Michel Sadelain, MD, PhD, on the Road to Synthetic Immunity: Novel CAR Designs
AACR Annual Meeting 2021
Michel Sadelain, MD, PhD, of Memorial Sloan Kettering Cancer Center, discusses the challenges in developing CAR T-cell therapy, as well as the progress being made, such as creating hybrid CAR and T-cell receptors that should enable T cells to recognize much lower levels of antigens. The field, he says, is poised to take on a range of solid tumors to extend the successes in hematologic malignancies.
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
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
Carey K. Anders, MD, of the Duke Cancer Center, discusses the ways in which treatment of brain metastases arising from solid tumors has moved into a new era of patient care and how the field may advance.
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).
