From the Clinic to the Bench and Back Again in One Dog Year: How a Cross-Species Pipeline to Identify New Treatments for Sarcoma Illuminates the Path Forward in Precision Medicine.

Published online

Journal Article

Cancer drug discovery is an inefficient process, with more than 90% of newly-discovered therapies failing to gain regulatory approval. Patient-derived models of cancer offer a promising new approach to identify new treatments; however, for rare cancers, such as sarcomas, access to patient samples is limited, which precludes development of patient-derived models. To address the limited access to patient samples, we have turned to pet dogs with naturally-occurring sarcomas. Although sarcomas make up <1% of all human cancers, sarcomas represent 15% of cancers in dogs. Because dogs have similar immune systems, an accelerated pace of cancer progression, and a shared environment with humans, studying pet dogs with cancer is ideal for bridging gaps between mouse models and human cancers. Here, we present our cross-species personalized medicine pipeline to identify new therapies for sarcomas. We explore this process through the focused study of a pet dog, Teddy, who presented with six synchronous leiomyosarcomas. Using our pipeline we identified proteasome inhibitors as a potential therapy for Teddy. Teddy was treated with bortezomib and showed a varied response across tumors. Whole exome sequencing revealed substantial genetic heterogeneity across Teddy's recurrent tumors and metastases, suggesting that intra-patient heterogeneity and tumoral adaptation were responsible for the heterogeneous clinical response. Ubiquitin proteomics coupled with exome sequencing revealed multiple candidate driver mutations in proteins related to the proteasome pathway. Together, our results demonstrate how the comparative study of canine sarcomas offers important insights into the development of personalized medicine approaches that can lead to new treatments for sarcomas in both humans and canines.

Full Text

Duke Authors

Cited Authors

  • Rao, SR; Somarelli, JA; Altunel, E; Selmic, LE; Byrum, M; Sheth, MU; Cheng, S; Ware, KE; Kim, SY; Prinz, JA; Devos, N; Corcoran, DL; Moseley, A; Soderblom, E; Hsu, SD; Eward, WC

Published Date

  • 2020

Published In

Volume / Issue

  • 10 /

Start / End Page

  • 117 -

PubMed ID

  • 32117764

Pubmed Central ID

  • 32117764

International Standard Serial Number (ISSN)

  • 2234-943X

Digital Object Identifier (DOI)

  • 10.3389/fonc.2020.00117

Language

  • eng

Conference Location

  • Switzerland