1
|
Falcetta F, Morosi L, Ubezio P, Giordano S, Decio A, Giavazzi R, Frapolli R, Prasad M, Franceschi P, D'Incalci M, Davoli E. Past-in-the-Future. Peak detection improves targeted mass spectrometry imaging. Anal Chim Acta 2018; 1042:1-10. [PMID: 30428975 DOI: 10.1016/j.aca.2018.06.067] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Revised: 06/19/2018] [Accepted: 06/24/2018] [Indexed: 11/30/2022]
Abstract
Mass spectrometry imaging is a valuable tool for visualizing the localization of drugs in tissues, a critical issue especially in cancer pharmacology where treatment failure may depend on poor drug distribution within the tumours. Proper preprocessing procedures are mandatory to obtain quantitative data of drug distribution in tumours, even at low intensity, through reliable ion peak identification and integration. We propose a simple preprocessing and quantification pipeline. This pipeline was designed starting from classical peak integration methods, developed when "microcomputers" became available for chromatography, now applied to MSI. This pre-processing approach is based on a novel method using the fixed mass difference between the analyte and its 5 d derivatives to set up a mass range gate. We demonstrate the use of this pipeline for the evaluating the distribution of the anticancer drug paclitaxel in tumour sections. The procedure takes advantage of a simple peak analysis and allows to quantify the drug concentration in each pixel with a limit of detection below 0.1 pmol mm-2 or 10 μg g-1. Quantitative images of paclitaxel distribution in different tumour models were obtained and average paclitaxel concentrations were compared with HPLC measures in the same specimens, showing <20% difference. The scripts are developed in Python and available through GitHub, at github.com/FrancescaFalcetta/Imaging_of_drugs_distribution_and_quantifications.git.
Collapse
Affiliation(s)
- Francesca Falcetta
- Department of Oncology, IRCCS Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa, 19-20156, Milan, Italy
| | - Lavinia Morosi
- Department of Oncology, IRCCS Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa, 19-20156, Milan, Italy
| | - Paolo Ubezio
- Department of Oncology, IRCCS Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa, 19-20156, Milan, Italy
| | - Silvia Giordano
- Mass Spectrometry Laboratory, Department of Environmental Health Sciences, IRCCS Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa, 19-20156, Milan, Italy
| | - Alessandra Decio
- Department of Oncology, IRCCS Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa, 19-20156, Milan, Italy
| | - Raffaella Giavazzi
- Department of Oncology, IRCCS Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa, 19-20156, Milan, Italy
| | - Roberta Frapolli
- Department of Oncology, IRCCS Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa, 19-20156, Milan, Italy
| | - Mridula Prasad
- IMM/Analytical Chemistry, Radboud University, Heyendaalseweg, 6525 AJ, Nijmegen, Netherlands; Biostatistics and Data Management Group, Fondazione Edmund Mach, 38010, San Michele all' Adige, Italy; Nanotechnology in Medicinal Chemistry, Department of Molecular Biotechnology and Health Sciences, Università di Torino, 10126, Torino, Italy
| | - Pietro Franceschi
- Biostatistics and Data Management Group, Fondazione Edmund Mach, 38010, San Michele all' Adige, Italy
| | - Maurizio D'Incalci
- Department of Oncology, IRCCS Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa, 19-20156, Milan, Italy
| | - Enrico Davoli
- Mass Spectrometry Laboratory, Department of Environmental Health Sciences, IRCCS Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa, 19-20156, Milan, Italy.
| |
Collapse
|