Programmed death ligand 1 (PD-L1) plays a pivotal role in cancer immune evasion and is a critical target for cancer immunotherapy. This review focuses on the regulation of PD-L1 through the dynamic processes of ubiquitination and deubiquitination, which are crucial for its stability and function. Here, we explored the intricate mechanisms involving various E3 ubiquitin ligases and deubiquitinating enzymes (DUBs) that modulate PD-L1 expression in cancer cells. Specific ligases are discussed in detail, highlighting their roles in tagging PD-L1 for degradation. Furthermore, we discuss the actions of DUBs that stabilize PD-L1 by removing ubiquitin chains. The interplay of these enzymes not only dictates PD-L1 levels but also influences cancer progression and patient response to immunotherapies. Furthermore, we discuss the therapeutic implications of targeting these regulatory pathways and propose novel strategies to enhance the efficacy of PD-L1/PD-1-based therapies. Our review underscores the complexity of PD-L1 regulation and its significant impact on the tumor microenvironment and immunotherapy outcomes.
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http://dx.doi.org/10.3390/ijms25052939 | DOI Listing |
Clin Exp Med
January 2025
LSU-LCMC Cancer Center, LSU School of Medicine, 1700 Tulane Avenue, Room 510, New Orleans, LA, 70112, USA.
Anti-tumor immunotherapy was rediscovered and rejuvenated in the last two decades with the discovery of CTLA-4, PD-1 and PD-L1 and the roles in inhibiting immune function and tumor evasion of anti-tumor immune response. Following the approval of the first checkpoint inhibitor ipilimumab against CTLA-4 in melanoma in 2011, there has been a rapid development of tumor immunotherapy. Furthermore, additional positive and negative molecules among the T-cell regulatory systems have been identified that that function to fine tune the stimulatory or inhibitory immune cells and modulate their functions (checkpoint modulators).
View Article and Find Full Text PDFAnn Surg Oncol
January 2025
Department of Surgery, Weill Cornell Medicine, New York, NY, USA.
Background: Guidelines for some pancreatic neuroendocrine tumors (NETs) have shifted towards active surveillance given the indolent nature of this malignancy. We sought to assess the safety of delayed surgery on colorectal NETs as a surrogate for surveillance.
Methods: Resected, stage I, well-differentiated colorectal primary NETs included in the Surveillance, Epidemiology, and End Results Program from 2010 to 2020 were included.
Objectives: To report 5-year outcomes from the STRATified CANcer Surveillance (STRATCANS) programme based on progression risks using National Institute for Health and Clinical Excellence (NICE) Cambridge Prognostic Group (CPG) at diagnosis, prostate specific antigen density and magnetic resonance imaging (MRI) visibility.
Patients And Methods: Men with CPG1 and CPG2 disease selecting active surveillance (AS) were included into STRATCANS and allocated to one of three increasing follow-up intensities. Outcome measures were: (i) treatment for CPG≥3 progression (main outcome), (ii) any treatment, (iii) conversion to watchful waiting (WW), (iv) patient self-attrition, and (v) mortality.
Adv Mater
January 2025
Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, 230032, China.
Lysosome-targeting chimeras (LYTACs) have recently emerged as a promising therapeutic strategy for degrading extracellular and membrane-associated pathogenic proteins by hijacking lysosome-targeting receptors. However, the antitumor performance of LYTAC is limited by its insufficient tumor accumulation and nonspecific activation. Additionally, the synergistic effects of LYTACs and other therapeutic modalities are crucial.
View Article and Find Full Text PDFCancer Med
February 2025
Department of Radiation Oncology (MAASTRO) GROW School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, the Netherlands.
Background: Lung cancer (LC) is the top cause of cancer deaths globally, prompting many countries to adopt LC screening programs. While screening typically relies on age and smoking intensity, more efficient risk models exist. We devised a Bayesian network (BN) for LC detection, testing its resilience with varying degrees of missing data and comparing it to a prior machine learning (ML) model.
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