DNA damage and mutation in stem and progenitor cells in the context of aging and cancer

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When protection mechanisms fail: acquisition of mutation

Despite the numerous mechanisms in place to protect stem cells from harmful effects of DNA damage, studies over the past 10 years revealed the extent to which genomic mutations arise in adult stem cells. Here we will present data demonstrating that genetic changes occurring in stem or progenitor cells contribute to tissue mosaicism. We will also highlight some of the recent literature from humans that has demonstrated that somatic genetic mosaicism is not a rare, pathological event, but a phenomenon present in many of our healthy adult tissues.

Evidence of surprising diversity in somatic genomes

Finding and studying somatic mutations in subsets of cells within a tissue is extremely challenging. While recent advances in genomic sequencing are beginning to unveil the extent to which somatic variation arises, classic genetic studies using visible marker phenotypes provided the first evidence of genetic mosaicism. Studies by Curt Stern using Drosophila first demonstrated spontaneous loss of heterozygosity (LOH) during development due to mitotic recombination between homologous chromosomes (Stern 1936b). Mitotic recombination is an important mechanism of LOH in cancer and other genetic disorders (Jonkman et al. 1997; Choate et al. 2010), though not yet well understood in healthy tissues. Somatic variation due to mobilization of transposable elements was later studied in maize by Barbara McClintock (1950). Evidence from reporter mice and DNA sequencing-based approaches suggest that Line1 element mobility contributes to genetic mosaicism in the nervous system (Coufal et al. 2009; Erwin et al. 2016; Upton et al. 2015; Muotri et al. 2005) and estimate a de novo Line1 element insertion frequency of 0.2 events per neuron in humans (Evrony et al. 2012). See (Faulkner and Garcia-Perez, 2017) for a more extensive review of this literature. How somatic mobilization of transposable elements impact adult tissues, is only beginning to be understood.
Additional mutagenic processes also shape somatic mosaicism. Sequencing clonally expanded human adult stem cells using organoids has demonstrated that around 40 de novo point mutations are acquired per year in liver, colon, and small intestine (Blokzijl et al. 2016); 13 de novo point mutations mutations per year in muscle stem cells (Franco et al. 2018); and about 200-400 total point mutations impact neural precursors (Lodato et al. 2015). One prominent mutational signature found in both human and mouse precursors is C-to-T transitions at CpG dinucleotides, thought to be due to deamination of 5-methylcytosine to thymine (Behjati et al. 2014; Blokzijl et al. 2016; Lodato et al. 2015). In addition, larger-scale gene deletion and rearrangements were detected using SNP array methodology, with around 14% of human colon crypts bearing a large-scale deletion or LOH event (Hsieh et al. 2013), which has been also documented in other tissues (O’Huallachain et al. 2012). Whole-genome sequencing of colon also recently confirms SNP and copy number changes in healthy tissue (Lee-Six et al. 2019). Aneuploidy and copy number variation in the brain and other tissues have similarly been reported, though frequencies vary depending on the detection technique (Rehen et al. 2002; Cai et al. 2014; O’Huallachain et al. 2012). Thus, it is now abundantly clear that human tissues have high degrees of genetic mosaicism. It is, therefore, critical to perform functional studies to understand the full impact of mosaicism on young, aged, healthy and diseased adult tissues.

