Dataset Information

Glycosylation Profiling of Neoplastic Biomarker Alpha Fetoprotein Through Intact Mass Protein Analysis

ABSTRACT: Alpha fetoprotein (AFP) is a circulating cancer biomarker implicated in multiple neoplastic malignancies, including hepatocellular carcinoma (HCC). AFP glycoforms with core fucosylation structure (AFP-L3) are used clinically as a biomarker, to predict risk of developing HCC and to monitor its recurrence. Mature AFP has a single glycosylation site, while there is a high degree of structural variation in AFP-glycan modifications. Because AFP has single glycosylation site, masses of intact AFP proteoforms can be used to differentiate and identify PTM in their native states. We developed a method for intact AFP glycoform analysis that utilizes AFP-specific immune-enrichment, followed by LC-high resolution mass spectrometry (LC-HRMS) analysis to differentiate and quantitate the relative abundance of AFP glycoforms and evaluated the method’s performance.

INSTRUMENT(S): 6550 iFunnel Q-TOF LC/MS

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Serum

SUBMITTER: Mark Kushnir

LAB HEAD: Yifei Yang

PROVIDER: PXD038606 | Pride | 2023-01-11

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	Sp_AFP_L3_1219-3_dilx4-1.d.zip	Other
	Sp_AFP_L3_1219-3_dilx4-1.xls	Xls
	Sp_AFP_L3_1219-3_dilx4-2.d.zip	Other
	Sp_AFP_L3_1219-3_dilx4-2.xls	Xls
	Sp_AFP_L3_1219-3_dilx4-3.d.zip	Other

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Publications

Glycosylation Profiling of the Neoplastic Biomarker Alpha Fetoprotein through Intact Mass Protein Analysis.

Dunbar Carmen C Kushnir Mark M MM Yang Yifei K YK

Journal of proteome research 20221221 1

Elevated serum alpha-fetoprotein (AFP) can be observed in liver cirrhosis and hepatocellular carcinoma (HCC). The glycosylation patterns of AFP have been shown to differentiate these conditions, with AFP glycoforms with core fucosylation (AFP-L3) serving as a malignancy risk predictor for HCC. We have developed a method to detect endogenously present AFP proteoforms and to quantify the relative abundance of AFP-L3 glycoforms (AFP-L3%) in serum samples. This method consists of immune enrichment o ...[more]

PMID: 36541409

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Project description:In cancer management, early and accurate diagnosis of hepatocellular carcinoma (HCC) is important for enhancing survival rate of patients. Currently, serum alpha-fetoprotein (AFP) is the only one biomarker for detection of HCC. However, serum AFP is not satisfactory for diagnosis of HCC due to its low accuracy (about 60-70%). In this study, we collected 109 serum samples (discovery set) from healthy control (HC) and patients with chronic hepatitis B (CHB), liver cirrhosis (LC) and HCC, and analyzed them with custom lncRNA microarray. Profiling analysis shows 181 differentially expressed lncRNAs between HCs and patients with CHB, LC and HCC. Then a 48-lncRNA diagnostic signature was identified with 100% predictive accuracy for all subjects in the discovery set. This diagnostic signature was verified with a cross-validation analysis in the discovery set. To further corroborate the signature, we gathered another 66 serum samples (validation set) and also analyzed them with microarray. The result indicates that the same signature has similar diagnostic accuracy for HC (100%), CHB (73%), LC (88%) and HCC (95%), implying a reproducible diagnostic biomarker for HCC. Receiver operating characteristic (ROC) analysis exhibits that this signature has significantly higher diagnostic accuracy for HCC and non-cancerous subjects (area under curve [AUC]: 0.994) than AFP (AUC: 0.773) in the discovery set and this was also verified in the validation set (0.964 vs 0.792). More importantly, the signature detected small HCC (<3cm) with 100% (13/13) accuracy while AFP with only 61.5% (8/13). Altogether, this study demonstrates that the serum 48-lncRNA signature is not only a powerful and sensitive biomarker for diagnosis of HCC but also a potential biomarker for LC. ***************************************************************** Submitter declares these data are subject to patent number ZL 2016 1 0397094. *****************************************************************