Germline DNA Repair Gene Mutations and Clonal Hematopoiesis (CH) in 24,849 Patients with BRCA-Associated Cancers
by
, , , , ,
Catherine H. Marshall
1
,
Ali T. Arafa
2,
Ellen Jaeger
3,
Stamatina Fragkogianni
3,
Anne Sonnenschein
3,
Elizabeth Mauer
3,
Lukasz P. Gondek
1,
Calvin Chao
3,
Jun Luo
4 and
Emmanuel S. Antonarakis
5,*
1
Sidney Kimmel Comprehensive Cancer Center, Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD 21287, USA
2
Department of Pharmacology, University of Minnesota, Minneapolis, MN 55455, USA
3
Tempus AI Inc., Chicago, IL 60654, USA
4
Department of Urology, James Buchanan Brady Urological Institute, Johns Hopkins School of Medicine, Baltimore, MD 21287, USA
5
Department of Medicine, University of Minnesota Masonic Cancer Center, Minneapolis, MN 55455, USA
*
Author to whom correspondence should be addressed.
Cancers 2025, 17(9), 1432; https://doi.org/10.3390/cancers17091432
Submission received: 25 February 2025
/
Revised: 4 April 2025
/
Accepted: 7 April 2025
/
Published: 25 April 2025
(This article belongs to the Collection Oncology: State-of-the-Art Research in the USA)
Simple Summary
Clonal hematopoiesis (CH) is the expansion of white blood cells with mutations in genes associated with hematologic malignancies found in patients without evidence of any hematologic malignancy. CH is associated with increasing age and exposure to certain cancer therapies. We hypothesized that having a germline cancer predisposition gene mutation might be associated with an increased risk of CH. We used the deidentified Tempus dataset to answer this question. Among patients with breast cancer, we did see an association with increased risk of CH; this was not seen among those with prostate, ovarian, and pancreatic cancer.
Abstract
Purpose: To determine if the risk of clonal hematopoiesis (CH) would be higher among those with germline alterations in homologous recombination repair genes (gHRR) in the four BRCA-associated cancers (breast, ovarian, prostate, pancreas) compared to those without inherited predisposition (the sporadic group). Methods: We retrospectively analyzed deidentified data from 24,849 patient samples from the Tempus database with a primary diagnosis of breast, ovarian, prostate, and pancreatic cancers. Germline pathogenic or likely pathogenic variants in BRCA1, BRCA2, ATM, PALB2, and CHEK2 were identified across all four cancer types. CH was determined based on the presence of pathogenic or likely pathogenic alterations in any one of 52 CH-associated genes with a variant allele fraction of at least 2% found in the normal match. Age-adjusted odds ratios were calculated for risk of CH across cancer types. Results: CH was identified in 14% of patients with BRCA-associated cancers. DNMT3A, PPM1D, and TET2 were the most common CH gene alterations. After adjusting for age at time of biopsy, having any germline alteration in the breast cancer cohort was associated with a 41% increased likelihood of CH (OR 1.41; 95% CI 1.07–1.84, p = 0.014). An increase in CH prevalence was not seen in the three other cancer types. Conclusions: When accounting for age at time of testing, pathogenic germline alterations in DNA repair genes were associated with an increased risk of CH only among patients with breast cancer, but not in those with ovarian, pancreatic, or prostate cancers.
1. Introduction
It is estimated that there were over 2 million new cancer diagnoses in the United States in 2024 and solid tumors make up the most common causes of cancer [1]. As cancer therapies improve and mortality rates decline, more consideration is needed of the potential comorbidities and risk factors patients may have that can contribute to morbidity related to cancer therapies [2]. Clonal hematopoiesis (CH) is one such risk factor that has been associated with a number of adverse outcomes including an increased risk of hematologic malignancy, cardiovascular disease, and death [3,4,5]. CH is common among patients with solid tumors [6]. Age is one of the strongest risk factors for CH, with the prevalence increasing in healthy patients with advancing age [3,7]. Smoking and certain prior cancer treatments, including alkylating chemotherapy, topoisomerase inhibitors, poly-ADP ribose polymerase (PARP) inhibitors, and radiation therapy, have also been associated with an increased risk of CH [8,9,10,11,12]. In the general population, the prevalence of CH ranges from about 10% in those age 70–79 to about 20% in those over 90 [7]. The prevalence of CH in patients with solid tumors seems to be higher with ranges between low estimates of about 14% and much higher estimates of around 65% depending on the tumor type, prior treatments, the detection sensitivity of the assay, and when in the course of disease CH is being investigated (treatment-naïve setting or after treatment for the primary malignancy) [6].
