Integrated bioinformatic analysis identifies UBE2Q1 as a potential prognostic marker for high grade serous ovarian cancer

UBE2Q1 as a novel cancer biomarker for lung adenocarcinoma: Short Title: Oncogenic function of UBE2Q1 in lung adenocarcinoma

PURPOSE

Ubiquitin-conjugating enzymes (E2s) participate in various tumor-promoting processes. UBE2Q1 is a member of the E2 family. This research aimed to detect the expression level of UBE2Q1 in human lung adenocarcinoma and to study its malignant biological function.

METHODS

Western blot, qRT-PCR and immunohistochemistry was used to measure the expression of UBE2Q1 in human lung adenocarcinoma tissues. The association between UBE2Q1 expression and clinic-pathological variables in 99 lung adenocarcinoma samples was analyzed by immunohistochemistry. In vitro experiment, establishing UBE2Q1 knockdown pattern, the markers of apoptosis, cell cycle and epithelial-mesenchymal transition (EMT) were analyzed by Western blot. CCK8, colony formation, Transwell and invasion assay analyzed the effect of UBE2Q1 knockdown on the proliferation, metastasis and invasion of lung cancer cells.

RESULTS

UBE2Q1 was overexpressed in lung adenocarcinoma, and the expression level of UBE2Q1 was related with TNM stage, tumor size, and lymph node metastasis. The high level of UBE2Q1 expression was also associated with poor survival and was an independent risk factor. In vitro, It was also confirmed that steady downregulation of UBE2Q1 could promote apoptosis, induce G2/M cell cycle arrest and regulate EMT. UBE2Q1 silencing dramatically reduce lung tumor cells proliferation, migration and invasion capacities.

CONCLUSIONS

UBE2Q1 may serve as a prognostic biomarker and a new therapeutic target of lung adenocarcinoma.

The proteogenomic landscape of multiple myeloma reveals insights into disease biology and therapeutic opportunities

Multiple myeloma (MM) is a plasma cell malignancy of the bone marrow. Despite therapeutic advances, MM remains incurable, and better risk stratification as well as new therapies are therefore highly needed. The proteome of MM has not been systematically assessed before and holds the potential to uncover insight into disease biology and improved prognostication in addition to genetic and transcriptomic studies. Here we provide a comprehensive multiomics analysis including deep tandem mass tag-based quantitative global (phospho)proteomics, RNA sequencing, and nanopore DNA sequencing of 138 primary patient-derived plasma cell malignancies encompassing treatment-naive MM, plasma cell leukemia and the premalignancy monoclonal gammopathy of undetermined significance, as well as healthy controls. We found that the (phospho)proteome of malignant plasma cells are highly deregulated as compared with healthy plasma cells and is both defined by chromosomal alterations as well as posttranscriptional regulation. A prognostic protein signature was identified that is associated with aggressive disease independent of established risk factors in MM. Integration with functional genetics and single-cell RNA sequencing revealed general and genetic subtype-specific deregulated proteins and pathways in plasma cell malignancies that include potential targets for (immuno)therapies. Our study demonstrates the potential of proteogenomics in cancer and provides an easily accessible resource for investigating protein regulation and new therapeutic approaches in MM.

The Role of Immunotherapy in the Treatment of Gynecologic Cancers: A Systematic Review

Gynecologic cancers remain a significant health burden worldwide. Immunotherapy has emerged as a promising treatment approach across various cancer types. To evaluate the efficacy and safety of immune checkpoint inhibitors, alone or in combination with other therapies, in the treatment of gynecologic cancers. We searched PubMed/MEDLINE, Cochrane Library, Embase, Web of Science, and ClinicalTrials.gov for clinical trials of immunotherapy in gynecologic cancers. Randomized controlled trials and prospective studies were included. MMAT tool was used to assess the quality of the studies. Risk of bias was assessed using appropriate tools for each study design. Seventeen studies met inclusion criteria, encompassing ovarian, endometrial, and cervical cancers. Immune checkpoint inhibitors, particularly in combination with standard therapies, demonstrated improved progression-free survival across multiple trials. Notable results include improved outcomes with pembrolizumab in endometrial and cervical cancers, and promising combinations of PARP inhibitors with checkpoint inhibitors in ovarian cancer. Safety profiles were generally consistent with known effects of immunotherapy. Immunotherapy shows significant promise in improving outcomes for patients with gynecologic cancers. Further research is needed to optimize patient selection and combination strategies.

