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Sgarminato V, Madrid-Wolff J, Boniface A, Ciardelli G, Tonda-Turo C, Moser C. 3D in vitromodeling of the exocrine pancreatic unit using tomographic volumetric bioprinting. Biofabrication 2024; 16:045034. [PMID: 39121863 DOI: 10.1088/1758-5090/ad6d8d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Accepted: 08/09/2024] [Indexed: 08/12/2024]
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer, a leading cause of cancer-related deaths globally. Initial lesions of PDAC develop within the exocrine pancreas' functional units, with tumor progression driven by interactions between PDAC and stromal cells. Effective therapies require anatomically and functionally relevantin vitrohuman models of the pancreatic cancer microenvironment. We employed tomographic volumetric bioprinting, a novel biofabrication method, to create human fibroblast-laden constructs mimicking the tubuloacinar structures of the exocrine pancreas. Human pancreatic ductal epithelial (HPDE) cells overexpressing the KRAS oncogene (HPDE-KRAS) were seeded in the multiacinar cavity to replicate pathological tissue. HPDE cell growth and organization within the structure were assessed, demonstrating the formation of a thin epithelium covering the acini inner surfaces. Immunofluorescence assays showed significantly higher alpha smooth muscle actin (α-SMA) vs. F-actin expression in fibroblasts co-cultured with cancerous versus wild-type HPDE cells. Additionally,α-SMA expression increased over time and was higher in fibroblasts closer to HPDE cells. Elevated interleukin (IL)-6 levels were quantified in supernatants from co-cultures of stromal and HPDE-KRAS cells. These findings align with inflamed tumor-associated myofibroblast behavior, serving as relevant biomarkers to monitor early disease progression and target drug efficacy. To our knowledge, this is the first demonstration of a 3D bioprinted model of exocrine pancreas that recapitulates its true 3-dimensional microanatomy and shows tumor triggered inflammation.
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Affiliation(s)
- Viola Sgarminato
- Laboratory of Applied Photonics Devices, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
| | - Jorge Madrid-Wolff
- Laboratory of Applied Photonics Devices, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Antoine Boniface
- Laboratory of Applied Photonics Devices, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Gianluca Ciardelli
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
| | - Chiara Tonda-Turo
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
| | - Christophe Moser
- Laboratory of Applied Photonics Devices, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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Lorenzo G, Ahmed SR, Hormuth DA, Vaughn B, Kalpathy-Cramer J, Solorio L, Yankeelov TE, Gomez H. Patient-Specific, Mechanistic Models of Tumor Growth Incorporating Artificial Intelligence and Big Data. Annu Rev Biomed Eng 2024; 26:529-560. [PMID: 38594947 DOI: 10.1146/annurev-bioeng-081623-025834] [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] [Indexed: 04/11/2024]
Abstract
Despite the remarkable advances in cancer diagnosis, treatment, and management over the past decade, malignant tumors remain a major public health problem. Further progress in combating cancer may be enabled by personalizing the delivery of therapies according to the predicted response for each individual patient. The design of personalized therapies requires the integration of patient-specific information with an appropriate mathematical model of tumor response. A fundamental barrier to realizing this paradigm is the current lack of a rigorous yet practical mathematical theory of tumor initiation, development, invasion, and response to therapy. We begin this review with an overview of different approaches to modeling tumor growth and treatment, including mechanistic as well as data-driven models based on big data and artificial intelligence. We then present illustrative examples of mathematical models manifesting their utility and discuss the limitations of stand-alone mechanistic and data-driven models. We then discuss the potential of mechanistic models for not only predicting but also optimizing response to therapy on a patient-specific basis. We describe current efforts and future possibilities to integrate mechanistic and data-driven models. We conclude by proposing five fundamental challenges that must be addressed to fully realize personalized care for cancer patients driven by computational models.
