Multifocality and recurrence risk: a quantitative model of field cancerization

A computational model for the cancer field effect

Introduction

The Cancer Field Effect describes an area of pre-cancerous cells that results from continued exposure to carcinogens. Cells in the cancer field can easily develop into cancer. Removal of the main tumor mass might leave the cancer field behind, increasing risk of recurrence.

Methods

The model we propose for the cancer field effect is a hybrid cellular automaton (CA), which includes a multi-layer perceptron (MLP) to compute the effects of the carcinogens on the gene expression of the genes related to cancer development. We use carcinogen interactions that are typically associated with smoking and alcohol consumption and their effect on cancer fields of the tongue.

Results

Using simulations we support the understanding that tobacco smoking is a potent carcinogen, which can be reinforced by alcohol consumption. The effect of alcohol alone is significantly less than the effect of tobacco. We further observe that pairing tumor excision with field removal delays recurrence compared to tumor excision alone. We track cell lineages and find that, in most cases, a polyclonal field develops, where the number of distinct cell lineages decreases over time as some lineages become dominant over others. Finally, we find tumor masses rarely form via monoclonal origin.

Computational modeling of locoregional recurrence with spatial structure identifies tissue-specific carcinogenic profiles

Introduction

Local and regional recurrence after surgical intervention is a significant problem in cancer management. The multistage theory of carcinogenesis precisely places the presence of histologically normal but mutated premalignant lesions surrounding the tumor - field cancerization, as a significant cause of cancer recurrence. The relationship between tissue dynamics, cancer initiation and cancer recurrence in multistage carcinogenesis is not well known.

Methods

This study constructs a computational model for cancer initiation and recurrence by combining the Moran and branching processes in which cells requires 3 or more mutations to become malignant. In addition, a spatial structure-setting is included in the model to account for positional relativity in cell turnover towards malignant transformation. The model consists of a population of normal cells with no mutation; several populations of premalignant cells with varying number of mutations and a population of malignant cells. The model computes a stage of cancer detection and surgery to eliminate malignant cells but spares premalignant cells and then estimates the time for malignant cells to re-emerge.

Results

We report the cellular conditions that give rise to different patterns of cancer initiation and the conditions favoring a shorter cancer recurrence by analyzing premalignant cell types at the time of surgery. In addition, the model is fitted to disease-free clinical data of 8,957 patients in 27 different cancer types; From this fitting, we estimate the turnover rate per month, relative fitness of premalignant cells, growth rate and death rate of cancer cells in each cancer type.

Discussion

Our study provides insights into how to identify patients who are likely to have a shorter recurrence and where to target the therapeutic intervention.

A spatial mutation model with increasing mutation rates

We consider a spatial model of cancer in which cells are points on the d-dimensional torus $\mathcal{T}=[0,L]^d$ , and each cell with $k-1$ mutations acquires a kth mutation at rate $\mu_k$ . We assume that the mutation rates $\mu_k$ are increasing, and we find the asymptotic waiting time for the first cell to acquire k mutations as the torus volume tends to infinity. This paper generalizes results on waiting for $k\geq 3$ mutations in Foo et al. (2020), which considered the case in which all of the mutation rates $\mu_k$ are the same. In addition, we find the limiting distribution of the spatial distances between mutations for certain values of the mutation rates.

Mathematical Modeling of Locoregional Recurrence Caused by Premalignant Lesions Formed Before Initial Treatment

