一种用于克服非小细胞肺癌治疗中抗原异质性的多靶向 CAR-T 细胞平台
A Multi-Targeting Chimeric Antigen Receptor-T Cell Platform to Overcome Antigen Heterogeneity in the Treatment of Non-Small Cell Lung Cancer.
这些发现支持采用多靶点CAR-T 策略来应对NSCLC及可能其他实体瘤中的抗原异质性。
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
应用人工智能算法评估早期非小细胞肺癌中 PD-L1 表达与 TIL（肿瘤浸润淋巴细胞）
英文原题：Assessment of PD-L1 expression and tumour infiltrating lymphocytes in early-stage non-small cell lung carcinoma with artificial intelligence algorithms.
查看英文原题
Assessment of PD-L1 expression and tumour infiltrating lymphocytes in early-stage non-small cell lung carcinoma with artificial intelligence algorithms.
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研究概要
这项初步研究支持使用 AI 算法对 NSCLC 患者的 PD-L1 和 TIL 进行评分。
研究思路结论见上方概要
目的
研究早期非小细胞肺癌（NSCLC）患者中程序性死亡配体1（PD-L1）表达和TIL（肿瘤浸润淋巴细胞）（TILs）的人工智能（AI）算法。
方法
该研究纳入了50例早期NSCLC样本。PD-L1免疫组化（IHC）染色切片（克隆SP263）由三位病理学家手动评分，并使用两种不同的AI工具（PathAI和Navify Digital Pathology）进行评分。TILs在H&E和CD8 IHC染色切片上分别使用两种不同算法（分别为PathAI和Navify Digital Pathology）进行数字化评估。分析了每种生物标志物的观察者间和方法间一致性。对于PD-L1，记录了手动评分与AI辅助评分的周转时间（TAT）。
结果
无论采用哪种方法，PD-L1低表达肿瘤中的一致性都更高。与手动评分相比，两种AI驱动工具均识别出显著更多PD-L1肿瘤比例评分等于或高于1%的病例（p=0.00015），这一发现具有潜在的治疗意义。关于TAT，手动评分与AI使用之间存在显著差异（所有比较的p值<0.0001）。PathAI算法计算的总TILs密度与Navify Digital Pathology软件计算的总CD8+细胞密度显著相关（τ=0.49（95% CI 0.37, 0.61），p值<0.0001）。
展开英文摘要原文
METHODS
The study included samples from 50 early-stage NSCLCs. PD-L1 immunohistochemistry (IHC) stained slides (clone SP263) were scored manually and with two different AI tools (PathAI and Navify Digital Pathology) by three pathologists. TILs were digitally assessed on H&E and CD8 IHC stained sections with two different algorithms (PathAI and Navify Digital Pathology, respectively). The agreement between observers and methods for each biomarker was analysed. For PD-L1, the turn-around time (TAT) for manual versus AI-assisted scoring was recorded.
RESULTS
Agreement was higher in tumours with low PD-L1 expression regardless of the approach. Both AI-powered tools identified a significantly higher number of cases equal or above 1% PD-L1 tumour proportion score as compared with manual scoring (p=0.00015), a finding with potential therapeutic implications. Regarding TAT, there were significant differences between manual scoring and AI use (p value <0.0001 for all comparisons). The total TILs density with the PathAI algorithm and the total density of CD8+ cells with the Navify Digital Pathology software were significantly correlated (τ=0.49 (95% CI 0.37, 0.61), p value<0.0001).
CONCLUSIONS
This preliminary study supports the use of AI algorithms for the scoring of PD-L1 and TILs in patients with NSCLC.
论文信息
- 作者
- Molero A、Hernandez S、Alonso M、Peressini M、Curto D、Lopez-Rios F、Conde E
- 第一作者单位
- Pathology, Complejo Asistencial de Segovia, Segovia, Spain.Spain
- 通讯作者单位
- Pathology, Hospital Universitario 12 de Octubre, Madrid, Spain fernandolopezriosmoreno@gmail.com.Spain
- 期刊
- Journal of clinical pathology2025 Jun 19
- 原文标识
- PubMed 39419594 · DOI 10.1136/jcp-2024-209766
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