Predicting colorectal cancer risk from adenoma detection via a two-type branching process model

Mathematical modeling the gene mechanism of colorectal cancer and the effect of radiation exposure

Cancer is the result of continuous accumulation of gene mutations in normal cells. The number of mutations is different in different types of cancer and even in different patients with the same type of cancer. Therefore, studying all possible numbers of gene mutations in malignant cells is of great value for the understanding of tumorigenesis and the treatment of cancer. To this end, we applied a stochastic mathematical model considering the clonal expansion of any premalignant cells with different mutations to analyze the number of gene mutations in colorectal cancer. The age-specific colorectal cancer incidence rates from the Surveillance, Epidemiology and End Results (SEER) registry in the United States and the Life Span Study (LSS) in Nagasaki and Hiroshima, Japan are chosen to test the reasonableness of the model. Our fitting results indicate that the transformation from normal cells to malignant cells may undergo two to five driver mutations for colorectal cancer patients without radiation-exposed environment, two to four driver mutations for colorectal cancer patients with low level radiation-exposure, and two to three driver mutations for colorectal cancer patients with high level radiation-exposure. Furthermore, the net growth rate of the mutated cells with radiation-exposure was is higher than that of the mutated cells without radiation-exposure for the models with two to five driver mutations. These results suggest that radiation environment may affect the clonal expansion of cells and significantly affect the development of tumors.

Mathematical modeling the order of driver gene mutations in colorectal cancer

Tumor heterogeneity is a large obstacle for cancer study and treatment. Different cancer patients may involve different combinations of gene mutations or the distinct regulatory pathways for inducing the progression of tumor. Investigating the pathways of gene mutations which can cause the formation of tumor can provide a basis for the personalized treatment of cancer. Studies suggested that KRAS, APC and TP53 are the most significant driver genes for colorectal cancer. However, it is still an open issue regarding the detailed mutation order of these genes in the development of colorectal cancer. For this purpose, we analyze the mathematical model considering all orders of mutations in oncogene, KRAS and tumor suppressor genes, APC and TP53, and fit it on data describing the incidence rates of colorectal cancer at different age from the Surveillance Epidemiology and End Results registry in the United States for the year 1973-2013. The specific orders that can induce the development of colorectal cancer are identified by the model fitting. The fitting results indicate that the mutation order with KRAS → APC → TP53, APC → TP53 → KRAS and APC → KRAS → TP53 explain the age-specific risk of colorectal cancer with very well. Furthermore, eleven pathways of gene mutations can be accepted for the mutation order of genes with KRAS → APC → TP53, APC → TP53 → KRAS and APC → KRAS → TP53, and the alternation of APC acts as the initiating or promoting event in the colorectal cancer. The estimated mutation rates of cells in the different pathways demonstrate that genetic instability must exist in colorectal cancer with alterations of genes, KRAS, APC and TP53.

Shape-specific characterization of colorectal adenoma growth and transition to cancer with stochastic cell-based models

Colorectal adenoma are precursor lesions on the pathway to cancer. Their removal in screening colonoscopies has markedly reduced rates of cancer incidence and death. Generic models of adenoma growth and transition to cancer can guide the implementation of screening strategies. But adenoma shape has rarely featured as a relevant risk factor. Against this backdrop we aim to demonstrate that shape influences growth dynamics and cancer risk. Stochastic cell-based models are applied to a data set of 197,347 Bavarian outpatients who had colonoscopies from 2006-2009, 50,649 patients were reported with adenoma and 296 patients had cancer. For multi-stage clonal expansion (MSCE) models with up to three initiating stages parameters were estimated by fits to data sets of all shapes combined, and of sessile (70% of all adenoma), peduncular (17%) and flat (13%) adenoma separately for both sexes. Pertinent features of adenoma growth present themselves in contrast to previous assumptions. Stem cells with initial molecular changes residing in early adenoma predominantly multiply within two-dimensional structures such as crypts. For these cells mutation and division rates decrease with age. The absolute number of initiated cells in an adenoma of size 1 cm is small around 103, related to all bulk cells they constitute a share of about 10-5. The notion of very few proliferating stem cells with age-decreasing division rates is supported by cell marker experiments. The probability for adenoma transiting to cancer increases with squared linear size and shows a shape dependence. Compared to peduncular and flat adenoma, it is twice as high for sessile adenoma of the same size. We present a simple mathematical expression for the hazard ratio of interval cancers which provides a mechanistic understanding of this important quality indicator. We conclude that adenoma shape deserves closer consideration in screening strategies and as risk factor for transition to cancer.

