基于 DNA 超分子水凝胶的保护性 NK 细胞储库用于增强三阴性乳腺癌治疗
Protective NK Cell Reservoir Based on DNA Supramolecular Hydrogel for Enhanced Triple-Negative Breast Cancer Therapy.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Prognostic value of tumor-infiltrating lymphocytes (TILs) in Luminal breast cancer: A novel computational method for assessing TILs abundance and spatial distribution patterns.
Prognostic value of tumor-infiltrating lymphocytes (TILs) in Luminal breast cancer: A novel computational method for assessing TILs abundance and spatial distribution patterns.
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管腔型乳腺癌中TIL(肿瘤浸润淋巴细胞)的预后意义仍存在争议,主要原因是TIL浸润通常较低、评估方法不一致,以及对空间分布模式考虑不足。为克服这些局限,研究者开发了一种先进的人工智能(AI)计算TIL评估(CTA)系统,符合国际视觉评估指南,可精准量化管腔型乳腺癌中TIL丰度(自动TIL,aTIL)及空间分布模式(聚集型aTIL-agg;分散型aTIL-dis)。综合分析显示,TIL水平升高与总生存期(OS)和无进展生存期(PFS)改善显著相关。
值得注意的是,与管腔A型相比,管腔B型TIL浸润显著较高。在管腔A型队列中,聚集型空间模式(aTIL-agg)是OS和PFS的有利预后指标;而在管腔B型病例中,总体TIL丰度(aTIL)和分散型模式(aTIL-dis)与生存改善相关。多变量Cox回归分析证实,aTIL、aTIL-agg和aTIL-dis在管腔A型患者中具有独立预测PFS的价值,但在管腔B型亚组未观察到显著关联。
本研究显示,AI驱动的TIL评估在预测管腔型乳腺癌患者临床结局方面具有潜在临床价值,并为理解这一分子亚型中的肿瘤-免疫相互作用提供了新见解。
The prognostic significance of tumor-infiltrating lymphocytes (TILs) in Luminal-type breast cancer remains controversial, primarily due to typically low TIL infiltration levels, methodological inconsistencies in assessment, and insufficient consideration of spatial distribution patterns.
To overcome these limitations, we developed an advanced artificial intelligence (AI)-driven computational TIL assessment (CTA) system, compliant with international visual assessment guidelines, which enables precise quantification of both TIL abundance (automatic TILs, aTILs) and spatial distribution patterns (aggregated: aTILs-agg; distributed: aTILs-dis) in Luminal-type breast cancer.
Our comprehensive analysis suggests that elevated TIL levels were significantly associated with improved overall survival (OS) and progression-free survival (PFS) outcomes.
Notably, Luminal B subtype demonstrated significantly higher TIL infiltration compared to Luminal A. In the Luminal A cohort, the aggregated spatial pattern (aTILs-agg) emerged as a favorable prognostic indicator for both OS and PFS, while in Luminal B cases, overall TIL abundance (aTILs) and distributed patterns (aTILs-dis) were associated with enhanced survival outcomes.
Multivariate Cox regression analysis confirmed the independent prognostic value of aTILs, aTILs-agg, and aTILs-dis for PFS in Luminal A patients, though no significant associations were observed in the Luminal B subgroup.
This study demonstrates the clinical utility of AI-powered TIL assessment as a promising prognostic indicator for predicting clinical outcomes in Luminal breast cancer patients, offering new insights into tumor-immune interactions within this molecular subtype.
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