Christian Marinaccio, PhD Candidate: Genetic Driver May Play a Role in Progression of Myeloproliferative Neoplasms to AML
2020 ASH Annual Meeting & Exposition
Christian Marinaccio, PhD Candidate, of Northwestern University, describes research he is conducting in the laboratory of John D. Crispino, PhD, which shows the loss of the tumor suppressor gene LKB1/STK11 facilitates progression of myeloproliferative neoplasms to acute myeloid leukemia (Abstract 1).
The ASCO Post Staff
Andrew D. Zelenetz, MD, PhD, of Memorial Sloan Kettering Cancer Center, offers his expert views on five treatment studies in mantle cell lymphoma focusing on the next-generation BTK inhibitor LOXO-305; lisocabtagene maraleucel; minimal residual disease monitoring following autologous stem cell transplantation with or without rituximab maintenance; the antibody-drug conjugate VLS-101; and venetoclax, lenalidomide, and rituximab (Abstracts 117, 118, 120, 121, 122).
The ASCO Post Staff
Andrew D. Zelenetz, MD, PhD, of Memorial Sloan Kettering Cancer Center, discusses phase II results from a single-center study that explored a novel approach for high-risk patients with mantle cell lymphoma. Among patients with TP53 wild-type disease, the data suggested this treatment was effective (Abstract 119).
The ASCO Post Staff
Matthew S. Davids, MD, of Dana-Farber Cancer Institute, summarizes three key studies from a session he co-moderated on ibrutinib plus venetoclax for first-line treatment of patients with chronic lymphocytic leukemia (CLL) and small lymphocytic lymphoma (SLL), long-term responses to these agents for relapsed and refractory CLL, and undetectable minimal residual disease following fixed-duration treatment with venetoclax and rituximab for CLL (Abstracts 123, 124, and 125).
The ASCO Post Staff
Sagar Lonial, MD, of the Emory University School of Medicine, summarizes key papers presented in a session he co-moderated on how second-generation CAR T cells can be used to treat patients with multiple myeloma (Session 653).
The ASCO Post Staff
Hassan Awada, MD, of the Taussig Cancer Institute, Cleveland Clinic Foundation, discusses the use of newer machine-learning techniques to help decipher a set of prognostic subgroups that could predict survival, thus potentially improving on traditional methods and moving acute myeloid leukemia into the era of personalized medicine (Abstract 34).