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Objective: In both industrialized and developing nations worldwide, lung adenocarcinoma is one of the deadliest malignant tumors and the primary cause of cancer-related deaths. Its cellular heterogeneity is unclear to the fullest extent, although in recent years, its prevalence in younger individuals has increased. Therefore, it is urgent to deepen the understanding of lung adenocarcinoma and explore new therapeutic methods.
Methods: CytoTRACE, Monocle, SCENIC, and enrichment analysis were used to analyze the single cell RNA data, we characterized the biological characteristics of mast cells (MCs) in lung adenocarcinoma patient samples. CellChat was used to analyze and validate the interaction between MCs and tumor cells in lung adenocarcinoma. Prognostic models were used to evaluate and predict the development trend and outcome of a patient's disease, such as the survival time of cancer patients. The python package SCENIC was used to evaluate the enrichment of transcription factors and the activity of regulators in lung adenocarcinoma cell subgroups. CCK-8 assay could validate the activity of a specific cell subgroup sequenced in single cell sequencing to confirm the role of this cell subgroup in tumor proliferation.
Results: Our analysis identified seven major cell types, further grouping MCs within them and identifying four distinct subgroups, including MCs with high DUSP2 expression, which showed some tumor-related characteristics. In addition, we identified the key signaling receptor EGFR and validated it through in vitro knockdown experiments, demonstrating its role in promoting cancer. In addition, we established an independent prognostic indicator, the DUSP2+ MCs risk score, which showed an association between groups with high risk scores and poor outcomes.
Conclusion: These findings shed light on the complex interactions in the lung adenocarcinoma tumor microenvironment and suggest that targeting specific MCs subgroups, particularly through the EGFR signaling pathway, may provide new therapeutic strategies.
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http://dx.doi.org/10.1016/j.tranon.2025.102295 | DOI Listing |
Genes Genomics
September 2025
Department of Clinical Laboratory, The First Affiliated Hospital of Guilin Medical University, Le Qun Road 15, Guilin, 541001, Guangxi, China.
Background: Lung cancer (LC) is the leading cause of cancer-related deaths globally. Genetic variants in mismatch repair (MMR) genes, such as MutS homolog 2 (MSH2), MutS homolog 6 (MSH6) and MutL homolog 1 (MLH1), may influence individual susceptibility and clinical outcomes in LC.
Objective: This study investigated the associations of genetic polymorphisms in MSH2, MSH6, and MLH1 with susceptibility and survival outcomes in lung cancer patients in the Guangxi Zhuang population.
Langenbecks Arch Surg
September 2025
Department of Surgery HBP Unit, Simone Veil Hospital, University of Reims Champagne-Ardenne, Troyes, France.
Introduction: Pancreatic adenocarcinomas (PDAC) have a poor prognosis, with a 5-year relative Survival rate of 11.5%. Only 20% of patients are initially eligible for resection, and 50% of patients presented with metastatic disease, currently only candidates' palliative treatment.
View Article and Find Full Text PDFMol Cell Biochem
September 2025
Department of Laboratory Medicine, The People's Hospital of Zhongjiang, No. 96, Dabei Street, Kaijiang Town, Zhongjiang County, Deyang City, 618100, Sichuan Province, China.
5-methylcytosine (m5C) methylation is a post-transcriptional modification of RNAs, and its dysregulation plays pro-tumorigenic roles in lung adenocarcinoma (LUAD). Here, this study elucidated the mechanism of action of NSUN2, a major m5C methyltransferase, on LUAD progression. mRNA expression was analyzed by quantitative PCR.
View Article and Find Full Text PDFInt J Surg
September 2025
Department of Respiratory and Critical Care Medicine, Hubei Province Clinical Research Center for Major Respiratory Diseases, Key Laboratory of Pulmonary Diseases of National Health Commission, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
Background: Precise preoperative discrimination of invasive lung adenocarcinoma (IA) from preinvasive lesions (adenocarcinoma in situ [AIS]/minimally invasive adenocarcinoma [MIA]) and prediction of high-risk histopathological features are critical for optimizing resection strategies in early-stage lung adenocarcinoma (LUAD).
Methods: In this multicenter study, 813 LUAD patients (tumors ≤3 cm) formed the training cohort. A total of 1,709 radiomic features were extracted from the PET/CT images.
AJR Am J Roentgenol
September 2025
Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China, 510120.