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
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Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
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Function: require_once
Background: Tertiary lymphoid structures (TLSs) are associated with favorable prognosis and enhanced response to anticancer therapy. A digital assessment of TLSs could provide an objective alternative that mitigates variability inherent in manual evaluation. This study aimed to develop and validate a digital gene panel based on biological prior knowledge for assessment of TLSs, and further investigate its associations with survival and multiple anticancer therapies.
Materials And Methods: The present study involved 1704 patients with gastric cancer from seven cancer centers. TLSs were identified morphologically through hematoxylin-and-eosin staining. The authors further developed a digital score based on targeted gene expression profiling to assess TLSs status, recorded as gene signature of tertiary lymphoid structures (gsTLS). For enhanced interpretability, we employed the SHapley Additive exPlanation (SHAP) analysis to elucidate its contribution to the prediction. The authors next evaluated the signature's associations with prognosis, and investigated its predictive accuracy for multiple anticancer therapies, including adjuvant chemotherapy and immunotherapy.
Results: The gsTLS panel with nine gene features achieved high accuracies in predicting TLSs status in the training, internal, and external validation cohorts (area under the curve, range: 0.729-0.791). In multivariable analysis, gsTLS remained an independent predictor of disease-free and overall survival (hazard ratio, range: 0.346-0.743, all P <0.05) after adjusting for other clinicopathological variables. SHAP analysis highlighted gsTLS as the strongest predictor of TLSs status compared with clinical features. Importantly, patients with high gsTLS (but not those with low gsTLS) exhibited substantial benefits from adjuvant chemotherapy ( P <0.05). Furthermore, the authors found that the objective response rate to antiprogrammed cell death protein 1 (anti-PD-1) immunotherapy was significantly higher in the high-gsTLS group (40.7%) versus the low-gsTLS group (5.6%, P =0.036), and the diagnosis was independent from Epstein-Barr virus, tumor mutation burden, and programmed cell death-ligand 1 (PD-L1) expression.
Conclusion: The gsTLS digital panel enables accurate assessment of TLSs status, and provides information regarding prognosis and responses to multiple therapies for gastric cancer.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11486929 | PMC |
http://dx.doi.org/10.1097/JS9.0000000000001834 | DOI Listing |
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