{"doi":"10.1021/acs.jproteome.1c00175","title":"A Panel of Glycopeptides as Candidate Biomarkers for Early Diagnosis of NASH Hepatocellular Carcinoma Using a Stepped HCD Method and PRM Evaluation","abstract":"Changes in N-glycosylation on specific peptide sites of serum proteins have been investigated as potential markers for diagnosis of nonalcoholic steatohepatitis (NASH)-related HCC. To accomplish this work, a novel workflow involving broad-scale marker discovery in serum followed by targeted marker evaluation of these glycopeptides were combined. The workflow involved an LC-Stepped HCD-DDA-MS/MS method coupled with offline peptide fractionation for large-scale identification of N-glycopeptides directly from pooled serum samples (each n = 10) as well as differential determination of N-glycosylation changes between disease states. We then evaluated several potentially diagnostic N-glycopeptides among 78 individual patient samples (40 cirrhosis, 28 early stage NASH HCC, and 10 late-stage NASH HCC) by LC-Stepped HCD-PRM-MS/MS to quantitatively analyze 65 targeted glycopeptides from 7 glycoproteins. Of these targets, we found site-specific N-glycopeptides n169GSLFAFR_HexNAc(4)Hex(5)NeuAc(2) and n242ISDGFDGIPDNVDAALALPAHSYSGR_HexNAc(5)Hex(6)Fuc(1)NeuAc(3) from VTNC were significantly increased comparing samples from patients with NASH cirrhosis and NASH HCC (p < 0.05). When combining results of these 2 glycopeptides with AFP, the ROC curve analysis demonstrated the AUC value increased to 0.834 (95% CI, 0.748–0.921) and 0.847 (95% CI, 0.766–0.932), respectively, as compared to that of AFP alone (AUC = 0.791, 95% CI, 0.690–0.892). These 2 glycopeptides may serve as potential biomarkers for early HCC diagnosis in patients with NASH related cirrhosis.","journal":"Journal of Proteome Research","year":2021,"id":166210,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":34,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9529,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":348902,"name":"Jianhui Zhu","orcid":"0000-0002-0051-7777","position":1,"is_corresponding":false},{"id":691755,"name":"Lingyun Pan","orcid":null,"position":2,"is_corresponding":false},{"id":348904,"name":"Jie Zhang","orcid":"0000-0002-1395-4853","position":3,"is_corresponding":false},{"id":411769,"name":"Zhijing Tan","orcid":"0000-0003-3618-5388","position":4,"is_corresponding":false},{"id":386697,"name":"Jocelyn Olivares","orcid":null,"position":5,"is_corresponding":false},{"id":106840,"name":"Amit G. Singal","orcid":"0000-0002-1172-3971","position":6,"is_corresponding":false},{"id":233439,"name":"Neehar D. Parikh","orcid":"0000-0002-5874-9933","position":7,"is_corresponding":false},{"id":348908,"name":"David M. Lubman","orcid":"0000-0001-7731-0232","position":8,"is_corresponding":false},{"id":477502,"name":"Yu Lin","orcid":"0000-0001-6579-484X","position":0,"is_corresponding":true}],"reference_count":50,"raw_metadata":null,"created_at":"2026-07-18T23:45:45.220559Z","pmid":"33929864","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}