Could the human papillomavirus vaccines drive virulence evolution?

Episome partitioning and symmetric cell divisions: Quantifying the role of random events in the persistence of HPV infections

Human Papillomaviruses (HPV) are one of the most prevalent sexually transmitted infections (STI) and the most oncogenic viruses known to humans. The vast majority of HPV infections clear in less than 3 years, but the underlying mechanisms, especially the involvement of the immune response, are still poorly known. Building on earlier work stressing the importance of randomness in the type of cell divisions in the clearance of HPV infection, we develop a stochastic mathematical model of HPV dynamics that combines the previous aspect with an explicit description of the intracellular level. We show that the random partitioning of virus episomes upon stem cell division and the occurrence of symmetric divisions dramatically affect viral persistence. These results call for more detailed within-host studies to better understand the relative importance of stochasticity and immunity in HPV infection clearance.

Every year, infections by Human Papillomaviruses (HPV) are responsible for a large share of infectious cancers. The prevalence of HPVs is very high, which makes it a major public health issue. Fortunately, most HPV infections (80 to 90%) are cleared naturally within three years. Among the few that persist into chronic infections, the majority also naturally regress. Hence for a given HPV infection, the risk of progression towards cancerous status is low. The immune response is often invoked to explain HPV clearance in non-persisting infections, but many uncertainties remain. Besides immunity, randomness was also suggested to play an important role. Here, we examine how random events occurring during the life cycle of the virus could alter the persistence of the virus inside the host. We develop a mechanistic model that explicitly follows the dynamic of viral copies inside host cells, as well as the dynamics of the epithelium. In our model, infection extinction occurs when all viral copies end up in differentiated cells and migrate towards the surface. This can happen upon cell division during the random allocation of the episomes (i.e. independent circular DNA copies of the viral genome) or when a stem cell divides symmetrically to generate two differentiated cells. We find that the combination of these random events drastically affects infection persistence. More generally, the importance of random fluctuations could match that of immunity and calls for further studies at the within-host and the epidemiological level.

NanoString Technology for Human Papillomavirus Typing

High-throughput HPV typing assays with increased automation, faster turnaround and type-specific digital readout would facilitate studies monitoring the impact of HPV vaccination. We evaluated the NanoString nCounter^® platform for detection and digital readout of 48 HPV types in a single reaction. NanoString (NS) used proprietary software to design CodeSets: type-specific probe pairs targeting 48 HPV types and the globin gene. We tested residual DNA extracts from epidemiologic specimens and defined samples (HPV plasmids at 10 to 10⁴ copies/reaction) directly (No-PCR) as well as after L1 consensus PCR of 45 (PCR-45) or 15 cycles (PCR-15). Assay and interpretation followed NS recommendations. We evaluated analytic performance by comparing NanoString results for types included in prior assays: Roche Linear Array (LA) or HPV TypeSeq assay. No-PCR results on 40 samples showed good type-specific agreement with LA (k = 0.621) but sensitivity was 65% with lower limit of detection (LOD) at 10⁴ plasmid copies. PCR-45 results showed almost perfect type-specific agreement with LA (k = 0.862), 82% sensitivity and LOD at 10 copies. PCR-15 results on 75 samples showed substantial type-specific agreement with LA (k = 0.796, 92% sensitivity) and TypeSeq (k = 0.777, 87% sensitivity), and LOD at 10 copies of plasmids. This proof-of-principle study demonstrates the efficacy of the NS platform with HPV CodeSet for type-specific detection using a low number of PCR cycles (PCR-15). Studies are in progress to evaluate assay reproducibility and analytic validation with a larger number of samples.

Potential Effects of Human Papillomavirus Type Substitution, Superinfection Exclusion and Latency on the Efficacy of the Current L1 Prophylactic Vaccines

There are >200 different types of human papilloma virus (HPV) of which >51 infect genital epithelium, with ~14 of these classed as high-risk being more commonly associated with cervical cancer. During development of the disease, high-risk types have an increased tendency to develop a truncated non-replicative life cycle, whereas low-risk, non-cancer-associated HPV types are either asymptomatic or cause benign lesions completing their full replicative life cycle. HPVs can also be present as non-replicative so-called “latent” infections and they can also show superinfection exclusion, where cells with pre-existing infections with one type cannot be infected with a different HPV type. Thus, the HPV repertoire and replication status present in an individual can form a complex dynamic meta-community which changes with respect to both time and exposure to different HPV types. In light of these considerations, it is not clear how current prophylactic HPV vaccines will affect this system and the potential for iatrogenic outcomes is discussed in light of recent outcome data.