Locoregional recurrence after surgery is a major unresolved issue in cancer treatment. Premalignant lesions are considered a cause of cancer recurrence. A study showed that premalignant lesions surrounding the primary tumor drove a high local cancer recurrence rate after surgery in head and neck cancer. Based on the multistage theory of carcinogenesis, cells harboring an intermediate number of mutations are not cancer cells yet but have a higher risk of becoming cancer than normal cells. This study constructed a mathematical model for cancer initiation and recurrence by combining the Moran and branching processes in which cells require two specific mutations to become malignant. There are three populations in this model: (i) normal cells with no mutation, (ii) premalignant cells with one mutation, and (iii) cancer cells with two mutations. The total number of healthy tissue is kept constant to represent homeostasis, and there is a rare chance of mutation every time a cell divides. If a cancer cell with two mutations arises, the cancer population proliferates, violating the homeostatic balance of the tissue. Once the number of cancer cells reaches a certain size, we conduct computational resection and remove the cancer cell population, keeping the ratio of normal and premalignant cells in the tissue unchanged. After surgery, we considered tissue dynamics and eventually observed the second appearance of cancer cells as recurrence. Consequently, we computationally revealed the conditions where the time to recurrence became short by parameter sensitivity analysis. Particularly, when the premalignant cells’ fitness is higher than normal cells, the proportion of premalignant cells becomes large after the surgical resection. Moreover, the mathematical model was fitted to clinical data on disease-free survival of 1,087 patients in 23 cancer types from the TCGA database. Finally, parameter values of tissue dynamics are estimated for each cancer type, where the likelihood of recurrence can be elucidated. Thus, our approach provides insights into the concept to identify the patients likely to experience recurrence as early as possible.

Lichen Sclerosis is Associated With a High Rate of Local Failure After Radio(chemo)therapy for Vulvar Cancer

AIMS

Radio(chemo)therapy plays an important role in the treatment of vulvar cancer, either as postoperative treatment or as definitive treatment in patients who present with inoperable disease. Only limited data are available regarding outcome after modern state of the art radio(chemo)therapy and more information regarding prognostic factors are warranted. The aim of this study was to evaluate disease outcomes after radio(chemo)therapy in patients with vulvar cancer with special emphasis on the impact of lichen sclerosis on local control.

MATERIALS AND METHODS

All consecutive patients (n = 109) from the western half of Denmark who were treated with definitive (n = 52) or postoperative (n = 57) radio(chemo)therapy between January 2013 and January 2020 were included. Local control, cause-specific survival and overall survival, as well as morbidity, were analysed using Kaplan-Meier statistics. Prognostic factors for local control were analysed in univariate and multivariate analysis.

RESULTS

At a median follow-up of 35 (4-95) months, 46 (42.0%) patients were diagnosed with recurrence. Eighty per cent of the recurrences were located to the vulva region, leading to a 5-year local control of 58.9% (confidence interval 47.9-69.9). Cause-specific survival was 62.9% (confidence interval 53.1-72.7), whereas overall survival was 58.0% (confidence interval 47.6-68.5). Grade 3-4 morbidity was diagnosed in 10 (9%) patients. Lichen sclerosis (hazard ratio 3.89; confidence interval 1.93-7.79) was an independent risk factors for local recurrence. Patients without lichen sclerosis had a 5-year local control rate of 83.6% (confidence interval 67.2-99.0) and 62.6% (confidence interval 43.2-82.0) after postoperative and definitive radio(chemo)therapy, respectively. In patients with lichen sclerosis, the local control rate was 44.0% (confidence interval 19.3-69.0) and 17.6% (confidence interval 0-30.0) after postoperative and definitive radio(chemo)therapy, respectively.

CONCLUSION

Radio(chemo)therapy plays an important role in the treatment of vulvar cancer. However, despite dose escalation, a substantial proportion of patients experienced local relapse. Pre-existing lichen sclerosis seems to have a significant impact on the risk of recurrence. This should influence surveillance programmes for these patients.

Intra-operative point-of-procedure delineation of oral cancer margins using optical coherence tomography

OBJECTIVES

Surgical margin status is a significant determinant of treatment outcome in oral cancer. Negative surgical margins can decrease the loco-regional recurrence by five-fold. The current standard of care of intraoperative clinical examination supplemented by histological frozen section, can result in a risk of positive margins from 5 to 17 percent. In this study, we attempted to assess the utility of intraoperative optical coherence tomography (OCT) imaging with automated diagnostic algorithm to improve on the current method of clinical evaluation of surgical margin in oral cancer.

MATERIALS AND METHODS

We have used a modified handheld OCT device with automated algorithm based diagnostic platform for imaging. Intraoperatively, images of 125 sites were captured from multiple zones around the tumor of oral cancer patients (n = 14) and compared with the clinical and pathologic diagnosis.

