Sidney Kimmel Cancer Center at Thomas Jefferson University
Philadelphia, Pennsylvania, 19107, United States
NCT Number: NCT03618654
This pilot phase I trial studies how well durvalumab given with or without metformin works in treating participants with head and neck squamous cell carcinoma. Monoclonal antibodies, such as durvalumab, may interfere with the ability of tumor cells to grow and spread. Metformin, a drug typically used for the treatment of diabetes, may help to reduce the metabolic activity of cancer cells and of surrounding supportive tissues. It is not yet known whether giving durvalumab with or without metformin may work better in treating participants with head and neck squamous carcinoma.
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Notify Me18 year and older
All sexes
Interventional
Early Phase 1
Philadelphia, Pennsylvania, 19107, United States
PRIMARY OBJECTIVES:
I. To investigate the combined effect of metformin and durvalumab on the immune tumor microenvironment, specifically with respect to alterations in T cell polarization (Th1/Th2 ratio) and tumor associated macrophage (TAM) (M1/M2 ratio) as measured by cytokine shifts in tumor specimens and peripheral blood.
SECONDARY OBJECTIVES:
I. To investigate the combined effect of metformin and durvalumab on the metabolic microenvironment, specifically with respect to alterations in immunohistochemical markers of the reverse Warburg effect.
II. To further characterize the alterations in intratumoral immune cell populations (effector T cells [Teff], regulatory T cells [Tregs], tumor associated macrophages [TAMs], and myeloid-derived suppressor cells [MDSC]).
III. To assess changes of the intratumoral immunophenotype and metabolism after exposure to durvalumab and metformin by transcriptome analysis using a ribonucleic acid-sequencing (RNA-seq) transcriptome analysis.
IV. To assess the efficacy of combined durvalumab and metformin treatment prior to surgery as determined by radiographic response and immune-related response criteria (irRC).
V. To assess the safety and tolerability of the combination of metformin and durvalumab.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Given PO
Other names: 1,1-Dimethylbiguanide, 657-24-9, N,N-Dimethylimidodicarbonimidic Diamide
Given IV
Other names: Imfinzi, Kappa-chain, Human Monoclonal MEDI4736 Heavy Chain, MEDI4736, Immunoglobulin G1
Time frame: Up to 6 months
The biomarker data will be compared for differences in means (or geometric means) between treatment arms using Student's t-tests on the raw data (or on log-transformed data depending on the degree and nature of skew in the data). Non-parametric alternatives, such as permutation tests, will be considered if the data are not approximately normal for any continuous outcome variables after log-transformation. A similar approach will be used for making pre vs. post treatment comparisons, when necessary, but with paired t-tests or their non-parametric alternatives. The response outcomes will be evaluated between treatment arms by Fisher's exact tests.
Time frame: Up to 6 months
Pre- and post-treatment patient tumor samples will be compared. The study will compare data from patients treated with durvalumab and metformin to patients treated with Durvalumab alone and to patients from our own historical controls of head and neck squamous carcinoma (HNSCC), both untreated and treated with metformin monotherapy
Time frame: Up to 6 months
The biomarker data will be compared for differences in means (or geometric means) between treatment arms using Student's t-tests on the raw data (or on log-transformed data depending on the degree and nature of skew in the data). Non-parametric alternatives, such as permutation tests, will be considered if the data are not approximately normal for any continuous outcome variables after log-transformation. A similar approach will be used for making pre vs. post treatment comparisons, when necessary, but with paired t-tests or their non-parametric alternatives.
Time frame: Baseline up to 6 months
The biomarker data will be compared for differences in means (or geometric means) between treatment arms using Student's t-tests on the raw data (or on log-transformed data depending on the degree and nature of skew in the data). Non-parametric alternatives, such as permutation tests, will be considered if the data are not approximately normal for any continuous outcome variables after log-transformation. A similar approach will be used for making pre vs. post treatment comparisons, when necessary, but with paired t-tests or their non-parametric alternatives.
Time frame: Up to 4 weeks post-treatment
The biomarker data will be compared for differences in means (or geometric means) between treatment arms using Student's t-tests on the raw data (or on log-transformed data depending on the degree and nature of skew in the data). Non-parametric alternatives, such as permutation tests, will be considered if the data are not approximately normal for any continuous outcome variables after log-transformation. A similar approach will be used for making pre vs. post treatment comparisons, when necessary, but with paired t-tests or their non-parametric alternatives. The response outcomes will be evaluated between treatment arms by Fisher's exact tests.
Time frame: Up to 6 months
The biomarker data will be compared for differences in means (or geometric means) between treatment arms using Student's t-tests on the raw data (or on log-transformed data depending on the degree and nature of skew in the data). Non-parametric alternatives, such as permutation tests, will be considered if the data are not approximately normal for any continuous outcome variables after log-transformation. A similar approach will be used for making pre vs. post treatment comparisons, when necessary, but with paired t-tests or their non-parametric alternatives.
Time frame: Up to 6 months
The biomarker data will be compared for differences in means (or geometric means) between treatment arms using Student's t-tests on the raw data (or on log-transformed data depending on the degree and nature of skew in the data). Non-parametric alternatives, such as permutation tests, will be considered if the data are not approximately normal for any continuous outcome variables after log-transformation. A similar approach will be used for making pre vs. post treatment comparisons, when necessary, but with paired t-tests or their non-parametric alternatives.
Time frame: Baseline up to 12 days post surgery
The possibility of measuring an increase in the release of circulating tumor DNA as an indicator of responsiveness or tumor progression is attractive and is supported by xenograft models. An attempt to correlate the mutations found in the circulating tumor DNA with the mutations in the tumor tissues will be performed. The identification of new mutations in circulating tumor DNA over time might inform the clinician about tumor evolution and provide evidence to support new treatment targets not identifiable in the primary tumor
Time frame: Baseline up to 38 days post visit 1.
Our clinical project will evaluate diagnostic utility of multimodality imaging method of digital blood flow quantification based on 3D high frequency Doppler ultrasound and photoacoustic (PA) imaging in patients with Head and Neck Squamous cell carcinoma before and after treatment with Durvalumab and Metformin. This will be done to correlate changes in tissue and tumor oxygenation of the specific tumor of interest measured via photoacoustic imaging with treatment response.
Sidney Kimmel Comprehensive Cancer Center at Thomas Jefferson University
Other
Window of Opportunity for Durvalumab (MEDI4736) Plus Metformin Trial of in Squamous Cell Carcinoma of the Head and Neck
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