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).
Brian I. Rini, MD, of Vanderbilt University, discusses the IMmotion151 trial results on overall survival and the association of gene expression and clinical outcomes with atezolizumab plus bevacizumab vs sunitinib in patients with locally advanced or metastatic renal cell carcinoma (Abstract CT188).
Katelyn T. Byrne, PhD, of the Perelman School of Medicine at the University of Pennsylvania, discusses the first in-depth analysis of the impact of selicrelumab, an anti-CD40 antibody, which was found to enrich T cells in pancreatic tumors, activate the immune system, and alter the tumor stroma (Abstract CT005).
Jeanne Tie, MD, MBChB, of the Peter MacCallum Cancer Centre, discusses how to improve the current, somewhat imprecise, approach based on pathologic staging alone, used to select patients for adjuvant treatment. Circulating tumor DNA analysis after curative-intent treatment may detect minimal residual disease and might be used to predict recurrence and adjuvant treatment efficacy across multiple tumor types.
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).
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).
