Background <p>Understanding cell–cell communication and its dependence on spatial organization is critical for unraveling tissue complexity and organ function, and it has been demonstrated that cells are influenced by their microenvironment and neighboring cells, affecting their gene expression and intercellular interactions. This study integrates single-cell RNA sequencing (scRNA-seq) with spatial transcriptomics (ST) to systematically assess how spatial niches influence gene expression and intercellular communication.</p> Results <p>Using breast cancer, brain cortex, and heart datasets, our analyses reveal limited global transcriptional changes in cells depending on their spatial microenvironment, with differential gene expression observed in half of the samples explored. Moreover, cell–cell communication predictions, derived from ligand-receptor pairs, exhibit minimal correlation with spatial colocalization of cell types.</p> Conclusions <p>Overall, our study underscores the limitations of using scRNA-seq data to capture niche-specific molecular interactions, even when spatial information is leveraged, and it highlights the need for novel strategies to refine our understanding of intercellular communication dynamics at the molecular level.</p>

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Systematic assessment of microenvironment-dependent transcriptional patterns and intercellular communication

  • Elena Pareja-Lorente,
  • Patrick Aloy

摘要

Background

Understanding cell–cell communication and its dependence on spatial organization is critical for unraveling tissue complexity and organ function, and it has been demonstrated that cells are influenced by their microenvironment and neighboring cells, affecting their gene expression and intercellular interactions. This study integrates single-cell RNA sequencing (scRNA-seq) with spatial transcriptomics (ST) to systematically assess how spatial niches influence gene expression and intercellular communication.

Results

Using breast cancer, brain cortex, and heart datasets, our analyses reveal limited global transcriptional changes in cells depending on their spatial microenvironment, with differential gene expression observed in half of the samples explored. Moreover, cell–cell communication predictions, derived from ligand-receptor pairs, exhibit minimal correlation with spatial colocalization of cell types.

Conclusions

Overall, our study underscores the limitations of using scRNA-seq data to capture niche-specific molecular interactions, even when spatial information is leveraged, and it highlights the need for novel strategies to refine our understanding of intercellular communication dynamics at the molecular level.