肿瘤细胞治疗研究
英文原题:AI-powered and manual assessment of tumor-infiltrating lymphocytes in early HER2-positive breast cancer in NSABP B-41.
AI-powered and manual assessment of tumor-infiltrating lymphocytes in early HER2-positive breast cancer in NSABP B-41.
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联合评估TIL(肿瘤浸润淋巴细胞)和基因表达特征(GES),有望指导乳腺癌个体化治疗。本研究纳入 III 期 NSABP B-41 试验中的 262 名患者;该试验评估新辅助 HER2 靶向治疗与化疗联用。研究采用人工和人工智能(AI)方法分析 TIL,并根据 RNA 测序分析 GES。在雌激素受体(ER)阴性患者中,作为连续变量的人工 TIL 较高与病理完全缓解(pCR)相关。无论 ER 状态如何,AI 评估的 TIL 均与 pCR 相关。免疫基因表达特征(iGES)也与 pCR 相关。人工 TIL 与无事件生存期(EFS)无关联,而 AI-TIL 显示边缘性关联。研究结果支持将 TIL 评估与 GES 结合,用作 HER2 阳性乳腺癌的预后生物标志物。未来需研究其预测价值,以指导治疗决策。
The assessment of tumor-infiltrating lymphocyte (TILs), together with gene expression signatures (GES), has the potential to guide personalized breast cancer therapy.
We included 262 patients from the phase III NSABP B-41 trial, which evaluated neoadjuvant HER2-targeted therapies in combination with chemotherapy.
We conducted a manual and artificial intelligence (AI)-based analyses of TILs, as well as GES from RNA sequencing. Higher manual TILs as a continuous variable were associated with pathologic complete response (pCR) in patients with estrogen receptor (ER)-negative disease. AI-based TILs were associated with pCR regardless of ER status.
Immune GES (iGES) were associated with pCR. Manual TILs were not associated with event-free survival (EFS), while AI-TIL showed a marginal association. These results support the use of TIL assessment, complemented by GES, as a prognostic biomarker in HER2-positive breast cancer. Future studies are needed to evaluate their predictive utility to guide treatment decisions.
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