Mutated clones are the new normal Tomasetti, Cristian
Science (American Association for the Advancement of Science),
06/2019, Letnik:
364, Številka:
6444
Journal Article
Recenzirano
Measuring and understanding the dynamics of clonal cell populations is key for cancer prevention
Cancers are formed by the expansion of harmful “mutational clones,” which are cell populations ...carrying the same DNA mutations. How harmful they are depends on which mutated genes they contain. On page 970 of this issue, Yizhak
et al.
(
1
) add to the evidence that normal tissues are not so normal after all. Examining a substantial number of healthy tissues from almost 500 individuals, they found a large number of acquired (somatic) DNA mutations—some of which are typically associated with cancer—and mutational clones of macroscopic size, in the absence of cancer pathology. The presence in normal tissues of clonal cell populations, with mutations in cancer-associated genes, is informative about how a tumor evolves from the first mutation to a benign growth and, finally, to cancer.
Cancers are caused by mutations that may be inherited, induced by environmental factors, or result from DNA replication errors (R). We studied the relationship between the number of normal stem cell ...divisions and the risk of 17 cancer types in 69 countries throughout the world. The data revealed a strong correlation (median = 0.80) between cancer incidence and normal stem cell divisions in all countries, regardless of their environment. The major role of R mutations in cancer etiology was supported by an independent approach, based solely on cancer genome sequencing and epidemiological data, which suggested that R mutations are responsible for two-thirds of the mutations in human cancers. All of these results are consistent with epidemiological estimates of the fraction of cancers that can be prevented by changes in the environment. Moreover, they accentuate the importance of early detection and intervention to reduce deaths from the many cancers arising from unavoidable R mutations.
Although it has been hypothesized that some of the somatic mutations found in tumors may occur before tumor initiation, there is little experimental or conceptual data on this topic. To gain insights ...into this fundamental issue, we formulated a mathematical model for the evolution of somatic mutations in which all relevant phases of a tissue’s history are considered. The model makes the prediction, validated by our empirical findings, that the number of somatic mutations in tumors of self-renewing tissues is positively correlated with the age of the patient at diagnosis. Importantly, our analysis indicates that half or more of the somatic mutations in certain tumors of self-renewing tissues occur before the onset of neoplasia. The model also provides a unique way to estimate the in vivo tissue-specific somatic mutation rates in normal tissues directly from the sequencing data of tumors. Our results have substantial implications for the interpretation of the large number of genome-wide cancer studies now being undertaken.
Significance The number of driver events required for human tumorigenesis has remained one of the fundamental issues in cancer research since the seminal studies of Armitage and Doll. This question ...has become even more important with the recent genome-wide sequencing studies of cancer, whose major goal is the identification of the driver genes responsible for tumor initiation and progression. By using a novel approach that combines conventional epidemiologic studies with genome-wide sequencing data, we show that only three sequential mutations are required to develop lung and colon adenocarcinomas, a number that is lower than what is typically thought to be required for the formation of cancers of these and other organs. This finding has important implications for the design of future cancer genome-sequencing efforts.
Cancer arises through the sequential accumulation of mutations in oncogenes and tumor suppressor genes. However, how many such mutations are required for a normal human cell to progress to an advanced cancer? The best estimates for this number have been provided by mathematical models based on the relation between age and incidence. For example, the classic studies of Nordling Nordling CO (1953) Br J Cancer 7(1):68–72 and Armitage and Doll Armitage P, Doll R (1954) Br J Cancer 8(1):1–12 suggest that six or seven sequential mutations are required. Here, we describe a different approach to derive this estimate that combines conventional epidemiologic studies with genome-wide sequencing data: incidence data for different groups of patients with the same cancer type were compared with respect to their somatic mutation rates. In two well-documented cancer types (lung and colon adenocarcinomas), we find that only three sequential mutations are required to develop cancer. This conclusion deepens our understanding of the process of carcinogenesis and has important implications for the design of future cancer genome-sequencing efforts.
In a randomized, controlled trial, a ctDNA-guided approach to the postsurgical treatment of stage II colon cancer reduced adjuvant chemotherapy use without compromising recurrence-free survival.
