A Molecular Clock Infers Heterogeneous Tissue Age Among Patients with Barrett's Esophagus

Underlying Mechanisms of the Protective Effects of Lifestyle Factors in the Prevention of Age-Related Diseases

The rise in life expectancy has significantly increased the occurrence of age-related chronic diseases, leading to escalating expenses for both society and individuals. Among the main factors influencing health and lifespan, lifestyle takes a forefront position. Specifically, nutrition, mental activity, and physical exercise influence the molecular and functional mechanisms that contribute to the prevention of major age-related diseases. Gaining deeper insights into the mechanisms that drive the positive effects of healthy lifestyles is valuable for creating interventions to prevent or postpone the development of chronic degenerative diseases. This review summarizes the main mechanisms that underlie the positive effect of lifestyle factors in counteracting the major age-related diseases involving brain health, musculoskeletal function, cancer, frailty, and cardiovascular diseases, among others. This knowledge will help to identify high-risk populations for targeted intervention trials and discover new biomarkers associated with healthy aging.

An improved epigenetic counter to track mitotic age in normal and precancerous tissues

The cumulative number of stem cell divisions in a tissue, known as mitotic age, is thought to be a major determinant of cancer-risk. Somatic mutational and DNA methylation (DNAm) clocks are promising tools to molecularly track mitotic age, yet their relationship is underexplored and their potential for cancer risk prediction in normal tissues remains to be demonstrated. Here we build and validate an improved pan-tissue DNAm counter of total mitotic age called stemTOC. We demonstrate that stemTOC's mitotic age proxy increases with the tumor cell-of-origin fraction in each of 15 cancer-types, in precancerous lesions, and in normal tissues exposed to major cancer risk factors. Extensive benchmarking against 6 other mitotic counters shows that stemTOC compares favorably, specially in the preinvasive and normal-tissue contexts. By cross-correlating stemTOC to two clock-like somatic mutational signatures, we confirm the mitotic-like nature of only one of these. Our data points towards DNAm as a promising molecular substrate for detecting mitotic-age increases in normal tissues and precancerous lesions, and hence for developing cancer-risk prediction strategies.

Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma

A variety of mutational processes drive cancer development, but their dynamics across the entire disease spectrum from pre-cancerous to advanced neoplasia are poorly understood. We explore the mutagenic processes shaping oesophageal adenocarcinoma tumorigenesis in 997 instances comprising distinct stages of this malignancy, from Barrett Oesophagus to primary tumours and advanced metastatic disease. The mutational landscape is dominated by the C[T > C/G]T substitution enriched signatures SBS17a/b, which are linked with TP53 mutations, increased proliferation, genomic instability and disease progression. The APOBEC mutagenesis signature is a weak but persistent signal amplified in primary tumours. We also identify prevalent alterations in DNA damage repair pathways, with homologous recombination, base and nucleotide excision repair and translesion synthesis mutated in up to 50% of the cohort, and surprisingly uncoupled from transcriptional activity. Among these, the presence of base excision repair deficiencies show remarkably poor prognosis in the cohort. In this work, we provide insights on the mutational aetiology and changes enabling the transition from pre-neoplastic to advanced oesophageal adenocarcinoma.

CNETML: maximum likelihood inference of phylogeny from copy number profiles of multiple samples

Phylogenetic trees based on copy number profiles from multiple samples of a patient are helpful to understand cancer evolution. Here, we develop a new maximum likelihood method, CNETML, to infer phylogenies from such data. CNETML is the first program to jointly infer the tree topology, node ages, and mutation rates from total copy numbers of longitudinal samples. Our extensive simulations suggest CNETML performs well on copy numbers relative to ploidy and under slight violation of model assumptions. The application of CNETML to real data generates results consistent with previous discoveries and provides novel early copy number events for further investigation.

