This is a observational study to investigate how the microbiome correlates with efficacy and toxicity of immune checkpoint inhibitors in patients with advanced cancer.
The gastrointestinal microbiome of a healthy individual is comprised of many hundreds of bacteria species and thousands of bacteria strains. The composition of bacteria in an individual's microbiome can change over time and this can be influenced by factors including diet, drugs, genetics and infection. These bacteria play a central role in digestion of food, development and regulation of our immune system as well as our resistance to pathogens. Recent evidence suggest that a patient's intestinal microbiota composition plays a critical, though as yet poorly defined, role in determining both therapeutic efficacy and likelihood of significant adverse events to T-cell checkpoint inhibitor immunotherapy. Immune checkpoint inhibitors are revolutionising treatment of many types of metastatic cancer, including melanoma, renal and non-small cell lung cancer, in the expectation of improving patient overall survival. However, they have limitations as they do not work for all patients and can cause unpredictable, complex immune-related toxicities. The investigators will perform a detailed study of cancer patients receiving checkpoint inhibitors. Saliva and a series of stool samples will be collected from each patient to analyse their microbiome and will be linked to treatment response, by examining blood samples and - if available - tumour and organ samples. The investigators hope this work will enable personalisation of patient immunotherapies based on microbiome biomarkers, as well as precisely manipulate a patient's microbiota to optimise their immunotherapy. In addition, participants who have consented to take part in an optional sub-study may be offered a single nasopharyngeal swab for COVID-19 antigen before study entry. The investigators hope that that this identify correlations between the microbiome and COVID-19. Comparison with a limited cohort of healthy household members (up to 360 volunteers) acting as controls will provide additional essential information about the role of the patient-specific microbiome.
Study Type
OBSERVATIONAL
Enrollment
1,800
A human immunoglobulin G4 (IgG4) monoclonal antibody, which binds to the programmed death-1 receptor (PD-1).
A human immunoglobulin G4-kappa (IgG4-kappa) monoclonal antibody that targets PD-1.
A human immunoglobulin G1 (IgG1) monoclonal antibody raised against cytotoxic T lymphocyte antigen-4 (CTLA-4).
Royal United Hospitals Bath NHS Foundation Trust
Bath, United Kingdom
RECRUITINGUniversity Hospitals Dorest NHS Foundation Trust
Bournemouth, United Kingdom
Can the microbiome signature predict progression-free survival (PFS) of 1 year or greater
The primary outcome measure is the ability to predict for PFS of 1 year or greater for patients with advanced melanoma, renal and non-small cell lung cancer (cohorts 1-6).
Time frame: Minimum 1 year PFS
Can the microbiome signature predict PFS
Measure the ability of the microbiome signature to predict 6 month PFS, 2 year PFS, overall response rate and median PFS in Cohorts 1-6.
Time frame: 1 year & 2 years PFS
Can the microbiome signature overall survival (OS)
Measure the ability of the microbiome signature to median OS in Cohorts 1-6.
Time frame: Up to 6 years
Can the microbiome signature to predict relapse
Measure the ability of the microbiome signature to predict for 1 or 2 year relapse after resection of high risk melanoma or renal cancer in cohorts 7-9.
Time frame: 1 year & 2 years relapse-free survival (RFS)
Does the microbiome correlate with treatment efficacy
To compare pre-treatment oral and gut microbiome findings and their association with treatment efficacy.
Time frame: Up to 6 years
Correlate microbiome findings with incidence and characteristics of immune-related adverse events
To correlate microbiome findings with incidence and characteristics of CTCAE V5-defined Grade 3 or greater immune-related adverse events in all enrolled cancer patients, and any association with response to immunosuppressants.
Time frame: Up to 6 years
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A human immunoglobulin G1-kappa (IgG1-kappa) monoclonal antibody that binds to programmed death ligand 1 (PD-L1).
A fully human monoclonal antibody raised to target cytotoxic T lymphocyte-associated antigen 4 (CTLA-4).
A humanised IgG1 monoclonal antibody raised to target programmed death-ligand 1 (PD-L1).
A humanised IgG1 monoclonal antibody raised to target vascular endothelial growth factor (VEGF).
University Hospitals Bristol NHS Foundation Trust
Bristol, United Kingdom
RECRUITINGCambridge University Hospitals NHS Foundation Trust
Cambridge, United Kingdom
RECRUITINGVelindre University NHS Trust
Cardiff, United Kingdom
RECRUITINGWestern General Hospital
Edinburgh, United Kingdom
RECRUITINGThe Queen Elizabeth Hospital King's Lynn NHS Foundation Trust
Kings Lynn, United Kingdom
RECRUITINGUniversity Hospitals of Leicester NHS Foundation Trust
Leicester, United Kingdom
RECRUITINGNorfolk and Norwich University Hospitals NHS Foundation Trust
Norwich, United Kingdom
RECRUITINGSheffield Teaching Hospitals NHS Foundation Trust
Sheffield, United Kingdom
RECRUITING...and 3 more locations
Correlation microbiome findings and known characteristics of patients
To correlate microbiome findings with aspects of pre-existing patient characteristics and behaviour including but not limited to diet, smoking history, BMI, use of antibiotics, steroids, proton pump inhibitors, non-steroidal anti-inflammatory drugs and probiotics.
Time frame: Up to 6 years
Control for the microbiome of cancer patients
To compare the microbiome signature of cancer patients with a household control group of people who are not known to have cancer.
Time frame: Up to 6 years
Build a library of biological samples for future research
To retain a library of biological samples (saliva, stool, blood and tumour as well as organ if available) with linked patient data for future research.
Time frame: Up to 6 years