SPONTANEOUSLY OCCURRING CLONAL HEMATOPOIESIS IN THE CANINE By Kimberley Sebastian A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Comparative Medicine and Integrative Biology – Master of Science 2022 ABSTRACT SPONTANEOUSLY OCCURRING CLONAL HEMATOPOIESIS IN THE CANINE By Kimberley Sebastian Clonal hematopoiesis of indeterminate potential (CHIP) is a clinical entity of aging humans that is characterized by cancer-associated mutations in white blood cells, without evidence of overt neoplasia. CHIP has been associated with an increased risk of hematologic cancers, cardiovascular disease, and all-cause mortality. We hypothesized that somatic mutations in specific genes associated with human CHIP would be detectable in the blood of aged dogs not known to have hematologic disorders. DNA from paired germline and whole blood samples from 93 geriatric canine patients affected by solid cancer were subjected to targeted next generation sequencing. Impact of the variants was predicted using Polymorphism Phenotyping version 2 software (PolyPhen-2, Harvard). Clinical and demographic data were extracted from medical records. Somatic variants were detected in peripheral blood of four (4.3 %) female dogs aged 12-15 years. Affected genes were ASXL1, KIT, SF3B1, TET2, RUNX1, and PPM1D. The variant in PPM1D was a nonsense mutation, while the other five variants were single nucleotide non-synonymous variants in protein coding regions of the genes. The single nucleotide variants in KIT and SF3B1 were predicted to be benign, while the variants in ASXL1, TET2, and RUNX1 were predicted to be damaging. A mutant RUNX1 cell line was designed and constructed with CRISPR technology, and the mutant cells had an increased growth rate compared to controls. These results support the presence of variants in CHIP-associated genes in geriatric canids similar to those observed in people, and the dog represents the first species in which the genetic lesion of CHIP has been documented. Further investigations are needed to confirm the association of this genetic lesion with clinical outcomes. ACKNOWLEDGMENTS I would like to express my sincere gratitude to my advisor, Dr. Bonnie Harrington, for the continuous support, motivation, enthusiasm and guidance throughout this thesis. I could not have imagined a better mentor. In addition to my advisor, I would like to thank the rest of my thesis committee: Prof. Katheryn Meek, Dr. Cynthia Lucidi, and Dr. Leanne Magestro for their encouragement and insightful comments. I thank my fellow lab mates, Cory Howard and Satyendra Singh, for their patience and their endless willingness to help. Finally, I would like to thank my family, especially Christopher, for always believing in my dreams. iii TABLE OF CONTENTS LIST OF TABLES........................................................................................................................ v LIST OF FIGURES .................................................................................................................... vi Chapter 1: Describing CHIP variants in the dog ......................................................................... 1 Introduction ............................................................................................................................ 1 Methods ................................................................................................................................. 7 Case Selection ................................................................................................................... 7 DNA Extraction and Sequencing ........................................................................................ 7 Visual Inspection of Variants and Impact Assessment ........................................................ 9 Results ..................................................................................................................................11 Discussion.............................................................................................................................16 Chapter 2: Generation of RUNX1 point mutation.......................................................................21 Introduction ...........................................................................................................................21 Methods ................................................................................................................................23 sgRNA and primer design .................................................................................................23 Cloning of sgRNA into the PX458 VQR-SpCas9 plasmid ..................................................24 Transformation of competent cells .....................................................................................25 Transfection of 17-71 dog cell line .....................................................................................26 Single cell sorting ..............................................................................................................27 Genotyping of clones.........................................................................................................28 Cell growth rate .................................................................................................................29 Results ..................................................................................................................................30 Discussion.............................................................................................................................32 APPENDICES ...........................................................................................................................34 Appendix A. Signalments and germline tissue for study dogs................................................35 Appendix B. Available CBC data for study dogs ....................................................................41 Appendix C. Coverage of target genes..................................................................................46 REFERENCES .........................................................................................................................52 iv LIST OF TABLES Table 1. Twelve canine genes selected for sequencing and investigating for the presence of CHIP. ........................................................................................................................................10 Table 2. Clinical histories of canine CHIP carriers and summary of the mutations identified by targeted next generation sequencing. .......................................................................................13 Table 3. (Appendix) Signalments and germline tissue for study dogs........................................35 Table 4. (Appendix) Available CBC data for study dogs. ...........................................................41 Table 5. (Appendix) Coverage of target genes. .........................................................................46 v LIST OF FIGURES Figure 1. Model of CHIP progression to hematopoietic malignancy............................................ 2 Figure 2. Schematic Canis familiaris genes with predicted deleterious CHIP-associated mutations. .................................................................................................................................14 Figure 3. Kaplan-Meier survival curves for dogs with and without CHIP-associated variants.....15 Figure 4. Plasmid PX458 VQR-SpCas9. ...................................................................................25 Figure 5. FACS scatter plots of control 17-71 cells and CRISPR 17-71 cells. ...........................28 Figure 6. Sanger sequencing confirmed the V105E-RUNX-1 17-71 cell line. ............................30 Figure 7. Bar chart showing the mutant cell line had a higher cell count after 72 hours of growth. ...................................................................................................................31 vi Chapter 1: Describing CHIP variants in the dog Introduction Clonal hematopoiesis (CH) refers to the overrepresentation of blood cells originating from a single clone, the frequency of which increases with age. CH is not a phenomenon inextricably linked to hematopoietic stem and precursor cells (HCPCs), as age-related somatic mutation accumulation also occurs in the skin, lung, and esophagus. Multiple studies have indicated environmental exposure during aging promotes mutant clones.1,2 The prototypical and first known example of nonneoplastic clonal hematopoiesis was published in 1996 when Busque, et al discovered nonrandom patterns of X-chromosome inactivation (XCI) in geriatric yet healthy women. 3 In 2012, the same group identified mutations in the cancer driver gene TET2, thus explaining the skewed hematopoietic activity.4 Clonal hematopoiesis of indeterminate potential (CHIP) is a recently discovered condition of humans characterized by the expansion of a subpopulation of hematopoietic cells in the blood arising from a single hematopoietic stem cell bearing a cancer-associated gene mutation.5-8 The current working definition for CHIP extends to include all patients whose white blood cells possess a mutation in a cancer driver gene at a variant allele fraction (VAF) >2 % and whom are not known to have any other hematologic disorder.9 The frequency of this phenomenon increases with age, and its impact on health is multifold. First, it is a pre-malignant state, with a low, but significant risk of progressing to certain blood cancers.7,8 Second, it predisposes individuals to non-neoplastic conditions, such as cardiovascular events, by enhancing macrophage activation and inflammation (Figure 1).10 For these reasons there is a 30-40 % increased risk of all-cause mortality in CHIP patients.5-8 Three large scale epidemiologic studies of CHIP have been conducted to date, all of which were published in 2014. These studies collectively involved over 30,000 human patients, and all of them used whole exome sequencing of peripheral blood to identify mutation-driven 1 CH.6-8 Interestingly, these studies resulted in the identification of a restricted set of genes. In particular, the most frequently mutated genes were the epigenetic modifiers DNMT3A (encoding DNA (cytosine-5-)-methyltransferase 3⍺), TET2 (encoding tet methylcytosine dioxygenase 2), and ASXL1 (encoding additional sex combs-like transcriptional regulator 1). Mutations in splicing factors, such as SF3B1 (encoding splicing factor 3d subunit 1), were also frequent. Of importance, somatic clones increased in frequency with age; by the age of 70 or older, 10 to 20 % of persons harbored mutant clones, in contrast to <1 % of persons younger than age 40.6-8 The commonly seen mutations in CHIP are also recurrent drivers of myelodysplastic syndromes (MDS), myeloproliferative neoplasms (MPN), acute myeloid leukemias (AML), and lymphomas.11,12 Thus, individuals with CHIP have the “first hit” needed for malignant transformation. Indeed, subjects with clonal hematopoiesis had ~10-fold increase of developing a hematologic malignancy which appeared to be associated with larger mutant clones.6,7 Figure 1. Model of CHIP progression to hematopoietic malignancy. Mutations in certain genes confer a competitive advantage leading to clonal expansion (yellow circle). If further cooperator mutations (blue circle with yellow rim) occur (e.g., RUNX1, FLT3), hematopoietic cancer results. Several studies have reported a 30-40 % increase in all-cause mortality, associated with CHIP.5-7 The risk was related to cardiovascular mortality, and further analysis confirmed the future risk of ischemic stroke and coronary heart disease was more than doubled in persons 2 with CHIP.10 The causal association of CHIP with cardiovascular disease has been confirmed using mouse models with loss of Tet2 in bone marrow stem cells. Hyperlipidemic mice with Tet2 loss had an increased size of atherosclerotic plaques that could not be explained by blood cell parameters such as low-density lipoprotein (LDL) and cholesterol, alone. The mutant bone marrow-derived macrophages up-regulated many proinflammatory molecules such as the NLRP3 inflammasome-mediated interleukin-β1.10,13 Few studies have also demonstrated equivocal links with type 2 diabetes6 and chronic obstructive pulmonary disease,5 though these conditions may represent reverse causation; it is anticipated that further studies in these areas may reveal more consolidated associations. There is also growing evidence that CHIP may underlie, at least in some part, the phenomenon referred to as “inflammaging,” a term used to describe chronic, age-related, low-grade, sterile inflammation in response to stimuli, such as non-self-pathogens, endogenous cell debris, and gut microbiota (quasi-self). This is thought to be the result of activation of the nuclear factor-𝜅β/inflammasome pathway.14-17 Studies have shown that CHIP is predominantly sporadic, and genetic factors are not thought to contribute significantly.18,19 The aging hematopoietic microenvironment has been implicated with regards to influencing clonality of stem cells,20 as has a pro-inflammatory milieu.21,22 Genotoxic exposure has also been implicated in the progression of CHIP, where clones appear to survive under selective pressure post chemotherapy and are a risk factor for