Comprehensive Analysis of Prognostic and Genetic Signatures for General Transcription Factor III (GTF3) in Clinical Colorectal Cancer Patients Using Bioinformatics Approaches

Abstract

Colorectal cancer (CRC) has the fourth-highest incidence of all cancer types, and its incidence has steadily increased in the last decade. The general transcription factor III (GTF3) family, comprising GTF3A, GTF3B, GTF3C1, and GTFC2, were stated to be linked with the expansion of different types of cancers; however, their messenger (m)RNA expressions and prognostic values in colorectal cancer need to be further investigated. To study the transcriptomic expression levels of GTF3 gene members in colorectal cancer in both cancerous tissues and cell lines, we first performed high-throughput screening using the Oncomine, GEPIA, and CCLE databases. We then applied the Prognoscan database to query correlations of their mRNA expressions with the disease-specific survival (DSS), overall survival (OS), and disease-free survival (DFS) status of the colorectal cancer patient. Furthermore, proteomics expressions of GTF3 family members in clinical colorectal cancer specimens were also examined using the Human Protein Atlas. Finally, genomic alterations of GTF3 family gene expressions in colorectal cancer and their signal transduction pathways were studied using cBioPortal, ClueGO, CluePedia, and MetaCore platform. Our findings revealed that GTF3 family members' expressions were significantly correlated with the cell cycle, oxidative stress, WNT/β-catenin signaling, Rho GTPases, and G-protein-coupled receptors (GPCRs). Clinically, high GTF3A and GTF3B expressions were significantly correlated with poor prognoses in colorectal cancer patients. Collectively, our study declares that GTF3A was overexpressed in cancer tissues and cell lines, particularly colorectal cancer, and it could possibly step in as a potential prognostic biomarker.

Keywords: GTF3A; GTF3B; GTF3C1; GTF3C2; bioinformatics; colorectal cancer.

Figure 1

GTF3 gene expression patterns in different cancers (ONCOMINE). The expressions of GTF3 family genes in cancer patients were compared to that of normal patients. A reduction in a gene’s rank percentile is represented by the color gradient. The thresholds applied were a p-value of <0.05, a multiple of change of two-fold, and a percentile gene rank of <10% in cancer versus normal cases.

Figure 2

Expressions of members of GTF3 family genes in colorectal cancer cell lines in the CCLE platform. (A) The CCLE database was used to plot a heatmap for all rows representing colorectal cancer cells based on expression levels of GTF3 family genes. GTF3 expression levels varied among colorectal cancer cell lines. Red indicates overexpression (top column), and blue indicates under-expression (bottom column) in cancer cells. (B) GTF3A expression in colorectal cancer cell lines. (C) GTF3B expression in colorectal cancer cell lines. (D) GTF3C1 expression in colorectal cancer cell lines. (E) GTF3C2 expression in colorectal cancer cell lines.

Figure 3

GTF3 expressions in colorectal cancer (GEPIA). (A–D) Expressions of member genes of the GTF3 family in various types of cancer. (E,F) Expressions of member genes of the GTF3 family in colorectal cancer. The red bar and box plots show tumor expression while green/black represent normal tissues.

Figure 4

Kaplan–Meier survival curve comparing high and low expressions of genes of members of the GTF3 family in colorectal cancer using the PrognoScan database with GSE17536 cohort data (n = 177). The Kaplan–Meier survival curve shows the correlation of disease-specific survival (DSS), overall survival (OS), and disease-free survival (DFS) of colorectal cancer patients with high and low expression levels of GTF3 family members.

Figure 5

Protein expression levels of members of the GTF3 family in all clinical colorectal cancer specimens from the Human Protein Atlas. GTF3A and GTF3C1 had strong positive protein expressions in colorectal cancer, whereas GTF3B and GTF3C2 had low protein expressions in colorectal cancer.

Figure 6

Colorectal cancer has been linked to genomic alterations in differentially expressed GTF3 genes. (A) The cBioPortal was used to perform an OncoPrint study of GTF3 family member genes, which showed the degree of gene amplification, deep deletions, and nucleotide substitutions linked to colorectal cancer. (B) Correlations between different GTF3s in colorectal cancer (cBioPortal) and insignificant correlations are marked by crosses. (C) Venn diagram of the GTF3 family co-expression network in TCGA colorectal cancer databases. The intersection of co-expression genes lists of each gene in the GTF3 family. The approach selected the top 15% of genes from the list of co-expression genes extracted from the TCGA Pancancer dataset. (D) Through a Cytoscape analysis, high correlations between GTF3 members and metastasis markers were observed.

Figure 7

GTF3A differentially expressed genes pathway developed by MetaCore. Experimental data from TCGA were linked to and visualized on pathway maps as thermometer-like figures. To study the gene networks and signaling pathways that could be affected by the chosen genes, we exported genes expressed with GTF3A and then uploaded them to the MetaCore platform for a path analysis. The MetaCore pathway analysis indicated that the “DNA damage_ATM/ATR regulation of G2M checkpoint cytoplasmic signaling”-related pathway was correlated with colorectal cancer development.

Figure 8

GTF3B differentially expressed genes pathway developed by MetaCore. Experimental data from TCGA were linked to and visualized on pathway maps as thermometer-like figures. To study the gene networks and signaling pathways that could be affected by the chosen genes, we exported genes expressed with GTF3B and then uploaded them to the MetaCore platform for a path analysis. The MetaCore pathway analysis indicated that the “chemotaxis lysophosphatidic acid signaling via GPCRs”-related pathway was correlated with colorectal cancer development.

Figure 9

GTF3C1 differentially expressed genes pathway developed by MetaCore. Experimental data from TCGA were linked to and visualized on pathway maps as thermometer-like figures. To study the gene networks and signaling pathways that could be affected by the chosen genes, we exported genes expressed with GTF3C1 and then uploaded them to the MetaCore platform for a path analysis. The MetaCore pathway analysis indicated that the “regulation of lipid metabolism_Regulation of lipid metabolism via LXR, NF-Y, and SREBP”-related pathway was correlated with colorectal cancer development.

Figure 10

GTF3C1 differentially expressed genes pathway developed by MetaCore. Experimental data from TCGA were linked to and visualized on pathway maps as thermometer-like figures. To study the gene networks and signaling pathways that could be affected by the chosen genes, we exported genes expressed with GTF3C2 and then uploaded them to the MetaCore platform for a path analysis. The MetaCore pathway analysis indicated that the “DNA damage_Role of Brca1 and Brca2 in DNA repair”-related pathway was correlated with colorectal cancer development.