Detection of lower levels of SNAP25 using multiple microarray systems and its functional significance in medulloblastoma

Huang, Chin Chou; Lee, Chia Long; Liu, Chih Yi; Huang, Shih‐Han; Hou, Jia‐Woei; Chen, Yi Hou; Chien, Chih Cheng; Ho, Chih Ming; Lo, Wen Cheng; Hung, Kun Long

doi:10.3892/ijmm.2017.2925

Cited by 8 publications

(8 citation statements)

References 60 publications

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“…Since the atomic representations were obtained by two-layer GCN, thus each atom might represent chemical sub-structure. The previous study showed that synaptosomal-associated protein 25 (SNAP25), was associated with the effects of targeted chemotherapy [Huang et al, 2017]. Hodel et al reported that the reduction of SNAP25 expression level providing a target for the development of therapeutic treatments [Hodel, 1998].…”

Section: Results and Analysismentioning

confidence: 99%

DTSyn: a dual-transformer-based neural network to predict synergistic drug combinations

Gao²,

Fang³

et al. 2022

Preprint

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Drug combination therapies are superior to monotherapy for cancer treatment in many ways when addressing tumor heterogeneity issue. For wet-lab experiment, screening out novel synergistic drug pairs is challenging due to the enormous searching space of possible drug pairs. Thus, computational methods have been developed to predict drug pairs with potential synergistic function. Notwithstanding the success of current models, the power of generalization to other datasets as wells as understanding of mechanism for chemical-chemical interaction or chemical-sample interaction are lack of study, hindering current algorithms from real application. In this paper, we proposed a deep neural model termed DTSyn (Dual Transformer model for drug pair Synergy prediction) based on multi-head attention mechanism to identify novel drug combinations. We designed a fine-granularity transformer for capturing chemical substructure-gene and gene-gene associations and a coarse-granularity transformer for extracting and chemical-chemical and chemical-cell line interactions. DTSyn achieves highest Receiver operating characteristic area under curve (ROC AUC) of 0.73, 0.78. 0.82 and 0.81 on four different cross validation tasks, outperforming all competing methods. Further, DTSyn achieved best True Positive Rate (TPR) over five independent datasets. The ablation study showed that both transformer blocks contributed to the performance of DTSyn. In addition, DTSyn can extract interactions among chemicals and cell lines, which may represent the mechanisms of drug action. Thus, we envision our model a valuable tool to prioritize synergistic drug pairs by utilizing chemicals and transcriptome data.

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Section: Results and Analysismentioning

confidence: 99%

DTSyn: a dual-transformer-based neural network to predict synergistic drug combinations

Gao²,

Fang³

et al. 2022

Preprint

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“…An increase in SNAP-25 expression was reported in neuroblastoma SH-SY5Y cells during neuritogenesis [ 33 ], and is overexpressed in tumor cells of prolactinomas [ 34 ]. On the other hand, a low expression level of SNAP-25 has been found in medulloblastoma tumors associated with defects in dendrite formation and in the impairment of targeted chemotherapy [ 35 ].…”

Section: Resultsmentioning

confidence: 99%

Proteomic Profiling of Retinoblastoma-Derived Exosomes Reveals Potential Biomarkers of Vitreous Seeding

Galardi

Colletti

Lavarello

et al. 2020

Cancers

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Retinoblastoma (RB) is the most common tumor of the eye in early childhood. Although recent advances in conservative treatment have greatly improved the visual outcome, local tumor control remains difficult in the presence of massive vitreous seeding. Traditional biopsy has long been considered unsafe in RB, due to the risk of extraocular spread. Thus, the identification of new biomarkers is crucial to design safer diagnostic and more effective therapeutic approaches. Exosomes, membrane-derived nanovesicles that are secreted abundantly by aggressive tumor cells and that can be isolated from several biological fluids, represent an interesting alternative for the detection of tumor-associated biomarkers. In this study, we defined the protein signature of exosomes released by RB tumors (RBT) and vitreous seeding (RBVS) primary cell lines by high resolution mass spectrometry. A total of 5666 proteins were identified. Among these, 5223 and 3637 were expressed in exosomes RBT and one RBVS group, respectively. Gene enrichment analysis of exclusively and differentially expressed proteins and network analysis identified in RBVS exosomes upregulated proteins specifically related to invasion and metastasis, such as proteins involved in extracellular matrix (ECM) remodeling and interaction, resistance to anoikis and the metabolism/catabolism of glucose and amino acids.

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“… Kobayashi et al (2016) found that SNAP25 protein was expressed in 46% (77/168) of diffuse large B-cell lymphoma (DLBCL) patients and associated with CD5 expression ( P = 0.018). Huang et al (2017) displayed the expression and functional significance of SNAP25 in medulloblastoma.…”

Section: Discussionmentioning

confidence: 99%

Mining the potential prognostic value of synaptosomal-associated protein 25 (SNAP25) in colon cancer based on stromal-immune score

Zou

Duan

et al. 2020

PeerJ

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Background Colon cancer is one of the deadliest tumors worldwide. Stromal cells and immune cells play important roles in cancer biology and microenvironment across different types of cancer. This study aimed to identify the prognostic value of stromal/immune cell-associated genes for colon cancer in The Cancer Genome Atlas (TCGA) database using bioinformatic technology. Methods The gene expression data and corresponding clinical information of colon cancer were downloaded from TCGA database. Stromal and immune scores were estimated based on the ESTIMATE algorithm. Sanger software was used to identify the differentially expressed genes (DEGs) and prognostic DEGs based on stromal and immune scores. External validation of prognostic biomarkers was conducted in Gene Expression Omnibus (GEO) database. Gene ontology (GO) analysis, pathway enrichment analysis, and gene set enrichment analysis (GSEA) were used for functional analysis. STRING and Cytoscape were used to assess the protein-protein interaction (PPI) network and screen hub genes. Quantitative real-time PCR (qRT-PCR) was used to validate the expression of hub genes in clinical tissues. Synaptosomal-associated protein 25 (SNAP25) was selected for analyzing its correlations with tumor-immune system in the TISIDB database. Results Worse overall survivals of colon cancer patients were found in high stromal score group (2963 vs. 1930 days, log-rank test P = 0.038) and high immune score group (2894 vs. 2230 days, log-rank test P = 0.076). 563 up-regulated and 9 down-regulated genes were identified as stromal-immune score-related DEGs. 70 up-regulated DEGs associated with poor outcomes were identified by COX proportional hazard regression model, and 15 hub genes were selected later. Then, we verified aquaporin 4 (AQP4) and SNAP25 as prognostic biomarkers in GEO database. qRT-PCR results revealed that AQP4 and SNAP25 were significantly elevated in colon cancer tissues compared with adjacent normal tissues (P = 0.003, 0.001). GSEA and TISIDB suggested that SNAP25 involved in cancer-related signaling pathway, immunity and metabolism progresses. Conclusion SNAP25 is a microenvironment-related and immune-related gene that can predict poor outcomes in colon cancer.

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Detection of lower levels of SNAP25 using multiple microarray systems and its functional significance in medulloblastoma

Cited by 8 publications

References 60 publications

DTSyn: a dual-transformer-based neural network to predict synergistic drug combinations

DTSyn: a dual-transformer-based neural network to predict synergistic drug combinations

Proteomic Profiling of Retinoblastoma-Derived Exosomes Reveals Potential Biomarkers of Vitreous Seeding

Mining the potential prognostic value of synaptosomal-associated protein 25 (SNAP25) in colon cancer based on stromal-immune score

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