Dysregulated miRNAs Targeting Adiponectin Signaling in Colorectal Cancer

Abstract

Dysregulation in miRNA expression has been reported in a variety of tumors, including colorectal cancer (CRC), where adiponectin regulates a number of processes related to tumorigenesis. The aim of this study was to identify a panel of heavily and consistently altered miRNAs in CRC that affect adiponectin signaling based on bioinformatics analysis and cross-referencing the available literature. Bioinformatics tools were used to analyze publicly available datasets to identify miRNAs targeting the adiponectin pathway that are substantially dysregulated in CRC. In parallel, a comprehensive literature review was conducted to gather and explore existing knowledge on the relationship between CRC, adiponectin signaling, and miRNA dysregulation. Bioinformatics analysis revealed a set of miRNAs that target adiponectin signaling and are consistently altered in CRC. Several candidate miRNAs, including miR-215-5p, miR-340-5p, miR-181a-5p, miR-150-5p, miR-96-5p, miR-19a-3p, and miR-21-5p, were identified as potential key regulators of the adiponectin cascade, while also being systemically dysregulated in CRC. Through gene ontology enrichment analysis, we further elucidated the biological processes and pathways impacted by these miRNAs, providing insight into their contributions to CRC. The literature review did not identify any previously reported shared connection between these miRNAs, adiponectin signaling, and CRC pathogenesis.

Keywords: adiponectin signaling; colorectal cancer; miRNAs.

Figure 1

Adiponectin signaling cascade and its relation to insulin signaling. Insulin-sensitizing effects of adiponectin. Solid lines represent direct interactions (arrows for activation and blunt-end lines for inhibition), whereas dashed lines represent indirect activation. Figure generated with BioRender https://www.biorender.com/. T-cadherin, Tissue Cadherin; AdipoR1/2, Adiponectin Receptor 1/2; IRS1/2, Insulin Receptor Substrate 1/2; PI3K, Phosphoinositide 3-Kinase; PDK1, Phosphoinositide-Dependent Kinase 1; Akt, Protein Kinase B; GLUT4, Glucose Transporter Type 4; AS160, Akt Substrate of 160 kDa;APPL1, Adaptor Protein, Phosphotyrosine Interacting with PH Domain and Leucine Zipper 1; LKB1,Liver Kinase B1; AMPK, AMP-Activated Protein Kinase; CaMKK, Calcium/Calmodulin-Dependent Protein Kinase Kinase; p38, p38 Mitogen-Activated Protein Kinase;SIRT1, Sirtuin 1; PGC-1α, Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-Alpha; PPARα,Peroxisome Proliferator-Activated Receptor Alpha; PP2A, Protein Phosphatase 2A; PKCζ, Protein Kinase C Zeta; NF-κB, Nuclear Factor Kappa B; ROS, Reactive Oxygen Species; ER, Endoplasmic Reticulum; Ca²⁺, Calcium Ion; Sphingosine-1-P, Sphingosine-1-Phosphate.

Figure 2

Meta-profiling heatmaps of most consistently dysregulated miRNAs in colorectal cancer tissue vs. normal tissue. (A) Downregulated miRNAs in colorectal cancer tissue vs. normal tissue. The green gradient represents the VC score decrease of miRNAs across multiple cancer vs. normal datasets, available from the dbDEMC 3.0 database from −19 (darkest green) to −4 (lightest green). Decrease of these miRNAs in CRC potentially dubs them tumor-suppressive, while some of the genes they regulate would potentially be oncogenes. (B) Upregulated miRNAs in colorectal cancer tissue vs. normal tissue. The red gradient represents the VC score increase of miRNAs across multiple cancer vs. normal datasets, available from the dbDEMC 3.0 database from +4 (lightest red) to +16 (darkest red). Increase of these miRNAs in CRC potentially means they could be oncogenic, while some of the genes they regulate would potentially be tumor-suppressors. Images were generated via the meta-profiling feature of dbDEMC 3.0.

Figure 3

Gene ontology network for all known targets of the most downregulated in CRC, adiponectin pathway-targeting miRNAs. Using miRTarBase, 1587 genes were found to be targeted by the four selected downregulated miRNAs, meaning that the expression of those genes and the activity of their associated pathways should be upregulated in CRC tissues. Circle sizes indicate number of mapped genes to pathway, while color indicates p values. Generated via Cytoscape’s ClueGO application, using the WikiPathways database.

Figure 4

Gene ontology network for all targets of the most upregulated in CRC, adiponectin pathway-targeting miRNAs. Using miRTarBase, 1329 genes were found to be targeted by the three selected upregulated miRNAs, meaning that the expression of those genes and the activity of their associated pathways should be downregulated in CRC tissues. Circle sizes indicate number of mapped genes to pathway, while color indicates p values. Generated via Cytoscape’s ClueGO application, using the WikiPathways database.

Figure 5

Simplified networks, depicting the most-targeted genes by the selected dysregulated miRNAs. (A) Downregulated miRNAs—these genes’ mRNA transcripts are targeted by at least three of the four miRNAs, meaning that their expression should be among the most upregulated in CRC tissues, i.e., they are potential oncogenes or prognostic markers. (B) Upregulated miRNAs—these genes’ mRNA transcripts are targeted by all three miRNAs; thus, their expression should be among the most downregulated in CRC tissues, i.e., they are potential tumor-suppressors or prognostic markers. Image generated through the network builder feature of MirNET analytics platform, degree cutoff value set at 2.