Temperature-compensated multiparameter SPR fiber-optic sensor for EGFR biomarker detection based on multi-mechanism signal amplification.

Authors

Pengxiao Guo, Jianshe Li, Huijing Du, Kanglei Wang, Lei Zhang, Shuguang Li

Published in

Analytica chimica acta. Volume 1421. Pages 346009. Nov 01, 2026. Epub Jul 24, 2026.

Abstract

Traditional surface plasmon resonance (SPR) sensors generally rely on a single sensing interface, making it difficult to achieve selective enhancement of different response mechanisms, thereby limiting their multiparameter detection capability and sensing performance. In this work, a multi-mechanism signal amplification SPR fiber-optic sensing platform based on interface-cooperative regulation is proposed for the simultaneous detection of epidermal growth factor receptor (EGFR) exon 20, pH, and temperature, while enabling real-time temperature compensation. By constructing functional interfaces with distinct physicochemical characteristics, synergistic signal amplification through multiple sensing mechanisms is achieved. Specifically, the Ag interface utilizes stable Ag-S bonding to enable efficient immobilization of probe DNA for the specific recognition of exon 20; the hydroxyl-rich Ag/TiO₂ interface facilitates the stable assembly of the PAA/CS functional layer to form a pH-responsive channel; and the Ag/MoS₂/PDMS composite structure provides temperature monitoring and compensation through its thermosensitive characteristics. Meanwhile, the synergistic optical regulation of the high-refractive-index TiO₂ layer and the two-dimensional MoS₂ material enhances the local electromagnetic field and enables effective spectral separation among multiple sensing channels, resulting in improved sensing performance. Experimental results demonstrate average sensitivities of 0.178 nm/nM, -22.59 nm/pH, and -4.439 nm/°C for exon 20, pH, and temperature detection, respectively. By introducing a real-time temperature compensation strategy, the accuracy and reliability of EGFR exon 20 detection are further improved. The proposed sensing platform provides a promising approach for lung cancer biomarker analysis and multimodal physiological monitoring in complex biological environments.

PMID:
42702441
Bibliographic data and abstract were imported from PubMed on 07 Sep 2026.

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