Search Results - EGA European Genome-Phenome Archive

Gene expression signatures associated with chronic endometritis revealed by RNA sequencing

Chronic endometritis (CE) is a persistent inflammatory condition of the endometrium characterized by the infiltration of plasma cells. CD138 immunohistochemistry is considered to improve the CE diagnosis rate. Using the number of CD138-positive cells equal or greater than five as a diagnostic criterion for CE, we identified 24 CE and 33 non-CE cases among women with infertility. We conducted RNA-sequencing analysis for these 57 cases in total as an attempt to elucidate the molecular pathogenesis of CE and to search for new biomarkers for CE. By comparing CE and non-CE groups, we identified 20 genes upregulated in the endometria of CE patients, including 12 immunoglobulin-related genes and eight non-immunoglobulin genes as differentially expressed genes. The eight genes were MUC5AC, LTF, CAPN9, MESP1, ACSM1, TVP23A, ALOX15, and MZB1. By analyzing samples in the proliferative and secretory phases of the menstrual cycle separately, we also identified four additional non-immunoglobulin genes upregulated in CE endometria: CCDC13 by comparing the samples in the proliferative phase, and OVGP1, MTUS2, and CLIC6 by comparing the samples in the secretory phase. Although the genes upregulated in CE may serve as novel diagnostic markers of CE, many of them were upregulated only in a limited number of CE cases showing an extremely high number of CD138-positive cells near or over one hundred. Exceptionally, TVP23A was upregulated in the majority of CE cases regardless of the number of CD138-positive cells. The upregulation of TVP23A in the endometria of CE cases may reflect the pathophysiology of a cell-type or cell-types intrinsic to the endometrium rather than the accumulation of plasma cells. Our data, consisting of clinical and transcriptomic information for CE and non-CE cases, helped us identify gene expression signatures associated with CE.

Study JGAS000621

Inherited Genetic Variation and Predisposition to Testicular Germ Cell Tumor: UPenn Local TGCT Study

Testicular germ cell tumors (TGCT) are the most common cancer in men ages 20-40. The incidence of TGCT has more than doubled over the past forty years, without clear etiology. Both genetic effects and environmental exposures, specifically during the pre-natal period, are likely to play an important role in determining TGCT susceptibility. TGCT is known to develop from primordial germ cells (PGCs). We hypothesize that variation in genes that impact upon the differentiation and maturation of PGCs will be important determinants of TGCT susceptibility and based on this hypothesis have selected three important pathways for study, i) male germ cell development, ii) androgen and estrogen biosynthesis and metabolism, and iii) IGF signaling. The proteins involved in early male germ cell development, normally only expressed in PGCs, are markers of and are overexpressed in TGCT. Markers of increased exposure to estrogen (or relatively decreased exposure to androgen) in utero and exogenous estrogen exposures, such as endocrine disruptors, have been associated with TGCT case status in multiple studies. IGF signaling is necessary for testis differentiation and maturation in mice and interacts synergistically with the estrogen signaling pathway. Additionally, we are interested in examining genetic factors predisposing to TGCT in an unbiased fashion, and thus will conduct a Genome Wide Association Study. As well disease susceptiblity, genetics are likely to play a role in disease progression, disease outcomes and response to treatement. We will also assess association of inherited genetics with these outcomes. We will analyze the contribution of genetic variants in these pathways to TGCT risk using a population-based case-control study in the Philadelphia metropolitian area. Our goal is the collection of 550 TGCT cases and 1100 age, race and cell phone use matched controls without a history of TGCT, which will yield 500 and 1000 white cases and controls, respectively, available for final analyses. All cases will be enumerated through the New Jersey and Pennsylvania state cancer registries. We will use a two-tiered approach for case recruitment: hospital clinic-based followed by registry-based. Hospital based cases will be identified within the Univeristy of Pennsylvania Health System and the University of Pennsylvania Cancer Network. All cases identified through this mechanism will be recruited irregardless of diagnosis date. The remaining cases will be identified through the New Jersey and Pennsylvania cancer registries and contacted following their protocols. Controls will be identified through random digit dialing and address based sampling. Both cases and controls will complete a questionnaire addressing known, presumed, and hypothesized risk factors for TGCT and provide a biospecimen. Pathological slides will be reviewed to cases to confirm diagnostic sub-type of TGCT. Haplotypes and functional SNPs will be typed in the genes of interest, as well as throughout the genome. Analyses will be conducted for specific variants, common haplotypes, alone and in conjunction with each other and exposure data after appropriate adjustment for potential confounders. The findings from this study will greatly contribute to our understanding of determinants of TGCT susceptibility.

