A Study for Identification of Predictive Immune Biomarker in Peripheral Blood for Nivolumab Therapy in NSCLC Patients

Study Overview
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Brief Summary
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The study aimed to elucidate predictive immune related biomarker to the responsiveness to the PD-1 blockade and evaluate the dynamics of immune cells in peripheral blood from NSCLC patients during nivolumab treatment. Hypothesis that The ratio of MDSC after 1st or 2nd cycle can predict the response to nivolumab in NSCLC patients earlier than the tumor assessment by imaging scan. The primary objective is to determine whether myeloid-derived suppressor cell (MDSC) ratio after 1st or 2nd cycle of nivolumab can be accurate predictive biomarkers of nivolumab in advanced NSCLC.

Detailed Description
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Non-small cell lung cancer (NSCLC) is the leading cause of cancer related mortality worldwide. Immune checkpoint blockade has emerged as a promising treatment modality in NSCLC. More recently, Programmed Cell Death 1 (PD-1) inhibitor was approved by FDA as ≥ second line treatment, which are major paradigm shift in NSCLC treatment. Subsequently two randomized phase III trials, comparing the overall survival (OS) of nivolumab with that of docetaxel as second line therapy, were completed. CheckMate-017 included squamous cell lung cancer patients and CheckMate-057 did non-squamous cell lung cancer patients. In both trials, nivolumab showed improvement of OS in all-comers regardless of PD-L1 expression. As a result of retrospective analysis, PD-L1 positivity was not predictive factor for the efficacy in squamous cell histology, but predictive factor for non-squamous histology. Finally, nivolumab was approved the all-comer NSCLC patients regardless of PD-L1 expression after failure to platinum based chemotherapy. Although tumor PD-L1 expression is currently the best predictive biomarker for PD-1 blockades, the prediction accuracy is not high enough to solidify the drug efficacy. Actually, PD-L1 negative patients can still respond to PD-1 blockades and some of PD-L1 positive patients do not respond to these therapy. Interestingly, the responders among PD-L1 negative patients showed comparable duration of response in those with PD-L1 positive in Checkmate 057 trial. Therefore, we need to select patients who are most likely to benefit from anti-PD-1 therapy and identify the better biomarker to predict the response to PD-1 blockades in NSCLC patients earlier than tumor assessment by imaging scan. To maximize the benefit of nivolumab in NSCLC patients, nivolumab should apply to all-comers, but we need to early decide to go or stop depending on predictive biomarker after 1st or 2nd cycle. It is well known that various immune suppressive mechanisms including an accumulation and activation of myeloid derived suppressor cells (MDSC) and regulatory T cells (Tregs) exist in tumor microenvironment of cancer patients. MDSC are one of the major components of the tumor microenvironment, demonstrating their potentials, such as tumor progression by promoting tumor cell survival, angiogenesis, invasion of healthy tissue by tumor cells, and metastases. Recent studies show that MDSC as a heterogenous group of myeloid progenitors with immuno suppressive function could be used as one of the promising biomarker candidate for cancer immunotherapies. Ipilimumab could affect the immune cells in peripheral blood from melanoma patients. This study demonstrated that responder to ipilimumab showed early increase of eosinophil counts, whereas non-responders presented that elevated monocytic MDSC increased serum levels of S100A8/A9 and HMGB1 that attract and activate MDSCs. This result suggests that measurement of MDSCs could be a predictive immune related biomarker to ipilimumab treatment. On the other hand, we do not know how PD-1 blockade affects the immune suppressive cells such as MDSC or Tregs and makes difference between responder and non-responder. Recently, we conducted pilot trial to compare the T lymphocytes and MDSC population in peripheral blood between responder and non-responder to nivolumab. Interestingly, our preliminary data demonstrated that after 1st cycle of the therapy CD11b+CD33+MDSC/CD45+ or CD14- ratio has significantly decreased in responder compared to non-responder. The cut-off value of peripheral MDSC ratio could be reliable biomarker for accurate prediction of nivolumab therapy in NSCLC patients. To validate our finding, we need to expand this study in NSCLC patients who will be treated with nivolumab.

Official Title
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A Study for Identification of Predictive Immune Biomarker in Peripheral Blood for Nivolumab Therapy in NSCLC Patients

Conditions
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Non -Small Cell Lung Cancer

Intervention / Treatment
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* Other: nivolumab


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Age≥ 18 years old. Histologically confirmed advanced NSCLC Metastatic or recurrent stage Failed to previous platinum based chemotherapy Performance status of Eastern Cooperative Oncology Group 0 to 1. Adequate organ function At least one measurable lesion according to Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 criteria. Exclusion Criteria: Symptomatic or uncontrolled brain metastasis History of autoimmune disease Other primary cancer within 3 years

Ages Eligible for Study
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Minimum Age: 20 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Intervention/Treatment |
| --- |
|Other: nivolumab|Subjects will be treated with 3mg/kg in nivolumab IV every 2 weeks for a maximum of 12 months.|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| MDSC markers | CD11b, Gr11b, | change from baseline blood biomarker at 6 weeks or progression | 
| Changes of Tregs markers | FOXP3, CD25, CD127, CD45RA | A) Within 7 days before treatment (Pre-treatment) B) Every 2 weeks of treatment up to 3 cycles (every cycle is 2 weeks)C) Within 28 days after progression (post-treatment) | 
| T cell/NK cell marker | CD3, CD4, CD8, FoxP3, CD56 | A) Within 7 days before treatment (Pre-treatment) B) Every 2 weeks of treatment up to 3 cycles (every cycle is 2 weeks)C) Within 28 days after progression (post-treatment) | 
| Immune checkpoint molecules | PD-1, LAG-3, TIGIT etc. | A) Within 7 days before treatment (Pre-treatment) B) Every 2 weeks of treatment up to 3 cycles (every cycle is 2 weeks)C) Within 28 days after progression (post-treatment) | 
| serum levels of S100A8/A9 |  | A) Within 7 days before treatment (Pre-treatment) B) Every 2 weeks of treatment up to 3 cycles (every cycle is 2 weeks)C) Within 28 days after progression (post-treatment) | 
| HMGB1 |  | A) Within 7 days before treatment (Pre-treatment) B) Every 2 weeks of treatment up to 3 cycles (every cycle is 2 weeks)C) Within 28 days after progression (post-treatment) | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| ORR(Objective response rate) |  | every 6 months up to 5years. | 
| PFS (progression free survival) |  | every 6 months up to 5years. | 
| OS (overall survival) | Overall survival will be followed continuously while subjects are on the study drug and every 6 months after discontinuation or progression for up to 5 years. | every 6 months up to 5years. | 
| Adverse Event | Adverse Events as assessed by CTCAE v4.0 | up to 12 months | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Non -small cell lung cancer