Dataset Information

CellMiner Cross-Database (CellMinerCDB) version 1.2: Exploration of patient-derived cancer cell line pharmacogenomics.

ABSTRACT: CellMiner Cross-Database (CellMinerCDB, discover.nci.nih.gov/cellminercdb) allows integration and analysis of molecular and pharmacological data within and across cancer cell line datasets from the National Cancer Institute (NCI), Broad Institute, Sanger/MGH and MD Anderson Cancer Center (MDACC). We present CellMinerCDB 1.2 with updates to datasets from NCI-60, Broad Cancer Cell Line Encyclopedia and Sanger/MGH, and the addition of new datasets, including NCI-ALMANAC drug combination, MDACC Cell Line Project proteomic, NCI-SCLC DNA copy number and methylation data, and Broad methylation, genetic dependency and metabolomic datasets. CellMinerCDB (v1.2) includes several improvements over the previously published version: (i) new and updated datasets; (ii) support for pattern comparisons and multivariate analyses across data sources; (iii) updated annotations with drug mechanism of action information and biologically relevant multigene signatures; (iv) analysis speedups via caching; (v) a new dataset download feature; (vi) improved visualization of subsets of multiple tissue types; (vii) breakdown of univariate associations by tissue type; and (viii) enhanced help information. The curation and common annotations (e.g. tissues of origin and identifiers) provided here across pharmacogenomic datasets increase the utility of the individual datasets to address multiple researcher question types, including data reproducibility, biomarker discovery and multivariate analysis of drug activity.

SUBMITTER: Luna A

PROVIDER: S-EPMC7779001 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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CellMiner Cross-Database (CellMinerCDB) version 1.2: Exploration of patient-derived cancer cell line pharmacogenomics.

Luna Augustin A Elloumi Fathi F Varma Sudhir S Wang Yanghsin Y Rajapakse Vinodh N VN Aladjem Mirit I MI Robert Jacques J Sander Chris C Pommier Yves Y Reinhold William C WC

Nucleic acids research 20210101 D1

CellMiner Cross-Database (CellMinerCDB, discover.nci.nih.gov/cellminercdb) allows integration and analysis of molecular and pharmacological data within and across cancer cell line datasets from the National Cancer Institute (NCI), Broad Institute, Sanger/MGH and MD Anderson Cancer Center (MDACC). We present CellMinerCDB 1.2 with updates to datasets from NCI-60, Broad Cancer Cell Line Encyclopedia and Sanger/MGH, and the addition of new datasets, including NCI-ALMANAC drug combination, MDACC Cell ...[more]

PMID: 33196823

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Project description:CellMiner (http://discover.nci.nih.gov/cellminer) and CellMinerCDB (https://discover.nci.nih.gov/cellminercdb/) are web-based applications for mining publicly available genomic, molecular, and pharmacologic datasets of human cancer cell lines including the NCI-60, Cancer Cell Line Encyclopedia, Genomics of Drug Sensitivity in Cancer, Cancer Therapeutics Response Portal, NCI/DTP small cell lung cancer, and NCI Almanac cell line sets. Here, we introduce our RNA sequencing (RNA-seq) data for the NCI-60 and their access and integration with the other databases. Correlation to transcript microarray expression levels for identical genes and identical cell lines across CellMinerCDB demonstrates the high quality of these new RNA-seq data. We provide composite and isoform transcript expression data and demonstrate diversity in isoform composition for individual cancer- and pharmacologically relevant genes, including HRAS, PTEN, EGFR, RAD51, ALKBH2, BRCA1, ERBB2, TP53, FGFR2, and CTNND1. We reveal cell-specific differences in the overall levels of isoforms and show their linkage to expression of RNA processing and splicing genes as well as resultant alterations in cancer and pharmacologic gene sets. Gene-drug pairings linked by pathways or functions show specific correlations to isoforms compared with composite gene expression, including ALKBH2-benzaldehyde, AKT3-vandetanib, BCR-imatinib, CDK1 and 20-palbociclib, CASP1-imexon, and FGFR3-pazopanib. Loss of MUC1 20 amino acid variable number tandem repeats, which is used to elicit immune response, and the presence of the androgen receptor AR-V4 and -V7 isoforms in all NCI-60 tissue of origin types demonstrate translational relevance. In summary, we introduce RNA-seq data to our CellMiner and CellMinerCDB web applications, allowing their exploration for both research and translational purposes. SIGNIFICANCE: The current study provides RNA sequencing data for the NCI-60 cell lines made accessible through both CellMiner and CellMinerCDB and is an important pharmacogenomics resource for the field.

