Models in Translational Oncology: A Public Resource Database for Preclinical Cancer Research

Abstract

The devastating diseases of human cancer are mimicked in basic and translational cancer research by a steadily increasing number of tumor models, a situation requiring a platform with standardized reports to share model data. Models in Translational Oncology (MiTO) database was developed as a unique Web platform aiming for a comprehensive overview of preclinical models covering genetically engineered organisms, models of transplantation, chemical/physical induction, or spontaneous development, reviewed here. MiTO serves data entry for metastasis profiles and interventions. Moreover, cell lines and animal lines including tool strains can be recorded. Hyperlinks for connection with other databases and file uploads as supplementary information are supported. Several communication tools are offered to facilitate exchange of information. Notably, intellectual property can be protected prior to publication by inventordefined accessibility of any given model. Data recall is via a highly configurable keyword search. Genome editing is expected to result in changes of the spectrum of model organisms, a reason to open MiTO for species-independent data. Registered users may deposit own model fact sheets (FS). MiTO experts check them for plausibility. Independently, manually curated FS are provided to principle investigators for revision and publication. Importantly, noneditable versions of reviewed FS can be cited in peer-reviewed journals.

Consensus guidelines for the definition, detection and interpretation of immunogenic cell death

“…304 Current efforts to circumvent, at least in part, these issues involve the use of orthotopic models (which offer improved microenvironmental features), transgenedriven models (which may offer a superior view on early oncogenesis) and carcinogen-driven models (which have superior heterogeneity). [305][306][307] However, not all of these systems are compatible with vaccination and/or abscopal assays, implying that ICD induction can only be imprecisely addressed by complementing in vitro observations with therapeutic efficacy in immunocompetent vs immunodeficient animals. Moreover, considerable efforts are being devoted to the development of humanized mice, which ultimately may enable the assessment of ICD induction in vivo with human cancer cells.…”

Modeling Endometrial Cancer: Past, Present, and Future

“…The exploitation of effective precision medicine platforms using different techniques and models, as has been shown for breast cancer and melanoma [122,130], is where the future of translational cancer research should point to for EC as well. In this view, initiatives like the recently established Models in Translational Oncology (MiTO) database will help to gather information about available models and help researchers in choosing the correct model to address a specific research question [131]. …”

Genetic Ancestry Analysis Reveals Misclassification of Commonly Used Cancer Cell Lines

“…In cancer research, biological model systems are used to understand the contribution of cellular mechanisms to tissue function, disease pathogenesis, and drug efficacy (1)(2)(3)(4). Human cell lines representing various tissues in normal and disease states are vital tools necessary to establish preclinical research models.…”