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Assistant Professor

Yong Zeng

PhD, Xiamen University

Dr. Yong Zeng

yong.zeng@sri.utoronto.ca

416-480-6100 - ext: 63382

Publications

Location
Sunnybrook Health Sciences Centre
Address
2075 Bayview Avenue , Office S236, Toronto, Ontario Canada M4N 3M5
Research Interests
Cancer Diagnosis and Therapy, Cancer Mechanisms and Models, Data Science and Computational Biology, Stem Cells and Regenerative Medicine

At A Glance

  • Computational systems biology and translational multi-omics
  • AI-driven large-scale multi-omics integration and prediction
  • Liquid biopsy analytics for disease detection and monitoring
  • Cell-cell communication and microenvironment interactions
  • Gene regulatory networks and signaling pathways modeling

Short Bio

Dr. Yong Zeng is a Scientist at Sunnybrook Research Institute and an Assistant Professor at the University of Toronto. He received his PhD in Systems Engineering from Xiamen University, China, and completed postdoctoral training at the Princess Margaret Cancer Centre under the supervision of Dr. Hansen He, where he developed expertise in computational biology and multi-omics data integration. He subsequently served as an Affiliate Scientist in the Genetics and Epigenetics Program at Princess Margaret Cancer Centre, under the mentorship of Drs. Mathieu Lupien and Hansen He, where he co-led collaborative research initiatives in liquid biopsy, single-cell multi-omics, and translational cancer research.

Dr. Zeng leads a research program in computational systems biology and translational multi-omics. He develops computational pipelines, analytical frameworks, and machine learning approaches to integrate large-scale molecular datasets, uncover regulatory mechanisms and cellular interactions, and translate these discoveries into clinically actionable biomarkers, therapeutic targets, and precision medicine strategies. He has authored numerous publications in leading journals and is an inventor on multiple U.S. patents in cancer biomarker discovery and RNA biology.

Research Synopsis

The Zeng Lab develops computational and AI-driven approaches to understand how molecular and cellular systems drive disease progression, therapeutic response, and treatment resistance. Our research integrates bulk, single-cell, spatial, and liquid biopsy multi-omics data with machine learning, systems biology, and network modeling to uncover the mechanisms underlying complex diseases. By transforming large-scale molecular data into mechanistic and clinically actionable insights, we aim to improve disease diagnosis, patient stratification, and therapeutic decision-making.

A major focus of the lab is understanding how gene regulatory networks, signaling pathways, and cell–cell interactions govern cellular states and behavior in health and disease. We develop computational frameworks to define dynamic cellular states, reconstruct regulatory and signaling networks, model interactions between diseased cells and their microenvironment, and identify biomarkers and therapeutic targets from both tissue- and liquid-biospy-based molecular data. We are particularly interested in leveraging AI and multi-omics integration to enable early disease detection, disease monitoring, and precision therapeutic intervention.

Our long-term vision is to bridge computational innovation with precision medicine. Through close collaboration with experimental scientists, clinicians, and industry partners, we seek to develop predictive models and translational frameworks that advance personalized medicine and improve patient outcomes. The lab offers an interdisciplinary and collaborative training environment for students and fellows interested in computational biology, data science, systems biology, multi-omics, and translational research, with opportunities to work at the interface of computational innovation and real-world clinical impact.

Recent Publications

  1. Zeng Y+, ✉️, Abelman DD+, Singhawansa A, Cheng N, Fang Y, Main SC, Bell E, Ye W, Luo P, Wilson SL, Stutheit-Zhao EY, Wong D, Znassi N, Chen K, Mohanraj S, Sanz-Garcia E, Notta F, Ghanekar A, Awadalla P, Lok BH, Hoffman MM, Kim RH, Zadeh G, De Carvalho DD, Bratman SV, Lupien M✉️, Pugh TJ✉️, He HH✉️. A pan-cancer compendium of 1,294 plasma cell-free DNA methylomes and fragmentomes enabling multicancer detection. Nature Cancer. 2026 Feb;7(2):384-398.

  2. Zeng Y+, ✉️, Jain R+, Lam M+, Ahmed M, Guo H, Xu W, Zhong Y, Wei GH, Xu W✉️, He HH✉️. DNA methylation modulated genetic variant effect on gene transcriptional regulation. Genome Biology. 2023 Dec 8;24(1):285.

  3. Zeng Y ✉️, Ye W, Stutheit-Zhao EY, Han M, Bratman SV, Pugh TJ✉️, He HH✉️. MEDIPIPE: an automated and comprehensive pipeline for cfMeDIP-seq data quality control and analysis. Bioinformatics. 2023 Jul 1;39(7).

