Feixiong  Cheng,  PhD

Feixiong Cheng, PhD

Assistant Staff

Lerner Research Institute, 9500 Euclid Avenue, Cleveland, Ohio 44195
Location: NE5-209
Email: chengf@ccf.org
Phone: (216) 444-7654
Fax: (216) 636-0009

 


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 of 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.

Dr. Chen’s lab at Cleveland Clinic’s Genomic Medicine Institute has two major focus areas:

Building an Individualized Network Medicine Infrastructure for Precision Cardio-Oncology

The growing awareness of cardiac dysfunction by cancer treatment has led to the emerging field of Cardio-Oncology. However, there are no guidelines in terms of how to prevent and treat the new cardiotoxicity in cancer survivors due to the limited experimental assays. Network medicine – a discipline that seeks to redefine disease and therapeutics from an integrated perspective using systems biology and network science – offers a non-invasive way to identify actionable biomarkers for Cardio-Oncology. Supported by NIH Career Development Award (K99/R00), Dr. Cheng’s lab is working on developing state-of-the-art systems biology and network medicine approaches in Cardio-Oncology that focuses on screening, monitoring and treating cancer survivors with cardiac dysfunction resulting from cancer treatments. The central, unifying hypothesis is that an integrated, network-based, systems biology approach that incorporates not only genetic variations, but also gene expression, metabolomic, proteomic, interactomic (the human protein-protein interactome), radiomic, exposomic data and real-world data (e.g., patient longitudinal data), along with careful deep phenotypic data, will prove to be the most effective way to identify clinical actionable biomarkers and mechanisms responsible for Cardio-Oncology, thereby achieving the goal of coordinated, patient-centered strategies for treatment and long-term heart and vascular care (e.g., heart failure and pulmonary vascular disease) for cancer survivors.

Nodetic and Edgetic Network Perturbations in Personal Cancer Mutanomes

Although cancer is often described as a disease of the genome, it is perhaps more appropriate to describe cancer as a “disease of the interactome.” Cellular networks gradually rewire throughout cancer initiation, progression and maintenance, leading to progressive shifts of local and global network properties and systems states, all of which in turn underlie tumorigenesis and drug resistance. Dr. Cheng’s lab focuses on developing computational and experimental systems biology approaches to understand cancer biology and pharmacogenomics from the point-of-view of network perturbations: most genomic variants lead to both “nodetic and edgetic perturbations” of cellular network systems and tumorigenesis and drug responses results from the combined effect of multiple nodetic and edgetic perturbations in cancer cells.

In other words ...

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.


Cheng F, Nussinov R. KRAS Activating Signaling Triggers Arteriovenous Malformations. Trends Biochem Sci. 2018 Jul;43(7):481-483. 

Cai C, Fang J, Guo P, Wang Q, Hong H, Moslehi J, Cheng F. In Silico Pharmacoepidemiologic Evaluation of Drug-Induced Cardiovascular Complications Using Combined Classifiers. J Chem Inf Model. 2018 May 29;58(5):943-956.

Peng X, Chen Z, Farshidfar F, Xu X, Lorenzi PL, Wang Y, Cheng F, Tan L, Mojumdar K, Du D, Ge Z, Li J, Thomas GV, Birsoy K, Liu L, Zhang H, Zhao Z, Marchand C, Weinstein JN; Cancer Genome Atlas Research Network., Bathe OF, Liang H. Molecular Characterization and Clinical Relevance of Metabolic Expression Subtypes in Human Cancers. Cell Rep. 2018 Apr 3;23(1):255-269.e4.

Cheng F, Loscalzo J. Pulmonary Comorbidity in Lung Cancer. Trends Mol Med. 2018 Mar;24(3):239-241. doi: 10.1016/j.molmed.2018.01.005.

Wu Z, Lu W, Yu W, Wang T, Li W, Liu G, Zhang H, Pang X, Huang J, Liu M, Cheng F, Tang Y. Quantitative and systems pharmacology 2. In silico polypharmacology of G protein-coupled receptor ligands via network-based approaches. Pharmacol Res. 2018 Mar;129:400-413.

Zhao J, Cheng F, Jia P, Cox N, Denny JC, Zhao Z. An integrative functional genomics framework for effective identification of novel regulatory variants in genome-phenome studies. Genome Med. 2018 Jan 29;10(1):7. 

