1
|
Borau C, Wertheim KY, Hervas-Raluy S, Sainz-DeMena D, Walker D, Chisholm R, Richmond P, Varella V, Viceconti M, Montero A, Gregori-Puigjané E, Mestres J, Kasztelnik M, García-Aznar JM. A multiscale orchestrated computational framework to reveal emergent phenomena in neuroblastoma. Comput Methods Programs Biomed 2023; 241:107742. [PMID: 37572512 DOI: 10.1016/j.cmpb.2023.107742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 07/19/2023] [Accepted: 07/31/2023] [Indexed: 08/14/2023]
Abstract
Neuroblastoma is a complex and aggressive type of cancer that affects children. Current treatments involve a combination of surgery, chemotherapy, radiotherapy, and stem cell transplantation. However, treatment outcomes vary due to the heterogeneous nature of the disease. Computational models have been used to analyse data, simulate biological processes, and predict disease progression and treatment outcomes. While continuum cancer models capture the overall behaviour of tumours, and agent-based models represent the complex behaviour of individual cells, multiscale models represent interactions at different organisational levels, providing a more comprehensive understanding of the system. In 2018, the PRIMAGE consortium was formed to build a cloud-based decision support system for neuroblastoma, including a multi-scale model for patient-specific simulations of disease progression. In this work we have developed this multi-scale model that includes data such as patient's tumour geometry, cellularity, vascularization, genetics and type of chemotherapy treatment, and integrated it into an online platform that runs the simulations on a high-performance computation cluster using Onedata and Kubernetes technologies. This infrastructure will allow clinicians to optimise treatment regimens and reduce the number of costly and time-consuming clinical trials. This manuscript outlines the challenging framework's model architecture, data workflow, hypothesis, and resources employed in its development.
Collapse
Affiliation(s)
- C Borau
- Multiscale in Mechanical and Biological Engineering (M2BE), Aragon Institute of Engineering Research (I3A), Mechanical Engineering Department, University of Zaragoza, Zaragoza, Spain.
| | - K Y Wertheim
- Department of Computer Science and InsigneoInstitute for In Silico Medicine, University of Sheffield, Sheffield, United Kingdom; Centre of Excellence for Data Science, Artificial Intelligence and Modelling and School of Computer Science, University of Hull, Kingston upon Hull, United Kingdom
| | - S Hervas-Raluy
- Multiscale in Mechanical and Biological Engineering (M2BE), Aragon Institute of Engineering Research (I3A), Mechanical Engineering Department, University of Zaragoza, Zaragoza, Spain
| | - D Sainz-DeMena
- Multiscale in Mechanical and Biological Engineering (M2BE), Aragon Institute of Engineering Research (I3A), Mechanical Engineering Department, University of Zaragoza, Zaragoza, Spain
| | - D Walker
- Department of Computer Science and InsigneoInstitute for In Silico Medicine, University of Sheffield, Sheffield, United Kingdom
| | - R Chisholm
- Department of Computer Science and InsigneoInstitute for In Silico Medicine, University of Sheffield, Sheffield, United Kingdom
| | - P Richmond
- Department of Computer Science and InsigneoInstitute for In Silico Medicine, University of Sheffield, Sheffield, United Kingdom
| | - V Varella
- Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Italy; Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - M Viceconti
- Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Italy; Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - A Montero
- Chemotargets SL, Baldiri Reixac 4, Parc Cientific de Barcelona (PCB), Barcelona, Spain
| | - E Gregori-Puigjané
- Chemotargets SL, Baldiri Reixac 4, Parc Cientific de Barcelona (PCB), Barcelona, Spain
| | - J Mestres
- Chemotargets SL, Baldiri Reixac 4, Parc Cientific de Barcelona (PCB), Barcelona, Spain
| | - M Kasztelnik
- ACC Cyfronet, AGH University of Science and Technology, Kraków, Poland
| | - J M García-Aznar
- Multiscale in Mechanical and Biological Engineering (M2BE), Aragon Institute of Engineering Research (I3A), Mechanical Engineering Department, University of Zaragoza, Zaragoza, Spain
| |
Collapse
|
2
|
Bubak M, Czechowicz K, Gubała T, Hose DR, Kasztelnik M, Malawski M, Meizner J, Nowakowski P, Wood S. The EurValve model execution environment. Interface Focus 2021; 11:20200006. [PMID: 33343876 DOI: 10.1098/rsfs.2020.0006] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/23/2020] [Indexed: 01/14/2023] Open
Abstract
The goal of this paper is to present a dedicated high-performance computing (HPC) infrastructure which is used in the development of a so-called reduced-order model (ROM) for simulating the outcomes of interventional procedures which are contemplated in the treatment of valvular heart conditions. Following a brief introduction to the problem, the paper presents the design of a model execution environment, in which representative cases can be simulated and the parameters of the ROM fine-tuned to enable subsequent deployment of a decision support system without further need for HPC. The presentation of the system is followed by information concerning its use in processing specific patient cases in the context of the EurValve international collaboration.
