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?:abstract
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SIMPLE SUMMARY: In recent years, immunotherapy has emerged as a pillar in the fight against cancer. However, the heterogeneity within the tumor microenvironment poses challenges to the efficacy of immunotherapy treatment strategies and may contribute to treatment resistance, progression and relapse. Hence, researchers have used transcriptional spatial profiling techniques to uncover the complex cancer immune profile while retaining critical spatial information of different cell types. This would help identify the source of tumor heterogeneity and uncover pathogenic mechanisms, potential drug targets and novel biomarkers. In this review, we discuss various approaches for transcriptional spatial profiling of cancer tissues such as in situ hybridization, digital spatial profiling and an emerging technology known as Visium Spatial Gene Expression Solution. We highlight the strengths and limitations of the different technologies and the potential and promise they hold in the advancement of cancer immunotherapy. ABSTRACT: Intratumoral heterogeneity poses a major challenge to making an accurate diagnosis and establishing personalized treatment strategies for cancer patients. Moreover, this heterogeneity might underlie treatment resistance, disease progression, and cancer relapse. For example, while immunotherapies can confer a high success rate, selective pressures coupled with dynamic evolution within a tumour can drive the emergence of drug-resistant clones that allow tumours to persist in certain patients. To improve immunotherapy efficacy, researchers have used transcriptional spatial profiling techniques to identify and subsequently block the source of tumour heterogeneity. In this review, we describe and assess the different technologies available for such profiling within a cancer tissue. We first outline two well-known approaches, in situ hybridization and digital spatial profiling. Then, we highlight the features of an emerging technology known as Visium Spatial Gene Expression Solution. Visium generates quantitative gene expression data and maps them to the tissue architecture. By retaining spatial information, we are well positioned to identify novel biomarkers and perform computational analyses that might inform on novel combinatorial immunotherapies.
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