Spatial Omics Solutions for Cancer Heterogeneity

Spatial Omics Solutions for Cancer Heterogeneity

The fact that people have not been able to overcome cancer has a lot to do with the heterogeneity of tumors. Many different genotypes or subtypes of cells can exist in the same tumor. The same tumor may show different treatment effects and prognoses in different individuals. What's more, tumor cells in the same body also have different characteristics and differences. This differentiation between cells can seriously affect the treatment effect and has been a challenge for cancer treatment.

During the growth process, tumors undergo multiple divisions and proliferation, and their daughter cells show molecular biological or genetic alterations. This results in differences in various aspects such as growth rate, invasive ability, sensitivity to drugs, and prognosis of tumors. The higher the heterogeneity, the more likely it is to be drug-resistant, the faster cancer progresses, and the worse the prognosis. But heterogeneity is a universal characteristic of cancer. So understanding the origin and regulatory mechanisms behind heterogeneity can provide key insights to help improve cancer diagnosis and treatment.

How we can reveal cancer heterogeneity with the help of spatial omics

To address this universal problem of malignancy, we must first gain insight into the tumor, including what heterogeneity looks like within the tumor and how different cancers are alike. CD Genomics' solution with the help of spatial multi-omics technology can provide rich information about the tumor genome. Systematically mapping the spatial composition of different tumor cells reconstructs and maps tumor heterogeneity and its tumor progression patterns.

Overview of analysis using SPATA and stLEARN.Figure 1. Overview of analysis using SPATA and stLEARN. (Nagasawa, S., et al., 2021)

What our customers can get

  • Spatial transcriptome sequencing and single-cell sequencing can be performed to construct single-cell maps and perform cell-type annotation.
  • Access to information on single-nucleotide variants (SNVs), insertions or deletions (Indels), copy number alterations (CNAs), structural variants (SVs), tumor purity subclonal drivers, subclonal selection, mutation signature information.
  • Allows microdissection-based, in situ hybridization (ISH)-based, in situ sequencing (ISS)-based, and in situ capture (ISC)-based spatial transcriptome (ST) analyses.
  • Allows detection of the behavior of small cells and the presence of heterogeneous cell populations within them, allowing for cancer cell subpopulation analysis.

Sample requirements: You can start with frozen samples. Broaden the selection of samples for analysis.

Technical advantages

  • Analyze cells with more parameters in a quantitative manner.
  • Can handle data analysis from QC to enrichment analysis and provide detailed gene expression profiles.
  • Identifies key gene expression changes in the process of drug resistance acquisition.
  • Multiple types of stromal cells can be characterized.

Our efforts in the field of cancer heterogeneity

Tumor heterogeneity is a complex process in which different clones and subclones are affected by multiple factors in the temporal and spatial dimensions. On a larger scale, solutions including single-cell and spatial multi-omics offered by CD Genomics can be applied to the heterogeneity analysis of multiple cancer cells. To help our customers to more deeply elucidate intra-tumor heterogeneity and tumor evolutionary history, providing a better tool for designing personalized therapeutic regimens for cancer patients.


  1. Nagasawa, S., et al., (2021). "Single-cell and spatial analyses of cancer cells: toward elucidating the molecular mechanisms of clonal evolution and drug resistance acquisition." Inflammation and Regeneration, 41, 22.
For research use only, not intended for any clinical use.

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