Rac3 Expression and its Clinicopathological Significance in Patients With Bladder Cancer

Background: Ras-related C3 botulinum toxin substrate 3 (Rac3) is overexpressed in malignancies and promotes tumor progression. However, the correlations between Rac3 expression and the clinicopathological characteristics and prognoses of patients with bladder cancer (BC) remain unclear.Methods: Data from The Cancer Genome Atlas (TCGA) were used to analyze Rac3 expression in BC and normal bladder tissues and validated using the Oncomine database, quantitative real-time PCR (qRT-PCR) and western blot. The Kaplan-Meier method was used to analyze the relationship between Rac3 expression and the prognosis of patients with BC. Cox univariate and multivariate analyses of BC patients overall survival (OS) were performed. Signaling pathways that potentially mediate Rac3 activity in BC were then analyzed by gene set enrichment analysis (GSEA).Results: The Rac3 expression in BC tissues was significantly higher than that in normal bladder tissues. Rac3 expression was significantly correlated with grade and stage. Overexpression of Rac3 was associated with a poor prognosis. GSEA showed that the cell cycle, DNA replication, p53 signaling pathway and mismatch repair were differentially enriched in the high Rac3 expression phenotype. The qRT-PCR and western blot results confirmed that the Rac3 expression in BC tissues was higher than that in normal bladder tissues.Conclusion: Rac3 is highly expressed in BC, which is related to the advanced clinicopathological variables and adverse prognosis of patients with BC. These results provide a new therapeutic target for BC.

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Overexpression of SHMT2 Predicts a Poor Prognosis and Promotes Tumor Cell Growth in Bladder Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.682856 ◽

2021 ◽

Vol 12 ◽

Author(s):

Peng Zhang ◽

Qian Yang

Keyword(s):

Cell Cycle ◽

Cell Proliferation ◽

Bladder Cancer ◽

Disease Free Survival ◽

Enrichment Analysis ◽

Tumor Grade ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Normal Bladder

SHMT2 was overexpressed in many tumors, however, the role of SHMT2 in bladder cancer (BLCA) remains unclear. We first analyzed the expression pattern of SHMT2 in BLCA using the TNMplot, Oncomine, the Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO) databases. Next, the association between SHMT2 expression and overall survival (OS)/disease-free survival (DFS) in BLCA patients were analyzed using TCGA and PrognoScan database. The correlation between SHMT2 expression and clinicopathology was determined using TCGA database. Furthermore, the genes co-expressed with SHMT2 and their underlying molecular function in BLCA were explored based on the Oncomine database, Metascape and gene set enrichment analysis (GSEA). Finally, the effects of SHMT2 on cell proliferation, cell cycle, and apoptosis were assessed using in vitro experiments. As a results, SHMT2 was significantly overexpressed in BLCA tissues and cells compared to normal bladder tissues and cells. A high SHMT2 expression predicts a poor OS of BLCA patients. In addition, SHMT2 expression was higher in patients with a high tumor grade and in those who were older than 60 years. However, the expression of SHMT2 was not correlated with gender, tumor stage, lymph node stage, and distant metastasis stage. Finally, overexpression of SHMT2 promoted BLCA cell proliferation and suppressed apoptosis, the silencing of SHMT2 significantly inhibited BLCA cell proliferation by impairing the cell cycle, and promoting apoptosis. SHMT2 mediates BLCA cells growth by regulating STAT3 signaling. In summary, SHMT2 regulates the proliferation, cell cycle and apoptosis of BLCA cells, and may act as a candidate therapeutic target for BLCA.

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Identification and Validation of an 6-Metabolism-Related Gene Signature and Its Correlation With Immune Checkpoint in Hepatocellular Carcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.783934 ◽

2021 ◽

Vol 11 ◽

Author(s):

He Ren ◽

Wanjing Li ◽

Xin Liu ◽

Shuliang Li ◽

Hao Guo ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Checkpoint ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Signature ◽

