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BackgroundOvarian cancer is one of the most lethal gynecological malignancies, in which platinum resistance is a common cause of its relapse and death. Glycosylation has been reported to be involved in drug resistance, and glycomic analyses of ovarian cancer may improve our understanding of the mechanisms underlying cancer cell drug resistance and provide potential biomarkers and therapeutic targets.MethodsThe serous ovarian cancer cell line A2780 and its platinum-resistant counterpart A2780-cp were used in this study. We performed a lectin array analysis to compare the glycosylation patterns of the two cell lines, a gene expression array was employed to probe the differences in glycogenes. Furthermore, the results were verified by lectin blots.ResultsA2780-cp cell exhibited stronger intensities of Lens culinaris (LCA) Canavalia ensiformis (ConA), and Lycopersicon esculentum (LEL) and weaker intensities of Sambucus nigra (SNA) lectins. The gene expression array analysis revealed increased expression of Fut8, B3gnt4, B3gnt5, B4galt2 and decreased expression of Fut1 and ST6GalNAc 6 expression were evident in the A2780-cp cells. The lectin blot confirmed the differences in LCA, ConA, SNA and LEL between the A2780 and A2780-cp cells.ConclusionsThe combination of the lectin and gene expression analyses showed that the levels of core fucosylation and poly-LacNAc were increased in the A2780-cp cells and the levels of Fuc α1-2(gal β1-4) GlcNAc and α2-6-linked sialic structures were decreased in the A2780-cp cells. These glycans represent potential biomarkers and might be involved in the mechanism of drug resistance in ovarian cancer.Electronic supplementary materialThe online version of this article (doi:10.1186/s12014-017-9155-z) contains supplementary material, which is available to authorized users.

Background : Peritoneal metastasis, associated with poor prognosis in gastric cancer, is difficult to discriminate from advanced gastric cancer preoperatively. However, operative diagnosis could bring both mental and physical trauma and economic burden for patients. Consequently, a non-invasive biomarker is necessary to reduce the burden of operative diagnosis and improve survival quality of patients. This study aims to elucidate the correlation between Immunoglobulin G (IgG) N-glycome and peritoneal metastasis and find potential biomarkers in preoperative discrimination of peritoneal metastasis from advanced gastric cancer based on the comprehensive sample set. Methods : A total of 373 gastric cancer patients were enrolled and randomly sorted into training cohort (n=249) and validation cohort (n=124). The IgG N-glycome composition was analyzed by ultra-performance liquid chromatography. Results : Twenty-four glycan peaks were directly detected and 15 traits based on the same structures were evaluated between peritoneal metastasis group and advanced gastric cancer group. Several differences in IgG glycosylation were found: sialylation and fucosylation were increased in peritoneal metastasis, while neutral glycosylation, monogalacosylation and bisecting GlcNAc were decreased. Based on the significant glycomics profile, a glyco-model composed of five glycan peaks (GP6, GP9, GP11, GP21 and GP23) was established with area under the receiver operating characteristic curve (AUC) value of 0.80 (training cohort) and 0.77 (validation cohort), which showed good potential in discriminating peritoneal metastasis from advanced gastric cancer. The diagnostic performance of this model was further validated in a combined cohort (AUC=0.79). Two patients with gastric cancer were selected to perform and demonstrate the usage of the diagnostic workflow. Conclusions : Here we firstly present IgG glycome profiles in a large number of preoperative peritoneal metastasis serums. The IgG glycan was highly associated with peritoneal metastasis. These findings enhance the understanding of peritoneal metastasis. Besides, our results suggested that the newly established glyco-model could be a reliable predictor of the presence of peritoneal metastasis in patients with advanced gastric cancer.

Purpose: Gastric cancer (GC), one of the world's top five most common cancers, is the third leading cause of cancer related death. It is urgent to identify non-invasive biomarkers for GC. The objective of our study was to find out non-invasive biomarkers for early detection and surveillance of GC based on glycomic analysis.Method: Ethyl esterification derivatization combined with MALDI-TOF MS analysis was employed for the comprehensive serum glycomic analysis in order to investigate glycan markers that would indicate the onset and progression of gastric cancer. Upon the discovery of the candidate biomarkers, those with great potential were further validated in an independent test set. Peaks were acquired by the software of MALDI-MS sample acquisition and processing and analyzed by the software of Progenesis MALDI. 
Results: The differences in glycosylation were found between non-cancer controls and gastric cancer samples: hybrid and multi-branched type (tri-, tetra-antennnary glycans) N-glycans were increased in GC, yet monoantennary, galactose, bisecting type and core fucose N-glycans were decreased. In training set, core fucose (AUC=0.923, 95%CI: 0.8485 to 0.9967) played an excellent diagnostic performance for the early detection of gastric cancer. The diagnostic potential of core fucose was further validated in an independent cohort (AUC=0.854, 95%CI: 0.7592 to 0.9483). Besides, several individual glycan structures reached both statistical criteria (p-values less than 0.05 and AUC scores that were at least moderately accurate) when comparing different stages of GC samples.Conclusion: We comprehensively evaluate the serum glycan changes in different stages of GC patients including peritoneal metastasis for the first time. We determined several N-glycan biomarkers, some of these have potential in distinguishing the early stage GC from healthy controls, and the others can help to monitor the progression of GC. The findings also enhance understanding of gastric cancer.

Background: Neoadjuvant chemotherapy (NACT) could improve prognosis and survival quality of patients with local advanced gastric cancer (LAGC) by providing an opportunity of radical operation for them. However, no effective method could predict the efficacy of NACT before surgery to avoid the potential toxicity, time-consuming and economic burden of ineffective chemotherapy. Some research has been investigated about the correlation between serum IgG glycosylation and gastric cancer, but the question of whether IgG glycome can reflect the tumor response to NACT is still unanswered. Method: Serum IgG glycome profiles were analyzed by Ultra Performance Liquid Chromatography in a cohort comprised of 49 LAGC patients of which 25 were categorized as belonging to the NACT response group and 24 patients were assigned to the non-response group. A logistic regression model was constructed to predict the response rate incorporating clinical features and differential N-glycans, while the precision of model was assessed by receiver operating characteristic (ROC) analysis. Results: IgG N-glycome analysis in pretreatment serum of LAGC patients comprises 24 directly detected glycans and 17 summarized traits. Compared with IgG glycans of non-response group, agalactosylated N-glycans increased while monosialylated N-glycans and digalactosylated N-glycans decreased in the response group. We constructed a model combining patients' age, histology, chemotherapy regimen, GP4(H3N4F1), GP6(H3N5F1), and GP18(H5N4F1S1), and ROC analysis showed this model has an accurate prediction of NACT response (AUC = 0.840) with the sensitivity of 64.00% and the specificity of 100%. Conclusion: We here firstly present the profiling of IgG N-glycans in pretreatment serum of LAGC. The alterations in IgG N-glycome may be personalized biomarkers to predict the response to NACT in LAGC and help to illustrate the relationship between immunity and effect of NACT.