RESULTS

OCT showed sensitivity and specificity of 100%, equivalent to histological diagnosis (kappa, ĸ = 0.922), in detection of malignancy within tumor and tumor margin areas. In comparison, for dysplastic lesions, OCT-based detection showed a sensitivity of 92.5% and specificity of 68.8% and a moderate concordance with histopathology diagnosis (ĸ = 0.59). Additionally, the OCT scores could significantly differentiate squamous cell carcinoma (SCC) from dysplastic lesions (mild/moderate/severe; p ≤ 0.005) as well as the latter from the non-dysplastic lesions (p ≤ 0.05).

CONCLUSION

The current challenges associated with clinical examination-based margin assessment could be improved with intra-operative OCT imaging. OCT is capable of identifying microscopic tumor at the surgical margins and demonstrated the feasibility of mapping of field cancerization around the tumor.

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.

The transformation of the nuclear nanoarchitecture in human field carcinogenesis

Morphological alterations of the nuclear texture are a hallmark of carcinogenesis. At later stages of disease, these changes are well characterized and detectable by light microscopy. Evidence suggests that similar albeit nanoscopic alterations develop at the predysplastic stages of carcinogenesis. Using the novel optical technique partial wave spectroscopic microscopy, we identified profound changes in the nanoscale chromatin topology in microscopically normal tissue as a common event in the field carcinogenesis of many cancers. In particular, higher-order chromatin structure at supranucleosomal length scales (20-200 nm) becomes exceedingly heterogeneous, a measure we quantify using the disorder strength (L_d ) of the spatial arrangement of chromatin density. Here, we review partial wave spectroscopic nanocytology clinical studies and the technology's promise as an early cancer screening technology.

An exactly solvable, spatial model of mutation accumulation in cancer

One of the hallmarks of cancer is the accumulation of driver mutations which increase the net reproductive rate of cancer cells and allow them to spread. This process has been studied in mathematical models of well mixed populations, and in computer simulations of three-dimensional spatial models. But the computational complexity of these more realistic, spatial models makes it difficult to simulate realistically large and clinically detectable solid tumours. Here we describe an exactly solvable mathematical model of a tumour featuring replication, mutation and local migration of cancer cells. The model predicts a quasi-exponential growth of large tumours, even if different fragments of the tumour grow sub-exponentially due to nutrient and space limitations. The model reproduces clinically observed tumour growth times using biologically plausible rates for cell birth, death, and migration rates. We also show that the expected number of accumulated driver mutations increases exponentially in time if the average fitness gain per driver is constant, and that it reaches a plateau if the gains decrease over time. We discuss the realism of the underlying assumptions and possible extensions of the model.

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.

Quantifying the Dynamics of Field Cancerization in Tobacco-Related Head and Neck Cancer: A Multiscale Modeling Approach

High rates of local recurrence in tobacco-related head and neck squamous cell carcinoma (HNSCC) are commonly attributed to unresected fields of precancerous tissue. Because they are not easily detectable at the time of surgery without additional biopsies, there is a need for noninvasive methods to predict the extent and dynamics of these fields. Here, we developed a spatial stochastic model of tobacco-related HNSCC at the tissue level and calibrated the model using a Bayesian framework and population-level incidence data from the Surveillance, Epidemiology, and End Results (SEER) registry. Probabilistic model analyses were performed to predict the field geometry at time of diagnosis, and model predictions of age-specific recurrence risks were tested against outcome data from SEER. The calibrated models predicted a strong dependence of the local field size on age at diagnosis, with a doubling of the expected field diameter between ages at diagnosis of 50 and 90 years, respectively. Similarly, the probability of harboring multiple, clonally unrelated fields at the time of diagnosis was found to increase substantially with patient age. On the basis of these findings, we hypothesized a higher recurrence risk in older than in younger patients when treated by surgery alone; we successfully tested this hypothesis using age-stratified outcome data. Further clinical studies are needed to validate the model predictions in a patient-specific setting. This work highlights the importance of spatial structure in models of epithelial carcinogenesis and suggests that patient age at diagnosis may be a critical predictor of the size and multiplicity of precancerous lesions. Cancer Res; 76(24); 7078-88. ©2016 AACR.

