scholarly journals High expression of oncogene cadherin-6 correlates with tumor progression and a poor prognosis in gastric cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zongxian Zhao ◽  
Shuliang Li ◽  
Shilong Li ◽  
Jun Wang ◽  
Hai Lin ◽  
...  

Abstract Background Gastric cancer (GC) is one of the most common and fatal cancers worldwide. Effective biomarkers to aid the early diagnosis of GC, as well as predict the course of disease, are urgently needed. Hence, we explored the role and function of cadherin-6 (CDH6) in the diagnosis and prognosis of gastric cancer. Methods The expression levels of CDH6 in cancerous and normal gastric tissue were analyzed using multiple public databases. Gene set enrichment analysis (GSEA) was performed using The Cancer Genome Atlas (TCGA) dataset. The diagnostic efficiency of CDH6 expression in GC patients was determined through receiver operating characteristic (ROC) curve analysis. The associations between clinical variables and CDH6 expression were evaluated statistically, and the prognostic factors for overall survival were analyzed by univariate and multivariate Cox regression. 44 GC tissue samples, 20 donor-matched adjacent normal tissue samples, and associated detailed clinical information, were collected from the Tianjin Medical University General Hospital. CDH6 expression levels were determined for further validation. Results CDH6 was upregulated in GC samples compared to normal gastric tissue. Furthermore, GSEA identified the tricarboxylic acid (TCA) cycle, extracellular matrix (ECM) receptor interaction, glyoxylate and dicarboxylate metabolism, oxidative phosphorylation, and the pentose phosphate pathway as differentially enriched in GC tissue samples. According to the area under the ROC curve (AUC) values (AUC = 0.829 in the TCGA and 0.966 in the GSE54129 dataset), CDH6 expression was associated with high diagnostic efficacy. Patients with high CDH6 levels in their GC tissues had a higher T number (according to the TNM classification) and a worse prognosis than those with low CDH6 expression. Univariate and multivariate Cox regression analysis showed that CDH6 was an independent risk factor for overall survival (univariate: HR = 1.305, P = 0.002, multivariate: HR = 1.481, P < 0.001). Conclusion CDH6 was upregulated in GC, and high CDH6 expression was indicative of a higher T number and a worse prognosis. Therefore, CDH6 represents a potentially independent molecular biomarker for the diagnostic and prognostic prediction of GC.

2021 ◽  
Author(s):  
Zongxian Zhao ◽  
Shuliang Li ◽  
Shilong Li ◽  
Jun Wang ◽  
Hai Lin ◽  
...  

Abstract BackgroundGastric cancer (GC) is one of the most common and fatal cancers worldwide and effective biomarkers aids in GC management and prognosis. Hence, we explored the role and function of cadherin 6 (CDH6) in diagnosis and prognosis of gastric cancer. MethodsThe expression level of CDH6 in GC tissue and normal gastric tissue were analyzed using multiple public databases. Gene set enrichment analysis (GSEA) was performed using The Cancer Genome Atlas dataset (TCGA). The diagnostic efficiency of CDH6 expression in GC patients was determined through receiver operating characteristic (ROC) curve analysis. The associations between clinical variables and expression of CDH6 were evaluated statistically and the prognostic factors for overall survival were analyzed by univariate and multivariate Cox regression. Forty-four GC tissues, corresponding adjacent normal tissues (n=20), and detailed clinical information were collected from Tianjin Medical University General Hospital, CDH6 expression level was detected for further validation. ResultsCDH6 was upregulated in GC samples compared with normal gastric tissue, and GSEA identified the citrate cycle tricarboxylic (TCA) cycle, extracellular matrix (ECM) receptor interaction, glyoxylate and dicarboxylate metabolism oxidative phosphorylation, and pentose phosphate pathway as differentially enriched in GCs. According to the area under the ROC curve (AUC) (AUC=0.829 in TCGA and 0.966 in GSE54129), CDH6 had high diagnostic efficiency. Patients with high expression of CDH6 was associated with higher T classification and worse prognoses than those with low CDH6 expression in GC. Univariate and multivariate Cox regression analysis showed that CDH6 was an independent risk factor for overall survival (univariate: HR = 1.305, P = 0.002, multivariate: HR = 1.481, P < 0.001). ConclusionCDH6 was upregulated in GC and high CDH6 expression indicated higher T classification and worse prognoses. CDH6 could be a potentially independent molecular biomarker for diagnosis and prognosis of GC.


