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Updated: Jul 24, 2025
Pancreatic Tissue Dissection to Isolate Viable Single Cells
Published on: May 26, 2023
Therapy-associated remodeling of pancreatic cancer revealed by single-cell spatial transcriptomics and optimal
Carina Shiau1, Jingyi Cao2, Mark T Gregory3
1Center for Systems Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Abstract:
In combination with cell intrinsic properties, interactions in the tumor microenvironment modulate therapeutic response. We leveraged high-plex single-cell spatial transcriptomics to dissect the remodeling of multicellular neighborhoods and cell-cell interactions in human pancreatic cancer associated with specific malignant subtypes and neoadjuvant chemotherapy/radiotherapy. We developed Spatially Constrained Optimal Transport Interaction Analysis (SCOTIA), an optimal transport model with a cost function that includes both spatial distance and ligand-receptor gene expression. Our results uncovered a marked change in ligand-receptor interactions between cancer-associated fibroblasts and malignant cells in response to treatment, which was supported by orthogonal datasets, including an ex vivo tumoroid co-culture system. Overall, this study demonstrates that characterization of the tumor microenvironment using high-plex single-cell spatial transcriptomics allows for identification of molecular interactions that may play a role in the emergence of chemoresistance and establishes a translational spatial biology paradigm that can be broadly applied to other malignancies, diseases, and treatments.
Insights
Tumor microenvironment interactions impact cancer treatment. High-plex spatial transcriptomics revealed how chemotherapy and radiotherapy alter cell-cell communication, offering insights into chemoresistance and guiding future cancer therapies.
Area of Science:
- Oncology
- Systems Biology
- Genomics
Background:
- Tumor microenvironment (TME) complexity influences therapeutic outcomes.
- Understanding cell-cell interactions within the TME is crucial for cancer treatment response.
Approach:
- Utilized high-plex single-cell spatial transcriptomics to analyze TME remodeling in pancreatic cancer.
- Developed Spatially Constrained Optimal Transport Interaction Analysis (SCOTIA) to model spatial and gene expression interactions.
- Validated findings using orthogonal datasets and an ex vivo tumoroid co-culture system.
Key Points:
- Identified significant changes in ligand-receptor interactions between cancer-associated fibroblasts and malignant cells post-treatment.
- SCOTIA model effectively integrates spatial proximity and molecular signaling for interaction analysis.
- High-plex spatial transcriptomics provides a powerful tool for dissecting TME dynamics.
Conclusions:
- Characterizing TME interactions aids in identifying mechanisms of chemoresistance.
- This study establishes a translational spatial biology framework applicable to diverse diseases and treatments.
- Findings pave the way for novel therapeutic strategies targeting TME communication.
