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: Acute myeloid leukemia (AML) is a highly aggressive hematologic malignancy with poor prognosis and high relapse rates. While the TNFAIP8 gene family (TNFAIP8, TNFAIP8L1, TNFAIP8L2, and TNFAIP8L3) is implicated in cancer and immune regulation, its role in AML remains unclear. This study utilized bioinformatics analyses to investigate their expression, prognostic significance, genetic alterations, and immune associations in AML.
Methods: The expression levels and clinical significance of TNFAIP8 family genes in AML were evaluated using UCSC XENA databases. Kaplan-Meier survival analysis was performed to assess overall survival (OS) differences, and receiver operating characteristic (ROC) curves were utilized to evaluate the prognostic predictive abilities of these genes. Genetic alterations were analyzed using the cBioPortal platform, while immune infiltration was examined through ssGSEA and Spearman correlation analysis. Functional enrichment analysis of co-expressed genes was conducted using the KEGG and GO databases.
Results: TNFAIP8, TNFAIP8L1, TNFAIP8L2, and TNFAIP8L3 were significantly overexpressed in AML tissues compared to normal tissues (P < 0.001). However, Kaplan-Meier survival analysis revealed no significant association between their expression levels and OS in AML patients. ROC curve analysis showed that TNFAIP8L2 had the highest predictive accuracy (AUC = 1.000) among the family members, followed by TNFAIP8L1 (AUC = 0.728), TNFAIP8 (AUC = 0.709), and TNFAIP8L3 (AUC = 0.629). Clinicopathological analysis indicated that TNFAIP8 and TNFAIP8L1 expressions were associated with poor cytogenetic risk, while TNFAIP8L3 expression correlated strongly with elevated bone marrow blasts (P < 0.001). Mutation analysis revealed a low frequency of genetic alterations, with TNFAIP8L1 being the only gene with mutations in 0.53% of cases. Immune infiltration analysis demonstrated that TNFAIP8 and TNFAIP8L3 were positively correlated with myeloid-derived suppressor cells (MDSCs), while TNFAIP8L1 expression was associated with natural killer (NK) cell enrichment.
Conclusion: TNFAIP8 family genes play distinct roles in AML pathogenesis and immune regulation. TNFAIP8L2 shows promise as a prognostic biomarker, while TNFAIP8 and TNFAIP8L1 may indicate adverse cytogenetic risk. The study highlights their potential as therapeutic targets in AML.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12058638 | PMC |
http://dx.doi.org/10.1007/s12672-025-02511-5 | DOI Listing |