Identification of CNGB1 as a Predictor of Response to Neoadjuvant Chemotherapy in Muscle-Invasive Bladder Cancer

SIMPLE SUMMARY: Chemotherapy is recommended prior to surgical removal of the bladder for muscle-invasive bladder cancer patients. Despite a survival benefit, some patients do not respond and experience substantial toxicity and delay in surgery. Therefore, the identification of chemotherapy responders before initiating therapy would be a helpful clinical asset. To date, there are no reliable biomarkers routinely used in clinical practice that identify patients most likely to benefit from chemotherapy and their identification is urgently required for more precise delivery of care. To address this issue, we compared gene expression profiles of biopsy materials from 30 chemotherapy-responder and -non-responder patients. This analysis revealed a novel signature gene set and CNGB1 as a simpler proxy as a promising biomarker to predict chemoresponsiveness of muscle-invasive bladder cancer patients. Our findings require further validation in larger patient cohorts and in a clinical trial setting. ABSTRACT: Cisplatin-based neoadjuvant chemotherapy (NAC) is recommended prior to radical cystectomy for muscle-invasive bladder cancer (MIBC) patients. Despite a 5–10% survival benefit, some patients do not respond and experience substantial toxicity and delay in surgery. To date, there are no clinically approved biomarkers predictive of response to NAC and their identification is urgently required for more precise delivery of care. To address this issue, a multi-methods analysis approach of machine learning and differential gene expression analysis was undertaken on a cohort of 30 MIBC cases highly selected for an exquisitely strong response to NAC or marked resistance and/or progression (discovery cohort). RGIFE (ranked guided iterative feature elimination) machine learning algorithm, previously demonstrated to have the ability to select biomarkers with high predictive power, identified a 9-gene signature (CNGB1, GGH, HIST1H4F, IDO1, KIF5A, MRPL4, NCDN, PRRT3, SLC35B3) able to select responders from non-responders with 100% predictive accuracy. This novel signature correlated with overall survival in meta-analysis performed using published NAC treated-MIBC microarray data (validation cohort 1, n = 26, Log rank test, p = 0.02). Corroboration with differential gene expression analysis revealed cyclic nucleotide-gated channel, CNGB1, as the top ranked upregulated gene in non-responders to NAC. A higher CNGB1 immunostaining score was seen in non-responders in tissue microarray analysis of the discovery cohort (n = 30, p = 0.02). Kaplan-Meier analysis of a further cohort of MIBC patients (validation cohort 2, n = 99) demonstrated that a high level of CNGB1 expression associated with shorter cancer specific survival (p < 0.001). Finally, in vitro studies showed siRNA-mediated CNGB1 knockdown enhanced cisplatin sensitivity of MIBC cell lines, J82 and 253JB-V. Overall, these data reveal a novel signature gene set and CNGB1 as a simpler proxy as a promising biomarker to predict chemoresponsiveness of MIBC patients.