AGER promotes proliferation and migration in cervical cancer

Survival and Enrichment Analysis of Epithelial-Mesenchymal Transition Genes in Bladder Urothelial Carcinoma

The escalating prevalence of bladder cancer, particularly urothelial carcinoma, necessitates innovative approaches for prognosis and therapy. This study delves into the significance of genes related to epithelial-mesenchymal transition (EMT), a process inherently linked to carcinogenesis and comparatively better studied in other cancers. We examined 1184 EMT-related gene expression levels in bladder urothelial cancer cases through the TCGA dataset. Genes shown to be differentially expressed in relation to survival underwent further network and enrichment analysis to uncover how they might shape disease outcomes. Our in silico analysis revealed a subset of 32 genes, including those significantly represented in biological pathways such as VEGF signaling and bacterium response. In addition, these genes interact with genes involved in the JAK-STAT signaling pathway. Additionally, some of those 32 genes have been linked to immunomodulators such as chemokines CCL15 and CCL18, as well as to various immune cell infiltrates. Our findings highlight the prognostic utility of various EMT-related genes and identify possible modulators of their effect on survival, allowing for further targeted wet lab research and possible therapeutic intervention.

Identification of four metabolic subtypes and key prognostic markers in lung adenocarcinoma based on glycolytic and glutaminolytic pathways

BACKGROUND

Glucose and glutamine are the main energy sources for tumor cells. Whether glycolysis and glutaminolysis play a critical role in driving the molecular subtypes of lung adenocarcinoma (LUAD) is unknown. This study attempts to identify LUAD metabolic subtypes with different characteristics and key genes based on gene transcription profiling data related to glycolysis and glutaminolysis, and to construct prognostic models to facilitate patient outcome prediction.

METHODS

LUAD related data were obtained from the Cancer Genome Atlas and Gene Expression Omnibus, including TCGA-LUAD, GSE42127, GSE68465, GSE72094, GSE29013, GSE31210, GSE30219, GSE37745, GSE50081. Unsupervised consensus clustering was used for the identification of LUAD subtypes. Differential expression analysis, weighted gene co-expression network analysis (WGCNA) and CytoNCA App in Cytoscape 3.9.0 were used for the screening of key genes. The Cox proportional hazards model was used for the construction of the prognostic risk model. Finally, qPCR analysis, immunohistochemistry and immunofluorescence colocalization were used to validate the core genes of the model.

RESULT

This study identified four distinct characterized LUAD metabolic subtypes, glycolytic, glutaminolytic, mixed and quiescent types. The glycolytic type had a worse prognosis than the glutaminolytic type. Nine genes (CXCL8, CNR1, AGER, ALB, S100A7, SLC2A1, TH, SPP1, LEP) were identified as hub genes driving the glycolytic/glutaminolytic LUAD. In addition, the risk assessment model constructed based on three genes (SPP1, SLC2A1 and AGER) had good predictive performance and could be validated in multiple independent external LUAD cohorts. These three genes were differentially expressed in LUAD and lung normal tissues, and might be potential prognostic markers for LUAD.

CONCLUSION

LUAD can be classified into four different characteristic metabolic subtypes based on the glycolysis- and glutaminolysis-related genes. Nine genes (CXCL8, CNR1, AGER, ALB, S100A7, SLC2A1, TH, SPP1, LEP) may play an important role in the subtype-intrinsic drive. This metabolic subtype classification, provides new biological insights into the previously established LUAD subtypes.

Prognostic Risk Signature and Comprehensive Analyses of Endoplasmic Reticulum Stress-Related Genes in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is the main pathological subtype of non-small-cell lung cancer. Endoplasmic reticulum stress (ERS) has been found to be involved in multiple tumor-related biological processes. At present, a comprehensive analysis of ERS-related genes in LUAD is still lacking. A total of 1034 samples from TCGA and GEO were used to screen differentially expressed genes. Further, Random Forest algorithm was utilized to screen characteristic genes related to prognosis. Then, LASSO Cox regression was used to construct a prognostic signature. Taking the median of signature score as the threshold, patients were separated into high-risk (HR) group and low-risk (LR) group. Tumor mutation burden (TMB), immune cell infiltration, cancer stem cell infiltration, expression of HLA, and immune checkpoints of the two risk groups were analyzed. TIDE score was used to evaluate the response of the two risk groups to immunotherapy. Finally, the gene expression was verified in clinical tissues with RT-qPCR. An eight-gene signature (ADRB2, AGER, CDKN3, GJB2, SFTPC, SLC2A1, SLC6A4, and SSR4) was constructed. TMB and cancer stem cell infiltration were higher in the HR group than the LR group. TIDE score and expression level of HLA were higher in the LR group than the HR group. Expression level of immune checkpoints, including CD28, CD27, IDO2, and others, were higher in the LR group. Multiple drugs approved by FAD, targeting ERS-related genes, were available for the treatment of LUAD. In summary, we established a stable prognostic model based on ERS-related genes to help the classification of LUAD patients and looked for new treatment strategies from aspects of immunity, tumor mutation, and tumor stem cell infiltration.

