Prognostic value of an immunohistochemical signature in patients with pulmonary squamous cell carcinoma undergoing complete surgical resection

BACKGROUND: The Tumor Node Metastasis (TNM) stage cannot accurately predict the prognosis of patients in pulmonary squamous cell carcinoma (SQCC). The aim of the present study was to evaluate the prognostic value of immunohistochemical (IHC)-based classifiers in patients with pulmonary SQCC who underwent complete surgery resection. METHODS: From January 2010 to December 2014, a total of 556 patients with SQCC who underwent complete radical resection were included. The patients were grouped into a discovery group (n=334) and a validation group (n=222). Using the least absolute shrinkage and selection operator (LASSO) regression model, we extracted IHCs that were associated with progression-free survival (PFS) and then built classifiers. Clinicopathological variables and the IHC-based classifiers were analyzed using univariable and multivariable logistic regression analyses. A nomogram to predict PFS was constructed and validated using bootstrap resampling. RESULTS: Following the LASSO regression model, 4 IHC markers associated with PFS were identified. We used the IHC-based classifiers to stratify patients in both groups into high- and low-risk groups. PFS was better in the low-risk group than in the high-risk group in both the discovery and validation groups. Multivariate analysis demonstrated that the IHC-based classifiers were independently prognostic in predicting the PFS of patients with SQCC. The performance of the nomogram was evaluated and proven to be clinically useful. CONCLUSIONS: By combining IHC-based classification and clinicopathology, we were able to have better insight into the prognostic assessment of patients with SQCC after surgery, which can inform postoperative patient management.