High GJB2 mRNA expression and its prognostic significance in lung adenocarcinoma: a study based on the TCGA database

Integrative analyses identified gap junction beta-2 as a prognostic biomarker and therapeutic target for breast cancer

Background

Increasing evidence has shown that connexins are involved in the regulation of tumor development, immune escape, and drug resistance. This study investigated the gene expression patterns, prognostic values, and potential mechanisms of connexins in breast cancer.

Methods

We conducted a comprehensive analysis of connexins using public gene and protein expression databases and clinical samples from our institution. Connexin mRNA expressions in breast cancer and matched normal tissues were compared, and multiomics studies were performed.

Results

Gap junction beta-2 mRNA was overexpressed in breast cancers of different pathological types and molecular subtypes, and its high expression was associated with poor prognosis. The tumor membrane of the gap junction beta-2 mutated group was positive, and the corresponding protein was expressed. Somatic mutation and copy number variation of gap junction beta-2 are rare in breast cancer. The gap junction beta-2 transcription level in the p110α subunit of the phosphoinositide 3-kinase mutant subgroup was higher than that in the wild-type subgroup. Gap junction beta-2 was associated with the phosphoinositide 3-kinase-Akt signaling pathway, extracellular matrix-receptor interaction, focal adhesion, and proteoglycans in cancer. Furthermore, gap junction beta-2 overexpression may be associated with phosphoinositide 3-kinase and histone deacetylase inhibitor resistance, and its expression level correlated with infiltrating CD8+ T cells, macrophages, neutrophils, and dendritic cells.

Conclusions

Gap junction beta-2 may be a promising therapeutic target for targeted therapy and immunotherapy and may be used to predict breast cancer prognosis.

Pan-cancer analysis of the prognostic and immunological role of GJB2: a potential target for survival and immunotherapy

Background

GJB2 plays an essential role in the growth and progression of several cancers. However, asystematic pan-cancer analysis of GJB2 is lacking. Therefore, in this study, we performed a comprehensive pan-cancer analysis to determine the potential role of GJB2 in prognostic prediction and cancer immunotherapy response.

Methods

The differential expression of GJB2 in the tumor and adjacent normal tissues of various cancer types was analyzed using the TIMER, GEPIA, and Sangerbox databases. GEPIA and Kaplan-Meier plotter databases were used to analyze the survival outcomes based on GJB2 expression levels in pan-cancer. Furthermore, the association of GJB2 expression with the immune checkpoint (ICP) genes, tumor mutational load (TMB), microsatellite instability (MSI), neoantigens, and tumor infiltration of immune cells was analyzed using via the Sangerbox database. The cBioPortal database was used to determine the characteristics of GJB2 gene alterations in the cancer tissues. The STRING database was used to identify the GJB2-binding proteins. GEPIA database was used to identify the GJB2 co-expressed genes. DAVID was used to perform the functional enrichment analysis of gene ontology (GO) terms and KEGG pathways associated with GJB2. Finally, the mechanistic role of GJB2 in pancreatic adenocarcinoma (PAAD) was analyzed using the LinkedOmics database.

Results

The GJB2 gene was highly expressed in a variety of tumors. Furthermore, GJB2 expression levels showed significant positive or negative association with the survival outcomes in various cancers. GJB2 expression levels cor related with tumor mutational burden, microsatellite instability, neoantigens, and tumor infiltration of immune cells in multiple cancers. This suggested that GJB2 played a critical role in the tumor microenvironment. Functional enrichment analysis showed that the biological role of GJB2 in tumors included modulation of gap junction-mediated intercellular transport, regulation of cell communication by electrical coupling, ion transmembrane transport, autocrine signaling, apoptotic signaling pathway, NOD-like receptor signaling pathway, p53 signaling pathway, and PI3K-Akt signaling pathway.

