Exploring GeoMx DSP Applications in Cancer Research

Introduction

GeoMx® Digital Spatial Profiler (DSP) is one of the leading revolutionary technologies that elevate spatial biology to new heights and is a core force in driving the forefront of spatial multi-omics research and clinical translation practices. It meets the research and application needs at different stages across various fields such as oncology, tumor immunology, infectious diseases, autoimmune diseases, neuroscience, developmental biology, and drug development. Today, we will explore the applications of GeoMx DSP spatial multi-omics in cancer research through four high-impact articles.

Determining Inter- and Intra-Tumor Heterogeneity of Metastatic Prostate Cancer Through Digital Spatial Gene Expression Profiling

Inter- and intra-tumor heterogeneity of metastatic prostate cancer determined by digital spatial gene expression profiling

Published in: Nature Communications

Impact Factor: 14.919

Published by: University of Washington

Research Background

Localized prostate cancer (PC) exhibits significant inter- and intra-tumor heterogeneity in terms of phenotype and molecular composition. While the application of technologies such as laser-assisted microdissection, proteomics, single-cell sequencing, and spatial transcriptomics has depicted the molecular diversity of PC, there is still a lack of understanding regarding the intra- and inter-tumor heterogeneity of PC metastatic lesions. In this study, the authors used digital spatial analysis (DSP) to investigate the inter- and intra-tumor variations in gene expression for the quantification and analysis of mRNA and proteins in PC metastatic lesions. Additionally, the authors employed DSP to classify tumor phenotypes based on gene expression programs that characterize androgen receptor (AR) activity, neuroendocrine (NE) differentiation, FGFR/MEK signaling, as well as the composition of immune cells and immune-regulating cytokines and chemokines.

Research Approach

Exploring GeoMx DSP Applications in Cancer Research

Research Conclusion

In this paper, the authors used DSP technology to quantify the transcript and protein abundance in different spatial regions of metastatic prostate cancer (mPC). By assessing multiple discrete regions of several metastatic lesions, the authors found a high level of inter-patient homogeneity in tumor phenotype. However, there were also significant exceptions, including tumors composed of regions with high and low androgen receptor (AR) and neuroendocrine activity. While the vast majority of metastatic lesions examined showed no significant inflammatory infiltration and lacked PD1, PD-L1, and CTLA4, the B7-H3/CD276 immune checkpoint protein was highly expressed, particularly in mPC with high AR activity. The authors’ results demonstrate the utility of DSP in accurately classifying tumor phenotypes, assessing tumor heterogeneity, and identifying tumor biology involving metastatic immune composition.

Single-Cell Atlas of Lineage States, Tumor Microenvironment, and Subtype-Specific Expression Programs in Gastric Cancer

Single-cell atlas of lineage states, tumor microenvironment, and subtype-specific expression programs in gastric cancer

Published in: Cancer Discovery

Impact Factor: 39.397

Published by: National University of Singapore, Yong Loo Lin School of Medicine

Research Background

Gastric cancer is one of the most prevalent and deadly cancers worldwide, often exhibiting significant histological, transcriptomic, and (epigenomic) differences among different patients, which indicates inter-patient heterogeneity. Previous studies using bulk RNA sequencing have identified personalized expression profiles for each gastric cancer patient, but the understanding of the mechanisms by which common cell types in the tumor microenvironment (such as immune cells, fibroblasts, and blood vessels) drive gastric cancer phenotypes and clinical variations is still insufficient. This paper combines single-cell transcriptomics and DSP spatial transcriptomics to further explore the single-cell landscape of the gastric cancer tumor microenvironment.

Research Approach

Research Conclusion

This paper analyzes gastric malignancies at single-cell resolution and identifies an increased proportion of plasma cells as a new feature of diffuse-type tumors. The authors also discovered different cancer-associated fibroblast subtypes, with the high INHBA-FAP cell population serving as a predictor of poor clinical prognosis. The authors’ findings emphasize the potential origins of dysregulated cell states within the gastric tumor ecosystem.

Nongenetic Evolution Drives Lung Adenocarcinoma Spatial Heterogeneity and Progression

Nongenetic evolution drives lung adenocarcinoma spatial heterogeneity and progression

Published in: Cancer Discovery

Impact Factor: 39.397

Published by: University of Lausanne, Switzerland

Research Background

Lung adenocarcinoma is the most common subtype of lung cancer, and in lung adenocarcinoma, disease progression and prognosis are associated with the emergence of morphologically diverse tumor regions known as histological patterns. However, the relationship between molecular and histological features remains unknown. To investigate the molecular characteristics of histological patterns in lung adenocarcinoma and how they shape the tumor microenvironment, the authors performed multi-region sampling of primary human lung adenocarcinoma, employing multi-omics studies including exome sequencing, transcriptome sequencing, methylation sequencing, single-cell sequencing, and DSP proteomics on over 2000 lung adenocarcinoma samples to identify carcinogenic processes and spatial features supporting nongenetic evolution as drivers of lung adenocarcinoma heterogeneity and progression.

Research Approach

Exploring GeoMx DSP Applications in Cancer Research

Research Conclusion

The research results provide a detailed molecular map of intra-tumoral spatial heterogeneity in lung adenocarcinoma, tracing the nongenetic pathways of cancer evolution. The authors classified lung adenocarcinoma based on the prevalence of histological patterns; however, individual tumors exhibited multiple patterns with unknown molecular features. The authors described the nongenetic mechanisms of intra-tumoral patterns and molecular markers predicting patient prognosis. Intra-tumoral patterns determine different immune microenvironments, providing a basis for research in the context of current immunotherapy.

Opposing Immune and Genetic Mechanisms Shape Oncogenic Programs in Synovial Sarcoma

Opposing immune and genetic mechanisms shape oncogenic programs in synovial sarcoma

Published in: Nature Medicine

Impact Factor: 53.22

Published by: Broad Institute

Research Background

Synovial sarcoma (SyS) is an aggressive mesenchymal tumor that uniformly expresses several immunogenic cancer/testis antigens that can be recognized by circulating T cells in the peripheral blood of SyS patients, yet T cell infiltration in the tumor remains very low, indicating the presence of unknown immune evasion mechanisms in synovial sarcoma. Therefore, in this paper, the authors combined single-cell transcriptome sequencing and DSP spatial transcriptomics to study cancer-immune interactions in SyS.

Research Approach

Research Conclusion

The authors identified a malignant subpopulation through single-cell sequencing that marked an immune-deprived niche in situ and predicted poor prognosis in two independent cohorts. Functional analyses indicated that this malignant cell state is controlled by the SS18-SSX fusion, suppressed by cytokines secreted by macrophages and T cells, and can be synergistically targeted with combinations of HDAC and CDK4/6 inhibitors. This drug combination enhances the immunogenicity of malignant cells in SyS models and leads to T cell reactivity and T cell-mediated cytotoxicity. This study provides a blueprint for researching the heterogeneity of fusion-driven malignancies and demonstrates the interplay between immune evasion and oncogenic processes, which can be targeted together in SyS and other malignancies.

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