Adjacent Lichen Sclerosis predicts local recurrence and second field tumour in women with vulvar squamous cell carcinoma

OBJECTIVE

In this study, we investigated if the presence of histologically abnormal epithelium adjacent to the primary tumour influenced the frequency, timing, and topography of local vulvar recurrences (LVR) following treatment for squamous cell carcinoma of the vulva (VSCC).

METHODS

The study population comprised a cohort of 201 consecutive cases with incident VSCC. LVR were categorised as local relapses (LR) if they occurred <2cm from the tumour margins, and as second field tumours (SFT) when ≥2cm from these margins. Univariable and multivariable competing risk modelling was performed to identify the prognostic factors associated with local disease recurrence.

RESULTS

The characterization of the epithelium adjacent to the invasive component was possible for 199 (99.0%) patients. Of these, 171 (85.9%) were found to have intraepithelial abnormalities found adjacent to the surgical specimen. Multivariable analyses revealed that, following adjustment, Lichen Sclerosis (LS) was associated with an increase in the incidence of LVR, LR and SFT (SHRs: 3.4, 2.7 and 4.4, respectively). Although the incidence of LR and SFT in women with LS associated VSCC was similar, the peak incidence of SFT occurred more than two years before that of LR.

CONCLUSIONS

Women with VSCC arising in a field of LS may continue to have an increased risk of developing LR and SFT for many years after resection of their primary tumour. Our study suggests that these women should be followed up more regularly so that LVR can be detected earlier; unless a more robust surveillance programme or chemopreventative treatments become available.

Spatial Moran models, II: cancer initiation in spatially structured tissue

We study the accumulation and spread of advantageous mutations in a spatial stochastic model of cancer initiation on a lattice. The parameters of this general model can be tuned to study a variety of cancer types and genetic progression pathways. This investigation contributes to an understanding of how the selective advantage of cancer cells together with the rates of mutations driving cancer, impact the process and timing of carcinogenesis. These results can be used to give insights into tumor heterogeneity and the "cancer field effect," the observation that a malignancy is often surrounded by cells that have undergone premalignant transformation.

A Computational Modeling Approach for Deriving Biomarkers to Predict Cancer Risk in Premalignant Disease

The lack of effective biomarkers for predicting cancer risk in premalignant disease is a major clinical problem. There is a near-limitless list of candidate biomarkers, and it remains unclear how best to sample the tissue in space and time. Practical constraints mean that only a few of these candidate biomarker strategies can be evaluated empirically, and there is no framework to determine which of the plethora of possibilities is the most promising. Here, we have sought to solve this problem by developing a theoretical platform for in silico biomarker development. We construct a simple computational model of carcinogenesis in premalignant disease and use the model to evaluate an extensive list of tissue sampling strategies and different molecular measures of these samples. Our model predicts that (i) taking more biopsies improves prognostication, but with diminishing returns for each additional biopsy; (ii) longitudinally collected biopsies provide slightly more prognostic information than a single biopsy collected at the latest possible time point; (iii) measurements of clonal diversity are more prognostic than measurements of the presence or absence of a particular abnormality and are particularly robust to confounding by tissue sampling; and (iv) the spatial pattern of clonal expansions is a particularly prognostic measure. This study demonstrates how the use of a mechanistic framework provided by computational modeling can diminish empirical constraints on biomarker development.

A spatial model predicts that dispersal and cell turnover limit intratumour heterogeneity

Most cancers in humans are large, measuring centimetres in diameter, and composed of many billions of cells. An equivalent mass of normal cells would be highly heterogeneous as a result of the mutations that occur during each cell division. What is remarkable about cancers is that virtually every neoplastic cell within a large tumour often contains the same core set of genetic alterations, with heterogeneity confined to mutations that emerge late during tumour growth. How such alterations expand within the spatially constrained three-dimensional architecture of a tumour, and come to dominate a large, pre-existing lesion, has been unclear. Here we describe a model for tumour evolution that shows how short-range dispersal and cell turnover can account for rapid cell mixing inside the tumour. We show that even a small selective advantage of a single cell within a large tumour allows the descendants of that cell to replace the precursor mass in a clinically relevant time frame. We also demonstrate that the same mechanisms can be responsible for the rapid onset of resistance to chemotherapy. Our model not only provides insights into spatial and temporal aspects of tumour growth, but also suggests that targeting short-range cellular migratory activity could have marked effects on tumour growth rates.

