scholarly journals Ultra-deep targeted sequencing of advanced oral squamous cell carcinoma identifies a mutation-based prognostic gene signature

Oncotarget ◽  
2015 ◽  
Vol 6 (20) ◽  
pp. 18066-18080 ◽  
Author(s):  
Shu-Jen Chen ◽  
Hsuan Liu ◽  
Chun-Ta Liao ◽  
Po-Jung Huang ◽  
Yi Huang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Gene Signature ◽  
Targeted Sequencing ◽  
Prognostic Gene ◽  
Prognostic Gene Signature

scholarly journals Identification of a Gene Signature for Rapid Screening of Oral Squamous Cell Carcinoma

2006 ◽  
Vol 12 (20) ◽  
pp. 5960-5971 ◽  
Author(s):  
Amy F. Ziober ◽  
Kirtesh R. Patel ◽  
Faizan Alawi ◽  
Phyllis Gimotty ◽  
Randall S. Weber ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Gene Signature ◽  
Rapid Screening

scholarly journals Ferroptosis-related gene signature predicts the prognosis in Oral squamous cell carcinoma patients

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hongyu Li ◽  
Xiliu Zhang ◽  
Chen Yi ◽  
Yi He ◽  
Xun Chen ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Immune Status ◽  
Risk Group ◽  
Risk Groups ◽  
Gene Signature ◽  
High Risk Group

Abstract Background The prognosis of oral squamous cell carcinoma (OSCC) patients is difficult to predict or describe due to its high-level heterogeneity and complex aetiologic factors. Ferroptosis is a novel form of iron-dependent cell death that is closely related to tumour growth and progression. This study aims to clarify the predictive value of ferroptosis-related genes (FRGs) on the overall survival(OS) of OSCC patients. Methods The mRNA expression profile of FRGs and clinical information of patients with OSCC were collected from the TCGA database. Candidate differentially expressed ferroptosis-related genes (DE-FRGs) were identified by analysing differences between OSCC and adjacent normal tissues. A gene signature of prognosis-related DE-FRGs was established by univariate Cox analysis and LASSO analysis in the training set. Patients were then divided into high- and low-risk groups according to the cut-off value of risk scores, A nomogram was constructed to quantify the contributions of gene signature and clinical parameters to OS. Then several bioinformatics analyses were used to verify the reliability and accuracy of the model in the validation set. Finally, single-sample gene set enrichment analysis (ssGSEA) was also performed to reveal the underlying differences in immune status between different risk groups. Results A prognostic model was constructed based on 10 ferroptosis-related genes. Patients in high-risk group had a significantly worse OS (p < 0.001). The gene signature was verified as an independent predictor for the OS of OSCC patients (HR > 1, p < 0.001). The receiver operating characteristic curve displayed the favour predictive performance of the risk model. The prediction nomogram successfully quantified each indicator’s contribution to survival and the concordance index and calibration plots showed its superior predictive capacity. Finally, ssGSEA preliminarily indicated that the poor prognosis in the high-risk group might result from the dysregulation of immune status. Conclusion This study established a 10-ferroptosis-releated gene signature and nomogram that can be used to predict the prognosis of OSCC patients, which provides new insight for future anticancer therapies based on potential FRG targets.

scholarly journals Identification and Validation of a Hypoxia-Immune-Based Prognostic mRNA Signature for Oral Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Shaohua Lv ◽  
Jianhao Li ◽  
Songlin Piao ◽  
jichen Li
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Immune Status ◽  
Cox Regression ◽  
Risk Group ◽  
Gene Signature ◽  
Low Risk

