Somatic mosaicism and cancer: inference based on a conditional Luria-Delbrück distribution

Somatic mosaicism for mutations in disease-causing genes has been reported in several recent studies. Examples include hemophilia A, many skin disorders, and several cancers such as retinoblastoma and familial adenomatous polyposis. Many of these disorders require multiple mutations in order to express the disease phenotype. For example, two recessive mutations to the retinoblastoma locus are required to initiate retinoblastomal tumors. I develop a mathematical framework for somatic mosaicism in which two recessive mutations cause disease. With my framework, I analyse the following question: Given an observed frequency of cells with two mutations and an easily scored aberrant phenotype, what is the conditional frequency distribution of cells carrying one mutation and therefore susceptible to transformation by a second mutation? This question is important because a high frequency of carrier cells can cause genetic counselors to misdiagnose a mosaic as an inherited heterozygote carrier and because widespread mosaicism can lead to some germline transmission. As more data accumulate, the observed distribution of mosaics can be compared against my predicted distribution. These sorts of studies will contribute to a broader understanding of the distribution of somatic mutations, a central topic in the study of cancer.     

Role of heterozygous APC mutation in niche succession and initiation of colorectal cancer--a computational study

Mutations in the adenomatous polyposis coli (APC) gene are found in most colorectal cancers. They cause constitutive activation of proliferative pathways when both alleles of the gene are mutated. However studies on individuals with familial adenomatous polyposis (FAP) have shown that a single mutated APC allele can also create changes in the precancerous colon crypt, like increased number of stem cells, increased crypt fission, greater variability of DNA methylation patterns, and higher somatic mutation rates. In this paper, using a computational model of colon crypt dynamics, we evolve and investigate a hypothesis on the effect of heterozygous APC mutation that explains these different observations. Based on previous reports and the results from the computational model we propose the hypothesis that heterozygous APC mutation has the effect of increasing the chances for a stem cell to divide symmetrically, producing two stem cell daughters. We incorporate this hypothesis into the model and perform simulation experiments to investigate the consequences of the hypothesis. Simulations show that this hypothesis links together the changes in FAP crypts observed in previous studies. The simulations also show that an APC(+/-) stem cell gets selective advantages for dominating the crypt and progressing to cancer. This explains why most colon cancers are initiated by APC mutation. The results could have implications for preventing or retarding the onset of colon cancer in people with inherited or acquired mutation of one APC allele. Experimental validation of the hypothesis as well as investigation into the molecular mechanisms of this effect may therefore be worth undertaking.     

Inherited pancreatic cancer: improvements in our understanding of genetics and screening

Inherited pancreatic cancers represent approximately 5-10% of all pancreatic cancers. Pancreatic cancer may be inherited as part of a known cancer syndrome or in association with hereditary pancreatitis or cystic fibrosis. However, most inherited pancreatic cancers do not occur in the context of a known syndrome, and these are referred to as familial pancreatic cancers. Growing evidence suggests the presence of a single autosomal dominant gene in familial pancreatic cancer kindreds, and a susceptibility locus on chromosome 4 has recently been identified in one such family. Pancreatic cancer is believed to arise from pancreatic dysplasia, and familial pancreatic cancer kindreds represent a particularly high-risk population for whom effective screening strategies are needed. One promising strategy has used endoscopic ultrasound to detected pancreatic dysplasia in members of familial pancreatic cancer kindreds.     

Lung cancer risk in germline p53 mutation carriers: association between an inherited cancer predisposition,cigarette smoking,and cancer risk

