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: 1075
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3195
Function: GetPubMedArticleOutput_2016
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: This study aimed to investigate the serum metabolite profiles during neoadjuvant chemoradiotherapy (NCRT) in locally advanced rectal cancer (LARC) using liquid chromatography-mass spectrometry (LC-MS) metabolomics analysis.
Methods: 60 serum samples were collected from 20 patients with LARC before, during, and after radiotherapy. LC-MS metabolomics analysis was performed to identify the metabolite variations. Functional annotation was applied to discover altered metabolic pathways. The key metabolites were screened and their ability to predict sensitivity to radiotherapy was calculated using random forests and ROC curves.
Results: The results showed that NCRT led to significant changes in the serum metabolite profiles. The serum metabolic profiles showed an apparent separation between different time points and different sensitivity groups. Moreover, the functional annotation showed that the differential metabolites were associated with a series of important metabolic pathways. Pre-radiotherapy (3Z,6Z)-3,6-Nonadiena and pro-radiotherapy 1-Hydroxyibuprofen showed good predictive performance in discriminating the sensitive and non-sensitive group to NCRT, with an AUC of 0.812 and 0.75, respectively. Importantly, the combination of different metabolites significantly increased the predictive ability.
Conclusion: This study demonstrated the potential of LC-MS metabolomics for revealing the serum metabolite profiles during NCRT in LARC. The identified metabolites may serve as potential biomarkers and therapeutic targets for the management of this disease. Furthermore, the understanding of the affected metabolic pathways may help design more personalized therapeutic strategies for LARC patients.
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http://dx.doi.org/10.1007/s12094-024-03537-x | DOI Listing |