Dynamic Alterations of Site-Specific N-Glycoform and Plasma Proteasome Signatures Stratify Chemotherapy Benefit in Pancreatic Ductal Adenocarcinoma.

IF 6.3 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Molecular & Cellular Proteomics Pub Date : 2026-09-01 Epub Date: 2026-08-17 DOI:10.1016/j.mcpro.2026.101642
Shanying Gui, Yaqiong Zhang, Tao Xia, Jiazi Qian, Zemin Fang, Wenhui Ouyang, Jie Wang, Jie Chen, Xiaojun Ren, Jianxin Lyu, Wei Cui, Hezhi Fang
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引用次数: 0

Abstract

Pancreatic ductal adenocarcinoma (PDAC) exhibits profound systemic remodeling during chemotherapy, yet how site-specific intact N-glycosylation in plasma is rewired by treatment remains largely undefined. Here, we perform an integrated plasma multi-omics study combining intact N-glycopeptidomics, deep proteomics, and metabolomics in a longitudinal cohort with paired pre- and post-chemotherapy samples and follow-ups (n = 177). Patients were further stratified according to radiographic treatment response. We identified 17,501 intact N-glycopeptides corresponding to 16,754 glycoforms, together with 6045 proteins and 1080 annotated metabolites. Paired analyses revealed extensive chemotherapy-associated changes across all three omics layers. Temporal glycopeptide and protein patterns were consistently enriched for complement, coagulation, extracellular-matrix, proteasome, and immune-related annotations, while oxidative-phosphorylation-related signatures showed relative depletion after treatment. Exploratory comparisons of within-patient changes (Δ = Post - Pre) between patients with partial response (PR) and those with stable or progressive disease highlighted 140 glycoforms, 18 glycosylation sites, and 103 proteins with response-associated patterns. These included coordinated increases in several proteasome-related plasma proteins in the PR group, as well as site- and glycoform-specific changes in complement- and acute-phase-related proteins. Response-associated differences in circulating metabolites further involved pyrimidine-, amino-acid-, and dipeptide-related features. Finally, leakage-controlled nested cross-validation prioritized 11 recurrent N-glycopeptide candidates and yielded modest prognostic discrimination, with a C-index of 0.591 and a 12-months area under the curve of 0.712. Collectively, this study provides a site- and glycoform-resolved view of chemotherapy-associated plasma molecular changes in PDAC and identifies candidate response- and prognosis-related features for future validation.

位置特异性n -糖形式和血浆蛋白酶体特征的动态改变分层化疗对胰腺导管腺癌的益处。
胰腺导管腺癌(PDAC)在化疗期间表现出深刻的全身重塑,然而,治疗如何重新连接血浆中特定部位的完整n -糖基化仍未明确。在这里,我们进行了一项综合血浆多组学研究,结合了完整的n -糖肽组学,深层蛋白质组学和代谢组学,在一个纵向队列中,配对化疗前和化疗后的样本和随访(n = 177)。根据放射治疗反应对患者进行进一步分层。我们鉴定了17,501个完整的n -糖肽,对应16,754个糖型,以及6,045个蛋白质和1,080个注释的代谢物。配对分析揭示了在所有三个组学层中广泛的化疗相关变化。补体、凝血、细胞外基质、蛋白酶体和免疫相关标记的时间糖肽和蛋白质模式持续丰富,而氧化磷酸化相关标记在治疗后显示相对减少。探索性比较部分缓解(PR)患者与疾病稳定或进展的患者之间的患者内部变化(Δ =后-前)突出了140个糖型,18个糖基化位点和103个具有反应相关模式的蛋白质。这包括PR组中几种蛋白酶体相关血浆蛋白的协同增加,以及补体期和急性期相关蛋白的位点特异性和糖型特异性变化。循环代谢物的反应相关差异进一步涉及嘧啶、氨基酸和二肽相关特征。最后,泄漏控制的嵌套交叉验证优先考虑了11个复发性n -糖肽候选物,并产生了适度的预后判别,c指数为0.591,曲线下12个月面积为0.712。总的来说,本研究提供了PDAC中化疗相关血浆分子变化的位点和糖型解析视图,并确定了候选反应和预后相关特征,以供未来验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Molecular & Cellular Proteomics
Molecular & Cellular Proteomics 生物-生化研究方法
CiteScore
11.50
自引率
4.30%
发文量
131
审稿时长
84 days
期刊介绍: The mission of MCP is to foster the development and applications of proteomics in both basic and translational research. MCP will publish manuscripts that report significant new biological or clinical discoveries underpinned by proteomic observations across all kingdoms of life. Manuscripts must define the biological roles played by the proteins investigated or their mechanisms of action. The journal also emphasizes articles that describe innovative new computational methods and technological advancements that will enable future discoveries. Manuscripts describing such approaches do not have to include a solution to a biological problem, but must demonstrate that the technology works as described, is reproducible and is appropriate to uncover yet unknown protein/proteome function or properties using relevant model systems or publicly available data. Scope: -Fundamental studies in biology, including integrative "omics" studies, that provide mechanistic insights -Novel experimental and computational technologies -Proteogenomic data integration and analysis that enable greater understanding of physiology and disease processes -Pathway and network analyses of signaling that focus on the roles of post-translational modifications -Studies of proteome dynamics and quality controls, and their roles in disease -Studies of evolutionary processes effecting proteome dynamics, quality and regulation -Chemical proteomics, including mechanisms of drug action -Proteomics of the immune system and antigen presentation/recognition -Microbiome proteomics, host-microbe and host-pathogen interactions, and their roles in health and disease -Clinical and translational studies of human diseases -Metabolomics to understand functional connections between genes, proteins and phenotypes
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