A Genomic-Clinicopathologic Nomogram Predicts Survival for Patients with Laryngeal Squamous Cell Carcinoma

Abstract

Background Long noncoding RNAs (lncRNAs), which have little or no ability to encode proteins, have attracted special attention due to their potential role in cancer disease. We aimed to establish a lncRNA signature and a nomogram incorporating the genomic and clinicopathologic factors to improve the accuracy of survival prediction for laryngeal squamous cell carcinoma (LSCC). Methods A LSCC RNA-sequencing (RNA-seq) dataset and the matched clinicopathologic information were downloaded from The Cancer Genome Atlas (TCGA). Using univariable Cox regression and least absolute shrinkage and selection operator (LASSO) analysis, we developed a thirteen-lncRNA signature related to prognosis. On the basis of multivariable Cox regression analysis results, a nomogram integrating the genomic and clinicopathologic predictors was built. The predictive accuracy and discriminative ability of the inclusive nomogram were confirmed by calibration curve and a concordance index (C-index), and compared with the TNM staging system by C-index and receiver operating characteristic (ROC) analysis. Decision curve analysis (DCA) was conducted to evaluate the clinical value of our nomogram. Results Thirteen overall survival- (OS-) related lncRNAs were identified, and the signature consisting of the selected thirteen lncRNAs could effectively divide patients into high-risk and low-risk subgroups, with area under curves (AUC) of 0.89 (3-year OS) and 0.885 (5-year OS). Independent factors derived from multivariable analysis to predict survival were margin status, tumor status, and lncRNA signature, which were all assembled into the nomogram. The calibration curve for the survival probability showed that the predictions based on the nomogram coincided well with actual observations. The C-index of the nomogram was 0.82 (0.77-0.87), and the area under curve (AUC) of the nomogram in predicting overall survival (OS) was 0.938, both of which were significantly higher than the traditional TNM stage. Decision curve analysis further demonstrated that our nomogram had larger net benefit than TNM stage. Conclusion An inclusive nomogram for patients with LSCC, comprising genomic and clinicopathologic variables, generates more accurate estimations of the survival probability when compared with TNM stage alone, but more data are needed before the nomogram is used in clinical practice.

Transcriptome Analyses Implicate Endogenous Retroviruses Involved in the Host Antiviral Immune System through the Interferon Pathway

“…Indeed, AL445490.1, which is the antisense sequence of IFI6, has been described to regulate the expression of neighboring genes to affect HCV replication (Liu et al 2019;Unfried and Fortes 2020). In addition, AL356414.1 was reported to be a prognosis-related lncRNA of laryngeal squamous cell carcinoma (Cui et al 2019), while AC116366.1 could reflect the immune infiltrating status of breast cancer (Li et al 2020), and they were found to be associated with viral infection in this study. Collectively, these results suggest that some particular old HERVs may play a role in the induction of innate immune response as well as in the evolution of host interferon regulatory network.…”

The LncRNA FGD5‐AS1/miR‐497‐5p axis regulates septin 2 (SEPT2) to accelerate cancer progression and increase cisplatin‐resistance in laryngeal squamous cell carcinoma

“…As one of the common malignancies in the head and neck, laryngeal squamous cell carcinoma (LSCC) brings a huge health burden for patients worldwide 1,2 . The risk factors that contribute to the onset, initiation, and development of LSCC are complicated and include smoking, alcohol drinking, environmental stress, radioactivity, viral infection, and microelement deficiency 3–6 . Currently, the main treatment strategies for LSCC include surgery, radiotherapy, and chemotherapy, but their therapeutic efficacy is seriously limited as the results of LSCC's complicated pathogenesis mechanisms 7–10 .…”

A dynamic prognostic nomogram to predict the benefit from surgical treatment modality for patients with laryngeal squamous cell carcinoma

“…Nomograms, characterized by its precise individual predictions for clinical events, have been more and more frequently used as adjuncts in risk calculations and clinical decision making 26 . Although previous studies have constructed several nomograms specific to laryngeal cancer, some studies integrated costly biomarkers into the model, which restricts its applicability in routine clinical practice, and some studies established the nomogram with older data, which may not be directly relevant to current patients 12,27 . Moreover, most of these studies transformed the continuous predictive variables as categorical ones, to some extent resulting in degrading survival prediction accuracy for individuals.…”