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Capasso M, Brignole C, Lasorsa VA, Bensa V, Cantalupo S, Sebastiani E, Quattrone A, Ciampi E, Avitabile M, Sementa AR, Mazzocco K, Cafferata B, Gaggero G, Vellone VG, Cilli M, Calarco E, Giusto E, Perri P, Aveic S, Fruci D, Tondo A, Luksch R, Mura R, Rabusin M, De Leonardis F, Cellini M, Coccia P, Iolascon A, Corrias MV, Conte M, Garaventa A, Amoroso L, Ponzoni M, Pastorino F. From the identification of actionable molecular targets to the generation of faithful neuroblastoma patient-derived preclinical models. J Transl Med 2024; 22:151. [PMID: 38351008 PMCID: PMC10863144 DOI: 10.1186/s12967-024-04954-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 02/03/2024] [Indexed: 02/16/2024] Open
Abstract
BACKGROUND Neuroblastoma (NB) represents the most frequent and aggressive form of extracranial solid tumor of infants. Although the overall survival of patients with NB has improved in the last years, more than 50% of high-risk patients still undergo a relapse. Thus, in the era of precision/personalized medicine, the need for high-risk NB patient-specific therapies is urgent. METHODS Within the PeRsonalizEd Medicine (PREME) program, patient-derived NB tumors and bone marrow (BM)-infiltrating NB cells, derived from either iliac crests or tumor bone lesions, underwent to histological and to flow cytometry immunophenotyping, respectively. BM samples containing a NB cells infiltration from 1 to 50 percent, underwent to a subsequent NB cells enrichment using immune-magnetic manipulation. Then, NB samples were used for the identification of actionable targets and for the generation of 3D/tumor-spheres and Patient-Derived Xenografts (PDX) and Cell PDX (CPDX) preclinical models. RESULTS Eighty-four percent of NB-patients showed potentially therapeutically targetable somatic alterations (including point mutations, copy number variations and mRNA over-expression). Sixty-six percent of samples showed alterations, graded as "very high priority", that are validated to be directly targetable by an approved drug or an investigational agent. A molecular targeted therapy was applied for four patients, while a genetic counseling was suggested to two patients having one pathogenic germline variant in known cancer predisposition genes. Out of eleven samples implanted in mice, five gave rise to (C)PDX, all preserved in a local PDX Bio-bank. Interestingly, comparing all molecular alterations and histological and immunophenotypic features among the original patient's tumors and PDX/CPDX up to second generation, a high grade of similarity was observed. Notably, also 3D models conserved immunophenotypic features and molecular alterations of the original tumors. CONCLUSIONS PREME confirms the possibility of identifying targetable genomic alterations in NB, indeed, a molecular targeted therapy was applied to four NB patients. PREME paves the way to the creation of clinically relevant repositories of faithful patient-derived (C)PDX and 3D models, on which testing precision, NB standard-of-care and experimental medicines.
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Affiliation(s)
- Mario Capasso
- Department of Medical Biotechnology, University of Naples Federico II, 80138, Naples, Italy
- CEINGE Advanced Biotecnology, 80138, Naples, Italy
| | - Chiara Brignole
