Identification of Plasma Protein Biomarkers for Predicting Lung Cancer

肺癌 医学 癌症 限制 疾病 生物标志物 阶段(地层学) 重症监护医学 肺癌筛查 诊断生物标志物 肺 肿瘤科 内科学 病理 生物 生物化学 古生物学 工程类 机械工程
作者
Ki Sa Sung,Sang Jun Han,Ji Hye Lee,Min‐Seok Kwon,Duk-Hwan Kim,Young Sun Oh
出处
期刊:Anticancer Research [International Institute of Anticancer Research (IIAR) Conferences 1997. Athens, Greece. Abstracts]
卷期号:44 (11): 5147-5155 被引量:1
标识
DOI:10.21873/anticanres.17340
摘要

Background/Aim: Lung cancer remains a leading cause of cancer-related mortality worldwide, necessitating the development of effective early diagnostic strategies. Despite advancements in imaging and screening technologies, late-stage diagnoses remain common, limiting treatment options and reducing survival rates. Thus, there is a critical need for reliable, minimally invasive biomarkers to improve early detection and patient outcomes. Plasma protein biomarkers offer promising potential for early lung cancer detection and continuous disease monitoring. This study explored the potential of specific plasma protein markers as early indicators of lung cancer. Patients and Methods: Plasma samples were collected from normal healthy individuals and lung cancer patients, and protein purification and analysis were conducted using LC-MS/MS. A mixed-effect model was applied to select lung cancer-related protein markers based on label-free relative quantification values. Results: We identified 29 proteins with potential for early lung cancer diagnosis, including complement proteins (CFB, C3, C8G, C1QA, C1R, C6), orosomucoid proteins (ORM1, ORM2), ceruloplasmin (CP), alpha-1-B glycoprotein (A1BG), and others. These proteins play diverse roles in immune response, inflammation, and cell signaling, suggesting their relevance in lung cancer pathophysiology. Conclusion: Our findings suggest the potential of plasma proteins as early diagnostic biomarkers for lung cancer. Further validation in larger cohorts is needed to confirm their clinical utility. Integrating these biomarkers into existing diagnostic modalities could enhance early detection accuracy, leading to improved patient outcomes.

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