Dataset Information

Prediction of radiotherapy response with a 5-microRNA signature-based nomogram in head and neck squamous cell carcinoma.

ABSTRACT: Radiotherapy is unlikely to benefit all patients with head and neck squamous cell carcinoma (HNSCC). Therefore, novel method is warranted to predict the radiotherapy response. Our study aimed to construct a microRNA (miRNA)-based nomogram to predict clinical outcomes of patients with HNSCC receiving radiotherapy. We screened out 56 differential miRNAs by analyzing 44 paired tumor and adjacent normal samples miRNA expression profiles from The Cancer Genome Atlas (TCGA). A total of 307 patients with HNSCC receiving adjuvant radiotherapy were randomly divided into a training set (n = 154) and a validation set (n = 153). In the training set, we combined the differential miRNA profiles with clinical outcomes, and LASSO regression model was applied to establish a 5-miRNA signature. The prediction accuracy of the 5-miRNA signature was further validated. In addition, target genes of these miRNAs were predicted, and Gene Ontology (GO) analysis as well as KEGG pathway analysis was executed. A 5-miRNA signature including miR-99a, miR-31, miR-410, miR-424, and miR-495 was identified. With a cutoff value of 1.2201 from Youden's index, the training set was divided into high-risk and low-risk groups, and the 5-year overall survival was significantly different (30% vs. 73%, HR 3.65, CI 2.46-8.16; P < 0.0001). Furthermore, our 5-miRNA signature revealed that only low-risk group would benefit from radiotherapy. Then, a nomogram combining 5-miRNA signature with clinical variables to predict radiotherapy response was constructed. The analysis of 108 target genes of these miRNAs revealed some potential mechanisms in HNSCC radiotherapy response for future investigations. In conclusion, the 5-miRNA signature-based nomogram is useful in predicting radiotherapy response in HNSCC and might become a promising tool to optimize radiation strategies.

SUBMITTER: Chen L

PROVIDER: S-EPMC5852342 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Prediction of radiotherapy response with a 5-microRNA signature-based nomogram in head and neck squamous cell carcinoma.

Chen Lin L Wen Yihui Y Zhang Jingwei J Sun Wei W Lui Vivian W Y VWY Wei Yi Y Chen Fenghong F Wen Weiping W

Cancer medicine 20180223 3

Radiotherapy is unlikely to benefit all patients with head and neck squamous cell carcinoma (HNSCC). Therefore, novel method is warranted to predict the radiotherapy response. Our study aimed to construct a microRNA (miRNA)-based nomogram to predict clinical outcomes of patients with HNSCC receiving radiotherapy. We screened out 56 differential miRNAs by analyzing 44 paired tumor and adjacent normal samples miRNA expression profiles from The Cancer Genome Atlas (TCGA). A total of 307 patients wi ...[more]

PMID: 29473326

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Project description:BackgroundHead and neck squamous cell carcinoma (HNSCC) is an extremely heterogeneous malignant cancer with poor prognosis. Pyroptosis is defined as a novel inflammation-dependent programmed cell death. However, the pyroptosis-associated gene expression in HNSCC and their relationship with prognosis are still indistinct.Material and methodsWe acquired the mRNA expression information of HNSCC patients from publicly available TCGA and GEO databases. We compared the tumor issues and adjacent normal tissues in terms of the gene expression for the purpose of identifying differentially expressed genes (DEGs). Based on these genes, we established a risk signature by the LASSO Cox regression in the TCGA cohort and validated the results in a GEO cohort. We also verified the levels of relevant mRNA expression in the model by RT-qPCR analysis. Eventually, functional enrichment approach was carried out to explore the potential mechanisms.ResultsOur team found a total of 18 differentially expressed genes (DEGs) between the HNSCC and healthy samples, and 4 DEGs displayed a remarkable association with the overall survival (OS) (P < 0.05). A 4-gene signature was constructed, presenting beneficial forecast power in both TCGA and GEO cohorts. Our team categorized patients into a group with high risk and another group with low risk as per the average risk value of the 4-gene feature. The individuals in the low risk group displayed a notably greater OS compared with the high risk one (P < 0.01). The Cox regression study demonstrated the independent forecast capability of the risk score. The receiver operating characteristic approach facilitated the verification of the forecast function of the gene signature. Posterior to verification, 4 genes were aberrantly expressed in the HNSCC and healthy samples. Functional study displayed that these groups presented diverse immunity conditions.ConclusionPyroptosis-associated genes are pivotal for the prognosis of HNSCC and can serve as potential therapeutic targets.

Project description:Background: Head and neck squamous cell carcinoma (HNSCC) is a highly prevalent and malignant tumor that is difficult to effectively prognosticate outcomes. Recent reports have suggested that inflammation is strongly related to tumor progression, and several biomarkers linked to inflammation have been demonstrated to be useful for making a prognosis. The goal of this research was to explore the relevance between the inflammatory-related genes and HNSCC prognosis. Methods: The clinical information and gene expression data of patients with HNSCC were acquired from publicly available data sources. A multigene prognostic signature model was constructed in The Cancer Genome Atlas and verified in the Gene Expression Omnibus database. According to the risk score calculated for each patient, they were divided into low- and high-risk groups based on the median. The Kaplan-Meier survival curve and receiver operating characteristic curve were applied to determine the prognostic value of the risk model. Further analysis identified the independent prognostic factors, and a prognostic nomogram was built. The relationship between tumor immune infiltration status and risk scores was investigated using Spearman correlation analysis. Finally, to confirm the expression of genes in HNSCC, quantitative real-time polymerase chain reaction (qRT-PCR) was performed. Results: A prognostic model consisting of 14 inflammatory-related genes was constructed. The samples with a high risk had an apparently shorter overall survival than those with a low risk. Independent prognostic analysis found that risk scores were a separate prognostic factor in HNSCC patients. Immune infiltration analysis suggested that the abundance of B cells, CD8 T cells, M2 macrophages, myeloid dendritic cells, and monocytes in the low-risk group was higher, while that of M0, M1 macrophages, and resting NK cells was obviously higher in the high-risk group. The risk scores were related to chemotherapeutic sensitivity and the expression of several immune checkpoint genes. Moreover, CCL22 and IL10 were significantly higher in HNSCC tissues, as determined by qRT-PCR. Conclusion: Taken together, we constructed a novel inflammatory response-related gene signature, which may be used to estimate outcomes for patients with HNSCC and may be developed into a powerful tool for forecasting the efficacy of immunotherapeutic and chemotherapeutic drugs for HNSCC.

Dataset Information

Prediction of radiotherapy response with a 5-microRNA signature-based nomogram in head and neck squamous cell carcinoma.

Publications

Prediction of radiotherapy response with a 5-microRNA signature-based nomogram in head and neck squamous cell carcinoma.

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