Blood · 2026
The ASH HematOmics Program supports integrative analysis of genomic and clinical data in hematologic diseases.
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Lu Congyu, Matt Gavriel Y, Paul Robin, Wang Jian, Sioson Edgar, Gangwani Karishma, Acić Aleksandar, Willems Andrew, Zaldívar Peraza Airen, Reilly Colleen, Pölönen Petri, Gao Qingsong, Li Qian, Pounds Stanley B, Zeng Andy G X, Li Sihan, Nadarajah Niroshan, Brady Samuel W, Iacobucci Ilaria, Haferlach Torsten, Rose Miquella C, Mullighan Charles G, Zhou Xin
Аннотация
The increasing availability of genomic and transcriptomic sequencing has uncovered diverse genomic alterations and distinct gene expression profiles driving hematologic diseases, yet a data integration and sharing platform dedicated to hematology remains lacking. We developed the American Society of Hematology (ASH) HematOmics Program (ASHOP; ashop.hematology.org), a resource for exploring somatic alterations and gene fusions, transcriptomic results, and clinical data from 5960 patients spanning B-cell precursor and T-cell acute lymphoblastic leukemia, acute myeloid leukemia, myelodysplastic syndromes, and chronic lymphocytic leukemia. Users can explore genomic alteration landscapes and comutation patterns via lollipop and matrix plots and analyze significantly altered genes in user-defined subcohorts. Transcriptomes can be explored through interactive uniform manifold approximation and projections, clustering, differential expression, and pathway enrichment. Genomic, transcriptomic features, and clinical outcomes can be correlated in a user-driven manner or combined to precisely define study cohorts. We illustrate the following 4 use cases of ASHOP: (1) stratification of DUX4-rearranged B-cell leukemias into Early/Multipotent and Committed subgroups with distinct outcomes, (2) characterization of HOXA/HOXB expression patterns in acute myeloid leukemias, (3) correlating mutational burden with mismatch repair deficiency and mutational signatures, and (4) investigation of TP53 alteration landscape. ASHOP is an open-access resource to inform genomic and transcriptomic data interpretation for hematologic malignancies and will expand to support additional diseases and data modalities from the ASH community.