2020 ◽  
Author(s):  
Wenfan Wang ◽  
Zhiqiang Chen ◽  
Qinghua Zhang ◽  
Yanjie You ◽  
Ailing Ma ◽  
...  

Abstract Background The purpose of this study was to assess the prognostic value of the expression of human epidermal growth factor receptor 2 (HER2), Ki67, and their combination levels in the prognosis of Chinese patients with resectable gastric cancer (GC). Methods A total of 2062 Chinese GC patients were recruited with HER2 and Ki67 expression being evaluated using immunohistochemistry. Patients were divided into four groups according to HER2 and Ki67 expression. The distributions between HER2 and Ki67 expression levels and clinicopathological characteristics were compared using the Chi-square test. The relationship between HER2 and Ki67 expression level and overall survival were evaluated with the univariate and multivariate Cox regression analysis. Results There was no statistical differences between the overall survival (OS) rate and the expression level of HER2 (P = 0.748) or Ki67 (P = 0.063), but there were significant relationships between the OS rates and the combining expression levels of HER2/Ki67 (P < 0.05). Further, Ki67, sex, T stage, N stage, TNM stage, and adjuvant chemotherapy were significant and independent risk factors for GC survival (P < 0.05). Conclusions Our study illustrated that Ki67, but not HER2 acted as an independent prognostic factor in Chinese resectable GC patients. The evaluation of the combining expression levels of HER2/Ki67 may be more useful to assess patient prognosis with resectable GC.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sheng Zheng ◽  
Zizhen Zhang ◽  
Ning Ding ◽  
Jiawei Sun ◽  
Yifeng Lin ◽  
...  

Abstract Introduction Angiogenesis is a key factor in promoting tumor growth, invasion and metastasis. In this study we aimed to investigate the prognostic value of angiogenesis-related genes (ARGs) in gastric cancer (GC). Methods mRNA sequencing data with clinical information of GC were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The differentially expressed ARGs between normal and tumor tissues were analyzed by limma package, and then prognosis‑associated genes were screened using Cox regression analysis. Nine angiogenesis genes were identified as crucially related to the overall survival (OS) of patients through least absolute shrinkage and selection operator (LASSO) regression. The prognostic model and corresponding nomograms were establish based on 9 ARGs and verified in in both TCGA and GEO GC cohorts respectively. Results Eighty-five differentially expressed ARGs and their enriched pathways were confirmed. Significant enrichment analysis revealed that ARGs-related signaling pathway genes were highly related to tumor angiogenesis development. Kaplan–Meier analysis revealed that patients in the high-risk group had worse OS rates compared with the low-risk group in training cohort and validation cohort. In addition, RS had a good prognostic effect on GC patients with different clinical features, especially those with advanced GC. Besides, the calibration curves verified fine concordance between the nomogram prediction model and actual observation. Conclusions We developed a nine gene signature related to the angiogenesis that can predict overall survival for GC. It’s assumed to be a valuable prognosis model with high efficiency, providing new perspectives in targeted therapy.


2021 ◽  
Vol 8 ◽  
Author(s):  
Jinfeng Zhu ◽  
Chen Luo ◽  
Jiefeng Zhao ◽  
Xiaojian Zhu ◽  
Kang Lin ◽  
...  

