Longitudinal peripheral blood markers as dynamic predictors to identify efficacy and safety of patients treated with immune checkpoint inhibitors (ICIs)

Lead Investigator: Jian-Guo Zhou, The Second Affiliated Hospital of Zunyi Medical University
Title of Proposal Research: Longitudinal peripheral blood markers as dynamic predictors to identify efficacy and safety of patients treated with immune checkpoint inhibitors (ICIs)
Vivli Data Request: 6762, 5935
Funding Source: None
Potential Conflicts of Interest: None

Summary of the Proposed Research:

The immune system protects the body from illness by recognizing and killing invaders such as bacteria and viruses. It is tightly controlled by the immune checkpoint response to avoid fighting its own body (autoimmunity) while retaining the potential to fight off invaders. Immune checkpoint involves the initiation, boosting and dampening immune responses in a well-regulated spatio-temporal manner. However, cancer cells evade immune attack by harnessing the immune checkpoint, e.g. by expressing the programmed cell death ligand 1 (PD-L1) protein, which binds to the PD-1 receptor on T cells, to delude T cells into recognizing cancer as “self”. Hence, immune checkpoint inhibitors (ICIs) have been developed to prevent cancers from immune evasion. Due to its high specificity and low toxicity, ICI therapy has become popular in recent years. However, even though 46.3% of US cancer patients were considered eligible for ICI treatment as reported by a cross-sectional study in 2018, treatment response remained below 20%. Therefore, identifying biomarkers from blood will enable real-time disease monitoring to facilitate evaluation of ICI therapeutic efficacy. Hence, this study aims to use blood biomarkers as dynamic predictors to monitor treatment outcomes and decide treatment termination. To identify the optimal dynamic predictors, this study analyzes the correlation between blood biomarkers over the course of treatment and treatment outcomes of cancer patients undergoing ICI therapy from shared clinical datasets. The identified predictors will be subject to validation in future prospective studies. The goal is to apply these biomarkers in future clinical practice to improve ICI treatment outcomes.

Statistical Analysis Plan:

1. Freedom from composite endpoint will be assessed using Kaplan–Meier analysis, first for the full cohort, and then according to median biomarker candidate value. Groups will be compared by means of the log-rank test. To plot the average temporal patterns of peripheral blood biomarker candidates in patients with and without progression or death, we will use the linear mixed effect models.

2. Further analysis involves the Z-score (i.e. the standardized form) of the log2-transformed biomarkers to allow for direct comparisons of different biomarker candidates.

3. Next, the joint model will be applied to estimate the association between patient-specific candidate biomarker levels and the hazard of the OS and PFS. Joint modeling combines linear mixed effect models for the temporal evolution of the repeated measurements with Cox proportional hazard models for the time-to-event data.

Requested Studies:

A Phase III, Open-Label, Multicenter, Randomized Study to Investigate the Efficacy and Safety of Atezolizumab (Anti-PD-L1 Antibody) Compared With Chemotherapy in Patients With Locally Advanced or Metastatic Urothelial Bladder Cancer After Failure With Platinum-Containing Chemotherapy
Sponsor: Roche
Study ID: NCT02302807
Sponsor ID: GO29294

A Phase II, Multicenter, Single-arm Study of MPDL3280A in Patients With PD-L1-Positive Locally Advanced or Metastatic Non-small Cell Lung Cancer
Sponsor: Roche
Study ID: NCT01846416
Sponsor ID: GO28625

A Phase II, Multicenter, Single-Arm Study of Atezolizumab in Patients With Locally Advanced or Metastatic Urothelial Bladder Cancer
Sponsor: Roche
Study ID: NCT02951767
Sponsor ID: GO29293 (Cohort 1)

A Phase II, Multicenter, Single-Arm Study of Atezolizumab in Patients With Locally Advanced or Metastatic Urothelial Bladder Cancer
Sponsor: Roche
Study ID: NCT02108652
Sponsor ID: GO29293 (Cohort 2)

A Phase II, Multicenter, Single-Arm Study OF Atezolizumab In Patients With PD-L1-Positive Locally Advanced Or Metastatic Non-Small Cell Lung Cancer
Sponsor: Roche
Study ID: NCT02031458
Sponsor ID: GO28754

