11810 results for "cancer rna-seq"

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• Intra-prostatic tumour evolution, steps in metastatic spread and histogenomic associations revealed by integration of multi-region whole genome sequencing with histopathological features

  We performed whole genome sequencing on 42 prostate cancer samples from the prostate, seminal vesicles and regional lymph nodes of five treatment-naive patients with locally advanced disease who underwent radical prostatectomy. Using cancer cell fractions computed from single nucleotide variants and copy number alterations, we reconstructed the tumour phylogenies, which in turn allowed us to infer key molecular steps in the progression of prostate cancer in these individuals. We mapped the clonal composition of cancer sampled across the prostate in each individual and inferred the routes of spread of cancer cells within the prostate and to seminal vesicles and lymph nodes.

  Study EGAS00001007438

• Cancer Genomics, ICR, summary data

  DAC for summary level data from the Cancer Genomics group, Division of Genetics and Epidemiology at the Institute of Cancer Research, Sutton, UK.

  Dac EGAC50000000050

• GIST_SSGXVIII_trial_targeted_gene_sequencing

  Targeted cancer gene sequencing of samples enrolled in the SSGXVIII trial from Finland.

  Study EGAS00001001054

• The_genetic_evolution_of_precursor_lesions_in_pancreatic_cancer

  Mapping genetic evolution of pancreatic cancer precursor lesions such as IPMNs and PanINs.

  Study EGAS00001001573

• IACS treatment on breast cancer bone metastases

  Off-target effect of IACS on breast cancer bone metastases.

  Study EGAS00001006908

• Detroit Research on Cancer Survivors (ROCS) and Disparities and Cancer Epidemiology - Colorectal Cancer (DANCE)

  The goals for this study were as follows:1. Enroll a total of 5,060 African Americans newly diagnosed with cancer into the Detroit Research on Cancer Survivors (Detroit ROCS) Cohort. These population-based cases will be ascertained through the Detroit Metropolitan Detroit Cancer Surveillance System (MDCSS), a founding member of the NCI SEER Program. Participation at baseline will include a written, web-based, or telephone interview, saliva and/or blood collection, and tumor block retrieval, with detailed cancer-related information coming from the MDCSS registry and medical records.2. Enroll a subgroup of colorectal cancer patients identified through the Louisiana Tumor Registry (LTR). An additional 500 colorectal cancer patients, approximately half non-Hispanic white and half African American, will be identified through the LTR and enrolled into the ROCS protocol. The survey is the same survey administered to the ROCS cohort. The Louisiana (“DANCE-CRC”) cohort will not be followed beyond baseline, and blood will not be collected (tumor tissue, however, will be collected, deidentified, and sent for processing through Dr. Rozek's laboratory at Georgetown University).The proposed cohorts will provide for a broad research agenda evaluating cancer outcomes in African Americans across a variety of factors from individual, provider, health care system and community perspectives. These factors include tumor characteristics driving individualized treatment planning, quality of life after a diagnosis and recurrence. Utilizing the MDCSS registry, we will enroll a large population-based sample of African-American cases with lung, breast, colorectal, and prostate cancers and their caregivers resulting in a cohort that will provide substantial benefit to the cancer research community. KCI has a strong history of research in the African-American community and the faculty represents a breadth of experience that includes clinical oncology, genetic epidemiology, environmental exposures, quality of life, treatment decision making, racism/discrimination, and health behaviors. Drs. Schwartz and Beebe-Dimmer have been and will continue to be generous collaborators with other institutions to ensure that this resource will be extensively utilized. The proposed overall cohort will be the only one of its kind, to our knowledge, filling a substantial gap in our understanding of the determinants driving cancer outcomes in African Americans. In addition to registry data detailing cancer specifics, yearly surveys have collected information about individualized treatment experiences, heath histories, family histories, quality of life after a diagnosis, recurrence and caregiving. Population: Adult cancer survivors (see inclusion criteria in next section) Molecular Technologies: Genotyping: Infinium Expanded Multi-Ethnic Genotyping Array (MEGAEX) DNA Sequencing: Illumina NovaSeq X Plus using XLEAP-SBS (sequencing by synthesis) Whole genome sequencingPrincipal Findings: The preliminary data collected reinforces differences by race in factors affecting cancer outcomes. Variants in DNA damage repair genes and HOXB13 may be important cancer risk factors for Black men diagnosed with prostate cancer, and are more frequently observed in men with a family history of cancer. ROCS participants reported high rates of a family history of cancer. The high rate of eligibility for Cancer genetic counseling among ROCS participants supports the need for interventions to increase referrals and uptake of genetic counseling among African Americans 60% of ROCS participants reported participating in regular physical activity (PA), with 24% reporting ≥150 min/wk. There were no differences by sex, but prostate cancer survivors were the most likely to report participating in regular PA, whereas lung cancer survivors were the least likely. Survivors who reported participating in regular PA reported higher health-related quality of life and lower depression. More African American than White survivors reported financial hardship and limiting care. More White than African American survivors reported utilizing assets, while more African American survivors reported cancer-related debt. Data available in dbGaP: Individual phenotype data Individual genotype data Individual sequencing dataSample types: Germline DNA

