{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T13:20:41Z","timestamp":1778851241840,"version":"3.51.4"},"reference-count":48,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2021,12,3]],"date-time":"2021-12-03T00:00:00Z","timestamp":1638489600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Cell Dev. Biol."],"abstract":"<jats:p>Primary open-angle glaucoma (POAG) is a progressive optic neuropathy and its damage to vision is irreversible. Therefore, early diagnosis assisted by biomarkers is essential. Although there were multiple researches on the identification of POAG biomarkers, few studies systematically revealed the transcriptome dysregulation mechanism of POAG from the perspective of pre- and post-transcription of genes. Here, we have collected multiple sets of POAG\u2019s aqueous humor (AH) tissue transcription profiles covering long non-coding RNA (lncRNA), mRNA and mircoRNA (miRNA). Through differential expression analysis, we identified thousands of significant differentially expressed genes (DEGs) between the AH tissue of POAG and non-glaucoma. Further, the DEGs were used to construct a competing endogenous RNA (ceRNA) regulatory network and 1,653 qualified lncRNA-miRNA-mRNA regulatory units were identified. Two ceRNA regulatory subnets were identified based on the random walk algorithm and revealed to be involved in the regulation of multiple complex diseases. At the pre-transcriptional regulation level, a transcriptional regulatory network was constructed and three transcription factors (<jats:italic>FOS, ATF4<\/jats:italic>, and <jats:italic>RELB<\/jats:italic>) were identified to regulate the expression of multiple genes and participate in the regulation of T cells. Moreover, we revealed the immune desert status of AH tissue for POAG patients based on immune infiltration analysis and identified a specific <jats:italic>AL590666.2<\/jats:italic>-<jats:italic>hsa\u2212miR\u2212339\u22125p<\/jats:italic>-<jats:italic>UROD<\/jats:italic> axis can be used as a biomarker of POAG. Taken together, the identification of regulatory mechanisms and biomarkers will contribute to the individualized diagnosis and treatment for POAG.<\/jats:p>","DOI":"10.3389\/fcell.2021.793638","type":"journal-article","created":{"date-parts":[[2021,12,3]],"date-time":"2021-12-03T06:56:34Z","timestamp":1638514594000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":16,"title":["Network Integration Analysis and Immune Infiltration Analysis Reveal Potential Biomarkers for Primary Open-Angle Glaucoma"],"prefix":"10.3389","volume":"9","author":[{"given":"Liyuan","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianyang","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaohui","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaojun","family":"Cai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"He","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2021,12,3]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1038\/nrc.2017.99","article-title":"Non-coding RNA Networks in Cancer","volume":"18","author":"Anastasiadou","year":"2018","journal-title":"Nat. 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