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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.

Background Peritoneal metastasis (PM) in gastric cancer (GC) remains an untreatable disease, and is difficult to diagnose preoperatively. Here, we aim to establish a novel prediction model. Methods The clinicopathologic characteristics of a cohort that included 86 non-metastatic GC patients and 43 PMGC patients from Zhongshan Hospital were retrospectively analysed to identify PM associated variables. Additionally, mass spectrometry and glycomic analysis were applied in the same cohort to find glycomic biomarkers in serum for the diagnosis of PM. A nomogram was established based on the associations between potential risk variables and PM. Results Overexpression of 4 N-glycans (H6N5L1E1: m/z 2620.93; H5N5F1E2: m/z 2650.98; H6N5E2, m/z 2666.96; H6N5L1E2, m/z 2940.08); weight loss ≥ 5 kg; tumour size ≥ 3 cm; signet ring cell or mucinous adenocarcinoma histology type; poor differentiation; diffuse or mixed Lauren classification; increased CA19-9, CA125, and CA724 levels; decreased lymphocyte count, haemoglobin, albumin, and pre-albumin levels were identified to be associated with PM. A nomogram that integrated with five independent risk factors (weight loss ≥ 5 kg, CA19-9 ≥ 37 U/mL, CA125 ≥ 35 U/mL, lymphocyte count Conclusions The nomogram achieved an individualized assessment of the risk of PM in GC patients; thus, the nomogram could be used to assist clinical decision-making before surgery.

Ovarian cancer is the most lethal gynecologic carcinoma; because the tumor often relapses shortly after treatment. Glycosylation plays important roles in cancer drug resistance and could be used as biomarkers to predict the drug response of patients. We used MALDI-QIT-TOF MS to analyze the serum glycomic from patients with different drug responses. Samples were collected before treatment; follow-up visit were performed after 6 months. Forty-eight drug-sensitive patients and 16 drug-resistant patients were enrolled. Compared with drug-sensitive patients, 5 glyco-subclasses and 5 single glycans were significantly altered in drug-resistant patients. Lewis type, α2,3 sialic acid and multibranch glycans were increased, α2,6 sialic acid glycans were decreased. The peak at m/z 2986.44 showed stronger prediction abilities than other single glycans, with an AUC of 0.83. A panel of three increased glycans (m/z 2401.36, H5N4F1S2, a Lewis type biantennary glycan; m/z 2986.44, H6N5S3, a triantennary trisialylated glycan; m/z 3086.39, H6N5F1S3, a Lewis type triantennary glycan) combined with CA125 achieved an AUC value of 0.88, showing a strong discrimination performance. This study provides new insights into N-glycosylation patterns in ovarian cancer patients with different drug response. These altered glycans might serve as biomarkers to reflect patients' drug sensitivity and to guide clinical treatment. Significance A large number of ovarian cancer patients experience tumor relapse shortly after initial treatment. Glycosylation plays important roles in cancer drug resistance and could be used as a biomarker to predict the drug response of patients. However, the glycosylation expressed in patients with different drug response have not been elucidated. In the present study, we used MALDI-QIT-TOF MS to analyze the serum glycomic levels of patients with different drug responses. Several glycans were changed significantly between these two groups. A panel of three increased glycans (m/z 2401.36, a Lewis type biantennary glycan, 2986.44, a triantennary trisialylated glycan, and 3086.39, a Lewis type triantennary glycan) combined with CA125 performed better descrimination of these two groups with AUC of 0.88. These altered glycans might serve as biomarkers to reflect patients' drug sensitivity and to guide clinical treatment.

