title: Multivariate analyses for biomarkers hunting and validation through on-tissue bottom-up or in-source decay in MALDI-MSI: application to prostate cancer.
abstract: The large amount of data generated using matrix-assisted laser desorption/ionization mass spectrometric imaging (MALDI-MSI) poses a challenge for data analysis. In fact, generally about 1.10(8)-1.10(9) values (m/z, I) are stored after a single MALDI-MSI experiment. This imposes processing techniques using dedicated informatics tools to be used since manual data interpretation is excluded. This work proposes and summarizes an approach that utilizes a multivariable analysis of MSI data. The multivariate analysis, such as principal component analysis-symbolic discriminant analysis, can remove and highlight specific m/z from the spectra in a specific region of interest. This approach facilitates data processing and provides better reproducibility, and thus, broadband acquisition for MALDI-MSI should be considered an effective tool to highlight biomarkers of interest. Additionally, we demonstrate the importance of the hierarchical classification of biomarkers by analyzing studies of clusters obtained either from digested or undigested tissues and using bottom-up and in-source decay strategies for in-tissue protein identification. This provides the possibility for the rapid identification of specific markers from different histological samples and their direct localization in tissues. We present an example from a prostate cancer study using formalin-fixed paraffin-embedded tissue.
authors.affiliation: MALDI Imaging team, Laboratoire de Spectrométrie de Masse Biologique Fondamentale et Appliquée (FABMS), EA 4550, Université Nord de France, Université Lille 1, Villeneuve d'Ascq, France.
authors.forename: David
authors.initials: D
authors.lastname: Bonnel
authors.forename: Rémi
authors.initials: R
authors.lastname: Longuespee
authors.forename: Julien
authors.initials: J
authors.lastname: Franck
authors.forename: Morad
authors.initials: M
authors.lastname: Roudbaraki
authors.forename: Pierre
authors.initials: P
authors.lastname: Gosset
authors.forename: Robert
authors.initials: R
authors.lastname: Day
authors.forename: Michel
authors.initials: M
authors.lastname: Salzet
authors.forename: Isabelle
authors.initials: I
authors.lastname: Fournier
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D014408:Biomarkers, Tumor / Q000032:analysis*; D005557:Formaldehyde; D006801:Humans; D008297:Male; D008969:Molecular Sequence Data; D015999:Multivariate Analysis; D016612:Paraffin Embedding; D011467:Prostate / Q000473:pathology; D011471:Prostatic Neoplasms / Q000175:diagnosis* / Q000473:pathology; D051381:Rats; D017208:Rats, Wistar; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*
chemical_list: D014408:Biomarkers, Tumor; D005557:Formaldehyde