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Biomedical subjects

Steven A Frank

Publications and source records attributed to Steven A Frank.

At least 19 recordsLinked to original sources
PubMed2006

Pathogen escape from host immunity by a genome program for antigenic variation.

The vector-borne bacterium Borrelia hermsii, a relapsing fever agent, switches gene expression of a surface protein between different antigenic variants, thereby causing sequential waves of immune escape within hosts and increasing the likelihood of transmission. Analogous programmed systems of antigenic variation occur in African trypanosomes and Plasmodium falciparum. In these examples, switch rates to individual variants differ over a wide range. We studied how B. hermsii determines switch rates in two experimental infections: one where variants were identified by specific antisera and one based on identification by DNA sequence. Unexpressed loci of variant antigens copy into a single expression site at rates determined by extragenic features of silent loci rather than similarity between coding sequences of variants at silent sites and the single expression site. Two elements, in particular, determine switch rates. One set of elements overlaps the 5' ends of the expressed gene and the silent loci; greater sequence identity between elements was associated with a higher switch rate. The second set of elements flanks the expression site on the 3' side and occurs at variable distances downstream from silent loci; the nearer an element to a silent locus, the greater the switch rate of that locus into the expression site. In combination, these two features of the genome provide a simple mechanism to modulate switch rate whereby silent loci form a hierarchy of switch rates into the expression site. Although the switching hierarchy causes changes in individual cells that are stochastic, ordering of variants within hosts is semipredictable.

Animals↗
PubMed2006

Within-host dynamics of antigenic variation.

Genomes of some parasites contain dozens of alternative and highly diverged surface antigens, of which only a single one is expressed in any cell. Individual cells occasionally change expression of their surface antigen, allowing them to escape immune surveillance. These switches appear to occur in a partly random way, creating a diverse set of antigenic variants. In spite of this diversity, the parasitemia develops as a series of outbreaks, in which each outbreak is dominated by relatively few antigenic types. Host-specific immunity eventually clears the dominant antigenic types, and a new outbreak follows from antigenic types that have apparently been present all along at low frequency. This pattern of sequential dominance by different antigenic types remains unexplained. We review the five most prominent theories, which have developed mainly from studies of the protozoans Trypanosoma and Plasmodium, and the bacterial spirochete Borrelia. The most promising theories depend on some combination of mechanisms to create favored connectivity pathways through the matrix of transitions between variants. Favored pathways may arise from biased switches at the molecular level of gene expression or from biases imposed by immune selection. We illustrate the concept of connectivity pathways by reanalysis of data on transitions between variants from Borrelia hermsii.

Animals↗
PubMed2005

Kinetics of cancer: a method to test hypotheses of genetic causation.

BACKGROUND: Mouse studies have recently compared the age-onset patterns of cancer between different genotypes. Genes associated with earlier onset are tentatively assigned a causal role in carcinogenesis. These standard analyses ignore the great amount of information about kinetics contained in age-onset curves. We present a method for analyzing kinetics that measures quantitatively the causal role of candidate genes in cancer progression. We use our method to demonstrate a clear association between somatic mutation rates of different DNA mismatch repair (MMR) genotypes and the kinetics of cancer progression. METHODS: Most experimental studies report age-onset curves as the fraction diagnosed with tumors at each age for each group. We use such data to estimate smoothed survival curves, then measure incidence rates at each age by the slope of the fitted curve divided by the fraction of mice that remain undiagnosed for tumors at that age. With the estimated incidence curves, we compare between different genotypes the median age of cancer onset and the acceleration of cancer, which is the rate of increase in incidence with age. RESULTS: The direction of change in somatic mutation rate between MMR genotypes predicts the direction of change in the acceleration of cancer onset in all 7 cases (p approximately 0.008), with the same result for the association between mutation rate and the median age of onset. CONCLUSION: Many animal experiments compare qualitatively the onset curves for different genotypes. If such experiments were designed to analyze kinetics, the research could move to the next stage in which the mechanistic consequences of particular genetic pathways are related to the dynamics of carcinogenesis. The data we analyzed here were not collected to test mechanistic and quantitative hypotheses about kinetics. Even so, a simple reanalysis revealed significant insights about how DNA repair genotypes affect separately the age of onset and the acceleration of cancer. Our method of comparing genotypes provides good statistical tests even with small samples for each genotype.

Adenoma↗
PubMed2005

Age-specific incidence of inherited versus sporadic cancers: a test of the multistage theory of carcinogenesis.

