14-3-3 proteins are a family of master regulators of intracellular signaling, yet their impact on proteasome function is unknown. We demonstrate that 14-3-3ζ binds the 11S proteasome activator, limiting proteasome assembly and cellular capacity for protein degradation. To define the functional impact of 14-3-3ζ proteasomal binding in myeloma cells, silencing and overexpression experiments are performed. We find that downregulation of 14-3-3ζ impairs myeloma cell growth and confers resistance to clinically used proteasome inhibitors. In a large cohort of newly diagnosed myeloma patients, elevated expression of 14-3-3ζ is associated with high risk myeloma genetic subtypes and worse prognosis overall. Our work demonstrates the important role of 14-3-3ζ in regulating proteasome function, myeloma cell growth and sensitivity to therapeutics, and suggests regulation of 14-3-3ζ as a new approach in myeloma therapy.
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http://dx.doi.org/10.1038/leu.2017.288 | DOI Listing |
J Clin Invest
January 2025
Division of Pediatric Hematology/Oncology, Department of Pediatrics, Pennsylvania State University College of Medicine, Hershey, United States of America.
Although nucleoporin 98 (NUP98) fusion oncogenes often drive aggressive pediatric leukemia by altering chromatin structure and expression of HOX genes, underlying mechanisms remain elusive. Here, we report that a Hoxb-associated lncRNA HoxBlinc was aberrantly activated in NUP98-PHF23 fusion-driven leukemias. HoxBlinc chromatin occupancies led to elevated MLL1 recruitment and aberrant homeotic topologically associated domains (TADs) that enhanced chromatin accessibilities and activated homeotic/hematopoietic oncogenes.
View Article and Find Full Text PDFBrief Bioinform
November 2024
School of Computer Science, Northwestern Polytechnical University, Xi'an, 710129 Shaanxi, China.
The identification of neoantigens is crucial for advancing vaccines, diagnostics, and immunotherapies. Despite this importance, a fundamental question remains: how to model the presentation of neoantigens by major histocompatibility complex class I molecules and the recognition of the peptide-MHC-I (pMHC-I) complex by T cell receptors (TCRs). Accurate prediction of pMHC-I binding and TCR recognition remains a significant computational challenge in immunology due to intricate binding motifs and the long-tail distribution of known binding pairs in public databases.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong, 999077, China.
The complexity of T cell receptor (TCR) sequences, particularly within the complementarity-determining region 3 (CDR3), requires efficient embedding methods for applying machine learning to immunology. While various TCR CDR3 embedding strategies have been proposed, the absence of their systematic evaluations created perplexity in the community. Here, we extracted CDR3 embedding models from 19 existing methods and benchmarked these models with four curated datasets by accessing their impact on the performance of TCR downstream tasks, including TCR-epitope binding affinity prediction, epitope-specific TCR identification, TCR clustering, and visualization analysis.
View Article and Find Full Text PDFInflammopharmacology
January 2025
Neuropharmacology Division, Department of Pharmacology, ISF College of Pharmacy, Moga, 142001, Punjab, India.
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by the accumulation of amyloid-β plaques and tau tangles, leading to cognitive decline and dementia. Insulin-like Growth Factor-1 (IGF-1) is similar in structure to insulin and is crucial for cell growth, differentiation, and regulating oxidative stress, synaptic plasticity, and mitochondrial function. IGF-1 exerts its physiological effects by binding to the IGF-1 receptor (IGF-1R) and activating PI3K/Akt pathway.
View Article and Find Full Text PDFGastric Cancer
January 2025
Department of Biochemistry and Molecular Biology, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China.
Background: Gastroesophageal junction adenocarcinoma (GEJAC) exhibits distinct molecular characteristics due to its unique anatomical location. We sought to investigate effective and reliable molecular classification of GEJAC to guide personalized treatment.
Methods: We analyzed the whole genomic, transcriptomic, T-cell receptor repertoires, and immunohistochemical data in 92 GEJAC patients and delineated the landscape of genetic and immune alterations.
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