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).
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).
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).
Vivek Subbiah, MD, of The University of Texas MD Anderson Cancer Center, discusses data on selpercatinib that showed promising activity across a variety of RET fusion–positive cancers, including treatment-refractory gastrointestinal malignancies. This analysis highlights the need for genomic profiling to identify actionable oncogenic drivers.
Enrique Grande, MD, PhD, of The University of Texas MD Anderson Cancer Center, Madrid, discusses phase III overall survival results from the IMvigor130 study of atezolizumab plus platinum and gemcitabine vs placebo plus platinum and gemcitabine in patients with previously untreated metastatic urothelial carcinoma (Abstract CT187).