RNA-Binding Motif protein 6 is a candidate serum biomarker for pancreatic cancer

Early diagnosis is crucial to improve outcomes for pancreatic cancer (PC) patients, however the lack of specific and validated biomarkers for the disease remains challenging. In this study, we analyzed the serum proteome of 22 PC patients, 12 pancreatitis patients (PP) and 45 healthy controls (HC), using magnetic bead-based weak cation exchange and matrix-assisted laser desorption ionization-time of flight mass spectrometry. Next, we established supervised neural network (SNN) algorithm model by ClinProTools and identified the candidate biomarker using liquid chromatography-electrospray ionization-tandem mass spectrometry. Finally, candidate biomarker was validated in tissue samples. The SNN algorithm model discriminated PC from HC with 92.97% sensitivity and 94.55% specificity. We identified 76 differentially expressed peptides, 7/76 peaks were significantly different among PC, PP and HC (P<0.05). Only one peak (m/z: 1466.99) tended to be up-regulated in samples from HC, PP and PC, which was identified as regions of RNA-binding motif protein 6 (RBM6). In subsequent tissue analysis, we verified RBM6 expression was significantly higher in PC tissues than paracancerous tissue. Our results indicate that RBM6 might serve as a candidate diagnostic biomarker for PC.

早期诊断对于改善胰腺癌（pancreatic cancer, PC）患者的预后至关重要，但目前仍缺乏针对该疾病的特异性且经过验证的生物标志物，这仍是临床诊疗面临的挑战。本研究采用基于磁珠的弱阳离子交换联合基质辅助激光解吸电离-飞行时间质谱技术，对22例胰腺癌患者、12例胰腺炎患者（pancreatitis, PP）及45例健康对照（healthy controls, HC）的血清蛋白质组进行了分析。随后，我们通过ClinProTools软件构建了监督神经网络（supervised neural network, SNN）算法模型，并利用液相色谱-电喷雾串联质谱技术鉴定了候选生物标志物。最后，我们在组织样本中对该候选生物标志物进行了验证。该SNN算法模型区分胰腺癌患者与健康对照的灵敏度为92.97%，特异度为94.55%。本研究共鉴定出76个差异表达肽段，其中7个峰在胰腺癌患者、胰腺炎患者与健康对照间存在显著差异（P<0.05）。仅有1个质荷比（m/z）为1466.99的峰在健康对照、胰腺炎患者及胰腺癌患者的样本中呈上调趋势，该峰被鉴定为RNA结合基序蛋白6（RNA-binding motif protein 6, RBM6）的相关区域。后续的组织分析验证显示，胰腺癌组织中RBM6的表达水平显著高于癌旁组织。本研究结果表明，RBM6或可作为胰腺癌潜在的诊断候选生物标志物。