Development and Clinical Validation of Novel 8-Gene Prognostic Signature Associated With the Proportion of Regulatory T Cells by Weighted Gene Co-Expression Network Analysis in Uterine Corpus Endometrial Carcinoma

Establishing and Validating an Innovative Focal Adhesion-Linked Gene Signature for Enhanced Prognostic Assessment in Endometrial Cancer

Studies have highlighted the significant role of focal adhesion signaling in cancer. Nevertheless, its specific involvement in the pathogenesis of endometrial cancer and its clinical significance remains uncertain. We analyzed TCGA-UCEC and GSE119041 datasets with corresponding clinical data to investigate focal adhesion-related gene expression and their clinical significance. A signature, "FA-riskScore," was developed using LASSO regression in the TCGA cohort and validated in the GSE dataset. The FA-riskScore was compared with four existing models in terms of their prediction performance. We employed univariate and multivariate Cox regression analyses towards FA-riskScore to assess its independent prognostic value. A prognostic evaluation nomogram based on our model and clinical indexes was established subsequently. Biological and immune differences between high- and low-risk groups were explored through functional enrichment, PPI network analysis, mutation mining, TME evaluation, and single-cell analysis. Sensitivity tests on commonly targeted drugs were performed on both groups, and Connectivity MAP identified potentially effective molecules for high-risk patients. qRT-PCR validated the expressions of FA-riskScore genes. FA-riskScore, based on FN1, RELN, PARVG, and PTEN, indicated a poorer prognosis for high-risk patients. Compared with published models, FA-riskScore achieved better and more stable performance. High-risk groups exhibited a more challenging TME and suppressive immune status. qRT-PCR showed differential expression in FN1, RELN, and PTEN. Connectivity MAP analysis suggested that BU-239, potassium-canrenoate, and tubocurarine are effective for high-risk patients. This study introduces a novel prognostic model for endometrial cancer and offers insights into focal adhesion's role in cancer pathogenesis.

Clinicopathological role of Cyclin A2 in uterine corpus endometrial carcinoma: Integration of tissue microarrays and ScRNA-Seq

BACKGROUND

The comprehensive expression level and potential molecular role of Cyclin A2 (CCNA2) in uterine corpus endometrial carcinoma (UCEC) remains undiscovered.

METHODS

UCEC and normal endometrium tissues from in-house and public databases were collected for investigating protein and messenger RNA expression of CCNA2. The transcription factors of CCNA2 were identified by the Cistrome database. The prognostic significance of CCNA2 in UCEC was evaluated through univariate and multivariate Cox regression as well as Kaplan-Meier curve analysis. Single-cell RNA-sequencing (scRNA-seq) analysis was performed to explore cell types in UCEC, and the AUCell algorithm was used to investigate the activity of CCNA2 in different cell types.

RESULTS

A total of 32 in-house UCEC and 30 normal endometrial tissues as well as 720 UCEC and 165 control samples from public databases were eligible and collected. Integrated calculation showed that the CCNA2 expression was up-regulated in the UCEC tissues (SMD = 2.43, 95% confidence interval 2.23∼2.64). E2F1 and FOXM1 were identified as transcription factors due to the presence of binding peaks on transcription site of CCNA2. CCNA2 predicted worse prognosis in UCEC. However, CCNA2 was not an independent prognostic factor in UCEC. The scRNA-seq analysis disclosed five cell types: B cells, T cells, monocytes, natural killer cells, and epithelial cells in UCEC. The expression of CCNA2 was mainly located in B cells and T cells. Moreover, CCNA2 was active in T cells and B cells using the AUCell algorithm.

CONCLUSION

CCNA2 was up-regulated and mainly located in T cells and B cells in UCEC. Overexpression of CCNA2 predicted unfavorable prognosis of UCEC.

[TRIM21 Inhibits the Proliferation and Migration of Lung Adenocarcinoma Cells by Interacting with ZSWIM1]

BACKGROUND

Lung adenocarcinoma (LUAD) is a highly morbid and fatal cancer. Despite advancements in modern medical treatment, the 5-year survival rate of patients remains suboptimal. Our previous study revealed that zinc finger SWIM-type containing 1 (ZSWIM1), a novel protein, promotes the proliferation, migration, and invasion of LUAD cells. The aim of this study is to investigate the impact of E3 ubiquitin ligase tripartite motif protein 21 (TRIM21) on ZSWIM1-mediated cell proliferation and migration.

