Evidence map›Paper›PMID 41323776›Full record

ArticleStem cells international2025

The Epithelial Cell-Associated Gene PMAIP1 Serves as a Prognostic Biomarker for Lung Adenocarcinoma and Can Regulate the Stemness of Lung Cancer.

Haoran Wang, Hui Zhang, Peipei Kang, Qin Ge, Xiaohong Chen, Gujun Cong

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Article in Stem cells international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Haoran WangDepartment of Anesthesiology, Tumor Hospital Affiliated to Nantong University, Nantong, Jiangsu 226300, China.ORCID https://orcid.org/0009-0001-6041-9810
Hui ZhangDepartment of Laboratory Medicine, Tumor Hospital Affiliated to Nantong University, Nantong, Jiangsu 226300, China.ORCID https://orcid.org/0009-0005-3796-0384
Peipei KangDepartment of Anesthesiology, Tumor Hospital Affiliated to Nantong University, Nantong, Jiangsu 226300, China.ORCID https://orcid.org/0009-0008-9528-2659
Qin GeDepartment of Radiation Oncology, Tumor Hospital Affiliated to Nantong University, Nantong, Jiangsu 226300, China.ORCID https://orcid.org/0000-0001-6735-0097
Xiaohong ChenDepartment of Anesthesiology, Tumor Hospital Affiliated to Nantong University, Nantong, Jiangsu 226300, China.ORCID https://orcid.org/0009-0006-7575-0887
Gujun CongDepartment of Laboratory Medicine, Nantong Fourth People's Hospital, Nantong, Jiangsu 226300, China.ORCID https://orcid.org/0009-0005-7193-3179

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epithelial cells are integral to tumor composition and engage with various immune cell types within the tumor microenvironment, influencing tumor progression and metastasis. A thorough exploration of the roles and mechanisms of these epithelial cells could enhance early detection strategies and treatment modalities for lung adenocarcinoma (LUAD). This research employed single-cell analysis techniques, complemented by machine learning algorithms, to identify genes associated with epithelial cells and evaluate their prognostic significance and implications for immunotherapy in LUAD patients. By leveraging multiple datasets and applying diverse clustering methods within machine learning, we successfully crafted and validated a diagnostic model specifically for LUAD. Among the genes linked to epithelial cells, the XGBoost and random forest techniques identified PMAIP1 as the most crucial gene in terms of prognosis. Additionally, this study investigated the relationship between PMAIP1 and the infiltration of immune cells. The expression levels of PMAIP1 and its relevance in LUAD were subsequently confirmed through immunohistochemical staining and in vitro cell experiments. This analysis revealed 17 key genes associated with epithelial cells by integrating single-cell analysis with clinical data from the TCGA-LUAD dataset, underscoring their significance in diagnosis, prognostic assessment, and possible treatment avenues for LUAD patients. Importantly, PMAIP1 is strongly linked to prognosis and responses to immunotherapy in LUAD, with experimental findings indicating its heightened expression in PRAD and its connection to adverse outcomes. Furthermore, reducing PMAIP1 expression has been shown to hinder the proliferation, metastasis, and stemness of LUAD cells. In summary, our findings indicate that PMAIP1 has potential as a prognostic biomarker and a target for immunotherapy in patients with LUAD.

Indexed as

epithelial cell-related geneLUADmachine learningPMAIP1single-cell analysis

Identifiers

PMID41323776
PMCPMC12662687

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.