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: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Background: Ulcerative colitis (UC), an idiopathic, chronic inflammatory disorder of the colonic mucosa, is commonly treated with antitumor necrosis factor α (anti-TNF-α) agents. However, only approximately two-thirds have an initial response to these therapies.
Methods: We integrated gene expression profiling from 3 independent data sets of 79 UC patients before they began anti-TNF-α therapy and calculated the differentially expressed genes between patient response and nonresponse to anti-TNF-α therapy and developed a de novo response-associated transcription signature score (logOR_Score) to demonstrate the predictive capability of anti-TNF-α therapy for therapeutic efficacy. Furthermore, we performed association analysis of the logOR_Score and clinical features, such as disease activity and immune microenvironment.
Results: A total of 2522 responsive and 1824 nonresponsive genes were identified from the integrated data set. Responsive genes were significantly enriched in metabolism-related pathways, whereas nonresponsive ones were associated with immune response-related pathways. The logOR_Score enabled the accurate prediction of the therapeutic efficacy of anti-TNF-α in 4 independent patient cohorts and outperformed the predictions made based on 6 transcriptome-based signatures. In terms of clinical features, the logOR_Score correlated highly with the activity of UC. From an immune microenvironment perspective, logOR_Scores of CD8+IL-17+ T cells, follicular B cells, and innate lymphoid cells significantly decreased in inflamed UC tissue.
Conclusions: The de novo response-associated transcription signature may provide novel insights into the personalized treatment of patients with UC. Comprehensive analyses of the response-related subtypes and the association between logOR_Score and clinical features and immune microenvironment may provide insights into the underlying UC pathogenesis.
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http://dx.doi.org/10.1093/ibd/izad060 | DOI Listing |