Dataset Information

Gene-expression signature predicts survival benefit from postoperative chemoradiotherapy in head and neck squamous cell carcinoma.

ABSTRACT: Postoperative radiotherapy or concurrent chemoradiotherapy are routine clinical options for the treatment of head and neck squamous cell carcinoma (HNSCC). However, the benefit of adding chemotherapy to radiotherapy is contested. The present study aimed to develop a gene signature to predict the clinical benefit of postoperative chemoradiotherapy using public data from The Cancer Genome Atlas. A 22-gene signature was established, which demonstrated the best predictive value. Patients were separated into low-score and high-score subgroups based on the expression score of the 22-gene signature. In the high-score subgroup, patients who received chemoradiotherapy demonstrated improved overall survival, relapse-free survival and local regional control compared with those who received radiotherapy alone. However, in the low-score subgroup adding chemotherapy to radiotherapy was associated with worse patient outcomes. The predictive value of the 22-gene signature was independent of the conventional clinical variables. Gene set enrichment analysis revealed that the expression signatures of hypoxia phenotype and stem-like traits were significantly enriched in the low-score subgroup. In addition, the low-score subgroup was associated with the gene sets involved in resistance to anticancer drugs. In conclusion, hypoxia- or stem-like gene expression properties are associated with chemotherapy-resistance in HNSCC. The 22-gene signature may be useful as a predictive marker to help distinguish patients who will benefit from postoperative concurrent chemoradiotherapy.

SUBMITTER: Chen J

PROVIDER: S-EPMC6036555 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Gene-expression signature predicts survival benefit from postoperative chemoradiotherapy in head and neck squamous cell carcinoma.

Chen Jin J Fu Guiming G Chen Yibo Y Zhu Guiquan G Wang Zhaohui Z

Oncology letters 20180613 2

Postoperative radiotherapy or concurrent chemoradiotherapy are routine clinical options for the treatment of head and neck squamous cell carcinoma (HNSCC). However, the benefit of adding chemotherapy to radiotherapy is contested. The present study aimed to develop a gene signature to predict the clinical benefit of postoperative chemoradiotherapy using public data from The Cancer Genome Atlas. A 22-gene signature was established, which demonstrated the best predictive value. Patients were separa ...[more]

PMID: 30013651

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Project description:BackgroundHead and neck squamous cell carcinoma (HNSCC) is a common cancer characterized by late diagnosis and poor prognosis. The aim of this study was to identify a novel ferroptosis-related DNA methylation signature as an alternative diagnosis index for patients with HNSCC.MethodsMethylome and transcriptome data of 499 HNSCC patients, including 275 oral squamous cell carcinoma (OSCC) samples, were obtained from The Cancer Genome Atlas (TCGA). An additional independent methylation dataset of 50 OSCC patients from the NCBI Gene Expression Omnibus (GEO) database was used for validation. As an index of ferroptosis activity, the ferroptosis score (FS) of each patient was inferred from the transcriptome data using single-sample gene set enrichment analysis. Univariate, multivariate, and LASSO Cox regression analyses were used to select CpG sites for the construction of a ferroptosis-related DNA methylation signature for diagnosis of patients.ResultsWe initially inferred the FS of each TCGA HNSCC patient and divided the samples into high- and low-FS subgroups. Results showed that the high-FS subgroup displayed poor overall survival. Moreover, 378 differentially methylated CpG sites (DMCs) were identified between the two HNSCC subgroups, with 16 selected to construct a 16-DNA methylation signature for risk prediction in HNSCC patients using the LASSO and multivariate Cox regression models. Relative operating characteristic (ROC) curve analysis showed great predictive efficiency for 1-, 3-, and 5-year HNSCC survival using the 16-DNA methylation signature. Its predictive efficiency was also observed in OSCC patients from the TCGA and GEO databases. In addition, we found that the signature was associated with the fractions of immune types in the tumor immune microenvironment (TIME), suggesting potential interactions between ferroptosis and TIME in HNSCC progression.ConclusionsWe established a novel ferroptosis-related 16-DNA methylation signature that could be applied as an alternative tool to predict prognosis outcome in patients with HNSCC, including OSCC.

Project description:BackgroundHead and neck squamous cell carcinoma (HNSCC) is a common malignancy that emanates from the lips, mouth, paranasal sinuses, oropharynx, larynx, nasopharynx, and from other pharyngeal cancers. The availability of high-throughput expression data has made it possible to use global gene expression data to analyze the relationship between metabolic-related gene expression and clinical outcomes in HNSCC patients.MethodIn this study, we used RNA sequencing (RNA-seq) data from the cancer genome atlas (TCGA), with validation in the GEO dataset to profile the metabolic microenvironment and define potential biomarkers for metabolic therapy.ResultsWe extracted data for 529 patients and 327 metabolic genes (198 upregulated and 129 downregulated genes) in the TCGA database. Carbonic anhydrase 9 (CA9) and CA6 had the largest logFCs in the upregulated and downregulated genes, respectively. Our Cox regression model data showed 51 prognostic-related genes with lysocardiolipin acyltransferase 1 (LCLAT1) and choline dehydrogenase (CHDH) being associated with the highest risk (HR = 1.144, 95% CI = 1.044 ~ 1.251) and the lowest risk (HR = 0.580, 95% CI = 0.400 ~ 0.839) in HNSCC, respectively. We next used the ROC curve to evaluate whether the differentially expressed metabolic-related genes could serve as early predictors of HNSCC. The findings showed an AUC of 0.745 and 0.618 in the TCGA and GEO analysis, respectively. Besides, the ability for the genes to predict clinicopathological HNSCC status was analyzed and the data showed that the AUC for age, gender, grade, stage, T, M, and N was 0.520, 0.495, 0.568, 0.606, 0.577, 0.476, and 0.673, respectively, in the TCGA dataset. On the other hand, the AUC for age, gender, stage, T, M, N, smoking, and HPV16-pos was 0.599, 0.531, 0.622, 0.606, 0.616, 0.550, 0.614, 0.519, and 0.397, respectively, in the GEO dataset.ConclusionTaken together, our study unearths a novel metabolic gene signature for the prediction of HNSCC prognosis based on the TCGA dataset. Our signature might point out the metabolic microenvironment disorders and provides potential treatment targets and prognostic biomarkers.

Dataset Information

Gene-expression signature predicts survival benefit from postoperative chemoradiotherapy in head and neck squamous cell carcinoma.

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Gene-expression signature predicts survival benefit from postoperative chemoradiotherapy in head and neck squamous cell carcinoma.

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