Identification of six candidate genes for endometrial carcinoma by bioinformatics analysis

The causal effects of genetically predicted alcohol consumption on endometrial cancer risk from a Mendelian randomization study

Endometrial cancer (EC) is a common gynecological tumor in females with an increasing incidence over the past few decades. Alcohol consumption has been linked to the occurrence of various cancers; However, epidemiological studies have shown inconsistent associations between alcohol consumption and EC risk. In order to avoid the influence of potential confounding factors and reverse causality in traditional epidemiological studies, we used a method based on genetic principles-Mendelian randomization (MR) analysis to test whether there is a causal relationship between alcohol consumption and EC. MR analysis was conducted using publicly available summary-level data from genome-wide association studies (GWAS). Fifty-seven single nucleotide polymorphisms (SNPs) were extracted as instrumental variables for alcohol exposure from the GWAS and Sequencing Consortium of Alcohol and Nicotine GWAS summary data involving 941,287 participants of European ancestry. SNPs for EC were obtained from the Endometrial Cancer Association Consortium, the Endometrial Cancer Epidemiology Consortium, and the UK Biobank, involving 121,885 European participants. The inverse variance weighted (IVW) method was used as the primary method to estimate the causal effect, and the MR-Egger regression and weighted median method were used as supplementary methods. Sensitivity analyses were conducted using the Mendelian Randomization Pleiotropy RESidual Sum and Outlier global test, MR-Egger intercept test, and leave-one-out analysis to evaluate the impact of pleiotropy on causal estimates. An increase of 1 standard deviation of genetically predicted log-transformed alcoholic drinks per day was associated with a 43% reduction in EC risk [odds ratio (OR) = 0.57, 95% confidence interval (CI) 0.41-0.79, P < 0.001]. Subgroup analysis of EC revealed that alcohol consumption was a protective factor for endometrioid endometrial cancer (EEC) (OR = 0.56, 95% CI 0.38-0.83, P = 0.004) but not for non-endometrioid endometrial cancer (NEC) (OR = 1.36, 95% CI 0.40-4.66, P = 0.626). The MR-Egger regression and weighted median method yielded consistent causal effects with the IVW method. The consistent results of sensitivity analyses indicated the reliability of our causal estimates. Additionally, alcohol consumption was associated with decreased human chorionic gonadotropin (HCG) and insulin-like growth factor 1 (IGF1) levels. This MR study suggests that genetically predicted alcohol consumption is a protective factor for EC, particularly for EEC, and this protective effect may be mediated through the reduction of HCG and IGF1.

The emerging role of ectodermal neural cortex 1 in cancer

Ectodermal neural cortex 1 (ENC1) is a protein that plays a crucial role in the regulation of various cellular processes such as cell proliferation, differentiation, and apoptosis. Numerous studies have shown that ENC1 is overexpressed in various types of cancers, including breast, lung, pancreatic, and colorectal cancer, and its upregulation is correlated with a poorer prognosis. In addition to its role in cancer growth and spreading, ENC1 has also been linked to neuronal process development and neural crest cell differentiation. In this review, we provide an overview of the current knowledge on the relationship between ENC1 and cancer. We discuss the molecular mechanisms by which ENC1 contributes to tumorigenesis, including its involvement in multiple oncogenic signaling pathways. We also summarize the potential of targeting ENC1 for cancer therapy, as its inhibition has been shown to significantly reduce cancer cell invasion, growth, and metastasis. Finally, we highlight the remaining gaps in our understanding of ENC1's role in cancer and propose potential directions for future research.

MicroRNA Landscape in Endometrial Carcinomas in an Asian population: Unraveling Subtype-Specific Signatures