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Affiliation(s)
- Guillermo Lorenzo
- Oden Institute for Computational Engineering and Sciences, University of Texas, Austin, Texas, USA
- Department of Civil Engineering and Architecture, University of Pavia, Pavia, Italy
| | - Syed Rakin Ahmed
- Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA
- Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Harvard Graduate Program in Biophysics, Harvard Medical School, Harvard University, Cambridge, Massachusetts, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - David A Hormuth
- Livestrong Cancer Institutes, University of Texas, Austin, Texas, USA
- Oden Institute for Computational Engineering and Sciences, University of Texas, Austin, Texas, USA
| | - Brenna Vaughn
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA;
| | | | - Luis Solorio
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA;
| | - Thomas E Yankeelov
- Department of Imaging Physics, MD Anderson Cancer Center, Houston, Texas, USA
- Department of Biomedical Engineering, Department of Oncology, and Department of Diagnostic Medicine, University of Texas, Austin, Texas, USA
- Livestrong Cancer Institutes, University of Texas, Austin, Texas, USA
- Oden Institute for Computational Engineering and Sciences, University of Texas, Austin, Texas, USA
| | - Hector Gomez
- School of Mechanical Engineering and Purdue Center for Cancer Research, Purdue University, West Lafayette, Indiana, USA
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA;
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da Silva L, Jiang J, Perkins C, Atanasova KR, Bray JK, Bulut G, Azevedo-Pouly A, Campbell-Thompson M, Yang X, Hakimjavadi H, Chamala S, Ratnayake R, Gharaibeh RZ, Li C, Luesch H, Schmittgen TD. Pharmacological inhibition and reversal of pancreatic acinar ductal metaplasia. Cell Death Discov 2022; 8:378. [PMID: 36055991 PMCID: PMC9440259 DOI: 10.1038/s41420-022-01165-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 08/04/2022] [Accepted: 08/11/2022] [Indexed: 01/04/2023] Open
Abstract
Pancreatic acinar cells display a remarkable degree of plasticity and can dedifferentiate into ductal-like progenitor cells by a process known as acinar ductal metaplasia (ADM). ADM is believed to be one of the earliest precursor lesions toward the development of pancreatic ductal adenocarcinoma and maintaining the pancreatic acinar cell phenotype suppresses tumor formation. The effects of a novel pStat3 inhibitor (LLL12B) and the histone deacetylase (HDAC) inhibitor trichostatin A (TSA) were investigated using 3-D cultures from p48Cre/+ and p48Cre/+LSL-KrasG12D/+ (KC) mice. LLL12B and TSA inhibited ADM in both KC and p48Cre/+ mouse pancreatic organoids. Furthermore, treatment with LLL12B or TSA on dedifferentiated acini from p48Cre/+ and KC mice that had undergone ADM produced morphologic and gene expression changes that suggest a reversal of ADM. Validation experiments using qRT-PCR (p48Cre/+ and KC) and RNA sequencing (KC) of the LLL12B and TSA treated cultures showed that the ADM reversal was more robust for the TSA treatments. Pathway analysis showed that TSA inhibited Spink1 and PI3K/AKT signaling during ADM reversal. The ability of TSA to reverse ADM was also observed in primary human acinar cultures. We report that pStat3 and HDAC inhibition can attenuate ADM in vitro and reverse ADM in the context of wild-type Kras. Our findings suggest that pharmacological inhibition or reversal of pancreatic ADM represents a potential therapeutic strategy for blocking aberrant ductal reprogramming of acinar cells.
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Affiliation(s)
- Lais da Silva
- Department of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Jinmai Jiang
- Department of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Corey Perkins
- Department of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Kalina Rosenova Atanasova
- Department of Medicinal Chemistry, College of Pharmacy, University of Florida, Gainesville, FL, USA
- Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL, USA
| | - Julie K Bray
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Gamze Bulut
- Department of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Ana Azevedo-Pouly
- Department of Surgery, University of Arkansas for Medical Sciences, University of Florida, Gainesville, FL, USA
| | - Martha Campbell-Thompson
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Xiaozhi Yang
- Department of Medicinal Chemistry, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Hesamedin Hakimjavadi
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Srikar Chamala
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Ranjala Ratnayake
- Department of Medicinal Chemistry, College of Pharmacy, University of Florida, Gainesville, FL, USA
- Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL, USA
| | - Raad Z Gharaibeh
- Department of Medicine, University of Florida, Gainesville, FL, USA
- Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL, USA
| | - Chenglong Li
- Department of Medicinal Chemistry, College of Pharmacy, University of Florida, Gainesville, FL, USA
- Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL, USA
| | - Hendrik Luesch
- Department of Medicinal Chemistry, College of Pharmacy, University of Florida, Gainesville, FL, USA
- Center for Natural Products, Drug Discovery and Development, University of Florida, Gainesville, FL, USA
| | - Thomas D Schmittgen
- Department of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, FL, USA.
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