TM-Score predicts immunotherapy efficacy and improves the performance of the machine learning prognostic model in gastric cancer.

Journal: International immunopharmacology
Published Date: May 8, 2024

Abstract

Immunotherapy is becoming increasingly important, but the overall response rate is relatively low in the treatment of gastric cancer (GC). The application of tumor mutational burden (TMB) in predicting immunotherapy efficacy in GC patients is limited and controversial, emphasizing the importance of optimizing TMB-based patient selection. By combining TMB and major histocompatibility complex (MHC) related hub genes, we established a novel TM-Score. This score showed superior performance for immunotherapeutic selection (AUC = 0.808) compared to TMB, MSI status, and EBV status. Additionally, it predicted the prognosis of GC patients. Subsequently, a machine learning model adjusted by the TM-Score further improved the accuracy of survival prediction (AUC > 0.8). Meanwhile, we found that GC patients with low TM-Score had a higher mutation frequency, higher expression of HLA genes and immune checkpoint genes, and higher infiltration of CD8 T cells, CD4 helper T cells, and M1 macrophages. This suggests that TM-Score is significantly associated with tumor immunogenicity and tumor immune environment. Notably, based on the RNA-seq and scRNA-seq, it was found that AKAP5, a key component gene of TM-Score, is involved in anti-tumor immunity by promoting the infiltration of CD4 T cells, NK cells, and myeloid cells. Additionally, siAKAP5 significantly reduced MHC-II mRNA expression in the GC cell line. In addition, our immunohistochemistry assays confirmed a positive correlation between AKAP5 and human leukocyte antigen (HLA) expression. Furthermore, AKAP5 levels were higher in patients with longer survival and those who responded to immunotherapy in GC, indicating its potential value in predicting prognosis and immunotherapy outcomes. In conclusion, TM-Score, as an optimization of TMB, is a more precise biomarker for predicting the immunotherapy efficacy of the GC population. Additionally, AKAP5 shows promise as a therapeutic target for GC.

Authors

  • Kanghui Xiang
    Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, Liaoning, China; Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, Liaoning, China; Liaoning Province Clinical Research Center for Cancer, The First Hospital of China Medical University, Shenyang, Liaoning, China; Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, The First Hospital of China Medical University, Shenyang, Liaoning, China.
  • Minghui Zhang
    Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China.
  • Bowen Yang
    Song are with Center for Cyber-Physical Systems, University of Georgia, Athens, GA 30602, USA.
  • Xu Liu
    School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore. liuxu16@bjut.edu.cn.
  • Yusi Wang
    Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, Liaoning, China; Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, Liaoning, China; Liaoning Province Clinical Research Center for Cancer, The First Hospital of China Medical University, Shenyang, Liaoning, China; Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, The First Hospital of China Medical University, Shenyang, Liaoning, China.
  • Hengxin Liu
    School of Microelectronics, Tianjin University, Tianjin, China.
  • Yujia Song
    Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, Liaoning, China; Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, Liaoning, China; Liaoning Province Clinical Research Center for Cancer, The First Hospital of China Medical University, Shenyang, Liaoning, China; Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, The First Hospital of China Medical University, Shenyang, Liaoning, China.
  • Yonghui Yuan
    Liaoning Cancer Hospital & Institute, Clinical Research Center for Malignant Tumor of Liaoning Province, Cancer Hospital of China Medical University, Shenyang, China.
  • Lingyun Zhang
    Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, Liaoning, China; Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, Liaoning, China; Liaoning Province Clinical Research Center for Cancer, The First Hospital of China Medical University, Shenyang, Liaoning, China; Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, The First Hospital of China Medical University, Shenyang, Liaoning, China. Electronic address: lyzhang@cmu.edu.cn.
  • Ti Wen
    Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, Liaoning, China; Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, Liaoning, China; Liaoning Province Clinical Research Center for Cancer, The First Hospital of China Medical University, Shenyang, Liaoning, China; Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, The First Hospital of China Medical University, Shenyang, Liaoning, China. Electronic address: wenti@cmu.edu.cn.
  • Guang-Wei Zhang
    Smart Hospital Management Department, the First Hospital of China Medical University, Shenyang, 110001, China. gwzhang@cmu.edu.cn.

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