therapy-associated AML and MDS.23 In addition, a subsequent smaller epidemiologic study has shown that humans with a history of solid cancers have an increased frequency of CHIP- associated mutations.24 The authors of this manuscript described two major hypotheses for the increased risk of CHIP. They hypothesized the increased risk of CHIP was either 1) secondary to DNA-damaging therapies used to treat the primary cancer, or 2) resultant from the same DNA-damaging event that led to the solid tumor. In spite of these associations, knowledge of factors (other than aging) that predispose to CHIP and its progression is largely incomplete. There is also an unmet need to develop 3 practical assays for the early detection of CHIP and explore methods of medical intervention that may abrogate progression to more serious disease. To implement these investigations, an appropriate animal model that closely replicates the physiologic consequences of CHIP, including its progression to blood cancer, is essential. Animal models provide invaluable information in the pursuit of knowledge of many disease states. Rodents, in particular, are heavily utilized due to their small size, short life span, and relatively low cost compared to other animal models. In addition, there are many genetically engineered strains of mice available to study specific diseases and their genome is relatively easy to edit. Mice with loss-of-function mutations in Tet2 and Dnmt3a have been generated by several groups. As discussed earlier, atherosclerotic mouse models undergoing autologous bone marrow transplantation from mice with a loss-of-function mutation in Tet2 show acceleration of atherosclerosis via activation of the Nlrp3-mediated inflammasome, further supporting the link between cardiovascular disease and CHIP.10 Mouse models with loss-of- function mutations in Tet2 or Dnmt3a have bone marrow precursor myeloid cells that have a survival advantage and enhanced self-renewal properties.25-27 In addition, those with Dnmt3a loss-of-function mutations have a propensity for both lymphoid and myeloid malignancies.28,29 Recently, spontaneous clonal hematopoiesis was identified in the bone marrow of elderly mice, albeit at much lower frequencies (~5 fold less) than humans probably due to their much shorter life span and, as such, will likely not provide a model for spontaneous CHIP.30 Non-human primates (NHPs), most commonly the rhesus macaque, are the animal model genetically most similar to humans; however, they are less frequently used due to their high cost, size, and unpredictable behavior in captivity. As far as the author is aware, there have been no studies reporting spontaneous CHIP in NHPs; however, the idea is conceivable. Macaques with loss-of- function mutations in TET2 have been generated using CRISPR/Cas9 lentiviral-induced mutations.31 Long-term studies documenting this group’s findings are not yet published. 4 As there is an inability to model useful spontaneous clonal hematopoiesis in mice and thus far, NPHs, companion dogs (Canis familiaris) offer a unique translational model. Unlike laboratory animals, companion dogs share an environment and lifestyle similar to humans. They are exposed to the same pollutants, and similar pathogens and infections which may play important parts in age-related disease. There are over 450 reported diseases in domestic dogs, and 360 of those have an analogous human counterpart.32,33 As a species, the dog has wide variation among breeds with regards to size, morphology, behavior and lifespan. There are ranges between breeds of more than two-fold in longevity, and lifespan is also strongly related to breed.34-36 Due to dog breeding practices towards a specific and recognized breed, the genetic variation between dog breeds is high, but within breeds is restrictive.37 This level of inbreeding makes genetic mapping of complex traits easier and may provide insights with regards to aging and associated diseases in humans. Spontaneously occurring cancers in canines are similar to those in humans. An additional advantage of the canine model is the high frequency with which this species is affected by blood cancers. Hematopoietic neoplasms in dogs have morphologic similarities to humans and are classified according to human World Health Organization (WHO) criteria.38,39 Dogs also share similar molecular features of MDS and AML with studies showing recurrent somatic mutations in JAK2, NRAS, KRAS, C-KIT, DNMT3L and FLT3 in dogs.40-42 In addition, dogs have an intact immune system and natural co-evolution of tumor and microenvironment. The domestic dog offers an excellent translational model for human cancers, whilst supporting discovery and development of novel therapeutics for both human and veterinary cancer patients.43 Despite recent advances in canine-specific genomics, transcriptomic, and proteomic investigations, much is still unknown regarding the structural and functional relationships between dog and human oncogenes and tumor suppressor genes.44-46 The recognition of the companion dog in comparative oncology is rapidly increasing with an increased growth of the 5 scientific literature and various collaborative efforts to enhance the clinical translation by supporting access and enrollment of pets with cancer into clinical trials. An excellent recent review of current comparative oncology clinical trials was recently published by LeBlanc and Mazcko and highlights the importance of novel model development.43 Thus far, CHIP has not been reported in the dog, which led to the major goal of this study: to demonstrate that somatic mutations in specific genes associated with human CHIP would be detectable in the blood of aged dogs not known to have hematologic disorders. An additional goal was to design and generate a dog cell line with a described CHIP mutation for use in future functional studies. 6 Methods Case Selection Paired germline and whole blood samples from 93 canine patients were obtained from The Ohio State University Veterinary Biospecimen Repository (IACUC protocol # 2010A0015- R3) (Appendix A). To enhance our ability to detect CHIP, patients were selected based on geriatric age (i.e., greater than 8 years) and/or to have a previous history of solid cancer but no concurrent evidence of circulating hematopoietic neoplasia, as assessed by the clinicians at The Ohio State University with a physical exam and when indicated, a complete blood count (CBC). A CBC was available at the time of DNA extraction for 73 dogs (Appendix B). Follow up clinical information was available for 29 dogs and was analyzed for concurrent inflammatory diseases and cause of death. DNA Extraction and Sequencing DNA was extracted from fresh, frozen germline and whole blood samples using a DNeasy Blood & Tissue Kit (Qiagen, 69504, Frederick, Maryland) according to manufacturer instructions. DNA was quantified using a spectrophotometric method (Nanodrop 2000, Thermo Scientific, Waltham, Massachusetts). Targeted sequencing of twelve prechosen genes (Table 1), based on the most common mutations in human CHIP and canine leukemia, was performed using next generation sequencing with the Ion Torrent platform and reagents from Life Technologies (Carlsbad, California). The canine whole genome DNA sequence CanFam 3.1 was downloaded from useast.ensembl.org, and the protein coding regions of 12 candidate genes were extracted using the Ensembl canine genome browser annotation. Primers for candidate genes were custom designed with the Ion Ampliseq Designer (ampliseq.com) and validated in silico with the Ion Torrent White Glove team. The library was prepared with Ion AmpliSeq Library kit 2.0 (4475345) with a custom designed panel of AmpliSeq primers (panel 7 design IAD165539). The target coverage of 166 regions was 96 %, and targets were covered in 404 amplicons, in 2 pools and of a 61.19 kb panel size (Appendix C); regions that lacked coverage were not in known hotspots. To run multiple samples on the same chip, we used IonExpress (Thermo Scientific, Waltham, Massachusetts) barcode adapters (kit #4471250 and #4474009). DNA was amplified on a GeneAmp PCR system 9700 Dual 96-well thermal cycler from Applied Biosystems (Thermo Scientific, Waltham, Massachusetts), using the following protocol: Initial hold 99 °C for 2 minutes, followed by 21 cycles at 99 °C for 15 seconds, 60 °C for 4 minutes, and a final hold 10 °C infinity. The PCR product was purified with Agencourt AMPure XP kit (A63881 Beckman Coulter, Indianapolis, Indiana). The library was quantified using real time PCR with Ion Library TAQMAN Quantitation kit 44688022 on an Applied Biosystems ViiA7 Real Time PCR System (Thermo Scientific, Waltham, Massachusetts) instrument to allow for optimal final dilution of the library for template preparation on OneTouch OT2 instrument (Thermo Scientific, Waltham, Massachusetts) with Ion 540 Kit OT2 (A27753). The ion sphere particle enrichment and purification were performed on Ion OneTouch2 ES. Purified ion sphere particles were sequenced on Ion Torrent Personal Genome Machine using an S5 instrument with 540 Kit OT2 (A27753) and 540 Chip Kit (A27766). Data were collected and analyzed using Torrent Server (4462616) with Torrent 5.6.0. Final analysis of the sequence data was performed using a combination of software Torrent Variant Caller v.5.6.8-1 (ThermoFisher, Waltham, Massachusetts) and Integrated Genomics Viewer 5.01 (Broad Institute, Cambridge, Massachusetts). Because canine polymorphisms are poorly characterized, we used pairwise comparison between germline derived DNA and blood derived DNA for every animal tested in our study. Positive CHIP calls were made only for variants that were detected in blood derived DNA and were absent from, or present at a much higher frequency than, matching germline DNA. The Canfam 3.1 reference sequence was used for analysis. The entire length of sequences was reviewed manually using these programs to assess for deviation from reference sequence and to evaluate the quality of sequence and the depth of coverage. 8 Variants and impact were annotated using snpEff v4.3t based on Ensembl CanFam 3.1.86 annotation. Results from all samples were integrated using in-house shell and R scripts. Ion Torrent run summaries were evaluated for loading density and quality of sequence, and in all cases, the majority of the reads were usable. Low quality sequence, when present, was discarded prior to analysis. Greater than 90 % of reads were mapped to on target regions for all dogs, and the average depth of coverage ranged from approximately 1,000 to 21,000. All synonymous variants and variants in non-protein coding regions were discarded. Visual Inspection of Variants and Impact Assessment Remaining variants were visually inspected in the Integrated Genomics Viewer 5.01 (Broad Institute, Cambridge, Massachusetts). Variants were discarded if the variant allele frequency was <2 %, the coverage at the variant location was less than 10 reads, the QV (Phred) score was less than 25, the variant was an insertion or deletion of a specific nucleotide in a string of at least 6 bases of that specific nucleotide (homopolymer region), the variant occurred in all samples, there were many visible variants surrounding the variant in question, or the variant was within 20 base pairs of the end of a read. The impact of the variants was predicted using Prediction of Functional Effects of Human nsSNPs software (PolyPhen-2, Harvard, Cambridge, Massachusetts). Sequencing files are publicly available in the National Center for Biotechnology Information Sequence Read Archive under the BioProject ID number PRJNA789308. 9 Table 1. Twelve canine genes selected for sequencing and investigating for the presence of CHIP. Check marks indicate reasons for gene selection and double check marks denote the most frequently mutated genes in human CHIP. Common in Human Documented in Canine Candidate Gene CHIP Cancer ASXL1 ✓✓ DNMT3A ✓✓ IDH1 ✓ IDH2 ✓ JAK2 ✓✓ ✓ KIT ✓ ✓ PPM1D ✓ ✓ RUNX1 ✓✓ SRSF2 ✓ SF3B1 ✓ TET2 ✓✓ ✓ TP53 ✓ ✓ 10 Results Of the 93 dogs included, 43 were male castrated, 4 were intact male, 42 were spayed female, and 4 were intact female; they ranged in age from 5 to 16 years (median = 12 years). Twenty-seven breeds, comprising 33 mixed breed dogs and 60 pure breeds were affected by 22 types of solid cancers. Four out of 93 dogs (4.3 %) carried variants in CHIP-associated genes in the blood (Table 2). Two of the dogs carried two variants. All dogs were female and ranged in age from 12-15 years. Previous solid cancer diagnoses were oral squamous cell carcinoma, thyroid carcinoma, soft tissue sarcoma, and osteosarcoma. The latter three diagnoses were made on the same day as DNA collection. The dog diagnosed with oral squamous cell carcinoma had DNA collected 480 days post cancer diagnosis. This dog received cyclophosphamide chemotherapy and radiotherapy prior to collection of the sample in which CHIP variants were detected. One dog received carboplatin chemotherapy only, and this occurred after blood collection for sequencing. The mutations identified were annotated as either moderate or high impact, and allele frequencies ranged from 8 % - 67 %. Five single non-synonymous nucleotide variants were identified, three of which were predicted to have deleterious effects. A truncating mutation affecting PPM1D was also identified. Schematical representation of genes with predicted deleterious effects is shown in Figure 2. A single dog carried mutations in both ASXL1 and KIT. The N949G substitution in ASXL1 occurred in exon 12, the most frequently affected exon in human CHIP,6-8 while the M234V substitution in KIT occurred in exon 4, a locus which is not commonly affected in cases of human or canine cancer.6-8 Co-occurrence of variants in TET2 and SF3B1 was noted in another dog. In a pattern similar to the previous dog, the TET2 S15N substitution with predicted deleterious effects occurred in exon 3, which is consistent with loci of human variants, while the SF3B1 E402G substitution affected exon 10, which differs from cases of human CHIP where 11 exon 14 and 15 are affected.6-8 The two remaining variants in RUNX1 and PPM1D each occurred in one dog. The RUNX1 variant was predicted to alter splicing and lead to a V105E substitution in the anti-parallel strands of the β-sheet in the Runt domain; this point mutation was in close proximity to published human mutations that result in the diminished heterodimerization within the β-subunit and, therefore, reduced function of the gene.47 The PPM1D mutation resulted in a stop codon at residue K535* of exon 6, also consistent with human CHIP.48 PPM1D variants are often acquired secondary to cancer therapy;49 it is unknown if this dog had received prior chemotherapy at the time of DNA collection. Progression to blood cancer was not observed in any of the dogs for which follow-up was available (29 dogs out of 93). The median survival for dogs carrying variants in CHIP- associated genes was 128 days compared to 270 days for dogs without variants (not significant, Figure 3). 