Less is known about the potential of inherited risk factors for CH. In the general population, genome-wide association studies have identified genes in the DNA repair pathway, such as ATM, as potentially contributing to an increased risk of CH [13]. Recently, germline mutations in a telomere-regulating gene, POT1, have also been linked to CH [14]. In an oncology population, there are less data. One previous study found that patients with germline ATM mutations have a higher risk of CH [15]. There are an increasing number of therapies being used that may increase the risk of CH and myeloid neoplasms among patients with cancer, and having a better understanding of pre-existing risk factors is needed [16]. Here, we used a large commercial clinical genomic database comprising DNA sequencing information from tumors and germlines to interrogate the prevalence of CH in germline-associated cancers and their sporadic counterparts. We hypothesized that the risk of CH would be higher among those with germline alterations in homologous recombination repair genes (gHRR) in the four BRCA-associated cancers (breast, ovarian, prostate, pancreas) compared to those without inherited predisposition (the sporadic group).
2. Materials and Methods
2.1. Patients
We retrospectively analyzed deidentified data from 24,862 patient samples from the Tempus database with a primary diagnosis of breast, ovarian, prostate, and pancreatic cancers (termed BRCA-associated cancers) who underwent paired germline and somatic DNA sequencing with Tempus xT testing. Patients were stratified based on the presence or absence of germline alterations in one of five DNA repair genes of interest. Those germline genes of interest included ATM, BRCA1, BRCA2, CHEK2, and PALB2. In scenarios where patients had more than one tumor sample, only the most recently sequenced sample was used.
2.2. Sequencing Methods
Next-generation sequencing was conducted using the Tempus xT assay (Tempus AI, Inc., Chicago, IL, USA), as previously described [17,18]. Briefly, Tempus xT is a targeted, tumor–normal-matched DNA panel that detects single-nucleotide variants, insertions and/or deletions, and copy number variants in 648 genes, as well as chromosomal rearrangements in 22 genes with high sensitivity and specificity. Germline pathogenic or likely pathogenic variants in BRCA1, BRCA2, ATM, PALB2, and CHEK2 were identified across all four cancer types from tumor–normal-matched analysis [19]. Patients with deleterious germline homologous recombination repair (HRR) variants were then separated in each cancer type from those that did not harbor any variants in these 5 HRR genes (termed the sporadic group). Classification of germline alterations was broadly based on recommendations from the American College of Medical Genetics (ACMG), the National Comprehensive Cancer Network (NCCN), and the published literature on inherited cancer syndromes [18]. CH was determined based on the presence of pathogenic or likely pathogenic alterations in any one of 52 CH-associated genes (Supplementary Table S1) with a variant allele fraction of at least 2% found in the normal match. This cut point was chosen as the clinical consequences of CH at variant allele frequencies of this level are the most commonly studied [4]. Pathogenicity is determined using Variants-Job, a proprietary tool to automate variant classification aligned to professional guidelines for variant curation. CH variant types included frameshift mutations; intron variants; splice donor, acceptor, and region variants; stop gains and losses; synonymous variants; disruptive in-frame deletions and insertions; and missense variants. These variants were distinguished from potential germline variants and sequencing artifacts based on features including number of supporting reads for the alternate allele, variant type and length, relative variant allele fraction in the tumor and normal match, and estimated copy number in the tumor.
