Systematic investigation of mitochondrial transfer between cancer cells and T cells at single-cell resolution

Hongyi Zhang, Xuexin Yu, Jianfeng Ye, Huiyu Li, Jing Hu, Yuhao Tan, Yan Fang, Esra Akbay, Fulong Yu, Chen Weng, Vijay G. Sankaran, Robert M. Bachoo, Elizabeth Maher, John Minna, Anli Zhang, Bo Li

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Mitochondria (MT) participate in most metabolic activities of mammalian cells. A near-unidirectional mitochondrial transfer from T cells to cancer cells was recently observed to “metabolically empower” cancer cells while “depleting immune cells,” providing new insights into tumor-T cell interaction and immune evasion. Here, we leverage single-cell RNA-seq technology and introduce MERCI, a statistical deconvolution method for tracing and quantifying mitochondrial trafficking between cancer and T cells. Through rigorous benchmarking and validation, MERCI accurately predicts the recipient cells and their relative mitochondrial compositions. Application of MERCI to human cancer samples identifies a reproducible MT transfer phenotype, with its signature genes involved in cytoskeleton remodeling, energy production, and TNF-α signaling pathways. Moreover, MT transfer is associated with increased cell cycle activity and poor clinical outcome across different cancer types. In summary, MERCI enables systematic investigation of an understudied aspect of tumor-T cell interactions that may lead to the development of therapeutic opportunities.

Original languageEnglish (US)
Pages (from-to)1788-1802.e10
JournalCancer Cell
Volume41
Issue number10
DOIs
StatePublished - Oct 9 2023

Keywords

  • Mitochondrial Transfer
  • Statistical Deconvolution
  • T cell dysfunction
  • Tumor-Immune Interaction
  • mtDNA sequencing
  • single cell genomics

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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