Project description:UnlabelledStudies in hypertension (HTN) pharmacogenomics seek to identify genetic sources of variable antihypertensive drug response. Genetic association studies have detected single-nucleotide polymorphisms (SNPs) that link to drug responses; however, to understand mechanisms underlying how genetic traits alter drug responses, a biological interface is needed. Patient-derived induced pluripotent stem cells (iPSCs) provide a potential source for studying otherwise inaccessible tissues that may be important to antihypertensive drug response. The present study established multiple iPSC lines from an HTN pharmacogenomics cohort. We demonstrated that established HTN iPSCs can robustly and reproducibly differentiate into functional vascular smooth muscle cells (VSMCs), a cell type most relevant to vasculature tone control. Moreover, a sensitive traction force microscopy assay demonstrated that iPSC-derived VSMCs show a quantitative contractile response on physiological stimulus of endothelin-1. Furthermore, the inflammatory chemokine tumor necrosis factor α induced a typical VSMC response in iPSC-derived VSMCs. These studies pave the way for a large research initiative to decode biological significance of identified SNPs in hypertension pharmacogenomics.SignificanceTreatment of hypertension remains suboptimal, and a pharmacogenomics approach seeks to identify genetic biomarkers that could be used to guide treatment decisions; however, it is important to understand the biological underpinnings of genetic associations. Mouse models do not accurately recapitulate individual patient responses based on their genetics, and hypertension-relevant cells are difficult to obtain from patients. Induced pluripotent stem cell (iPSC) technology provides a great interface to bring patient cells with their genomic data into the laboratory and to study hypertensive responses. As an initial step, the present study established an iPSC bank from patients with primary hypertension and demonstrated an effective and reproducible method of generating functional vascular smooth muscle cells.

Project description:ObjectivesWe built a novel mock pharmacogenomics web portal to deliver pharmacogenomic information and results to patients. Utilizing a patient focus group, we then sought to understand patient insights on desired features of an effective pharmacogenomics patient portal.MethodsThe mock YourPGx Portal delivered four sample pharmacogenomic results (omeprazole, simvastatin, clopidogrel, and codeine). Patients from our existing institutional, prospective pharmacogenomics implementation study were recruited to pilot the mock portal and then asked to participate in a focus group discussion led by two facilitators. All patients had been previously genotyped, but none had been directly provided access to their own genotyping results and none had previously used the YourPGx portal. The focus group discussion explored nine domains: (1) factors influencing drug response, (2) concerns about drug effects, (3) understanding of genomics and pharmacogenomics, (4) reasons to undergo pharmacogenomic testing, (5) sources of pharmacogenomic information for patient education, (6) attributes of pharmacogenomic sources of information, (7) considerations about privacy and personal pharmacogenomic information, (8) sharing of pharmacogenomic information, and (9) features of an effective patient portal.ResultsThe median age of patients (n = 10) was 65.5 years old (range 38-72), 70% female, 50% Caucasian/30% Black, and 60% held a bachelor/advanced degree. When asked about resources for seeking pharmacogenomic information, patients preferred consulting their providers first, followed by self-education, then using information provided by university research organizations. A theme emerged regarding attributes of these sources, namely a desire for understandability and trust. Patients said that the effectiveness of a pharmacogenomics patient portal is improved with use of symbolisms/graphics and clear and concise content. Effective use of colors, quantifying information, consistency, and use of layperson's language were additional important facets. Patients communicated the appeal of secured phone/app-enabled access and said that they would desire linking to their electronic medical records to allow sharing of information with different members of their healthcare team.ConclusionsPatients named providers as their primary source of pharmacogenomic information, but a pharmacogenomics patient portal that is carefully constructed to incorporate desired features may be a favorable tool to effectively deliver pharmacogenomic information and results to patients.

Dataset Information

CellMiner Cross-Database (CellMinerCDB) version 1.2: Exploration of patient-derived cancer cell line pharmacogenomics.

Publications

CellMiner Cross-Database (CellMinerCDB) version 1.2: Exploration of patient-derived cancer cell line pharmacogenomics.

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