Racial Disparities in Clonal Hematopoiesis Among Solid Cancer Patients with Cardiovascular Diseases

• Published in: Blood 2024-11, Vol.144 (Supplement 1), p.5636-5636
• Main Authors: Aguilar, Jeff Justin, Dhillon, Vikram, Dhiman, Sandhya, Williams, Breanna, Virk, Sonubar, Dyson, Gregory, Boerner, Julie, Assad, Hadeel, Balasubramanian, Suresh Kumar
• Format: Article
• Language: English
• ISSN: 0006-4971; 1528-0020
• DOI: 10.1182/blood-2024-204416

Introduction Clonal hematopoiesis of indeterminate potential (CHIP) is associated with an increased risk of cardiovascular disease, higher all-cause mortality, and elevated likelihood of developing hematological malignancies. Prior studies reported CHIP at a higher prevalence in solid cancer patients (~25-30%), possibly due to increased exposure to mutagenic/epigenetic stressors inherent in this population, common risk factors shared between solid cancers and CHIP or the oncogenic therapies they receive. Environmental factors may influence the epigenetic landscape, impacting the progression of CHIP to myeloid neoplasms (MN), including AML. Despite many studies, there is little known about the patterns of CHIP/CCUS among BAA and other minority groups. By assessing critical mutations in precursor conditions, we aim to improve health outcomes by preventing their clonal progression, given their poorer prognosis in overt disease stages. Notably, BAA AML patients have historically low survival rates due to socioeconomic, healthcare disparities, and biological factors. We here conducted a population sequencing study in our catchment area to study the prevalence of CHIP lesions in a racially distinct solid cancer population. Methods 76 adult female cancer patients (breast, endometrial, ovarian, uterine) with a history of cardiometabolic disease (Hx of HTN, HLD, DM, PVD, CAD) who were treated at Karmanos Cancer Institute with curative intent for solid cancer were sampled at their diagnosis prior to exposure to cytotoxic chemo or radiotherapy. The study was supported under the overarching proposal of ACHIEVE GreatER: Addressing Cardiometabolic Health Inequities by Early PreVEntion in the Great LakEs Region (NIH/NIMHD Grant #5P50MD017351). Race/ethnicity data was self-reported. Whole exome sequencing was used to identify CHIP mutation and single-nucleotide polymorphism (SNP) array data. A variant calling pipeline with Genome Analysis ToolKit was used to identify somatic variants, including variant quality score recalibration method for quality filtering and minimum variant allele frequency (VAF) of 0.02. Putative somatic CHIP mutations were further filtered using a list of commonly identified CHIP genes based on prior literature. Likely germline variants, defined as single nucleotide variants with VAF > 0.3, were excluded. Based on the literature, the following were exceptions and counted as somatic: DNMT3A R882, SRSF2 P95, SF3B1 K666 and K700, JAK2 V617. Chi-square