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<p>In drug discovery, assessing and stratifying drug efficacy on cells is vital. To demonstrate the efficacy of drugs on cells in different cell cycle phases, it is essential not only to analyze multidimensional protein data on the single-cell level but also to establish a methodology for extracting key molecules from subtle differences in cellular states in response to the drug. Here we introduce a single cell-PLOM-CON analysis method by combining multiplex immunofluorescence and image-based covariation network analysis and reveal several changes of proteins in early cell state changes across different cell cycle phases in HeLa cells, induced by anticancer drugs, bleomycin, cytarabine and aspirin, before any visible effects of drugs on the cell cycle appeared. Furthermore, the dynamical network biomarker theory reveals that cyclin B1 at the G2 phase is a presage protein signal of S-phase arrest induced by anticancer drugs with modes of action (MoA) similar to cytarabine. This integrated approach allows for the extraction of early protein biomarkers in initial states of drug efficacy and for drug stratification using subtle differences in MoA.</p>

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Unveiling and stratifying cell cycle-dependent drug efficacy using a single-cell PLOM-CON approach with correlation anomaly and presage protein signals

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月30日

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  • Yoshiyuki Noguchi,
  • Rina Kunishige,
  • Naeko Shinozaki-Narikawa,
  • Hiroshi Yamashita,
  • Kazuyuki Aihara,
  • Masayuki Murata,
  • Fumi Kano

摘要

In drug discovery, assessing and stratifying drug efficacy on cells is vital. To demonstrate the efficacy of drugs on cells in different cell cycle phases, it is essential not only to analyze multidimensional protein data on the single-cell level but also to establish a methodology for extracting key molecules from subtle differences in cellular states in response to the drug. Here we introduce a single cell-PLOM-CON analysis method by combining multiplex immunofluorescence and image-based covariation network analysis and reveal several changes of proteins in early cell state changes across different cell cycle phases in HeLa cells, induced by anticancer drugs, bleomycin, cytarabine and aspirin, before any visible effects of drugs on the cell cycle appeared. Furthermore, the dynamical network biomarker theory reveals that cyclin B1 at the G2 phase is a presage protein signal of S-phase arrest induced by anticancer drugs with modes of action (MoA) similar to cytarabine. This integrated approach allows for the extraction of early protein biomarkers in initial states of drug efficacy and for drug stratification using subtle differences in MoA.