David Dingli

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.

A) symmetric stem cell replication and cancer

Most tissues in metazoans undergo continuous turnover due to cell death or epithelial shedding. Since cellular replication is associated with an inherent risk of mutagenesis, tissues are maintained by a small group of stem cells (SCs) that replicate slowly to maintain their own population and that give rise to differentiated cells. There is increasing evidence that many tumors are also maintained by a small population of cancer stem cells that may arise by mutations from normal SCs. SC replication can be either symmetric or asymmetric. The former can lead to expansion of the SC pool. We describe a simple model to evaluate the impact of (a)symmetric SC replication on the expansion of mutant SCs and to show that mutations that increase the probability of asymmetric replication can lead to rapid mutant SC expansion in the absence of a selective fitness advantage. Mutations in several genes can lead to this process and may be at the root of the carcinogenic process.

Compartmental architecture and dynamics of hematopoiesis.

Background Blood cell formation is maintained by the replication of hematopoietic stem cells (HSC) that continuously feed downstream “compartments” where amplification and differentiation of cells occurs, giving rise to all blood lineages. Whereas HSC replicate slowly, committed cells replicate faster as they become more differentiated. Methodology/Significant Finding We propose a multi-compartment model of hematopoiesis, designed on the principle of cell flow conservation under stationary conditions. Cells lost from one compartment due to differentiation are replaced by cells from the upstream compartment. We assume that there is a constant relationship between cell input and output in each compartment and fix the single parameter of the model using data available for granulocyte maturation. We predict that ∼31 mitotic events separate the HSC from the mature cells observed in the circulation. Besides estimating the number of compartments, our model allows us to estimate the size of each compartment, the rate of cell replication within each compartment, the mean time a given cell type contributes to hematopoiesis, the amplification rate in each compartment, as well as the mean time separating stem-cell replication and mature blood-cell formation. Conclusions Despite its simplicity, the model agrees with the limited in vivo data available and can make testable predictions. In particular, our prediction of the average lifetime of a PIG-A mutated clone agrees closely with the experimental results available for the PIG-A gene mutation in healthy adults. The present elucidation of the compartment structure and dynamics of hematopoiesis may prove insightful in further understanding a variety of hematopoietic disorders.

Allometric Scaling of the Active Hematopoietic Stem Cell Pool across Mammals

Background Many biological processes are characterized by allometric relations of the type Yu200a=u200aY 0 Mb between an observable Y and body mass M, which pervade at multiple levels of organization. In what regards the hematopoietic stem cell pool, there is experimental evidence that the size of the hematopoietic stem cell pool is conserved in mammals. However, demands for blood cell formation vary across mammals and thus the size of the active stem cell compartment could vary across species. Methodology/Principle Findings Here we investigate the allometric scaling of the hematopoietic system in a large group of mammalian species using reticulocyte counts as a marker of the active stem cell pool. Our model predicts that the total number of active stem cells, in an adult mammal, scales with body mass with the exponent ¾. Conclusion/Significance The scaling predicted here provides an intuitive justification of the Hayflick hypothesis and supports the current view of a small active stem cell pool supported by a large, quiescent reserve. The present scaling shows excellent agreement with the available (indirect) data for smaller mammals. The small size of the active stem cell pool enhances the role of stochastic effects in the overall dynamics of the hematopoietic system.

On the Origin of Multiple Mutant Clones in Paroxysmal Nocturnal Hemoglobinuria

The pool of hematopoietic stem cells that actively contributes to hematopoiesis is small, and the cells replicate slowly. Patients with paroxysmal nocturnal hemoglobinuria invariably have a mutation in the PIG‐A gene, and many have more than one clone of PIG‐A mutated cells. Typically there is a dominant clone and a smaller second clone. By using a combination of stochastic dynamics and models of hematopoiesis, we show that it is very unlikely that more than one PIG‐A mutated clone arises at the level of the hematopoietic stem cells. More likely, the smaller clone develops in the progenitor cell pool that would be expected to contribute to hematopoiesis for a shorter period of time. We provide estimates for the duration of these contributions and testable hypotheses that can shed important insights on this acquired hematopoietic stem cell disorder.

