NCT07396259

Predicting Clinical Efficacy of Immunotherapy Using Pre-treatment andContinuousMonitoring of PD-L1 TPS/CPS on CTCs, and Immunity Exhaustion Scores

Dynamically Predicting Clinical Efficacy of Immunotherapy Using Pre-treatment andContinuousMonitoring of PD-L1 TPS/CPS on CTCs, and Immunity Exhaustion Scores - AProspectiveBiomarker Study

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 150 (estimated)
• Sponsor: Chang Gung Memorial Hospital · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Accepted

Summary

Head and neck cancer is ranked among the fifth to eighth most prevalent cancers worldwide and is associated with a high mortality rate. Immunotherapy has been established as the first-line standard of care for recurrent and metastatic head and neck cancer. However, patient selection is currently guided by the histological Combined Positive Score (CPS) (KN-048) or Tumor Proportion Score (TPS) (KN-040). A significant limitation is the inability to re-test tumor tissue when disease status changes necessitate therapeutic adjustment, as new tissue is often unavailable. Consequently, liquid biopsy, which allows for repeatable testing and thus constitutes a dynamic biomarker, becomes crucial. Nevertheless, its definitive role in predicting the efficacy of IT has yet to be thoroughly investigated. In this study, our team endeavors to define the CPS score of peripheral circulating tumor cells (CTCs) and evaluate the predictive ability of CTC TPS/CPS for clinical response, using objective clinical outcomes as the ultimate measure.

Detailed description

Head and neck cancer ranks as the fifth to eighth most common cancer globally and is associatedwitha high mortality rate. Since the publication of the KEYNOTE-048 study in 2019, immunotherapyhasbecome the first-line standard treatment for recurrent and metastatic head and neck cancer. However,selecting the appropriate patient population requires CPS (KEYNOTE-048) or TPS (KEYNOTE-040)scores based on tissue samples. Unfortunately, obtaining updated tissue samples can be challenging,especially when disease status changes necessitate treatment adjustments. This is where theimportanceof liquid biopsies as dynamic biomarkers becomes increasingly evident. However, there is still alackofin-depth research on whether liquid biopsies can genuinely predict the efficacy of immunotherapy. According to international consensus, TPS (Tumor Proportion Score) is defined as thenumberofcancer cells expressing PD-L1 divided by the total number of cancer cells, which canbeeasilydetermined using simple immunofluorescence staining. CPS (Combined Positive Score) is definedas100 x \[(Number of CTCs expressing PD-L1)+(Number of immune cells expressing PD-L1)\]/(CTCnumbers). Thus, analyzing CPS requires staining peripheral immune cells in CTCsamples. Thereisnoconsensus on which immune cells should be included in the analysis. This study aims to definetheCPSscore for peripheral CTCs and evaluate the predictive capability of CTC TPS/CPS in correlatingwithclinical response. Our team conducted a preliminary analysis of PD-L1 expression in CTC samples toexaminethehypothesis. It investigated the correlation between CPS/TPS expression in CTCs versus PD-L1incancer tissue in early 2024. The results showed a high degree of correlation, indicatingthatthemethodology of this study (CTC TPS and CTC CPS) is feasible. With slight adjustments tobetteralignwith clinical responses, this approach can be practically applied to head and neck cancer patientswhoare about to undergo immunotherapy, thus demonstrating the high feasibility of our research. Therefore, this three-year proposal aims to answer the following important questions: Is thereahighcorrelation between tissue and CTC PD-L1 expression in head and neck cancer patients, andcanitbecalibrated according to actual clinical immunotherapy responses? (2) What is the relationshipbetweenCTC PD-L1 expression and immune exhaustion markers in head and neck cancer patients (hostvs.cancer biomarkers)? (3) Can we establish a dynamic model that continuously predicts andcorrelateswith clinical responses?

Conditions

• Circulating Tumor Cells (CTCs)
• Immunotherapy
• PD-L1 Expression
• Liquidbiopsies

Timeline

• Start date: 2025-02-25
• Primary completion: 2030-12-31
• Completion: 2030-12-31
• First posted: 2026-02-09
• Last updated: 2026-02-09

Locations

1 site across 1 country: Taiwan