CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:The Possible Role of Anti- and Protumor-Infiltrating Lymphocytes in Pathologic Complete Response in Early Breast Cancer Patients Treated with Neoadjuvant Systemic Therapy.
The Possible Role of Anti- and Protumor-Infiltrating Lymphocytes in Pathologic Complete Response in Early Breast Cancer Patients Treated with Neoadjuvant Systemic Therapy.
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肿瘤微环境由促肿瘤和抗肿瘤免疫细胞共同组成,可影响癌细胞行为。本研究旨在评估乳腺癌患者确诊时核心针活检中的TIL(肿瘤浸润淋巴细胞)密度及亚型,能否预测新辅助全身治疗(NST)后的病理完全缓解(pCR;ypT0/is ypN0)。根据推定的抗肿瘤免疫细胞(CD8+、CXCL13+)和促肿瘤免疫细胞(PD-1+、FOXP3+)比例确定TIL亚型。本前瞻性非干预研究纳入171名接受NST的患者。全队列TIL密度中位数为10%(四分位距3.5–23.8),59例(35%)达到pCR。TIL密度与pCR正相关,单变量及多变量分析结果均如此。在多变量Logistic回归模型中,校正年龄(p=0.232)、Ki-67(p=0.001)、淋巴结阴性状态(p=0.024)及HER2阳性/三阴性相对于管腔B样亚型(p<0.001)后,TIL密度仍为pCR的独立预测因素(p=0.012,OR 1.27;95% CI 1.05–1.54)。在本研究样本中,PD-1阳性和FOXP3阳性TIL比例较高均与pCR概率升高相关,但未达到统计学显著性;在同时纳入全部四种标志物的模型中,无法确定关联方向。探索性多变量分析显示,只有CD8+ TIL较高与pCR相关。总之,TIL密度及其亚型均与pCR相关。
The tumor microenvironment, composed of pro- and antitumor immune cells, affects cancer cell behavior.
We aimed to evaluate whether tumor-infiltrating lymphocyte (TIL) density and TIL subtypes in core biopsies at the diagnosis of breast cancer patients could predict a pathologic complete response (pCR; ypT0/is ypN0) from neoadjuvant systemic therapy (NST). The TIL subtypes were determined based on the proportions of presumably antitumor (CD8+, CXCL13+) and protumor (PD-1+, FOXP3+) immune cells. A prospective, noninterventional study, including 171 participants undergoing NST, was performed. The median TIL density for the entire cohort was 10% (IQR: 3. 5-23. 8), and 59 (35%) patients achieved pCR. TIL density was positively associated with pCR (univariately and multivariably).
In the multivariable logistic regression model, TIL density was an independent predictor of pCR ( p = 0. 012, OR 1. 27; 95% CI 1. 05-1. 54) when controlled for age ( p = 0. 232), Ki-67 ( p = 0. 001), node-negative status ( p = 0. 024), and HER2+/triple negative vs. luminal B-like subtype ( p < 0. 001).
In our sample, higher proportions of PD-1+ TILs and FOXP3+ TILs were associated with a higher probability of pCR but the association was not statistically significant and we could not make any conclusions on the direction of associations in the model with all four biomarkers. In the exploratory multivariable analysis, we showed that only higher CD8+ TILs were associated with pCR.
In conclusion, TIL density and its subtypes are associated with pCR.
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