4.6 Article

A Novel Approach for Quantifying Cancer Cells Showing Hybrid Epithelial/Mesenchymal States in Large Series of Tissue Samples: Towards a New Prognostic Marker

期刊

CANCERS
卷 12, 期 4, 页码 -

出版社

MDPI
DOI: 10.3390/cancers12040906

关键词

computational pathology; hybrid E/M state; partial EMT; prognosis; quantification; sequential immunohistochemistry; tissue-based biomarker; urothelial carcinoma; whole-slide imaging

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资金

  1. European Regional Development Fund
  2. Walloon Region of Belgium (Wallonia-biomed) [411132-957270]
  3. Fonds Erasme pour la Recherche Medicale (Brussels, Belgium
  4. grant: Bourse Convention d'Excellence de Gai ffier d'Emeville 2015-2021)

向作者/读者索取更多资源

In cancer biology, epithelial-to-mesenchymal transition (EMT) is associated with tumorigenesis, stemness, invasion, metastasis, and resistance to therapy. Evidence of co-expression of epithelial and mesenchymal markers suggests that EMT should be a stepwise process with distinct intermediate states rather than a binary switch. In the present study, we propose a morphological approach that enables the detection and quantification of cancer cells with hybrid E/M states, i.e., which combine partially epithelial (E) and partially mesenchymal (M) states. This approach is based on a sequential immunohistochemistry technique performed on the same tissue section, the digitization of whole slides, and image processing. The aim is to extract quantitative indicators able to quantify the presence of hybrid E/M states in large series of human cancer samples and to analyze their relationship with cancer aggressiveness. As a proof of concept, we applied our methodology to a series of about a hundred urothelial carcinomas and demonstrated that the presence of cancer cells with hybrid E/M phenotypes at the time of diagnosis is strongly associated with a poor prognostic value, independently of standard clinicopathological features. Although validation on a larger case series and other cancer types is required, our data support the hybrid E/M score as a promising prognostic biomarker for carcinoma patients.

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