Cancer-Associated Mutations but No Cancer: Insights into the Early Steps of Carcinogenesis and Implications for Early Cancer Detection

Abstract

Cancer is a disease of aging fueled by the accumulation of somatic mutations. While mutations in tumors are well characterized, little is known about the early mutational processes that initiate tumorigenesis. Recent advances in next-generation sequencing (NGS) have enabled the detection of mutations in normal tissue, revealing an unanticipated high level of age-related somatic mutations affecting most individuals and tissues. Surprisingly, many of these mutations are similar to mutations commonly found in tumors, suggesting an ongoing process of positive selection and clonal expansion akin to what occurs in cancer, but within normal tissue. Here we discuss some of the most important biological and clinical implications of these novel findings, with a special focus on their impact for cancer detection and prediction.

Cancer-Associated Mutations Are Frequent within Normal Tissue

Somatic mutations (see Glossary) accumulate with aging and contribute to cancer [1], but little is known about how or when this process actually occurs. Until recently, the main challenge to studying this process was technical: the frequency of somatic mutations within normal tissue is well below the detection limit of conventional sequencing technologies. With the advent of next-generation sequencing (NGS) and, more recently, error-corrected NGS (ecNGS) [2], mutations in normal tissue have started to be characterized with unprecedented resolution (reviewed in [3]). Two main features have emerged. First, somatic mutations are highly prevalent, to the extent that it is unlikely for any two somatic cells to have the exact same genome [4]. Second, a large proportion of these mutations occur in cancer genes and harbor signs of positive selection [3], supporting the striking conclusion that ‘clonal evolutionary processes typically thought of as operative only in neoplasia are, in fact, a ubiquitous part of normal aging’ [5].

The presence of cancer mutations within normal tissue has been recognized for decades [6,7] and has been extensively studied in the context of field cancerization and preneoplastic diseases [8-10]. However, the ubiquitous presence of these mutations across tissues and individuals was unanticipated. The first reports of extensive cancer mutations in patients without cancer occurred in 2014 when three groups simultaneously reported mutations in leukemia genes in the blood of ~10% of healthy individuals aged 65 or older [11-13]. This phenomenon, called clonal hematopoiesis of indeterminate potential (CHIP) [14], was not initially observed in younger individuals. However, the subsequent use of ecNGS revealed the presence of CHIP in 3% of individuals aged 20–29 [15] and 95% of individuals aged 50–60 [16]. Sequencing of induced pluripotent stem cells and single-cell analysis from leukocytes across a wide range of ages (newborn to centenarians) has demonstrated the presence of somatic mutations in cells from all individuals of all ages [17,18]. These mutations often affected genes or loci implicated in cancer, increased near linearly with age, and, in one study [18], were associated with increased risk of leukemia and mortality.

In a groundbreaking report in 2015, Martincorena et al. reported the presence of thousands of clones harboring cancer-associated mutations in normal skin of four individuals aged 55 to 73 [19], demonstrating that the phenomenon is not limited to the hematopoietic compartment. A year later, using an ecNGS method called Duplex Sequencing [20,21], our group observed the presence of very low frequency TP53 mutations (variant allele frequency ~0.01%) in peritoneal fluid and leukocytes of women with and without ovarian cancer [22]. These mutations were found in nearly all samples analyzed (ages 32 to 85) and their frequency increased with age. In addition, these mutations were primarily nonsynonymous, clustered in common TP53 mutational hotspots, and were frequently predicted to be inactivating, strongly suggesting that they were positively selected.

Since the publication of these initial reports, several additional studies have documented the presence of cancer-associated mutations in a variety of normal solid tissues and benign conditions, including esophagus [23,24], colon [25], brain [26], endometrium [27-30], several gynecological tissues [29], and a comprehensive set of 29 human tissues [31]. These findings are quickly expanding and reshaping our understanding of human carcinogenesis. Our goal is to discuss the emerging biological and clinical implications derived from this growing body of literature in order to illuminate research efforts moving forward.

