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<p>Digital medicine leverages digital biomarkers by algebraically integrating multiple biomarkers to reflect disease status. Colorimetric analysis offers an intuitive readout, but colorimetric-based digital medicine remains underexplored. Here we show an Enzymatic Colorimetric Encoding-based Digital Medicine platform (EnCODE). By harnessing enzyme-catalyzed multicolor encoding in tandem with the programmability of DNA technology, EnCODE converts multidimensional miRNA information into recognizable optical signals. We demonstrate that these signals are decodable and can be interpreted by visual inspection or spectral analysis, facilitating dimensionality reduction and visualization of disease states. Additionally, EnCODE integrates a continuous weighting mechanism that enables accurate mapping of digital biomarkers. In a cohort of 163 pancreatic cancer clinical samples, EnCODE achieves 96% detection sensitivity and 90% overall accuracy—comparable to the 96% sensitivity and 91% overall accuracy with conventional molecular diagnostic methods. We increase data density through three-dimensional color encoding and hyperspectral imaging-based analysis, enabling an intuitive color-coded molecular readout.</p>

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Enzymatic colorimetric encoding-based digital medicine for pancreatic cancer diagnosis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月13日

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  • Dongsheng Mao,
  • Chenbin Liu,
  • Runchi Zhang,
  • Zhiyuan Ma,
  • Liang Wu,
  • Mingjin Zhu,
  • Xiaochen Tang,
  • Wen Chen,
  • Jie Deng,
  • Hongquan Gou,
  • Xiong Dun,
  • Jingqi Chen,
  • Zhaocheng Liu,
  • Wenxing Li,
  • Fenyong Sun,
  • Xiaoli Zhu

摘要

Digital medicine leverages digital biomarkers by algebraically integrating multiple biomarkers to reflect disease status. Colorimetric analysis offers an intuitive readout, but colorimetric-based digital medicine remains underexplored. Here we show an Enzymatic Colorimetric Encoding-based Digital Medicine platform (EnCODE). By harnessing enzyme-catalyzed multicolor encoding in tandem with the programmability of DNA technology, EnCODE converts multidimensional miRNA information into recognizable optical signals. We demonstrate that these signals are decodable and can be interpreted by visual inspection or spectral analysis, facilitating dimensionality reduction and visualization of disease states. Additionally, EnCODE integrates a continuous weighting mechanism that enables accurate mapping of digital biomarkers. In a cohort of 163 pancreatic cancer clinical samples, EnCODE achieves 96% detection sensitivity and 90% overall accuracy—comparable to the 96% sensitivity and 91% overall accuracy with conventional molecular diagnostic methods. We increase data density through three-dimensional color encoding and hyperspectral imaging-based analysis, enabling an intuitive color-coded molecular readout.