Role of DNA methylation in the relationship between glioma risk factors and glioma incidence: a two-step Mendelian randomization study

Genetic evidence suggests glioma risk is altered by leukocyte telomere length, allergic disease (asthma, hay fever or eczema), alcohol consumption, childhood obesity, low-density lipoprotein cholesterol (LDLc) and triglyceride levels. DNA methylation (DNAm) variation influences many of these glioma-related traits and is an established feature of glioma. Yet the causal relationship between DNAm variation with both glioma incidence and glioma risk factors is unknown. We applied a two-step Mendelian randomization (MR) approach and several sensitivity analyses (including colocalization and Steiger filtering) to assess the association of DNAm with glioma risk factors and glioma incidence. We used data from a recently published catalogue of germline genetic variants robustly associated with DNAm variation in blood (32,851 participants) and data from a genome-wide association study of glioma risk (12,488 cases and 18,169 controls, sub-divided into 6191 glioblastoma cases and 6305 non-glioblastoma cases). MR evidence indicated that DNAm at 3 CpG sites (cg01561092, cg05926943, cg01584448) in one genomic region (HEATR3) had a putative association with glioma and glioblastoma risk (False discovery rate [FDR] < 0.05). Steiger filtering provided evidence against reverse causation. Colocalization presented evidence against genetic confounding and suggested that differential DNAm at the 3 CpG sites and glioma were driven by the same genetic variant. MR provided little evidence to suggest that DNAm acts as a mediator on the causal pathway between risk factors previously examined and glioma onset. To our knowledge, this is the first study to use MR to appraise the causal link of DNAm with glioma risk factors and glioma onset. Subsequent analyses are required to improve the robustness of our results and rule out horizontal pleiotropy.

DNA Methylation, Aging, and Cancer Risk: A Mini-Review

Accumulation of somatic mutations and genomic instability are hallmarks of both aging and cancer. Epigenetic alterations occur across cell types and tissues with advancing age. DNA methylation-based estimates of biologic age can predict important age-related outcomes, including risk of frailty and mortality, and most recently have been shown to be associated with risk of developing cancer. In this mini-review, we examine pathways known to exhibit altered methylation in aging tissues, pre-malignant lesions, and tumors and review methodologies of epigenetic clocks that reliably predict cancer risk, including those derived from methylation studies of peripheral blood, as well as those methylation levels from within the tissues at high risk of cancer.

Evolution and progression of Barrett's oesophagus to oesophageal cancer

Cancer cells are shaped through an evolutionary process of DNA mutation, cell selection and population expansion. Early steps in this process are driven by a set of mutated driver genes and structural alterations to the genome through copy number gains or losses. Oesophageal adenocarcinoma (EAC) and the pre-invasive tissue, Barrett's oesophagus (BE), provide an ideal example in which to observe and study this evolution. BE displays early genomic instability, specifically in copy number changes that may later be observed in EAC. Furthermore, these early changes result in patterns of progression (that is, 'born bad', gradual or catastrophic) that may help to describe the evolution of EAC. As only a small proportion of patients with BE will go on to develop cancer, a better understanding of these patterns and the resulting genomic changes should improve early detection in EAC and may provide clues for the evolution of cancer more broadly.

Epigenetic Alterations in the Gastrointestinal Tract: Current and Emerging Use for Biomarkers of Cancer

Colorectal cancer, liver cancer, stomach cancer, pancreatic cancer, and esophageal cancer are leading causes of cancer-related deaths worldwide. A fundamental trait of virtually all gastrointestinal cancers is genomic and epigenomic DNA alterations. Cancer cells acquire genetic and epigenetic alterations that drive the initiation and progression of the cancers by altering the molecular and cell biological processes of the cells. These alterations, as well as other host and microenvironment factors, ultimately mediate the clinical behavior of the precancers and cancers and can be used as biomarkers for cancer risk determination, early detection of cancer and precancer, determination of the prognosis of cancer and prediction of the response to therapy. Epigenetic alterations have emerged as one of most robust classes of biomarkers and are the basis for a growing number of clinical tests for cancer screening and surveillance.