METHODS

The interaction and co-localization between TRIM21 and ZSWIM1 were verified using co-immunoprecipitation (Co-IP) and immunofluorescence (IF). The effects of TRIM21 and ZSWIM1 on the proliferation and migration of LUAD cells were assessed through MTT and Transwell assays, respectively. Western blot (WB) analysis was conducted to evaluate the impact of TRIM21 and ZSWIM1 on the expression of epithelial-mesenchymal transition (EMT) markers in LUAD cells. The influence of TRIM21 on the ubiquitination of ZSWIM1 was examined using Co-IP combined with WB.

RESULTS

TRIM21 was found to interact and co-localize with ZSWIM1. Overexpression of TRIM21 inhibited the proliferation and migration of LUAD cells. Overexpression of TRIM21 reduced the promoting effect of ZSWIM1 on the proliferation, migration, and invasion of lung adenocarcinoma cells, and reversed the impact of ZSWIM1 on the expression of E-cadherin and Vimentin. Conversely, knockdown of TRIM21 further enhanced the promoting effect of ZSWIM1 on the proliferation and migration of LUAD cells. Mechanistically, we observed that overexpression of TRIM21 significantly enhanced the ubiquitination level of ZSWIM1, leading to a decrease in ZSWIM1 protein expression.

CONCLUSIONS

TRIM21 binds to and promotes the ubiquitination of ZSWIM1, resulting in reduced protein expression of ZSWIM1, which leads to the inhibition of ZSWIM1-mediated promotion of proliferation, migration, and invasion in LUAD cells.

Structures and Functions of the Human GATOR1 Complex

Eukaryotic cells coordinate available nutrients with their growth through the mechanistic target of rapamycin complex 1 (mTORC1) pathway, in which numerous evolutionarily conserved protein complexes survey and transmit nutrient inputs toward mTORC1. mTORC1 integrates these inputs and activates downstream anabolic or catabolic programs that are in tune with cellular needs, effectively maintaining metabolic homeostasis. The GAP activity toward Rags-1 (GATOR1) protein complex is a critical negative regulator of the mTORC1 pathway and, in the absence of amino acid inputs, is activated to turn off mTORC1 signaling. GATOR1-mediated inhibition of mTORC1 signaling is tightly regulated by an ensemble of protein complexes that antagonize or promote its activity in response to the cellular nutrient environment. Structural, biochemical, and biophysical studies of the GATOR1 complex and its interactors have advanced our understanding of how it regulates cellular metabolism when amino acids are limited. Here, we review the current research with a focus on GATOR1 structure, its enzymatic mechanism, and the growing group of proteins that regulate its activity. Finally, we discuss the implication of GATOR1 dysregulation in physiology and human diseases.

The role and participation of immune cells in the endometrial tumor microenvironment

The tumor microenvironment is surrounded by blood vessels and consists of malignant, non-malignant, and immune cells, as well as signalling molecules, which primarily affect the therapeutic response and curative effects of drugs in clinical studies. Tumor-infiltrating immune cells participate in tumor progression, impact anticancer therapy, and eventually lead to the development of immune tolerance. Immunotherapy is evolving as a promising therapeutic intervention to stimulate and activate the immune system to suppress cancer cell growth. Endometrial cancer (EC) is an immunogenic disease, and in recent years, immunotherapy has shown benefit in the treatment of recurrent and advanced EC. This review discusses the key molecular pathways associated with the intra-tumoral immune response and the involvement of circulatory signalling molecules. Specific immunologic signatures in EC which offer targets for immunomodulating agents, are also discussed. We have summarized the available literature in support of using immunotherapy in EC. Lastly, we have also discussed ongoing clinical trials that may offer additional promising immunotherapy options in the future. The manuscript also explored innovative approaches for screening and identifying effective drugs, and to reduce the financial burdens for the development of personalized treatment strategies. Collectively, we aim to provide a comprehensive review of the role of immune cells and the tumor microenvironment in the development, progression, and treatment of EC.

