TMU and NTU Hospital Join Forces to Advance Precision Medicine in Liver Cancer and Kidney Disease
Source: National Taiwan University Hospital (NTUH)
Published on 2025-05-06
On 3 May 2025, Taipei Medical University (TMU) has partnered with National Taiwan University Hospital (NTUH) to integrate multi-omics, AI and big data in translational medicine.
The institutions jointly held the inaugural “Collaborative Research Results Symposium” to present key findings on liver cancer and chronic kidney disease (CKD), demonstrating Taiwan’s leadership in biomedical innovation.

Liver Cancer: From Molecular Profiling to Targeted Therapy
Liver cancer remains a major public health issue in Taiwan. While virus-related cases have declined due to preventive efforts, metabolic syndromes and fatty liver disease are emerging drivers. To address this evolving challenge, TMU and NTUH researchers constructed a multi-omics framework to investigate tumor heterogeneity and uncover molecular pathways for personalized treatment.
Under the leadership of NTUH Vice Superintendent Dr. Jia-Horng Kao and with TMU faculty including Professor Ching-Wen Chang and Dr. Yi-Wen Huang, the research team analyzed genomic, transcriptomic, and kinomic data to identify high-impact molecular signatures. TMU’s contribution included characterization of tumor immune microenvironments and validation of gene-target relationships using clinical cohorts.
A major outcome was the development of a high-throughput screening platform that combines gene interference with drug inhibition. This approach revealed two potential therapeutic pathways—STK40-YAP-MAPK and SLK-ROCK—with demonstrated relevance to patient survival. By selectively modulating YAP activity via upstream regulators STK40 and SLK, researchers proposed a novel and safer strategy for controlling liver tumor growth.
These findings not only clarify previously undruggable oncogenic mechanisms but also showcase the power of integrative AI-based discovery pipelines in advancing precision oncology.
CKD and Cardiorenal Syndrome: Predictive Tools for Population Health
Taiwan continues to lead globally in dialysis prevalence, highlighting the urgency of early intervention in CKD. Led by TMU Vice President Professor Kuan-Yu Hung and supported by TMU President Mai-Szu Wu and Shuang Ho Hospital Vice Superintendent Mei-Yi Wu, the “CKD Kidney Function Trajectory Study” is pioneering risk stratification models based on real-world clinical and molecular data.
Analyzing longitudinal data from over 100 patients, the study applied group-based trajectory modeling (GBTM) to identify distinct disease progression pathways. Concurrently, molecular profiling of immune cells and gene expression aims to identify predictive biomarkers that could delay or prevent dialysis initiation.
Further expanding its scope, the team conducted a nationwide survey of more than 600,000 individuals to evaluate the burden of cardiorenal metabolic syndrome (CKM). Findings emphasized its strong correlation with cardiovascular mortality, underscoring the need for integrated disease management.
A parallel study involving 513 nephrologists revealed that providers’ self-efficacy significantly impacts care quality, guiding future improvements in clinical training and workforce resilience.
Building an Ecosystem for Sustainable Innovation
This collaboration between TMU and NTUH exemplifies the role of institutional synergy in driving high-impact research. Beyond scientific discovery, the alliance underscores the need for data integration, cross-disciplinary expertise, and shared infrastructure to support sustainable development in precision medicine.
Moving forward, TMU will continue to lead in shaping a collaborative research ecosystem—one that bridges academic rigor and clinical applicability to address major health challenges and deliver better outcomes for patients across Taiwan and beyond.




































































































































































































































































































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