15017 results for "cancer studies using rna-seq"

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• Understanding the genetic risk underlying racial disparities in uterine fibroids

  Fibroids affect 77% of women by onset of menopause in the U.S. and account for $2.1 billion in healthcare costs each year. Fibroids negatively impact reproductive health causing heavy and painful menses, pelvic pain and pressure, pregnancy complications, and interventions including myomectomy and hysterectomy. Until recently, tumor tissue and cell culture studies investigating fibroid growth have been the primary sources for understanding fibroid pathophysiology. Genetic analysis can provide a powerful and cost effective tool to identify etiological and causal factors, especially since a genetic predisposition to fibroids has already been documented from twin studies. As much as 69% of risk is explained by genetic factors. Racial disparities also support a role for genetics with fibroid risk. African American women have earlier age of onset, more numerous and larger fibroids with a greater lifetime incidence compared to Caucasians. We propose to identify genetic markers for risk of fibroids through a genome-wide association study (GWAS) of African American and Caucasian participants, leveraging ancestral differences to narrow down genomic regions for targeted follow- up analyses. To accomplish this we will take advantage of a unique Vanderbilt resource, the BioVU DNA databank. BioVU currently has over 122,470 adults linked to electronic medical records. From BioVU we have already identified 2,902 African American and Caucasian subjects who meet our stringent inclusion criteria to conduct a GWAS of fibroids, including pelvic imaging. Available imaging is critical, because many women with fibroids are asymptomatic and without imaging, studies may misclassify as many as 51% of women. We have also defined definitive controls who reached menopause without fibroids. We have a strong group of nationally known fibroid researchers who will provide over 10,000 samples for replication. Our first Specific Aim is to conduct a GWAS for association between common single nucleotide polymorphisms (SNPs) and fibroid risk. Using a case-control design we will perform a GWAS in 2,902 (1,451 fibroid cases and 1,451 controls) women from BioVU stratified by African American and Caucasian race. Secondary admixture mapping (AM) analyses will also be performed to identify chromosomal regions of interest to prioritize for replication. Our second Aim is to resequence chromosome regions identified from GWAS and AM to discover rare variants. Finally, in Aim 3 we will replicate SNPs selected from Aim 1 and 2 in independent samples of at least 3,230 fibroid cases and 7,097 controls. We propose an efficient and cost-effective approach to identify genetic risk factors for fibroids, by taking advantage of imaging information and DNA available through BioVU. This study represents the largest GWAS of uterine fibroids and the first among African Americans leveraging emerging technologies and new statistical approaches to conduct this study. Our proposed study will fundamentally change knowledge about fibroids and lay the ground work for breakthroughs in understanding mechanisms of fibroid formation and in identifying novel therapeutic approaches.

  Study phs001409

• Comparing nodal versus bony metastatic spread using tumour phylogenies

  The role of lymph node metastases in distant prostate cancer dissemination and lethality is ill defined. Patients with metastases restricted to lymph nodes have a better prognosis than those with distant metastatic spread, suggesting the possibility of distinct aetiologies. To explore this, we traced patterns of cancer dissemination using tumour phylogenies inferred from genome-wide copy-number profiling of 48 samples across 3 patients with lymph node metastatic disease and 3 patients with osseous metastatic disease. Our results show that metastatic cells in regional lymph nodes originate from evolutionary advanced extra-prostatic tumour cells rather than less advanced central tumour cell populations. In contrast, osseous metastases do not exhibit such a constrained developmental lineage, arising from either intra or extra-prostatic tumour cell populations, at early and late stages in the evolution of the primary. Collectively, this comparison suggests that lymph node metastases may not be an intermediate developmental step for distant osseous metastases, but rather represent a distinct metastatic lineage.

  Study EGAS00001001801

• WGS of human colorectal cancer organoid exposed to genotoxic pks+ E. coli

  Organoid cultures were exposed to different E.Coli strains and a dye control. In total 25 organoid cultures were whole-genome sequenced using the Novaseq6000 platforms. The data is deposited as .bam format.

  Dataset EGAD50000000304

• CRC cell line MPRA

  Massively Parallel Reporter Assays (MPRA) of colorectal cell lines HCEC-1CT (normal colon) and HT29 and SW403 (MSS cancer). Probes identified using the CRC GWAS.

  Dataset EGAD50000000596

• Dataset for "HPV integration induces gene fusions" (pacBio)

  pacBio whole-genome sequencing data for "HPV integration induces gene fusions" We performed long read whole-genome sequencing on four HPV+ head and neck cancer samples using pacBio HiFi. The sequence reads were submitted in fastq format.

