Integrating miRNAs and Bacterial DNA for Early Detection of Lung Cancer

Abstract Purpose The early detection is crucial for improved outcomes in lung cancer, which remains a leading cause of cancer-erelated deaths. There is an urgent need for precise molecular biomarkers to diagnose early-stage lung cancer. To address this, we assessed the potential of integrating diverse molecular biomarkers across both plasma and sputum to improve the accuracy of diagnosis, given the heterogeneous nature of lung cancer arising from multifactorial molecular aberrations. Methods We utilized droplet digital PCR to quantify miRNAs in plasma and bacterial DNA in sputum collected from 114 lung cancer patients and 121 cancer-free smokers. The participants were randomly divided into a development cohort and a validation cohort. Logistic regression models with constrained parameters were employed to optimize a signature with the highest sensitivity and specificity for early detection of lung cancer. Results The individual plasma miRNAs and sputum bacterial biomarkers had sensitivities of 62%-71% and specificities of 61%-79% for diagnosing lung cancer. A panel of plasma miRNA or sputum bacterial biomarkers produced sensitivities of 79%-85% and specificities of 74%-82%. An integrated signature comprising two miRNAs in plasma and three bacterial biomarkers in sputum was developed in the development cohort, and it exhibited a higher sensitivity (87%) and specificity (89%) in comparison to individual biomarkers. The signature’s diagnostic value was confirmed in the validation cohort, regardless of tumor stage, histological type, and demographic factors. Conclusion The integration of miRNA and bacterial biomarkers across both plasma and spu-tum samples offered an effective approach for the diagnosis of lung cancer.