Study phs001307

The BC Cancer Agency's Personalized Onco-Genomics Project

The BC Cancer Agency's Personalized Onco-Genomics (POG) Project involves molecular and clinical characterization of individual cancer patients to guide their treatment. The project aims to use whole genome and transcriptome data together with patient information to match treatments to cancer driver alterations and support clinical decision-making. Incorporating genomic data into decision-making should enable more rational development of treatment plans, facilitate enrollment into appropriate clinical trials and potentially identify less toxic and more effective therapeutic options.

Study EGAS00001001159

CRCbiome: Gut metagenome of Norwegian screening participants using FIT sampling

The study aims to characterize the gut metagenome of Norwegian screening participants and assess the ability of the gut metagenome to identify those at need for colonoscopy. Background: Colorectal cancer (CRC) screening reduces CRC incidence and mortality. However, current screening methods are either hampered by invasiveness or suboptimal performance, limiting their effectiveness as primary screening methods. To aid in the development of a non-invasive screening test with improved sensitivity and specificity, we have initiated a prospective biomarker study (CRCbiome), nested within a large randomized CRC screening trial in Norway. We aim to develop a microbiome-based classification algorithm to identify advanced colorectal lesions in screening participants testing positive for an immunochemical fecal occult blood test (FIT). We will also examine interactions with host factors, diet, lifestyle and prescription drugs. The prospective nature of the study also enables the analysis of changes in the gut microbiome following the removal of precancerous lesions. Methods: The CRCbiome study recruits participants enrolled in the Bowel Cancer Screening in Norway (BCSN) study, a randomized trial initiated in 2012 comparing once-only sigmoidoscopy to repeated biennial FIT, where women and men aged 50–74 years at study entry are invited to participate. Since 2017, participants randomized to FIT screening with a positive test result have been invited to join the CRCbiome study. Self-reported diet, lifestyle and demographic data are collected prior to colonoscopy after the positive FIT-test (baseline). Screening data, including colonoscopy findings are obtained from the BCSN database. Fecal samples for gut microbiome analyses are collected both before and 2 and 12 months after colonoscopy. Samples are analyzed using metagenome sequencing, with taxonomy profiles, and gene and pathway content as primary measures. CRCbiome data will also be linked to national registries to obtain information on prescription histories and cancer relevant outcomes occurring during the 10 year follow-up period. Discussion: The CRCbiome study will increase our understanding of how the gut microbiome, in combination with lifestyle and environmental factors, influences the early stages of colorectal carcinogenesis. This knowledge will be crucial to develop microbiome-based screening tools for CRC. By evaluating biomarker performance in a screening setting, using samples from the target population, the generalizability of the findings to future screening cohorts is likely to be high.

Study EGAS50000000170

Umbrella Study of MASTER/H021 data (not to be released, pool)

Study EGAS00001004338

20_Matched_Pair_Breast_Cancer_Genomes

We propose to definitively characterise the somatic genetics of 20 breast cancers through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing coupled with integrated transcriptomic data.

Study EGAS00001000170

Age-dependent association of clonal hematopoiesis with COVID-19 mortality in patients over 60 years

Genomic DNA extracted from peripheral blood of COVID-19 patients (n = 241 deceased, n = 239 survivors) was sequenced with the Myeloid Solutions™ panel of SOPHiA Genetics.

Study EGAS50000000001

Von Hippel-Lindau syndrome multi-region exome sequencing project from two patients undertaken at Cancer Research UK's London Research Institute

Multi-region whole exome sequencing of tumours from patients with Von Hippel-Lindau syndrome reveals convergence of mutayional events upon the PI3L-AKT-mTOR signalling pathway.

