A novel perspective suggesting high sustained energy expenditure may be net protective against cancer

Authors: Peter A Biro, Frédéric Thomas, Beata Ujvari, Christa Beckmann

Source: EVOLUTION MEDICINE AND PUBLIC HEALTH (JAN 2022)

Abstract

Energy expenditure (EE) is generally viewed as tumorigenic, due to production of reactive oxygen species (ROS) that can damage cells and DNA. On this basis, individuals within a species that sustain high EE should be more likely to develop cancer.

Here, we argue the opposite, that high EE may be net protective effect against cancer, despite high ROS production. This is possible because individuals that sustain high EE have a greater energetic capacity (=greater energy acquisition, expenditure and ability to up-regulate output), and can therefore allocate energy to multiple cancer-fighting mechanisms with minimal energetic trade-offs.

Our review finds that individuals sustaining high EE have greater antioxidant production, lower oxidative stress, greater immune function and lower cancer incidence. Our hypothesis and literature review suggest that EE may indeed be net protective against cancer, and that individual variation in energetic capacity may be a key mechanism to understand the highly individual nature of cancer risk in contemporary human populations and laboratory animals.

Season, weight, and age, but not transmissible cancer, affect tick loads in the endangered Tasmanian devil

Authors: Sophia Belkhir; Rodrigo Hamede; Frédéric Thomas; Beata Ujvari; Antoine M. Dujon

Source: INFECTION GENETICS AND EVOLUTION (JAN 2022)

Abstract

The Tasmanian devil (Sarcophilus harrisii) is a carnivorous marsupial threatened by a transmissible cancer, devil facial tumour disease (DFTD). While we have a good understanding of the effect of the transmissible cancer on its host, little information is available about its potential interactions with ectoparasites.

With this study, we aimed to determine the factors driving tick loads in a DFTD affected Tasmanian devil population, using long-term mark-recapture data. We investigated the effect of a range of life history traits (age, weight, sex, body condition) and of DFTD (time since DFTD arrival and presence of tumours) on the ectoparasitic tick load of the devils.

Mixed effect models revealed that tick load in Tasmanian devils was primarily driven by season, weight, body condition and age. Young devils had more ticks compared to older or healthier devils. The reduction in Tasmanian devil population size over the past 14 years at the studied site had little effect on tick infestation.

We also found that devils infected by DFTD had a similar tick load compared to those free of observable tumours, suggesting no interaction between the transmissible cancer and tick load. Our study highlights seasonality and life cycle as primary drivers of tick infestation in Tasmanian devils and the need for further investigations to integrate devil stress and immune dynamics with ectoparasite counts.

Transmissible cancer influences immune gene expression in an endangered marsupial, the Tasmanian devil (Sarcophilus harrisii)

Authors: Nynke Raven, Marcel Klaassen, Thomas Madsen, Frédéric Thomas, Rodrigo K. Hamede, Beata Ujvari

Source: Molecular Ecology (FEB 2022)

Abstract

Understanding the effects of wildlife diseases on populations requires insight into local environmental conditions, host defence mechanisms, host life-history trade-offs, pathogen population dynamics, and their interactions. The survival of Tasmanian devils (Sarcophilus harrisii) is challenged by a novel, fitness limiting pathogen, Tasmanian devil facial tumour disease (DFTD), a clonally transmissible, contagious cancer.

In order to understand the devils’ capacity to respond to DFTD, it is crucial to gain information on factors influencing the devils’ immune system. By using RT-qPCR, we investigated how DFTD infection in association with intrinsic (sex and age) and environmental (season) factors influences the expression of 10 immune genes in Tasmanian devil blood.

Our study showed that the expression of immune genes (both innate and adaptive) differed across seasons, a pattern that was altered when infected with DFTD. The expression of immunogbulins IgE and IgM:IgG showed downregulation in colder months in DFTD infected animals.

We also observed strong positive association between the expression of an innate immune gene, CD16, and DFTD infection. Our results demonstrate that sampling across seasons, age groups and environmental conditions are beneficial when deciphering the complex ecoevolutionary interactions of not only conventional host-parasite systems, but also of host and diseases with high mortality rates, such as transmissible cancers.

Cancer risk across mammals

Authors: Orsolya Vincze, Fernando Colchero, Jean-Francois Lemaître, Dalia A. Conde, Samuel Pavard, Margaux Bieuville, Araxi O. Urrutia, Beata Ujvari, Amy M. Boddy, Carlo C. Maley, Frédéric Thomas & Mathieu Giraudeau

Source: Nature (JAN 2022)

Abstract

Cancer is a ubiquitous disease of metazoans, predicted to disproportionately affect larger, long-lived organisms owing to their greater number of cell divisions, and thus increased probability of somatic mutations.