Knudson [Knudson, A. G. (1971) Proc. Natl. Acad. Sci. USA 68, 820-823] suggested that progression of retinoblastoma follows from two mutational events. Individuals who inherit one mutated gene copy should follow an age-onset pattern set by only a single rate-limiting step for transformation, whereas normal individuals should follow an age-onset pattern set by two rate-limiting events. Knudson's analysis of inherited and sporadic cases of retinoblastoma supported this prediction. However, retinoblastoma has a peculiar age-onset pattern concentrated in early life, because the retinal tissue completes most of its cell division by 5 years of age. Here, I compare age-specific incidences of inherited and sporadic forms of colon cancer, a much more typical form of human cancer. My simple mathematical analysis based on multistage theory explains the observed differences in age-onset patterns between inherited and sporadic cases. I also analyze recent retinoblastoma data and provide a mathematical analysis and interpretation. My analysis supports Knudson's two-hit theory but is much simpler and easier to understand than the original mathematical theory, which was based on a complicated model of cell division in the retina. My simpler theory for retinoblastoma makes clear the common basis for understanding multistage progression in tissues as different as the retina and colon.

Adult↗
PubMed2004

A multistage theory of age-specific acceleration in human mortality.

BACKGROUND: Humans die at an increasing rate until late in life, when mortality rates level off. The causes of the late-life mortality plateau have been debated extensively over the past few years. Here, I examine mortality patterns separately for each of the leading causes of death. The different causes of death show distinct mortality patterns, providing some clues about the varying acceleration of mortality at different ages. RESULTS: I examine mortality patterns by first plotting the data of mortality rate versus age on a log-log scale. The slope of the age-specific mortality rate at each age is the age-specific acceleration of mortality. About one-half of total deaths have causes with similar shapes for the age-specific acceleration of mortality: a steady rise in acceleration from midlife until a well-defined peak at 80 years, followed by a nearly linear decline in acceleration. This first group of causes includes heart disease, cerebrovascular disease, and accidental deaths. A second group, accounting for about one-third of all deaths, follows a different pattern of age-specific acceleration. These diseases show an approximately linear rise in acceleration to a peak at 35-45 years of age, followed by a steep and steady decline in acceleration for the remainder of life. This second group includes cancer, chronic respiratory diseases, and liver disease. I develop a multistage model of disease progression to explain the observed patterns of mortality acceleration. CONCLUSIONS: A multistage model of disease progression can explain both the early-life increase and late-life decrease in mortality acceleration. An early-life rise in acceleration may be caused by increasing rates of transition between stages as individuals grow older. The late-life decline in acceleration may be caused by progression through earlier stages, leaving only a few stages remaining for older individuals.

Adult↗
PubMed2004

Somatic mutation of p53 leads to estrogen receptor alpha-positive and -negative mouse mammary tumors with high frequency of metastasis.

Approximately 70% of human breast cancers are estrogen receptor alpha (ERalpha)-positive, but the origins of ERalpha-positive and -negative tumors remain unclear. Hormonal regulation of mammary gland development in mice is similar to that in humans; however, most mouse models produce only ERalpha-negative tumors. In addition, these mouse tumors metastasize at a low rate relative to human breast tumors. We report here that somatic mutations of p53 in mouse mammary epithelial cells using the Cre/loxP system leads to ERalpha-positive and -negative tumors. p53 inactivation under a constitutive active WAPCre(c) in prepubertal/pubertal mice, but not under MMTVCre in adult mice, leads to the development of ERalpha-positive tumors, suggesting that target cells or developmental stages can determine ERalpha status in mammary tumors. Importantly, these tumors have a high rate of metastasis. An inverse relationship between the number of targeted cells and median tumor latency was also observed. Median tumor latency reaches a plateau when targeted cell numbers exceed 20%, implying the existence of saturation kinetics for breast carcinogenesis. Genetic alterations commonly observed in human breast cancer including c-myc amplification and Her2/Neu/erbB2 activation were seen in these mouse tumors. Thus, this tumor system reproduces many important features of human breast cancer and provides tools for the study of the origins of ERalpha-positive and -negative breast tumors in mice.

Alleles↗
PubMed2004

Genetic variation in cancer predisposition: mutational decay of a robust genetic control network.

A computational model of cancer progression is used to study how mutations in genes that control tumor initiation and progression accumulate in populations. The model assumes that cancer occurs only after a cell lineage has progressed through a series of stages. The greater the number of stages, the more strongly the individual is protected against cancer. It is shown that an extra stage initially improves the survival of individuals by decreasing mortality from cancer. However, the additional buffering by an extra stage reduces the impact of any single hereditary mutation and therefore allows the accumulation of more nonlethal mutations in the population. Extra stages thereby lead to the evolution of partially decreased cancer mortality and significantly increased genetic predisposition to disease in the population as a whole. In general, the model illustrates how all robust control networks allow the accumulation of deleterious mutations. An increase in the number of buffering components leads to significant mutational decay in the protection provided by each buffering component and increased genetic predisposition to disease. An extra buffering component's net contribution to survival and reproduction is often small.

Aging↗
PubMed2004

Age-specific acceleration of cancer.

