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Related Experiment Video

Updated: Sep 15, 2025

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From tissue architecture to clinical insights: Spatial transcriptomics in solid tumor studies.

Arpit Sharma1, Shruti S Raut2, Alok Shukla2

  • 1Biomolecular Engineering Laboratory, School of Biochemical Engineering, Indian Institute of Technology (BHU), Varanasi, India; Department of Pharmacology, Institute of Medical Sciences-Banaras Hindu University, Varanasi, India.

Seminars in Oncology
|July 15, 2025
PubMed
Summary

Spatial transcriptomics reveals tumor microenvironment complexity for better cancer diagnosis and treatment. This technology maps gene expression in intact tissues, aiding in biomarker discovery and advancing precision oncology.

Keywords:
Cancer biomarkersPrecision oncologySpatial transcriptomicsTumor heterogeneityTumor microenvironment

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Area of Science:

  • Oncology
  • Molecular Biology
  • Genomics

Background:

  • Cancer's heterogeneity impacts diagnosis, prognosis, and treatment response.
  • The tumor microenvironment (TME) plays a critical role alongside genetic alterations.
  • Spatial transcriptomics preserves gene expression context in tissues, enabling TME analysis.

Purpose of the Study:

  • To review advancements in spatial transcriptomics technologies.
  • To explore applications of spatial transcriptomics in solid tumor research.
  • To discuss future trends and challenges in the field.

Main Methods:

  • Evolution of spatial transcriptomics from in situ hybridization to imaging and sequencing platforms.
  • Integration with single-cell multiomics and computational algorithms.
  • Analysis of spatially resolved transcriptomics data.

Main Results:

  • Spatial transcriptomics deciphers tumor architecture and intercellular communication.
  • Reveals molecular landscapes of tumor cores, invasive edges, and immune niches.
  • Identifies novel prognostic and predictive biomarkers through integrated multiomics.

Conclusions:

  • Spatial transcriptomics is transforming cancer research and biomarker discovery.
  • Challenges in resolution, data processing, and standardization need addressing.
  • Emerging trends like 3D profiling and AI will drive precision oncology and improve patient outcomes.