Genetics research最新文献

Background: Advanced glycation end products' receptor (AGER) is a multiligand receptor that interacts with a wide range of ligands. Previous studies have shown that abnormal AGER expression is closely related to immune infiltration and tumorigenesis. However, the AGER DNA methylation relationship between prognosis and infiltrating immune cells in LUAD and LUSC is still unclear.

Methods: AGER expression in pan-cancer was obtained by using the UALCAN databases. Kaplan-Meier plotter showed the correlation of AGER mRNA expression levels and clinicopathological parameters. The protein expression levels for AGER were derived from Human Protein Atlas Database Analysis. The copy number, somatic mutation, and DNA methylation of AGER were presented with UCSC Xena database. TIMER platform and TISIDB website were used to show the correlation between AGER expression and tumor immune cell infiltration level.

Results: The expression level of AGER was significantly reduced in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Low expression of AGER was significantly correlated with histology, stage, lymph node metastasis, and tumor protein 53 (TP53) mutation and could be used as a potential indicator of poor prognosis of LUAD and LUSC. Moreover, AGER expression was positively correlated with the infiltrating immune cells. Further analysis showed that copy number variation (CNV), mutation, and DNA methylation were involved in AGER downregulation. In addition, we also found that hypermethylated AGER was significantly correlated with tumor-infiltrating lymphocytes.

Conclusion: AGER may be a candidate for the prognostic biomarker of LUAD and LUSC related to tumor immune microenvironment.

Salvador homologue 1 (SAV1), which is reported to act as a tumor suppressor in different types of cancer, is one of the key components of the Hippo pathway. However, the expression and mechanisms of SAV1 in the development and progression of gastric cancer (GC) remain to be elucidated. Immunohistochemistry (IHC) was performed in the present study to assess the expression levels of SAV1 and lysine-specific demethylase 2B (KDM2B) in GC tissues. The biological effects of SAV1 on GC cell proliferation, migration, and invasion were studied in vitro. KDM2B transcriptionally regulates SAV1 expression in several GC cell lines, and molecular experiments were performed to investigate underlying mechanisms. The expression level of SAV1 was significantly decreased in GC tissues and cell lines, negatively associated with tumor invasion depth, lymph node metastasis, and TNM stage, and positively associated with the overall survival of patients with GC. SAV1 overexpression inhibited the proliferation, migration, and invasion of GC cells. Further mechanistic studies revealed that KDM2B transcriptionally regulated SAV1 expression and further regulated the Hippo signaling pathway. To conclude, the present study demonstrated that KDM2B transcriptionally regulated SAV1 expression and promoted GC progression.

The outbreak of monkeypox may be considered a novel and urgent threat after the coronavirus disease (COVID-19). No wide-ranging studies have been conducted on this disease since it was first reported. We systematically assessed the functional role of gene expression in cells infected with the monkeypox virus using transcriptome profiling and compared the functional relation with that of COVID-19. Based on the Gene Expression Omnibus database, we obtained 212 differentially expressed genes (DEGs) of GSE36854 and GSE21001 of monkeypox datasets. Enrichment analyses, including KEGG and gene ontology (GO) analyses, were performed to identify the common function of 212 DEGs of GSE36854 and GSE21001. CytoHubba and Molecular Complex Detection were performed to determine the core genes after a protein-protein interaction (PPI). Metascape/COVID-19 was used to compare DEGs of monkeypox and COVID-19. GO analysis of 212 DEGs of GSE36854 and GSE21001 for monkeypox infection showed cellular response to cytokine stimulus, cell activation, and cell differentiation regulation. KEGG analysis of 212 DEGs of GSE36854 and GSE21001 for monkeypox infection showed involvement of monkeypox in COVID-19, cytokine-cytokine receptor interaction, inflammatory bowel disease, atherosclerosis, TNF signaling, and T cell receptor signaling. By comparing our data with published transcriptome of severe acute respiratory syndrome coronavirus 2 infections in other cell lines, the common function of monkeypox and COVID-19 includes cytokine signaling in the immune system, TNF signaling, and MAPK cascade regulation. Thus, our data suggest that the molecular connections identified between COVID-19 and monkeypox elucidate the causes of monkeypox.

Background: Sex and gender have a large impact in human health and disease prediction. According to genomic/genetics, men differ from women by a limited number of genes in Y chromosome, while the phenotypes of the 2 sexes differ markedly.

