Spatial Transcriptomics Unveils Regional Heterogeneity and Subclonal Dynamics in the Lung Adenocarcinoma Microenvironment
Abstract
Background and objective Lung adenocarcinoma has high incidence and mortality rates. While single-cell transcriptomics reveals tumor cell heterogeneity, it lacks spatial detail, leaving the spatial dynamics and functional heterogeneity largely unexplored. This study aims to utilize spatial transcriptomics to provide a comprehensive cellular landscape of lung adenocarcinoma, addressing the limitations of single-cell analysis.Methods Utilizing cell type-specific markers and spatial transcriptomics data derived from single-cell transcriptomic analysis, we performed cell deconvolution, assessed tissue preferences, constructed trajectories, and analyzed spot-spot interactions to create a comprehensive cellular landscape of lung adenocarcinoma.Results We conducted unsupervised dimensionality reduction clustering on 125,203 single cells from single-cell transcriptomics, and used this data to deconvolute the cellular composition of each of the 3990 spots in a separately analyzed spatial transcriptomics sample. By constructing a trajectory from the tumor's periphery to its core, we discovered that pathways related to oxygen level responses were significantly upregulated, while immune response pathways were notably downregulated. Pseudotime analysis identified fibroblast areas closely associated with the tumor, with neighboring tumor areas exhibiting strong epithelial-mesenchymal transition and tumor migration characteristics, defined as the direction of tumor invasion. Further dimensionality reduction clustering within the tumor area differentiated six subgroups, each showing significant spatial and functional heterogeneity. Notably, the Ca_0 subgroup is closely linked to the tumor invasion process, whereas the Ca_1 subgroup is significantly associated with poor prognosis. Interaction analysis suggests that the Ca_1 subgroup may facilitate overall tumor progression by promoting angiogenesis and immune escape, rather than by directly participating in tumor invasion.Conclusions This study provides an in-depth analysis of the spatial-functional heterogeneity in lung adenocarcinoma and its microenvironment, revealing four functionally heterogeneous groups with significant spatial and functional diversity within the tumor microenvironment. The study also identifies key areas and gene expression changes closely associated with tumor invasion and progression, highlighting critical aspects of tumor dynamics.
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Proteogenomic studies in hepatocellular carcinoma have identified three molecular classes: immune-hot with favorable outcomes, proliferative and TP53-enriched with angiogenic signaling and poorer outcomes, and CTNNB1-enriched with mTOR-pathway activation.
“In hepatocellular carcinoma, for example, proteogenomic studies integrating whole-genome sequencing, RNA sequencing, and quantitative proteomics have identified three molecular classes: immune-“hot” with favorable outcomes, proliferative and TP53-enriched with angiogenic signaling and poorer outcomes, and CTNNB1-enriched with mTOR-pathway activation [88,89,90].”
From Artificial Intelligence in Clinical Oncology: From Productivity Enhancement to Creative Discovery (2025) · cites this paper as [90]
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- Authors
- An, H., Fang, W., Chen, H., Huang, W., Liu, H., Zhang, Z., Zhao, H., Zhang, Y., Zhao, M., Qiu, J., & Li, W.
- Affiliations
- Shandong University (CN)
- Qingdao Municipal Hospital (CN)
- Shandong Tumor Hospital (CN)
- Shandong First Medical University (CN)
- Corresponding author
- Zhao, Hanzhu
- Zhao, Miaoqing
- Qiu, Jianfeng
- Venue
- Computer Methods and Programs in Biomedicine
- Publisher
- Elsevier BV
- Published
- 2025-10
- Volume
- 270
- Pages
- 108929
- ISSN
- 0169-2607 (ISSN-L)
- OpenAlex
- W4411870354
- Cited by
- 6
- References
- 68
- Citations by year
- 2026: 5 · 2025: 1
- FWCI
- 1.79
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Computer Methods and Programs in Biomedicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Keywords
- lung adenocarcinoma, tumor microenvironment, spatial heterogeneity, cell type deconvolution, tumor invasion, epithelial-mesenchymal transition, tumor progression, angiogenesis, immune evasion, pseudotime trajectory, cell-cell interactions, prognostic subgroups
- MeSH terms
- Adenocarcinoma of Lung, Humans, Lung Neoplasms, Gene Expression Regulation, Neoplastic, Cluster Analysis, Gene Expression Profiling, Epithelial-Mesenchymal Transition, Single-Cell Analysis, Tumor Microenvironment, Transcriptome
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