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Updated: Jun 2, 2026
Monitoring PD-1-Blocking Antibodies Bound to T Cells Derived from a Drop of Peripheral Blood
Published on: February 5, 2020
Transcriptomic Determinants of Circulating Immunity Predict Immune-Related Adverse Events (irAEs) in Cancer Patients
Liting You1,2,3,4, Jianzhao Zhai1,2,3, Zhaodan Xin1,2,3
1Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China.
Background:
Despite the remarkable success of immune checkpoint inhibitor (ICI) therapy in solid tumors, immune-related adverse events (irAEs) have posed great challenges in the whole-course management of ICI immunotherapy. Reliable biomarkers helping to predict irAEs are still limited and lacking.
Methods:
Cancer patients receiving PD-1/PD-L1 blockade were enrolled without limiting tumor type, immunotherapy drugs, or affected organs. Blood samples were collected for PBMC isolation. Whole transcriptomic RNA sequencing was used to discover biomarkers in PBMCs of irAEs patients, validated by RT-PCR in the test set. IrAEs-free survival analysis and subgroup analysis were performed. LASSO regression prediction classifiers were conducted.
Results:
One hundred and two patients were enrolled, with 42 in the training set and 60 in the testing set. The transcriptomic profile of PBMCs distinguished irAEs patients of different grades from non-irAEs patients. Five candidate biomarkers were identified: FXYD7, SPSB2, SLC35E2A, C2, and SERPING1. Lower expression of FXYD7, SPSB2, and SLC35E2A was associated with shorter irAEs-free survival [FXYD7, HR = 3.67, p = 0.0004; SLC35E2A, HR = 3.12, p = 0.0001; SPSB2, HR = 3.41, p = 0.0110]. Higher expression of C2 and SERPING1 was associated with shorter irAEs-free survival in severe cases [C2, HR = 0.30, p = 0.0011; SERPING1, HR = 0.39, p = 0.0082]. Classifiers based on these biomarkers predicted irAEs of all grades (AUC = 0.91) and severe irAEs (AUC = 0.94), with FXYD7, C2, and SERPING1 as key variables.
Conclusions:
Together, we revealed crucial circulating immunological determinants in irAEs and provided promising biomarkers to help predict irAEs, which will enlighten future precise management and targeted treatment strategies for irAEs.
