HN1 as a diagnostic and prognostic biomarker for liver cancer

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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ARID1A Upregulation Predicts Poor Survival in Patients with Liver Cancer

10.21203/rs.3.rs-166724/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 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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Clinical Value of lncRNA LUCAT1 Expression in Liver Cancer and its Potential Pathways

Journal of Gastrointestinal and Liver Diseases ◽

10.15403/jgld-356 ◽

2019 ◽

Vol 28 (4) ◽

pp. 439-447 ◽

Cited By ~ 7

Author(s):

Yan Jiao ◽

Yanqing Li ◽

Bai Ji ◽

Hongqiao Cai ◽

Yahui Liu

Keyword(s):

Liver Cancer ◽

Roc Curve ◽

Cox Regression ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cancer Prognosis ◽

Rank Test ◽

P Value ◽

Rna Seq ◽

Cox Regression Analysis

Background and Aims: Emerging studies indicate that long noncoding RNAs (lncRNAs) play a role as prognostic markers in many cancers, including liver cancer. Here, we focused on the lncRNA lung cancer-associated transcript 1 (LUCAT1) for liver cancer prognosis. Methods: RNA-seq and phenotype data were downloaded from the Cancer Genome Atlas (TCGA). Chisquare tests were used to evaluate the correlations between LUCAT1 expression and clinical features. Survival analysis and Cox regression analysis were used to compare different LUCAT1 expression groups (optimal cutoff value determined by ROC). The log-rank test was used to calculate the p-value of the Kaplan-Meier curves. A ROC curve was used to evaluate the diagnostic value. Gene Set Enrichment Analysis (GSEA) was performed, and competing endogenous RNA (ceRNA) networks were constructed to explore the potential mechanism. Results: Data mining of the TCGA -Liver Hepatocellular Carcinoma (LIHC) RNA-seq data of 371 patients showed the overexpression of LUCAT1 in cancerous tissue. High LUCAT1 expression was associated with age (p=0.007), histologic grade (p=0.009), T classification (p=0.022), and survival status (p=0.002). High LUCAT1 patients had a poorer overall survival and relapse-free survival than low LUCAT1 patients. Multivariate analysis identified LUCAT1 as an independent risk factor for poor survival. The ROC curve indicated modest diagnostic performance. GSEA revealed the related signaling pathways, and the ceRNA network uncovered the underlying mechanism. Conclusion: High LUCAT1 expression is an independent prognostic factor for liver cancer.

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Clinical characteristics and prognostic value of MEX3A mRNA in liver cancer

PeerJ ◽

10.7717/peerj.8252 ◽

2020 ◽

Vol 8 ◽

pp. e8252 ◽

Cited By ~ 5

Author(s):

Dingquan Yang ◽

Yan Jiao ◽

Yanqing Li ◽

Xuedong Fang

Keyword(s):

Liver Cancer ◽

Clinical Data ◽

Rna Binding ◽

Rna Binding Proteins ◽

Prognostic Significance ◽

The Cancer Genome Atlas ◽

Rna Seq ◽

Diagnostic Ability ◽

Kaplan Meier ◽

Cox Analysis

Background MEX3A is an RNA-binding proteins (RBPs) that promotes the proliferation, invasion, migration and viability of cancer cells. The aim of this study was to explore the clinicopathological characteristics and prognostic significance of MEX3A mRNA expression in liver cancer. Methods RNA-Seq and clinical data were collected from The Cancer Genome Atlas (TCGA). Boxplots were used to represent discrete variables of MEX3A. Chi-square tests were used to analyze the correlation between clinical features and MEX3A expression. Receiver operating characteristic (ROC) curves were used to confirm diagnostic ability. Independent prognostic ability and values were assessed using Kaplan–Meier curves and Cox analysis. Results We acquired MEX3A RNA-Seq from 50 normal liver tissues and 373 liver cancer patients along with clinical data. We found that MEX3A was up-regulated in liver cancer which increased according to histological grade (p < 0.001). MEX3A showed moderate diagnostic ability for liver cancer (AUC = 0.837). Kaplan–Meier curves and Cox analysis revealed that the high expression of MEX3A was significantly associated with poor survival (OS and RFS) (p < 0.001). Moreover, MEX3A was identified as an independent prognostic factor of liver cancer (p < 0.001). Conclusions MEX3A expression shows promise as an independent predictor of liver cancer prognosis.