MicroRNAs (MiRNAs) are small, non-coding RNA molecules that function in RNA silencing and post-transcriptional regulation of gene expression. We analyzed the differential expression of miRNAs in 119 endometrial carcinomas, measuring their expression in histological subtypes, molecular subtypes, and tumors with CTNNB1 mutations. Tumors were subdivided into histological and molecular subtypes as defined by The Cancer Genome Atlas. The expression levels of 352 miRNAs were quantified using the PanoramiR panel. Mir-449a, mir-449b-5p, and mir-449c-5p were the top three miRNAs showing increased expression in both endometrioid and de-differentiated carcinomas but were not significantly increased in serous and clear cell carcinomas. The miRNAs with the most increased expression in serous and clear cell carcinomas were miR-9-3p and miR-375, respectively. We also identified 62 differentially expressed miRNAs among different molecular subtypes. Using sequential forward selection, we built subtype classification models for some molecular subtypes of endometrial carcinoma, comprising 5 miRNAs for MMR-deficient tumors, 10 miRNAs for p53-mutated tumors, and 3 miRNAs for CTNNB1-mutated tumors, with areas under curves of 0.75, 0.85, and 0.78, respectively. Our findings confirm the differential expression of miRNAs between various endometrial carcinoma subtypes and may have implications for the development of diagnostic and prognostic tools.

Changes in the expression of cancer- and metastasis-related genes and proteins after metformin treatment under different metabolic conditions in endometrial cancer cells

Research question

Hyperinsulinemia and elevated estrogen levels are known risk factors for endometrial cancer (EC) development and are associated with obesity, type 2 diabetes mellitus (T2DM), insulin resistance, among others. Metformin, an insulin-sensitizing drug, displays anti-tumor effects in cancer patients, including EC, but the mechanism of action is still not completely understood. In the present study, the effects of metformin on gene and protein expression were investigated in pre- and postmenopausal EC in vitro models in order to identify candidates that are potentially involved in the drug's anti-cancer mechanism.

Design

After treating the cells with metformin (0.1 and 1.0 mmol/L), changes in the expression of >160 cancer- and metastasis-related gene transcripts were evaluated with RNA arrays. A total of 19 genes and 7 proteins were selected for a follow-up expression analysis, including further treatment conditions, in order to evaluate the influence of hyperinsulinemia and hyperglycemia on metformin-induced effects.

Results

Changes in the expression of BCL2L11, CDH1, CDKN1A, COL1A1, PTEN, MMP9 and TIMP2 were analyzed on gene and protein level. The consequences resulting from the detected expression changes as well as the influence of varying environmental influences are discussed in detail. With the presented data, we contribute to a better understanding of the direct anti-cancer activity of metformin as well as its underlying mechanism of action in EC cells.

Conclusions

Although further research will be necessary to confirm the data, the influence of different environmental settings on metformin-induced effects could be highlighted with the presented data. Additionally, gene and protein regulation were not similar in the pre- and postmenopausal in vitro models.

Computational approaches for discovering significant microRNAs, microRNA-mRNA regulatory pathways, and therapeutic protein targets in endometrial cancer

Endometrial cancer (EC) is a urogenital cancer affecting millions of post-menopausal women, globally. This study aims to identify key miRNAs, target genes, and drug targets associated with EC metastasis. The global miRNA and mRNA expression datasets of endometrial tissue biopsies (24 tumors +3 healthy tissues for mRNA and 18 tumor +4 healthy tissues for miRNAs), were extensively analyzed by mapping of DEGs, DEMi, biological pathway enrichment, miRNA-mRNA networking, drug target identification, and survival curve output for differentially expressed genes. Our results reveal the dysregulated expression of 26 miRNAs and their 66 target genes involved in focal adhesions, p53 signaling pathway, ECM-receptor interaction, Hedgehog signaling pathway, fat digestion and absorption, glioma as well as retinol metabolism involved in cell growth, migration, and proliferation of endometrial cancer cells. The subsequent miRNA-mRNA network and expression status analysis have narrowed down to 2 hub miRNAs (hsa-mir-200a, hsa-mir-429) and 6 hub genes (PTCH1, FOSB, PDGFRA, CCND2, ABL1, ALDH1A1). Further investigations with different systems biology methods have prioritized ALDH1A1, ABL1 and CCND2 as potential genes involved in endometrial cancer metastasis owing to their high mutation load and expression status. Interestingly, overexpression of PTCH1, ABL1 and FOSB genes are reported to be associated with a low survival rate among cancer patients. The upregulated hsa-mir-200a-b is associated with the decreased expression of the PTCH1, CCND2, PDGFRA, FOSB and ABL1 genes in endometrial cancer tissue while hsa-mir-429 is correlated with the decreased expression of the ALDH1A1 gene, besides some antibodies, PROTACs and inhibitory molecules. In conclusion, this study identified key miRNAs (hsa-mir-200a, hsa-mir-429) and target genes ALDH1A1, ABL1 and CCND2 as potential biomarkers for metastatic endometrial cancers from large-scale gene expression data using systems biology approaches.