  4. Wang S+, Zeng Y+, Zhu L, Zhang M, Zhou L, Yang W, Luo W, Wang L, Liu Y, Zhu H, Xu X, Su P, Zhang X, Ahmed M, Chen W, Chen M, Chen S, Slobodyanyuk M, Xie Z, Guan J, Zhang W, Khan AA, Sakashita S, Liu N, Pham NA, Boutros PC, Ke Z, Moran MF, Cai Z, Cheng C, Yu J, Tsao MS✉️, He HH✉️. The N6-methyladenosine Epitranscriptomic Landscape of Lung Adenocarcinoma. Cancer Discovery. 2024 Nov 1;14(11):2279-2299.

  5. Wang S+, Gao S+, Zeng Y+, Zhu L, Mo Y, Wong CC, Bao Y, Su P, Zhai J, Wang L, Soares F, Xu X, Chen H, Hezaveh K, Ci X, He A, McGaha T, O'Brien C, Rottapel R, Kang W, Wu J, Zheng G, Cai Z, Yu J✉️, He HH✉️. N6-Methyladenosine Reader YTHDF1 Promotes ARHGEF2 Translation and RhoA Signaling in Colorectal Cancer. Gastroenterology. 2022 Apr;162(4):1183-1196.

  6. Xu X, Wang Y, Zhu H, Lam M, Luo W, Teng M, Liu Y, Guo WY, Aastha A, Xu X, Chen S, Ci X, Wang S, Zeng Y, Zhu G, Kislinger T, Lupien M, Tsao MS, He HH. METTL3-based epitranscriptomic editing screening identifies functional m(6)A sites in cancers. Nat Cancer. 2026 Mar;7(3):469-483.

  7. Xu X, Zhu H, Hugh-White R, Livingstone J, Eng S, Zeltser N, Wang Y, Pajdzik K, Chen S, Houlahan KE, Luo W, Liu S, Xu X, Sheng M, Guo WY, Arbet J, Song Y, Wang M, Zeng Y, Wang S, Zhu G, Gao T, Chen W, Ci X, Xu W, Xu K, Orain M, Picard V, Hovington H, Bergeron A, Lacombe L, Têtu B, Fradet Y, Lupien M, Wei GH, Koritzinsky M, Bristow RG, Fleshner NE, Wu X, Shao Y, He C, Berlin A, van der Kwast T, Leong H, Boutros PC, He HH. The landscape of N(6)-methyladenosine in localized primary prostate cancer. Nat Genet. 2025 Apr;57(4):934-948.

  8. Su P, Liu Y, Chen T, Xue Y, Zeng Y, Zhu G, Chen S, Teng M, Ci X, Guo M, He MY, Hao J, Chu V, Xu W, Wang S, Mehdipour P, Xu X, Marhon SA, Soares F, Pham NA, Wu BX, Her PH, Feng S, Alshamlan N, Khalil M, Krishnan R, Yu F, Chen C, Burrows F, Hakem R, Lupien M, Harding S, Lok BH, O'Brien C, Berlin A, De Carvalho DD, Brooks DG, Schramek D, Tsao MS, He HH. In vivo CRISPR screens identify a dual function of MEN1 in regulating tumor-microenvironment interactions. Nat Genet. 2024 Sep;56(9):1890-1902.

  9. Chen S, Petricca J, Ye W, Guan J, Zeng Y, Cheng N, Gong L, Shen SY, Hua JT, Crumbaker M, Fraser M, Liu S, Bratman SV, van der Kwast T, Pugh T, Joshua AM, De Carvalho DD, Chi KN, Awadalla P, Ji G, Feng F, Wyatt AW, He HH. The cell-free DNA methylome captures distinctions between localized and metastatic prostate tumors. Nat Commun. 2022 Oct 29;13(1):6467.

  10. Chen S, Huang V, Xu X, Livingstone J, Soares F, Jeon J, Zeng Y, Hua JT, Petricca J, Guo H, Wang M, Yousif F, Zhang Y, Donmez N, Ahmed M, Volik S, Lapuk A, Chua MLK, Heisler LE, Foucal A, Fox NS, Fraser M, Bhandari V, Shiah YJ, Guan J, Li J, Orain M, Picard V, Hovington H, Bergeron A, Lacombe L, Fradet Y, Têtu B, Liu S, Feng F, Wu X, Shao YW, Komor MA, Sahinalp C, Collins C, Hoogstrate Y, de Jong M, Fijneman RJA, Fei T, Jenster G, van der Kwast T, Bristow RG, Boutros PC, He HH. Widespread and Functional RNA Circularization in Localized Prostate Cancer. Cell. 2019 Feb 7;176(4):831-843.e22.

Graduate Students

Faizan Hasan