  Study phs003116

• DNA Methylation Markers and Pancreatic Cancer Risk in 3 Cohort Studies (NHS, PHS, HPFS)

  Pancreatic cancer is the 4th leading cause of cancer deaths in the US. Due to the lack of early symptoms, pancreatic cancer is difficult to identify at early stages and no screening is available for the general population. Identifying pancreatic cancer at earlier stages could significantly improve survival with increased opportunities for surgery. New high-dimensional arrays designed to measure DNA methylation levels at hundreds of thousands of CpG sites throughout the genome have opened opportunities to examine the role of DNA methylation in cancer risk using blood samples. Using this method, archived samples from prospective studies can be used to examine early changes in the DNA methylation levels in individuals who develop cancer months or years later, providing new opportunities to better understand biological mechanisms and, perhaps, identify biomarkers for early detection. Pancreatic cancer cases and matched controls were obtained from 3 large cohort studies, the Nurses' Health Study (NHS), the Physician's Health Study (PHS), and the Health Professionals Follow-up Study (HPFS), to measure DNA methylation in stored buffy coats using a nested case-control study design.

  Study phs001917

• Genetic Epidemiology of Ovarian Cancer Histotypes

  Epithelial ovarian cancer is a highly fatal malignancy with known genetic etiology; however, it is estimated that a substantial portion of narrow sense heritability remains to be discovered. The goal of this research was to use genetic information from distantly related ovarian cancer cases to identify regions of the genome that may harbor rare risk variants for epithelial ovarian cancer. The study was conducted in the setting of the Utah Population Database, a statewide data resource in which extensive ancestry data are linked to Utah Cancer Registry records. Focusing on families with a statistically significant excess risk of epithelial ovarian cancer, we used the Infinium Global Screening Array v.3.0 to generate germline genotyping data for distantly related cases. We then applied Shared Genomic Segment Analysis to each set of related cases to identify genomic regions that may harbor ovarian cancer risk variants. Eleven regions were identified. Genotype data are available through dbGaP for one case from each pedigree. Genotype data from other ovarian cancer cases within the high-risk pedigrees as well as the pedigrees' corresponding structures can be requested and made available with approval from the Utah Resource for Genetic and Epidemiologic Research (RGE).

  Study phs003140

• noninvasive lung cancer subtyping

  Accurate diagnosis of lung cancer is important for treatment decision-making. Currently, the gold standard for diagnosing histological subtypes of lung cancer relies on tumor biopsies. Recently, liquid biopsy, particularly cell-free DNA (cfDNA), has shown promising results in cancer detection and classification. In this study, we investigated the potential of cfDNA methylome for the noninvasive classification of lung cancer histological subtypes. Specifically, we focused on the two most prevalent lung cancer subtypes, lung adenocarcinoma and lung squamous cell carcinoma. Using a fragment-based marker discovery approach, we identified robust subtype-specific methylation markers from tumor samples. These markers were successfully validated in independent cohorts and associated with subtype-specific transcription activity. Leveraging these markers, we constructed a subtype classification model using cfDNA methylation profiles, achieving an AUC of 0.808 in the cross-validation and an AUC of 0.747 in the independent validation. Additionally, tumor copy number variations inferred from cfDNA methylome analysis revealed potential implications for treatment selection. In summary, our study demonstrates the potential of cfDNA methylome analysis for noninvasively lung cancer subtyping, offering insights for cancer monitoring and early detection.

  Study EGAS00001007717

• RNAseq_Pulldown_

  We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses. In this experiment cDNA derived form Breast Cancer Cell lines was used in an Agilent whole exome pulldown experiment.

  Study EGAS00001000230