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.
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).
Lipika Goyal, MD, of Massachusetts General Hospital, discusses phase II results of the FOENIX-CCA2 trial, which explored the clinical benefit of futibatinib, an FGFR1–4 inhibitor, tested in patients with intrahepatic cholangiocarcinoma that harbored FGFR2 gene fusions or other rearrangements (Abstract CT010).
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).
Rita Nanda, MD, of the University of Chicago, discusses the latest data on novel treatment strategies for triple-negative breast cancer, including immune checkpoint, PARP, and ATK inhibitors; antibody-drug conjugates; and targeting the androgen receptor.