Ontogenic growth of the haemopoietic stem cell pool in humans

Recently, the size of the active stem cell pool has been predicted to scale allometrically with the adult mass of mammalian species with a 3/4 power exponent, similar to what has been found to occur for the resting metabolic rate across species. Here we investigate the allometric scaling of human haemopoietic stem cells (HSCs) during ontogenic growth and predict a linear scaling with body mass. We also investigate the allometric scaling of resting metabolic rate during growth in humans and find a linear scaling with mass similar to that of the haemopoietic stem cell pool. Our findings suggest a common underlying organizational principle determining the linear scaling of both the stem cell pool and resting metabolic rate with mass during ontogenic growth within the human species, combined with a 3/4 scaling with adult mass across mammalian species. It is possible that such common principles remain valid for haemopoiesis in other mammalian species.

Serum M-spike and transplant outcome in patients with multiple myeloma.

High dose therapy with autologous stem cell transplantation (HDT‐ASCT) has prolonged survival in patients with multiple myeloma. Patients who achieve a complete response (CR) benefit the most from this form of therapy. Thus, achieving a CR is an important goal of therapy and it will be beneficial if the probability of achieving CR can be determined for any patient before transplant. Here we report that pretransplant monoclonal protein level (M‐spike) was found to be an important predictor. Thus, we used knowledge of the rate of M‐protein production by myeloma cells together with the clearance of the protein to estimate the pretransplant disease burden. We show that the pretransplant disease burden, based on the M‐spike, is the only predictor for achieving CR. A simple function that describes this probability is presented. We also provide an estimate of the rate of tumor regrowth in patients who obtain a CR and in patients who only get a partial response with HDT‐ASCT. The significant expansion of myeloma cells after HDT‐ASCT is clearly evident. Clinical trials must be designed that take into account these kinetic aspects of the disease. (Cancer Sci 2007; 98: 1035–1040)

In vivo and in silico studies on single versus multiple transplants for multiple myeloma

High‐dose therapy and autologous stem cell transplantation (HDT‐ASCT) have significantly improved survival in multiple myeloma (MM). However, patients are not cured, responses are variable and only about 40% of patients achieve a complete response (CR). Optimal timing of the procedure and knowledge of the relapse kinetics may assist physicians when they consider this therapeutic modality for their patients. We analyzed myeloma tumor burden and kinetics before and after HDT‐ASCT in a cohort of 265 patients. Disease burden was estimated from serial M‐spike measurements and the data fitted to the Gompertz function to determine the general parameters for all patients. Functions that couple disease burden and kinetics with time to progression (TTP) were derived and used to determine the optimal timing of transplantation. Patients who achieve CR with the first episode of HDT‐ASCT should not be routinely offered tandem transplantation but carefully monitored and transplanted at an optimal disease burden. If CR is not achieved with a first trial of HDT‐ASCT, the probability of CR after a tandem second trial is ∼10%. TTP after tandem transplants (with its higher associated mortality) cannot be superior to TTP achieved with optimally timed serial transplants. Individualized HDT‐ASCT for patients with MM is possible and may optimize results. (Cancer Sci 2007; 98: 734–739)

Successful Cancer Treatment: Eradication of Cancer Stem Cells

The increasing incidence of cancer in many countries is a consequence of our success as a species. Otherwise, cancer would be a rare event. This is no accident, and its justification can be found at the root of the evolution of multicellular organisms. Indeed, the emergence of multicellular organisms required coordination and cooperation between cells that became increasingly specialized resulting in an overall benefit for the organism. Multicellularity also brings with it the risk of cancer, viewed as the deregulated proliferation of a new and particular cell-type population that can threaten the integrity and survival of the organism (Hanahan and Weinberg, 2000). Studies during the last 40–50 years have shown that cancer is an acquired genetic disorder due to mutations that activate proto-oncogenes, silence tumor suppressor genes or induce genomic instability (Vogelstein and Kinzler, 2004). Genetic mutations can be due to exogenous genotoxic agents such as ionizing radiation or chemotherapeutic agents that interact with DNA. However, the genome replication machinery is also prone to errors that inevitably result in mutations being incorporated in cells (Kunkel and Bebenek, 2000). Hence, individuals with mutations in DNA-repair enzymes have an intrinsically higher risk of cancer.