Overview of combined adjuvant strategies for tumor biomarker detection

Cancer is one of the leading causes of death worldwide, and early tumor detection can significantly reduce mortality rates. Liquid biopsy is a minimally invasive, repeatable method with a high economic benefit ratio, and it shows excellent prospects for tumor diagnosis. However, the detection methods relying on classical biomarkers have limited sensitivity and accuracy. The application of auxiliary reagents, such as iRGD, promotes the release of alpha-fetoprotein (AFP) to improve the detection efficiency of liver cancer. Artificial intelligence (AI) technology is increasingly being applied as an assistant in tumor diagnosis. It can automatically identify tumor lesions in imaging, analyze tumor-related gene mutations, classify circulating tumor cells (CTCs), and integrate multi-omics data. These auxiliary means have enhanced the efficiency of tumor screening or detection. In this review, we summarize the combined applications of iRGD and AFP. We also discuss emerging new detection techniques, including CTCs, circulating tumor DNA (ctDNA), exosomes, and tumor-educated platelets (TEPs), specifically with the help of AI. The aim is to better understand the auxiliary role of the iRGD reagent and AI technology in early tumor detection.