Tao Meng1, Zhangzhang Lan2, Xiaoling Zhao3, Li Niu3,4, Chuan Chen4, Wenyong Zhang2. 1. Department of Gastrointestinal Surgery, Xinjiang Medical University Tumor Hospital, Urumqi, China. 2. School of Medicine, Southern University of Science and Technology, Shenzhen, China. 3. CheerLand Clinical Laboratory Co., Ltd., Peking University Medical Industrial Park, Zhongguancun Life Science Park, Beijing, China. 4. Shenzhen Cheerland Biotechnology Co., Ltd., Cheerland-Watson Center for Life Sciences and Technology, Shenzhen, China.
Abstract
Background: Colorectal cancer (CRC) is the 3rd most common cancer and the 2nd leading cause of cancer-related death. Numerous studies have found that aberrations in cellular molecules play an important role in the development of tumors. Studying and determining the interactions between these molecules can contribute to the diagnosis, treatment, and prognosis of tumors. Methods: The GSE151021, GSE156720, and GSE156719 data sets were analyzed to screen the differentially expressed messenger RNAs (DEmRNAs), long non-coding RNAs (DElncRNAs), and microRNAs (DEmiRNAs) in CRC. Database for Annotation, Visualization and Integrated Discovery (DAVID) and the Search Tool for the Retrieval of Interacting Genes/Proteins software were used to examine gene enrichment and the hub genes. Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and UALCAN was used to verify the expression of the hub genes. To analyze the overall survival (OS) of the hub genes, Kaplan-Meier plotter (KM plotter) was performed. Finally, the miRCancer database, TargetScan, and GSE156719 were used to identify the targets of the identified miRNAs. To predict the lncRNA-miRNA interactions, we used DIANA-LncBase v2 and GSE156720. Finally, the visualization protein‑protein interaction (PPI), competitive endogenous RNA (ceRNA) network was constructed using Cytoscape v3.1. Results: By analyzing GSE151021 and GSE156720, 23 upregulated mRNAs and 10 downregulated mRNAs were identified as sharing the differentially expressed genes (DEGs) between CRC and adjacent tissues. Furthermore, nucleolar protein 14 (NOP14), the sonic hedgehog (SHH) signaling molecule, phorbol-12-myristate-13-acetate-induced protein 1 (PMAIP1), the BCL2 apoptosis regulator (BCL2), and zinc finger E-box binding homeobox 2 (ZEB2) were considered hub genes. The constructed lncRNA-miRNA-mRNA network revealed 7 intersecting miRNAs (4 upregulated and 3 downregulated), 79 lncRNAs (40 upregulated and 39 downregulated), and 5 mRNAs (3 upregulated and 2 downregulated). Finally, we determined that the dysregulation of lncRNAs, such as HCG16, CASC9, SNHG16, HAND2-AS1, and NR2F1-AS1, secluded altered the expression of several miRNAs, such as hsa-miR-193a-5p, hsa-miR-485-5p, hsa-miR-17-5p, and hsa-miR-92a-3p, and affected the occurrence and development of CRC. Conclusions: We identified a series of DElncRNAs, DEmRNAs, and DEmiRNAs in CRC that might be considered potential biomarkers in understanding the complex molecular pathways leading to CRC development. 2022 Journal of Gastrointestinal Oncology. All rights reserved.
Background: Colorectal cancer (CRC) is the 3rd most common cancer and the 2nd leading cause of cancer-related death. Numerous studies have found that aberrations in cellular molecules play an important role in the development of tumors. Studying and determining the interactions between these molecules can contribute to the diagnosis, treatment, and prognosis of tumors. Methods: The GSE151021, GSE156720, and GSE156719 data sets were analyzed to screen the differentially expressed messenger RNAs (DEmRNAs), long non-coding RNAs (DElncRNAs), and microRNAs (DEmiRNAs) in CRC. Database for Annotation, Visualization and Integrated Discovery (DAVID) and the Search Tool for the Retrieval of Interacting Genes/Proteins software were used to examine gene enrichment and the hub genes. Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and UALCAN was used to verify the expression of the hub genes. To analyze the overall survival (OS) of the hub genes, Kaplan-Meier plotter (KM plotter) was performed. Finally, the miRCancer database, TargetScan, and GSE156719 were used to identify the targets of the identified miRNAs. To predict the lncRNA-miRNA interactions, we used DIANA-LncBase v2 and GSE156720. Finally, the visualization protein‑protein interaction (PPI), competitive endogenous RNA (ceRNA) network was constructed using Cytoscape v3.1. Results: By analyzing GSE151021 and GSE156720, 23 upregulated mRNAs and 10 downregulated mRNAs were identified as sharing the differentially expressed genes (DEGs) between CRC and adjacent tissues. Furthermore, nucleolar protein 14 (NOP14), the sonic hedgehog (SHH) signaling molecule, phorbol-12-myristate-13-acetate-induced protein 1 (PMAIP1), the BCL2 apoptosis regulator (BCL2), and zinc finger E-box binding homeobox 2 (ZEB2) were considered hub genes. The constructed lncRNA-miRNA-mRNA network revealed 7 intersecting miRNAs (4 upregulated and 3 downregulated), 79 lncRNAs (40 upregulated and 39 downregulated), and 5 mRNAs (3 upregulated and 2 downregulated). Finally, we determined that the dysregulation of lncRNAs, such as HCG16, CASC9, SNHG16, HAND2-AS1, and NR2F1-AS1, secluded altered the expression of several miRNAs, such as hsa-miR-193a-5p, hsa-miR-485-5p, hsa-miR-17-5p, and hsa-miR-92a-3p, and affected the occurrence and development of CRC. Conclusions: We identified a series of DElncRNAs, DEmRNAs, and DEmiRNAs in CRC that might be considered potential biomarkers in understanding the complex molecular pathways leading to CRC development. 2022 Journal of Gastrointestinal Oncology. All rights reserved.
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