Search Results - EGA European Genome-Phenome Archive

Trial of Onco-Panel for Geneprofiling to Estimate both Adverse events and Response by cancer treatment (TOP-GEAR)

Bam files and fastq files in a hospital-based prospective study (TOP-GEAR project, the 2nd stage) to investigate the feasibility and utility of NGS-based analysis of 114 cancer-associated genes (the NCC Oncopanel test). DOI: 10.1111/cas.13969

Study JGAS000662

Genomic analysis of high-risk prostate cancer.

Whole genome sequencing analysis of high risk localised primary prostate cancer samples including metastatic samples was performed across 153 tumour samples with matching germline sequencing (whole blood). Samples were all fresh frozen frozen section confirmed tumour specimens and associated clinical and pathological metadata is available for these specimens.

Study EGAS00001003088

PHRT study of longitudinal sampling in ovarian cancer

High-grade serous ovarian cancer presents significant challenges due to its poor prognosis and high heterogeneity, both of which complicate treatment responses. This project aims to understand intra-patient tumor evolution by investigating different sampling sites (primary and metastatic) at the time of diagnosis and during disease recurrence.

Study EGAS50000001424

Genomic Signatures Reveal DNA Damage Response Deficiency in Brain Metastases of Colorectal Cancer

Brain metastasis (BM) of colorectal cancer (CRC) is rare but lethal and lacks effective therapies or a good understanding of its genomic landscapes. We conduct an analysis of whole-exome sequencing (WES, Illumina HiSeq 2500 sequencing platform) on 11 patient-matched BMs, primary CRC tumours, and adjacent normal tissues; and whole-genome sequencing (WGS, Illumina HiSeq X Ten platform) on 8 patient-matched BMs, primary CRC tumors, and adjacent normal tissues to uncover the whole-genome mutational landscape of colorectal cancer with brain metastasis.

Dataset EGAD00001005030

WGS and WES of Advance Prostate Cancer

The dataset consists of BAM files of 2 pairs of matched tumor/normal samples of a men with advanced prostate cancer. One pair is whole genome sequencing: WGS_T/WGS_N for tumor and normal samples, respectively; and the other pair is whole exome sequencing: WES_T/WES_N for tumor and normal specimens, respectively. Details can be found at the publication titled: "Molecular Medicine Tumor Board: Whole Genome Sequencing to Inform on Personalized Medicine for a Man with Advanced Prostate Cancer"

Dataset EGAD00001006487

Employing_single_cell_sequencing_for_detection_of_mutational_signatures_reflecting_on_going_mutagenesis_

12 single cells will be sequenced from a previously single-cell derived clone of a JSC-1 cell line. Additional 12 single cells are likely to be sequenced from a previously single-cell derived clone of a SW756 line. Both belong to CGP’s panel of approximately 1000 human cancer cell lines.

Study EGAS00001002679

Succession Of Transiently Active Tumour-Initiating Cell Clones inHuman Pancreatic Cancer

To elucidate whether newly acquired genetic alterations during serial transplantation of patient derived primary pancreatic cancer cultures contribute to the observed clonal dynamics in vivo, all coding genes of two patient derived primary cultures and derived genetically marked serial xenografts (1°/2°/3°) were sequenced.

Study EGAS00001000882

Fibroblast heterogeneity and immunosuppressive environment in Human breast cancer

Carcinoma-associated fibroblasts (CAF) are key players in the tumor microenvironment. Here, by combining 6 well-known stromal markers, we identify four CAF subsets (CAF-S1 to CAF-S4) in human breast cancer (BC) that exhibit distinct activation patterns and accumulate differently in BC subtypes.

Study EGAS00001002508

Predictor_ChemoNEAR_TNBC

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.

Study EGAS00001002806

Breast_Cancer_Somatic_Genetics_Study_

We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in 500 cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

Study EGAS00001000195

Signatures of Aristolochic Acid Mutagenesis in Bladder Cancer

This study looks at signatures of Aristolochic Acid mutagenesis in bladder cancer, based on exome and whole genome sequencing data. Thirteen bladder tumors and their matched normal DNAs were sequenced on Illumina platforms. Among them eleven were exome sequenced and two were whole genome sequenced.

Study EGAS00001000975

Copy number and mutation profiling of Stage 1 epithelial ovarian cancer biopsies

This project aims at characterizing the genome-wide copy number profile and the variant profile of 139 genes om the five major histotytpes of early-stage (stage I) epithelial ovarian cancer (EOC), to provide insight in the the aethiology and development of the disease.

Study EGAS00001004961

Chemotherapy accelerates genomic aging of normal blood in children treated for cancer

Whole genome sequencing (WGS) data obtained from clonally expanded hematopoietic stem and progenitor cells (HSPCs) from pediatric cancer patients before and after therapy exposure. In addition, WGS data of cord-blood derived HSPCs clones exposed to various chemotherapeutics and radiation was obtained.