A review on mechanobiology of cell adhesion networks in different stages of sporadic colorectal cancer to explain its tumorigenesis

Sporadic colorectal cancer (CRC) is strongly linked to extraneous factors, like poor diet and lifestyle, but not to inherent factors like familial genetics. The changes at the epigenomics and signalling pathways are known across the sporadic CRC stages. The catch is that temporal information of the onset, the feedback loop, and the crosstalk of signalling and noise are still unclear. This makes it challenging to diagnose and treat colon cancer effectively with no relapse. Various microbial cells and native cells of the colon, contribute to sporadic CRC development. These cells secrete autocrine and paracrine for their bioenergetics and communications with other cell types. Imbalances of the biochemicals affect the epithelial lining of colon. One side of this epithelial lining is interfacing the dense colon tissue, while the other side is exposed to microbiota and excrement from the lumen. Hence, the epithelial lining is prone to tumorigenesis due to the influence of both biochemical and mechanical cues from its complex surrounding. The role of physical transformations in tumorigenesis have been limitedly discussed. In this context, cellular and tissue structures, and force transductions are heavily regulated by cell adhesion networks. These networks include cell anchoring mechanism to the surrounding, cell structural integrity mechanism, and cell effector molecules. This review will focus on the progression of the sporadic CRC stages that are governed by the underlaying cell adhesion networks within the epithelial cells. Additionally, current and potential technologies and therapeutics that target cell adhesion networks for treatments of sporadic CRC will be incorporated.

Modeling age-specific incidence of colon cancer via niche competition

Cancer development is a multistep process often starting with a single cell in which a number of epigenetic and genetic alterations have accumulated thus transforming it into a tumor cell. The progeny of such a single benign tumor cell expands in the tissue and can at some point progress to malignant tumor cells until a detectable tumor is formed. The dynamics from the early phase of a single cell to a detectable tumor with billions of tumor cells are complex and still not fully resolved, not even for the well-known prototype of multistage carcinogenesis, the adenoma-adenocarcinoma sequence of colorectal cancer. Mathematical models of such carcinogenesis are frequently tested and calibrated based on reported age-specific incidence rates of cancer, but they usually require calibration of four or more parameters due to the wide range of processes these models aim to reflect. We present a cell-based model, which focuses on the competition between wild-type and tumor cells in colonic crypts, with which we are able reproduce epidemiological incidence rates of colon cancer. Additionally, the fraction of cancerous tumors with precancerous lesions predicted by the model agree with clinical estimates. The correspondence between model and reported data suggests that the fate of tumor development is majorly determined by the early phase of tumor growth and progression long before a tumor becomes detectable. Due to the focus on the early phase of tumor development, the model has only a single fit parameter, the time scale set by an effective replacement rate of stem cells in the crypt. We find this effective rate to be considerable smaller than the actual replacement rate, which implies that the time scale is limited by the processes succeeding clonal conversion of crypts.

Cancer development is a multistep process often starting with a single cell turning into a tumor cell whose progeny growths via clonal expansion into a macroscopic tumor with billions of cells. While experimental insight exists on the cellular scale and cancer registries provide statistics on detectable tumors, the complex dynamics leading from the microscopic cellular scale to a macroscopic tumor is still not fully resolved. Models of cancer biology are commonly used to explain incidence rates but usually require the fit of several biological parameters due to the complexity of the incorporated processes. We employ a cell-based model based on the competition in colonic crypts, to reproduce epidemiological age-specific incidence rates of colon cancer. Due to the focus on the early stage of tumor development, only the time scale in the model has to be calibrated. The agreement between theoretical prediction and epidemiological observation suggests that the fate of tumor development is dominated by the early phase of tumor development long before a tumor becomes detectable.

Longitudinal changes in personalized platelet count metrics are good indicators of initial 3-year outcome in colorectal cancer

BACKGROUND

Platelet count or complete blood count (CBC)-based ratios including lymphocyte-to-monocyte (LMR), neutrophil-to-lymphocyte (NLR), hemoglobin-to-platelet (HPR), red blood cell count distribution width-to-platelet (RPR), and platelet-to-lymphocyte (PLR) ratio are good predictors of colorectal cancer (CRC) survival. Their change in time is not well documented, however.

AIM

To investigate the effect of longitudinal CBC ratio changes on CRC survival and their possible associations with clinicopathological properties, comorbidities, and anamnestic data.

METHODS

A retrospective longitudinal observational study was conducted with the inclusion of 835 CRC patients, who attended at Semmelweis University, Budapest. CBC ratios and two additional newly defined personalized platelet count metrics (pPLTD and pPLTS, the platelet counts relative to the measurement at the time of CRC diagnosis and to the one 4-6 wk after tumor removal surgery, respectively) were recorded.