While elevated cancer risk with larger body size and/or longevity has been documented within species, Peto’s paradox indicates the apparent lack of such an association among taxa. Yet, unequivocal empirical evidence for Peto’s paradox is lacking, stemming from the difficulty of estimating cancer risk in non-model species.

Here we build and analyse a database on cancer-related mortality using data on adult zoo mammals (110,148 individuals, 191 species) and map age-controlled cancer mortality to the mammalian tree of life. We demonstrate the universality and high frequency of oncogenic phenomena in mammals and reveal substantial differences in cancer mortality across major mammalian orders.

We show that the phylogenetic distribution of cancer mortality is associated with diet, with carnivorous mammals (especially mammal-consuming ones) facing the highest cancer-related mortality. Moreover, we provide unequivocal evidence for the body size and longevity components of Peto’s paradox by showing that cancer mortality risk is largely independent of both body mass and adult life expectancy across species.

These results highlight the key role of life-history evolution in shaping cancer resistance and provide major advancements in the quest for natural anticancer defences.

The evolution and ecology of benign tumors

Authors: Justine Boutry, Sophie Tissot, Beata Ujvari, Jean-Pascal Capp, Mathieu Giraudeau, Aurora M. Nedelcu, Frédéric Thomas

Source: Biochimica et Biophysica Acta (BBA) – Reviews on Cancer (JAN 2022)

Abstract

Tumors are usually classified into two main categories – benign or malignant, with much more attention being devoted to the second category given that they are usually associated with more severe health issues (i.e., metastatic cancers).

Here, we argue that the mechanistic distinction between benign and malignant tumors has narrowed our understanding of neoplastic processes. This review provides the first comprehensive discussion of benign tumors in the context of their evolution and ecology as well as interactions with their hosts. We compare the genetic and epigenetic profiles, cellular activities, and the involvement of viruses in benign and malignant tumors. We also address the impact of intra-tumoral cell composition and its relationship with the tumoral microenvironment.

Lastly, we explore the differences in the distribution of benign and malignant neoplasia across the tree of life and provide examples on how benign tumors can also affect individual fitness and consequently the evolutionary trajectories of populations and species.

Overall, our goal is to bring attention to the non-cancerous manifestations of tumors, at different scales, and to stimulate research on the evolutionary ecology of host–tumor interactions on a broader scale.

Ultimately, we suggest that a better appreciation of the differences and similarities between benign and malignant tumors is fundamental to our understanding of malignancy both at mechanistic and evolutionary levels.

Odors and cancer: Current status and future directions

Authors: Flora Gouzerh, Jean-Marie Bessière, Beata Ujvari, Frédéric Thomas , Antoine M Dujon, Laurent Dormont

Source: Biochimica Et Biophysica Acta-reviews On Cancer (NOV2021)

Abstract

Cancer is the second leading cause of death in the world. Because tumors detected at early stages are easier to treat, the search for biomarkers-especially non-invasive ones-that allow early detection of malignancies remains a central goal to reduce cancer mortality.

Cancer, like other pathologies, often alters body odors, and much has been done by scientists over the last few decades to assess the value of volatile organic compounds (VOCs) as signatures of cancers. We present here a quantitative review of 208 studies carried out between 1984 and 2020 that explore VOCs as potential biomarkers of cancers.

We analyzed the main findings of these studies, listing and classifying VOCs related to different cancer types while considering both sampling methods and analysis techniques. Considering this synthesis, we discuss several of the challenges and the most promising prospects of this research direction in the war against cancer.

Bridging Tumorigenesis and Therapy Resistance With a Non-Darwinian and Non-Lamarckian Mechanism of Adaptive Evolution

Authors: Francesco Catania, Beata Ujvari, Benjamin Roche, Jean-Pascal Capp and Frédéric Thomas

Source: FRONTIERS IN ONCOLOGY (SEP 2021)

Abstract

Although neo-Darwinian (and less often Lamarckian) dynamics are regularly invoked to interpret cancer’s multifarious molecular profiles, they shine little light on how tumorigenesis unfolds and often fail to fully capture the frequency and breadth of resistance mechanisms. This uncertainty frames one of the most problematic gaps between science and practice in modern times.

Here, we offer a theory of adaptive cancer evolution, which builds on a molecular mechanism that lies outside neo-Darwinian and Lamarckian schemes. This mechanism coherently integrates non-genetic and genetic changes, ecological and evolutionary time scales, and shifts the spotlight away from positive selection towards purifying selection, genetic drift, and the creative-disruptive power of environmental change.

The surprisingly simple use-it or lose-it rationale of the proposed theory can help predict molecular dynamics during tumorigenesis. It also provides simple rules of thumb that should help improve therapeutic approaches in cancer.

