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Comprehensive Molecular Analyses of a Macrophages-Related Gene Signature With Regard to Prognosis, Immune Features, and Biomarkers for Immunotherapy in Hepatocellular Carcinoma Based on WGCNA and LASSO Algorithm

61 Pages Posted: 8 Dec 2021

See all articles by Tao Wang

Tao Wang

Sichuan University - Department of Liver Surgery & Liver Transplantation Center

Shu Shen

Sichuan University - Department of Liver Surgery & Liver Transplantation Center

Yi Yang

Sichuan University - Department of Liver Surgery & Liver Transplantation Center

Ming Yang

Sichuan University - Department of Liver Surgery & Liver Transplantation Center

Xianwei Yang

University of Electronic Science and Technology of China (UESTC) - Department of Thyroid Surgery

Yiwen Qiu

Sichuan University - Department of Liver Surgery & Liver Transplantation Center

Wentao Wang

Sichuan University - Department of Liver Surgery & Liver Transplantation Center

More...

Abstract

Macrophages has been reported to exert a crucial role in hepatocellular carcinoma (HCC). Herein, our study was aimed to explore the macrophage-related genes and established macrophage-related signature (MRS) model to predict the overall survival (OS) of patients with HCC based on these genes. We screened the macrophage-related gene module by weighted gene co-expression network analysis (WGCNA), the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis was utilized for further selection, and the selected genes were entered into stepwise regression to develop the MRS model, which was further validated in Gene Expression Omnibus (GEO) and the International Cancer Genome Consortium (ICGC) datasets. We analyzed the biological phenotypes associated with macrophages in terms of functional enrichment, tumor immune signature and tumor mutational signature. The patient’s response to immunotherapy is inferred by the tumor immune dysfunction and exclusion (TIDE) score, the immunophenotype score (IPS) and the IMvigor210 dataset. A novel MRS model was established based on the LASSO regression coefficients of PON1, IL15RA, NEIL3, HILPDA, PFN2, HAVCR1, ANXA10, CDCA8, EPO, S100A9, TTK, KLRB1, SPP1, STC2, CYP26B1, GPC1, G6PD and CBX2. No matter in which dataset, MRS has been identified as an independent risk factor affecting poor OS in HCC patients. Additionally, our research indicated that high risk score of MRS model was significantly related to tumor staging, pathological grade, the tumor-node-metastasis (TNM) stage and survival. Several genes of the human leukocyte antigen (HLA) family and immune checkpoints were highly expressed in the high-risk group. In addition, the frequency of tumor mutations is also higher in the high-risk group. According to our analyses, the higher risk score of the MRS model may respond better to immunotherapy.

Funding Information: This research was supported by the Science and Technology Program of Sichuan Science and Technology Department (No. 2019YFS0029, 2019YFS0529), the National Natural Science Foundation of China (No. 81770566, 82170543,82000599) and the New Medical Technology Foundation of West China Hospital of Sichuan University (No. XJS2016004).

Declaration of Interests: All the authors disclose no conflicts.

Ethics Approval Statement: Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

Keywords: Macrophages-related genes, hepatocellular carcinoma, immunity, prognosis;immune drug response;

Suggested Citation

Wang, Tao and Shen, Shu and Yang, Yi and Yang, Ming and Yang, Xianwei and Qiu, Yiwen and Wang, Wentao, Comprehensive Molecular Analyses of a Macrophages-Related Gene Signature With Regard to Prognosis, Immune Features, and Biomarkers for Immunotherapy in Hepatocellular Carcinoma Based on WGCNA and LASSO Algorithm. Available at SSRN: https://ssrn.com/abstract=3980540 or http://dx.doi.org/10.2139/ssrn.3980540

Tao Wang

Sichuan University - Department of Liver Surgery & Liver Transplantation Center ( email )

Chengdu
China

Shu Shen

Sichuan University - Department of Liver Surgery & Liver Transplantation Center ( email )

Chengdu
China

Yi Yang

Sichuan University - Department of Liver Surgery & Liver Transplantation Center ( email )

Chengdu
China

Ming Yang

Sichuan University - Department of Liver Surgery & Liver Transplantation Center ( email )

Chengdu
China

Xianwei Yang

University of Electronic Science and Technology of China (UESTC) - Department of Thyroid Surgery ( email )

Chengdu
China

Yiwen Qiu

Sichuan University - Department of Liver Surgery & Liver Transplantation Center ( email )

Chengdu
China

Wentao Wang (Contact Author)

Sichuan University - Department of Liver Surgery & Liver Transplantation Center ( email )

Chengdu
China

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