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Original Article
Tumor Unraveling molecular similarities between colorectal polyps and colorectal cancer: a systems biology approach -
Mehran Radak
, Hossein Fallahi -
Intestinal Research 2024;22(2):199-207.
DOI: https://doi.org/10.5217/ir.2023.00162
Published online: February 6, 2024
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- Correspondence to Hossein Fallahi, Department of Biology, School of Sciences, Razi University, Baq-e-Abrisham, Kermanshah 6714967346, Islamic Republic of Iran. Tel: +98-8334274545, Fax: +98-8334274555, E-mail: h.fallahi@razi.ac.ir
• Received: November 6, 2023 • Revised: November 27, 2023 • Accepted: December 29, 2023
© Copyright 2024. Korean Association for the Study of Intestinal Diseases.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
-
Background/Aims
- Colorectal cancer (CRC) and colorectal polyps are intimately linked, with polyps acting as precursors to CRC. Understanding the molecular mechanisms governing their development is crucial for advancing diagnosis and treatment. Employing a systems biology approach, we investigated the molecular similarities between polyp and CRC.
-
Methods
- We analyzed gene expression profiles, protein-protein interactions, transcription factors, and gene ontology to identify common differentially expressed genes (DEGs) and unravel shared molecular pathways.
-
Results
- Our analysis revealed 520 commonly dysregulated genes in polyps and CRC, serving as potential biomarkers and pivotal contributors to disease progression. Gene ontology analysis elucidated distinct biological processes associated with upregulated and downregulated DEGs in both conditions, highlighting common pathways, including signal transduction, cell adhesion, and positive regulation of cell proliferation. Moreover, protein-protein interaction networks shed light on subnetworks involved in rRNA processing, positive regulation of cell proliferation, mRNA splicing, and cell division. Transcription factor analysis identified major regulators and differentially expressed transcription factors in polyp and CRC. Notably, we identified common differentially expressed transcription factors, including ZNF217, NR3C1, KLF5, GATA6, and STAT3, with STAT3 and NR3C1 exhibiting increased expression.
-
Conclusions
- This comprehensive analysis enriches our understanding of the molecular mechanisms underlying polyp formation and CRC development, providing potential targets for further investigation and therapeutic intervention. Our findings contribute substantively to crafting personalized strategies for refining the diagnosis and treatment of polyps and CRC.
INTRODUCTION
METHODS
RESULTS
DISCUSSION
-
Funding Source
The authors received no financial support for the research, authorship, and/or publication of this article.
-
Conflict of Interest
No potential conflict of interest relevant to this article was reported.
-
Data Availability Statement
Data used in this study is freely available and can be obtained from NCBI using above-mentioned GSE code “GSE41258.”
-
Author Contributions
Conceptualization: Radak M, Fallahi H. Formal analysis: Radak M. Investigation: Radak M, Fallahi H. Methodology: Radak M. Resources: Fallahi H. Software: Radak M. Supervision; Validation: Fallahi H. Writing - original draft: Radak M. Writing - review & editing: Fallahi H. Approval of final manuscript: all authors.
NOTES
Supplementary Material
Supplementary Table 1.
Supplementary Table 2.
Supplementary Table 3.
Supplementary Table 4.
Fig. 1.Cases the identification of differentially expressed genes (DEGs) in various colorectal disease types. (A) The bar graph provides a visual representation of the DEGs, clearly indicating the count of upregulated and downregulated genes for each specific disease type. (B) The Venn diagram illustrates the overlapping instances of DEGs among different colorectal disease types, enabling a comprehensive comparison. (C) The bar chart demonstrates the fold change in expression of 520 DEGs commonly observed across all disease types. CRC, colorectal cancer.
Fig. 2.The findings of the gene ontology analysis for the differentially expressed genes (DEGs). (A) The main biological processes (BP) associated with upregulated genes in CRC. (B) The main BP linked to downregulated genes in CRC. (C) The main BP connected to upregulated genes in polyps. (D) The main BP associated with downregulated genes in polyps. (E) The 10 most significant BP shared by both diseases. The number below the diagram indicates the number of genes involved in the process as a percentage of the total number of genes involved, while, the number in front of the column indicates the number of genes involved in the process. CRC, colorectal cancer.
Fig. 3.Protein-protein interaction networks with module annotations. The colored nodes represent the modules identified through overlapping neighborhood expansion. The tables provide annotations for the modules, with only those modules having P-values less than 0.05 being chosen. In the network, the color of the nodes indicates the presence of modules, and larger-sized nodes indicate a greater degree of connectivity. (A) Colorectal cancer (CRC) network. (B) Polyp network. (C) Common differentially expressed genes (DEGs) proteins networks.
Fig. 4.Three gene regulatory networks: (A) the colorectal cancer DE-TF network, (B) the polyp DE-TF network, and (C) the common DE-TF network. In these networks, blue indicates upregulated TFs, while red indicates downregulated TFs. DE-TFs, differentially expressed transcription factors.
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XML DownloadUnraveling molecular similarities between colorectal polyps and colorectal cancer: a systems biology approach
Fig. 1. Cases the identification of differentially expressed genes (DEGs) in various colorectal disease types. (A) The bar graph provides a visual representation of the DEGs, clearly indicating the count of upregulated and downregulated genes for each specific disease type. (B) The Venn diagram illustrates the overlapping instances of DEGs among different colorectal disease types, enabling a comprehensive comparison. (C) The bar chart demonstrates the fold change in expression of 520 DEGs commonly observed across all disease types. CRC, colorectal cancer.
Fig. 2. The findings of the gene ontology analysis for the differentially expressed genes (DEGs). (A) The main biological processes (BP) associated with upregulated genes in CRC. (B) The main BP linked to downregulated genes in CRC. (C) The main BP connected to upregulated genes in polyps. (D) The main BP associated with downregulated genes in polyps. (E) The 10 most significant BP shared by both diseases. The number below the diagram indicates the number of genes involved in the process as a percentage of the total number of genes involved, while, the number in front of the column indicates the number of genes involved in the process. CRC, colorectal cancer.
Fig. 3. Protein-protein interaction networks with module annotations. The colored nodes represent the modules identified through overlapping neighborhood expansion. The tables provide annotations for the modules, with only those modules having P-values less than 0.05 being chosen. In the network, the color of the nodes indicates the presence of modules, and larger-sized nodes indicate a greater degree of connectivity. (A) Colorectal cancer (CRC) network. (B) Polyp network. (C) Common differentially expressed genes (DEGs) proteins networks.
Fig. 4. Three gene regulatory networks: (A) the colorectal cancer DE-TF network, (B) the polyp DE-TF network, and (C) the common DE-TF network. In these networks, blue indicates upregulated TFs, while red indicates downregulated TFs. DE-TFs, differentially expressed transcription factors.
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Unraveling molecular similarities between colorectal polyps and colorectal cancer: a systems biology approach