Background: Although Carbohydrate antigen 19-9 (CA19-9) is considered clinically useful and informative for pancreatic carcinoma (PC), false positive results, and false negative results have restricted its clinical use. Especially missed or delayed diagnosis of PC patients with negative CA19-9 value limited the utility. To improve prognosis of PC patients, the discovery of reliable biomarkers to assist CA19-9 is desired. Serum IgG galactosylation based on our previous report was altered in PC patients comparing to healthy controls. The objective of this study was to explore the diagnostic significance of IgG galactosylation in assisting CA19-9 for PC in a comprehensive way. Methods: Serum IgG galactosylation profiles were analyzed by MALDI-MS in cohort 1 (n = 252) and cohort 2 in which all CA19-9 levels were negative (n = 133). In each cohort, not only healthy controls and PC patients but also benign pancreatic disease (BPD) patients were enrolled. Peaks were acquired by the software of MALDI-MS sample acquisition, followed by being processed and analyzed by the software of Progenesis MALDI. IgG Gal-ratio, which was calculated from the relative intensity of peaks G0, G1, and G2 according to the formula (G0/(G1+G2×2)), was employed as an index for indicating the distribution of IgG galactosylation. Results: The Gal-ratio was elevated in PC comparing with that in non-cancer group (healthy controls and BPD). The area under the receiver operating characteristic curve (AUC) of IgG Gal-ratio was higher than that of CA19-9 (0.912 vs. 0.814). The performance was further improved when Gal-ratio and CA19-9 were combined (AUC: 0.928). Meanwhile, Gal-ratio also had great diagnostic value with a sensitivity of 92.31% (AUC: 0.883) in detection of PC at early stage. Notably, IgG Gal-ratio has great sensitivity (90.63%) and specificity (76.81%) in CA19-9-negative PC patients. Conclusions: IgG Gal-ratio had a great performance in detection of PC and could be used to assist CA19-9 in improving diagnosis performance through early stage detection, differentiation from BPD, and PC diagnosis with CA19-9-negative level.

Distribution of IgG galactosylation as a promising biomarker for cancer screening in multiple cancer types

Background: Neuroblastoma (NB) is the most frequent pediatric malignant neoplasm that originates from embryonic neural crest cells. Urinary catecholamines in 24-h urine are most commonly analyzed for the diagnosis of neuroblastoma at good sensitivity; however, it is challenging to collect 24-h urine samples in a pediatric population. Therefore, development of more rapid, non-invasive and cost-effective tools for the diagnosis of NB remains needed. Serum immunoglobulin G (IgG) galactosylation have been found highly associated with adult cancers in our previous study. Methods: To explore the potential use of serum IgG galactosylation in aiding diagnosis of neuroblastoma, serum IgG galactosylation profiles of 26 neuroblastoma cases and 30 age-matched non-malignant controls were analyzed by MALDI MS. The alteration of IgG galactosylation in neuroblastoma patients was measured by a Gal-ratio formula: G0/(G1+G2×2), calculating the relative intensities of agalactosylated N-glycan (G0) vs mono-galactosyl N-glycan (G1) and digalactosyl N-glycan (G2). Results: The results showed that IgG Gal-ratios were significantly higher in neuroblastoma cases compared with non-malignant controls (p=5.0×10-4). And the Gal-ratio data generated sensitivity and specificity of 84.62% and 60.00%, combined with an AUC (area under the curve) of 0.80. Conclusions: The analysis of serum IgG galactosylation distribution may play a suggestive role for neuroblastoma diagnosis, or serve as a potential biomarker for NB diagnosis.

Background Ovarian 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. Methods The 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. Results A2780-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. Conclusions The 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 material The online version of this article (doi:10.1186/s12014-017-9155-z) contains supplementary material, which is available to authorized users.

Background Ovarian cancer is the most lethal gynecological malignancy due to its frequent recurrence and drug resistance even after successful initial treatment. Accumulating scientific evidence indicates that subpopulations of cancer cells with stem cell-like properties, such as so-called side population (SP) cells, are primarily responsible for these recurrences. A better understanding of SP cells may provide new clues for detecting and targeting these cancer-initiating cells and ultimately help to eradicate cancer. Changes in glycosylation patterns are remarkable features of SP cells. Here, we isolated SP cells from ovarian cancer cell lines and analyzed their glycosylation patterns using multiple glycomic strategies. Methods Six high-grade serous ovarian cancer cell lines were used for SP cell isolation. Among them, HO8910 pm, which contained the highest proportion of SP cells, was used for glycomic analysis of SP cells. Cell lysate of SP cells and main population cells was applied to lectin microarray and mass spectrometry for glycan profiling. Differently expressed glycan structures were further verified by lectin blot, flow cytometry, and real-time PCR analysis of their relevant enzymes. Results Expression of core fucosylated N-glycan and tumor-associated Tn, T and sT antigens were increased in SP cells. By contrast, SP cells exhibited decreased hybrid glycan, α2,3-linked sialic glycan and multivalent sialyl-glycan. Conclusions Glycan structures, such as Tn, T, sT antigens, and core fucosylation may serve as biomarkers of ovarian cancer stem cells. Electronic supplementary material The online version of this article (doi:10.1186/s12014-016-9131-z) contains supplementary material, which is available to authorized users.