71 research outputs found

    Abscopal effect observed in visceral and osseous metastases after liver SBRT in combination with nivolumab and relatlimab for sinonasal mucosal melanoma—a case report

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    BackgroundPrimary sinonasal mucosal melanoma (SNMM) is a rare, aggressive histology usually diagnosed at advanced stages and associated with poor prognosis. Evidence regarding etiology, diagnosis, and treatment mainly derives from case reports, retrospective series, and national databases. In the treatment of metastatic melanoma, anti-CTLA-4 and anti-PD-1 checkpoint blockade increased 5-year overall survival from ~10% (prior to 2011) to ~50% (between 2011 and 2016). In March of 2022, the FDA approved the use of relatlimab, a novel anti-LAG3 immune checkpoint inhibitor, for the treatment of melanoma.Case presentationA 67-year-old woman with locally advanced SNMM underwent debulking surgery, adjuvant RT, and first-line immunotherapy (ImT) with nivolumab but developed local progression. The patient started a second course of ImT with nivolumab and ipilimumab, but this was discontinued after two cycles due to an immune-related adverse event (irAE, hepatitis with elevated liver enzymes). Interval imaging identified visceral and osseous metastases including multiple lesions in the liver and in the lumbar spine. She went on to receive a third course of ImT with nivolumab and the novel agent relatlimab with concurrent stereotactic body radiation therapy (SBRT) to the largest liver tumor only, delivered in five 10-Gy fractions using MRI guidance. A PET/CT performed 3 months after SBRT demonstrated complete metabolic response (CMR) of all disease sites including non-irradiated liver lesions and spinal metastatic sites. After two cycles of the third course of ImT, the patient developed severe immune-related keratoconjunctivitis and ImT was discontinued.ConclusionThis case report describes the first complete abscopal response (AR) in an SNMM histology and the first report of AR following liver SBRT with the use of relatlimab/nivolumab combination ImT for metastatic melanoma in the setting of both visceral and osseous lesions. This report suggests that the combination of SBRT with ImT potentiates the adaptive immune response and is a viable path for immune-mediated tumor rejection. The mechanisms behind this response are hypothesis-generating and remain an area of active research with exceedingly promising potential

    IFITM3 incorporation sensitizes influenza A virus to antibody-mediated neutralization

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    The disease severity of influenza is highly variable in humans, and one genetic determinant behind these differences is the IFITM3 gene. As an effector of the interferon response, IFITM3 potently blocks cytosolic entry of influenza A virus (IAV). Here, we reveal a novel level of inhibition by IFITM3 in vivo: We show that incorporation of IFITM3 into IAV particles competes with incorporation of viral hemagglutinin (HA). Decreased virion HA levels did not reduce infectivity, suggesting that high HA density on IAV virions may be an antagonistic strategy used by the virus to prevent direct inhibition. However, we found that IFITM3-mediated reduction in HA content sensitizes IAV to antibody-mediated neutralization. Mathematical modeling predicted that this effect decreases and delays peak IAV titers, and we show that, indeed, IFITM3-mediated sensitization of IAV to antibody-mediated neutralization impacts infection outcome in an in vivo mouse model. Overall, our data describe a previously unappreciated interplay between the innate effector IFITM3 and the adaptive immune response

    Lung Inflammation Predictors in Combined Immune Checkpoint-Inhibitor and Radiation Therapy—Proof-of-Concept Animal Study