Prediction of Prognosis, Immunotherapy and Chemotherapy with an Immune-Related Risk Score Model for Endometrial Cancer

Endometrial cancer (EC) is the most common gynecologic cancer. The overall survival remains unsatisfying due to the lack of effective treatment screening approaches. Immunotherapy as a promising therapy has been applied for EC treatment, but still fails in many cases. Therefore, there is a strong need to optimize the screening approach for clinical treatment. In this study, we employed co-expression network (GCN) analysis to mine immune-related GCN modules and key genes and further constructed an immune-related risk score model (IRSM). The IRSM was proved effective as an independent predictor of poor prognosis. The roles of IRSM-related genes in EC were confirmed by IHC. The molecular basis, tumor immune microenvironment and clinical characteristics of the IRSM were revealed. Moreover, the IRSM effectiveness was associated with immunotherapy and chemotherapy. Patients in the low-risk group were more sensitive to immunotherapy and chemotherapy than those in the high-risk group. Interestingly, the patients responding to immunotherapy were also more sensitive to chemotherapy. Overall, we developed an IRSM which could be used to predict the prognosis, immunotherapy response and chemotherapy sensitivity of EC patients. Our analysis not only improves the treatment of EC but also offers targets for personalized therapeutic interventions.

ST6GALNAC4 promotes hepatocellular carcinogenesis by inducing abnormal glycosylation

Hepatocellular carcinoma (HCC) is one of the most lethal tumor types worldwide. Glycosylation has shown promise in the study of tumor mechanisms and treatment. The glycosylation status of HCC and the underlying molecular mechanisms are still not fully elucidated. Using bioinformatic analysis we obtained a more comprehensive characterization of glycosylation of HCC. Our analysis presented that high glycosylation levels might correlate with tumor progression and poor prognosis. Subsequent Experiments identified key molecular mechanisms for ST6GALNAC4 promoting malignant progression by inducing abnormal glycosylation. We confirmed the contribution of ST6GALNAC4 to proliferation, migration, and invasion in vitro and in vivo. Mechanistic studies revealed that ST6GALNAC4 may be induced abnormal TGFBR2 glycosylation, resulting in the higher protein levels of TGFBR2 and TGF[Formula: see text] pathway increased activation. Our study also provided a further understand of immunosuppressive function of ST6GALNAC4 through T antigen-galectin3+ TAMs axis. This study has provided one such possibility that galectin3 inhibitors might be an acceptable treatment choice for HCC patients with high T antigen expression.

An Integrated Analysis Identified TAGLN2 As an Oncogene Indicator Related to Prognosis and Immunity in Pan-Cancer

Background: Transgelin-2 (TAGLN2) has long been regarded as an actin-binding protein that modulates actin gelation and controls actin cytoskeleton dynamics. However, recent studies have reported that TAGLN2 can directly or indirectly participate in multiple cancer-related processes, including cell migration, proliferation, differentiation, and apoptosis. To further investigate the role of TAGLN2 in carcinogenesis, a comprehensive analysis was launched to evaluate the expression status and prognostic value of TAGLN2 in pan-cancer. Methods: Herein, data was retrieved from publicly online websites and databases, including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), UCSC Xena, cBioPortal, Human Protein Atlas (HPA), TIMER2.0, CancerSEA, GDSC, and ImmuCellAI. Gene expression pattern and its correlation with prognosis were assessed across cancer types. Moreover, an analysis was conducted to explore the relationships between TAGLN2 and methylation, copy number values (CNVs), tumor microenvironment (TME), immune cell infiltration, immune-relevance genes, tumor mutation burden (TMB), microsatellite instability (MSI), and IC50. Additionally, R package "clusterProfiler" was utilized to perform enrichment analysis on TAGLN2. Finally, the ability of TAGLN2 as an oncogene was preliminarily verified in vitro in UCEC. Results: Our findings revealed that TAGLN2 was specifically overexpressed and related to an unfavorable prognosis in most cancers. There was a significant connection between TAGLN2 expression and methylation and CNVs. Besides, we identified TAGLN2 correlated to TME, immune cell infiltration, immune-relevant genes, TMB, and MSI, suggesting an immunoregulatory role in cancers. Notably, TAGLN2 expression showed a positive correlation with macrophages, and cancer-associated fibroblasts, whereas a negative correlation with the infiltration degree of B cells. Mechanically, the results obtained from Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) provided theory-supportive evidence that TAGLN2 interlinkages with immunity and programmed cell death. Overall, anti-tumor drugs were overtly associated with TAGLN2 dysregulation among diverse cancers. At last, UCEC cell lines with TAGLN2-depleting had an inhibition of the migration and invasion ability. Conclusions: These findings enriched the knowledge about the role of TAGLN2 in tumorigenesis and progression, revealing TAGLN2 may serve as a potential therapeutic strategy for various malignancies.

