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Spatial Transcriptomics in Lung Cancer and Pulmonary Diseases: A Comprehensive Review
Da Hyun Kang1, Yoonjoo Kim1, Ji Hyeon Lee1
1Division of Pulmonology and Critical Care Medicine, Department of Internal Medicine, College of Medicine, Chungnam National University, Daejeon 34134, Republic of Korea.
Cancers
|June 26, 2025
Summary
Spatial transcriptomics (ST) reveals lung tissue's cellular landscape and disease mechanisms. This technology maps gene expression in situ, aiding in understanding respiratory diseases and guiding personalized treatments.
Area of Science:
- Molecular Biology
- Genomics
- Respiratory Medicine
Background:
- Spatial transcriptomics (ST) advances lung research by preserving gene expression's spatial context.
- Conventional methods miss localized cellular interactions and transcriptional patterns crucial for understanding lung diseases.
Purpose of the Study:
- To review the emerging role of ST in respiratory research.
- To highlight ST's potential in disease classification, understanding treatment resistance, and guiding personalized interventions.
Main Methods:
- Spatial transcriptomics (ST) techniques analyze gene expression within the native tissue architecture.
- ST enables mapping of cellular niches, cell-cell interactions, and transcriptional hotspots in lung tissue.
Main Results:
- ST has delineated distinct tumor microenvironments in lung cancer, identifying prognostically significant gene signatures.
- ST has mapped immune cells, inflammatory mediators, and fibroblast subtypes in COPD, asthma, and IPF, providing mechanistic insights.
- Recent ST studies offer spatial insights into drug action within tissues.
Conclusions:
- ST revolutionizes understanding of lung cellular organization and pathology.
- ST provides a powerful tool for refining disease classification and understanding therapeutic resistance in respiratory diseases.
- Spatially guided personalized interventions are a promising future application of ST in respiratory medicine.
