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Multicolor SERS-encoded immuno-cocktail for longitudinal precise tracking of CTCs phenotypes in lung cancer therapeutics.

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Biosensors & bioelectronics 2026 Vol.295() p. 118277
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Fan M, Yu Z, Luo K, Chen P, Lin D, Lin Y, Lin X, Chen J, Feng S

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Tumor heterogeneity and drug resistance remain major obstacles to the implementation of personalized therapeutic strategies in lung cancer.

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  • 표본수 (n) 24

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BibTeX ↓ RIS ↓
APA Fan M, Yu Z, et al. (2026). Multicolor SERS-encoded immuno-cocktail for longitudinal precise tracking of CTCs phenotypes in lung cancer therapeutics.. Biosensors & bioelectronics, 295, 118277. https://doi.org/10.1016/j.bios.2025.118277
MLA Fan M, et al.. "Multicolor SERS-encoded immuno-cocktail for longitudinal precise tracking of CTCs phenotypes in lung cancer therapeutics.." Biosensors & bioelectronics, vol. 295, 2026, pp. 118277.
PMID 41349442

Abstract

Tumor heterogeneity and drug resistance remain major obstacles to the implementation of personalized therapeutic strategies in lung cancer. Circulating tumor cell (CTC)-based liquid biopsy provides a powerful, minimally invasive tool for tracking dynamic changes in tumor heterogeneity and elucidating mechanisms of treatment response and drug resistance. Herein, we present a portable, field-deployable surface-enhanced Raman scattering (SERS) immunoprobe platform capable of multiplexed detection of CTC membrane biomarkers to monitor tumor heterogeneity throughout the course of therapy. Utilizing a cocktail of multicolor-encoded immunoprobes, the platform achieves single-cell phenotypic resolution via antigen-specific spectral fingerprinting, validated by flow cytometry. It demonstrates ultra-sensitive CTC quantification (limit of detection of 1.7 cells/mL) and precise molecular subtyping across four cell lines (HCC827, A549, BEAS-2B, and HeLa). Integrated with orthogonal partial least squares discriminant analysis (OPLS-DA), the platform accurately distinguishes clinically relevant cell types with 99 % classification accuracy, successfully stratifying metastatic versus non-metastatic lung cancer (n = 24) and capturing treatment-driven CTC evolution in longitudinal studies (n = 7). Our results highlight a transformative strategy for real-time interception of drug resistance trajectories, positioning dynamic CTC phenotyping as a critical tool for adaptive therapy and prognostic assessment in precision oncology.

MeSH Terms

Humans; Neoplastic Cells, Circulating; Lung Neoplasms; Spectrum Analysis, Raman; Biosensing Techniques; Cell Line, Tumor; Biomarkers, Tumor; Phenotype

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