Molecular prognostic factors for individualized treatment of squamous cell carcinoma (SCC) are poorly defined. Our study developed and validated a novel molecular tools aid in preinguinal and postinguinal lymphadenectomy risk stratification in node-positive penile SCC. Patients with node-positive penile SCC who underwent inguinal or ilioinguinal lymphadenectomy were divided into three cohorts: a discovery set, a development set and a validation set. The local ethics committee approved the study. The primary endpoint was cancer-specific survival (CSS). At the discovery stage, 17 CpG sites were significantly associated with CSS. In the development set, we constructed a 3-CpG-based prognostic score for survival prediction. The hazard ratio (HR) of the panel (dichotomized using the optimal cutoff) was 5.8 in the multivariate analyses (P < .001). The addition of the methylation score significantly improved the pN-stage C-index from 0.70 to 0.79 (incremental C = 0.09, P < .001). In the validation set, the methylation panel showed a HR of 9.9 in the multivariate analyses. The addition of the molecular marker improved the pN-stage C-index from 0.69 to 0.78 (incremental C = 0.09, P < .001). The methylation score remarkably separated survival curves in different pN stages, which indicate that the tool can be applied to tailor the treatment in both preinguinal and postinguinal lymphadenectomy settings. We developed and validated a prognostic methylation panel for node-positive penile SCC. The tool may aid in the risk stratification of the population with heterogeneous outcomes and needs prospective validation. Patients in high-risk group may benefit from more aggressive therapy or clinical trials.
International journal of cancer. 2020 Oct 22 [Epub ahead of print]
Weijie Gu, Fangning Wan, Jun Chen, Hualei Gan, Beihe Wang, Yu Wei, Guiming Zhang, Jiaquan Zhou, Xuefei Ding, Peipei Zhang, Shengming Jin, Qinghua Xu, Dingwei Ye, Yao Zhu
Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China., Division of Biomedical Statistics and Informatics and Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota, USA., Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China., Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China., Department of Urology, Hainan General Hospital, Haikou, China., Department of Urology, Northern Jiangsu People's Hospital, Yangzhou, China., Department of Pathology, Ruijin Hospital, Jiao Tong University, Shanghai, China., Institute of Machine Learning and Systems Biology, College of Electronics and Information Engineering, Tongji University, Shanghai, China.