Abstract A039: Transcriptomic analysis of canine osteosarcoma from a precision medicine perspective reveals limitations of differential gene expression studies

Abstract

Despite significant advances in cancer diagnosis and treatment, osteosarcoma (OSA), an aggressive primary bone tumor, has eluded attempts at improving patient survival for many decades. Spontaneously occurring OSA in the dog shares remarkably similar clinical, histological, and molecular characteristics and therefore serves as an excellent model for the disease. The difficulty in managing OSA lies in its extreme genetic complexity, drug-resistance, and heterogeneity, making it improbable that a single-target treatment would be beneficial for the majority of affected individuals. Precision medicine seeks to fill this gap by addressing the intra- and inter-tumoral heterogeneity to improve patient outcome and survival. Characterization of differentially expressed genes (DEGs) provides insight into the phenotype and can be useful for informing appropriate therapies as well as development of novel treatments. To identify relevant DEGs, RNA profiles of primary tumor should be contrasted with that of normal tissue derived from the same cell-of-origin as the tumor prior to chemotherapy, as convoluted drug-resistant pathways make interpretation difficult. Traditional DEG analysis combines patient data to derive statistically inferred genes that are dysregulated in the group; however, the results from this approach are not necessarily consistent across individual patients, thus contradicting the basis of precision medicine. In this preliminary study, we use transcriptomic sequencing of RNA isolated from primary canine OSA tumor and patient-matched normal bone from seven dogs prior to chemotherapy to identify DEGs in the group. We then evaluate the universality of these changes in transcript levels among patients by deriving individual-level fold-change values using strict filtering parameters. The results from this study can be useful for reframing our perspective of transcriptomic analysis from a precision medicine perspective by identifying variations in DEGs among individuals. Citation Format: Rebecca L. Nance, Sara Cooper, Dmytro Starenki, Xu Wang, Maninder Sandey, Jey Koehler, Payal Agarwal, Brad Matz, Stephanie Lindley, Annette Smith, Ashley Smith, Noelle Bergman, Bruce F. Smith. Transcriptomic analysis of canine osteosarcoma from a precision medicine perspective reveals limitations of differential gene expression studies [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr A039.