Clinicopathological Characteristics ◽

Gene Set Enrichment Analysis ◽

Operating Characteristics ◽

Kaplan Meier ◽

Characteristics Analysis

Hepatocellular carcinoma (HCC) is a common malignant tumor with relatively high malignancy and rapid disease progression. Metabolism-related genes (MRGs) are involved in the pathogenesis of HCC. This study explored potential key MRGs and their effect on T-cell immune function in the tumor immune microenvironment to provide new insight for the treatment of HCC. Of 456 differentially expressed MRGs identified from TCGA database, 21 were screened by MCODE and cytoHubba algorithms. From the key module, GAD1, SPP1, WFS1, GOT2, EHHADH, and APOA1 were selected for validation. The six MRGs were closely correlated with survival outcomes and clinicopathological characteristics in HCC. Receiver operating characteristics analysis and Kaplan-Meier plots showed that these genes had good prognostic value for HCC. Gene set enrichment analysis of the six MRGs indicated that they were associated with HCC development. TIMER and GEPIA databases revealed that WFS1 was significantly positively correlated and EHHADH was negatively correlated with tumor immune cell infiltration and immune checkpoint expression. Finally, quantificational real-time polymerase chain reaction (qRT-PCR) confirmed the expression of WFS1 and EHHADH mRNA in our own patients’ cohort samples and four HCC cell lines. Collectively, the present study identified six potential MRG biomarkers associated with the prognosis and tumor immune infiltration of HCC, thus providing new insight into the pathogenesis and treatment of HCC.

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Identification of an IRGP Signature to Predict Prognosis and Immunotherapeutic Efficiency in Bladder Cancer

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.607090 ◽

2021 ◽

Vol 8 ◽

Author(s):

Liang-Hao Zhang ◽

Long-Qing Li ◽

Yong-Hao Zhan ◽

Zhao-Wei Zhu ◽

Xue-Pei Zhang

Keyword(s):

Bladder Cancer ◽

Stromal Cells ◽

Molecular Mechanisms ◽

Proportional Hazards ◽

Enrichment Analysis ◽

Cox Proportional Hazards ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Consensus Clustering ◽

Validation Set

BackgroundIdentify immune-related gene pairs (IRGPs) signature related to the prognosis and immunotherapeutic efficiency for bladder cancer (BLCA) patients.Materials and MethodsOne RNA-seq dataset (The Cancer Genome Atlas Program) and two microarray datasets (GSE13507 and GSE31684) were included in this study. We defined these cohorts as training set to construct IRGPs and one immunotherapy microarray dataset as validation set. Identifying BLCA subclasses based on IRGPs by consensus clustering. The Lasso penalized Cox proportional hazards regression model was used to construct prognostic signature and potential molecular mechanisms were analyzed.ResultsThis signature can accurately predict the overall survival of BLCA patients and was verified in the immunotherapy validation set. IRGP-signatures can be used as independent prognostic risk factor in various clinical subgroups. Use the CIBERSORT algorithm to assess the abundance of infiltrating immune cells in each sample, and combine the results of the gene set enrichment analysis of a single sample to explore the differences in the immune microenvironment between IRPG signature groups. According to the results of GSVA, GSEA, and CIBERSORT algorithm, we found that IRGP is strikingly positive correlated with tumor microenvironment (TME) stromal cells infiltration, indicating that the poor prognosis and immunotherapy might be caused partly by enrichment of stromal cells. Finally, the results from the TIDE analysis revealed that IRGP could efficiently predict the response of immunotherapy in BLCA.ConclusionThe novel IRGP signature has a significant prognostic value for BLCA patients might facilitate personalized for immunotherapy.

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Overexpression of CENPF correlates with poor prognosis and tumor bone metastasis in breast cancer

Cancer Cell International ◽

10.1186/s12935-019-0986-8 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 17

Author(s):

Jingbo Sun ◽

Jingzhan Huang ◽

Jin Lan ◽

Kun Zhou ◽

Yuan Gao ◽

...

Keyword(s):

Breast Cancer ◽

Bone Metastasis ◽

Western Blot ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Free Survival ◽

Gene Set ◽

Oncomine Database ◽

Kaplan Meier

Abstract Background Centromere Protein F (CENPF) associates with the centromere–kinetochore complex and influences cell proliferation and metastasis in several cancers. The role of CENPF in breast cancer (BC) bone metastasis remains unclear. Methods Using the ONCOMINE database, we compared the expression of CENPF in breast cancer and normal tissues. Findings were confirmed in 60 BC patients through immunohistochemical (IHC) staining. Microarray data from GEO and Kaplan–Meier plots were used analyze the overall survival (OS) and relapse free survival (RFS). Using the GEO databases, we compared the expression of CENPF in primary lesions, lung metastasis lesions and bone metastasis lesions, and validated our findings in BALB/C mouse 4T1 BC models. Based on gene set enrichment analysis (GSEA) and western blot, we predicted the mechanisms by which CENPF regulates BC bone metastasis. Results The ONCOMINE database and immunohistochemical (IHC) showed higher CENPF expression in BC tissue compared to normal tissue. Kaplan–Meier plots also revealed that high CENPF mRNA expression correlated to poor survival and shorter progression-free survival (RFS). From BALB/C mice 4T1 BC models and the GEO database, CENPF was overexpressed in primary lesions, other target organs, and in bone metastasis. Based on gene set enrichment analysis (GSEA) and western blot, we predicted that CENPF regulates the secretion of parathyroid hormone-related peptide (PTHrP) through its ability to activate PI3K–AKT–mTORC1. Conclusion CENPF promotes BC bone metastasis by activating PI3K–AKT–mTORC1 signaling and represents a novel therapeutic target for BC treatment.