We recently observed a significantly increased risk for lung cancer in carriers of p53 germline mutations. Because cigarette smoking is known to play an important role in increasing the risk for lung cancer in the general population, we wanted to determine the role of cigarette smoking in lung cancer risk in people with a genetic susceptibility based on a p53 germline mutation. We studied 1263 people from 97 families enrolled in a cohort study of families systematically ascertained through childhood soft-tissue sarcoma patients treated at the M.D. Anderson Cancer Center, University of Texas, between 1944 and 1975. We assessed the incidence of lung and smoking-related cancers in 33 carriers of germline p53 mutations and in 1,230 noncarriers to determine whether there was an association between an inherited cancer predisposition, cigarette smoking, and cancer risk. We analyzed the association between cigarette smoking, mutation status, and lung and other smoking-related cancers by the Kaplan-Meier method and the Cox proportional hazards model with adjustments for birth year, race, and sex. In the hazards model, we incorporated a robust variance estimation to adjust for familial correlation. We observed an increased risk of a variety of histological types of lung cancer in the carriers of the p53 germline mutation. Mutation carriers who smoked had a 3.16-fold (95% confidence interval =1.48–6.78) higher risk for lung cancer than the mutation carriers who did not smoke. Our results demonstrate that cigarette smoking significantly increases lung cancer risk in carriers of a germline p53 mutation. This finding could be useful in designing strategies for early detection and treatment of lung and smoking-related cancers in individuals with this inherited cancer predisposition.     

Genetic progression and the waiting time to cancer

Cancer results from genetic alterations that disturb the normal cooperative behavior of cells. Recent high-throughput genomic studies of cancer cells have shown that the mutational landscape of cancer is complex and that individual cancers may evolve through mutations in as many as 20 different cancer-associated genes. We use data published by Sjöblom et al. (2006) to develop a new mathematical model for the somatic evolution of colorectal cancers. We employ the Wright-Fisher process for exploring the basic parameters of this evolutionary process and derive an analytical approximation for the expected waiting time to the cancer phenotype. Our results highlight the relative importance of selection over both the size of the cell population at risk and the mutation rate. The model predicts that the observed genetic diversity of cancer genomes can arise under a normal mutation rate if the average selective advantage per mutation is on the order of 1%. Increased mutation rates due to genetic instability would allow even smaller selective advantages during tumorigenesis. The complexity of cancer progression can be understood as the result of multiple sequential mutations, each of which has a relatively small but positive effect on net cell growth.     

Mutation as a cause of genetic disease

Mutational changes can be conveniently classified into two sorts: those that appear to involve single genes and are generally referred to as gene mutations, and those that involve chromosomal segments containing many genes, or even whole chromosomes, and are referred to as chromosomal mutations. Both of these kinds of mutation occur in germ-cell lineages and contribute substantially to inherited disease, or pre-disposition to disease, and both also occur in somatic cells and contribute to acquired disease. The mutation rates for inherited disease ascribed to mutation in a single gene differ for different genes and are age-dependent. Moreover, a single disease entity, such as haemophilia B, may be the result of any one of a number of different alterations within the gene responsible for the disease. The mutation rate for inherited chromosomal mutation is also age-dependent, particularly so in the case of mutations involving alterations in chromosome number. Studies in experimental animals demonstrate that exposure to physical or chemical mutagens results in increasing the incidence of inherited gene and chromosomal mutations. However, such increases have not been unequivocally demonstrated in human populations exposed to known mutagens. Studies on mutation in human lymphoid or epithelial somatic cells clearly demonstrate an increased frequency in cells taken from people exposed to ionizing radiations or chemical mutagens or in cells exposed in vitro. The consequences of such mutations will depend upon their nature and the origins and functions of the cells in which they occur. Of particular importance are mutations influencing cell growth and proliferation, and both gene and chromosomal mutations are implicated as causal factors in the development of human cancers.     

A machine learning framework to trace tumor tissue-of-origin of 13 types of cancer based on DNA somatic mutation

Carcinoma of unknown primary (CUP), defined as metastatic cancers with unknown cancer origin, occurs in 3‐5 per 100 cancer patients in the United States. Heterogeneity and metastasis of cancer brings great difficulties to the follow-up diagnosis and treatment for CUP. To find the tissue-of-origin (TOO) of the CUP, multiple methods have been raised. However, the accuracies for computed tomography (CT) and positron emission tomography (PET) to identify TOO were 20%–27% and 24%–40% respectively, which were not enough for determining targeted therapies. In this study, we provide a machine learning framework to trace tumor tissue origin by using gene length-normalized somatic mutation sequencing data. Somatic mutation data was downloaded from the Data Portal (Release 28) of the International Cancer Genome Consortium (ICGC), and 4909 samples for 13 cancers was used to identify primary site of cancers. Optimal results were obtained based on a 600-gene set by using the random forest algorithm with 10-fold cross-validation, and the average accuracy and F1-score were 0.8822 and 0.8886 respectively across 13 types of cancer. In conclusion, we provide an effective computational framework to infer cancer tissue-of-origin by combining DNA sequencing and machine learning techniques, which is promising in assisting clinical diagnosis of cancers.     

