Dynamics of metastasis suppressor gene inactivation

For most cancer cell types, the acquisition of metastatic ability leads to clinically incurable disease. Twelve metastasis suppressor genes (MSGs) have been identified that reduce the metastatic propensity of cancer cells. If these genes are inactivated in both alleles, metastatic ability is promoted. Here, we develop a mathematical model of the dynamics of MSG inactivation and calculate the expected number of metastases formed by a tumor. We analyse the effects of increased mutation rates and different fitness values of cells with one or two inactivated alleles on the ability of a tumor to form metastases. We find that mutations that are negatively selected in the main tumor are unlikely to be responsible for the majority of metastases produced by a tumor. Most metastases-causing mutations will be present in all (or most) cells in the main tumor.     

Genetic instability and clonal expansion

Inactivation of tumor suppressor genes can lead to clonal expansion. We study the evolutionary dynamics of this process and calculate the probability that inactivation of a tumor suppressor gene is preceded by mutations in genes that confer genetic instability. Unstable cells might have a slower rate of clonal expansion than stable cells because of an increased probability of generating lethal mutations or inducing apoptosis. We show that the different growth rates of genetically stable and unstable cells during clonal expansion represent, in general, only a small disadvantage for genetic instability. The intuitive reason for this conclusion is that robust clonal expansion, where cellular birth rates are significantly greater than death rates, occurs on a much faster time scale than waiting for those mutations that allow clonal expansion. Moreover, in special cases where clonal expansion is very slow, genetically unstable cells have a higher probability to accumulate additional mutations during clonal expansion that confer a selective advantage. Clonal expansion represents a major disadvantage for genetic instability only when inactivation of the tumor suppressor gene leads to a very small increase of the cellular reproductive rate that is cancelled by the increased mortality of unstable cells.     

Endometrial cancer

Endometrial cancer is the most common gynaecological malignancy in the developed world. The majority of cases can be divided into two broad categories based on clinico-pathological and molecular characteristics; Type I oestrogen-dependent with endometrioid morphology and Type II non-oestrogen-dependent with serous papillary or clear cell morphology. As has been described for other malignancies, such as colorectal carcinoma, the transition from normal endometrium to carcinoma is thought to involve a stepwise accumulation of alterations in cellular regulatory pathways leading to dysfunctional cell growth. This article reviews the current knowledge of the molecular changes commonly associated with endometrial cancer and presents possible progression models.     

Immortalized cells as experimental models to study cancer

The development of cancer is a multi-step process in which normal cells sustain a series of genetic alterations that together program the malignant phenotype. Much of our knowledge of cancer biology results from the detailed study of specimens and cell lines derived from patient tumors. While these approaches continue to yield critical information regarding the identity, number, and types of alterations found in human tumors, further progress in understanding the molecular basis of malignant transformation depends upon the generation and use of increasingly sophisticated experimental models of cancer. Over the past several years, the recognition that telomeres and telomerase play essential roles in regulating cell lifespan now permits the development of new models of human cancer. Here we review recent progress in the use of immortalized human cells as a foundation for understanding the molecular basis of cancer.     

Stochastic dynamics of metastasis formation

Tumor metastasis accounts for the majority of deaths in cancer patients. The metastatic behavior of cancer cells is promoted by mutations in many genes, including activation of oncogenes such as RAS and MYC. Here, we develop a mathematical framework to analyse the dynamics of mutations enabling cells to metastasize. We consider situations in which one mutation is necessary to confer metastatic ability to the cell. We study different population sizes of the main tumor and different somatic fitness values of metastatic cells. We compare mutations that are positively selected in the main tumor with those that are neutral or negatively selected, but faster at forming metastases. We study whether metastatic potential is the property of all (or the majority of) cells in the main tumor or only the property of a small subset. Our theory shows how to calculate the expected number of metastases that are formed by a tumor.     

Genetic instability and the quasispecies model

Genetic instability is a defining characteristic of cancers. Microsatellite instability (MIN) leads to by elevated point mutation rates, whereas chromosomal instability (CIN) refers to increased rates of losing or gaining whole chromosomes or parts of chromosomes during cell division. CIN and MIN are, in general, mutually exclusive. The quasispecies model is a very successful theoretical framework for the study of evolution at high mutation rates. It predicts the existence of an experimentally verified error catastrophe. This catastrophe occurs when the mutation rates exceed a threshold value, the error threshold, above which replicative infidelity is incompatible with cell survival. We analyse the semiconservative quasispecies model of both MIN and CIN tumors. We consider the role of post-methylation DNA repair in tumor cells and demonstrate that DNA repair is fundamental to the nature of the error catastrophe in both types of tumors. We find that CIN introduces a plateau in the maximum viable mutation rate for a repair-free model, which does not exist in the case of MIN. This provides a plausible explanation for the mutual exclusivity of CIN and MIN.     