Prophylactic host behaviour discourages pathogen exploitation

Much work has considered the evolution of pathogens, but little is known about how they respond to changes in host behaviour. We build a model of sublethal disease effects where hosts are able to choose to engage in prophylactic measures that reduce the likelihood of disease transmission. This choice is mediated by utility costs and benefits associated with prophylaxis, and the fraction of hosts engaged in prophylaxis is also affected by population dynamics. When prophylactic host behaviour occurs, we find that the level of pathogen host exploitation is reduced, by the action of selection, relative to the level that would otherwise be predicted in the absence of prophylaxis. Our work emphasizes the significance of the transmission-recovery trade-off faced by the pathogen and the ability of the pathogen to influence host prophylactic behaviour.

Modelling the evolution of viral oncogenesis

Most human oncogenic viruses share several characteristics, such as being DNA viruses, having long (co)evolutionary histories with their hosts and causing either latent or chronic infections. They can reach high prevalences while causing relatively low case mortality, which makes them quite fit according to virulence evolution theory. After analysing the life histories of DNA oncoviruses, we use a mathematical modelling approach to investigate how the virus life cycle may generate selective pressures favouring or acting against oncogenesis at the within-host or at the between-host level. In particular, we focus on two oncoprotein activities, namely extending cell life expectancy and increasing cell proliferation rate. These have immediate benefits (increasing viral population size) but can be associated with fitness costs at the epidemiological level (increasing recovery rate or risk of cancer) thus creating evolutionary trade-offs. We interpret the results of our nested model in light of the biological features and identify future perspectives for modelling oncovirus dynamics and evolution. This article is part of the theme issue 'Silent cancer agents: multi-disciplinary modelling of human DNA oncoviruses'.

Human Papillomavirus Genotype Replacement: Still Too Early to Tell?

Background

Although human papillomavirus (HPV) vaccines are highly efficacious in protecting against HPV infections and related diseases, vaccination may trigger replacement by nontargeted genotypes if these compete with the vaccine-targeted types. HPV genotype replacement has been deemed unlikely, based on the lack of systematic increases in the prevalence of nonvaccine-type (NVT) infection in the first decade after vaccination, and on the presence of cross-protection for some NVTs.

Methods

To investigate whether type replacement can be inferred from early postvaccination surveillance, we constructed a transmission model in which a vaccine type and an NVT compete through infection-induced cross-immunity. We simulated scenarios of different levels of cross-immunity and vaccine-induced cross-protection to the NVT. We validated whether commonly used measures correctly indicate type replacement in the long run.

Results

Type replacement is a trade-off between cross-immunity and cross-protection; cross-immunity leads to type replacement unless cross-protection is strong enough. With weak cross-protection, NVT prevalence may initially decrease before rebounding into type replacement, exhibiting a honeymoon period. Importantly, vaccine effectiveness for NVTs is inadequate for indicating type replacement.

Conclusions

Although postvaccination surveillance thus far is reassuring, it is still too early to preclude type replacement. Monitoring of NVTs remains pivotal in gauging population-level impacts of HPV vaccination.

Host exposure history modulates the within-host advantage of virulence in a songbird-bacterium system

The host immune response can exert strong selective pressure on pathogen virulence, particularly when host protection against reinfection is incomplete. Since emerging in house finch populations, the bacterial pathogen Mycoplasma gallisepticum (MG) has been increasing in virulence. Repeated exposure to low-doses of MG, a proxy for what birds likely experience while foraging, provides significant but incomplete protection against reinfection. Here we sought to determine if the within-host, pathogen load advantage of high virulence is mediated by the degree of prior pathogen exposure, and thus the extent of immune memory. We created variation in host immunity by experimentally inoculating wild-caught, MG-naïve house finches with varying doses and number of exposures of a single pathogen strain of intermediate virulence. Following recovery from priming exposures, individuals were challenged with one of three MG strains of distinct virulence. We found that the quantitative pathogen load advantage of high virulence was strongly mediated by the degree of prior exposure. The greatest within-host load advantage of virulence was seen in hosts given low-dose priming exposures, akin to what many house finches likely experience while foraging. Our results show that incomplete host immunity produced by low-level prior exposure can create a within-host environment that favors more virulent pathogens.