2.3. Statistical Methods
Patients with germline alterations in BRCA1, BRCA2, ATM, CHEK2, and PALB2 were compared to those without germline HRR alterations (sporadic). Those patients with more than one germline alteration of interest were excluded given we were trying to understand the individual contributions of each germline genetic alteration and did not want to confound the results by combining patients with multiple concurrent germline alterations. Statistical comparisons were conducted between all germline groups using the Kruskal–Wallis rank sum test and Pearson’s chi-squared test for continuous variables (age at biopsy) and categorical variables (sex, race, ethnicity, and stage of disease), respectively. Dunn’s post hoc test was performed to assess which specific germline groups had significant differences in age at biopsy, with false discovery rate correction for multiple testing. Associations between age at biopsy, presence of germline mutations, specific germline mutations, sex, and prior radiation exposure on CH prevalence were assessed using Firth’s logistic regression, with confidence intervals calculated by penalized profile likelihood-based methods. Analyses were only performed on groups with size > 10. Statistical significance was established at an alpha level of 0.05, indicating that differences with a p-value below this threshold were considered significant.
3. Results
Overall, 24,849 patients were included after 13 patients were excluded for having multiple germline mutations in genes of interest. CH was identified in 3548 (14%) of 24,849 patients. Most patients (2879/3548, 81%) had one pathogenic CH variant identified, while 530 (15%) had two and 139 (4%) had more than two pathogenic CH variants. The most common CH variants found were in DNMT3A (N = 1330, 37%), followed by PPM1D (N = 700, 20%), TET2 (N = 585, 16%), TP53 (N = 301, 8.5%), and ASXL1 (N = 304, 8.6%) (Figure 1). The presence of CH was associated with increasing age at time of biopsy (odds ratio (OR) 1.05 per year of increasing age, 95% CI 1.05–1.06, p < 0.001).
3.1. Breast Cancer
In 8086 patients with breast cancer, there were 7591 patients without germline alterations, 116 patients (1.4%) with germline BRCA1 alterations, 176 (2.2%) with germline BRCA2 alterations, 69 (0.9%) with germline ATM alterations, 54 (0.7%) with germline PALB2 alterations, and 80 (1.0%) with germline CHEK2 alterations. The median age at sample collection was different across groups, with the lowest among those with germline BRCA1 alterations (median 48, IQR 38–59) and those with germline CHEK2 with the oldest median age of 63 (IQR 55–70, p < 0.001) (Table 1). Overall, 12% of the patients had CH, which ranged from 9% of those with germline BRCA1 alterations to 22% among those with germline PALB2 alterations. The most common CH alterations were in DNMT3A followed by PPM1D, TET2, and TP53 (Figure 2A). The presence of CH was associated with increasing age (OR 1.05 per year; 95% CI 1.05–1.06, p < 0.001) and prior radiation exposure (OR 1.20, 95% CI 1.01–1.41, p = 0.034). After adjusting for age at time of biopsy, we found an association between having any germline alteration and an increased likelihood of CH (OR 1.41; 95% CI 1.07–1.84, p = 0.014); however, there was no significant increase in CH among any of the patient populations with individual germline alterations (Figure 2B).
3.2. Ovarian Cancer
In 5018 patients with ovarian cancer, there were 4689 patients without germline alterations, 175 patients (3.5%) with germline BRCA1 alterations, 102 (2.0%) with germline BRCA2 alterations, 27 (0.5%) with germline ATM alterations, 12 (0.2%) with germline PALB2 alterations, and 13 (0.3%) with germline CHEK2 alterations. The median age at sample collection was lowest among those with BRCA1 alterations (56, IQR 49–64) compared to those with germline PALB2 mutations, which had the oldest median age of 70 (IQR 64–73, p < 0.001 for group difference) (Table 2).
Overall, 15% of the patients had CH which ranged from 11% of those with germline ATM alterations to 23% among those with germline CHEK2 alterations. The most common alterations overall were in PPM1D, DNMT3A, TET2, TP53, and ASXL1 (Figure 3A). The presence of CH was associated with increasing age (OR 1.05 per year; 95% CI 1.04–1.06, p < 0.001). There was no association between having any germline alteration and the likelihood of CH and there was no significant increase in CH among any of the patient populations with germline alterations (Figure 3B) after adjusting for age at biopsy.
