The Effect of the Microbiome on Immune Checkpoint Inhibitor Response in Melanoma Patients
Study Details
Study Description
Brief Summary
This pilot trial studies the effect of the microbiome on immune checkpoint inhibitors response in patients with melanoma by collecting stool and blood samples. Gut microbiome plays a critical role in response to immune checkpoint inhibitors. Studying the change in an individual's microbiome due to corticosteroid use may help researchers to determine whether an individual's microbiome can predict their response and toxicity to immune checkpoint inhibitors.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
|
Detailed Description
PRIMARY OBJECTIVE:
- To determine if the microbiome alpha-diversity is predictive of response (Response Evaluation Criteria in Solid Tumors [RECIST] version [v] 1.1) at a 12-week computed tomography (CT) scan or toxicity.
SECONDARY OBJECTIVE:
- To determine the recruitment and compliance rates for longitudinal biospecimen collection, including stool, in melanoma patients.
EXPLORATORY OBJECTIVE:
- To determine if individual microbes or their changes in relative abundance are predictive of response or toxicity.
OUTLINE:
Patients complete a Food Frequency Questionnaire (FFQ) at baseline, undergo collection of stool samples at baseline, within 2 days of starting corticosteroid treatment (if applicable), when asked for a control sample, and at 12 weeks, and undergo collection of blood samples and computed tomography (CT) at baseline and 12 weeks.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Ancillary-correlative (questionnaire, sample collection, CT) Patients complete a FFQ at baseline, undergo collection of stool samples at baseline, within 2 days of starting corticosteroid treatment (if applicable), when asked for a control sample, and at 12 weeks, and undergo collection of blood samples and CT at baseline and 12 weeks. |
Procedure: Biospecimen Collection
Undergo collection of blood and stool
Other Names:
Procedure: Computed Tomography
Undergo CT
Other Names:
Other: Laboratory Biomarker Analysis
Correlative studies
Other: Questionnaire Administration
Complete questionnaire
|
Outcome Measures
Primary Outcome Measures
- Baseline microbiome alpha diversity in responders versus (vs) non-responders [At 12 weeks]
This analysis will follow a logistic regression structure. The dependent variable, response to treatment, will be evaluated using standardized criteria (Response Evaluation Criteria in Solid Tumors [RECIST] version [v] 1.1). Each patient will be classified as "respond", "stable" or "progression'' as a categorical variable and then binarized, with "respond" or "stable" in the category "responders", and "progression" in the category "non-responders". Independent variables will be alpha-diversity. Additional covariates will be included in the model to control for differences in age, sex, body mass index (BMI), Food Frequency Questionnaire (FFQ) dietary index, and medication history.
- Baseline microbiome alpha diversity in patients prescribed corticosteroids vs those who were not prescribed corticosteroids [Within the 12-week treatment window]
This analysis will follow a logistic regression structure. The dependent variable, toxicity, will be evaluated by corticosteroid prescription. Dependent variables including alpha-diversity or individual microbes will be independent variables.
Secondary Outcome Measures
- Recruitment rates for longitudinal biospecimen collection, including stool, in melanoma patients [12 weeks]
Recruitment rates will be defined as the fraction of screened adults who are eligible and agree to participate within the Cutaneous Oncology Clinic, with an estimated recruitment of 30%. Will track the monthly collection of data and documented reasons for missing any scheduled collection dates. The recruitment rate will be used in combination with the variance of the biospecimen data in power calculations to estimate the sample size needed for future trials.
- Compliance rates for longitudinal biospecimen collection, including stool, in melanoma patients [12 weeks]
Compliance will be defined as 90% of baseline, endpoint and corticosteroid collection. Will track the monthly collection of data and documented reasons for missing any scheduled collection dates. The compliance rate will be used in combination with the variance of the biospecimen data in power calculations to estimate the sample size needed for future trials.
Other Outcome Measures
- Microbes as significant predictors in logistic regressions where the outcomes are binary (clinical response or treatment toxicity requiring corticosteroids), with the inputs as relative abundances of individual microbes [At baseline, 12 weeks, or at corticosteroid prescription]
Individual microbe relative abundances will be compared between responders and non-responders with additional filtering to accommodate the sparseness of the microbiome data matrix. Specifically, microbes will be compared that are the most abundant, as well as being present in greater than 50% of the samples. An arcsine root transformation will be applied to the microbe relative abundances to approximate a Gaussian distribution, and then a generalized linear model applied where ''response'' is the response variable and individual microbes are the predictor variables. P-values will be corrected by the Bonferroni method and then visualized by volcano plot. Microbes and covariates found to be most significant in the model will be combined into a single model to estimate the percent variance explainable by these predictors. Analyses will be performed in R using the stats package.
Eligibility Criteria
Criteria
Inclusion Criteria:
- Eligible patients include adults with stage III, IV melanoma, to be treated with pembrolizumab or nivolumab, regardless of other concurrent therapy or line of treatment
Exclusion Criteria:
- Patients will be excluded if they are undergoing active systemic or oral corticosteroid use at start of immune checkpoint inhibitors (ICI) cycle 1, with the exception of adrenal replacement dosing.
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Ohio State University Comprehensive Cancer Center | Columbus | Ohio | United States | 43210 |
Sponsors and Collaborators
- Ohio State University Comprehensive Cancer Center
Investigators
- Principal Investigator: Daniel Spakowicz, PhD, Ohio State University Comprehensive Cancer Center
Study Documents (Full-Text)
More Information
Publications
None provided.- OSU-19125
- NCI-2020-01625