Wanli Yang1, Wei Zhou1, Xinhui Zhao2, Xiaoqian Wang1, Lili Duan1, Yiding Li1, Liaoran Niu1, Junfeng Chen1, Yujie Zhang1, Yu Han3, Daiming Fan4, Liu Hong5. 1. State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, No.127, Changle West Road, Xi'an, 710032, Shaanxi Province, China. 2. Department of Thyroid and Breast Surgery, The Affiliated Hospital of Northwest University & Xi'an No.3 Hospital, Northwest University, Xi'an, 710018, Shaanxi Province, China. 3. Department of Otolaryngology, Xijing Hospital, Fourth Military Medical University, No.127, Changle West Road, Xi'an, 710032, Shaanxi Province, China. hanyufmmu@126.com. 4. State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, No.127, Changle West Road, Xi'an, 710032, Shaanxi Province, China. hlhyhj@126.com. 5. State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, No.127, Changle West Road, Xi'an, 710032, Shaanxi Province, China. hongliufmmu@163.com.
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.
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.
Authors: Steve Oghumu; Thomas J Knobloch; Cesar Terrazas; Sanjay Varikuti; Jennifer Ahn-Jarvis; Claire E Bollinger; Hans Iwenofu; Christopher M Weghorst; Abhay R Satoskar Journal: Int J Cancer Date: 2016-06-16 Impact factor: 7.396
Authors: Kimberly D Miller; Rebecca L Siegel; Chun Chieh Lin; Angela B Mariotto; Joan L Kramer; Julia H Rowland; Kevin D Stein; Rick Alteri; Ahmedin Jemal Journal: CA Cancer J Clin Date: 2016-06-02 Impact factor: 508.702