3.3. Prostate Cancer
There were 5271 prostate cancer patients included with 18 (0.3%) having germline BRCA1 alterations, 139 (2.6%) with BRCA2 alterations, 49 (0.9%) with germline ATM alterations, 15 (0.3%) with germline PALB2 alterations, and 27 (0.5%) with germline CHEK2 alterations. Median age was significantly different across the group; it was the highest among those with germline CHEK2 alterations (72 years; IQR 66–79) and the lowest among those with germline BRCA2 alterations (65 years; IQR 60–70 years, p = 0.002) (Table 3). CH was present in 17% of the patients overall with DNMT3A being the most common gene followed by TET2, ASXL1, and then PPM1D alterations (Figure 4A). CH was associated with increasing age (OR 1.06 per year; 95% CI 1.05–1.07; p < 0.001) and prior radiation treatment (OR 1.36; 95% CI 1.06–1.73; p = 0.016). Germline alterations were not associated with an increased risk of CH after adjusting for age at biopsy (Figure 4B).
3.4. Pancreatic Cancer
Of the 6474 patients with pancreatic cancer, 27 (0.4%) had BRCA1 alterations, 108 (1.7%) had BRCA2 alterations, 76 (1.2%) had germline ATM alterations, 25 (0.4%) had PALB2 alterations, and 27 (0.4%) had CHEK2 alterations. Median age ranged from 62 (IQR 54–71) among those with germline BRCA1 alterations to 68 (IQR 62–74) among those with germline CHEK2 alterations (p = 0.002 for group comparison) (Table 4). Overall, 14% of patients had CH, with the age-related CH genes (DNMT3A, TET2, and ASXL1) predominating (Figure 5A). CH was associated with older age (OR 1.06 per year, 95% CI 1.05–1.07, p < 0.001) and prior radiation exposure (OR 1.40, 95% CI 1.04–1.84, p = 0.025) but was not associated with the presence of a germline alteration after adjusting for age at biopsy (Figure 5B).
4. Discussion
In this study of patients with BRCA-associated solid tumors (breast, ovarian, pancreatic, and prostate cancers), we found that clonal hematopoiesis (CH) was common and was associated with advancing age and prior radiation exposure, as has been found in other studies [7,11,20]. The prevalence of CH is similar to what has been found in other studies of patients with prostate cancer [6]. Patients with germline DNA repair alterations in some, but not all, cancers have younger ages of onset [21,22]. Therefore, this may confound subsequent studies exploring a potential link between germline alterations in DNA repair genes and CH among patients who have already developed cancer. The novel finding in our study is that after controlling for age, which is necessary when considering the potential differences in age of onset of inherited malignancies, the presence of a germline alteration in any of the five DNA repair genes studied (ATM, BRCA1/2, CHEK2, PALB2) was not associated with a higher prevalence of CH, except in aggregate among women with breast cancer. This suggests that there may be differences by cancer type, and that the risk of CH among patients with cancer needs to be explored not only in aggregate but also by subtype of cancer. Other prior studies have found germline ATM alterations to contribute to an increased risk of CH, which we did not observe in our study [13,15]. A possible reason for this is that our sample size was smaller and we limited our sample size to enrich the population with BRCA-associated cancers. Another consideration is that our study really is reflective of treatment-related CH, which develops after selective pressure imposed by cancer therapies and is distinct from age-related CH [23]. Therapy-related CH includes mutations in PPM1D and TP53 which are almost always seen as a result of selective pressures from previous cancer treatment [24,25]. This is evident in our study as PPM1D alterations were the most common CH alterations among patients with ovarian cancer and the second most common CH alteration among patients with breast cancer. TP53 mutations were also the fourth or fifth most common alteration found in the cohort overall. This likely reflects differences in exposure to therapies, such as PARP inhibitors, which are associated with the development of CH and are widely used in breast and ovarian cancer but less so in pancreas and prostate cancers [26,27,28]. Future research will be needed to determine how CH develops longitudinally in various at-risk populations of patients with cancer, and how it changes after exposure to cancer therapies among patients with inherited germline predispositions as there is some early evidence that this process varies and may even be blunted among patients with germline DNA repair alterations [29]. Germline genetic alterations are being used to personalize therapeutic choices for patients, and the long-term implications of how these therapies interact with germline predispositions and the development of CH remain an active area of research. A more thorough understanding of how CH interacts with tumors and the tumor microenvironment is also needed as early research suggests an impact on the microenvironment [30].
