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

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 significantly better clinical outcomes than those that didn't (p = 0.0006, Log Rank), and this predictor significantly associated with longer disease free intervals in a Cox multivariate analysis (hazard ratio = 0.3102, p = 0.0124).Our data show that intra- and interspecies gene expression models can successfully predict response in canine OS, which may improve outcome in dogs and serve as pre-clinical validation for similar methods in human cancer research.

SUBMITTER: Fowles JS

PROVIDER: S-EPMC4759767 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Project description:The cell density-dependent control of gene expression is employed by many bacteria for regulating a variety of physiological functions, including the generation of bioluminescence, sporulation, formation of biofilms, and the expression of virulence factors. Although periodontal organisms do not appear to secrete acyl-homoserine lactone signals, several species, e.g., Porphyromonas gingivalis, Prevotella intermedia, and Fusobacterium nucleatum, have recently been shown to secrete a signal related to the autoinducer II (AI-2) of the signal system 2 pathway in Vibrio harveyi. Here, we report that the periodontal pathogen Actinobacillus actinomycetemcomitans expresses a homolog of V. harveyi luxS and secretes an AI-2-like signal. Cell-free conditioned medium from A. actinomycetemcomitans or from a recombinant Escherichia coli strain (E. coli AIS) expressing A. actinomycetemcomitans luxS induced luminescence in V. harveyi BB170 >200-fold over controls. AI-2 levels peaked in mid-exponential-phase cultures of A. actinomycetemcomitans and were significantly reduced in late-log- and stationary-phase cultures. Incubation of early-log-phase A. actinomycetemcomitans cells with conditioned medium from A. actinomycetemcomitans or from E. coli AIS resulted in a threefold induction of leukotoxic activity and a concomitant increase in leukotoxin polypeptide. In contrast, no increase in leukotoxin expression occurred when cells were exposed to sterile medium or to conditioned broth from E. coli AIS(-), a recombinant strain in which luxS was insertionally inactivated. A. actinomycetemcomitans AI-2 also induced expression of afuA, encoding a periplasmic iron transport protein, approximately eightfold, suggesting that LuxS-dependent signaling may play a role in the regulation of iron acquisition by A. actinomycetemcomitans. Finally, A. actinomycetemcomitans AI-2 added in trans complemented a luxS knockout mutation in P. gingivalis by modulating the expression of the luxS-regulated genes uvrB and hasF in this organism. Together, these results suggest that LuxS-dependent signaling may modulate aspects of virulence and the uptake of iron by A. actinomycetemcomitans and induce responses in other periodontal organisms in mixed-species oral biofilm.

Project description:Osteosarcoma (OS) is a heterogeneous and rare disease with a disproportionate impact because it mainly affects children and adolescents. Lamentably, more than half of patients with OS succumb to metastatic disease. Clarification of the etiology of the disease, development of better strategies to manage progression, and methods to guide personalized treatments are among the unmet health needs for OS patients. Progress in managing the disease has been hindered by the extreme heterogeneity of OS; thus, better models that accurately recapitulate the natural heterogeneity of the disease are needed. For this study, we used cell lines derived from two spontaneous canine OS tumors with distinctly different biological behavior (OS-1 and OS-2) for heterotypic in vivo modeling that recapitulates the heterogeneous biology and behavior of this disease. Both cell lines demonstrated stability of the transcriptome when grown as orthotopic xenografts in athymic nude mice. Consistent with the behavior of the original tumors, OS-2 xenografts grew more rapidly at the primary site and had greater propensity to disseminate to lung and establish microscopic metastasis. Moreover, OS-2 promoted formation of a different tumor-associated stromal environment than OS-1 xenografts. OS-2-derived tumors comprised a larger percentage of the xenograft tumors than OS-1-derived tumors. In addition, a robust pro-inflammatory population dominated the stromal cell infiltrates in OS-2 xenografts, whereas a mesenchymal population with a gene signature reflecting myogenic signaling dominated those in the OS-1 xenografts. Our studies show that canine OS cell lines maintain intrinsic features of the tumors from which they were derived and recapitulate the heterogeneous biology and behavior of bone cancer in mouse models. This system provides a resource to understand essential interactions between tumor cells and the stromal environment that drive the progression and metastatic propensity of OS.

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

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