Preoperative Prediction Nomogram Based on a Novel Serum miRNA Signature and CT Scans for Lymph Node Metastasis in Colorectal Cancer

Background: Preoperative prediction of lymph node (LN) status is of crucial importance for appropriate treatment planning in patients with colorectal cancer (CRC). Here, we sought to develop and validate a non-invasive nomogram model to preoperatively predict LN metastasis in CRC. Methods: In the discovery set (n=20), LN-status-related miRNAs were screened from high-throughput sequencing data of human CRC serum samples. In the training set (n=218), a miRNA panel-clinicopathologic nomogram was developed by logistic regression analysis for preoperative prediction of LN metastasis. In the validation set (n=198), we validated the above nomogram with respect to its discrimination, calibration and clinical application. Findings: We identified four differently expressed miRNAs (miR-122-5p, miR-146b-5p, miR-186-5p and miR-193a-5p), which, when combined in the miRNA-based panel, could provide higher LN prediction capability compared with computed tomography (CT) scans (P<0.05 in both training and validation sets). Furthermore, a nomogram integrating the miRNA-based panel and CT-reported LN status was constructed in the training set, which performed well in both training and validation sets (AUC: 0.913 and 0.883, respectively). Decision curve analysis demonstrated the clinical usefulness of the nomogram. Interpretation: Our nomogram is a reliable prediction model that can be conveniently and efficiently used to improve the accuracy of preoperative prediction of LN metastasis in patients with CRC. Funding: This project was supported by National Natural Science Foundation of China (Nos. 81472025, 81772271, 81601846, 81702084 and 81301506), Shandong Technological Development Project (2016CYJS01A02), Taishan Scholar Program of Shandong Province, Natural Science of Basic Scientific Research Foundation of Shandong University (2017BTS01), Science Foundation of Qilu Hospital of Shandong University (2015QLMS51) and Fundamental Research Funds of Shandong University (2014QLKY03). Declaration of Interest: The authors declare no potential conflicts of interest. Ethical Approval: Ethical approval was obtained for this retrospective study, and the informed consent requirement was waved.