Prognostic Implication of Energy Metabolism-Related Gene Signatures in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the major non-small-cell lung cancer pathological subtype with poor prognosis worldwide. Herein, we aimed to build an energy metabolism-associated prognostic gene signature to predict patient survival.

Methods

The gene expression profiles of patients with LUAD were downloaded from the TCGA and GEO databases, and energy metabolism (EM)-related genes were downloaded from the GeneCards database. Univariate Cox and LASSO analyses were performed to identify the prognostic EM-associated gene signatures. Kaplan–Meier and receiver operating characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signatures. A CIBERSORT analysis was used to evaluate the correlation between the risk model and immune cells. A nomogram was used to predict the survival probability of LUAD based on a risk model.

Results

We constructed a prognostic signature comprising 13 EM-related genes (AGER, AHSG, ALDH2, CIDEC, CYP17A1, FBP1, GNB3, GZMB, IGFBP1, SORD, SOX2, TRH and TYMS). The Kaplan–Meier curves validated the good predictive ability of the prognostic signature in TCGA AND two GEO datasets (p<0.0001, p=0.00021, and p=0.0034, respectively). The area under the curve (AUC) of the ROC curves also validated the predictive accuracy of the risk model. We built a nomogram to predict the survival probability of LUAD, and the calibration curves showed good predictive ability. Finally, a functional analysis also unveiled the different immune statuses between the two different risk groups.

Conclusion

Our study constructed and verified a novel EM-related prognostic gene signature that could improve the individualized prediction of survival probability in LUAD.

RAGE is a potential biomarker implicated in immune infiltrates and cellular senescence in lung adenocarcinoma

Background

Receptor for Advanced Glycation End‐products (RAGE) is an oncogene abnormally expressed in various cancers. However, the clinical value of RAGE and the biological role of RAGE in lung cancer have not been fully investigated.

Methods

We compared the RAGE expression using several public databases. The relationship between RAGE expression and clinicopathological variables was assessed. The R software package was used to carry out enrichment analyses of RAGE co‐expression and gene set enrichment analysis (GSEA). Additionally, we used the TIMER database to assess the association between immune infiltration and RAGE expression. The correlation between RAGE expression and senescence biomarkers in lung adenocarcinoma was analyzed using the TCGA database.

Results

Our findings indicated that the expression of RAGE was downregulated in lung adenocarcinoma, and down‐regulation of RAGE was related to poor overall survival and disease‐free survival. Functional enrichment analysis indicated that RAGE co‐expression genes were mainly associated with neutrophil activation involved in immune response, neutrophil degranulation, and regulation of leukocyte‐mediated immunity. Correlation analysis revealed that RAGE expression was closely related to the purity of the tumor and immune infiltration. GSEA indicated that the RAGE‐related differential genes were mainly enriched in senescence‐related pathways. Besides, the RAGE expression was significantly associated with senescence‐related genes.

Conclusion

Down‐regulation of RAGE expression was associated with poor prognosis, as well as defective immune infiltration and cellular senescence in lung adenocarcinoma.

