Application of Spatial Transcriptomics in Digestive System Tumors

Abstract

In the field of digestive system tumor research, spatial transcriptomics technologies are used to delve into the spatial structure and the spatial heterogeneity of tumors and to analyze the tumor microenvironment (TME) and the inter-cellular interactions within it by revealing gene expression in tumors. These technologies are also instrumental in the diagnosis, prognosis, and treatment of digestive system tumors. This review provides a concise introduction to spatial transcriptomics and summarizes recent advances, application prospects, and technical challenges of these technologies in digestive system tumor research. This review also discusses the importance of combining spatial transcriptomics with single-cell RNA sequencing (scRNA-seq), artificial intelligence, and machine learning in digestive system cancer research.

Keywords: digestive system tumors; inter-cellular interaction; spatial heterogeneity; spatial transcriptomics; tumor microenvironment.

Figure 1

Schematic diagram of three different spatial transcriptomics methods. (A) In situ hybridization methods sequence the transcripts within the tissue after rolling circle amplification (RCA), while in situ sequencing methods identify the transcripts by hybridizing with fluorescent probes. (B) In sequencing-based methods, transcripts within the tissue are captured by poly(dT) on spatially barcoded microarray slides, after which transcripts are reverse transcribed and sequenced by next-generation sequencing (NGS).

Figure 2

Considerations for selecting a suitable spatial transcriptomics method. When selecting a suitable spatial transcriptomics method, the experiment objective, the capture efficiency and spatial resolution, the sample tissue area, the quality of mRNAs, and the sensitivity and detection efficiency should be taken into consideration.