Methods and applications for single-cell and spatial multi-omics

Vandereyken, Katy; Sifrim, Alejandro; Thienpont, Bernard; Voet, Thierry

doi:10.1038/s41576-023-00580-2

Cited by 387 publications

(254 citation statements)

References 188 publications

(268 reference statements)

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“…PLGA nanoparticles downregulate the expression of MHC class II molecules, thereby inducing immune tolerance. The rapid development of high‐dimensional multiomics technologies [ 100 ] has enabled the in‐depth elucidation of the spatiotemporal evolution of nanoimmunology interplay at single‐cell resolution. The emerging applicability of single‐cell multiomics approaches in nanomaterial‐mediated antigen‐specific immunotherapy will advance our knowledge of this interdisciplinary field, offering new guidelines for the design of nanomaterials with increased targeted immune modulation.…”

Section: Discussionmentioning

confidence: 99%

Regulation of Antigen‐Specific Immunotherapy with Nanomaterials

Ye,

Jia,

Ren

et al. 2023

Advanced NanoBiomed Research

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Nonspecific immunotherapies often induce general immune activation or suppression. Conversely, antigen‐specific immunotherapy, which refers to dampening or augmenting adaptive immunity against a disease‐specific antigen, increases T‐cell target specificity to pathological tissues, thereby reducing side effects on the rest of the immune system. Advances in engineering strategies for nanomaterials have enabled the feasible modulation of their physicochemical features to incorporate antigens and inherently interact with innate immune cells, which remarkably amplifies the orchestration of antigen‐specific immune responses against cancer and autoimmune diseases. From this contemporary perspective, the basic principles of antigen‐specific immunotherapy are briefly introduced and we elucidate how the latest nanoengineering paradigms regulate the functions of heterogeneous subsets of immune cells, such as antigen‐presenting cells, B cells, and regulatory or cytotoxic T cells, promoting antigen‐specific immunotherapy to treat autoimmune diseases and cancer. An outlook on prospects and remaining challenges have been discussed for, translating scientific discoveries of powerful nanomaterials into medical advances in antigen‐specific immunotherapy, thus offering new treatment modalities for patients with unmet needs.

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Section: Discussionmentioning

confidence: 99%

Regulation of Antigen‐Specific Immunotherapy with Nanomaterials

Ye,

Jia,

Ren

et al. 2023

Advanced NanoBiomed Research

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“…Emerging work in this area may enable single cell‐level spatial transcriptomic profiling to mitigate this challenge in the near future, though these strategies often have trade‐offs between the number of genes that can be examined and the number of cells that can be profiled in the tissue. [ 178–180 ]…”

Section: Elucidating Microenvironmental and Tumor Cell Heterogeneity ...mentioning

confidence: 99%

Exploring New Dimensions of Tumor Heterogeneity: The Application of Single Cell Analysis to Organoid‐Based 3D In Vitro Models

Landon‐Brace,

Li,

McGuigan

2023

Adv Healthcare Materials

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Modelling the heterogeneity of the tumor microenvironment (TME) in vitro is essential to investigating fundamental cancer biology and developing novel treatment strategies that holistically address the factors affecting tumor progression and therapeutic response. Thus, the development of new tools for both in vitro modelling, such as patient‐derived organoids (PDOs) and complex 3D in vitro models, and single cell omics analysis, such as single‐cell RNA‐sequencing, represents a new frontier for investigating tumor heterogeneity. Specifically, the integration of PDO‐based 3D in vitro models and single cell analysis offers a unique opportunity to explore the intersecting effects of interpatient, microenvironmental, and tumor cell heterogeneity on cell phenotypes in the TME. In this review, we discuss the current use of PDOs in complex 3D in vitro models of the TME and highlight emerging directions in the development of these models. Next, we examine work that has successfully applied single cell analysis to PDO‐based models and identify important experimental considerations for this approach. Finally, we highlight open questions that may be amenable to exploration using the integration of PDO‐based models and single cell analysis. Ultimately, such investigations may facilitate the identification of novel therapeutic targets for cancer that address the significant influence of tumor‐TME interactions.This article is protected by copyright. All rights reserved

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“…Multiple cutting-edge ST technologies have been commercialized, varying significantly in aspects such as resolution and throughput (Larsson, Frisén and Lundeberg 2021; Moses and Pachter 2022; Williams et al . 2022; Vandereyken et al . 2023).…”

Section: Introductionmentioning

confidence: 99%

Uncover spatially informed shared variations for single-cell spatial transcriptomics with STew

Guo,

Vargas,

Fritz

et al. 2023

Preprint

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Motivation: The recent spatial transcriptomics (ST) technologies have enabled characterization of gene expression patterns and spatial information, advancing our understanding of cell lineages within diseased tissues. Several analytical approaches have been proposed for ST data, but effectively utilizing spatial information to unveil the shared variation with gene expression remains a challenge. Results: We introduce STew, a Spatial Transcriptomic multi-viEW representative learning method, to jointly analyze spatial information and gene expression in a scalable manner, followed by a data-driven statistical framework to measure the goodness of model fit. Through benchmarking using Human DLPFC data with true manual annotations, STew achieved superior performance in both clustering accuracy and continuity of identified spatial domains compared with other methods. STew is also robust to generate consistent results insensitive to model parameters, including sparsity constraints. We next applied STew to various ST data acquired from 10x Visium and Slide-seqV2, encompassing samples from both mouse and human brain, which revealed spatially informed cell type clusters. We further identified a pro-inflammatory fibroblast spatial niche using ST data from psoriatic skins. Hence, STew is a generalized method to identify both spatially informed clusters and disease-relevant niches in complex tissues. Availability: Source code and the R software tool STew are available from github.com/fanzhanglab/STew.

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Methods and applications for single-cell and spatial multi-omics

Cited by 387 publications

References 188 publications

Regulation of Antigen‐Specific Immunotherapy with Nanomaterials

Regulation of Antigen‐Specific Immunotherapy with Nanomaterials

Exploring New Dimensions of Tumor Heterogeneity: The Application of Single Cell Analysis to Organoid‐Based 3D In Vitro Models

Uncover spatially informed shared variations for single-cell spatial transcriptomics with STew

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