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PubMed2026

Increased expression of Ribonucleic acid export 1 (RAE1) gene promotes gastric carcinogenesis and is associated with Hippo signaling pathway.

BACKGROUND: Ribonucleic acid export 1 (RAE1) autoantibody may have good potential for early detection of gastric cancer (GC). However, the carcinogenicity of RAE1 in GC remains unknown. We aimed to explore the role and the potential mechanism for RAE1 in the carcinogenesis of GC. METHODS: Immunohistochemical assay was applied to analyze the expression of RAE1 in GC and precancerous lesion (PL) tissues and its relationship with clinical characteristics. The effects of RAE1 on proliferation, migration, apoptosis, and cell cycle were explored by constructing RAE1 knockdown and overexpression in GC cells. The effects of RAE1 knockdown on tumor growth were observed in a murine xenograft model. The signaling pathways involved in GC development that may be affected by RAE1 were investigated by transcriptome sequencing and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. RESULTS: Immunohistochemical expression of RAE1 was significantly higher in early GC patients than in PL and normal tissues, and the RAE1 expression was correlated with clinical stage (P<0.001). In vitro, knockdown of RAE1 inhibited the proliferation and migration of GC cells with promoted apoptosis and arrested cell cycle in the S phase, while overexpression of RAE1 showed the opposite trend. In vivo, knockdown of RAE1 inhibited the growth of subcutaneous graft tumors in mice. Transcriptome sequencing and subsequent analysis of RAE1 knockdown cells revealed that the Hippo signaling pathway was activated by RAE1 knockdown. CONCLUSIONS: RAE1 promotes GC cells proliferation and migration and is associated with the inhibition of the Hippo signaling pathway, and may be a potential biomarker for early diagnosis and treatment of GC.

Gastric cancer (GC)↗

PubMed2026

Machine Learning-Based Preoperative Predicting TERT Promoter Mutation and EGFR Gene Amplification Phenotype in IDH Wild-Type Glioblastoma Using Advanced MR Habitat Imaging.

BACKGROUND AND PURPOSE: The telomerase reverse transcriptase (TERT) gene promoter mutation is a crucial factor for identifying an isocitrate dehydrogenase (IDH) wild-type glioblastoma with poor prognosis, and the epidermal growth factor receptor (EGFR) amplification may be a potential prognostic factor. The purpose of this study was to investigate the value of the tumor habitats imaging model on advanced MRI in predicting TERT promoter mutation and EGFR gene amplification phenotype of IDH wild-type glioblastoma. MATERIALS AND METHODS: One hundred seventy-nine patients with pretreatment conventional MRI, DWI, and DSC-PWI were included. The data were divided into the training set (n=112), test set (n=29), and time-independent validation set (n=38). Based on the ADC and CBV map, the solid tumor area was split into several habitat subregions using the k-means clustering algorithm (hypovascular hypercellular area, hypervascular area, and hypovascular hypocellular area). In the training set, TERT promoter mutation and EGFR gene amplification phenotype prediction models were constructed using the random forest method. The reliability of prediction models was validated in the test and the time-independent validation sets. Receiver operating characteristic (ROC) curve analysis, calibration curve, and decision curve analysis (DCA) were used. RESULTS: The area under the curve (AUC) of the training, test, and validation sets of the TERT promoter prediction model was 0.877, 0.783, and 0.796, respectively. The accuracy of the TERT promoter prediction model was 82.1%, 75.9%, and 76.3%, respectively. The AUCs of the 3 sets for the EGFR gene amplification status prediction model were 0.877, 0.784, and 0.878, respectively. The accuracy of the EGFR gene amplification status prediction model was 79.5%, 75.9%, and 89.5%, respectively. Moreover, the prediction probability of these models was in good agreement with the actual result. CONCLUSIONS: The tumor habitat imaging model based on advanced MRI was useful for accurately predicting TERT promoter mutation and EGFR amplification status in IDH wild-type glioblastoma.

Humans↗