Within-patient phylogenetic reconstruction reveals early events in Barrett's Esophagus

Barrett's Esophagus is a neoplastic condition which progresses to esophageal adenocarcinoma in 5% of cases. Key events affecting the outcome likely occur before diagnosis of Barrett's and cannot be directly observed; we use phylogenetic analysis to infer such past events. We performed whole-genome sequencing on 4-6 samples from 40 cancer outcome and 40 noncancer outcome patients with Barrett's Esophagus, and inferred within-patient phylogenies of deconvoluted clonal lineages. Spatially proximate lineages clustered in the phylogenies, but temporally proximate ones did not. Lineages with inferred loss-of-function mutations in both copies of TP53 and CDKN2A showed enhanced spatial spread, whereas lineages with loss-of-function mutations in other frequently mutated loci did not. We propose a two-phase model with expansions of TP53 and CKDN2A mutant lineages during initial growth of the segment, followed by relative stasis. Subsequent to initial expansion, mutations in these loci as well as ARID1A and SMARCA4 may show a local selective advantage but do not expand far: The spatial structure of the Barrett's segment remains stable during surveillance even in patients who go on to cancer. We conclude that the cancer/noncancer outcome is strongly affected by early steps in formation of the Barrett's segment.

Inferring Tumor Proliferative Organization from Phylogenetic Tree Measures in a Computational Model

We use a computational modeling approach to explore whether it is possible to infer a solid tumor's cellular proliferative hierarchy under the assumptions of the cancer stem cell hypothesis and neutral evolution. We work towards inferring the symmetric division probability for cancer stem cells, since this is believed to be a key driver of progression and therapeutic response. Motivated by the advent of multiregion sampling and resulting opportunities to infer tumor evolutionary history, we focus on a suite of statistical measures of the phylogenetic trees resulting from the tumor's evolution in different regions of parameter space and through time. We find strikingly different patterns in these measures for changing symmetric division probability which hinge on the inclusion of spatial constraints. These results give us a starting point to begin stratifying tumors by this biological parameter and also generate a number of actionable clinical and biological hypotheses regarding changes during therapy, and through tumor evolutionary time. [Cancer; evolution; phylogenetics.].

Optimal Timing for Cancer Screening and Adaptive Surveillance Using Mathematical Modeling

Cancer screening and early detection efforts have been partially successful in reducing incidence and mortality, but many improvements are needed. Although current medical practice is informed by epidemiologic studies and experts, the decisions for guidelines are ultimately ad hoc. We propose here that quantitative optimization of protocols can potentially increase screening success and reduce overdiagnosis. Mathematical modeling of the stochastic process of cancer evolution can be used to derive and optimize the timing of clinical screens so that the probability is maximal that a patient is screened within a certain "window of opportunity" for intervention when early cancer development may be observable. Alternative to a strictly empirical approach or microsimulations of a multitude of possible scenarios, biologically based mechanistic modeling can be used for predicting when best to screen and begin adaptive surveillance. We introduce a methodology for optimizing screening, assessing potential risks, and quantifying associated costs to healthcare using multiscale models. As a case study in Barrett's esophagus, these methods were applied for a model of esophageal adenocarcinoma that was previously calibrated to U.S. cancer registry data. Optimal screening ages for patients with symptomatic gastroesophageal reflux disease were older (58 for men and 64 for women) than what is currently recommended (age > 50 years). These ages are in a cost-effective range to start screening and were independently validated by data used in current guidelines. Collectively, our framework captures critical aspects of cancer evolution within patients with Barrett's esophagus for a more personalized screening design. SIGNIFICANCE: This study demonstrates how mathematical modeling of cancer evolution can be used to optimize screening regimes, with the added potential to improve surveillance regimes. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/81/4/1123/F1.large.jpg.

Computational modelling suggests that Barrett's oesophagus may be the precursor of all oesophageal adenocarcinomas

OBJECTIVE

Barrett's oesophagus (BE) is a known precursor to oesophageal adenocarcinoma (OAC) but current clinical data have not been consolidated to address whether BE is the origin of all incident OAC, which would reinforce evidence for BE screening efforts. We aimed to answer whether all expected prevalent BE, diagnosed and undiagnosed, could account for all incident OACs in the US cancer registry data.

