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Novel insights from spatial transcriptome analysis in solid tumors

Since its first application in 2016, spatial transcriptomics has become a rapidly evolving technology in recent years. Spatial transcriptomics enables transcriptomic data to be acquired from intact tissue sections and provides spatial distribution information and remedies the disadvantage of single-...

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Detalles Bibliográficos
Autores principales: Du, Jun, An, Zhi-Jie, Huang, Zou-Fang, Yang, Yu-Chen, Zhang, Ming-Hui, Fu, Xue-Hang, Shi, Wei-Yang, Hou, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10539699/
https://www.ncbi.nlm.nih.gov/pubmed/37781515
http://dx.doi.org/10.7150/ijbs.83098
Descripción
Sumario:Since its first application in 2016, spatial transcriptomics has become a rapidly evolving technology in recent years. Spatial transcriptomics enables transcriptomic data to be acquired from intact tissue sections and provides spatial distribution information and remedies the disadvantage of single-cell RNA sequencing (scRNA-seq), whose data lack spatially resolved information. Presently, spatial transcriptomics has been widely applied to various tissue types, especially for the study of tumor heterogeneity. In this review, we provide a summary of the research progress in utilizing spatial transcriptomics to investigate tumor heterogeneity and the microenvironment with a focus on solid tumors. We summarize the research breakthroughs in various fields and perspectives due to the application of spatial transcriptomics, including cell clustering and interaction, cellular metabolism, gene expression, immune cell programs and combination with other techniques. As a combination of multiple transcriptomics, single-cell multiomics shows its superiority and validity in single-cell analysis. We also discuss the application prospect of single-cell multiomics, and we believe that with the progress of data integration from various transcriptomics, a multilayered subcellular landscape will be revealed.