Under physiological conditions, immune checkpoint molecules downregulate the activation and effector function of myocardial antigen-reactive T cells through an immunosuppressive pathway, thus enabling myocardial T cells to maintain immune homeostasis under the action of central and peripheral tolerance mechanisms. The PD-1/PD-L1 signalling pathway is particularly important for limiting the ability of T cells to attack the heart. Immune checkpoint inhibitors (ICIs) specifically block this PD-1/PD-L1-mediated restriction of T cell activation and other immunosuppressive pathways by targeting immune checkpoints. In recent years, with the wide use of ICIs in cancer treatment, even though the incidence of immunomyocarditis is low, it has attracted increasing attention because of its complex clinical symptoms, rapid progression of disease and high mortality rates. The pathogenesis, genetic susceptibility factors and predictive biomarkers of immunomyocarditis still need to be understood, and multidisciplinary cooperation in the clinical treatment of this complication is necessary.
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http://dx.doi.org/10.2147/JIR.S311616 | DOI Listing |
Clin Lung Cancer
December 2024
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD.
Objective: To determine the association between concurrent statin use with immune checkpoint inhibitors (ICIs) and lung cancer-specific and overall mortality in patients with nonsmall cell lung cancer (NSCLC).
Materials And Methods: SEER-Medicare was used to conduct a retrospective study of Medicare beneficiaries ≥65 years of age diagnosed with NSCLC between 2007 and 2017 treated with an ICI. Patients were followed from date of first ICI claim until death, 1 month from last ICI claim, or 12/31/2018, whichever came first.
Respir Investig
January 2025
Department of Respiratory Medicine, International Medical Center, Saitama Medical University, 1397-1 Yamane, Hidaka-City, Saitama, 350-1298, Japan. Electronic address:
Pleural mesothelioma (PM) is a rare and highly aggressive malignancy originating from the pleural lining, with a median overall survival of merely 1 year. This cancer primarily arises from mesothelial cells following exposure to carcinogenic, biopersistent mineral fibers, particularly asbestos. The histological subtypes of mesothelioma are epithelioid (approximately 60%), sarcomatoid (20%), and biphasic (20%), exhibiting epithelioid and sarcomatoid characteristics.
View Article and Find Full Text PDFInt Immunopharmacol
January 2025
TriArm Therapeutics, Niudun Road 200, 201203 Shanghai, China. Electronic address:
Background: The immunosuppressive microenvironment negatively affects the efficacy of chimeric antigen receptor T (CAR-T) cells in solid tumors. Fusion protein that combining extracellular domain of inhibitory checkpoint protein and the cytoplasmic domain of stimulatory molecule may improve the efficacy of CAR-T cells by reversing the suppressive signals.
Methods: To generate optimal PD1-TLR10 fusion proteins, PD1 extracellular domain and TLR10 intracellular domain were connected by transmembrane domain from PD1, CD28, or TLR10, respectively.
BI 1703880, a novel STimulator of INterferon Genes (STING) agonist, has demonstrated preclinical antitumor activity. As STING activation can upregulate programmed death ligand 1 and human leukocyte antigen in tumor cells, a combination of BI 1703880 and an anti-programmed cell death protein 1-antibody, such as ezabenlimab, may improve efficacy. This first-in-human phase Ia study (NCT05471856) is evaluating BI 1703880 plus ezabenlimab in patients with advanced solid tumors.
View Article and Find Full Text PDFDiagn Interv Radiol
January 2025
Huadong Hospital, Fudan University, Department of Thoracic Surgery, Shanghai, China.
Purpose: Patients with advanced non-small cell lung cancer (NSCLC) have varying responses to immunotherapy, but there are no reliable, accepted biomarkers to accurately predict its therapeutic efficacy. The present study aimed to construct individualized models through automatic machine learning (autoML) to predict the efficacy of immunotherapy in patients with inoperable advanced NSCLC.
Methods: A total of 63 eligible participants were included and randomized into training and validation groups.
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