The evolutionary dynamics and fitness landscape of clonal hematopoiesis

Watson, Caroline J.; Papula, Alana; Poon, Gladys Y. P.; Wong, Winghing; Young, Andrew L.; Druley, Todd E.; Fisher, Daniel S.; Blundell, Jamie R.

doi:10.1126/science.aay9333

Cited by 334 publications

(437 citation statements)

References 70 publications

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“…Using the structure of the HSC lineage tree, we inferred the fitness advantage of JAK2-mutated HSCs in 2 MPN patients during the pre-diagnosis period to be approximately 40-65%. Our inferred fitness advantage is larger than that found in a population-level study of CHIP, which analyzed peripheral blood variant allele fractions in large cohorts of individuals 40 . This discrepancy suggests that the development of full-blown MPN may require a faster-growing JAK2-mutant clone than that observed in clonal hematopoiesis.…”

Section: Discussioncontrasting

confidence: 68%

Reconstructing the lineage histories and differentiation trajectories of individual cancer cells inJAK2-mutant myeloproliferative neoplasms

Egeren

Escabi

Nguyen

et al. 2020

Preprint

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Some cancers originate from a single mutation event in a single cell. For example, blood cancers known as myeloproliferative neoplasms (MPN) are thought to originate through the acquisition of a driver mutation (most commonly JAK2-V617F) in a hematopoietic stem cell (HSC). However, when the mutation first occurs in individual patients and how it impacts the behavior of HSCs in their native context is not known. Here we quantified the impact of the JAK2-V617F mutation on the proliferation dynamics of HSCs and the differentiation trajectories of their progenies in individual MPN patients. We reconstructed the lineage history of individual HSCs obtained from MPN patients using the patterns of spontaneous somatic mutations accrued in their genomes over time. Strikingly, we found that the JAK2-V617F mutation occurred in a single HSC several decades before MPN diagnosis - at age 9±2 years in a 34-year-old patient, and at age 19±3 years in a 63-year-old patient. For each patient, we inferred the number of mutated HSCs over time and computed their fitness. The population of JAK2-mutated HSCs grew exponentially by 63±15% and 44±13% every year in the two patients, respectively. To contrast the differentiation trajectories of the JAK2-mutated HSCs with those of healthy HSCs, we simultaneously measured the full transcriptome and somatic mutations in single hematopoietic stem and progenitor cells (HSPCs). We found that the fraction of JAK2-mutant HSPCs varied significantly across different myeloid cell types within the same patient. The erythroid progenitor cells were often entirely JAK2-mutant, even when the peripheral blood JAK2-V617F allele burden was low. The novel biological insights uncovered by this work have implications for the prevention and treatment of MPN, as well as the accurate assessment of disease burden in patients. The technology platforms and computational frameworks developed here are broadly applicable to other types of hematological malignancies and cancers.

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Section: Discussioncontrasting

confidence: 68%

Reconstructing the lineage histories and differentiation trajectories of individual cancer cells inJAK2-mutant myeloproliferative neoplasms

Egeren

Escabi

Nguyen

et al. 2020

Preprint

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“…Some of these events were identical and occurring in both compartments. This is in line with the findings from other healthy tissues, which all confirm the presence of mutations in cancer-associated genes in the normal epithelium and blood 1,[3][4][5][6][7]24 . However, in the breast, there is preferential accumulation of mutations in ESR1 and RUNX1, mutated in approximately 60% of samples in the parous and nulliparous group, respectively (Fig.…”

Section: Mutational Burden Within Breast-cancer Associated Genessupporting

confidence: 90%

Mutational landscapes of normal breast during age and pregnancy determine cancer risk

Cereser

Tabassum

Belluz

et al. 2020

Preprint

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The accumulation of somatic mutations in the healthy breast throughout life and pregnancy is poorly understood. Similarly, the mutational landscape of both epithelial and stromal components of the mammary gland has not been investigated. Both are relevant for breast cancer (BC), as the interplay between age, pregnancy, and cancer risk has not been fully characterized. We describe whole genome sequencing analysis of epithelial and stromal compartments from the normal breast. We show that, in a similar way to other normal organs, the mutational burden of the mammary nulliparous epithelium significantly increases with age. In a nulliparous status, mutated clones are maintained at a consistently small size throughout the life of the individual; however, at parity, pre-existent clones significantly increase in size with age. Both epithelial and stromal compartments of the healthy breast contain pre-existing known cancer mutations, albeit at low rate, indicative of subsequent positive selection for mutations in tissue-specific driver genes. In line with this, both compartments also present gene enrichment in preferentially mutated cancer pathways. Our results show that mutational landscapes differ between the parous and nulliparous epithelium and suggest an explanation for both differential breast cancer risk and development of pregnancy-associated BC (PABC).

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“…As we demonstrated in Williams et al 21 , mutation frequency and driver dN/dS are expected to be positively associated showing the highest values at the largest clone sizes (Fig 2B). Accordingly, and as observed recently in clonal hematopoiesis 22 , the allele frequency spectrum (Cancer Cell fraction or CCF) of synonymous and non-synonymous mutations (Fig. 2C) showed that the observed high driver dN/dS is a consequence of proportionally fewer synonymous mutations at higher CCF thresholds compared to nonsynonymous mutations.…”

Section: Evolutionary Dynamics Of Dn/ds During Immunoediting Reveals supporting

confidence: 88%

“…The application of evolutionary theory allows us to infer cell growth dynamics, the number of driver alterations 17,18 and their selective fitness coefficients [19][20][21][22] , as well as the impact of deleterious mutations during cancer progression 23,24 . An evolutionary metric recently used to detect selection in cancer studies is the ratio of nonsynonymous to synonymous mutations, dN/dS 7,8,[25][26][27] .…”

Section: Introductionmentioning

confidence: 99%

dN/dSdynamics quantify tumour immunogenicity and predict response to immunotherapy

Zapata

Caravagna

Williams

et al. 2020

Preprint

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Immunoediting is a major force during cancer evolution that selects for clones with low immunogenicity (adaptation), or clones with mechanisms of immune evasion (escape). However, quantifying immunogenicity in the cancer genome and how the tumour-immune coevolutionary dynamics impact patient outcomes remain unexplored. Here we show that the ratio of nonsynonymous to synonymous mutations (dN/dS) in the immunopeptidome quantifies tumor immunogenicity and differentiates between adaptation and escape. We analysed 8,543 primary tumors from TCGA and validated immune dN/dS as a measure of selection associated with immune infiltration in immune-adapted tumours. In a cohort of 308 metastatic patients that received immunotherapy, pre-treatment lesions in non-responders showed increased immune selection (dN/dS<1), whereas responders did not and instead harboured a higher proportion of genetic escape mechanisms. Ultimately, these findings highlight the potential of evolutionary genomic measures to predict clinical response to immunotherapy.

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The evolutionary dynamics and fitness landscape of clonal hematopoiesis

Cited by 334 publications

References 70 publications

Reconstructing the lineage histories and differentiation trajectories of individual cancer cells inJAK2-mutant myeloproliferative neoplasms

Reconstructing the lineage histories and differentiation trajectories of individual cancer cells inJAK2-mutant myeloproliferative neoplasms

Mutational landscapes of normal breast during age and pregnancy determine cancer risk

dN/dSdynamics quantify tumour immunogenicity and predict response to immunotherapy

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