Survival-Based Biomarker Module Identification Associated with Oral Squamous Cell Carcinoma (OSCC)

Biology

卷:10

Prithvi Singh¹  Ravins Dohare¹  Amit Kumar Verma²  Kapil Dev²  Shweta Sankhwar³  Mohammed A. Alsahli⁴  Faris Alrumaihi⁴  Arshad Husain Rahmani⁴  Saleh A. Almatroodi⁴  Arpita Rai⁵  Anuradha Sinha⁶ 

[1] Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India;

[2] Department of Biotechnology, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi 110025, India;

[3] Department of Computer Science, Maitreyi College, University of Delhi, New Delhi 110021, India;

[4] Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah 51452, Saudi Arabia;

[5] Department of Oral Medicine and Radiology, Dental Institute, Rajendra Institute of Medical Sciences, Bariatu, Ranchi 834009, India;

[6] Department of Oral Pathology, St. George Hospital Campus, Government Dental College & Hospital, Mumbai 400001, India;

关键词: module;    survival rate;    weighted network;    key genes;    protein–protein interaction;   

DOI  :  10.3390/biology10080760

来源: DOAJ

【 摘 要 】

Head and neck squamous cell carcinoma (HNSC) is one of the most common malignant tumors worldwide with a high rate of morbidity and mortality, with 90% of predilections occurring for oral squamous cell carcinoma (OSCC). Cancers of the mouth account for 40% of head and neck cancers, including squamous cell carcinomas of the tongue, floor of the mouth, buccal mucosa, lips, hard and soft palate, and gingival. OSCC is the most devastating and commonly occurring oral malignancy, with a mortality rate of 500,000 deaths per year. This has imposed a strong necessity to discover driver genes responsible for its progression and malignancy. In the present study we filtered oral squamous cell carcinoma tissue samples from TCGA-HNSC cohort, which we followed by constructing a weighted PPI network based on the survival of patients and the expression profiles of samples collected from them. We found a total of 46 modules, with 18 modules having more than five edges. The KM and ME analyses revealed a single module (with 12 genes) as significant in the training and test datasets. The genes from this significant module were subjected to pathway enrichment analysis for identification of significant pathways and involved genes. Finally, the overlapping genes between gene sets ranked on the basis of weighted PPI module centralities (i.e., degree and eigenvector), significant pathway genes, and DEGs from a microarray OSCC dataset were considered as OSCC-specific hub genes. These hub genes were clinically validated using the IHC images available from the Human Protein Atlas (HPA) database.

【 授权许可】

Unknown