How can HPV-induced cervical cancer be controlled by a combination of drug therapy? A mathematical study

This paper deals with a control strategy through impulsive drug treatment to study the effect of Chemotherapy and CTL activator drug to eradicate the cervical cancer. CTL kills the HPV infected cells and helps to prevent cervical cancer. Dendritic cell (DC) plays a crucial role in this disease dynamics in enhancing the activity of CTL. To explore these effects, we have formulated a mathematical model consisting of six compartments to describe the interactions between HPV and three classes of cervical cells (susceptible, infected, cancerous), with DC and CTL. Calculating the basic reproduction ratio, we find that there exists a disease-free equilibrium point and an endemic equilibrium point. In our study, we have shown that though DC enhances the activity of CTL, it is not sufficient to eradicate the disease totally. How we could restrict the cancer development by using double drug in an impulsive way with particular drug doses is being reflected in the results. To illustrate our results, numerical simulations are also presented.

Detecting within-host interactions from genotype combination prevalence data

Parasite genetic diversity can provide information on disease transmission dynamics but most mathematical and statistical frameworks ignore the exact combinations of genotypes in infections. We introduce and validate a new method that combines explicit epidemiological modelling of coinfections and regression-Approximate Bayesian Computing (ABC) to detect within-host interactions. Using a susceptible-infected-susceptible (SIS) model, we show that, if sufficiently strong, within-host parasite interactions can be detected from epidemiological data. We also show that, in this simple setting, this detection is robust even in the face of some level of host heterogeneity in behaviour. These simulations results offer promising applications to analyse large datasets of multiple infection prevalence data, such as those collected for genital infections by Human Papillomaviruses (HPVs).

Natural history, dynamics, and ecology of human papillomaviruses in genital infections of young women: protocol of the PAPCLEAR cohort study

INTRODUCTION

Human papillomaviruses (HPVs) are responsible for one-third of all cancers caused by infections. Most HPV studies focus on chronic infections and cancers, and we know little about the early stages of the infection. Our main objective is to better understand the course and natural history of cervical HPV infections in healthy, unvaccinated and vaccinated, young women, by characterising the dynamics of various infection-related populations (virus, epithelial cells, vaginal microbiota and immune effectors). Another objective is to analyse HPV diversity within hosts, and in the study population, in relation to co-factors (lifestyle characteristics, vaccination status, vaginal microbiota, human genetics).

METHODS AND ANALYSIS

The PAPCLEAR study is a single center longitudinal study following 150 women, aged 18-25 years, for up to 2 years. Visits occur every 2 or 4 months (depending on HPV status) during which several variables are measured, such as behaviours (via questionnaires), vaginal pH, HPV presence and viral load (via qPCR), local concentrations of cytokines (via MesoScale Discovery technology) and immune cells (via flow cytometry). Additional analyses are outsourced, such as titration of circulating anti-HPV antibodies, vaginal microbiota sequencing (16S and ITS1 loci) and human genotyping. To increase the statistical power of the epidemiological arm of the study, an additional 150 women are screened cross-sectionally. Finally, to maximise the resolution of the time series, participants are asked to perform weekly self-samples at home. Statistical analyses will involve classical tools in epidemiology, genomics and virus kinetics, and will be performed or coordinated by the Centre National de la Recherche Scientifique (CNRS) in Montpellier.

ETHICS AND DISSEMINATION

This study has been approved by the Comité de Protection des Personnes Sud Méditerranée I (reference number 2016-A00712-49); by the Comité Consultatif sur le Traitement de l'Information en matière de Recherche dans le domaine de la Santé (reference number 16.504); by the Commission Nationale Informatique et Libertés (reference number MMS/ABD/AR1612278, decision number DR-2016-488) and by the Agence Nationale de Sécurité du Médicament et des Produits de Santé (reference 20160072000007). Results will be published in preprint servers, peer-reviewed journals and disseminated through conferences.

TRIAL REGISTRATION NUMBER

NCT02946346; Pre-results.

Host contact dynamics shapes richness and dominance of pathogen strains

The interaction among multiple microbial strains affects the spread of infectious diseases and the efficacy of interventions. Genomic tools have made it increasingly easy to observe pathogenic strains diversity, but the best interpretation of such diversity has remained difficult because of relationships with host and environmental factors. Here, we focus on host-to-host contact behavior and study how it changes populations of pathogens in a minimal model of multi-strain interaction. We simulated a population of identical strains competing by mutual exclusion and spreading on a dynamical network of hosts according to a stochastic susceptible-infectious-susceptible model. We computed ecological indicators of diversity and dominance in strain populations for a collection of networks illustrating various properties found in real-world examples. Heterogeneities in the number of contacts among hosts were found to reduce diversity and increase dominance by making the repartition of strains among infected hosts more uneven, while strong community structure among hosts increased strain diversity. We found that the introduction of strains associated with hosts entering and leaving the system led to the highest pathogenic richness at intermediate turnover levels. These results were finally illustrated using the spread of Staphylococcus aureus in a long-term health-care facility where close proximity interactions and strain carriage were collected simultaneously. We found that network structural and temporal properties could account for a large part of the variability observed in strain diversity. These results show how stochasticity and network structure affect the population ecology of pathogens and warn against interpreting observations as unambiguous evidence of epidemiological differences between strains.

