Emerging biomarkers for precision cancer medicine: Discovery, validation and clinical application
Dr. Jian-Hua Mao
Lawrence Berkeley National Laboratory / University of California [Berkeley, USA]
The advent of biotechnologies, especially next-generation sequencing, has extensively cataloged the multi-omics landscape of human cancer, which has deepened insights into its heterogeneity and expanded our understanding of the disease. This growing understanding of patient-to-patient variability at the genomic level in human cancer is advancing our ability to direct the appropriate treatment to the appropriate patient at the appropriate time - a hallmark of "precision cancer medicine". Precision cancer medicine is based on improved clinical or non-clinical methods (including biomarkers) for a more discriminating and precise diagnosis of diseases; targeted therapies of the choice or the best drug for each patient among those available; dose adjustment methods to optimize the benefit-risk ratio of the drugs chosen; and biomarkers of efficacy, toxicity, treatment discontinuation, relapse, etc. Therefore, the predictive biomarkers are an urgent need. Utilizing multi-omics data together with biological and functional studies, we rediscover the genes that play critical roles in cancer, and develop biomarker assays to support precision medicine patient selection strategies. Additionally, we use the mouse population-based and cross-species approach to identify potential biomarkers and therapeutic targets which could lead to development of new and more effective treatments. In summary, the discovery of cancer genes can lead to screen for at-risk individuals, biomarkers for early diagnosis, prognosis and therapeutic responses towards precision cancer medicine.