Study EGAS00001000907

Aligned Low pass whole genbome sequencing of cell free and tumour DNA from 5 patients with high grade serous ovarian cancer. Samples have been aligned to hg19 and bam files uploaded

This is the aligned bam files of 5 patients, with sequential sampltes from patients comprising cfDNA and FFPE extracted tumour DNA

Dataset EGAD50000001632

Shallow whole genome sequencing data from circulating tumour DNA (ctDNA) data of High Grade Serous Ovarian Cancer Patients (batch 1)

The dataset contains shallow whole genome sequencing data of 128 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 128 samples are plasma samples that have been collected before treatment. The files provided are paired fastq files.

Dataset EGAD50000000949

Hi-C in breast healthy, primary cancer and metastatic tissues

Hi-C libraries have been prepared by enzymatic digestion with MboI restriction enzyme and sonication (Covaris). Illumina single-indexig primers have been use to amplify ligated fragments. Hi-C experiments have been performed on 10 slices (50um thick) of fresh-frozen tissues or 10x10e6 Pleural Effusion cells. Raw paired-end fastq.gz files are provided.

Dataset EGAD50000000643

methylation_bc_cervix

Raw methylation data from cervical samples in individuals with breast cancer.

Dataset EGAD00010002081

Primary breast cancers and paired brain metastases

Targeted next-generation-sequencing of 494 cancer-associated genes was done in a series of 14 frozen pairs of matched primary breast cancers and brain metastases (28 samples). DNA libraries of all coding exons were prepared using the Haloplex Target Enrichment System. Sequencing was done using the 2*150bp paired-end technology on the Illumina NextSeq500 platform.

Dataset EGAD00001004309

PanCurX Translational Research Initiative - WGS mapped reads

Integration of Genomic and Transcriptional Features in Pancreatic Cancer Reveals Increased Cell Cycle Progression in Metastases - WGS mapped reads

Dataset EGAD00001004551

Whole genome sequencing

The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC) is not well understood. We performed whole genome sequencing on primary and metastatic sites from highly clinically annotated HGSC samples. Samples were obtained pre-treatment based on a laparoscopic triage algorithm from patients who underwent R0 tumor debulking, or received neoadjuvant chemotherapy (NACT) with excellent or poor response.

Dataset EGAD00001005240

Predictor_ChemoNEAR_TNBC (2019-08-14)

In this study a collection of core biopsies from breast cancer patients receiving neoadjuvant chemotherapy as part of the ChemoNEAR trial will be investigated. The study is intended to detect early acquired resistance in women with diagnosed breast carcinoma. Samples will undergo whole genome sequencing and analysis, including use of HR Predict. . This dataset contains all the data available for this study on 2019-08-14.

Dataset EGAD00001005255

WGS from PDAC samples

Bam files from WGS of PDAC samples described in: Transcription phenotypes of pancreatic cancer are driven by genomic events events during tumour evolution

Dataset EGAD00001006152

Whole exome sequencing of long-term, never relapse exceptional responders of trastuzumab-treated HER2+ metastatic breast cancer

The dataset contains Whole Exome Sequencing data (BAM files) of 22 samples from HER2+ metastatic breast patients. For 9 of the 13 tumours samples there are paired controls available from normal tissue. There are 8 tumours samples that are from treatment-responder patients and 5 tumours samples from non responder patients.

Dataset EGAD00001006217

Genomic and transcriptomic data of glioma specimens

Dataset consists of 207 glioma samples of WHO grades II, III and IV. Dataset consists 182 tumor derived genomic data of ~700 cancer-related and epigenetic-related genes with matched blood samples for 48 specimens. Dataset also consists transcriptomic data for 105 specimens. In total 335 bam files were deposited.

Dataset EGAD00001006299

PGDx elio™ tissue complete assay: targeted sequencing analyses of tissue DNA

The dataset "PGDx elio™ tissue complete assay: targeted sequencing analyses of tissue DNA" includes paired end FASTQ reads of 28 tissue samples from metastatic colorectal cancer patients. Sequencing was performed using a panel consisting of 505 genes, targeting 2,500x depth across the targeted regions.

Dataset EGAD00001009720

CASCADE germline whole genome sequencing data

High-coverage whole genome sequencing data (median coverage: 23.5X, range: 14.14X-32.62X)) from white blood cells of the patients from isolated buffy coat of the blood drawn postmortem from patients who participated in the CASCADE rapid autopsy program and died of metastatic castration resistant prostate cancer.

Dataset EGAD00001009493

12214 results for "cancer rna-seq"

in 49.45 milliseconds.