PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 8, 2026Blood1 citations

The ASH HematOmics Program supports integrative analysis of genomic and clinical data in hematologic diseases

View Full Paper
CLCongyu LuGMGavriel Y. MattRPRobin Paul

Key Points

  • The aim is to develop a platform for integrative analysis of genomic and clinical data in hematologic diseases.
  • Development of the ASH HematOmics Program platform for data integration.
  • Analysis of genomic alterations and gene fusions from 5,960 patients.
  • Interactive tools for exploring transcriptomic results and clinical data correlation.
  • Illustration of four key use cases involving mutational burden and gene expression patterns.
  • Ability to stratify B-cell leukemias into distinct subgroups with different outcomes.
  • Characterization of gene expression patterns in acute myeloid leukemias.
  • Correlation of mutational burden with repair deficiency and mutational signatures.
  • Exploration of the TP53 alteration landscape.

Abstract

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 5,960 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 co-mutation patterns via lollipop and matrix plots, and analyze significantly altered genes in user-defined sub-cohorts. Transcriptomes can be explored through interactive UMAPs, 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 four 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, (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.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Lu et al. (2026) studied this question.

synapsesocial.com/papers/69d5f10974eaea4b11a7a830https://doi.org/10.1182/blood.2025032031
Ask AI
Helpful
Bookmark
Share
View Full Paper