A Phase III, Open-Label, Multicenter, Randomized Study to Investigate the Efficacy and Safety of Atezolizumab (Anti-PD-L1 Antibody) Compared With Docetaxel in Patients With Non-Small Cell Lung Cancer After Failure With Platinum Containing Chemotherapy
Sponsor: Roche
Study ID: NCT02008227
Sponsor ID: GO28915

A Phase II, Randomized Study of Atezolizumab (Anti-PD-L1 Antibody) Administered as Monotherapy or in Combination With Bevacizumab Versus Sunitinib in Patients With Untreated Advanced Renal Cell Carcinoma
Sponsor: Roche
Study ID: NCT01984242
Sponsor ID: WO29074

A Phase II, Open-label, Multicenter, Randomized Study to Investigate the Efficacy and Safety of MPDL3280A (Anti−PD-L1 Antibody) Compared With Docetaxel in Patients With Non−Small Cell Lung Cancer After Platinum Failure
Sponsor: Roche
Study ID: NCT01903993
Sponsor ID: GO28753

The following study was added to the request February 7, 2022:

Phase III, Open-Label, Randomized Study of Atezolizumab (MPDL3280A, Anti-PD-L1 Antibody)in Combination With Carboplatin+Paclitaxel With or Without Bevacizumab Compared WithCarboplatin + Paclitaxel + Bevacizumab in Chemotherapy-Naïve Patients With Stage IV Non-Squamous Non-Small Cell Lung Cancer
Sponsor: Roche
Study ID: NCT02366143
Sponsor ID: GO29436

(Note: Additional studies added as part of Data Request 6762)

Phase 2 Study of Carboplatin, Etoposide, and Atezolizumab With or Without Trilaciclib in Patients With Untreated Extensive Stage Small Cell Lung Cancer
Data Contributor: Project Data Sphere
Study ID: NCT03041311
Sponsor ID: G1T28-05

A Randomized, Multicenter, Double-Blind, Placebo-Controlled Phase II Study of the Efficacy and Safety of Trastuzumab Emtansine in Combination With Atezolizumab or Atezolizumab-Placebo in Patients With HER2-Positive Locally Advanced or Metastatic Breast Cancer Who Have Received Prior Trastuzumab and Taxane Based Therapy
Data Contributor: Roche
Study ID: NCT02924883
Sponsor ID: WO30085

A Phase III, Open-Label, Randomized Study of Atezolizumab (Anti-PD-L1 Antibody) in Combination With Bevacizumab Versus Sunitinib in Patients With Untreated Advanced Renal Cell Carcinoma
Data Contributor: Roche
Study ID: NCT02420821
Sponsor ID: WO29637

A Phase III Multicenter, Randomized, Open-Label Study Evaluating the Efficacy and Safety of Atezolizumab (MPDL3280A, Anti-PD-L1 Antibody) in Combination With Carboplatin+Nab-Paclitaxel for Chemotherapy-Naive Patients With Stage IV Non-Squamous Non-Small Cell Lung Cancer
Data Contributor: Roche
Study ID: NCT02367781
Sponsor ID: GO29537

A Phase III, Open-Label, Multicenter, Randomized Study Evaluating the Efficacy and Safety of Atezolizumab (MPDL3280A, Anti-PD-L1 Antibody) in Combination With Carboplatin+Paclitaxel or Atezolizumab in Combination With Carboplatin+Nab-Paclitaxel Versus Carboplatin+Nab-Paclitaxel in Chemotherapy-Naive Patients With Stage IV Squamous Non-Small Cell Lung Cancer
Data Contributor: Roche
Study ID: NCT02367794
Sponsor ID: GO29437

A Multistage, Phase II Study Evaluating the Safety and Efficacy of Cobimetinib Plus Paclitaxel, Cobimetinib Plus Atezolizumab Plus Paclitaxel, or Cobimetinib Plus Atezolizumab Plus Nab-Paclitaxel as First-Line Treatment for Patients With Metastatic Triple-Negative Breast Cancer
Data Contributor: Roche
Study ID: NCT02322814
Sponsor ID: WO29479

