Abstract 3211: Therapeutic effects of radiotherapy on cancer cell lines using RadioGx computational platform
Authors: Manem Venkata S. , Lambie Meghan , Smirnov Petr , Freeman Mark , Kofia Victor , Abazeed Mohamed E. , Bratman Scott V. , Haibe-Kains Benjamin 
Published: August 2018

Purpose: Radiotherapy (RT) is the foundation of curative treatment regimens for many cancer types and is often delivered with drugs to produce synergistic effects. The “precision medicine” paradigm in which genomic biomarkers guide therapeutic decisions has eluded RT. To support preclinical discovery of biomarker-directed RT dose and drug combinations, we built a computational platform for integrating and interrogating radiogenomics data sets.

Methods: RadioGx integrates in vitro cancer cell line survival data with multimodal molecular profiles from the NCI-60 and Cancer Cell Line Encyclopedia (CCLE) cell line panels. We fit published radiation response data from both clonogenic and high-throughput viability assays to established radiobiologic models of clonogenic survival. We assessed the concordance of radiation response profiles across different survival endpoints (i.e., surviving fraction at 2Gy [SF2] and Area Under the Curve of the radiobiologic model [AUC]). By comparing radiation response with transcriptomic data, we examined indicators of radiosensitivity at the pathway level. We integrated drug response data from Cancer Therapeutics Response Portal (CTRP v2) using an interface between RadioGx and our previously published pharmacogenomics platform, PharmacoGx. Using the oxygen modification factor in established radiobiologic models, we identified pathways that are enriched under hypoxic conditions.

Results: RadioGx includes 600 radiation dose response data, 511 gene expression data sets, and 504 drug dose response data for chemotherapeutic compounds. Goodness-of-fit (given by R2 value) of the linear-quadratic radiobiologic model ranged from 0.927 to 0.99 (median=0.998, n=57) for the clonogenic assay and from 0.043 to 0.99 (median=0.952, n=535) for the viability assay. The concordance between SF2 and AUC using the clonogenic assay and the viability assay was 0.79 (n=12) and 0.82 (n=15), respectively. Among cell lines with survival data from both assays (n=28) across two different studies, the concordance of SF2 and AUC was 0.68 and 0.62, respectively. By interrogating the 504 cell lines that were profiled using the viability assay, we found drugs that behaved similar to RT were enriched in three pharmacologic classes, namely, drugs that impact mitosis, DNA replication, or cytoskeleton. Pathway analysis of radiation response under hypoxia revealed two key DNA repair pathways, namely, DNA double-strand break repair by NHEJ and DNA damage-induced 14-3-3, to be enriched compared to normoxic conditions.

Conclusions: Our work is a major step towards analyzing preclinical models of radiation response using in vitro survival and transcriptomic data. RadioGx coupled with PharmacoGx lays the foundation for the identification of synergistic drug-RT combinations, which can further push the boundaries of translational research towards precision radiation medicine.

Citation Format: Venkata S. Manem, Meghan Lambie, Petr Smirnov, Mark Freeman, Victor Kofia, Mohamed E. Abazeed, Scott V. Bratman, Benjamin Haibe-Kains. Therapeutic effects of radiotherapy on cancer cell lines using RadioGx computational platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3211.