Integrating single-nucleus barcoding with spatial transcriptomics via Stamp-seq to reveal immunotherapy...

Area of Science:

• Spatial transcriptomics
• Cellular biology
• Cancer research

Background:

• Understanding spatial cell organization is crucial for development, tissue homeostasis, and disease pathology.
• Current spatial transcriptomic methods face challenges in cell state assignment, gene detection, and cost.

Purpose of the Study:

• To develop a novel method, Stamp-seq, for high-resolution spatial transcriptomic profiling.
• To enable precise cell state assignment and spatial mapping with reduced cost.
• To investigate cellular ecosystems in non-small cell lung carcinoma (NSCLC) and their response to chemoimmunotherapy.

Main Methods:

• Development of Stamp-seq using custom DNA sequencing chips with high-density, restriction enzyme-cleavable spatial barcodes.
• Achieving single physical cell resolution with an average 4 μm localization error.
• Application of Stamp-seq to delineate cellular ecosystems in NSCLC and spatially resolve B-cell receptor (BCR) clonotypes.

Main Results:

• Stamp-seq provides precise subtype classification and spatial mapping at reduced cost.
• Identified a distinct IGHG1+ plasma cell-enriched community within chemoimmunotherapy-responsive NSCLC ecosystems.
• Elucidated the spatiotemporal trajectory of IGHG1+ plasma cells, from origin to tumor cell contact.

Conclusions:

• Stamp-seq enables powerful spatial cellular subtyping and molecular tracking.
• The IGHG1+ plasma cell niche serves as a potential prognostic biomarker for chemoimmunotherapy response in NSCLC.