  Dataset EGAD50000001304

• FFPE CPA Accreditation Study Part 2

  FFPE CPA accreditation of genome-scale sequencing in routinely collected formalin-fixed paraffin-embedded (FFPE) cancer specimens versus matched fresh-frozen samples using targeted pulldown capture prior to Illumina sequencing.

  Dataset EGAD00001000868

• Mutation analysis of 77 genes in cfDNA from metastatic CRC patients

  Aligned NGS data (BAM) of 77 frequently mutated genes in cancer using the AVENIO Expanded platform.

  Dataset EGAD00001010294

• CancerLocator: Non-Invasive Cancer Diagnosis and Tissue-of-Origin Prediction Using Methylation Profiles of Cell-Free DNA

  Background: The detection and characterization of cell-free DNA in plasma is one of the most promising new areas in cancer diagnosis. Liquid biopsy, unlike traditional tissue biopsy, has the potential to diagnose a variety of different malignancies. Results: Here we propose a probabilistic method, CancerLocator, which exploits the diagnostic potential of cell-free DNA by determining not only the presence but also the location of tumors. CancerLocator simultaneously infers the proportions and the tissue-of-origin of tumor-derived cell-free DNA in a blood sample using genome-wide DNA methylation data. We comprehensively evaluate CancerLocator with simulations and real data, and compare its performance with that of two established multi-class classification methods. We show that the predicted tumor burdens are highly consistent with the true values. In addition, when the proportion of tumor-derived DNAs in the cell-free DNAs is low, the two popular machine learning methods completely fail for cancer diagnosis, while CancerLocator successfully overcomes the challenge. CancerLocator also achieves promising results on patient plasma samples, despite the fact that the DNA methylation data from these samples has very low sequencing coverage. Conclusions: CfDNA methylation may be developed as an important approach for non-invasive early cancer diagnosis.

  Study EGAS00001002211

• CancerDetector: Ultrasensitive and Non-Invasive Cancer Detection at the Resolution of Individual Reads using Cell-free DNA Methylation Sequencing Data

  The detection of tumor-derived cell-free DNA in plasma is one of the most promising directions in cancer diagnosis. The major challenge in such approach is how to identify the tiny amount of tumor DNAs out of total cell-free DNAs in blood. Here we propose an ultrasensitive cancer detection method, termed “CancerDetector”, using the DNA methylation profiles of cell-free DNAs. The key of our method is to probabilistically model the joint methylation patterns of multiple adjacent CpG sites on an individual sequencing read, in order to exploit the pervasive nature of DNA methylation for signal amplification. Therefore, CancerDetector can sensitively identify a trace amount of tumor cfDNAs in plasma, at the level of individual reads. We evaluated CancerDetector on the simulated data, and showed a high concordance of the predicted and true tumor burden. Testing CancerDetector on real plasma data demonstrated its high sensitivity and specificity in detecting tumor DNAs. In addition, the predicted tumor burden showed great consistency with tumor size and survival outcome. Note that all of those testing were performed on sequencing data at low to medium coverage (1X to 10X). Therefore, CancerDetector holds the great potential to detect cancer early and cost-effectively.

  Study EGAS00001002728

• A benchmarking resource for NGS testing of cancer predisposition genes

  A benchmarking resource of 639 individuals, to assess the analytical sensitivity of cancer predisposition gene (CPG) testing.The dataset includes sequencing data generated using the TruSight Cancer Panel (TSCP) a targeted NGS assay for analysis of CPGs and orthogonally generated data supporting at least one pathogenic variant in a CPG for a total of 645 pathogenic CPG variants.The set of pathogenic CPG variants includes strong representation of some of the most challenging types of pathogenic variants, with 339 indels, including 16 complex indels and 24 insertions or deletions with length greater than 5bp, and 74 exon CNVs, including 23 single exon CNVs. There are 502 pathogenic variants in BRCA1 or BRCA2, making this an important first-line validation dataset for laboratories performing NGS testing of BRCA1 and BRCA2.

  Study EGAS00001002993

• Type 1 Diabetes Genetics Consortium (T1DGC): Case-only RNA-Seq Study

  Peripheral blood mononuclear cells (PBMC) from 82 T1D cases from the T1DGC study were fractionated by positive selection on magnetic beads into CD4+ T cells, CD8+ T cells and CD19+ B cells. RNA purification, library preparation and sequencing to an average of 50 million reads per sample were performed by the HudsonAlpha Genome Services Laboratory. The resulting dataset includes 82 subjects with data from at least one cell type; sequence data from all 3 cell types is available from 79 subjects. The individuals in this study can be linked to the phs000911 T1DGC ImmunoChip study via subject ids to obtain both genotypic and phenotypic information, including genotypes used for expression quantitative trait locus analysis.

