NEUTROFLOW: Development and Validation of a Pan-cancer Neutrophil Biomarker Test for Predicting Clinical Benefit From Immunotherapy Based on Flow Cytometry Analysis of Blood Samples
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 600
- 试验地点
- 3
- 主要终点
- Quantification of Ly6E high (Ly6Ehi) neutrophils in blood using the NeutroFlow flow cytometry assay
研究概览
简要总结
The NeutroFlow study is a multi-center clinical trial designed to develop a computational model that converts flow cytometry results into a prediction of clinical benefit. The study analyzes Ly6Ehi neutrophils in biological samples from patients treated with immune checkpoint inhibitors to evaluate their likelihood of benefiting from treatment. Blood samples are collected prior to treatment and used to support the ongoing development of the algorithm.
详细描述
The recent introduction of cancer immunotherapy based on immune checkpoint inhibitors (ICIs) has revolutionised the treatment landscape for a broad range of cancer types. However, response to ICIs varies widely between patients, with the majority experiencing resistance to therapy. Moreover, the increasing use of these costly drugs coupled with management of ICI-related toxicities creates a substantial economic burden. Current biomarker tests for determining eligibility for ICIs have limited predictive performance, and many require invasive tumour biopsies. Thus, novel (and preferentially non-invasive) biomarkers for predicting ICI clinical benefit are desperately needed for better guiding clinical decisions. NeutroFlow directly addresses this unmet need. The neutroFlow study is based on a comprehensive academic research describing a flow cytometry assay for measuring a novel predictive biomarker in the blood - Ly6Ehi neutrophil - that accurately predicts therapeutic benefit from ICIs, outperforming the approved PD-L1 biomarker.
The objective of the NeutroFlow study is to develop a clinical decision-support tool that includes an antibody panel for detecting Ly6Ehi neutrophils using standard flow cytometry (FC) and a computational model that converts the FC readout into a prediction of clinical benefit.
Patients will provide a single blood sample before starting treatment, and clinical data will be collected from their medical records.
In the first phase of the trial, blood sample data and clinical information will be used to develop the antibody panel and train the prediction algorithm. In the second phase, the algorithm will be validated by comparing its theoretical predictions with the patients' actual objective response rates.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients newly diagnosed with advanced-stage/metastatic NSCLC, melanoma, HNSCC, RCC, or TNBC, who are due to receive first-line treatment with a PD-(L)1 inhibitor, either as monotherapy or in combination with other agents, according to current standard-of-care regimens, including (but not limited to) the following approved options: NSCLC. Monotherapy: Pembrolizumab, Atezolizumab, Cemiplimab. Combination: Pembrolizumab + chemotherapy; Nivolumab + Ipilimumab; Cemiplimab + chemotherapy; Atezolizumab + chemotherapy + Bevacizumab.
- •Melanoma. Monotherapy: Nivolumab, Pembrolizumab. Combination: Nivolumab + Ipilimumab; Nivolumab + Relatlimab.
- •HNSCC. Monotherapy: Pembrolizumab, Cemiplimab. Combination: Pembrolizumab + chemotherapy.
- •RCC. Combination only: Nivolumab + Ipilimumab; Nivolumab + Cabozantinib; Pembrolizumab + Lenvatinib or Axitinib; Avelumab + Axitinib.
- •TNBC. Combination only: Pembrolizumab + chemotherapy.
- •Male or female aged at least 18 years
- •ECOG PS: 0/1-2
- •Normal hematologic, renal and liver function:
- •Absolute neutrophil count > 1500/mm³ Platelets > 100,000/mm³ Hemoglobin > 9 g/dL Creatinine concentration ≤ 1.4 mg/dL, or creatinine clearance > 40 mL/min, Total bilirubin < 1.5 mg/dL ALT + AST levels ≤ 3 times above the upper normal limit
排除标准
- •Any concurrent and/or other active malignancy that has required systemic treatment within 2 years of the first dose of treatment.
- •For NSCLC: presence of activating EGFR, ALK, ROS1, RET, NTRK alterations linked to an approved first-line targeted drug.
结局指标
主要结局
Quantification of Ly6E high (Ly6Ehi) neutrophils in blood using the NeutroFlow flow cytometry assay
时间窗: Baseline (up to 1 month before treatment initiation)
Peripheral blood samples will be collected from patients up to 1 month prior to treatment initiation. Ly6Ehi neutrophil populations will be quantified using the NeutroFlow multiparametric flow cytometry assay
Prediction of clinical benefit rate using baseline Ly6Ehi neutrophils levels
时间窗: Baseline (blood draw) to 6, 12, 18, and 24 months post treatment initiation
The patients clinical benefit (CB) will be defined according to RECIST 1.1 criteria to one of the following categories: complete response (CR), partial response (PR), or stable disease (SD). Baseline Ly6Ehi neutrophil levels will be used as input in a computational predictive model to estimate the likelihood of CB for each patient. The model will be trained and validated with independent patient cohorts, using cross-validation and ROC AUC metrics to assess predictive performance. Sensitivity, specificity, positive predictive value, and negative predictive value will also be calculated. Predictions will be assessed at multiple timepoints: 6, 12, 18, and 24 months post-initiation of anti-PD-(L)1 therapy. Subgroup analyses will include age, sex, cancer type, disease stage, and treatment line.
次要结局
- Clinical benefit rate across individual cancer types(Baseline to 6, 12, 18, and 24 months post treatment initiation (per indication))
- Clinical benefit rate by PD-(L)1 treatment regimen(Baseline to 6, 12, 18, and 24 months post treatment initiation)
- Correlation between Ly6Ehi neutrophil levels and PD-L1 status (TPS/CPS)(Baseline (PD-L1 and neutrophils assessed prior to treatment))
- Correlation between Ly6Ehi neutrophil levels and other clinical response-associated parameters(Baseline (clinical parameters collected prior to treatment))