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<p>Rapid and accurate diagnosis of oral cancer aggressiveness is associated with preoperative guidance and postoperative treatment. However, traditional diagnostic methods are time-consuming and easily misdiagnosed, which makes it challenging to achieve high-precision classification. Herein, we introduce a recognition engineering-mediated multichannel nanosensor for the analysis of tumor metabolites, allowing for sensitive and rapid <i>in vitro</i> and intraoperative cancer malignancy discrimination. This nanosensor system utilizes engineered carbon dots (CDs) with various ratios of amino and carboxyl functional groups, assembled as a “shell” on gold nanoparticles (AuNPs). The multichannel nanosensor displayed distinct fingerprint patterns for fourteen tumor metabolites such as amino acids, nucleic acids, and other metabolites. It offers rapid “turn-on” fluorescence-encoded profiling, generating unique signatures for cancer malignancy within 15 min. The nanosensor demonstrated 100% accuracy in identifying the oral squamous cell carcinoma (OSCC) subtype and assessing malignancy levels. It will provide detailed pathology for the identification of clinical cancer tissue samples, including cancer cell subtype and differentiation grade. Together, our study highlights the potential of the fluorescent-encoded multichannel nanosensor as a powerful <i>in vitro</i> and intraoperative diagnostic tool for cancer malignancy and treatment guidance in advanced clinical oncology.</p>

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Machine learning-assisted multichannel nanosensor based on core-shell carbon dot/gold nanoparticle composites for rapid and precise intraoperative oral cancer malignancy diagnosis

  • 期刊论文

  • 发表日期：

    2025年6月25日

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  • Yuquan Xiao,
  • Boru Peng,
  • Xiaohua Zhu,
  • Ying Long,
  • Feng Liu,
  • Meiling Liu,
  • Haitao Li,
  • Youyu Zhang,
  • Shouzhuo Yao

摘要

Rapid and accurate diagnosis of oral cancer aggressiveness is associated with preoperative guidance and postoperative treatment. However, traditional diagnostic methods are time-consuming and easily misdiagnosed, which makes it challenging to achieve high-precision classification. Herein, we introduce a recognition engineering-mediated multichannel nanosensor for the analysis of tumor metabolites, allowing for sensitive and rapid in vitro and intraoperative cancer malignancy discrimination. This nanosensor system utilizes engineered carbon dots (CDs) with various ratios of amino and carboxyl functional groups, assembled as a “shell” on gold nanoparticles (AuNPs). The multichannel nanosensor displayed distinct fingerprint patterns for fourteen tumor metabolites such as amino acids, nucleic acids, and other metabolites. It offers rapid “turn-on” fluorescence-encoded profiling, generating unique signatures for cancer malignancy within 15 min. The nanosensor demonstrated 100% accuracy in identifying the oral squamous cell carcinoma (OSCC) subtype and assessing malignancy levels. It will provide detailed pathology for the identification of clinical cancer tissue samples, including cancer cell subtype and differentiation grade. Together, our study highlights the potential of the fluorescent-encoded multichannel nanosensor as a powerful in vitro and intraoperative diagnostic tool for cancer malignancy and treatment guidance in advanced clinical oncology.