Upregulated ENC1 predicts unfavorable prognosis and correlates with immune infiltration in endometrial cancer

A better knowledge of the molecular process behind uterine corpus endometrial carcinoma (UCEC) is important for prognosis prediction and the development of innovative targeted gene therapies. The purpose of this research is to discover critical genes associated with UCEC. We analyzed the gene expression profiles of TCGA-UCEC and GSE17025, respectively, using Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis. From four sets of findings, a total of 95 overlapping genes were retrieved. On the 95 overlapping genes, KEGG pathway and GO enrichment analysis were conducted. Then, we mapped the PPI network of 95 overlapping genes using the STRING database. Twenty hub genes were evaluated using the Cytohubba plugin, including NR3C1, ATF3, KLF15, THRA, NR4A1, FOSB, PER3, HLF, NTRK3, EGR3, MAPK13, ARNTL2, PKM2, SCD, EIF5A, ADHFE1, RERGL, TUB, and ENC1. The expression levels of NR3C1, PKM2, and ENC1 were shown to be adversely linked with the survival time of UCEC patients using univariate Cox regression analysis and Kaplan-Meier survival calculation. ENC1 were also overexpressed in UCEC tumor tissues or cell lines, as shown by quantitative real-time PCR and Western blotting. Then we looked into it further and discovered that ENC1 expression was linked to tumor microenvironment and predicted various immunological checkpoints. In conclusion, our data indicate that ENC1 may be required for the development of UCEC and may serve as a future biomarker for diagnosis and therapy.

The potential key genes and pathways associated with Wilms tumor in quest of proper candidates for diagnostic and therapeutic purposes

To designate the probable most important differentially expressed genes and genetic pathways in Wilms tumor and assess their expression and diagnostic potential by RT-PCR and statistical analysis. Systematic review of the literature and various bioinformatics analysis was carried out to gather and narrow down data. The expression of end-resulting genes was compared in Wilms tumor and normal tissue samples using RT-PCR. Statistical tests reported the diagnostic accuracy of genes and their correlation with clinicopathological features. Four genes including CDH1, NCAM1, EGF, and IGF2 were designated. The panel combining them has 100% sensitivity and specificity in differentiating tumors from normal tissue. Eight pathways, most involved in cell-cell and cell-basal matrix junction interactions, were found to be associated with disease pathogenesis. The suggested genes should undergo further evaluation to be validated as diagnostic biomarkers. Further research on the eight proposed pathways is recommended.

Exploration of the Molecular Mechanism of Danzhi Xiaoyao Powder in Endometrial Cancer through Network Pharmacology

Endometrial cancer (EC) is a common malignant tumor of the female reproductive system. Current treatments such as surgery and long-term hormone therapy are ineffective and have side effects. Danzhi Xiaoyao powder (DXP) can inhibit the growth of EC cells and induce apoptosis, but the pharmacological and molecular mechanisms of anticancer effects are still unclear. In this study, active components and potential targets of DXP were obtained from public databases. Protein effects and regulatory pathways of common targets were analyzed by protein-protein interaction (PPI), GO and KEGG. The results of network pharmacology showed that there are 87 common targets between EC and DXP. GO enrichment analysis showed that these targets were associated with response to oxidative stress, response to nutrient levels, hormone receptor binding and nuclear hormone receptor binding, etc. The results of KEGG analysis indicated that IL-17, TNF, PI3K/AKT, and RAS/RAF/MEK/ERK (ERK) signaling pathway were enriched in the anti-EC of DXP. Additionally, we cultured HEC-1B and KLE cells for validate experiments. DXP showed an inhibition of proliferation, migration, and cell cycle of both cells. Moreover, the expression of RAS, p-RAF, p-MEK, ERK, and p-ERK related proteins were downregulated. In conclusion, DXP might inhibit the proliferation of EC cells via apoptosis. Furthermore, DXP-induced inhibition of EC development might involve RAS/RAF/MEK/ERK pathway.

Determination of a six-gene prognostic model for cervical cancer based on WGCNA combined with LASSO and Cox-PH analysis

AIM

This study aimed to establish a risk model of hub genes to evaluate the prognosis of patients with cervical cancer.

