Multi‐Biomarker Profiling for Precision Diagnosis of Lung Cancer

Abstract Multi‐biomarker analysis can enhance the accuracy of the single‐biomarker analysis by reducing the errors caused by genetic and environmental differences. For this reason, multi‐biomarker analysis shows higher accuracy in early and precision diagnosis. However, conventional analysis methods have limitations for multi‐biomarker analysis because of their long pre‐processing times, inconsistent results, and large sample requirements. To solve these, a fast and accurate precision diagnostic method is introduced for lung cancer by multi‐biomarker profiling using a single drop of blood. For this, surface‐enhanced Raman spectroscopic immunoassay (SERSIA) is employed for the accurate, quick, and reliable quantification of biomarkers. Then, it is checked the statistical relation of the multi‐biomarkers to differentiate between healthy controls and lung cancer patients. This approach has proven effective; with 20 µL of blood serum, lung cancer is diagnosed with 92% accuracy. It also accurately identifies the type and stage of cancer with 87% and 85%, respectively. These results show the importance of multi‐biomarker analysis in overcoming the challenges posed by single‐biomarker diagnostics. Furthermore, it markedly improves multi‐biomarker‐based analysis methods, illustrating its important impact on clinical diagnostics.