Aging, Inflammation, and Comorbidity in Cancers—A General In Silico Study Exemplified by Myeloproliferative Malignancies

(1) Background: We consider dormant, pre-cancerous states prevented from developing into cancer by the immune system. Inflammatory morbidity may compromise the immune system and cause the pre-cancer to escape into an actual cancerous development. The immune deficiency described is general, but the r...

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Bibliographic Details
Published in:Cancers 2023-09, Vol.15 (19), p.4806
Main Authors: Ottesen, Johnny T, Andersen, Morten
Format: Article
Language:English
Subjects:
Aging
Analysis
Blood
Cancer
Cancer patients
Cardiovascular disease
Comorbidity
Competition
COVID-19
Cytokines
Development and progression
Disease susceptibility
Epidemiology
Health aspects
Hypotheses
Immune response
Immune system
Immunodeficiency
Infections
Inflammation
Inflammatory diseases
Malignancy
Mathematical models
Morbidity
Mutation
Oncology, Experimental
Ordinary differential equations
Pathogens
Patients
Physiological aspects
Prevention
Stem cells
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Summary:(1) Background: We consider dormant, pre-cancerous states prevented from developing into cancer by the immune system. Inflammatory morbidity may compromise the immune system and cause the pre-cancer to escape into an actual cancerous development. The immune deficiency described is general, but the results may vary across specific cancers due to different variances (2) Methods: We formulate a general conceptual model to perform rigorous in silico consequence analysis. Relevant existing data for myeloproliferative malignancies from the literature are used to calibrate the in silico computations. (3) Results and conclusions: The hypothesis suggests a common physiological origin for many clinical and epidemiological observations in relation to cancers in general. Examples are the observed age-dependent prevalence for hematopoietic cancers, a general mechanism-based explanation for why the risk of cancer increases with age, and how somatic mutations in general, and specifically seen in screenings of citizens, sometimes are non-increased or even decrease when followed over time. The conceptual model is used to characterize different groups of citizens and patients, describing different treatment responses and development scenarios.
ISSN:2072-6694
2072-6694
DOI:10.3390/cancers15194806