Jia Wu

Biomarkers that can stratify patients with clinical relevance are critically needed for precision medicine in the cancer field. However, spatial heterogeneity of molecular subpopulations within a tumor has posed critical challenges of biospecimen-derived metrics. By contrast, medical imaging captures a comprehensive macroscopic picture of tumor phenotype as well as its surrounding environment. Though imaging is used daily in oncology, e.g., clinical TNM stage, studies of intrinsic phenotypes are needed to explore rich imaging descriptors. With NIH K99 support, Dr. Wu has proposed innovative artificial intelligence pipelines to extract quantitative imaging features of the tumor and its adjacent parenchyma, and more importantly, these imaging markers are proven to be independent and complementary to the clinicopathologic and molecular marker. At MD Anderson, Dr. Wu directs a lab that focuses on addressing unmet clinical challenges of precision oncology through leveraging multidisciplinary knowledge, including artificial intelligence, medical image analysis, bioinformatics, and more. His research will be centered on developing useful radiologic markers with three general aims, with Aim 1 to discover clinically relevant radiologic patterns to assist cancer diagnosis, prognosis, and optimize treatment; Aim 2 to identify biological underpinnings of putative radiologic patterns through integrating with 'omic' and pathologic data; Aim 3 validate and translate the newly discovered radiologic markers into clinical practice to improve cancer patient management.