Email

bing.zhang@bcm.edu

Positions

Professor

Lester and Sue Smith Breast Center
Baylor College of Medicine
Houston, TX US

Professor

Department of Molecular and Human Genetics
Baylor College of Medicine

Member

Dan L Duncan Comprehensive Cancer Center
Baylor College of Medicine
Houston, Texas United States

McNair Scholar

Baylor College of Medicine
Houston, Texas United States

Addresses

BCM-Jewish Building (Office)

Room: 648D
Houston, TX 77030
United States
Phone: (713) 798-1443
bing.zhang@bcm.edu

Education

BS from Nanjing University

Nanjing, China

PhD from Chinese Academy of Sciences

Shanghai, China

Postdoctoral Training at Oak Ridge National Laboratory

Oak Ridge, Tennessee United States

Honors & Awards

CPRIT Scholar in Cancer Research

Cancer Prevention Research Institute of Texas (09/2016 - 08/2021)

McNair Scholar

McNair Medical Institute (08/2016 - 07/2024)

Professional Interests

• Bioinformatics
• Systems biology
• Precision oncology

Professional Statement

The long-term goal of my research is to develop computational and statistical methods and tools that help translate cancer omics data into better diagnosis, prognosis and treatment of human cancer. Current work in my laboratory focuses on the integrative analysis of cancer proteomics and genomics data, a new research field named cancer proteogenomics. Proteins are the functional units in the cell and primary drug targets; however, we know very little about cancer proteomes. Through participating in the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC), my lab has developed several novel methods and tools for the integrative analysis of cancer genomic and proteomic data (Wang et al., 2012; Shi et al., 2013; Wang et al., 2017; Vasaikar et al., 2018; Wen et al., 2019). We led two CPTAC colon cancer studies (Zhang et al., 2014; Vasaikar et al., 2019), demonstrating the power of proteogenomics in revealing new cancer drivers and vulnerabilities inaccessible from genomic assessment alone. Our methods have also been used in the CPTAC breast and ovarian cancer studies (Mertins et al., 2016; Zhang et al., 2016).

Success of these studies have led to the expansion of the CPTAC program to more cancer types. I am now leading a CPTAC data analysis center at BCM, with first-hand access to all genomics and proteomics data generated on these new cancer types. We also have close collaboration with cancer biologists and clinicians to experimentally validate our computational predictions in cell lines, patient-derived xenografts (PDXs) and clinical trials.

With access to these data and collaborations, my group is working on three key challenges. First, can we use these data to better predict cancer patient survival and treatment response? Second, can we use these data to find more effective treatment strategies? Third, can we make these data easily accessible and useful to cancer researchers without programming skills?

Websites

Selected Publications

• Vasaikar S, Huang C, Wang X, Petyuk VA, Savage SR, Wen B, Dou Y, Zhang Y, Shi Z, Arshad OA, Gritsenko MA, Zimmerman LJ, McDermott JE, …... Ellis M, Thiagarajan M, Kinsinger CR, Rodriguez H, Smith RD, Rodland KD, Liebler DC, Liu T, Zhang B, CPTAC "Proteogenomic analysis of human colon cancer reveals new therapeutic opportunities." Cell. 2019;177:1035-1049.
• Zhang B, Wang J, Wang X, Zhu J, Liu Q, Shi Z, Chambers MC, Zimmerman LJ, Shaddox KF, Kim S, Davies SR, Wang S, Wang P, Kinsinger CR, Rivers RC, Rodriguez H, Townsend RR, Ellis MJ, Carr SA, Tabb DL, Coffey RJ, Slebos RJ, Liebler DC, CPTAC "Proteogenomic characterization of human colon and rectal cancer." Nature. 2014;513:382-387.
• Vasaikar SV, Straub P, Wang J, Zhang B "LinkedOmics: analyzing multi-omics data within and across 32 cancer types." Nucleic Acids Res. 2018;46:D956-D963.
• Wen B, Wang X, Zhang B "PepQuery enables fast, accurate, and convenient proteomic validation of novel genomic alterations." Genome Res. 2019;29:485-493.

Funding

IPGDAC, an integrative proteogenomic data analysis center for CPTAC

NIH/NCI

Proteogenomics-driven therapeutic discovery in hepatocellular carcinoma

NIH/NCI

Leveraging multi-omics data to improve cancer treatment

CPRIT

Identification of tumor subtype-specific cell surface receptors and candidate neoantigens

Bristol-Myers Squibb