There are several limitations of our study. While our study included nearly 25,000 patients overall, the number of patients with germline alterations is still relatively small by comparison so we cannot completely rule out an association of small magnitude between a particular germline HRR mutation and CH prevalence. However, if such an association exists, the effect size is likely small. Additionally, in considering studies of effects of germline alterations on CH among patients with cancer, age is a significant confounder, not only influencing the age of onset of the cancer itself, but also potentially influencing the onset of specific CH clones, for example, with ATM clonal hematopoiesis mutations appearing earlier than others [13]. We did not explore multiple samples from patients and only considered the most recent sample. This was because CH is associated with age and we wanted to choose the latest sample to determine if there was a signal. Finally, there are potential limitations in germline genetic sequencing [31]. As liquid biopsies are increasingly being used in clinical practice, the identification of CH will undoubtedly increase and most significantly, can potentially interfere with the interpretation of actionable mutations [32,33].
5. Conclusions
Common CH variants are found across patients with BRCA-associated tumor types, with an overall CH prevalence of 14% in these cancers. When accounting for age at time of testing, pathogenic germline alterations in DNA repair genes were associated with an increased risk of CH only among those with breast, but not in patients with ovarian, pancreatic, or prostate cancer. The clinical implications of CH detection in BRCA-associated cancers requires further exploration.
Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers17091432/s1, Table S1: 52 CH-associated genes with alterations identified.
Author Contributions
Conceptualization, C.H.M., L.P.G. and E.S.A.; Methodology C.H.M., A.T.A., E.J., S.F., A.S., E.M., L.P.G., C.C., J.L. and E.S.A.; Formal analysis, E.J., S.F., A.S. and E.M.; Writing—original C.H.M. and E.S.A.; Writing—review and editing, C.H.M., A.T.A., E.J., S.F., A.S., E.M., L.P.G., C.C., J.L. and E.S.A. All authors have read and agreed to the published version of the manuscript.
Funding
This work was funded by Tempus Labs®. C.H.M. was partially supported by NCI P30 CA006973, PCF Young Investigator Award, and the Commonwealth Fund. E.S.A. is partially supported by NCI grant P30 CA077598 and DOD grant W81XWH-22-2-0025.
Institutional Review Board Statement
Tempus AI, Inc. has been granted an IRB exemption (Advarra Pro00072742) permitting the use of de-identified clinical, molecular, and multimodal data to derive or capture results, insights, or discoveries.
Informed Consent Statement
All patient-level data were de-identified in accordance with the Health Insurance Portability and Accountability Act (HIPAA).
Data Availability Statement
Deidentified data used in the research was collected in a real-world health care setting and is subject to controlled access for privacy and proprietary reasons. When possible, derived data supporting the findings of this study have been made available within the paper and its Supplementary Table S1.
Conflicts of Interest
C.H.M—Honorarium from Tempus AI, Astellas, MashupMD, McGraw Hill. Travel from Dava Oncology. Royalties from McGrawHill (unrelated to this work) E.S.A. reports grants and personal fees from Janssen, Sanofi, Bayer, Bristol Myers Squibb, Curium, MacroGenics, Merck, Pfizer, AstraZeneca, and Clovis; personal fees from Aadi Bioscience, Aikido Pharma, Astellas, Amgen, Blue Earth, Corcept Therapeutics, Exact Sciences, Hookipa Pharma, Invitae, Eli Lilly, Foundation Medicine, Menarini-Silicon Biosystems, Tango Therapeutics, Tempus AI and Z-alpha; grants from Novartis, Celgene, and Orion; and has a patent for an AR-V7 biomarker technology that has been licensed to Qiagen. Ellen Jaeger, Stamatina Fragkogianni, Anne Sonnenschein, Elizabeth Mauer, and Calvin Chao are employees of and receive stock from Tempus AI, Inc.
Abbreviations
The following abbreviations are used in this manuscript:
| CH | Clonal hematopoiesis |
| gHRR | Germline Homologous recombination repair |
| HRR | Homologous recombination repair |
| IQR | Interquartile range |
| OR | Odds ratio |
| PARP | poly-ADP ribose polymerase |
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Figure 1.
