{"title":"Challenges and Opportunities in the Clinical Translation of High-Resolution Spatial Transcriptomics.","authors":"Tancredi Massimo Pentimalli, Nikos Karaiskos, Nikolaus Rajewsky","doi":"10.1146/annurev-pathmechdis-111523-023417","DOIUrl":null,"url":null,"abstract":"<p><p>Pathology has always been fueled by technological advances. Histology powered the study of tissue architecture at single-cell resolution and remains a cornerstone of clinical pathology today. In the last decade, next-generation sequencing has become informative for the targeted treatment of many diseases, demonstrating the importance of genome-scale molecular information for personalized medicine. Today, revolutionary developments in spatial transcriptomics technologies digitalize gene expression at subcellular resolution in intact tissue sections, enabling the computational analysis of cell types, cellular phenotypes, and cell-cell communication in routinely collected and archival clinical samples. Here we review how such molecular microscopes work, highlight their potential to identify disease mechanisms and guide personalized therapies, and provide guidance for clinical study design. Finally, we discuss remaining challenges to the swift translation of high-resolution spatial transcriptomics technologies and how integration of multimodal readouts and deep learning approaches is bringing us closer to a holistic understanding of tissue biology and pathology.</p>","PeriodicalId":50753,"journal":{"name":"Annual Review of Pathology-Mechanisms of Disease","volume":null,"pages":null},"PeriodicalIF":28.4000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Review of Pathology-Mechanisms of Disease","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1146/annurev-pathmechdis-111523-023417","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PATHOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Pathology has always been fueled by technological advances. Histology powered the study of tissue architecture at single-cell resolution and remains a cornerstone of clinical pathology today. In the last decade, next-generation sequencing has become informative for the targeted treatment of many diseases, demonstrating the importance of genome-scale molecular information for personalized medicine. Today, revolutionary developments in spatial transcriptomics technologies digitalize gene expression at subcellular resolution in intact tissue sections, enabling the computational analysis of cell types, cellular phenotypes, and cell-cell communication in routinely collected and archival clinical samples. Here we review how such molecular microscopes work, highlight their potential to identify disease mechanisms and guide personalized therapies, and provide guidance for clinical study design. Finally, we discuss remaining challenges to the swift translation of high-resolution spatial transcriptomics technologies and how integration of multimodal readouts and deep learning approaches is bringing us closer to a holistic understanding of tissue biology and pathology.
期刊介绍:
The Annual Review of Pathology: Mechanisms of Disease is a scholarly journal that has been published since 2006. Its primary focus is to provide a comprehensive overview of recent advancements in our knowledge of the causes and development of significant human diseases. The journal places particular emphasis on exploring the current and evolving concepts of disease pathogenesis, as well as the molecular genetic and morphological changes associated with various diseases. Additionally, the journal addresses the clinical significance of these findings.
In order to increase accessibility and promote the broad dissemination of research, the current volume of the journal has transitioned from a gated subscription model to an open access format. This change has been made possible through the Annual Reviews' Subscribe to Open program, which allows all articles published in this volume to be freely accessible to readers. As part of this transition, all articles in the journal are published under a Creative Commons Attribution (CC BY) license, which encourages open sharing and use of the research.