Clonal expansion in blood and solid tissues

Mosaic patches of adult tissue, or “clones”, can result from a long-lived stem or progenitor cell acquiring a mutation driving positive selection due to increased fitness, or from neutral drift of an alteration with no impact on fitness (Snippert et al. 2010; Traulsen et al. 2013). Evidence for age-dependent clonal expansion of mutant stem cell lineages in the blood dates back to the 90s where probes for the inactive X-chromosome were used and detected its skewing during aging (Fey et al. 1994; Busque et al. 1990). More recently, the study of “healthy” control blood using sequencing-based approaches led to surprising evidence for clonal expansion of lineages having somatic mutation in the genes TET2, DNMT3a, and ASLX1 during adult aging (Busque et al. 2012; Jacobs et al. 2012; Laurie et al. 2012; Holstege et al. 2014; Welch et al. 2012). The physiological implications of blood clonality will be discussed further below but for an extensive review on clonal haematopoiesis see (Jaiswal and Ebert 2019).
Mounting evidence similarly indicates that solid tissues also have a high degree of genetic mosaicism with mutant progenitor cells giving rise to expanding mutant lineages under positive selection. In the 90s, it was recognized with PCR and through whole-mount tissue staining that sun-exposed normal human skin acquires clones of mutant TP53 (Nakazawa et al. 1993; Jonason A S et al. 1996). In recent years, these finding were greatly extended using targeted deep sequencing of 74 cancer driver genes on biopsies of normal sun-exposed eyelid epidermis and normal esophagus tissue. Frequent mutation of genes was found, including in NOTCH1 and TP53, that expand clonally and accumulate with age (Martincorena et al., 2015, 2018; Yokoyama et al., 2019). Additional recent evidence for large clonal expansions across numerous tissues including breast and lung has been demonstrated with mutational analysis of RNAseq data (Yizhak et al. 2019). Furthermore, other tissues show clear examples of somatic mutation-driven clonal expansion. In humans, megaencephaly syndromes leading to a clonal overgrowth of part of the brain arise through activating mutations of the AKT/PI3K pathway that can be due to somatic mutations arising in neural precursor cells (Lee et al. 2012; Rivière et al. 2012; Lodato et al. 2017; Poduri et al. 2012). Interestingly, somatic mutations activiating PI3K have also been found to lead to Proteus syndrome, with patients having overgrowth of fibrous and adipose tissues (Lindhurst et al. 2012). Thus, positive selection of mutant lineages is prevalent in human tissues. The implications on cancer initiation of somatic mutations in driving early lineage expansion and selection will be further discussed below.

DNA damage and somatic mutation in adult tissues: roles in cancer initiation and aging

What is the impact of these mutations on tissues? Clearly cancer initiation is one detrimental consequence, but not all mutations lead to cancer. Here the functional implications of somatic genetic mosaicism will be highlighted.

Somatic mutations and cancer initiation

For over a hundred years, it has been recognized that cancer cells are distinct from normal ones due to the presence of aberrant genomes (Boveri 1914).Therefore, recent revelations that normal tissues harbor extensive mutations, raise important questions about the relationship between apparently healthy tissue and cancer: do mutations that provide positive selection in a tissue actually promote the eventual acquisition of additional genetic mutations leading to cancer as described in a classical multistep carcinogenesis model? Alternatively, in some instances, might these be two distinct selection processes with cancer requiring a divergent path from one that optimizes growth within an otherwise healthy tissue? As previously discussed, multiple modes of cell and lineage competition actively shape the nature of selection within a tissue and, in theory, could respond differently to expanding mutant lineages versus precancerous clones.
Evidence from clonal hematopoiesis supports a multistep process where a first mutation in healthy tissue precedes additional mutation (Figure 1.3A-D), increasing cancer risk. Indeed, longitudinal studies of patients with clonal hematopoiesis detected by SNP arrays support a strong increased risk of developing not only hematological cancer (Laurie et al. 2012; Jacobs et al. 2012; Welch et al. 2012; Genovese et al. 2014; Jaiswal et al. 2014; Coombs et al. 2017), but also lung and kidney cancers (Jacobs et al. 2012). Exome sequencing revealed that known tumor suppressor genes of myeloid cancers such as TET2, DNMT3A and ASXL1, were mutated in apparently healthy blood (Busque et al. 2012; Genovese et al. 2014; Jaiswal et al. 2014; McKerrell et al. 2015; Coombs et al. 2017). Thus, the acquisition of these mutations in healthy blood is thought to represent the earlier phase in the development of leukemogenesis and suggests a period of latency that precedes it. Therefore, an understanding of how processes such as stem cell competition for niche occupancy may influence the switch from a premalignant state to a malignant one is important (Figure 1.3B,D).
Recent studies in the skin and esophagus support the idea of healthy tissue acquiring premalignant drivers, but also suggest the intriguing possibility that healthy tissues may have distinct selective pressures than those in cancer. Targeted deep sequencing of normal oesophageal epithelium from young and old donors revealed that the number of detectable mutations and the sizes of mutant clones increased with donor age (Martincorena, et al., 2018). NOTCH1 and TP53, canonical drivers of Esophageal squamous cell carcinoma (ESCC), were found to be under selection in normal tissue (Martincorena et al., 2018b; Yokoyama et al., 2019). Thus, the presence of clonal expansions in the normal epithelium suggests that these clones have a premalignant capacity and their persistence can lead to cancer initiation (Figure 1.3B,D). These data strongly support the concept of “field cancerization” (Slaughter and Southwick 1953), previously proposed to predispose the esophagus to development of subsequent multiple tumors via initial precancerous drivers such as p53 (Tian et al. 1998). Nevertheless, an intriguing finding is that mutations in NOTCH1 and PPM1D are much more prevalent in normal skin than in cancer (Martincorena et al., 2018b; Yokoyama et al., 2019). This suggests that different fitness of certain mutations exist in “normal” tissue versus cancer, complicating the notion of a linear multistep mutation accumulation process. Future studies will be necessary to understand these fitness differences and potentially capitalize on them for clinical benefit.

