METHODS: Based on the EM transcriptomic datasets GSE7305 and GSE23339, as well as the IBD transcriptomic datasets GSE87466 and GSE126124, differential gene analysis was performed using the limma package in the R environment. Co-expressed differentially expressed genes were identified, and a protein-protein interaction (PPI) network for the differentially expressed genes was constructed using the 11.5 version of the STRING database. The MCODE tool in Cytoscape facilitated filtering out protein interaction subnetworks. Key genes in the PPI network were identified through two topological analysis algorithms (MCC and Degree) from the CytoHubba plugin. Upset was used for visualization of these key genes. The diagnostic value of gene expression levels for these key genes was assessed using the Receiver Operating Characteristic (ROC) curve and Area Under the Curve (AUC) The CIBERSORT algorithm determined the infiltration status of 22 immune cell subtypes, exploring differences between EM and IBD patients in both control and disease groups. Finally, different gene expression trends shared by EM and IBD were input into CMap to identify small molecule compounds with potential therapeutic effects.

RESULTS: 113 differentially expressed genes (DEGs) that were co-expressed in EM and IBD have been identified, comprising 28 down-regulated genes and 86 up-regulated genes. The co-expression differential gene of EM and IBD in the functional enrichment analyses focused on immune response activation, circulating immunoglobulin-mediated humoral immune response and humoral immune response. Five hub genes (SERPING1、VCAM1、CLU、C3、CD55) were identified through the Protein-protein Interaction network and MCODE.High Area Under the Curve (AUC) values of Receiver Operating Characteristic (ROC) curves for 5hub genes indicate the predictive ability for disease occurrence.These hub genes could be used as potential biomarkers for the development of EM and IBD. Furthermore, the CMap database identified a total of 9 small molecule compounds (TTNPB、CAY-10577、PD-0325901 etc.) targeting therapeutic genes for EM and IBD.

METHODS: We introduce a new node representation method based on initial information fusion, called FFANE, which amalgamates PPI networks and protein sequence data to enhance the precision of PPIs' prediction. A Gaussian kernel similarity matrix is initially established by leveraging protein structural resemblances. Concurrently, protein sequence similarities are gauged using the Levenshtein distance, enabling the capture of diverse protein attributes. Subsequently, to construct an initial information matrix, these two feature matrices are merged by employing weighted fusion to achieve an organic amalgamation of structural and sequence details. To gain a more profound understanding of the amalgamated features, a Stacked Autoencoder (SAE) is employed for encoding learning, thereby yielding more representative feature representations. Ultimately, classification models are trained to predict PPIs by using the well-learned fusion feature.

RESULTS: When employing 5-fold cross-validation experiments on SVM, our proposed method achieved average accuracies of 94.28%, 97.69%, and 84.05% in terms of Saccharomyces cerevisiae, Homo sapiens, and Helicobacter pylori datasets, respectively.

RECENT FINDINGS: Several F-box containing proteins have been characterized either as tumor suppressors (FBXW8, FBXL3, FBXW8, FBXL3, FBXO1, FBXO4, and FBXO18) or as oncogenes (FBXO5, FBXO9, and SKP2). Besides, F-box members like βTrcP1 and βTrcP2, the ones with context-dependent functionality, have also been studied and reported. FBXW7 is a well-studied F-box protein and is a tumor suppressor. FBXW7 regulates the activity of a range of substrates, such as c-Myc, cyclin E, mTOR, c-Jun, NOTCH, myeloid cell leukemia sequence-1 (MCL1), AURKA, NOTCH through the well-known ubiquitin-proteasome system (UPS)-mediated degradation pathway. NOTCH signaling is a primitive pathway that plays a crucial role in maintaining normal tissue homeostasis. FBXW7 regulates NOTCH protein activity by controlling its half-life, thereby maintaining optimum protein levels in tissue. However, aberrations in the FBXW7 or NOTCH expression levels can lead to poor prognosis and detrimental outcomes in patients. Therefore, the FBXW7-NOTCH axis has been a subject of intense study and research over the years, especially around the interactome's role in driving cancer development and progression. Several studies have reported the effect of FBXW7 and NOTCH mutations on normal tissue behavior. The current review attempts to critically analyze these mutations prognostic value in a wide range of tumors. Furthermore, the review summarizes the recent findings pertaining to the FBXW7 and NOTCH interactome and its involvement in phosphorylation-related events, cell cycle, proliferation, apoptosis, and metastasis.