Spatial Stochastic Models for Cancer Initiation and Progression

The multistage carcinogenesis hypothesis has been formulated by a number of authors as a stochastic process. However, most previous models assumed “perfect mixing” in the population of cells, and included no information about spatial locations. In this work, we studied the role of spatial dynamics in carcinogenesis. We formulated a 1D spatial generalization of a constant population (Moran) birth–death process, and described the dynamics analytically. We found that in the spatial model, the probability of fixation of advantageous and disadvantageous mutants is lower, and the rate of generation of double-hit mutants (the so-called tunneling rate) is higher, compared to those for the space-free model. This means that the results previously obtained for space-free models give an underestimation for rates of cancer initiation in the case where the first event is the generation of a double-hit mutant, e.g. the inactivation of a tumor-suppressor gene.     

Tumor suppressor microRNAs: A novel non-coding alliance against cancer

Tumor initiation and progression are the outcomes of a stepwise accumulation of genetic alterations. Among these, gene amplification and aberrant expression of oncogenic proteins, as well as deletion or inactivation of tumor suppressor genes, represent hallmark steps. Mounting evidence collected over the last few years has identified different populations of non-coding RNAs as major players in tumor suppression in almost all cancer types. Elucidating the diverse molecular mechanisms underlying the roles of non-coding RNAs in tumor progression might provide illuminating insights, potentially able to assist improved diagnosis, better staging and effective treatments of human cancers. Here we focus on several groups of tumor suppressor microRNAs, whose downregulation exerts a profound oncologic impact and might be harnessed for the benefit of cancer patients.     

DNp73 a matter of cancer: Mechanisms and clinical implications

The p53 family proteins carry on a wide spectrum of biological functions from differentiation, cell cycle arrest, apoptosis, and chemosensitivity of tumors. NH2-terminally truncated p73 (referred to as DNp73) acts as a potent inhibitor of all these tumor suppressor properties, implying that it has oncogenic functions in human tumorigenesis. This was favored by the observation that high DNp73 expression levels in a variety of cancers are associated with adverse clinico-pathological characteristics and the response failure to chemotherapy. The actual challenge is the deciphering of the molecular mechanisms by which DNp73 promotes malignancy and to unravel the regulatory pathways for controlling TP73 isoform expression. This review is focused on recent findings leaving no doubt that N-terminally truncated p73 proteins are operative during oncogenesis, thus underscoring its significance as a marker for disease severity in patients and as target for cancer therapy.     

The molecular biology of cancer

The process by which normal cells become progressively transformed to malignancy is now known to require the sequential acquisition of mutations which arise as a consequence of damage to the genome. This damage can be the result of endogenous processes such as errors in replication of DNA, the intrinsic chemical instability of certain DNA bases or from attack by free radicals generated during metabolism. DNA damage can also result from interactions with exogenous agents such as ionizing radiation, UV radiation and chemical carcinogens. Cells have evolved means to repair such damage, but for various reasons errors occur and permanent changes in the genome, mutations, are introduced. Some inactivating mutations occur in genes responsible for maintaining genomic integrity facilitating the acquisition of additional mutations. This review seeks first to identify sources of mutational damage so as to identify the basic causes of human cancer. Through an understanding of cause, prevention may be possible. The evolution of the normal cell to a malignant one involves processes by which genes involved in normal homeostatic mechanisms that control proliferation and cell death suffer mutational damage which results in the activation of genes stimulating proliferation or protection against cell death, the oncogenes, and the inactivation of genes which would normally inhibit proliferation, the tumor suppressor genes. Finally, having overcome normal controls on cell birth and cell death, an aspiring cancer cell faces two new challenges: it must overcome replicative senescence and become immortal and it must obtain adequate supplies of nutrients and oxygen to maintain this high rate of proliferation. This review examines the process of the sequential acquisition of mutations from the prospective of Darwinian evolution. Here, the fittest cell is one that survives to form a new population of genetically distinct cells, the tumor. This review does not attempt to be comprehensive but identifies key genes directly involved in carcinogenesis and demonstrates how mutations in these genes allow cells to circumvent cellular controls. This detailed understanding of the process of carcinogenesis at the molecular level has only been possible because of the advent of modern molecular biology. This new discipline, by precisely identifying the molecular basis of the differences between normal and malignant cells, has created novel opportunities and provided the means to specifically target these modified genes. Whenever possible this review highlights these opportunities and the attempts being made to generate novel, molecular based therapies against cancer. Successful use of these new therapies will rely upon a detailed knowledge of the genetic defects in individual tumors. The review concludes with a discussion of how the use of high throughput molecular arrays will allow the molecular pathologist/therapist to identify these defects and direct specific therapies to specific mutations.     

An analytical contrast between fitness maximization and selection for mixability

It has been recently shown numerically that sex enables selection for alleles that perform well across different genetic contexts, i.e., selection for mixability. Here we capture this result analytically in a simple case. This serves a dual purpose. First, it provides a clear distinction between fitness maximization and selection for mixability. Second, it points out a limitation of the traditional analytical approach as applied to mixability.     

