Programme(s) to which this project applies:
|☑ MPhil/PhD||☒ MRes[Med]||☒ URIS|
Liver cancer (Hepatocellular Carcinoma, HCC) is a particularly prevalent and deadly disease in Hong Kong and China. Despite definite improvements in the outcome of patients with HCC, the overall prognosis of this cancer is still unsatisfactory. To date, treatment for HCC has still followed a traditional “one-size-for-all” strategy where stratification of patients is only based on disease stage; and therapy is often inefficient or ineffective for many individuals. HCC is a biologically complex and highly heterogeneous disease. Distinguishing drivers from passenger mutations is of crucial importance. In an era of precision medicine, monitoring clinically relevant driver-dependent genetic alterations is important for stratifying patients for targeted therapies.
The development of effective therapies has been hindered by a shortage of reliable human models. Cancer cell lines cultured in 2D plastic plates do not represent the molecular signatures and drug sensitivity of tumours of origin, whereas patient-derived xenografts have limited scalability and are time-consuming in maintenance. 3D organoids cultured in Matrigel accurately recapitulate tissue architecture and function, constituting a superior platform for drug screening and cancer biology studies. Our group has had some success in generating HCC organoids from human tumours as well as non-tumour hepatocytes from adjacent non-tumour tissue. While these patient-derived HCC organoids are an immense resource to basic and pre-clinical studies as they highly recapitulate the mutation and global gene expression of the original patient tumour, it is hard to pinpoint the driver genes from passenger genes in the vast array of mutations documented in each patient-derived organoid line. Models for in-depth analyses of pathway interference in a defined mutation spectrum will provide a more simplistic model for study. Non-germline mosaic genetic engineered mouse models of HCC, generated by hydrodynamic tail vein delivery of DNA plasmids into hepatocytes, have gained increasing importance in the field of HCC research in recent years. Building on and integrating our expertise in organoid culture and hydrodynamic tail vein injection (HTVI) HCC mouse models, our current project aims to establish and characterize diverse driver-dependent HCC organoids that is representative of the common mutations and copy number alterations documented in HCC using the HTVI technique; and then apply the use of this established platform for various basic and applied research uses.
Multiple MPhil and PhD student positions currently available
Dr SKY Ma, School of Biomedical Sciences
Dr Stephanie Ma's research group in the School of Biomedical Sciences, Li Ka Shing Faculty of Medicine at the University of Hong Kong has a long-standing interest in identifying novel stemness vulnerabilities in cancer using the Asian prevalent cancer type hepatocellular carcinoma (HCC) as a model system. We believe that targeting cancer stem cells is a new venture for precision medicine in oncology. Our current goals are to establish new molecular signatures and markers for predicting the occurrence, recurrence, and drug resistance, to improve patient stratification, and identify actionable targets directed at cancer stemness for precision medicine.
For more information or to express interest for this project, please email the supervisor or the specified contact point in the project description. Interested candidates are advised to enclose with your email:
Information on the research programme, funding support and admission documentations could be referenced online at the Research Postgraduate Admissions website. General admission enquiries should be directed to email@example.com.
HKUMed MBBS students interested in the Master of Research in Medicine (MRes[Med]) programme may visit the programme website for more information.
HKUMed UG students interested in the Undergraduate Research Internship Scheme (URIS) may visit the scheme’s website for more information.