12 Table 2. Clinical histories of canine CHIP carriers and summary of the mutations identified by targeted next generation sequencing. All dogs were aged 12 years or older and had been previously diagnosed with a solid cancer. Two dogs received radiotherapy and chemotherapy or chemotherapy, alone. Six unique mutations were identified, and their functional impact was scored using PolyPhen II software (Harvard), where a score of 0 is suggestive that the mutation is tolerated and a score of 1.0 is suggestive the mutation is deleterious. Case 1 Case 2 Case 3 Case 4 Sex FS FS FI FI Age 15 12 12 12 Breed Mixed Mixed Saluki Border collie Food atopy, Reactive Other medical Pollakiuria, metastatic pulmonary SCC microfilariasis, histiocytosis, ocular None conditions pyometra, mammary lipid precipitates, masses epistaxis Cancer Oral SCC Thyroid carcinoma STS OSA diagnosis Cancer Chemotherapy, RT, surgical excision, lung Chemotherapy, limb None Surgical excision treatment lobectomy amputation Euthanized 128 Euthanized 483 days post cancer diagnosis Euthanized 1 day post cancer diagnosis days post cancer Outcome Lost to follow up due to post lung lobectomy complications due to QoL concerns diagnosis due to QoL concerns Gene mutated ASXL1 KIT SF3B1 TET2 RUNX1 PPM1D Type of Splice region variant Missense Missense Missense Missense Stop codon mutation (suspect) Exon 12 4 10 3 5 6 Nucleotide chr24:21801101:A:G chr13:47148941:A:G chr37:6937498:T:C chr32:26104689:G:A chr31:30254159:T:A chr9:35857110:A:T position VAF (%) 16 12 62 67 34 8 Codon position p.Asp949Gly p.Met234Val p.Glu402Gly p.Ser15Asn p.Val105Glu p.Lys535* PolyPhen II Deleterious (0.901) Tolerated Tolerated Deleterious (1.000) Deleterious (1.000) NA prediction FS, female spayed; FI, female intact; SCC, squamous cell carcinoma; RT, radiotherapy; dx, diagnosis; QoL, quality of life; STS, soft tissue sarcoma; OSA, osteosarcoma; NA, not applicable as the PolyPhen II software only analyzes SNPs 13 Figure 2. Schematic Canis familiaris genes with predicted deleterious CHIP-associated mutations. The diagrams represent ASXL1 (A), TET2 (B), RUNX1 (C), and PPM1D (D) genes. Grey vertical bars represent exons. Yellow exons show those most commonly affected in human CHIP. Dot and line represent the variant found in this cohort of dog 14 Figure 3. Kaplan-Meier survival curves for dogs with and without CHIP-associated variants. The median survival for dogs with CHIP was 128 days, compared to 270 days without CHIP. (Three dogs with CHIP and 29 dogs without CHIP.) Using the Mantel-Cox test, there was no significant difference between survival of the two groups (p = 0.5177). 15 Discussion Variants in CHIP-associated genes were present in this cohort of dogs with a history of solid cancers but no known evidence of hematologic disorders. Of the six variants identified, two (33%) occurred in the second and third most commonly mutated genes in human CHIP (TET2 and ASXL1), and three (50%) occurred in the top 10 most frequently mutated genes in human CHIP.6-8 The genomic loci of these variants were also similar to humans; the three single nucleotide variants predicted to have deleterious effects and the truncating mutation in PPM1D all occurred in exons and domains that are frequently affected in cases of human CHIP.6-8 In contrast to publications involving human CHIP, none of the dogs harbored mutations in DNMT3A, the most commonly mutated gene in human CHIP.5-8 But this is not surprising as mutations in DNMT3A have not been detected in canine AML. Taken together, these data suggest some similarities between canine and human CHIP, though the frequencies with which certain genes are mutated may vary between the two species. It is also likely that variants exist in additional genes not sequenced in the current study. A larger sample size and more complete sequencing are needed to determine the true frequency with which certain genes are mutated, as well as identify the most commonly mutated genes in the dog. In humans, mutations in DNMT3A and TET2 are thought to convey a competitive survival advantage and enhanced self-renewal.7,8 Whereas, mutations in PPM1D allow entry into the cell cycle despite the presence of DNA damage, conferring the stem cell advantage in the setting of cytotoxic drugs.9 The effects of other driver mutations, such as SF3B1 and ASXL1 are currently unknown. Mutations in KIT and RUNX1, thought to be cooperating mutations in CHIP, are commonly associated with MDS and AML.10,11 Mechanisms of clonal expansion in CHIP are largely unknown; cells with mutations in PPM1D (encoding Mg2+/Mn2+-dependent protein phosphatase 1D), a regulator of p53, can enter the cell cycle despite the presence of DNA damage, conferring the stem cell advantage in the setting of 16 cytotoxic drugs.48 A study has recently shown that treatment with a PPM1D inhibitor reverses a chemotherapy-resistance phenotype and selectively kills PPM1D mutant cells.49 Truncating mutations typically occur in exon 6 in humans, and the affected dog in this study also had a truncating mutation in exon 6. DNMT3A and TET2 have opposite biochemical functions where the DNMT3A enzyme is responsible for de novo methylation of the fifth position in cytosine bases of DNA,50 and TET2 is one of three enzymes responsible for demethylation via oxidation of 5-methylcytosine to 5- hydroxymethylcytosine.51,52 Loss-of-function mutations in either of these genes in mouse models lead to a competitive survival advantage with enhanced self-renewal properties, and also propensity towards leukemia, with cooperating mutations.25-28 Of note, TET2 has also been identified as a mediator of transcriptional regulation for inflammatory cytokines, such as interleukin-6 (IL-6). Normally, TET2 recruits histone deactylase 2 (HDAC2) to deacetylate IL-6, repressing its transcription, and thus IL-6 levels.53 This is an important step in the termination of an inflammatory response in macrophages and dendritic cells. A recent study showed that upregulated expression of IL-6 from hematopoietic stem and progenitor cells (HSPCs) in Tet2- knockout mice led to apoptotic resistance, suggesting that Tet2-mutated clones may propagate in an inflammatory bone marrow microenvironment.54,55 In humans, most commonly nonsense or frameshift mutations occur before, occasionally within, the catalytic domain, and missense mutations or in-frame deletions occur in the catalytic domain. All of these lead to inactivation of TET2. 56,57 In our study, a missense mutation occurs in the non-catalytic domain.6 ASXL1 is an epigenetic modifier, like DNMT3A and TET2, and is involved in multiple histone modifications which suggests its function is of a scaffolding protein. Most mutations that have been detected in CHIP are frameshift or nonsense mutations of the exon 12.6-8 Deletion of ASXL1 or mutant ASXL1 in mice alters histone modifications and ultimately results in myeloid transformation.58 The mice also show decreased functioning of HSPCs which is unexpected to result in a clonal advantage.59 Somatic mutations in ASXL1 are frequently detected in various 17 types of myeloid malignancies such as MDS,60,61 chronic myelomonocytic leukemia (CMML),62 MPN,63 and AML.61,64,65 The variant detected in this study occurs in the Asx homology domain which studies in Drosophila show is indispensable for histone modifications by Trithorax group (TrxG) and Polycomb group (PcG) proteins.66 RUNX1 is a sequence-specific DNA binding protein that requires its non-DNA binding partner, core binding factor beta (CBFβ). A translocation of RUNX1, t(8;21)(q22;q22) results in acute myeloid leukemia-1. Other translocations, important in AML, involve those of the genes that encode CBFβ (inv(16)(p13;q22) and t(16;16)(p13;q22)) and are referred to as CBF-AML.67 Point mutations in RUNX1 have been found in de novo and therapy-related AML, MDS, CMML and acute lymphocytic leukemia (ALL).68,69 Germline mutations are associated with the autosomal dominant “pre-leukemia” syndrome familial platelet disorder with predisposition to AML (FDP/AML). Loss of RUNX1 in mouse HPSCs confers increased self-renewal activity.70 Many missense mutations have been identified in the Runt domain (exons 3-5) that result in these neoplasms, many of which involves residues at the DNA binding interface.71 The variant in one of the study dogs also occurred in the Runt domain in one of the ten anti-parallel strands of the β-sheet, in particular, βD. SF3B1, a component of the spliceosome that is involved in 3’-splice site recognition during pre-messenger RNA processing, is the most commonly mutated gene found in MDS, especially in patients with refractory anemia with ringed sideroblasts (RARS).60,72,73 In a recent study, SF3B1 knockdown in human myeloid cell lines resulted in inhibition of cell growth, cell cycle arrest, and impairment of erythroid differentiation.74 Another study, in knockdown mice showed decreased numbers of HPSC.75,76 Mutations in SF3B1 must confer a survival advantage, but how this occurs is still unknown. In human CHIP, point missense mutations most commonly occur in exons 14 and 15.6-8 KIT is occasionally mutated in human CHIP6-8 and often in core binding factor AML (CBF-AML).77,78 It is a receptor tyrosine kinase (RTK) that has an important role in 18 hematopoiesis and over expression is common in myeloid leukemias. Mutations in C-KIT using human cells in vitro has been shown to increase cellular proliferation.79 C-KIT mutations have also been identified in some dogs with acute myeloid leukemia (affecting exon 12 at codons 815 and 817).42 Mutations in C-KIT are well documented in canine mast cell tumors80,81 and gastrointestinal stromal tumors.82 Mutations in human CHIP have been reported in exon 136 and the most commonly mutated sites in human AML affect exon 17 at codons 816 and 822,78,83 and exon 7 at codons 715 and 815.83,84 The association of CHIP with inflammatory diseases such as atherosclerosis was not seen in this pilot study for which follow up data was available. Atherosclerosis is an uncommon spontaneous disease in species other than humans and non-human primates.85 However, other chronic inflammatory diseases in dogs are similar to humans, such as some endocrinopathies, glomerulonephropathies, and osteoarthritis. Findings of inflammatory diseases in 3 of the 4 dogs with CHIP-associated variants were pollakiuria, food atopy, pyometra, and reactive histiocytosis. These conditions may conceivably have been associated with chronic stimulation of the inflammatory response. All dogs were selected for advanced age and a history of solid cancer which was strongly selective for CHIP. This study was purposefully designed to identify CHIP in the canine population, therefore individuals considered as high-risk for CHIP were chosen to increase the probability that CHIP would be detected in dogs. Future directions are to establish a cohort of healthy and non-healthy dogs to document CHIP-associated mutations over time, as well as further establish concurrent clinical diagnoses associated with inflammatory disease and development or progression of CHIP. Many of our cases had incomplete clinicopathologic data or medical records due to sampling from a referral population where primary care veterinarians assume animal care once tertiary referral clinicians discharge the patients. Ideally, following patients from a primary care setting would be beneficial in recording and management of complete and thorough medical data. 19 The pathogenicity of the variants found was assessed using a software developed by Harvard University, PolyPhen-II. This software predicts deleterious or tolerated mutations in genes with complex algorithms to compare wild-type and mutant sequences using the sequence, phylogenetic, and