Upregulation of CCT3 promotes cervical cancer progression through FN1

The mechanisms underlying cervical cancer progression have not yet been fully elucidated; thus, further investigations are required. Chaperonin containing TCP1 subunit 3 (CCT3) expression was found to be upregulated in several types of human cancer. However, the roles of CCT3 in cervical cancer remain poorly understood. Thus, the present study aimed to determine the roles of CCT3 in the progression of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). For this purpose, the Tumor Immune Estimation Resource and Gene Expression Profiling Interactive Analysis databases were used to analyze the mRNA and protein expression levels of CCT3 in CESC samples. The effects of CCT3 on the proliferation and migration of CESC in vitro were determined using various experiments, including proliferation, Transwell and flow cytometric assays. The results revealed that CCT3 expression was significantly upregulated in CESC, which was associated with a poor prognosis. The silencing of CCT3 suppressed CESC cell proliferation, migration and invasiveness in vitro. Additionally, CCT3-knockdown promoted CESC cell apoptosis and cell cycle arrest, and suppressed fibronectin 1 (FN1) protein expression. Furthermore, rescue assays demonstrated that CCT3 promoted CESC proliferation and migration via FN1. In conclusion, the findings of the present study demonstrated that CCT3 is closely associated with the progression of CESC. Thus, CCT3 may be considered a novel, promising biomarker, and a possible therapeutic target for CESC.

Development and validation of a prognostic immune-associated gene signature in clear cell renal cell carcinoma

BACKGROUND

Recent studies have demonstrated that immune-associated genes (IAGs) play an important role in the occurrence and progression of clear renal clear cell carcinoma (ccRCC). Novel biomarkers and a reliable prognostic prediction model for ccRCC patients are still limited. The objective of this study was to develop a IAGs signature and validate its prognostic value in ccRCC using bioinformatic methods and publicly database.

METHODS

In the present study, we identified differentially expressed IAGs in ccRCC based on The Cancer Genome Atlas (TCGA) database. A prognostic IAGs risk model was further developed and its prognostic and predictive value was evaluated by survival analysis and nomogram.

RESULTS

A total of 681 differentially expressed IAGs were identified and seven IAGs (IFI30, WNT5A, IRF9, AGER, PLAUR, TEK, BID) were finally selected in a IAGs signature. Survival analysis revealed that high IAGs risk scores were significantly related to poor survival outcomes. The IAGs signature was demonstrated as an independent prognostic factor and closely related to the metastasis status of ccRCC. A nomogram with clinicopathologic characteristics and IAGs signature was also constructed to superiorly predict prognosis of ccRCC patients.

CONCLUSIONS

We identified seven IAGs as a potential signature for reflecting the prognosis of ccRCC based on TCGA database. Further clinical trials are needed to validate our observations and the mechanisms underlying the prognostic value of IAGs signature in ccRCC also deserve further experimental exploration.

Downregulation of microRNA-205 inhibits cell invasion and angiogenesis of cervical cancer through TSLC1-mediated Akt signaling pathway

Cervical cancer (CC) is a common gynecological cancer and a leading cause of cancer-related deaths in women globally. Therefore, this study explores the action of microRNA-205 (miR-205) in the invasion, migration, and angiogenesis of CC through binding to tumor suppressor lung cancer 1 (TSLC1). Initially, the microarray analysis was used to select the candidate gene and the regulatory microRNA. Then, the target relationship between miR-205 and TSLC1 as well as the expression of miR-205, TSLC1, and p-Akt/total Akt in CC cells were determined. Afterwards, CC cell invasion and migration were detected after the treatment of miR-205 mimics/inhibitors and short hairpin RNA against TSLC1. After coculture of cancer cells and vascular endothelial cells, cell proliferation, tube formation, and microvessel density (MVD) were detected to determine the roles of miR-205 in angiogenesis. Finally, tumor growth in nude mice was measured in vivo. TSLC1 was determined as the candidate gene, which was found to be targeted and negatively regulated by miR-205. Then, downregulated miR-205 or forced TSLC1 expression inhibited invasion, migration, and angiogenesis in CC, corresponding to suppressed cell proliferation, tube formation, and expression of IL-8, VEGF, and bFGF, as well as the inhibited activation of the Akt signaling pathway. Furthermore, downregulation of miR-205 was found to exert an inhibitory role in tumor formation and MVD by elevating TSLC1 in CC in vivo. This study demonstrated that downregulated miR-205 inhibited cell invasion, migration, and angiogenesis in CC by inactivating the Akt signaling pathway via TSLC1 upregulation.

MiR-155-5p accelerates the metastasis of cervical cancer cell via targeting TP53INP1

Background: The dysregulation of microRNAs has been implicated in the progression of different malignancies. Herein, we sought to identify the precise roles of miR-155-5p in the progression of cervical cancer.

