Evidence map›Paper›PMID 42381064›Full record

ArticleCancer cell international2026

Single-cell-marker-based subtyping and multi-level analyses uncover the prognostic effects, dysregulations and therapeutic indicative potential of an eight-gene signature in lung adenocarcinoma.

Xiuzhi Zhang, Fengqi Chen, Wenke Sun, Hanke Ma, Feifei Liang, Liping Dai, Chunyan Kang, Xiaoli Liu

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Article in Cancer cell international, 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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8 authors.

Xiuzhi ZhangDepartment of Pathology, Henan Medical College, Zhengzhou, 451191, China.
Fengqi ChenHenan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, 450052, China.
Wenke SunHenan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, 450052, China.
Hanke MaHenan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, 450052, China.
Feifei LiangHenan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, 450052, China.
Liping DaiHenan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, 450052, China. lpdai@zzu.edu.cn.
Chunyan KangDepartment of Pathology, Henan Medical College, Zhengzhou, 451191, China. kcy200608@163.com.
Xiaoli LiuLaboratory Department, Henan Provincial People's Hospital, Zhengzhou, 450003, China. lxlzts@126.com.

Funding

Henan Provincial Science and Technology Key R&D Project 252102310109Henan Provincial Soft Science Research Program 252400410244the Key Projects of Higher Education Institutions in Henan Province 24B320005
6 · The paper itself

Abstract

backgroundLung adenocarcinoma (LUAD), the predominant subtype of non-small cell lung cancer, exhibits substantial molecular heterogeneity, complicating the identification of reliable prognostic and therapeutic markers. Single-cell transcriptome analysis, combined with other omics and multi-level analyses, offers a feasible solution to address this issue.

methodsWe clustered, annotated, and identified landmark genes for single cells in LUAD dataset. Using the expression profiles of these marker genes, we classified TCGA-LUAD samples via non-negative matrix factorization (NMF) clustering. The LUAD subtypes were compared for prognosis, tumor stage, gene expression, aging and stemness scores, and immunotherapy response (assessed by TIDE). LASSO-Cox regression analysis selected key genes for a prognostic model, which was validated in training and external datasets. RT-qPCR was used to validate mRNA expression levels. Protein-level dysregulation was confirmed through proteomics and immunohistochemistry (IHC). Additionally, the functional effects of the key genes and their drug-sensitivity associations were explored in LUAD cell lines.

resultsSingle cells were annotated into 12 types/subtypes, including three epithelial-associated and two fibroblast-associated subtypes. The top 100 marker genes for each cell type/subtype were identified. Based on these marker gene expressions, TCGA-LUAD samples were classified into C1 and C2 subtypes. Compared with C1 LUADs, C2 LUADs exhibited poorer prognosis, a higher proportion of late-stage tumors, higher MKI67 expression, and higher levels of aging and stemness, but lower MHC II gene expression and TIDE scores. LASSO-Cox regression analysis identified an eight-gene signature that effectively distinguished patient outcomes in both training and validation datasets. Dysregulation of these eight genes was confirmed at the mRNA level by RT-qPCR and at the protein level by proteomic and IHC analyses. Moreover, these eight genes were associated with sensitivity to 3-28 anti-cancer drugs in LUAD cell lines.

conclusionSubtyping based on single-cell derived marker genes and multi-level analyses provide a comprehensive understanding of LUAD biology. The distinct features of C1 and C2 subtypes highlight the need for tailored therapies. The eight-gene signature may serve as a novel prognostic, diagnostic, and therapeutic indicator.

Indexed as

Drug sensitivityImmune responseLung adenocarcinomaMHC IIMulti-omicsPrognosisSubtyping

Identifiers

PMID42381064
PMCPMC13587500

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