Prognostic Nomogram to Predict the Overall Survival of Patients with “driver-gene-negative” Lung Adenocarcinoma (LUAD) and Its’ Biological Basis Deciphering

Objectives: Assessing the prognosis of patients with “driver-gene-negative” lung adenocarcinoma (LUAD patients negative for EGFR, KRAS, BRAF, HER2, MET, ALK, RET and ROS1 were identified as “driver-gene-negative”) is of significant clinical importance. We aimed to devise a prognostic nomogram for this LUAD subgroup and to define its biological basis.Materials and methods: Prognostic nomogram were established based on a retrospective study of 294 patients with surgical resected “driver-gene-negative” LUAD at The First Affiliated Hospital of Sun Yat-sen University between September 2003 and June 2015. The concordance index (C-index) and calibration curve were used to determine its predictive accuracy and discriminatory capacity. Patients were classified into low- and high-risk subgroups according to nomogram scores. To define the biological basis, we carried out gene set enrichment analysis in an independent dataset of 49 “driver-gene-negative” LUAD patients.Results: The nomogram built on the independent factors including CTC, age and stage achieved C-index of 0.785 [95% confidence interval (CI) 0.753-0.817] for predicting OS of “driver-gene-negative” LUAD. The calibration curves for OS probabilities showed a good agreement between the nomogram prediction and actual observation. High-risk patients had shorter OS [hazard ratio (HR) = 7.43, 95% CI 5.20-10.42, p<0.0001]. The genetic analysis suggested the biological basis for the role of the predictive model may be due to changes in cell proliferation, metabolism and neurological disease, indicating a relationship between increased proliferative potential and preferential poor prognosis.Conclusions: The prognostic nomogram showed promising prediction efficacy and is expected to predict the prognosis of “driver-gene-negative” LUAD. The easy-to-use nomogram and the enriched pathways can help clinical decision-making, guide follow-up planning, and develop new therapeutic targets.