Expression and correlation analysis of Skp2 and CBX7 in cervical cancer

Long non-coding RNA Linc00657 up-regulates Skp2 to promote the progression of cervical cancer through lipid reprogramming and regulation of immune microenvironment

More and more evidence shows that long non-coding RNA (lncRNA) plays an important role in the biological behavior of many kinds of malignant tumors, but the specific function of lncRNA Linc00657 in cervical cancer is still unknown. The purpose of this study is to explore the effect of Linc00657 on the malignant progression of cervical cancer and its potential mechanism. In two kinds of cervical cancer cell lines and normal cervical epithelial cells, qRT-PCR showed increased expression of Linc00657 in cervical cancer cells. Through MTT, clone formation test, flow cytometry, wound healing test and Transwell test, it has been found that overexpression of Linc00657 could promote the proliferation,migration and invasion of cervical cancer cells，and inhibit apoptosis. Through the StarBase database, it was found that there may be a mutual regulatory relationship between Linc00657 and Skp2, and Skp2 may be the downstream target of Linc00657. QRT-PCR detection confirmed that the expression of Skp2 was increased in cervical cancer cells with overexpression of Linc00657. TIMER2 database found that Skp2 was associated with lipid metabolic enzymes and immune cell infiltration. It was found that Linc00657 knockdown inhibited tumor growth and metastasis and inhibited the expression of Skp2 in vivo. In short, our research shows that Linc00657 has carcinogenic properties in cervical cancer, and LINC00657 promotes the occurrence of cervical cancer by up-regulating the expression of Skp2. We predict that Linc00657/mir30s/Skp2 axis plays a role in the malignant progression of cervical cancer. In addition, Skp2 may participate in cancer immune response and promote lymph node metastasis of cervical cancer through lipid reprogramming. These findings also provide promising targets for the diagnosis and treatment of cervical cancer.

Decoding the interaction between miR-19a and CBX7 focusing on the implications for tumor suppression in cancer therapy

Cancer is a complex and multifaceted disease characterized by uncontrolled cell growth, genetic alterations, and disruption of normal cellular processes, leading to the formation of malignant tumors with potentially devastating consequences for patients. Molecular research is important in the diagnosis and treatment, one of the molecular mechanisms involved in various cancers is the fluctuation of gene expression. Non-coding RNAs, especially microRNAs, are involved in different stages of cancer. MicroRNAs are small RNA molecules that are naturally produced within cells and bind to the 3'-UTR of target mRNA, repressing gene expression by regulating translation. Overexpression of miR-19a has been reported in human malignancies. Upregulation of miR-19a as a member of the miR-17-92 cluster is key to tumor formation, cell proliferation, survival, invasion, metastasis, and drug resistance. Furthermore. bioinformatics and in vitro data reveal that the miR-19a-3p isoform binds to the 3'UTR of CBX7 and was identified as the miR-19a-3p target gene. CBX7 is known as a tumor suppressor. This review initially describes the regulation of mir-19a in multiple cancers. Accordingly, the roles of miR-19 in affecting its target gene expression CBX7 in carcinoma also be discussed.

A cellular senescence-related genes model allows for prognosis and treatment stratification of cervical cancer: a bioinformatics analysis and external verification

BACKGROUND

Cervical cancer (CC) is highly lethal and aggressive with an increasing trend of mortality for females. Molecular characterization-based methods hold great promise for improving the diagnostic accuracy and for predicting treatment response.

METHODS

The mRNAs expression data of CC patients and cellular senescence-related genes were obtained from the Cancer Genome Atlas (TCGA) and CellAge databases, respectively. Differentially expressed genes (DEGs) of senescence related genes between tumor and normal tissues were used for Least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic model. Univariate and LASSO regression analyses were applied to establish a predictive nomogram. The performance of the nomogram were evaluated by Kaplan-Meier curve, receiver operating characteristic (ROC), Harrell's concordance index (C-index), and calibration curve. GSE44001 and GSE52903 were used for external validation.

RESULTS

We established a cellular senescence-related genes-based stratified model, and a multivariable-based nomogram, which could accurately predict the prognosis of CC patients in the TCGA database. The Kaplan-Meier curve indicated that patients in the low-risk group had considerably better overall survival (OS, P =2.021e-05). The area under the ROC curve (AUC) of this model was 0.743 for OS. Multivariate analysis found that the 6-gene risk signature (HR=3.166, 95%CI: 1.660-6.041, P<0.001) was an independent risk factor for CC patients. We then designed an OS-associated nomogram that included the risk signature and clinicopathological factors. The AUC reached 0.860 for predicting 5-year OS. The nomogram showed excellent consistency between the predictions and actual survival observations. Two external GEO validations were corresponding to the gene expression pattern in TCGA.

