Prognostic Nomogram Based on Histological Characteristics of Fibrotic Tumor Stroma in Patients Who Underwent Curative Resection for Intrahepatic Cholangiocarcinoma

Abstract

Background Fibrotic tumor stroma (FTS) has been implicated in cancer promotion in several neoplasms. The histological features of FTS are convenient and easily accessible in clinical routine in intrahepatic cholangiocarcinoma (ICC) specimens. The goal of this study was to explore prognostic impacts of the quantity and maturity of FTS on surgical ICC patients. Moreover, we aimed to propose an efficient prognostic nomogram for postoperative ICC patients. Materials and Methods The clinical profiles of 154 consecutive postoperative ICC patients were retrospectively analyzed. Tumor‐stroma ratio and morphological maturity of FTS were evaluated on hematoxylin and eosin‐stained tumor sections. CD3, CD8, and α‐smooth muscle actin (α‐SMA) staining were performed on corresponding tissue microarrays. The nomogram was established on variables selected by multivariate analyses and was validated in 10‐fold cross‐validation. Results Rich tumor stroma and strong α‐SMA expression were associated with poor overall survival (OS). However, in multivariate analyses, these two biomarkers failed to stratify both OS and recurrence‐free survival (RFS). Immature FTS was correlated with tumor multiplicity, advanced clinical stage, and sparser CD3 and CD8 positive tumor‐infiltrating lymphocytes (TILs) and was identified as an independent prognostic indicator for both OS and RFS. The nomogram comprising FTS maturity, tumor number, microvascular invasion, and lymph node metastasis possessed higher predictive power relative to conventional staging systems. Conclusion Immature FTS was an independent risk factor for survival and was associated with sparser CD3 and CD8 positive TILs in ICC. The prognostic nomogram integrating the maturity of FTS offers a more accurate risk stratification for postoperative ICC patients. Implications for Practice Accumulating evidence has suggested that fibrotic components in tumor microenvironment (TME) play a complicated and vital role in TME reprogramming and cancer progression. However, in clinical practice, the evaluation of fibrotic tumor stroma (FTS) is still neglected to some extent. This study's findings indicated that, in intrahepatic cholangiocarcinoma (ICC), the histological maturity of FTS is a robust prognostic indicator for patients who underwent curative resection. Moreover, prognostic nomogram constructed on the maturity of FTS possessed higher predictive power relative to the conventional tumor‐node‐metastasis staging systems. Taken together, the evaluation of FTS should be emphasized in clinical routine for more accurate prognostic prediction in postoperative ICC patients.

A novel online prognostic tool to predict long‐term survival after liver resection for intrahepatic cholangiocarcinoma: The “metro‐ticket” paradigm

“…To date, several prognostic models and nomograms have been developed to determine the prognosis of patients undergoing surgery for hepato‐pancreato‐biliary malignancies . In comparison with the traditional AJCC staging system, these nomograms are thought to tailor prognostication based on the individual patient characteristics and clinicopathological factors, and, thus, have been proposed for a number of cancers . Nevertheless, the clinical applicability of nomograms is limited due to the lack of a simple calculator available for use among clinicians.…”

Precancerous niche (PCN), a product of fibrosis with remodeling by incessant chronic inflammation

“…Creating a prognostic normogram of inflammatory fibrotic stroma was demonstrated in CCC by combining histopathological charcteristics together with CD3, CD4 and a-smooth muscle actin (a-SMA) staining of tissue microarrays [268]. Tumor cells aggregate to fibroblasts which further drive the cascade of chronic inflammation, fibrosis, and remodeling [269].…”

Distant metastasis prediction via a multi-feature fusion model in breast cancer

“…The most common metastatic sites are the bone, brain, liver, and lung [ 8 ]. Although several predictive models for DM in BC have been recently reported, a multi-feature fusion model can have better predictive ability [ 9 , 13 , 14 ].…”