ArCH: improving the performance of clonal hematopoiesis variant calling and interpretation.

MOTIVATION: The acquisition of somatic mutations in hematopoietic stem and progenitor stem cells with resultant clonal expansion, termed clonal hematopoiesis (CH), is associated with increased risk of hematologic malignancies and other adverse outcomes. CH is generally present at low allelic fractions, but clonal expansion and acquisition of additional mutations leads to hematologic cancers in a small proportion of individuals. With high depth and high sensitivity sequencing, CH can be detected in most adults and its clonal trajectory mapped over time. However, accurate CH variant calling is challenging due to the difficulty in distinguishing low frequency CH mutations from sequencing artifacts. The lack of well-validated bioinformatic pipelines for CH calling may contribute to lack of reproducibility in studies of CH. RESULTS: Here, we developed ArCH, an Artifact filtering Clonal Hematopoiesis variant calling pipeline for detecting single nucleotide variants and short insertions/deletions by combining the output of four variant calling tools and filtering based on variant characteristics and sequencing error rate estimation. ArCH is an end-to-end cloud-based pipeline optimized to accept a variety of inputs with customizable parameters adaptable to multiple sequencing technologies, research questions, and datasets. Using deep targeted sequencing data generated from six acute myeloid leukemia patient tumor: normal dilutions, 31 blood samples with orthogonal validation, and 26 blood samples with technical replicates, we show that ArCH improves the sensitivity and positive predictive value of CH variant detection at low allele frequencies compared to standard application of commonly used variant calling approaches. AVAILABILITY AND IMPLEMENTATION: The code for this workflow is available at: https://github.com/kbolton-lab/ArCH.

Social, Behavioral, and Clinical Risk Factors Are Associated with Clonal Hematopoiesis.

BACKGROUND: Risk factors including smoking, alcohol intake, physical activity (PA), and sleep patterns have been associated with cancer risk. Clonal hematopoiesis (CH), including mosaic chromosomal alterations and clonal hematopoiesis of indeterminate potential, is linked to increased hematopoietic cancer risk and could be used as common preclinical intermediates for the better understanding of associations of risk factors with rare hematologic malignancies. METHODS: We analyzed cross-sectional data from 478,513 UK Biobank participants without hematologic malignancies using multivariable-adjusted analyses to assess the associations between lifestyle factors and CH types. RESULTS: Smoking was reinforced as a potent modifiable risk factor for multiple CH types, with dose-dependent relationships persisting after cessation. Males in socially deprived areas of England had a lower risk of mosaic loss of chromosome Y (mLOY), females with moderate/high alcohol consumption (2-3 drinks/day) had increased mosaic loss of the X chromosome risk [OR = 1.17; 95% confidence interval (CI), 1.09-1.25; P = 8.31 × 10-6] compared with light drinkers, active males (moderate-high PA) had elevated risks of mLOY (PA category 3: OR = 1.06; 95% CI, 1.03-1.08; P = 7.57 × 10-6), and men with high body mass index (≥40) had reduced risk of mLOY (OR = 0.57; 95% CI, 0.51-0.65; P = 3.30 × 10-20). Sensitivity analyses with body mass index adjustment attenuated the effect in the mLOY-PA associations (IPAQ2: OR = 1.03; 95% CI, 1.00-1.06; P = 2.13 × 10-2 and IPAQ3: OR = 1.03; 95% CI, 1.01-1.06; P = 7.77 × 10-3). CONCLUSIONS: Our study reveals associations between social deprivation, smoking, and alcohol consumption and CH risk, suggesting that these exposures could contribute to common types of CH and potentially rare hematologic cancers. IMPACT: This study underscores the impact of lifestyle factors on CH frequency, emphasizing social, behavioral, and clinical influences and the importance of sociobehavioral contexts when investigating CH risk factors.

Clonal Hematopoiesis and Clinical Outcomes in Metastatic Castration-Resistant Prostate Cancer Patients Given Androgen Receptor Pathway Inhibitors (Alliance A031201).

PURPOSE: Mutations in hematopoietic progenitor cells accumulate with age leading to clonal expansion, termed clonal hematopoiesis (CH). CH in the general population is associated with hematopoietic neoplasms and reduced overall survival (OS), predominantly through cardiovascular adverse events (CVAE). Because androgen receptor pathway inhibitors (ARPI) used in metastatic castration-resistant prostate cancer (mCRPC) are also associated with CVAEs and because CH negatively impacted survival in an advanced solid tumor cohort, we hypothesized that CH in mCRPC may be associated with increased CVAEs and inferior survival. EXPERIMENTAL DESIGN: A targeted DNA sequencing panel captured common CH mutations in pretreatment blood samples from 957 patients enrolled in Alliance A031201: a randomized trial of enzalutamide ± abiraterone/prednisone in the first-line mCRPC setting. The primary outcome was the impact of CH on OS; the secondary outcomes were progression-free survival (PFS) and CVAEs. RESULTS: Baseline comorbidities were similar by CH status. No differences in OS/progression-free survival were detected regardless of treatment arm or the variant allele frequency threshold used to define CH [primary: 2% (normal-CH, N-CH); exploratory: 0.5% (low-CH) and 10% (high-CH, H-CH)]. Patients with H-CH (7.2%) and TET2-mutated N-CH (6.0%) had greater odds of any CVAE (14.5% vs. 4.0%; P = 0.0004 and 12.3% vs. 4.2%; P = 0.010, respectively). More major CVAEs were observed in patients with H-CH (5.8% vs. 1.9%; P = 0.042) and N-CH (3.4% vs. 1.8%; P = 0.147). CONCLUSIONS: CH did not affect survival in patients with mCRPC treated with ARPIs in A031201. H-CH and TET2-mutated CH were associated with more CVAEs. These findings inform the risk/benefit discussion about ARPIs in mCRPC.