Biological Implications of Cancer-Associated Mutations within Normal Tissue as an Aging Phenotype

The Darwinian principles of mutation, selection, and clonal expansion were adapted by Nowell to explain cancer evolution more than 40 years ago [32]. During this time, a cumulative body of evidence has demonstrated the evolutionary nature of cancer [33,34], but the early stages of carcinogenesis have been remarkably difficult to study due to the lack of suitable methods to detect incipient mutated clones within normal tissue. Prior to the development of such methods, mathematical modeling based on the positive correlation of mutational burden in tumors with patient age indicated that a large proportion of tumor mutations likely occur prior to tumor formation [35]. Supporting these findings, the analysis of mutational signatures in cancers identified two signatures that strongly correlated with patient age across almost all cancer/tissue types [36,37]. This indirect evidence of the accumulation of somatic mutations with age via their identification in cancer tissue has now been directly validated by sequencing healthy tissue. These studies not only have confirmed the age-related accumulation of mutations, but have also provided important clues to understand somatic evolution and the early steps of human carcinogenesis. We summarize some of the emerging biological implications of these findings.

Biological Implication #1: Positive Selection of Cancer-Associated Mutations Is a Normal Phenotype of Aging

DNA mutations occur as a consequence of exogenous cellular factors (e.g., UV light, smoking) and endogenous cellular factors (e.g., replication) and are inevitable throughout life. While most mutations are likely to be neutral or deleterious, a subset of mutations can provide proliferative advantages that lead to the expansion of the cell that carries them (Figure 1, Key Figure). This process of positive selection and clonal expansion underlies the evolution of cancer, but numerous reports have now confirmed that it is also a normal process of human aging (reviewed in [3]). While mutated clones can arise by random genetic drift, numerous lines of evidence support the fact that most age-related clonal expansions originate by positive selection. Martincorena and colleagues demonstrated that the most commonly mutated genes in normal human skin (i.e., NOTCH1-3, TP53, FAT1, and RBM10) carry positively selected mutations as indicated by a dN/dS ratio (nonsynonymous to synonymous substitutions) greater than one [19]. This phenomenon is not exclusive to skin, as an excess of nonsynonymous mutations was also observed in mutated genes identified in the normal esophagus [23,24] and TP53 mutations in peritoneal fluid and uterine lavages from women without cancer [22,29].

Figure 1. Key Figure. Somatic Evolution as a Process of Normal Human Aging and Cancer.

DNA mutations inevitably accumulate throughout life due to DNA replication and environmental and lifestyle factors. Mutations might be neutral (grey lines), deleterious (X), or might confer a proliferative advantage and the cell clonally expands (green, blue, yellow). These initial clonal expansions provide pools of mutated cells in which subsequent mutations could enable transformation properties. The large majority of clones, however, do not evolve into malignancy, which is likely due to the action of tumor suppressor mechanisms. In a subset of individuals, at older ages, tumor suppressor mechanisms are bypassed by the accumulation of additional mutations that abrogate these mechanisms and/or by their declining action with age (e.g., decreased immunity). Additional rounds of mutation, selection, and clonal expansions enable cancer cells to acquire the malignant properties characteristic of this disease. A biopsy taken at mid-age (blue broken line rectangle) might carry cancer-associated mutations from cells that have clonally expanded but are not malignant (often termed biological background mutations). In a biopsy taken when cancer has developed (orange broken line rectangle), the tumor derived clone might be identifiable due to its larger size compared with the background clones. Abbreviation: ROS, reactive oxygen species.

In addition to the enrichment for nonsynonymous mutations, the distribution of mutations within the affected genes also supports the notion of somatic selection. Under conditions of genetic drift, the expectation would be for mutations to be approximately evenly distributed throughout a gene. Contrary to this expectation, mutations frequently cluster in functionally relevant portions of the cancer-associated gene, such as DNA binding domains or regions involved in protein–protein interactions. Moreover, these patterns are nearly identical to the distribution of mutations seen in tumor sequencing data [19,22,23,29]. Most remarkably, the recent analysis of TP53 mutations across a century of human lifespan revealed a progressive transition from random mutations in newborn tissue to cancer-like mutations in centenarian tissue, illustrating the cumulative action of positive selection throughout a lifetime [29].

