Comprehensive Gene Expression Analysis and Identification of Stat-1 as Master Regulator in Oral Squamous Cell Carcinoma

Ariya S.S.; Akhila Rachel James; Baby Joseph

doi:10.61841/y9wxeh94

Authors

Ariya S.S. Department of Biotechnology, Hindustan Institute of Technology and Science, Chennai, Tamilnadu, India Author
Akhila Rachel James Department of Biotechnology, Hindustan Institute of Technology and Science, Chennai, Tamilnadu, India. Author
Dr. Baby Joseph Prof., Dean Research, Department of Research, Hindustan Institute of Technology and Science, No: 1., Rajeev Gandhi Saalai (OMR), Padur, Kelambakkam, Chennai, Kancheepuram Dist, Tamilnadu, India. Author

DOI:

https://doi.org/10.61841/y9wxeh94

Keywords:

Oral Squamous Cell Carcinoma (OSCC), The Cancer Genome Atlas

Abstract

Gene expression profiling and analysis help in the identification of master regulators inducing disease. The GEO dataset GSE74530, comprising samples from 6 normal and 6 oral cancer patients, was analyzed using the R package of the Bioconductor program GEO2R. The differentially expressed genes among the samples were identified using the Benjamini-Hochberg method. The up-regulated and down-regulated genes were identified based on fc value > 2.0 and p-value < 0.5. A protein interaction network was constructed for the up-regulated and down-regulated genes with data from the BioGrid and Reactome databases. The network was further explored by applying mathematical models for topological interaction analysis to determine the hub genes. Signal transducer and activator of transcription 1 (STAT1) was identified as the master regulator of oral squamous cell carcinoma (OSCC). Cross-validation with the Cancer Genome Atlas (TCGA) followed by gene ontology and functional enrichment analysis also revealed the role of STAT1 in the progression of OSCC. Survival analysis with respect to expression of gene also showed the decrease in rate of patient prognosis with increase in expression of STAT1.

Downloads

Download data is not yet available.

References

[1] Johnson NW, Jayasekara P, Amarasinghe AA. Squamous cell carcinoma and precursor lesions of the oral

cavity: epidemiology and etiology. Periodontol 2000. 2011;57:19–37.

[2] Ahmed SP, Jayan L, Dineshlumar T, Raman S. Oral Squamous Cell Carcinoma under microscopic vision:

A review of histological variants and their prognostic indicators. SRM J Res Dent Sci 2019;10:90-7.

[3] Pires FR, Ramos AB, Oliveira JB, Tavares AS, Luz PS, Santos TC. Oral squamous cell carcinoma:

clinicopathological features from 346 cases from a single oral pathology service during an 8-year

period. Journal of applied oral science: revista FOB. 2013;21(5):460–7. 10.1590/1679-775720130317

[4] Ohno S. Major sex-determining genes. Springer-Verlag; Berlin, Germany: 1979

[5] Oghumu S, Knobloch TJ, Terrazas C, Varikuti S et al. Deletion of macrophage migration inhibitory factor

inhibits murine oral carcinogenesis: Potential role for chronic pro-inflammatory immune mediators. Int J

Cancer 2016 Sep 15;139(6):1379-90.

[6] Edgar Ron, Michael Domrachev, and Alex E. Lash. Gene Expression omnibus: NCBI gene expression and

hybridization array data repository. Nucleic Acid Research; 2002; 30(1):207-10.

[7] Barrett, Tanya, Stephen E. Wilhite, Pierre Ledoux, Carlos Evangelista, Irene F. Kim, Maxim Tomashevsky,

et al. NCBI GEO: archive for functional genomics data sets—update. Nucleic Acids Res. 2013; 41:D991-5.

[8] Gentleman Robert C, Vincent J Carey, Douglas M Bates, Ben Bolstad, Marcel Dettling, Sandrine Dudoit,

et al. Bioconductor: open software development for computational biology and bioinformatics. Genome

Biol. 2004;5(10):R80.

[9] Benjamini, Yoav, and Yosef Hochberg. Controlling the False Discovery Rate: A Practical and Powerful

Approach to Multiple Testing. Journal of the Royal Statistical Society. Series B (Methodological) 1995;

57(1):289-300.

[10] G. Dennis, Jr, Brad T Sherman, Douglas A Hosack, Jun Yang, Wei Gao, H Clifford Lane, and Richard A

Lempicki, David: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol. 2003;

4(9): R60.

[11] M. Kanehisa, Yoko Sato, Masayuki Kawashima, Miho Furumichi, and Mao Tanabe. KEGG as a reference

resource for gene and protein annotation. Nucleic Acids Research, 44: D1, 2016, D457–D462.

[12] E. Eden, Roy Navon, Israel Steinfeld, Doron Lipson, and Zohar Yakhini. G Orilla: a tool for discovery and

visualization of enriched GO terms in ranked gene lists. BMC Bioinformatics 10, 48 (2009).

[13] Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment

for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498-504.

[14] Villaveces Jose M., Rafael C. Jimenez, and Bianca H. Habermann. PsicquicGraph, a BioJS component to

Visualize molecular interactions from PSICQUIC servers. Version 1F1000Res. 2014; 3-44.

[15] Chin Chia-Hao, Shu-Hwa Chen, Hsin-Hung Wu, Chin-Wen Ho, Ming-Tat Ko, and Chung-Yen Lin.

CytoHubba: identifying hub objects and sub-networks from complex interactomes. BMC Syst Biol. 2014;

8(4):1-7.

[16] Darshan S. Chandrashekar, Bhuwan Bashel, Sai Akshaya Hodigere Balasubramanya, Chad J. Creighton, Israel Ponce-Rodriguez, and Balabhadrapatruni V.S.K. Chakravarthi. UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses. Neoplasia 2017; 19(8): 649–658.

[17] Uhlén M, Fagerberg L, Hallström BM, Lindskog C, Oksvold P, Mardinoglu A, et al. Proteomics. Tissue-based map of the human proteome. Science. 2015; 347(6220):1260419.

[18] Zhang Y, Liu Z. STAT1 in cancer: friend or foe? Discov Med. 2017, 24 (130): 19-29.

[19] Meissl K, Maschler SM, and Strobl MB. The good and the bad faces of STAT1 in solid tumors. Cytokine. 2017, 89: 12-20.