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A Comprehensive Prognostic and Immune Analysis of SLC41A3 in Pan-Cancer

Frontiers in Oncology ◽

10.3389/fonc.2020.586414 ◽

2021 ◽

Vol 10 ◽

Author(s):

Jun Liu ◽

Shanqiang Zhang ◽

Wenjie Dai ◽

Chongwei Xie ◽

Ji-Cheng Li

Keyword(s):

Overall Survival ◽

Immune Cells ◽

Cox Regression ◽

Expression Profiles ◽

Prognostic Significance ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Cancer Prognosis ◽

Cox Regression Analysis ◽

Pan Cancer

SLC41A3, as a member of the 41st family of solute carriers, participates in the transport of magnesium. The role of SLC41A3 in cancer prognosis and immune regulation has rarely been reported. This study was designed to analyze the expression status and prognostic significance of SLC41A3 in pan-cancers. The mRNA expression profiles of SLC41A3 were obtained from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx), the Broad Institute Cancer Cell Line Encyclopedia (CCLE), and the International Cancer Genome Consortium (ICGC). The Cox regression and Kaplan-Meier analyses were used to evaluate the prognostic value of SLC41A3 in pan-cancer. Furthermore, the correlation between SLC41A3 expression and immune cells infiltration, immune checkpoint, mismatch repair (MMR), DNA methyltransferase (DNMT), tumor mutation burden (TMB), and microsatellite instability (MSI) were calculated using data form TCGA database. The results showed that the expression of SLC41A3 was down-regulated in kidney renal clear cell carcinoma (KIRC), and was associated with poor overall survival and tumor-specific mortality. Whereas, the expression of SLC41A3 was up-regulated in liver hepatocellular carcinoma (LIHC), and the results of Cox regression analysis revealed that SLC41A3 was an independent factor for LIHC prognosis. Meanwhile, a nomogram including SLC41A3 and stage was built and exhibited good predictive power for the overall survival of LIHC patients. Additionally, correlation analysis suggested a significant correlation between SLC41A3 and TMB, MSI, MMR, DNMT, and immune cells infiltration in various cancers. The overall survival and disease-specific survival analysis revealed that the combined SLC41A3 expression and immune cell score, TMB, and MSI were significantly associated with clinical outcomes in ACC, LIHC, and UVM patients. Therefore, we proposed that SLC41A3 may serve as a potential prognostic biomarker for cancer.

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Low expression of CIP4 in predicting worse overall survival: A potential biomarker for laryngeal cancer

PLoS ONE ◽

10.1371/journal.pone.0253545 ◽

2021 ◽

Vol 16 (9) ◽

pp. e0253545

Author(s):

Lucheng Fang ◽

Licai Shi ◽

Wen Wang ◽

Xiu Wu ◽

Tingting Hu ◽

...

Keyword(s):

