The Correlation Between CD8+ Tumor-Infiltrating Lymphocytes and the Efficacy of Neoadjuvant Therapy in Breast Cancer
Related Experiment Video
Updated: Mar 18, 2026
Author Spotlight: A Model to Study the Systemic and Local Dynamics of CD8+ T Cells During LN Metastasis
Published on: January 26, 2024
Guosheng Feng1, Mingqiang Zhong2, Danmin Xie1
1Department of Medical Oncology, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, People's Republic of China.
Objective:
This study aims to investigate the correlation between the CD8+ tumor-infiltrating lymphocytes (TILs) expression and the efficacy of neoadjuvant therapy (NAT) in breast cancer, while previous studies have reported inconsistent findings regarding the predictive value of CD8+ TILs.
Methods:
Data from 94 breast cancer patients who underwent NAT between January 2017 and June 2019 were retrospectively analyzed. Preoperative CD8+ TILs expression was evaluated through immunohistochemistry, and its association with clinical and pathological responses to NAT was assessed.
Results:
Univariate analysis indicated that tumor stage, axillary lymph node status, and intratumoral CD8+ TILs were correlated with clinical complete response (cCR). Multivariate analysis identified intratumoral CD8+ TILs as an independent predictor of cCR (OR 3.038; p=0.02). Patients achieving pathological complete response (pCR) exhibited significantly higher intratumoral CD8+ TILs expression compared to those without (p=0.04). Univariate analysis also linked estrogen receptor (ER), progesterone receptor (PR), HER2 status, and intratumoral CD8+ TILs to pCR, with multivariate analysis confirming intratumoral CD8+ TILs as an independent predictor (OR 4.036; p=0.02).
Conclusion:
Our findings suggest that intratumoral CD8+ TILs are an independent predictor of the efficacy of neoadjuvant therapy in breast cancer. In the future, incorporating intratumoral CD8+ TILs into existing clinicopathological predictive models and combining their assessment with other immune biomarkers may enable the development of more robust predictive tools, thereby providing a solid foundation for truly individualized and precision-based neoadjuvant treatment in breast cancer.
