title: Novel prediction of anticancer drug chemosensitivity in cancer cell lines: evidence of moderation by microRNA expressions.
abstract: The objectives of this study are (1) to develop a novel "moderation" model of drug chemosensitivity and (2) to investigate if miRNA expression moderates the relationship between gene expression and drug chemosensitivity, specifically for HSP90 inhibitors applied to human cancer cell lines. A moderation model integrating the interaction between miRNA and gene expressions was developed to examine if miRNA expression affects the strength of the relationship between gene expression and chemosensitivity. Comprehensive datasets on miRNA expressions, gene expressions, and drug chemosensitivities were obtained from National Cancer Institute's NCI-60 cell lines including nine different cancer types. A workflow including steps of selecting genes, miRNAs, and compounds, correlating gene expression with chemosensitivity, and performing multivariate analysis was utilized to test the proposed model. The proposed moderation model identified 12 significantly-moderating miRNAs: miR-15b*, miR-16-2*, miR-9, miR-126*, miR-129*, miR-138, miR-519e*, miR-624*, miR-26b, miR-30e*, miR-32, and miR-196a, as well as two genes ERCC2 and SF3B1 which affect chemosensitivities of Tanespimycin and Alvespimycin - both HSP90 inhibitors. A bootstrap resampling of 2,500 times validates the significance of all 12 identified miRNAs. The results confirm that certain miRNA and gene expressions interact to produce an effect on drug response. The lack of correlation between miRNA and gene expression themselves suggests that miRNA transmits its effect through translation inhibition/control rather than mRNA degradation. The results suggest that miRNAs could serve not only as prognostic biomarkers for cancer treatment outcome but also as interventional agents to modulate desired chemosensitivity.
authors.forename: Daniel S
authors.initials: DS
authors.lastname: Yang
mesh_terms: D000465:Algorithms; D000970:Antineoplastic Agents / Q000494:pharmacology* / Q000627:therapeutic use; D016227:Benzoquinones / Q000494:pharmacology; D014408:Biomarkers, Tumor / Q000378:metabolism; D045744:Cell Line, Tumor; D015972:Gene Expression Regulation, Neoplastic / Q000187:drug effects*; D018841:HSP90 Heat-Shock Proteins / Q000037:antagonists & inhibitors / Q000378:metabolism; D006801:Humans; D047029:Lactams, Macrocyclic / Q000494:pharmacology; D016015:Logistic Models; D035683:MicroRNAs / Q000378:metabolism*; D009369:Neoplasms / Q000175:diagnosis / Q000188:drug therapy; D020411:Oligonucleotide Array Sequence Analysis; D010750:Phosphoproteins / Q000235:genetics / Q000378:metabolism; D000072260:RNA Splicing Factors; D017413:Ribonucleoprotein, U2 Small Nuclear / Q000235:genetics / Q000378:metabolism; D051759:Xeroderma Pigmentosum Group D Protein / Q000235:genetics / Q000378:metabolism
chemical_list: D000970:Antineoplastic Agents; D016227:Benzoquinones; D014408:Biomarkers, Tumor; D018841:HSP90 Heat-Shock Proteins; D047029:Lactams, Macrocyclic; D035683:MicroRNAs; D010750:Phosphoproteins; D000072260:RNA Splicing Factors; D017413:Ribonucleoprotein, U2 Small Nuclear; C112491:SF3B1 protein, human; C448659:17-(dimethylaminoethylamino)-17-demethoxygeldanamycin; C112765:tanespimycin; D051759:Xeroderma Pigmentosum Group D Protein