CONCLUSIONS

Our results suggested a six-senescence related signature and established a prognostic nomogram that reliably predicted the overall survival for CC. These findings may be beneficial to personalized treatment and medical decision-making.

Systematic investigation of the clinical significance and prognostic value of the CBXs in esophageal cancer

Esophageal cancer (ESCA), one of the most aggressive malignant tumors, has been announced to be the ninth most common cancer and the sixth leading cause of cancer-related death in the world. Chromobox family members (CBXs) are important epigenetic regulators which are related with the transcription of target genes. The role of CBXs in carcinomas has been reported in many studies. However, the function and prognostic value of different CBXs in ESCA are still largely unknown. In this article, we first performed differential expression analysis through several methods including Oncomine and Gene Expression Profiling Interactive Analysis. The results led us to determine the differential expression of CBXs in pan-cancer, especially ESCA. Then we evaluated the prognostic value of different CBX messenger RNA (mRNA) expression in patients with ESCA through the Kaplan-Meier plotter and the Human Protein Atlas database. In addition, we used cBioPortal to explore all genetic alterations and mutations in the CBXs in ESCA. Simultaneously, the correlation between its expression and the level of immune infiltration of ESCA was visualized by TIMER. Finally, the biological function of CBXs in ESCA is obtained through Biological Enrichment Analysis including gene ontology and Kyoto Encyclopedia of Genes and Genomes. The expression levels of CBX3/4/5 and CBX8 in ESCA tissues increased significantly and the expression level of CBX7 decreased through differential expression analysis. Additionally, CBX1 is significantly related to the clinical cancer stage and disease-free survival of ESCA patients. The high mRNA expression of CBX4 is related to the short overall survival of patients with esophageal squamous cell carcinoma, and the high mRNA expression of CBX3/7/8 is related to the short overall survival of patients with esophageal adenocarcinoma, indicating that CBX1/3/4/7/8 may be a potential prognostic biomarker for the survival of ESCA patients. Besides, the expression of CBXs is significantly related to the infiltration of a variety of immune cells, including six types of CD4-positive T-lymphocytes, macrophages, neutrophils, bursindependentlymphocyte, CD8-positive T-lymphocytes cells and dendritic cells in ESCA. Moreover, we found that CBXs are mainly associated with the inhibition of cell cycle and apoptosis pathway. Further, enrichment analysis indicated that CBXs and correlated genes were enriched in mismatch repair, DNA replication, cancer pathways, and spliceosomes. Our research may provide new insights into the choice of prognosis biomarkers of the CBXs in ESCA.

A novel risk score model based on fourteen chromatin regulators-based genes for predicting overall survival of patients with lower-grade gliomas

Background: Low grade gliomas(LGGs) present vexatious management issues for neurosurgeons. Chromatin regulators (CRs) are emerging as a focus of tumor research due to their pivotal role in tumorigenesis and progression. Hence, the goal of the current work was to unveil the function and value of CRs in patients with LGGs.

Methods: RNA-Sequencing and corresponding clinical data were extracted from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) database. A single-cell RNA-seq dataset was sourced from the Gene Expression Omnibus (GEO) database. Altogether 870 CRs were retrieved from the published articles in top academic journals. The least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression analysis were applied to construct the prognostic risk model. Patients were then assigned into high- and low-risk groups based on the median risk score. The Kaplan–Meier (K-M) survival curve and receiver operating characteristic curve (ROC) were performed to assess the prognostic value. Sequentially, functional enrichment, tumor immune microenvironment, tumor mutation burden, drug prediction, single cell analysis and so on were analyzed to further explore the value of CR-based signature. Finally, the expression of signature genes were validated by immunohistochemistry (IHC) and quantitative real-time PCR (qRT-PCR).

Results: We successfully constructed and validated a 14 CRs-based model for predicting the prognosis of patients with LGGs. Moreover, we also found 14 CRs-based model was an independent prognostic factor. Functional analysis revealed that the differentially expressed genes were mainly enriched in tumor and immune related pathways. Subsequently, our research uncovered that LGGs patients with higher risk scores exhibited a higher TMB and were less likely to be responsive to immunotherapy. Meanwhile, the results of drug analysis offered several potential drug candidates. Furthermore, tSNE plots highlighting the magnitude of expression of the genes of interest in the cells from the scRNA-seq assay. Ultimately, transcription expression of six representative signature genes at the mRNA level was consistent with their protein expression changes.

Conclusion: Our findings provided a reliable biomarker for predicting the prognosis, which is expected to offer new insight into LGGs management and would hopefully become a promising target for future research.