Potential Clinical Uses of Identifying New Hematologic Malignancy Predisposition Gene
2023 ASH
Hamish S. Scott, PhD, and Chris Hahn, PhD, both of Australia’s SA Pathology and Centre for Cancer, discuss ERG, a new predisposition gene for bone marrow failure and hematologic malignancy. Identifying causal germline ERG variants has direct clinical implications for diagnosis, counseling, surveillance, and treatment strategies, according to Drs. Scott and Hahn (Abstract LBA5).
The ASCO Post Staff
Jeffrey E. Rubnitz, MD, PhD, of St. Jude Children’s Research Hospital, discusses study findings suggesting that pharmacogenomic differences between Black and White patients should be considered when tailoring induction regimens to improve outcomes of all patients and bridge the racial disparity gap in acute myeloid leukemia treatment (Abstract 386).
The ASCO Post Staff
Ibrahim Aldoss, MD, of City of Hope National Medical Center, discusses phase II safety and efficacy results from the Augment-101 study. This trial showed that patients with heavily pretreated, relapsed or refractory KMT2-rearranged acute leukemia benefited from monotherapy with the menin-KMT2A inhibitor revumenib, with high overall response rates and undetectable measurable residual disease (Abstract LBA-5).
The ASCO Post Staff
Mikkael A. Sekeres, MD, of the Sylvester Comprehensive Cancer Center at the University of Miami Miller School of Medicine, reviews key abstracts from ASH 2023 on treatment of myelofibrosis, chronic lymphocytic leukemia, large B-cell lymphoma, and acute myeloid leukemia (Abstracts 620, 631, 781, 425).
The ASCO Post Staff
Sanjal H. Desai, MBBS, of the University of Minnesota, discusses results from a multicenter cohort, which shows that, for transplant-eligible patients with relapsed or refractory classical Hodgkin lymphoma, PD-1–based salvage therapy at any point before transplantation is associated with improved progression-free survival, compared with brentuximab vedotin or chemotherapy-based salvage regimens (Abstract 182).
The ASCO Post Staff
Andrew Srisuwananukorn, MD, of The Ohio State University Comprehensive Cancer Center, discusses a novel artificial intelligence model that can distinguish between prefibrotic primary myelofibrosis and essential thrombocythemia. This proposed model may assist clinicians in identifying patients who may benefit from disease-specific therapies or enrollment in clinical trials (Abstract 901).