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A Glycolysis-Based Long Non-coding RNA Signature Accurately Predicts Prognosis in Renal Carcinoma Patients

Frontiers in Genetics ◽

10.3389/fgene.2021.638980 ◽

2021 ◽

Vol 12 ◽

Author(s):

Honghao Cao ◽

Hang Tong ◽

Junlong Zhu ◽

Chenchen Xie ◽

Zijia Qin ◽

...

Keyword(s):

Clinical Significance ◽

Risk Score ◽

Cox Regression ◽

Risk Group ◽

Enrichment Analysis ◽

Roc Curves ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Survival Prediction ◽

Kaplan Meier

BackgroundThe prognosis of renal cell carcinoma (RCC) varies greatly among different risk groups, and the traditional indicators have limited effect in the identification of risk grade in patients with RCC. The purpose of our study is to explore a glycolysis-based long non-coding RNAs (lncRNAs) signature and verify its potential clinical significance in prognostic prediction of RCC patients.MethodsIn this study, RNA data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate cox regression displayed six significantly related lncRNAs (AC124854.1, AC078778.1, EMX2OS, DLGAP1-AS2, AC084876.1, and AC026401.3) which were utilized in construction of risk score by a formula. The accuracy of risk score was verified by a series of statistical methods such as receiver operating characteristic (ROC) curves, nomogram and Kaplan-Meier curves. Its potential clinical significance was excavated by gene enrichment analysis.ResultsKaplan-Meier curves and ROC curves showed reliability of the risk score to predict the prognosis of RCC patients. Stratification analysis indicated that the risk score was independent predictor compare to other traditional clinical parameters. The clinical nomogram showed highly rigorous with index of 0.73 and precisely predicted 1-, 3-, and 5-year survival time of RCC patients. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene set enrichment analysis (GSEA) depicted the top ten correlated pathways in both high-risk group and low-risk group. There are 6 lncRNAs and 25 related mRNAs including 36 lncRNA-mRNA links in lncRNA-mRNA co-expression network.ConclusionThis research demonstrated that glycolysis-based lncRNAs possessed an important value in survival prediction of RCC patients, which would be a potential target for future treatment.

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Mining the TCGA Database for Microenvironment‐Related Genes with Prognostic Value in Gastric Cancer

10.21203/rs.3.rs-175261/v1 ◽

2021 ◽

Author(s):

Ting Liu ◽

Zheng Gong ◽

Hong Zhang ◽

Yi Wan ◽

Ming-Han Ren ◽

...

Keyword(s):

Gastric Cancer ◽

Distant Metastasis ◽

Clinical Stage ◽

Enrichment Analysis ◽

Clinicopathological Characteristics ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Gene Set Enrichment ◽

Gene Set ◽

Protein Protein Interaction

Abstract BackgroundGastric cancer (GC) is the fifth most common cancer worldwide. Previous studies have suggested that the tumor microenvironment (TME) plays an important role in the development and prognosis of GC. In this study, we aimed to identify genes in tumor-infiltrating immune cells (TICs) that influence the progression and prognosis of GC. MethodsWe used the ESTIMATE algorithm to calculate the scores of the stromal and immune components of the TME in 407 GC samples collected from The Cancer Genome Atlas (TCGA) database.The differentially expressed genes (DEGs) were intersected by a protein-protein interaction (PPI) network and analyzed by univariate Cox regression.Further analysis showed the correlation between MCEMP1 and the clinicopathological characteristics of GC patients (clinical stage, distant metastasis) and survival.Then we used Gene set enrichment analysis (GSEA) and CIBERSORT analysis to examine the relationship between MCEMP1 and the TME.ResultsThe analysis revealed that the expression of MCEMP1 was positively correlated with the clinicopathological characteristics of GC patients (clinical stage, distant metastasis) and negatively correlated with survival. Gene set enrichment analysis (GSEA) indicated that gene sets in the MCEMP1 high expression group were concentrated mainly in immune-related pathways. CIBERSORT analysis of the proportion of TICs revealed that neutrophils and M2 macrophages were positively correlated with MCEMP1 expression, suggesting that MCEMP1 is responsible for preservation of the immune-dominant status of the TME. ConclusionHigh MCEMP1 expression might be a biomarker of a poor prognosis in GC patients and provide a clue regarding the different statuses of the TME, offering additional insight into therapy for GC.

