breathing cycle (consisting of typically 5-8 respiratory phases) from each acquired dMRI scan to represent the whole dynamic thoraco-abdominal body region. The algorithm selects 175-280 slices (35 sagittal locations × 5-8 respiratory phases) from the 1400 acquired slices in an optimal manner using an optical flux method. Image processing: Intensity standardization is performed on every time point/3D volume of the 4D image so that image values have the same tissue-specific meaning across all subjects. Object segmentation: For each subject, there are 10 objects segmented at both EE and EI time points in this database. They include the thoracoabdominal skin outer boundary, left and right lungs, liver, spleen, left and right kidneys, diaphragm, and left and right hemi-diaphragms. All dMRI scans utilize large field of view images, which include the full thorax and abdomen to the inferior aspect of the kidneys in the sagittal plane. We used a pretrained U-Net based deep learning network to first segment all objects, and then all auto-segmentation results were visually checked and manually refined as needed, under the supervision of a radiologist with over 25 years of expertise in MRI and thoracoabdominal radiology. Manual segmentations have been performed for all objects in all datasets. Volumetric measurements based on object segmentations for lung volumes (left and right separately) at EE and EI, as well as for chest wall and diaphragm excursion volumes (left and right separately) are reported. ConclusionsThe provided database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for normal children. The database has 4,000 3D segmentations from 200 normal children, which to our knowledge is the largest and only such dMRI dataset to date. All images and object segmentations are saved in DICOM. All DICOM files (176,574 in total) have been anonymized, and PHI has been removed. The database can be used as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The large amount of object segmentations can potentially benefit AI-based research on image-based object segmentation and analysis.

  Study phs004002

• High Sensitivity ctDNA Analysis Using a Novel Panel and NOIR-SS Technology for Monitoring Advanced Urothelial Carcinoma

  This dataset contains sequencing data generated by targeted amplicon analysis using the NOIR-SS method in 15 patients with advanced urothelial carcinoma. Formalin-fixed paraffin-embedded (FFPE) tumor tissues (15 samples) and plasma cfDNA (50 samples) were analyzed. Tumor tissues were subjected to targeted panel sequencing to identify mutations in TP53, FGFR3, TERT, and KRAS/HRAS. Plasma cfDNA was analyzed using a tumor-informed approach focusing on the mutations identified in matched tumor tissues. Sequencing was performed on the Ion PGM or Ion S5 XL platform. Raw sequencing data are provided in FASTQ format under controlled access.

  Study JGAS000836

• Genetic Basis of Breast Cancer Resistance in BRCA1 Mutation Carrier

  Our study addressed a specific question in NCI RFA-CA-12-022: "What underlying causal events - e.g., genetic, epigenetic, biologic, behavioral, or environmental - allow certain individuals to survive beyond the expected limits of otherwise highly lethal cancers?". A germline mutation in BRCA1 (BRCA1+) is the most penetrant genetic predisposition for breast cancer. Nevertheless, a portion of BRCA1+ carriers does not develop breast cancer in their lifetime, suggesting that the genetic predisposition can be antagonized by resistant factors. BRCA1+ was inherited from an ancestor of the carrier family thousand years ago. We hypothesize that evolution could select certain genetic components to suppress oncogenesis caused by the predisposition. We compared germline variants in all genes in 27 pairs of breast cancer-unaffected and -affected BRCA1+ carriers, each pair inherited the same BRCA1+. We identified 12 deleterious variants enriched in breast cancer-unaffected carriers, all are common variants. A variant rs3735400 is located in ANLN, a cytokinesis-essential gene. Overexpression of variant-containing ANLN and suppressed expression of endogenous ANLN decrease ANLN nuclear localization and delay cell growth. Our findings suggest that common variants can be selected to resist oncogenesis imposed by BRCA1+.

  Study phs001243

• Genomic Characterization CS-MATCH-0007 Arm B

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing, RNA sequencing and if possible, whole-genome, methylation and miRNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH clinical trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm B is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with HER2- activating mutations are treated with Afatinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002028

• NCI-Maryland Prostate Cancer Case-Control Study

  The study seeks to examine the genetic and ancestral basis of prostate cancer-associated inflammation using a genome-wide association approach. The study population are the participants of the NCI Maryland Prostate Cancer Case-Control study. This study recruited both African American and European American men, and investigated the causes for the excessive burden of prostate cancer among African American men in more general terms. We measured 82 blood-based immune-oncology markers, and genotyped the participants using the HumanOmni5-Quad BeadChip, which provides a significant genome coverage for genetically-admixed and diverse populations, to evaluate the genetic basis and evidence for causality of any immune-inflammation marker that is associated with prostate cancer risk. We want to assess how germline genetics influence the abundance levels of these 82 markers in African American and European American men, which may contribute to differences between them.

  Study phs002939

• Genomic Characterization CS-MATCH-0007 Arm Z1I

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm Z1I is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with BRCA1, BRCA2 mutations are treated with AZD1775. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002058

• Genomic Characterization CS-MATCH-0007 Arm Z1A

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm Z1A is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with NRAS mutations are treated with Binimetinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs001973

• Genomic Characterization CS-MATCH-0007 Arm W

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm W is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with FGFR fusions, mutations, amplifications are treated with AZD4547. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including tumor tissue and whole blood.

  Study phs001948

• Genomic Characterization CS-MATCH-0007 Arm S2

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm S2 is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with GNAQ or GNA11 mutations are treated with Trametinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002178

• Genomic Characterization CS-MATCH-0007 Arm R

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm R is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with BRAF fusions, non-V600K or non-V600E mutations, are treated with Trametinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002029

• Genomic Characterization CS-MATCH-0007 Arm S1

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm S1 is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with NF1 mutations are treated with Trametinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002153