Prediction of neoadjuvant chemotherapeutic efficacy in patients with locally advanced gastric cancer by serum IgG glycomics profiling
Prediction of neoadjuvant chemotherapeutic efficacy in patients with locally advanced gastric cancer by serum IgG glycomics profiling
复制标题
通过血清IgG糖组学分析预测局部晚期胃癌患者新辅助化疗疗效
DOI：
10.1186/s12014-020-9267-8
复制
发表时间：
2020-02-06
影响因子：
3.8
通讯作者：
Gu, Jianxin
中科院分区：
文献类型：
--
作者：
Qin, Ruihuan;Yang, Yupeng;Gu, Jianxin
研究背景新辅助化疗（NACT）可以为局部进展期胃癌（LAGC）患者提供根治性手术机会，从而改善其预后和生存质量。然而，没有有效的方法可以在术前预测NACT的疗效，以避免无效化疗带来的潜在毒性、耗时和经济负担。一些研究已经调查了血清IgG糖基化与胃癌之间的相关性，但IgG糖组是否可以反映肿瘤对NACT的反应的问题仍然没有答案。 方法采用超高效液相色谱法对49例LAGC患者的血清IgG糖组谱进行分析，其中25例属于NACT反应组，24例属于无反应组。构建逻辑回归模型来预测结合临床特征和差异性N-聚糖的缓解率，同时通过受试者工作特征（ROC）分析评估模型的精度。结果LAGC患者治疗前血清中的IgGN-糖组分析包括24个直接检测到的聚糖和17个总结性状。与非反应组的IgG聚糖相比，反应组的半乳糖基化N-聚糖增加，而单唾液酸化N-聚糖和双半乳糖基化N-聚糖减少。我们结合患者的年龄、组织学、化疗方案、GP4(H3N4F1)、GP6(H3N5F1)和GP18(H5N4F1S1)构建了一个模型，ROC分析显示该模型能够准确预测NACT反应(AUC = 0.840)，敏感性为64.00%，特异性为100%。 LAGC 预处理血清中 IgGN-聚糖的分析。 IgGN-糖组的改变可能是个性化生物标志物，用于预测 LAGC 对 NACT 的反应，并有助于说明免疫与 NACT 效果之间的关系。
BackgroundNeoadjuvant 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.MethodSerum 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 differentialN-glycans, while the precision of model was assessed by receiver operating characteristic (ROC) analysis.ResultsIgGN-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, agalactosylatedN-glycans increased while monosialylatedN-glycans and digalactosylatedN-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%.ConclusionWe here firstly present the profiling of IgGN-glycans in pretreatment serum of LAGC. The alterations in IgGN-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.