Collapse
Affiliation(s)
- M Bubak
- Department of Computer Science, AGH University of Science and Technology, Kraków, Poland.,ACC Cyfronet AGH University of Science and Technology, Kraków, Poland.,Sano Centre for Computational Medicine, Kraków, Poland
| | - K Czechowicz
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - T Gubała
- ACC Cyfronet AGH University of Science and Technology, Kraków, Poland.,Sano Centre for Computational Medicine, Kraków, Poland
| | - D R Hose
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - M Kasztelnik
- ACC Cyfronet AGH University of Science and Technology, Kraków, Poland.,Sano Centre for Computational Medicine, Kraków, Poland
| | - M Malawski
- Department of Computer Science, AGH University of Science and Technology, Kraków, Poland.,ACC Cyfronet AGH University of Science and Technology, Kraków, Poland.,Sano Centre for Computational Medicine, Kraków, Poland
| | - J Meizner
- ACC Cyfronet AGH University of Science and Technology, Kraków, Poland.,Sano Centre for Computational Medicine, Kraków, Poland
| | - P Nowakowski
- ACC Cyfronet AGH University of Science and Technology, Kraków, Poland.,Sano Centre for Computational Medicine, Kraków, Poland
| | - S Wood
- Medical Physics and Clinical Engineering, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| |
Collapse
|
3
|
Ignacak A, Kasztelnik M, Sliwa T, Korbut RA, Rajda K, Guzik TJ. Prolactin--not only lactotrophin. A "new" view of the "old" hormone. J Physiol Pharmacol 2012; 63:435-443. [PMID: 23211297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Received: 12/13/2010] [Accepted: 09/18/2012] [Indexed: 06/01/2023]
Abstract
Prolactin (PRL) is a hormone mainly secreted by the anterior pituitary. Recent studies have shown that it may also be produced by many extrapituitary cells. The PRL gene expression is controlled by two independent promoter regions, which may be differentially regulated in the pituitary and extrapituitary organs. Proteolytic modifications of PRL generate variants of the hormone. A16 kDa PRL fragment, acting through a specific receptor, has both an antiangiogenic activity as well as an inhibitory effect on tumor growth. Stimulation of the PRL receptor involves many signal transduction pathways, for example JAK2/STAT, MAPK, c-src and Fyn kinase cascade, and these pathways may vary in different tissues. PRL synthesis and secretion is mainly regulated by the inhibitory influence of dopamine but other hormones are also involved in these mechanisms. The essential biological action of PRL is the stimulation of lactogenesis and galactopoesis. Apart from its classical functions, PRL affects other aspects of human body function including osmoregulation, metabolism and regulation of the immune and the central nervous system. Hyperprolactinemia is a common syndrome affecting both men and women. It is manifested by the presence of galactorrhoea and through the symptoms of hypogonadotrophic hypogonadism. Following on from the fact that PRL has so many pleiotropic tissue specific effects it is not surprising to learn that hyperprolactinaemia is a systemic condition which may predispose to numerous cardiovascular and immune-mediated reactions. The exact effects of PRL on both immune and cardiovascular systems are being currently unraveled and may lead to the introduction of novel therapeutic approaches in the future.
Collapse
Affiliation(s)
- A Ignacak
- Department of Internal and Agricultural Medicine and Institute of Pharmacology, Jagiellonian University School of Medicine, Cracow, Poland.
| | | | | | | | | | | |
Collapse
|