Work

Predictive value of peripheral blood CD4+ T and NK cells on efficacy and long-term survival in advanced HCC patients receiving immunotherapy

Year: 2025

Type: article

Abstract: Background Early assessment of the efficacy of immune checkpoint inhibitor (ICI) therapy in advanced hepatocellular carcinoma (HCC) patients plays a crucial role. In this study, we systematically analyzed the predictive values of various lymphocyte subpopulations (CD4 + T, CD8 + T, and NK cells) at different time points of pretreatment (W0), 3 weeks (W3) and 6 weeks (W6) post-treatment and their relative changes compared to W0 for objective response (OR). Materials and methods We systematically reviewed the clinical data of these patients in our hospital. Logistic regression analyses were conducted to identify variables predicting OR. Cut-off values were determined by maximizing Youden index. Then, patients were stratified based on these cut-off values, and Kaplan-Meier analysis with log-rank test was used to compare progression-free survival (PFS) and overall survival (OS) between groups. Results A total of 41 patients were included. Multivariate logistic regression analysis revealed that W3 CD4 + T cells (%) and W3 NK cells(%) were independent predictors of treatment efficacy. The odds ratios (95% confidence interval) and p-values were 1.140 (1.020-1.274), 0.021 and 2.232 (1.025-4.860), 0.043, respectively. Combining these two indicators yielded even better performance: all patients in the “All High” group achieved OR, whereas none in the “All Low” group did. Furthermore, whether used individually or in combination, they all could stratify patients by PFS and OS. Conclusions W3 CD4 + T cells (%) and W3 NK cells (%) can predict the efficacy and long-term survival (PFS and OS) of these patients. Their combination offers improved predictive performance.

Source: Frontiers in Immunology

DOI: 10.3389/fimmu.2025.1683328

Authors: Zheng Pan, Shihang Song, Yuan An, Lianyue Guan, Hongyu Liu, Wei Li

Institutions: Jilin University, Ezhou Central Hospital

Language: English

Topic: Cancer Immunotherapy and Biomarkers

Subfield: Oncology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,801