Search PubMedSearch

PubMed · 42008361

Genomic Evolution of Myeloproliferative Neoplasms and Therapy-Associated Mutagenesis.

Abstract

UNLABELLED: Philadelphia-negative myeloproliferative neoplasms are chronic blood neoplasms. Treatments control blood counts, but disease can progress to myelofibrosis or acute myeloid leukemia. We performed longitudinal whole-genome and targeted sequencing in 30 patients, integrating clonal dynamics with 7,986 blood counts and clinical histories. Distinct evolutionary patterns distinguished stable from progressive disease, with leukemic transformation arising via TP53 loss, stepwise driver mutation acquisition within complex clones, or emergence of independent leukemic clones. In contrast, stable disease showed long-term clonal equilibrium without new drivers. Phylogenetic analysis using 203 whole-genomes of hematopoietic colonies revealed age-appropriate polyclonal hematopoiesis in triple-negative essential thrombocythemia and germline predisposition to thrombocytosis, supporting non-neoplastic origins. Therapy-associated mutagenesis was observed, including C > G mutations following azacitidine and characteristic T > A/T > G after hydroxycarbamide exposure in blood cells, although not in skin where UV damage predominated. These findings demonstrate that progression is genomically encoded years in advance and support serial monitoring and further study of treatment-related mutagenesis. SIGNIFICANCE: Longitudinal whole-genome sequencing shows MPN progression is genomically encoded years before clinical transformation, with distinct evolutionary routes to leukemia and MF. It identifies DNA mutagenesis associated with HC and 5-azacitidine, suggests some triple-negative cases are nonclonal, and supports serial clinical genomic monitoring for improved risk stratification and long-term management. See related commentary by Agarwal and Sankaran, p. 1724.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Daniel Leongamornlert, Joe Lee, Aleksandra E Kamizela, Ken To, Daniel Myers, Nicholas Williams, Kudzai Nyamondo, Xin Wang, Jing Guo, Ruchira K Dissanayake, Jane Price, Amer J Durrani, Jonathan Lambert, Michael Spencer Chapman, John E Pimanda, E Joanna Baxter, Anthony R Green, Anna L Godfrey, Jyoti Nangalia. 2026-09-01. Genomic Evolution of Myeloproliferative Neoplasms and Therapy-Associated Mutagenesis.. https://doi.org/10.1158/2159-8290.cd-26-0410

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans