Accurate and Flexible Single Cell to Spatial Transcriptome Mapping with Celloc DOI Creative Commons
Wang Yin, Xiaobin Wu, Linxi Chen

et al.

Small Science, Journal Year: 2024, Volume and Issue: unknown

Published: June 26, 2024

Accurate mapping between single‐cell RNA sequencing (scRNA‐seq) and low‐resolution spatial transcriptomics (ST) data compensates for both limited resolution of ST missing information scRNA‐seq. Celloc, a method developed this purpose, incorporates graph attention autoencoder comprehensive loss functions to facilitate flexible single cell‐to‐spot mapping. This enables either the dissection cell composition within each spot or assignment locations every in scRNA‐seq data. Celloc's performance is benchmarked on simulated data, demonstrating superior accuracy robustness compared state‐of‐the‐art methods. Evaluations real datasets suggest that Celloc can reconstruct cellular structures with various types across different tissues histological regions.

Language: Английский

New-generation technologies for spatial tissue analysis, indispensable tools for deciphering intratumor heterogeneity in the development of antibody-drug conjugates and radio-immunoconjugates for cancer treatment DOI Creative Commons
Nina Radosevic‐Robin, Myriam Kossaï,

Frédérique Penault‐Llorca

et al.

Translational Breast Cancer Research, Journal Year: 2023, Volume and Issue: 4, P. 28 - 28

Published: Oct. 1, 2023

Abstract: Technologies allowing in situ tissue molecular analysis of the "high-plex" type (>20 molecules per section) are 21st century inventions that revolutionizing our knowledge biology malignant tumors and many benign alterations. These technologies based on specific probe labeling systems for detection components [proteins, messenger RNA (mRNA)], as well detailed image analysis, combined with computational tools. We synthetically presenting such multiplex immunofluorescence (mIF), imaging mass cytometry (IMC), multiplexed ion beam (MIBI), ones not hybridizations (ISHs) using various principles. All them supported by powerful software which enable both segmentation data analysis. In context cancer treatment personalization, these can reveal areas tumor and/or cellular subpopulations responsible good or bad responses to anticancer drugs. Thus, they represent an unprecedented aid exploration intratumor heterogeneity (ITH), has already been shown be one main reasons therapeutic failure targeted treatments. The arrival antibody-drug conjugates (ADCs) radio-immunoconjugates (RICs) arsenal oncology imposes a deep ITH, where spatial emerging category biomarkers—spatial biomarkers.

Language: Английский

Citations

7
Spatial multi-omics analysis of the microenvironment in traumatic spinal cord injury: a narrative review DOI Creative Commons

Run Peng,

Liang Zhang, Yongqi Xie

et al.

Frontiers in Immunology, Journal Year: 2024, Volume and Issue: 15

Published: Aug. 29, 2024

Traumatic spinal cord injury (tSCI) is a severe to the central nervous system that categorized into primary and secondary injuries. Among them, local microenvironmental imbalance in caused by includes accumulation of cytokines chemokines, reduced angiogenesis, dysregulation cellular energy metabolism, dysfunction immune cells at site injury, which severely impedes neurological recovery from (SCI). In recent years, single-cell techniques have revealed heterogeneity multiple genomic, transcriptomic, proteomic, metabolomic levels after tSCI, further deepening our understanding mechanisms underlying tSCI. However, spatial information about tSCI microenvironment, such as cell location cell-cell interactions, lost these approaches. The application multi-omics technology can solve this problem combining data obtained immunohistochemistry multiparametric analysis reveal changes microenvironment different times SCI. review, we systematically review progress study SCI, including discuss potential future therapeutic strategies.

Language: Английский

Citations

2
Next‐generation spatial transcriptomics: unleashing the power to gear up translational oncology DOI Creative Commons
Nan Wang, Weifeng Hong,

Yixing Wu

et al.

MedComm, Journal Year: 2024, Volume and Issue: 5(10)

Published: Oct. 1, 2024

The growing advances in spatial transcriptomics (ST) stand as the new frontier bringing unprecedented influences realm of translational oncology. This has triggered systemic experimental design, analytical scope, and depth alongside with thorough bioinformatics approaches being constantly developed last few years. However, harnessing power biology streamlining an array ST tools to achieve designated research goals are fundamental require real-world experiences. We present a review by updating technical scope across different principal basis timeline manner hinting on generally adopted techniques used within community. also current progress bioinformatic propose pipelined workflow toolbox available for data exploration. With particular interests tumor microenvironment where is broadly utilized, we summarize up-to-date made via ST-based technologies narrating studies categorized into either mechanistic elucidation or biomarker profiling (translational oncology) multiple cancer types their ways deploying through ST. updated offers guidance forward-looking viewpoints endorsed many high-resolution utilized disentangle biological questions that may lead clinical significance future.

Language: Английский

Citations

2
STAB2: an updated spatio-temporal cell atlas of the human and mouse brain DOI Creative Commons
Yucheng Yang, Ziquan Gan, Jinglong Zhang

et al.

Nucleic Acids Research, Journal Year: 2023, Volume and Issue: 52(D1), P. D1033 - D1041

Published: Oct. 30, 2023

Abstract The brain is constituted of heterogeneous types neuronal and non-neuronal cells, which are organized into distinct anatomical regions, show precise regulation gene expression during development, aging function. In the current database release, STAB2 provides a systematic cellular map human mouse by integrating recently published large-scale single-cell single-nucleus RNA-sequencing datasets from diverse regions across lifespan. We applied hierarchical strategy unsupervised clustering on integrated transcriptomic to precisely annotate cell subtypes in brain. Currently, includes 71 61 different defined brain, respectively. It covers 63 subregions 15 developmental stages 38 30 generating comprehensive atlas for exploring spatiotemporal dynamics mammalian also augmented web interfaces querying visualizing specific types. freely available at https://mai.fudan.edu.cn/stab2.

Language: Английский

Citations

5
Accurate and Flexible Single Cell to Spatial Transcriptome Mapping with Celloc DOI Creative Commons
Wang Yin, Xiaobin Wu, Linxi Chen

et al.

Small Science, Journal Year: 2024, Volume and Issue: unknown

Published: June 26, 2024

Accurate mapping between single‐cell RNA sequencing (scRNA‐seq) and low‐resolution spatial transcriptomics (ST) data compensates for both limited resolution of ST missing information scRNA‐seq. Celloc, a method developed this purpose, incorporates graph attention autoencoder comprehensive loss functions to facilitate flexible single cell‐to‐spot mapping. This enables either the dissection cell composition within each spot or assignment locations every in scRNA‐seq data. Celloc's performance is benchmarked on simulated data, demonstrating superior accuracy robustness compared state‐of‐the‐art methods. Evaluations real datasets suggest that Celloc can reconstruct cellular structures with various types across different tissues histological regions.

Language: Английский

Citations

1