Conclusions

Our study demonstrated that GJB2 played a significant role in tumorigenesis and tumor immunity in multiple cancers. Furthermore, GJB2 is a potential prognostic biomarker and a promising therapeutic target in multiple types of cancers.

Evolutionary Analysis of TCGA Data Using Over- and Under- Mutated Genes Identify Key Molecular Pathways and Cellular Functions in Lung Cancer Subtypes

We identify critical conserved and mutated genes through a theoretical model linking a gene’s fitness contribution to its observed mutational frequency in a clinical cohort. “Passenger” gene mutations do not alter fitness and have mutational frequencies determined by gene size and the mutation rate. Driver mutations, which increase fitness (and proliferation), are observed more frequently than expected. Non-synonymous mutations in essential genes reduce fitness and are eliminated by natural selection resulting in lower prevalence than expected. We apply this “evolutionary triage” principle to TCGA data from EGFR-mutant, KRAS-mutant, and NEK (non-EGFR/KRAS) lung adenocarcinomas. We find frequent overlap of evolutionarily selected non-synonymous gene mutations among the subtypes suggesting enrichment for adaptations to common local tissue selection forces. Overlap of conserved genes in the LUAD subtypes is rare suggesting negative evolutionary selection is strongly dependent on initiating mutational events during carcinogenesis. Highly expressed genes are more likely to be conserved and significant changes in expression (>20% increased/decreased) are common in genes with evolutionarily selected mutations but not in conserved genes. EGFR-mut cancers have fewer average mutations (89) than KRAS-mut (228) and NEK (313). Subtype-specific variation in conserved and mutated genes identify critical molecular components in cell signaling, extracellular matrix remodeling, and membrane transporters. These findings demonstrate subtype-specific patterns of co-adaptations between the defining driver mutation and somatically conserved genes as well as novel insights into epigenetic versus genetic contributions to cancer evolution.

Glycoprotein M6A Suppresses Lung Adenocarcinoma Progression via Inhibition of the PI3K/AKT Pathway

Lung adenocarcinoma is the most common subtype of lung cancer and has high morbidity and mortality. Glycoprotein M6A (GPM6A) is a neuronal membrane glycoprotein reported to be related with cancer. However, studies on GPM6A in lung adenocarcinoma are rare. This study aimed to investigate the role of GPM6A in lung adenocarcinoma and its potential mechanism. GPM6A mRNA expression was analysed in 33 types of cancers using The Cancer Genome Atlas (TCGA) datasets. It was compared among normal lung tissues, lung adenocarcinoma tissues, and adjacent tissues using the Oncomine database. Real-time quantitative polymerase chain reaction (RT-qPCR) was performed to detect GPM6A expression in human lung adenocarcinoma cell lines (A549 and H1299) and normal pulmonary epithelial cells (BEAS-2B). When GPM6A was inhibited, cell proliferative capacity was detected by Cell Counting Kit 8 (CCK8), EdU, and colony formation assays. Cell migration ability was detected by wound healing and transwell assays. The expression of epithelial-mesenchymal transition (EMT) markers was detected by Western blotting (WB) and RT-qPCR. When GPM6A was overexpressed, cell proliferation and migration were detected again. Ten nude mice were subcutaneously injected with cells overexpressing GPM6A or empty vector, and the tumor size was recorded on day 14 and then measured every 3 days thereafter. The final tumor weight was measured on day 36. Furthermore, the expressions of phosphoinositide 3-kinase (PI3K), phosphorylated PI3K, AKT, and phosphorylated AKT were detected by WB. Results showed that GPM6A mRNA expression decreased in 15 types of tumors in TCGA dataset. GPM6A expression was lower in lung adenocarcinoma than in normal lung tissues or adjacent tissues in the Oncomine dataset. Similar results were found in lung adenocarcinoma cells. The function study showed that GPM6A downregulation enhanced the proliferation, migration, and EMT of lung adenocarcinoma cells, while GPM6A upregulation inhibited their development. The xenograft results suggested that GPM6A upregulation delayed tumor growth and reduced tumor weight. Moreover, WB showed that GPM6A knockdown activated the PI3K/AKT pathway, while GPM6A upregulation inhibited the activation of the PI3K/AKT pathway. In conclusion, GPM6A suppresses lung adenocarcinoma progression via inhibition of the PI3K/AKT pathway. Thus, GPM6A could be a possible treatment target for lung cancer therapy.

