ABSTRACT: Immunotherapies produce remarkable, long-term responses in subsets of patients with non-small cell lung cancer, but unfortunately, most patients do not respond to such treatment. Current biomarkers to predict which patients will benefit have limited accuracy, and decisions to continue or suspend treatment are mainly guided by monitoring of radiographic changes in tumor size. However, unusual immune-related response patterns such as pseudo-progression, mixed response, and delayed response can make scans difficult to interpret. Circulating tumor DNA (ctDNA) has emerged as a highly promising biomarker for monitoring immunotherapy efficacy. Several studies involving various immunotherapy agents and multiple types of cancer have demonstrated that early reduction in ctDNA levels during treatment are predictive of tumor response and improved survival outcomes. However, existing technologies that measure ctDNA by probing for common somatic mutations will fail in patients whose tumors lack these mutations. This limitation is being addressed by creating customized assays based on patient-specific tumor mutation profiles; but this approach is complex, expensive, and slow. We have developed a ctDNA assay technology based on detection of epigenetic features that are found in virtually all cancer cell genomes. Our Phase I data indicate that our approach has broad patient coverage and can be applied to multiple types of cancer without requiring tumor profiling and assay customization. In this Phase II project, we aim to build data to support the clinical utility of our assay technology for monitoring of lung cancer immunotherapy response. We also aim to advance our current research-mode assay to rigorous clinical- grade testing standards for use in clinical practice.

PROJECT NARRATIVE: Some lung cancer patients have robust and durable tumor responses to immunotherapy, whereas others derive no benefit from such treatment. A blood test that monitors for changes in the amount of tumor DNA in the circulation could help to distinguish responders from non-responders, thereby improving clinical outcomes in such patients.