Evaluation of the potential role of long non-coding RNA LINC00961 in luminal breast cancer: a case-control and systems biology study

LncRNAs in Immune and Stromal Cells Remodel Phenotype of Cancer Cell and Tumor Microenvironment

Emerging studies suggest that long non-coding RNAs (lncRNAs) participate in the mutual regulation of cells in tumor microenvironment, thereby affecting the anti-tumor immune activity of immune cells. Additionally, the intracellular pathways mediated by lncRNAs can affect the expression of immune checkpoints or change the cell functions, including cytokines secretion, of immune and stromal cells in tumor microenvironment, which further influences cancer patients' prognosis and treatment response. With the in-depth research, lncRNAs have shown great potency as a new immunotherapy target and predict immunotherapy response. The research on lncRNAs provides us with a new insight into developing new immunotherapy drugs and predicting the outcome of immunotherapy. With development of RNA sequencing technology, amounts of lncRNAs were found to be dysregulated in immune and stromal cells rather than tumor cells. These lncRNAs function through ceRNA network or regulating transcript factor activity, thus leading abnormal differentiation and activation of immune and stromal cells. Here, we review the function of lncRNAs in the immune microenvironment and focus on the alteration of lncRNAs in immune and stromal cells, and discuss how these alterations affect tumor growth, metastasis and treatment response.

Identifying endoplasmic reticulum stress-related genes as new diagnostic and prognostic biomarkers in clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is one of the most common cancers worldwide, and its incidence is increasing every year. Endoplasmic reticulum stress (ERS) caused by protein misfolding has broad and profound effects on the progression and metastasis of various cancers. Accumulating evidence suggests that ERS is closely related to the occurrence and progression of ccRCC. This study aimed to identify ERS-related genes for evaluating the prognosis of ccRCC.

Methods

Transcriptomic expression profiles were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), and clinical data were downloaded from the TCGA. First, the differentially expressed genes (DEGs) were analyzed using the limma package, and the DEGs related to ERS (ERS-DEGs) were identified from the GeneCards database. Second, a function and pathway enrichment analysis and a Gene Set Enrichment Analysis (GSEA) were performed. Third, a protein-protein interaction (PPI) network was constructed to identify the hub genes, and a gene-micro RNA (miRNA) network and gene-transcription factor (TF) network were established using the hub genes. Finally, a least absolute shrinkage and selection operator (LASSO) regression analysis was conducted to establish a diagnostic model, and a Cox analysis was used to analyze the correlations between the expression of the characteristic genes and the clinical characteristics.

Results

We identified 11 signature genes and established a diagnostic model. Further, the Cox analysis results revealed a correlation between the expression levels of the signature genes and the clinical characteristics. Ultimately, five signature genes (i.e., TNFSF13B, APOL1, COL5A3, and CDH5) were found to be associated with a poor prognosis.

Conclusions

This study suggests that TNFSF13B, APOL1, COL5A3, and CDH5 may have potential as prognostic biomarkers in ccRCC and may provide new evidence to support targeted therapy in ccRCC.

Assessment of Significant Pathway Signaling and Prognostic Value of GNG11 in Ovarian Serous Cystadenocarcinoma

BACKGROUND

GNG11 (G protein subunit gamma 11) is a member of guanine nucleotide-binding protein (G protein) gamma family. Few studies elucidated the role of GNG11 in human disease, especially in tumors. The present study initially analyzed the function of GNG11 in ovarian serous cystadenocarcinoma.

METHODS

The differential expression of GNG11 mRNA in ovarian cancer and normal tissues was evaluated through Oncomine, CCLE, Gepia, UCSC Xena and UALCAN databases. The protein expression of GNG11 was assessed via HPA database. Prognosis analysis was performed by Kaplan-Meier Plotter. Restrict survival analysis to subtypes including tumor grade, cancer stage and TP53 mutation status was then carried out. GSEA enrichment analysis was performed to explore the significant pathways associated with GNG11 in ovarian cancer. Finally, the upstream miRNAs of GNG11 were predicted by DIANA, Target Scan, miRDB and miRWalk databases, and the potential key KEGG pathways were subsequently determined by DIANA.

RESULTS

The mRNA expression of GNG11 was down-regulated in ovarian cancer patients (P<0.05). The cancer stage of patients correlated with the expression of GNG11 (P<0.05). Survival analysis indicated that GNG11 high expression statistically shortened the overall survival time of patients (HR=1.26, P=0.0043) compared with low expression group, especially for the patients with earlier stage (HR=2.48, P=0.035) and lower grade (HR=1.72, P=0.0016). Subsequently, the consistent upstream miRNA of GNG11, hsa-miR-22-5p, was predicted from 4 databases. The differential expression profile of hsa-miR-22-5p in blood was observed in ovarian cancer patients. According to the GSEA analysis on GNG11 and KEGG analysis on hsa-miR-22-5p, the consistent pathway of ECM-receptor interaction was observed (all P<0.01). ECM-receptor interaction pathway and differential expression of hsa-miR-22-5p in blood suggested the migration risk of ovarian cancer.

CONCLUSION

High expression of GNG11 indicated the poor prognosis of ovarian cancer patients. GNG11 might play a crucial role in the biological process of ovarian serous cystadenocarcinoma by ECM-receptor interaction pathway, thus affecting the prognosis of patients.

Knockdown of UCA1 restrains cell proliferation and metastasis of diffuse large B-cell lymphoma by counteracting miR-331-3p expression

Long non-coding RNA urothelial cancer associated 1 (UCA1) has been reported to act as a carcinogen in bladder cancer, while its role in diffuse large B-cell lymphoma (DLBCL) remains unclear. The present study was designed to explore the expression pattern and role of UCA1 in DLBCL. The expression pattern of UCA1 and microRNA (miR)-331-3p in DLBCL tissues and cell lines were detected by RT-qPCR. Dual luciferase reporter assay was performed to explore the relationship between UCA1 and miR-331-3p. Cell proliferation was explored by MTT assay. Cell migration and invasion abilities were assessed by Transwell assay. In the present study, it was revealed that the expression of UCA1 was significantly upregulated, while miR-331-3p was downregulated in DLBCL tissues and cell lines. Moreover, UCA1 was revealed to competitively bind with miR-331-3p in DLBCL. Functionally, knockdown of UCA1 was revealed to suppress cell proliferation, migration and invasion in DLBCL cells. Furthermore, upregulation of miR-331-3p prevented cell proliferation, migration and invasion in DLBC cells. In conclusion, the present findings firstly demonstrated that UCA1 silencing restrained DLBCL cell proliferation and metastases viability by suppressing miR-331-3p expression. It is suggested that UCA1 could be a possible medicinal target and biomarker for DLBCL.