Revisiting the diagnostic performance of exosomes: harnessing the feasibility of combinatorial exosomal miRNA profiles for colorectal cancer diagnosis

Abstract

Abstract The challenges associated with liquid biopsy of colorectal cancer (CRC) are closely linked to the substantial variations observed in gene expression profiles among patients. This variability complicates the selection of an ideal biomarker for accurate diagnosis. In this report, we propose that employing a combination of miRNAs offers a better change for enhancing the accuracy of CRC diagnosis compared to solely relying on single miRNAs. As an illustrative example, we measured 9 miRNAs from 45 patient samples (comprising 31 CRC cases and 14 healthy controls) via RT-qPCR. We then utilized two methods: (1) LASSO regression for marker ranking and (2) linear discriminant analysis (LDA) to identify the optimal weighted combination of multiple markers. Our data indicates that combination of triple markers, selected based on their ranking, exhibited the highest diagnostic performance, including a sensitivity of 93.6% (95% confidence interval, CI 79.3–98.9%), specificity of 100% (CI 78.5–100.0%), positive predictive value (PPV) of 100%, negative predictive value (NPV) of 87.5%, and an overall accuracy of 95.6%. In contrast, the diagnostic performance of each individual miRNA used in the triple marker combination ranged from 53.3 to 80.0% in accuracy. While we acknowledge the need for further extensive studies involving larger patient cohorts and the consideration of additional miRNA candidates, our research undeniably highlights the potential of combining multiple markers as a robust methodology for identifying biomarkers among heterogeneous patient profiles.

Keywords

• Molecular diagnosis
• Exosomal miRNAs
• Colorectal cancer
• Linear discriminant analysis