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Identification of a FLG-wide-type bladder cancer subtype with poor prognosis and prediction use in immune checkpoint

10.21203/rs.3.rs-1014390/v1 ◽

2021 ◽

Author(s):

Liang Chen ◽

Liulin Xiong ◽

Weinan Chen ◽

Lizhe An ◽

Huanrui Wang ◽

...

Keyword(s):

Bladder Cancer ◽

Immune Checkpoint ◽

Poor Prognosis ◽

Expression Profiles ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Immune Biomarkers

Abstract Background Bladder cancer (BLCA) is one of most common urinary tract malignant tumor and immunotherapy have generated a great deal of interest in BLCA. Immune checkpoint blockade (ICB) therapy has significantly progressed the treatment of BLCA. Multiple studies have suggested that specific genetic mutations may serve as immune biomarkers for ICB therapy. Objective In this study, we aimed to investigate the role of mutations genes and subtypes in prognosis and immune checkpoint prediction in BLCA. Method Mutation information and expression profiles were acquired from The Cancer Genome Atlas (TCGA) database. Integrated bioinformatics analysis was carried out to explore the mutation genes of BLCA. Functional enrichment analysis Gene Ontology (GO) and Gene set enrichment analysis (GSEA) was conducted. The infiltrating immune cells and the prediction of ICB between different subtypes group were explored using immuCellAI algorithm. Results The mutation genes Filaggrin (FLG) gene were identified. Following the study on its subtypes and functional enrichment analysis, Sub2 of FLG-wide type was found to have relationships with poor prognosis and immune infiltration BLCA. What’s more, Sub2 of FLG-wide type may be used as a biomarker to predict the prognosis of BLCA patients receiving ICB. Conclusion This research provides a new basis and ideas for guiding the clinical application of BLCA immunotherapy.

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A glycolysis-based 4-mRNA signature correlates with the prognosis and cell cycle process in patients with bladder cancer

10.21203/rs.3.rs-19386/v2 ◽

2020 ◽

Author(s):

Chen Zhang ◽

Xin Gou ◽

Weiyang He ◽

Huaan Yang ◽

Hubin Yin

Keyword(s):

Cell Cycle ◽

Bladder Cancer ◽

Enrichment Analysis ◽

Risk Groups ◽

Gene Signature ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Related Gene ◽

Cancer Subtypes ◽

Cancer Tissues

Abstract Background: Bladder cancer is one of the most prevalent malignancies worldwide. However, traditional indicators have limited predictive effects on the clinical outcomes of bladder cancer. The aim of this study was to develop and validate a glycolysis-related gene signature for predicting the prognosis of patients with bladder cancer that have limited therapeutic options.Methods: mRNA expression profiling was obtained from patients with bladder cancer from The Cancer Genome Atlas (TCGA) database. Gene set enrichment analysis (GSEA) was conducted to identify glycolytic gene sets that were significantly different between bladder cancer tissues and paired normal tissues. A prognosis-related gene signature was constructed by univariate and multivariate Cox analysis. Kaplan-Meier curves and time-dependent receiver operating characteristic (ROC) curves were utilized to evaluate the signature. A nomogram combined with the gene signature and clinical parameters was constructed. Correlations between glycolysis-related gene signature and molecular characterization as well as cancer subtypes were analyzed. RT-qPCR was applied to analyze gene expression. Functional experiments were performed to determine the role of PKM2 in the proliferation of bladder cancer cells.Results: Using a Cox proportional regression model, we established that a 4-mRNA signature (NUP205, NUPL2, PFKFB1 and PKM) was significantly associated with prognosis in bladder cancer patients. Based on the signature, patients were split into high and low risk groups, with different prognostic outcomes. The gene signature was an independent prognostic indicator for overall survival. The ability of the 4-mRNA signature to make an accurate prognosis was tested in two other validation datasets. GSEA was performed to explore the 4-mRNA related canonical pathways and biological processes, such as the cell cycle, hypoxia, p53 pathway, and PI3K/AKT/mTOR pathway. A heatmap showing the correlation between risk score and cell cycle signature was generated. RT-qPCR revealed the genes that were differentially expressed between normal and cancer tissues. Experiments showed that PKM2 plays essential roles in cell proliferation and the cell cycle.Conclusion: The established 4‑mRNA signature may act as a promising model for generating accurate prognoses for patients with bladder cancer, but the specific biological mechanism needs further verification.