Genetic counselling and testing for susceptibility to breast,ovarian and colon cancer: where are we today?

Recent advances in our understanding of the genetic characteristics of cancer will change approaches to genetic screening and counselling. Cancer results from multiple, cumulative mutations in genes that regulate cell replication and differentiation. In familial cancer a germ-line mutation is passed on in an autosomal dominant pattern, but cancer will develop in people who inherit the defect only if other mutations also occur in susceptible somatic cells. The tumour-suppressor gene known as BRCA1 is thought to affect half of those families who have an inherited breast cancer syndrome and most families with a breast and ovarian cancer syndrome. Another gene, BRCA2, is thought to affect most of the remaining families with a breast-cancer-only syndrome. Hereditary nonpolyposis colon cancer (HNPCC) is caused by mutations in surveillance genes that protect DNA from the spontaneous errors that occur during cell division. Because there are no outcome data on which to base practice guidelines for genetic screening or management of asymptomatic carriers in families at risk, testing should be restricted to research settings.     

Heteroplasmic mutation of mitochondrial DNA D-loop and 4977-bp deletion in human cancer cells during mitochondrial DNA depletion

Somatic mutations in mitochondrial DNA (mtDNA) have been demonstrated in various human cancers. Many cancers have high frequently of mtDNA with homoplasmic point mutations, and carry less frequently of mtDNA with large-scale deletions as compared with corresponding non-cancerous tissue. Moreover, most cancers harbor a decreased copy number of mtDNA than their corresponding non-cancerous tissue. However, it is unclear whether the process of decreasing in mtDNA content would be involved in an increase in the heteroplasmic level of somatic mtDNA point mutation, and/or involved in a decrease in the proportion of mtDNA with large-scale deletion in cancer cells. In this study, we provided evidence that the heteroplasmic levels of variations in cytidine number in np 303-309 poly C tract of mtDNA in three colon cancer cells were not changed during an ethidium bromide-induced mtDNA depleting process. In the mtDNA depleting process, the proportions of mtDNA with 4977-bp deletion in cybrid cells were not significantly altered. These results suggest that the decreasing process of mtDNA copy number per se may neither contribute to the shift of homoplasmic/heteroplasmic state of point mutation in mtDNA nor to the decrease in proportion of mtDNA with large-scale deletions in cancer cells. Mitochondrial genome instability and reduced mtDNA copy number may independently occur in human cancer.     

The evolution of two mutations during clonal expansion

Knudson's two-hit hypothesis proposes that two genetic changes in the RB1 gene are the rate-limiting steps of retinoblastoma. In the inherited form of this childhood eye cancer, only one mutation emerges during somatic cell divisions while in sporadic cases, both alleles of RB1 are inactivated in the growing retina. Sporadic retinoblastoma serves as an example of a situation in which two mutations are accumulated during clonal expansion of a cell population. Other examples include evolution of resistance against anticancer combination therapy and inactivation of both alleles of a metastasis-suppressor gene during tumor growth. In this article, we consider an exponentially growing population of cells that must evolve two mutations to (i) evade treatment, (ii) make a step toward (invasive) cancer, or (iii) display a disease phenotype. We calculate the probability that the population has evolved both mutations before it reaches a certain size. This probability depends on the rates at which the two mutations arise; the growth and death rates of cells carrying none, one, or both mutations; and the size the cell population reaches. Further, we develop a formula for the expected number of cells carrying both mutations when the final population size is reached. Our theory establishes an understanding of the dynamics of two mutations during clonal expansion.     

