A simpler method of preprocessing MALDI-TOF MS data for differential biomarker analysis: stem cell and melanoma cancer studies

Raw MS spectral profiles were preprocessed using the proposed approach to identify peak regions in the spectra. The preprocessed data was then analysed using bespoke machine learning algorithms for data reduction and ion selection. Using the selected ions, an ANN-based predictive model was constructed to examine the predictive power of these ions for classification.Our model identified 10 candidate marker ions for both data sets. These ion panels achieved over 90% classification accuracy on blind validation data. Receiver operating characteristics analysis was performed and the area under the curve for melanoma and cord blood classifiers was 0.991 and 0.986, respectively.The results suggest that our data preprocessing technique removes unwanted characteristics of the raw data, while preserving the predictive components of the data. Ion identification analysis can be carried out using MALDI-TOF-MS data with the proposed data preprocessing technique coupled with bespoke algorithms for data reduction and ion selection.Matrix-assisted laser desorption/ionisation mass spectrometry (MALDI MS) based proteomics is a powerful screening technique for biomarker discovery. Recent growth in personalised medicine has promoted the development of protein profiling for understanding the roles of individual proteins in the context of amino status, cellular pathways and, subsequently response to therapy. Frequently used ionisation methods in recent MS technologies include electrospray ionisation (ESI), surface-enhanced laser desorption/ionisation (SELDI) and MALDI. Reviews on these methods can be found in the literature [1,2]. One of the commonly used mass analyser techniques in proteomic MS analysis is time-of-flight (TOF), the analysis based on the time measurement for an ion (i.e. signal wave) to travel along a flight tube to the detector. This time representation can be translated into mass to charge ratio (m/z) and therefore the mass of the analyte. Data can be exported as a list