Tumor Functional Heterogeneity Unraveled by scRNA-seq Technologies

González-Silva, Laura; Quevedo, Laura; Varela, Ignacio

doi:10.1016/j.trecan.2021.02.001

Cited by 36 publications

(35 citation statements)

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“…1f-g ). In recent years, the advent of single-cell transcriptomics approaches has identified a substantial degree of transcriptomic heterogeneity in most if not all types of cancer 47 . Tumor heterogeneity often increases as tumors progress, and may be a predictor of poor clinical outcomes as it is believed to be a major contributor to drug resistance 48 .…”

Section: Discussionmentioning

confidence: 99%

Spatially resolved transcriptomics reveals the architecture of the tumor/microenvironment interface

Hunter

Moncada²,

Weiss

et al. 2020

Preprint

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During tumor progression, cancer cells come into contact with new cell types in the microenvironment, but it is unclear how tumor cells adapt to new environments. Here, we integrate spatial transcriptomics and scRNA-seq to characterize tumor/microenvironment interactions during the initial steps of invasion. Using a zebrafish model of melanoma, we identify a unique "interface" cell state at the tumor/microenvironment boundary. This interface is composed of specialized tumor and microenvironment cells that upregulate a common set of cilia genes, and cilia proteins are enriched only where the tumor contacts the microenvironment. Cilia gene expression is regulated by ETS-family transcription factors, which normally act to suppress cilia genes outside of the interface. An ETS-driven interface is conserved across ten patient samples, suggesting it is a conserved feature of human melanoma. Our results demonstrate the power of spatial transcriptomic approaches in uncovering mechanisms that allow tumors to invade into the microenvironment.

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Section: Discussionmentioning

confidence: 99%

Spatially resolved transcriptomics reveals the architecture of the tumor/microenvironment interface

Hunter

Moncada²,

Weiss

et al. 2020

Preprint

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“…scRNA-seq data has also been used in seeking molecular and cellular basis of TME. The distinct transcriptional signatures of malignant cells with different genomic backgrounds help classify tumor subtypes and the design of targeted treatments in a higher resolution ( 120 ). Comparing the ecosystems of primary and early-relapse HCC tissues, Sun et al.…”

Section: Application Of Single-cell Omics In Tumor Immunologymentioning

confidence: 99%

Applications of Single-Cell Omics in Tumor Immunology

Liu

Zhang

et al. 2021

Front. Immunol.

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The tumor microenvironment (TME) is an ecosystem that contains various cell types, including cancer cells, immune cells, stromal cells, and many others. In the TME, cancer cells aggressively proliferate, evolve, transmigrate to the circulation system and other organs, and frequently communicate with adjacent immune cells to suppress local tumor immunity. It is essential to delineate this ecosystem’s complex cellular compositions and their dynamic intercellular interactions to understand cancer biology and tumor immunology and to benefit tumor immunotherapy. But technically, this is extremely challenging due to the high complexities of the TME. The rapid developments of single-cell techniques provide us powerful means to systemically profile the multiple omics status of the TME at a single-cell resolution, shedding light on the pathogenic mechanisms of cancers and dysfunctions of tumor immunity in an unprecedently resolution. Furthermore, more advanced techniques have been developed to simultaneously characterize multi-omics and even spatial information at the single-cell level, helping us reveal the phenotypes and functionalities of disease-specific cell populations more comprehensively. Meanwhile, the connections between single-cell data and clinical characteristics are also intensively interrogated to achieve better clinical diagnosis and prognosis. In this review, we summarize recent progress in single-cell techniques, discuss their technical advantages, limitations, and applications, particularly in tumor biology and immunology, aiming to promote the research of cancer pathogenesis, clinically relevant cancer diagnosis, prognosis, and immunotherapy design with the help of single-cell techniques.

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“…Single-cell technologies provide opportunities to investigate whether inherent order exists in tumor samples (reviewed in (González-Silva, Quevedo, and Varela 2020; Irish, Kotecha, and Nolan 2006)). Most single-cell sequencing technologies employ microfluidics for single-cell isolation (e.g., Fluidigm-based scRNAseq) or employ droplet-based barcoding of individual cells (e.g., Drop-seq) (Macosko et al 2015).…”

Section: Introductionmentioning

confidence: 99%

“…Most single-cell sequencing technologies employ microfluidics for single-cell isolation (e.g., Fluidigm-based scRNAseq) or employ droplet-based barcoding of individual cells (e.g., Drop-seq) (Macosko et al 2015). These technologies have revealed intra-tumor heterogeneity in cancer stem cells, EMT, immune load, clonal evolution, and response to treatment (González-Silva, Quevedo, and Varela 2020; Hong et al 2019; Ireland et al 2020). Since these cells are taken from their native context, such heterogeneity can appear random while the spatial organization was over-looked.…”

Section: Introductionmentioning

confidence: 99%

Spatial epitope barcoding reveals subclonal tumor patch behaviors

Rovira-Clavé

Drainas

Jiang

et al. 2021

Preprint

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Intratumoral variability is a seminal feature of human tumors contributing to tumor progression and response to treatment. Current technologies are unsuitable to accurately track phenotypes and subclonal evolution within tumors, especially in response to genetic manipulations. Here, we developed epitope combinatorial tags (EpicTags), which we coupled to multiplexed ion beam imaging (EpicMIBI) for in situ tracking of barcodes within tissue microenvironments. Using this platform, we dissected the spatial component of cell lineages and phenotypes in a xenograft model of small-cell lung cancer. We observed emergent properties from mixed clones leading to the preferential expansion of subclonal patches for both neuroendocrine and non-neuroendocrine cancer cell states in this model. In tumors harboring a fraction of PTEN-deficient cancer cells, we uncovered a non-autonomous increase of subclonal patch size in PTEN wild-type cancer cells. EpicMIBI can facilitate in situ interrogation of cell-intrinsic and cell-extrinsic processes involved in intratumoral heterogeneity.

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Tumor Functional Heterogeneity Unraveled by scRNA-seq Technologies

Cited by 36 publications

References 0 publications

Spatially resolved transcriptomics reveals the architecture of the tumor/microenvironment interface

Spatially resolved transcriptomics reveals the architecture of the tumor/microenvironment interface

Applications of Single-Cell Omics in Tumor Immunology

Spatial epitope barcoding reveals subclonal tumor patch behaviors

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