title: Cluster-based comparison of the peptide mass fingerprint obtained by MALDI-TOF mass spectrometry. A case study: long-term stability of rituximab.
abstract: We evaluated the use of the peptide mass fingerprint (PMF) obtained by matrix assisted laser desorption and ionization (MALDI) time-of-flight mass spectrometry (TOF-MS) to track changes in the structure of a protein. The first problem we had to overcome was the inherent complexity of the PMF, which makes it difficult to compare. We dealt with this problem by developing a cluster-based comparison algorithm which takes into account the proportional error made by the mass spectrometer. This procedure involves grouping together similar masses in an intelligent manner, so that we can determine which data correspond to the same peptide (any slight differences can be explained as experimental errors), and which of them are too different and thus more likely to represent different peptides. The proposed algorithm was applied to track changes in a commercially available monoclonal antibody (mAb), namely rituximab (RTX), prepared under the usual hospital conditions and stored refrigerated (4 °C) and frozen (-20 °C) for a long term study. PMFs were obtained periodically over three months. For each checked time, five replicates of the PMFs were obtained in order to evaluate the similarities between them by means of the occurrences of the particular peptides (m/z). After applying the algorithm to the PMF, different approaches were used to analyse the results. Surprisingly, all of them suggested that there were no differences between the two storage conditions tested, i.e. the RTX samples were almost equally well preserved when stored refrigerated at 4 °C or frozen at -20 °C. The cluster-based methodology is new in protein mass spectrometry and could be useful as an easy test for major changes in proteins and biopharmaceutics for diverse applications in industry and other fields, and could provide additional stability data in relation to the practical use of anticancer drugs.
authors.affiliation: CITIC-UGR, Department of Computer Science and Artificial Intelligence, University of Granada, ETSIIT, C/Periodista Daniel Saucedo Aranda s/n, 18071 Granada, Spain.
authors.forename: Pablo J
authors.initials: PJ
authors.lastname: Villacorta
authors.forename: Antonio
authors.initials: A
authors.lastname: Salmerón-García
authors.forename: David A
authors.initials: DA
authors.lastname: Pelta
authors.forename: José
authors.initials: J
authors.lastname: Cabeza
authors.forename: Antonio
authors.initials: A
authors.lastname: Lario
authors.forename: Natalia
authors.initials: N
authors.lastname: Navas
mesh_terms: D000465:Algorithms; D058846:Antibodies, Monoclonal, Murine-Derived / Q000032:analysis* / Q000737:chemistry*; D000970:Antineoplastic Agents / Q000032:analysis / Q000737:chemistry; D016000:Cluster Analysis; D006801:Humans; D010449:Peptide Mapping / Q000379:methods*; D000069283:Rituximab; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*
chemical_list: D058846:Antibodies, Monoclonal, Murine-Derived; D000970:Antineoplastic Agents; D000069283:Rituximab