DESIGN

We used a multiscale computational model of OAC that includes the evolutionary process from normal oesophagus through BE in individuals from the US population. The model was previously calibrated to fit Surveillance, Epidemiology and End Results cancer incidence curves. Here, we also utilised age-specific and sex-specific US census data for numbers at-risk. The primary outcome for model validation was the expected number of OAC cases for a given calendar year. Secondary outcomes included the comparisons of resulting model-predicted prevalence of BE and BE-to-OAC progression to the observed prevalence and progression rates.

RESULTS

The model estimated the total number of OAC cases from BE in 2010 was 9970 (95% CI: 9140 to 11 980), which recapitulates nearly all OAC cases from population data. The model simultaneously predicted 8%-9% BE prevalence in high-risk males age 45-55, and 0.1%-0.2% non-dysplastic BE-to-OAC annual progression in males, consistent with clinical studies.

CONCLUSION

There are likely few additional OAC cases arising in the US population outside those expected from individuals with BE. Effective screening of high-risk patients could capture the majority of population destined for OAC progression and potentially decrease mortality through early detection and curative removal of small (pre)cancers during surveillance.

Barrett's Esophagus and Esophageal Adenocarcinoma Biomarkers

Esophageal adenocarcinoma is a major cause of cancer-related morbidity and mortality in Western countries. The incidences of esophageal adenocarcinoma and its precursor Barrett's esophagus have increased substantially in the last four decades. Current care guidelines recommend that endoscopy be used for the early detection and monitoring of patients with Barrett's esophagus; however, the efficacy of this approach is unclear. To prevent the increasing morbidity and mortality from esophageal adenocarcinoma, there is a tremendous need for early detection and surveillance biomarker assays that are accurate, low-cost, and clinically feasible to implement. The last decade has seen remarkable advances in the development of minimally invasive molecular biomarkers, an effort led in large part by the Early Detection Research Network (EDRN). Advances in multi-omics analysis, the development of swallowable cytology collection devices, and emerging technology have led to promising assays that are likely to be implemented into clinical care in the next decade. In this review, an updated overview of the molecular pathology of Barrett's esophagus and esophageal adenocarcinoma and emerging molecular biomarker assays, as well as the role of EDRN in biomarker discovery and validation, will be discussed.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

A comparison of epigenetic mitotic-like clocks for cancer risk prediction

Background

DNA methylation changes that accrue in the stem cell pool of an adult tissue in line with the cumulative number of cell divisions may contribute to the observed variation in cancer risk among tissues and individuals. Thus, the construction of epigenetic “mitotic” clocks that can measure the lifetime number of stem cell divisions is of paramount interest.

Methods

Building upon a dynamic model of DNA methylation gain in unmethylated CpG-rich regions, we here derive a novel mitotic clock (“epiTOC2”) that can directly estimate the cumulative number of stem cell divisions in a tissue. We compare epiTOC2 to a different mitotic model, based on hypomethylation at solo-WCGW sites (“HypoClock”), in terms of their ability to measure mitotic age of normal adult tissues and predict cancer risk.

Results

Using epiTOC2, we estimate the intrinsic stem cell division rate for different normal tissue types, demonstrating excellent agreement (Pearson correlation = 0.92, R² = 0.85, P = 3e−6) with those derived from experiment. In contrast, HypoClock’s estimates do not (Pearson correlation = 0.30, R² = 0.09, P = 0.29). We validate these results in independent datasets profiling normal adult tissue types. While both epiTOC2 and HypoClock correctly predict an increased mitotic rate in cancer, epiTOC2 is more robust and significantly better at discriminating preneoplastic lesions characterized by chronic inflammation, a major driver of tissue turnover and cancer risk. Our data suggest that DNA methylation loss at solo-WCGWs is significant only when cells are under high replicative stress and that epiTOC2 is a better mitotic age and cancer risk prediction model for normal adult tissues.

