In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 77, No. 13_Supplement ( 2017-07-01), p. 1560-1560
Abstract:
Resistance to therapy, including conventional chemotherapy, targeted therapy and immunotherapy, continues to plague cancer treatment. Moreover, mechanisms governing resistance are poorly characterized leading to a dearth of rational combinatorial and sequential treatment strategies. While drug response data is abundant across myriad tumor types and drug classes, there exists no high-throughput method to probe such data with a query as simple as “If tumors are resistant to drug X, to what drug(s) are they sensitive?”- a seemingly trivial problem beset by immense data sets and imprecise definitions of sensitivity and resistance. Here, we present DISARM, a novel approach designed specifically to screen for drugs that are active in spite of resistance to a reference drug. DISARM selects candidates based on the proportion of samples that are resistant to a reference drug but sensitive to a candidate drug with simultaneous consideration to relatively lower IC50 values for candidate drugs and higher IC50 values for reference drugs. As candidates may work in only a subset of resistant models and precise delineation between sensitivity and resistance may vary between experimental settings, DISARM permits flexibility in dichotomizing drug data and uses grid search to optimize specifications. To illustrate, we analyzed publically available cell line data (IC50 data) from several cancer types for which platinum-based therapy is a standard of care, identifying multiple drugs that demonstrate activity in cisplatin-resistant models across tumor types such as the BCL-2 inhibitor obatoclax in small cell lung cancer, lung adenocarcinoma, gastric adenocarcinoma and bladder cancer, and the farnesyltransferase inhibitor tipifarnib in small cell lung cancer, bladder cancer, esophageal cancer, colon adenocarcinoma and head and neck squamous cell carcinoma. Frequently, multiple drugs from the same class were selected by DISARM for a single tumor type and, in these cases, we found statistically significant similarity between sensitive cell lines suggesting a subset of cisplatin-resistant cell lines that are repeatedly sensitive to a drug class. While translating preclinical observations into approved clinical use is often thwarted by an inability to identify predictive biomarkers, DISARM also allows us to select cell lines that are especially sensitive to candidate drugs or drug classes on which to perform biomarker analysis. To demonstrate this approach, we chose drugs with activity in multiple cancer types and compared mRNA and protein expression data to highlight potentially novel common and tumor-specific biomarkers for concomitant candidate drug sensitivity and cisplatin resistance. Thus, DISARM offers a simple yet effective approach for both drug and biomarker discovery within a specified clinical niche. Citation Format: Carl M. Gay, Pan Tong, Robert J. Cardnell, Xiao Su, Nene N. Kalu, Upasana Banerjee, Rasha O. Bara, Faye M. Johnson, John V. Heymach, Jing Wang, Lauren A. Byers. Differential sensitivity analysis for resistant malignancies (DISARM), a novel approach for drug screen analysis, identifies common candidate drugs across platinum-resistant cancer types [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1560. doi:10.1158/1538-7445.AM2017-1560
Type of Medium:
Online Resource
ISSN:
0008-5472
,
1538-7445
DOI:
10.1158/1538-7445.AM2017-1560
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2017
detail.hit.zdb_id:
2036785-5
detail.hit.zdb_id:
1432-1
detail.hit.zdb_id:
410466-3
Permalink
