Ni Xihao, Wang Weitao, Sun Huimin, An Ran, Lei Ying, Wang Chang-Liang
School of Clinical Medicine, Shandong Second Medical University, Weifang, Shandong Province, People's Republic of China.
Department of Pathology, Weifang People's Hospital, Weifang, Shandong Province, People's Republic of China.
PLoS One. 2025 Mar 19;20(3):e0320487. doi: 10.1371/journal.pone.0320487. eCollection 2025.
Tumor-infiltrating lymphocytes (TILs) are associated with lymph node metastasis and prognosis in breast cancer. Therefore, we explored the value of TILs in predicting sentinel lymph node metastasis (SLNM) in patients with early-stage (cT1-2N0) breast cancer and provided a new method for preoperative assessment of SLNM status.
This study included 337 patients with early-stage breast cancer who underwent surgery at our hospital from January 2022 to December 2023. The expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki-67 in the patients was assessed using immunohistochemistry (IHC). TILs in the core needle biopsy samples were evaluated histopathologically, and patients were divided into high and low TILs groups based on the density of TILs. Statistical analysis was conducted, and a predictive model was established.
The study found that patients with high TILs had a significantly lower rate of SLNM compared to those with low TILs (P < 0.001). The cT stage and the level of TILs were identified as independent predictive factors for SLNM. The ROC curve analysis indicated that the density of TILs has good predictive efficacy for SLNM. Based on the results of the multivariate regression analysis, a nomogram predictive model for SLNM was constructed.
Our study showed that the density of TILs and cT stage are independent predictive factors for SLNM in early-stage (cT1-2N0) breast cancer, and the predictive effect of TILs density on SLNM is significant in Luminal and triple-negative breast cancers.
肿瘤浸润淋巴细胞(TILs)与乳腺癌的淋巴结转移及预后相关。因此,我们探讨了TILs在预测早期(cT1-2N0)乳腺癌患者前哨淋巴结转移(SLNM)中的价值,并为术前评估SLNM状态提供了一种新方法。
本研究纳入了2022年1月至2023年12月在我院接受手术的337例早期乳腺癌患者。采用免疫组织化学(IHC)评估患者雌激素受体(ER)、孕激素受体(PR)、人表皮生长因子受体2(HER2)和Ki-67的表达。对粗针活检样本中的TILs进行组织病理学评估,并根据TILs密度将患者分为高TILs组和低TILs组。进行统计分析并建立预测模型。
研究发现,高TILs患者的SLNM发生率显著低于低TILs患者(P < 0.001)。cT分期和TILs水平被确定为SLNM的独立预测因素。ROC曲线分析表明,TILs密度对SLNM具有良好的预测效能。基于多因素回归分析结果,构建了SLNM的列线图预测模型。
我们的研究表明,TILs密度和cT分期是早期(cT1-2N0)乳腺癌SLNM的独立预测因素,且TILs密度对Luminal型和三阴性乳腺癌的SLNM预测效果显著。