METHODS

Based on TCGA and GTEx databases, the differentially expressed genes (DEGs) were screened and then analyzed using GO and KEGG analyses. The weighted gene co-expression network (WGCNA) was then used to perform modular analysis of DEGs. Univariate Cox regression analysis combined with LASSO and Cox-pH was used to select the prognostic genes. Then, multivariate Cox regression analysis was used to screen the hub genes. The risk model was established based on hub genes and evaluated by risk curve, survival state, Kaplan-Meier curve, and receiver operating characteristic (ROC) curve.

RESULTS

We screened 1265 DEGs between cervical cancer and normal samples, of which 620 were downregulated and 645 were upregulated. GO and KEGG analyses revealed that most of the upregulated genes were related to the metastasis of cancer cells, while the downregulated genes mostly acted on the cell cycle. Then, WGCNA mined six modules (red, blue, green, brown, yellow, and gray), and the brown module with the most DEGs and related to multiple cancers was selected for the follow-up study. Eight genes were identified by univariate Cox regression analysis combined with the LASSO Cox-pH model. Then, six hub genes (SLC25A5, ENO1, ANLN, RIBC2, PTTG1, and MCM5) were screened by multivariate Cox regression analysis, and SLC25A5, ANLN, RIBC2, and PTTG1 could be used as independent prognostic factors. Finally, we determined that the risk model established by the six hub genes was effective and stable.

CONCLUSIONS

This study supplies the prognostic value of the risk model and the new promising targets for the cervical cancer treatment, and their biological functions need to be further explored.

The MCM3AP-AS1/miR-126/VEGF axis regulates cancer cell invasion and migration in endometrioid carcinoma

BACKGROUND

Long non-coding RNA (lncRNA) MCM3AP-AS1 plays an oncogenic role in several malignancies, but its role in endometrioid carcinoma (EC) is unclear. This study was carried out to explore the role of MCM3AP-AS1 in EC.

METHODS

A total of 60 EC patients were enrolled in this study. Expression levels of MCM3AP Antisense RNA 1 (MCM3AP-AS1), microRNA-126 (miR-126), and vascular endothelial growth factor (VEGF) in tissues and transfetced cells were measured by RT-qPCR. Cell transfections were performed to explore the interaction among MCM3AP-AS1, miR-126 and VEGF. Transwell assays were perfromed to evaluate the invasion and migration abilities of HEC-1 cells after transfection.

RESULTS

MCM3AP-AS1 was upregulated in EC and predicted poor survival. MCM3AP-AS1 directly interacted with miR-126. In EC cells, overexpression of MCM3AP-AS1 and miR-126 did not significantly affect the expression of each other. In addition, overexpression of MCM3AP-AS1 increased the expression levels of VEGF, a target of miR-126. Moreover, overexpression of MCM3AP-AS1 and VEGF increased the migration and invasion rates of EC cells, while overexpression of miR-126 suppressed these cell behaviors. Overexpression of MCM3AP-AS1 attenuated the role of miR-126 in cell invasion and migration.

CONCLUSIONS

Therefore, MCM3AP-AS1 may serve as a competing endogenous RNA (ceRNA) of miR-126 to upregulate VEGF, thereby regulating cancer cell behaviors in EC.

Identification of Potential Biomarkers Associated with Prognosis in Gastric Cancer via Bioinformatics Analysis

Background

Gastric cancer (GC) is one of the leading causes of cancer-related mortality worldwide. We aimed to identify differentially expressed genes (DEGs) and their potential mechanisms associated with the prognosis of GC patients.

Material/Methods

This study was based on gene profiling information for 37 paired samples of GC and adjacent normal tissues from the GSE118916, GSE79973, and GSE19826 datasets in the Gene Expression Omnibus database. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to investigate the biological role of the DEGs. The protein–protein interaction (PPI) network was constructed by Cytoscape, and the Kaplan-Meier plotter was used for prognostic analysis.

