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应用于临床结直肠癌队列的计算病理学可识别预测预后的免疫和内皮细胞空间模式。

Computational pathology applied to clinical colorectal cancer cohorts identifies immune and endothelial cell spatial patterns predictive of outcome.

作者信息

Trahearn Nicholas, Sakr Chirine, Banerjee Abhirup, Lee Seung Hyun, Baker Ann-Marie, Kocher Hemant M, Angerilli Valentina, Morano Federica, Bergamo Francesca, Maddalena Giulia, Intini Rossana, Cremolini Chiara, Caravagna Giulio, Graham Trevor, Pietrantonio Filippo, Lonardi Sara, Fassan Matteo, Sottoriva Andrea

机构信息

Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.

UCL Cancer Institute, UCL, London, UK.

出版信息

J Pathol. 2025 Feb;265(2):198-210. doi: 10.1002/path.6378.

Abstract

Colorectal cancer (CRC) is a histologically heterogeneous disease with variable clinical outcome. The role the tumour microenvironment (TME) plays in determining tumour progression is complex and not fully understood. To improve our understanding, it is critical that the TME is studied systematically within clinically annotated patient cohorts with long-term follow-up. Here we studied the TME in three clinical cohorts of metastatic CRC with diverse molecular subtype and treatment history. The MISSONI cohort included cases with microsatellite instability that received immunotherapy (n = 59, 24 months median follow-up). The BRAF cohort included BRAF V600E mutant microsatellite stable (MSS) cancers (n = 141, 24 months median follow-up). The VALENTINO cohort included RAS/RAF WT MSS cases who received chemotherapy and anti-EGFR therapy (n = 175, 32 months median follow-up). Using a Deep learning cell classifier, trained upon >38,000 pathologist annotations, to detect eight cell types within H&E-stained sections of CRC, we quantified the spatial tissue organisation and colocalisation of cell types across these cohorts. We found that the ratio of infiltrating endothelial cells to cancer cells, a possible marker of vascular invasion, was an independent predictor of progression-free survival (PFS) in the BRAF+MISSONI cohort (p = 0.033, HR = 1.44, CI = 1.029-2.01). In the VALENTINO cohort, this pattern was also an independent PFS predictor in TP53 mutant patients (p = 0.009, HR = 0.59, CI = 0.40-0.88). Tumour-infiltrating lymphocytes were an independent predictor of PFS in BRAF+MISSONI (p = 0.016, HR = 0.36, CI = 0.153-0.83). Elevated tumour-infiltrating macrophages were predictive of improved PFS in the MISSONI cohort (p = 0.031). We validated our cell classification using highly multiplexed immunofluorescence for 17 markers applied to the same sections that were analysed by the classifier (n = 26 cases). These findings uncovered important microenvironmental factors that underpin treatment response across and within CRC molecular subtypes, while providing an atlas of the distribution of 180 million cells in 375 clinically annotated CRC patients. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

摘要

结直肠癌(CRC)是一种组织学上异质性的疾病,临床结局各异。肿瘤微环境(TME)在决定肿瘤进展中所起的作用复杂且尚未完全了解。为了增进我们的理解,在具有长期随访的临床注释患者队列中系统地研究TME至关重要。在此,我们在三个具有不同分子亚型和治疗史的转移性CRC临床队列中研究了TME。MISSONI队列包括接受免疫治疗的微卫星不稳定病例(n = 59,中位随访24个月)。BRAF队列包括BRAF V600E突变的微卫星稳定(MSS)癌症(n = 141,中位随访24个月)。VALENTINO队列包括接受化疗和抗EGFR治疗的RAS/RAF野生型MSS病例(n = 175,中位随访32个月)。使用一个基于超过38,000个病理学家注释训练的深度学习细胞分类器,来检测CRC苏木精和伊红染色切片中的八种细胞类型,我们量化了这些队列中细胞类型的空间组织和共定位。我们发现,浸润性内皮细胞与癌细胞的比例,这一血管侵犯的可能标志物,是BRAF+MISSONI队列中无进展生存期(PFS)的独立预测因子(p = 0.033,HR = 1.44,CI = 1.029 - 2.01)。在VALENTINO队列中,这种模式在TP53突变患者中也是独立的PFS预测因子(p = 0.009,HR = 0.59,CI = 0.40 - 0.88)。肿瘤浸润淋巴细胞是BRAF+MISSONI队列中PFS的独立预测因子(p = 0.016,HR = 0.36,CI = 0.153 - 0.83)。肿瘤浸润巨噬细胞升高预示着MISSONI队列中PFS改善(p = 0.031)。我们使用针对17种标志物(应用于分类器分析的相同切片)的高度多重免疫荧光验证了我们的细胞分类(n = 26例)。这些发现揭示了重要的微环境因素,这些因素是CRC分子亚型之间及内部治疗反应的基础,同时提供了375例临床注释CRC患者中1.8亿个细胞分布图谱。© 2025作者。《病理学杂志》由约翰·威利父子有限公司代表大不列颠及爱尔兰病理学会出版。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232f/11717494/9e9ecf79403c/PATH-265-198-g001.jpg

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