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Morosi L, Matteo C, Meroni M, Ceruti T, Fuso Nerini I, Bello E, Frapolli R, D'Incalci M, Zucchetti M, Davoli E. Quantitative measurement of pioglitazone in neoplastic and normal tissues by AP-MALDI mass spectrometry imaging. Talanta 2022; 237:122918. [PMID: 34736656 DOI: 10.1016/j.talanta.2021.122918] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 09/24/2021] [Accepted: 09/29/2021] [Indexed: 11/26/2022]
Abstract
Pioglitazone is a Peroxisome Proliferator-Activated Receptor (PPAR) agonist of the thiazolidinedione class of compounds with promising anticancer activity. An innovative quantitative mass spectrometry imaging (MSI) method and a HPLC-UV method were developed and validated to investigate its distribution in tumor and liver tissues. The MSI method is based on stable isotope normalization and resulted highly specific and sensitive (0.2 pmol/spot). The correct identification of the drug ion signal is confirmed by MS/MS analysis on tissue. The method shows an optimal lateral resolution (25 μm) relying on the ionization efficiency and fine laser diameter of the atmospheric pressure MALDI source. The HPLC-UV method is simple and straightforward involving quick protein precipitation and shows good sensitivity (50ng/sample) using a small starting volume of biological sample. Thus, it is applicable to samples obtained from both preclinical models and clinical surgical procedures. MSI and HPLC-UV assays were validated assessing linearity, intra- and inter-day precision and accuracy, limit of quantification, selectivity and recovery. These are the first methods developed and validated for the analysis of pioglitazone in tissues, and they were applied successfully to myxoid liposarcoma xenograft-bearing mice, which received clinically relevant drug doses. Pioglitazone was measured by either method in sections of tumor and liver 2, 6 and 24 h post-treatment. Drug distribution was relatively homogeneous.
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Affiliation(s)
- Lavinia Morosi
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, Via Mario Negri 2, Milan, Italy
| | - Cristina Matteo
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, Via Mario Negri 2, Milan, Italy
| | - Marina Meroni
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, Via Mario Negri 2, Milan, Italy
| | - Tommaso Ceruti
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, Via Mario Negri 2, Milan, Italy
| | - Ilaria Fuso Nerini
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, Via Mario Negri 2, Milan, Italy
| | - Ezia Bello
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, Via Mario Negri 2, Milan, Italy
| | - Roberta Frapolli
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, Via Mario Negri 2, Milan, Italy.
| | - Maurizio D'Incalci
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, Via Mario Negri 2, Milan, Italy
| | - Massimo Zucchetti
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, Via Mario Negri 2, Milan, Italy
| | - Enrico Davoli
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Mass Spectrometry Research Center for Health and Environment and Laboratory of Mass Spectrometry, Via Mario Negri 2, Milan, Italy
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Morosi L, Meroni M, Ubezio P, Fuso Nerini I, Minoli L, Porcu L, Panini N, Colombo M, Blouw B, Kang DW, Davoli E, Zucchetti M, D'Incalci M, Frapolli R. PEGylated recombinant human hyaluronidase (PEGPH20) pre-treatment improves intra-tumour distribution and efficacy of paclitaxel in preclinical models. JOURNAL OF EXPERIMENTAL & CLINICAL CANCER RESEARCH : CR 2021; 40:286. [PMID: 34507591 PMCID: PMC8434701 DOI: 10.1186/s13046-021-02070-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 08/10/2021] [Indexed: 01/04/2023]
Abstract
BACKGROUND Scarce drug penetration in solid tumours is one of the possible causes of the limited efficacy of chemotherapy and is related to the altered tumour microenvironment. The abnormal tumour extracellular matrix (ECM) together with abnormal blood and lymphatic vessels, reactive stroma and inflammation all affect the uptake, distribution and efficacy of anticancer drugs. METHODS We investigated the effect of PEGylated recombinant human hyaluronidase PH20 (PEGPH20) pre-treatment in degrading hyaluronan (hyaluronic acid; HA), one of the main components of the ECM, to improve the delivery of antitumor drugs and increase their therapeutic efficacy. The antitumor activity of paclitaxel (PTX) in HA synthase 3-overexpressing and wild-type SKOV3 ovarian cancer model and in the BxPC3 pancreas xenograft tumour model, was evaluated by monitoring tumour growth with or without PEGPH20 pre-treatment. Pharmacokinetics and tumour penetration of PTX were assessed by HPLC and mass spectrometry imaging analysis in the same tumour models. Tumour tissue architecture and HA deposition were analysed by histochemistry. RESULTS Pre-treatment with PEGPH20 modified tumour tissue architecture and improved the antitumor activity of paclitaxel in the SKOV3/HAS3 tumour model, favouring its accumulation and more homogeneous intra-tumour distribution, as assessed by quantitative and qualitative analysis. PEGPH20 also reduced HA content influencing, though less markedly, PTX distribution and antitumor activity in the BxPC3 tumour model. CONCLUSION Remodelling the stroma of HA-rich tumours by depletion of HA with PEGPH20 pre-treatment, is a potentially successful strategy to improve the intra-tumour distribution of anticancer drugs, increasing their therapeutic efficacy, without increasing toxicity.
