Peripheral blood lymphocytes subtypes as new predictors for neoadjuvant therapy efficacy in breast cancer. (11th April 2022) - Feng, Jikun; Yi, Jiarong; Zouxu, Xiazi; Li, Jianxia; Xiong, Zhenchong; Huang, Xinjian; Zhong, Wenjing; Huang, Weiling; Ye, Feng; Wang, Xi
Abstract: Background: Host immunity plays an important role in tumor development and treatment. Tumor‐infiltrating lymphocytes (TILs) have been proven to predict the efficacy of neoadjuvant therapy (NAT) in breast cancer (BC) patients, but their application is limited due to various reasons. This study aims to explore the relationship between peripheral blood lymphocytes (PBLs) subsets distribution and the efficacy of NAT. Methods: Between December 2017 and March 2021, a total of 116 BC patients appropriate for NAT in Sun Yat‐Sen University cancer center were enrolled, pre‐NAC baseline blood samples were taken for further flow cytometry analysis to quantitatively evaluate the PBLs subsets distribution, and corresponding clinical information including pathological complete response (pCR) rate of NAT response were recorded. Results: Baseline CD3+ T cells(OR 1.11, 1.03–1.21, p = 0.011), CD8+ T cells (OR 1.09, 1.02–1.18, p = 0.015), and NK cells (OR 0.91, 0.83–0.98, p = 0.028) in PBLs subgroup distribution were independent predictors of pCR in BC patients receiving NAT, in which CD8+ T cells had the highest predictive ability (AUC = 0.76). Compared with some previous prediction indicators, its prediction ability has been improved to some extent. Conclusion: Peripheral baseline CD3+ T cells, CD8+ T cells, and NK cells were independent predictors of pCR in BC patients receiving NAT, in which CD8+ T cells had the highest predictive ability. Therefore, it can provide newly non‐invasive, relatively accurate and easily accessible predictors for corresponding patients, and help clinicians better understand tumor immunity. Abstract : A retrospective study to find the correlation between PBLs subtypes and NAT efficacy, aiming to explore the independent predictors of pCR with great prediction ability.