ID
45183
Descripción
Principal Investigator: Todd Golub, Broad Institute of MIT and Harvard Dana Farber Cancer Institute, Boston, MA, USA MeSH: Multiple Myeloma https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000348 This project was designed to describe genetic abnormalities in primary samples from patients with multiple myeloma by next generation sequencing. We generated sequence data from multiple myeloma (MM) patients analyzing DNA both from tumor cells (purified from bone marrow using CD138 selection as a marker of plasma cells) and from normal peripheral blood cells (either whole blood or Ficoll-purified mononuclear cells). Using massively parallel sequencing technology (Illumina GA-2 or HiSeq)), we performed whole-genome sequencing (WGS) and/or whole-exome sequencing (WES). The initial set currently deposited contains data from 38 MM patients (23 patients surveyed by WGS and 16 patients by WES, with one patient analyzed by both approaches). Genomes were sampled to high depth, obtaining an average of 33X coverage and 104X coverage for WGS and WES tumors, respectively. The normal samples had similar coverage. Our goal is to help researchers understand the complex genetic landscape of multiple myeloma and provide a resource for the generation of biological hypotheses.
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Versiones (2)
- 20/8/22 20/8/22 - Simon Heim
- 12/10/22 12/10/22 - Adrian Schulz
Titular de derechos de autor
Todd Golub, Broad Institute of MIT and Harvard Dana Farber Cancer Institute, Boston, MA, USA
Subido en
12 de octubre de 2022
DOI
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Licencia
Creative Commons BY 4.0
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dbGaP phs000348 Towards a Genomic Understanding of Myeloma
This sample attributes data table is collected from patients diagnosed with multiple myeloma. Variables include body site where sample was collected, analyte type, and tumor status.
- StudyEvent: SEV1
- Eligibility Criteria
- This subject consent data table contains a listing of subject IDs and subject consent groups.
- The subject sample mapping data table contains a mapping of study subject IDs to sample IDs and sample use. dbGaP samples are defined as the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs.
- This subject phenotype data table is collected from patients diagnosed with multiple myeloma. The phenotype variables collected were sociodemography (n=2 variables; gender and race), physical observations (n=4 variables; presence and absence of lytic lesions, survival status and age of diagnosis), laboratory measurements (n=14 variables; heavy and light chain class, M-spike, hemoglobin levels, platelet counts, CRP, kappa and lambda levels, creatinine, calcium, LDH and albumin serum levels), and treatment history (n=1 variable).
- This sample attributes data table is collected from patients diagnosed with multiple myeloma. Variables include body site where sample was collected, analyte type, and tumor status.
Similar models
This sample attributes data table is collected from patients diagnosed with multiple myeloma. Variables include body site where sample was collected, analyte type, and tumor status.
- StudyEvent: SEV1
- Eligibility Criteria
- This subject consent data table contains a listing of subject IDs and subject consent groups.
- The subject sample mapping data table contains a mapping of study subject IDs to sample IDs and sample use. dbGaP samples are defined as the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs.
- This subject phenotype data table is collected from patients diagnosed with multiple myeloma. The phenotype variables collected were sociodemography (n=2 variables; gender and race), physical observations (n=4 variables; presence and absence of lytic lesions, survival status and age of diagnosis), laboratory measurements (n=14 variables; heavy and light chain class, M-spike, hemoglobin levels, platelet counts, CRP, kappa and lambda levels, creatinine, calcium, LDH and albumin serum levels), and treatment history (n=1 variable).
- This sample attributes data table is collected from patients diagnosed with multiple myeloma. Variables include body site where sample was collected, analyte type, and tumor status.
C1299222 (UMLS CUI [1,2])
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