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Affiliation(s)
- Lavinia Morosi
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, via M. Negri 2, 20156, Milan, Italy.,Present address: IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089 Rozzano, Milan, Italy
| | - Marina Meroni
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, via M. Negri 2, 20156, Milan, Italy
| | - Paolo Ubezio
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, via M. Negri 2, 20156, Milan, Italy
| | - Ilaria Fuso Nerini
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, via M. Negri 2, 20156, Milan, Italy.,Present address: IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089 Rozzano, Milan, Italy
| | - Lucia Minoli
- Department of Veterinary Medicine, University of Milan, Lodi, Italy.,Mouse and Animal Pathology Laboratory (MAPLab), Fondazione UniMi, Milan, Italy
| | - Luca Porcu
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, via M. Negri 2, 20156, Milan, Italy
| | - Nicolò Panini
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, via M. Negri 2, 20156, Milan, Italy
| | - Marika Colombo
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, via M. Negri 2, 20156, Milan, Italy
| | | | - David W Kang
- Halozyme Therapeutics, San Diego, California, USA
| | - Enrico Davoli
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Laboratory of Mass Spectrometry, Milan, Italy
| | - Massimo Zucchetti
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, via M. Negri 2, 20156, Milan, Italy
| | - Maurizio D'Incalci
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, via M. Negri 2, 20156, Milan, Italy.,Present address: IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089 Rozzano, Milan, Italy.,Present address: Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20090, Pieve Emanuele, Milan, Italy
| | - Roberta Frapolli
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology, via M. Negri 2, 20156, Milan, Italy.
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Davoli E, Zucchetti M, Matteo C, Ubezio P, D'Incalci M, Morosi L. THE SPACE DIMENSION AT THE MICRO LEVEL: MASS SPECTROMETRY IMAGING OF DRUGS IN TISSUES. MASS SPECTROMETRY REVIEWS 2021; 40:201-214. [PMID: 32501572 DOI: 10.1002/mas.21633] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 04/24/2020] [Accepted: 04/29/2020] [Indexed: 06/11/2023]
Abstract
Mass spectrometry imaging (MSI) has seen remarkable development in recent years. The possibility of getting quantitative or semiquantitative data, while maintaining the spatial component in the tissues has opened up unique study possibilities. Now with a spatial window of few tens of microns, we can characterize the events occurring in tissue subcompartments in physiological and pathological conditions. For example, in oncology-especially in preclinical models-we can quantitatively measure drug distribution within tumors, correlating it with pharmacological treatments intended to modify it. We can also study the local effects of the drug in the tissue, and their effects in relation to histology. This review focuses on the main results in the field of drug MSI in clinical pharmacology, looking at the literature on the distribution of drugs in human tissues, and also the first preclinical evidence of drug intratissue effects. The main instrumental techniques are discussed, looking at the different instrumentation, sample preparation protocols, and raw data management employed to obtain the sensitivity required for these studies. Finally, we review the applications that describe in situ metabolic events and pathways induced by the drug, in animal models, showing that MSI makes it possible to study effects that go beyond the simple concentration of the drug, maintaining the space dimension. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.