Biological Implication #2: Tumor Suppression Mechanisms Must Be Extremely Robust

Given the high frequency of positively selected clones in normal tissue, why is clinically diagnosed cancer not more common in the human population? A possible explanation relies on the action of tumor suppressor mechanisms, which can be viewed as nature’s solution to prevent cancer formation in multicellular organisms [38]. Malignant transformation requires the bypass of tumor suppressor mechanisms operating in a given tissue at a given time. These include, among others, contact inhibition, senescence, and immune surveillance (Figure 1). While nonmalignant clones may have acquired some of the early hallmarks of cancer (e.g., self-sufficiency in growth signals, insensitivity to antigrowth signals, or evasion of apoptosis [39]) resulting in their selective clonal expansion, they seemingly are unable to further their progression. The high prevalence of cancer-associated mutations in the absence of apparent cancer suggests that their occurrence is not rate limiting to tumor formation. Moreover, the observed presence of cancer-associated mutations in early life indicates that these mutations can exist for long periods of time without ever converting to overt disease, suggesting that tumor suppression mechanisms must be far more effective and multifactorial than generally appreciated. Indeed, the success of suppression mechanisms is exemplified by two cases: (i) TP53, considered the most important tumor suppressor gene, is commonly mutated in human noncancerous tissues [19,23,24,29]. The frequent loss of function in this gene points to many additional suppression layers that must be overcome prior to tumor formation. (ii) Data from CHIP studies indicate that individuals with identified mutant clones involving genes related to hematological malignancies have a 12.9-fold increased risk of hematologic cancer. However, the absolute risk is still only ~1% per year [11], indicating that in the vast majority of cases the clones never result in malignancy. Of note, while tumor suppressor mechanisms are remarkably successful in preventing cancer in early life, their efficiency might decrease later in life, contributing to the increased incidence of cancer at older age. The decline of the immune system [40], epigenetic remodeling [41], and the antagonistic pleiotropic effects of senescence [42] are well-known age-related features that are worth investigating in the context of malignant transformation of pre-existing clonal expansions at older age.

While tumor suppressor mechanisms are critical to restrain potential premalignant clones, there are additional explanations for the disconnect between the high frequency of putative pathogenic mutations in human tissue and the relatively low rate of cancer occurrence. One possibility is that the occurrence of mutations in certain tumor suppressors or proto-oncogenes may not be an important driver of proliferation and oncogenic transformation in certain tissue types in which they are observed; for example, KRAS mutations are observed at low to moderate frequencies in a wide variety of cancers, but are highly prevalent in lung, colon, and pancreatic cancers [43]. This observation suggests that clones carrying KRAS mutations are likely to be highly tumorigenic in these susceptible tissues, but less so in others. In less susceptible tissues, KRAS clones might only become important in conjunction with other driver gene mutations. The biological underpinnings behind the tissue-specific effects of cancer-associated mutations is poorly understood, but has been proposed to depend on the epigenetic state of cells within a tissue [44]. Importantly, this tissue specificity likely applies not only to the primary genetic drivers of cancer, but also cell non-autonomous tumor suppression mechanisms (e.g., cell contact inhibition based on tissue architecture). Another possible explanation for the high prevalence of age-related clonal expansions is that certain genes in specific tissue contexts might enhance cellular proliferation that is beneficial for tissue maintenance, as recently demonstrated in liver regeneration [45]. This might also be the case of NOTCH expansions in the normal esophagus [23,24,46]. We note that the short-term benefit of enhanced tissue regeneration may come at a cost; namely, an increased long-term risk of oncogenic transformation.

Biological Implication #3: Cancer Is a Continuum

The frequent acquisition of cancer-associated mutations decades prior to tumorigenesis suggests that cancer is an evolutionary process that takes places throughout life and across a wide variety of tissues. Early epidemiological studies involving cancer occurrence and age were consistent with a multistep process involving the acquisition of two to seven rate-limiting mutations in most cancers [47,48]. In a seminal paper, Vogelstein and colleagues synthesized years of work involving both histopathological and clinical data to argue that mutations leading to colon cancer accrue during sequential rounds of clonal selection years prior to diagnosis. They further hypothesized that this is a generalized phenomenon for carcinogenesis [49]. The current spate of sequencing data supports these early hypotheses, but indicates that the path to carcinogenesis is far longer, more pervasive, and more gradual than theory initially predicted. Moreover, new insights suggest that a large fraction of cells, and not just a small population, exist along this continuum.

In Figure 1, we have represented the early stages of clonal expansion within normal tissue and the end stage of malignant transformation. However, in many tissues, benign conditions exist that harbor mutations in cancer driver genes [50]; for example, ulcerative colitis, Barrett’s esophagus, and endometriosis are diseases that carry cancer driver mutations, but progression to malignancy is relatively uncommon [8,27,51]. These findings highlight the idea that cancer is a continuum with overt malignant disease as the clinical endpoint. While we use the term ‘precancerous’ to refer to the evolutionary stages prior to malignancy, it does not imply that these stages inevitably lead to cancer. On the contrary, as described earlier, cancer appears as a relatively rare outcome given the high prevalence of potentially precancerous clones. From a clinical perspective those clones offer both advantages and disadvantages in cancer management, which we discuss in the next section.

