Related Experiment Video
Updated: Aug 23, 2025
Author Spotlight: Investigating Immune Cell Dynamics in the Tumor Microenvironment — Challenges and Innovations in Cancer Prognosis
Published on: April 12, 2024
A Prognostic Nomogram for Hepatocellular Carcinoma Based on Wound Healing and Immune Checkpoint Genes
Beiyuan Hu1, Xiaotian Shen1, Wei Qin1
1Department of General Surgery, Huashan Hospital & Cancer Metastasis Institute, Institutes of Biomedical Sciences, Fudan University, Shanghai, China.
Background And Aims:
Wound healing and tumor progression share some common biological features; however, how variations in wound healing patterns affect hepatocellular carcinoma (HCC) prognosis remains unclear.
Methods:
We analyzed the wound healing patterns of 594 HCC samples from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) and correlated them with immune infiltration and the expression levels of immune checkpoint genes. A risk score, which we named the "heal.immune" score, was established via stepwise Cox estimation. We constructed a nomogram based on age, sex, TNM stage, and heal.immune score and explored its predictive value for HCC prognosis. Seventy-four clinical patients were enrolled in this study, and all were from Huashan Hospital of Fudan University between 2015 and 2017 to serve as an independent validation group.
Results:
We identified two distinct wound healing patterns in HCC. The biological processes of healing cluster 1 (C1) are related to metabolism, while those of healing cluster 2 (C2) are related to the inflammatory response and immune cell accumulation. A total of 565 wound healing-related genes (based on Gene Ontology) and 25 immune checkpoint genes were considered. By analyzing differentially expressed genes and implementing a stepwise Cox estimation analysis, six genes with p values less than 0.02 in a multivariate Cox estimation were chosen as the "heal.immune" gene set (FCER1G, PLAT, ITGA5, CCNB1, CD86 and CD40). The "heal.immune" gene set, as an OS risk factor, was further validated in Fudan cohort. We constructed a nomogram to predict the 1-, 3- and 5-year overall survival (OS) in the TCGA cohort. The area under curve vales of the receiver characteristic operator curves were 0.82, 0.76 and 0.73 in the training group and 0.84, 0.76 and 0.72 in the test group.
Conclusions:
We established a prognostic nomogram based on the heal.immune gene signature, which includes six wound healing- and immunity-related genes. This nomogram accurately predicts the OS of HCC patients.
