However, the utility of LPA as a biomarker has not been completely tapped for certain discrepancies. According to Prof Wenk, there is a need for a better method to detect and diagnose cancers, and lipidomics analysis could bring revolution in the diagnosis of ovarian cancer at an early stage.

Prof Wenk and his team at NUS have developed a mass spectrometry technology that provides classification between healthy cell and diseased cell and further classification of benign cell and malign cell. Prof Wenk says the technology is capable of distinguishing an early-stage cancer from a late-stage cancer and whether a sample is cancerous or normal. The invention employs conventional techniques of chemistry, molecular biology, microbiology, recombinant DNA and immunology. In the method, the team creates assay of concentration of sample derived from bodily fluids, such as blood, blood serum or extracts from tissue.

"Mass spectrometry technology performs generation process where a data set of lipid is characterized and analyzed. The objective of the study is not only to identify patients but also to separate the benign from the malignant. Currently, there is no available tool to identify the benign from the malignant unless the growth is surgically removed and sent for various pathological tests. Our research is able to do so and extrapolate the model to separate late from early stage of malignancy and the performance could be better than CA125," explains Prof Wenk.

"The strength of this method relies not only in using one set or class of biomarkers but a complete profile, and then use it as a diagnostic tool. The patient is relieved of the unwanted trauma of going through a surgery for such a small sample," he adds.

Application
Prof Wenk and his team are focusing on developing novel lipid-based biomarkers for the early detection of a wide range of diseases apart from ovarian cancer, such as gastric cancers, neurodegenerative deases, Alzheimer's disease, stroke and schizophrenia, inflammatory disorders, infectious diseases such as tuberculosis and dengue fever.