Clinical Implications of Cancer-Associated Mutations within Normal Tissue

Clinical Implication #1: Cancer Mutations Are Not Specific to Cancer and Challenge Early Detection

Perhaps the most important clinical implication derived from the findings of clonal evolution within normal tissue is that cancer-associated mutations, or at least a subset of them, are not specific for cancer. These findings are likely to have profound repercussions for current efforts to detect cancer early using liquid biopsies [52]. While our ability to interrogate blood biopsies for the presence of circulating tumor DNA (ctDNA) has increased dramatically in recent years, thanks to improved methods of plasma collection and more sensitive sequencing technologies [53], tumor mutation specificity has emerged as an unexpected new challenge that requires attention (Figure 2).

Figure 2. Features of Cancer Mutations in Normal Tissue (A), Identified Challenges (B), and Potential Solutions (C).

The high prevalence of cancer-associated mutations in normal tissue challenges the specificity of cancer diagnostic tests based on liquid biopsies. This challenge highlights the urgent need to characterize mutations in normal tissue in order to enable the distinction of age-related clonal expansions from truly carcinogenic ones.

Until recently, the assumption had been that mutations in cancer-associated genes were specific to cancer. However, cumulative evidence indicates that mutations in certain cancer genes are positively selected throughout life, leading to clonal expansions that accumulate across tissues as individuals age [3] (Figure 2A). This poses a significant concern for false positive results in liquid biopsy tests [54] (Figure 2B). False positive results can potentially harm patients, as they lead to unnecessary diagnostic tests, overtreatment, and psychological distress. These harms must be avoided at all costs and strongly argues for prioritizing a better understanding and characterization of these mutations.

Several cell-free DNA (cfDNA) studies have identified mutations in TP53 and KRAS in control groups (i.e., individuals without known cancer) at different proportions, ranging from 1% to 11% of individuals [55-57]. However, using ecNGS technologies, we and others have demonstrated that leukocytes carry mutations in cancer genes at a much higher frequency, close to 95–100% of adults [16,22]. This observation presents the possibility that false positives could arise from CHIP-associated mutations from contaminating leukocyte DNA in cfDNA samples either due to apoptosis or to the lysis of leukocytes prior to plasma extraction. Thus, deep sequencing of cfDNA with ecNGS is likely to reveal an even greater proportion of false positives than those found in the earlier case–control studies. Indeed, ultra-deep sequencing of cfDNA from a woman without cancer revealed several TP53 mutations, one of them pathogenic and commonly found in cancers [29].

In the context of cancer detection, we call these mutations ‘biological background’ to acknowledge the fact that they are not technical errors and to distinguish them from tumor-derived mutations. While biological background mutations introduce a significant challenge for cancer detection, there are potential solutions that could be implemented to improve the performance of future early cancer detection tests (Figure 2C).

Characterization of Mutations

Currently, very little is known about the accumulation of cancer-associated mutations in human tissues, including plasma, during normal aging. This knowledge is essential, not only to better understand cancer evolution and human aging, but also to enable optimal study design and data interpretation in studies aimed at developing tests for early cancer detection. Of particular interest is determining which genes or mutations are predictive of clinically relevant disease; for example, mutations in both TP53 and TERT promoters are prevalent across a wide variety of cancer types [43,58]. However, to date, TP53 mutations, but not TERT promoter mutations, have been widely reported to be present in normal tissues. Determining which mutations, if any, are most specific for a cancer diagnosis across multiple tissue types will be essential in realizing their full potential as a diagnostic or prognostic marker.

Age-Dependent Thresholds

Biological background mutations are typically present at very low frequency. Thus, when developing tests for early cancer detection, it will be necessary to establish and use conservative mutant allele frequency thresholds above the biological background, so that only mutations at frequency greater than the threshold are considered potentially indicative of cancer. Importantly, these thresholds will likely be different for each gene and tissue type being tested. Because biological background mutations increase with age, these thresholds might be more efficacious if they are age-dependent, in order to enable higher sensitivity for mutation detection at a younger age.