One of the great challenges of cancer research is to explain the epidemiological patterns of cancer incidence based on the molecular processes that lead to uncontrolled cellular proliferation. The epidemiological data demonstrate that the age-specific incidence of many cancers increases in an approximately linear way with age when plotted on a log-log scale, with different slopes for different cancers. However, those epidemiological data also show that cancers of various tissues depart from log-log linearity in particular ways. Here, I illustrate those departures from log-log linearity by introducing plots of the age-specific acceleration of cancer. I then develop a very general model of cancer progression, which I use to explain the observed differences between tissues in age-specific acceleration. In one application of the model, I show that the spectacular rise and fall in age-specific acceleration observed in prostate cancer may be explained by multiple rounds of clonal expansion. In a second application, I demonstrate that the steady decline in age-specific acceleration of breast cancer may occur because precancerous mutations accumulate in many cellular lineages.

Age Factors↗
PubMed2004

Problems of somatic mutation and cancer.

Somatic mutation plays a key role in transforming normal cells into cancerous cells. The analysis of cancer progression therefore requires the study of how point mutations and chromosomal mutations accumulate in cellular lineages. The spread of somatic mutations depends on the mutation rate, the number of cell divisions in the history of a cellular lineage, and the nature of competition between different cellular lineages. We consider how various aspects of tissue architecture and cellular competition affect the pace of mutation accumulation. We also discuss the rise and fall of somatic mutation rates during cancer progression.

Cell Lineage↗
PubMed2004

Genetic predisposition to cancer - insights from population genetics.

Individuals differ in their inherited tendency to develop cancer. Major single-gene defects that cause early cancer onset have been known for many years from their inheritance patterns, and inherited defects that have weaker effects on predisposition were also suspected to exist. Recent progress in cancer genetics has identified specific loci that are involved in cancer progression, many of which have key roles in DNA repair, cell-cycle control and cell-death pathways. Those loci, which are often mutated somatically during cancer progression, sometimes also contain inherited mutations. Recent genetic studies and quantitative population-genetic analyses provide a framework for understanding the frequency of inherited mutations and the consequences of these mutations for increased predisposition to cancer.

Age Factors↗
PubMed2003

Somatic selection for and against cancer.

In multicellular organisms, cells cooperate within a well-defined developmental program. Cancer is a breakdown of such cooperation: cells mutate to phenotypes of uncoordinated proliferation. We study basic principles of the architecture of solid tissues that influence the rate of cancer initiation. In particular, we explore how somatic selection acts to prevent or to promote cancer. Cells with mutations in oncogenes or tumor suppressor genes often have increased proliferation rates. Somatic selection increases their abundance and thus enhances the risk of cancer. Many potentially harmful mutations, however, increase the probability of triggering apoptosis and, hence, initially lead to cells with reduced net proliferation rates. Such cells are eliminated by somatic selection, which therefore also works to reduce the risk of cancer. We show that a tissue organization into small compartments avoids the rapid spread of mutations in oncogenes and tumor suppressor genes, but promotes genetic instability. In small compartments, genetic instability, which confers a selective disadvantage for the cell, can spread by random drift. If both deleterious and advantageous mutations participate in tumor initiation, then we find an intermediate optimum for the compartment size.

Animals↗
PubMed2003

Stochastic elimination of cancer cells.

Tissues of multicellular organisms consist of stem cells and differentiated cells. Stem cells divide to produce new stem cells or differentiated cells. Differentiated cells divide to produce new differentiated cells. We show that such a tissue design can reduce the rate of fixation of mutations that increase the net proliferation rate of cells. It has, however, no consequence for the rate of fixation of neutral mutations. We calculate the optimum relative abundance of stem cells that minimizes the rate of generating cancer cells. There is a critical fraction of stem cell divisions that is required for a stochastic elimination ('wash out') of cancer cells.

Animals↗
PubMed2003

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.

Gene Frequency↗
PubMed2003

Patterns of cell division and the risk of cancer.

Epidermal and intestinal tissues divide throughout life to replace lost surface cells. These renewing tissues have long-lived basal stem cell lineages that divide many times, each division producing one stem cell and one transit cell. The transit cell divides a limited number of times, producing cells that move up from the basal layer and eventually slough off from the surface. If mutation rates are the same in stem and transit divisions, we show that minimal cancer risk is obtained by using the fewest possible stem divisions subject to the constraints imposed by the need to renew the tissue. In this case, stem cells are a necessary risk imposed by the constraints of tissue architecture. Cairns suggested that stem cells may have lower mutation rates than transit cells do. We develop a mathematical model to study the consequences of different stem and transit mutation rates. Our model shows that stem cell mutation rates two or three orders of magnitude less than transit mutation rates may favor relatively more stem divisions and fewer transit divisions, perhaps explaining how renewing tissues allocate cell divisions between long stem and short transit lineages.

Cell Division↗