7082 results for "canc*"

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• Integrated Clinical and Transcriptomic Profiling to Characterize Disease Phenotype

  Personalized medicine requires that we first address the challenge of genetic heterogeneity, prominent in rare cancers to common disease. While current clinical DNA sequence data successfully identify novel genetic variants, the genomic data alone are insufficient biomarkers of clinical phenotype. There is an unmet need for systematic integration of specific functional genomic data with patient genetic data, in order to bridge the knowledge gap between genetic variation and clinical phenotype. This specific study is focused on functional genomic data from platelets as disease-specific cells that are also ideal for proof-of-principle transcriptomic investigation (being anucleate), and highly-relevant to multiple disease processes.

  Study phs002121

• Pan Cancer Investigation of Human Leukocyte Antigen Loss of Heterozygosity

  Cancer cells can escape immune recognition through human leukocyte antigen (HLA) loss of heterozygosity (LOH) which results in deletion of HLA alleles, causing a reduction in presentation of tumor neoantigens. Despite its influence on immunotherapy response, few methods exist to detect HLA LOH, and accuracy of the approaches is poorly defined. Here, we present DASH (Deletion of Allele-Specific HLAs), a machine learning-based algorithm developed to detect HLA LOH from paired tumor-normal sequencing data. Using DASH to characterize HLA LOH in 610 patients across 15 cancer types, we found that 18% of patients had loss of heterozygosity in at least one HLA allele, suggesting the HLA LOH is a widespread, and potentially key immune resistance strategy in multiple cancers.

  Study phs002783

• Pancreatic Cancer Case Control Association Study

  Pancreatic cancer is the fourth leading cause of cancer death in the United States. This is in large part due to the rapidly fatal course of this disease, as the vast majority of patients die within months of diagnosis and the five-year survival rate is less than 5. We have brought together over 8000 participants from 9 studies of pancreatic cancer, to conduct a GWAS of pancreatic cancer. The studies were drawn from the Pancreatic Cancer Case-Control consortium and include case-control studies from the United States, Europe and Australia. Sites include: Johns Hopkins National Familial Pancreas Tumor Registry, Mayo Clinic Biospecimen Resource for Pancreas Research, Ontario Pancreas Cancer Study (OPCS), Yale University, MD Anderson Case Control Study, Queensland Pancreatic Cancer Study, University of California San Francisco Molecular Epidemiology of Pancreatic Cancer Study, International Agency of Cancer Research and Memorial Sloan Kettering Cancer Center.

  Study phs000648

• Baylor College of Medicine Advancing Sequencing in Childhood Cancer Care (BASIC3) Clinical Exome Sequencing Study - Clinical Sequencing Exploratory Research Consortium

  The BASIC3 (Baylor College of Medicine Advancing Sequencing in Childhood Cancer Care) study is a National Genome Human Research Institute (NHGRI) and National Cancer Institute-funded Clinical Sequencing Exploratory Research (CSER) consortium project that focuses on prospective implementation of clinical whole exome sequencing in the pediatric oncology clinic. The primary study objective are to integrate information from CLIA-certified germline and tumor exome sequencing into the care of newly diagnosed solid tumor patients at Texas Children's Cancer Center, and to perform parallel evaluation of the impact of tumor and germline exomes on families and physicians. Blood and frozen tumor (if available) samples are collected from children undergoing surgery or biopsy of newly diagnosed solid tumors and subjected to exome sequencing in a CLIA-certified laboratory. Germline and tumor (if applicable) exome sequencing reports are generated and submitted into the electronic health record and returned to each patient/family by their primary oncologist. If specific (optional) consent is obtained, research sequencing studies (including transcriptome sequencing) are performed in addition to the clinical exome sequencing.

  Study phs001026

• Aurora US Metastatic Breast Cancer Retrospective Project

  The AURORA US Metastatic Breast Cancer project is funded by the Breast Cancer Research Foundation (BCRF) Evelyn H. Lauder Founder's Fund for Metastatic Breast Cancer Research. This multi-center effort conducted within the Translational Breast Cancer Research Consortium (TBCRC) and cancer researchers to better understand the metastatic process through the study of both the primary and metastatic tissue. In the retrospective phase, TBCRC sites submitted matched primary and metastatic tissues and blood from previous collections for piloting the process. Samples were profiled using whole genome DNA sequencing, whole exome DNA sequencing, DNA methylation arrays, and RNA sequencing. The final freeze set for samples with successful nucleic acid extraction and molecular assays included 55 patients with 31 primary tissues and 102 metastases. Twenty patients had tissue collected at autopsy and included 19 with more than one metastasis. Metastases were from 20 different tissue locations with the most common sites being liver, lung, lymph node, and brain. The median age at primary diagnosis was 49 years. The clinical subtypes of the primary tumors were 34% Triple Negative, 30% ER+HER2-, 11% ER+HER2+, and 7% ER-HER2+. Patients received an average of 3 lines of therapy in the metastatic setting. The median overall survival from primary diagnosis was 4.5 years and overall survival from metastatic diagnosis was 2 years.

