Search Results - EGA European Genome-Phenome Archive

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

Genome_Diversity_in_Africa_Project__Benin

Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene–disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region.The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group).Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformaticsThis 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 EGAS00001001688

Exploration of predictive biomarkers for postoperative recurrence of stage II/III colorectal cancer using genomic sequencing

To identify biomarkers that can predict treatment outcomes, we compared the mutational profiles of surgically resected specimens from patients with recurrent cancer with those from patients with non-recurrent cancer. Target sequencing, whole-exome sequencing (WES), or whole-genome sequencing (WGS) was perfomed.

Study JGAS000335

Heat selection enables highly scalable methylome profiling in cell-free DNA for noninvasive monitoring of cancer patients

Genome-wide analysis of cell-free DNA (cfDNA) methylation profile has been recognized as a promising approach for sensitive and specific detection of many cancers. However, scaling such genome-wide assays for clinical translation is impractical due to the high cost of whole genome bisulfite sequencing. We have shown that the small fraction of GC-rich genome is highly enriched in CpG sites and disproportionately harbors the majority of cancer-specific methylation signature. Here, we report on the simple but effective Heat enrichment of CpG-rich regions for Bisulfite Sequencing (Heatrich-BS) platform that allows for focused methylation profiling in these highly informative regions. Our novel method and bioinformatics algorithm enable accurate tumor burden estimation with high sensitivity and quantitative tracking of colorectal cancer patient’s response to treatment, at much reduced sequencing cost suitable for frequent monitoring. We also show, for the first time, tumor epigenetic subtyping from cfDNA using Heatrich-BS, which could enable patient stratification from non-invasive liquid biopsy. As such, Heatrich-BS holds great potential for highly scalable screening and regular monitoring of cancer using liquid biopsy.

Study EGAS00001006198

DNA methylation landscape of prostate cancer

Metastases from primary prostate cancers to rare locations, such as the brain, are becoming more common due to longer life expectancy thanks to improved treatments. Epigenetic dysregulation is a feature of primary prostate cancer, and distinct DNA methylation profiles are associated with the mutually exclusive SPOP mutant or TMPRSS2-ERG fusion genetic backgrounds. Using a cohort of 42 patients with prostate cancer brain metastases (PCBM), with matched primary samples available for 17 patients, we carried out DNA methylation analysis using Illumina EPIC array. We examined the epigenetic distinction between primary PCa and PCBM, the association between epigenetic alterations and mutational background, and particular epigenetic alterations that may be associated with PCBM in particular. Multiregion sampling of PCBM revealed epigenetic heterogeneity in metastases. We found aberrant methylation in PCBM is associated with mutational background, PRC2 complex activity and upregulation of EZH2, an effect that is particularly pronounced in SPOP mutant PCBM. While we detected a hypermethylator phenotype in PCBM, we also observed hypomethylation occurring at the promoters of genes involved in neuroactive ligand-receptor interactions or the calcium signalling pathway, such as GABRB3 and GRM5, a change not observed in non-brain prostate cancer metastases.

Study EGAS00001006670

Efficient prediction of a spatial transcriptomics profile better characterizes breast cancer tissue sections without costly experimentation

Spatial transcriptomics is an emerging technology requiring costly reagents and considerable skills, limiting the identification of transcriptional markers related to histology. Here, we show that predicted spatial gene-expressions in unmeasured regions and tissues can enhance biologists�� histological interpretations. We developed the Deep learning model for Spatial gene Clusters and Expression, DeepSpaCE and confirmed its performance using the spatial-transcriptome profiles and immunohistochemistry images of consecutive human breast cancer tissue sections. For example, the predicted expression patterns of SPARC, an invasion marker, highlighted a small tumor-invasion region that is difficult to identify using raw data of spatial transcriptome alone because of a lack of measurements. We further developed semi-supervised DeepSpaCE using unlabeled histology images and increased the imputation accuracy of consecutive sections, enhancing applicability for a small sample size. Our method enables users to derive hidden histological characters via spatial transcriptome and gene annotations, leading to accelerated biological discoveries without additional experiments.