Fang J, Wu Z, Cai C, Wang Q, Tang Y, Cheng F. Quantitative and Systems Pharmacology. 1. In Silico Prediction of Drug-Target Interactions of Natural Products Enables New Targeted Cancer Therapy. J Chem Inf Model. 2017 Nov 27;57(11):2657-2671

Fang J, Gao L, Ma H, Wu Q, Wu T, Wu J, Wang Q, Cheng F. Quantitative and Systems Pharmacology 3. Network-Based Identification of New Targets for Natural Products Enables Potential Uses in Aging-Associated Disorders. Front Pharmacol. 2017 Oct 18;8:747.

Yu W, Lu W, Chen G, Cheng F, Su H, Chen Y, Liu M, Pang X. Inhibition of histone deacetylases sensitizes EGF receptor-TK inhibitor-resistant non-small-cell lung cancer cells to erlotinib in vitro and in vivo. Br J Pharmacol. 2017 Oct;174(20):3608-3622. 

Liu H, Zhao R, Fang H, Cheng F, Fu Y, Liu YY. Entropy-based consensus clustering for patient stratification.Bioinformatics. 2017 Sep 1;33(17):2691-2698.


Lu W, Cheng F, Yan W, Li X, Yao X, Song W, Liu M, Shen X, Jiang H, Chen J, Li J, Huang J. Selective targeting p53WT lung cancer cells harboring homozygous p53 Arg72 by an inhibitor of CypA. Oncogene. 2017 Aug 17;36(33):4719-4731.

Cheng F, Hong H, Yang S, Wei Y. Individualized network-based drug repositioning infrastructure for precision oncology in the panomics era. Brief Bioinform. 2017 Jul 1;18(4):682-697.

Hanker AB, Estrada MV, Bianchini G, Moore PD, Zhao J, Cheng F, Koch JP, Gianni L, Tyson DR, Sánchez V, Rexer BN, Sanders ME, Zhao Z, Stricker TP, Arteaga CL. Extracellular Matrix/Integrin Signaling Promotes Resistance to Combined Inhibition of HER2 and PI3K in HER2+ Breast Cancer. Cancer Res. 2017 Jun 15;77(12):3280-3292.

Zhao J, Cheng F, Zhao Z. Tissue-Specific Signaling Networks Rewired by Major Somatic Mutations in Human Cancer Revealed by Proteome-Wide Discovery. Cancer Res. 2017 Jun 1;77(11):2810-2821.

Fang J, Liu C, Wang Q, Lin P, Cheng F. In silico polypharmacology of natural products. Brief Bioinform. 2017 Apr 27.

Lu W, Yao X, Ouyang P, Dong N, Wu D, Jiang X, Wu Z, Zhang C, Xu Z, Tang Y, Zou S, Liu M, Li J, Zeng M, Lin P, Cheng F, Huang J. Drug Repurposing of Histone Deacetylase Inhibitors That Alleviate Neutrophilic Inflammation in Acute Lung Injury and Idiopathic Pulmonary Fibrosis via Inhibiting Leukotriene A4 Hydrolase and Blocking LTB4 Biosynthesis. J Med Chem. 2017 Mar 9;60(5):1817-1828.

Wu Z, Cheng F, Li J, Li W, Liu G, Tang Y. SDTNBI: an integrated network and chemoinformatics tool for systematic prediction of drug-target interactions and drug repositioning. Brief Bioinform. 2017 Mar 1;18(2):333-347.

Cheng F, Loscalzo J. Autoimmune Cardiotoxicity of Cancer Immunotherapy. Trends Immunol. 2017 Feb;38(2):77-78.

Shen Q, Cheng F, Song H, Lu W, Zhao J, An X, Liu M, Chen G, Zhao Z, Zhang J. Proteome-Scale Investigation of Protein Allosteric Regulation Perturbed by Somatic Mutations in 7,000 Cancer Genomes. Am J Hum Genet. 2017 Jan 5;100(1):5-20.

01/03/2019 |  

Personal Mutanomes Meet Precision Oncology

Thanks to remarkable scientific and technological advancements of late, researchers now have a deluge of sequencing data, which, with the right analysis, may help with the discovery and development of targeted cancer treatments. In a cover article published in Pharmacological Reviews, Cleveland Clinic’s Feixiong Cheng, PhD, Genomic Medicine, and collaborators review the current use of personal mutanomes in the discovery of modern oncology drugs, including therapies that are targeted to specific genomic or molecular profiles, as well as immunotherapies.