Cancer modeling: From mechanistic to data-driven approaches, and from fundamental insights to clinical applications

https://doi.org/10.1016/j.jocs.2020.101198Get rights and content
Under a Creative Commons license
open access

Highlights

  • This paper aims at reviewing the published literature about cancer modeling and mathematical oncology.

  • In silico contributions to basic cancer science are discussed, using the hallmarks of cancer as a guidance.

  • The mathematical models developed specifically for clinical applications are discussed.

  • Clarifications about the existing guidelines for the use of in silico modeling in clinical practice are provided.

Abstract

Cancer is still one of the major causes of death worldwide. Even if its comprehension is improving continuously, the complexity and heterogeneity of this group of diseases invariably make some cancer cases incurable and lethal. By focusing only on one or two cancerous molecular species simultaneously, traditional in vitro and in vivo approaches do not provide a global view on this disease and are sometimes unable to generate significant insights about cancer. In silico techniques are increasingly used in the oncology domain for their remarkable integration capacity. In basic cancer research, a vast number of mathematical and computational models has been implemented in the past decades, allowing for a better understanding of these complex diseases, generating new hypotheses and predictions, and guiding scientists towards the most impactful experiments. Although clinical uptake of such in silico approaches is still limited, some treatment strategies are currently under investigation in phase I or II clinical trials. Besides being responsible for new therapeutic ideas, in silico models could play a significant role in optimizing clinical trial design and patient stratification. This review provides a non-exhaustive overview of models according to their intrinsic features. In silico contributions to basic cancer science are discussed, using the hallmarks of cancer as a guidance. Subsequently, in silico cancer models, that are a part of currently ongoing clinical trials, are addressed. In a forward-looking section, issues such as the need for adequate regulatory processes related to in silico models, and advances in model technologies are discussed.

Keywords

Mathematical oncology
In silico methods
Cancer biology
Computational modeling
In silico clinical trials

Cited by (0)

Sophie Bekisz is a Ph.D. student at the University of Liège, graduated as Biomedical Engineer in 2018. She is a FRIA grantee of the Fonds de la Recherche Scientifique – FNRS. Her research focus is on the modelling of the process of lymphangiogenesis with mathematical and computational tools. Classical biomedical approaches using in vitro and in vivo models are combined with engineering approaches using in silico (computer) models. This multidisciplinary character enables to better understand the fundamental mechanisms regulating lymphangiogenesis.

Liesbet Geris is Collen-Francqui Research Professor in Biomechanics and Computational Tissue Engineering at the university of Liège and KU Leuven in Belgium. Her research focusses on the multi-scale and multi-physics modeling of biological processes. Together with her team and their clinical and industrial collaborators, she uses these models to investigate the etiology of non-healing fractures, to design in silico potential cell-based treatment strategies and to optimize manufacturing processes of these tissue engineering constructs. Liesbet is scientific coordinator of the Prometheus platform for Skeletal Tissue Engineering (50+ researchers). She has edited several books on computational modeling and tissue engineering. She has received 2 prestigious ERC grants (starting in 2011 and consolidator in 2017) to finance her research and has received a number of young investigator and research awards from the in silico and regenerative medicine communities. She is a former member and chair of the Young Academy of Belgium (Flanders) and member of the strategic alliance committee of the Tissue Engineering and Regenerative Medicine Society. She is the current executive director of the Virtual Physiological Human Institute and in that capacity she advocates the use of in silico modeling in healthcare through liaising with the clinical community, the European Commission and Parliament, regulatory agencies (EMA, FDA) and various other stakeholders. Besides her research work, she is often invited to give public lectures on the challenges of interdisciplinary in research, women in academia and digital healthcare.