RESULTS

The 835 CRC patients had a total of 4608 measurements (5.52 visits/patient, in average). Longitudinal survival models revealed that the increases/decreases in LMR [hazard ratio (HR): 0.4989, P < 0.0001], NLR (HR: 1.0819, P < 0.0001), HPR (HR: 0.0533, P = 0.0038), pPLTD (HR: 4.9229, P < 0.0001), and pPLTS (HR: 4.7568, P < 0.0001) values were poor prognostic signs of disease-specific survival. The same was obtained for all-cause mortality. Most abnormal changes occurred within the first 3 years after the diagnosis of CRC. RPR and PLR had an only marginal effect on disease-specific (P = 0.0675) and all-cause mortality (Bayesian 95% credible interval: 0.90-186.05), respectively.

CONCLUSION

LMR, NLR, and HPR are good metrics to follow the prognosis of the disease. pPLTD and pPLTS perform just as well as the former, while the use of RPR and PLR with the course of the disease is not recommended. Early detection of the abnormal changes in pPLTD, pPLTS, LMR, NLR, or HPR may alert the practicing oncologist for further therapy decisions in a timely manner.

Mathematical modeling for mutator phenotype and clonal selection advantage in the risk analysis of lung cancer

Cancer is one of the leading diseases for human mortality. Although substantial research works have been conducted to investigate the initiation and progression of cancer disease, it is still an active debate regarding the function of mutations conferring a clone advantage and the importance of mutator phenotypes caused by the mutation of stability genes. To address this issue further, we develop a mathematical model based on the incidence data of non-small cell lung cancer and small cell lung cancer from the Surveillance Epidemiology and End Results registry in the USA. The key biological parameters have been analyzed to investigate the potential effective measures for inhibiting the risk of lung cancer. Although the first event is the gene mutation that leads to clonal expansion of cells for lung cancer, the simulation results show that the clonal advantage of cancer cells alone is insufficient to cause tumorigenesis. Our analysis suggests that mutations in genes that keep genetic stability are critical in the development of lung cancer. This implies that mutator phenotype is an important indicator for the diagnosis of lung cancer, which can enable early detection and treatment to reduce the risk of lung cancer effectively. Furthermore, the parameter analysis indicates that it would be highly effective to control the risk of lung cancer by inhibiting the transformation rate from the normal cells to mutated cells and the clonal expansion of cells with fewer gene mutations.

Aspirin's effect on kinetic parameters of cells contributes to its role in reducing incidence of advanced colorectal adenomas, shown by a multiscale computational study

Aspirin intake has been shown to lead to significant protection against colorectal cancer, for example with an up to twofold reduction in colorectal adenoma incidence rates at higher doses. The mechanisms contributing to protection are not yet fully understood. While aspirin is an anti-inflammatory drug and can thus influence the tumor microenvironment, in vitro and in vivo experiments have recently shown that aspirin can also have a direct effect on cellular kinetics and fitness. It reduces the rate of tumor cell division and increases the rate of cell death. The question arises whether such changes in cellular fitness are sufficient to significantly contribute to the epidemiologically observed protection. To investigate this, we constructed a class of mathematical models of in vivo evolution of advanced adenomas, parameterized it with available estimates, and calculated population level incidence. Fitting the predictions to age incidence data revealed that only a model that included colonic crypt competition can account for the observed age-incidence curve. This model was then used to predict modified incidence patterns if cellular kinetics were altered as a result of aspirin treatment. We found that changes in cellular fitness that were within the experimentally observed ranges could reduce advanced adenoma incidence by a sufficient amount to account for age incidence data in aspirin-treated patient cohorts. While the mechanisms that contribute to the protective effect of aspirin are likely complex and multi-factorial, our study demonstrates that direct aspirin-induced changes of tumor cell fitness can significantly contribute to epidemiologically observed reduced incidence patterns.

Epidemiology of neoplastic colorectal polyps in a Caribbean country

Screening is practiced to identify and remove neoplastic colorectal polyps prior to their transformation into colorectal cancer (CRC). The aim of the present study was to document the epidemiology of neoplastic colorectal polyps in order to obtain important data that may then be used to guide screening protocols in Jamaica. For this purpose, an audit was performed to identify all consecutive patients who had neoplastic polyps detected at a screening colonoscopy at a facility in Jamaica from January 1, 2015 to December 30, 2018. The following data were collected: Patient demographics, polyp location, polyp synchronicity and histopathological information. The results revealed that a total of 480 colonoscopies were performed over the study period. With the exclusion of 2 patients with innumerable polyps as a part of polyposis syndrome, there were a total of 92 neoplastic polyps in 68 patients. Polyps were most commonly located in the right colon (55.6%), followed by the left colon (38%) and rectum (6.5%). Upon the histological evaluation, 63 polyps were found to be benign adenomas with mild to moderate dysplastic alterations, 15 were adenomas with severe dysplasia and/or carcinoma in situ and 14 had foci of invasive carcinomas. On the whole, the present study demonstrates that ~15% of the patients screened had neoplastic polyps that were recognized as precursor lesions for CRC. The majority of these were in the right colon. These results support the call for policy makers to institute national CRC screening programs, such as the National Comprehensive Cancer Network harmonized guidelines for the Caribbean.

