Identification and Verification of a Biomarker Panel for Early Diagnosis of Lung Cancer Patients

Background: Lung cancer is the most common cause of cancer related mortality worldwide, characterised by late clinical presentation (49-53% of patients are diagnosed at stage IV) and consequently poor outcomes. One challenge in identifying biomarkers of early disease is the collection of samples from patients prior to symptomatic presentation. An additional complication in determining differential biomarkers arises from protein expression change from non-specific systemic responses and co-morbidities such as Chronic Obstructive Pulmonary Disease (COPD). Methods: We employed isobaric tagging, relative quantification mass spectrometry to analyse protein markers that differed in blood entering and egressing from the tumour bearing lobe of the diseased lung immediately prior to lung resection surgery. These potential biomarkers were assessed as lung cancer early detection biomarkers using the orthogonal mass spectrometry (MS) technique Sequential window acquisition of all theoretical fragment ion spectra (SWATH) MS which we showed had equivalent quantification value to a selected reaction monitoring (SRM) approach. Findings: In a second cohort, SWATH-MS was used to measure 974 proteins in serum samples taken <50 months prior to and at lung cancer diagnosis. Two proteins found to increase in expression egressing from a tumour had value as biomarkers. SWATH-MS profiling followed by machine learning generated a predictive 13 protein panel resulted in a mean AUC of 0.80, an accuracy of 0.78, a sensitivity of 0.79 and a specificity of 0.78. Interpretation: Thus, whilst tumour egressing proteins did not contribute significantly to a MS early detection biomarker signature, SWATH-MS and machine learning have great potential value for early detection biomarker algorithms. Funding Statement: Mass spectrometry was supported with equipment grants from Bloodwise and Medical Research Council. This work was supported by the CRUK Manchester Centre award (C5759/A25254). CD and ADW are supported by the NIHR Manchester Biomedical Research Centre. CD is also supported via core funding to the CRUK Manchester Institute and via the CRUK Lung Cancer Centre of Excellence (C5759/A20465). The pulmonary vein study was funded by Roy Castle Lung Cancer Foundation (PC) and the North West Lung Centre Charity (PC). UKCTOCS was funded by the Medical Research Council (G9901012 and G0801228), Cancer Research UK (C1479/A2884), the Department of Health and with additional support from The Eve Appeal. Senior investigators at UCL supported by the NIHR University College London Hospitals (UCLH) Biomedical Research Centre. Declaration of Interests: The authors have no financial conflicts of interest. Ethics Approval Statement: UKCTOCS was approved by the UK North West Multicentre Research Ethics Committee (North West MREC 00/8/34) with site specific approval from the local regional ethics committees and the Caldicott guardians (data controllers) of the primary care trusts. All women gave written consent for use of samples and data in ethically approved secondary studies. The subset of samples used for the present study has been approved by the Yorkshire & The Humber - Sheffield Research Ethics Committee (REC Ref 15/YH/0044).