Fig. 3: Transcriptomic modeling resolves unclassified LCNECs into NSCLC-like and SCLC-like molecular subtypes.
From: Integrated molecular and clinical characterization of pulmonary large cell neuroendocrine carcinoma
A Receiver operating characteristic (ROC) curve demonstrating the performance of a support vector machine (SVM) classifier trained to distinguish NSCLC-like from SCLC-like LCNECs based on 2168 transcriptomic features (AUC = 0.98). B Confusion matrix showing classification accuracy within the validation cohort. C Unsupervised UMAP projection of transcriptomic profiles reveals three distinct molecular clusters. D Overlay of classifier-derived labels onto the UMAP demonstrates concordance between predicted subtypes and transcriptomic clustering, enabling reclassification of previously unclassified LCNECs into biologically coherent groups. NSCLC non-small cell lung cancer, Unc Unclassified.