Molecular Management of High-Grade Serous Ovarian Carcinoma

High-grade serous ovarian carcinoma (HGSOC) represents the most common form of epithelial ovarian carcinoma. The absence of specific symptoms leads to late-stage diagnosis, making HGSOC one of the gynecological cancers with the worst prognosis. The cellular origin of HGSOC and the role of reproductive hormones, genetic traits (such as alterations in P53 and DNA-repair mechanisms), chromosomal instability, or dysregulation of crucial signaling pathways have been considered when evaluating prognosis and response to therapy in HGSOC patients. However, the detection of HGSOC is still based on traditional methods such as carbohydrate antigen 125 (CA125) detection and ultrasound, and the combined use of these methods has yet to support significant reductions in overall mortality rates. The current paradigm for HGSOC management has moved towards early diagnosis via the non-invasive detection of molecular markers through liquid biopsies. This review presents an integrated view of the relevant cellular and molecular aspects involved in the etiopathogenesis of HGSOC and brings together studies that consider new horizons for the possible early detection of this gynecological cancer.

Ubiquitin Proteasome Gene Signatures in Ependymoma Molecular Subtypes

The ubiquitin proteasome system (UPS) is critically important for cellular homeostasis and affects virtually all key functions in normal and neoplastic cells. Currently, a comprehensive review of the role of the UPS in ependymoma (EPN) brain tumors is lacking but may provide valuable new information on cellular networks specific to different EPN subtypes and reveal future therapeutic targets. We have reviewed publicly available EPN gene transcription datasets encoding components of the UPS pathway. Reactome analysis of these data revealed genes and pathways that were able to distinguish different EPN subtypes with high significance. We identified differential transcription of several genes encoding ubiquitin E2 conjugases associated with EPN subtypes. The expression of the E2 conjugase genes UBE2C, UBE2S, and UBE2I was elevated in the ST_EPN_RELA subtype. The UBE2C and UBE2S enzymes are associated with the ubiquitin ligase anaphase promoting complex (APC/c), which regulates the degradation of substrates associated with cell cycle progression, whereas UBE2I is a Sumo-conjugating enzyme. Additionally, elevated in ST_EPN_RELA were genes for the E3 ligase and histone deacetylase HDAC4 and the F-box cullin ring ligase adaptor FBX031. Cluster analysis demonstrated several genes encoding E3 ligases and their substrate adaptors as EPN subtype specific genetic markers. The most significant Reactome Pathways associated with differentially expressed genes for E3 ligases and their adaptors included antigen presentation, neddylation, sumoylation, and the APC/c complex. Our analysis provides several UPS associated factors that may be attractive markers and future therapeutic targets for the subtype-specific treatment of EPN patients.

Identification of hub biomarkers and immune cell infiltration in polymyositis and dermatomyositis

Objective: Polymyositis (PM) and dermatomyositis (DM) are heterogeneous disorders. However, the etiology of PM/DM development has not been thoroughly clarified.

Methods: Gene expression data of PM/DM were obtained from Gene Expression Omnibus. We used robust rank aggregation (RRA) to identify differentially expressed genes (DEGs). Gene Ontology functional enrichment and pathway analyses were used to investigate potential functions of the DEGs. Weighted gene co-expression network analysis (WGCNA) was used to establish a gene co-expression network. CIBERSORT was utilized to analyze the pattern of immune cell infiltration in PM/DM. Protein–protein interaction (PPI) network, Venn, and association analyses between core genes and muscle injury were performed to identify hub genes. Receiver operating characteristic analyses were executed to investigate the value of hub genes in the diagnosis of PM/DM, and the results were verified using the microarray dataset GSE48280.

Results: Five datasets were included. The RRA integrated analysis identified 82 significant DEGs. Functional enrichment analysis revealed that immune function and the interferon signaling pathway were enriched in PM/DM. WGCNA outcomes identified MEblue and MEturquoise as key target modules in PM/DM. Immune cell infiltration analysis revealed greater macrophage infiltration and lower regulatory T-cell infiltration in PM/DM patients than in healthy controls. PPI network, Venn, and association analyses of muscle injury identified five putative hub genes: TRIM22, IFI6, IFITM1, IFI35, and IRF9.

