Early diagnosis of cancer is essential for improving the survival rate of cancer patients. However, the research on molecular diagnosis of early cancer is still challenging, facing hurdles of low accuracy as well as complicated procedures. Thus, it is crucial to develop a new generation of technology for early cancer diagnosis.
Da Han, a professor at the Institute of Molecular Medicine, Shanghai Jiao Tong University School of Medicine, focuses on the elucidation of the physicochemical principles governing the nucleic acid molecules and the development of “intelligent” molecular tools that can perform diagnostic and therapeutic functions. Da’s work realized the early diagnosis of cancer using DNA molecular computation, which has drawn great attention from researchers all around the world.
Da’s interdisciplinary education and working experiences inspired him to explore the junctions of two research fields of computing and bioengineering. He completed his doctoral studies under the supervision of Dr. Weihong Tan at the University of Florida, focusing on bioanalytical sensing. Before founding his own research group in Shanghai Jiao Tong University, Da had worked at Intel as a Technology Development Process Engineer for four years. He then chose to integrate his experiences in computing and sensing principles to study molecular diagnosis based on DNA computation.
Da Han designed a DNA molecular computation platform for the analysis of miRNA profiles and achieved rapid and accurate cancer diagnosis using clinical serum samples with an accuracy of 86.4%. This is the first example that uses DNA molecular computation for cancer diagnosis without manual intervention and complicated instruments in blood samples. Moreover, it will open the doors of using the power of DNA computation towards low-cost, non-invasive, and routine early cancer screening and classification, as well as monitoring cancer recurrence.
Da Han’s next research goal is focusing on expanding the sizes of clinical samples, which will further verify the diagnostic accuracy of this DNA computing platform and promote the clinical translation of this novel diagnostic method.