title: Current Advances in the Application of Raman Spectroscopy for Molecular Diagnosis of Cervical Cancer.
abstract: Raman spectroscopy provides a unique biochemical fingerprint capable of identifying and characterizing the structure of molecules, cells, and tissues. In cervical cancer, it is acknowledged as a promising biochemical tool due to its ability to detect premalignancy and early malignancy stages. This review summarizes the key research in the area and the evidence compiled is very encouraging for ongoing and further research. In addition to the diagnostic potential, promising results for HPV detection and monitoring treatment response suggest more than just a diagnosis prospective. A greater body of evidence is however necessary before Raman spectroscopy is fully validated for clinical use and larger comprehensive studies are required to fully establish the role of Raman spectroscopy in the molecular diagnostics of cervical cancer.
authors.affiliation: DIT Centre for Radiation and Environmental Science, Focas Research Institute, Dublin Institute of Technology, Kevin Street, Dublin 8, Ireland ; School of Physics, Dublin Institute of Technology, Kevin Street, Dublin 8, Ireland.
authors.forename: Inês Raquel Martins
authors.initials: IR
authors.lastname: Ramos
authors.affiliation: School of Biological Sciences, Dublin Institute of Technology, . Kevin Street, Dublin 8, Ireland.
authors.forename: Alison
authors.initials: A
authors.lastname: Malkin
authors.affiliation: DIT Centre for Radiation and Environmental Science, Focas Research Institute, Dublin Institute of Technology, Kevin Street, Dublin 8, Ireland ; School of Physics, Dublin Institute of Technology, Kevin Street, Dublin 8, Ireland.
authors.forename: Fiona Mary
authors.initials: FM
authors.lastname: Lyng
mesh_terms: D005260:Female; D006801:Humans; D030361:Papillomavirus Infections / Q000175:diagnosis* / Q000378:metabolism; D013059:Spectrum Analysis, Raman / Q000379:methods*; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis* / Q000378:metabolism