Tumor recurrence is one of the most important risk factors that can negatively affect the survival rate of colorectal cancer (CRC) patients. However, the key regulators dictating this process and their exact mechanisms are understudied. This study aimed to construct a gene co-expression network to predict the hub genes affecting CRC recurrence and to inspect the regulatory network of hub genes and transcription factors (TFs). A total of 177 cases from the GSE17536 dataset were analyzed via weighted gene co-expression network analysis to explore the modules related to CRC recurrence. Functional annotation of the key module genes was assessed through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The protein and protein interaction network was then built to screen hub genes. Samples from the Cancer Genome Atlas (TCGA) were further used to validate the hub genes. Construction of a TFs-miRNAs-hub genes network was also conducted using StarBase and Cytoscape approaches. After identification and validation, a total of five genes (TIMP1, SPARCL1, MYL9, TPM2, and CNN1) were selected as hub genes. A regulatory network of TFs-miRNAs-targets with 29 TFs, 58 miRNAs, and five hub genes was instituted, including model GATA6-MIR106A-CNN1, SP4-MIR424-TPM2, SP4-MIR326-MYL9, ETS1-MIR22-TIMP1, and ETS1-MIR22-SPARCL1. In conclusion, the identification of these hub genes and the prediction of the Regulatory relationship of TFs-miRNAs-hub genes may provide a novel insight for understanding the underlying mechanism for CRC recurrence.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8058478 | PMC |
http://dx.doi.org/10.3389/fgene.2021.649752 | DOI Listing |
Curr Res Transl Med
January 2025
Department of Hematology, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, China. Electronic address:
Background: Almost all multiple myeloma (MM) patients will eventually develop disease that has relapsed with or become refractory to current therapeutic regimes. However, the pervious clinical parameters have been proved inaccurate for defining MM relapse, and molecular targets have become the focuses of interests. Prognostic predictions based on molecular targets have been more effective to this day.
View Article and Find Full Text PDFOMICS
January 2025
Department of Biotechnology, Brainware University, Barasat, West Bengal, India.
Next-generation cancer phenomics by deployment of multiple molecular endophenotypes coupled with high-throughput analyses of gene expression offer veritable opportunities for triangulation of discovery findings in non-small cell lung cancer (NSCLC) research. This study reports differentially expressed genes in NSCLC using publicly available datasets (GSE18842 and GSE229253), uncovering 130 common genes that may potentially represent crucial molecular signatures of NSCLC. Additionally, network analyses by GeneMANIA and STRING revealed significant coexpression and interaction patterns among these genes, with four notable hub genes-, , and -identified as pivotal in NSCLC progression.
View Article and Find Full Text PDFCurr Drug Discov Technol
December 2024
Department of Pharmacy Practice, SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu District, Tamilnadu, 603203, India.
Background: Clopidogrel, an antiplatelet drug commonly used in cardiovascular disease, is metabolized by the liver mainly through CYP2C19. Concomitant use of Proton pump inhibitors along with clopidogrel may affect the potency of clopidogrel by CYP2C19 inhibition. However, a novel PPI, ilaprazole is known to differ in its pharmacokinetic features, given the potential differences between ilaprazole's interactions and their metabolism with clopidogrel.
View Article and Find Full Text PDFHeliyon
July 2024
Cancer Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Background: Breast cancer is a highly malignant disease worldwide, but there are currently no sufficient molecular biomarkers to predict patient prognosis and guide radiotherapy. The tumor microenvironment (TME) is an important factor affecting tumor biological function, and changes in its composition are equally relevant to tumor progression and prognosis during radiotherapy.
Methods: Here, we performed bioinformatic analyses using data obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases to screen for molecular biomarkers related to the TME that may influence radiotherapy sensitivity.
Cureus
December 2024
Community Medicine, Siksha 'O' Anusandhan Deemed to be University Institute of Medical Sciences and SUM Hospital, Bhubaneswar, IND.
Gastric cancer (GC) has become a major challenge in oncology research, primarily due to its detection at advanced stages. In this study, we identified and validated the pharmacological mechanisms involved in treating gastric cancer using an integrated approach combining network pharmacology, molecular docking, and a dynamic approach. Gastric cancer-related genes were obtained from DisGeNET, Genecard, and Malacard databases, while potential targets of bioactive compounds were predicted using SwissTargetPrediction.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!