Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&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: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
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
Current treatment methods for patients diagnosed with gliomas have shown limited success. This is partly due to the lack of prognostic genes available to accurately predict disease outcomes. The aim of this study was to investigate novel prognostic genes based on the molecular profile of tumor samples and their correlation with clinical parameters. In the current study, microarray data (GSE4412 and GSE7696) downloaded from Gene Expression Omnibus were used to identify differentially expressed prognostic genes (DEPGs) by significant analysis of microarray (SAM) between long-term survivors (>2 years) and short-term survivors (≤2 years). DEPGs generated from these two datasets were intersected to obtain a list of common DEPGs. The expression of a subset of common DEPGs was then independently validated by real-time reverse transcription quantitative PCR (qPCR). Survival value of the common DEPGs was validated using known survival data from the GSE4412 and TCGA dataset. After intersecting DEPGs generated from the above two datasets, three genes were identified which may potentially be used to determine glioma patient prognosis. Independent validation with glioma patients tissue ( = 70) and normal brain tissue ( = 19) found , and were up-regulated in glioma tissue. Survival value validation showed that the three genes correlated with patient survival by Kaplan-Meir analysis, including grades, age and therapy.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5133809 | PMC |
http://dx.doi.org/10.3390/ijms17111808 | DOI Listing |
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