The influence of social behaviour on competition between virulent pathogen strains

Infectious disease interventions like contact precautions and vaccination have proven effective in disease control and elimination. The priority given to interventions can depend strongly on how virulent the pathogen is, and interventions may also depend partly for their success on social processes that respond adaptively to disease dynamics. However, mathematical models of competition between pathogen strains with differing natural history profiles typically assume that human behaviour is fixed. Here, our objective is to model the influence of social behaviour on the competition between pathogen strains with differing virulence. We couple a compartmental Susceptible-Infectious-Recovered model for a resident pathogen strain and a mutant strain with higher virulence, with a differential equation of a population where individuals learn to adopt protective behaviour from others according to the prevalence of infection of the two strains and the perceived severity of the respective strains in the population. We perform invasion analysis, time series analysis and phase plane analysis to show that perceived severities of pathogen strains and the efficacy of infection control against them can greatly impact the invasion of more virulent strain. We demonstrate that adaptive social behaviour enables invasion of the mutant strain under plausible epidemiological scenarios, even when the mutant strain has a lower basic reproductive number than the resident strain. Surprisingly, in some situations, increasing the perceived severity of the resident strain can facilitate invasion of the more virulent mutant strain. Our results demonstrate that for certain applications, it may be necessary to include adaptive social behaviour in models of the emergence of virulent pathogens, so that the models can better assist public health efforts to control infectious diseases.

Recurring infection with ecologically distinct HPV types can explain high prevalence and diversity

The high prevalence of human papillomavirus (HPV), the most common sexually transmitted infection, arises from the coexistence of over 200 genetically distinct types. Accurately predicting the impact of vaccines that target multiple types requires understanding the factors that determine HPV diversity. The diversity of many pathogens is driven by type-specific or "homologous" immunity, which promotes the spread of variants to which hosts have little immunity. To test for homologous immunity and to identify mechanisms determining HPV transmission, we fitted nonlinear mechanistic models to longitudinal data on genital infections in unvaccinated men. Our results provide no evidence for homologous immunity, instead showing that infection with one HPV type strongly increases the risk of infection with that type for years afterward. For HPV16, the type responsible for most HPV-related cancers, an initial infection increases the 1-year probability of reinfection by 20-fold, and the probability of reinfection remains 14-fold higher 2 years later. This increased risk occurs in both sexually active and celibate men, suggesting that it arises from autoinoculation, episodic reactivation of latent virus, or both. Overall, our results suggest that high HPV prevalence and diversity can be explained by a combination of a lack of homologous immunity, frequent reinfections, weak competition between types, and variation in type fitness between host subpopulations. Because of the high risk of reinfection, vaccinating boys who have not yet been exposed may be crucial to reduce prevalence, but our results suggest that there may also be large benefits to vaccinating previously infected individuals.

Why Human Papillomavirus Acute Infections Matter

Most infections by human papillomaviruses (HPVs) are `acute', that is non-persistent. Yet, for HPVs, as for many other oncoviruses, there is a striking gap between our detailed understanding of chronic infections and our limited data on the early stages of infection. Here we argue that studying HPV acute infections is necessary and timely. Focusing on early interactions will help explain why certain infections are cleared while others become chronic or latent. From a molecular perspective, descriptions of immune effectors and pro-inflammatory pathways during the initial stages of infections have the potential to lead to novel treatments or to improved handling algorithms. From a dynamical perspective, adopting concepts from spatial ecology, such as meta-populations or meta-communities, can help explain why HPV acute infections sometimes last for years. Furthermore, cervical cancer screening and vaccines impose novel iatrogenic pressures on HPVs, implying that anticipating any viral evolutionary response remains essential. Finally, hints at the associations between HPV acute infections and fertility deserve further investigation given their high, worldwide prevalence. Overall, understanding asymptomatic and benign infections may be instrumental in reducing HPV virulence.