Methods: In this study, serum samples from six healthy Bahraini men and women were analyzed by liquid chromatography-mass spectrometry (LC-MS/MS). Bioinformatics databases and tools were used for protein/peptide (PPs) identification and gene localization. The PPs that differed significantly (p < 0.05, ANOVA) in abundance with a fold change (FC) of ≥1.5 were identified.

Results: Revealed 20 PPs, 11 were upregulated in women with very high FC (up to 8 folds), and 9 were upregulated in men but with much lower FC. The PPs are encoded by genes located in autosomal chromosomes, indicative of sex-biased gene expression. The only PP related to sex, the sex hormone-binding globulin, was upregulated in women. The remaining PPs were involved in immunity, lipid metabolism, gene expression, connective tissue, and others, with some overlap in function.

Conclusions: The upregulated PPs in men or women are mostly reflecting the functon or risk/protection provided by the PPs to the specific sex, e.g., Apo-B100 of LDLC. Finally, the basis of sex-biased gene expression and sex phenotypic differences needs further investigation.

When it comes to aggressiveness and prognosis, immune cells play an important role in the microenvironment of gastric cancer (GC). Currently, there is no well-established evidence that immune status typing is reliable as a prognostic tool for gastric cancer. This study aimed to develop a genetic signature based on immune status typing for the stratification of gastric cancer risk. TCGA data were used for gene expression and clinical characteristics analysis. A ssGSEA algorithm was applied to type the gastric cancer cohorts. A multivariate and univariate Cox regression and a lasso regression were conducted to determine which genes are associated with gastric cancer prognosis. Finally, we were able to produce a 6-gene prognostic prediction model using immune-related genes. Further analysis revealed that the prognostic prediction model is closely related to the prognosis of patients with GC. Nomograms incorporating genetic signatures and risk factors produced better calibration results. The relationship between the risk score and gastric cancer T stage was also significantly correlated with multiple immune markers related to specific immune cell subsets. According to these results, patients' outcomes and tumor immune cell infiltration correlate with risk scores. In addition, immune cellular-based genetic signatures can contribute to improved risk stratification for gastric cancer. Clinical decisions regarding immunotherapy and followup can be guided by these features.

Pancreatic adenocarcinoma (PAAD) has been a huge challenge to public health due to its increasing incidence, frequent early metastasis, and poor outcome. The molecular basis of tumorigenesis and metastasis in PAAD is largely unclear. Here, we identified a novel tumor-suppressor long noncoding RNA (lncRNA) MBNL1-AS1, in PAAD and revealed its downstream mechanism. Quantitative real-time PCR (qRT-PCR) data showed that MBNL1-AS1 expression was significantly downregulated in PAAD tissues and cells, which was closely associated with metastasis and poor prognosis. Cell counting kit-8 (CCK-8) assay, transwell assay, and western blot verified that overexpression of MBNL1-AS1 suppressed cell proliferation, migration, and epithelial mesenchymal transformation (EMT) behavior in PAAD cells. By using a dual luciferase reporter gene system, we confirmed that miR-301b-3p was a direct target of MBNL1-AS1. Further mechanismic study revealed that upregulation of miR-301b-3p abolished the inhibitory effect of MBNL1-AS1 overexpression on cell proliferation, tumorigenesis, migration and EMT. Our results demonstrate that MBNL1-AS1 plays a tumor-suppressive role in PAAD mainly by downregulating miR-301b-3p, providing a novel therapeutic target for PAAD.

Methylenetetrahydrofolate reductase (MTHFR) plays a major role in the metabolism of folates and homocysteine, which in turn can affect gene expression and ultimately promote the development of breast cancer. Thus, mutations in the MTHFR gene could influence homocysteine, methionine, and S-adenosylmethionine levels and, indirectly, nucleotide levels. Imbalance in methionine and S-adenosylmethionine synthesis affects protein synthesis and methylation. These changes, which affect gene expression, may ultimately promote the development of breast cancer. We therefore hypothesized that such mutations could also play an important role in the occurrence and pathogenesis of breast cancer in a Malian population. In this study, we used the PCR-RFLP technique to identify the different genotypic profiles of the C677T MTHFR polymorphism in 127 breast cancer women and 160 healthy controls. The genotypic distribution of the C677T polymorphism in breast cancer cases was 88.2% for CC, 11.0% for CT, and 0.8% for TT. Healthy controls showed a similar distribution with 90.6% for CC, 8.8% for CT, and 0.6% for TT. We found no statistical association between the C677T polymorphism and breast cancer risk for the codominant models CT and TT (p > 0.05). The same trend was observed when the analysis was extended to other genetic models, including dominant (p = 0.50), recessive (p = 0.87), and additive (p = 0.50) models. The C677T polymorphism of MTHFR gene did not influence the risk of breast cancer in the Malian samples.