Conclusions: Our bioinformatics analysis identified new genetic biomarkers of the pathogenesis of PM/DM. We demonstrated that immune cell infiltration plays a pivotal part in the occurrence of PM/DM.

Identification of novel genes in Behcet's disease using integrated bioinformatic analysis

Behcet’s disease (BD) is a chronic vascular inflammatory disease. However, the etiology and molecular mechanisms underlying BD development have not been thoroughly understood. Gene expression data for BD were obtained from the Gene Expression Omnibus database. We used robust rank aggregation (RRA) to identify differentially expressed genes (DEGs) between patients with BD and healthy controls. Gene ontology functional enrichment was used to investigate the potential functions of the DEGs. Protein–protein interaction (PPI) network analysis was performed to identify the hub genes. Receiver operating characteristic analyses were performed to investigate the value of hub genes in the diagnosis of BD. GSE17114 and GSE61399 datasets were included, comprising 32 patients with BD and 26 controls. The RRA integrated analysis identified 44 significant DEGs among the GSE17114 and GSE61399 CD4 + T lymphocytes. Functional enrichment analysis revealed that protein tyrosine/threonine phosphatase activity and immunoglobulin binding were enriched in BD. PPI analysis identified FCGR3B as a hub gene in the CD4 + T lymphocytes of BD patients. Our bioinformatic analysis identified new genetic features, which will enable further understanding of the pathogenesis of BD.

Integrated weighted gene co-expression network analysis reveals biomarkers associated with prognosis of high-grade serous ovarian cancer

Background

Ovarian cancer is the gynecologic tumor with the highest fatality rate, and high‐grade serous ovarian cancer (HGSOC) is the most common and malignant type of ovarian cancer. One important reason for the poor prognosis of HGSOC is the lack of effective diagnostic and prognostic biomarkers. New biomarkers are necessary for the improvement of treatment strategies and to ensure appropriate healthcare decisions.

Methods

To construct the co‐expression network of HGSOC samples, we applied weighted gene co‐expression network analysis (WGCNA) to assess the proteomic data obtained from the Clinical Proteomic Tumor Analysis Consortium (CPTAC), and module‐trait relationship was then analyzed and plotted in a heatmap to choose key module associated with HGSOC. Subsequently, hub genes with high connectivity in key module were identified by Cytoscape software. Furthermore, the biomarkers were selected through survival analysis, followed by evaluation using the relative operating characteristic (ROC) analysis.

Results

A total of 9 modules were identified by WGCNA, and module‐trait analysis revealed that the brown module was significantly associated with HGSOC (cor = 0.7). Ten hub genes with the highest connectivity were selected by protein‐protein interaction analysis. After survival and ROC analysis, ALB, APOB and SERPINA1 were suggested to be the biomarkers, and their protein levels were positively correlated with HGSOC prognosis.

Conclusion

We conducted the first gene co‐expression analysis using proteomic data from HGSOC samples, and found that ALB, APOB and SERPINA1 had prognostic value, which might be applied for the treatment of HGSOC in the future.

Resilience in Long-Term Viral Infection: Genetic Determinants and Interactions

Virus-induced neurological sequelae resulting from infection by Theiler's murine encephalomyelitis virus (TMEV) are used for studying human conditions ranging from epileptic seizures to demyelinating disease. Mouse strains are typically considered susceptible or resistant to TMEV infection based on viral persistence and extreme phenotypes, such as demyelination. We have identified a broader spectrum of phenotypic outcomes by infecting strains of the genetically diverse Collaborative Cross (CC) mouse resource. We evaluated the chronic-infection gene expression profiles of hippocampi and thoracic spinal cords for 19 CC strains in relation to phenotypic severity and TMEV persistence. Strains were clustered based on similar phenotypic profiles and TMEV levels at 90 days post-infection, and we categorized distinct TMEV response profiles. The three most common profiles included "resistant" and "susceptible," as before, as well as a "resilient" TMEV response group which experienced both TMEV persistence and mild neurological phenotypes even at 90 days post-infection. Each profile had a distinct gene expression signature, allowing the identification of pathways and networks specific to each TMEV response group. CC founder haplotypes for genes involved in these pathways/networks revealed candidate response-specific alleles. These alleles demonstrated pleiotropy and epigenetic (miRNA) regulation in long-term TMEV infection, with particular relevance for resilient mouse strains.