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

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.

Plasma Proteomic Signature Predicts Myeloid Neoplasm Risk.

PURPOSE: Clonal hematopoiesis (CH) is thought to be the origin of myeloid neoplasms (MN). Yet, our understanding of the mechanisms driving CH progression to MN and clinical risk prediction of MN remains limited. The human proteome reflects complex interactions between genetic and epigenetic regulation of biological systems. We hypothesized that the plasma proteome might predict MN risk and inform our understanding of the mechanisms promoting MN development. EXPERIMENTAL DESIGN: We jointly characterized CH and plasma proteomic profiles of 46,237 individuals in the UK Biobank at baseline study entry. During 500,036 person-years of follow-up, 115 individuals developed MN. Cox proportional hazard regression was used to test for an association between plasma protein levels and MN risk. RESULTS: We identified 115 proteins associated with MN risk, of which 30% (N = 34) were also associated with CH. These were enriched for known regulators of the innate and adaptive immune system. Plasma proteomics improved the prediction of MN risk (AUC = 0.85; P = 5×10-9) beyond clinical factors and CH (AUC = 0.80). In an independent group (N = 381,485), we used inherited polygenic risk scores (PRS) for plasma protein levels to validate the relevance of these proteins toMNdevelopment. PRS analyses suggest that most MN-associated proteins we identified are not directly causally linked toMN risk, but rather represent downstream markers of pathways regulating the progression of CH to MN. CONCLUSIONS: These data highlight the role of immune cell regulation in the progression of CH to MN and the promise of leveraging multi-omic characterization of CH to improveMN risk stratification. See related commentary by Bhalgat and Taylor, p. 3095.

What Clonal Hematopoiesis Can Teach Us About MDS.

Clonal hematopoiesis (CH), defined as the clonal expansion of mutated hematopoietic stem and progenitor cells (HSPCs), is a common aging process. CH is a risk factor for the development of hematologic malignancies, most commonly myeloid neoplasms (MNs) including acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and myeloproliferative neoplasm (MPN). Recent work has elucidated how the development and cellular fitness of CH is shaped by aging, environmental exposures, and the germline (inherited) genetic background of an individual. This in turn has provided valuable insights into the pathogenesis of MNs including MDS. Here, in this review, we discuss the genetic origins of CH, the environmental stressors that influence CH, and the implications of CH on health outcomes including MDS. Since MNs have shared risk factors and underlying biology, most of our discussion regarding the implications of CH surrounds MN in general rather than focusing specifically on MDS. We conclude with future directions and areas of investigation including how intervention studies of CH might inform future therapeutic approaches to MN including MDS.

Molecular Subclasses of Clear Cell Ovarian Carcinoma and Their Impact on Disease Behavior and Outcomes.

PURPOSE: To identify molecular subclasses of clear cell ovarian carcinoma (CCOC) and assess their impact on clinical presentation and outcomes. EXPERIMENTAL DESIGN: We profiled 421 primary CCOCs that passed quality control using a targeted deep sequencing panel of 163 putative CCOC driver genes and whole transcriptome sequencing of 211 of these tumors. Molecularly defined subgroups were identified and tested for association with clinical characteristics and overall survival. RESULTS: We detected a putative somatic driver mutation in at least one candidate gene in 95% (401/421) of CCOC tumors including ARID1A (in 49% of tumors), PIK3CA (49%), TERT (20%), and TP53 (16%). Clustering of cancer driver mutations and RNA expression converged upon two distinct subclasses of CCOC. The first was dominated by ARID1A-mutated tumors with enriched expression of canonical CCOC genes and markers of platinum resistance; the second was largely comprised of tumors with TP53 mutations and enriched for the expression of genes involved in extracellular matrix organization and mesenchymal differentiation. Compared with the ARID1A-mutated group, women with TP53-mutated tumors were more likely to have advanced-stage disease, no antecedent history of endometriosis, and poorer survival, driven by their advanced stage at presentation. In women with ARID1A-mutated tumors, there was a trend toward a lower rate of response to first-line platinum-based therapy. CONCLUSIONS: Our study suggests that CCOC consists of two distinct molecular subclasses with distinct clinical presentation and outcomes, with potential relevance to both traditional and experimental therapy responsiveness. See related commentary by Lheureux, p. 4838.