Schaff Dylan L, Fasse Aria J, White Phoebe E, Vander Velde Robert J, Shaffer Sydney M
Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19146, USA.
Department of Chemistry, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19146, USA; Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA.
Cell Syst. 2024 Mar 20;15(3):213-226.e9. doi: 10.1016/j.cels.2024.01.011. Epub 2024 Feb 23.
Cancer cells exhibit dramatic differences in gene expression at the single-cell level, which can predict whether they become resistant to treatment. Treatment perpetuates this heterogeneity, resulting in a diversity of cell states among resistant clones. However, it remains unclear whether these differences lead to distinct responses when another treatment is applied or the same treatment is continued. In this study, we combined single-cell RNA sequencing with barcoding to track resistant clones through prolonged and sequential treatments. We found that cells within the same clone have similar gene expression states after multiple rounds of treatment. Moreover, we demonstrated that individual clones have distinct and differing fates, including growth, survival, or death, when subjected to a second treatment or when the first treatment is continued. By identifying gene expression states that predict clone survival, this work provides a foundation for selecting optimal therapies that target the most aggressive resistant clones within a tumor. A record of this paper's transparent peer review process is included in the supplemental information.
癌细胞在单细胞水平上表现出显著的基因表达差异,这可以预测它们是否会对治疗产生耐药性。治疗会使这种异质性持续存在,导致耐药克隆之间出现多种细胞状态。然而,当应用另一种治疗方法或继续使用相同的治疗方法时,这些差异是否会导致不同的反应仍不清楚。在这项研究中,我们将单细胞RNA测序与条形码技术相结合,以跟踪经过长期和连续治疗的耐药克隆。我们发现,同一克隆内的细胞在多轮治疗后具有相似的基因表达状态。此外,我们还证明,当接受第二种治疗或继续第一种治疗时,单个克隆具有不同的命运,包括生长、存活或死亡。通过识别预测克隆存活的基因表达状态,这项工作为选择针对肿瘤内最具侵袭性的耐药克隆的最佳治疗方法提供了基础。本文透明的同行评审过程记录包含在补充信息中。