Rejection of adenovirus infection is independent of coxsackie and adenovirus receptor expression in cisplatin-resistant human lung cancer cells

mRNA markers for survival prediction in glioblastoma multiforme patients: a systematic review with bioinformatic analyses

BACKGROUND

Glioblastoma multiforme (GBM) is a type of fast-growing brain glioma associated with a very poor prognosis. This study aims to identify key genes whose expression is associated with the overall survival (OS) in patients with GBM.

METHODS

A systematic review was performed using PubMed, Scopus, Cochrane, and Web of Science up to Journey 2024. Two researchers independently extracted the data and assessed the study quality according to the New Castle Ottawa scale (NOS). The genes whose expression was found to be associated with survival were identified and considered in a subsequent bioinformatic study. The products of these genes were also analyzed considering protein-protein interaction (PPI) relationship analysis using STRING. Additionally, the most important genes associated with GBM patients' survival were also identified using the Cytoscape 3.9.0 software. For final validation, GEPIA and CGGA (mRNAseq_325 and mRNAseq_693) databases were used to conduct OS analyses. Gene set enrichment analysis was performed with GO Biological Process 2023.

RESULTS

From an initial search of 4104 articles, 255 studies were included from 24 countries. Studies described 613 unique genes whose mRNAs were significantly associated with OS in GBM patients, of which 107 were described in 2 or more studies. Based on the NOS, 131 studies were of high quality, while 124 were considered as low-quality studies. According to the PPI network, 31 key target genes were identified. Pathway analysis revealed five hub genes (IL6, NOTCH1, TGFB1, EGFR, and KDR). However, in the validation study, only, the FN1 gene was significant in three cohorts.

CONCLUSION

We successfully identified the most important 31 genes whose products may be considered as potential prognosis biomarkers as well as candidate target genes for innovative therapy of GBM tumors.

Revisiting characteristics of oncogenic extrachromosomal DNA as mobile enhancers on neuroblastoma and glioma cancers

Cancer can be induced by a variety of possible causes, including tumor suppressor gene failure and proto-oncogene hyperactivation. Tumor-associated extrachromosomal circular DNA has been proposed to endanger human health and speed up the progression of cancer. The amplification of ecDNA has raised the oncogene copy number in numerous malignancies according to whole-genome sequencing on distinct cancer types. The unusual structure and function of ecDNA, and its potential role in understanding current cancer genome maps, make it a hotspot to study tumor pathogenesis and evolution. The discovery of the basic mechanisms of ecDNA in the emergence and growth of malignancies could lead researchers to develop new cancer therapies. Despite recent progress, different aspects of ecDNA require more investigation. We focused on the features, and analyzed the bio-genesis, and origin of ecDNA in this review, as well as its functions in neuroblastoma and glioma cancers.

Integrative analysis of DNA methylation and gene expression profiles to identify biomarkers of glioblastoma

Glioblastoma multiforme (GBM) is the most common, most invasive, and malignant type of primary brain tumor with poor prognosis and poor survival rate. Using GSE22891 the expression and methylation status of same GBM patients was evaluated to identify key epigenetic genes in GBM. Using |log2FC| > 1 and FDR 〈 0.05 as the threshold, DEGs including 4910 downregulated and 2478 upregulated were screened and by |log2FC| 〉 0.2 and p-value < 0.05, 3223 DMCs were detected. By merging the results of DEGs and DMCs, 643 genes were selected for network analysis by WGCNA, and based on expression values three modules and by methylation values, one module was selected. Using STRING and Cytoscape databases, PPI network of genes of all modules were constructed separately. According to the PPI network, core genes were picked out. The expression status of core genes was evaluated using GSE77043, GSE42656, GSE30563, GSE22891, GSE15824, and GSE122498, and 50 genes were validated. The methylation status of 50 genes was explored using GSE50923, GSE22891, and GSE36245, and finally, 12 hub genes including ARHGEF7, RAB11FIP4, PPP1R16B, OLFM1, CLDN10, BCAT1, C1QB, C1QC, IFI16, NUP37, PARP9, and PCLAF were selected. Using GEPIA database, the expression and by cBioportal the survival plot and also scatterplot of methylation versus expression of 12 hub genes were extracted based on TCGA. To determine the diagnostic values of the hub genes, the receiver operating characteristic (ROC) curve and the area under the curve (AUC) were extracted based on GSE22891 and GSE122498. Finally, we evaluated the expression level of the genes in tissue of 83 GBM patients and also non-tumoral adjacent (as control) tissues.

