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Osteosarcoma

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Liposarcoma

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Disease Attributes

Neoplasms, Connective and Soft Tissue

Neoplasms by Histologic Type

Neoplasms, Bone Tissue

Neoplasms, Connective Tissue

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Soft Tissue Sarcoma

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Durvalumab

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Immunoglobulin G

Immunoglobulins, Intravenous

Antineoplastic Agents, Immunological

Immunologic Factors

Patients receive oleclumab IV over 1 hour every 2 weeks for 5 doses, then every 4 weeks thereafter. Patients also receive durvalumab IV over 1 hour every 4 weeks. Cycle repeat every 28 days in the absence of disease progression or unacceptable toxicity.

Oleclumab

Neeta Somaiah

This phase II trial investigates how well oleclumab and durvalumab work in treating patients with sarcoma that has come back (recurrent) or does not respond to treatment (refractory) or has spread to other places in the body (metastatic). Immunotherapy with monoclonal antibodies, such as oleclumab and durvalumab, may help the body's immune system attack the cancer, and may interfere with the ability of tumor cells to grow and spread.

PRIMARY OBJECTIVES:

I. To estimate the tumor response (Response Evaluation Criteria in Solid Tumors \[RECIST\]) at 4 months in patients with relapsed/refractory sarcoma. (Cohorts 1 and 2) II. To determine the event-free survival (EFS) rate at 4 months after initiation of the treatment in patients with relapsed/refractory osteosarcoma receiving novel immunotherapeutic agents. (Cohort 3)

SECONDARY OBJECTIVES:

I. To determine the progression-free survival (PFS) rate at 12 weeks after initiation of the treatment in patients with relapsed/refractory sarcoma receiving novel immunotherapeutic agents.

II. To estimate the tumor response (Immune-related Response Criteria \[irRC\] and RECIST) in patients with relapsed/refractory sarcoma.

III. To evaluate the safety and tolerability of receiving novel immunotherapeutic agents in patients with relapsed/refractory sarcoma.

IV. To estimate the median PFS and overall survival (OS) in patients with relapsed/refractory sarcoma receiving novel immunotherapeutic agents.

EXPLORATORY OBJECTIVES:

I. To determine expression of biomarkers (including but not limited to CD73, PD-1 and PD-L1) in pre \& post treatment (tx) samples.

II. Quantification and characterization of the immune infiltrate (and other histologic and immunohistologic changes) from tissue samples prior to treatment initiation and post treatment (biopsy at week 6).

III. Identification/quantification of immunologic changes (CD4+, CD8+, Teff, Treg cells and NK cells) in peripheral blood.

IV. Determining an immunoscore based on baseline tumor sample (identification of molecular response/resistance patterns/future therapy options).

OUTLINE:

Patients receive oleclumab intravenously (IV) over 1 hour every 2 weeks for 5 doses, then every 4 weeks thereafter. Patients also receive durvalumab IV over 1 hour every 4 weeks. Cycle repeat every 28 days in the absence of disease progression or unacceptable toxicity.

After completion of study treatment, patients are followed up at 30 days, and then every 3 months for up to 5 years.

Oleclumab and Durvalumab for the Treatment of Recurrent, Refractory, or Metastatic Sarcoma

A Phase II Multi-Arm Study to Test the Efficacy of Oleclumab and Durvalumab in Multiple Sarcoma Subtypes

Evaluated using immunohistochemistry (CD73, PD-1/PD-L1) expression analysis). Exploratory data analysis and graphical methods will be applied to examine the distribution of the biomarker data, error checking, and outlier identification. T-test/analysis of variance (ANOVA) or their nonparametric counterparts, Wilcoxon rank-sum test/Kruskal-Wallis test will be used to detect differences of the biomarkers between groups. Linear mixed effect models for repeated measures analysis (Liang, 1986) will be employed to assess the change in biomarkers over time with multi-covariates including disease characteristics (tumor stage, site, pathology), and other prognostic factors. Appropriate transformation of the outcome assessment values will be used to satisfy the normality assumption of linear mixed effect model.

Evaluated using immunofluorescence analysis. Exploratory data analysis and graphical methods will be applied to examine the distribution of the biomarker data, error checking, and outlier identification. T-test/ANOVA or their nonparametric counterparts, Wilcoxon rank-sum test/Kruskal-Wallis test will be used to detect differences of the biomarkers between groups. Linear mixed effect models for repeated measures analysis (Liang, 1986) will be employed to assess the change in biomarkers over time with multi-covariates including disease characteristics (tumor stage, site, pathology), and other prognostic factors. Appropriate transformation of the outcome assessment values will be used to satisfy the normality assumption of linear mixed effect model.

Evaluated using flow cytometry analysis. Exploratory data analysis and graphical methods will be applied to examine the distribution of the biomarker data, error checking, and outlier identification. T-test/ANOVA or their nonparametric counterparts, Wilcoxon rank-sum test/Kruskal-Wallis test will be used to detect differences of the biomarkers between groups. Linear mixed effect models for repeated measures analysis (Liang, 1986) will be employed to assess the change in biomarkers over time with multi-covariates including disease characteristics (tumor stage, site, pathology), and other prognostic factors. Appropriate transformation of the outcome assessment values will be used to satisfy the normality assumption of linear mixed effect model.

Defined as complete response (CR) or partial response (PR) per Response Evaluation Criteria in Solid Tumors (RECIST) 1.1.

Defined as the time from enrollment to disease progression, death, or discontinuation of treatment for any reason (for example toxicity, patient preference, or initiation of new treatment without documented disease progression). Defined by RECIST 1.1. Will be estimated using the Kaplan-Meier method. Log-rank test will be performed to test the difference in survival between groups. Regression analysis of survival data based on the Cox proportional hazards model will be conducted. The proportional hazards assumption will be evaluated graphically and analytically, and regression diagnostics (e.g., martingale and Shoenfeld residuals) will be examined to ensure the models are appropriate.

Defined as the time from treatment onset to either disease progression as defined by RECIST 1.1. Will be estimated using the Kaplan-Meier method. Log-rank test will be performed to test the difference in survival between groups. Regression analysis of survival data based on the Cox proportional hazards model will be conducted. The proportional hazards assumption will be evaluated graphically and analytically, and regression diagnostics (e.g., martingale and Shoenfeld residuals) will be examined to ensure the models are appropriate.

Defined by Immune-related Response Criteria (irRC) and RECIST.

Graded according to National Cancer Institute Common Terminology Criteria for Adverse Events version 5.0. Toxicity data by grade and relationship with the treatment by cohorts and 3 cohorts combined, will be summarized by frequency tables. For the toxicity endpoint, per-treated analysis will be used to include any patient who received the treatment regardless of the eligibility nor the duration or dose of the treatment received. Toxicity rate will be estimated with 95% confidence interval.

Will be estimated using the Kaplan-Meier method. Log-rank test will be performed to test the difference in survival between groups. Regression analysis of survival data based on the Cox proportional hazards model will be conducted. The proportional hazards assumption will be evaluated graphically and analytically, and regression diagnostics (e.g., martingale and Shoenfeld residuals) will be examined to ensure the models are appropriate.

Spots Global Cancer Trial Database for refractory dedifferentiated liposarcoma