Understanding NPC Molecular Subtypes Associated with Clinical Outcome and Their Impact on Tumor Microenvironment


Grant Data
Project Title
Understanding NPC Molecular Subtypes Associated with Clinical Outcome and Their Impact on Tumor Microenvironment
Principal Investigator
Dr Dai, Wei   (Principal Investigator (PI))
Co-Investigator(s)
Dr Lo Wing Ip Anthony   (Co-Investigator)
Dr Chan King Chi   (Co-Investigator)
Duration
36
Start Date
2022-01-01
Amount
1499988
Conference Title
Understanding NPC Molecular Subtypes Associated with Clinical Outcome and Their Impact on Tumor Microenvironment
Presentation Title
Keywords
EBV methylation, Homologous deficiency, Mutational signature, Nasopharyngeal carcinoma, Tumor microenvironment
Discipline
Others - Medicine, Dentistry and Health
HKU Project Code
08192296
Grant Type
Health and Medical Research Fund - Full Grant
Funding Year
2020
Status
On-going
Objectives
Objectives: Our aim is to identify the NPC molecular subtypes by genomic and transcriptomic approaches associated with early disease progression and to explore the potential therapeutic targets for NPC treatment. Hypothesis to be tested: The NPC patients with the BRCAness signature discovered in our recent study have more aggressive disease and may not respond well for the chemoradiotherapy treatment (CRT). The tumors with this signature have increased neoantigen load and more infiltrating cytotoxic T cells and increased PD-1/PDL-1 expression. Design and Subjects: Sixty NPC patients will be included in this study including 30 patients with poor outcomes with disease progression (recurrence/metastasis) within one year of treatment and 30 age/gender matched patients with a good outcome with disease-free survival (DFS) for at least 5 years after treatment. The whole-exome sequencing (WES), RNA sequencing, bisulfite pyrosequencing and multiplex immunohistochemistry (mIHC) approaches will be utilized. Instruments: Equipment includes the Covaris, Quibt, Bioanalyzer, Thermal cycler, Illumina NovalSeq platform, high performance computing facility, Vectra Multispectral imaging system etc. Interventions: NA Main outcome measures: NA Data Analysis: Multiple benchmark open-source bioinformatics tools will be applied for the analysis. Comparison will be made between the good/poor survival groups. Correlation between the BRCAness signature and EBV methylation will be evaluated. The immune cell populations and PD-1/PDL-1 expression will be compared between the signature-positive and -negative groups. Expected Results: We expect to confirm the association between BRCAness signature and early disease progression, identify other novel molecular subtypes associated with clinical outcomes, and explore the potential therapeutic targets for NPC.