Biomarkers of Response to Combination Cabozantinib + Nivolumab in Advanced Renal Cell Carcinoma
Abstract
The treatment of advanced kidney cancer has undergone significant changes in the last two decades, beginning with the introduction of tyrosine kinase inhibitors (TKIs), a class of drugs that inhibit multiple tyrosine kinases including the VEGF receptors, and followed by checkpoint inhibitor therapy, a form of cancer immunotherapy that helps the body recognize and attack cancer cells. The current front-line management of patients diagnosed with advanced kidney cancer involves the combination of TKIs and/or immunotherapy in the hopes of maximizing patients survival. The tremendous improvement in the treatment of kidney cancer due to the advent of such therapies is, unfortunately, not applicable to all patients. The dire consequences of not knowing which tumors are likely to respond include experiencing side-effects during treatment despite not deriving benefit from it, becoming burdened with the undue financial cost of drugs, and experiencing substantial anxiety throughout the trial-and-error treatment experience. To overcome such shortcomings, researchers and clinicians hope to develop tools that can help identify patients prior to starting treatment that are more likely to respond to a certain combination therapy (e.g., checkpoint inhibitor therapy combined with TKI), thereby sparing patients who are unlikely to respond to the ordeal of unnecessary treatment, prevalent toxic side-effects of treatment, and high costs associated with therapy. Our team has previously worked toward this objective by attempting to replicate the association of various markers with outcome (e.g., survival) using tumor specimens obtained from participants enrolled in clinical trials treated with immunotherapy in the second-line setting, meaning that they had previously been treated with another therapy. In the current work, we hope to once again reconsider some of these previously identified markers from the second-line setting and assess their association with a clinical outcome using tumor specimens obtained from participants enrolled in trials that were treated with immunotherapy and TKI who had never received any other treatment following a kidney cancer diagnosis (i.e., in the first-line setting). Ultimately, the proposed work would not only grant clinicians and patients the possibility of developing a reliable tool, called a predictive biomarker, that can pre-emptively select (or unselect) patients for specific immunotherapy-based treatment, it will also provide researchers and clinicians an opportunity to better understand kidney cancer cells and the tumor microenvironment. The tumor microenvironment is the environment around a tumor, including the surrounding blood vessels, infiltrating inflammatory cells, and a variety of associated tissue cells. The tumor and the surrounding microenvironment are closely related and interact constantly, and, therefore, understanding how a treatment is effective against a tumor also needs to consider the treatment s impact on the tumor s unique environment. From a worldwide perspective, both the U.S. Food and Drug Administration and the European Medicines Agency (EMA) are encouraging the development of biomarkers as companion diagnostics in general practice. From the economical burden and cost-effectiveness point of view, there is a clear and compelling argument to develop and test biomarkers that can be accurately and safely used in clinical practice to identify the responsive subpopulation. While a handful of biomarkers have reached clinical practice in other cancers, there is currently no predictive biomarker designed for treatment management decisions in kidney cancer. In other cancers, the identification, development/identification, and validation/reconfirmation of biomarkers based on rigorous scientific studies and tested in focused, well-designed clinical trials allowed more efficient clinical development, as well as an associated reduced failure rates of drug development. For the k
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 28, 2022
- Source ID
- W81XWH2210523
Entities
People
- Sabina Signoretti
Organizations
- United States Army