Study EGAS00001005141

The NCAA-DoD Concussion Assessment, Research, and Education (CARE) Consortium

Study Description: Established in 2014, the U.S. Department of Defense (DoD) and the National Collegiate Athletic Association (NCAA) funded the Concussion Assessment, Research and Education (CARE) Consortium to inform science, clinical care and public policy related to concussion and repetitive head impact exposure (HIE) in U.S. Military Service Academy (MSA) cadets and collegiate student-athletes. The primary aims of the initial study were to: (1) establish a multisite research consortium to characterize the effects of concussion and repetitive head impact exposure on brain health, (2) characterize the clinical sequelae and natural history of concussion, (3) characterize the effect of concussion and repetitive head impacts on brain structure and brain function. The 30 member institutions of the CARE Consortium (26 civilian universities/colleges and 4 military service academies) agreed to invite all varsity athletes to undergo multimodal clinical assessments at preseason baseline, and at 5 additional timepoints after concussion diagnosis. At the service academies, non-varsity athlete cadets/midshipmen were also studied. Assessment Categories At Each Time Point Baseline: • Demographics • Personal and Family History • Neurocognitive Assessment • Neurological Status • Postural Stability • Symptoms ACUTE POST-INJURY FOLLOW-UP (CARE 1.0) (24 hrs; 48hrs; Asymptomatic; Unrestricted Return to Play (RTP); 6 mos) • Neurocognitive Assessment • Neurological Status • Postural Stability • Symptoms CUMULATIVE & PERSISTENT EFFECTS. (CARE 2.0) In-Person Exit Visit; Post-grad Online • Demographics • Personal and Family History • Neurocognitive Assessment • Neurological Status • Postural Stability • Symptoms • PROs • MROs (at academies only) LONG-TERM EFFECTS (CARE/SALTOS Integrated (CSI))Annual Online Assessment (at MSAs only); In-Person Research Visits • Demographics • Symptoms • Psychological health • PROs • MROs (at academies only)A subset of athletes at 6 of the CARE institutions underwent additional assessments including multimodal MRI, proteomic and genomic biomarker characterization, and head impact quantification (helmet-based sensors). Assessment time points for the ARC/pARC Neurocognitive and Behavioral Testing was done at Baseline, <48hrs Post-Injury, Cleared for Return to Play Progression (Asymptomatic), Unrestricted Return to Play, 7 days following Return to Play, and at >60 days after final game of junior year until end of collegiate career.Blood biomarker collection was done at Baseline, <48hrs Post-Injury, Cleared for Return to Play Progression (Asymptomatic), 7 days following Return to Play, and at >60 days after final game of junior year until end of collegiate career. Multi-modal MRI studies were done at Baseline, <48hrs Post-Injury, Cleared for Return to Play Progression (Asymptomatic), 7 days following Return to Play, and at >60 days after final game of junior year until end of collegiate career. However, please note that only athletes from one study performance site completed a multi-modal MRI study at baseline.

