The increasing incidence of hepatocellular carcinoma (HCC) is of great concern globally, but the molecular pathogenesis of these tumors remains unclear. Sorafenib is a first-line drug for the treatment of advanced HCC. However, the efficacy of sorafenib in improving patient survival is limited, and most patients inevitably develop resistance to this drug. Recent studies have demonstrated that the activation of the IRE1α–XBP1s pathway might play a protective role in the response to sorafenib and contribute to malignancy in HCC. Here, we found that RCN1, an endoplasmic reticulum resident protein, is significantly upregulated in sorafenib-resistant HCC cells and promotes tumor progression. Our analysis showed that RCN1 may be an independent predictor of tumor recurrence and overall survival. Mechanistically, RCN1 promotes the dissociation of GRP78 from IRE1α in sorafenib-resistant cells by interacting with GRP78 through its EFh1/2 domain. Subsequently, the IRE1α–XBP1s pathway, a branch of the unfolded protein response, is sustainably activated. Interestingly, IRE1α–XBP1s pathway activity is required for c-MYC signaling, one of the most highly activated oncogenic pathways in HCC. These results suggest that RCN1-targeted therapy might be a feasible strategy for the treatment of HCC.
Background. GXYLT2 (glucoside xylosyltransferase 2) was known as an important gene that regulates classical Notch signaling and is involved in progression in human tumors. However, the correlation between GXYLT2 expression and bladder cancer remains unclear. Methods. GXYLT2 expression was analyzed by ONCOMINE database, GEPIA database, and TIMER database. The Cancer Genome Atlas (TCGA) was utilized to confirm relationships between GXYLT2 and molecular subtypes of BLCA (bladder cancer). We discovered prognostic value of GXYLT2 in BLCA using GEPIA, LinkedOmics database, and Kaplan-Meier Plotter database. Subsequently, correlations between GXYLT2 and tumor immune infiltration were investigated through TIMER and TISIDB website. We then downloaded data of patients with BLCA from TCGA website, to conduct functional annotations and to construct protein-protein interaction network through STRING and Enrich web servers. Results. Significant differences were observed between GXYLT2 expression of bladder cancer and normal tissues. GXYLT2 was a poor prognostic biomarker in BLCA with impact on diverse clinical characteristics. We found that GXYLT2 was closely related to tumor immune infiltrated cells and immune genes. Functional annotations indicated that GXYLT2 was linked to immune-related pathways. Conclusions. The results suggested that GXYLT2 was associated with a poor prognosis and tumor immune cell infiltration of BLCA. GXYLT2 could be a promising therapeutic target in bladder cancer.
Background: Gastric cancer (GC) is one of the most common cancers in the world. Patients with GC who experienced early relapse have poor prognosis. We aim to develop an early relapse-associated gene signature to optimize prognosis prediction in patients with replapsing GC. Methods: The GC cohorts including GSE62254 set (N=300) and GSE15459 set (N=192) were extracted from Gene Expression Omnibus (GEO) database. Propensity score matching (1:1) based on pathological stage was executed between patients with early relapse and long-term survival from GSE62254 set. Global transcriptome analysis was performed between the two groups to identify early relapse-associated gene. Based on the differentially expressed genes, we developed a classifier incorporating 5 genes that using LASSO Cox regression model. The signature’s prognostic value was internally validated in 210 GC patients and validated in GSE15459 set externally. The patients from GSE62254 set could be divided into high-risk or low-risk group.Results: In the train set, patients in high-risk group had poor prognosis as compared to those in low-risk group [hazard ratio (HR): 3.002, 95% confidence interval (CI): 2.132-4.226, P<0.001)]. Good reproducibility for the prognostic value of early relapse-associated gene signature was verified in the internal validation set (HR: 2.772, 95% CI: 1.836–4.184, P<0.001) and another external validation set (HR: 1.733, 95% CI: 1.149–2.614, P=0.009). Also, we developed a nomogram which integrated the five mRNA classifier, pathological stage and lymph node ratio (LNR) to evaluate prognosis based on GSE62254 set. Time-dependent receiver-operating characteristic at 1 year demonstrated that integrated signature had better prognostic accuracy [area under curve (AUC=0.849)] than the American Joint Commission on Cancer TNM staging system (AUC=0.773) and LNR (AUC=0.811) in GSE62254 set. Conclusions: This study suggest that an early relapse-associated gene signature that can robustly divide gastric cancer patients into two groups with distinctive prognosis. This classifier may contribute to select gastric cancer patients with poor prognosis who require more frequent follow-up and more aggressive therapeutic intervention.
BackgroundBreast cancer (BC) is the most common malignant tumor in women and widely known for its poor prognosis. More and more research has discovered that cyclin E1 (CCNE1) plays an important role in progression of various types of cancer. But its specific mechanism in BC progression still needs further research to explore.MethodsAt first, we determined the expression and prognostic value of CCNE1 through The Cancer Genome Atlas (TCGA) database and The Genotype-Tissue Expression (GTEx) data. Then, we predicted the upstream non-coding RNAs of CCNE1 through StarBase, GEPIA, and Kaplan-Meier plotter database. We further studied the correlation of CCNE1 expression with BC immune cell infiltration, biomarkers of immune cells and immune checkpoints expression through TIMER and GEPIA databases.ResultsThe results suggested that CCNE1 was significantly upregulated in BC and its high expression was correlated with poor prognosis in BC patients. Next, we identified long noncoding RNA (lncRNA) LINC00511 / microRNA-195-5p (miR-195-5p) / CCNE1 axis as the most potential pathway that could regulate CCNE1 expression in BC through StarBase, GEPIA, and Kaplan-Meier plotter database. Furthermore, our in-depth research discovered that CCNE1 expression level was significantly correlated with tumor immune cell infiltration, biomarkers of immune cells, and immune checkpoint expression in BC.ConclusionIn summary, high expression level of CCNE1 was significantly correlated with poor prognosis, tumor immune infiltration and escape in BC.
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