Materials and methods: The expressions of miR-155-5p in cervical carcinoma cells and clinical tissues were assessed using qRT-PCR analysis. The functions of miR-155-5p on the growth of cervical cancer cell were investigated using MTT and colony formation. The Transwell and wound closure assays were selected to explore the influence of miR-155-5p on the invasion and migration of cervical cancer cell. The effect of miR-155-5p on cervical carcinoma cell growth and metastasis in vivo was investigated using xenograft model and experimental lung metastasis model. Bioinformatics analysis and luciferase reporter assay were applied to identify that tumor protein p53-inducible nuclear protein 1 (TP53INP1) was the target of miR-155-5p.

Results: MiR-155-5p was significantly upregulated in cervical cancer tissue than that in control normal tissue. Downexpression of miR-155-5p decreased the growth, migration as well as invasiveness abilities of cervical cancer cell in vitro whereas overregulation of miR-155-5p caused the opposite outcomes. In addition, the in vivo mice xenograft model suggested that downexpression of miR-155-5p restrained the progression of cervical cancer cell whereas overexpression of miR-155-5p caused opposite outcomes. Furthermore, we revealed that TP53INP1 was the target of miR-155-5p and the level of TP53INP1 was inversely associated with miR-155-5p level in cervical carcinoma. Furthermore, TP53INP1 knockdown mimicked the influence of miR-155-5p on cervical cancer proliferation, migration and invasion phenotypes. Finally, overexpression of TP53INP1 impaired the promote effect of miR-155-5p on cervical cancer cell and downregulation of TP53INP1 counteracted the suppressive impact of miR-155-5p on the aggressiveness of cervical cancer cell.

Conclusion: Our study indicated that miR-155-5p regulated the development of cervical cancer cell by regulating the expression of TP53INP1.

Cell migration on microposts with surface coating and confinement

Understanding cell migration in a 3D microenvironment is essential as most cells encounter complex 3D extracellular matrix (ECM) in vivo Although interactions between cells and ECM have been studied previously on 2D surfaces, cell migration studies in 3D environment are still limited. To investigate cell migration under various degrees of confinements and coating conditions, 3D platforms with micropost arrays and controlled fibronectin (FN) protein coating were developed. MC3T3-E1 cells spread and contacted the top surface of microposts if FN was coated on top. When FN was coated all over the microposts, cells were trapped between microposts with 3 μm spacing and barely moved. As the spacing between microposts increased from 3 to 5 μm, cells became elongated with limited cell movement of 0.18 μm/min, slower than the cell migration speed of 0.40 μm/min when cells moved on top. When cells were trapped in between the microposts, cell nuclei were distorted and actin filaments formed along the sidewalls of microposts. With the addition of a top cover to introduce cell confinement, the cell migration speed was 0.23 and 0.84 μm/min when the channel height was reduced from 20 to 10 μm, respectively. Cell traction force was monitored at on the top and bottom microposts with 10 μm channel height. These results show that the MC3T3-E1 cell morphology, migration speed, and movement position were affected by surface coating and physical confinement, which will provide significant insights for in vivo cell migration within a 3D ECM.

Identification of differentially expressed genes and enriched pathways in lung cancer using bioinformatics analysis

Lung cancer is the leading cause of cancer‑associated mortality worldwide. The aim of the present study was to identify the differentially expressed genes (DEGs) and enriched pathways in lung cancer by bioinformatics analysis, and to provide potential targets for diagnosis and treatment. Valid microarray data of 31 pairs of lung cancer tissues and matched normal samples (GSE19804) were obtained from the Gene Expression Omnibus database. Significance analysis of the gene expression profile was used to identify DEGs between cancer tissues and normal tissues, and a total of 1,970 DEGs, which were significantly enriched in biological processes, were screened. Through the Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, 77 KEGG pathways associated with lung cancer were identified, among which the Toll‑like receptor pathway was observed to be important. Protein‑protein interaction network analysis extracted 1,770 nodes and 10,667 edges, and identified 10 genes with key roles in lung cancer with highest degrees, hub centrality and betweenness. Additionally, the module analysis of protein‑protein interactions revealed that 'chemokine signaling pathway', 'cell cycle' and 'pathways in cancer' had a close association with lung cancer. In conclusion, the identified DEGs, particularly the hub genes, strengthen the understanding of the development and progression of lung cancer, and certain genes (including advanced glycosylation end‑product specific receptor and epidermal growth factor receptor) may be used as candidate target molecules to diagnose, monitor and treat lung cancer.