An extracellular matrix-based signature associated with immune microenvironment predicts the prognosis of patients with hepatocellular carcinoma

Xinyun Zhang; Mengmeng Jiang; Xihao Zhang; Jinliang Zhang; Hongxing Guo; Chenxuan Wu

doi:10.1016/j.clinre.2022.101877

An extracellular matrix-based signature associated with immune microenvironment predicts the prognosis of patients with hepatocellular carcinoma

Clin Res Hepatol Gastroenterol. 2022 Apr;46(4):101877. doi: 10.1016/j.clinre.2022.101877. Epub 2022 Mar 5.

Authors

Xinyun Zhang¹, Mengmeng Jiang¹, Xihao Zhang², Jinliang Zhang², Hongxing Guo³, Chenxuan Wu⁴

Affiliations

¹ Department of Medical Oncology, The Third Central Hospital of Tianjin, China; Artificial Cell Engineering Technology Research Center, Tianjin, China; Tianjin Institute of Hepatobiliary Disease, Tianjin, China; Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases.
² Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Department of Hepatobiliary Surgery, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer.
³ Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, The Third Central Hospital of Tianjin, China. Electronic address: kuohx@hotmail.com.
⁴ Department of Medical Oncology, The Third Central Hospital of Tianjin, China; Artificial Cell Engineering Technology Research Center, Tianjin, China; Tianjin Institute of Hepatobiliary Disease, Tianjin, China; Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases. Electronic address: chenxuanwu1@126.com.

PMID: 35257959
DOI: 10.1016/j.clinre.2022.101877

Abstract

Objective: Increased data showed that genes related to extracellular matrix (ECM) are important to hepatocellular carcinoma (HCC) development. In contrast, no research was carried out that proposed that ECM-related genes should be reliable prognostic signature.

Methods: This study used data from The Cancer Genome Atlas along with The International Cancer Genome Consortium to gather ECM-related gene expression as well as clinical information related to the extracellular matrix. The least absolute shrinkage, Cox analysis, along with selection operator Cox regression and random forest have been utilized for establishing an ECM-related prognostic models.

Results: A series of investigations led us to identify 13 ECMs which we utilized to construct a prognostic signature with a larger area under the curve of 0.808. HCC patients have been categorized into 2 main groups based on the risk score formula: low risk along with high risk. The findings of the Kaplan-Meier curve revealed that there had been a statistically significant difference between these two groups. Our ECM-related signature can be utilized as independent predictor of survival in HCC. Low-risk patients stratified by the final model presented higher sensitivity to 8 targeted drugs (especially sorafenib) and 2 common chemo-drugs. Our gene set enrichment analysis outcomes recommended that high-risk group have been enriched in ECM, tumorigenesis, as well as immune-related pathways. Immune cell analysis showed that high-risk group had lower cell fraction of CD8+ T cells, Macrophages M1, B naïve cells, memory resting CD4+ T cells, Monocytes, resting Dendritic cells and activated Mast cells, along with higher PD-1 and CTLA4 expression levels as compared to low-risk group.

Conclusion: Our identified ECM-related signature can also give new insight into underlying mechanisms along with therapeutic strategies in order to treat HCC.

Keywords: CIBERSORT; Extracellular matrix; Hepatocellular carcinoma; Prognosis; Tumor microenvironment.

MeSH terms

Biomarkers, Tumor / genetics
Carcinoma, Hepatocellular* / genetics
Extracellular Matrix / pathology
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Humans
Liver Neoplasms* / pathology
Prognosis
Tumor Microenvironment

Substances

Biomarkers, Tumor