Multi-cancer early detection based on serum surface-enhanced Raman spectroscopy with deep learning: a large-scale case-control study.

Journal: BMC medicine
PMID: 39984977

Abstract

BACKGROUND: Early detection of cancer can help patients with more effective treatments and result in better prognosis. Unfortunately, established cancer screening technologies are limited for use, especially for multi-cancer early detection. In this study, we described a serum-based platform integrating surface-enhanced Raman spectroscopy (SERS) technology with resampling strategy, feature dimensionality enhancement, deep learning and interpretability analysis methods for sensitive and accurate pan-cancer screening.

Authors

  • Yuxiang Lin
    Department of Breast Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian Province, 350001, China.
  • Qiyi Zhang
    Network Technology Center, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, 350003, China.
  • Hanxi Chen
    Department of Breast Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian Province, 350001, China.
  • Shuhang Liu
    Key Laboratory of Optoelectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, Fujian, 350117, China.
  • Kaiming Peng
    College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, PR China; Institute of Carbon Neutrality, Tongji University, Shanghai, 200092, PR China.
  • Xiaojie Wang
    Beijing University of Posts and Telecommunications, China.
  • Liyong Zhang
    School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China. Electronic address: zhly@dlut.edu.cn.
  • Jun Huang
    Department of Endoscopy, Jiangxi Cancer Hospital, Nanchang, China.
  • Xiuqing Yan
    Department of Nursing, Fujian Medical University Union Hospital, Fuzhou, Fujian Province, 350001, China.
  • Xueliang Lin
    Fujian Provincial Key Laboratory for Advanced Micro-Nano Photonics Technology and Devices, Institute for Photonics Technology, Quanzhou Normal University, Quanzhou, 362000, China.
  • Uddin M D Hasan
    Department of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian, 350122, China.
  • Mahabub Sarwara
    Department of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian, 350122, China.
  • Fangmeng Fu
    Department of Breast Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian Province 350001, China; Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian Province 350001, China; Breast Cancer Institute, Fujian Medical University, Fuzhou, Fujian Province 350001, China. Electronic address: ffm@fjmu.edu.cn.
  • Shangyuan Feng
    Key Laboratory of OptoElectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou 350117, PR China.
  • Chuan Wang
    Department of Endocrinology and Metabolism, Qilu Hospital, Shandong University, Jinan, China.

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