  Study phs002622

• Division of Cancer Epidemiology and Genetics (DCEG) Imputation Reference Dataset

  We have built a new resource for imputation of SNPs for existing and future genome-wide association studies (GWAS), known as the Division of Cancer Epidemiology and Genetics (DCEG) Reference Set. The first build of the data set includes 728 cancer-free individuals of European descent from three large prospectively sampled studies, 98 African-American individuals from the Prostate, Lung, Colon, and Ovary Cancer Screening Trial (PLCO), 74 Chinese individuals from a Chinese clinical trial in Shanxi, China (SHNX), and 349 unrelated individuals from the HapMap Project (see Molecular Data Section for details on arrays used). The final harmonized dataset includes 2.8 million autosomal polymorphic SNPs on 1,249 subjects after rigorous quality control metrics were applied.

  Study phs000396

• The Spatio-Temporal Evolution of Multiple Myeloma from Baseline to Relapse-Refractory States

  In multiple myeloma, the spatio-temporal evolution patterns of cancer cells in the bone marrow remain largely unknown. Here, we applied spatial-longitudinal sequencing, including a total of 179 samples collected from 25 patients during a follow-up of up to 14 years. Our study highlights focal bone lesions (FL) as hotspots of tumor evolution and provides possible explanations for their negative prognostic impact. We show a close phylogenetic relationship between baseline FL and relapse clones. In patients with ≥3 FDG-PET-positive FL at diagnosis, relapse was driven by multiple distinct sub-clones, whereas in other patients, a single-cell expansion was typically seen (p<0.01). Applying imaging-guided sampling, we identified a novel evolutionary pattern with unique treatment-resistant sub-clones at distinct locations. We observed multiple selective clonal sweeps, resistant clones that can be hidden over years, and epigenetic modifier mutations as a new class of relapse aberrations. Here we show that imaging can enhance tumor evolution studies and response assessment. The sophisticated evolution mechanisms in myeloma and presence of single cells that can drive relapse even after 10 years of remission suggest that a prerequisite for curative therapies would be to overcome not only tumor heterogeneity but also dormancy.

  Study phs002625

• Breakpoint detection using long insert whole genome sequencing

  In this study, we hypothesize that shallow long insert whole genome sequencing (LI-WGS) increases our power for detecting breakpoints compared to shallow short insert WGS. We performed a priori analyses to demonstrate the benefits of LI-WGS, developed a long insert library preparation protocol based off Illumina's protocol, and compared LI-WGS against short insert WGS on test samples. We then used long insert WGS to identify translocations and copy number changes in tumor and germline samples collected from cancer patients with different malignancies.

  Study phs000646

• MP2PRT: Comprehensive Genomic Profiling to Identify Alterations Associated with Relapse for NCI Standard Risk (SR) B-Lineage ALL and NCI High Risk (HR) B-Lineage ALL with Favorable Genetic Features

  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. This study, titled "Comprehensive Genomic Profiling to Identify Alterations Associated with Relapse for NCI Standard Risk (SR) B-Lineage ALL and NCI High Risk (HR) B-Lineage ALL with Favorable Genetic Features," is one of the selected studies under this program. For this study, genomic characterization (WGS 30X, WXS, Total RNAseq) was performed on NCI Standard Risk B-lineage ALL patients who relapse and subsets of NCI High Risk B-lineage ALL patients who relapse as well as two non-relapse control cases for each relapse case. It was hypothesized that the comprehensive characterization of these sample sets will allow the identification of somatic genetic features that will facilitate early intervention to improve cure rates for those enrolled on future trials. Data were generated and genetic subtype was integrated with clinical variables, including age, presenting white blood cell count, sex, race, and levels of minimal residual disease at the end of induction. Additional secondary alterations were identified and included if they occurred in more than 10 patients. The study has been completed and a manuscript has been prepared.

  Study phs002005

• De Novo Characterization of Cell-Free DNA Fragmentation Hotspots in Plasma Whole-Genome Sequencing

  The raw sequencing data deposited here are low-coverage (~1X) whole-genome sequencing (WGS) of plasma cell-free DNA (cfDNA). The purpose is to validate the performance of early-stage cancer diagnosis in the Zhou et al. 2020 BioRxiv paper, mainly for two types of cancer: early-stage liver cancer and breast cancer. The cases and controls are matched with age, gender, smoking history, and alcohol usage. We developed a computational method to identify the cfDNA fragmentation hotspots from pooled low-coverage cfDNA WGS data. We found the cfDNA fragmentation hotspots are highly enriched in regulatory regions, such as open chromatin regions. The signals from these regions can help the diagnosis of early-stage cancers and their tissues-of-origin.

  Study phs003062