Abstract Background: Oral squamous cell carcinoma (OSCC) is a frequently encountered head and neck malignancy. Increasing evidence points towards an aberrant immune response and chronic cell hypoxia in the development of OSCC. However, there is a lack of a reliable hypoxia-immune-based gene signature that may serve to accurately prognosticate OSCC. Methods: The mRNA expression data of OSCC patients was extracted from the TCGA database. Hypoxia status was identified using the t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm. Both ESTIMATE and single-sample gene-set enrichment analysis (ssGSEA) was used for further evaluation of immune status. The DEGs in different hypoxia and immune status were determined. A Machine learning method-Least Absolute Shrinkage and Selection operator (LASSO) Cox regression analysis allowed us to select prognostically significant hypoxia- and immune-related mRNAs in order to construct prognostic gene signature to predict the overall survival (OS) of OSCC patients. Results: A total of 773 DEGs were classified into either Hypoxia_High and Hypoxia_Low groups. Immune-associated DEG expressions were used to divide individuals into Immune_High, Immune_ Medium and Immune_Low groups. A total of 193 mRNAs which were significant in both immune function and hypoxia status were identified. With the Lasso Cox regression model, 8 signature mRNAs (FAM122C, RNF157, RANBP17, SOWAHA, KIAA1211, RIPPLY2, INSL3, and DNAH1) associated with OS were selected for further calculation of their respective risk scores. The risk score showed a significant association with age, perineural and lymphovascular invasion. In the GEO validation cohort, a better OS was observed in patients from the low-risk group in comparison to those in the high-risk group. High-risk patients also demonstrated different immune infiltration characteristics from the low-risk group. All individuals from the TCGA OSCC cohort showed similar trends in all 6 immune checkpoints, with those of the low-risk group yielding higher immune indicator scores in contrast to their high-risk counterparts. Conclusion: The hypoxia-immune-based gene signature has prognostic potential in OSCC.

scholarly journals Prognostic biomarkers and therapeutic targets in oral squamous cell carcinoma: a study based on cross-database analysis

Hereditas ◽  
2021 ◽  
Vol 158 (1) ◽  
Author(s):  
Wanli Yang ◽  
Wei Zhou ◽  
Xinhui Zhao ◽  
Xiaoqian Wang ◽  
Lili Duan ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Molecular Mechanisms ◽  
Cox Regression ◽  
Gene Signature ◽  
Genetic Alterations ◽  
Prognostic Biomarkers ◽  
Hub Genes

Abstract Background Oral squamous cell carcinoma (OSCC) is a malignant cancer, the survival rate of patients is disappointing. Therefore, it is necessary to identify the driven-genes and prognostic biomarkers in OSCC. Methods Four Gene Expression Omnibus (GEO) datasets were integratedly analyzed using bioinformatics approaches, including identification of differentially expressed genes (DEGs), GO and KEGG analysis, construction of protein-protein interaction (PPI) network, selection of hub genes, analysis of prognostic information and genetic alterations of hub genes. ONCOMINE, The Cancer Genome Atlas (TCGA) and Human Protein Atlas databases were used to evaluate the expression and prognostic value of hub genes. Tumor immunity was assessed to investigate the functions of hub genes. Finally, Cox regression model was performed to construct a multiple-gene prognostic signature. Results Totally 261 genes were found to be dysregulated. 10 genes were considered to be the hub genes. The Kaplan-Meier analysis showed that upregulated SPP1, FN1, CXCL8, BIRC5, PLAUR, and AURKA were related to poor outcomes in OSCC patients. FOXM1 and TPX2 were considered as the potential immunotherapeutic targets with future clinical significance. Moreover, we constructed a nine-gene signature (TEX101, DSG2, SCG5, ADA, BOC, SCARA5, FST, SOCS1, and STC2), which can be utilized to predict prognosis of OSCC patients effectively. Conclusion These findings may provide new clues for exploring the molecular mechanisms and targeted therapy in OSCC. The hub genes and risk gene signature are helpful to the personalized treatment and prognostic judgement.

scholarly journals Identification of Hypoxia-Related Molecular Classification and Associated Gene Signature in Oral Squamous Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Chen Li ◽  
Xin Chen ◽  
Xiaolin Ren ◽  
Jia-lin Chen ◽  
Hao Chen ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Treatment Strategies ◽  
Molecular Classification ◽  
Gene Signature ◽  
Treatment Programs ◽  
Related Risk

The high heterogeneity of oral squamous cell carcinoma (OSCC) is the main obstacle for individualized treatment. Recognizing the characteristics of different subtypes and investigating the promising strategies for each subclass are of great significance in precise treatment. In this study, we systematically evaluated hypoxia-mediated patterns together with immune characteristics of 309 OSCC patients in the TCGA training set and 97 patients in the GSE41613 testing set. We further identified two different hypoxia subtypes with distinct immune microenvironment traits and provided treatment programs for the two subclasses. In order to assess hypoxia level individually, we finally constructed a hypoxia-related risk score, which could predict the clinical outcome and immunotherapy response of OSCC patients. In summary, the recognition of different hypoxia patterns and the establishment of hypoxia-related risk score might enhance our understanding of the tumor microenvironment of OSCC and provide more personalized treatment strategies in the future.

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