Risk of lung cancer due to external environmental factor and epidemiological data analysis

Lung cancer is a cancer with the fastest growth in the incidence and mortality all over the world, which is an extremely serious threat to human's life and health. Evidences reveal that external environmental factors are the key drivers of lung cancer, such as smoking, radiation exposure and so on. Therefore, it is urgent to explain the mechanism of lung cancer risk due to external environmental factors experimentally and theoretically. However, it is still an open issue regarding how external environment factors affect lung cancer risk. In this paper, we summarize the main mathematical models involved the gene mutations for cancers, and review the application of the models to analyze the mechanism of lung cancer and the risk of lung cancer due to external environmental exposure. In addition, we apply the model described and the epidemiological data to analyze the influence of external environmental factors on lung cancer risk. The result indicates that radiation can cause significantly an increase in the mutation rate of cells, in particular the mutation in stability gene that leads to genomic instability. These studies not only can offer insights into the relationship between external environmental factors and human lung cancer risk, but also can provide theoretical guidance for the prevention and control of lung cancer.

Colorectal EMR outcomes in octogenarians versus younger patients referred for removal of large (≥20 mm) nonpedunculated polyps

BACKGROUND AND AIMS

Data are limited on safety and outcomes of colorectal EMR in octogenarians (≥80 years old). We sought to review outcome data for patients aged ≥80 in a prospectively collected database of patients referred for large polyp removal.

METHODS

We retrospectively evaluated a database of patients referred for large (≥20 mm) nonpedunculated polyp removal. From 2000 to 2019, we compared the rates of follow-up, recurrence, adverse events, and synchronous neoplasia detection between younger patients and patients aged ≥80.

RESULTS

There were 167 patients aged ≥80 years and 1686 <80 years. Patients in the elderly group returned for surveillance less often (67.1% vs 75.1%, P = .024), had greater first follow-up recurrence rates (27.5% vs 13.8%, P < .001), but had similar adverse event rates (1.8% vs 2.8%, P = .619) compared with younger patients. Rates of synchronous neoplasia were similar and high in both groups.

CONCLUSIONS

EMR is safe and well tolerated for large polyp removal in patients over 80 years old. Patients aged ≥80 years are less likely to present for follow-up after EMR. They had a higher recurrence rate and a similarly high prevalence of synchronous precancerous lesions. Follow-up after EMR should be encouraged in the elderly, and an attempt to clear the colon of synchronous disease at the time of the initial EMR may be warranted.

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.

A mathematical model of ctDNA shedding predicts tumor detection size

Early cancer detection aims to find tumors before they progress to an incurable stage. To determine the potential of circulating tumor DNA (ctDNA) for cancer detection, we developed a mathematical model of tumor evolution and ctDNA shedding to predict the size at which tumors become detectable. From 176 patients with stage I to III lung cancer, we inferred that, on average, 0.014% of a tumor cell's DNA is shed into the bloodstream per cell death. For annual screening, the model predicts median detection sizes of 2.0 to 2.3 cm representing a ~40% decrease from the current median detection size of 3.5 cm. For informed monthly cancer relapse testing, the model predicts a median detection size of 0.83 cm and suggests that treatment failure can be detected 140 days earlier than with imaging-based approaches. This mechanistic framework can help accelerate clinical trials by precomputing the most promising cancer early detection strategies.

Mathematical model of colorectal cancer initiation

Quantifying evolutionary dynamics of cancer initiation and progression can provide insights into more effective strategies of early detection and treatment. Here we develop a mathematical model of colorectal cancer initiation through inactivation of two tumor suppressor genes and activation of one oncogene, accounting for the well-known path to colorectal cancer through loss of tumor suppressors APC and TP53 and gain of the KRAS oncogene. In the model, we allow mutations to occur in any order, leading to a complex network of premalignant mutational genotypes on the way to colorectal cancer. We parameterize the model using experimentally measured parameter values, many of them only recently available, and compare its predictions to epidemiological data on colorectal cancer incidence. We find that the reported lifetime risk of colorectal cancer can be recovered using a mathematical model of colorectal cancer initiation together with experimentally measured mutation rates in colorectal tissues and proliferation rates of premalignant lesions. We demonstrate that the order of driver events in colorectal cancer is determined primarily by the fitness effects that they provide, rather than their mutation rates. Our results imply that there may not be significant immune suppression of untreated benign and malignant colorectal lesions.