In situ spatial profiling: Gaining molecular and cellular insights within content and context

Abstract

For years, valuable clinical samples preserved in formalin-fixed paraffin-embedded tissues were underutilized. However, with advanced spatial multiomics profiling tools, crucial information has become increasingly accessible. Integrating genomic data with spatial information has unveiled crucial insights into cellular activities, enhancing our comprehension of biology. Measuring cellular gene expression while capturing spatial context - including morphology and intercellular relationships - is vital for understanding both normal and diseased biological processes. To date, this approach has illuminated the mechanisms of complex diseases, such as cancer and has facilitated the discovery of biomarkers for early disease detection and new therapeutic targets, accelerating progress in cancer immunotherapies. Cutting-edge single-cell analysis tools are rapidly emerging as the gold standard for investigating intricate biological systems and medical specimens, fueling a multi-billion-dollar industry. Single-cell spatial research, in particular, is inherently cross-disciplinary and addresses questions that remain hidden when focusing solely on the genome or transcriptome of large cell populations. Leveraging advances in single-cell spatial profiling can offer insights into improving cancer immunotherapy and other modern medical treatments. This review will delve into the diverse applications of spatial profiling technology, showcasing examples that demonstrate its ability to provide a detailed picture of the underlying molecular and cellular mechanisms within cells. As a comprehensive reference, this review empowers researchers and industry leaders to harness single-cell and spatial omics for breakthroughs in biomedicine and translational science.

Keywords

Formalin-fixed paraffin-embedded tissues / Genomics / Single-cell analysis / Spatial profiling / Transcriptomics

Acknowledgments

None.

Funding

None.

Conflict of interest

The authors declare that they have no competing interests.

Author contributions

Conceptualization: Chen Yeh

Formal analysis: Shu-Ti Lin, Ian Molyneaux

Investigation: Shu-Ti Lin, Chen Yeh

Methodology: Shu-Ti Lin, Ian Molyneaux

Visualization: Shu-Ti Lin, Ian Molyneaux

Writing - original draft: Shu-Ti Lin

Writing - review & editing: Chen Yeh

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data

Not applicable.

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