ARID1A Upregulation Predicts Poor Survival in Patients with Liver Cancer

Abstract Objective: ARID1A has been identified as a possible biomarker for certain cancers. There is, however, some debate regarding its function in liver cancer. Methods: Associations between clinical variables and ARID1A were evaluated. Cox and Kaplan – Meier analysis were used to examine clinicalopathological factors linked to overall survival of patients with liver cancer. Gene Set Enrichment Analysis (GSEA) was conducted using the dataset of the Cancer Genome Atlas. Results: High expression of ARID1A was correlated with the gender and tumor topography (T) diagnosis of liver cancer. Patients with elevated ARID1A expression had poorer prognosis than those with low ARID1A expression. The study also showed that ARID1A was an independent risk factor for overall survival. GSEA established pathways involved in ERBB signaling, cancer, insulin signaling, mTOR signaling, MAPK signaling, VEGF signaling, Ubiquitin signaling, and Wnt signaling as differentially enriched in ARID1A-high expression liver cancer. Conclusion: ARID1A has been shown to be expressed at high rates of liver cancer and to represent a possible independent molecular marker for diagnosis and prognosis of liver cancer.

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ARID1A Upregulation Predicts Poor Survival in Patients With Liver Cancer

10.21203/rs.3.rs-146505/v1 ◽

2021 ◽

Author(s):

Feng Jiang ◽

Ke Wei ◽

Ming Wang ◽

Chuyan Wu

Keyword(s):

Overall Survival ◽

Liver Cancer ◽

Enrichment Analysis ◽

Mapk Signaling ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

High Expression ◽

Diagnosis And Prognosis ◽

Kaplan Meier ◽

Erbb Signaling

Abstract Objective: ARID1A has been identified as a possible biomarker for certain cancers. There is, however, some debate regarding its function in liver cancer. Methods: Associations between clinical variables and ARID1A were evaluated. Cox and Kaplan – Meier analysis were used to examine clinical pathological factors linked to overall survival of patients with liver cancer. Gene set enrichment analysis (GSEA) was conducted using the dataset of the cancer genome atlas(TCGA). Results: High expression of ARID1A was correlated with the gender and tumor topography (T) diagnosis of liver cancer. Patients with elevated ARID1A expression had poorer prognosis than those with low ARID1A expression. The study also showed that ARID1A was an independent risk factor for overall survival. GSEA established pathways involved in ERBB signaling, cancer, insulin signaling, mTOR signaling, MAPK signaling, VEGF signaling, Ubiquitin signaling, and Wnt signaling as differentially enriched in ARID1A-high expression liver cancer. Conclusion: ARID1A has been shown to be expressed at high rates of liver cancer and to represent a possible independent molecular marker for diagnosis and prognosis of liver cancer.

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High expression of PIMREG predicts poor survival outcomes and is correlated with immune infiltrates in lung adenocarcinoma

PeerJ ◽

10.7717/peerj.11697 ◽

2021 ◽

Vol 9 ◽

pp. e11697

Author(s):

Feng Jiang ◽

Min Liang ◽

Xiaolu Huang ◽

Wenjing Shi ◽

Yumin Wang

Keyword(s):

Prognostic Value ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

High Expression ◽

Gene Set Enrichment ◽

Gene Set ◽

Kaplan Meier ◽

Cancer Genome Atlas

Background PIMREG is upregulated in multiple cancer types. However, the potential role of PIMREG in lung adenocarcinoma (LUAD) remains unclear. The present study aimed to explore its clinical significance in LUAD. Methods Using the Cancer Genome Atlas (TCGA) databases, we obtained 513 samples of LUAD and 59 normal samples from the Cancer Genome Atlas (TCGA) databases to analyze the relationship between PIMREG and LUAD. We used t and Chi-square tests to evaluate the level of expression of PIMREG and its clinical implication in LUAD. The prognostic value of PIMREG in LUAD was identified through the Kaplan–Meier method, Cox regression analysis, and nomogram. Gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were performed to screen biological pathways and analyze the correlation of the immune infiltrating level with the expression of PIMREG in LUAD. Results PIMREG was highly expressed in patients with LUAD. Specifically, the level of PIMREG gradually increased from pathological stage I to IV. Further, we validated the higher expression of PIMREG expressed in LUAD cell lines. Moreover, PIMREG had a high diagnostic value, with an -AUC of 0.955. Kaplan–Meier survival and Cox regression analyses revealed that the high expression of PIMREG was independently associated with poor clinical outcomes. In our prognostic nomogram, the expression of PIMREG implied a significant prognostic value. Gene set enrichment analysis (GSEA) identified that the high expression PIMREG phenotype was involved in the mitotic cell cycle, mRNA splicing, DNA repair, Rho GTPase signaling, TP53 transcriptional regulation, and translation pathways. Next, we also explored the correlation of PIMREG and tumor-immune interactions and found a negative correlation between PIMREG and the immune infiltrating level of T cells, macrophages, B cells, dendritic cells (DCs) , and CD8+ T cells in LUAD. Conclusions High levels of PIMREG correlated with poor prognosis and immune infiltrates in LUAD.

