{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,12]],"date-time":"2026-07-12T23:04:21Z","timestamp":1783897461508,"version":"3.55.0"},"reference-count":44,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T00:00:00Z","timestamp":1783900800000},"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. Genet."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Tumor-associated inflammation is an important contributor to cancer progression and therapeutic resistance. However, the molecular regulators linking inflammatory signaling with tumor biology in lung adenocarcinoma (LUAD) remain incompletely defined.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We implemented an integrative multi-cohort and machine learning framework to identify inflammation-associated candidate regulators in LUAD. Immune-inflammatory genes derived from hallmark pathways were intersected with differentially expressed and prognosis-associated genes in TCGA-LUAD. Transcriptomic and clinical data from TCGA and 13 independent GEO cohorts were integrated for model development and validation. Multi-algorithm prioritization was applied to derive a consensus prognostic signature and nominate core candidates. Multi-omics analyses were conducted to characterize genomic alterations and immune associations. Functional relevance was examined using loss-of-function experiments in lung cancer cell lines.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We identified 52 inflammation-associated candidate genes and derived a 10-gene core signature with moderate prognostic performance across independent cohorts, while cohort and endpoint heterogeneity remained evident. Among these genes, PANX1 emerged as a focused candidate for further characterization based on an integrative assessment of model contribution, recurrence across analyses, and biological plausibility. Multi-omics analyses linked PANX1 expression to copy-number alterations, mutational context, and inferred immune microenvironment features. PANX1 was significantly upregulated in lung cancer cells, and its knockdown inhibited cell proliferation, reduced extracellular ATP release, and suppressed pro-inflammatory cytokine expression, including IL6, TNFA, and IL1B.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>By integrating large-scale multi-cohort analysis, machine learning prioritization, and experimental validation, this study identifies PANX1 as a potential inflammation-associated regulator in LUAD. These findings support a previously underrecognized association between PANX1 and inflammatory tumor biology and suggest its potential value as a biomarker candidate, while further mechanistic and translational validation is required.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fgene.2026.1831053","type":"journal-article","created":{"date-parts":[[2026,7,12]],"date-time":"2026-07-12T22:10:25Z","timestamp":1783894225000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Machine learning prioritization identifies PANX1 as an inflammation-associated candidate regulator in lung adenocarcinoma"],"prefix":"10.3389","volume":"17","author":[{"given":"Ya","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Geriatrics, The Affiliated Huai\u2019an Hospital of Xuzhou Medical University","place":["Huai\u2019an, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tingyuan","family":"Fan","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine, The Yangzhou Clinical Medical College of Xuzhou Medical University","place":["Yangzhou, Jiangsu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaye","family":"Miao","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine, The Yangzhou Clinical Medical College of Xuzhou Medical University","place":["Yangzhou, Jiangsu, China"]},{"name":"Department of Laboratory Medicine, Northern Jiangsu People\u2019s Hospital","place":["Yangzhou, Jiangsu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuanli","family":"Ren","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine, The Yangzhou Clinical Medical College of Xuzhou Medical University","place":["Yangzhou, Jiangsu, China"]},{"name":"Department of Laboratory Medicine, Northern Jiangsu People\u2019s Hospital","place":["Yangzhou, Jiangsu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,13]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"140","DOI":"10.5414\/np301501","article-title":"Expression of pannexin1 in lung cancer brain metastasis and immune microenvironment","volume":"42","author":"Abdo","year":"2023","journal-title":"Clin. 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