  Study phs001426

• cfMeDIP data for 67 VPC samples

  We analyzed the cell free DNA methylomes using 67 plasma samples from patients with mCRPC prostate cancer in the VPC project. Methylation was profiled using the methylated DNA immunoprecipitation coupled to next generation sequencing (MeDIP) technology.

  Dataset EGAD00001008711

• Deciphering somatic mosaic structural variation in human blood lineages using single-cell multiomics

  Somatic mosaicism (SM), referring to the presence of somatic mutations in sub-populations of cells within healthy individuals, is associated with an increased risk of a variety of diseases, including cancer. Blood is at particularly high risk of SM, given its rapid turnover and functionally- heterogeneous cell-type composition. While the roles of point mutations and large-scale rearrangements in blood SM have been scrutinised in recent years, the functional impact of mosaic structural variants (mSVs) remains poorly understood. Using haplotype-resolved single-cell multi-omics, we explored the mSV landscape of human hematopoietic stem and progenitor cells (HSPCs).

  Study EGAS00001006567

• Application of targeted long-read methylation sequencing to dissected lung cancer tissues

  To investigate DNA methylation patterns within the tumor microenvironment, multiple regions were dissected from fresh-frozen sections of two lung adenocarcinoma specimens using the Millisect system. These regions were annotated based on spatial transcriptome data. DNA samples extracted from these regions were subjected to targeted long-read methylation sequencing using t-nanoEM. To establish a control dataset, short-read whole-genome sequencing (WGS) was performed on the tumor and normal parts, and long-read WGS was performed on the tumor part.

  Study JGAS000757

• Atherosclerosis Risk in Communities Study (ARIC-BioLINCC)

  Data Access NOTE:Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. At present, the ARIC sIRB has determined that ARIC data cannot be shared with for-profit entities.Related Studies Other ARIC data available include: Imaging studies (ARIC-Imaging), Genetics and genomics (ARIC, phs000280.v8.p2), Collaborative Cohort of Cohorts for COVID-19 Research (C4R): ARIC (phs002988.v1.p1), and as a component of the Sleep Heart Health Study (SHHS-BioLINCC, phs003637.v1.p1). Available Data Data available for request include ARIC v1-v8 examination cycles, collated annual follow-up communication data for contact years 2-32, and follow-up for mortality, heart disease, and stroke events through 2019. Also included are data from ancillary studies. Objectives The objectives of ARIC are to: 1) investigate associations of factors, including those not previously measured in cohort studies, with prevalence of atherosclerosis and incidence of CHD, clinical stroke and other cardiovascular diseases; and 2) measure cardiovascular disease occurrence and trends and relate these to community levels of, and changes in, risk factors, medical care and atherosclerosis. Background At the time of project initiation, the NHLBI had long recognized the need for longitudinal studies to identify the biochemical and physiological markers and specific environmental factors which place individuals at high risk for the major atherosclerosis diseases. The development of reliable ultrasound examination of peripheral arteries enhanced the expected benefit of such studies. Community surveillance planning began for ARIC in response to recommendations of the 1978 NHLBI Workshop on the Decline in CHD Mortality and has been extended in its purpose to evaluate the large geographic differences in U.S. mortality. Participants Black and white men and women, age 45-64 at entry; sample size: 15,792. Design ARIC is a large-scale, long-term prospective study that measures associations of established and suspected coronary heart disease risk factors with both atherosclerosis and new CHD events in men and women from four geographically diverse communities. The project has two components: community surveillance of morbidity and mortality; and repeated examinations of a representative cohort of men and women in each community. The community surveillance involves abstracting hospital records and death certificates and investigating out-of-hospital deaths. The representative cohorts include approximately 4,000 persons from each community. Community surveillance data includes detailed hospital record abstraction, ECG tracings, and event adjudication. Data from out-of-hospital events in the community include physician, informant, and coroner questionnaires as well as death certificate data and event adjudication. Community surveillance ended in 2014.Cohort participants were examined four times at three year intervals between 1987 and 1998, and have been continuously contacted annually to update their medical histories. Atherosclerosis was measured by carotid ultrasonography. Risk factors studied include: blood lipids, lipoprotein cholesterols, and apolipoproteins; plasma hemostatic factors; blood chemistries and hematology; sitting, supine and standing blood pressures; anthropometry; fasting blood glucose and insulin levels; ECG findings; cigarette and alcohol use; physical activity levels; dietary aspects; and family history. Clinic visits were restarted in 2011 with ARIC visit 5.

  Study phs003738