Prediction of neoadjuvant chemotherapeutic efficacy in patients with locally advanced gastric cancer by serum IgG glycomics profiling.

Abstract

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.

• Authors: Ruihuan Qin, Yupeng Yang, Hao Chen, Wenjun Qin, Jing Han, Yong Gu, Yiqing Pan, Xi Cheng, Junjie Zhao, Xuefei Wang, Shifang Ren, Yihong Sun, Jianxin Gu
• Journal: Clinical proteomics (Clin Proteomics) Vol. 17 Pg. 4 ( 2020) ISSN: 1542-6416 [Print] England
• PMID: 32042279 (Publication Type: Journal Article)
• Copyright: © The Author(s) 2020.