Heterogeneity of microsatellite mutations within and between loci,and implications for human demographic histories.

Microsatellites have been widely used to reconstruct human evolution. However, the efficient use of these markers relies on information regarding the process producing the observed variation. Here, we present a novel approach to the locus-by-locus characterization of this process. By analyzing somatic mutations in cancer patients, we estimated the distributions of mutation size for each of 20 loci. The same loci were then typed in three ethnically diverse population samples. The generalized stepwise mutation model was used to test the predicted relationship between population and mutation parameters under two demographic scenarios: constant population size and rapid expansion. The agreement between the observed and expected relationship between population and mutation parameters, even when the latter are estimated in cancer patients, confirms that somatic mutations may be useful for investigating the process underlying population variation. Estimated distributions of mutation size differ substantially amongst loci, and mutations of more than one repeat unit are common. A new statistic, the normalized population variance, is introduced for multilocus estimation of demographic parameters, and for testing demographic scenarios. The observed population variation is not consistent with a constant population size. Time estimates of the putative population expansion are in agreement with those obtained by other methods.     

Application of multiplex PCR with histopathologic features for detection of familial breast cancer in formalin-fixed, paraffin-embedded histologic specimens

Breast cancer is the most common malignancy among females in the world. Age and familial history are the major risk factors for the development of this disease in Iran. Mutations of BRCA1 and BRCA2 genes are associated with a greatly increased risk for development of familial breast cancer. Frequency of BRCA mutations was identified in familial breast cancers (FBC) and non-familial breast cancers (NFBC) by molecular genetics, morphological and Immunohistochemical methods. Thirty forth formalin-fixed, paraffin-embedded breast tissue tumors were analyzed from 16 patients with FBC and 18 patients with NFBC. Three 5382insC mutations detected by multiplex PCR in 16 familial breast cancers. Immunohistochemical method was used to detect estrogen receptor (ER) and progesterona receptor (PR) and TP53. Comparison of ER, PR and TP53 exhibited high difference (P < 0.0001) in familial breast cancers and non-familial breast cancers. Our results demonstrated that 5382insC mutation, ER, PR, TP53, mitotic activity, polymorphism, necrosis and tubules can serve as the major risk factors for the development of FBC.     

Evolution of resistance during clonal expansion

Acquired drug resistance is a major limitation for cancer therapy. Often, one genetic alteration suffices to confer resistance to an otherwise successful therapy. However, little is known about the dynamics of the emergence of resistant tumor cells. In this article, we consider an exponentially growing population starting from one cancer cell that is sensitive to therapy. Sensitive cancer cells can mutate into resistant ones, which have relative fitness alpha prior to therapy. In the special case of no cell death, our model converges to the one investigated by Luria and Delbrück. We calculate the probability of resistance and the mean number of resistant cells once the cancer has reached detection size M. The probability of resistance is an increasing function of the detection size M times the mutation rate u. If Mu < 1, then the expected number of resistant cells in cancers with resistance is independent of the mutation rate u and increases with M in proportion to M(1-1/alpha) for advantageous mutants with relative fitness alpha>1, to l nM for neutral mutants (alpha = 1), but converges to an upper limit for deleterious mutants (alpha<1). Further, the probability of resistance and the average number of resistant cells increase with the number of cell divisions in the history of the tumor. Hence a tumor subject to high rates of apoptosis will show a higher incidence of resistance than expected on its detection size only.     

