Developing the Mass Spectrometry-Based Multi-Omics Technologies for Exploring the Energy Metabolism Pathways of Renal Cancer and Clinical Applications

About five hundreds of Taiwanese die due to kidney cancer ever year. The most common one is renal cell carcinoma (RCC) which accounts for 60-70% of cases. However, many of symptoms caused by RCC are non-specific and may relate to a non-cancerous kidney or urinary tract problem. Patients are often (~30%) diagnosed at the metastatic stage with a poor prognosis results. A systematic analysis of the molecular pathways dysregulated in kidney cancer will be helpful to gain a better understanding of the driving force of the disease and will form the basis for the development of novel marker panels and targeted therapies. Post-genomic research methods including transcriptomics, proteomics and metabolomics are becoming increasingly important in modern biological research. Integration the omic-changes from multiple fields is expected to benefit the understanding of disease initiation and progression comprehensively. Proteomic and metabolomics profiles are more dynamic which changes to reflect a cell’s environment than static genome. The analytical challenges of proteomics and metabolomics are relatively difficult compared to genomic platform, particularly high-through and multiplex quantification of novel proteins and metabolites. Our previous work using shotgun proteomics revealed the up-expression of glycolysis pathway and suppressed expressions of multiple proteins involved in oxidative phosphorylation, now referred as the Warburg effect, than normal cells. It is now believed that the old biology has been neglected for over 30 years and be revitalized in recent literatures. It is also concluded that Warburg effect might be only the tip of iceberg with multiple metabolic changes during malignant transformation. Although kidney is now considered to be a disease caused by multiple dysregulated cell metabolism. However, little attention has been emphasized to patient-specific differences, integration of multi-omics data, and relevance in clinical outcomes. With the advances in high through-put and mutiplexable analytical platforms (MRM-MS and AIMS), we plan to switch the focus from the individual gene for biomarker discovery to exploring the post-genomic products (proteins and metabolites) changes involved in energy metabolism pathways for understanding the initiation and progression of renal cancer. The analytical platform will be developed in the project using isotopic dimethylation for proteins and isotopic dansylation for metabolites. We plan to analyze 40 and 30 proteins associated with oxidative phosphorylation and glycolysis pathways, respectively. Each protein will be quantified according two signature peptides. Nine and seven metabolites associated with oxidative phosphorylation and glycolysis pathways, respectively, will be selected as target metabolites for assay development as well. The expression differences of energy metabolic pathways between one normal renal cell line and three cancer cell line models will be compared. The platform will be applied to measure the clinical cancer and adjacent normal tissue specimens of thirty RCC patients to explore the relevance of dysregulation in energy metabolome with clinical outcomes. We expect the established quantitative method and information will be useful to profile the abnormalities of energy metabolic pathways in RCC and provide an opportunity for cancer therapy. The pathway map constructed by this project in clinical specimens can provide more insight than limited sub-network biomarkers.

Project ID:PA10406-1337
External Project ID:MOST104-2113-M182-001-MY2