{"title":"Cancer cell states: Lessons from ten years of single-cell RNA-sequencing of human tumors","authors":"Itay Tirosh, Mario L. Suva","doi":"10.1016/j.ccell.2024.08.005","DOIUrl":null,"url":null,"abstract":"<p>Human tumors are intricate ecosystems composed of diverse genetic clones and malignant cell states that evolve in a complex tumor micro-environment. Single-cell RNA-sequencing (scRNA-seq) provides a compelling strategy to dissect this intricate biology and has enabled a revolution in our ability to understand tumor biology over the last ten years. Here we reflect on this first decade of scRNA-seq in human tumors and highlight some of the powerful insights gleaned from these studies. We first focus on computational approaches for robustly defining cancer cell states and their diversity and highlight some of the most common patterns of gene expression <em>intra</em>-tumor heterogeneity (eITH) observed across cancer types. We then discuss ambiguities in the field in defining and naming such eITH programs. Finally, we highlight critical developments that will facilitate future research and the broader implementation of these technologies in clinical settings.</p>","PeriodicalId":9670,"journal":{"name":"Cancer Cell","volume":null,"pages":null},"PeriodicalIF":48.8000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Cell","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.ccell.2024.08.005","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Human tumors are intricate ecosystems composed of diverse genetic clones and malignant cell states that evolve in a complex tumor micro-environment. Single-cell RNA-sequencing (scRNA-seq) provides a compelling strategy to dissect this intricate biology and has enabled a revolution in our ability to understand tumor biology over the last ten years. Here we reflect on this first decade of scRNA-seq in human tumors and highlight some of the powerful insights gleaned from these studies. We first focus on computational approaches for robustly defining cancer cell states and their diversity and highlight some of the most common patterns of gene expression intra-tumor heterogeneity (eITH) observed across cancer types. We then discuss ambiguities in the field in defining and naming such eITH programs. Finally, we highlight critical developments that will facilitate future research and the broader implementation of these technologies in clinical settings.
期刊介绍:
Cancer Cell is a journal that focuses on promoting major advances in cancer research and oncology. The primary criteria for considering manuscripts are as follows:
Major advances: Manuscripts should provide significant advancements in answering important questions related to naturally occurring cancers.
Translational research: The journal welcomes translational research, which involves the application of basic scientific findings to human health and clinical practice.
Clinical investigations: Cancer Cell is interested in publishing clinical investigations that contribute to establishing new paradigms in the treatment, diagnosis, or prevention of cancers.
Insights into cancer biology: The journal values clinical investigations that provide important insights into cancer biology beyond what has been revealed by preclinical studies.
Mechanism-based proof-of-principle studies: Cancer Cell encourages the publication of mechanism-based proof-of-principle clinical studies, which demonstrate the feasibility of a specific therapeutic approach or diagnostic test.