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    Purpose: Combined radiotherapy (RT) and immune checkpoint-inhibitor (ICI) therapy can act synergistically to enhance tumor response beyond what either treatment can achieve alone. Alongside the revolutionary impact of ICIs on cancer therapy, life-threatening potential side effects, such as checkpoint-inhibitor-induced (CIP) pneumonitis, remain underreported and unpredictable. In this preclinical study, we hypothesized that routinely collected data such as imaging, blood counts, and blood cytokine levels can be utilized to build a model that predicts lung inflammation associated with combined RT/ICI therapy. Materials and Methods: This proof-of-concept investigational work was performed on Lewis lung carcinoma in a syngeneic murine model. Nineteen mice were used, four as untreated controls and the rest subjected to RT/ICI therapy. Tumors were implanted subcutaneously in both flanks and upon reaching volumes of ~200 mm3 the animals were imaged with both CT and MRI and blood was collected. Quantitative radiomics features were extracted from imaging of both lungs. The animals then received RT to the right flank tumor only with a regimen of three 8 Gy fractions (one fraction per day over 3 days) with PD-1 inhibitor administration delivered intraperitoneally after each daily RT fraction. Tumor volume evolution was followed until tumors reached the maximum size allowed by the Institutional Animal Care and Use Committee (IACUC). The animals were sacrificed, and lung tissues harvested for immunohistochemistry evaluation. Tissue biomarkers of lung inflammation (CD45) were tallied, and binary logistic regression analyses were performed to create models predictive of lung inflammation, incorporating pretreatment CT/MRI radiomics, blood counts, and blood cytokines. Results: The treated animal cohort was dichotomized by the median value of CD45 infiltration in the lungs. Four pretreatment radiomics features (3 CT features and 1 MRI feature) together with pre-treatment neutrophil-to-lymphocyte (NLR) ratio and pre-treatment granulocyte-macrophage colony-stimulating factor (GM-CSF) level correlated with dichotomized CD45 infiltration. Predictive models were created by combining radiomics with NLR and GM-CSF. Receiver operating characteristic (ROC) analyses of two-fold internal cross-validation indicated that the predictive model incorporating MR radiomics had an average area under the curve (AUC) of 0.834, while the model incorporating CT radiomics had an AUC of 0.787. Conclusions: Model building using quantitative imaging data, blood counts, and blood cytokines resulted in lung inflammation prediction models justifying the study hypothesis. The models yielded very-good-to-excellent AUCs of more than 0.78 on internal cross-validation analyses

    Application of a biologically contained reporter system to study gain-of-function H5N1 influenza a viruses with pandemic potential

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    Natural adaptation of an antigenically novel avian influenza A virus (IAV) to be transmitted efficiently in humans has the potential to trigger a devastating pandemic. Understanding viral genetic determinants underlying adaptation is therefore critical for pandemic preparedness, as the knowledge gained enhances surveillance and eradication efforts, prepandemic vaccine design, and efficacy assessment of antivirals. However, this work has risks, as making gain-of-function substitutions in fully infectious IAVs may create a pathogen with pandemic potential. Thus, such experiments must be tightly controlled through physical and biological risk mitigation strategies. Here, we applied a previously described biological containment system for IAVs to a 2009 pandemic H1N1 strain and a highly pathogenic H5N1 strain. The system relies on deletion of the essential viral hemagglutinin (HA) gene, which is instead provided in trans, thereby restricting multicycle virus replication to genetically modified HA-complementing cells. In place of HA, a Renilla luciferase gene is inserted within the viral genome, and a live-cell luciferase substrate allows real-time quantitative monitoring of viral replication kinetics with a high dynamic range. We demonstrate that biologically contained IAV-like particles exhibit wild-type sensitivities to approved antivirals, including oseltamivir, zanamivir, and baloxavir. Furthermore, the inability of these IAV-like particles to genetically acquire the host-encoded HA allowed us to introduce gain-of-function substitutions in the H5 HA gene that promote mammalian transmissibility. Biologically contained "transmissible" H5N1 IAV-like particles exhibited wild-type sensitivities to approved antivirals, to the fusion inhibitor S20, and to neutralization by existing H5 monoclonal and polyclonal sera. This work represents a proof of principle that biologically contained IAV systems can be used to safely conduct selected gain-of-function experiments.IMPORTANCE Understanding how animal influenza viruses can adapt to spread in humans is critical to prepare for, and prevent, new pandemics. However, working safely with pathogens that have pandemic potential requires tight regulation and the use of high-level physical and biological risk mitigation strategies to stop accidental loss of containment. Here, we used a biological containment system for influenza viruses to study strains with pandemic potential. The system relies on deletion of the essential HA gene from the viral genome and its provision by a genetically modified cell line, to which virus propagation is therefore restricted. We show that this method permits safe handling of these pathogens, including gain-of-function variants, without the risk of generating fully infectious viruses. Furthermore, we demonstrate that this system can be used to assess virus sensitivity to both approved and experimental drugs, as well as the antigenic profile of viruses, important considerations for evaluating prepandemic vaccine and antiviral strategies

    Application of a Biologically Contained Reporter System To Study Gain-of-Function H5N1 Influenza A Viruses with Pandemic Potential

