Su Kyeom Kim, Jungho Bae, Mi Jeong Lee, Dai Hoon Han, Seung-Woo Cho
{"title":"Liver-Specific Extracellular Matrix Enables High-Fidelity Patient-Derived Hepatocellular Carcinoma Xenograft Models.","authors":"Su Kyeom Kim, Jungho Bae, Mi Jeong Lee, Dai Hoon Han, Seung-Woo Cho","doi":"10.34133/bmr.0242","DOIUrl":null,"url":null,"abstract":"<p><p>Patient-derived tumor xenograft (PDX) models serve as powerful tools in oncology research owing to their ability to capture patient-specific tumor heterogeneity and clinical behavior. However, the conventional matrices derived from murine tumors, commonly used to generate PDX models, suffer from key limitations such as lack of tissue specificity, high production costs, and inconsistent batch quality. In response, our study investigates the use of decellularized liver extracellular matrix (Liver ECM) as a biomimetic alternative that more accurately recapitulates the native hepatic microenvironment. We demonstrate that Liver ECM, enriched with liver-specific biochemical cues, enables robust engraftment, growth, and metastasis of patient-derived hepatocellular carcinoma cells in both subcutaneous and orthotopic PDX models. Notably, orthotopic models established with Liver ECM exhibited enhanced metastatic behavior, particularly to the intestine, compared to those formed using conventional matrices. Transcriptomic analysis further revealed activation of key pathways associated with cancer progression, including angiogenesis, apoptosis, migration, and inflammation. Additionally, we extend the application of Liver ECM to patient-derived organoid xenografts, which showed improved tumorigenicity and retained pathophysiological features of the original tumor tissue. Together, these findings underscore the potential of liver-specific ECM as a superior platform for generating physiologically relevant PDX models and enhancing the translational relevance of preclinical cancer studies.</p>","PeriodicalId":93902,"journal":{"name":"Biomaterials research","volume":"29 ","pages":"0242"},"PeriodicalIF":9.6000,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12369845/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomaterials research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34133/bmr.0242","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Patient-derived tumor xenograft (PDX) models serve as powerful tools in oncology research owing to their ability to capture patient-specific tumor heterogeneity and clinical behavior. However, the conventional matrices derived from murine tumors, commonly used to generate PDX models, suffer from key limitations such as lack of tissue specificity, high production costs, and inconsistent batch quality. In response, our study investigates the use of decellularized liver extracellular matrix (Liver ECM) as a biomimetic alternative that more accurately recapitulates the native hepatic microenvironment. We demonstrate that Liver ECM, enriched with liver-specific biochemical cues, enables robust engraftment, growth, and metastasis of patient-derived hepatocellular carcinoma cells in both subcutaneous and orthotopic PDX models. Notably, orthotopic models established with Liver ECM exhibited enhanced metastatic behavior, particularly to the intestine, compared to those formed using conventional matrices. Transcriptomic analysis further revealed activation of key pathways associated with cancer progression, including angiogenesis, apoptosis, migration, and inflammation. Additionally, we extend the application of Liver ECM to patient-derived organoid xenografts, which showed improved tumorigenicity and retained pathophysiological features of the original tumor tissue. Together, these findings underscore the potential of liver-specific ECM as a superior platform for generating physiologically relevant PDX models and enhancing the translational relevance of preclinical cancer studies.