Analysis of Leukocyte Mutations

As mentioned previously, leukocytes carry background mutations that might leak into cfDNA and lead to false positives. Thus, a cautionary measure when looking for tumor mutations in cfDNA is to sequence paired leukocyte DNA simultaneously. This approach would allow for the subtraction of mutations arising from contaminating leukocyte DNA present in the cell-free fraction.

Longitudinal Biopsies

Another potential solution to increase specificity is the collection of longitudinal biopsies. Regardless of the extent of background mutations, if a clone is repeatedly observed over time at frequencies progressively increasing above background, it might be considered an indication of potential progression towards cancer, indicating further follow up.

Clinical Implication #2: The Measurement of Clonal Expansions Might Predict Cancer Risk

While clonally expanded mutations in normal tissue challenge the specificity of cancer detection, they might offer an opportunity for novel approaches to cancer prediction. This concept was originally investigated in the context of preneoplastic diseases, such as ulcerative colitis and Barrett’s esophagus, in which preneoplastic fields of histologically normal epithelium (i.e., ‘field effect’ [9,59]) have been extensively characterized [8,51,60]. These fields carry abundant molecular alterations, including somatic mutations, aneuploidy, and epigenetic changes, some of which have been leveraged as potential cancer risk factors [8]. It has been hypothesized, however, that the most useful metric to predict malignant transformation is not a specific molecular alteration, but the measurement of clonality [10]. This idea is illustrated in Figure 1 with a blue rectangle (biopsy) that includes color bands (clones). Because these clones are potential precursors of cancer, it is expected that individuals with more clones (genetic diversity) or larger clones (expansions) will be at a higher probability of developing cancer. Support for this hypothesis is provided by the demonstration that cancer progression is associated with genetic diversity in Barrett’s esophagus [61,62] and clonal expansions in ulcerative colitis [63,64].

Additional evidence for the prognostic value of clonal expansions comes from recent deep sequencing studies in preleukemic samples. In patients that developed acute myeloid leukemia (AML), blood biopsies collected more than 5 years prior to diagnosis were already enriched for mutations in AML-associated genes and carried large clonal expansions [65,66]. It is possible, however, that blood mutations could inform not only about the risk of hematological malignancies, but solid cancers as well. Our reasoning is that individuals with constitutionally higher levels of background mutations, for example, due to genetic factors (e.g., deficient DNA repair) or environmental exposures (e.g., smoking), might carry an increased burden of clonal expansions in blood, as well as in susceptible tissues in which cancer could eventually develop. This hypothesis is supported by prior studies in blood using SNP arrays, which reported an increase of both hematological cancers and solid cancers in patients with clonal expansions (reviewed in [4]). NGS studies have reported higher levels of clonal hematopoiesis in smokers [67] and an elevated number of cancer-associated mutations in the esophagus of heavy drinkers and smokers [24]. Given the potential clinical utility and the increasing availability of efficient and affordable ecNGS, the value of clonal expansions as a biomarker of cancer risk, or potentially other diseases, deserves further investigation.

Concluding Remarks

Modern sequencing platforms have revealed the genetic underpinnings driving oncogenesis. The cataloging of recurrent mutated genes has been used to great effect for prognostic indicators and targeted therapy development. The hope has been to exploit these same mutations as a means for population screening and early cancer detection. It is now apparent that some of the mutations seen in tumors are also prevalent in normal tissue and accumulate in an age-dependent manner, complicating these initial hopes. These findings have important biological and clinical implications and open up a host of important questions for the fields of cancer biology and clinical oncology (see Outstanding Questions).

Outstanding Questions.

Which mutations or mutated genes enable age-related clonal expansions and which enable further malignant transformation?

What is the tissue specificity for different mutated genes and how does this inform on the underlying biology behind different cancer types?

What are the tumor suppression mechanisms preventing the oncogenic transformation of cells already harboring mutations in key tumor suppressor pathways?

How are tumor suppressor mechanisms different in the young and old?

How do lifestyle style factors and environment contribute to somatic mutations and clonal expansions?

How does genetic predisposition to cancer contribute to somatic mutations and clonal expansions?

Are certain clonal expansions indicative or predictive of cancer and what are the best methods to quantify them?

In what biological context are clonal expansions benign?

Can interventions be developed that reduce or modify the accumulation of clonal expansions to prevent cancer?

