Detection and Quantification of Tp53 and p53-Anti-p53 Autoantibody Immune Complex: Promising Biomarkers in Early Stage Lung Cancer Diagnosis

Biosensors

Jung-Hoon Kim¹  Keum-Soo Song¹  Shrikant Dashrath Warkad¹  Hey-Jin Kim²  Satish Balasaheb Nimse³  Taisun Kim³ 

[1] Biometrix Technology, Inc., 2-2 Bio Venture Plaza 56, Chuncheon 24232, Korea;Department of Laboratory Medicine, Korea Cancer Center Hospital, Korea Institute of Radiological and Medical Sciences, Seoul 01812, Korea;Institute of Applied Chemistry and Department of Chemistry, Hallym University, Chuncheon 200702, Korea;

关键词: stage I;    lung cancer;    NSCLS;    SCLC;    p53;    autoantibody;   

DOI  :  10.3390/bios12020127

来源: DOAJ

【 摘 要 】

Lung cancer is a leading cause of death worldwide, claiming nearly 1.80 million lives in 2020. Screening with low-dose computed tomography (LDCT) reduces lung cancer mortality by about 20% compared to standard chest X-rays among current or heavy smokers. However, several reports indicate that LDCT has a high false-positive rate. In this regard, methods based on biomarker detection offer excellent potential for developing noninvasive cancer diagnostic tests to complement LDCT for detecting stage 0∼IV lung cancers. Herein, we have developed a method for detecting and quantifying a p53-anti-p53 autoantibody complex and the total p53 antigen (wild and mutant). The LOD for detecting Tp53 and PIC were 7.41 pg/mL and 5.74 pg/mL, respectively. The detection ranges for both biomarkers were 0–7500 pg/mL. The known interfering agents in immunoassays such as biotin, bilirubin, intra-lipid, and hemoglobin did not detect Tp53 and PIC, even at levels that were several folds higher levels than their normal levels. Furthermore, the present study provides a unique report on this preliminary investigation using the PIC/Tp53 ratio to detect stage I–IV lung cancers. The presented method detects lung cancers with 81.6% sensitivity and 93.3% specificity. These results indicate that the presented method has high applicability for the identification of lung cancer patients from the healthy population.

【 授权许可】

Unknown