1. Identifying Clear Cell Renal Cell Carcinoma Coexpression Networks Associated with Opioid Signaling and Survival.
- Author
-
Scarpa JR, DiNatale RG, Mano R, Silagy AW, Kuo F, Irie T, McCormick PJ, Fischer GW, Hakimi AA, and Mincer JS
- Subjects
- Adult, Aged, Aged, 80 and over, Carcinoma, Renal Cell diagnosis, Carcinoma, Renal Cell pathology, Case-Control Studies, Cell Proliferation drug effects, Cell Proliferation genetics, Cohort Studies, Epistasis, Genetic drug effects, Epistasis, Genetic physiology, Female, Gene Expression Profiling, Gene Expression Regulation, Neoplastic drug effects, Humans, Kidney Neoplasms diagnosis, Kidney Neoplasms pathology, Male, Middle Aged, Mortality, Prognosis, Signal Transduction drug effects, Signal Transduction genetics, Survival Analysis, Analgesics, Opioid pharmacology, Carcinoma, Renal Cell genetics, Carcinoma, Renal Cell mortality, Gene Regulatory Networks drug effects, Kidney Neoplasms genetics, Kidney Neoplasms mortality
- Abstract
While opioids constitute the major component of perioperative analgesic regimens for surgery in general, a variety of evidence points to an association between perioperative opioid exposure and longer term oncologic outcomes. The mechanistic details underlying these effects are not well understood. In this study, we focused on clear cell renal cell carcinoma (ccRCC) and utilized RNA sequencing and outcome data from both The Cancer Genome Atlas, as well as a local patient cohort to identify survival-associated gene coexpression networks. We then projected drug-induced transcriptional profiles from in vitro cancer cells to predict drug effects on these networks and recurrence-free, cancer-specific, and overall survival. The opioid receptor agonist, leu-enkephalin, was predicted to have antisurvival effects in ccRCC, primarily through Th2 immune- and NRF2 -dependent macrophage networks. Conversely, the antagonist, naloxone, was predicted to have prosurvival effects, primarily through angiogenesis, fatty acid metabolism, and hemopoesis pathways. Eight coexpression networks associated with survival endpoints in ccRCC were identified, and master regulators of the transition from the normal to disease state were inferred, a number of which are linked to opioid pathways. These results are the first to suggest a mechanism for opioid effects on cancer outcomes through modulation of survival-associated coexpression networks. While we focus on ccRCC, this methodology may be employed to predict opioid effects on other cancer types and to personalize analgesic regimens in patients with cancer for optimal outcomes. SIGNIFICANCE: This study suggests a possible molecular mechanism for opioid effects on cancer outcomes generally, with implications for personalization of analgesic regimens., (©2020 American Association for Cancer Research.)
- Published
- 2021
- Full Text
- View/download PDF