In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 12_Supplement ( 2022-06-15), p. 1442-1442
Abstract:
The molecular pathogenesis of Prostate cancer (PCa) is poorly understood, which limits the diagnosis and treatment options. PCa is one of the leading malignant tumors in US men. This research aims to investigate various molecular regulatory pathways triggered by differentially expressed genes (DEGs) to discover Hub genes as diagnostic or therapeutic targets to improve PCa prognosis. We used eight PCa Microarray datasets (GSE46602, GSE38241, GSE69223, GSE3325, GSE32571, GSE55945, GSE104749, and GSE26126) from the NCBI/GEO. We identified DEGs from datasets by comparing PCa (n=247) and control prostate tissues (n=221) using GEO2R with the criteria of |log2FC| (fold change) ≥ 1 and P-value & lt; 0.05. We implemented volcano plot analysis and generated Venn diagrams to identify overlapping genes. We then applied DAVID.6.8, Gene Ontology (GO) and KEGG pathway analysis to potentially associate DEGs' with biological functions and pathways in PCa pathogenesis. The protein-protein interaction (PPI) networks of the recognized DEGs and the significant nodes were constructed by STRING and visualized by Cytoscape and GeneMANIA. Finally, module analysis of the PPI network was performed by MCODE and CytoHubba to identify the Hub genes. The eight GEO datasets include total DEGs = 11595, upregulated = 3795, and downregulated genes = 3548. We identified 472 DEGs overlappings (the Key Genes) among the eight datasets with 357 downregulated and 115 upregulated genes. The GO and KEGG analysis for genes showed that they were principally involved in cell adhesion, focal adhesion, cell proliferation, calcium signaling pathway, extracellular exosome, and cancer pathways. The top significant (P-Value & lt;1.20E-03) transcriptional factors (TFs) connected with downregulated (BACH1, AP1, BACH2, LYF1, SRF, and NF1) and upregulated (MYOD, NFKAPPAB, MSX1, ROAZ, PAX5, and MYCMAX) genes. The PPI networks and the significance analysis were performed (STRING local clustering coefficient of 0.37, average node degree 4.53 and PPI enrichment p-value & lt; 1.0E-16), GeneMANIA maximum resultant genes = 20, and maximum resultant attributes=10. MCODE scores & gt; 7, degree cutoff = 2, node score cutoff = 0.1, Max depth = 100 and k-score = 2). CytoHubba included two topological analysis methods (DNMC and MCC). Results discovered eleven Hub genes (BDNF, CCK, GRIA2, NTRK2, SNAP25, SYN1, SYT1, ACTG2, ANXA2, ANXA6, and MFGE8). The 11 Hub genes among 472 DEGs directly correlate to the recurrence and prognosis of PCa. The discovered Hub genes and pathways may be potentially involved in PCa etiology in different patients. Recognizing these Hub genes may further assist in understanding molecular pathology to develop diagnostic and treatment regimens for a better prognosis of PCa patients. Citation Format: Diaaidden Alwadi, Alok Deoraj, Quentin Felty, Deodutta Roy. Discovery of recurrence and prognosis associated genes in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1442.
Type of Medium:
Online Resource
ISSN:
1538-7445
DOI:
10.1158/1538-7445.AM2022-1442
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2022
detail.hit.zdb_id:
2036785-5
detail.hit.zdb_id:
1432-1
detail.hit.zdb_id:
410466-3
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