Multiplex plasma protein assays as a diagnostic tool for lung cancer

IF 4.5 2区 医学 Q1 ONCOLOGY Cancer Science Pub Date : 2024-07-30 DOI:10.1111/cas.16300
Mohammad Tanvir Ahamed, Jenny Forshed, Adrian Levitsky, Janne Lehtiö, Amanj Bajalan, Maria Pernemalm, Lars E. Eriksson, Björn Andersson
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Abstract

Lack of the established noninvasive diagnostic biomarkers causes delay in diagnosis of lung cancer (LC). The aim of this study was to explore the association between inflammatory and cancer-associated plasma proteins and LC and thereby discover potential biomarkers. Patients referred for suspected LC and later diagnosed with primary LC, other cancers, or no cancer (NC) were included in this study. Demographic information and plasma samples were collected, and diagnostic information was later retrieved from medical records. Relative quantification of 92 plasma proteins was carried out using the Olink Immuno-Onc-I panel. Association between expression levels of panel of proteins with different diagnoses was assessed using generalized linear model (GLM) with the binomial family and a logit-link function, considering confounder effects of age, gender, smoking, and pulmonary diseases. The analysis showed that the combination of five plasma proteins (CD83, GZMA, GZMB, CD8A, and MMP12) has higher diagnostic performance for primary LC in both early and advanced stages compared with NC. This panel demonstrated lower diagnostic performance for other cancer types. Moreover, inclusion of four proteins (GAL9, PDCD1, CD4, and HO1) to the aforementioned panel significantly increased the diagnostic performance for primary LC in advanced stage as well as for other cancers. Consequently, the collective expression profiles of select plasma proteins, especially when analyzed in conjunction, might have the potential to distinguish individuals with LC from NC. This suggests their utility as predictive biomarkers for identification of LC patients. The synergistic application of these proteins as biomarkers could pave the way for the development of diagnostic tools for early-stage LC detection.

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作为肺癌诊断工具的多重血浆蛋白测定。
由于缺乏成熟的非侵入性诊断生物标志物,导致肺癌(LC)诊断延迟。本研究旨在探索炎症和癌症相关血浆蛋白与肺癌之间的关联,从而发现潜在的生物标志物。本研究纳入了因怀疑患有肺癌而转诊的患者,这些患者后来被确诊为原发性肺癌、其他癌症或无癌症(NC)。研究人员收集了患者的人口统计学信息和血浆样本,随后从病历中检索了诊断信息。使用 Olink Immuno-Onc-I panel 对 92 种血浆蛋白进行了相对定量。考虑到年龄、性别、吸烟和肺部疾病等混杂因素的影响,采用二项式族和对数连接功能的广义线性模型(GLM)评估了蛋白质表达水平与不同诊断之间的关系。分析表明,与 NC 相比,五种血浆蛋白(CD83、GZMA、GZMB、CD8A 和 MMP12)组合对早期和晚期原发性 LC 的诊断率更高。而对其他癌症类型的诊断率较低。此外,将四种蛋白质(GAL9、PDCD1、CD4 和 HO1)纳入上述面板,可显著提高对晚期原发性 LC 及其他癌症的诊断率。因此,精选血浆蛋白的集体表达谱,尤其是在联合分析时,有可能将 LC 患者与 NC 患者区分开来。这表明它们可作为鉴别 LC 患者的预测性生物标记物。这些蛋白质作为生物标志物的协同应用,可为开发早期 LC 检测的诊断工具铺平道路。
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来源期刊
Cancer Science
Cancer Science 医学-肿瘤学
自引率
3.50%
发文量
406
审稿时长
2 months
期刊介绍: Cancer Science (formerly Japanese Journal of Cancer Research) is a monthly publication of the Japanese Cancer Association. First published in 1907, the Journal continues to publish original articles, editorials, and letters to the editor, describing original research in the fields of basic, translational and clinical cancer research. The Journal also accepts reports and case reports. Cancer Science aims to present highly significant and timely findings that have a significant clinical impact on oncologists or that may alter the disease concept of a tumor. The Journal will not publish case reports that describe a rare tumor or condition without new findings to be added to previous reports; combination of different tumors without new suggestive findings for oncological research; remarkable effect of already known treatments without suggestive data to explain the exceptional result. Review articles may also be published.
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Issue Information In this issue Issue Information In this issue Real-world genome profiling in Japanese patients with pancreatic ductal adenocarcinoma focusing on HRD implications
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