7098 results for "canc*"

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• Tumor Profiler Project - OV cell-free DNA data additional samples

  The dataset contains amplicon sequencing data from 7 samples from 7 different patients with ovarian cancers. Cell free DNA was collected from plasma. Sequencing was performed on an Ion Torrent platform and the sequencing data is provided in bam format. These samples are from patients not classified as having high-grade serous adenocarcinoma.

  Dataset EGAD50000001412

• Tumor Profiler Project - OV bulk transcriptomics data

  The dataset contains bulk transcriptomics data from 39 samples from 36 different patients with ovarian cancer. 34 samples were collected from the tumor, 5 samples from ascites. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format.

  Dataset EGAD50000001413

• Multi-Omics Study of Lung Cancer in Smokers From EAGLE

  EAGLE (Environment And Genetics in Lung cancer Etiology) is a population-based case-control study examining the full spectrum of lung cancer etiology from smoking initiation, smoking dependency to lung cancer development and outcome. It combines a traditional molecular epidemiology design with more integrative approaches by examining epidemiological, molecular, and clinical data together. To comprehensively investigate the effect of tobacco smoking behaviors on genomic or epigenomic alterations, we performed a multi-omics study including whole-genomic, transcriptomic, and epigenomic profiles in a total of 221 individuals from the EAGLE study.

  Study phs002992

• Integrating Circulating Tumor DNA Analysis and Radiomics for Dynamic Risk Assessment in Localized Lung Cancer

  DNA was isolated from pre-treatment and mid-treatment plasma samples and matched germline samples from patients undergoing chemoradiation therapy for stage IIB-IIIB non-small cell lung cancer. Sequencing libraries were hybrid captured using custom selector pools designed to target genes frequently mutated in non-small cell lung cancer prior to ultra-deep next generation sequencing.

  Study phs003947

• Somatic Mutations in 3,929 HPV-Positive Exfoliated Cervical Cell Samples

  We investigated the detection, timing, and HPV type specificity of cervical somatic hotspot mutations (i.e., previously reported cancer driver mutations) in 3,929 HPV-positive exfoliated cervical cell samples from individuals undergoing routine cervical screening in the U.S. using deep-targeted sequencing of 20 candidate genes. Our study included samples from 3,351 women with the following infection outcomes: 1,478 HPV16-, HPV18- and/or HPV45-positive controls (i.e., HPV infections that did not progress to precancer and/or subsequently cleared), 1,712 cervical precancers, and 161 invasive cervical cancers. We utilized residual exfoliated cervical cell samples from women routinely screened for cervical cancer precursors at Kaiser Permanente Northern California (KPNC) as part of the prospective KPNC-NCI HPV Persistence and Progression (PaP) cohort. We included 3,929 samples collected from these 3,351 women, including 974 serial sample from 396 women collected prior to their most recent screening visit to evaluate somatic hotspot mutation detection prior to diagnosis.

  Study phs003691

• Clinical Proteomic Tumor Analysis Consortium (CPTAC) Proteogenomic Confirmatory Study of Breast, Colon, Lung, and Ovarian Tumors

  Recently, significant progress has been made in characterizing and sequencing the genomic alterations in statistically robust numbers of samples from several types of cancer. For example, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and other similar efforts are identifying genomic alterations associated with specific cancers (e.g., copy number aberrations, rearrangements, point mutations, epigenomic changes, etc.). The availability of these multi-dimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions. Understanding the comprehensive functional changes in cancer proteomes arising from genomic alterations and other factors is the next logical step in the development of high-value candidate protein biomarkers. Hence, proteomics can greatly advance the understanding of molecular mechanisms of disease pathology via the analysis of changes in protein expression, their modifications and variations, as well as protein-protein interaction, signaling pathways and networks responsible for cellular functions such as apoptosis and oncogenesis. Realizing this great potential, the NCI launched the second phase of the CPTC initiative in September 2011. Renamed the Clinical Proteomic Tumor Analysis Consortium, CPTAC is beginning to leverage its analytical outputs from Phase I to define cancer proteomes on genomically-characterized biospecimens. The purpose of this integrative approach is to provide the broad scientific community with knowledge that links genotype to proteotype and ultimately phenotype. The data contained in this dataset are derived from samples designed to confirm CPTAC findings from the TCGA samples. These confirmatory samples contain breast, ovarian, colon, and lung tumors collected via a protocol optimized for proteomics. Specifically, ischemic time of the sample was controlled and restricted to less than 30 minutes. ACGT, Inc. produced whole exome, mRNAseq, and miRNAseq for these samples. Corresponding proteomic data are available at: https://cptac-data-portal.georgetown.edu/cptacPublic/ The study design was to profile colon, breast, ovarian, and lung tumors both genomically and proteomically. Germline DNA was obtained from blood. Normal control samples for proteomics varied by organ site: adjacent colon tissue for colon cases, contralateral breast tissue for some breast cases, and Fallopian tube fimbria for some ovarian cases. Lung cases had no normal control for proteomic analysis. All cancer samples were derived from primary and untreated tumors.

  Study phs000892

• Childhood Cancer Data Initiative (CCDI): Pediatric In Vivo Testing Program – Sarcomas and other Solid Tumors

  The primary goal of this project involves the comprehensive molecular profiling of patient-derived xenograft (PDX) mouse tumor models. Molecular profiling of each PDX model will include whole exome sequencing (WES), RNAseq, MethylEPIC arrays, CytoSNP array, and DNA fingerprint for quality control. Limited clinical demographic data (e.g. diagnosis, disease site, disease status) will be obtained. This data can be utilized to validate PDX models with matched patient tumors and can be used to guide model selection for downstream preclinical drug testing.

  Study phs003161

• Human Tumor Atlas Network (HTAN)

  An NCI-funded Cancer Moonshot initiative to construct 3-dimensional atlases of the dynamic cellular, morphological, and molecular features of human cancers as they evolve from precancerous lesions to advanced disease.

  Study phs002371

• MP2PRT-MNG: Identifying Novel Molecular Markers of Response to Radiotherapy in Meningiomas Using Samples from the RTOG-0539 (NCT00895622)

  The Molecular Profiling to Predict Response to Treatment (MP2PRT) program is part of the NCI's Cancer Moonshot Initiative. The aim of this program is the retrospective characterization and analysis of biospecimens collected from completed NCI-sponsored trials of the National Clinical Trials Network and the NCI Community Oncology Research Program. NRG RTOG (Radiation Therapy Oncology Group)-0539, which was a nonrandomized phase II cooperative group trial in 2009, was selected for inclusion in this program. NRG RTOG-0539 assigned patients with histologically confirmed diagnosis of meningioma to 1 of 3 risk groups based on 2007 WHO grade, resection extent, and recurrence status, and radiotherapy was given per protocol to the intermediate- and high-risk cases. Under the MP2PRT program, DNA methylation profiling, RNA sequencing, and whole exome sequencing were performed on clinical trial cases with available tissue for molecular analyte extraction and subsequent sequencing. Raw molecular data with metadata are available for this study.

  Study phs003707

• NCI's Collection of Studies for General Cancer Research

  This collection contains all of NCIs authorized individual-level genomic datasets currently in dbGaP that are approved for Cancer Research (DS-CA) use only and limitations outlined in the model Data Use Certification Agreement. Access to this study will include any additional authorized individual-level DS-CA datasets that become available. Renewal of this study is required annually. To request access to this study collection, select phs003967.v1.p1 in the dbGaP Authorized Access System.

  Study phs003967