Dr. Feixiong Cheng
Cleveland Clinic Genomic Medicine Institute, Cleveland, OH, USA
Feixiong Cheng, PhD, is a principal investigator with Cleveland Clinic’s Genomic Medicine Institute. Dr. Cheng is a computational biologist by training, with expertise in analyzing, visualizing, and mining data from real world (e.g., electronic health records, and health care claims) and experiments that profile the molecular state of human cells and tissues by interactomics, transcriptomics, genomics, proteomics, and metabolomics for drug discovery and precision patient care. Dr. Cheng is working to develop computational and experimental network medicine technologies for advancing the characterization of disease heterogeneity, thereby approaching the goal of coordinated, patient-centered strategies to innovative diagnostics and therapeutics development.
The primary goal of Dr. Cheng’s lab is to combine tools from genomics, network medicine, bioinformatics, computational biology, chemical biology, and experimental pharmacology and systems biology assays (e.g., single cell sequencing and iPS-derived cardiomyocytes), to address the challenging questions toward understanding of various human complex diseases (e.g., cardio-oncology, pulmonary vascular diseases, and cancer), which could have a major impact in identifying novel real-world data-driven diagnostic biomarkers and therapeutic targets for precision medicine.
From 2013 to 2017, Dr. Cheng was trained as Postdoctoral Research Fellow in the field of pharmacogenomics and network medicine across Vanderbilt University Medical Center, Northeastern University, and Dana-Farber Cancer Institute. During 2017-2018, Dr. Cheng was promoted to Research Assistant Professor working with two of the world’s leading experts in the field of network medicine, Drs. Albert-Laszlo Barabasi and Joseph Loscalzo, with dual appointment at Northeastern University and Harvard Medical School. Dr. Cheng has received several awards, including NIH Pathway to Independence Award (K99/R00), SCI highly cited papers reward, and Vanderbilt Postdoc of the Year Honorable mention.
Session 4: DRUG REPURPOSING AND NETWORK MEDICINE
DAY 3: September 13, 2019 | 10:10 AM - 10:30 AM
Network-Based Analysis to Prioritize Metabolic Interventions in Patients With Anthracycline-Induced Cardiac Dysfunction
Feixiong Cheng, PhD, Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH
There are over 15.5 million cancer survivors in the United States (U.S.); furthermore, cardiovascular disease is the second leading cause of mortality and morbidity in cancer survivors after recurrent malignancy. Comorbidity between cardiovascular disease and cancer suggests an underlying shared disease etiologies, including genetic and environmental. One critical issue is that comorbidity is typically associated with various cancer treatments, such as anthracycline-induced cardiac dysfunction (doxorubicin [Dox]). However, there are no guidelines in terms of how to prevent and treat the new cardiac dysfunction in cancer survivors. Metabolic interventions play crucial roles in the reduced risk of cancer and heart diseases. However, traditional nutritional epidemiological approaches have limited success without consideration of confounding factors. In this study, we developed a network-based methodology for cardio-oncology that focuses on screening, monitoring, and treating anthracycline-related heart failure. Specifically, we built an integrative network model which incorporates multi-omics profiles into the human protein-protein interactome. These multi-omics data include transcriptomics from human induced pluripotent stem cell-derived cardiomyocytes, metabolomics from Dox-induced heart failure rat models, and large-scale echocardiogram data from Cleveland Clinic Epic database. Via network analysis, we identified that several novel metabolic pathways (i.e., AMPK signaling pathway) were significantly associated with Dox-related cardiac dysfunction. Pharmacologic intervention of the dysregulated metabolic pathways reveals potential protective effect for Dox-related cardiac dysfunction. In summary, this highly integrative network methodology will thereby approach the goal of translating rapidly metabolic intervention for anthracycline-induced cardiovascular complications.