A potential panel of two-long non-coding RNA signature to predict recurrence of patients with laryngeal cancer

Prognostic Significance of Oxidation Pathway Mutations in Recurrent Laryngeal Squamous Cell Carcinoma

Simple Summary

Organ preservation protocols have become first line therapy for the majority of advanced laryngeal cancers. Unfortunately, up to one third of patients will develop recurrent disease requiring salvage surgery. These tumors tend to display aggressive features when compared to primary disease. The aim of this study is to identify genomic alterations associated with poor prognosis in the recurrent setting to guide precision therapy and identify potential targetable pathways. Here we show that mutations in the oxidation pathway, specifically the KEAP1-NFR2 pathway, predict survival in a cohort of patients undergoing salvage laryngectomy.

Abstract

Organ preservation protocols are commonly used as first line therapy for advanced laryngeal cancer. Recurrence thereafter is associated with poor survival. The aim of this study is to identify genetic alterations associated with survival among patients with recurrent laryngeal cancer undergoing salvage laryngectomy. Sixty-two patients were sequenced using a targeted panel, of which twenty-two also underwent transcriptome sequencing. Alterations were grouped based on biologic pathways and survival outcomes were assessed using Kaplan-Meier analysis and multivariate cox regression. Select pathways were evaluated against The Cancer Genome Atlas (TCGA) data. Patients with mutations in the Oxidation pathway had significantly worse five-year disease specific survival (1% vs. 76%, p = 0.02), while mutations in the HN-Immunity pathway were associated with improved five-year disease specific survival (100% vs. 62%, p = 0.02). Multivariate analysis showed mutations in the Oxidation pathway remained an independent predictor of disease specific survival (HR 3.2, 95% CI 1.1–9.2, p = 0.03). Transcriptome analysis of recurrent tumors demonstrated that alterations in the Oxidation pathway were associated a positive Ragnum hypoxia signature score, consistent with enhanced pathway activity. Further, TCGA analyses demonstrated the prognostic value of oxidation pathway alterations in previously untreated disease. Alterations in the Oxidation pathway are associated with survival among patients with recurrent laryngeal cancer. These prognostic genetic biomarkers may inform precision medicine protocols and identify putatively targetable pathways to improve survival in this cohort.

Development and validation of nomograms to accurately predict risk of recurrence for patients with laryngeal squamous cell carcinoma: Cohort study

BACKGROUND

Recurrence is still major obstacle to long-term survival in laryngeal squamous cell carcinoma (LSCC). We aimed to establish and validate a nomogram to precisely predict recurrence probability in patients with LSCC.

METHODS

A total of 283 consecutive patients with LSCC received curative-intend surgery between 2011 and 2014 at were enrolled in this study. Subsequently, 283 LSCC patients were randomly assigned to a training cohort (N = 171) and a validation cohort (N = 112) in a 3:2 ratio. According to the results of multivariable Cox regression analysis in the training cohort, we developed a nomogram. The predictive accuracy and discriminative ability of the nomogram were evaluated by calibration curve and concordance index (C-index), and compared with TNM stage system by C-index, receiver operating characteristic (ROC) analysis. Decision curve analysis (DCA) was performed to estimate clinical value of our nomogram.

RESULTS

Six independent factors rooted in multivariable analysis of the training cohort to predict recurrence were age, tumor site, smoking, alcohol, N stage and hemoglobin, which were all integrated into the nomogram. The calibration curve for the probability of recurrence presented that the nomogram-based predictions were in good correspondence with actual observations. The C-index of the nomogram was 0.81 (0.75-0.88), and the area under curve (AUC) of nomogram in predicting recurrence free survival (RFS) was 0.894, which were significantly better than traditional TNM stage. Decision curve analysis further affirmed that our nomogram had a larger net benefit than TNM stage. The results were confirmed in the validation cohort.

CONCLUSION

A risk prediction nomogram for patients with LSCC, incorporating readily assessable clinicopathologic variables, generates more accurate estimations of the recurrence probability when compared TNM stage alone, but still needs additional data before being used in clinical implications.

