Histopathology-based immunoscore predicts recurrence for intrahepatic cholangiocarcinoma after hepatectomy

Abstract

Intrahepatic cholangiocarcinoma (ICC) is a rare malignancy with poor prognosis. The evaluation of recurrence risk after liver resection is of great importance for ICCs. We aimed to assess the prognostic value of intra- and peritumoral immune infiltrations and to establish a novel histopathology-related immunoscore (HRI) associated with ICC recurrence. A total of 280 ICC patients who received curative resection between February 2005 and July 2011 were enrolled in our study. Patients were randomly assigned to the derivation cohort (n = 176) or the validation cohort (n = 104). Sixteen immune biomarkers in both intra- and peritumoral tissues were examined by immunohistochemistry. The least absolute shrinkage and selection operator (LASSO) Cox model was used to establish the HRI score. Cox regression analysis was used for multivariate analysis. Nine recurrence-related immune features were identified and integrated into the HRI score. The HRI score was used to categorize patients into low-risk and high-risk groups using the X-tile software. Kaplan-Meier analysis presented that the HRI score showed good stratification between low-risk and high-risk groups in both the derivation cohort (P < 0.001) and the validation cohort (P = 0.014), respectively. Multivariate analysis demonstrated that serum γ-glutamyl transpeptidase, carbohydrate antigen 19-9, lymphoid metastasis, tumor numbers, and the HRI score were independent risk factors associated with recurrence-free survival (RFS). The combination of Shen's model and HRI score provided better performance in recurrence prediction compared with traditional staging systems. The HRI score might serve as a promising RFS predictor for ICC with prognostic values.

Keywords: Immunoscore; Intrahepatic cholangiocarcinoma; Prognosis; Recurrence.

Fig. 1

Selection of immune features using the LASSO regression analysis in intrahepatic cholangiocarcinoma patients. a, b Nine immune features were selected by LASSO method. Left panel a: the two dotted vertical lines were drawn at the optimal values by minimum criteria and 1-s.e. criteria. Right panel b: LASSO coefficient profiles of the 32 immune features. c The expression pattern of selected immune features, including CD3_P, CD8_T, CD45RA_T, CD45RA_P, CD66b_T, CD68_T, FOXP3_T, PD1_T and PD-L1_T in three different patients. Bar, 20 μm. LASSO least absolute shrinkage and selection operator

Fig. 2

a ROC curves for the HRI score and nine selected immune features in the derivation cohort and the validation cohort. b Kaplan–Meier survival curves, the discrimination performance and the HRI distribution of the nine immune features in the derivation and the validation cohort, respectively. Upper panel: the Kaplan–Meier survival curves showing high-risk and low-risk groups in both cohorts. Middle panel: HRI distribution of the nine-immune-feature-based classifier and patient recurrence status. Lower panel: heat map presenting density of the nine immune features in ICC patients. ROC receiver operating characteristic, HRI histopathology-related immunoscore

Fig. 3

ROC curves for three staging systems, Shen’s model, and the combination of HRI and Shen’s model in the derivation cohort and the validation cohort (Liver Cancer Study Group of Japan [LCSGJ]; American Joint Committee on Cancer [AJCC] 7th edition; AJCC 8th edition). ROC receiver operating characteristic