Progression to Acute Myeloid Leukemia Explained by Multi Omics Analysis

Progression to Acute Myeloid Leukemia Explained by Multi Omics Analysis

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ATLANTA, USA—A new research method has elucidated cellular processes (involving mutated TP53 oncogene) that can convert a relatively benign myeloproliferative neoplasm into acute myeloid leukemia. Fin

ATLANTA, USA—A new research method has elucidated cellular processes (involving mutated TP53 oncogene) that can convert a relatively benign myeloproliferative neoplasm into acute myeloid leukemia.

Findings from Oxford University in the UK (using the novel genetic sequencing tool called: single cell multi omics) were reported at the American Society of Hematology (ASH) 2021 Annual Meeting Plenary Session, by Oxford scientist Alba Rodriguez-Meira DPhil, PhD, from the Weatherall Institute of Molecular Medicine in Oxford—winner of an ASH Abstract Achievement Award. She discusses her award-winning research with Audio Journal of Oncology reporter Peter Goodwin.

In an inspiring oral presentation at ASH, Alba Rodriguez-Meira explained how her group’s research on the TP53 gene had made it possible to analyze the genome of a large number of individual cells from a relatively small sample of patients and healthy controls. https://ash.confex.com/ash/2021/webprogram/Paper150191.html

The study findings should provide predictive, prognostic and therapeutic tools that could improve otherwise dismal outcomes in subgroups of patients with hematologic malignancies.

Our single cell multi omics analysis, coupled with in-vitro and in-vivo analysis, has allowed us to depict a model of TP53 -mediated transformation in myeloproliferative neoplasms in which inflammatory signaling leads to suppression of wild-type and MPN cells while giving a fitness advantage to TP53 [mutated] cells with leukemic stem-cell properties. From our study we hope to find this is applicable to many other cancer types,” said Rodriguez-Meira at the ASH session.

Single-cell multi omics analysis in a small patient cohort can theoretically be used to derive the gene signature that is highly relevant in much larger patient cohorts.

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