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. 2022 Mar 18:15:3097-3120.
doi: 10.2147/IJGM.S345336. eCollection 2022.

In silico Analysis of Publicly Available Transcriptomics Data Identifies Putative Prognostic and Therapeutic Molecular Targets for Papillary Thyroid Carcinoma

Asma Almansoori #  1 , Poorna Manasa Bhamidimarri #  1 , Riyad Bendardaf  2   3 , Rifat Hamoudi  1   2   4
Affiliations

In silico Analysis of Publicly Available Transcriptomics Data Identifies Putative Prognostic and Therapeutic Molecular Targets for Papillary Thyroid Carcinoma

Asma Almansoori et al. Int J Gen Med. .

Abstract

Background: Thyroid cancer is the most common endocrine malignancy. However, the molecular mechanism involved in its pathogenesis is not well characterized.

Purpose: The objective of this study is to identify key cellular pathways and differentially expressed genes along the thyroid cancer pathogenesis sequence as well as to identify potential prognostic and therapeutic targets.

Methods: Publicly available transcriptomics data comprising a total of 95 samples consisting of 41 normal, 28 non-aggressive and 26 metastatic papillary thyroid carcinoma (PTC) cases were used. Transcriptomics data were normalized and filtered identifying 9394 differentially expressed genes. The genes identified were subjected to pathway analysis using absGSEA identifying PTC related pathways. Three of the genes identified were validated on 508 thyroid cancer biopsies using RNAseq and TNMplot.

Results: Pathway analysis revealed a total of 2193 differential pathways among non-aggressive samples and 1969 among metastatic samples compared to normal tissue. Pathways for non-aggressive PTC include calcium and potassium ion transport, hormone signaling, protein tyrosine phosphatase activity and protein tyrosine kinase activity. Metastatic pathways include growth, apoptosis, activation of MAPK and regulation of serine threonine kinase activity. Genes for non-aggressive are KCNQ1, CACNA1D, KCNN4, BCL2, and PTK2B and metastatic PTC are EGFR, PTK2B, KCNN4 and BCL2. Three of the genes identified were validated using clinical biopsies showing significant overexpression in aggressive compared to non-aggressive PTC; EGFR (p < 0.05), KCNN4 (p < 0.001) and PTK2B (p < 0.001). DrugBank database search identified several FDA approved drug targets including anti-EGFR Vandetanib used to treat thyroid cancer in addition to others that may prove useful in treating PTC.

Conclusion: Transcriptomics analysis identified putative prognostic targets including EGFR, PTK2B, BCL2, KCNQ1, KCNN4 and CACNA1D. EGFR, PTK2B and KCN44 were validated using thyroid cancer clinical biopsies. The drug search identified FDA approved drugs including Vandetanib in addition to others that may prove useful in treating the disease.

Keywords: BIG data analytics; FFPE clinical biopsies; RNAseq; absolute GSEA; pathway analysis; pharmacotranscriptomics; thyroid cancer.

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Conflict of interest statement

The authors report no competing interests in this work.

Figures

Figure 1
Figure 1
Flow chart of transcriptomics data normalisation and gene set enrichment analysis
Figure 2
Figure 2
Representation of heatmaps and graphs for GSEA for significant pathways with enrichment scores. (A) The result file for normal and non-aggressive dataset is presented here with graph for enrichment score. (B) Graphical representation for the GSEA for normal versus metastatic data
Figure 3
Figure 3
Intersection of DEGs among non-aggressive and metastatic set compared to normal samples
Figure 4
Figure 4
Box plots for log fold expression from microarray data for the three differentially expressed genes identified from in silico analysis between healthy, non-aggressive and metastatic groups. (A) differential expression of EGFR, (B) differential expression of PTK2B and (C) differential expression of KCNN4. *p < 0.05, ***p < 0.01
Figure 5
Figure 5
Metascape analysis for the high frequent genes from (A) normal versus non-aggressive set and (B) normal versus metastatic set
Figure 6
Figure 6
Metascape for DEGs commonly upregulated in both non-aggressive and metastatic PTC
Figure 7
Figure 7
Immune cells enriched in non-aggressive and metastatic PTC in comparison to normal thyroid tissue
Figure 8
Figure 8
Pathway analysis using Metascape on Ukrainian thyroid cancer samples
Figure 9
Figure 9
Pathway analysis using Metascape on Brazilian thyroid cancer samples
Figure 10
Figure 10
Pathway analysis using Metascape on South Korean thyroid cancer samples
Figure 11
Figure 11
Differential gene expression in six tissue biopsies from thyroid cancer patients from UAE. *p < 0.05, ***p < 0.01
Figure 12
Figure 12
TNM Plot output of the three differentially expressed genes identified from in silico analysis on large independent cohort of 58 normal and 502 non-aggressive and 8 metastatic thyroid cancer cases. (A) differential expression of EGFR, (B) differential expression of PTK2B and (C) differential expression of KCNN4
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