From Single-Modal Signal Recognition to Multidimensional Precision Detection: Breakthroughs and Innovations of Multi-Modal Sensors in Tumor Biomarker Detection.
6 affiliations
- 1Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital, Taiyuan 030032, China.
- 2School of Pharmacy, Shanxi Medical University, Taiyuan 030001, China.
- 3Key Laboratory of Cellular Physiology, Shanxi Medical University, Ministry of Education, Taiyuan 030001, China.
- 4Medicinal Basic Research Innovation Center of Chronic Kidney Disease, Shanxi Medical University, Ministry of Education, Taiyuan 030001, China.
- 5School of Basic Medical Sciences, Shanxi Medical University, Taiyuan 030001, China.
- 6The Radiology Department, Shanxi Provincial People's Hospital Affiliated to Shanxi Medical University, Taiyuan 030001, China.
Abstract
The sensitive detection of tumor markers is of great significance for clinical diagnosis. Due to the extremely low abundance of early tumor biomarkers and severe background interference from biological matrices, traditional single-modal atomolar biological testing generally has limitations such as high false positives and narrow linear ranges, making it difficult to meet the clinical needs of precise diagnosis and treatment. This has driven the iterative development of biosensing technology from a single signal readout mode to multi-modal collaborative analysis, significantly improving the sensitivity and accuracy of complex biological sample detection. Dual-modal sensors integrate two complementary sensing mechanisms, whereas multi-modal sensors produce three or more independent signal outputs. By combining such mechanisms, for example electrochemistry and optics, these platforms can establish a signal cross-validation and self-calibration detection system. This multidimensional analysis strategy can mitigate interference caused by environmental factors and human operational errors to a certain extent, lowering detection limits and broadening the linear range, thereby potentially providing higher-reliability data support for early tumor diagnosis. This work systematically reviews the technological evolution and performance differences in tumor biomarker sensors from single-mode to multi-mode in recent years, with a focus on summarizing the cutting-edge research progress in this field. It provides a comprehensive reference for researchers and facilitates further applications of multi-modal sensors in point-of-care detection, and artificial intelligence-assisted analysis.
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BibTeX
@article{chang2026from,
title = {{From Single-Modal Signal Recognition to Multidimensional Precision Detection: Breakthroughs and Innovations of Multi-Modal Sensors in Tumor Biomarker Detection.}},
author = {Ruimiao Chang and Jingjing Wang and Yong Li and Shuai Jia and Liping Li and Ruiping Zhang},
journal = {Biosensors},
year = {2026},
month = oct,
doi = {10.3390/bios16100579},
url = {https://europepmc.org/article/MED/42930126},
note = {CC BY},
}
RIS
TY - JOUR
TI - From Single-Modal Signal Recognition to Multidimensional Precision Detection: Breakthroughs and Innovations of Multi-Modal Sensors in Tumor Biomarker Detection.
AU - Ruimiao Chang
AU - Jingjing Wang
AU - Yong Li
AU - Shuai Jia
AU - Liping Li
AU - Ruiping Zhang
PY - 2026
DA - 2026/10/15
JO - Biosensors
DO - 10.3390/bios16100579
UR - https://europepmc.org/article/MED/42930126
AB - The sensitive detection of tumor markers is of great significance for clinical diagnosis. Due to the extremely low abundance of early tumor biomarkers and severe background interference from biological matrices, traditional single-modal atomolar biological testing generally has limitations such as high false positives and narrow linear ranges, making it difficult to meet the clinical needs of precise diagnosis and treatment. This has driven the iterative development of biosensing technology from a single signal readout mode to multi-modal collaborative analysis, significantly improving the sensitivity and accuracy of complex biological sample detection. Dual-modal sensors integrate two complementary sensing mechanisms, whereas multi-modal sensors produce three or more independent signal outputs. By combining such mechanisms, for example electrochemistry and optics, these platforms can establish a signal cross-validation and self-calibration detection system. This multidimensional analysis strategy can mitigate interference caused by environmental factors and human operational errors to a certain extent, lowering detection limits and broadening the linear range, thereby potentially providing higher-reliability data support for early tumor diagnosis. This work systematically reviews the technological evolution and performance differences in tumor biomarker sensors from single-mode to multi-mode in recent years, with a focus on summarizing the cutting-edge research progress in this field. It provides a comprehensive reference for researchers and facilitates further applications of multi-modal sensors in point-of-care detection, and artificial intelligence-assisted analysis.
SN - 2079-6374
ER -