structural information available. To prove the predicted deleterious variants are pathogenic, future plans are to assess pathogenicity with in vitro techniques. In conclusion, our results support the presence of variants in CHIP-associated genes in geriatric canids. A major deficiency of this study is the inability to associate CHIP carrier status with clinical outcome, which was largely due to small sample size and the pre-existing diagnosis of solid cancer in all dogs. To justify use of the dog as a model of human CHIP, it will be necessary to document the association of this genetic lesion with clinical disease, such as blood cancer and inflammatory conditions, and future studies will accomplish this. Regardless, this represents the first domestic species in which the genetic lesion of CHIP has been documented, and results of this study may have significant relevance to multiple fields of medicine where this precursor aberration leads to pathogenic diseases. With further clinical investigations, it is possible that the companion dog may become an additional model for CHIP. 20 Chapter 2: Generation of RUNX1 point mutation Introduction As previously discussed, the variant in RUNX1 in this cohort was a non-synonymous suspected splice region variant and predicted to have deleterious effects. Errors during the splicing process can lead to improper removal of introns and cause alterations of the open reading frame. As such, this variant was chosen to be replicated in a dog cell line for future mechanistic studies. It was hypothesized that the mutant cell line would have an increased growth rate compared to wild-type controls. Cloning attempts were made to generate CRISPR cell lines with the TET2 variant mutation observed in the pilot study; however, they were unsuccessful. RUNX1 is an important transcription factor and is required for precise hematopoiesis; the high incidence of RUNX1 mutations in multiple types of hematologic malignancies, previously discussed, provides strong support for its role in orderly hematopoiesis. RUNX1 mutations alone are not associated with CHIP, but are often identified with driver mutations.6-8 In addition, RUNX1 mutations are observed in ~8 % of individuals with clonal cytopenia of undetermined significance (CCUS) and are associated with increased evolution to myeloid malignancy.86-88 Importantly, malignancies with RUNX1 mutations are more likely to have decreased survival.69 A recent publication specifies curation rules for RUNX1 variant annotation which include DNA binding, heterodimerization with CBFβ, transactivation, and cellular localization.89 Missense mutation in the runt homology domain is associated with decreased or complete loss of DNA-binding ability; however, it maintains the ability to bind to CBFβ. It is suspected that RUNX1 mutated clones have a competitive advantage through two major functions. The first is intracellular mutant clone induction of inflammatory signaling pathways and hypoxia-inducible factor-1A (HIF1A) signaling pathways, and the suppression of TP53-related cellular responses 21 and ribosome biogenesis. The second is the function of mature mutant clones that produce inflammatory cytokines and, therefore, contribute to the inflammatory microenvironment.90-94 Exactly how the inflammatory microenvironment promotes hematopoietic malignancies is largely unknown. In addition, the specific inflammatory pathways and where exactly in the multistep process of hematopoiesis the mutation is gained remain to be elucidated. The exact temporal relationship of RUNX1 mutations with other driver mutations is also incompletely understood and may or may not be related to this inflammatory microenvironment. Looking at the specific inflammatory pathways RUNX1 mutant cells use to gain a selection advantage and thrive in the microenvironment could lead to the development of therapeutics to abrogate this inflammatory response before full blown malignancy is achieved. Identifying additional factors that predispose to development of hematopoietic malignancy in RUNX1 mutant cells could potentially identify those patients at a higher risk for developing cancer, and therapeutics could be used proactively, rather than reactively. RNA-guided Cas9 nucleases from the microbial clustered regularly interspaced short palindromic repeats (CRISPR) adaptive immune system are used as an efficient tool for genomic engineering in eukaryotic cells by specifying a 20-nucleotide targeting sequence within its guide RNA. Here, we describe a system for introducing a point mutation in a canine primitive B-cell lymphoma cell line (17-71) and hypothesize that the mutant cell line will have a growth advantage compared to the non-mutated cell line. 22 Methods sgRNA and primer design The exon 5 genome of the dog (CanFam 3.1) RUNX1 was downloaded in FASTA format from Ensembl (ensembl.org) and the region surrounding the base pair mutation was selected for design of a single guide RNA (sgRNA). The construct was designed for the PX458 VQR- SpCas9 plasmid (Figure 4) as published by the Zhang lab95 as follows, where N is a nucleotide: 5’- CACCGNNNNNNNNNNNNNNNNNNNN -3’ 3- CNNNNNNNNNNNNNNNNNNNNCAAA - 5’ The sgRNA was designed using the CRISPOR design tool (crispor.tefor.net) and a suitable sgRNA was chosen. The tool gives a score; the higher the score, the more faithful the sgRNA will be. The score incorporates off-target loci and therefore, a sgRNA can be chosen that does not have any, or minimal, off-target sites. For homologous direct repair (HDR), which is favored for point mutations, the sgRNA is designed to target the Cas9 to cut as close to the point at which the single base change is to be introduced; here the protospacer adjacent motif (PAM) site was designed to cut 3 bp proximal to the cut site, which for the SpCas9 is 5’-NGG. The designed sgRNA were as follows: 5’- CACCGTGTCCCTTGGTTGGCTTAGG -3’ 3- CACAGGGAACCAACCGAATCCCAAA - 5’ To encourage HDR a single-stranded oligo DNA nucleotide (ssODN) was designed. A ssODN is a repair template that contains the desired base change flanked by 60 nucleotide homology arms, and a silent PAM mutation. The silent PAM mutation is shown here in bold orange (AGG to AAG) which prevents further Cas9 cleavage after the mutant is generated and avoids introduction of an unwanted missense mutation. The ssODN design was as follows: 23 5’- CAATGGCATAAACGTTTACAGCATTTCTGATGTCTGCATCTGTCCCTTGGTTGGCTTAGGA AGTGGCTCTGGGGGATGTCCCCGACGGCACTCTGGTCACTGTAATGGCGGGCAATGATG AA - 3’ Primers were designed flanking the sgRNA genomic target site using the Primer-BLAST tool by the NIH U.S. National Library of Medicine as follows: The sequence of the forward primer was 5’- AAGCAATTAATACACCAATGGCA -3’ and reverse primer 5’- CTGCGGTGGATTTCTAA -3’. Cloning of sgRNA into the PX458 VQR-SpCas9 plasmid Each oligo was resuspended to a concentration of 100 m with DNA-free water. 1 g of the plasmid (PX458-VQR) (Addgene, Watertown, Massachusetts) was digested with 1 L BbsI (New England Biolabs, Ipswich, Massachusetts), 2 L 10X NEbuffer (New England Biolabs, Ipswich, Massachusetts), and 13 L of distilled water (ddH2O). The digested plasmid was purified with a QIAquick DNA purifying kit (Qiagen, Hilden, Germany), as per the manufacturer’s instructions. The oligos were phosphorylated as follows: 1 L forward oligo, 1 L reverse oligo, 2L 10X T4 ligation buffer (New England Biolabs, Ipswich, Massachusetts), 2L ATP (New England Biolabs, Ipswich, Massachusetts), 1 L ligase (PNK) (New England Biolabs, Ipswich, Massachusetts), 13 L ddH2O, and annealed at 37 C for 30 minutes, followed by 95 C for 5 minutes, ramped down to 25 C at 5 C/minute. The plasmid and phosphorylated and annealed oligo duplex were ligated at room temperature for 10 minutes as follows: 0.5 ng digested plasmid, 37.5 ng oligo duplex (1:200 dilution), T4 DNA ligase reactive buffer (10X) (New England Biolabs, Ipswich, Massachusetts), and ddH2O to a total volume of 20 L. 24 Figure 4. Plasmid PX458 VQR-SpCas9. The plasmid was used to introduce a DNA double strand break at a PAM site close to the single nucleotide mutation. The PAM site for this plasmid is 5’-NGG. The plasmid was a gift from Feng Zhang (Addgene plasmid # 48138; http://n2t.net/addgene:48138; RRID:Addgene_48138) Transformation of competent cells Competent cells (Escherichia coli DH5) were thawed on ice. Twenty L of the ligation reaction were added to 50 L of competent cells, mixed by flicking, and incubated on ice for 30 minutes. The cells were heat shocked for 45 seconds in a water bath at 42 C and the tube was immediately returned to ice for 2 minutes. 1000 L of LB was added and incubated at 37 C for one hour with shaking. 90 L and 10 L were plated on LB agar-ampicillin plates and incubated 25 overnight at 37 C. The following day, 2 or 3 colonies were picked and inoculated into separate 5 mL cultures with LB-ampicillin liquid medium. The cultures were incubated at 37 C overnight with shaking. The plasmid DNA was isolated from the cultures using QIAprep spin minkit (Qiagen, Hilden, Germany), according to the manufacturer’s instructions. The sequence of each plasmid was verified by Sanger sequencing using the U6 sequencing primer (5’- ATACGATACAAGCTGTTAGAGA -3’). Transfection of 17-71 dog cell line 17-71 cells were grown in complete medium (10 % FBS, 1 % of 10,000 IU penicillin-10, 000 g streptomycin- 29.2 mg/mL glutamine (Thermo Fischer Scientific, Waltham, Massachusetts), RPMI media (Thermo Fischer Scientific, Waltham, Massachusetts)) and kept in an incubator at 37 C. The day before transfection, approximately 1 x 105 cells/well were plated in a 6 well plate with 2 mL/well of complete medium to achieve a desired confluence of 50-80 %. For electroporation, the cells were washed twice with Opti-MEM medium (Thermo Fischer Scientific, Waltham, Massachusetts), and resuspended at approximately 1 x 108 cells/L. 20 g of the vector plasmid and 1 L of the ssODN (10 M) and 2 x 107 cells were added to a cuvette designed for use with the Gemini BTX electroporator (BTX Harvard Apparatus, Holliston, Massachusetts) and the preset human protocol for T-cells was used (360 V for 1 ms and 1 pulse). The cells were incubated for 48 hours and prepared for flow cytometry cell sorting. Control cells were treated the same way, minus the vector. 26 Single cell sorting For single cell sorting of the GFP-positive cells, 96-well plates were prepared with 150 L/well of conditioned medium (50 % fresh medium and 50 % medium from a 75 cm2 flask with cells at approximately 70 % confluence, followed by filtration with a 0.2 m filter). The cells were pelleted at 1000 rpm for 5 minutes. The supernatant was discarded, the cells were washed with flow media buffer (1mM EDTA, 25 mM HEPES pH 7.0, 5 % heat-inactivated FBS and phosphate buffered saline were filtered through a 0.2 m filter, sterilized, and stored at 4 C), and centrifuged at 1000 rpm for 5 minutes. The supernatant was removed, the pellet was resuspended in 4 mL of flow media buffer, and the cells were passed through a 70 m strainer. The tubes were kept on ice and proceeded to fluorescence-activated cell sorting (FACS) (Figure 5). The GFP-positive live cells were immediately sorted into single cells and plated into a well in the 96-well plate. The plate was spun at 1000 rpm for 2 minutes and returned to the incubator for 2 weeks at 37 C. The colonies were checked every 48 hours for 2 weeks to identify cell colonies. Once confluent, the cell colony was transferred to a well in a 12-well plate with 1 mL of complete media. Once the 12-well plate was confluent, the cell colonies were transferred to a 25 cm2 flask. The cells were passaged into two 25 cm2 flasks and once the flasks reached approximately 70 % confluence, one flask of cells was frozen, and one flask was used to genotype the clones. 27 Figure 5. FACS scatter plots of control 17-71 cells and CRISPR 17-71 cells. The gate is set for the live DAPI-labeled single cells (A and C). Live single cells expressing GFP (i.e., the inserted plasmid) are shown in B and D. Genotyping of clones 1 L of each cell colony was added to 10 L of 10X Master PCR mix (Thermo Fischer Scientific, Waltham, Massachusetts), 4.5 L of the previously designed forward primer, and 4.5 L of the reverse primer. DNA was amplified on a GeneAmp PCR system 9700 Dual 96-well thermal cycler from Applied Biosystems (Thermo Fischer Scientific, Waltham, Massachusetts), using the following protocol: Initial hold 94 °C for 2min, followed by 40 cycles at 94 °C for 15sec, 60 °C for 15sec, 68 °C for 20sec, and a final hold 4 °C infinity. The PCR product was purified with GeneJET protocol (Thermo Fischer Scientific, Waltham, Massachusetts). 1 L of the PCR product and buffer were Sanger sequenced. The mutations were visually inspected in 4peaks (nucleobytes.com). 28 Cell growth rate Three separate frozen aliquots of V105E-RUNX-1 17-71 cells and three frozen aliquots of 17-71 cells that underwent the sample procedures outlined above but did not have a mutation, as identified by genotyping, were grown from the same concentration in 25 cm2 flasks for three days and cells were counted from each flask using an automated cell counter (Countess 3, Thermo Fischer Scientific, Waltham, Massachusetts). Briefly, the cells were mixed to ensure homogeneity, 10 L of each was added to 10 L of 0.4 % trypan blue, 10 L of this mixture was added to the sample well of the Countess cartridge, and the cartridge was loaded into the machine. The average number of cells was recorded over the three flasks for each cell line. A one-tailed t-test with the null hypothesis of the mutant cells will have no difference in growth rate compared to the control and an alternative hypothesis of the mutant cells will have a faster growth rate than control was performed in Word Excel with degrees of freedom = 4, and  = 0.1. 