The Clinical Significance and Immunization of MSMO1 in Cervical Squamous Cell Carcinoma Based on Bioinformatics Analysis

Identification of E3 ubiquitin ligase-associated prognostic genes and construction of a prediction model for uterine cervical cancer based on bioinformatics analysis

E3 ligases are engaged in a variety of physiological processes within cells and use ubiquitin-labeled substrates to control their activity and stability. Although some research has indicated that E3 ligases or particular substrates have an impact on the treatment that cervical cancer patients get after their diagnosis, The exact purpose of these enzymes in the occurrence and evolution of cancer of the cervical region (CC) is not clear. In order to extract and analyze relevant mRNA gene expression data as well as clinical patient data, we used open databases. A reliable risk prediction model was developed by applying the least absolute shrinkage and selection operator (LASSO) technique in conjunction with Cox regression analysis. Column-line plots were combined to analyze the predictive model, and the GSE44001 dataset served as an external validation.Four gene models:proteasome (prosome, macropain) 26S subunit, non-ATPase, 14(PSMD14),proteasome (prosome, macropain) subunit, alpha type, 4(PSMA4,),zinc finger and BTB domain containing 16(ZBTB16),and ankyrin repeat domain 9(ANKRD9). Gene expression levels in both healthy and cancerous tissues have been confirmed by the HPA database. Next, the investigation focused on immunological state and tumor mutation load. The high-risk group and Cluster B had distinct levels of immune cell infiltration and a worse prognosis. Additionally, KEGG and GO analyses of differentially expressed genes (DEGs) between the high- and low-risk groups were performed, as well as tumor microenvironment (TME) investigations. Targeting E3 ligases may be an efficient strategy to treat cervical cancer (CC), according to a novel and comprehensive E3 ubiquitination ligase-associated gene model that has been presented.

Identification and functional activity of Nik related kinase (NRK) in benign hyperplastic prostate

OBJECTIVE

Benign prostatic hyperplasia (BPH) is common in elder men. The current study aims to identify differentially expressed genes (DEGs) in hyperplastic prostate and to explore the role of Nik related kinase (NRK) in BPH.

METHODS

Four datasets including three bulk and one single cell RNA-seq (scRNA-seq) were obtained to perform integrated bioinformatics. Cell clusters and specific metabolism pathways were analyzed. The localization, expression and functional activity of NRK was investigated via RT-PCR, western-blot, immunohistochemical staining, flow cytometry, wound healing assay, transwell assay and CCK-8 assay.

RESULTS

A total of 17 DEGs were identified by merging three bulk RNA-seq datasets. The findings of integrated single-cell analysis showed that NRK remarkably upregulated in fibroblasts and SM cells of hyperplasia prostate. Meanwhile, NRK was upregulated in BPH samples and localized almost in stroma. The expression level of NRK was significantly correlated with IPSS and Qmax of BPH patients. Silencing of NRK inhibited stromal cell proliferation, migration, fibrosis and EMT process, promoted apoptosis and induced cell cycle arrest, while overexpression of NRK in prostate epithelial cells showed opposite results. Meanwhile, induced fibrosis and EMT process were rescued by knockdown of NRK. Furthermore, expression level of NRK was positively correlated with that of α-SMA, collagen-I and N-cadherin, negatively correlated with that of E-cadherin.

CONCLUSION

Our novel data identified NRK was upregulated in hyperplastic prostate and associated with prostatic stromal cell proliferation, apoptosis, cell cycle, migration, fibrosis and EMT process. NRK may play important roles in the development of BPH and may be a promising therapeutic target for BPH/LUTS.

Non-coding RNAs in Recurrent implantation failure

Recurrent implantation failure (RIF), defined as the inability to achieve conception following multiple consecutive in-vitro fertilization (IVF) attempts, represents a complex and multifaceted challenge in reproductive medicine. The emerging role of non-coding RNAs in RIF etiopathogenesis has only gained prominence over the last decade, illustrating a new dimension to our understanding of the intricate network underlying RIF. Successful embryo implantation demands a harmonious synchronization between an adequately decidualized endometrium, a competent blastocyst, and effective maternal-embryonic interactions. Emerging evidence has clarified the involvement of a sophisticated network of non-coding RNAs, including microRNAs, circular RNAs, and long non-coding RNAs, in orchestrating these pivotal processes. Disconcerted expression of these molecules can disrupt the delicate equilibrium required for implantation, amplifying the risk of RIF. This comprehensive review presents an in-depth investigation of the complex role played by non-coding RNAs in the pathogenesis of RIF. Furthermore, it underscores the vast potential of non-coding RNAs as diagnostic biomarkers and therapeutic targets, with the ultimate goal of enhancing implantation success rates in IVF cycles. As ongoing research continues to unravel the intercalated web of molecular interactions, exploiting the power of non-coding RNAs may offer promising avenues for mitigating the challenges posed by RIF and improving the outcomes of assisted reproduction.

