Suresh S. Ramalingam, MD, FACP, FASCO / Arjun Balar, MD / Yelena Janjigian, MD - Revisiting PD-L1 as an Immunotherapy Biomarker Across the Cancer Spectrum: Current and Emerging Standards of Testing, Scoring, and Assay Interpretation


Manage episode 295511082 series 2771425
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Go online to to view the activity, download slides and practice aids, and complete the post-test to earn credit. Cancer immunotherapies have transformed the treatment of many tumors. With the remarkable expansion of checkpoint inhibitors and combinations across the cancer spectrum, reliable predictive biomarkers are essential to guide clinical decisions about treatment selection. PD-L1 expression is the most established immunotherapy biomarker, and several others are in clinical use or showing promise. However, many research questions and practical challenges remain about biomarker testing, scoring, and interpretation in different tumors to identify patients who are most likely to benefit from cancer immunotherapies. This PeerView Clinical and Laboratory Accelerator based on a recent web broadcast provides practical guidance for navigating the complexities of cancer immunotherapy biomarker testing. Oncology and pathology experts focus on the nuances of PD-L1 expression assessment, along with other relevant biomarkers, in different solid tumors and how to use this information to direct clinical decisions regarding treatment selection for appropriate patients. Ongoing research efforts and innovations to refine and expand the role of cancer immunotherapy biomarkers are explored as well. Upon completion of this accredited CE activity, participants should be better able to: Assess the latest evidence on PD-L1 as a pan-tumor biomarker and the rationale for its use to predict benefit from cancer immunotherapies, Analyze practical considerations and complexities of PD-L1 biomarker testing and interpretation, including benefits/limitations of different testing methodologies/platforms/assays, standardization/harmonization options, cut points, digital pathology, artificial intelligence/machine learning, and other nuances, Incorporate the latest evidence and recommendations for PD-L1 biomarker testing in clinical and laboratory settings across tumor types, Integrate appropriate strategies for interdisciplinary collaboration and coordination among all members of the healthcare team to optimize the selection and interpretation of PD-L1 biomarker testing to guide clinical decision-making.

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