Nonreplicating Adenoviral Vectors: Improving Tropism and Delivery of Cancer Gene Therapy

Recent preclinical and clinical studies have used viral vectors in gene therapy research, especially nonreplicating adenovirus encoding strategic therapeutic genes for cancer treatment. Adenoviruses were the first DNA viruses to go into therapeutic development, mainly due to well-known biological features: stability in vivo, ease of manufacture, and efficient gene delivery to dividing and nondividing cells. However, there are some limitations for gene therapy using adenoviral vectors, such as nonspecific transduction of normal cells and liver sequestration and neutralization by antibodies, especially when administered systemically. On the other hand, adenoviral vectors are amenable to strategies for the modification of their biological structures, including genetic manipulation of viral proteins, pseudotyping, and conjugation with polymers or biological membranes. Such modifications provide greater specificity to the target cell and better safety in systemic administration; thus, a reduction of antiviral host responses would favor the use of adenoviral vectors in cancer immunotherapy. In this review, we describe the structural and molecular features of nonreplicating adenoviral vectors, the current limitations to their use, and strategies to modify adenoviral tropism, highlighting the approaches that may allow for the systemic administration of gene therapy.

CDK1 and CCNB1 as potential diagnostic markers of rhabdomyosarcoma: validation following bioinformatics analysis

Background

Rhabdomyosarcoma (RMS), a common soft-tissue malignancy in pediatrics, presents high invasiveness and mortality. However, besides known changes in the PAX3/7-FOXO1 fusion gene in alveolar RMS, the molecular mechanisms of the disease remain incompletely understood. The purpose of the study is to recognize potential biomarkers related with RMS and analyse their molecular mechanism, diagnosis and prognostic significance.

Methods

The Gene Expression Omnibus was used to search the RMS and normal striated muscle data sets. Differentially expressed genes (DEGs) were filtered using R software. The DAVID has become accustomed to performing functional annotations and pathway analysis on DEGs.

The protein interaction was constructed and further processed by the STRING tool and Cytoscape software. Kaplan–Meier was used to estimate the effect of hub genes on the ending of sarcoma sufferers, and the expression of these genes in RMS was proved by real-time polymerase chain reaction (RT-PCR). Finally, the expression of CDK1 and CCNB1 in RMS was validated by immunohistochemistry (IHC).

Results

A total of 1932 DEGs were obtained, amongst which 1505 were up-regulated and 427were down-regulated. Up-regulated genes were largely enriched in the cell cycle, ECM-receptor interaction, PI3K/Akt and p53 pathways, whilst down-regulated genes were primarily enriched in the muscle contraction process. CDK1, CCNB1, CDC20, CCNB2, AURKB, MAD2L1, HIST2H2BE, CENPE, KIF2C and PCNA were identified as hub genes by Cytoscape analyses. Survival analysis showed that, except for HIST2H2BE, the other hub genes were highly expressed and related to poor prognosis in sarcoma. RT-PCR validation showed that CDK1, CCNB1, CDC20, CENPE and HIST2H2BE were significantly differential expression in RMS compared to the normal control. IHC revealed that the expression of CDK1 (28/32, 87.5%) and CCNB1 (26/32, 81.25%) were notably higher in RMS than normal controls (1/9, 11.1%; 0/9, 0%). Moreover, the CCNB1 was associated with the age and location of the patient’s onset.

Conclusions

These results show that these hub genes, especially CDK1 and CCNB1, may be potential diagnostic biomarkers for RMS and provide a new perspective for the pathogenesis of RMS.