ArticleComputational and structural biotechnology journal2022
Classification of lung adenocarcinoma based on stemness scores in bulk and single cell transcriptomes.
Article in Computational and structural biotechnology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Single-cell and transcriptomic profiling reveal stemness-driven immune evasion in obstructive sleep apnea (OSA) associated lung cancer.Journal of Cancer · 2026Article
- In silico-based analysis and in vitro experiments identify SIGMAR1 as a potential marker of putative lung cancer stem cells.Discover oncology · 2025Article
- Integrated Bioinformatic Analyses Reveal Thioredoxin as a Putative Marker of Cancer Stem Cells and Prognosis in Prostate Cancer.Cancer informatics · 2025Article
- The evolution of lung adenocarcinoma precursors is associated with chromosomal instability and transition from innate to adaptive immune response/evasion.Research square · 2024Article
- Identifying cancer subtypes based on embryonic and hematopoietic stem cell signatures in pan-cancer.Cellular oncology (Dordrecht, Netherlands) · 2024Article
- Stromal Signals Dominate Gene Expression Signature Scores That Aim to Describe Cancer Cell-intrinsic Stemness or Mesenchymality Characteristics.Cancer research communications · 2024Article
- Proteomics-based clustering of lung adenocarcinoma identifies three subtypes with significantly different clinical and molecular features.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2024Article
- The Tumor Stemness Indice mRNAsi can Act as Molecular Typing Tool for Lung Adenocarcinoma.Biochemical genetics · 2023Article
- Bioinformatics analysis based on DNA methylation data identified in lung adenocarcinoma subgroups with different immune characteristics and clinical outcomes.Journal of thoracic disease · 2023Article
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Abstract
Tumor stemness is associated with tumor progression and therapy resistance. The recent advances in sequencing, genomics, and computational technologies have facilitated investigation into the tumor stemness cell-like characteristics. We identified subtypes of lung adenocarcinoma (LUAD) in bulk tumors or single cells based on the enrichment scores of 12 stemness signatures by clustering analysis of their transcriptomic profiles. Three stemness subtypes of LUAD were identified: St-H, St-M, and St-L, having high, medium, and low stemness signatures, respectively, consistently in six different datasets. Among the three subtypes, St-H was the most enriched in epithelial-mesenchymal transition, invasion, and metastasis signaling, genomically instable, irresponsive to immunotherapies and targeted therapies, and hence had the worst prognosis. We observed that intratumor heterogeneity was significantly higher in high-stemness than in low-stemness bulk tumors, but significantly lower in high-stemness than in low-stemness single cancer cells. Moreover, tumor immunity was stronger in high-stemness than in low-stemness cancer cells, but weaker in high-stemness than in low-stemness bulk tumors. These differences between bulk tumors and single cancer cells could be attributed to the non-tumor cells in bulk tumors that confounded the results of correlation analysis. Furthermore, pseudotime analysis showed that many St-H cells were at the beginning of the cell evolution trajectory, compared to most St-L cells in the terminal or later phase, suggesting that many low-stemness cells are originated from high-stemness cells. The stemness-based classification of LUAD may provide novel insights into the tumor biology as well as precise clinical management of this disease.
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