Overall Survival ◽

Wnt Signaling ◽

Signaling Pathways ◽

Laryngeal Cancer ◽

Cox Regression ◽

Univariate Analysis ◽

Gene Set Enrichment Analysis ◽

Kaplan Meier ◽

Potential Biomarker ◽

The Relationship

Previous reports indicate that Cdc42-interacting protein-4 (CIP4) has previously been reported to plays an important role in the progression of various cancers. However, its correlation with laryngeal cancer (LC) remains unreported. Data from TCGA and GEO databases were used to evaluate the role of CIP4 in LC. Based on GEO and TCGA datasets, we analyzed the differences in CIP4 expression between normal and tumor samples. The Wilcoxon signed-rank test was used to analyze the relationship between clinical features and CIP4. Cox regression and the Kaplan-Meier analyses were used to identify the clinical characteristics associated with the overall survival. Also, the GEPIA database was used to confirm the relationship between CIP4 and overall survival. Lastly, Gene Set Enrichment Analysis (GSEA) was performed based on the TCGA dataset. CIP4 expression in LC was significantly associated with gender and tumor stage (p-values<0.05). Similar to GEPIA validation, Kaplan-Meier survival analysis demonstrated that LC with CIP4-low exhibited a worse prognosis than that with CIP4-high. Univariate analysis revealed that CIP4-high significantly correlated with better overall survival (HR: 0.522, 95% CI: 0.293–0.830, P = 0.026). Besides, multivariate analysis revealed that CIP4 remained independently associated with the overall survival (HR: 0.61, 95% CI: 0.326–0.912, P = 0.012). GSEA showed that the p53, WNT signaling, TGF-β signaling pathways, etc. were enriched in a phenotype high CIP4 expression. In summary, the CIP4 gene is a potential prognostic molecular marker for patients diagnosed with laryngeal cancer. Moreover, the p53, WNT signaling, and TGF-β signaling pathways are potentially associated with CIP4 in LC.

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Overexpression of HOXA10 is associated with unfavorable prognosis of acute myeloid leukemia

10.21203/rs.3.rs-16941/v1 ◽

2020 ◽

Author(s):

Chao Guo ◽

Qian-qian Ju ◽

Chun-xia Zhang ◽

Ming Gong ◽

Zhen-ling Li ◽

...

Keyword(s):

Cox Regression ◽

Cox Model ◽

Prognostic Significance ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Risk Scores ◽

High Group ◽

Cox Regression Analysis ◽

Kaplan Meier ◽

The Impact

Abstract Background HOXA family genes were crucial transcription factors involving cell proliferation and apoptosis. While few studies have focused on HOXA10 in AML. We aimed to investigate the prognostic significance of HOXA10. Methods We downloaded datasets from GEO and BeatAML database, to compare HOXA expression level between AML patients and controls. Kaplan-Meier curves were used to estimate the impact of HOXA10 expression on AML survival. The differentially expressed genes, miRNAs, lncRNAs and methylated regions between HOXA10-high and -low groups were obtained using R (version 3.6.0). Accordingly, the gene set enrichment analysis (GSEA) was accomplished using MSigDB database. Moreover, the regulatory TFs/microRNAs/lncRNAs of HOXA10 were identified. A LASSO-Cox model fitted OS to clinical and HOXA10-associated genetic variables by glmnet package. Results HOXA10 was overexpressed in AML patients than that in controls. The HOXA10-high group is significantly associated with shorter OS and DFS. A total of 1219 DEGs, 131 DEmiRs, 282 DElncRs were identified to be associated with HOXA10. GSEA revealed that 12 suppressed and 3 activated pathways in HOXA10-high group. Furthermore, the integrated regulatory network targeting HOXA10 was established. The LASSO-Cox model fitted OS to AML-survival risk scores, which included age, race, molecular risk, expression of IKZF2/LINC00649/LINC00839/FENDRR and has-miR-424-5p. The time dependent ROC indicated a satisfying AUC (1-year AUC 0.839, 3-year AUC 0.871 and 5-year AUC 0.813). Conclusions Our study identified HOXA10 overexpression as an adverse prognostic factor for AML. The LASSO-COX regression analysis revealed novel prediction model of OS with superior diagnostic utility.

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The overexpression of FKBP4 in patients with lung adenocarcinoma predicts poor prognosis and tumor progression

10.21203/rs.3.rs-733351/v1 ◽

2021 ◽

Author(s):

Sha Tian ◽

Shang qing Wang ◽

Piao Zheng ◽

Xu Zhu ◽

Huan Han ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Signaling Pathways ◽

Cancer Progression ◽

Poor Prognosis ◽

Cox Regression ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Clinicopathological Parameters ◽

