Early prediction of clinical response to checkpoint inhibitor therapy in human solid tumors through mathematical modeling.
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ABSTRACT:
SUBMITTER: Butner JD
PROVIDER: S-EPMC8629426 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The emergence of immune 'checkpoint inhibitors' such as cytotoxic T-lymphocyte antigen 4 (CTLA-4) and programmed death receptor 1 (PD-1) has revolutionized treatment of solid tumors including melanoma, lung cancer, among many others. The goal of checkpoint inhibitor combination therapy is to improve clinical response and minimize toxicities. Rational design of checkpoint combinations considers immune-mediated mechanisms of antitumor activity: immunogenic cell death, antigen release and presentation, activation of T-cell responses, lymphocytic infiltration into tumors and depletion of immunosuppression. Potential synergistic combinations include checkpoint blockade with conventional (radiation, chemotherapy and targeted therapies) and newer immunotherapies (cancer vaccines, oncolytic viruses, among others). Reliable biomarkers are necessary to define patients who will achieve best clinical benefit with minimal toxicity in combination therapy.
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Project description:BackgroundImmune checkpoint inhibitors (ICIs) have been increasingly used in cancer treatment, and a subset of patients undergo pseudoprogression. Recognizing the incidence of pseudoprogression is critical for clinical practice.PurposeTo evaluate by systematic review and meta-analysis the incidence of pseudoprogression in cancer treatment with ICIs, and compare the incidence according to response criteria, tumor types, and immunotherapeutic agents.Materials and MethodsMedline and Embase were searched to identify relevant studies published before December 31, 2018. Clinical trials, post hoc analysis of clinical trials, and prospective studies on ICI treatment in patients with malignant solid tumors were included. Pooled incidence of pseudoprogression for all included studies, per definition of pseudoprogression, cancer type, and drug type, was obtained by random-effects models with inverse variance weighting model.ResultsSeventeen studies with 3402 patients were analyzed. The pooled incidence of pseudoprogression was 6.0% (95% confidence interval: 5.0%, 7.0%). The definition of pseudoprogression were divided into four categories: progressive disease followed by partial response (PR) or complete response (CR) but not stable disease (SD) with Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 (six studies); progressive disease followed by SD or PR or CR with RECIST 1.1 (five studies); progressive disease followed by SD or PR or CR with RECIST 1.0 (three studies); and progressive disease followed by SD or PR or CR with immune-related response criteria (irRC) (three studies). Incidence of pseudoprogression varied from 4.5% to 8.0% per definition, ranged from 5.0% to 7.0% per cancer type, and was 5.6% with the monotherapy of programmed cell death-1 inhibitor.ConclusionThe overall incidence of pseudoprogression was 6.0% and was less than 10% in subgroup analyses according to the definitions of pseudoprogression, cancer type, and immune checkpoint inhibitor type. Varying definitions across trials and studies indicates the need for uniform criteria of pseudoprogression for solid tumors.© RSNA, 2020Online supplemental material is available for this article.See also the article by Dodd and MacDermott in this issue.
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Project description:The B-raf gene is mutated in up to 66% of human malignant melanomas, and its protein product, BRAF kinase, is a key part of RAS-RAF-MEK-ERK (MAPK) pathway of cancer cell proliferation. BRAF-targeted therapy induces significant responses in the majority of patients, and the combination BRAF/MEK inhibitor enhances clinical efficacy, but the response to BRAF inhibitor and to BRAF/MEK inhibitor is short lived. On the other hand, treatment of melanoma with an immune checkpoint inhibitor, such as anti-PD-1, has lower response rate but the response is much more durable, lasting for years. For this reason, it was suggested that combination of BRAF/MEK and PD-1 inhibitors will significantly improve overall survival time.This paper develops a mathematical model to address the question of the correlation between BRAF/MEK inhibitor and PD-1 inhibitor in melanoma therapy. The model includes dendritic and cancer cells, CD 4+ and CD 8+ T cells, MDSC cells, interleukins IL-12, IL-2, IL-6, IL-10 and TGF- β, PD-1 and PD-L1, and the two drugs: BRAF/MEK inhibitor (with concentration γ B ) and PD-1 inhibitor (with concentration γ A ). The model is represented by a system of partial differential equations, and is used to develop an efficacy map for the combined concentrations (γ B ,γ A ). It is shown that the two drugs are positively correlated if γ B and γ A are at low doses, that is, the growth of the tumor volume decreases if either γ B or γ A is increased. On the other hand, the two drugs are antagonistic at some high doses, that is, there are zones of (γ B ,γ A ) where an increase in one of the two drugs will increase the tumor volume growth, rather than decrease it.It will be important to identify, by animal experiments or by early clinical trials, the zones of (γ B ,γ A ) where antagonism occurs, in order to avoid these zones in more advanced clinical trials.
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2016-03-16 | E-GEOD-79208 | biostudies-arrayexpress