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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.

SUBMITTER: Cui J

PROVIDER: S-EPMC6886334 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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

Cui Jie J Wen Qingquan Q Tan Xiaojun X Chen Zhen Z Liu Genglong G

Disease markers 20191120

<h4>Background</h4>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).<h4>Methods</h4>A LSCC RNA-sequencing (RNA-seq) dataset and the matched clinicopathologic information were downloa ...[more]

PMID: 31827637

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Project description:To the best of our knowledge, this is the first study established a nomogram to predict survival probability in Asian patients with LSCC. A risk prediction nomogram for patients with LSCC, incorporating easily assessable clinicopathologic factors, generates more precise estimations of the survival probability when compared TNM stage alone, but still need additional data before being used in clinical application. BACKGROUND:Due to a wide variation of tumor behavior, prediction of survival in laryngeal squamous cell carcinoma (LSCC) patients received curative-intent surgery is an important but formidable challenge. We attempted to establish a nomogram to precisely predict survival probability in LSCC patients. METHODS:A total of 369 consecutive LSCC patients underwent curative resection between 2008 and 2012 at Hunan Province Cancer Hospital were included in the present study. Subsequently, 369 LSCC patients were assigned to a training set (N=261) and a validation set (N=108) at random. On the basis of multivariable Cox regression analysis results, we developed a nomogram. The predictive accuracy and discriminative ability of the nomogram were confirmed by calibration curve and a concordance index (C-index), and compared with TNM stage system by C-index, receiver operating characteristic (ROC) analysis. RESULTS:Six independent parameters to predict prognosis were age, pack years, N-stage, lymph node ratio (LNR), anemia and albumin, which were all assembled into the nomogram. The calibration curve verified excellent models' concordance. The C-index of the nomogram was 0.73 (0.68-0.78), and the area under curve (AUC) of nomogram in predicting overall survival (OS) was 0.766, which were significantly higher than traditional TNM stage. Decision curve analysis further demonstrated that our nomogram had a larger net benefit than the TNM stage. CONCLUSION:A risk prediction nomogram for patients with LSCC, incorporating easily assessable clinicopathologic factors, generates more precise estimations of the survival probability when compared TNM stage alone, but still need additional data before being used in clinical application.

Project description:BACKGROUND:Immunoscore, as a prognostic tool defined to quantify in situ immune cell infiltrates, appears to be superior to the TNM staging system. In esophageal squamous cell carcinoma (ESCC), no immunoscore has been established; however, in situ tumor immunology is recognized as highly important. Our study aimed to construct a comprehensive immunoprofile for ESCC. METHODS:The infiltration of four immune cell types (CD8+/CD4+/Foxp3+/CD33+ cells), the expression of both inhibitory (PD-1/PD-L1/Tim-3/LAG-3) and stimulatory checkpoints (OX-40/ICOS), and IDO1 were evaluated by IHC staining and multi-color immunofluorescence in two independent cohorts (95 patients in the primary cohort and 55 patients in the validation cohort). The association with patients' overall survival was analyzed by the Kaplan-Meier method and the Cox model. Nomogram-based immunoprofile was established using the independent prognostic variables. To determine its predictive accuracy and discriminatory capacity, the C-index and calibration curve were calculated. RESULTS:Significant correlation of PD-L1 expression in tumor cells with PD-1+ T cell infiltration was found (P?=?0.035), indicating the activation of the inhibitory PD-1/PD-L1 pathway in ESCC cases. More PD-L1+ ICs, Tim-3+ ICs and LAG-3+ ICs were found in the CD8-rich tumor microenvironment, which is in accordance with the feedback nature of immune system. After adjustment by TNM stage, four immune variables including the infiltration of CD8+/Foxp3+/CD33+ cells and the PD-L1 expression by tumor cells were selected to construct a prognostic nomogram. The calibration curves showed good accuracy of the nomogram for survival prediction. To overcome the complexity of applying a nomogram in a clinical setting, a simple immunoprofile was then established according to the points of each factor from the nomogram. Our immunoprofile model could separate same-stage patients into different risk subgroups, and showed superior accuracy for survival prediction than the TNM staging system based on the C-index calculation and ROC analysis. CONCLUSIONS:Our nomogram-based immunoprofile can provide more accurate prognosis prediction and is an important complement to the TNM staging system for operable ESCC patients.

Dataset Information

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

Publications

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

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