# Discovery and Validation of Biomarkers for Early Cancer Detection Using Mass Spectrometry > **NIH NIH R50** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2020 · $62,907 ## Abstract Abstract: I have been conducting cancer research projects in discovery of clinically relevant cancer biomarkers in the Laboratory of Cancer Proteomics at the University of Michigan Medical Center for eight years. Over the years, I have been engaged in research projects to develop mass spectrometry (MS)-based methods and assays to identify and validate protein markers in patient blood and tissues for early detection of HCC and pancreatic cancer. These projects have been supported by NCI based RO1 and R21 grants that are either from Dr. Lubman, the laboratory director, or from our collaborators. I have made significant contributions to these research programs and have authored and co-authored 24 peer-reviewed articles related to these projects. My major contributions include: 1) developed a high-throughput 96-well plate platform for glycan extraction and processes for a large number of samples, with a combination of MS-based assays for quantitation of changes in glycan structures that can be used as markers for cancer; 2) established an automated HPLC-based column immobilized with specific antibody for high-purity, single step enrichment of target glycoproteins from serum for subsequent glycomic/glycoproteomic analyses; 3) developed a quantitative MS method to detect fucosylated glycans at low levels in target serum glycoproteins by utilizing a novel labeling reagent; 4) built an innovative strategy of isobaric protein-level labeling for serum glycoprotein quantification analysis by nano LC-MS/MS. I am currently involved in the NCI-funded program of `Serum Glyco-Markers of Early HCC, where a phase II validation study of serum bifucosylated haptoglobin for early detection of HCC on an EDRN blinded set of 760 serum samples is in progress. Under this award, I will continue to develop novel methods and strategies in glycomics and glycoproteomics for discovery of cancer glyco-biomarkers on archived serum samples, which include: 1) to develop a new method to identify core- fucosylated glycopeptides in serum glycoproteins involved in the development of HCC and then screen for these specific glycopeptides among HCC and cirrhosis patients using MRM-MS; 2) to develop a large-scale intact N- glycopeptide analysis in low-abundant serum glycoproteins using LC-EThcD-MS/MS to uncover unique changes of site-specific serum N-glycopeptides correlated with HCC; 3) to identify site-specific glycan changes as well as sialylation aberrations in target serum glycoproteins that are highly associated with HCC using HILIC- LC-MS/MS and PGC-LC-MS/MS, respectively. I will also expand my research to develop an exosome-based MS assay for discovery of unique changes in glycans/site-specific N-glycopeptides in serum-derived exosomes between HCC and cirrhosis patients and to apply these methods for identification and validation of potential glyco-markers in other types of cancer. These methods provide new strategies for detection and accurate quantitation of detailed changes in gl... ## Key facts - **NIH application ID:** 9981683 - **Project number:** 5R50CA221808-03 - **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR - **Principal Investigator:** Jianhui Zhu - **Activity code:** R50 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $62,907 - **Award type:** 5 - **Project period:** 2018-09-13 → 2021-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/9981683 ## Citation > US National Institutes of Health, RePORTER application 9981683, Discovery and Validation of Biomarkers for Early Cancer Detection Using Mass Spectrometry (5R50CA221808-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9981683. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*