Cancer cell states: Lessons from ten years of single-cell RNA-sequencing of human tumors

Itay Tirosh*, Mario L. Suva*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

38 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1497-1506
Number of pages10
JournalCancer Cell
Volume42
Issue number9
Early online date29 Aug 2024
DOIs
Publication statusPublished - 9 Sept 2024

Funding

This work was supported by an ERC (European Research Council) consolidator grant 101044318 (I.T.), the MGH Research Scholars Award (M.L.S.), and grant from the Mark Foundation Emerging Leader Award (M.L.S.). I.T. is the incumbent of the Dr. Celia Zwillenberg-Fridman and Dr. Lutz Zwillenberg Career Development Chair, and is supported by the Zuckerman STEM Leadership Program. We thank members of the Tirosh and Suva labs for helpful discussions. Publisher Copyright: Copyright © 2024. Published by Elsevier Inc.

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

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