Often, resistance to drugs is an obstacle to a successful treatment of cancer. In spite of the importance of the problem, the actual mechanisms that control the evolution of drug resistance are not ...fully understood. Many attempts to study drug resistance have been made in the mathematical modeling literature. Clearly, in order to understand drug resistance, it is imperative to have a good model of the underlying dynamics of cancer cells. One of the main ingredients that has been recently introduced into the rapidly growing pool of mathematical cancer models is stem cells. Surprisingly, this all-so-important subset of cells has not been fully integrated into existing mathematical models of drug resistance. In this work we incorporate the various possible ways in which a stem cell may divide into the study of drug resistance. We derive a previously undescribed estimate of the probability of developing drug resistance by the time a tumor is detected and calculate the expected number of resistant cancer stem cells at the time of tumor detection. To demonstrate the significance of this approach, we combine our previously undescribed mathematical estimates with clinical data that are taken from a recent six-year follow-up of patients receiving imatinib for the first-line treatment of chronic myelogenous leukemia. Based on our analysis we conclude that leukemia stem cells must tend to renew symmetrically as opposed to their healthy counterparts that predominantly divide asymmetrically.
Recent evidence arising from DNA sequencing of healthy human tissues has clearly indicated that our organs accumulate a relevant number of somatic mutations due to normal endogenous mutational ...processes, in addition to those caused by environmental factors. A deeper understanding of the evolution of this endogenous mutational load is critical for understanding what causes cancer. Here we present a mathematical model of tumor evolution that is able to predict the expected number of endogenous somatic mutations present in various tissue types of a patient at a given age. These predictions are then compared to those observed in patients. We also obtain an improved fitting of the variation in cancer incidence across cancer types, showing that the endogenous mutational processes can explain 4/5 of the variation in cancer risk. Overall, these results offer key insights into cancer etiology, by providing further evidence for the major role these endogenous processes play in cancer.
Research in many fields emphasizes the value of prevention
Prevention of any disease can occur at two levels: (i) avoiding or reducing risk factors coupled with increases in protective factors ...(primary prevention, which is preferable when it can be practiced) and (ii) detection and intervention early in the course of disease evolution (secondary prevention). But despite substantial epidemiologic data showing that a large proportion of cancers and cancer deaths are preventable, decreases in cancer mortality rates in developed countries have lagged far behind decreases in mortality rates from heart disease (
1
), another major disease amenable to prevention (for example, 18 versus 68% decrease, respectively, between 1969 and 2013 in the United States) (
2
). We believe that one main factor explaining the relatively modest reduction in mortality is the limited support for cancer prevention research, which receives only 2 to 9% of global cancer research funding (
3
). As a United Nations (UN) High-Level Meeting begins this week to review efforts to combat noncommunicable diseases, a key question is how to prioritize resources to realize the potential of cancer prevention.
Earlier detection is key to reducing cancer deaths. Here, we describe a blood test that can detect eight common cancer types through assessment of the levels of circulating proteins and mutations in ...cell-free DNA. We applied this test, called CancerSEEK, to 1005 patients with nonmetastatic, clinically detected cancers of the ovary, liver, stomach, pancreas, esophagus, colorectum, lung, or breast. CancerSEEK tests were positive in a median of 70% of the eight cancer types. The sensitivities ranged from 69 to 98% for the detection of five cancer types (ovary, liver, stomach, pancreas, and esophagus) for which there are no screening tests available for average-risk individuals. The specificity of CancerSEEK was greater than 99%: only 7 of 812 healthy controls scored positive. In addition, CancerSEEK localized the cancer to a small number of anatomic sites in a median of 83% of the patients.
Little et al. 1 misrepresent our findings 2 by making incorrect statements that are similar to those previously found in some media. The problem with these types of statements has been already ...pointed out by others 3. Specifically, the authors at times confuse the concept of absolute risk with that of relative risk. We never suggested that “most cancers arose by chance”-as stated in the first sentence of the Abstract of 1. Instead, we stated that the variation in cancer risk is largely explained by stem cell divisions 2. We interpreted this correlation as indicating that replicative mutations associated with stem cell divisions (bad luck) was largely responsible for this variation.
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