Modelling hepatocellular carcinoma microenvironment phenotype to evaluate drug efficacy
Abstract Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related death worldwide. Treating HCC is challenging because of the poor drug effectiveness and the lack of tools to predict patient responses. To resolve these issues, we established a patient-centric spheroid model us...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-84304-4 |
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| author | Sara Cherradi Salomé Roux Marie Dupuy Séverine Tabone-Eglinger Edouard Tuaillon Marianne Ziol Eric Assenat Hong Tuan Duong |
| author_facet | Sara Cherradi Salomé Roux Marie Dupuy Séverine Tabone-Eglinger Edouard Tuaillon Marianne Ziol Eric Assenat Hong Tuan Duong |
| author_sort | Sara Cherradi |
| collection | DOAJ |
| description | Abstract Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related death worldwide. Treating HCC is challenging because of the poor drug effectiveness and the lack of tools to predict patient responses. To resolve these issues, we established a patient-centric spheroid model using HepG2, TWNT-1, and THP-1 co-culture, that mimics HCC phenotype. We developed a target-independent cell killing (TICK) exclusion strategy to monitor the therapeutic response. We demonstrated that our model reproduced the Barcelona Clinic Liver Cancer (BCLC) molecular classification, displayed known alterations of epigenetic players, and responded to tyrosine kinase inhibitors (TKIs) such as sorafenib, cabozantinib, and lenvatinib in a patient-dependent manner. Importantly, we reported for the first time that our model correctly predicted 34 clinical outcomes to TKIs out of 37 case studies on 32 HCC patients confirming that patient-centric spheroids, combined with our TICK exclusion strategy, are valuable models for drug discovery and opening a near perspective to personalized care. |
| format | Article |
| id | doaj-art-7767c6e24ec94dcf9df7a92178bca375 |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-7767c6e24ec94dcf9df7a92178bca3752025-08-20T02:36:34ZengNature PortfolioScientific Reports2045-23222025-01-0115111110.1038/s41598-024-84304-4Modelling hepatocellular carcinoma microenvironment phenotype to evaluate drug efficacySara Cherradi0Salomé Roux1Marie Dupuy2Séverine Tabone-Eglinger3Edouard Tuaillon4Marianne Ziol5Eric Assenat6Hong Tuan Duong7PredictCan Biotechnologies SAS, Biopôle EuromédecinePredictCan Biotechnologies SAS, Biopôle EuromédecineService d’Oncologie Médicale, Hôpital Saint Eloi, Centre Hospitalier Universitaire de MontpellierPlateforme de Gestion des Echantillons Biologiques, Centre Léon Bérard, Cancer Research Center of Lyon, Université de Lyon, Université Claude Bernard Lyon 1, INSERM 1052, CNRS 5286Centre de Ressources Biologiques (CRB), Centre Hospitalier Universitaire de MontpellierCentre de Ressources Biologiques du Groupe hospitalier Paris Seine Saint-DenisService d’Oncologie Médicale, Hôpital Saint Eloi, Centre Hospitalier Universitaire de MontpellierPredictCan Biotechnologies SAS, Biopôle EuromédecineAbstract Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related death worldwide. Treating HCC is challenging because of the poor drug effectiveness and the lack of tools to predict patient responses. To resolve these issues, we established a patient-centric spheroid model using HepG2, TWNT-1, and THP-1 co-culture, that mimics HCC phenotype. We developed a target-independent cell killing (TICK) exclusion strategy to monitor the therapeutic response. We demonstrated that our model reproduced the Barcelona Clinic Liver Cancer (BCLC) molecular classification, displayed known alterations of epigenetic players, and responded to tyrosine kinase inhibitors (TKIs) such as sorafenib, cabozantinib, and lenvatinib in a patient-dependent manner. Importantly, we reported for the first time that our model correctly predicted 34 clinical outcomes to TKIs out of 37 case studies on 32 HCC patients confirming that patient-centric spheroids, combined with our TICK exclusion strategy, are valuable models for drug discovery and opening a near perspective to personalized care.https://doi.org/10.1038/s41598-024-84304-4Patient-centric spheroid modelHepatocellular carcinomaTargeted therapyTyrosine kinase inhibitorsPrediction of clinical outcomes |
| spellingShingle | Sara Cherradi Salomé Roux Marie Dupuy Séverine Tabone-Eglinger Edouard Tuaillon Marianne Ziol Eric Assenat Hong Tuan Duong Modelling hepatocellular carcinoma microenvironment phenotype to evaluate drug efficacy Scientific Reports Patient-centric spheroid model Hepatocellular carcinoma Targeted therapy Tyrosine kinase inhibitors Prediction of clinical outcomes |
| title | Modelling hepatocellular carcinoma microenvironment phenotype to evaluate drug efficacy |
| title_full | Modelling hepatocellular carcinoma microenvironment phenotype to evaluate drug efficacy |
| title_fullStr | Modelling hepatocellular carcinoma microenvironment phenotype to evaluate drug efficacy |
| title_full_unstemmed | Modelling hepatocellular carcinoma microenvironment phenotype to evaluate drug efficacy |
| title_short | Modelling hepatocellular carcinoma microenvironment phenotype to evaluate drug efficacy |
| title_sort | modelling hepatocellular carcinoma microenvironment phenotype to evaluate drug efficacy |
| topic | Patient-centric spheroid model Hepatocellular carcinoma Targeted therapy Tyrosine kinase inhibitors Prediction of clinical outcomes |
| url | https://doi.org/10.1038/s41598-024-84304-4 |
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