Spatial Omics Solutions for Pathology

Pathology is a branch of medical science concerned primarily with the causes, origins, and nature of the disease. It involves the examination of tissues, organs, and body fluids to study and diagnose disease. It bridges the gap between science and medicine, supporting everything from diagnostic tests and treatment recommendations to the use of cutting-edge genetic techniques and disease prevention.

Figure 1. Spatial mRNA expression of ACHE in human postmortem lumbar and cervical spinal cord. (Silas M., et al., 2019)

If you want to be able to visualize and study molecules, cells, and tissues in a larger structural context, then spatial omics techniques will help researchers to understand how the location and proximity of specific tissues and cell populations in disease affect and regulate whole-cell function.

Our spatial-omics solutions in pathology research

The relationship between cells and tissues is crucial for the study of normal development and pathological processes. CD Genomics can integrate high-throughput transcriptome analysis of tissue sections with morphological context with the help of spatial histology technologies (MERFISH, Slide-seq). This allows gene expression profiles to be localized back to their original locations, enabling spatial transcriptome mapping in pathological tissues. to help our clients understand how cell populations are involved in disease pathogenesis, how they respond to therapy, and how they reflect their propensity to metastasize.

• Understanding the location of possible false negatives/false positives by looking at gene expression regions.
• Draw morphological conclusions by adding gene expression dimensions.

General project flow

Sample requirements

• Freshly frozen tissue sections, OCT-embedded tissue
• Tissue sections with extracted RNA free of degradation and RIN value≥7
• No species restrictions

*Please consult staff for special materials before processing

Technical features and advantages

• Capable of detecting genes with low expression levels.
• Enables unbiased and high-throughput gene expression analysis of intact tissue sections from a wide range of samples.
• Allows characterization of cell populations without prior knowledge of cell subtypes or cellular markers.
• Allows spatial characterization of disease heterogeneity such as tumors.
• Batch measurements with high cellular coverage.

Practical application areas

• Adding gene expression information for morphological assessment.
• Identification of positive/negative regions by gene expression information.
• Identification of unknown molecular features associated with cellular/tissue morphology.
• Spatial gene expression information capture of pathological sections.

Reference

1. Silas M., et al., (2019). "Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis." SCIENCE, 364 (6435): 89-93.