ArticleNanomaterials (Basel, Switzerland)2019
Detection of Circulating Tumor Cells Using Membrane-Based SERS Platform: A New Diagnostic Approach for 'Liquid Biopsy'.
Article in Nanomaterials (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Plasmonic nanoparticle sensors: current progress, challenges, and future prospects.Nanoscale horizons · 2024Review
- SERS biosensors for liquid biopsy towards cancer diagnosis by detection of various circulating biomarkers: current progress and perspectives.Nano convergence · 2024Review
- SERS sensing for cancer biomarker: Approaches and directions.Bioactive materials · 2024Review
- Advancing Brain Research through Surface-Enhanced Raman Spectroscopy (SERS): Current Applications and Future Prospects.Biosensors · 2024Review
- Article
- Circulating Tumour Cells: Detection and Application in Advanced Non-Small Cell Lung Cancer.International journal of molecular sciences · 2023Review
- Raman Spectroscopy Combined with Malaria Protein for Early Capture and Recognition of Broad-Spectrum Circulating Tumor Cells.International journal of molecular sciences · 2023Article
- Biosensors for the Isolation and Detection of Circulating Tumor Cells (CTCs) in Point-of-Care Settings.Micromachines · 2023Review
- Machine learning-augmented surface-enhanced spectroscopy toward next-generation molecular diagnostics.Nanoscale advances · 2023Review
- Isolation, Detection and Analysis of Circulating Tumour Cells: A Nanotechnological Bioscope.Pharmaceutics · 2023Review
- Mg-Doped ZnO Nanoparticles with Tunable Band Gaps for Surface-Enhanced Raman Scattering (SERS)-Based Sensing.Nanomaterials (Basel, Switzerland) · 2022Article
- Highly Efficient Blood Protein Analysis Using Membrane Purification Technique and Super-Hydrophobic SERS Platform for Precise Screening and Staging of Nasopharyngeal Carcinoma.Nanomaterials (Basel, Switzerland) · 2022Article
- Microfluidic SERS devices: brightening the future of bioanalysis.Discover materials · 2022Review
- Recent Development of Nanomaterials-Based Cytosensors for the Detection of Circulating Tumor Cells.Biosensors · 2021Review
- Aggregation-Enhanced Photoluminescence and Photoacoustics of Atomically Precise Gold Nanoclusters in Lipid Nanodiscs (NANOAdvanced functional materials · 2021Article
- Research Progress for the Clinical Application of Circulating Tumor Cells in Prostate Cancer Diagnosis and Treatment.BioMed research international · 2021Review
- Effect of Varying Expression of EpCAM on the Efficiency of CTCs Detection by SERS-Based Immunomagnetic Optofluidic Device.Cancers · 2020Article
- Application of Bacteriophages in Nanotechnology.Nanomaterials (Basel, Switzerland) · 2020Review
- Heterogeneity of Circulating Tumor Cells in Breast Cancer: Identifying Metastatic Seeds.International journal of molecular sciences · 2020Review
- Article
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Authors and funding
8 authors.
Funding
Abstract
The detection and monitoring of circulating tumor cells (CTCs) in blood is an important strategy for early cancer evidence, analysis, monitoring of therapeutic response, and optimization of cancer therapy treatments. In this work, tailor-made membranes (MBSP) for surface-enhanced Raman spectroscopy (SERS)-based analysis, which permitted the separation and enrichment of CTCs from blood samples, were developed. A thin layer of SERS-active metals deposited on polymer mat enhanced the Raman signals of CTCs and provided further insight into CTCs molecular and biochemical composition. The SERS spectra of all studied cells-prostate cancer (PC3), cervical carcinoma (HeLa), and leucocytes as an example of healthy (normal) cell-revealed significant differences in both the band positions and/or their relative intensities. The multivariate statistical technique based on principal component analysis (PCA) was applied to identify the most significant differences (marker bands) in SERS data among the analyzed cells and to perform quantitative analysis of SERS data. Based on a developed PCA algorithm, the studied cell types were classified with an accuracy of 95% in 2D PCA to 98% in 3D PCA. These results clearly indicate the diagnostic efficiency for the discrimination between cancer and normal cells. In our approach, we exploited the one-step technology that exceeds most of the multi-stage CTCs analysis methods used and enables simultaneous filtration, enrichment, and identification of the tumor cells from blood specimens.
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Registered trials
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