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
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Purpose: N6-methyladenosine (mA) methylation plays a critical role in diverse biological processes. However, knowledge regarding the constitution of mA on tumor microenvironment (TME) and tumor-infiltrating lymphocytes (TILs) across cancer types is still lacking. We performed comprehensive immuno-genomic analyses to reveal molecular characterization of the mA regulators and immune-related genes (IRGs) across TME and TIL heterogeneity.
Methods: We comprehensively analyzed the properties of mA regulators in genomic profiles from The Cancer Genome Atlas (TCGA) according to expression perturbations of crucial IRGs, CD274, CD8A, GZMA, and PRF1. The four IRGs were proved to be reliable biomarkers of TILs and TME CIBERSORT and ESTIMATE analyses, and their co-expression relationship was certified by TIMER analysis. Based on their median values, the samples from the pan-cancer tissues (N = 11,057) were classified into eight TME types. The RNA expression levels of 13 mA regulators were compared across TME subtypes. Single-sample Gene Set Enrichment Analysis (ssGSEA) was also used to classify TME clusters, expression variants of IRGs and mA regulators were verified among TME clusters. Meanwhile, the correlation between mA regulators and tumor mutational burden (TMB) were tested. Finally, the impacts of IRGs and TME clusters in clinical characteristics and outcomes were revealed.
Results: CD274, CD8A, GZMA, and PRF1 showed similar TILs' characteristics, of which the level of T cells CD8 and T cells CD4 memory activated are consistent with the expression levels of the four IRGs and higher immune infiltration. Besides, CD274, CD8A, GZMA, and PRF1 were positively correlated with the stromal score or immune score in almost all 33 tumor types. All of four IRGs showed impact between tumor pathological stages or clinical outcomes. Among TME type I to type IV, mA regulators' expression drift changed from high-level to low-level in ESCA, BLCA, HNSC, CESC, BRCA, and GBM. However among TME type V to type VIII, mA regulators drew a shift from low-level to high-level expression in CESC, BLCA, ESCA, KIRP, HNSC, BRCA, KIRC, COAD, LAML, GBM, and KICH. In ssGSEA analyses, IRGs' expression levels were elevated with the immune infiltration degree and mA regulators' expression level varied among three TIL subgroups. With different TMB levels, expression differences of mA regulators were observed in BLCA, BRCA, COAD, LGG, LUAD, LUSC, STAD, THCA, and UCEC.
Conclusion: We identified four crucial IRGs affecting TILs, TME characteristics and clinical parameters. Expression variants of mA regulators among the subgroups of TME types and ssGSEA clusters suggested that mA regulators may be essential factors for phenotypic modifications of IRGs and thus affecting TME characteristics across multiple tumor types.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7876474 | PMC |
http://dx.doi.org/10.3389/fonc.2020.618374 | DOI Listing |
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