New Insights From Genomic Classification Affecting Choice of Targeted Agents or Immunotherapy

October 10, 2019
Robert L. Ferris, MD, PhD

Targeted Therapies in Oncology, October 2019, Volume 8, Issue 13

At the recent <em>20th Annual </em>International Lung Cancer Congress&reg; in Huntington Beach, California, a number of very prominent contributors to the lung cancer translational and clinical field provided updates regarding novel strategies to address unmet needs.

Robert l. Ferris, MD, PhD

The transformation in cancertherapy between progress in genomic subclassification based on targetable alterations in oncogenic signaling pathways versus induction of neoantigens permitting successful cancer immunotherapy is perhaps nowhere more relevant and prevalent than in both non—small cell and small cell lung cancer (SCLC). At the recent20th AnnualInternational Lung Cancer Congress® in Huntington Beach, California, a number of very prominent contributors to the lung cancer translational and clinical field provided updates regarding novel strategies to address unmet needs. David R. Gandara, MD, reminded us that predictive, biomarker-driven trials will only be developed for both tyrosine kinase inhibitors (TKIs), as well as immune check- point inhibitors, if we can design clinical trials with integrated statistically robust biomarker companion assays. He indicated that 3 prerequisites for a more personalized approach would facilitate this development: tissue or blood-based profiling, linkage of predictive genomic biomarkers with targeted agents, and clinical trial designs with robust statistics to define the activity of a subset of individuals for the drug hitting its target. Some similarly designed trials include the Lung Cancer Master Protocol (Lung-MAP), an umbrella design study with substudies based on a genomic profile. There are proliferating and large prevalence cancers such as non—small cell lung cancer (NSCLC) that are well suited to drive patient selection and drug combinations. Certainly, acquired resistance may occur and sequential personalized, genomically-driven biomarker-oriented studies need to be designed.

Gandara also pointed out that combination therapies for lung cancer, particularly unless they are biomarker driven to detect smaller-effect sizes in the general population or greater—effect sizes in smaller subsets based on robust clinical trials, may lead to recruitment fatigue. Some PD-1/PD-L1 trials have seen decline in recruitment with these all-comer phase III designs that are not efficiently optimizing the benefit for selected populations. He strongly recommended that designing the trials to build in predictive biomarkers will advance the field of immunotherapy, much as the genomic biomarker-driven precision oncology field has done forALK- orEGFR-driven NSCLC. Indeed, new markers and alterations such asKRASare creating opportunities, which has long been difficult to target. Furthermore, the mutational burden subgroup may have immunotherapy combinations as well.