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TIL(肿瘤浸润淋巴细胞)的空间特征与乳腺癌进展

英文原题:Spatial Characterization of Tumor-Infiltrating Lymphocytes and Breast Cancer Progression.

查看英文原题

Spatial Characterization of Tumor-Infiltrating Lymphocytes and Breast Cancer Progression.

PubMed 2022/04/26(内容时间) Cancers (Basel) Q2 · IF 4.8(JCR 2025)

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中文摘要

TIL(肿瘤浸润淋巴细胞)(TILs)已被确立为乳腺癌中稳健的预后生物标志物,在辅助和新辅助治疗背景下预测治疗反应方面也展现出新兴的应用价值。本研究在来自癌症基因组图谱(TCGA BRCA)和卡罗来纳乳腺癌研究(UNC CBCS)的两个独立乳腺癌队列中,评估了TILs在预测总生存期和无进展间期中的作用。我们利用机器学习和计算机视觉算法,在经苏木精和伊红(H&E)染色的乳腺癌数字全切片图像(WSIs)中表征TIL浸润。采用多个参数来表征TIL浸润的整体丰度和空间特征。单因素和多因素分析显示,瘤周和瘤内TILs的大聚集(森林)与更长的生存期相关,而瘤内TILs的缺失(荒漠)与复发风险增加相关。具有两个或以上高风险空间特征的患者与显著更短的无进展间期(PFI)相关。本研究证明了Pathomics在评估TIL浸润的丰度和空间分布模式作为乳腺癌重要生物标志物的临床意义方面的实际效用。

展开英文摘要原文

Tumor-infiltrating lymphocytes (TILs) have been established as a robust prognostic biomarker in breast cancer, with emerging utility in predicting treatment response in the adjuvant and neoadjuvant settings. In this study, the role of TILs in predicting overall survival and progression-free interval was evaluated in two independent cohorts of breast cancer from the Cancer Genome Atlas (TCGA BRCA) and the Carolina Breast Cancer Study (UNC CBCS).

We utilized machine learning and computer vision algorithms to characterize TIL infiltrates in digital whole-slide images (WSIs) of breast cancer stained with hematoxylin and eosin (H&E). Multiple parameters were used to characterize the global abundance and spatial features of TIL infiltrates.

Univariate and multivariate analyses show that large aggregates of peritumoral and intratumoral TILs (forests) were associated with longer survival, whereas the absence of intratumoral TILs (deserts) is associated with increased risk of recurrence. Patients with two or more high-risk spatial features were associated with significantly shorter progression-free interval (PFI).

This study demonstrates the practical utility of Pathomics in evaluating the clinical significance of the abundance and spatial patterns of distribution of TIL infiltrates as important biomarkers in breast cancer.

论文信息

作者
Fassler DJ、Torre-Healy LA、Gupta R、Hamilton AM、Kobayashi S、Van Alsten SC、Zhang Y、Kurc T
单位
Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11790, USA.United States
期刊
Cancers2022 Apr 26
原文标识
PubMed 35565277 · DOI 10.3390/cancers14092148