Screening and validation of potential markers associated with uterine corpus endometrial carcinoma and polycystic ovary syndrome based on bioinformatics methods

Background: Endometrial cancer (UCEC) is a commonly occurring tumor in females, and polycystic ovary syndrome (PCOS) is closely related to UCEC, but the molecular mechanisms remain unclear. This article aims to explore potential molecular mechanisms in UCEC and PCOS, as well as identify prognostic genes for UCEC. Methods: Bioinformatics methods were employed to screen for DEGs in UCEC and PCOS. The shared DEGs were analyzed by constructing a protein-protein interaction (PPI) network using the String database and Cytoscape software. The enrichment analysis was performed using Metascape. The shared DEGs associated with the prognosis of UCEC were identified through univariate and lasso Cox regression methods. A multivariate Cox regression model was constructed and internally validated. The expression and test efficiency of the key prognostic genes were verified using external datasets for UCEC and PCOS. Furthermore, the Gepia database was utilized to analyze the expression of key prognostic genes and their correlation with the disease-free survival (RFS) of UCEC. Tumor mutation burden (TMB), immune infiltration, and the correlation of immune cells were assessed for the prognostic genes of UCEC. Results: There were 151 shared DEGs identified between UCEC and PCOS through bioinformatics screening. These shared DEGs were primarily enriched in leukocyte activation. Following model construction and verification, nine genes were determined to be prognostic for UCEC from the shared DEGs. Among them, TSPYL5, KCNJ15, RTN1, HMOX1, DCAF12L1, VNN2, and ANXA1 were confirmed as prognostic genes in UCEC through external validation. Additionally, RTN1 was identified as a key gene in both UCEC and PCOS. Gepia analysis revealed that higher expression of RTN1 was associated with RFS in UCEC. Immune infiltration analysis of the shared DEGs demonstrated significant differences in the expression of various immune cells between UCEC high and low TMB groups. The seven key prognostic genes in UCEC exhibited regulatory relationships with immune cells. Conclusion: This study identified TSPYL5, KCNJ15, RTN1, HMOX1, DCAF12L1, VNN2, and ANXA1 as the key prognostic DEGs of UCEC. These genes are associated with UCEC survival, TMB, immune cell infiltration, and immune cell regulation. Among them, RTN1 may serve as a potential biomarker for both UCEC and PCOS.

Weighted correlation network analysis identifies multiple susceptibility loci for low-grade glioma

BACKGROUND

The current molecular classifications cannot completely explain the polarized malignant biological behavior of low-grade gliomas (LGGs), especially for tumor recurrence. Therefore, we tried to identify suspicious hub genes related to tumor recurrence in LGGs.

METHODS

In this study, we constructed a gene-miRNA-lncRNA co-expression network for LGGs by a weighted gene co-expression network analysis (WGCNA). GDCRNATools and the WGCNA R package were mainly used in data analysis.

RESULTS

Sequencing data from 502 LGG patients were analyzed in this study. Compared with recurrent glioma tissues, we identified 774 differentially expressed (DE) mRNAs, 49 DE miRNAs, and 129 DE lncRNAs in primary LGGs and ultimately determined that the expression of MKLN1 was related to tumor recurrence in LGG.

CONCLUSION

This study identified the potential biomarkers for the pathogenesis and recurrence of LGGs and proposed that MKLN1 could be a potential therapeutic target.