The prognostic value and biological significance of gap junction beta protein 2 (GJB2 or Cx26) in cervical cancer

Objective

To evaluate the prognostic value and explore the biological significance of gap junction protein beta 2 (GJB2 or Cx26) in cervical cancer (CC).

Methods

We first compared GJB2 expression between CC and normal tissues using public databases and immunohistochemistry (IHC). Based on The Cancer Genome Atlas data (TCGA cohort, n = 304) and tissue microarray samples (OBC cohort, n = 111), we explored the prognostic value of GJB2 for CC patients using bioinformatics analysis and IHC scoring. To explore the biological significance of GJB2, Gene set enrichment analysis (GSEA) and Gene Ontology (GO) were performed. The impact of GJB2 on the immune microenvironment was analyzed by CIBERSORTx and ESTIMATE algorithms. We finally investigated the relationship between GJB2 and drug sensitivity based on the Genomics of Drug Sensitivity in Cancer (GDSC).

Results

The expression of GJB2 was significantly increased in CC over normal tissues. Both the TCGA and OBC cohort found that patients with high GJB2 expression had shorter overall survival (OS) time, and high GJB2 expression was the independent risk factor for prognosis (TCGA: HR, 2.566; 95% CI, 1.066–6.180; p = 0.036; OBC: HR, 2.198; 95% CI, 1.019–4.741; p = 0.045). GJB2 was correlated with patient clinical factors such as tumor size and differentiation grade. The p53 signaling pathway and toll-like receptor pathway may be regulated by GJB2. The abundance of various immune cells was significantly different between the low and high GJB2 expression groups. The ImmuneScore was significantly increased in the high GJB2 expression group. In addition, the expression level of GJB2 was positively correlated with the natural log of the half-maximal inhibitory concentration (LN_IC50) value of cisplatin/paclitaxel (Spearman r = 0.238/0.153, p < 0.001).

Conclusion

GJB2 can serve as a potential prognostic marker of poor survival and a therapeutic target in CC. Moreover, GJB2 may affect the immune microenvironment and is correlated with chemoresistance.

Establishing an 8-gene immune prognostic model based on TP53 status for lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) results in a majority of cancer burden worldwide. TP53 is the most commonly mutated in LUAD. This study aimed to reveal the relation between TP53 and tumor microenvironment (TME) for improving LUAD treatment.

Methods

Differentially expressed genes (DEGs) related to immunity were analyzed between TP53‐WT and TP53‐MUT groups. Least absolute shrinkage and selection operator (LASSO) Cox regression was applied to screen prognostic DEGs. Two independent datasets were included to evaluate the robustness of the prognostic model.

Results

An 8‐gene prognostic model containing ANLN, CCNB1, DLGAP5, FAM83A, GJB2, NAPSA, SFTPB, and SLC2A1 was established based on DEGs. LUAD samples were classified into high‐ and low‐risk groups with differential overall survival in the two datasets. M0 macrophages, M1 macrophages, and activated memory CD4 T cells were more enriched in high‐risk group. Immune checkpoints of PDCD1, LAG3, and CD274 were also high‐expressed in high‐risk group.

Conclusion

The study improved the understanding of the role of TP53 in the TME modulation. The 8‐gene model had robust performance to predict LUAD prognosis in clinical practice. In addition, the eight prognostic genes may also serve as potential targets for designing therapeutic drugs for LUAD patients.

