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. 2022 May 13;12(1):7952.
doi: 10.1038/s41598-022-11590-1.

Integrated computational analysis reveals HOX genes cluster as oncogenic drivers in head and neck squamous cell carcinoma

U Sangeetha Shenoy  1 , Richard Morgan  2 , Keith Hunter  3 , Shama Prasada Kabekkodu  1 , Raghu Radhakrishnan  4
Affiliations

Integrated computational analysis reveals HOX genes cluster as oncogenic drivers in head and neck squamous cell carcinoma

U Sangeetha Shenoy et al. Sci Rep. .

Abstract

Alterations in homeobox (HOX) gene expression are involved in the progression of several cancer types including head and neck squamous cell carcinoma (HNSCC). However, regulation of the entire HOX cluster in the pathophysiology of HNSCC is still elusive. By using different comprehensive databases, we have identified the significance of differentially expressed HOX genes (DEHGs) in stage stratification and HPV status in the cancer genome atlas (TCGA)-HNSCC datasets. The genetic and epigenetic alterations, druggable genes, their associated functional pathways and their possible association with cancer hallmarks were identified. We have performed extensive analysis to identify the target genes of DEHGs driving HNSCC. The differentially expressed HOX cluster-embedded microRNAs (DEHMs) in HNSCC and their association with HOX-target genes were evaluated to construct a regulatory network of the HOX cluster in HNSCC. Our analysis identified sixteen DEHGs in HNSCC and determined their importance in stage stratification and HPV infection. We found a total of 55 HNSCC driver genes that were identified as targets of DEHGs. The involvement of DEHGs and their targets in cancer-associated signaling mechanisms have confirmed their role in pathophysiology. Further, we found that their oncogenic nature could be targeted by using the novel and approved anti-neoplastic drugs in HNSCC. Construction of the regulatory network depicted the interaction between DEHGs, DEHMs and their targets genes in HNSCC. Hence, aberrantly expressed HOX cluster genes function in a coordinated manner to drive HNSCC. It could provide a broad perspective to carry out the experimental investigation, to understand the underlying oncogenic mechanism and allow the discovery of new clinical biomarkers for HNSCC.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
The workflow of in silico analysis of the HOX genes and HOX-embedded miRNA network in Head and Neck Squamous Cell Carcinoma (HNSCC).
Figure 2
Figure 2
Differentially expressed HOX genes (DEHGs) and their genetic variation in HNSCC: (a) Single Nucleotide Variants (SNV): Oncoplot showing the top ten mutated genes in the HNSCC data set. The type of SNV is color-coded as shown in the figure. Bar plots on the side and top of the figure, show the number of variants in each sample and gene respectively. (b) Copy Number Variation (CNV): Pie chart represents the global profile that shows the proportion of heterozygous or homozygous CNV of each gene in HNSCC. c) CNV profile shows the percentage of heterozygous amplification, about each gene with > 5% CNV in HNSCC. Red color bubble intensity represents the positive correlation between higher gene expression levels and the high frequency of CNVs. The size of the point positively correlates with statistical significance.
Figure 3
Figure 3
Co-expression analysis: (a) Overview of PPI Network of 16 DEHGs, with > 0.7 confidence score constructed using STRING v11.5 database. The network includes 8 edges between 16 nodes that show the co-expression amongst DEHGs. (b) Pathway analysis: A heatmap showing DEHGs that activate (A) and inhibit (I) pathways in HNSCC using GSCALite.
Figure 4
Figure 4
Survival analysis of DEHGs: (a) Represents the survival analysis of DEHGs by constructing the prediction model using Random Forest Algorithm: Patients with prediction score larger than 0.5 is considered as high risk, while lower than 0.5 is classified under low risk using log-rank test. (b) The contribution of each DEHGs to HNSCC prognosis. (c) The Kaplan–Meier survival plot represents the number of patients surviving at each specific time point. (d-g) Kaplan–Meier plot of DEHGs associated with overall survival (OS) and disease-free survival (DFS).
Figure 5
Figure 5
HOX genes and drug sensitivity: A bubble plot showing the interaction between the DEHGs and the known and novel therapeutic drugs.
Figure 6
Figure 6
DEHMs in HNSCC: (a–f) The box plots representing the gene expression of HOX-embedded miRNAs in HNSCC, analyzed using UALCAN.
Figure 7
Figure 7
Functional role of DEHMs and their interactive network: (a) KEGG pathway analysis of upregulated targets of DEHMs. (b) KEGG pathway analysis of downregulated targets of DEHMs. (c) Interaction between DEHGs and DEHMs. (d) Venn diagram showing the targets of DEHGs driving HNSCC. (e) Functional regulatory network of entire HOX cluster genes, their targets, and DEHMs constructed using Cytoscape. The network includes nodes representing DEHGs (yellow squares) and interaction targets (green squares) derived from publicly available databases.
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References

    1. Mody MD, Rocco JW, Yom SS, Haddad RI, Saba NF. Head and neck cancer. Lancet (London, England) 2021;398:2289–2299. doi: 10.1016/S0140-6736(21)01550-6. - DOI - PubMed
    1. Ferlay J, et al. Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. Int. J. Cancer. 2019;144:1941–1953. doi: 10.1002/ijc.31937. - DOI - PubMed
    1. Vučičević Boras V, et al. Environmental and behavioural head and neck cancer risk factors. Cent. Eur. J. Public Health. 2019;27:106–109. doi: 10.21101/cejph.a5565. - DOI - PubMed
    1. Sabatini ME, Chiocca S. Human papillomavirus as a driver of head and neck cancers. Br. J. Cancer. 2020;122:306–314. doi: 10.1038/s41416-019-0602-7. - DOI - PMC - PubMed
    1. Gaździcka J, Gołąbek K, Strzelczyk JK, Ostrowska Z. Epigenetic modifications in head and neck cancer. Biochem. Genet. 2020;58:213–244. doi: 10.1007/s10528-019-09941-1. - DOI - PMC - PubMed

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