An ordinary differential equation model for the multistep transformation to cancer

Cancer is viewed as a multistep process whereby a normal cell is transformed into a cancer cell through the acquisition of mutations. We reduce the complexities of cancer progression to a simple set of underlying rules that govern the transformation of normal cells to malignant cells. In doing so, we derive an ordinary differential equation model that explores how the balance of angiogenesis, cell death rates, genetic instability, and replication rates give rise to different kinetics in the development of cancer. The key predictions of the model are that cancer develops fastest through a particular ordering of mutations and that mutations in genes that maintain genomic integrity would be the most deleterious type of mutations to inherit. In addition, we perform a sensitivity analysis on the parameters included in the model to determine the probable contribution of each. This paper presents a novel approach to viewing the genetic basis of cancer from a systems biology perspective and provides the groundwork for other models that can be directly tied to clinical and molecular data.     

An ANN model for the identification of deleterious nsSNPs in tumor suppressor genes

Human genetic variations primarily result from single nucleotide polymorphisms (SNPs) that occurs approximately every 1000 bases in the overall human population. The non-synonymous SNPs (nsSNPs), lead to amino acid changes in the protein product may account for nearly half of the known genetic variations linked to inherited human diseases and cancer. One of the main problems of medical genetics today is to identify nsSNPs that underlie disease-related phenotypes in humans. An attempt was made to develop a new approach to predict such nsSNPs. This would enhance our understanding of genetic diseases and helps to predict the disease. We detect nsSNPs and all possible and reliable alleles by ANN, a soft computing model using potential SNP information. Reliable nsSNPs are identified, based on the reconstructed alleles and on sequence redundancy. The model gives good results with mean specificity (95.85&), sensitivity (97.40&) and accuracy (96.25&). Our results indicate that ANNs can serve as a useful method to analyze quantitative effect of nsSNPs on protein function and would be useful for large-scale analysis of genomic nsSNP data. AVAILABILITY: The database is available for free at http://www.snp.mirworks.in.     

The stochastic model of non-equilibrium mutagen-induced alterations of DNA: implication to genetic instability in cancer

Genetic alterations such as point mutations, chromosomal rearrangements, modification of DNA methylation and chromosome aberrations accumulate during the lifetime of an organism. They can be caused by intrinsic errors in the DNA replication and repair as well as by external factors such as exposure to mutagenic substances or radiation. The main purpose of the present work is to begin an exploration of the stochastic nature of non-equilibrium DNA alteration caused by events such as tautomeric shifts. This is done by modeling the genetic DNA code chain as a sequence of DNA-bit values ('1' for normal bases and '-1' for abnormal bases). We observe the number of DNA-bit changes resulting from the random point mutation process which, in the model, is being induced by a stochastic Brownian mutagen (BM) as it diffuses through the DNA-bit systems. Using both an analytical and Monte Carlo (MC) simulation techniques, we observe the local and global number of DNA-bit changes. It is found that in 1D, the local DNA-bit density behaves like 1/t, the global total number of the switched (abnormal) DNA-bit increases as t. The probability distribution P(b, 0, t) of b(0, t) is log-normal. It is also found that when the number of mutagens is increased, the number of the total abnormal DNA-bits does not grow linearly with the number of mutagens. All analytic results are in good agreement with the simulation results.     

C-terminal tensin-like (CTEN): A promising biomarker and target for cancer

C-terminal tensin-like (cten, also known as tensin4, TNS4) is a member of the tensin family. Cten protein, like the other three tensin family members, localizes to focal adhesion sites but only shares sequence homology with other tensins at its C-terminal region, which contains the SH2 and PTB domains. Cten is abundantly expressed in normal prostate and placenta and is down-regulated in prostate cancer. However, overexpression of cten frequently associates with tumors derived from breast, colon, lung, stomach, skin and pancreas. A variety of cancer-associated growth factors and cytokines induce cten expression. Up-regulated cten promotes cell motility, prolongs epidermal growth factor receptor signaling, and enhances tumorigenicity. Emerging findings suggest that cten is a promising biomarker and therapeutic target for various cancers.     

The tumor suppressor p53 can reduce stable transfection in the presence of irradiation

The tumor suppressor p53 is believed to play an essential role in maintaining genome stability. Although it is currently unknown how p53 is involved in this important biological safeguard, several previous publications indicate that p53 can help to maintain genome integrity through the recombination-mediated DNA repair process. The integration of linearized plasmid DNA into the host chromosome utilizes the same repair process, and the frequency can be measured by clonogenic assays in which cells that were stably transfected by plasmid integration can be scored by their colony-forming abilities. To gain insight into whether p53 has a direct role in plasmid integration into the host chromosome, we determined the frequency of stable transfection with CHO cells expressing either wild-type or mutant p53 in the presence and absence of irradiation. We found that low-dose irradiation (50 to 100 cGy) increased stable transfection frequencies in CHO cells regardless of their p53 status. However, the increase of transfection frequency was significantly lower in CHO cells expressing wild-type p53. Our data thus suggest that wild-type p53 can suppress plasmid DNA integration into the host genome. This p53 function may play a direct and significant role in maintaining genome stability.