Autocrine signaling can explain the emergence of Allee effects in cancer cell populations

• Published in: PLoS computational biology 2022-03, Vol.18 (3), p.e1009844-e1009844
• Main Authors: Gerlee, Philip, Altrock, Philipp M, Malik, Adam, Krona, Cecilia, Nelander, Sven
• Format: Article
• Language: English
• Subjects: Apoptosis; Autocrine Communication; Autocrine mechanisms; Autocrine signalling; Biochemistry & Molecular Biology; Biology and Life Sciences; Brain cancer; Brain research; Brain tumors; Cancer; Cancer cells; Cell and Molecular Biology; Cell death; Cell division; Cell growth; Cell size; Cell- och molekylärbiologi; Cellular signal transduction; Dispersal; dynamics; Ecological effects; Ecology; Ecology and Environmental Sciences; evolutionary; Feedback; Funding; Growth factors; Growth rate; heterogeneity; Humans; invasion; Mathematical & Computational Biology; Mathematical models; Medicine and Health Sciences; Models, Biological; Neoplasms; Oncology, Experimental; Partial differential equations; Physiological aspects; Population Density; Population Dynamics; proliferation; Signaling; Tumor cell lines; Tumors
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1009844

In many human cancers, the rate of cell growth depends crucially on the size of the tumor cell population. Low, zero, or negative growth at low population densities is known as the Allee effect; this effect has been studied extensively in ecology, but so far lacks a good explanation in the cancer setting. Here, we formulate and analyze an individual-based model of cancer, in which cell division rates are increased by the local concentration of an autocrine growth factor produced by the cancer cells themselves. We show, analytically and by simulation, that autocrine signaling suffices to cause both strong and weak Allee effects. Whether low cell densities lead to negative (strong effect) or reduced (weak effect) growth rate depends directly on the ratio of cell death to proliferation, and indirectly on cellular dispersal. Our model is consistent with experimental observations from three patient-derived brain tumor cell lines grown at different densities. We propose that further studying and quantifying population-wide feedback, impacting cell growth, will be central for advancing our understanding of cancer dynamics and treatment, potentially exploiting Allee effects for therapy.