29 Results Sanger sequencing was repeated twice and confirmed the valine (GTG) to glutamine (GAA) codon mutation in the dog 17-71 cell line (Figure 6). Figure 6. Sanger sequencing confirmed the V105E-RUNX-1 17-71 cell line. The codon was replaced from the wide type GTG, encoding valine, to GAA, encoding glutamine. V105E-RUNX-1 17-71 cells had a statistically significant increased growth rate over 72 hours compared to control 17-71 cells (Figure 7). The calculated t value was 4.116 and the critical t value was 2.131. As the calculated t value was higher, we accepted the alternative hypothesis that the mutant cells have a faster growth rate than controls. The calculated p value was 0.007. 30 Figure 7. Bar chart showing the mutant cell line had a higher cell count after 72 hours of growth. Three aliquots from each cell line were grown separately via routine cell culture and automated cell counts were obtained after 72 hours of uninterrupted growth (one tailed t-test, p = 0.007). 31 Discussion The mutant V105E-RUNX1 17-71 cell line was successfully created, and the mutant cells had a faster growth rate than controls. This potentially indicates that this point mutation confers a competitive survival advantage and is similar to point mutations in human AML and MDS. RUNX1 point mutations in humans are found in MDS and AML with minimal differentiation (M0), AML-MDS, therapy-associated AML, and ALL.69,71 The most recent WHO classification of tumors also added a provisional category for AML associated with RUNX1 mutations highlighting its importance in myeloid malignancies.96 Point mutations have been reported throughout the whole Runt domain and also the C-terminal moiety where the transactivation domain Is located. Most of the cases are heterozygous, and as such, haploinsufficiency appears to be the basis for the pathogenesis. Interestingly, the regions most affected by mutations correspond to the loop-containing regions responsible for DNA binding; however, the regions are still capable of CBFβ, which may explain the dominant negative effects of these mutants.97,98 Assessing DNA and CBFβ binding in this cell line would further elucidate its functional effects. The point mutation was not achieved in a human cell line; ideally, this would be performed in human pluripotent stem cells to better replicate the precursor cells affected by CHIP. In addition, further functional studies as discussed by the ClinGen Myeloid Malignancy Variant Curation Expert Panel89 would be required to prove definitively that the mutation is deleterious. The molecular characterization of leukemia in dogs has been limited. Nevertheless, mutational analysis of dogs with acute leukemias has confirmed similar mutations in genes involved in human AML.40-42 To the best of our knowledge, the prevalence of RUNX1 mutations has not been assessed in canine leukemia or lymphoma. This study shows a point mutation in a 32 region similar to those described in human AML and as such, additional studies could potentially focus on identifying similar mutations in this human hot spot region via PCR in canine blood or tissue samples with hematologic malignancies. If the dog proves to frequently have this mutation in certain blood cancers, it could be a useful model to study potential therapeutic targets, such as CBFβ inhibitors,99 or be used to develop additional small molecule inhibitors of RUNX1 or CBF. In conclusion, we document for the first time a likely functional pathologic point mutation variant in RUNX1 in a dog cell line. If the variant is functional in a human cell line, the dog could prove relevant as an additional animal model for studies of CHIP and hematopoietic malignancies. 33 APPENDICES 34 Appendix A. Signalments and germline tissue for study dogs Table 3. (Appendix) Signalments and germline tissue for study dogs. Germline ID Breed Sex Age (yr) Cancer Other disease tissue Squamous Cell Pollakuria, metastatic pulmonary 1 Mixed Breed FS 15 Muscle Carcinoma squamous cell carcinoma 2 Mixed Breed FS 12 Thyroid carcinoma None Skin Food atopy, microfilariasis, 3 Saluki F 12 Soft Tissue Sarcoma Skin pyometra, mammary masses Reactive histiocytosis, ocular lipid 4 Border Collie F 12 Osteosarcoma Intestine precipitates, epistaxis Superficial pyoderma, flea bite Mast Cell Tumor (grade hypersensitivity, 5 Mixed Breed FS 12 II) seborrhea sicca, yeast otitis, Skin STS (grade I) spinal pain, chronic kidney disease Soft tissue sarcoma Degenerative osteoarthritis, 6 Mixed Breed MC 13 Skin (Grade I) chronic kidney disease Osteoarthritis, periodontal Soft tissue sarcoma disease, renal disease, 7 Mixed Breed MC 12 (Hemangiopericytoma; Skin nonerosive polyarthropathy, grade I) cranial cruciate ligament disease Hemangiosarcoma- Idiopathic epilepsy, Golden 8 FS 14 splenic, liver and hypothyroidism, pyoderma, otitis Muscle Retriever pulmonary nodules externa, hypertension Mast cell tumor, 9 Vizsla F 12 gastrointestinal stromal Osteoarthritis Skin tumor, adrenal mass Osteoarthritis, periodontal 10 Rottweiler MC 11 Mast Cell Tumor disease, chronic kidney disease, Skin hypertension 11 Mixed Breed FS 15 Melanoma NA Skin Golden Pyoderma, otitis externa, 12 MC 11 Soft Tissue Sarcoma Skin Retriever pododermatitis Asteroid hyalosis, periodontal 13 Mixed Breed MC 11 Osteosarcoma disease, mitral endocardosis, Skin osteoarthritis Labrador Hemangiosarcoma 14 M 12 Otitis externa, osteoarthritis Skin Retriever (primary bone) German Apocrine gland anal sac 15 MC 11 Bilateral hip dysplasia Skin Shepherd adenocarcinoma Osteoarthritis, chronic diarrhea, 16 St. Bernard MC 7 Osteosarcoma Muscle atopy 35 Table 3. (cont’d) 17 Greyhound MC 11 Osteosarcoma Osteoarthritis Muscle Labrador Intestinal 18 FS 12 Chronic nonregenerative anemia Skin Retriever adenocarcinoma Labrador 19 MC 12 Hemangiopericytoma Osteoarthritis Muscle Retriever English 20 FS 12 Soft Tissue Sarcoma Chronic cough Skin Setter 21 Greyhound FS 11 Osteosarcoma Protein losing nephropathy Skin Labrador Squamous Cell Otitis externa, seasonal atopy, 22 FS 11 Skin Retriever Carcinoma osteoarthritis Miniature Pulmonary carcinoma, 23 MC 12 Cystoliths Skin Schnauzer papillary Soft tissue sarcoma 24 Mixed Breed MC 12 NA Skin (Fibrosarcoma grade II) 25 Lhasa Apso FS 11 Carcinoma Seasonal atopy Skin Golden 26 FS 13 Osteosarcoma Osteoarthritis, hip dysplasia Skin Retriever Osteosarcoma Squamous Cell Osteoarthritis, chronic cough, Bouvier Des Carcinoma (10/01/13) 27 MC 15 polyneuropathy, pyoderma, Muscle Flanders MCT (6/24/10) cataracts, hypothyroidism Lymphoma (Indolent) (6/8/12 - T cell) Labrador 28 MC 10 Oral Malignant Melanoma Cranial cruciate ligament disease Muscle Retriever Soft tissue sarcoma 29 Beagle FS 10 (Peripheral Nerve Sheath Cranial cruciate ligament disease Muscle Tumor; grade II/III) 30 Mixed Breed MC 12 Hemangiosarcoma NA Skin 31 Mixed Breed FS 14 Thyroid carcinoma Hypothyroidism, hypertension Skin Pyoderma, pulmonary 32 Mixed Breed MC 13 Hemangiosarcoma Muscle hypertension Basset Compensated endocardiosis of 33 FS 11 Oral Malignant Melanoma Skin Hound mitral valve Scottish Transitional Cell 34 FS 12 Otitis externa Skin Terrier Carcinoma 36 Table 3. (cont’d) Mitral valve disease, 35 Greyhound FS 12 Osteosarcoma Skin osteoarthritis 36 Mixed Breed MC 12 Salivary adenocarcinoma Brainstem mass Skin Soft tissue sarcoma Golden 37 MC 12 (Peripheral Nerve Sheath T3-L3 spinal pain Muscle Retriever Tumor) Non-angiomatous, Glomerulonephropathy, 38 Greyhound FS 12 nonlymphomatous splenic Skin hypertension sarcoma 39 Greyhound MC 11 Osteosarcoma Fracture of distal humerus muscle Golden 40 FS 12 Hemangiosarcoma Leukopenia secondary to sepsis Skin Retriever Hypothyroidism, periodontal 41 Greyhound FS 13 Osteosarcoma Skin disease, osteoarthritis Soft tissue sarcoma 42 Mixed Breed FS 14 (hemangiopericytoma), NA Skin Osteosarcoma Transitional Cell Non regenerative anemia, 43 Mixed Breed MC 14 Skin Carcinoma keratoconjunctivitis sicca Osteoarthritis, periodontal 44 Mixed Breed MC 12 Osteosarcoma Skin disease Mitral valve degeneration, 45 Mixed Breed MC 10 Carcinoma Muscle cystitis, idiopathic epilepsy Multiple Soft Tissue Golden 46 MC 13 Sarcomas, Metastatic NA Skin Retriever Carcinoma Cocker 47 MC 14 Chondrosarcoma NA Skin Spaniel Soft tissue sarcoma 48 Mixed Breed FS 13 Osteoarthritis Skin (Hemangiopericytoma) 49 Mixed Breed MC 14 Prostatic carcinoma Cranial cruciate ligament disease Skin Golden Urinary 50 MC 13 Osteosarcoma Osteoarthritis Retriever Bladder 51 Mastiff MC 5 Osteosarcoma NA Skin 52 Whippet MC 12 Thyroid carcinoma Protein losing nephropathy Skin 53 Shar-pei FS 12 Mast Cell Tumor Pyoderma Skin 37 Table 3. (cont’d) 54 Border Collie MC 12 Pulmonary Carcinoma Cranial cruciate ligament disease Skin Cocker Anemia, thrombocytopenia, 55 MC 12 Hemangiosarcoma Skin Spaniel osteoarthritis Labrador 56 FS 12 Osteosarcoma (Mandible) Pyoderma Skin Retriever Squamous Cell Carcinoma Benign prostatic hyperplasia, 57 Mixed Breed MC 12 Soft tissue sarcoma - periodontal disease, bilateral hip Skin 2016 dysplasia (Hemangiopericytoma) 58 Rottweiler FS 7 Melanoma Cranial cruciate ligament disease Gingiva Soft tissue sarcoma (Peripheral Nerve Sheath 59 Irish Terrier FS 12 Seizures Skin Tumor)- 8/12/11 Mast Cell Tumor -9/26/11 Soft tissue sarcoma German 60 FS 8 (Peripheral Nerve Sheath Exocrine pancreatic insufficiency Muscle Shepherd Tumor) soft tissue sarcoma (Peripheral nerve sheath 61 Mixed Breed FS 12 tumor) , Nonangiomatous, NA Skin nonlymphomatous splenic sarcoma Labrador 62 MC 12 Mast Cell Tumor Pyoderma, otitis externa Muscle Retriever 63 Vizsla FS 12 Histiocytic Sarcoma NA Skin Labrador 64 FS 13 Histiocytic Sarcoma NA Skin Retriever Non-regenerative anemia, 65 Mixed Breed MC 14 Hemangiosarcoma Skin thrombocytopenia Miniature Soft Tissue Sarcoma, Hypertension, gall bladder 66 MC 13 Skin Schnauzer Hepatocellular carcinoma mucocele Golden 67 MC 10 Maxillary Fibrosarcoma Dermatitis Skin Retriever perianal gland 68 Mixed Breed MC 13 Paradoxical vestibular disease Skin adenocarcinoma 69 Beagle MC 9 Carcinoma NA Oral mucosa 70 Mixed Breed FS 12 Histiocytic Sarcoma Osteoarthritis Skin Transitional Cell 71 Mixed Breed FS 12 Renal disease Skin Carcinoma 38 Table 3. (cont’d) Labrador 72 FS 13 Soft Tissue Sarcoma NA Skin Retriever Jack Russel 73 MC 12 Mast Cell Tumor NA Muscle Terrier Pyoderma, otitis externa, 74 Mixed Breed MC 5 Soft tissue sarcoma Skin alopecia, pancreatitis 75 Mixed Breed M 16 Maxillary fibrosarcoma Periodontal disease Skin 76 Mixed Breed FS 12 Mast Cell Tumor NA Skin Golden Squamous Cell Peridontal disease, osteoarthritis, 77 FS 12 Lip Retriever Carcinoma anemia, thrombocytopenia Golden 78 MC 12 Mast Cell Tumor NA Skin Retriever Labrador 79 FS 12 Soft Tissue Sarcoma NA Tongue Retriever 80 Mixed Breed FS 12 Hepatocellular Carcinoma NA Skin 81 Boxer M 12 Soft Tissue Sarcoma NA Skin 82 Greyhound F 12 Osteosarcoma NA Liver Colon carcinoma, 83 Mixed Breed FS 11 carcinoma of perineal NA Skin skin 84 Mixed Breed FS 12 Mast Cell Tumor NA Muscle Boston Soft tissue sarcoma 85 MC 12 NA Skin Terrier (Hemangiopericytoma) 86 Mixed Breed M 14 Osteosarcoma NA Skin Adrenal mass, periodontal 87 ShihTzu MC 12 Pulmonary carcinoma disease, hyperadrenocorticism, Muscle polycystic kidneys Squamous Cell 88 ShihTzu FS 8 NA Muscle Carcinoma Insulinoma/mast cell 89 Mixed Breed FS 13 Periodontal disease Skin tumor Australian 90 MC 13 Mast Cell Tumor NA Oral mucosa Shepherd 39 Table 3. (cont’d) Protein losing nephropathy, mitral 91 Mixed Breed MC 12 Hepatocellular Carcinoma Skin valve disease Shetland 92 FS 13 Hemangiosarcoma Osteoarthritis Skin Sheepdog Cocker 93 MC 14 Chondrosarcoma NA Liver Spaniel F, female; FS, female spayed; M, male; MC, male castrated; NA, not available 40 Appendix B. Available CBC data for study dogs Table 4. (Appendix) Available CBC data for study dogs. ID Hct % Hgb RBC MCV MCHC MCH WBC Platelet count Microscopic g/dL 𝘅 106 /µL fL g/dL pg 𝘅 103 /µL 𝘅 103 /µL findings 1 49% 16.9 7.23 68 34.5 23.4 10.6 541 None noted 3 55.9 19 8.62 64.8 34 22 8.14 208 None noted 4 51.3 17.1 7.56 67.9 33.3 22.6 9.41 179 None noted Reactive lymphocytes Slight 5 39 13.4 5.4 72 34.8 NA 12.4 400 anisocytosis and poikilocytosis Occasional reactive lymphocytes Slight anisocytosis 6 44 15.8 6.5 69 35.5 NA 11.9 488 Rare polychromasia, Slight poikilocytosis Occasional reactive lymphocytes 7 39 13.8 6.1 64 35.3 NA 17 317 Slight anisocytosis, polychromasia, and poikilocytosis 8 27.3 9.6 4.26 64.1 35.2 22.5 19.75 190 None reported Reactive lymphocytes Slight 10 45 14.6 6.9 65 32.7 NA 8.1 431 anisocytosis and poikilocytosis Occasional reactive lymphocytes Slight 11 40 14.2 6 66 35.9 NA 14.8 663 anisocytosis, polychromasia, and poikilocytosis Occasional target cells 12 41.8 14.4 6 69.7 34.4 24 12.2 252 None reported Occasional reactive 13 39 13.5 6.1 64 35 NA 6.2 221 lymphocytes Slight anisocytosis and poikilocytosis Reactive lymphocytes Slight anisocytosis Rare 14 42 13.9 5.9 71 33.2 NA 5.7 177 polychromasia Moderate poikilocytosis Rare acanthocytes 15 43.5 