Dennis J. Slamon, MD, PhD, on Exploiting Cancer Biology in Developing New Treatment Paradigms
AACR Annual Meeting 2021
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
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
Ralph R. Weichselbaum, MD, of the University of Chicago, discusses oligometastasis as a part of the metastatic spectrum where ablative therapies, such as surgery or stereotactic body radiotherapy, may be curative alone or with systemic agents, as well as some potential biomarkers to guide treatment selection.
The ASCO Post Staff
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).
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
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).