ZSWIM1 Promotes the Proliferation and Metastasis of Lung Adenocarcinoma Cells through the STK38/MEKK2/ERK1/2 Axis

Investigating the functions of the proteins with no or less functional annotations is an important goal of the HPP (Human Proteome Project) Grand Project. In this study, we investigated the function of such a protein, ZSWIM1 (C20orf162), its gene located on chromosome 20. Its expression is upregulated in lung adenocarcinoma compared with the adjacent normal tissues and negatively correlated with the overall survival. Overexpressing ZSWIM1 markedly promotes the proliferation, migration, invasion as well as epithelial-to-mesenchymal transition in lung adenocarcinoma cells, while knocking down ZSWIM1 functions oppositely. The interactome of ZSWIM1 was identified by immunoprecipitation-mass spectrometry, and we verified the interaction of ZSWIM1 with the potential partner, STK38. ZSWIM1 antagonized the function of STK38. Mechanically, ZSWIM1 promoted the activation of MEKK2/ERK1/2 pathway through interacting with STK38, leading to the release of MEKK2. Taken together, ZSWIM1 can be annotated as an oncogene in lung adenocarcinoma, and the STK38/MEKK2/ERK1/2 axis mediates its promoting role in lung adenocarcinoma.

The Modifying Effect of Obesity on the Association of Matrix Metalloproteinase Gene Polymorphisms with Breast Cancer Risk

Objective: We investigated the possible modifying effect of obesity on the association of matrix metalloproteinase (MMP) gene polymorphisms with breast cancer (BC) risk. Methods: A total of 1104 women divided into two groups according to their body mass index (BMI): BMI ≥ 30 (119 BC, and 190 control) and BMI < 30 (239 BC, and 556 control) were genotyped for specially selected (according to their association with BC in the previous study) 10 single-nucleotide polymorphisms (SNP) of MMP1, 2, 3, 8, and 9 genes. Logistic regression association analysis was performed in each studied group of women (with/without obesity). Functional annotation of BC-correlated MMP polymorphic variants was analyzed by in silico bioinformatics. Results: We observed significant differences in the involvement of MMP SNPs in BC in obese and non-obese women. Polymorphic loci MMP9 (c.836 A > G (rs17576) and c. 1721 C > G (rs2250889)) were BC-protective factors in obese women (OR 0.71, allelic model, and OR 0.55, additive model, respectively). Genotypes TT MMP2 (c.-1306 C > T,rs243865) and AA MMP9 (c. 1331-163 G > A,rs3787268) determined BC susceptibility in non-obese women (OR 0.31, and OR 2.36, respectively). We found in silico substantial multidirectional influences on gene expression in adipose tissue BC-related polymorphic loci: BC risk allele A-rs3787268 in non-obese women is associated with low expression NEURL2, PLTP, RP3-337O18.9, SPATA25, and ZSWIM1, whereas BC risk allele A-rs17576 in obese women is associated with high expression in the same genes in visceral and/or subcutaneous adipose. Conclusions: our study indicated that obesity has a significant modifying effect on the association of MMP genes with BC risk in postmenopausal women.

Pan-Cancer Gene Analysis of m6A Modification and Immune Infiltration in Uterine Corpus Endometrial Carcinoma

Objective

This investigation was to test the potential role of m6A-related long non-coding RNAs (lncRNAs) and immune infiltration as crucial factors in the diagnosis and treatment of uterine corpus endometrial cancer (UCEC).

Method

The UCEC RNA-seq data were downloaded in the Cancer Genome Atlas (TCGA, https://portal.gdc.cancer.gov/). There were 587 samples totally, containing 543 UCEC cases and 35 healthy cases. The clinical information of UCEC cases included survival time, survival status, gender, age, stage, and TMN stage. Twenty-three m6A-related genes were found in published journals. The RNA-seq documents of UCEC were downloaded in the Cancer Genome Atlas (TCGA). The hub gene data of UCEC were downloaded from GEPIA2 database. The different packages of R language were applied to calculate and analyze in this research.