14.9 6.68 65 34.2 22.2 8.6 393 None reported 16 44.8 14.8 6.61 67.8 33 22.4 5.31 148 None reported 41 Table 4. (cont’d) Rare reactive lymphocytes 18 32 11.6 5 65 35.6 NA 6.1 104 Slight anisocytosis and poikilocytosis Rare target cells 3+ anisocytosis, 19 39.9 11.9 6.24 64 29.7 19 2.37 277 1+ hypochromasia Slight anisocytosis 20 45 15.4 6.2 72 34.2 na 10 267 and poikilocytosis 21 52.2 17.8 7.3 71.5 34.1 24.4 3.56 179 None reported Slight anisocytosis 22 43 15.5 6.7 65 35.8 na 5.9 253 and poikilocytosis Slight anisocytosis 24 46 15.6 7.4 62 34.1 na 9.1 316 and poikilocytosis 25 46.6 16.3 7.08 65.8 35 23 10.54 256 None noted Slight anisocytosis 27 38 13 5.4 70 34.3 na 11.5 595 and poikilocytosis Rare reactive lymphocytes Slight 32 40 14.4 6.3 63 36.5 NA 15.3 122 anisocytosis, poikilocytosis and polychromasia Reactive lymphocytes Slight 34 45 16.2 6.9 66 36 NA 10.2 399 anisocytosis and poikilocytosis Rare polychromasia 35 53.4 18.9 7.42 72 35.4 25.5 6.6 249 None reported Reactive lymphocytes Slight 37 44 14.9 6 73 34.1 NA 7.7 219 anisocytosis and poikilocytosis 38 43.4 15.7 6.26 69.3 36.2 25.07 12.79 317 None reported 39 55.5 18.4 7.43 74.6 33.1 24.72 10.78 301 None reported 40 35 11.7 5.11 59 33.4 22.9 5.4 197 None reported 41 56.4 19.6 7.35 76.8 34.8 26.72 6.13 236 None reported Slight anisocytosis 42 47.2 15.5 6.71 70.3 32.8 23.1 6.1 469 and poikilocytosis 43 36 12 5.1 70 33.8 NA 4.4 225 None reported Reactive lymphocytes Slight 44 48 16.5 7.5 64 34.3 NA 11.3 396 anisocytosis, poikilocytosis and polychromasia Slight anisocytosis 45 33 11.5 4.85 68 34.8 23.7 16.23 660 and poikilocytosis Slight anisocytosis 46 31 11.2 4.5 68 36.3 NA 8.4 191 and poikilocytosis Occasional reactive lymphocytes 47 40 13.7 6.2 65 34.2 NA 9.3 529 Slight poikilocytosis and occasional target cells 42 Table 4. (cont’d) Occasional reactive lymphocytes Rare to occasional acanthocytes, schistocytes, and 48 31 11 4.9 64 35.7 NA 7.6 365 keratocytes Moderate anisocytosis, poikilocytosis, and rare polychromasia 49 43 16.7 6.9 62 38.8 24.2 24.36 405 None reported Slight anisocytosis, 51 34 12 5.5 62 35 NA 27.1 300 polychromasia, and poikilocytosis 53 41.9 14.4 6.54 64.1 34.4 22 8.75 146 None noted 55 19.76 6.8 3.02 65 34.5 22.5 43.98 41 Spherocytes Occasional reactive 56 50 17.1 7.6 65 34.6 NA 15.2 389 lymphocytes Rare polychromasia Reactive lymphocytes Slight 57 47 15.5 6.5 72 33 NA 9.2 351 anisocytosis and poikilocytosis Slight anisocytosis 58 38.8 13.4 5.83 66.6 34.6 23 7.51 437 and poikilocytosis Slight anisocytosis 59 37.3 12.6 5.14 72.6 33.8 24.5 16.46 485 and poikilocytosis Slight anisocytosis 60 42.5 14.8 6.58 64.6 34.8 22.5 7.3 171 and poikilocytosis Reactive lymphocytes Slight 61 34 11.9 5.6 61 34.8 NA 15.5 774 anisocytosis, poikilocytosis Target cells Reactive lymphocytes Slight anisocytosis, 62 45 15.6 7.5 61 34.5 NA 7.3 239 poikilocytosis and polychromasia Occasional target cells Slight anisocytosis 63 35 12.3 5 71 34.8 NA 10.3 178 Rare poikilocytosis and target cells Slight anisocytosis 64 40.7 14 6.18 65.9 34.4 22.7 6.24 278 and poikilocytosis Occasional reactive 65 29 10.3 4.6 63 36 NA 15.7 51.3 lymphocytes Slight anisocytosis and poikilocytosis 43 Table 4. (cont’d) Reactive lymphocytes Slight 66 36 11.8 4.9 75 32.6 NA 10.8 734 anisocytosis, polychromasia, poikilocytosis Slight anisocytosis 67 46.2 16 7.15 64.6 34.6 22.4 10.15 398 and poikilocytosis Slight anisocytosis 68 31 11.1 4.7 70 34.1 NA 109.2 469 and poikilocytosis 69 32.8 11.2 5.44 60.3 34.1 20.6 2.97 598 None reported Reactive lymphocytes Slight 70 35 12.9 5.8 60 37.2 NA 17.2 565 anisocytosis and occasional polychromasia 71 34.7 11.8 4.9 70.8 34 24.1 6.75 227 None reported Rare reactive lymphocytes Slight 73 34 11.8 5 68 35 NA 8.7 856 anisocytosis, poikilocytosis and polychromasia Rare reactive lymphocytes Slight anisocytosis and 74 54 18.8 7.3 74 34.9 NA 14.5 215 poikilocytosis and rare polychromasia Slight anisocytosis and poikilocytosis 76 38 13.6 5.7 66 36.1 NA 21.4 566 and target cells present 77 43 14.7 6.4 67 34 23.1 9.8 227 None reported Slight anisocytosis 78 34 11.8 4.96 68.5 34.7 23.8 7.18 330 and poikilocytosis Occasional reactive lymphocytes 79 40 13.6 5.8 69 34.1 NA 11 329 Slight anisocytosis and poikilocytosis Rare target cells Reactive lymphocytes Slight 80 41 13.5 6.4 64 33.2 NA 7.3 392 anisocytosis and poikilocytosis Slight anisocytosis 81 43 14.4 5.8 74 33.6 NA 8.4 251 and poikilocytosis Occasional reactive 82 55 19.1 7.3 75 34.3 NA 10.9 103 lymphocytes Slight anisocytosis and poikilocytosis Slight anisocytosis 83 42 14 6.4 65 33.5 NA 8.5 325 and poikilocytosis 44 Table 4. (cont’d) Occasional reactive lymphocytes Slight anisocytosis 84 50 15.9 6.3 80 31.9 NA 8.9 255 Rare polychromasia, Slight poikilocytosis Rare reactive lymphocytes Slight anisocytosis 85 49 17.6 7.3 68 35.7 NA 12.4 581 and poikilocytosis Rare polychromasia Occasional reactive 86 42 13.9 6.7 63 33.4 NA 7 666 lymphocytes Slight anisocytosis and poikilocytosis 88 42 14.4 6.2 68 34.4 NA 10.5 583 None reported Slight anisocytosis 89 39 12.3 5.3 73 31.9 NA 7.9 213 and poikilocytosis Occasional reactive 91 39 12.8 5.4 73 32.5 NA 11.2 277 lymphocytes Slight anisocytosis of RBC Slight anisocytosis, polychromasia, 92 22 6.7 3.2 68 30.7 NA 48.4 89 and poikilocytosis Mild cytoplasmic basophilia of leukocytes Hct, hematocrit; Hgb, hemoglobin; RBC, red blood cell concentration; MCV, mean corpuscular volume; MCHC, mean corpuscular hemoglobin concentration; MCH, mean corpuscular hemoglobin; WBC, white blood cell concentration; NA, not available 45 Appendix C. Coverage of target genes Table 5. (Appendix) Coverage of target genes. WG_IAD165539_region.20181130.results_coverage_summary Request_ID Type Name C Chr_ Chr_ #_Amp Total_ Covered Missed_ Overall_C hr Start End licons Bases _Bases Bases overage WG_IAD1655 GENOME_ ENSCAFE00 ch 9332 9332 1 266 153 113 0.575 39_region REGION 000295916 r1 1921 2186 WG_IAD1655 GENOME_ ENSCAFE00 ch 9332 9332 1 80 80 0 1 39_region REGION 000299563 r1 2493 2572 WG_IAD1655 GENOME_ ENSCAFE00 ch 9336 9336 3 275 275 0 1 39_region REGION 000023004 r1 8076 8350 WG_IAD1655 GENOME_ ENSCAFE00 ch 9337 9337 1 124 124 0 1 39_region REGION 000023005 r1 7034 7157 WG_IAD1655 GENOME_ ENSCAFE00 ch 9338 9338 1 118 118 0 1 39_region REGION 000023006 r1 7550 7667 WG_IAD1655 GENOME_ ENSCAFE00 ch 9339 9339 2 146 146 0 1 39_region REGION 000023007 r1 3198 3343 WG_IAD1655 GENOME_ ENSCAFE00 ch 9340 9340 3 322 322 0 1 39_region REGION 000023009 r1 0304 0625 WG_IAD1655 GENOME_ ENSCAFE00 ch 9340 9340 2 120 120 0 1 39_region REGION 000023012 r1 1365 1484 WG_IAD1655 GENOME_ ENSCAFE00 ch 9340 9340 2 158 158 0 1 39_region REGION 000023014 r1 7369 7526 WG_IAD1655 GENOME_ ENSCAFE00 ch 9340 9340 1 112 112 0 1 39_region REGION 000023016 r1 9415 9526 WG_IAD1655 GENOME_ ENSCAFE00 ch 9341 9341 2 187 187 0 1 39_region REGION 000023017 r1 1592 1778 WG_IAD1655 GENOME_ ENSCAFE00 ch 9341 9341 1 128 115 13 0.898 39_region REGION 000023021 r1 2653 2780 WG_IAD1655 GENOME_ ENSCAFE00 ch 9341 9341 2 135 135 0 1 39_region REGION 000023025 r1 5218 5352 WG_IAD1655 GENOME_ ENSCAFE00 ch 9341 9341 1 88 88 0 1 39_region REGION 000023029 r1 6434 6521 WG_IAD1655 GENOME_ ENSCAFE00 ch 9341 9341 2 128 128 0 1 39_region REGION 000023033 r1 9678 9805 WG_IAD1655 GENOME_ ENSCAFE00 ch 9342 9342 2 139 139 0 1 39_region REGION 000023036 r1 0576 0714 WG_IAD1655 GENOME_ ENSCAFE00 ch 9342 9342 1 152 152 0 1 39_region REGION 000023039 r1 2517 2668 WG_IAD1655 GENOME_ ENSCAFE00 ch 9342 9342 2 151 151 0 1 39_region REGION 000023040 r1 2808 2958 WG_IAD1655 GENOME_ ENSCAFE00 ch 9342 9342 1 137 137 0 1 39_region REGION 000023042 r1 3797 3933 WG_IAD1655 GENOME_ ENSCAFE00 ch 9342 9342 1 190 190 0 1 39_region REGION 000023045 r1 6620 6809 WG_IAD1655 GENOME_ ENSCAFE00 ch 9342 9342 1 125 125 0 1 39_region REGION 000023049 r1 7407 7531 WG_IAD1655 GENOME_ ENSCAFE00 ch 9342 9342 2 173 173 0 1 39_region REGION 000023050 r1 7704 7876 WG_IAD1655 GENOME_ ENSCAFE00 ch 9343 9343 2 118 118 0 1 39_region REGION 000023052 r1 3066 3183 WG_IAD1655 GENOME_ ENSCAFE00 ch 9343 9343 1 114 114 0 1 39_region REGION 000023061 r1 5111 5224 46 Table 5. (cont’d) WG_IAD1655 GENOME_ ENSCAFE00 chr1 93435667 93435774 1 108 108 0 1 39_region REGION 000320624 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47107802 47108604 8 803 803 0 1 39_region REGION 000318704 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47144084 47144120 1 37 37 0 1 39_region REGION 000293717 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47144447 47144716 2 270 270 0 1 39_region REGION 000022598 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47147501 47147782 3 282 282 0 1 39_region REGION 000022599 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47148867 47149003 1 137 137 0 1 39_region REGION 000022600 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47153583 47153754 2 172 172 0 1 39_region REGION 000022601 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47157660 47157849 1 190 190 0 1 39_region REGION 000022602 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47160927 47161042 1 116 116 0 1 39_region REGION 000022603 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47175058 47175172 1 115 115 0 1 39_region REGION 000022604 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47176922 47177103 1 182 182 0 1 39_region REGION 000022605 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47178312 47178418 1 107 107 0 1 39_region REGION 000022606 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47178512 47178638 2 127 127 0 1 39_region REGION 000022607 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47178924 47179028 1 105 105 0 1 39_region REGION 000022608 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47179115 47179225 1 111 111 0 1 39_region REGION 000022609 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47180416 47180566 1 151 151 0 1 39_region REGION 000022611 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47182449 47182540 1 92 92 0 1 39_region REGION 000022612 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47183018 47183145 1 128 128 0 1 39_region REGION 000022613 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47184250 47184372 1 123 123 0 1 39_region REGION 000022614 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47187863 47187974 1 112 112 0 1 39_region REGION 000022615 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47188088 47188187 1 100 100 0 1 39_region REGION 000022616 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47188541 47188646 1 106 106 0 1 39_region REGION 000022617 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47189703 47190029 4 327 327 0 1 39_region REGION 000022618 WG_IAD1655 GENOME_ ENSCAFE00 chr13 47189703 47192057 19 2355 2355 0 1 39_region REGION 000307341 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19492193 19492334 1 142 142 0 1 39_region REGION 000257596 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19493109 19493227 1 119 119 0 1 39_region REGION 000045109 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19494050 19494119 1 70 70 0 1 39_region REGION 000045104 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19496046 19496131 2 86 86 0 1 39_region REGION 000045096 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19497240 19497388 1 149 149 0 1 39_region REGION 000045089 47 Table 5. (cont’d) WG_IAD1655 GENOME_ ENSCAFE00 chr17 19497578 19497668 1 91 91 0 1 39_region REGION 000045083 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19498504 19498655 1 152 152 0 1 39_region REGION 000045077 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19500469 19500553 1 85 85 0 1 39_region REGION 000045071 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19500795 19500978 3 184 184 0 1 39_region REGION 000045065 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19501152 19501264 2 113 113 0 1 39_region REGION 000045060 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19501873 19501952 1 80 80 0 1 39_region REGION 000045058 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19502705 19502749 1 45 45 0 1 39_region REGION 000045056 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19502857 19503006 1 150 150 0 1 39_region REGION 000045055 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19503342 19503498 1 157 157 0 1 39_region REGION 000045053 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19503793 19503900 1 108 108 0 1 39_region REGION 000045051 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19504176 19504334 1 159 159 0 1 39_region REGION 000045047 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19504599 19504814 2 216 216 0 1 39_region REGION 000045043 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19527910 19528056 1 147 147 0 1 39_region REGION 000045041 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19530681 19530727 1 47 47 0 1 39_region REGION 000324742 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19534652 19534922 3 271 271 0 1 39_region REGION 000045035 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19549441 19549545 1 105 105 0 1 39_region REGION 000045031 WG_IAD1655 GENOME_ ENSCAFE00 chr17 19562840 19562902 1 63 63 0 1 39_region REGION 000045029 WG_IAD1655 GENOME_ ENSCAFE00 chr24 21731567 21731649 1 83 83 0 1 39_region REGION 000290364 WG_IAD1655 GENOME_ ENSCAFE00 chr24 21733974 21734085 1 112 112 0 1 39_region REGION 000330261 WG_IAD1655 GENOME_ ENSCAFE00 chr24 21793571 21793691 