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).
Jorge E. Cortes, MD, of the Georgia Cancer Center at Augusta University, reviews four important studies of treatment advances in chronic myeloid leukemia (CML): nilotinib vs dasatinib in newly diagnosed disease; final 5-year results from the BFORE trial on bosutinib vs imatinib for chronic phase (CP) CML; data from the OPTIC trial on ponatinib for CP-CML; and a novel class of mutated cancer-related genes associated with the Philadelphia translocation (Abstracts 45, 46, 48, 49).
Caron A. Jacobson, MD, of the Dana-Farber Cancer Institute, discusses results from the ZUMA-9 C2 study, an ongoing trial that is exploring axicabtagene ciloleucel in patients with relapsed or refractory large B-cell lymphoma (Abstract 2100).
Curtis Lachowiez, MD, of The University of Texas MD Anderson Cancer Center, discusses an interim analysis of a phase Ib/II study showing that venetoclax plus chemotherapy represents an effective regimen, particularly in patients with newly diagnosed and relapsed or refractory acute myeloid leukemia. The regimen appears to be an effective bridge to hematopoietic stem cell transplantation (Abstract 332).
Nitin Jain, MD, of The University of Texas MD Anderson Cancer Center, reviews six important abstracts on CAR T-cell treatments for B-cell acute lymphoblastic leukemia (ALL): successful 24-hour manufacture of CAR T-cell therapy; ALLCAR19, a novel fast-off rate therapy; donor-derived CD19-targeted treatment; CAR 2.0 therapy to manage post-transplant relapse; UCART22, allogeneic engineered T cells expressing anti-CD22 chimeric antigen receptor; and inotuzumab ozogamicin in pediatric CD-22–positive disease (Session 614, Abstracts 159-164).
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).