Transcriptome Analysis Identifies ALCAM Overexpression as a Prognosis Biomarker in Laryngeal Squamous Cell Carcinoma

BACKGROUND

Laryngeal squamous cell carcinoma (LSCC) is one of the most incident tumors in the world, especially in developing countries, such as Brazil. Different from other tumors, LSCC prognosis did not improve during the past four decades. Therefore, the objective of this study was to develop biomarkers that can predict LSCC patient's prognosis.

RESULTS

Transcriptome analysis pointed out 287 overexpressed genes in LSCC in comparison to adjacent mucosa. Among these, a gene-pattern signature was created with 24 genes associated with prognosis. The Bayesian clustering of both Brazil and The Cancer Genome Atlas (TCGA) data pointed out clusters of samples possessing significative differences in the prognosis, and the expression panel of three genes (ALCAM, GBP6, and ME1) was capable to distinguish patients with worse prognosis with an accuracy of 97%. Survival analyses with TCGA data highlighted ALCAM gene expression as an independent prognostic factor for LSCC. This was further confirmed through immunohistochemistry, using a validation set of Brazilian patients. ALCAM expression was not associated with prognosis for other head and neck tumor sites.

CONCLUSION

ALCAM overexpression seems to be an independent prognosis biomarker for LSCC patients.

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

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.

Linc00423 as a tumor suppressor in retroperitoneal liposarcoma via activing MAPK signaling pathway through destabilizing of NFATC3

Unraveling the noncoding RNA expression networks governing cancer initiation and development is essential while remains largely uncompleted in retroperitoneal liposarcoma (RLS). Through RNA-seq technologies and computational biology, deregulated long noncoding RNAs (lncRNAs) are being identified and reveal that lncRNAs are implicated in serial steps of RLS development. High-throughput sequencing with computational methods for assembling the transcriptome of five paired RLS patient’s tissues. We found that long intergenic noncoding RNA 423 (linc00423) was downregulated in RLS tissues. Gain-of-function assays revealed that overexpressed linc00423 obviously inhibited RLS cell growth in vitro and in vivo. Additionally, RNA sequence, RNA-pulldown and RIP assays evidenced that linc00423 involved in MAPK signaling pathway via destabilizing of nuclear factor of activated T-cells 3 (NFATC3). Summing up, our findings demonstrated that linc00423 acted as the tumor suppressor in RLS cells through regulating the protein level of NFATC3 at a post-transcriptional level and negatively regulated the MAPK signaling pathway at a transcriptional level. Linc00423 might serve as a candidate prognostic biomarker and a target for novel therapies of RLS patients.

An integrated mRNA-lncRNA signature for relapse prediction in laryngeal cancer

Patients with laryngeal cancer with early relapse usually have a poor prognosis. In this study, we aimed to identify a multi-gene signature to improve the relapse prediction in laryngeal cancer. One microarray data set GSE27020 (training set, N = 109) and one RNA-sequencing data set (validation set, N = 85) were included into the analysis. In the training set, the microarray expression profile was re-annotated into an mRNA-long noncoding RNA (lncRNA) biphasic profile. Then, LASSO Cox regression model identified nine relapse-related RNA (eight mRNA and one lncRNA), and a risk score was calculated for each sample according to the model coefficients. Patients with high-risk showed poorer relapse-free survival than patients with low risk (hazard ratios (HR): 6.189, 95% confidence interval (CI): 3.075-12.460, P < 0.0001). The risk score demonstrated good accuracy in predicting the relapse (area under time-dependent receiver-operating characteristic (AUC): 0.859 at 1 year, 0.822 at 3 years, and 0.815 at 5 years). The results were validated in the validation set (HR: 3.762, 95% CI: 1.594-8.877, P = 0.011; AUC: 0.770 at 1 year, 0.769 at 3 years, and 0.728 at 5 years). The multivariate analysis reached consistent results after adjustment by multiple confounders. When compared with a 27-gene signature, a 2-lncRNA signature, and Tumor-Node-Metastasis stage, the risk score also showed better performance (P < 0.05). In conclusion, we successfully developed a robust mRNA-lncRNA signature that can accurately predict the relapse in laryngeal cancer.