Conclusions

These results have profound implications for our understanding of epigenetic clocks and for developing cancer risk prediction or early detection assays. We propose that measurement of DNAm at the 163 epiTOC2 CpGs in adult pre-neoplastic lesions, and potentially in serum cell-free DNA, could provide the basis for building feasible pre-diagnostic or cancer risk assays. epiTOC2 is freely available from 10.5281/zenodo.2632938

Epigenetic Aging: More Than Just a Clock When It Comes to Cancer

The incidence of cancer, adjusted for secular trends, is directly related to age, and advanced chronologic age is one of the most significant risk factors for cancer. Organismal aging is associated with changes at the molecular, cellular, and tissue levels and is affected by both genetic and environmental factors. The specific mechanisms through which these age-associated molecular changes contribute to the increased risk of aging-related disease, such as cancer, are incompletely understood. DNA methylation, a prominent epigenetic mark, also changes over a lifetime as part of an "epigenetic aging" process. Here, we give an update and review of epigenetic aging, in particular, the phenomena of epigenetic drift and epigenetic clock, with regard to its implication in cancer etiology. We discuss the discovery of the DNA methylation-based biomarkers for biological tissue age and the construction of various epigenetic age estimators for human clinical outcomes and health/life span. Recent studies in various types of cancer point to the significance of epigenetic aging in tumorigenesis and its potential use for cancer risk prediction. Future studies are needed to assess the potential clinical impact of strategies focused on lowering cancer risk by preventing premature aging or promoting healthy aging.

From Colitis to Cancer: An Evolutionary Trajectory That Merges Maths and Biology

Patients with inflammatory bowel disease have an increased risk of developing colorectal cancer, and this risk is related to disease duration, extent, and cumulative inflammation burden. Carcinogenesis follows the principles of Darwinian evolution, whereby somatic cells acquire genomic alterations that provide them with a survival and/or growth advantage. Colitis represents a unique situation whereby routine surveillance endoscopy provides a serendipitous opportunity to observe somatic evolution over space and time in vivo in a human organ. Moreover, somatic evolution in colitis is evolution in the ‘fast lane': the repeated rounds of inflammation and mucosal healing that are characteristic of the disease accelerate the evolutionary process and likely provide a strong selective pressure for inflammation-adapted phenotypic traits. In this review, we discuss the evolutionary dynamics of pre-neoplastic clones in colitis with a focus on how measuring their evolutionary trajectories could deliver a powerful way to predict future cancer occurrence. Measurements of somatic evolution require an interdisciplinary approach that combines quantitative measurement of the genotype, phenotype and the microenvironment of somatic cells–paying particular attention to spatial heterogeneity across the colon–together with mathematical modeling to interpret these data within an evolutionary framework. Here we take a practical approach in discussing how and why the different “evolutionary ingredients” can and should be measured, together with our viewpoint on subsequent translation into clinical practice. We highlight the open questions in the evolution of colitis-associated cancer as a stimulus for future work.

Implications of Epigenetic Drift in Colorectal Neoplasia

Many normal tissues undergo age-related drift in DNA methylation, providing a quantitative measure of tissue age. Here, we identify and validate 781 CpG islands (CGI) that undergo significant methylomic drift in 232 normal colorectal tissues and show that these CGI continue to drift in neoplasia while retaining significant correlations across samples. However, compared with normal colon, this drift advanced (∼3-4-fold) faster in neoplasia, consistent with increased cell proliferation during neoplastic progression. The observed drift patterns were broadly consistent with modeled adenoma-to-carcinoma sojourn time distributions from colorectal cancer incidence data. These results support the hypothesis that, beginning with the founder premalignant cell, cancer precursors frequently sojourn for decades before turning into cancer, implying that the founder cell typically arises early in life. At least 77% to 89% of the observed drift variance in distal and rectal tumors was explained by stochastic variability associated with neoplastic progression, whereas only 55% of the variance was explained for proximal tumors. However, gene-CGI pairs in the proximal colon that underwent drift were significantly and primarily negatively correlated with cancer gene expression, suggesting that methylomic drift participates in the clonal evolution of colorectal cancer. Methylomic drift advanced in colorectal neoplasia, consistent with extended sojourn time distributions, which accounts for a significant fraction of epigenetic heterogeneity in colorectal cancer. Importantly, these estimated long-duration premalignant sojourn times suggest that early dietary and lifestyle interventions may be more effective than later changes in reducing colorectal cancer incidence. SIGNIFICANCE: These findings present age-related methylomic drift in colorectal neoplasia as evidence that premalignant cells can persist for decades before becoming cancerous.See related commentary by Sapienza, p. 437.