1 121 121 0 1 39_region REGION 000078429 WG_IAD1655 GENOME_ ENSCAFE00 chr24 21793768 21793865 1 98 98 0 1 39_region REGION 000078432 WG_IAD1655 GENOME_ ENSCAFE00 chr24 21794434 21794527 1 94 94 0 1 39_region REGION 000078437 WG_IAD1655 GENOME_ ENSCAFE00 chr24 21794986 21795138 1 153 153 0 1 39_region REGION 000078443 WG_IAD1655 GENOME_ ENSCAFE00 chr24 21796392 21796555 1 164 164 0 1 39_region REGION 000078451 WG_IAD1655 GENOME_ ENSCAFE00 chr24 21796651 21796747 1 97 97 0 1 39_region REGION 000078457 WG_IAD1655 GENOME_ ENSCAFE00 chr24 21798334 21798439 1 106 106 0 1 39_region REGION 000078465 WG_IAD1655 GENOME_ ENSCAFE00 chr24 21798722 21799355 5 634 634 0 1 39_region REGION 000078476 WG_IAD1655 GENOME_ ENSCAFE00 chr24 21799891 21804772 39 4882 4882 0 1 39_region REGION 000078488 WG_IAD1655 GENOME_ ENSCAFE00 chr3 53070718 53070802 1 85 85 0 1 39_region REGION 000131755 48 Table 5. (cont’d) WG_IAD1655 GENOME_ ENSCAFE00 chr3 53071120 53071212 1 93 93 0 1 39_region REGION 000131732 WG_IAD1655 GENOME_ ENSCAFE00 chr3 53071320 53071417 1 98 98 0 1 39_region REGION 000131720 WG_IAD1655 GENOME_ ENSCAFE00 chr3 53071592 53071704 1 113 113 0 1 39_region REGION 000131717 WG_IAD1655 GENOME_ ENSCAFE00 chr3 53073528 53073679 1 152 152 0 1 39_region REGION 000131715 WG_IAD1655 GENOME_ ENSCAFE00 chr3 53073874 53074010 2 137 137 0 1 39_region REGION 000131714 WG_IAD1655 GENOME_ ENSCAFE00 chr3 53074826 53074969 3 144 144 0 1 39_region REGION 000131712 WG_IAD1655 GENOME_ ENSCAFE00 chr3 53075052 53075212 3 161 161 0 1 39_region REGION 000131706 WG_IAD1655 GENOME_ ENSCAFE00 chr3 53076447 53076612 1 166 166 0 1 39_region REGION 000131702 WG_IAD1655 GENOME_ ENSCAFE00 chr3 53077475 53077566 2 92 92 0 1 39_region REGION 000131696 WG_IAD1655 GENOME_ ENSCAFE00 chr3 53082217 53082680 4 464 464 0 1 39_region REGION 000317459 WG_IAD1655 GENOME_ ENSCAFE00 chr31 30170967 30171442 4 476 476 0 1 39_region REGION 000303975 WG_IAD1655 GENOME_ ENSCAFE00 chr31 30177933 30178094 1 162 162 0 1 39_region REGION 000104076 WG_IAD1655 GENOME_ ENSCAFE00 chr31 30209968 30210159 3 192 192 0 1 39_region REGION 000104110 WG_IAD1655 GENOME_ ENSCAFE00 chr31 30233276 30233380 2 105 105 0 1 39_region REGION 000104062 WG_IAD1655 GENOME_ ENSCAFE00 chr31 30254040 30254196 1 157 157 0 1 39_region REGION 000104049 WG_IAD1655 GENOME_ ENSCAFE00 chr31 30260450 30260703 3 254 254 0 1 39_region REGION 000104034 WG_IAD1655 GENOME_ ENSCAFE00 chr31 30266612 30266705 1 94 94 0 1 39_region REGION 000251675 WG_IAD1655 GENOME_ ENSCAFE00 chr31 30419856 30419972 1 117 117 0 1 39_region REGION 000312331 WG_IAD1655 GENOME_ ENSCAFE00 chr31 30420093 30420332 2 240 240 0 1 39_region REGION 000317947 WG_IAD1655 GENOME_ ENSCAFE00 chr32 26021552 26021994 3 443 427 16 0.964 39_region REGION 000302105 WG_IAD1655 GENOME_ ENSCAFE00 chr32 26059693 26059837 2 145 145 0 1 39_region REGION 000287772 WG_IAD1655 GENOME_ ENSCAFE00 chr32 26104600 26108084 28 3485 3485 0 1 39_region REGION 000118877 WG_IAD1655 GENOME_ ENSCAFE00 chr32 26109778 26109868 1 91 91 0 1 39_region REGION 000283371 WG_IAD1655 GENOME_ ENSCAFE00 chr32 26111293 26111386 1 94 94 0 1 39_region REGION 000118909 WG_IAD1655 GENOME_ ENSCAFE00 chr32 26111985 26112193 2 209 209 0 1 39_region REGION 000245329 WG_IAD1655 GENOME_ ENSCAFE00 chr32 26126985 26127135 1 151 151 0 1 39_region REGION 000317146 WG_IAD1655 GENOME_ ENSCAFE00 chr32 26129145 26129234 1 90 90 0 1 39_region REGION 000331029 WG_IAD1655 GENOME_ ENSCAFE00 chr32 26137124 26137261 1 138 138 0 1 39_region REGION 000303624 WG_IAD1655 GENOME_ ENSCAFE00 chr32 26139602 26139956 3 355 355 0 1 39_region REGION 000323679 49 Table 5. (cont’d) WG_IAD1655 GENOME_ ENSCAFE00 chr32 26142047 26144313 18 2267 2267 0 1 39_region REGION 000293142 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6920834 6924501 29 3668 3668 0 1 39_region REGION 000319785 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6924808 6925024 2 217 217 0 1 39_region REGION 000118469 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6926751 6927023 3 273 273 0 1 39_region REGION 000118467 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6929028 6929159 2 132 132 0 1 39_region REGION 000118465 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6929503 6929623 1 121 121 0 1 39_region REGION 000118463 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6931099 6931210 3 112 112 0 1 39_region REGION 000118460 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6931304 6931486 2 183 183 0 1 39_region REGION 000118458 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6931763 6931984 2 222 222 0 1 39_region REGION 000118455 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6932914 6933039 1 126 126 0 1 39_region REGION 000118451 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6933175 6933321 1 147 147 0 1 39_region REGION 000118447 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6933428 6933573 1 146 146 0 1 39_region REGION 000118444 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6933849 6934119 3 271 271 0 1 39_region REGION 000118443 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6934247 6934333 2 87 87 0 1 39_region REGION 000118441 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6935050 6935229 2 180 180 0 1 39_region REGION 000118438 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6935781 6935882 1 102 102 0 1 39_region REGION 000118426 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6935979 6936176 2 198 198 0 1 39_region REGION 000118416 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6937464 6937585 1 122 122 0 1 39_region REGION 000118412 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6937829 6938041 1 213 195 18 0.915 39_region REGION 000118407 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6938941 6939178 3 238 238 0 1 39_region REGION 000118400 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6943306 6943476 2 171 171 0 1 39_region REGION 000118392 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6944427 6944506 1 80 80 0 1 39_region REGION 000118385 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6946341 6946455 1 115 115 0 1 39_region REGION 000118375 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6947063 6947167 1 105 105 0 1 39_region REGION 000118361 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6949248 6949414 2 167 167 0 1 39_region REGION 000118349 WG_IAD1655 GENOME_ ENSCAFE00 chr37 6962328 6962848 4 521 521 0 1 39_region REGION 000316981 WG_IAD1655 GENOME_ ENSCAFE00 chr37 16512895 16512985 1 91 91 0 1 39_region REGION 000253596 WG_IAD1655 GENOME_ ENSCAFE00 chr37 16514285 16514447 1 163 163 0 1 39_region REGION 000148526 WG_IAD1655 GENOME_ ENSCAFE00 chr37 16515382 16515522 1 141 141 0 1 39_region REGION 000148514 50 Table 5. (cont’d) WG_IAD1655 GENOME_ ENSCAFE00 chr37 16517599 16517750 1 152 152 0 1 39_region REGION 000148505 WG_IAD1655 GENOME_ ENSCAFE00 chr37 16519669 16519846 2 178 178 0 1 39_region REGION 000148492 WG_IAD1655 GENOME_ ENSCAFE00 chr37 16521138 16521243 2 106 106 0 1 39_region REGION 000148485 WG_IAD1655 GENOME_ ENSCAFE00 chr37 16524275 16524566 2 292 292 0 1 39_region REGION 000148469 WG_IAD1655 GENOME_ ENSCAFE00 chr37 16527154 16527291 1 138 138 0 1 39_region REGION 000148446 WG_IAD1655 GENOME_ ENSCAFE00 chr37 16530017 16530083 1 67 67 0 1 39_region REGION 000300858 WG_IAD1655 GENOME_ ENSCAFE00 chr37 16531098 16531352 3 255 255 0 1 39_region REGION 000325685 WG_IAD1655 GENOME_ ENSCAFE00 chr5 32560598 32561487 7 890 890 0 1 39_region REGION 000311903 WG_IAD1655 GENOME_ ENSCAFE00 chr5 32562109 32562215 1 107 107 0 1 39_region REGION 000181406 WG_IAD1655 GENOME_ ENSCAFE00 chr5 32562594 32562667 1 74 74 0 1 39_region REGION 000181403 WG_IAD1655 GENOME_ ENSCAFE00 chr5 32562954 32563090 1 137 137 0 1 39_region REGION 000181399 WG_IAD1655 GENOME_ ENSCAFE00 chr5 32563352 32563461 2 110 110 0 1 39_region REGION 000181397 WG_IAD1655 GENOME_ ENSCAFE00 chr5 32563684 32563796 2 113 113 0 1 39_region REGION 000181396 WG_IAD1655 GENOME_ ENSCAFE00 chr5 32563878 32564064 2 187 187 0 1 39_region REGION 000181392 WG_IAD1655 GENOME_ ENSCAFE00 chr5 32564567 32564806 2 240 240 0 1 39_region REGION 000254320 WG_IAD1655 GENOME_ ENSCAFE00 chr5 32564897 32564918 1 22 22 0 1 39_region REGION 000181390 WG_IAD1655 GENOME_ ENSCAFE00 chr5 32565071 32565172 2 102 102 0 1 39_region REGION 000181389 WG_IAD1655 GENOME_ ENSCAFE00 chr5 32573982 32574109 2 128 128 0 1 39_region REGION 000322991 WG_IAD1655 GENOME_ ENSCAFE00 chr9 4028695 4029056 3 362 362 0 1 39_region REGION 000056063 WG_IAD1655 GENOME_ ENSCAFE00 chr9 4029266 4029569 2 304 304 0 1 39_region REGION 000056064 WG_IAD1655 GENOME_ ENSCAFE00 chr9 35855967 35857452 11 1486 1480 6 0.996 39_region REGION 000193584 WG_IAD1655 GENOME_ ENSCAFE00 chr9 35862571 35862813 3 243 243 0 1 39_region REGION 000193581 WG_IAD1655 GENOME_ ENSCAFE00 chr9 35868946 35869136 1 191 191 0 1 39_region REGION 000193575 WG_IAD1655 GENOME_ ENSCAFE00 chr9 35886212 35886336 1 125 125 0 1 39_region REGION 000193567 WG_IAD1655 GENOME_ ENSCAFE00 chr9 35895600 35895828 3 229 229 0 1 39_region REGION 000193565 WG_IAD1655 GENOME_ ENSCAFE00 chr9 35913413 35913884 3 472 472 0 1 39_region REGION 000193562 51 REFERENCES 52 REFERENCES 1. Blokzijl F, De Ligt J, Jager M, et al. Tissue-specific mutation accumulation in human adult stem cells during life. Nature. 2016;538(7624):260-264. 2. Yizhak K, Aguet F, Kim J, et al. RNA sequence analysis reveals macroscopic somatic clonal expansion across normal tissues. Science. 2019;364(6444). 3. Fey MF, Liechti-Gallati S, Von Rohr A, et al. Clonality and X-inactivation patterns in hematopoietic cell populations detected by the highly informative M27 beta DNA probe. Blood. 1994;83(4):931-938. 4. Busque L, Patel JP, Figueroa ME, et al. Recurrent somatic TET2 mutations in normal elderly individuals with clonal hematopoiesis. Nature genetics. 2012;44(11):1179-1181. 5. Zink F, Stacey SN, Norddahl GL, et al. Clonal hematopoiesis, with and without candidate driver mutations, is common in the elderly. Blood. 2017;130(6):742-752. 6. Jaiswal S, Fontanillas P, Flannick J, et al. Age-related clonal hematopoiesis associated with adverse outcomes. New England Journal of Medicine. 2014;371(26):2488-2498. 7. Genovese G, Kähler AK, Handsaker RE, et al. Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence. New England Journal of Medicine. 2014;371(26):2477- 2487. 8. Xie M, Lu C, Wang J, et al. Age-related mutations associated with clonal hematopoietic expansion and malignancies. Nature medicine. 2014;20(12):1472-1478. 9. Steensma DP, Bejar R, Jaiswal S, et al. Clonal hematopoiesis of indeterminate potential and its distinction from myelodysplastic syndromes. Blood. 2015;126(1):9-16. 10. Jaiswal S, Natarajan P, Silver AJ, et al. Clonal hematopoiesis and risk of atherosclerotic cardiovascular disease. New England Journal of Medicine. 2017;377(2):111-121. 11. Couronné L, Bastard C, Bernard OA. TET2 and DNMT3A mutations in human T-cell lymphoma. New England Journal of Medicine. 2012;366(1):95-96. 12. Reddy A, Zhang J, Davis NS, et al. Genetic and functional drivers of diffuse large B cell lymphoma. Cell. 2017;171(2):481-494. 13. Fuster JJ, MacLauchlan S, Zuriaga MA, et al. Clonal hematopoiesis associated with TET2 deficiency accelerates atherosclerosis development in mice. Science. 2017;355(6327):842-847. 14. Franceschi C, Campisi J. Chronic inflammation (inflammaging) and its potential contribution to age-associated diseases. Journals of Gerontology Series A: Biomedical Sciences and Medical Sciences. 2014;69(Suppl_1):S4-S9. 53 15. Cook EK, Luo M, Rauh MJ. Clonal hematopoiesis and inflammation: Partners in leukemogenesis and comorbidity. Experimental hematology. 2020;83:85-94. 16. Franceschi C, Garagnani P, Parini P, Giuliani C, Santoro A. Inflammaging: a new immune–metabolic viewpoint for age-related diseases. Nature Reviews Endocrinology. 2018;14(10):576-590. 17. Ferrucci L, Fabbri E. Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty. Nature Reviews Cardiology. 2018;15(9):505-522. 18. Fabre MA, McKerrell T, Zwiebel M, et al. Concordance for clonal hematopoiesis is limited in elderly twins. Blood, The Journal of the American Society of Hematology. 2020;135(4):269-273. 19. Hansen JW, Pedersen DA, Larsen LA, et al. Clonal hematopoiesis in elderly twins: concordance, discordance, and mortality. Blood. 2020;135(4):261-268. 20. Vas V, Senger K, Dörr K, Niebel A, Geiger H. Aging of the microenvironment influences clonality in hematopoiesis. PloS one. 2012;7(8):e42080. 21. Zhang B, Chu S, Agarwal P, et al. Inhibition of interleukin-1 signaling enhances elimination of tyrosine kinase inhibitor–treated CML stem cells. Blood. 2016;128(23):2671-2682. 22. Abegunde SO, Buckstein R, Wells RA, Rauh MJ. An inflammatory environment containing TNFα favors Tet2-mutant clonal hematopoiesis. Experimental hematology. 2018;59:60-65. 23. Lindsley RC, Saber W, Mar BG, et al. Prognostic mutations in myelodysplastic syndrome after stem-cell transplantation. New England Journal of Medicine. 2017;376(6):536-547. 24. Ptashkin RN, Mandelker DL, Coombs CC, et al. Prevalence of clonal hematopoiesis mutations in tumor-only clinical genomic profiling of solid tumors. JAMA oncology. 2018;4(11):1589-1593. 25. Ko M, Bandukwala HS, An J, et al. Ten-Eleven-Translocation 2 (TET2) negatively regulates homeostasis and differentiation of hematopoietic stem cells in mice. Proceedings of the National Academy of Sciences. 