Poor Overall Survival ◽

Kaplan Meier

Abstract Background: The FK506-binding protein 4 ( FKBP4 ), a tumor-related gene, plays a vital role in tumorigenesis and cancer progression. The study is aimed to clarify the effect of FKBP4 in lung adenocarcinoma (LUAD). Methods: Relying on The Cancer Genome Atlas (TCGA) cohort, the FKBP4 expression difference between LUAD tissues and non-tumor tissues was first detected, and verified with public tissue microarrays (TMAs), clinical LUAD specimen cohort and Gene Expression Omnibus (GEO) cohort. Then, logistic regression analysis and chi-square test were applied to detect the correlation between FKBP4 expression and clinicopathological parameters. Kaplan-Meier survival analysis and Cox regression model were utilized to evaluate the effect of FKBP4 expression on survival. Signaling pathways related to LUAD were obtained via employing Gene Set Enrichment Analysis (GSEA). Results: The FKBP4 expression level in LUAD samples was dramatically higher than that in non-tumor samples. High FKBP4 expression in LUAD is associated with gender, pathological stage, T classification, lymph node metastasis and distant metastasis. The Kaplan-Meier curve indicated a poor prognosis for LUAD patients with high FKBP4 expression. Multivariate analysis suggested that the high FKBP4 expression was a vital independent predictor of poor overall survival (OS). GSEA showed that a total of 15 signaling pathways were enriched in samples with high FKBP4 expression phenotype. Conclusions: FKBP4 may be an oncogene in LUAD, and is promised to become a prognostic indicator and therapeutic target for LUAD.

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CCNA2 Expression and Its Prognostic Significance in cholangiocarcinoma

10.21203/rs.3.rs-111136/v1 ◽

2020 ◽

Author(s):

Jie Zhang ◽

Jingjun Zhang ◽

Hairong Liu ◽

Qinyang Chen ◽

Pengcheng Li ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

Signaling Pathways ◽

Expression Profiles ◽

Prognostic Significance ◽

Gene Set Enrichment Analysis ◽

Resected Specimen ◽

Ppi Network ◽

Kaplan Meier ◽

Geo Database

Abstract Background: Cholangiocarcinoma（CCA）is a rare malignancy and it has become a significant health burden worldwide. An increasing number of studies have demonstrated the crucial correlation of immunophenotypic characteristics modifications in resected specimen of CCA. However, the accurate prognostic markers is still lacking in the prognosis of CCA. Methods: Gene expression profiles and clinical data of CCA were downloaded from the Gene Expression Omnibus（GEO）database. GO and KEGG analysis were applied for differentially expressed genes in cholangiocarcinoma, and PPI network was constructed in Cytoscape software. The expression difference of Cyclin A2 (CCNA2) in CCA tissues and adjacent noncancerous tissues was analyzed by R software and verified by comprehensive analysis. The relationship between CCNA2 expression and immune infiltration was assessed in the the Cancer Genome Atlas (TCGA) database. Kaplan–Meier survival analysis were chosen to assess the effect of CCNA2 expression on survival. Gene set enrichment analysis (GSEA) was used to screen the signaling pathways involved in CCA between the low and the high CCNA2 expression group.Results: The expression of CCNA2 in CCA was significantly higher than that in adjacent cancerous tissues (P < 0.001) from the GEO database. The top 10 hub genes were mined by the Degree, MCC, and Closeness method based on the PPI network. CCNA2 was screened as the candidates to be further analyzed and validated. The Kaplan–Meier curves suggested that patients with high CCNA2 expression had a poor prognosis. Multivariate analysis showed that a high expression of CCNA2 was an important independent predictor of poor overall survival (P = 0.033). Cibersort analysis showed that the fraction of T cells CD4 (naive, P < 0.0001), T cells CD4 (memory, P = 0.0055), T cells (follicular, P = 0.0063), NK cells ( P = 0.0149), dendritic cells ( P = 0.029), neutrophils ( P = 0.0113) is significantly correlated with the expression of CCNA2, which highlighted the CCNA2 expression in immune infiltrates. GSEA indicated that 12 signaling pathways were evidently enriched in samples with the high-CCNA2 phenotype.Conclusions: CCNA2 might act as an oncogene in the progression of CCA and could be regarded as a potential prognostic indicator and therapeutic target for CCA.

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