CheckMate 038 study (NCT01621490): PH 1 Biomarker Study of Nivolumab and Ipilimumab and Nivolumab in Combination With Ipilimumab in Advanced Melanoma (PD-1); official name: An Exploratory Study of the Biologic Effects of Nivolumab and Ipilimumab Monotherapy and Nivolumab in Combination With Ipilimumab Treatment in Subjects With Advanced Melanoma (Unresectable or Metastatic);
Data Contributor: Bristol Myers Squibb
Study ID: NCT01621490
Sponsor ID: NCT01621490

BMS study CA209-026, https://clinicaltrials.gov/ct2/show/NCT02041533
Data Contributor: Bristol Myers Squibb
Sponsor ID: CA209-026

Public Disclosures:

  1. Zhou J, Wong AH, Wang H, et al. 329 Early blood cell count test (BCT) for survival prediction for non-small cell lung cancer patients treated with atezolizumab: integrated analysis of 4 multicenter clinical trials. Journal for ImmunoTherapy of Cancer 2021;9: doi: 10.1136/jitc-2021-SITC2021.329
  2. Zhou J, Yang J, Wang H, et al. Machine learning based on blood biomarkers predicts fast progression in advanced NSCLC patients treated with immunotherapy. Annals of Oncology (2022) 33 (suppl_2): S27-S70. doi: 10.1016/j.annonc.2022.02.069 
  3. Ma, SC., Bai, X., Guo, XJ., Liu, L., Xiao, LS., Lin, Y., Tan, JL., Cai, XT., Wen, YX., Ma, H., Fu, QJ., Leng, MX., Zhang, YP., Long, LL., Guo, ZQ., Wu, DH., Zhou, JG., Dong, ZY. Organ-specific metastatic landscape dissects PD-(L)1 blockade efficacy in advanced non-small cell lung cancer: applicability from clinical trials to real-world practice. BMC Med 20, 120 (2022). doi: 10.1186/s12916-022-02315-2
  4. Development and validation of longitudinal c-reactive protein as dynamic response predictor for PD-L1 blockade in advanced NSCLC: Findings from four atezolizumab clinical trials. Jian-Guo Zhou, Xiaofei Chen, Ada Hang-Heng Wong, Haitao Wang, Fangya Tan, Si-Si He, Gang Shen, YunJia Wang, Ruihong Wang, Shamus R. Carr, Benjamin Frey, Rainer Fietkau, Markus Hecht, Hu Ma, David S. Schrump, and Udo S Gaipl. Journal of Clinical Oncology 2022 40:16_suppl, e21113-e21113. doi: 10.1200/JCO.2022.40.16_suppl.e21113\
  5. Zhou, J.G., Wong, A.H.H., Wang, H., Tan, F., Chen, X., Jin, S.H., He, S., Shen, G., Wang, Y.J., Frey, B. and Fietkau, R. Elucidation of the application of blood test biomarkers to predict immune-related adverse events (irAEs) in atezolizumab-treated NSCLC patients by using machine learning methods. Frontiers in Immunology, p.3081. doi: 10.3389/fimmu.2022.862752
  6. Zhou J, Wong A, Wang H, Jin S, Tan F, Chen Y, He S, Shen G, Frey B, Fietkau R, Hecht M, Carr S, Wang R, Shen B, Schrump D, Ma H and Gaipl US(2022) Definition of a new blood cell count (BCT) score for early survival prediction for non-small cell lung cancer patients treated with atezolizumab: Integrated analysis of 4 multicenter clinical trials. Front. Immunol. 13:961926. doi:10.3389/fimmu.2022.961926
  7. Zhou, J.G., Yang, J., Wang, H., Wong, A.H.H., Tan, F., Chen, X., Shen, G., Wang, Y.J., Frey, B., Fietkau, R. and Hecht, M., Machine Learning Based on Blood Test Biomarkers Predicts Fast Progression in Advanced NSCLC Patients Treated with Immunotherapy. Doi: 10.1136/bmjonc-2023-000128