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:Assessment of Tumor-Infiltrating Lymphocytes in Triple-Negative Breast Cancer: Interobserver Variability and Contributing Factors.
Assessment of Tumor-Infiltrating Lymphocytes in Triple-Negative Breast Cancer: Interobserver Variability and Contributing Factors.
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吉隆坡医院Canselor Tuanku Muhriz的两名顾问病理医师依据TIL-WG指南独立评估64例TNBC。采用组内相关系数(ICC)和Cohen κ系数量化观察者间一致性。评分差异超过10%的病例交由第三位病理医师复核,并通过共识讨论探究潜在干扰因素。
间质TIL评分观察者间一致性中等(ICC=.58),瘤内TIL一致性较高(ICC=.71)。显著变异主要归因于三个干扰因素:TIL分布异质、肿瘤-间质界面界定不清,以及局灶性致密淋巴细胞浸润。
研究结果凸显制定标准化TIL评分方案的必要性,也提示经验证的AI工具未来可能有助于减轻观察者差异。
Background/Objectives: Tumor-infiltrating lymphocytes (TILs) are emerging as a crucial prognostic biomarker in triple-negative breast cancer (TNBC).
However, their clinical utility remains constrained by the subjectivity and interobserver variability of manual scoring, despite standardization efforts by the International TILs Working Group (TIL-WG).
This study aimed to evaluate the interobserver agreement among pathologists in scoring stromal and intratumoral TILs from H&E-stained TNBC slides and to identify contributing histological factors. Methods: Two consultant pathologists at Hospital Canselor Tuanku Muhriz, Kuala Lumpur, independently assessed 64 TNBC cases using TIL-WG guidelines. Interobserver agreement was quantified using the intraclass correlation coefficient (ICC) and Cohen's kappa coefficient. Cases with over 10% scoring discrepancies underwent review by a third pathologist, and a consensus discussion was held to explore the underlying confounders.
Results: Our results showed moderate interobserver agreement for stromal TILs (ICC = 0. 58) and strong agreement for intratumoral TILs (ICC = 0. 71). Significant variability was attributed to three main confounding variables: heterogeneous TIL distribution, poorly defined tumor-stroma interface, and focal dense lymphoid infiltrates. Conclusions: These findings highlight the need for standardized TIL scoring protocols and suggest that validated AI-based tools may help mitigate observer variability in future TIL assessments.
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