A nomogram based on the 3-gene signature and clinical characteristics for predicting lymph node metastasis in papillary thyroid cancer.

Abstract

BackgroundPrecise recognition of neck lymph node metastasis (LNM) is essential for choosing the suitable scope of operation for papillary thyroid cancer(PTC) patients.ObjectiveThe purpose of our study was to establish an effective nomogram integrating both gene biomarkers and clinicopathologic features for preoperatively predicting LNM in PTC patients.MethodsWe gathered clinical information and gene expression data for PTC samples from The Cancer Genome Atlas database (TCGA). WGCNA and differential analysis were applied to identify LNM-related differentially expressed genes in PTC patients. We developed a risk score based on the 3-gene signature predicting LNM using the LASSO regression analysis. Furthermore, multivariate logistic regression analysis was performed to establish a nomogram. We evaluated the discriminative ability of the nomogram by calculating the area under the ROC curve. Besides, we applied the decision curve analyses and calibration curve to assess the nomogram's actual benefits and accuracy.ResultsSignificant predictors of LNM in PTC patients were eventually screened to develop a nomogram, which included age, histological type, focus type, T stage, and risk score calculated based on IQGAP2, BTBD11 and MT1G expression levels. The AUC value of the nomogram for training and validation set was 0.802 (95% CI 0.750-0.855) and 0.718 (95% CI 0.624-0.811). Moreover, the nomogram has outstanding calibration and actual clinical patient benefits.ConclusionsWe identified a nomogram based on the 3-gene signature and clinical characteristics that effectively predicted LNM in PTC patients, which offers guidance for the preoperative assessment the appropriate scope of operation in PTC patients.