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. 2022 Dec 3;10(12):3122.
doi: 10.3390/biomedicines10123122.

Identification of the Transcriptional Regulatory Role of RUNX2 by Network Analysis in Lung Cancer Cells

Beatriz Andrea Otálora-Otálora  1   2 , Cristian González Prieto  3 , Lucia Guerrero  3 , Camila Bernal-Forigua  4 , Martin Montecino  5 , Alejandra Cañas  6   7 , Liliana López-Kleine  3 , Adriana Rojas  4
Affiliations

Identification of the Transcriptional Regulatory Role of RUNX2 by Network Analysis in Lung Cancer Cells

Beatriz Andrea Otálora-Otálora et al. Biomedicines. .

Abstract

The use of a new bioinformatics pipeline allowed the identification of deregulated transcription factors (TFs) coexpressed in lung cancer that could become biomarkers of tumor establishment and progression. A gene regulatory network (GRN) of lung cancer was created with the normalized gene expression levels of differentially expressed genes (DEGs) from the microarray dataset GSE19804. Moreover, coregulatory and transcriptional regulatory network (TRN) analyses were performed for the main regulators identified in the GRN analysis. The gene targets and binding motifs of all potentially implicated regulators were identified in the TRN and with multiple alignments of the TFs' target gene sequences. Six transcription factors (E2F3, FHL2, ETS1, KAT6B, TWIST1, and RUNX2) were identified in the GRN as essential regulators of gene expression in non-small-cell lung cancer (NSCLC) and related to the lung tumoral process. Our findings indicate that RUNX2 could be an important regulator of the lung cancer GRN through the formation of coregulatory complexes with other TFs related to the establishment and progression of lung cancer. Therefore, RUNX2 could become an essential biomarker for developing diagnostic tools and specific treatments against tumoral diseases in the lung after the experimental validation of its regulatory function.

Keywords: coexpression networks; diagnostic and prognostic biomarkers; differentially expressed genes (DEGs); gene regulatory network (GRN); lung cancer (LC); transcription factors (TFs).

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Bioinformatics pipeline used in this work and results in every step: 1. Gene regulatory network (GRN) construction using an in-house methodology. 2. Coregulatory analysis of the main transcription factors (TFs) identified in step 1. 3. Database (DB) search of the reported targets of the most relevant TF (RUNX2) identified in step 2. 4. Identification of potential binding motifs of RUNX2 based on the targets.
Figure 2
Figure 2
Coregulatory networks of transcription factors related to the establishment and progression of NSCLC lung cancer.
Figure 3
Figure 3
Transcriptional regulatory network of RUNX2 and its coregulators BRCA1, FOXM1, and RUNX1 (gray squares). In blue are the downregulated targets, and in red are the upregulated targets.
Figure 4
Figure 4
Transcriptional regulators in lung cancer and their association with the acquisition of the hallmarks of cancer and the signaling pathways associated with the establishment and progression of lung cancer. Figure adapted from Figure 1 in Ref. [57], Figure 2 in Ref. [58], Figure 5 in Ref. [59], Figure 3 in Ref. [60], Figure 1 in Ref. [61], and Figures 1 and 3 in Ref. [62].
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