Molecular Evolution of Metaplasia to Adenocarcinoma in the Esophagus

Esophageal adenocarcinoma (EAC) develops from Barrett's esophagus (BE), a condition where the normal squamous epithelia is replaced by specialized intestinal metaplasia in response to chronic gastroesophageal acid reflux. In a minority of individuals, BE can progress to low- and high-grade dysplasia and eventually to intra-mucosal and then invasive carcinoma. BE provides researchers with a unique model to characterize the process by which a carcinoma arises from its precursor lesion. Molecular studies of BE have demonstrated that it is not simply a metaplastic tissue, but rather it harbors frequent alterations that are also present in dysplastic BE and in EAC. Both BE and EAC are characterized by loss of heterozygosity, aneuploidy, specific genetic mutations, and clonal diversity. Epigenetic abnormalities, primary alterations in DNA methylation, are also frequently seen in BE and EAC. Candidate gene and array-based approaches have demonstrated that numerous tumor suppressor genes exhibit aberrant promoter methylation, and some of these altered genes are associated with the neoplastic progression of BE. It has also been shown that the BE and EAC epigenomes are characterized by hypomethylation of intragenic and non-coding regions Recent studies have also provided new insight into the evolutionary forces underlying the molecular alterations seen in BE and EAC and into the molecular pathogenesis of EAC.

Recent advances in Barrett's esophagus

Barrett's esophagus (BE) is the only known precursor of esophageal adenocarcinoma, one of the few cancers with increasing incidence in developed countries. The pathogenesis of BE is unclear with regard to either the cellular origin of this metaplastic epithelium or the manner in which malignant transformation occurs, although recent data indicate a possible junctional origin of stem cells for BE. Treatment of BE may be achieved using endoscopic eradication therapy; however, there is a lack of discriminatory tools to identify individuals at sufficient risk for cancer development in whom intervention is warranted. Reduction in gastroesophageal reflux of gastric contents including acid is mandatory to achieve remission from BE after endoscopic ablation, and can be achieved using medical or nonmedical interventions. Research topics of greatest interest include the mechanism of BE development and transformation to cancer, risk stratification methods to identify individuals who may benefit from ablation of BE, optimization of eradication therapy, and surveillance methods to ensure that remission is maintained after eradication is achieved.

Models of epigenetic age capture patterns of DNA methylation in glioma associated with molecular subtype, survival, and recurrence

Background

Models of epigenetic aging (epigenetic clocks) have been implicated as potentially useful markers for cancer risk and prognosis. Using 2 previously published methods for modeling epigenetic age, Horvath's clock and epiTOC, we investigated epigenetic aging patterns related to World Health Organization grade and molecular subtype as well as associations of epigenetic aging with glioma survival and recurrence.

Methods

Epigenetic ages were calculated using Horvath's clock and epiTOC on 516 lower-grade glioma and 141 glioblastoma cases along with 136 nontumor (normal) brain samples. Associations of tumor epigenetic age with patient chronological age at diagnosis were assessed with correlation and linear regression, and associations were validated in an independent cohort of 203 gliomas. Contribution of epigenetic age to survival prediction was assessed using Cox proportional hazards modeling. Sixty-three samples from 18 patients with primary-recurrent glioma pairs were also analyzed and epigenetic age difference and rate of epigenetic aging of primary-recurrent tumors were correlated to time to recurrence.

Results

Epigenetic ages of gliomas were near-universally accelerated using both Horvath's clock and epiTOC compared with normal tissue. The 2 independent models of epigenetic aging were highly associated with each other and exhibited distinct aging patterns reflective of molecular subtype. EpiTOC was found to be a significant independent predictor of survival. Epigenetic aging of gliomas between primary and recurrent tumors was found to be highly variable and not significantly associated with time to recurrence.

Conclusions

We demonstrate that epigenetic aging reflects coherent modifications of the epigenome and can potentially provide additional prognostic power for gliomas.

