SpatialSNV: A novel method for identifying and analyzing spatially resolved SNVs in tumor microenvironments

Area of Science:

• Oncology
• Genomics
• Bioinformatics

Background:

• Single-nucleotide variants (SNVs) are crucial in tumor development but their role in shaping tumor microenvironments is understudied.
• Spatial transcriptomics enables mapping SNVs within the tumor context, offering new insights into microenvironment dynamics.

Purpose of the Study:

• To develop a method for identifying effective SNVs across tumor sections using spatial transcriptomics.
• To explore the relationship between SNVs, tumor evolution, and the tumor microenvironment.
• To investigate SNV-driven tumor-immune system crosstalk and identify potential therapeutic targets.

Main Methods:

• Development of SpatialSNV tool for SNV identification from spatial transcriptomics data.
• Analysis of SNV distribution and correlation with microenvironmental factors.
• Identification of spatially correlated SNV groups and their association with tumor-immune interactions.

Main Results:

• SpatialSNV successfully identified SNVs reflecting regional tumor evolution and microenvironmental characteristics.
• SNVs diminished with distance from tumor margins and were linked to inflammatory and hypoxic regions.
• Spatially correlated SNVs implicated specific roles in tumor-immune crosstalk, with S100A11L40P identified as a potential therapeutic target in colorectal cancer.

Conclusions:

• SpatialSNV provides a framework for understanding tumor-immune crosstalk using spatial transcriptomics and SNV analysis.
• The approach facilitates the exploration of tumor heterogeneity and the identification of novel therapeutic targets.
• The scalable and adaptable nature of SpatialSNV makes it valuable for cancer research.