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Genomics

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...

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Updated: Jan 18, 2026

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

Spatial multi-omics technologies and applications in cancer.

¹School of Basic Medicine, Central South University, Changsha, China.

|September 11, 2025

Summary

This summary is machine-generated.

Spatial multi-omics integrates multiple genomics technologies for analyzing cells within tissues. This approach aids in understanding tumor development and personalizing cancer therapy by mapping cellular interactions and gene expression.

Keywords:

Immune Precise medicine Spatial metabolomics Spatial proteomics Spatial transcriptomics Tumor

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Last Updated: Jan 18, 2026

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Published on: July 6, 2022

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Published on: November 14, 2025

Area of Science:

Biotechnology
Genomics
Cancer Research

Background:

Spatial multi-omics combines various genomics technologies for simultaneous data acquisition from tissue sections.
This integration allows for joint analysis of cells within their native tissue microenvironment.
It offers a 3D view of tissues, facilitating the study of cell-cell interactions.

Purpose of the Study:

To review and guide the selection of appropriate spatial multi-omics techniques.
To highlight advances in spatial multi-omics for cancer research.
To elucidate the advantages and disadvantages of different spatial multi-omics approaches.

Main Methods:

Integration of multiple genomics technologies within a single platform.
Simultaneous data acquisition from parallel or identical tissue sections.
Joint analysis of cellular and molecular features in spatial context.

Main Results:

Revealed spatial cellular interactions and tumor microenvironment characteristics.
Enabled identification of tertiary lymphoid structures (TLS) and immune cell functions.
Established spatial maps and gene databases for human tumors, aiding personalized therapy.

Conclusions:

Spatial multi-omics is crucial for reconstructing tumorigenesis processes.
Advances in this technology facilitate personalized cancer diagnosis and treatment.
Future development requires enhanced spatial and temporal resolution, throughput, and sensitivity for novel discoveries.