The efficacy of a photolyase-based device on the cancerization field: a clinical and thermographic study

Background

At skin level, a cancerization field (CF) indicates some chronically photoexposed areas in which, besides a primary tumor, histological or biomolecular modifications without clinical signs are present. Active telethermography (ATT) allows us to observe the imaging of a hyperthermic halo (HH) surrounding the tumor . The Authors hypothesize HH as a possible expression of CF.

Objectives

The aim of this study were to verify whether HHs have the same histological or immunohistochemical characteristics as the CF and, secondly, to evaluate the efficacy of a device containing the enzyme photolyase in modifying thermographic parameters in these area.

Methods

The study included 30 patients affected by actinic keratosis, evaluated clinically and by ATT at time 0 and after 3, 6 and 9 months.

Results

The ATT showed the presence of HHs in all the patients and, after the treatment, a significant modification of both the extension of these areas and the thermal parameters. In 5 patients for whom, while operated, two other biopsies were performed, respectively on the HH and on a perilesional non-hyperthermic area, in the HH, we detected a p53 and Ki 67 over-expression.

Conclusions

Our results indicate that ATT could represent a useful paraclinic method in identifying CFs in subjects at risk.

Open questions and novel concepts in oral cancer surgery

The persistence of cancerous cells after surgery in oral squamous cell carcinoma (OSCC) represents a major challenge, as it often leads to local recurrences and secondary primary tumors, which are eventually responsible for a large proportion of deaths. This persistence is currently evaluated by histological analyses. In this review we discuss some important pitfalls of the histopathological analysis, such as margin evaluation, specimen shrinkage and T staging. In addition, we critically analyze the appropriateness of current surgical techniques in relation to the concept of field cancerization. Finally, we describe some novel imaging and molecular approaches, which might be useful in tailoring surgical resections and encourage the use of OSCC animal models to explore and provide proof of concept of the feasibility and potential clinical utility of innovative surgical protocols.

HPV clearance and the neglected role of stochasticity

Clearance of anogenital and oropharyngeal HPV infections is attributed primarily to a successful adaptive immune response. To date, little attention has been paid to the potential role of stochastic cell dynamics in the time it takes to clear an HPV infection. In this study, we combine mechanistic mathematical models at the cellular level with epidemiological data at the population level to disentangle the respective roles of immune capacity and cell dynamics in the clearing mechanism. Our results suggest that chance—in form of the stochastic dynamics of basal stem cells—plays a critical role in the elimination of HPV-infected cell clones. In particular, we find that in immunocompetent adolescents with cervical HPV infections, the immune response may contribute less than 20% to virus clearance—the rest is taken care of by the stochastic proliferation dynamics in the basal layer. In HIV-negative individuals, the contribution of the immune response may be negligible.

Worldwide, 5% of all cancers are associated with the sexually transmitted human papillomavirus (HPV). The most common cancer types attributed to HPV are cervical and anal cancers, but HPV-related head and neck cancers are on the rise, too. Even though the lifetime risk of infection with HPV is as high as 80%, most infections clear spontaneously within 1–2 years, and only a small fraction progress to cancer. In order to identify who is at risk for HPV-related cancer, a better understanding of the underlying biology is of great importance. While it is generally accepted that the immune system plays a key role in HPV clearance, we investigate here a mechanism which could be equally important: the stochastic division dynamics of stem cells in the infected tissues. Combining mechanistic mathematical models at the cell-level with population-level data, we disentangle the contributions from immune system and cellular dynamics in the clearance process. We find that cellular stochasticity may play an even more important role than the immune system. Our findings shed new light onto open questions in HPV immunobiology, and may influence the way we vaccinate and screen individuals at risk of HPV-related cancers.