{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T15:54:55Z","timestamp":1753890895853,"version":"3.41.2"},"reference-count":28,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,4,4]],"date-time":"2025-04-04T00:00:00Z","timestamp":1743724800000},"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><jats:title>Background<\/jats:title><jats:p>Identifying uncommon neutrophilic leukemias presents a challenging task, owing to the analogous morphological characteristics and the dearth of molecular markers. The transcriptomic profile of bone marrow cells in this disease subset has been rarely explored.<\/jats:p><\/jats:sec><jats:sec><jats:title>Material and Methods<\/jats:title><jats:p>The OHSU-CNL dataset, encompassing clinical parameters and parallel transcriptomic matrix, was downloaded from the Genomic Data Commons (GDC) database. Distinctive co-expressed gene modules and pivotal genes for chronic neutrophilic leukemia (CNL) were identified using R software. Subsequently, a diagnostic model for CNL denoted as CNL-5 was formulated employing least absolute shrinkage and selection operator (LASSO) regression analysis. The diagnostic power of the CNL-5 model was compared with conventional clinical\/genetic markers via multi-ROC analysis. The divergence in overall survival between CNL-5 risk groups was delineated by Kaplan\u2013Meier analysis, and the predictive power (AUC and Harrison\u2019s C index) was determined by time-dependent ROC. Cell signaling pathways associated with CNL-5 risk were identified by genomic set enrichment analysis (GSEA).<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Neither clinical indicators nor genetic markers were sufficient to classify neutrophilic leukemias. Through weighted gene co-expression network analysis (WGCNA), the brown module was discerned to be CNL-specific (p = 8e\u221216, R<jats:sup>2<\/jats:sup> = 0.5). Using LASSO analysis, the CNL-5 model, with risk scores based on the weighted expression value of five genes (PDCD7\/CR2\/ZSCAN20\/TRIM68\/LILRA6) dichotomized patients into CNL-like and Atypical-CNL groups. Compared to the Atypical-CNL group, the CNL-like group demonstrated a clinical phenotype more consistent with CNL and had a significantly higher prevalence of CSF3R mutations (p\u00a0&amp;lt;\u00a00.05). Additionally, the AUC of the CNL-5 risk model surpassed that of conventional clinical\/genetic markers, as validated by the GSE42731 dataset. Poorer survival was revealed in the high-risk group than in the low-risk group defined by the CNL-5 model. GSEA identified CNL-5-associated pathways, such as the inhibition of oxidative phosphorylation and the activation of IL6-JAK-STAT3 signaling.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>A novel expression signature-based diagnostic assessment for CNL was developed, which showed better diagnostic utility than conventional indicators.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fgene.2025.1556519","type":"journal-article","created":{"date-parts":[[2025,4,4]],"date-time":"2025-04-04T11:45:30Z","timestamp":1743767130000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Transcriptomic signature can distinguish chronic neutrophilic leukemia from ambiguous neutrophilic leukemias"],"prefix":"10.3389","volume":"16","author":[{"given":"Chao","family":"Guo","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhen-Ling","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2025,4,4]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"2391","DOI":"10.1182\/blood-2016-03-643544","article-title":"The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia","volume":"127","author":"Arber","year":"2016","journal-title":"Blood"},{"key":"B2","doi-asserted-by":"publisher","first-page":"400","DOI":"10.1111\/bjh.13600","article-title":"Chronic neutrophilic leukaemia and plasma cell-related neutrophilic leukaemoid reactions","volume":"171","author":"Bain","year":"2015","journal-title":"Br. 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