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Affiliation(s)
- Enrico Davoli
- Laboratory of Mass Spectrometry, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Massimo Zucchetti
- Laboratory of Antitumoral Pharmacology, Department of Oncology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Cristina Matteo
- Laboratory of Antitumoral Pharmacology, Department of Oncology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Paolo Ubezio
- Laboratory of Antitumoral Pharmacology, Department of Oncology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Maurizio D'Incalci
- Laboratory of Antitumoral Pharmacology, Department of Oncology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Lavinia Morosi
- Laboratory of Antitumoral Pharmacology, Department of Oncology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
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He Q, Sun C, Liu J, Pan Y. MALDI-MSI analysis of cancer drugs: Significance, advances, and applications. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2021.116183] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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Morosi L, Matteo C, Ceruti T, Giordano S, Ponzo M, Frapolli R, Zucchetti M, Davoli E, D'Incalci M, Ubezio P. Quantitative determination of niraparib and olaparib tumor distribution by mass spectrometry imaging. Int J Biol Sci 2020; 16:1363-1375. [PMID: 32210725 PMCID: PMC7085221 DOI: 10.7150/ijbs.41395] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2019] [Accepted: 01/18/2020] [Indexed: 12/15/2022] Open
Abstract
Rationale: Optimal intratumor distribution of an anticancer drug is fundamental to reach an active concentration in neoplastic cells, ensuring the therapeutic effect. Determination of drug concentration in tumor homogenates by LC-MS/MS gives important information about this issue but the spatial information gets lost. Targeted mass spectrometry imaging (MSI) has great potential to visualize drug distribution in the different areas of tumor sections, with good spatial resolution and superior specificity. MSI is rapidly evolving as a quantitative technique to measure the absolute drug concentration in each single pixel. Methods: Different inorganic nanoparticles were tested as matrices to visualize the PARP inhibitors (PARPi) niraparib and olaparib. Normalization by deuterated internal standard and a custom preprocessing pipeline were applied to achieve a reliable single pixel quantification of the two drugs in human ovarian tumors from treated mice. Results: A quantitative method to visualize niraparib and olaparib in tumor tissue of treated mice was set up and validated regarding precision, accuracy, linearity, repeatability and limit of detection. The different tumor penetration of the two drugs was visualized by MSI and confirmed by LC-MS/MS, indicating the homogeneous distribution and higher tumor exposure reached by niraparib compared to olaparib. On the other hand, niraparib distribution was heterogeneous in an ovarian tumor model overexpressing the multidrug resistance protein P-gp, a possible cause of resistance to PARPi. Conclusions: The current work highlights for the first time quantitative distribution of PAPRi in tumor tissue. The different tumor distribution of niraparib and olaparib could have important clinical implications. These data confirm the validity of MSI for spatial quantitative measurement of drug distribution providing fundamental information for pharmacokinetic studies, drug discovery and the study of resistance mechanisms.
