New Technology for Mapping the Tumor Ecosystem Can Improve Cancer Research

Spatially resolved transcriptomics (SRT)technology can be used to promote individualized treatment and identify therapeutic targets for patients with cancer, according to a systemic review published in Advanced Science. SRT technology is able to map tumor cells’ distribution in space, provide information on the tumor’s relationship to the surrounding microenvironment, and find its gene expression.

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“This can help us to resolve the spatial structure of tumor microenvironment (TME) in more dimensions, which significantly improves our understanding of cell-cell interactions and spatial effects in the TME,” study authors wrote.

The systematic review addresses how SRT technology, represented by single cell RNA sequencing (scRNA-seq) and largely based on next-generation sequencing (NGS) technology, can show more about the relationship between tumor cell function, spacing, and its surrounding microenvironment.

SRT Technology

There are 2 classifications of SRT: The first is imaging-based methods. Imaging-based SRT technology includes in situ hybridization (ISH) and in situ sequencing (ISS), which can capture in situ images of RNA molecules to map their spatial representation, but they are limited by their target ranges, field of view, and sensitivity.

According to the study authors, NGS is the next phase of SRT technology. NGS-based technology sequences copy DNA using spatial barcodes, resulting in a high-resolution map of the tumor location within a microenvironment. With this technique, investigators can also map the tumor cell genome to assess its transcript source, and it is not limited by direct visualization, unlike imaging-based methods.

The applications for SRT technology are numerous, the study authors note. Foremost, it can differentiate normal cells from tumor cells to improve understanding about different tumor structures, compositions, and replication patterns. Moreover, NGS-based SRT technology can map a tumor’s entire transcriptional landscape to identify tumor subtypes and metastasis-promoting genes. All this data, in effect, can promote earlier and more effective cancer diagnosis, more effective treatment recommendations and options, and strategies to prevent metastasis.

SRT can be used to locate stromal cells that promote tumor cell growth, multiplication, and metastasis. In previous studies, investigators used SRT to map the spatial relationship between certain types of stromal cells and tumor cells, which allowed them to identify how location is linked to its growth-promoting activity. So, on a larger scale, stromal cells could be an effective drug target.

SRT technology can also map the spatial distribution of immune cells in the TME. This is important because different immune cells populate different tumor types and have different levels of anti-tumor activity within the microenvironment. As a result, not every tumor is likely to respond to the same type of immunotherapy—understanding this can lead to increased use of effective and heterogenized therapies.

In addition, SRT shows that immune cells in the microenvironment are also influenced by stromal cells, which leads to immunosuppression. Investigators can broaden their understanding of spatial interactions between immune cells and stromal cells with SRT and potentially identify new drug target opportunities.

Finally, the technology could uncover specific spatial structures in the TME, including the tertiary lymphoid structure (TLS). This cellular aggregate is common in many cancer types, and it functions by promoting immune cells to enter a tumor site and have an antitumor response. Since SRT can map its distribution in space and gene set expression, investigators can use TLS to discover new targeted tumor treatments.

Conclusion

SRT technology can provide a host of services to holistically benefit patients and research, from tracking tumor cell progression to understanding its distribution, genome, and cell interactions, as well as the potential of TLS in the tumor microenvironment, according to the study authors.

Furthermore, a larger number of studies are pairing SRT technology with spatial-omics analyses to understand how tumor cell types, interactions, distribution, and spatial structures can be used for cancer research. This research is also highlighting the importance of individualized treatment based on TME and other heterogenous factors.

Study authors conclude, “a spatial multi-omics strategy centered on SRT technology will benefit clinical practice and improve the prognosis for cancer patients.”

Reference

Wang Q, Zhi Y, Zi M, et al. Spatially Resolved Transcriptomics Technology Facilitates Cancer Research. Adv. Sci. 2023, 2302558. DOI: 10.1002/advs.202302558