In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 10_Supplement ( 2022-05-15), p. A020-A020
Abstract:
Osteosarcoma is a rare pediatric cancer characterized by poor prognosis and a high likelihood of metastasis, for which no systemic treatments have been successfully developed in the past 30 years [1]. The lack of effective biologically relevant osteosarcoma tumor models is a significant obstacle to the development of effective therapeutics [2] . Therefore, developing a framework that addresses this issue is essential in further advancing therapeutics studies. We postulate that a comparative genomics approach, evaluating whole-transcriptome osteosarcoma response in species closely related to humans, would highlight immune and other differences in each species that will better guide the design of human therapeutics. To investigate this, we compile RNA-seq data from studies of mice, human, and canine osteosarcoma [3], and perform an integrated analysis of disease in these three species. We build a tri-species multi-layer network of regulatory interactions in osteosarcomas to identify evolutionary links between osteosarcomas. Each layer of our network represents the interactions in one species, and the integrated network captures interactions preserved across species. We perform enrichment analysis on these networks and statistically evaluate differences between the topologies of the regulatory networks of these three species, investigating the functional impact of species-specific interactions and how each affects drug response. Additionally, we survey the literature to identify mutations in osteosarcomas from each species, and calculate diffusion scores for mutated genes in each layer of the network compared to genes mutated in osteosarcoma. As future work, we aim to utilize our comparative genomics approach and leverage the differences between interaction networks of related species to compute the likelihood of identifying early-stage therapeutic trials that will fail in later stages, thus avoiding costly experiments and guiding drug development. Citation Format: Tina Salehi Torabi, Soumya Gottipati, Tamer Kahveci, Kiley Graim. Multi-species regulatory analysis of osteosarcoma to reduce clinical trial failure rates [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 A020.
Type of Medium:
Online Resource
ISSN:
1538-7445
DOI:
10.1158/1538-7445.EVODYN22-A020
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2022
detail.hit.zdb_id:
2036785-5
detail.hit.zdb_id:
1432-1
detail.hit.zdb_id:
410466-3
