BackgroundSurvival time for lung cancer is poor with over 90% of patients dying within five years of diagnosis primarily due to detection at late stage. The main objective of this study was to evaluate Fourier transform infrared spectroscopy (FTIR) as a high throughput and cost effective method for identifying biochemical changes in sputum as biomarkers for detection of lung cancer.MethodsSputum was collected from 25 lung cancer patients in the Medlung observational study and 25 healthy controls. FTIR spectra were generated from sputum cell pellets using infrared wavenumbers within the 1800 to 950 cm-1 "fingerprint" region.ResultsA panel of 92 infrared wavenumbers had absorbances significantly different between cancer and normal sputum spectra and were associated with putative changes in protein, nucleic acid and glycogen levels in tumours. Five prominent significant wavenumbers at 964 cm-1, 1024 cm-1, 1411 cm-1, 1577 cm-1 and 1656 cm-1 separated cancer spectra from normal spectra into two distinct groups using multivariate analysis (group 1: 100% cancer cases; group 2: 92% normal cases). Principal components analysis revealed that these wavenumbers were also able to distinguish lung cancer patients who had previously been diagnosed with breast cancer. No patterns of spectra groupings were associated with inflammation or other diseases of the airways.ConclusionsOur results suggest that FTIR applied to sputum might have high sensitivity and specificity in diagnosing lung cancer with potential as a non-invasive, cost-effective and high-throughput method for screening.Trial RegistrationClinicalTrials.gov: NCT00899262

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Historically, structural elucidation of unknown analytes by mass spectrometry alone has involved tandem mass spectrometry experiments using electron ionization. Most target molecules for bioanalysis in the metabolome are unsuitable for detection by this previous methodology. Recent publications have used high-resolution accurate mass analysis using an LTQ-Orbitrap with the more modern approach of electrospray ionization to identify new metabolites of known metabolic pathways. We have investigated the use of this methodology to build accurate mass fragmentation maps for the structural elucidation of unknown compounds. This has included the development and validation of a novel multi-dimensional LC/MS/MS methodology to identify known uremic analytes in a clinical hemodialysate sample. Good inter- and intra-day reproducibility of both chromatographic stages with a high degree of mass accuracy and precision was achieved with the multi-dimensional liquid chromatography/tandem mass spectrometry (LC/MS/MS) system. Fragmentation maps were generated most successfully using collision-induced dissociation (CID) as, unlike high-energy CID (HCD), ions formed by this technique could be fragmented further. Structural elucidation is more challenging for large analytes >270 Da and distinguishing between isomers where their initial fragmentation pattern is insufficiently different. For small molecules (<200 Da), where fragmentation data may be obtained without loss of signal intensity, complete structures can be proposed from just the accurate mass fragmentation data. This methodology has led to the discovery of a selection of known uremic analytes and two completely novel moieties with chemical structural assignments made.

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