Sheahan Jordana, Wang Iris, Galettis Peter, Watson David I, Joshi Virendra, Hill Michelle M, Lipscombe Richard, Peters Kirsten, Bringans Scott
Proteomics International, Broadway, P.O. Box 3008, Perth 6009, WA, Australia.
Department of Surgery, Flinders Medical Centre, College of Medicine and Public Health, Flinders University, Adelaide 5042, SA, Australia.
Proteomes. 2025 Jun 4;13(2):23. doi: 10.3390/proteomes13020023.
Esophageal adenocarcinoma (EAC) diagnosis involves invasive and expensive endoscopy with biopsy, but rising EAC incidence has not been reduced by increased surveillance. This study aimed to develop and clinically validate a novel glycoprotein biomarker blood test for EAC, named PromarkerEso.
Serum glycoprotein relative concentrations were measured using a lectin-based magnetic bead array pulldown method, with multiple reaction monitoring mass spectrometry in 259 samples across three independent cohorts. A panel of glycoproteins: alpha-1-antitrypsin, alpha-1-antichymotrypsin, complement C9 and plasma kallikrein, were combined with clinical factors (age, sex and BMI) in an algorithm to categorize the samples by the risk of EAC.
PromarkerEso demonstrated a strong discrimination of EAC from the controls (area under the curve (AUC) of 0.91 in the development cohort and 0.82 and 0.98 in the validation cohorts). The test exhibited a high sensitivity for EAC (98% in the development cohort, and 99.9% and 91% in the validation cohorts) and a high specificity (88% in the development cohort, and 86% and 99% in the validation cohorts). PromarkerEso identified individuals with and without EAC (96% and 95% positive and negative predictive values).
This less invasive approach for EAC detection with the novel combination of these glycoprotein biomarkers and clinical factors coalesces in a potential step toward improved diagnosis.
食管腺癌（EAC）的诊断需要通过侵入性且昂贵的内镜活检，但增加监测并未降低EAC发病率的上升。本研究旨在开发并临床验证一种用于EAC的新型糖蛋白生物标志物血液检测方法，名为PromarkerEso。
使用基于凝集素的磁珠阵列下拉法测量血清糖蛋白相对浓度，并通过多反应监测质谱法对三个独立队列中的259个样本进行检测。一组糖蛋白：α-1-抗胰蛋白酶、α-1-抗糜蛋白酶、补体C9和血浆激肽释放酶，与临床因素（年龄、性别和体重指数）结合在一个算法中，以根据EAC风险对样本进行分类。
PromarkerEso对EAC与对照表现出很强的区分能力（在开发队列中的曲线下面积（AUC）为0.91，在验证队列中分别为0.82和0.98）。该检测方法对EAC表现出高灵敏度（在开发队列中为98%，在验证队列中分别为99.9%和91%）和高特异性（在开发队列中为88%，在验证队列中分别为86%和99%）。PromarkerEso能够识别患有和未患有EAC的个体（阳性和阴性预测值分别为96%和95%）。
这种结合这些糖蛋白生物标志物和临床因素的新型组合用于EAC检测的侵入性较小的方法，是朝着改善诊断迈出的潜在一步。