    No full text
    Natural adaptation of an antigenically novel avian influenza A virus (IAV) to be transmitted efficiently in humans has the potential to trigger a devastating pandemic. Understanding viral genetic determinants underlying adaptation is therefore critical for pandemic preparedness, as the knowledge gained enhances surveillance and eradication efforts, prepandemic vaccine design, and efficacy assessment of antivirals. However, this work has risks, as making gain-of-function substitutions in fully infectious IAVs may create a pathogen with pandemic potential. Thus, such experiments must be tightly controlled through physical and biological risk mitigation strategies. Here, we applied a previously described biological containment system for IAVs to a 2009 pandemic H1N1 strain and a highly pathogenic H5N1 strain. The system relies on deletion of the essential viral hemagglutinin (HA) gene, which is instead provided in trans, thereby restricting multicycle virus replication to genetically modified HA-complementing cells. In place of HA, a Renilla luciferase gene is inserted within the viral genome, and a live-cell luciferase substrate allows real-time quantitative monitoring of viral replication kinetics with a high dynamic range. We demonstrate that biologically contained IAV-like particles exhibit wild-type sensitivities to approved antivirals, including oseltamivir, zanamivir, and baloxavir. Furthermore, the inability of these IAV-like particles to genetically acquire the host-encoded HA allowed us to introduce gain-of-function substitutions in the H5 HA gene that promote mammalian transmissibility. Biologically contained “transmissible” H5N1 IAV-like particles exhibited wild-type sensitivities to approved antivirals, to the fusion inhibitor S20, and to neutralization by existing H5 monoclonal and polyclonal sera. This work represents a proof of principle that biologically contained IAV systems can be used to safely conduct selected gain-of-function experiments

    Lung Inflammation Predictors in Combined Immune Checkpoint-Inhibitor and Radiation Therapy—Proof-of-Concept Animal Study

    No full text
    Purpose: Combined radiotherapy (RT) and immune checkpoint-inhibitor (ICI) therapy can act synergistically to enhance tumor response beyond what either treatment can achieve alone. Alongside the revolutionary impact of ICIs on cancer therapy, life-threatening potential side effects, such as checkpoint-inhibitor-induced (CIP) pneumonitis, remain underreported and unpredictable. In this preclinical study, we hypothesized that routinely collected data such as imaging, blood counts, and blood cytokine levels can be utilized to build a model that predicts lung inflammation associated with combined RT/ICI therapy. Materials and Methods: This proof-of-concept investigational work was performed on Lewis lung carcinoma in a syngeneic murine model. Nineteen mice were used, four as untreated controls and the rest subjected to RT/ICI therapy. Tumors were implanted subcutaneously in both flanks and upon reaching volumes of ~200 mm3 the animals were imaged with both CT and MRI and blood was collected. Quantitative radiomics features were extracted from imaging of both lungs. The animals then received RT to the right flank tumor only with a regimen of three 8 Gy fractions (one fraction per day over 3 days) with PD-1 inhibitor administration delivered intraperitoneally after each daily RT fraction. Tumor volume evolution was followed until tumors reached the maximum size allowed by the Institutional Animal Care and Use Committee (IACUC). The animals were sacrificed, and lung tissues harvested for immunohistochemistry evaluation. Tissue biomarkers of lung inflammation (CD45) were tallied, and binary logistic regression analyses were performed to create models predictive of lung inflammation, incorporating pretreatment CT/MRI radiomics, blood counts, and blood cytokines. Results: The treated animal cohort was dichotomized by the median value of CD45 infiltration in the lungs. Four pretreatment radiomics features (3 CT features and 1 MRI feature) together with pre-treatment neutrophil-to-lymphocyte (NLR) ratio and pre-treatment granulocyte-macrophage colony-stimulating factor (GM-CSF) level correlated with dichotomized CD45 infiltration. Predictive models were created by combining radiomics with NLR and GM-CSF. Receiver operating characteristic (ROC) analyses of two-fold internal cross-validation indicated that the predictive model incorporating MR radiomics had an average area under the curve (AUC) of 0.834, while the model incorporating CT radiomics had an AUC of 0.787. Conclusions: Model building using quantitative imaging data, blood counts, and blood cytokines resulted in lung inflammation prediction models justifying the study hypothesis. The models yielded very-good-to-excellent AUCs of more than 0.78 on internal cross-validation analyses
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