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Prior CTLA-4 Inhibition May Influence Response to PD-1 Inhibitors in Patients With Advanced Melanoma


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Researchers have found that responses to PD-1 inhibitor treatment in patients with advanced melanoma may depend on whether they had received previous treatment with CTLA-4 inhibitors, according to a new study published by Campbell et al in Cancer Cell.

“In our large set of data, features that have been used to predict responses to PD-1 [inhibitor] therapy—often called biomarkers—related to the presence of certain immune cell types in the tumor and the genetic profile of the tumors themselves were modified by a patient’s treatment history,” emphasized lead study author Katie Campbell, PhD, a postdoctoral research fellow in the Department of Hematology/Oncology at the University of California, Los Angeles (UCLA) Jonsson Comprehensive Cancer Center.

Background

Typical treatments for patients with advanced melanoma include immunotherapies such as PD-1 inhibitors and CTLA-4 inhibitors, either in combination or as monotherapies.

“As translational scientists, when we work with clinicians, one of the goals is to think about how biomarkers can be used to inform clinical benefit. If we can predict which patients are or are not going to respond to therapy from studying their biopsies, we can start to more strategically define which therapies or combinations of therapies should be used and when,” explained co–senior study author Antoni Ribas, MD, PhD, Professor of Medicine, Surgery, and Molecular and Medical Pharmacology; Director of the Tumor Immunology Program at the Jonsson Comprehensive Cancer Center; and Director of the Parker Institute for Cancer Immunotherapy Center at UCLA.

Although immunotherapy is becoming increasingly common in treating late-stage cancers, most studies on biomarkers and factors determining treatment effectiveness are based on small series of samples.

Study Methods and Results

In the new study, the researchers conducted an analysis of seven datasets generated over the past decade—which included tumor biopsy results from over 500 patients with melanoma—and assembled and harmonized a large set of tumor and clinical data in order to identify key factors associated with treatment responses.

“The cohesive processing of clinical data sets requires collaboration among experts with knowledge in computer science, statistics, biology, immunotherapy, informatics, and translational and clinical medicine. We undertook this project to establish a resource for other researchers, with the goal of identifying statistically significant correlations of melanoma responses to PD-1 [inhibitor] therapy,” Dr. Campbell noted. “As we performed the analyses, the greatest differences were seen when we accounted for a patient’s prior treatment with CTLA-4 [inhibitors]. [T]he context in which a biopsy is collected needs to be considered to better define how biomarkers should be implemented in the clinical setting,” she underscored.

By processing the DNA and RNA sequencing data on one cohesive pipeline from the patients involved in the study, the researchers were able to control for some of the differences across patients, tumors, and treatment histories. They also considered clinical demographics that may be important for understanding why a patient did or did not respond to PD-1 inhibitors.

Conclusions and Next Steps

Although the findings did not specifically explain how or when to clinically apply the biomarker information, they provided a foundation and a road map for future research.

The researchers suggested that their work has provided a single, cohesive genomic reference dataset that may identify the molecular characteristics associated with either treatment response or resistance—and could potentially further help researchers understand the molecular and clinical stratification of advanced melanoma.

“Since the current treatment paradigm for melanoma involves combinations or sequential use of immune checkpoint [inhibitors], our study supports how these therapies may work together to effectively treat melanoma. It also highlights the importance of a patient’s prior treatment history as a modifying factor to consider when planning a treatment strategy,” Dr. Ribas concluded.

Disclosure: The research in this study was supported by Bristol Myers Squibb and the REVIVE program at the Parker Institute. Additional funding was provided by grants from the National Institutes of Health. For full disclosures of the study authors, visit cell.com.

The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.
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