MSRB3 promotes the progression of clear cell renal cell carcinoma via regulating endoplasmic reticulum stress

Exploration of hub genes, lipid metabolism, and the immune microenvironment in stomach carcinoma and cholangiocarcinoma

Background

Gastric cancer (GC) is the 5th most common cause of cancer in the world and the 3rd largest cause of cancer-related death. It is usually associated with a variety of cancers, of which cholangiocarcinoma (CCA) combined with GC accounts for about 1.6%. This study sought to examine the hub genes and role of lipid metabolism in the development and diagnosis of GC and CCA.

Methods

To screen potential hub genes, The Cancer Genome Atlas (TCGA) data sets, including the GC (STAD, dataset of GC) and CCA (CHOL, dataset of CCA) data sets, were used to conduct a differentially expressed gene (DEG) analysis and an enrichment analysis of the DEGs. A weighted-gene co-expression network analysis (WGCNA) was conducted to identify the significant gene module and then find the hub genes in the module. To verify the 4 hub genes, we conducted a differentiation analysis of the 4 genes in GC and CCA and found that there were differences. A survival analysis of the hub genes was performed and mutations were mapped. Additionally, tumor immune microenvironment (TIME) and immune analyses were performed to evaluate how lipid metabolism affects the development of GC with CCA.

Results

The principal component analysis showed that both GC and CCA had distinct up-regulated and down-regulated genes, which are involved in a variety of metabolic processes. Upon WGCNA, the turquoise and blue modules were meaningful, and the hub genes were identified from these 2 modules. Four hub genes were identified: amyloid beta precursor protein binding family B member 1 (APBB1), Homo sapiens armadillo repeat containing X-linked 1 (ARMCX1), DAZ interacting zinc finger protein 1 (DZIP1), and methionine sulfoxide reductase B3 (MSRB3). In survival analysis, increased expression of the 4 hub genes was associated with inferior survival outcomes, with variations in all 4 genes. Additionally, we demonstrated that genes related to lipid metabolism had an effect on immune function.

Conclusions

APBB1, ARMCX1, DZIP1, and MSRB3 affect the development of GC and CCA and can be used as biomarkers. The expression of lipid metabolism genes is related to the TIME of patients with GC and CCA.

Endoplasmic Reticulum Stress-Related Signature Predicts Prognosis and Drug Response in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer. The maximum number of deaths associated with kidney cancer can be attributed to ccRCC. Disruption of cellular proteostasis results in endoplasmic reticulum (ER) stress, which is associated with various aspects of cancer. It is noteworthy that the role of ER stress in the progression of ccRCC remains unclear. We classified 526 ccRCC samples identified from the TCGA database into the C1 and C2 subtypes by consensus clustering of the 295 ER stress-related genes. The ccRCC samples belonging to subtype C2 were in their advanced tumor stage and grade. These samples were characterized by poor prognosis and malignancy immune microenvironment. The upregulation of the inhibitory immune checkpoint gene expression and unique drug sensitivity were also observed. The differentially expressed genes between the two clusters were explored. An 11-gene ER stress-related prognostic risk model was constructed following the LASSO regression and Cox regression analyses. In addition, a nomogram was constructed by integrating the clinical parameters and risk scores. The calibration curves, ROC curves, and DCA curves helped validate the accuracy of the prediction when both the TCGA dataset and the external E-MTAB-1980 dataset were considered. Moreover, we analyzed the differentially expressed genes common to the E-MTAB-1980 and TCGA datasets to screen out new therapeutic compounds. In summary, our study can potentially help in the comprehensive understanding of ER stress in ccRCC and serve as a reference for future studies on novel prognostic biomarkers and treatments.

The Lipid Droplet Knowledge Portal: A resource for systematic analyses of lipid droplet biology

Lipid droplets (LDs) are organelles of cellular lipid storage with fundamental roles in energy metabolism and cell membrane homeostasis. There has been an explosion of research into the biology of LDs, in part due to their relevance in diseases of lipid storage, such as atherosclerosis, obesity, type 2 diabetes, and hepatic steatosis. Consequently, there is an increasing need for a resource that combines datasets from systematic analyses of LD biology. Here, we integrate high-confidence, systematically generated human, mouse, and fly data from studies on LDs in the framework of an online platform named the "Lipid Droplet Knowledge Portal" (https://lipiddroplet.org/). This scalable and interactive portal includes comprehensive datasets, across a variety of cell types, for LD biology, including transcriptional profiles of induced lipid storage, organellar proteomics, genome-wide screen phenotypes, and ties to human genetics. This resource is a powerful platform that can be utilized to identify determinants of lipid storage.

Identification of circRNA-miRNA-mRNA Regulatory Network in Bladder Cancer by Integrated Analysis

INTRODUCTION

Bladder cancer (BC) is a common malignant tumor in the urinary system with high mortality and recurrence rates. This study sought to identify crucial circular RNAs (circRNAs) associated with BC.

METHODS

The mRNA, miRNA, and circRNA expression profiles of BC were downloaded from GEO database. The differentially expressed mRNAs (DEmRNAs), miRNAs (DEmiRNAs), and circRNAs (DEcircRNAs) were identified using bioinformatics method. Combining circRNA-miRNA pairs with miRNA-mRNA pairs, the competing endogenous RNA (ceRNA; DEcircRNA-DEmi-RNA-DEmRNA) regulatory network was constructed. Functional annotation of host gene of DEcircRNAs and DEmRNAs in ceRNA regulatory network were performed. qRT-PCR validation was performed.

RESULTS

A total of 4,003 DEmRNAs, 25 DEmiRNAs, and 119 DEcircRNAs were obtained. The ceRNA network contained 18 circRNA-miRNA pairs and 699 mi-RNA-mRNA pairs, including 17 circRNAs, 4 miRNAs, and 624 mRNAs. Functional annotation of DEmRNAs in ceRNA regulatory network revealed that these DEmRNAs were significantly enriched in glycerolipid metabolism, p53 signaling pathway, and oocyte meiosis. Except for hsa_circ_0028173, expression of the others in the qRT-PCR results was consistent with that in our integrated analysis, generally.

CONCLUSION

We speculate that hsa_circ_0008035/hsa-miR-107/MSRB3 and hsa_circ_0028173/hsa-miR-338-3p/TPX2/GATA3 interaction pairs may play a vital role in BC.