Signature microRNAs and long noncoding RNAs in laryngeal cancer recurrence identified using a competing endogenous RNA network

The aim of the present study was to identify novel microRNA (miRNA) or long noncoding RNA (lncRNA) signatures of laryngeal cancer recurrence and to investigate the regulatory mechanisms associated with this malignancy. Datasets of recurrent and nonrecurrent laryngeal cancer samples were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus database (GSE27020 and GSE25727) to examine differentially expressed miRNAs (DE-miRs), lncRNAs (DE-lncRs) and mRNAs (DEGs). miRNA-mRNA and lncRNA-miRNA networks were constructed by investigating the associations among these RNAs in various databases. Subsequently, the interactions identified were combined into a competing endogenous RNA (ceRNA) regulatory network. Feature genes in the miRNA-mRNA network were identified via topological analysis and a recursive feature elimination algorithm. A support vector machine (SVM) classifier was established using the betweenness centrality values in the miRNA-mRNA network, consisting of 32 optimal feature-coding genes. The classification effect was tested using two validation datasets. Furthermore, coding genes in the ceRNA network were examined via pathway enrichment analyses. In total, 21 DE-lncRs, 507 DEGs and 55 DE-miRs were selected. The SVM classifier exhibited an accuracy of 94.05% (79/84) for sample classification prediction in the TCGA dataset, and 92.66 and 91.07% in the two validation datasets. The ceRNA regulatory network comprised 203 nodes, corresponding to mRNAs, miRNAs and lncRNAs, and 346 lines, corresponding to the interactions among RNAs. In particular, the interactions with the highest scores were HLA complex group 4 (HCG4)-miR-33b, HOX transcript antisense RNA (HOTAIR)-miR-1-MAGE family member A2 (MAGEA2), EMX2 opposite strand/antisense RNA (EMX2OS)-miR-124-calcitonin related polypeptide α (CALCA) and EMX2OS-miR-124-γ-aminobutyric acid type A receptor γ2 subunit (GABRG2). Gene enrichment analysis of the genes in the ceRNA network identified that 11 pathway terms and 16 molecular function terms were significantly enriched. The SVM classifier based on 32 feature coding genes exhibited high accuracy in the classification of laryngeal cancer samples. miR-1, miR-33b, miR-124, HOTAIR, HCG4 and EMX2OS may be novel biomarkers of recurrent laryngeal cancer, and HCG4-miR-33b, HOTAIR-miR-1-MAGEA2 and EMX2OS-miR-124-CALCA/GABRG2 may be associated with the molecular mechanisms regulating recurrent laryngeal cancer.

Long non-coding RNA TRPM2-AS as a potential biomarker for hepatocellular carcinoma

BACKGROUND

There is increasing evidence that long non-coding RNAs are involved in hepatocellular carcinoma (HCC) tumorigenesis. The expression level of TRPM2-AS in HCC and its clinical association remain poorly defined.

METHOD

qRT-PCR was performed to detect the expression of TRPM2-AS in 108 HCC patients. The correlations between TRPM2-AS expression and clinicopathological factors and prognosis were evaluated. The inference of TRPM2-AS to the proliferation and apoptosis of HCC cells was detected.

AIMS

The aim of our study was to explore the expression of TRPM2-AS in hepatocellular carcinoma (HCC) and the relation with prognosis and clinical features.

RESULTS

The expression of TRPM2-AS was higher in most HCC tissues and was significantly correlated with tumor size, AJCC stage, tumor differentiation, and the prognosis of HCC patients. Interfering TRPM2-AS expression using siRNA significantly inhibited cell proliferation and promoted cell apoptosis in two HCC cell lines.

CONCLUSION

Long non-coding RNA TRPM2-AS is upregulated in HCC and represents a new biomarker for HCC and the inhibition of TRPM2-AS promotes apoptosis in HCC cells in vitro.