Gain and loss of phosphorylation sites in human cancer

MOTIVATION: Coding-region mutations in human genes are responsible for a diverse spectrum of diseases and phenotypes. Among lesions that have been studied extensively, there are insights into several of the biochemical functions disrupted by disease-causing mutations. Currently, there are more than 60 000 coding-region mutations associated with inherited disease catalogued in the Human Gene Mutation Database (HGMD, August 2007) and more than 70 000 polymorphic amino acid substitutions recorded in dbSNP (dbSNP, build 127). Understanding the mechanism and contribution these variants make to a clinical phenotype is a formidable problem. RESULTS: In this study, we investigate the role of phosphorylation in somatic cancer mutations and inherited diseases. Somatic cancer mutation datasets were shown to have a significant enrichment for mutations that cause gain or loss of phosphorylation when compared to our control datasets (putatively neutral nsSNPs and random amino acid substitutions). Of the somatic cancer mutations, those in kinase genes represent the most enriched set of mutations that disrupt phosphorylation sites, suggesting phosphorylation target site mutation is an active cause of phosphorylation deregulation. Overall, this evidence suggests both gain and loss of a phosphorylation site in a target protein may be important features for predicting cancer-causing mutations and may represent a molecular cause of disease for a number of inherited and somatic mutations.     

Mitochondria harbouring mutant mtDNA--a cuckoo in the nest?

Mutations of the mitochondrial DNA (mtDNA) are associated with a number of human diseases. To become relevant in terms of pathology, a mutation must generally affect at least 50-70% of mtDNA molecules in a tissue. One way to reach this level is by inheritance. Mitotic segregation of mtDNA in the female germline can result in large increases in the percentage of mutant mtDNA between generations. A different explanation is required if a particular mtDNA mutation accumulates over time in somatic cells. We discuss the possibility that mutant mtDNA, by causing deficient oxidative phosphorylation, may become preferentially replicated and may thus thrive in the cell like a cuckoo in the nest. However, despite preferential replication, a de novo mtDNA mutation will be confined to that particular cell or a small clone of daughter cells. Significant accumulation can only occur if the cell harbouring the mutant mtDNA undergoes malignant transformation and therefore starts proliferating continuously. This type of amplification of mutant mtDNA has recently been demonstrated in certain bone marrow disorders (myelodysplastic syndromes) and in colon cancer cell lines. Finally, in postmitotic tissues, an inherited mutation which is present in virtually all cells of the tissue, may accumulate through replicative advantage. This may contribute to the development of degenerative diseases.     

Testing and characterizing the two-stage model of carcinogenesis for a wide range of human cancers

The age dependence of incidence for 45 cancer types in three populations is analyzed on a two-stage kinetic model containing three determinable parameters: (i) the fraction of population at risk for a cancer; (ii) the product of the frequencies of cancer-producing mutations, and (iii) the growth rate of the transformed clone from which a cancer ultimately evolves. The model, simplifying that proposed by others, fits many cancers. Data are easily handled in terms of the derived parameters, providing the basis for epidemiological analysis, here applied in detail to liver, cervix and testis cancers for nearly 50 world-wide populations. We identify 12 cancers for which only a limited fraction of the population is at risk. We argue that the appearance of most cancers requires at least three mutational events. For child, youth, or early adult cancers, one mutation may be congenital. We arrange the various cancers in a descending scale, defining six groups that differ in the derived mutation frequencies. A cancer appearing later in life, for which the whole population can be at risk, shows a low mutation frequency, consistent with background spontaneous mutation. The other cancers require increases in mutation frequency, arising from an increased rate of cell division and/or mutation rate.     

Lineage selection and the evolution of multistage carcinogenesis

A wide array of proto-oncogenes and tumour suppressor genes are involved in the prevention of cancer. Each form of cancer requires mutations in a characteristic group of genes, but no single group controls all cancers. This lack of generality shows that the control of cancer is not an ancient, fixed property of cells. By contrast, it supports a dynamic evolutionary model, whereby genetic controls over unregulated cell growth are recruited independently through evolutionary time in different tissues within different taxa. The complexity of this genetic control can be predicted from a population genetic model of lineage selection driven by the detrimental fitness effects of cancer. Cancer occurs because the genetic control of cell growth is vulnerable to somatic mutations (or 'hits'), particularly in large, continuously dividing tissues. Thus, compared to small rodents, humans must have evolved more complex genetic controls over cell growth in at least some of their tissues because of their greater size and longevity; an expectation relevant to the application of mouse data to humans. Similarly, the 'two-hit' model so successfully applied to retinoblastoma, which originates in a small embryonic tissue, is unlikely to be generally applicable to other human cancers; instead, more complex scenarios are expected to dominate, with complexity depending upon a tissue's size and its pattern of proliferation.     