Quercitrin restrains the growth and invasion of lung adenocarcinoma cells by regulating gap junction protein beta 2

Lung adenocarcinoma (LUAD) is the most prevalent subtype of non-small cell lung cancer (NSCLC) with high lethality, and quercitrin exhibits anticancer characteristics. Here, we attempted to uncover the anticancer activity of quercitrin in LUAD. In this work, quercitrin prohibited the cell viability and clone-formation of LUAD cells in vitro. Meanwhile, quercitrin treatment reduced the aggressive phenotypes in LUAD cells. Further, Gap Junction Protein Beta 2 (GJB2) expression was aberrantly higher in LUAD when compared within control tissue. The higher expression of GJB2 is associated with an inferior overall survival for patients with LUAD. Finally, the reintroduction of GJB2 offset the inhibiting influence of quercitrin in LUAD cells. Altogether, these findings disclosed that quercitrin suppressed the growth and metastatic-related traits of LUAD cells partly via regulating GJB2 expression.

MicroRNA 181a-2-3p Alleviates the Apoptosis of Renal Tubular Epithelial Cells via Targeting GJB2 in Sepsis-Induced Acute Kidney Injury

Acute kidney injury (AKI) is the most common complication of sepsis. MicroRNAs (miRNAs) play important roles in the sepsis-induced AKI. This paper aimed to explore the role of miRNA 181a-2-3p (miR-181a-2-3p) in the sepsis-induced AKI and the underlying mechanism. Our results revealed that miR-181a-2-3p showed low expression levels in patients with sepsis and mouse models undergoing cecal ligation and puncture (CLP). The addition of miR-181a-2-3p antagonists aggravated the sepsis-induced kidney injuries and inflammatory response in CLP mouse models, as suggested by hematoxylin and eosin (H&E) staining and quantitative real-time PCR (qRT-PCR). In addition, miR-181a-2-3p mimic alleviated the lipopolysaccharide (LPS)-induced inflammatory response, along with apoptosis of TCMK-1. Moreover, results from the GSE46955 data set indicated that GJB2 was highly expressed in septic patients but lowly expressed after recovery. Further, the dual-luciferase reporter assay and RNA immunoprecipitation (RIP) assay were carried out, which confirmed that GJB2 was a target of miR-181a-2-3p, and overexpression of GJB2 reversed the anti-inflammatory and antiapoptotic effects of miR-181a-2-3p mimic on the LPS-induced sepsis cell models. In conclusion, miR-181a-2-3p alleviates the inflammatory response and cell apoptosis of septic patients and animal models by upregulating GJB2 expression, which may provide a new therapeutic strategy for sepsis.

Identification of a 14-Gene Prognostic Signature for Diffuse Large B Cell Lymphoma (DLBCL)

Although immunotherapy is a potential strategy to resist cancers, due to the inadequate acknowledge, this treatment is not always effective for diffuse large B cell lymphoma (DLBCL) patients. Based on the current situation, it is critical to systematically investigate the immune pattern. According to the result of univariate and multivariate cox proportional hazards, LASSO regression and Kaplan-Meier survival analysis on immune-related genes (IRGs), a prognostic signature, containing 14 IRGs (AQP9, LMBR1L, FGF20, TANK, CRP, ORM1, JAK1, BACH2, MTCP1, IFITM1, TNFSF10, FGF12, RFX5, and LAP3), was built. This model was validated by external data, and performed well. DLBCL patients were divided into low- and high-risk groups, according to risk scores from risk formula. The results of CIBERSORT showed that different immune status and infiltration pattern were observed in these two groups. Gene set enrichment analysis (GSEA) indicated 12 signaling pathways were significantly enriched in the high-risk group, such as natural killer cell-mediated cytotoxicity, toll-like receptor signaling pathway, and so on. In summary, 14 clinically significant IRGs were screened to build a risk score formula. This formula was an accurate tool to provide a certain basis for the treatment of DLBCL patients.