Dataset Information

Correlation between electrical characteristics and biomarkers in breast cancer cells.

ABSTRACT: Both electrical properties and biomarkers of biological tissues can be used to distinguish between normal and diseased tissues, and the correlations between them are critical for clinical applications of conductivity (σ) and permittivity (ε); however, these correlations remain unknown. This study aimed to investigate potential correlations between electrical characteristics and biomarkers of breast cancer cells (BCC). Changes in σ and ε of different components in suspensions of normal cells and BCC were analyzed in the range of 200 kHz-5 MHz. Pearson's correlation coefficient heatmap was used to investigate the correlation between σ and ε of the cell suspensions at different stages and biomarkers of cell growth and microenvironment. σ and ε of the cell suspensions closely resembled those of tissues. Further, the correlations between Na⁺/H⁺ exchanger 1 and ε and σ of cell suspensions were extremely significant among all biomarkers (p_ε < 0.001; p_σ < 0.001). There were significant positive correlations between cell proliferation biomarkers and ε and σ of cell suspensions (p_ε/σ < 0.05). The microenvironment may be crucial in the testing of cellular electrical properties. ε and σ are potential parameters to characterize the development of breast cancer.

SUBMITTER: Wang Y

PROVIDER: S-EPMC8275571 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Correlation between electrical characteristics and biomarkers in breast cancer cells.

Wang Yang Y Li Ying Y Huang Jie J Zhang Yan Y Ma Ren R Zhang Shunqi S Yin Tao T Liu Shangmei S Song Yan Y Liu Zhipeng Z

Scientific reports 20210712 1

Both electrical properties and biomarkers of biological tissues can be used to distinguish between normal and diseased tissues, and the correlations between them are critical for clinical applications of conductivity (σ) and permittivity (ε); however, these correlations remain unknown. This study aimed to investigate potential correlations between electrical characteristics and biomarkers of breast cancer cells (BCC). Changes in σ and ε of different components in suspensions of normal cells and ...[more]

PMID: 34253828

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Project description:BackgroundThere is insufficient research on the correlation between the apparent diffusion coefficient and clinicopathological characteristics of breast cancer patients. The present study is to investigate the correlation between the apparent diffusion coefficient and pathological characteristics of patients with invasive breast cancer.MethodsFrom January 2019 to September 2020, 122 cases of invasive breast cancer and 21 cases of benign tumors were retrospectively enrolled. The apparent diffusion coefficient was compared between the two groups, and the correlation between the apparent diffusion coefficient and the pathological characteristics of the patients with invasive breast cancer were analyzed.ResultsCompared with the benign tumor group, the apparent diffusion coefficient in the invasive breast cancer group was significantly lower (0.89±0.17 vs. 1.47±0.27 10-3 mm2/s, P=0.000). Using the apparent diffusion coefficient to diagnose patients with invasive breast cancer, the area under receiver operating characteristic (ROC) curve was 0.966±0.021 [95% confidence interval (CI): 0.924-1.000, P=0.000], and the best diagnostic cut-off value was 1.16 (10-3 mm2/s), with sensitivity and specificity of 0.905 and 0.902, respectively. The apparent diffusion coefficient was used to diagnose vascular tumor thrombus in patients with invasive breast cancer. The area under the ROC curve was 0.641±0.068 (95% CI: 0.508-0.774, P=0.047), and the best diagnostic threshold was 0.835 (10-3 mm2/s), with sensitivity and specificity of 0.676 and 0.650, respectively. The apparent diffusion coefficient in patients with high expression of Ki-67 (%) was significantly reduced (0.87±0.17 vs. 1.00±0.16 10-3 mm2/s, P=0.000). The apparent diffusion coefficient was not significantly correlated with age, menopause, lesion size, estrogen receptor, progesterone receptor, or lymph node metastasis in patients with invasive breast cancer (P>0.05).ConclusionsIn patients with invasive breast cancer the apparent diffusion coefficient was significantly reduced. It was able to differentiate invasive breast cancer and vascular tumor thrombus, and was also related to Ki-67 (%) high expression.

Project description:Breast cancer (BC) is the second most frequently diagnosed cancer and accounts for approximately 25% of new cancer cases in Canadian women. Using biomarkers as a less-invasive BC diagnostic method is currently under investigation but is not ready for practical application in clinical settings. During the last decade, extracellular vesicles (EVs) have emerged as a promising source of biomarkers because they contain cancer-derived proteins, RNAs, and metabolites. In this study, EV proteins from small EVs (sEVs) and medium EVs (mEVs) were isolated from BC MDA-MB-231 and MCF7 and non-cancerous breast epithelial MCF10A cell lines and then analyzed by two approaches: global proteomic analysis and enrichment of EV surface proteins by Sulfo-NHS-SS-Biotin labeling. From the first approach, proteomic profiling identified 2459 proteins, which were subjected to comparative analysis and correlation network analysis. Twelve potential biomarker proteins were identified based on cell line-specific expression and filtered by their predicted co-localization with known EV marker proteins, CD63, CD9, and CD81. This approach resulted in the identification of 11 proteins, four of which were further investigated by Western blot analysis. The presence of transmembrane serine protease matriptase (ST14), claudin-3 (CLDN3), and integrin alpha-7 (ITGA7) in each cell line was validated by Western blot, revealing that ST14 and CLDN3 may be further explored as potential EV biomarkers for BC. The surface labeling approach enriched proteins that were not identified using the first approach. Ten potential BC biomarkers (Glutathione S-transferase P1 (GSTP1), Elongation factor 2 (EEF2), DEAD/H box RNA helicase (DDX10), progesterone receptor (PGR), Ras-related C3 botulinum toxin substrate 2 (RAC2), Disintegrin and metalloproteinase domain-containing protein 10 (ADAM10), Aconitase 2 (ACO2), UTP20 small subunit processome component (UTP20), NEDD4 binding protein 2 (N4BP2), Programmed cell death 6 (PDCD6)) were selected from surface proteins commonly identified from MDA-MB-231 and MCF7, but not identified in MCF10A EVs. In total, 846 surface proteins were identified from the second approach, of which 11 were already known as BC markers. This study supports the proposition that Evs are a rich source of known and novel biomarkers that may be used for non-invasive detection of BC. Furthermore, the presented datasets could be further explored for the identification of potential biomarkers in BC.

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Correlation between electrical characteristics and biomarkers in breast cancer cells.

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Correlation between electrical characteristics and biomarkers in breast cancer cells.

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