Results

Among 587 cases in our study, we discovered 3039 lncRNAs in the TCGA-UCEC database. After the differential analysis, 23 m6A-associated genetics were screened and twenty-one m6A-associated differential genetics were found. In the end, we obtained 20 m6A-related lncRNAs. LNCTAM34A was considered as a predictive gene through univariate and multivariate Cox regression analysis. In addition to the above, patients with high LNCTAM34A expression had better outcomes than those with low LNCTAM34A expression. The high-risk cohort had greater scores of activated dendritic cells (aDCs), B cells, and T cell regulatory (Tregs) than low-risk cohort; in the meanwhile, high-risk cohort had lower scores of DCs and iDCs. Then, the high-risk cohort displayed greater scores in the immune functions of MHC class I, para-inflammation, and type I IFN response than those of low-risk cohort. Among 27 immune-inducible genes, the level of CD244, KIR3DLI, NRP1, PDCD1LG2, and TNFRSF8 was reduced in UCEC samples and the level of CD27, CD28, CD70, CD80, CD86, HAVCR2, ICOS, IDO1, LAIR1, PDCD1, TIGIT, TNFRSF18, -25, -9, -14, and VTCN1 was increased in UCEC samples.

Conclusion

The key role of M6A-related lncRNAs in immune microenvironment in high-risk patients of UCEC. The patients with strong expression of LNCTAM34A have a good prognosis, and LNCTAM34A can be used as a prognostic gene for UCEC. m6A-related lncRNAs can be used as a potential treatment for UCEC. Our observations can be used as a hypothetical basis for future in vitro and animal experiments.

Analysis of the Prognostic Significance and Immune Infiltration of the Amino Acid Metabolism-Related Genes in Colon Adenocarcinoma

Amino acid metabolization is verified to be a part in the progression of cancer. However, genes related to the amino acid metabolism have not been identified in colon adenocarcinoma (COAD). A systematic prognostic model of COAD becomes a pressing need. Among genes related to the amino acid metabolism, RIMKLB, ASPG, TH, MTAP, AZIN2, PSMB2, HDC, ACMSD, and PSMA8 were identified to construct a risk model. Kaplan–Meier (K–M) analyses demonstrated that the high-risk group achieved a poor prognosis. Area under the respective ROC (AUC) values indicated the robustness of the model. To highlight its clinical value, multivariate Cox was used to obtain the optimal variables to construct a nomogram. A higher tumor mutation burden was observed in the high-risk group. However, the low-risk group had a stronger immune infiltration. Seven molecular subtypes were found by consensus cluster. Twenty-two hub genes were identified related to the ESTIMATE score using WGCNA. In brief, our research constructed a stable prognostic model related to the amino acid metabolism in COAD, revealing its connection to the immune microenvironment. The model guided the outcome of COAD and the direction of immunotherapy.

The Expression of Pyroptosis-Related Gene May Influence the Occurrence, Development, and Prognosis of Uterine Corpus Endometrial Carcinoma

BACKGROUND

Increasing evidence has demonstrated that pyroptosis exerts key roles in the occurrence, development, and prognosis of uterine corpus endometrial carcinoma (UCEC). However, the mechanism of pyroptosis and its predictive value for prognosis remain largely unknown.

METHODS

UCEC data were acquired from The Cancer Genome Atlas (TCGA) database. The differentially expressed genes in UCEC vs. normal cases were selected to perform a weighted correlation network analysis (WGCNA). Forty-two UCEC-associated pyroptosis-related genes were identified via applying differential expression analysis. Protein-protein interaction (PPI) and gene correlation analyses were applied to explore the relationship between 21 UCEC key genes and 42 UCEC-associated pyroptosis-related genes. The expression of 42 UCEC-associated pyroptosis-related genes of different grades was also calculated. The immune environment of UCEC was evaluated. Furthermore, pyroptosis-related genes were filtered out by the co-expression. Univariate and a least absolute shrinkage and selection operator (LASSO) Cox analyses were implemented to yield a pyroptosis-related gene model. We also performed consensus classification to regroup UCEC samples into two clusters. A clinically relevant heatmap and survival analysis curve were implemented to explore the clinicopathological features and relationship between two clusters. Furthermore, a Kaplan-Meier survival analysis was implemented to analyze the risk model.

RESULTS

Twenty-one UCEC key genes and 42 UCEC-associated pyroptosis-related genes were identified. The PPI and gene correlation analysis showed a clear relationship. The expression of 42 UCEC-associated pyroptosis-related genes of different grades was also depicted. A risk model based on pyroptosis-related genes was then developed to forecast overall survival among UCEC patients. Finally, Cox regression analysis verified this model as an independent risk factor for UCEC patients.

CONCLUSIONS

The expression of pyroptosis-related gene may influence UCEC occurrence, development, and prognosis.