A novel prognostic classification integrating lipid metabolism and immune co-related genes in acute myeloid leukemia

Background

As a severe hematological malignancy in adults, acute myeloid leukemia (AML) is characterized by high heterogeneity and complexity. Emerging evidence highlights the importance of the tumor immune microenvironment and lipid metabolism in cancer progression. In this study, we comprehensively evaluated the expression profiles of genes related to lipid metabolism and immune modifications to develop a prognostic risk signature for AML.

Methods

First, we extracted the mRNA expression profiles of bone marrow samples from an AML cohort from The Cancer Genome Atlas database and employed Cox regression analysis to select prognostic hub genes associated with lipid metabolism and immunity. We then constructed a prognostic signature with hub genes significantly related to survival and validated the stability and robustness of the prognostic signature using three external datasets. Gene Set Enrichment Analysis was implemented to explore the underlying biological pathways related to the risk signature. Finally, the correlation between signature, immunity, and drug sensitivity was explored.

Results

Eight genes were identified from the analysis and verified in the clinical samples, including APOBEC3C, MSMO1, ATP13A2, SMPDL3B, PLA2G4A, TNFSF15, IL2RA, and HGF, to develop a risk-scoring model that effectively stratified patients with AML into low- and high-risk groups, demonstrating significant differences in survival time. The risk signature was negatively related to immune cell infiltration. Samples with AML in the low-risk group, as defined by the risk signature, were more likely to be responsive to immunotherapy, whereas those at high risk responded better to specific targeted drugs.

Conclusions

This study reveals the significant role of lipid metabolism- and immune-related genes in prognosis and demonstrated the utility of these signature genes as reliable bioinformatic indicators for predicting survival in patients with AML. The risk-scoring model based on these prognostic signature genes holds promise as a valuable tool for individualized treatment decision-making, providing valuable insights for improving patient prognosis and treatment outcomes in AML.

Identification of iron metabolism-related predictive markers of endometriosis and endometriosis-relevant ovarian cancer

Endometriosis is associated with ovarian cancers, mainly endometrioid and clear-cell carcinomas. Iron metabolism has been shown to play a role in endometriosis. Therefore, it is vital to explore the relationship between iron metabolism and ovarian cancer and to identify novel markers for diagnostics and therapeutics. The endometriosis dataset GSE51981 and the ovarian cancer dataset GSE26712 were obtained from the gene expression omnibus database, and differentially expressed genes were identified. Iron metabolism genes were obtained from molecular signatures database, and hub genes from the 3 datasets were obtained. Seven hub genes were identified by bioinformatic analysis, and 3 hub genes (NCOA4, ETFDH, and TYW1) were further selected by logistic regression, which were verified in an independent endometriosis dataset (GSE25628) and ovarian cancer dataset (GSE14407), showing good predictive diagnostic value (area under the receiver operating characteristic curve of 0.88 and 0.9, respectively). Gene Ontology, gene set enrichment analysis, and immune infiltration analysis further confirmed the related functions, pathways, and immune relationship between iron metabolism and ovarian cancer. This study highlights the potential of targeting iron metabolism in the prevention of potential ovarian cancer and in the further exploration of endometriosis and endometriosis-relevant ovarian cancer therapeutics.

Fatty acid synthase (FASN) inhibits the cervical squamous cell carcinoma (CESC) progression through the Akt/mTOR signaling pathway

BACKGROUND

Cervical cancer is a malignant tumor that affects females and remains the cause of the highest morbidity and mortality among women worldwide. Currently, gene-targeted therapy is a novel treatment option for clinicians. Furthermore, fatty acid synthase (FASN) plays a therapeutic role in various cancers. Nonetheless, the mechanism of action of this enzyme in cervical squamous cell carcinoma and cervical duct adenocarcinoma (CESC) has not yet been reported.

METHODS

RNA (ribonucleic acid) sequencing data and clinical information were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). The expression levels of FASN were obtained from Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and Human Protein Atlas (HPA). Univariate and multivariate Cox regression analyses were utilized to assess independent prognostic factors associated with survival. A nomogram and receiver operating characteristic curve (ROC) were employed to evaluate survival and predictive power. In vitro experiments and real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) were conducted to identify cell interference efficiency. MTS, monoclonal formation, and EDU assays were used to determine cell viability. Wound healing and invasion assays (transwell assay) were used to evaluate cell migration and invasion. Finally, Hoechst 33342, propidium iodide (PI) staining and Annexin V-FITC staining were used to assess apoptosis and the cell cycle, while western blotting was utilized to determine the protein expression levels.

