Regulation of OLC1 protein expression by the anaphase-promoting complex

Development and Validation of an Inflammatory Response-Related Gene Signature for Predicting the Prognosis of Pancreatic Adenocarcinoma

Pancreatic adenocarcinoma (PAAD) is a highly dangerous malignant tumor of the digestive tract, and difficult to diagnose, treat, and predict the prognosis. As we all know, tumor and inflammation can affect each other, and thus the inflammatory response in the microenvironment can be used to affect the prognosis. So far, the prognostic value of inflammatory response-related genes in PAAD is still unclear. Therefore, this study aimed to explore the inflammatory response-related genes for predicting the prognosis of PAAD. In this study, the mRNA expression profiles of PAAD patients and the corresponding clinical characteristics data of PAAD patients were downloaded from the public database. The least absolute shrinkage and selection operator (LASSO) Cox analysis model was used to identify and construct the prognostic gene signature in The Cancer Genome Atlas (TCGA) cohort. The PAAD patients used for verification are from the International Cancer Genome Consortium (ICGC) cohort. The Kaplan-Meier method was used to compare the overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were performed to identify the independent predictors of OS. Gene set enrichment analysis (GSEA) was performed to obtain gene ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and the correlation between gene expression and immune infiltrates was investigated via single sample gene set enrichment analysis (ssGSEA). The GEPIA database was performed to examine prognostic genes in PAAD. LASSO Cox regression analysis was used to construct a model of inflammatory response-related gene signature. Compared with the low-risk group, patients in the high-risk group had significantly lower OS. The receiver operating characteristic curve (ROC) analysis confirmed the signature's predictive capacity. Multivariate Cox analysis showed that risk score is an independent predictor of OS. Functional analysis shows that the immune status between the two risk groups is significantly different, and the cancer-related pathways were abundant in the high-risk group. Moreover, the risk score is significantly related to tumor grade, stage, and immune infiltration types. It was also obtained that the expression level of prognostic genes was significantly correlated with the sensitivity of cancer cells to anti-tumor drugs. In addition, there are significant differences in the expression of PAAD tissues and adjacent non-tumor tissues. The novel signature constructed from five inflammatory response-related genes can be used to predict prognosis and affect the immune status of PAAD. In addition, suppressing these genes may be a treatment option.

ZHX2 mediates proteasome inhibitor resistance via regulating nuclear translocation of NF-κB in multiple myeloma

Background

Multiple myeloma (MM) is an incurable hematological malignancy. Although proteasome inhibitors and immunomodulators have significantly improved patient outcomes, some patients respond poorly to treatment and almost all patients will relapse. Mechanisms of proteasome inhibitor resistance in multiple myeloma have not been fully elucidated. ZHX2 is a transcription regulator degraded via proteasome and presents both oncogenic or tumor suppressive effect in different cancers, however, it is still unknown that the role of ZHX2 in myeloma. In this study, we aim to demonstrate the effect and mechanism of ZHX2 on proteasome inhibitor resistance in MM.

Methods

GSE24080 gene expression profile datasets from Gene Expression Omnibus (GEO) were analyzed to evaluate the relationship between ZHX2 expression level and survival in MM. Expression of ZHX2 in human MM cell lines at baseline and after bortezomib (BTZ) treatment was determined by Western blotting (WB). The proliferation and apoptosis rate of MM cells treated with BTZ after the knockdown of ZHX2 were analyzed by flow cytometry. Nuclear translocation of NF‐κB after the knockdown of ZHX2 was evaluated by WB and immunofluorescence, and the expression of NF‐κB target genes was measured by real‐time quantitative PCR. Co‐immunoprecipitation (Co‐IP) and WB were used to detect the interaction of ZHX2 with NF‐κB.

Results

We found that higher ZHX2 expression was correlated with poorer clinical outcomes of patients. In addition, ZHX2 expression was relatively higher in RPMI‐8226 and MM.1S cell lines and the level of ZHX2 protein was upregulated after BTZ treatment. Knockdown of ZHX2 significantly enhanced the sensitivity of MM cells to BTZ, inhibited nuclear translocation of NF‐κB, and reduced mRNA expression of NF‐κB target genes. It was also revealed that ZHX2 directly binds to NF‐κB.

Conclusion

Our study showed that ZHX2 can promote proteasome inhibitor resistance in MM cells by regulating the nuclear translocation of NF‐κB.