Sea Turtles in the Cancer Risk Landscape: A Global Meta-Analysis of Fibropapillomatosis Prevalence and Associated Risk Factors

Authors: Antoine M. Dujon, Gail Schofield, Roberto M. Venegas, Frédéric Thomas and Beata Ujvari

Source: Pathogens (OCT2021)

Abstract

Several cancer risk factors (exposure to ultraviolet-B, pollution, toxins and pathogens) have been identified for wildlife, to form a “cancer risk landscape.” However, information remains limited on how the spatiotemporal variability of these factors impacts the prevalence of cancer in wildlife.

Here, we evaluated the cancer risk landscape at 49 foraging sites of the globally distributed green turtle (Chelonia mydas), a species affected by fibropapillomatosis, by integrating data from a global meta-analysis of 31 publications (1994–2019).

Evaluated risk factors included ultraviolet light exposure, eutrophication, toxic phytoplanktonic blooms, sea surface temperature, and the presence of mechanical vectors (parasites and symbiotic species).

Prevalence was highest in areas where nutrient concentrations facilitated the emergence of toxic phytoplankton blooms. In contrast, ultraviolet light exposure and the presence of parasitic and/or symbiotic species did not appear to impact disease prevalence.

Our results indicate that, to counter outbreaks of fibropapillomatosis, management actions that reduce eutrophication in foraging areas should be implemented.

On the need for integrating cancer into the One Health perspective

Authors: Antoine M. Dujon, Joel S. Brown, Delphine Destoumieux-Garzón, Marion Vittecoq, Rodrigo Hamede, Aurélie Tasiemski, Justine Boutry ,Sophie Tissot, Catherine Alix-Panabieres, Pascal Pujol, François Renaud, Frédéric Simard ,Benjamin Roche, Beata Ujvari, Frédéric Thomas

Source: EVOLUTIONARY APPLICATIONS (SEP 2021)

Abstract

Recent pandemics have highlighted the urgency to connect disciplines studying animal, human, and environment health, that is, the “One Health” concept. The One Health approach takes a holistic view of health, but it has largely focused on zoonotic diseases while not addressing oncogenic processes.

We argue that cancers should be an additional key focus in the One Health approach based on three factors that add to the well-documented impact of humans on the natural environment and its implications on cancer emergence.

First, human activities are oncogenic to other animals, exacerbating the dynamics of oncogenesis, causing immunosuppressive disorders in wildlife with effects on host–pathogen interactions, and eventually facilitating pathogen spillovers.

Second, the emergence of transmissible cancers in animal species (including humans) has the potential to accelerate biodiversity loss across ecosystems and to become pandemic. It is crucial to understand why, how, and when transmissible cancers emerge and spread.

Third, translating knowledge of tumor suppressor mechanisms found across the Animal Kingdom to human health offers novel insights into cancer prevention and treatment strategies.

Machine learning is a powerful tool to study the effect of cancer on species and ecosystems

Authors: Antoine M. Dujon, Marion Vittecoq, Georgina Bramwell, Frédéric Thomas, Beata Ujvari

Source: METHODS IN ECOLOGY AND EVOLUTION (AUG 2021)

Abstract

Cancer is an understudied but important process in wildlife. Cancerous cells are proposed to have had significant effect on the evolution of metazoan species due to their negative effect on host fitness. However, gaining knowledge on the impact of cancer on species and ecosystems is currently relatively slow as it requires expertise in both ecology and oncology. The field can greatly benefit from automation to reduce the need of excessive manpower and analyse complex ecological datasets.

In this commentary, we examine how machine learning has been used to gain knowledge on oncogenic processes in wildlife. Using a landscape ecology approach, we explore spatial scales ranging from the size of a molecule up to whole ecosystems and detail, for each level, how machine learning has been used, or could contribute to obtain insights on cancer in wildlife populations and ecosystems.

We illustrate how machine learning is a powerful toolbox to conduct studies at the interface of ecology and oncology. We provide guidance for the readers of both fields on how to implement machine learning tools in their research and identify directions to move the field forward using this promising technology. We demonstrate how applying machine learning to complex ecological datasets will (a) contribute to quantitating the effect of cancer at different life stages in wildlife; (b) allow the mining of long-term datasets to understand the spatiotemporal variability of cancer risk factors and (c) contribute to mitigating cancer risk factors and the conservation of endangered species.

With this study, we aim to facilitate the use of machine learning to wildlife species and to encourage discussion between the scientists of the fields of oncology and ecology. We highlight the importance of international and pluridisciplinary collaborations to collect high-quality datasets on which efficient machine learning algorithms can be trained.