We have examined the relative mRNA expression of the complement (C) regulatory proteins CD59, CD55 and CD46 in RNA isolated from 50 primary breast cancer specimens using a semiquantitative RT-PCR approach. Having normalized the mRNA expression levels of the C regulators relative to actin, we subsequently correlated their expression with estrogen receptor (ER) and various clinical, pathologic and biochemical features of the disease. CD59 and CD46 were detected in all clinical biopsies, while CD55 mRNA was detected in the majority of samples. The comparative levels of expression between the 3 regulators analyzed, using Spearman rank correlation test, revealed a significant association (p = 0.01; r = 0.36) between CD46 and CD59. CD46 exhibited the most striking pattern of association, with increased levels of expression being associated with ER-positive samples and lower levels of expression associated with a loss of differentiation and epidermal growth factor receptor positivity. Application of Spearman rank correlation test revealed CD46 expression was significantly associated with expression of ER at the level of protein (p = 0.031; r = 0.31) and mRNA (p < 0.001; r = 0.52). CD46 expression also correlated with insulin-like growth factor receptor-positive samples using Spearman rank correlation test (p = 0.016; r = 0.34), but negatively associated with tumor samples either exhibiting histologic grade 3 when compared to grades 1 or 2 or displaying elevated levels of inflammatory cell infiltrate. Immunohistochemical analysis of a limited series (n = 8) of paraffin-embedded breast cancers indicated that the level of CD46 protein expression directly associates with that of the mRNA and, where prominent, is localized in the tumor epithelial cell population, including at the plasma membrane. These data provide new information on expression of these important regulators in breast cancer and suggest that CD46 should be evaluated as a novel prognostic indicator.
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Brief Bioinform
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
Biotherapeutics Molecule Discovery, Boehringer Ingelheim Pharmaceutical Inc., 900 Ridgebury Road, Ridgefield, CT 06877, United States.
Antibody generation requires the use of one or more time-consuming methods, namely animal immunization, and in vitro display technologies. However, the recent availability of large amounts of antibody sequence and structural data in the public domain along with the advent of generative deep learning algorithms raises the possibility of computationally generating novel antibody sequences with desirable developability attributes. Here, we describe a deep learning model for computationally generating libraries of highly human antibody variable regions whose intrinsic physicochemical properties resemble those of the variable regions of the marketed antibody-based biotherapeutics (medicine-likeness).
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.
View Article and Find Full Text PDFTIGIT and PVRIG are immune checkpoints co-expressed on activated T and NK cells, contributing to tumor immune evasion. Simultaneous blockade of these pathways may enhance therapeutic efficacy, positioning them as promising dual targets for cancer immunotherapy. This study aimed to develop a bispecific antibody (BsAb) to co-target TIGIT and PVRIG.
View Article and Find Full Text PDFEmerg Microbes Infect
January 2025
Key Laboratory of Jiangxi Province for Transfusion Medicine, Department of Blood Transfusion, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, China.
The tRNA-derived small RNAs (tsRNAs) are a new class of non coding RNAs, which are stable in body fluids and can be used as potential biomarkers for disease diagnosis. However, the exact value of tsRNAs in the diagnosis of tuberculosis (TB) is still unclear. The objective of the present study was to evaluate the performance of the serum tsRNAs biosignature to distinguish between active TB, healthy controls, latent TB infection, and other respiratory diseases.
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