<p>Tumor markers are of great value for predicting tumor progression and clarifying the molecular mechanisms of tumorigenesis. In terms of rapid detection, lateral flow immunoassay (LFIA) has become a key tool for tumor marker detection, favored for its speed, cost-effectiveness, and ease of operation—all of which are crucial for early cancer screening, treatment monitoring, and point-of-care testing (POCT) in various settings. Although widely used to detect core markers, LFIA performance is limited by signal tracers, antibody affinity, and test strip design; these issues need to be addressed to expand its clinical utility. This review summarizes the latest progress of LFIA in tumor marker detection over the past five years, highlighting marker-specific detection optimizations, novel test strip devices, and integrated innovations with artificial intelligence/machine learning. These innovations significantly outperform traditional readout methods in quantitative accuracy. The review also outlines multi-dimensional strategies for sensitivity enhancement (dual/multimodal detection, sensor structure optimization, auxiliary signal amplification) and identifies future development trends, such as improving multiplex detection, adapting to non-invasive samples, and standardizing production, ultimately advancing LFIA from qualitative screening to a clinically reliable tool for precision oncology.</p> Graphical abstract <p></p>