Results

We identified 119 DEGs, including 21 upregulated and 98 downregulated genes, in GC. The 21 upregulated genes were mainly enriched in extracellular matrix-receptor interaction, focal adhesion, and transforming growth factor-β signaling, while the 98 downregulated genes were significantly associated with gastric acid secretion, retinol metabolism, and metabolism of xenobiotics by cytochrome P450. Thirty hub DEGs were obtained for further analysis. Twenty-five of the 30 hub DEGs were significantly associated with the prognosis of GC, and 21 of the 25 hub DEGs showed consistent expression trends within the 3 profile datasets. KEGG reanalysis of these 21 hub DEGs showed that COL1A1, COL1A2, COL2A1, COL11A1, THBS2, and SPP1 were mainly enriched in the extracellular matrix-receptor interaction pathways.

Conclusions

We identified 6 genes that were significantly related to the prognosis of GC patients. These genes and pathways could serve as potential prognostic markers and be used to develop treatments for GC patients.

Lower mutant-allele tumor heterogeneity is a biomarker in FGFR3-mutant bladder cancer for better prognosis

Background

Bladder cancer displays a broad mutational spectrum and intratumor heterogeneity (ITH), which results in difference in molecular phenotypes and resistance to therapies. However, there are currently no clinically available measures to predict patient prognosis using ITH. We aimed to establish a clinically relevant biomarker by using ITH for informing predictive of outcomes.

Methods

We used the Bioconductor R package Maftools to efficiently and comprehensively analyze somatic variants of muscle-invasive bladder cancer (MIBC) from The Cancer Genome Atlas (TCGA). We then used a mutant-allele tumor heterogeneity (MATH) algorithm to measure ITH and explored its correlation with clinical parameters as well as mutational subtypes.

Results

We observed a broad range of somatic mutations in MIBC from TCGA. MATH value was higher for the high-grade group than for the low-grade group (p < 0.05). There was a strong correlation between higher MATH value and presence of TP53 mutations (p = 0.008), as well as between lower MATH value and presence of FGFR3 mutations (p = 0.006). Patients with FGFR3 mutation and low MATH value exhibit longer overall survival time than that of all BLCA patients (p = 0.044), which was replicated in another bladder cancer database composed of 109 BLCA patients.

Conclusion

Measures of tumor heterogeneity may be useful biomarkers for identifying patients with bladder cancer. Low MATH value was an independent risk factor that predicted better prognosis for patients with FGFR3 mutation compared to all BLCA patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-020-02084-3.

Silencing of SPP1 Suppresses Progression of Tongue Cancer by Mediating the PI3K/Akt Signaling Pathway

Background:

In the present study, we aimed to find an effective target for the treatment of tongue cancer using gene chip screening and signal pathway research.

Methods:

We used microarray screening and gene expression profile analyses to find important differentially expressed genes in tongue cancer. We constructed a protein-protein interaction network, and used enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes to screen for important genes. We then silenced the genes of interest in SCC154 cells to study the relationship with the Phosphatidylinositol 3-kinase/Akt signal pathway. Western blot analyses, the 3-(4,5Dimethylthiazol-yl)-2,5Dimethylthiazol-2-yl)-2,5diphenyltetrazolium bromide (MTT) test, and immunofluorescence assays were used to compare the expression levels of Phosphatidylinositol 3-kinase/Akt signal pathway-related proteins, cell viability, and cell proliferation ability in normal SCC154 cells, Si-RNA SCC154 cells, and gene-silenced SCC154 cells. The scratch test, Transwell test, and western blotting were used to determine migration, invasion, and carcinogenesis.

Results:

Using GSE9844, GSE13601, and GSE31056 gene chips, we identified 93 upregulated genes and 76 downregulated genes in tongue cancer. Using the protein-protein interaction network and Kyoto Encyclopedia of Genes and Genomes enrichment analyses, we further identified 47 differentially expressed genes. Using Kaplan-Meier plotter online tools, we also identified 3 genes (SPP1, Recombinant Human Secreted Phosphoprotein 1; PLAU, plasminogen activator urinary; and APP, amyloid precursor protein). Compared with normal SCC154 cells and Si-RNA control SCC154 cells, the expressions of Phosphatidylinositol 3-kinase/Akt pathway proteins in si-SPP1 SCC154 cells were significantly decreased (*P < 0.05), and the protein activities and proliferation abilities were also significantly decreased (*P < 0.05), while the migration ability, invasion ability, and cancer forming ability were significantly increased (*P < 0.05).

Conclusion:

Inhibition of the SPP1 gene may have a therapeutic effect on tongue cancer, and could be an effective target for the treatment of this disorder.