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In Silico Reconstruction of Primary and Metastatic Tumor Architecture Using Geographic Information System-Augmented

Jin Young Yoo1, Sabrina Akter1, Qianying Zuo1

  • 1Department of Food Science and Human Nutrition, University of Illinois Urbana-Champaign, Urbana, Illinois.

Cancer Research
|February 24, 2026
PubMed
Summary
This summary is machine-generated.

We developed GIS-ROTA, a new framework using spatial transcriptomics to map tumor microenvironment functions. This method reveals spatial patterns linked to estrogen response, metabolism, and metastasis in breast cancer.

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Area of Science:

  • Oncology
  • Bioinformatics
  • Genomics

Background:

  • Tumor microenvironment complexity influences cancer progression and treatment outcomes.
  • Spatial transcriptomics reveals cellular and transcriptional heterogeneity within tumors.

Purpose of the Study:

  • To introduce GIS-ROTA, a novel analytical framework for reconstructing tumor architecture.
  • To integrate biological knowledge with spatial data for interpretable domain identification.

Main Methods:

  • Developed Geographic Information System (GIS)-augmented in silico reconstruction of tumor architecture (GIS-ROTA).
  • Integrated pathway/cell type enrichment analysis with spatial autocorrelation.
  • Applied GIS-ROTA to Visium spatial transcriptomics data from breast cancer samples.

Main Results:

  • Identified functional spatial domains within the tumor microenvironment.
  • Revealed co-localization of estrogen response and metabolic pathways.
  • Observed mutual exclusivity between estrogen response and metastasis/immune pathways.

Conclusions:

  • GIS-ROTA provides a biologically informed approach to analyze spatial transcriptomics data.
  • The framework yields functionally relevant spatial patterns, aiding interpretability.
  • GIS-ROTA can identify novel therapeutic targets for breast cancer treatment.