|Title||Identifying Clear Cell Renal Cell Carcinoma Coexpression Networks Associated with Opioid Signaling and Survival.|
|Publication Type||Journal Article|
|Year of Publication||2020|
|Authors||Scarpa JR, DiNatale RG, Mano R, Silagy AW, Kuo F, Irie T, McCormick PJ, Fischer GW, A Hakimi A, Mincer JS|
|Date Published||2020 Dec 14|
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 oncological 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 RNAseq and outcomes data from both TCGA 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 anti-survival effects in ccRCC, primarily through Th2 immune and NRF2-dependent macrophage networks. Conversely, the antagonist naloxone was predicted to have pro-survival 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 cancer patients for optimal outcomes.
|Alternate Journal||Cancer Res|