Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Perineural invasion (PNI) is a prominent characteristic of pancreatic ductal adenocarcinoma (PDAC). PNI is associated with tumor progression, local recurrence and neuropathic pain; therefore, the identification of biomarkers associated with PNI may be beneficial in assessing the prognosis for patients with PDAC. Using an model of PNI, five pancreatic cancer cell lines (PANC-1, CFPAC-1, CAPAN-2, SW1990 and ASPC-1) were divided into two groups: High-(comprising PANC-1, CFPAC-1 and CAPAN-2) and low PNI (comprising SW1990 and ASPC-1). Differentially expressed genes (DEGs) between the two groups were identified using the GSE26088 dataset, and were regarded as PNI-associated genes. A total of 445 DEGs associated with PNI (fold change >1.5 or <0.66; P<0.05) were identified, which included 176 up- and 269 downregulated genes. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis and function annotation were performed, and the NetworkAnalyst database was used for protein-protein interaction network analysis to identify hub genes. A total of 20 hub genes (gene degree, ≥6) were identified. PNI was associated with the function 'chemokine signaling pathway'. The DEGs and hub genes were validated using the GSE102238 dataset and clinical tissue microarrays. Fibroblast growth factor 2 (FGF2) and catenin α 2 were demonstrated to be associated with PNI using the GSE102238 dataset. Furthermore, clinical tissue microarray analysis demonstrated that FGF2 was associated with PNI and poor prognosis. The present study provided a potential method for the reliable identification of PNI-associated genes, although further investigation is required to validate these results.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7405440 | PMC |
http://dx.doi.org/10.3892/ol.2020.11866 | DOI Listing |
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