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HN1 as a diagnostic and prognostic biomarker for liver cancer

Bioscience Reports ◽

10.1042/bsr20200316 ◽

2020 ◽

Vol 40 (7) ◽

Author(s):

Zhicheng Liu ◽

Dingquan Yang ◽

Yanqing Li ◽

Yan Jiao ◽

Guangchao Lv

Keyword(s):

Overall Survival ◽

Liver Cancer ◽

Signaling Pathways ◽

Cox Model ◽

Prognostic Significance ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cancer Prognosis ◽

Kaplan Meier ◽

Specificity And Sensitivity

Abstract Background: The present study aimed to examine the diagnostic and prognostic value of HN1 in terms of overall survival (OS) and recurrence-free survival (RFS) in liver cancer and its potential regulatory signaling pathway. Methods: We obtained clinical data and HN1 RNA-seq expression data of liver cancer patients from The Cancer Genome Atlas database, and analyzed the differences and clinical association of HN1 expression in different clinical features. We uesd receiver-operating characteristic curve to evaluate the diagnosis capability of HN1. We analyzed and evaluated the prognostic significance of HN1 by Kaplan–Meier curves and Cox analysis. Gene Set Enrichment Analysis (GSEA) was used to identify signaling pathways related to HN1 expression. Results: HN1 mRNA was up-regulated in liver cancer, and was associated with age, histologic grade, stage, T classification, M classification, and vital status. HN1 mRNA had ideal specificity and sensitivity for the diagnosis (AUC = 0.855). Besides, the analysis of Kaplan–Meier curves and Cox model showed that HN1 mRNA was strongly associated with the overall survival and could be well-predicted liver cancer prognosis, as an independent prognostic variable. GSEA analysis identified three signaling pathways that were enriched in the presence of high HN1 expression. Conclusion: HN1 serves as a biomarker of diagnosis and prognosis in liver cancer.

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APLN: A potential novel biomarker for cervical cancer

Science Progress ◽

10.1177/00368504211011341 ◽

2021 ◽

Vol 104 (2) ◽

pp. 003685042110113

Author(s):

Yusha Chen ◽

Xiaoqian Lin ◽

Jinwen Zheng ◽

Jiancui Chen ◽

Huifeng Xue ◽

...

Keyword(s):

Cervical Cancer ◽

Cox Regression ◽

Clinical Stage ◽

Mapk Signaling ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

High Expression ◽

Receptor Interaction ◽

Primary Therapy ◽

Advanced Clinical Stage

Apelin (APLN) is recently demonstrated a direct association with many malignant diseases. However, its effects on cervical cancer remain unclear. This study therefore aims to evaluate the association between APLN expression and cervical cancer using publicly available data from The Cancer Genome Atlas (TCGA). The Pearson χ2 test and Fish exact test, as well as logistic regression, were used to evaluate the relationship between clinicopathological factors in cervical cancer and the expression of APLN. Additionally, the Cox regression and Kaplan-Meier methods were conducted to analyze the Overall Survival (OS) of cervical cancer patients in TCGA. Finally, gene set enrichment analysis (GSEA) was performed to establish its biological functions. High expression of APLN in cervical cancer was significantly associated with a more advanced clinical stage (OR = 1.91 (1.21–3.05) for Stage II, Stage III, and Stage IV vs Stage I, p = 0.006). Additionally, it was associated with poor outcome after primary therapy (OR = 2.14 (1.03–4.59) for Progressive Disease (PD), Stable Disease (SD), and Partial Response (PR) vs Complete Remission (CR), p = 0.045) and high histologic grade (OR = 1.67 (1.03–2.72) for G3 and G4 vs G1 and G2, p = 0.037). Moreover, multivariate analysis showed that high expression of APLN was associated with a shorter OS. GSEA demonstrated that six KEGG pathways, including PPAR signaling, ECM-receptor interaction, focal adhesion, MAPK signaling, TGF-beta signaling, and Gap junction pathways were differentially enriched in the high expression APLN phenotype. The recent study suggests that APLN plays an important role in the progression of cervical cancer and might be a promising prognostic biomarker of the disease.

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An angiogenesis-related long noncoding RNA signature correlates with prognosis in patients with hepatocellular carcinoma

Bioscience Reports ◽

10.1042/bsr20204442 ◽

2021 ◽

Vol 41 (4) ◽

Author(s):

Dengliang Lei ◽

Yue Chen ◽

Yang Zhou ◽

Gangli Hu ◽

Fang Luo

Keyword(s):

Hepatocellular Carcinoma ◽

Liver Cancer ◽

Long Noncoding Rna ◽

Noncoding Rna ◽

Enrichment Analysis ◽

Clinical Information ◽

Roc Curves ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Highly Correlated

Abstract Hepatocellular carcinoma (HCC) is one of the most prevalent and lethal cancers worldwide. Neovascularization is closely related to the malignancy of tumors. We constructed a signature of angiogenesis-related long noncoding RNA (lncRNA) to predict the prognosis of patients with HCC. The lncRNA expression matrix of 424 HCC patients was downloaded from The Cancer Genome Atlas (TCGA). First, gene set enrichment analysis (GSEA) was used to distinguish the differentially expressed genes of the angiogenesis genes in liver cancer and adjacent tissues. Next, a signature of angiogenesis-related lncRNAs was constructed using univariate and multivariate analyses, and receiver operating characteristic (ROC) curves were used to assess the accuracy. The signature and relevant clinical information were used to construct the nomogram. A 5-lncRNA signature was highly correlated with overall survival (OS) in HCC patients and performed well in evaluations using the C-index, areas under the curve, and calibration curves. In summary, the 5-lncRNA model can serve as an accurate signature to predict the prognosis of patients with liver cancer, but its mechanism of action must be further elucidated by experiments.

