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Chemotherapy in synergy with innate immune agonists enhances T cell priming for checkpoint inhibitor treatment in pancreatic cancer.
Biomark Res
January 2025
Department of Oncology and the Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA.
Background: The combination of conventional chemotherapy and immune checkpoint inhibitors (ICIs) has been unsuccessful for pancreatic ductal adenocarcinoma (PDAC). Administration of maximum tolerated dose of chemotherapy drugs may have immunosuppressive effects.
Methods: We thus tested, by using the preclinical model of PDACs including the genetically engineered mouse KPC spontaneous pancreatic tumor model and the pancreatic KPC tumor orthotopic implant model, the combinations of synthetic innate immune agonists including STING and NLRP3 agonist, respectively, and ICIs with or without chemotherapy.
Advances in CAR T cell therapy: antigen selection, modifications, and current trials for solid tumors.
Front Immunol
January 2025
Department of Medicine, Division of Hematology/Oncology, David Geffen School of Medicine at University of California, Los Angeles (UCLA), Los Angeles, CA, United States.
Chimeric antigen receptor (CAR) T cell therapy has revolutionized the treatment of hematologic malignancies, achieving remarkable clinical success with FDA-approved therapies targeting CD19 and BCMA. However, the extension of these successes to solid tumors remains limited due to several intrinsic challenges, including antigen heterogeneity and immunosuppressive tumor microenvironments. In this review, we provide a comprehensive overview of recent advances in CAR T cell therapy aimed at overcoming these obstacles.
View Article and Find Full Text PDFThe evolving landscape of adjuvant therapy in T1-T2N0 resected non-small cell lung cancer: a narrative review.
J Thorac Dis
December 2024
Department of Surgery, Yale University School of Medicine, Yale University, New Haven, CT, USA.
Background And Objective: Lung cancer recurrence after complete surgical resection of early-stage T1-T2N0 non-small cell lung cancer (NSCLC) remains a problem due to unrecognized micrometastatic disease. The objective of this review is to present and summarize data from major randomized trials in which have studied the survival benefit of adjuvant therapy for early-stage NSCLC.
Methods: Information used to write this paper was collected from PubMed and the National Clinical Trial registry from the National Library of Medicine.
Silencing of lncRNA Gm26917 Attenuates Alveolar Macrophage-mediated Inflammatory Response in LPS-induced Acute Lung Injury Via Inhibiting NKRF Ubiquitination.
Inflammation
January 2025
Department of Microbiology and Parasitology, Anhui Provincial Laboratory of Pathogen Biology, School of Basic Medical Sciences, Anhui Medical University, Hefei, 230032, Anhui, China.
The inflammatory response mediated by alveolar macrophages plays a crucial role in the development of acute lung injury. Numerous studies have reported that lncRNAs are highly expressed in acute lung injury in mouse models and cell lines, and acute lung injury (ALI) can be effectively alleviated by targeting these lncRNAs. The aim of this study was to explore the mechanism by LncRNA Gm26917 regulates the inflammatory response in alveolar macrophages during acute lung injury mouse model.
View Article and Find Full Text PDFLD-informed deep learning for Alzheimer's gene loci detection using WGS data.
Alzheimers Dement (N Y)
January 2025
Indiana Alzheimer Disease Research Center and Center for Neuroimaging, Department of Radiology and Imaging Sciences Indiana University School of Medicine Indianapolis Indiana USA.
Introduction: The exponential growth of genomic datasets necessitates advanced analytical tools to effectively identify genetic loci from large-scale high throughput sequencing data. This study presents Deep-Block, a multi-stage deep learning framework that incorporates biological knowledge into its AI architecture to identify genetic regions as significantly associated with Alzheimer's disease (AD). The framework employs a three-stage approach: (1) genome segmentation based on linkage disequilibrium (LD) patterns, (2) selection of relevant LD blocks using sparse attention mechanisms, and (3) application of TabNet and Random Forest algorithms to quantify single nucleotide polymorphism (SNP) feature importance, thereby identifying genetic factors contributing to AD risk.
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