ArticleCancer medicine2022
Peripheral blood lymphocytes subtypes as new predictors for neoadjuvant therapy efficacy in breast cancer.
Article in Cancer medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Efficacy and Safety of Shen-Ling-Lian-Xia Granule Combined With Neoadjuvant Chemotherapy in Patients With Triple-Negative Breast Cancer: Protocol for a Randomized, Double-Blind, Multicenter Clinical Trial.JMIR research protocols · 2026Article
- Natural Killer Cell Activity and Response to Neoadjuvant Treatment in Breast Cancer Patients.International journal of molecular sciences · 2025Article
- The role of peripheral T lymphocyte subsets and PD-1 expression as a biomarker for neoadjuvant treatment response in breast cancer.Medicine · 2025Article
- Immune characteristics and clinical significance of peripheral blood lymphocytes in breast cancer.BMC cancer · 2024Article
- Peripheral blood lymphocytes subtypes as new predictors for neoadjuvant therapy efficacy in breast cancer.Cancer medicine · 2022Article
- A Neutrophil-Based Predictive Model for Axillary De-Escalation After Neoadjuvant Therapy in Node-Positive Breast Cancer.IET systems biologyArticle
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10 authors.
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Abstract
backgroundHost 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.
methodsBetween 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.
resultsBaseline 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.
conclusionPeripheral 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.
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