The existing biomarkers are insufficient for predicting the prognosis of pancreatic ductal adenocarcinoma (PDAC). Intraductal papillary mucinous neoplasm (IPMN) is a precursor to PDAC; therefore, identifying biomarkers from differentially expressed genes (DEGs) of PDAC and IPMN is a new and reliable strategy for predicting the prognosis of PDAC. In this study, four datasets were downloaded from the Gene Expression Omnibus database and standardized using the R package 'limma.' A total of 51 IPMN and 81 PDAC samples were analyzed, and 341 DEGs in PDAC and IPMN were identified; DEGs were involved in the extracellular matrix and tumor microenvironment. An acceptable survival prognosis was demonstrated by SDC1 and ITGA2, which were highly expressed during in vitro PDAC cell proliferation, apoptosis, and migration. SDC1 was enriched in interferon alpha (IFN-α) response and ITGA2 was primarily detected in epithelial-mesenchymal transition (EMT), which was verified using western blotting. We concluded that SDC1 and ITGA2 are potential prognostic biomarkers for PDAC associated with IPMN. Downregulation of SDC1 and ITGA2 expression in PDAC occurs via a mechanism involving possible regulation of IFN-α response, EMT, and immunity, which may act as new targets for PDAC therapy.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10618477 | PMC |
| http://dx.doi.org/10.1038/s41598-023-44646-x | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Integrated bioinformatics analysis reveals upregulated extracellular matrix hub genes in pancreatic cancer: Implications for diagnosis, prognosis, immune infiltration, and therapeutic strategies.
Cancer Rep (Hoboken)
April 2024
Department of Biochemistry and Molecular Biology, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh.
Background: Pancreatic cancer (PC) stands out as one of the most formidable malignancies and exhibits an exceptionally unfavorable clinical prognosis due to the absence of well-defined diagnostic indicators and its tendency to develop resistance to therapeutic interventions. The primary objective of this present study was to identify extracellular matrix (ECM)-related hub genes (HGs) and their corresponding molecular signatures, with the intent of potentially utilizing them as biomarkers for diagnostic, prognostic, and therapeutic applications.
Methods: Three microarray datasets were sourced from the NCBI database to acquire upregulated differentially expressed genes (DEGs), while MatrisomeDB was employed for filtering ECM-related genes.
Intercellular Molecular Crosstalk Networks within Invasive and Immunosuppressive Tumor Microenvironment Subtypes Associated with Clinical Outcomes in Four Cancer Types.
Biomedicines
November 2023
School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China.
Heterogeneity is a critical basis for understanding how the tumor microenvironment (TME) contributes to tumor progression. However, an understanding of the specific characteristics and functions of TME subtypes (subTMEs) in the progression of cancer is required for further investigations into single-cell resolutions. Here, we analyzed single-cell RNA sequencing data of 250 clinical samples with more than 200,000 cells analyzed in each cancer datum.
View Article and Find Full Text PDFThe existing biomarkers are insufficient for predicting the prognosis of pancreatic ductal adenocarcinoma (PDAC). Intraductal papillary mucinous neoplasm (IPMN) is a precursor to PDAC; therefore, identifying biomarkers from differentially expressed genes (DEGs) of PDAC and IPMN is a new and reliable strategy for predicting the prognosis of PDAC. In this study, four datasets were downloaded from the Gene Expression Omnibus database and standardized using the R package 'limma.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!