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. 2024 Oct 8;8(19):5215-5224.
doi: 10.1182/bloodadvances.2024012929.

Impact of cancer therapy on clonal hematopoiesis mutations and subsequent clinical outcomes

Affiliations

Impact of cancer therapy on clonal hematopoiesis mutations and subsequent clinical outcomes

Kevin T Nead et al. Blood Adv. .

Abstract

Exposure to cancer therapies is associated with an increased risk of clonal hematopoiesis (CH). The objective of our study was to investigate the genesis and evolution of CH after cancer therapy. In this prospective study, we undertook error-corrected duplex DNA sequencing in blood samples collected before and at 2 time points after chemoradiation in patients with esophageal or lung cancer recruited from 2013 to 2018. We applied a customized workflow to identify the earliest changes in CH mutation count and clone size and determine their association with clinical outcomes. Our study included 29 patients (87 samples). Their median age was 67 years, and 76% (n = 22) were male; the median follow-up period was 3.9 years. The most mutated genes were DNMT3A, TET2, TP53, and ASXL1. We observed a twofold increase in the number of mutations from before to after treatment in TP53, which differed from all other genes examined (P < .001). Among mutations detected before and after treatment, we observed an increased clone size in 38% and a decreased clone size in 5% of TP53 mutations (odds ratio, 3.7; 95% confidence interval [CI], 1.75-7.84; P < .001). Changes in mutation count and clone size were not observed in other genes. Individuals with an increase in the number of TP53 mutations after chemoradiation experienced shorter overall survival (hazard ratio, 7.07; 95% CI, 1.50-33.46; P = .014). In summary, we found an increase in the number and size of TP53 CH clones after chemoradiation that were associated with adverse clinical outcomes.

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Conflict of interest statement

Conflicts-of-interest disclosure: C.T. recieves royalties from Wolters Kluwer and consulting fees and honoraria from Siemen Healthineer, Lantheus, Telix, Molli Surgical, and Boston Scientific. Z.L. serves on the advisory board of AIQ, Inc and Reheva Biosciences. S.H.L. reports grants from STCube, BeyondSpring, and Nektar Therapeutics; serves on the advisory board of AstraZeneca; reports consultant fees from XRad Therapeutics; and is a cofounder of and has stocks in Seek Diagnostics. The remaining authors declare no competing financial interests.

Figures

None
Graphical abstract
Figure 1.
Figure 1.
Total CH mutations detected before treatment and at posttreatment follow-up. Bar plot of the number of total mutations in each gene detected before chemoradiation therapy and at last follow-up, stratified by gene.
Figure 2.
Figure 2.
CH mutation types detected before treatment and at posttreatment follow-up in each gene. “Other” includes variants in 3′ and 5′ untranslated regions, upstream and downstream gene variants, and intronic variants.
Figure 3.
Figure 3.
Changes in variant count and VAF before treatment to last follow-up by gene. (A) Line plot in which each line represents an individual study participant and shows the absolute change in the number of mutations before treatment to last follow-up. (B) Line plot in which each line represents an individual mutation and the relative fold change in VAF before treatment to last follow-up. VUS, variant of uncertain significance.
Figure 4.
Figure 4.
Correlation between VAF before and after treatment. Mutations present at both before treatment and last follow-up are shown. Dashed line represents a reference R value of 1.0.
Figure 5.
Figure 5.
OS curves according to the absolute change in the number of CH mutations from before treatment to last follow-up. (A) OS probability curve comparing individuals with increased vs not increased total mutation count in all genes from before treatment to last follow-up. (B) OS probability curve comparing individuals with increased vs not increased total mutation count in TP53 from before treatment to last follow-up.

Comment in

References

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