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<p>Chemoresistance to 5-fluorouracil (5-FU) remains a critical barrier in colorectal cancer (CRC) management. This study integrates multi-omics data from 26,192 human samples to elucidate the RNA methylation-mediated crosstalk between tumor-associated macrophages (TAMs) and tumor cells. Machine learning models were able to effectively stratify patients by risk and identified a core signature of six genes (including SCG2), whose expression patterns were associated with poor prognosis and chemotherapy resistance-related phenotypes. Mechanistically, 5-FU elevates m6A modification in TAMs, polarizing them toward the M2 phenotype. SCG2 mRNA methylation promotes TNF-α ubiquitination, reducing its levels and thereby sustaining NF-κB activation in tumor cells to drive PCD resistance. The core candidate genes (CCGs) model effectively predicts survival outcomes. Targeting SCG2 represents a novel strategy to reverse chemoresistance by disrupting TAMs-tumor crosstalk, offering actionable targets for personalized therapy optimization.</p>

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Targeting m6A-SCG2-TAMs axis overcomes 5-FU resistance in colorectal cancer via a multi-omics model

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月3日

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  • Yiming Sun,
  • Ke Peng,
  • Yuening Li,
  • Daofeng Zheng,
  • Ling Liu,
  • Jiuheng Yin,
  • Kun Yu,
  • Cong Xu,
  • João Conde,
  • Zhixi Li,
  • Chengliang Yin,
  • Wensheng Wang,
  • Weidong Xiao

摘要

Chemoresistance to 5-fluorouracil (5-FU) remains a critical barrier in colorectal cancer (CRC) management. This study integrates multi-omics data from 26,192 human samples to elucidate the RNA methylation-mediated crosstalk between tumor-associated macrophages (TAMs) and tumor cells. Machine learning models were able to effectively stratify patients by risk and identified a core signature of six genes (including SCG2), whose expression patterns were associated with poor prognosis and chemotherapy resistance-related phenotypes. Mechanistically, 5-FU elevates m6A modification in TAMs, polarizing them toward the M2 phenotype. SCG2 mRNA methylation promotes TNF-α ubiquitination, reducing its levels and thereby sustaining NF-κB activation in tumor cells to drive PCD resistance. The core candidate genes (CCGs) model effectively predicts survival outcomes. Targeting SCG2 represents a novel strategy to reverse chemoresistance by disrupting TAMs-tumor crosstalk, offering actionable targets for personalized therapy optimization.