Synergistic role of activated CD4+ memory T cells and CXCL13 in augmenting cancer immunotherapy efficacy
Wenhao Ouyang,
Qing Peng,
Zijia Lai,
Hong Huang,
Zhenjun Huang,
Xinxin Xie,
Ruichong Lin,
Zehua Wang,
Herui Yao,
Yunfang Yu
Affiliations
Wenhao Ouyang
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Department of Medicine Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
Qing Peng
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Department of Medicine Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
Zijia Lai
Clinical Medicine College, Guangdong Medical University, Zhanjiang, China
Hong Huang
Clinical Medicine College, Guilin Medical University, Guilin, China
Zhenjun Huang
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Department of Medicine Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
Xinxin Xie
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Department of Medicine Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
Ruichong Lin
Faculty of Medicine, Macau University of Science and Technology, Taipa, Macao, China
Zehua Wang
Faculty of Medicine, Macau University of Science and Technology, Taipa, Macao, China
Herui Yao
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Department of Medicine Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China; Corresponding author. Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Phase I Clinical Trial Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, Guangzhou 510120, China.
Yunfang Yu
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Department of Medicine Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China; Faculty of Medicine, Macau University of Science and Technology, Taipa, Macao, China; Corresponding author. Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Department of Medical Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, Guangzhou 510120, China.
The development of immune checkpoint inhibitors (ICIs) has significantly advanced cancer treatment. However, their efficacy is not consistent across all patients, underscoring the need for personalized approaches. In this study, we examined the relationship between activated CD4+ memory T cell expression and ICI responsiveness. A notable correlation was observed between increased activated CD4+ memory T cell expression and better patient survival in various cohorts. Additionally, the chemokine CXCL13 was identified as a potential prognostic biomarker, with higher expression levels associated with improved outcomes. Further analysis highlighted CXCL13's role in influencing the Tumor Microenvironment, emphasizing its relevance in tumor immunity. Using these findings, we developed a deep learning model by the Multi-Layer Aggregation Graph Neural Network method. This model exhibited promise in predicting ICI treatment efficacy, suggesting its potential application in clinical practice.
