Clonal hematopoiesis (CH) is an age-associated pre-malignant condition characterized by expansion of hematopoietic stem and progenitor cells carrying somatic mutations predominantly in DNMT3A, TET2 and ASXL1 genes. CH can be a precursor to both myeloid and lymphoid complications in patients with solid cancers. In non-prostatic malignancies, radiation and DNA-damaging systemic therapies are recognized to positively select for CH that carries alterations in DNA damage response genes and are consequently at higher risk for progression to treatment-related myeloid neoplasms.
CH can be characterized by applying bioinformatics techniques to parallel sequencing of plasma cell-free DNA and leukocyte DNA. In collaboration with clinicians, I study how CH co-evolves with cancer under the selective pressures of therapy, aiming to understand the interplay between tumor evolution, treatment exposure, and hematopoietic health. My research goals are to integrate CH monitoring into personalized treatment strategies, using insights from clonal dynamics to guide therapy and mitigate long-term hematologic risks in high-risk patients.
Epigenomic regulation plays a central role in prostate cancer cell phenotype, influencing disease presentation and treatment resistance. Because metastatic prostate cancer often spreads to bone, access to tissue for chromatin analysis is limited, motivating the development of noninvasive approaches. My research leverages plasma cell-free DNA to profile histone modifications and chromatin accessibility, capturing diverse tumor phenotypes and lineage states across metastatic sites. By integrating these epigenomic signals with clinical and genomic features such as ctDNA fraction, site of metastasis, and histopathologic subtype I aim to map tumor phenotypes, track lineage plasticity during therapy, and identify biomarkers for individualized resistance monitoring. Ultimately, my work seeks to establish plasma cfDNA chromatin profiling as a practical tool for both biological discovery and clinical translation in aggressive prostate cancer.
MRD detection enables sensitive monitoring of residual cancer cells that persist after treatment. Detection of MRD has been associated with poor survival outcomes in various solid tumor settings. Using plasma cell-free DNA and tumor-derived sequencing data from clinical trial cohorts I track MRD in real time to evaluate treatment response and detect early signs of relapse.