Intra- and interspecies gene expression models for predicting drug response in canine osteosarcoma

BMC Bioinformatics
Jared S FowlesDaniel L Gustafson

Abstract

Genomics-based predictors of drug response have the potential to improve outcomes associated with cancer therapy. Osteosarcoma (OS), the most common primary bone cancer in dogs, is commonly treated with adjuvant doxorubicin or carboplatin following amputation of the affected limb. We evaluated the use of gene-expression based models built in an intra- or interspecies manner to predict chemosensitivity and treatment outcome in canine OS. Models were built and evaluated using microarray gene expression and drug sensitivity data from human and canine cancer cell lines, and canine OS tumor datasets. The "COXEN" method was utilized to filter gene signatures between human and dog datasets based on strong co-expression patterns. Models were built using linear discriminant analysis via the misclassification penalized posterior algorithm. The best doxorubicin model involved genes identified in human lines that were co-expressed and trained on canine OS tumor data, which accurately predicted clinical outcome in 73 % of dogs (p = 0.0262, binomial). The best carboplatin model utilized canine lines for gene identification and model training, with canine OS tumor data for co-expression. Dogs whose treatment matched our predictions had signif...Continue Reading

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Jan 5, 2017·Genes, Chromosomes & Cancer·Stephen A RamseyShay Bracha
Jun 28, 2016·Molecular BioSystems·F CecilianiC Lecchi
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Jun 5, 2021·Veterinary World·Dolly Patricia Pardo-MoraJosé Maurício Sforcin

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Datasets Mentioned

BETA
FACC
GSE76126

Methods Mentioned

BETA
amputation
PCR
genotyping
chip

Clinical Trials Mentioned

NCT01228942

Software Mentioned

Affymetrix
Basic Local Alignment Search Tool ( BLAST )
Bioconductor
BLAST
Array Express
R package “ WGCNA ”
Significance Analysis of Microarrays ( SAM )
FACCosteo CARBO
R
SAM

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