Study JGAS000290

CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Summary Results from Genomic Studies

GWAS have successfully identified genetic loci associated with a variety of conditions such as type 2 diabetes and coronary disease. The large number of statistical tests required in GWAS has posed a special challenge because few studies that have DNA and high-quality phenotype data are sufficiently large to provide adequate statistical power for detecting small to modest effect sizes. Even before the era of GWAS, the requirement for large sample sizes and the importance of replication have served as powerful incentives for collaboration. Meta-analyses combining summary data from multiple sources have improved the ability to detect new loci. The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium was formed to facilitate GWAS meta-analyses and replication among multiple large and well-phenotyped cohort studies. The design of the CHARGE Consortium was formed initially from 5 prospective cohort studies from the United States and Europe: the Age, Gene/Environment Susceptibility (AGES) - Reykjavik Study, the Atherosclerosis Risk in Communities (ARIC) Study, the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), and the Rotterdam Study (RS). Additional studies have expanded the CHARGE consortium based upon the phenotypes and willingness to share information across the research community. In order to facilitate investigators across the world to examine relationships between phenotypes and genetic markers within CHARGE published reports, an open site is made available on dbGaP that provides the rsID and the p-value for inspection. Access to detailed summary statistics (including minor allele frequency, odds ratio/effect size) requires approval of a Data Access Request (DAR).

Study phs000930

Genomic Analysis of Nucleic Acid Sequences from Pancreatic Cancer

Our study aims to perform multi-omics analysis of pancreatic ductal adenocarcinoma. We performed dual single-cell RNA sequencing and whole genome sequencing on fresh tumor specimens and dual bulk RNA-sequencing and 16S amplicon sequencing on frozen tumor specimens to identify human and non-human nucleic acid sequences. Additionally, we identified microbial sequences and found that bacterial taxonomic profiles from the same sample strongly correlated across technologies.

Study phs003035

Targeted DNA sequencing on 37 Merkel Cell Carcinomas from New Zealand with known Merkel cell polyomavirus status

To determine the genomic landscape of NZ virus-negative MCCs (VN-MCC), assess genomic evolution in metastases, and catalogue the distribution of TP53 and RB1 variants from international studies.

Study EGAS00001006873

Analysis of IDHwt-glioblastoma samples from paired primary and recurrent tumor samples

IDHwt-glioblastomas rapidly recur after initial treatment. To study genetic evolution in glioblastoma, we analyzed whole genomes of 21 pairs of primary and recurrent tumor samples using next generation sequencing. In addition we sequenced RNA from 16 tumor pairs and a panel of 50 glioma-associated genes in tumor pairs from 43 patients (including 14 of the 21 patients included in the WGS discovery set). Glioblastoma subtypes were determined using 450k/EPIC methylation arrays. This study was supported within the e:med program of the German Ministry of Education and Research (BMBF) by the collaborative research project ‘SYS-GLIO - Systems-based prediction of the biological and clinical behavior of gliomas’ (https://www.sys-med.de/de/demonstratoren/sys-glio/) This study is part of the Heidelberg Center for Personalized Oncology - HIPO-043

Study EGAS00001003184

Human skin cancer (BCC, SCC, melanoma) and healthy control skin

Smart-seq2 single cell RNA sequencing of human BCC, SCC, melanoma (ALM) and healthy control skin samples.

Dataset EGAD50000000540

Bacterial SNPs in the human gut microbiome associate with host BMI

Genome-wide association studies (GWAS) have revolutionized the field of genetics, providing numerous associations between human SNPs and health traits. Likewise, metagenome-wide association studies (MWAS) between bacterial SNPs and human traits can suggest mechanistic links between the microbiota and its host. However, very few such studies have been done to date, in part due to the large number of samples required to address the variable coverage of bacteria across samples and the fact that most bacteria are present in only a subset of the population. Here, we devised an MWAS framework to detect SNPs and associate them with host phenotypes systematically. We recruited and obtained gut metagenomic samples from a cohort of 7,190 healthy individuals and discovered 1,358 statistically significant associations between a bacterial SNP and host body mass index (BMI). To address the possible effects of population structure and linkage disequilibrium, we applied a clumping procedure, and found 40 independent associations between SNPs and host BMI. We uncovered BMI-associated SNPs in the genomes of 27 bacterial species, even though the relative abundance of 12 of these species was not associated with the phenotype. We separated genome-wide sub-species variations from local associations in individual SNPs, and demonstrated how this framework can highlight specific bacterial functions of interest. Our results demonstrate the importance of considering nucleotide-level diversity in microbiome studies and pave the way toward a better understanding of interpersonal gut microbiome differences and their health implications.

Study EGAS00001007204

Mapping the breast cancer metastatic cascade onto circulating tumour DNA using genetic and epigenetic clonal tracking

Dataset EGAD00001005507

RNASeq files for GenomePaint paper

RNASeq files for GenomePaint paper titled "Exploration of coding and non-coding variants in cancer using GenomePaint."

Dataset EGAD00001006680

15028 results for "cancer studies using rna-seq"

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