Study phs002175

Genome-Wide Association Study of Patients with Coccidioidomycosis

BackgroundValley Fever is typically an infection of the lungs caused by the fungi Coccidioides immitis and Coccidioides posadasii. The incidence of Coccidioidomycosis (CM), or infection with Coccidioides, has dramatically increased over the last 20 years. This is particularly true in the Southwest of the United States, where people often breathe fungal spores that arise from the soil. Reasons for increased infection rates are thought to include population growth and construction in these endemic regions, an increase in the number of people whose immune systems are compromised due to infection or treatment with drugs required for organ transplants, climate change, as well as improved testing practices and greater physician awareness. Mild CM most commonly presents itself with flu-like symptoms and rashes, which can last weeks to months. Individuals with compromised immune systems, specifically-- substantial suppression of the immune cells known as T cells, can develop severe pulmonary and disseminated disease. Infection that remains localized to the lungs is referred to as pulmonary disease, but when the infection spreads out of the lungs into other parts of the body it represents a more serious condition referred to as a disseminated disease, or disseminated CM. In nature, Coccidioides spp. exists as mold and lives in dust and soil. When the contaminated soil or dust is disturbed by human activity, animals, or weather, the Coccidiodies spores are released into the air. Airborne spores are taken up by breathing and settle in the lungs. Once in the moist and warm environment of the lung, spores transform into spherules, which divide and become filled with smaller spores, called endospores. When the spherules get large enough, they rupture and release these endospores, which can spread and disseminate to surrounding tissue. The cycle then repeats itself as these endospores develop into new spherules3. Different ethnic groups have been described to vary in their susceptibility to developing disseminated CM after initial infection with Coccidioides. For example, evidence suggests that African-American and Filipino patients suffer the disseminated disease at a greater rate than other ethnicities. The suggestion that race plays a role in the clinical expression of the disease is still a source of debate amongst the scientific community and any genetic mechanisms responsible for these differences have yet to be fully elucidated. If our genetic makeup influences our ability to limit the spread of infection, finding which DNA differences cause these variances could provide clues to how the body successfully fights infection, and provide opportunities to boost the body’s ability to do this. Further, if we are able to identify the specific genetic risk factors that correlate with the development of disseminated infection, physicians could perform genetic screenings to identify high-risk patients and provide them with preemptive antifungal therapy prior to developing disseminated disease.The genome, made up of DNA, contains all of the information needed for humans to develop and grow. Genome-wide association studies (GWAS) allow us to look for inherited differences that are more common between people who share a particular trait, for example, height or susceptibility to certain diseases, compared to those who do not share the trait. Although some traits and diseases are controlled by a single gene, the majority are influenced by contribution from several, or even many, different genes. To find evidence of genes that contribute to specific traits, GWAS typically compares genome information from large numbers of people who have a particular disease (referred to as “cases”) looking for DNA sequences that are common among these samples, and are different from DNA sequences seen in large numbers of people who lack the trait, but are as much like the cases as possible (referred to as “controls”). The DNA sequence data from each group, cases versus controls, are analyzed to see if there are specific genomic differences that tend to be associated with the disease. MethodsTwo separate GWAS approaches were taken to look for genetic differences that could be responsible for the observed differences between the different patient populations we are studying. The first method, known as genotyping, scans for differences at a set of positions across the genome, which includes both the genes that encode our proteins and the larger amount of DNA that does not. The second method, known as exome sequencing, allows us to compare the entire sequence of the portion of the genome that codes for proteins.  For this study, DNA from patients with either pulmonary or disseminated CM were genotyped and exome sequenced to look for DNA differences that are associated with one condition or the other. All patients were at least 18 years old, had no evidence of immunosuppression, and had proven or probable pulmonary coccidioidomycosis according to established diagnostic criteria. Of these patients, a subset demonstrated disseminated disease, i.e., they showed evidence of coccidioidal infection outside of the thorax by biopsy/aspiration, had radiographic imaging, and show positive coccidioidal serology. Our criteria for including patients with the pulmonary disease were that they must not require ongoing antifungal treatment or show evidence of active CM (in skin test positive patients), show no evidence of extrapulmonary dissemination, and have no evidence of ongoing pulmonary infection (pulmonary nodules are accepted) beyond six months from diagnosis.Patient DNA was purified from blood or from sputum samples by the labs of our collaborators, Drs. George Thompson (UC Davis School of Medicine) and John Galgiani (University of Arizona Health Sciences). Genome-wide association (GWAS) analysis was carried out to look for candidate loci associated with pulmonary versus disseminated disease, taking into account the population structure of the samples. Single nucleotide or insertion/deletion variants were identified from whole-exome sequences (WES) using the Picard/BWA/GATK pipeline. ResultsTable 1. Pulmonary versus Disseminated Cases of Coccidiomycosis for GWAS, Sorted by EthnicityEthnicityPulmonary CasesDisseminated CasesAsian85Black/African American1664Caucasian/White4015Filipino03Hispanic/Latino3414Indian21Mexican American1039Pacific Islander01Samoan03Vietnamese10Unknown16917More than one race02Total373134Table 1 shows the number of samples analyzed from patients with pulmonary versus disseminated disease, and patient ethnicity, where known. In all, we worked with 507 samples, including 134 samples from patients with disseminated disease and 373 samples from patients with pulmonary disease. Of these, 505 samples were genotyped using the Multi-Ethnic Global Array from Illumina Inc. In addition, we were able to generate whole-exome sequence from 498 patient samples. No significant associations were detected that differed between samples from patients with pulmonary versus disseminated disease; that is, no particular DNA sequences were found to be significantly enriched in patients with disseminated disease compared to patients with pulmonary disease. The ability to detect genetic association between specific sequences and genetically determined traits is influenced by several factors, including how many patient samples are available to compare, how many different genes contribute to the trait and how strong their contributions are. When the number of genes is small and the contribution of each gene is great, smaller numbers of patient samples are needed to detect an association. When more genes are involved, or the contribution from each gene is more modest, larger numbers of patient samples must be examined. While we were not able to detect any associated within this study, it does not mean that subsequent studies would not find this connection. Our study suggests significantly more samples should be analyzed in further studies.Whole-exome sequences were generated from 498 samples and were aligned to reference sequences to identify positions where the sequences differed from the reference. These data are being analyzed to determine if any variants are associated with pulmonary, versus disseminated, disease. 

Study phs002170

14983 results for "cancer studies using rna-seq"

in 18.97 milliseconds.