Evidence map›Paper›PMID 42209795›Full record

ArticleFunctional & integrative genomics2026

A clinically relevant SLC2A1-associated malignant epithelial cell state predicts prognosis and immunotherapy response in lung adenocarcinoma.

Linqian Song, Shiyun Xing, Peijie Li, Yunliang Cao, Hu Ma

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Article in Functional & integrative genomics, 2026. 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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5 · Who and what money

Authors and funding

5 authors.

Linqian SongDepartment of Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, Guizhou, P. R. China.
Shiyun XingDepartment of Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, Guizhou, P. R. China.
Peijie LiDepartment of Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, Guizhou, P. R. China.
Yunliang CaoDepartment of Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, Guizhou, P. R. China.
Hu MaDepartment of Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, Guizhou, P. R. China. mahuab@163.com.ORCID http://orcid.org/0000-0003-1654-1576

Funding

Guizhou Provincial Administration of Traditional Chinese Medicine's Traditional Chinese Medicine and Ethnic Medicine Science and Technology Research Project QZYY-2023-108Noncommunicable Chronic Diseases - National Science and Technology Major Project 2023ZD0502105the National Natural Science Foundation of China 82504050Zunyi Municipal Science and Technology Cooperation Project HZ [2025] 129
6 · The paper itself

Abstract

Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related mortality, with therapeutic resistance largely driven by unresolved malignant epithelial heterogeneity within the tumor microenvironment. However, the epithelial cell states that underlie poor prognosis and immunotherapy resistance remain incompletely defined. We performed an integrative multi-omics analysis combining large-scale single-cell RNA sequencing, spatial transcriptomics, and bulk transcriptomic data with clinical outcomes. The Scissor algorithm was applied to identify prognosis-associated epithelial cell states, followed by construction of a risk score model. External validation was conducted across multiple independent cohorts, including immunotherapy-treated datasets. We identified a prognostically relevant Scissor⁺ malignant epithelial cell state associated with adverse survival. This state was characterized by activation of MYC, epithelial-mesenchymal transition, hypoxia, and NF-κB signaling, and was linked to an immunosuppressive tumor microenvironment. Based on this state, we developed a Scissor⁺ epithelial cell-derived risk score (SERS), which demonstrated robust and reproducible prognostic performance across multiple cohorts and was associated with reduced responsiveness to immunotherapy. Further analyses identified SLC2A1 as a key gene associated with this malignant epithelial state. Functional experiments confirmed that SLC2A1 promotes tumor cell proliferation, migration, and invasion. In addition, cell-cell communication analysis suggested a potential SLC2A1-CAF-collagen signaling axis linking epithelial cell states with stromal interactions. This study defines a clinically relevant malignant epithelial cell state in LUAD and establishes a framework linking cell states, molecular features, and microenvironmental interactions. These findings provide potential biomarkers for prognostic stratification and immunotherapy response prediction in LUAD.

Indexed as

Adenocarcinoma of LungBiomarkers, TumorGlucose Transporter Type 1ImmunotherapyLung NeoplasmsEpithelial CellsEpithelial-Mesenchymal TransitionGene Expression Regulation, NeoplasticHumansPrognosisTumor MicroenvironmentBiomarkers, TumorGlucose Transporter Type 1Lung adenocarcinomaMalignant epithelial cell statesPrognostic risk modelSingle-cell RNA sequencingSLC2A1Tumor microenvironment

Identifiers

PMID42209795
PMCPMC13219086

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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.