Much like the history of cancer research, the initially promising findings generated by tumor sequencing studies have proved to be more complicated than first expected. Careful research will be needed to better understand the evolutionary process of these mutated clones within different human tissues and with aging. In addition, elucidating why mutated cells only rarely become clinically relevant disease will be critical to understand carcinogenesis. Such work may allow for interventions that prevent, reduce, or modify the expansion of these potentially deleterious mutations.

In addition to better understanding the biology of these cancer-associated mutations, their pervasive nature in normal tissue points to a need for a more nuanced terminology. Mutations frequently seen in cancer are commonly referred to as ‘driver mutations’, due to their assumed causative role in cancer; for example, TP53 is, by far, the most frequently mutated gene across all cancer types, yet is also frequently mutated in normal tissues and other benign conditions that rarely progress to malignancy. The disconnect between the presence of classic ‘driver mutations’ and the actual occurrence of cancer suggests the need to distinguish between classes of driver genes; for example, a distinction could potentially be made between genes that are specific for cancer (i.e., ‘obligate drivers’), which induce or enhance proliferation and are indicative of oncogenic transformation, versus genes with a permissive role (i.e., ‘permissive drivers’), which only become relevant in tumorigenesis subsequent to an obligate driver.

More immediate concerns arise due to the rapidly expanding field of clinical sequencing. The presence of these mutations complicates the utility of these applications. Premature deployment without proper care will likely lead to unacceptably high false positive rates, with potentially disastrous consequences for patients. It will be essential to develop new technologies, metrics (e.g., size or number of clones, mutation type, etc.), and analytical thresholds that minimize this risk. While the unexpected presence of these mutations is a complicating factor, they also provide an opportunity to better understand fundamental cancer biology and may offer a better hope for cancer prevention as we learn more about them.

Highlights.

Sequencing of normal tissues has revealed abundant mutations in cancer-associated genes, which increase with age across different tissues. Thus, mutations in certain cancer genes are not specific to cancer, but a normal phenotype of aging.

These findings reveal somatic evolution, and are consistent with cancer as a multistep process. Precancerous cells likely exist along a genetic continuum and only rarely culminate in clinically defined cancer.

Tumor suppressor mechanisms are critical to stop the progression of mutated clones. The weakening of these mechanisms at late age and/or the bypass by additional mutations renders pre-existing clones susceptible to malignant transformation.

Cancer-associated mutations in liquid biopsies compromise the specificity of DNA sequencing tests for cancer detection and minimal residual disease tracking. We highlight approaches to address this issue.

Glossary

Biological background mutations

somatic mutations present at low frequency within normal tissue or liquid biopsies. The term ‘biological background’ is mainly used to distinguish these mutations from ‘tumor derived’ mutations identified in liquid biopsies

Cancer-associated mutations

mutations frequently identified in human cancers

Cancer driver mutation

mutations that promote cancer development by providing a selective growth advantage

Cell-free DNA (cfDNA)

all freely diffusible DNA in the bloodstream or other bodily fluid, regardless of the cell of origin

Circulating tumor DNA (ctDNA)

tumor-derived DNA fragments, typically observed in the bloodstream. A special case of cell-free DNA

Clonal expansion

the generation of daughter cells all arising originally from a single cell

Clonal hematopoiesis of indeterminate potential (CHIP)

detectable clonal expansions of somatic mutations associated with hematologic malignancy in blood or marrow of individuals without hematologic malignancy

Error-corrected next-generation sequencing (ecNGS)

a group of methods that reduce the error rate of modern next-generation sequencing platforms and allow for the detection of rare somatic mutations

Field cancerization

the biological process in which a region of a tissue exhibits genetic alterations associated with cancer. These alterations frequently surround tumors

Liquid biopsy

a class of tests designed as an alternative to surgical biopsies. These tests typically search for cancer cells or fragments of DNA from a tumor that are circulating in the blood, but can include other nontissue sample types, such as urine or uterine lavage

Mutational signature

characteristic combinations of mutation types and sequence contexts arising from specific mutagenesis processes within a cell.

Next-generation sequencing (NGS)

a group of technologies defined by their ability to simultaneously sequence millions of DNA or RNA fragments. Also referred to as ‘massively parallel sequencing’.

Somatic mutation

a nonheritable mutation that occurs after conception in any tissue with the exception of the germline

Tumor suppressor mechanism

a group of genetic, cellular, and intercellular processes that act to prevent uncontrolled cellular proliferation and tumor formation.