title: A pharmacogenomic method for individualized prediction of drug sensitivity.
abstract: Identifying the best drug for each cancer patient requires an efficient individualized strategy. We present MATCH (Merging genomic and pharmacologic Analyses for Therapy CHoice), an approach using public genomic resources and drug testing of fresh tumor samples to link drugs to patients. Valproic acid (VPA) is highlighted as a proof-of-principle. In order to predict specific tumor types with high probability of drug sensitivity, we create drug response signatures using publically available gene expression data and assess sensitivity in a data set of >40 cancer types. Next, we evaluate drug sensitivity in matched tumor and normal tissue and exclude cancer types that are no more sensitive than normal tissue. From these analyses, breast tumors are predicted to be sensitive to VPA. A meta-analysis across breast cancer data sets shows that aggressive subtypes are most likely to be sensitive to VPA, but all subtypes have sensitive tumors. MATCH predictions correlate significantly with growth inhibition in cancer cell lines and three-dimensional cultures of fresh tumor samples. MATCH accurately predicts reduction in tumor growth rate following VPA treatment in patient tumor xenografts. MATCH uses genomic analysis with in vitro testing of patient tumors to select optimal drug regimens before clinical trial initiation.
authors.affiliation: Division of Internal Medicine, Department of Oncology, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.
authors.forename: Adam L
authors.initials: AL
authors.lastname: Cohen
authors.forename: Raffaella
authors.initials: R
authors.lastname: Soldi
authors.forename: Haiyu
authors.initials: H
authors.lastname: Zhang
authors.forename: Adam M
authors.initials: AM
authors.lastname: Gustafson
authors.forename: Ryan
authors.initials: R
authors.lastname: Wilcox
authors.forename: Bryan E
authors.initials: BE
authors.lastname: Welm
authors.forename: Jeffrey T
authors.initials: JT
authors.lastname: Chang
authors.forename: Evan
authors.initials: E
authors.lastname: Johnson
authors.forename: Avrum
authors.initials: A
authors.lastname: Spira
authors.forename: Stefanie S
authors.initials: SS
authors.lastname: Jeffrey
authors.forename: Andrea H
authors.initials: AH
authors.lastname: Bild
mesh_terms: D000818:Animals; D014408:Biomarkers, Tumor / Q000235:genetics; D001943:Breast Neoplasms / Q000188:drug therapy*; D045744:Cell Line, Tumor; D019008:Drug Resistance, Neoplasm; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D015894:Genome, Human; D006801:Humans; D051379:Mice; D020411:Oligonucleotide Array Sequence Analysis; D010597:Pharmacogenetics / Q000379:methods*; D010641:Phenotype; D012680:Sensitivity and Specificity; D014635:Valproic Acid / Q000494:pharmacology*
chemical_list: D014408:Biomarkers, Tumor; D014635:Valproic Acid