Distribution of clonal hematopoiesis (CH) mutations occurring in ≥1% of patients with CH overall.
Figure 1.
Distribution of clonal hematopoiesis (CH) mutations occurring in ≥1% of patients with CH overall.
Figure 2.
(A) Distribution of clonal hematopoiesis (CH) mutations occurring in ≥1% of patients with breast cancer and CH. (B) combined forest plots for age-adjusted odds of having CH with having any germline alteration in BRCA1, BRCA2, ATM, PALB2, or CHEK2, and by specific gene (compared to the sporadic counterparts).
Figure 2.
(A) Distribution of clonal hematopoiesis (CH) mutations occurring in ≥1% of patients with breast cancer and CH. (B) combined forest plots for age-adjusted odds of having CH with having any germline alteration in BRCA1, BRCA2, ATM, PALB2, or CHEK2, and by specific gene (compared to the sporadic counterparts).
Figure 3.
(A) Distribution of clonal hematopoiesis (CH) mutations occurring in ≥1% of patients with ovarian cancer and CH. (B) combined forest plots for age-adjusted odds of having CH with having any germline alteration in BRCA1, BRCA2, ATM, PALB2, or CHEK2, and by specific gene (compared to the sporadic counterparts).
Figure 3.
(A) Distribution of clonal hematopoiesis (CH) mutations occurring in ≥1% of patients with ovarian cancer and CH. (B) combined forest plots for age-adjusted odds of having CH with having any germline alteration in BRCA1, BRCA2, ATM, PALB2, or CHEK2, and by specific gene (compared to the sporadic counterparts).
Figure 4.
(A) Distribution of clonal hematopoiesis (CH) mutations occurring in ≥1% of patients with prostate cancer and CH. (B) combined forest plots for age-adjusted odds of having CH with having any germline alteration in BRCA1, BRCA2, ATM, PALB2, or CHEK2, and by specific gene (compared to the sporadic counterparts).
Figure 4.
(A) Distribution of clonal hematopoiesis (CH) mutations occurring in ≥1% of patients with prostate cancer and CH. (B) combined forest plots for age-adjusted odds of having CH with having any germline alteration in BRCA1, BRCA2, ATM, PALB2, or CHEK2, and by specific gene (compared to the sporadic counterparts).
Figure 5.
(A) Distribution of clonal hematopoiesis (CH) mutations occurring in ≥1% of patients with pancreatic cancer and CH. (B) combined forest plots for age-adjusted odds of having CH with having any germline alteration in BRCA1, BRCA2, ATM, PALB2, or CHEK2, and by specific gene (compared to the sporadic counterparts).
Figure 5.
(A) Distribution of clonal hematopoiesis (CH) mutations occurring in ≥1% of patients with pancreatic cancer and CH. (B) combined forest plots for age-adjusted odds of having CH with having any germline alteration in BRCA1, BRCA2, ATM, PALB2, or CHEK2, and by specific gene (compared to the sporadic counterparts).
Table 1.
Breast cancer cohort demographics.
| Sporadic | gBRCA1 | gBRCA2 | gATM | gPALB2 | gCHEK2 | |
|---|---|---|---|---|---|---|
| N (%) | 7591 (94) | 116 (1) | 176 (2) | 69 (1) | 54 (1) | 80 (1) |
| Age at testing, mean | 60 | 48 | 56 | 59 | 58 | 63 |
| IQR | 50, 69 | 38, 59 | 45, 64 | 44, 69 | 50, 74 | 55, 70 |
| N (%) Female | 7511 (99) | 116 (100) | 164 (93) | 68 (99) | 54 (100) | 78 (98) |
| Race, N (%) | ||||||
| White | 3761 (50) | 46 (40) | 72 (41) | 35 (51) | 26 (48) | 45 (56) |
| Black | 725 (10) | 9 (8) | 19 (11) | 4 (6) | 3 (6) | 1 (1) |
| Asian | 232 (3) | 5 (4) | 7 (4) | 2 (3) | 3 (6) | 1 (1) |
| Other | 409 (5) | 8 (7) | 14 (8) | 1 (1) | 5 (9) | 5 (6) |
| Hispanic, N (%) | 489 (6) | 9 (8) | 17 (10) | 4 (6) | 6 (11) | 6 (8) |
| Stage | ||||||
| I | 127 (2) | 0 (0) | 2 (1) | 0 (0) | 1 (2) | 0 (0) |
| II | 309 (4) | 5 (4) | 9 (5) | 3 (4) | 6 (11) | 2 (3) |
| III | 333 (4) | 5 (4) | 9 (5) | 4 (6) | 0 (0) | 1 (1) |
| IV | 3973 (52) | 49 (42) | 87 (49) | 39 (57) | 30 (56) | 52 (65) |
| N (%) with CH | 899 (12) | 10 (9) | 23 (13) | 12 (17) | 12 (22) | 17 (21) |
Table 2.