Aging in a Relativistic Biological Space-Time

Here we present a theoretical and mathematical perspective on the process of aging. We extend the concepts of physical space and time to an abstract, mathematically-defined space, which we associate with a concept of “biological space-time” in which biological dynamics may be represented. We hypothesize that biological dynamics, represented as trajectories in biological space-time, may be used to model and study different rates of biological aging. As a consequence of this hypothesis, we show how dilation or contraction of time analogous to relativistic corrections of physical time resulting from accelerated or decelerated biological dynamics may be used to study precipitous or protracted aging. We show specific examples of how these principles may be used to model different rates of aging, with an emphasis on cancer in aging. We discuss how this theory may be tested or falsified, as well as novel concepts and implications of this theory that may improve our interpretation of biological aging.

Evolution of Barrett's esophagus through space and time at single-crypt and whole-biopsy levels

The low risk of progression of Barrett's esophagus (BE) to esophageal adenocarcinoma can lead to over-diagnosis and over-treatment of BE patients. This may be addressed through a better understanding of the dynamics surrounding BE malignant progression. Although genetic diversity has been characterized as a marker of malignant development, it is still unclear how BE arises and develops. Here we uncover the evolutionary dynamics of BE at crypt and biopsy levels in eight individuals, including four patients that experienced malignant progression. We assay eight individual crypts and the remaining epithelium by SNP array for each of 6-11 biopsies over 2 time points per patient (358 samples in total). Our results indicate that most Barrett's segments are clonal, with similar number and inferred rates of alterations observed for crypts and biopsies. Divergence correlates with geographical location, being higher near the gastro-esophageal junction. Relaxed clock analyses show that genomic instability precedes and is enhanced by genome doubling. These results shed light on the clinically relevant evolutionary dynamics of BE.

Precancer in ulcerative colitis: the role of the field effect and its clinical implications

Cumulative evidence indicates that a significant proportion of cancer evolution may occur before the development of histological abnormalities. While recent improvements in DNA sequencing technology have begun to reveal the presence of these early preneoplastic clones, the concept of 'premalignant field' was already introduced by Slaughter more than half a century ago. Also referred to as 'field effect', 'field defect' or 'field cancerization', these terms describe the phenomenon by which molecular alterations develop in normal-appearing tissue and expand to form premalignant patches with the potential to progress to dysplasia and cancer. Field effects have been well-characterized in ulcerative colitis, an inflammatory bowel disease that increases the risk of colorectal cancer. The study of the molecular alterations that define these fields is informative of mechanisms of tumor initiation and progression and has provided potential targets for early cancer detection. Herein, we summarize the current knowledge about the molecular alterations that comprise the field effect in ulcerative colitis and the clinical utility of these fields for cancer screening and prevention.

An evolutionary perspective on field cancerization

Tumorigenesis begins long before the growth of a clinically detectable lesion and, indeed, even before any of the usual morphological correlates of pre-malignancy are recognizable. Field cancerization, which is the replacement of the normal cell population by a cancer-primed cell population that may show no morphological change, is now recognized to underlie the development of many types of cancer, including the common carcinomas of the lung, colon, skin, prostate and bladder. Field cancerization is the consequence of the evolution of somatic cells in the body that results in cells that carry some but not all phenotypes required for malignancy. Here, we review the evidence of field cancerization across organs and examine the biological mechanisms that drive the evolutionary process that results in field creation. We discuss the clinical implications, principally, how measurements of the cancerized field could improve cancer risk prediction in patients with pre-malignant disease.

Evolution of Premalignant Disease

Where does cancer come from? Although the cell-of-origin is difficult to pinpoint, cancer clones harbor information about their clonal ancestries. In an effort to find cells before they evolve into a life-threatening cancer, physicians currently diagnose premalignant diseases at frequencies that substantially exceed those of clinical cancers. Cancer risk prediction relies on our ability to distinguish between which premalignant features will lead to cancer mortality and which are characteristic of inconsequential disease. Here, we review the evolution of cancer from premalignant disease, and discuss the concept that even phenotypically normal cell progenies inherently gain more malignant potential with age. We describe the hurdles of prognosticating cancer risk in premalignant disease by making reference to the underlying continuous and multivariate natures of genotypes and phenotypes and the particular challenge inherent in defining a cell lineage as "cancerized."

