Multiplex Sensing of Biomarkers on the Cancer Cell Surface by an Epithelial-Mesenchymal Transition (EMT) Sensing Panel Enables Precise Differentiating of Cancer Cells at Various EMT Stages.
Siyi WangYushuang GuoXin WangXuan ZhangTing YangJian-Hua WangPublished in: Analytical chemistry (2024)
Epithelial-mesenchymal transition (EMT) is a complex process that plays a critical role in tumor progression. In this study, we present an EMT sensing panel for the classification of cancer cells at different EMT stages. This sensing panel consists of three types of fluorescent probes based on boronic acid-functionalized carbon-nitride nanosheet (BCN) derivatives. The selective response toward different EMT-associated biomarkers, namely, EpCAM, N-cadherin, and sialic acid (SA), was achieved by conjugating the corresponding antibodies to each BCN derivative, whereas the rare-earth-doping ensures simultaneous sensing of the three biomarkers with fluorescent emission of the three probes at different wavelengths. Sensitive sensing of the three biomarkers was achieved at the protein level with LODs reaching 1.35 ng mL -1 for EpCAM, 1.62 ng mL -1 for N-cadherin, and 1.54 ng mL -1 for SA. The selective response of these biomarkers on the cell surface also facilitated sensitive detection of MCF-7 cells and MDA-MB-231 cells with LODs of 2 cells/mL and 2 cells/mL, respectively. Based on the simultaneous sensing of the three biomarkers on cancer cells that underwent different extents of EMT, precise discrimination and classification of cells at various EMT stages were also achieved with an accuracy of 93.3%. This EMT sensing panel provided a versatile tool for monitoring the EMT evolution process and has the potential to be used for the evaluation of the EMT-targeting therapy and metastasis prediction.
Keyphrases
- epithelial mesenchymal transition
- induced apoptosis
- transforming growth factor
- cell cycle arrest
- signaling pathway
- cell surface
- quantum dots
- sensitive detection
- endoplasmic reticulum stress
- small molecule
- living cells
- deep learning
- mass spectrometry
- pi k akt
- mesenchymal stem cells
- circulating tumor cells
- cell death
- squamous cell carcinoma
- oxidative stress
- magnetic resonance
- stem cells
- poor prognosis
- cell adhesion
- risk assessment
- long non coding rna
- high throughput
- human health
- drug delivery
- protein protein
- reduced graphene oxide