Background: In Ethiopia, livestock contributes 45% of agricultural GDP. Despite the economic role played by the sector, there have been little efforts to genetically improve the indigenous cattle. Morphological characterization of selected Ethiopian indigenous cattle has been made for (Bonga, Jimma, and Kerayu) cattle types. But, the selected indigenous cattle were not characterized at molecular level (genetic diversity information). Hence, this work was initiated to detect and determine the genetic diversity and population structure of selected Ethiopian indigenous cattle ecotypes using microsatellite markers.

Results: Different alleles were identified (131) and thirty-three of these alleles were unique to specific ecotypes. All loci used were informative with PIC values ranging from 0.5 (TGLA126) to 0.84 (ETH10) with a mean of 0.70 per locus. The Shannon information index ranged from (I = 1.02) ILST006 to (I = 1.63) ETH10 with an average of 1.28 revealing there is genetic diversity. Moreover, analysis of molecular variance (AMOVA) revealed 84% genetic variation within a population and 13% variation among populations. The value of F-statistics (Fst) (0.129 = 13%) indicated that there was moderate genetic differentiation among ecotypes. The (UPGMA) revealed, Bonga and Jimma clustered together while Kerayu cattle were relatively distinct, Principal coordinates analysis (PCOA) and structure analysis grouped the individual into different clusters confirming the presence of ecotype admixture due to geographical origins and uncontrolled mating.

Conclusion: In general, this study has successfully characterized the genetic diversity and population structure of Bonga, Jimma, and Kerayu cattle ecotypes using high polymorphic/informative microsatellite markers. According to this study, Kerayu cattle have high AR and PA when compared to Bonga and Jimma cattle populations. So, the Kerayu population is more diverse than others and it is the hotspot for genetic diversity study. The generated information is very relevant for breeder and genetic conservation.

Background: Non-small cell lung cancer (NSCLC) is the most prevalent malignant tumor of the lung cancer, for which the molecular mechanisms remain unknown. In this study, we identified novel biomarkers associated with the pathogenesis of NSCLC aiming to provide new diagnostic and therapeutic approaches for NSCLC by bioinformatics analysis.

Methods: From the Gene Expression Omnibus database, GSE118370 and GSE10072 microarray datasets were obtained. Identifying the differentially expressed genes (DEGs) between lung adenocarcinoma and normal samples was done. By using bioinformatics tools, a protein-protein interaction (PPI) network was constructed, modules were analyzed, and enrichment analyses were performed. The expression and prognostic values of 14 hub genes were validated by the GEPIA database, and the correlation between hub genes and survival in lung adenocarcinoma was assessed by UALCAN, cBioPortal, String and Cytoscape, and Timer tools.

Results: We found three genes (PIK3R1, SPP1, and PECAM1) that have a clear correlation with OS in the lung adenocarcinoma patient. It has been found that lung adenocarcinoma exhibits high expression of SPP1 and that this has been associated with poor prognosis, while low expression of PECAM1 and PIK3R1 is associated with poor prognosis (P < 0.05). We also found that the expression of SPP1 was associated with miR-146a-5p, while the high expression of miR-146a-5p was related to good prognosis (P < 0.05). On the contrary, the lower miR-21-5p on upstream of PIK3R1 is associated with a higher surviving rate in cancer patients (P < 0.05). Finally, we found that the immune checkpoint genes CD274(PD-L1) and PDCD1LG2(PD-1) were also related to SPP1 in lung adenocarcinoma.

Conclusions: The results indicated that SPP1 is a cancer promoter (oncogene), while PECAM1 and PIK3R1 are cancer suppressor genes. These genes take part in the regulation of biological activities in lung adenocarcinoma, which provides a basis for improving detection and immunotherapeutic targets for lung adenocarcinoma.