RESULTS

FASN was aberrantly expressed in various cancers, including CESC, where it was highly expressed. Kaplan-Meier, univariate, multivariate Cox regression analyses and ROC curve indicated that FASN is a potential key indicator of survival prognosis among CESC patients and demonstrated good predictive ability and efficacy. Complementary in vitro experiments confirmed that FASN is an important target for CESC therapy.

CONCLUSION

The current study validated the biological and clinical significance of FASN in CESC prognosis, suggesting that FASN knockdown may exert antitumor activity against cervical cancer through the Akt/mTOR signaling pathway.

A sensitive double antibodies sandwich ELISA for the diagnosis and therapeutic evaluation of cervical cancer

BACKGROUND

Vascular endothelial growth factor (VEGF) is a highly specific factor for tumors growth. However, the study on the mechanism of VEGF in cervical cancer, and the correlation between the expression level of VEGF and the therapeutic evaluation, prognosis of cervical cancer is not clear till now.

METHODS

In this study, RT-qPCR and IHC were used to evaluate the abnormal expression of VEGF in cervical cancer. The survival plots of the VEGF expression related to OS were observed by using the KM plotter. The mAbs against VEGF were screened and identified by ELISA addicted test, indirect ELISA, Western-blot, and dot-ELISA. We designed and prepared the overlapping truncations (V1, V2, V3) of VEGF to identify the B cell epitopes. Then, the epitopes recognized by anti-VEGF mAbs were mapped and displayed on a 3D structure of VEGF by using the PyMOL software. The highly specific and sensitive sandwich ELISA was established to detect the total VEGF quantification in 206 clinical sera samples, thus to evaluate the changes of VEGF before and after chemoradiotherapy in cervical cancer patients.

RESULTS

The VEGF was high expressed in cervical cancer tissues and cells, resulting a poor prognosis of cervical cancer. The mAbs 2E5 and 6D9 were selected with the titer of 1:256000 and 1:128000 respectively. The mAbs both had strong ability to combine with VEGF protein within 15 min and were identified as subclass IgG1 with κ-type light chains. 2E5 bound to V1 and V2, recognizing the N-terminal (1-121 aa) of VEGF, however 6D9 bound to V3, recognizing the C-terminal (116-174 aa) of VEGF. The 206 clinical samples were tested with the established VEGF-DAS-ELISA and calculated according to the equation (y = 0.0042088× + 0.105109, R² = 0.998). The results indicated that the expression levels of VEGF in cervical cancer samples were positively higher than those in normal samples. Importantly, we found the expression level of sera VEGF in cervical cancer patients decreased significantly after chemoradiotherapy. Therefore, the variable of VEGF levels in cervical cancer patients before and after treatment can be used as a new indicator of efficacy evaluation to guide the clinical treatment of cervical cancer.

CONCLUSION

A sensitive DAS-ELISA was established successfully, using which we can track the VEGF to evaluate the efficacy and estimate prognosis of cervical cancer. It is helpful for the diagnosis, therapeutic evaluation and prognosis of cervical cancer.

Down-regulation of MSMO1 promotes the development and progression of pancreatic cancer

Background: Methylsterol monooxygenase 1 (MSMO1), as a completely unique tumor biomarker, plays a vital role in the malignant progression of various cancer. Until now, the potential function and pathway of MSMO1 in the development of pancreatic cancer (PC) has not been explored yet, to our knowledge. Methods: We systematically explored the detail function of MSMO1 in Epithelial-mesenchymal transition (EMT) and cell proliferation of PC in vitro and in vivo. Results: MSMO1 expression was much lower in PC tissues than that in paired normal pancreas. MSMO1 positive expression was negatively associated with T stage, lymph node metastasis and vascular permeation of PC patients. Meanwhile, positive MSMO1 expression indicated a significantly better prognosis and an independent favorable prognostic factor. MSMO1 silencing promoted cell invasion and migration via activating EMT and PI3K-AKT-mTOR pathway [p-PI3K (Tyr458), p-AKT (Ser473) and p-mTOR (Ser2448)] in Capan-2, Panc-1 and SW1990 cells. In vivo, subcutaneous tumor size was enhanced by MSMO1 silencing following with the consistent change of EMT and PI3K/AKT signaling shown in vitro. The motivation of EMT and PI3K-AKT-mTOR pathway was also demonstrated in MSMO1 silencing mouse PANC02 cells. Conclusion: Down-regulation of MSMO1 in PC was associated with advanced progression and poor prognosis of PC patients. MSMO1 acts as a tumor suppressor via inhibiting the aggressive malignant biology of PC accompanying with regulating EMT and PI3K/AKT signaling.