PDF(Pubmed)
Abstract：
UNASSIGNED: Biliary tract cancer (BTC) is associated with a dismal prognosis, partly because it is typically diagnosed late, highlighting the need for diagnostic biomarkers. The purpose of this project was to identify and validate multiprotein signatures that could differentiate patients with BTC from non-cancer controls.
UNASSIGNED: In this study, we included treatment-naïve patients with BTC, healthy controls, and patients with benign conditions including benign biliary tract disease. Participants were divided into three non-overlapping cohorts: a case-control-based discovery cohort (BTC = 186, controls = 249); a case-control-based validation cohort (validation cohort 1: BTC = 113, controls = 241); and a cohort study-based validation cohort including participants (BTC = 8, controls = 132) referred for diagnostic work-up for suspected cancer (validation cohort 2). Immuno-Oncology (I-O)-related proteins were measured in serum and plasma using a proximity extension assay (Olink Proteomics). Lasso and Ridge regressions were used to generate protein signatures of I-O-related proteins and carbohydrate antigen 19-9 (CA19-9) in the discovery cohort.
UNASSIGNED: Sixteen protein signatures, including 2 to 82 proteins, were generated. All signatures included CA19-9 and chemokine C-C motif ligand 20. Signatures discriminated between patients with BTC vs. controls, with AUCs ranging from 0.95 to 0.99 in the discovery cohort and 0.94 to 0.97 in validation cohort 1. In validation cohort 2, AUCs ranged from 0.84 to 0.94. Nine signatures achieved a specificity of 82% to 84% while keeping a sensitivity of 100% in validation cohort 2. All signatures performed better than CA19-9, and signatures including >15 proteins showed the best performance.
UNASSIGNED: The study demonstrated that it is possible to generate protein signatures that can successfully differentiate patients with BTC from non-cancer controls.
UNASSIGNED: We attempted to find blood sample-based protein profiles that could differentiate patients with biliary tract cancer from those without cancer. Several profiles were found and tested in different groups of patients. The profiles were successful at identifying most patients with biliary tract cancer, pointing towards the utility of multiprotein signatures in this context.
UNASSIGNED: In this study, we included treatment-naïve patients with BTC, healthy controls, and patients with benign conditions including benign biliary tract disease. Participants were divided into three non-overlapping cohorts: a case-control-based discovery cohort (BTC = 186, controls = 249); a case-control-based validation cohort (validation cohort 1: BTC = 113, controls = 241); and a cohort study-based validation cohort including participants (BTC = 8, controls = 132) referred for diagnostic work-up for suspected cancer (validation cohort 2). Immuno-Oncology (I-O)-related proteins were measured in serum and plasma using a proximity extension assay (Olink Proteomics). Lasso and Ridge regressions were used to generate protein signatures of I-O-related proteins and carbohydrate antigen 19-9 (CA19-9) in the discovery cohort.
UNASSIGNED: Sixteen protein signatures, including 2 to 82 proteins, were generated. All signatures included CA19-9 and chemokine C-C motif ligand 20. Signatures discriminated between patients with BTC vs. controls, with AUCs ranging from 0.95 to 0.99 in the discovery cohort and 0.94 to 0.97 in validation cohort 1. In validation cohort 2, AUCs ranged from 0.84 to 0.94. Nine signatures achieved a specificity of 82% to 84% while keeping a sensitivity of 100% in validation cohort 2. All signatures performed better than CA19-9, and signatures including >15 proteins showed the best performance.
UNASSIGNED: The study demonstrated that it is possible to generate protein signatures that can successfully differentiate patients with BTC from non-cancer controls.
UNASSIGNED: We attempted to find blood sample-based protein profiles that could differentiate patients with biliary tract cancer from those without cancer. Several profiles were found and tested in different groups of patients. The profiles were successful at identifying most patients with biliary tract cancer, pointing towards the utility of multiprotein signatures in this context.
摘要：
未经证实：胆道癌（BTC）与预后不良有关，部分原因是它通常被诊断为晚期，强调对诊断性生物标志物的需求。该项目的目的是鉴定和验证可以区分BTC患者与非癌症对照的多蛋白特征。
未经批准：在这项研究中，我们包括未接受BTC治疗的患者，健康的控制,以及良性疾病包括良性胆道疾病的患者。参与者分为三个不重叠的队列：基于病例对照的发现队列（BTC=186，对照=249）；基于病例对照的验证队列（验证队列1：BTC=113，对照=241）；以及基于队列研究的验证队列，其中包括参与者（BTC=8，对照=132），用于疑似癌症的诊断检查（验证队列2）。使用邻近延伸测定(Olink蛋白质组学)在血清和血浆中测量免疫肿瘤学(I-O)相关蛋白。套索和里奇回归用于在发现队列中产生I-O相关蛋白质和碳水化合物抗原19-9(CA19-9)的蛋白质特征。
未经证实：十六个蛋白质特征，包括2到82种蛋白质，产生了。所有特征包括CA19-9和趋化因子C-C基序配体20。BTC患者与BTC患者之间的区别特征controls,发现队列的AUC范围为0.95至0.99，验证队列1的AUC范围为0.94至0.97。在验证队列2中,AUC范围为0.84至0.94。在验证队列2中,9个签名实现82%至84%的特异性,同时保持100%的灵敏度。所有特征表现优于CA19-9,并且包括>15种蛋白质的特征表现出最佳性能。
UNASSIGNED：该研究表明，有可能产生可以成功区分BTC患者与非癌症对照的蛋白质特征。
UNASSIGNED：我们试图寻找基于血液样本的蛋白质谱，以区分患有胆道癌的患者和没有癌症的患者。在不同组的患者中发现并测试了几种概况。这些资料成功地识别了大多数胆道癌患者，指出多蛋白签名在这种情况下的实用性。
未经批准：在这项研究中，我们包括未接受BTC治疗的患者，健康的控制,以及良性疾病包括良性胆道疾病的患者。参与者分为三个不重叠的队列：基于病例对照的发现队列（BTC=186，对照=249）；基于病例对照的验证队列（验证队列1：BTC=113，对照=241）；以及基于队列研究的验证队列，其中包括参与者（BTC=8，对照=132），用于疑似癌症的诊断检查（验证队列2）。使用邻近延伸测定(Olink蛋白质组学)在血清和血浆中测量免疫肿瘤学(I-O)相关蛋白。套索和里奇回归用于在发现队列中产生I-O相关蛋白质和碳水化合物抗原19-9(CA19-9)的蛋白质特征。
未经证实：十六个蛋白质特征，包括2到82种蛋白质，产生了。所有特征包括CA19-9和趋化因子C-C基序配体20。BTC患者与BTC患者之间的区别特征controls,发现队列的AUC范围为0.95至0.99，验证队列1的AUC范围为0.94至0.97。在验证队列2中,AUC范围为0.84至0.94。在验证队列2中,9个签名实现82%至84%的特异性,同时保持100%的灵敏度。所有特征表现优于CA19-9,并且包括>15种蛋白质的特征表现出最佳性能。
UNASSIGNED：该研究表明，有可能产生可以成功区分BTC患者与非癌症对照的蛋白质特征。
UNASSIGNED：我们试图寻找基于血液样本的蛋白质谱，以区分患有胆道癌的患者和没有癌症的患者。在不同组的患者中发现并测试了几种概况。这些资料成功地识别了大多数胆道癌患者，指出多蛋白签名在这种情况下的实用性。