Mechanistic mathematical models: An underused platform for HPV research

Health economic modeling has become an invaluable methodology for the design and evaluation of clinical and public health interventions against the human papillomavirus (HPV) and associated diseases. At the same time, relatively little attention has been paid to a different yet complementary class of models, namely that of mechanistic mathematical models. The primary focus of mechanistic mathematical models is to better understand the intricate biologic mechanisms and dynamics of disease. Inspired by a long and successful history of mechanistic modeling in other biomedical fields, we highlight several areas of HPV research where mechanistic models have the potential to advance the field. We argue that by building quantitative bridges between biologic mechanism and population level data, mechanistic mathematical models provide a unique platform to enable collaborations between experimentalists who collect data at different physical scales of the HPV infection process. Through such collaborations, mechanistic mathematical models can accelerate and enhance the investigation of HPV and related diseases.

Modeling the Mechanisms by Which HIV-Associated Immunosuppression Influences HPV Persistence at the Oral Mucosa

Human immunodeficiency virus (HIV)-infected patients are at an increased risk of co-infection with human papilloma virus (HPV), and subsequent malignancies such as oral cancer. To determine the role of HIV-associated immune suppression on HPV persistence and pathogenesis, and to investigate the mechanisms underlying the modulation of HPV infection and oral cancer by HIV, we developed a mathematical model of HIV/HPV co-infection. Our model captures known immunological and molecular features such as impaired HPV-specific effector T helper 1 (Th1) cell responses, and enhanced HPV infection due to HIV. We used the model to determine HPV prognosis in the presence of HIV infection, and identified conditions under which HIV infection alters HPV persistence in the oral mucosa system. The model predicts that conditions leading to HPV persistence during HIV/HPV co-infection are the permissive immune environment created by HIV and molecular interactions between the two viruses. The model also determines when HPV infection continues to persist in the short run in a co-infected patient undergoing antiretroviral therapy. Lastly, the model predicts that, under efficacious antiretroviral treatment, HPV infections will decrease in the long run due to the restoration of CD4+ T cell numbers and protective immune responses.

Combined SYBR Green real-time polymerase chain reaction and microarray method for the simultaneous determination of human papillomavirus loads and genotypes

Objective

The aim of this study was to describe the principle of the Cheil HPV DNA Chip assay and evaluate its accuracy. In order to quantify the human papillomavirus (HPV) load and identify HPV genotypes simultaneously, this assay combined the two methods: SYBR Green quantitative real-time polymerase chain reaction (PCR) and DNA microarray.

Methods

We designed novel consensus primer sets that target the conserved region of the HPV L1 gene for quantifying and detecting a broad range of HPV types by quantitative real-time PCR. Subsequently, using the PCR products, DNA microarray was performed with 36 HPV type-specific probes. To validate this method, direct sequencing and correlation analysis among HPV genotype, viral load, and cytological abnormality was performed by Cohen’s kappa values, two-sided McNemar chi-square test, Kruskal-Wallis test, and odds ratios.

Results

The kappa value of the Cheil HPV DNA Chip was 0.963 (95% confidence interval, 0.919 to 0.98), which was significantly higher than the value of 0.527 (95% confidence interval, 0.447 to 0.59) obtained using a conventional HPV DNA Chip. HPV16 (χ²=62.28, P<0.01), HPV33 (χ²=7.18, P<0.01), and HPV58 (χ²=9.52, P<0.01), which are classified as high-risk HPVs, were detected at significant levels in samples with high-grade lesions. And viral loads tended to be higher in groups with high odds ratios.

Conclusion

The Cheil HPV DNA Chip is an effective diagnostic assay for simultaneously detecting HPV genotypes and loads in cervical samples.

Dating the origin and dispersal of Human Papillomavirus type 16 on the basis of ancestral human migrations

A major limitation when reconstructing the origin and evolution of HPV-16 is the lack of reliable substitution rate estimates for the viral genes. On the basis of the hypothesis of human HPV-16 co-divergence, we estimated a mean evolutionary rate of 1.47×10(-7) (95% HPD=0.64-2.47×10(-7)) subs/site/year for the viral LCR region. The results of a Bayesian phylogeographical analysis suggest that the currently circulating HPV-16 most probably originated in Africa about 110 thousand years ago (Kya), before giving rise to four known geographical lineages: the Asian/European lineage, which most probably originated in Asia a mean 38 Kya, and the Asian/American and two African lineages, which probably respectively originated about 33 and 27 Kya. These data closely reflect current hypotheses concerning modern human expansion based on studies of mitochondrial DNA phylogeny. The correlation between ancient human migration and the present HPV phylogeny may be explained by the co-existence of modes of transmission other than sexual transmission.