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Affiliation(s)
- Lavinia Morosi
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology
| | - Cristina Matteo
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology
| | - Tommaso Ceruti
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology
| | - Silvia Giordano
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Laboratory of Mass Spectrometry
| | - Marianna Ponzo
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology
| | - Roberta Frapolli
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology
| | - Massimo Zucchetti
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology
| | - Enrico Davoli
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Laboratory of Mass Spectrometry
| | - Maurizio D'Incalci
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology
| | - Paolo Ubezio
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology
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Zhang J, Du Q, Song X, Gao S, Pang X, Li Y, Zhang R, Abliz Z, He J. Evaluation of the tumor-targeting efficiency and intratumor heterogeneity of anticancer drugs using quantitative mass spectrometry imaging. Theranostics 2020; 10:2621-2630. [PMID: 32194824 PMCID: PMC7052894 DOI: 10.7150/thno.41763] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2019] [Accepted: 01/01/2020] [Indexed: 12/24/2022] Open
Abstract
The development of improved or targeted drugs that discriminate between normal and tumor tissues is the key therapeutic issue in cancer research. However, the development of an analytical method with a high accuracy and sensitivity to achieve quantitative assessment of the tumor targeting of anticancer drugs and even intratumor heterogeneous distribution of these drugs at the early stages of drug research and development is a major challenge. Mass spectrometry imaging is a label-free molecular imaging technique that provides spatial-temporal information on the distribution of drugs and metabolites in organisms, and its application in the field of pharmaceutical development is rapidly increasing. Methods: The study presented here accurately quantified the distribution of paclitaxel (PTX) and its prodrug (PTX-R) in whole-body animal sections based on the virtual calibration quantitative mass spectrometry imaging (VC-QMSI) method, which is label-free and does not require internal standards, and then applied this technique to evaluate the tumor targeting efficiency in three treatment groups-the PTX-injection treatment group, PTX-liposome treatment group and PTX-R treatment group-in nude mice bearing subcutaneous A549 xenograft tumors. Results: These results indicated that PTX was widely distributed in multiple organs throughout the dosed body in the PTX-injection group and the PTX-liposome group. Notably, in the PTX-R group, both the prodrug and metabolized PTX were mainly distributed in the tumor tissue, and this group showed a significant difference compared with the PTX-liposome group, the relative targeting efficiency of PTX-R group was increased approximately 50-fold, leading to substantially decreased systemic toxicities. In addition, PTX-R showed a significant and specific accumulation in the poorly differentiated intratumor area and necrotic area. Conclusion: This method was demonstrated to be a reliable, feasible and easy-to-implement strategy to quantitatively map the absorption, distribution, metabolism and excretion (ADME) of a drug in the whole-body and tissue microregions and could therefore evaluate the tumor-targeting efficiency of anticancer drugs to predict drug efficacy and safety and provide key insights into drug disposition and mechanisms of action and resistance. Thus, this strategy could significantly facilitate the design and optimization of drugs at the early stage of drug research and development.
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Affiliation(s)
- Jin Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Qianqian Du
- Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Xiaowei Song
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Shanshan Gao
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Xuechao Pang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Yan Li
- Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Ruiping Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Zeper Abliz
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
- Center for Imaging and Systems Biology, Minzu University of China, Beijing, 100081, China
| | - Jiuming He
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
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Pérez-Guaita D, Quintás G, Kuligowski J. Discriminant analysis and feature selection in mass spectrometry imaging using constrained repeated random sampling - Cross validation (CORRS-CV). Anal Chim Acta 2019; 1097:30-36. [PMID: 31910967 DOI: 10.1016/j.aca.2019.10.039] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 10/16/2019] [Accepted: 10/18/2019] [Indexed: 12/20/2022]
Abstract
The identification of biomarkers through Mass spectrometry imaging (MSI) is gaining popularity in the clinical field. However, considering the complexity of spectral and spatial variables faced, data mining of the hyperspectral images can be troublesome. The discovery of markers generally depends on the creation of classification models which should be validated to ensure the statistical significance of the discriminants m/z detected. Internal validation using resampling methods such as cross validation (CV) are widely used for model selection, the estimation of its generalization performance and biomarker discovery when sample sizes are limited and an independent test set is not available. Here, we introduce for first time the use of Constrained Repeated Random Subsampling CV (CORRS-CV) on multi-images for the validation of classification models on MSI. Although several aspects must be taken into account (e.g. image size, CORRS-CV∂value, the similarity across spatially close pixels, the total computation time), CORRS-CV provides more accurate estimates of the model performance than k-fold CV using of biological replicates to define the data split when the number of biological replicates is scarce and holding images back for testing is a waste of valuable information. Besides, the combined use of CORRS-CV and rank products increases the robustness of the selection of discriminant features as candidate biomarkers which is an important issue due to the increased biological, environmental and technical variabilities when analysing multiple images, especially from human tissues collected in clinical studies.
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Affiliation(s)
| | - Guillermo Quintás
- Health & Biomedicine, LEITAT Technological Center, Barcelona, Spain; Unidad Analítica, Health Research Institute Hospital La Fe, Valencia, Spain.
| | - Julia Kuligowski
- Neonatal Research Unit, Health Research Institute Hospital La Fe, Valencia, Spain
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