Ovarian cancer cohort demographics.
| Sporadic | gBRCA1 | gBRCA2 | gATM | gPALB2 | gCHEK2 | |
|---|---|---|---|---|---|---|
| N (%) | 4689 (93) | 175 (4) | 102 (2) | 27 (1) | 12 (<1) | 13 (<1) |
| Age at testing, median | 65 | 56 | 64 | 63 | 70 | 58 |
| IQR | 56, 72 | 49, 64 | 57, 69 | 54, 71 | 64, 73 | 45, 70 |
| Race, N (%) | ||||||
| White | 2576 (55) | 93 (53) | 51 (50) | 14 (52) | 10 (83) | 7 (54) |
| Black | 260 (6) | 8 (5) | 5 (5) | 2 (7) | 0 (0) | 0 (0) |
| Asian | 124 (3) | 6 (3) | 5 (5) | 1 (4) | 0 (0) | 0 (0) |
| Other | 199 (4) | 10 (6) | 2 (2) | 1 (4) | 0 (0) | 0 (0) |
| Hispanic, N (%) | 258 (6) | 15 (9) | 2 (2) | 0 (0) | 0 (0) | 0 (0) |
| Stage | ||||||
| I | 87 (2) | 1 (1) | 0 (0) | 0 (0) | 0 (0) | 0 (0) |
| II | 96 (2) | 2 (1) | 1 (1) | 0 (0) | 1 (8) | 0 (0) |
| III | 647 (14) | 14 (8) | 10 (10) | 1 (4) | 1 (8) | 2 (15) |
| IV | 855 (18) | 31 (18) | 16 (16) | 5 (19) | 2 (17) | 4 (31) |
| N (%) with CH | 715 (15) | 28 (16) | 19 (19) | 3 (11) | 2 (17) | 3 (23) |
Table 3.
Prostate cancer cohort demographics.
| Sporadic | gBRCA1 | gBRCA2 | gATM | gPALB2 | gCHEK2 | |
|---|---|---|---|---|---|---|
| N (%) | 5023 (95) | 18 (<1) | 139 (3) | 49 (1) | 15 (<1) | 27 (1) |
| Age at testing, median | 66 | 65 | 63 | 66 | 69 | 70 |
| IQR | 61, 74 | 60, 78 | 60, 70 | 62, 74 | 63, 73 | 66, 79 |
| Race, N (%) | ||||||
| White | 2366 (47) | 9 (50) | 74 (53) | 24 (49) | 10 (67) | 16 (59) |
| Black | 555 (11) | 0 (0) | 16 (12) | 4 (8) | 0 (0) | 0 (0) |
| Asian | 89 (2) | 2 (11) | 0 (0) | 1 (2) | 0 (0) | 0 (0) |
| Other | 158 (3) | 0 (0) | 4 (3) | 1 (2) | 1 (7) | 0 (0) |
| Hispanic, N (%) | 239 (5) | 1 (6) | 10 (7) | 3 (6) | 0 (0) | 0 (0) |
| Stage | ||||||
| I | 8 (<1) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) |
| II | 64 (1) | 1 (6) | 0 (0) | 0 (0) | 0 (0) | 0 (0) |
| III | 193 (4) | 1 (6) | 4 (3) | 1 (2) | 0 (0) | 1 (4) |
| IV | 2487 (50) | 4 (22) | 75 (54) | 24 (49) | 10 (67) | 21 (78) |
| N (%) with CH | 834 (17) | 6 (33) | 19 (14) | 9 (18) | 4 (27) | 5 (19) |
Table 4.
