ArticleCancer biomarkers : section A of Disease markers2019
Sub-terahertz vibrational spectroscopy of ovarian cancer and normal control tissue for molecular diagnostic technology.
Article in Cancer biomarkers : section A of Disease markers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- A new horizon for neuroscience: terahertz biotechnology in brain research.Neural regeneration research · 2025Article
- Effect of terahertz radiation on cells and cellular structures.Frontiers of optoelectronics · 2025Review
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7 authors.
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Abstract
We introduce here recently developed highly resolved Sub-Terahertz resonance spectroscopy of biological molecules and cells combined with molecular dynamics (MD) computational analysis as a new approach for optical visualization and quantification of the presence of microRNAs, particularly the mir-200 family, as potential biomarkers in samples from tissue of epithelial ovarian cancers for disease early detection, analysis, prognosis and treatment.
methodA set of samples for this study was prepared from anonymized archival formalin-fixed, paraffin-embedded ovarian epithelial tissue containing regions of invasive neoplastic cells from cases of high-histologic grade serous papillary ovarian carcinoma. Control samples were normal mucosa from fallopian tubes of patients with no known malignancy. Spectroscopic characterization of tissue samples in this study was performed using a continuous wave, frequency domain automated spectrometer operating at room temperature in the spectral region of 310-500 GHz. The spectral results were compared with molecular dynamics simulations and absorption coefficient calculations utilized to predict the absorption spectra.
resultsThe characteristic spectroscopic features in absorption spectra, particularly the presence of absorption peaks near 13 cm-1 have been identified as cancer indicators. Tissue samples heterogeneity, reflected by diverse spectral signatures, provides additional, very specific information that may be used for identification of cancer subtypes, clinical behavior or sensitivity to specific therapies. Further work is warranted to determine if this signature can be detected in bio-fluids from ovarian cancer patients. If strongly correlated with cancer burden, it may then be investigated as a potential new biomarker for disease monitoring, and also perhaps as a biomarker for cancer screening.
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