Single nucleotide polymorphisms (SNPs) are inherited from parents and they measure heritable events

Single nucleotide polymorphisms (SNPs) are extensively used in case-control studies of practically all cancer types. They are used for the identification of inherited cancer susceptibility genes and those that may interact with environmental factors. However, being genetic markers, they are applicable only on heritable conditions, which is often a neglected fact. Based on the data in the nationwide Swedish Family-Cancer Database, we review familial risks for all main cancers and discuss the evidence for a heritable component in cancer. The available evidence is not conclusive but it is consistent in pointing to a minor heritable etiology in cancer, which will hamper the success of SNP-based association studies. Empirical familial risks should be used as guidance for the planning of SNP studies. We provide calculations for the assessment of familial risks for assumed allele frequencies and gene effects (odds ratios) for different modes of inheritance. Based on these data, we discuss the gene effects that could account for the unexplained proportion of familial breast and lung cancer. As a conclusion, we are concerned about the indiscriminate use of a genetic tool to cancers, which are mainly environmental in origin. We consider the likelihood of a successful application of SNPs in gene-environment studies small, unless established environmental risk factors are tested on proven candidate genes.     

A mathematical model of breast cancer development, local treatment and recurrence

Cancer development is a stepwise process through which normal somatic cells acquire mutations which enable them to escape their normal function in the tissue and become self-sufficient in survival. The number of mutations depends on the patient's age, genetic susceptibility and on the exposure of the patient to carcinogens throughout their life. It is believed that in every malignancy 4-6 crucial similar mutations have to occur on cancer-related genes. These genes are classified as oncogenes and tumour suppressor genes (TSGs) which gain or lose their function respectively, after they have received one mutative hit or both of their alleles have been knocked out. With the acquisition of each of the necessary mutations the transformed cell gains a selective advantage over normal cells, and the mutation will spread throughout the tissue via clonal expansion. We present a simplified model of this mutation and expansion process, in which we assume that the loss of two TSGs is sufficient to give rise to a cancer. Our mathematical model of the stepwise development of breast cancer verifies the idea that the normal mutation rate in genes is only sufficient to give rise to a tumour within a clinically observable time if a high number of breast stem cells and TSGs exist or genetic instability is involved as a driving force of the mutation pathway. Furthermore, our model shows that if a mutation occurred in stem cells pre-puberty, and formed a field of cells with this mutation through clonal formation of the breast, it is most likely that a tumour will arise from within this area. We then apply different treatment strategies, namely surgery and adjuvant external beam radiotherapy and targeted intraoperative radiotherapy (TARGIT) and use the model to identify different sources of local recurrence and analyse their prevention.     

Repair and regeneration: opportunities for carcinogenesis from tissue stem cells

This review will discuss the mechanisms of repair and regeneration in various tissue types and how dysregulation of these mechanisms may lead to cancer. Normal tissue homeostasis involves a careful balance between cell loss and cell renewal. Stem and progenitor cells perform these biologic processes as the functional units of regeneration during both tissue homeostasis and repair. The concept of tissue stem cells capable of giving rise to all differentiated cells within a given tissue led to the concept of a cellular hierarchy in tissues and in tumors. Thus, only a few cells may be necessary and sufficient for tissue repair or tumor regeneration. This is known as the hierarchical model of tumorigenesis. This report will compare this model with the stochastic model of tumorigenesis. Under normal circumstances, the processes of tissue regeneration or homeostasis are tightly regulated by several morphogen pathways to prevent excessive or inappropriate cell growth. This review presents the recent evidence that dysregulation of these processes may provide opportunities for carcinogenesis for the long-lived, highly proliferative tissue stem cell population. New findings of cancer initiating tissue stem cells identified in several solid and circulating cancers including breast, brain and hematopoietic tumors will also be reviewed. Finally, this report reviews the cellular biology of cancer and its relevance to the development of more effective cancer treatment protocols.