Pancreas cancer cohort demographics.
| Sporadic | gBRCA1 | gBRCA2 | gATM | gPALB2 | gCHEK2 | |
|---|---|---|---|---|---|---|
| N (%) | 6211 (96) | 27 (<1) | 108 (2) | 76 (1) | 25 (<1) | 27 (<1) |
| Age at testing, median | 67 | 62 | 65 | 65 | 64 | 68 |
| IQR | 60, 74 | 54, 71 | 58, 72 | 61, 72 | 55, 67 | 62, 74 |
| N (%) Female | 2898 (47) | 11 (41) | 48 (44) | 37 (49) | 14 (56) | 11 (41) |
| Race, N (%) | ||||||
| White | 3071 (49) | 10 (37) | 50 (46) | 30 (39) | 22 (88) | 19 (70) |
| Black | 393 (6) | 3 (11) | 4 (4) | 6 (8) | 0 (0) | 0 (0) |
| Asian | 132 (2) | 0 (0) | 6 (6) | 1 (1) | 0 (0) | 0 (0) |
| Other | 164 (3) | 2 (7) | 4 (4) | 4 (5) | 0 (0) | 0 (0) |
| Hispanic, N (%) | 243 (4) | 1 (4) | 8 (7) | 5 (7) | 0 (0) | 0 (0) |
| Stage | ||||||
| I | 203 (3) | 2 (7) | 6 (6) | 2 (3) | 0 (0) | 1 (4) |
| II | 416 (7) | 2 (7) | 5 (5) | 9 (12) | 1 (4) | 3 (11) |
| III | 321 (5) | 1 (4) | 3 (3) | 6 (8) | 2 (8) | 2 (7) |
| IV | 3372 (54) | 15 (56) | 73 (68) | 28 (37) | 15 (60) | 16 (59) |
| N (%) with CH | 889 (14) | 3 (11) | 13 (12) | 16 (21) | 3 (12) | 4 (15) |
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Marshall, C.H.; Arafa, A.T.; Jaeger, E.; Fragkogianni, S.; Sonnenschein, A.; Mauer, E.; Gondek, L.P.; Chao, C.; Luo, J.; Antonarakis, E.S. Germline DNA Repair Gene Mutations and Clonal Hematopoiesis (CH) in 24,849 Patients with BRCA-Associated Cancers. Cancers 2025, 17, 1432. https://doi.org/10.3390/cancers17091432
AMA Style
Marshall CH, Arafa AT, Jaeger E, Fragkogianni S, Sonnenschein A, Mauer E, Gondek LP, Chao C, Luo J, Antonarakis ES. Germline DNA Repair Gene Mutations and Clonal Hematopoiesis (CH) in 24,849 Patients with BRCA-Associated Cancers. Cancers. 2025; 17(9):1432. https://doi.org/10.3390/cancers17091432
Chicago/Turabian StyleMarshall, Catherine H., Ali T. Arafa, Ellen Jaeger, Stamatina Fragkogianni, Anne Sonnenschein, Elizabeth Mauer, Lukasz P. Gondek, Calvin Chao, Jun Luo, and Emmanuel S. Antonarakis. 2025. "Germline DNA Repair Gene Mutations and Clonal Hematopoiesis (CH) in 24,849 Patients with BRCA-Associated Cancers" Cancers 17, no. 9: 1432. https://doi.org/10.3390/cancers17091432
APA StyleMarshall, C. H., Arafa, A. T., Jaeger, E., Fragkogianni, S., Sonnenschein, A., Mauer, E., Gondek, L. P., Chao, C., Luo, J., & Antonarakis, E. S. (2025). Germline DNA Repair Gene Mutations and Clonal Hematopoiesis (CH) in 24,849 Patients with BRCA-Associated Cancers. Cancers, 17(9), 1432. https://doi.org/10.3390/cancers17091432
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