Nature Communications (Dec 2023)

Single cell multi-omics reveal intra-cell-line heterogeneity across human cancer cell lines

  • Qionghua Zhu,
  • Xin Zhao,
  • Yuanhang Zhang,
  • Yanping Li,
  • Shang Liu,
  • Jingxuan Han,
  • Zhiyuan Sun,
  • Chunqing Wang,
  • Daqi Deng,
  • Shanshan Wang,
  • Yisen Tang,
  • Yaling Huang,
  • Siyuan Jiang,
  • Chi Tian,
  • Xi Chen,
  • Yue Yuan,
  • Zeyu Li,
  • Tao Yang,
  • Tingting Lai,
  • Yiqun Liu,
  • Wenzhen Yang,
  • Xuanxuan Zou,
  • Mingyuan Zhang,
  • Huanhuan Cui,
  • Chuanyu Liu,
  • Xin Jin,
  • Yuhui Hu,
  • Ao Chen,
  • Xun Xu,
  • Guipeng Li,
  • Yong Hou,
  • Longqi Liu,
  • Shiping Liu,
  • Liang Fang,
  • Wei Chen,
  • Liang Wu

DOI
https://doi.org/10.1038/s41467-023-43991-9
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 21

Abstract

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Abstract Human cancer cell lines have long served as tools for cancer research and drug discovery, but the presence and the source of intra-cell-line heterogeneity remain elusive. Here, we perform single-cell RNA-sequencing and ATAC-sequencing on 42 and 39 human cell lines, respectively, to illustrate both transcriptomic and epigenetic heterogeneity within individual cell lines. Our data reveal that transcriptomic heterogeneity is frequently observed in cancer cell lines of different tissue origins, often driven by multiple common transcriptional programs. Copy number variation, as well as epigenetic variation and extrachromosomal DNA distribution all contribute to the detected intra-cell-line heterogeneity. Using hypoxia treatment as an example, we demonstrate that transcriptomic heterogeneity could be reshaped by environmental stress. Overall, our study performs single-cell multi-omics of commonly used human cancer cell lines and offers mechanistic insights into the intra-cell-line heterogeneity and its dynamics, which would serve as an important resource for future cancer cell line-based studies.