Scholarlink

<p>DNA replication stress is a hallmark of cancer that is exploited by chemotherapies. Current assays for replication stress have low throughput and poor resolution whilst being unable to map the movement of replication forks genome-wide. We present a new method that uses nanopore sequencing and artificial intelligence to map forks and measure their rates of movement and stalling in melanoma and colon cancer cells treated with chemotherapies. Our method can differentiate between fork slowing and fork stalling in cells treated with hydroxyurea, as well as inhibitors of ATR, WEE1, and PARP1. These different therapies yield different characteristic signatures of replication stress. We assess the role of the intra-S-phase checkpoint on fork slowing and stalling and show that replication stress dynamically changes over S-phase. Finally, we demonstrate that this method is applicable and consistent across two different flow cell chemistries (R9.4.1 and R10.4.1) from Oxford Nanopore Technologies. This method requires sequencing on only one nanopore flow cell per sample, and the cost-effectiveness enables functional screens to determine how human cancers respond to replication-targeted therapies.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A high-resolution, nanopore-based artificial intelligence assay for DNA replication stress in human cancer cells

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年8月19日

查看全文
  • Mathew J. K. Jones,
  • Subash Kumar Rai,
  • Pauline L. Pfuderer,
  • Alexis Bonfim-Melo,
  • Julia K. Pagan,
  • Paul R. Clarke,
  • Francis Isidore Garcia Totañes,
  • Catherine J. Merrick,
  • Sarah E. McClelland,
  • Michael A. Boemo

摘要

DNA replication stress is a hallmark of cancer that is exploited by chemotherapies. Current assays for replication stress have low throughput and poor resolution whilst being unable to map the movement of replication forks genome-wide. We present a new method that uses nanopore sequencing and artificial intelligence to map forks and measure their rates of movement and stalling in melanoma and colon cancer cells treated with chemotherapies. Our method can differentiate between fork slowing and fork stalling in cells treated with hydroxyurea, as well as inhibitors of ATR, WEE1, and PARP1. These different therapies yield different characteristic signatures of replication stress. We assess the role of the intra-S-phase checkpoint on fork slowing and stalling and show that replication stress dynamically changes over S-phase. Finally, we demonstrate that this method is applicable and consistent across two different flow cell chemistries (R9.4.1 and R10.4.1) from Oxford Nanopore Technologies. This method requires sequencing on only one nanopore flow cell per sample, and the cost-effectiveness enables functional screens to determine how human cancers respond to replication-targeted therapies.