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Label-Free Malignancy Phenotyping of Living Cancer Cells by High-Performance Surface-Enhanced Raman Spectroscopy

Jiwon Yun1, Hyeim Yu1, Youngho Yun2

  • 1Department of Intelligent Robotics Engineering, Pukyong National University, Busan 48513, Republic of Korea.

Micromachines
|May 4, 2026
PubMed
Summary
This summary is machine-generated.

A novel chip-based Surface-Enhanced Raman Spectroscopy (SERS) platform allows label-free analysis of living cells without nanoparticle uptake. This technology enables nonperturbative cellular phenotyping and accurate cancer cell classification.

Keywords:
cancerlabel-freeliving cellsmultivariate analysissurface-enhanced Raman spectroscopy

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Area of Science:

  • Nanotechnology
  • Spectroscopy
  • Cell Biology

Background:

  • Surface-enhanced Raman spectroscopy (SERS) offers label-free molecular fingerprinting but often requires internalized nanoparticles, causing variability and cellular perturbation.
  • Existing SERS methods for living cells face challenges with nanoparticle uptake, localization, aggregation, and potential impact on cell physiology.

Purpose of the Study:

  • To develop a chip-like SERS substrate for direct culture and label-free analysis of living cells.
  • To enable nonperturbative acquisition of intrinsic cellular vibrational fingerprints under physiological conditions.
  • To assess the platform's capability for distinguishing between different cancer cell types and their heterogeneity.

Main Methods:

  • Fabrication of an Au/SiO2 nanolaminate SERS substrate with defined nanogaps for uniform enhancement at 785 nm excitation.
  • Direct culture of MCF-7 and MDA-MB-231 breast cancer cells on the substrate for label-free SERS measurements.
  • Application of principal component analysis (PCA) and linear discriminant analysis (LDA) for spectral data analysis and classification.
  • Bright-field imaging to confirm cell adhesion and morphology preservation.

Main Results:

  • The nanolaminate substrate provided uniform SERS enhancement over a large, culture-compatible area with high hotspot uniformity.
  • Reproducible acquisition of intrinsic cellular vibrational fingerprints was achieved without Raman tags or nanoparticle uptake.
  • MDA-MB-231 cells showed greater spectral variations, indicating higher heterogeneity compared to MCF-7 cells.
  • PCA and LDA achieved 99% classification accuracy between MCF-7 and MDA-MB-231 cells, with preserved cell morphology.

Conclusions:

  • The chip-based, label-free SERS platform enables scalable and nonperturbative living cell phenotyping.
  • This technology facilitates the reproducible acquisition of cellular vibrational fingerprints under physiological conditions.
  • The platform shows potential for rapid malignancy classification and treatment response screening in subtle cancer states.