Zhang Shan-Qiang, Pan Su-Ming, Lai Shu-Zhen, Situ Hui-Jing, Liu Jun, Dai Wen-Jie, Liang Si-Xian, Zhou Li-Qing, Lu Qi-Qi, Ke Pei-Feng, Zhang Fan, Chen Hai-Bin, Li Ji-Cheng
Medical Research Center, Yuebei People's Hospital, Shantou University Medical College, Shaoguan, China.
Department of Radiation Oncology, Yuebei People's Hospital, Shantou University Medical College, Shaoguan, China.
Front Oncol. 2022 Jun 30;12:889516. doi: 10.3389/fonc.2022.889516. eCollection 2022.
Induction chemotherapy (IC) can alleviate locoregionally advanced nasopharyngeal carcinoma (LA-NPC), but effectiveness differs between patients, toxicity is problematic, and effective blood-based IC efficacy predictors are lacking. Here, we aimed to identify biomarkers for early identification of IC beneficiaries.
Sixty-four pairs of matched plasma samples collected before and after IC from LA-NPC patients including 34 responders and 30 non-responders, as well as 50 plasma samples of healthy individuals, were tested using data-independent acquisition mass spectrometry. The proteins associated with clinical traits or IC benefits were investigated by weighted gene co-expression network analysis (WGCNA) and soft cluster analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional annotations were performed to determine the potential function of the identified proteins. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of candidate biomarkers in predicting IC beneficiaries.
Compared with healthy individuals, 1027 differentially expressed proteins (DEPs) were found in the plasma of LA-NPC patients. Based on feedback from IC outcomes, 463 DEPs were identified in the pre-IC plasma between responders and non-responders. A total of 1212 DEPs represented the proteomic changes before and after IC in responders, while 276 DEPs were identified in post-IC plasma between responders and non-responders. WGCNA identified nine protein co-expression modules correlated with clinical traits. Soft cluster analysis identified four IC benefits-related protein clusters. Functional enrichment analysis showed that these proteins may play a role in IC immunity, complement, coagulation, glycosaminoglycan and serine. Four proteins differentially expressed in all group comparisons, paraoxonase/arylesterase 1 (PON1), insulin-like growth factor-binding protein 3 (IGFBP-3), rheumatoid factor D5 light chain (v-kappa-3) and RNA helicase (DDX55), were associated with clinical traits or IC benefits. A four-protein model accurately identified potential IC beneficiaries (AUC=0.95) while diagnosing LA-NPC (AUC=0.92), and the prediction performance was verified using the models to confirm the effective IC (AUC=0.97) and evaluate IC outcome (AUC=0.94).
The plasma protein profiles among IC responders and non-responders were different. PON1, IGFBP3, v-kappa-3 and DDX55 could serve as potential biomarkers for early identification of IC beneficiaries for individualised treatment of LA-NPC.
诱导化疗（IC）可缓解局部晚期鼻咽癌（LA-NPC），但患者间疗效存在差异，毒性问题突出，且缺乏有效的基于血液的IC疗效预测指标。在此，我们旨在识别用于早期识别IC受益患者的生物标志物。
对64对来自LA-NPC患者IC前后采集的匹配血浆样本（包括34名反应者和30名无反应者）以及50名健康个体的血浆样本，采用数据非依赖采集质谱法进行检测。通过加权基因共表达网络分析（WGCNA）和软聚类分析研究与临床特征或IC获益相关的蛋白质。进行基因本体论和京都基因与基因组百科全书功能注释以确定所识别蛋白质的潜在功能。采用受试者工作特征曲线下面积（AUC）评估候选生物标志物预测IC受益患者的性能。
与健康个体相比，在LA-NPC患者血浆中发现了1027种差异表达蛋白（DEP）。根据IC结果反馈，在反应者和无反应者的IC前血浆中识别出463种DEP。共有1212种DEP代表反应者IC前后的蛋白质组变化，而在反应者和无反应者的IC后血浆中识别出276种DEP。WGCNA识别出9个与临床特征相关的蛋白质共表达模块。软聚类分析识别出4个与IC获益相关的蛋白质簇。功能富集分析表明，这些蛋白质可能在IC免疫、补体、凝血、糖胺聚糖和丝氨酸方面发挥作用。在所有组间比较中差异表达的4种蛋白质，对氧磷酶/芳基酯酶1（PON1）、胰岛素样生长因子结合蛋白3（IGFBP-3）、类风湿因子D5轻链（v-kappa-3）和RNA解旋酶（DDX55），与临床特征或IC获益相关。一种四蛋白模型在诊断LA-NPC（AUC=0.92）时能准确识别潜在的IC受益患者（AUC=0.95），并且该模型用于确认有效IC（AUC=0.97）和评估IC结果（AUC=0.94）时，预测性能得到了验证。
IC反应者和无反应者之间的血浆蛋白质谱不同。PON1、IGFBP3、v-kappa-3和DDX55可作为潜在生物标志物，用于早期识别IC受益患者，以对LA-NPC进行个体化治疗。