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Construction of a CXC Chemokine-Based Prediction Model for the Prognosis of Colon Cancer

BioMed Research International ◽

10.1155/2020/6107865 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Kaisheng Liu ◽

Minshan Lai ◽

Shaoxiang Wang ◽

Kai Zheng ◽

Shouxia Xie ◽

...

Keyword(s):

Gene Expression ◽

Colon Cancer ◽

Overall Survival ◽

Prediction Model ◽

Enrichment Analysis ◽

Forecast Model ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Characteristic Analysis ◽

Incidence And Mortality

Colon cancer is the third most common cancer, with a high incidence and mortality. Construction of a specific and sensitive prediction model for prognosis is urgently needed. In this study, profiles of patients with colon cancer with clinical and gene expression data were downloaded from Gene Expression Omnibus and The Cancer Genome Atlas (TCGA). CXC chemokines in patients with colon cancer were investigated by differential expression gene analysis, overall survival analysis, receiver operating characteristic analysis, gene set enrichment analysis (GSEA), and weighted gene coexpression network analysis. CXCL1, CXCL2, CXCL3, and CXCL11 were upregulated in patients with colon cancer and significantly correlated with prognosis. The area under curve (AUC) of the multigene forecast model of CXCL1, CXCL11, CXCL2, and CXCL3 was 0.705 in the GSE41258 dataset and 0.624 in TCGA. The prediction model was constructed using the risk score of the multigene model and three clinicopathological risk factors and exhibited 92.6% and 91.8% accuracy in predicting 3-year and 5-year overall survival of patients with colon cancer, respectively. In addition, by GSEA, expression of CXCL1, CXCL11, CXCL2, and CXCL3 was correlated with several signaling pathways, including NOD-like receptor, oxidative phosphorylation, mTORC1, interferon-gamma response, and IL6/JAK/STAT3 pathways. Patients with colon cancer will benefit from this prediction model for prognosis, and this will pave the way to improve the survival rate and optimize treatment for colon cancer.

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The increasing expression of GPX7 related to the malignant clinical features leading to poor prognosis of glioma patients

Chinese Neurosurgical Journal ◽

10.1186/s41016-021-00235-3 ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Jiawei Yao ◽

Xin Chen ◽

Zhendong Liu ◽

Ruotian Zhang ◽

Cheng Zhang ◽

...

Keyword(s):

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Multidimensional Data ◽

Normal Brain ◽

Cox Regression Analysis ◽

Diagnosis And Prognosis ◽

Kaplan Meier ◽

Potential Biomarker ◽

Therapy Target

Abstract Background Glioma is the most common malignant brain tumor in adults. The standard treatment scheme of glioma is surgical resection combined alternative radio- and chemotherapy. However, the outcome of glioma patients was unsatisfied. Here, we aimed to explore the molecular and biological function characteristics of GPX7 in glioma. Methods The multidimensional data of glioma samples were downloaded from Chinese Glioma Genome Atlas (CGGA). RT-qPCR method was used to identify the expression status of GPX7. Kaplan–Meier curves and Cox regression analysis were used to explore the prognostic value of GPX7. Gene Set Enrichment Analysis (GSEA) was applied to investigate the GPX7-related functions in glioma. Results The results indicated that the expression of GPX7 in glioma was higher compared to that in normal brain tissue. Univariate and multivariate Cox regression analyses confirmed that the expression value of GPX7 was an independent prognostic factor in glioma. The GSEA analysis showed that GPX7 was significantly enriched in the cell cycle pathway, ECM pathway, focal adhesion pathway, and toll-like receptor pathway. Conclusions The GPX7 was recommended as an independent risk factor for patients diagnosed with glioma for the first time and GPX7 could be potentially used as the therapy target in future. Furthermore, we attempted to explore a potential biomarker for improving the diagnosis and prognosis of patients with glioma.

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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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Rac3 Expression and its Clinicopathological Significance in Patients With Bladder Cancer

Pathology & Oncology Research ◽

10.3389/pore.2021.598460 ◽

2021 ◽

Vol 27 ◽

Author(s):

Mei Chen ◽

Zhenyu Nie ◽

Hui Cao ◽

Yuanhui Gao ◽

Xiaohong Wen ◽

...

Keyword(s):

Bladder Cancer ◽

Western Blot ◽

Enrichment Analysis ◽

Clinicopathological Characteristics ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Qrt Pcr ◽

P53 Signaling ◽

Kaplan Meier ◽

Normal Bladder

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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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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