A clinical trial identifying exosome protein biomarkers in patients with advanced hormone receptor-positive breast cancer treated with palbociclib and tamoxifen
WHO:
Dr. Kent Hoskins
Associate Professor, University of Illinois College of Medicine
Director, UIC Familial Breast Cancer Program at UI Health
Co-chair, Breast Cancer Clinical Trial Working Group, Big Ten Cancer Research Consortium
Member, University of Illinois Cancer Center, Translational Oncology Program
Dr. Oana Danciu
Associate Professor, Hematology/Oncology, University of Illinois College of Medicine
Associate Director for Clinical Research, University of Illinois Cancer Center
Director, Clinical Trials Office, University of Illinois Cancer Center
Steering Committee Member, Big Ten Cancer Research Consortium
Yu “Tom” Gao, PhD
Assistant Professor, Pharmaceutical Sciences, University of Illinois Chicago College of Pharmacy
Member, University of Illinois Cancer Center, Translational Oncology Program
Serving as principal investigator, Danciu designed the clinical trial and provided samples, while Hoskins led the trial’s correlative science working with University of Illinois Cancer Center member Tom Gao, PhD, and his lab. In addition to the University of Illinois Cancer Center, the clinical trial was conducted at multiple Big Ten Cancer Research Consortium sites: Penn State Cancer Institute; Masonic Cancer Center, University of Minnesota; Breslin Cancer Center, Michigan State University; Fred and Pamela Buffet Cancer Center, University of Nebraska; Carbone Cancer Center, University of Wisconsin; and Rutgers Cancer Institute of New Jersey.
WHAT:
Combining palbociclib – a CDK 4/6 inhibitor that blocks certain molecules involved in promoting the growth of cancer cells – with endocrine therapy (ET) doubles a patient’s survival time from clinical trial initiation to disease progression or death from any cause compared with ET alone in hormone receptor-positive, advanced breast cancer. Not all patients, however, respond, and those who do eventually develop resistance and disease progression.
Over the past decade, researchers have discovered that exosomes – membrane-bound extracellular vesicles that are released from tumors into the bloodstream that contains proteins and other molecules derived from the tumor – can promote tumor development and progression. Through his research, Hoskins provided analysis of exosome cargo which can provide a “dynamic and functional read-out of biological pathways that are activated in cancer cells.”
HOW:
By examining differences in the protein content of exosomes prior to treatment, Hoskins, Gao and his laboratory were able to predict which tumors are likely to respond to the treatment and which patients are unlikely to respond, “which if confirmed in larger studies could lead to development of biomarkers to improve the selection of patients for this treatment,” he said.
Hoskins and Gao utilized single-cell mass spectrometry, a powerful new technique for proteomic analysis, to examine the exosomes. By examining the differences in the exosomes protein content prior to treatment, “we were able to predict which tumors are likely to respond to the treatment and which patients weren’t. Should this be confirmed in larger studies, it could lead to developing biomarkers to improve the selection of patients for this treatment,” he said. “We will continue to use this proteomic approach to identify the mechanisms of drug resistance that emerge in the cancer cells as they are exposed to these medications.”
FINDINGS:
More than 700 exosome proteins were discovered in the blood samples. Significant enrichment of exosome-specific markers were observed when comparing patient samples with healthy donor samples. Exosomal protein networks in pretreatment samples predicted treatment response with 95% sensitivity and 85% specificity in unsupervised clustering.
Ultra-sensitive proteomic analysis combined with deep learning methods provides a detailed picture of the proteome landscape of plasma exosomes in advanced breast cancer patients and is ideally suited for serial analyses to study the emergence of resistance mechanisms, Hoskins said. The approach also demonstrated unparalleled accuracy as a predictive biomarker to identify patients unlikely to respond to CDK 4/6i and ET.
“Samples collected over the course of a trial are a valuable resource to identify mechanisms of drug resistance that develop in the tumor during study treatment,” Hoskins said. “This can provide important insight into new approaches to prevent the emergence of resistance to treatment.”