2011;108(35):14566-14571. 26. Moran-Crusio K, Reavie L, Shih A, et al. Tet2 loss leads to increased hematopoietic stem cell self-renewal and myeloid transformation. Cancer cell. 2011;20(1):11-24. 27. Challen GA, Sun D, Jeong M, et al. Dnmt3a is essential for hematopoietic stem cell differentiation. Nature genetics. 2012;44(1):23-31. 28. Celik H, Mallaney C, Kothari A, et al. Enforced differentiation of Dnmt3a-null bone marrow leads to failure with c-Kit mutations driving leukemic transformation. Blood. 2015;125(4):619-628. 29. Mayle A, Yang L, Rodriguez B, et al. Dnmt3a loss predisposes murine hematopoietic stem cells to malignant transformation. Blood. 2015;125(4):629-638. 54 30. Chin DWL, Yoshizato T, Virding SC, et al. Aged healthy mice acquire clonal hematopoiesis mutations. Blood. 2022;139(4):629-634. 31. Shin T, Chen S, Cordes S, et al. Macaque CRISPR/Cas9 age-related clonal hematopoiesis model demonstrates expansion of TET2-mutated clones and applicability for testing mitigation approaches. Blood. 2020;136:27-28. 32. Parker HG, Ostrander EA. Canine genomics and genetics: running with the pack. PLoS Genet. 2005;1(5):e58. 33. Wayne RK, Ostrander EA. Lessons learned from the dog genome. TRENDS in Genetics. 2007;23(11):557-567. 34. Michell AR. Longevit of British breeds of dog and its relationships with-sex, size, cardiovascular variables and disease. Veterinary Record. 1999;145(22):625-629. 35. Parker HG, Kim LV, Sutter NB, et al. Genetic structure of the purebred domestic dog. Science. 2004;304(5674):1160-1164. 36. Egenvall A, Bonnett BN, Shoukri M, Olson P, Hedhammar Å, Dohoo I. Age pattern of mortality in eight breeds of insured dogs in Sweden. Preventive veterinary medicine. 2000;46(1):1-14. 37. Pollinger JP, Lohmueller KE, Han E, et al. Genome-wide SNP and haplotype analyses reveal a rich history underlying dog domestication. Nature. 2010;464(7290):898-902. 38. Valli VE, Myint MS, Barthel A, et al. Classification of canine malignant lymphomas according to the World Health Organization criteria. Veterinary pathology. 2011;48(1):198-211. 39. McManus PM. Classification of myeloid neoplasms: a comparative review. Veterinary Clinical Pathology. 2005;34(3):189-212. 40. Beurlet S, Krief P, Sansonetti A, et al. Identification of JAK2 mutations in canine primary polycythemia. Experimental hematology. 2011;39(5):542-545. 41. Bronzini I, Aresu L, Paganin M, et al. DNA methylation and targeted sequencing of methyltransferases family genes in canine acute myeloid leukaemia, modelling human myeloid leukaemia. Veterinary and Comparative Oncology. 2017;15(3):910-918. 42. Usher SG, Radford AD, Villiers EJ, Blackwood L. RAS, FLT3, and C-KIT mutations in immunophenotyped canine leukemias. Experimental hematology. 2009;37(1):65-77. 43. LeBlanc AK, Mazcko CN. Improving human cancer therapy through the evaluation of pet dogs. Nature Reviews Cancer. 2020:1-16. 44. Lindblad-Toh K, Wade CM, Mikkelsen TS, et al. Genome sequence, comparative analysis and haplotype structure of the domestic dog. Nature. 2005;438(7069):803-819. 45. Ostrander EA, Dreger DL, Evans JM. Canine cancer genomics: lessons for canine and human health. Annual Review of Animal Biosciences. 2019;7:449-472. 55 46. Ostrander EA, Wang G-D, Larson G, et al. Dog10K: an international sequencing effort to advance studies of canine domestication, phenotypes and health. National science review. 2019;6(4):810-824. 47. Nagata T, Gupta V, Sorce D, et al. Immunoglobulin motif DNA recognition and heterodimerization of the PEBP2/CBF Runt domain. Nature structural biology. 1999;6(7):615- 619. 48. Hsu JI, Dayaram T, Tovy A, et al. PPM1D mutations drive clonal hematopoiesis in response to cytotoxic chemotherapy. Cell Stem Cell. 2018;23(5):700-713. 49. Kahn JD, Miller PG, Silver AJ, et al. PPM1D-truncating mutations confer resistance to chemotherapy and sensitivity to PPM1D inhibition in hematopoietic cells. Blood. 2018;132(11):1095-1105. 50. Schübeler D. Function and information content of DNA methylation. Nature. 2015;517(7534):321-326. 51. He Y-F, Li B-Z, Li Z, et al. Tet-mediated formation of 5-carboxylcytosine and its excision by TDG in mammalian DNA. Science. 2011;333(6047):1303-1307. 52. Ito S, Shen L, Dai Q, et al. Tet proteins can convert 5-methylcytosine to 5-formylcytosine and 5-carboxylcytosine. Science. 2011;333(6047):1300-1303. 53. Zhang Q, Zhao K, Shen Q, et al. Tet2 is required to resolve inflammation by recruiting Hdac2 to specifically repress IL-6. Nature. 2015;525(7569):389-393. 54. Cai Z, Kotzin JJ, Ramdas B, et al. Inhibition of inflammatory signaling in Tet2 mutant preleukemic cells mitigates stress-induced abnormalities and clonal hematopoiesis. Cell Stem Cell. 2018;23(6):833-849. 55. Cull AH, Rauh MJ. Success in bone marrow failure? Novel therapeutic directions based on the immune environment of myelodysplastic syndromes. Journal of Leukocyte Biology. 2017;102(2):209-219. 56. Delhommeau F, Dupont S, Valle VD, et al. Mutation in TET2 in myeloid cancers. New England Journal of Medicine. 2009;360(22):2289-2301. 57. Langemeijer SMC, Kuiper RP, Berends M, et al. Acquired mutations in TET2 are common in myelodysplastic syndromes. Nature genetics. 2009;41(7):838-842. 58. Wang J, Li Z, He Y, et al. Loss of Asxl1 leads to myelodysplastic syndrome–like disease in mice. Blood, The Journal of the American Society of Hematology. 2014;123(4):541-553. 59. Abdel-Wahab O, Gao J, Adli M, et al. Deletion of Asxl1 results in myelodysplasia and severe developmental defects in vivoConditional deletion of Asxl1 results in MDS. The Journal of experimental medicine. 2013;210(12):2641-2659. 60. Haferlach T, Nagata Y, Grossmann V, et al. Landscape of genetic lesions in 944 patients with myelodysplastic syndromes. Leukemia. 2014;28(2):241-247. 56 61. Boultwood J, Perry J, Pellagatti A, et al. Frequent mutation of the polycomb-associated gene ASXL1 in the myelodysplastic syndromes and in acute myeloid leukemia. Leukemia. 2010;24(5):1062-1065. 62. Gelsi‐Boyer V, Trouplin V, Roquain J, et al. ASXL1 mutation is associated with poor prognosis and acute transformation in chronic myelomonocytic leukaemia. British journal of haematology. 2010;151(4):365-375. 63. Lundberg P, Karow A, Nienhold R, et al. Clonal evolution and clinical correlates of somatic mutations in myeloproliferative neoplasms. Blood. 2014;123(14):2220-2228. 64. Döhner H, Weisdorf DJ, Bloomfield CD. Acute myeloid leukemia. New England Journal of Medicine. 2015;373(12):1136-1152. 65. Welch JS, Ley TJ, Link DC, et al. The origin and evolution of mutations in acute myeloid leukemia. Cell. 2012;150(2):264-278. 66. Milne TA, Sinclair DAR, Brock HW. The Additional sex combs gene of Drosophila is required for activation and repression of homeotic loci, and interacts specifically with Polycomb and super sex combs. Molecular and General Genetics MGG. 1999;261(4-5):753-761. 67. Liu P, Tarle SA, Hajra A, et al. Fusion between transcription factor CBF beta/PEBP2 beta and a myosin heavy chain in acute myeloid leukemia. Science. 1993;261(5124):1041- 1044. 68. Grossmann V, Kern W, Harbich S, et al. Prognostic relevance of RUNX1 mutations in T- cell acute lymphoblastic leukemia. Haematologica. 2011;96(12):1874. 69. Gaidzik VI, Teleanu V, Papaemmanuil E, et al. RUNX1 mutations in acute myeloid leukemia are associated with distinct clinico-pathologic and genetic features. Leukemia. 2016;30(11):2160-2168. 70. Ichikawa M, Asai T, Saito T, et al. AML-1 is required for megakaryocytic maturation and lymphocytic differentiation, but not for maintenance of hematopoietic stem cells in adult hematopoiesis. Nature medicine. 2004;10(3):299-304. 71. Mangan JK, Speck NA. RUNX1 mutations in clonal myeloid disorders: from conventional cytogenetics to next generation sequencing, a story 40 years in the making. Critical Reviews™ in Oncogenesis. 2011;16(1-2). 72. Papaemmanuil E, Gerstung M, Malcovati L, et al. Clinical and biological implications of driver mutations in myelodysplastic syndromes. Blood. 2013;122(22):3616-3627. 73. Malcovati L, Papaemmanuil E, Bowen DT, et al. Clinical significance of SF3B1 mutations in myelodysplastic syndromes and myelodysplastic/myeloproliferative neoplasms. Blood, The Journal of the American Society of Hematology. 2011;118(24):6239-6246. 74. Dolatshad H, Pellagatti A, Fernandez-Mercado M, et al. Disruption of SF3B1 results in deregulated expression and splicing of key genes and pathways in myelodysplastic syndrome hematopoietic stem and progenitor cells. Leukemia. 2015;29(5):1092-1103. 57 75. Matsunawa M, Yamamoto R, Sanada M, et al. Haploinsufficiency of Sf3b1 leads to compromised stem cell function but not to myelodysplasia. Leukemia. 2014;28(9):1844-1850. 76. Wang C, Sashida G, Saraya A, et al. Depletion of Sf3b1 impairs proliferative capacity of hematopoietic stem cells but is not sufficient to induce myelodysplasia. Blood. 2014;123(21):3336-3343. 77. Goemans BF, Zwaan CM, Miller M, et al. Mutations in KIT and RAS are frequent events in pediatric core-binding factor acute myeloid leukemia. Leukemia. 2005;19(9):1536-1542. 78. Shimada A, Taki T, Tabuchi K, et al. KIT mutations, and not FLT3 internal tandem duplication, are strongly associated with a poor prognosis in pediatric acute myeloid leukemia with t (8; 21): a study of the Japanese Childhood AML Cooperative Study Group. Blood. 2006;107(5):1806-1809. 79. Kitayama H, Tsujimura T, Matsumura I, et al. Neoplastic transformation of normal hematopoietic cells by constitutively activating mutations of c-kit receptor tyrosine kinase. 1996. 80. London CA, Galli SJ, Yuuki T, Hu Z-Q, Helfand SC, Geissler EN. Spontaneous canine mast cell tumors express tandem duplications in the proto-oncogene c-kit. Experimental hematology. 1999;27(4):689-697. 81. Webster JD, Yuzbasiyan-Gurkan V, Miller RA, Kaneene JB, Kiupel M. Cellular proliferation in canine cutaneous mast cell tumors: associations with c-KIT and its role in prognostication. Veterinary Pathology. 2007;44(3):298-308. 82. Frost D, Lasota J, Miettinen M. Gastrointestinal stromal tumors and leiomyomas in the dog: a histopathologic, immunohistochemical, and molecular genetic study of 50 cases. Veterinary Pathology. 2003;40(1):42-54. 83. Beghini A, Ripamonti CB, Cairoli R, et al. KIT activating mutations: incidence in adult and pediatric acute myeloid leukemia, and identification of an internal tandem duplication. Haematologica. 2004;89(8):920-925. 84. Care RS, Valk PJM, Goodeve AC, et al. Incidence and prognosis of c‐KIT and FLT3 mutations in core binding factor (CBF) acute myeloid leukaemias. British journal of haematology. 2003;121(5):775-777. 85. Hayashi Y, Harada Y, Huang G, Harada H. Myeloid neoplasms with germ line RUNX1 mutation. International Journal of Hematology. 2017;106(2):183-188. 86. Kwok B, Hall JM, Witte JS, et al. MDS-associated somatic mutations and clonal hematopoiesis are common in idiopathic cytopenias of undetermined significance. Blood. 2015;126(21):2355-2361. 87. Jajosky AN, Sadri N, Meyerson HJ, et al. Clonal cytopenia of undetermined significance (CCUS) with dysplasia is enriched for MDS‐type molecular findings compared to CCUS without dysplasia. European Journal of Haematology. 2021;106(4):500-507. 88. Malcovati L, Gallì A, Travaglino E, et al. Clinical significance of somatic mutation in unexplained blood cytopenia. Blood. 2017;129(25):3371-3378. 58 89. Luo X, Feurstein S, Mohan S, et al. ClinGen myeloid malignancy variant curation expert panel recommendations for germline RUNX1 variants. Blood advances. 2019;3(20):2962-2979. 90. Bellissimo DC, Chen C-h, Zhu Q, et al. Runx1 negatively regulates inflammatory cytokine production by neutrophils in response to Toll-like receptor signaling. Blood advances. 2020;4(6):1145-1158. 91. Hayashi Y, Zhang Y, Yokota A, et al. Pathobiological pseudohypoxia as a putative mechanism underlying myelodysplastic syndromes. Cancer discovery. 2018;8(11):1438-1457. 92. Wu D, Ozaki T, Yoshihara Y, Kubo N, Nakagawara A. Runt-related transcription factor 1 (RUNX1) stimulates tumor suppressor p53 protein in response to DNA damage through complex formation and acetylation. Journal of Biological Chemistry. 2013;288(2):1353-1364. 93. Cai X, Gao L, Teng L, et al. Runx1 deficiency decreases ribosome biogenesis and confers stress resistance to hematopoietic stem and progenitor cells. Cell stem cell. 2015;17(2):165-177. 94. Muto T, Walker CS, Choi K, et al. Adaptive response to inflammation contributes to sustained myelopoiesis and confers a competitive advantage in myelodysplastic syndrome HSCs. Nature immunology. 2020;21(5):535-545. 95. Ran F, Hsu PD, Wright J, Agarwala V, Scott DA, Zhang F. Genome engineering using the CRISPR-Cas9 system. Nature protocols. 2013;8(11):2281-2308. 96. Arber DA, Orazi A, Hasserjian R, et al. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood. 2016;127(20):2391-2405. 97. Harada H, Harada Y, Tanaka H, Kimura A, Inaba T. Implications of somatic mutations in the AML1 gene in radiation-associated and therapy-related myelodysplastic syndrome/acute myeloid leukemia. Blood. 2003;101(2):673-680. 98. Vegesna V, Takeuchi S, Hofmann W-K, et al. C/EBP-β, C/EBP-δ, PU. 1, AML1 genes: mutational analysis in 381 samples of hematopoietic and solid malignancies. Leukemia research. 2002;26(5):451-457. 99. Illendula A, Gilmour J, Grembecka J, et al. Small molecule inhibitor of CBFβ-RUNX binding for RUNX transcription factor driven cancers. EBioMedicine. 2016;8:117-131. 59