- Laboratory of Experimental Therapies in Oncology, IRCCS Istituto Giannina Gaslini, Via G. Gaslini 5, 16147, Genoa, Italy
| | | | - Veronica Bensa
- Laboratory of Experimental Therapies in Oncology, IRCCS Istituto Giannina Gaslini, Via G. Gaslini 5, 16147, Genoa, Italy
| | - Sueva Cantalupo
- Department of Medical Biotechnology, University of Naples Federico II, 80138, Naples, Italy
- CEINGE Advanced Biotecnology, 80138, Naples, Italy
| | | | | | - Eleonora Ciampi
- Laboratory of Experimental Therapies in Oncology, IRCCS Istituto Giannina Gaslini, Via G. Gaslini 5, 16147, Genoa, Italy
| | - Marianna Avitabile
- Department of Medical Biotechnology, University of Naples Federico II, 80138, Naples, Italy
- CEINGE Advanced Biotecnology, 80138, Naples, Italy
| | - Angela R Sementa
- Pathological Anatomy, IRCCS Istituto Giannina Gaslini, 16147, Genoa, Italy
| | - Katia Mazzocco
- Pathological Anatomy, IRCCS Istituto Giannina Gaslini, 16147, Genoa, Italy
| | - Barbara Cafferata
- Pathological Anatomy, IRCCS Istituto Giannina Gaslini, 16147, Genoa, Italy
| | - Gabriele Gaggero
- Pathological Anatomy, IRCCS Istituto Giannina Gaslini, 16147, Genoa, Italy
| | - Valerio G Vellone
- Pathological Anatomy, IRCCS Istituto Giannina Gaslini, 16147, Genoa, Italy
| | - Michele Cilli
- Animal Facility, IRCCS Policlinico San Martino, 16100, Genoa, Italy
| | - Enzo Calarco
- Laboratory of Experimental Therapies in Oncology, IRCCS Istituto Giannina Gaslini, Via G. Gaslini 5, 16147, Genoa, Italy
| | - Elena Giusto
- Laboratory of Experimental Therapies in Oncology, IRCCS Istituto Giannina Gaslini, Via G. Gaslini 5, 16147, Genoa, Italy
| | - Patrizia Perri
- Laboratory of Experimental Therapies in Oncology, IRCCS Istituto Giannina Gaslini, Via G. Gaslini 5, 16147, Genoa, Italy
| | - Sanja Aveic
- Pediatric Research Institute Città Della Speranza, 35127, Padua, Italy
| | - Doriana Fruci
- Department of Emato-Oncology, Bambino Gesù Children's Hospital, 00146, -Rome, Italy
| | - Annalisa Tondo
- Department of Emato-Oncology, Anna Meyer Children's Hospital, 50139, Florence, Italy
| | - Roberto Luksch
- Emato-Oncology Unit, Fondazione IRCCS Istituto Nazionale Dei Tumori, 20133, Milan, Italy
| | - Rossella Mura
- Emato-Oncology Unit, Azienda Ospedaliera Brotzu, 09047, Cagliari, Italy
| | - Marco Rabusin
- Pediatric Department, Institute for Maternal and Child Health, IRCCS Burlo Garofolo, 34137, Trieste, Italy
| | | | - Monica Cellini
- Emato-Oncology Unit, University-Hospital Polyclinic of Modena, 41124, Modena, Italy
| | - Paola Coccia
- University-Hospital of Marche, Presidio Ospedaliero "G. Salesi", 60126, Ancona, Italy
| | - Achille Iolascon
- Department of Medical Biotechnology, University of Naples Federico II, 80138, Naples, Italy
- CEINGE Advanced Biotecnology, 80138, Naples, Italy
| | - Maria V Corrias
- Laboratory of Experimental Therapies in Oncology, IRCCS Istituto Giannina Gaslini, Via G. Gaslini 5, 16147, Genoa, Italy
| | - Massimo Conte
- Clinical Oncology Unit, IRCCS Istituto Giannina Gaslini, 16147, -Genoa, Italy
| | - Alberto Garaventa
- Clinical Oncology Unit, IRCCS Istituto Giannina Gaslini, 16147, -Genoa, Italy
| | - Loredana Amoroso
- Clinical Oncology Unit, IRCCS Istituto Giannina Gaslini, 16147, -Genoa, Italy
| | - Mirco Ponzoni
- Laboratory of Experimental Therapies in Oncology, IRCCS Istituto Giannina Gaslini, Via G. Gaslini 5, 16147, Genoa, Italy.
