Detection of Circulating Tumor Cells Using Membrane-Based SERS Platform: A New Diagnostic Approach for 'Liquid Biopsy'.
Agnieszka KamińskaTomasz R SzymborskiEvelin WitkowskaEwa Kijeńska-GawrońskaWojciech ŚwieszkowskiKrzysztof NicińskiJoanna Trzcińska-DanielewiczAgnieszka GirstunPublished in: Nanomaterials (Basel, Switzerland) (2019)
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.
Keyphrases
- circulating tumor cells
- raman spectroscopy
- gold nanoparticles
- sensitive detection
- label free
- induced apoptosis
- prostate cancer
- cell cycle arrest
- circulating tumor
- single cell
- cancer therapy
- electronic health record
- cell death
- oxidative stress
- endoplasmic reticulum stress
- machine learning
- stem cells
- data analysis
- squamous cell
- big data
- mesenchymal stem cells
- cell proliferation
- climate change
- risk assessment
- real time pcr
- cell free
- heavy metals
- solid state
- health risk