A serum Biomarker model to diagnose pancreatic cancer using proteomic fingerprint technology

Serum α2,6-sialylated glycoform of serotransferrin as a glycobiomarker for diagnosis and prediction of clinical severity in cholangiocarcinoma

BACKGROUND

Glycoprotein sialylation changes are associated with severe development of various cancers. We previously discovered the sialylation of serotransferrin (TF) in cholangiocarcinoma (CCA) using glycoproteomics approach. However, a simple and reliable method for validating sialylation of a specific glycobiomarker is urgently needed.

METHODS

We identified the altered glycosylation in CCA tissues by glycoproteomics approach using mass spectrometry. An enzyme-linked lectin assay (ELLA) was developed for determining the serum levels of sialylated TF in CCA, hepatocellular carcinoma (HCC) and healthy controls in training and validation cohorts.

RESULTS

The nine highly sialylated glycoforms of TF were markedly abundant in CCA tumor tissues than in control. Serum SNA-TF and MAL1-TF were significantly higher in CCA patients. Under receiver operating characteristic curve, serum SNA-TF concentrations significantly differentiated CCA from healthy control. Higher SNA-TF were significantly correlated with severe tumor stages and lymph node metastasis. The combined SNA-TF, MAL1-TF, and CA19-9 as a novel glycobiomarkers panel demonstrated the highest specificity (96.2%) for distinguishing CCA from HCC patients. In CCA patients with low CA19-9 levels, SNA-TF in combination with CA19-9 achieved in 97% diagnostic accuracy.

CONCLUSIONS

Sialylated serotransferrin glycoforms could be used as a novel glycobiomarker for diagnosis and prediction of clinical severity in CCA patients.

S100A9, GIF and AAT as potential combinatorial biomarkers in gastric cancer diagnosis and prognosis

PURPOSE

We have mined the gastric fluid proteome for potential gastric cancer (GC) biomarkers that may enhance disease detection and facilitate prognostic monitoring.

EXPERIMENTAL DESIGN

In biomarker discovery, a total of 12 patient gastric fluid samples (stages I, III, IV and gastritis) were analysed by 2DE for expression changes that correlated with GC status or disease progression. Gastric fluid proteins showing differential expression with GC were identified by MALDI-TOF/TOF MS as putative biomarkers. Levels of these potential biomarker candidates were independently validated by Western blotting in further 60 gastritis and GC patients. A targeted approach that recruits biomarker candidates for panel consideration was adopted to test if two or more biomarkers in combination improved diagnostic power.

RESULTS

From the 15 differentially regulated proteins identified, expression levels of S100A9, GIF and AAT in the gastric fluid clearly correlated with GC status. S100A9/AAT (AUC = 0.81) and S100A9/GIF (AUC = 0.92) were revealed as promising biomarker pairs for early GC diagnosis and disease monitoring, respectively.

CONCLUSION AND CLINICAL RELEVANCE

Early diagnosis, accurate staging and constant disease monitoring remain the prerequisites for effective treatment against GC. As current biomarkers like CA19-9 and carcinoembryonic antigen (CEA) lack sensitivity and specificity, there is a pressing need for novel GC detection and monitoring methods. To this end, S100A9, GIF and AAT from the gastric fluid may significantly augment existing methods of GC detection and monitoring, and eliminate the need for invasive tissue biopsies.