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NRAS Expression is Associated With Prognosis and Tumor Immune Microenvironment in Lung Adenocarcinoma

10.21203/rs.3.rs-862652/v1 ◽

2021 ◽

Author(s):

Yueren Yan ◽

Zhendong Gao ◽

Han Han ◽

Yue Zhao ◽

Yang Zhang ◽

...

Keyword(s):

T Cells ◽

Lung Adenocarcinoma ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Expression Level ◽

Immune Microenvironment ◽

Kaplan Meier ◽

Tumor Immune Microenvironment ◽

Cox Analysis

Abstract Purpose: NRAS plays a pivotal role in progression of various kinds of somatic malignancies; however, the correlation between NRAS and lung adenocarcinoma is less known. We aim to analyze the prognostic value of NRAS expression in lung adenocarcinoma, and explore the relationship between NRAS and tumor immune microenvironment. Methods: We obtained the transcriptome pofiles and clinical data of LUAD from The Cancer Genome Atlas database and three Genome Expression Omnibus datasets. Specimens from 325 patients with completely resected lung adenocarcinoma were collected for immunohistochemical assays of NRAS, PD-L1, PD-1 and TIM-3. Then we performed gene set enrichment analysis to investigate cancer-related and immune-related signaling pathways. TIMER algorithms were performed to evaluate tumor immune infiltrating cells and immune-related biomarkers.Results: Compared with adjacent non-tumor tissue, NRAS expression was significantly upregulated in LUAD tissue. NRAS expression was significantly correlated with more advanced stage and positive lymph nodes. Kaplan-Meier curves and Cox analysis suggested that high NRAS expression led to a poor prognosis, and could be an independent prognostic factor in LUAD patients. Besides, NRAS expression was positively correlated with CD8+ T cells, macrophages, and neutrophils, and negatively correlated with B cells and CD4+ T cells. The expression level of NRAS was positively correlated with PD-L1, PD-1, and TIM-3 both at RNA and protein level. Conclusions: To conclude, we found NRAS a novel prognostic biomarker in LUAD. Besides, the expression level of NRAS may influence the prognosis of LUAD via various kinds of cancer-related pathways and remodeling TIM.

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Immunoglobulin superfamily member 10 is a novel prognostic biomarker for breast cancer

PeerJ ◽

10.7717/peerj.10128 ◽

2020 ◽

Vol 8 ◽

pp. e10128

Author(s):

Mengxue Wang ◽

Meng Dai ◽

Yu-shen Wu ◽

Ziying Yi ◽

Yunhai Li ◽

...

Keyword(s):

Breast Cancer ◽

Quantitative Polymerase Chain Reaction ◽

Enrichment Analysis ◽

Clinical Information ◽

Tumor Stage ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Immunoglobulin Superfamily ◽

Qrt Pcr ◽

Mtorc1 Signaling

Background Immunoglobulin superfamily member 10 (IGSF10) is a member of the immunoglobulin superfamily that is expressed at high levels in both the gallbladder and ovary. Currently, the role and possible mechanism of IGSF10 in breast cancer remain unclear. Method By applying real-time quantitative polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC), the expression of IGSF10 in breast cancer cells and tissues was detected. We collected the clinical information from 700 patients with breast cancer in The Cancer Genome Atlas (TCGA), and analyzed the relationship between IGSF10 expression and the clinicopathological features and survival outcomes of these patients. The potential mechanisms and pathways associated with IGSF10 in breast cancer were explored by performing a gene set enrichment analysis (GSEA). Results According to TCGA data, qRT-PCR and IHC experiments, levels of the IGSF10 mRNA and protein were significantly decreased in breast cancer tissues. IGSF10 expression was significantly correlated with age, tumor size, and tumor stage. Moreover, shorter overall survival (OS) and relapse-free survival (RFS) correlated with lower IGSF10 expression, according to the survival analysis. The multivariate analysis identified that IGSF10 as an independent prognostic factor for the OS (hazard ratio (HR) = 1.793, 95% confidence interval (CI) [1.141–2.815], P = 0.011) and RFS (HR = 2.298, 95% CI [1.317–4.010], P = 0.003) of patients with breast cancer. Based on the GSEA, IGSF10 was involved in DNA repair, cell cycle, and glycolysis. IGSF10 was also associated with the PI3K/Akt/mTOR and mTORC1 signaling pathways. Conclusions This study revealed a clear relationship between IGSF10 expression and the tumorigenesis of breast cancer for the first time. Therefore, further studies are needed to understand the mechanism of IGSF10 in breast cancer.

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