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深度学习辅助的肿瘤细胞密度与 TIL(肿瘤浸润淋巴细胞)密度联合测量作为结直肠癌预后生物标志物

英文原题:Deep-learning enabled combined measurement of tumour cell density and tumour infiltrating lymphocyte density as a prognostic biomarker in colorectal cancer.

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Deep-learning enabled combined measurement of tumour cell density and tumour infiltrating lymphocyte density as a prognostic biomarker in colorectal cancer.

PubMed 2025/03/03(内容时间) BJC Rep Q2 · IF 3.8(JCR 2025)

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研究概要

DL 衍生的 TIL 和 TCD 评分在 CRC 中具有独立预后价值。TIL 和 TCD 低的患者癌症特异性死亡风险最高。DL 对 TIL 和 TCD 的量化可与其他经验证的预后生物标志物联合用于常规临床实践。

研究思路结论见上方概要

在结直肠癌(CRC)肿瘤微环境中,TIL(肿瘤浸润淋巴细胞)(TILs)和肿瘤细胞密度(TCD)是公认的预后标志物。利用深度学习(DL)在苏木精-伊红(HE)全切片图像(WSIs)上测量TILs和TCD可能有助于管理。

127例CRC患者原发肿瘤的HE WSIs被纳入。DL用于量化肿瘤不同区域的TILs以及腔表面的TCD。分析了TILs、TCD与癌症特异性生存之间的关系。

中位 TIL 密度在浸润边缘高于管腔表面(963 vs 795 TILs/mm 2,P = 0.010)。在多变量分析中,TILs 和 TCD 均为独立预后因素(分别为 HR 4.28,95% CI 1.87-11.71,P = 0.004;HR 2.72,95% CI 1.19-6.17,P = 0.017)。与 TCD 和 TILs 评分高的患者相比,TCD 和 TILs 均低的患者生存最差(HR 10.0,95% CI 2.51-39.78,P = 0.001)。

展开英文摘要原文

Within the colorectal cancer (CRC) tumour microenvironment, tumour infiltrating lymphocytes (TILs) and tumour cell density (TCD) are recognised prognostic markers. Measurement of TILs and TCD using deep-learning (DL) on haematoxylin and eosin (HE) whole slide images (WSIs) could aid management.

HE WSIs from the primary tumours of 127 CRC patients were included. DL was used to quantify TILs across different regions of the tumour and TCD at the luminal surface. The relationship between TILs, TCD, and cancer-specific survival was analysed.

Median TIL density was higher at the invasive margin than the luminal surface (963 vs 795 TILs/mm 2 , P = 0.010). TILs and TCD were independently prognostic in multivariate analyses (HR 4.28, 95% CI 1.87-11.71, P = 0.004; HR 2.72, 95% CI 1.19-6.17, P = 0.017, respectively). Patients with both low TCD and low TILs had the poorest survival (HR 10.0, 95% CI 2.51-39.78, P = 0.001), when compared to those with a high TCD and TILs score.

DL derived TIL and TCD score were independently prognostic in CRC. Patients with low TILs and TCD are at the highest risk of cancer-specific death. DL quantification of TILs and TCD could be used in combination alongside other validated prognostic biomarkers in routine clinical practice.

论文信息

作者
Westwood AC、Wilson BI、Laye J、Grabsch HI、Mueller W、Magee DR、Quirke P、West NP
第一作者单位
Division of Pathology and Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK.United Kingdom
通讯作者单位
Division of Pathology and Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK. N.P.West@leeds.ac.uk.United Kingdom
期刊
BJC reports2025 Mar 3
原文标识
PubMed 40033106 · DOI 10.1038/s44276-025-00123-8