Zai Lab

Hua Gong

Cancer research has benefited tremendously from the recent technological advancement of single-cell spatial assessment. In the past decade, scientists have developed multiple single-cell technologies such as single-cell RNA-sequencing (scRNA-seq), single-cell ATAC-seq (scATAC-seq), single-cell DNA methylome, and single-cell proteomics (SCP). These technologies have allowed us to make remarkable advances in revealing the mechanisms of human diseases. Excitingly, spatial omics technologies with increasingly higher resolution have been developed to combine single-cell techniques with next-generation sequencing or multiplexed imaging, which enables us to examine spatial distribution of RNA and proteins within tissues. Here, we discuss the cutting-edge spatial omics technologies and their applications in oncology drug development.

Spatial techniques have been combined with a wide range of single-cell omics technologies such as transcriptomics, proteomics and genomics. The two most widely used spatial transcriptomics platforms include 10X Genomics’ Visium and NanoString’s GeoMx Digital Spatial Profiler (DSP). Both Visum and GeoMx DSP employ sequencing-based technologies to profile whole transcriptome RNA expression, although they use different techniques to retain spatial information. Currently, spatial proteomics such as MIBI-TOF and CODEX multiplexed imaging platforms can be employed to examine dozens of proteins via antibody-based methods. Other spatial omics technologies such as spatial assays for chromatin accessibility and spatial genomics based on DNA seqFISH are also actively explored in research settings, although they are not commercially available yet. Overall, these spatial omics technologies will enable us to study complex biological systems and accelerate the development of new therapies for oncology.

Application of spatial omics technologies in studying the pathogenesis of cancers

Examination of the spatial localization of any given cell, relative to its neighboring cells or structures, can profoundly impact our capacity to understand the pathogenesis of cancers, especially interrogating the spatial immune microenvironment in human cancers. In glioblastomas, exhausted T cells were recently demonstrated to be preferentially spatially located within mesenchymal-like tumor regions.  A subset of HMOX1⁺ myeloid cells, located at the tumor microenvironment interface, release interleukin-10 and then drive the induction of T-cell exhaustion, thereby resulting in the immunosuppressive tumor microenvironment in glioblastomas. Hence, the applications of spatial technologies in biomedical research have remarkably improved our understanding of the pathogenesis of cancers.

Application of spatial omics technologies in the discovery of novel drug targets

Spatial technologies can be a powerful tool for identifying novel drug targets for drug development. For example, spatial transcriptomics analysis demonstrated that FAP⁺ fibroblasts and SPP1⁺ macrophages are colocalized in the desmoplastic microenvironment from analysis of colorectal cancer patients’ specimens. 

The interaction of FAP⁺ fibroblasts and SPP1⁺ macrophages promotes the formation of extracellular matrix and collagen fibril organization, which serves to limit the infiltration of effector immune cells into tumor tissues. Thus, therapeutic strategies to disrupt the interaction of FAP⁺ fibroblasts with SPP1⁺ macrophages may turn out to improve immunotherapy with checkpoint inhibitors. Together, spatial technologies can play an extremely instrumental role in the discovery of novel oncology drug targets.

Application of spatial omics technologies in the discovery of predictive biomarkers for oncology drug development

Spatial technologies have also been widely used for discovering predictive biomarkers for drug development. For instance, a recent spatial proteomics study characterized the dynamic changes in the expression of 40 tumor and immune marker proteins in response to neoadjuvant HER2-targeted therapy in HER2-positive breast cancers. The results showed that CD45 and CD8 displayed the greatest increase in tumor regions after the treatment. Furthermore, the expression levels of CD45 protein serve as a robust biomarker to predict the response to neoadjuvant HER2-targeted therapy in human breast cancers.

“The applications of spatial technologies in biomedical research have remarkably improved our understanding of the pathogenesis of cancers.”

Similarly, spatial transcriptomics analysis also identified a subpopulation of stem-like CDH12-expressing epithelial cells in bladder cancer. CDH12⁺ cancer cells co-localize with CD8 T-cells and promote T-cell exhaustion through PD-L1 and PD-L2. Hence, a CDH12-expressing epithelial cell subpopulation can predict response to immunotherapy in bladder cancer. In our own experience, we have been using MIBI-TOF and CODEX multiplexed imaging platforms to explore the predictive values of NK cells in our drug development programs. These examples consistently show that spatial technologies can offer a compelling framework for designing biomarker-guided translational medicine studies and clinical trials.

In conclusion, spatial technologies are a powerful breakthrough tool that has the potential to revolutionize drug target and biomarker discovery. By providing a more detailed understanding of the spatial organization of genes and proteins within cells and tissues, spatial omics studies can identify novel drug targets and biomarkers that were previously undiscovered. As this technology continues to advance and the cost of spatial omics studies drops, it is likely that we will see an increasing number of drugs and biomarkers that are discovered using spatial technologies in oncology and other disease areas.