Ralph R. Weichselbaum, MD, on Oligometastasis: Biologic Basis and Therapeutic Opportunities
AACR Annual Meeting 2021
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
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).
The ASCO Post Staff
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.
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
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
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).