Identification of a key role of widespread epigenetic drift in Barrett's esophagus and esophageal adenocarcinoma

Background

Recent studies have identified age-related changes in DNA methylation patterns in normal and cancer tissues in a process that is called epigenetic drift. However, the evolving patterns, functional consequences, and dynamics of epigenetic drift during carcinogenesis remain largely unexplored. Here we analyze the evolution of epigenetic drift patterns during progression from normal squamous esophagus tissue to Barrett’s esophagus (BE) to esophageal adenocarcinoma (EAC) using 173 tissue samples from 100 (nonfamilial) BE patients, along with publically available datasets including The Cancer Genome Atlas (TCGA).

Results

Our analysis reveals extensive methylomic drift between normal squamous esophagus and BE tissues in nonprogressed BE patients, with differential drift affecting 4024 (24%) of 16,984 normally hypomethylated cytosine-guanine dinucleotides (CpGs) occurring in CpG islands. The majority (63%) of islands that include drift CpGs are associated with gene promoter regions. Island CpGs that drift have stronger pairwise correlations than static islands, reflecting collective drift consistent with processive DNA methylation maintenance. Individual BE tissues are extremely heterogeneous in their distribution of methylomic drift and encompass unimodal low-drift to bimodal high-drift patterns, reflective of differences in BE tissue age. Further analysis of longitudinally collected biopsy samples from 20 BE patients confirm the time-dependent evolution of these drift patterns. Drift patterns in EAC are similar to those in BE, but frequently exhibit enhanced bimodality and advanced mode drift. To better understand the observed drift patterns, we developed a multicellular stochastic model at the CpG island level. Importantly, we find that nonlinear feedback in the model between mean island methylation and CpG methylation rates is able to explain the widely heterogeneous collective drift patterns. Using matched gene expression and DNA methylation data in EAC from TCGA and other publically available data, we also find that advanced methylomic drift is correlated with significant transcriptional repression of ~ 200 genes in important regulatory and developmental pathways, including several checkpoint and tumor suppressor-like genes.

Conclusions

Taken together, our findings suggest that epigenetic drift evolution acts to significantly reduce the expression of developmental genes that may alter tissue characteristics and improve functional adaptation during BE to EAC progression.

Electronic supplementary material

The online version of this article (10.1186/s13148-017-0409-4) contains supplementary material, which is available to authorized users.

Modelling the molecular mechanisms of aging

The aging process is driven at the cellular level by random molecular damage that slowly accumulates with age. Although cells possess mechanisms to repair or remove damage, they are not 100% efficient and their efficiency declines with age. There are many molecular mechanisms involved and exogenous factors such as stress also contribute to the aging process. The complexity of the aging process has stimulated the use of computational modelling in order to increase our understanding of the system, test hypotheses and make testable predictions. As many different mechanisms are involved, a wide range of models have been developed. This paper gives an overview of the types of models that have been developed, the range of tools used, modelling standards and discusses many specific examples of models that have been grouped according to the main mechanisms that they address. We conclude by discussing the opportunities and challenges for future modelling in this field.

Spatial Measures of Genetic Heterogeneity During Carcinogenesis

In this work we explore the temporal dynamics of spatial heterogeneity during the process of tumorigenesis from healthy tissue. We utilize a spatial stochastic model of mutation accumulation and clonal expansion in a structured tissue to describe this process. Under a two-step tumorigenesis model, we first derive estimates of a non-spatial measure of diversity: Simpson's Index, which is the probability that two individuals sampled at random from the population are identical, in the premalignant population. We next analyze two new measures of spatial population heterogeneity. In particular we study the typical length scale of genetic heterogeneity during the carcinogenesis process and estimate the extent of a surrounding premalignant clone given a clinical observation of a premalignant point biopsy. This evolutionary framework contributes to a growing literature focused on developing a better understanding of the spatial population dynamics of cancer initiation and progression.