| | - Fabio Pastorino
- Laboratory of Experimental Therapies in Oncology, IRCCS Istituto Giannina Gaslini, Via G. Gaslini 5, 16147, Genoa, Italy
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Fazel M, Jazani S, Scipioni L, Vallmitjana A, Zhu S, Gratton E, Digman MA, Pressé S. Building Fluorescence Lifetime Maps Photon-by-Photon by Leveraging Spatial Correlations. ACS PHOTONICS 2023; 10:3558-3569. [PMID: 38406580 PMCID: PMC10890823 DOI: 10.1021/acsphotonics.3c00595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Fluorescence lifetime imaging microscopy (FLIM) has become a standard tool in the quantitative characterization of subcellular environments. However, quantitative FLIM analyses face several challenges. First, spatial correlations between pixels are often ignored as signal from individual pixels is analyzed independently thereby limiting spatial resolution. Second, existing methods deduce photon ratios instead of absolute lifetime maps. Next, the number of fluorophore species contributing to the signal is unknown, while excited state lifetimes with <1 ns difference are difficult to discriminate. Finally, existing analyses require high photon budgets and often cannot rigorously propagate experimental uncertainty into values over lifetime maps and number of species involved. To overcome all of these challenges simultaneously and self-consistently at once, we propose the first doubly nonparametric framework. That is, we learn the number of species (using Beta-Bernoulli process priors) and absolute maps of these fluorophore species (using Gaussian process priors) by leveraging information from pulses not leading to observed photon. We benchmark our framework using a broad range of synthetic and experimental data and demonstrate its robustness across a number of scenarios including cases where we recover lifetime differences between species as small as 0.3 ns with merely 1000 photons.
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Affiliation(s)
- Mohamadreza Fazel
- Center for Biological Physics and Department of Physics, Arizona State University, Tempe, Arizona 85287, United States
| | - Sina Jazani
- Center for Biological Physics and Department of Physics, Arizona State University, Tempe, Arizona 85287, United States
| | - Lorenzo Scipioni
- Department of Biomedical Engineering, University of California Irvine, Irvine, California 92697, United States; Laboratory of Fluorescence Dynamics, The Henry Samueli School of Engineering, University of California, Irvine, California 92697, United States
| | - Alexander Vallmitjana
- Department of Biomedical Engineering, University of California Irvine, Irvine, California 92697, United States; Laboratory of Fluorescence Dynamics, The Henry Samueli School of Engineering, University of California, Irvine, California 92697, United States
| | - Songning Zhu
- Department of Biomedical Engineering, University of California Irvine, Irvine, California 92697, United States; Laboratory of Fluorescence Dynamics, The Henry Samueli School of Engineering, University of California, Irvine, California 92697, United States
| | - Enrico Gratton
- Department of Biomedical Engineering, University of California Irvine, Irvine, California 92697, United States; Laboratory of Fluorescence Dynamics, The Henry Samueli School of Engineering, University of California, Irvine, California 92697, United States
| | - Michelle A Digman
- Department of Biomedical Engineering, University of California Irvine, Irvine, California 92697, United States; Laboratory of Fluorescence Dynamics, The Henry Samueli School of Engineering, University of California, Irvine, California 92697, United States
| | - Steve Pressé
- Center for Biological Physics and Department of Physics, Arizona State University, Tempe, Arizona 85287, United States; School of Molecular Science, Arizona State University, Tempe, Arizona 85287, United States
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Mahmoud A, Ganesh K. Mouse Models of Metastasis and Dormancy. Cold Spring Harb Perspect Med 2023:a041386. [PMID: 37696656 PMCID: PMC10925556 DOI: 10.1101/cshperspect.a041386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/13/2023]
Abstract
Metastasis is the ultimate and often lethal stage of cancer. Metastasis occurs in three phases that may vary across individuals: First, dissemination from the primary tumor. Second, tumor dormancy at the metastatic site where micrometastatic cancer cells remain quiescent or, in dynamic cycles of proliferation and elimination, remaining clinically undetectable. Finally, cancer cells are able to overcome microenvironmental constraints for outgrowth, or the formation of clinically detectable macrometastases that colonize distant organs and are largely incurable. A variety of approaches have been used to model metastasis to elucidate molecular mechanisms and identify putative therapeutic targets. In particular, metastatic dormancy has been challenging to model in vivo due to the sparse numbers of cancer cells in micrometastasis nodules and the long latency times required for tumor outgrowth. Here, we review state-of-the art genetically engineered mouse, syngeneic, and patient-derived xenograft approaches for modeling metastasis and dormancy. We describe the advantages and limitations of various metastasis models, novel findings enabled by such approaches, and highlight opportunities for future improvement.
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Affiliation(s)
- Ahmed Mahmoud
- Program in Pharmacology, Weill Cornell Graduate School of Medical Sciences, New York, New York 10065, USA
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA
| | - Karuna Ganesh
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA
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