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Mingyi Ju,1,2,* Longyang Jiang,1,2,* Qian Wei,1,2 Lifeng Yu,1,2 Lianze Chen,1,2 Yan Wang,1,2 Baohui Hu,1,2 Ping Qian,1,2 Ming Zhang,1,2 Chenyi Zhou,1,2 Zinan Li,1,2 Minjie Wei,1â 3 Lin Zhao,1,2 Jiali Han4 1Department of Pharmacology, School of Pharmacy; China Medical University, Shenyang, Liaoning Province, 110122, Peopleâs Republic of China; 2Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang, Liaoning Province, 110122, Peopleâs Republic of China; 3Liaoning Medical Diagnosis and Treatment Center, Shenyang, Liaoning Province, Peopleâs Republic of China; 4Department of Otolaryngology, The First Hospital of China Medical University, Shenyang, Liaoning, 110001, Peopleâs Republic of China*These authors contributed equally to this workCorrespondence: Jiali HanDepartment of Otolaryngology, The First Hospital of China Medical University, Shenyang, Liaoning, 110001, Peopleâs Republic of ChinaTel +86 18102489275Email jiali_han@163.comLin ZhaoDepartment of Pharmacology, School of Pharmacy, China Medical University, No. 77 Puhe Road, Shenyang North New Area, Shenyang, 110122, Liaoning, Peopleâs Republic of ChinaTel +86 18900911856Email zl_cmu@163.com; lzhao@cmu.edu.cnObjective: Although many curative treatments are being applied in the clinic, a significant number of patients with liver hepatocellular carcinoma (LIHC) suffer from drug resistance. The tumour microenvironment (TME) has been found to be closely associated with resistance, suggesting that identification of predictive biomarkers related to the TME for resistance in LIHC will be very rewarding. However, there has been no study dedicated to identifying a TME-related biomarker that has the potential to predict resistance in LIHC.Methods: An integrated analysis was conducted based on data of patients with LIHC suffering from drug resistance from the TCGA database and four GEO datasets. Subsequently, we also validated the expression levels of the identified genes in paraffin-embedded LIHC samples by immunohistochemistry.Results: In this study, we developed a robust and acute TME-related signature consisted of five immune-related genes (FABP6, CD4, PRF1, EREG and COLEC10) that could independently predict both the RFS and OS of LIHC patients. Moreover, the TME-related signature was significantly associated with the immune score, immune cytolytic activity (CYT), HLA, interferon (IFN) response and tumour-infiltrating lymphocytes (TILs), and it might influence tumour immunity mainly by affecting B cells, CD8+ T cells and dendritic cells. Furthermore, our analysis also indicated that the TME-related signature was correlated with the immunotherapy response and had an enormous potential to predict sorafenib resistance in LIHC.Conclusion: Our findings demonstrated a TME-related signature which can independently predict both the RFS and OS of LIHC patients, highlighting the predictive potential of the signature for immunotherapy response and sorafenib resistance, potentially enabling more precise and personalized sorafenib treatment in LIHC in the future.Keywords: liver cancer, tumour microenvironment, immunotherapy, sorafenib resistance, prognostic signature |
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