Matthew G. Vander Heiden, MD, PhD, and Karen H. Vousden, PhD: A Conversation About the Role of Diet in Cancer
AACR Annual Meeting 2021
Karen H. Vousden, PhD, of The Francis Crick Institute, and Matthew G. Vander Heiden, MD, PhD, of the Koch Institute for Integrative Cancer Research at MIT, discuss emerging evidence that diet may affect which nutrients are available to tumor cells, which can influence both tumor growth and response to therapy. Clinicians may be able to personalize dietary interventions to optimize patient care.
The ASCO Post Staff
Matthew J. Matasar, MD, of Memorial Sloan Kettering Cancer Center, discusses phase III results of the CHRONOS-3 trial, which showed that copanlisib plus rituximab led to a 48% reduction in the risk of disease progression or death compared with placebo plus rituximab in patients with relapsed indolent non-Hodgkin lymphoma (Abstract CT001).
The ASCO Post Staff
Dennis J. Slamon, MD, PhD, of the UCLA David Geffen School of Medicine, reflects on the ways in which breast cancer research pioneered the targeted treatment approach, as understanding of the basic biology of tumors deepened and new pathways were uncovered. He sees a future ripe with possibilities for new molecular targets to further improve outcomes for patients with breast cancer and other types of tumors.
The ASCO Post Staff
Richard S. Finn, MD, of UCLA Medical Center, discusses updated efficacy and safety data from the IMbrave150 trial of patients receiving atezolizumab plus bevacizumab vs sorafenib as first-line treatment for unresectable hepatocellular carcinoma (Abstract CT009).
The ASCO Post Staff
Georgina V. Long, MD, PhD, of the Melanoma Institute Australia, University of Sydney, discusses results of the CheckMate 915 trial, which may reinforce nivolumab as an adjuvant standard of care in patients with stage IIIB–D/IV melanoma, with or without complete lymphadenectomy (Abstract CT004).
The ASCO Post Staff
Joann G. Elmore, MD, MPH, of the UCLA Fielding School of Public Health, discusses previous studies that show wide variability in cancer diagnoses, the uncertainties introduced by computer-aided detection tools, and new research on artificial intelligence and machine learning that may lead to more consistent and accurate diagnoses and prognoses, potentially improving treatment (Abstract SY01-03).
