Pre-operative biomarkers may predict nodal status in pancreatic ductal adenocarcinoma

Noah S. Brown , Matthew A. Firpo , Courtney L. Scaife
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Abstract

Introduction

The current standard for preoperative nodal staging for pancreatic adenocarcinoma, endoscopic ultrasound, varies widely in its accuracy, with pathologic concurrence as low as 41 %. Patients who are found to have 4 or more pathologically positive lymph nodes are defined as N2 nodal status. These patients experience extremely poor overall survival.

Objective

We sought to identify any biomarkers specific to this patient population to better stratify these patients pre-operatively.

Methods

We began with an existing database of patients with histologically confirmed pancreatic adenocarcinoma treated at the University of Utah between January 2004 and October 2019. These patients and their biological samples have already been screened using a 31 analyte panel to detect early stage disease. We recategorized these patients using the updated AJCC 8th edition introducing N2 disease. The individual analytes were then screened for their ability to distinguish N2 disease.

Results

Basigin (BSG) was significantly elevated in N2 disease (mean 17.45, SD 13.53) compared to N0 disease (mean 12.09, SD 11.47), p = 0.014 by Dunn's test) while Leucine-rich alpha-2-glycoprotein 1 (LRG1) was significantly decreased in N2 disease (mean 3446.21, SD 2719.12) compared to N0 disease (mean 5727.25, SD 3236.40, p = 0.025).

Conclusion

BSG and LRG1 could be useful in preoperatively identifying candidates that would benefit most from resection. This offers a foundation for future studies to combine biomarkers and clinical factors into a machine learning algorithm to reliably distinguish N2 disease in the preoperative setting. This may affect the pre-surgical discussion and provide vital prognostic information to patients.
术前生物标志物可以预测胰腺导管腺癌的淋巴结状态
目前胰腺腺癌术前淋巴结分期的标准是内镜超声,其准确性差异很大,病理一致性低至41% %。发现有4个或更多病理阳性淋巴结的患者定义为N2淋巴结状态。这些患者的总体生存率极低。目的:我们试图确定任何特定于该患者群体的生物标志物,以便在手术前更好地对这些患者进行分层。方法:我们从一个现有的数据库开始,该数据库包含2004年1月至2019年10月在犹他大学接受治疗的组织学证实的胰腺腺癌患者。这些患者及其生物样本已经使用31种分析物进行筛选,以发现早期疾病。我们使用更新的AJCC第8版重新分类这些患者,介绍N2疾病。然后筛选个体分析物区分N2疾病的能力。结果N2病中basigin (BSG)水平显著高于N0病(平均17.45,SD 13.53)(平均12.09,SD 11.47), Dunn试验p = 0.014);N2病中富亮氨酸α -2-糖蛋白1 (LRG1)水平显著低于N0病(平均5727.25,SD 3236.40, p = 0.025)(平均3446.21,SD 2719.12)。结论bsg和LRG1可用于术前确定切除后获益最大的候选肿瘤。这为未来的研究奠定了基础,将生物标志物和临床因素结合到机器学习算法中,在术前可靠地区分N2疾病。这可能会影响术前讨论,并为患者提供重要的预后信息。
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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