Circulating tumor (ct)DNA may serve as an early predictor of treatment response with immune checkpoint inhibitors for patients with non-small cell lung cancer (NSCLC), researchers reported.
Mark Stewart, PhD, of Friends of Cancer Research in Washington, D.C., and colleagues assessed the role of ctDNA for monitoring response to immune checkpoint inhibitors through a standardized approach by examining clinical trial data from five independent studies. The results, published in JCO Precision Oncology, showed a strong association across different outcomes.
In the following interview, Stewart, who is vice president for Science Policy, leading the organization’s research and policy agenda as well as overseeing the conduct of research projects to inform ongoing policy discussions, reflected on the significance of the study.
What does the article add to the literature?
Stewart: A number of published reports have shown associations between changes in ctDNA and clinical outcomes in small, independent clinical trials. The goal of this study was to assess the feasibility of bringing together distinct datasets, develop methods for combining data, and evaluate whether we could observe similar findings when these data were aggregated into a single dataset.
The data included in this analysis were from patients with advanced NSCLC treated with an immune checkpoint inhibitor. The findings demonstrated that it is possible to bring together distinct datasets and harmonize around common features to demonstrate associations between changes in ctDNA and clinical outcomes.
This is ultimately an important step for generating the types of evidence needed to support the use of ctDNA as a surrogate or intermediate endpoint for regulatory decision-making about treatment response.
The article builds on the mounting data that changes in ctDNA are associated with clinical outcomes. Despite the heterogeneity that existed across the clinical trial datasets, including use of different diagnostic assays to measure ctDNA, eligibility criteria, ctDNA collection timepoints, and immune checkpoint inhibitors, we were able to account for these variables and show that results from different clinical trials can be harmonized.
This helps demonstrate the generalizability of data across studies and provides greater confidence that changes in ctDNA can predict clinical outcomes. Importantly, we identified ctDNA metrics that were strongly associated with various clinical outcomes — when ctDNA levels decrease while on treatment, patients had better outcomes whereas when ctDNA levels increased while on treatment, patients had worse outcomes.
How could ctDNA measurements help guide treatment decisions, either independently or in conjunction with radiographic evaluation?
Stewart: Use of surrogate endpoints in oncology drug development has helped accelerate the development and availability of breakthrough drugs for patients with serious and life-threatening disease. To facilitate robust drug development, particularly as investigation of new therapies accelerates into earlier lines of therapies where it can take much longer for traditional endpoints to readout, there is a need for new, validated surrogate endpoints that can provide earlier measures of treatment efficacy.
Additionally, in instances where a patient has non-measurable disease or a therapy leads to unusual patterns of response on imaging, radiographic imaging may need to be complemented with another objective measure like ctDNA. Use of ctDNA could provide patients greater access to clinical trials and improve interpretability of currently available endpoints for a wider range of therapeutic classes.
Our work to date has focused on evaluating the use of ctDNA as a novel endpoint for drug development, but one could imagine the use of ctDNA by patients and physicians to guide treatment decisions more quickly and accurately during routine care.
What is the importance of setting common standards for ctDNA evaluation?
Stewart: Having common standards can help maximize the data generated and lead to more generalizable data from clinical trials that are integrating ctDNA measurements. Past validation efforts of novel surrogate endpoints have shown that the quicker we can align definitions, study protocols, and establish performance metrics, the quicker we can validate its use for regulatory decision-making.
What is the next step in this research?
Stewart: Given that this study was set up as a proof of concept, we are currently expanding our analysis to look at other cancer types and drug classes.
We currently have de-identified patient-level data from 20 different clinical studies to investigate additional research questions that can help evaluate the use of ctDNA as a surrogate endpoint and inform optimal approaches for integrating ctDNA measurements into future clinical studies.
What’s your main message for practicing oncologists?
Stewart: ctDNA is a multifaceted biomarker that can provide meaningful information along a patient’s cancer journey using a minimally invasive procedure. FDA draft guidance has acknowledged the potential role of ctDNA as a surrogate endpoint for measuring treatment efficacy, but the guidance quickly notes that additional evidence is necessary to validate its use.
We need to couple the excitement associated with this emerging biomarker with robust evidence to fully realize its promise in cancer research and care. By working together, we can reach our goal in a more efficient and rapid manner.
Read the study here.