Patient-derived explants of colorectal cancer: Histopathological and molecular analysis of long-term cultures

Sara da Mata, Teresa Franchi-Mendes, Sofia Abreu, Bruno Filipe, Sónia Morgado, Marta Mesquita, Cristina Albuquerque, Ricardo Fonseca, Vítor E. Santo, Erwin R. Boghaert, Isadora Rosa, Catarina Brito

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


Colorectal cancer (CRC) is one of the most common cancers worldwide. Although short-term cultures of tumour sections and xenotransplants have been used to determine drug efficacy, the results frequently fail to confer clinically useful information. Biomarker discovery has changed the paradigm for advanced CRC, though the presence of a biomarker does not necessarily translate into therapeutic success. To improve clinical outcomes, translational models predictive of drug response are needed. We describe a simple method for the fast establishment of CRC patient-derived explant (CRC-PDE) cultures from different carcinogenesis pathways, employing agitation-based platforms. A total of 26 CRC-PDE were established and a subset was evaluated for viability (n = 23), morphology and genetic key alterations (n = 21). CRC-PDE retained partial tumor glandular architecture and microenvironment features were partially lost over 4 weeks of culture. Key proteins (p53 and Mismatch repair) and oncogenic driver mutations of the original tumours were sustained throughout the culture. Drug challenge (n = 5) revealed differential drug response from distinct CRC-PDE cases. These findings suggest an adequate representation of the original tumour and highlight the importance of detailed model characterisation. The preservation of key aspects of the CRC microenvironment and genetics supports CRC-PDE potential applicability in pre-and co-clinical settings, as long as temporal dynamics are considered.

Original languageEnglish
Article number4695
Issue number18
Publication statusPublished - Sep 2021


  • Colorectal cancer
  • Patient-derived explants
  • Translational models


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