Identification and Analysis of Potential Autophagy-Related Biomarkers in Endometriosis by WGCNA

Multi-omics integration highlights the role of ubiquitination in endometriosis fibrosis

BACKGROUND

Endometriosis, characterized by the presence of active endometrial-like tissues outside the uterus, causes symptoms like dysmenorrhea and infertility due to the fibrosis of endometrial cells, which involves excessive deposition of extracellular matrix (ECM) proteins. Ubiquitination, an important post-transcriptional modification, regulates various biological processes in human diseases. However, its role in the fibrosis process in endometriosis remains unclear.

METHODS

We employed multi-omics approaches on two cohorts of endometriosis patients with 39 samples. GO terms and KEGG pathways enrichment analyses were used to investigate the functional changes involved in endometriosis. Pearson's correlation coefficient analysis was conducted to explore the relationship between global proteome and ubiquitylome in endometriosis. The protein expression levels of ubiquitin-, fibrosis-related proteins, and E3 ubiquitin-protein ligase TRIM33 were validated via Western blot. Transfecting human endometrial stroma cells (hESCs) with TRIM33 small interfering RNA (siRNA) in vitro to explore how TRIM33 affects fibrosis-related proteins.

RESULTS

Integration of proteomics and transcriptomics showed genes with concurrent change of both mRNA and protein level which involved in ECM production in ectopic endometria. Ubiquitylomics distinguished 1647 and 1698 ubiquitinated lysine sites in the ectopic (EC) group compared to the normal (NC) and eutopic (EU) groups, respectively. Further multi-omics integration highlighted the essential role of ubiquitination in key fibrosis regulators in endometriosis. Correlation analysis between proteome and ubiquitylome showed correlation coefficients of 0.32 and 0.36 for ubiquitinated fibrosis proteins in EC/NC and EC/EU groups, respectively, indicating positive regulation of fibrosis-related protein expression by ubiquitination in ectopic lesions. We identified ubiquitination in 41 pivotal proteins within the fibrosis-related pathway of endometriosis. Finally, the elevated expression of TGFBR1/α-SMA/FAP/FN1/Collagen1 proteins in EC tissues were validated across independent samples. More importantly, we demonstrated that both the mRNA and protein levels of TRIM33 were reduced in endometriotic tissues. Knockdown of TRIM33 promoted TGFBR1/p-SMAD2/α-SMA/FN1 protein expressions in hESCs but did not significantly affect Collagen1/FAP levels, suggesting its inhibitory effect on fibrosis in vitro.

CONCLUSIONS

This study, employing multi-omics approaches, provides novel insights into endometriosis ubiquitination profiles and reveals aberrant expression of the E3 ubiquitin ligase TRIM33 in endometriotic tissues, emphasizing their critical involvement in fibrosis pathogenesis and potential therapeutic targets.

Identification of signature genes for renal ischemia‒reperfusion injury based on machine learning and WGCNA

Background

As an inevitable event after kidney transplantation, ischemia‒reperfusion injury (IRI) can lead to a decrease in kidney transplant success. The search for signature genes of renal ischemia‒reperfusion injury (RIRI) is helpful in improving the diagnosis and guiding clinical treatment.

Methods

We first downloaded 3 datasets from the GEO database. Then, differentially expressed genes (DEGs) were identified and applied for functional enrichment analysis. After that, we performed three machine learning methods, including random forest (RF), Lasso regression analysis, and support vector machine recursive feature elimination (SVM-RFE), to further predict candidate genes. WGCNA was also executed to screen candidate genes from DEGs. Then, we took the intersection of candidate genes to obtain the signature genes of RIRI. Receiver operating characteristic (ROC) analysis was conducted to measure the predictive ability of the signature genes. Kaplan‒Meier analysis was used for association analysis between signature genes and graft survival. Verifying the expression of signature genes in the ischemia cell model.

Results

A total of 117 DEGs were screened out. Subsequently, RF, Lasso regression analysis, SVM-RFE and WGCNA identified 17, 25, 18 and 74 candidate genes, respectively. Finally, 3 signature genes (DUSP1, FOS, JUN) were screened out through the intersection of candidate genes. ROC analysis suggested that the 3 signature genes could well diagnose and predict RIRI. Kaplan‒Meier analysis indicated that patients with low FOS or JUN expression had a longer OS than those with high FOS or JUN expression. Finally, we validated using the ischemia cell model that compared to the control group, the expression level of JUN increased under hypoxic conditions.

Conclusions

Three signature genes (DUSP1, FOS, JUN) offer a good prediction for RIRI outcome and may serve as potential therapeutic targets for RIRI intervention, especially JUN. The prediction of graft survival by FOS and JUN may improve graft survival in patients with RIRI.

Analysis of Long Non-Coding RNA (lncRNA) UCA1, MALAT1, TC0101441, and H19 Expression in Endometriosis

Endometriosis is a disease of complex etiology. Hormonal, immunological, and environmental factors are involved in its formation. In recent years, special attention has been paid to genetic mechanisms that can have a significant impact on the increased incidence of endometriosis. The study aimed to analyze the expression of four long non-coding RNA (lncRNA) genes, UCA1, MALAT1, TC0101441, and H19, in the context of the risk of developing endometriosis. The material for genetic testing for the expression of lncRNA genes were tissue slices embedded in paraffin blocks from patients with endometriosis (n = 100) and the control group (n = 100). Gene expression was determined by the RT-PCR technique. The expression of the H19 gene in endometriosis patients was statistically significantly lower than in the control group. A statistically significant association was found between H19 gene expression in relation to The Revised American Society for Reproductive Medicine classification of endometriosis (rASRM) in the group of patients with endometriosis. Research suggests that H19 expression plays an important role in the pathogenesis of endometriosis.

Construction of a Redox-Related Prognostic Model with Predictive Value in Survival and Therapeutic Response for Patients with Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) represents the most common histological subtype of lung cancer. Redox plays a significant role in oncogenesis and antitumor immunity. In this study, we aimed to investigate the prognostic redox-associated genes and construct a redox-based prognostic signature for LUAD.

Materials and Methods

A discovery cohort containing 479 LUAD samples from The Cancer Genome Atlas (TCGA) was analyzed. We identified prognostic redox-associated genes by weighted correlation network analysis (WGCNA) and univariate Cox regression analysis to construct a prognostic model via least absolute shrinkage and selection operator (LASSO)-multivariate Cox regression analyses. The performance of the redox-based model was validated in the TCGA cohort and an independent cohort of 456 samples by Cox regression analyses, log-rank test, and receiver operating characteristic (ROC) curves. Correlations of the model with clinicopathological variables and lymphocyte infiltration were assessed. Gene set enrichment analysis (GSEA) was used to clarify the underlying mechanism of the prognostic model. We constructed a nomogram based on the model and created calibration curves to show the accordance between actual survival and predicted survival of the nomogram.

Results

Stepwise analyses identified 6 prognostic redox-associated genes of LUAD and constructed a prognostic model that performed well in both the discovery and validation cohorts. The model was found to be associated with tumor stage, mutation of TP53 and EGFR, and lymphocyte infiltration. The model was mainly involved in the regulation of the cell cycle, DNA replication and repair, NADH metabolism, and the p53 signaling pathway. Calibration curves showed the high predictive accuracy of the nomogram.

Conclusions

This study explored the role of redox-associated genes in LUAD and constructed a prognostic model of LUAD. The signature was also associated with tumor progression and therapeutic response to immunotherapy. These findings contributed to uncovering the underlying mechanism and discovering novel prognostic predictor of LUAD.