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An impact of mutations and DNA damage on aging?

Aside from initiating and driving cancer evolution, what impact do somatic mutations have on aging? Here some of the potential detrimental consequences of mutation on tissues will be discussed.
Studies from clonal hematopoiesis have demonstrated a collapse of clonal diversity with very few stem cells contributing to the aging blood (Figure 1.3C). This results from “winner” HSC clones expanding and, in an apparent zero-sum game, “loser” HSCs failing to contribute to blood. This was strikingly demonstrated from sequencing the blood of a hematologically asymptomatic supercentenarian (aged 115 years old) revealing that approximately 65% of her healthy blood compartment was dominated by the progeny of two hematopoietic stem cell (HSC) clones (Holstege et al. 2014). Extending on earlier work discussed above (Busque et al. 2012; Jacobs et al. 2012; Laurie et al. 2012; Welch et al. 2012), a study using whole-genome sequencing from the peripheral blood of ~11,000 Icelanders of different ages found that a striking 50% of patients older than 85 had clonal hematopoiesis (Zink et al. 2017a). Thus, abundant evidence indicates that mutations arise in HSCs (or in very upstream precursor cells) during aging and lead to selection of mutant lineages, however, the functional impact of collapse of clonal diversity is still not fully understood. One feature of the aging hematopoietic system in humans and mouse is a bias towards myeloid lineages (Sudo et al. 2000; Ganuza et al. 2019; Yamamoto et al. 2017). While unlikely to explain all of the myeloid bias of HSCs that occurs during aging, TET2 deletion is sufficient in mouse to lead to a myeloid disorder (Li et al. 2011) and is strongly associated with myeloid dysplasia in humans (Buscarlet et al. 2018). Thus, a failure to maintain the repertoire of differentiated cell types present in youth can arise from a loss of clonal diversity. Interestingly, a reduction in the clonality of mouse muscle stem cells upon repeated injury was found (Tierney et al. 2018). While the role of mutation or DNA damage was not evoked in this study, it is feasible that increased replication stress might indeed drive some stem cell lineages to contribute less to the tissue, possibly explaining the observed collapse in clonality in the muscle.
(A) Mutations arise in stem cells of young tissues.
(B) Age-dependent clonal expansion of mutant stem cells via positive selection or neutral drift give rise to mosaic patches. These may have a premalignant capacity and their persistence can lead to cancer initiation.
(C) Clonal expansion can lead to the age-related collapse in clonal diversity with very few stem cells contributing to the aging tissue. The functional impact of collapse of clonal diversity is still not fully understood but it can impact age-associated lineage skewing, in some cases.
(D) Clonal expansion of cancer driver genes can lead to cancer initiation.
Hypercompetitive lineages may render other lineages “losers”, but deleterious mutations may also create “loser” lineages cell-autonomously through suboptimal growth, stem cell functional decline, or loss from the tissue of the stem cell or lineage. Is there evidence for this? Quantifying deleterious mutations is a difficult task as these mutations will be either lost or only be present in a few cells.
As a work-around, techniques from evolutionary biology have been applied to look at negative selection of point mutations within somatic tissues. By considering the normalized ratio of non-synonymous to synonymous mutations, one can deduce the amount of detrimental mutations which had been lost. Strikingly, no evidence of negative selection was found in human tissues or in numerous types of cancer (Martincorena et al. 2017; Franco et al. 2018), arguing that the arising point mutations were not detrimental to the survival of the cell in which they arose. It is not yet clear how other types of mutational processes may create burdens on the cell or be selected against. For example, it is more likely that large-scale deletions or mitotic recombination-based LOH, both affecting hundreds to thousands of genes, would reduce cellular fitness. Similarly, de novo transposition events may also impair cellular function through transcriptional deregulation. The extent to which this occurs or might trigger cell death or cell selection mechanisms at the tissue level, is not yet known.

