Dataset Information

Stochastic models of Mendelian and reverse transcriptional inheritance in state-structured cancer populations.

ABSTRACT: Recent evidence suggests that a polyaneuploid cancer cell (PACC) state may play a key role in the adaptation of cancer cells to stressful environments and in promoting therapeutic resistance. The PACC state allows cancer cells to pause cell division and to avoid DNA damage and programmed cell death. Transition to the PACC state may also lead to an increase in the cancer cell's ability to generate heritable variation (evolvability). One way this can occur is through evolutionary triage. Under this framework, cells gradually gain resistance by scaling hills on a fitness landscape through a process of mutation and selection. Another way this can happen is through self-genetic modification whereby cells in the PACC state find a viable solution to the stressor and then undergo depolyploidization, passing it on to their heritably resistant progeny. Here, we develop a stochastic model to simulate both of these evolutionary frameworks. We examine the impact of treatment dosage and extent of self-genetic modification on eco-evolutionary dynamics of cancer cells with aneuploid and PACC states. We find that under low doses of therapy, evolutionary triage performs better whereas under high doses of therapy, self-genetic modification is favored. This study generates predictions for teasing apart these biological hypotheses, examines the implications of each in the context of cancer, and provides a modeling framework to compare Mendelian and non-traditional forms of inheritance.

SUBMITTER: Bukkuri A

PROVIDER: S-EPMC9338039 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Stochastic models of Mendelian and reverse transcriptional inheritance in state-structured cancer populations.

Bukkuri Anuraag A Pienta Kenneth J KJ Austin Robert H RH Hammarlund Emma U EU Amend Sarah R SR Brown Joel S JS

Scientific reports 20220729 1

Recent evidence suggests that a polyaneuploid cancer cell (PACC) state may play a key role in the adaptation of cancer cells to stressful environments and in promoting therapeutic resistance. The PACC state allows cancer cells to pause cell division and to avoid DNA damage and programmed cell death. Transition to the PACC state may also lead to an increase in the cancer cell's ability to generate heritable variation (evolvability). One way this can occur is through evolutionary triage. Under thi ...[more]

PMID: 35906318

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Project description:Parkinson's disease is a common, progressive neurodegenerative disorder, affecting 3% of those older than 75 years of age. Clinically, Parkinson's disease (PD) is associated with resting tremor, postural instability, rigidity, bradykinesia, and a good response to levodopa therapy. Over the last 15 years, numerous studies have confirmed that genetic factors contribute to the complex pathogenesis of PD. Highly penetrant mutations producing rare, monogenic forms of the disease have been discovered in singular genes such as SNCA, Parkin, DJ-1, PINK 1, LRRK2, and VPS35. Unique variants with incomplete penetrance in LRRK2 and GBA have been shown to be strong risk factors for PD in certain populations. Additionally, over 20 common variants with small effect sizes are now recognized to modulate the risk for PD. Investigating Mendelian forms of PD has provided precious insight into the pathophysiology that underlies the more common idiopathic form of disease; however, no treatment methodologies have developed. Furthermore, for identified common risk alleles, the functional basis underlying risk principally remains unknown. The challenge over the next decade will be to strengthen the findings delivered through genetic discovery by assessing the direct, biological consequences of risk variants in tandem with additional high-content, integrated datasets. This review discusses monogenic risk factors and mechanisms of Mendelian inheritance of Parkinson disease. Highly penetrant mutations in SNCA, Parkin, DJ-1, PINK 1, LRRK2 and VPS35 produce rare, monogenic forms of the disease, while unique variants within LRRK2 and GBA show incomplete penetrance and are strong risk factors for PD. Additionally, over 20 common variants with small effect sizes modulate disease risk. The challenge over the next decade is to strengthen genetic findings by assessing direct, biological consequences of risk variants in tandem with high-content, integrated datasets. This article is part of a special issue on Parkinson disease.

Dataset Information

Stochastic models of Mendelian and reverse transcriptional inheritance in state-structured cancer populations.

Publications

Stochastic models of Mendelian and reverse transcriptional inheritance in state-structured cancer populations.

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