title: Raman microscopy in the diagnosis and prognosis of surgically resected nonsmall cell lung cancer.
abstract: The main curative therapy for patients with nonsmall cell lung cancer is surgery. Despite this, the survival rate is only 50%, therefore it is important to more efficiently diagnose and predict prognosis for lung cancer patients. Raman spectroscopy is useful in the diagnosis of malignant and premalignant lesions. The aim of this study is to investigate the ability of Raman microscopy to diagnose lung cancer from surgically resected tissue sections, and predict the prognosis of these patients. Tumor tissue sections from curative resections are mapped by Raman microscopy and the spectra analzsed using multivariate techniques. Spectra from the tumor samples are also compared with their outcome data to define their prognostic significance. Using principal component analysis and random forest classification, Raman microscopy differentiates malignant from normal lung tissue. Principal component analysis of 34 tumor spectra predicts early postoperative cancer recurrence with a sensitivity of 73% and specificity of 74%. Spectral analysis reveals elevated porphyrin levels in the normal samples and more DNA in the tumor samples. Raman microscopy can be a useful technique for the diagnosis and prognosis of lung cancer patients receiving surgery, and for elucidating the biochemical properties of lung tumors.
authors.affiliation: The Queen's University of Belfast, Centre for Infection and Immunity, Respiratory Medicine Research Group, Microbiology Building, Grosvenor Road, Belfast, BT12 6BN United Kingdom. nmagee@doctors.org.uk
authors.forename: Nicholas David
authors.initials: ND
authors.lastname: Magee
authors.forename: James Renwick
authors.initials: JR
authors.lastname: Beattie
authors.forename: Chris
authors.initials: C
authors.lastname: Carland
authors.forename: Richard
authors.initials: R
authors.lastname: Davis
authors.forename: Kieran
authors.initials: K
authors.lastname: McManus
authors.forename: Ian
authors.initials: I
authors.lastname: Bradbury
authors.forename: Dean Andrew
authors.initials: DA
authors.lastname: Fennell
authors.forename: Peter William
authors.initials: PW
authors.lastname: Hamilton
authors.forename: Madeleine
authors.initials: M
authors.lastname: Ennis
authors.forename: John Joseph
authors.initials: JJ
authors.lastname: McGarvey
authors.forename: Joseph Stuart
authors.initials: JS
authors.lastname: Elborn
mesh_terms: D000465:Algorithms; D002289:Carcinoma, Non-Small-Cell Lung / Q000175:diagnosis* / Q000601:surgery*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008175:Lung Neoplasms / Q000175:diagnosis* / Q000601:surgery*; D008853:Microscopy / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods; D011379:Prognosis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013059:Spectrum Analysis, Raman / Q000379:methods*; D016896:Treatment Outcome