Nine-factor-based immunohistochemistry classifier predicts recurrence for early-stage hepatocellular carcinoma after curative resection

Abstract

Abstract Background Immunoscore have shown a promising prognostic value in many cancers. We aimed to establish and validate an immune classifier to predict survival after curative resection of hepatocellular carcinoma (HCC) patients who have undergone curative resection. Methods The immunohistochemistry (IHC) classifier assay was performed on 664 patients with Barcelona Clinic Liver Cancer (BCLC) stage 0 or A HCC. A nine-feature-based HCC-IHC classifier was then constructed by the least absolute shrinkage and selection operator method. The associations between the HCC-IHC classifier and patient outcomes were assessed. Herein, a nomogram was generated from the Cox regression coefficients and evaluated by decision curve analysis. Results We constructed an HCC-IHC classifier based on nine features; significant differences were found between the low-HCC-IHC classifier patients and high-HCC-IHC classifier patients in the training cohort in the 5-year relapse-free survival rates (46.7% vs. 26.7%, respectively; P < 0.001). The HCC-IHC classifier-based nomogram presented better accuracy than traditional staging systems. Conclusions In conclusion, the HCC-IHC classifier could effectively predict recurrence in early-stage HCC patients and supplemented the prognostic value of the BCLC staging system. The HCC-IHC classifier may facilitate patient decision-making and individualise the management of postoperative patients with early-stage HCC.