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Histopathologic pattern and molecular risk stratification are associated with prognosis in patients with stage IB
Weiran Liu1, Chen Chen2, Qiang Zhang2
1Department of Anesthesiology, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Background:
The benefit of adjuvant therapy remains controversial in completely resected (R0) stage IB non-small cell lung cancer (NCLSC) patients. In this study, we aimed to explore potential prognostic factors in stage IB NSCLC patients.
Methods:
This study included 215 patients with R0 stage IB lung adenocarcinoma (LUAD) (tumor size: 3-4 cm). DNA sequencing was performed with surgical samples of 126 patients using a panel of 9 driver genes. The molecular risk stratification was assessed by a 14-gene quantitative polymerase chain reaction assay.
Results:
Among the 215 patients, 67.9% had micropapillary/solid (MIP/SOL)-predominant tumors. Epidermal growth factor receptor (EGFR) mutations were detected in 75 of 126 patients (59.5%). MIP/SOL tumors harbored less common EGFR mutations than the other histologic patterns (50.6% vs. 79.5%, P=0.003). Molecular risk stratification was successfully assessed in 99 patients, of whom 37.4%, 26.3%, and 36.4% were high, intermediate, and low risk, respectively. The MIP/SOL pattern was associated with shorter disease-free survival (DFS) [hazard ratio (HR) =2.16, 95% confidence interval: 1.28-3.67; P=0.01]. The molecular high-risk patients had shorter DFS than the low- (HR =2.93, P=0.01) and intermediate-risk patients (HR =2.35, P=0.06). The prognostic value of molecular risk stratification was also significant in the MIP/SOL subset (median DFS high-risk: 45 months, low and intermediate risk: not reached; P=0.03).
Conclusions:
Our study showed that both the MIP/SOL pattern and molecular high-risk category were adverse prognostic factors in stage IB NSCLC patients. Our results suggest that combining histologic classification and molecular risk stratification may help to identify the subset of patients with poor prognosis.