Contributions of persistent DNA damage to stem cell decline

A large body of literature using induced DNA damage has explored the effects of persistent DNA damage including on HSCs, NSCs, and muscle stem cells and has demonstrated the sufficiency of DNA damage to drive early aging phenotypes. For some excellent reviews of the subject (Williams and Schumacher 2017; Niedernhofer et al. 2018). While much of this work is not exclusively on stem cells, collectively these studies demonstrate that unrepaired DNA damage can perturb general cellular function in a number of ways including: 1. Leading to cell cycle arrest, 2. Driving apoptosis or cellular senescence, 3. Physically disrupting transcription (Garinis et al. 2009), 4. Causing large transcriptomic changes including growth signaling and metabolic pathways (Edifizi et al. 2017), 5. Altering chromatin organization through relocalization of factors to DNA damage sites (Oberdoerffer et al. 2008).

Table of contents :

Chapter 1 : Introduction
1.1 DNA damage and mutation in stem and progenitor cells in the context of aging and cancer
Stem cells and tissue dynamics
DNA damage and how it leads to mutation
Mechanisms protecting the stem cell and tissue from the effects of DNA damage
When protection mechanisms fail: acquisition of mutation
DNA damage and somatic mutation in adult tissues: roles in cancer initiation and aging
Contributions of persistent DNA damage to stem cell decline
Towards an understanding of DNA damage and mutation in adult tissues
Concluding remarks
1.2 Loss of heterozygosity (LOH): a common cause of genome alteration in somatic cells Mitotic recombination-driven LOH
DSBs: Drivers of MR
Yeast: a paradigm for studying mechanisms of MR
Another cause of LOH: Aneuploidy
Concluding remarks
1.3 The Drosophila intestine: A model to study genome alterations such as LOH in stem cells
A dynamic tissue in a powerful in vivo model
Structure of the Drosophila intestine
The role of Notch in regulating cell fate
The aging gut
Impact of the environment on the Drosophila midgut
Advantages of using the Drosophila midgut as a model system to study genome instability in adult stem cells
Chapter 2 : Results
Results Overview
2.1 Mitotic Recombination as a Mechanism Driving Spontaneous Loss of Heterozygosity in Drosophila Intestinal Stem Cells (article in preparation).
Abstract
Introduction
Results
Spontaneous loss of heterozygosity increases with age
Whole genome sequencing to determine the mechanism of LOH
LOH arises through mitotic recombination in both males and females.
LOH through mitotic recombination also happens on other chromosome arms
Rad51 promotes loss of heterozygosity
Whole-genome sequencing data supports cross over via a double-Holliday structure
Mapping of LOH initiation regions provides insight into potential sequence drivers of MR
Infection with the pathogenic enteric bacteria Ecc15 increases loss of heterozygosity
Discussion
2.2 Aneuploidy as a mechanism driving spontaneous loss of heterozygosity in Drosophila intestinal stem cells
Context
Results
Sequencing evidence for aneuploidy-driven LOH
The H4K16ac histone mark is a good readout for activation of dosage compensation in the Drosophila intestine
Loss of X (aneuploidy) is detected in aging N55E11/+ females
Discussion
Chapter 3: Discussion
Discussion Overview
3.1 Technical evaluation of the work and experimental caveats
Sample size of sequenced tumours
Tumour purity
Controversy surrounding R-loops
Additional biological repeats and RNAi lines
3.2 Discussion of results
Exploiting the clonal nature of LOH neoplasia in the Drosophila intestine: the novelty
Mechanisms of LOH
Genomic Drivers of MR
Impact of the stem cell niche and environment on LOH
LOH with age
3.3 Implications of the research and conclusions
Implications of the research and perspectives
Conclusions

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