Spatial transcriptomics of tumor microenvironment in formalin-fixed paraffin-embedded breast cancer

Romanens, Lou; Chaskar, Prasad; Tille, Jean-Christophe; Ryser, Stephan; Liaudet, Nicolas; Hu-Heimgartner, Ketty; Heimgartner, Killian; Kaya, Gürkan; Tsantoulis, Petros; Labidi-Galy, Sana Intidhar

doi:10.1101/2020.01.31.928143

Cited by 7 publications

(4 citation statements)

References 50 publications

(38 reference statements)

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“…Given these limitations, researchers and developers have focused efforts on finding a one-stop solution that offers both the breadth and depth of sequencing coverage of biomarkers as well as adequate resolution and spatial information. Spatial transcriptomics (ST) holds great promise in this area, providing researchers with the ability to identify novel biomarkers and insight into the dynamic interplay between tumour cells, adipose tissue, vessels, tertiary lymphoid structures, and the stroma in the TME [ 25 ]. In this review, we outline the features of the various technologies that are available for such transcriptional spatial profiling in cancer tissues and the potential and promise they hold in the advancement of cancer immunotherapy.…”

Section: Introductionmentioning

confidence: 99%

Transcriptional Spatial Profiling of Cancer Tissues in the Era of Immunotherapy: The Potential and Promise

Nerurkar

Goh

Cheung

et al. 2020

Cancers

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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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Section: Introductionmentioning

confidence: 99%

Transcriptional Spatial Profiling of Cancer Tissues in the Era of Immunotherapy: The Potential and Promise

Nerurkar

Goh

Cheung

et al. 2020

Cancers

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“…Using laser capture microdissection (LCM), Romanens et al . extracted tissues related to breast cancer that were preserved in FFPE blocks using an optimized protocol for hematoxylin and eosin (H&E) staining with the best parameters for dyes, incubation time, the thickness of tissue, and surface area for microdissection ( 20 ). In the study, Romanens and colleagues spatially characterized tumor and immune cells in triple-negative breast cancer.…”

Section: Resultsmentioning

confidence: 99%

Recent advances in spatially resolved transcriptomics: challenges and opportunities

Lee

Yoo

Choi

2022

BMB Rep

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Single-cell RNA sequencing (scRNA-seq) has greatly advanced our understanding of cellular heterogeneity by profiling individual cell transcriptomes. However, cell dissociation from the tissue structure causes a loss of spatial information, which hinders the identification of intercellular communication networks and global transcriptional patterns present in the tissue architecture. To overcome this limitation, novel transcriptomic platforms that preserve spatial information have been actively developed. Significant achievements in imaging technologies have enabled in situ targeted transcriptomic profiling in single cells at single-molecule resolution. In addition, technologies based on mRNA capture followed by sequencing have made possible profiling of the genome-wide transcriptome at the 55-100 μm resolution. Unfortunately, neither imaging-based technology nor capture-based method elucidates a complete picture of the spatial transcriptome in a tissue. Therefore, addressing specific biological questions requires balancing experimental throughput and spatial resolution, mandating the efforts to develop computational algorithms that are pivotal to circumvent technology-specific limitations. In this review, we focus on the current state-of-the-art spatially resolved transcriptomic technologies, describe their applications in a variety of biological domains, and explore recent discoveries demonstrating their enormous potential in biomedical research. We further highlight novel integrative computational methodologies with other data modalities that provide a framework to derive biological insight into heterogeneous and complex tissue organization.

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“…In particular, the inflammatory fibroblasts and endothelial cells are co‐localised in this region (Figure 2B). As for immune cells, their distribution is closely linked with the compartment zones 23,121 . Combined scRNA‐seq and ST revealed the pancreatic cancer subtype‐specific compartment reprogramming in response to neoadjuvant chemotherapy 7 .…”

Section: Spatial Omics In Cancer Research: From Bench To Bedsidementioning

confidence: 99%

Spatial omics: Navigating to the golden era of cancer research

Cheng

Wang

et al. 2022

Clinical & Translational Med

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The idea that tumour microenvironment (TME) is organised in a spatial manner will not surprise many cancer biologists; however, systematically capturing spatial architecture of TME is still not possible until recent decade. The past five years have witnessed a boom in the research of high‐throughput spatial techniques and algorithms to delineate TME at an unprecedented level. Here, we review the technological progress of spatial omics and how advanced computation methods boost multi‐modal spatial data analysis. Then, we discussed the potential clinical translations of spatial omics research in precision oncology, and proposed a transfer of spatial ecological principles to cancer biology in spatial data interpretation. So far, spatial omics is placing us in the golden age of spatial cancer research. Further development and application of spatial omics may lead to a comprehensive decoding of the TME ecosystem and bring the current spatiotemporal molecular medical research into an entirely new paradigm.

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Spatial transcriptomics of tumor microenvironment in formalin-fixed paraffin-embedded breast cancer

Cited by 7 publications

References 50 publications

Transcriptional Spatial Profiling of Cancer Tissues in the Era of Immunotherapy: The Potential and Promise

Transcriptional Spatial Profiling of Cancer Tissues in the Era of Immunotherapy: The Potential and Promise

Recent advances in spatially resolved transcriptomics: challenges and opportunities

Spatial omics: Navigating to the golden era of cancer research

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