Immune checkpoint receptors (ICR) modulate the immune response and are critical hubs for immunotherapy. However, data on their role in T lymphoid malignancies, such as cutaneous T cell lymphoma (CTCL), is sparse. We aimed to explore the role of ICR in the malignant features of transformed T lymphocytes and evaluate the effect of ICR-targeting monoclonal antibodies, often used as immunotherapy for solid tumors. We used the CTCL cell line HH and the Sézary cell line Hut78 to examine ICR expression and the effects of ICR inhibition on cell viability and proliferation. Despite their shared T cell progeny, the different CTCL cell lines exhibit markedly different ICR expression profiles. Programmed cell death-ligand 1 (PD-L1) was expressed by both cell lines, while programmed death-1 (PD-1) was expressed only by the HH cell line. Common to all malignant T cells was an autonomous hyper-proliferative state that did not require T cell receptor stimulation. A monoclonal antibody blocking PD-1 had a small but statistically significant augmenting effect on T cell proliferation. Of note, when the cells were exposed to ionizing radiation, healthy lymphocytes and those derived from the HH cell line were salvaged by anti-PD-L1. We show a regulatory role of ICR, mainly PD-1 and its ligand PD-L1, on cutaneous T cell malignancy.
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http://dx.doi.org/10.1007/s12026-022-09308-6 | DOI Listing |
J Am Chem Soc
January 2025
Key Laboratory of Bioorganic Phosphorus Chemistry and Chemical Biology (Ministry of Education), Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China.
Effective delivery and controlled release of metallo-prodrugs with sustained activation and rapid response feed the needs of precise medicine in metal chemotherapeutics. However, gold-based anticancer drugs often suffer from detoxification binding and extracellular transfer by sulfur-containing peptides. To address this challenge, we integrate a thiol-activated prodrug strategy of newly prepared hypercoordinated carbon-centered gold(I) clusters (HCGCs) with their photosensitization character to augment the mitochondrial release of Au(I) in tumors.
View Article and Find Full Text PDFHistol Histopathol
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Department of Neurology, The Affiliated People's Hospital of Jiangsu University, Zhenjiang Jiangsu, PR China.
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View Article and Find Full Text PDFJ Physiol Investig
January 2025
Department of Physiology, China Medical University, Taichung, Taiwan.
In a previous report, we showed that voltage-gated K+ (Kv) Kv1 and Kv2 channels are involved in cAMP-induced neuritogenesis of mouse neuronal N2A cells. In this report, we examined the effects of tannic acid (TA) on Kv channels and neuritogenesis in N2A cells. TA (15 μM) mildly enhanced Kv currents at -30 to -20 mV but strongly inhibited Kv currents at higher voltages, causing a preferential activation of currents at low voltages.
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November 2024
School of Engineering, Westlake University, No. 600 Dunyu Road, 310030 Zhejiang, P.R. China.
Single-cell RNA sequencing (scRNA-seq) offers remarkable insights into cellular development and differentiation by capturing the gene expression profiles of individual cells. The role of dimensionality reduction and visualization in the interpretation of scRNA-seq data has gained widely acceptance. However, current methods face several challenges, including incomplete structure-preserving strategies and high distortion in embeddings, which fail to effectively model complex cell trajectories with multiple branches.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Guangdong Provincial Key Laboratory of Mathematical and Neural Dynamical Systems, Great Bay University, No. 16 Daxue Rd, Songshanhu District, Dongguan, Guangdong, 523000, China.
Multimodal omics provide deeper insight into the biological processes and cellular functions, especially transcriptomics and proteomics. Computational methods have been proposed for the integration of single-cell multimodal omics of transcriptomics and proteomics. However, existing methods primarily concentrate on the alignment of different omics, overlooking the unique information inherent in each omics type.
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