Background: Lysyl oxidase (LOX) is a key enzyme for the cross-linking of collagen and elastin in the extracellular matrix. This study evaluated the prognostic role of LOX in gastric cancer (GC) by analyzing the data of The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) dataset.Methods: The Wilcoxon rank-sum test was used to calculate the expression difference of LOX gene in gastric cancer and normal tissues. Western blot and immunohistochemical staining were used to evaluate the expression level of LOX protein in gastric cancer. Kaplan-Meier analysis was used to calculate the survival difference between the high expression group and the low expression group in gastric cancer. The relationship between statistical clinicopathological characteristics and LOX gene expression was analyzed by Wilcoxon or Kruskal-Wallis test and logistic regression. Univariate and multivariate Cox regression analysis was used to find independent risk factors affecting the prognosis of GC patients. Gene set enrichment analysis (GSEA) was used to screen the possible mechanisms of LOX and GC. The CIBERSORT calculation method was used to evaluate the distribution of tumor-infiltrating immune cell (TIC) abundance.Results: LOX is highly expressed in gastric cancer tissues and is significantly related to poor overall survival. Wilcoxon or Kruskal-Wallis test and Logistic regression analysis showed, LOX overexpression is significantly correlated with T-stage progression in gastric cancer. Multivariate Cox regression analysis on TCGA and GEO data found that LOX (all p &lt; 0.05) is an independent factor for poor GC prognosis. GSEA showed that high LOX expression is related to ECM receptor interaction, cancer, Hedgehog, TGF-beta, JAK-STAT, MAPK, Wnt, and mTOR signaling pathways. The expression level of LOX affects the immune activity of the tumor microenvironment in gastric cancer.Conclusion: High expression of LOX is a potential molecular indicator for poor prognosis of gastric cancer.


2020 ◽  
Author(s):  
Ran Wei ◽  
Jichuan Quan ◽  
Shuofeng Li ◽  
Zhao Lu ◽  
Xu Guan ◽  
...  

Abstract Background: Cancer stem cells (CSCs), which are characterized by self-renewal and plasticity, are highly correlated with tumor metastasis and drug resistance. To fully understand the role of CSCs in colorectal cancer (CRC), we evaluated the stemness traits and prognostic value of stemness-related genes in CRC.Methods: In this study, the data from 616 CRC patients from The Cancer Genome Atlas (TCGA) were assessed and subtyped based on the mRNA expression-based stemness index (mRNAsi). The correlations of cancer stemness with the immune microenvironment, tumor mutational burden (TMB) and N6-methyladenosine (m6A) RNA methylation regulators were analyzed. Weighted gene co-expression network analysis (WGCNA) was performed to identify the crucial stemness-related genes and modules. Furthermore, a prognostic expression signature was constructed using Lasso-penalized Cox regression analysis. The signature was validated via multiplex immunofluorescence staining of tissue samples in an independent cohort of 48 CRC patients.Results: This study suggests that high mRNAsi scores are associated with poor overall survival in stage Ⅳ CRC patients. Moreover, the levels of TMB and m6A RNA methylation regulators were positively correlated with mRNAsi scores, and low mRNAsi scores were characterized by increased immune activity in CRC. The analysis identified 2 key modules and 34 key genes as prognosis-related candidate biomarkers. Finally, a 3-gene prognostic signature (PARPBP, KNSTRN and KIF2C) was explored together with specific clinical features to construct a nomogram, which was successfully validated in an external cohort. Conclusions: There is a unique correlation between CSCs and the prognosis of CRC patients, and the novel biomarkers related to cell stemness could accurately predict the clinical outcomes of these patients.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Renshen Xiang ◽  
Wei Song ◽  
Jun Ren ◽  
Jing Wu ◽  
Jincheng Fu ◽  
...  

Abstract Background Although numerous studies demonstrate the role of cancer stem cells in occurrence, recurrence, and distant metastases in gastric cancer (GC), little is known about the evolving genetic and epigenetic changes in the stem and progenitor cells. The purpose of this study was to identify the stem cell subtypes in GC and examine their clinical relevance. Methods Two publicly available datasets were used to identify GC stem cell subtypes, and consensus clustering was performed by unsupervised machine learning methods. The cancer stem cell (CSC) typing-related risk scoring (RS) model was established through multivariate Cox regression analysis. Results Cross-platform dataset-based two stable GC stem cell subtypes, namely low stem cell enrichment (SCE_L) and high stem cell enrichment (SCE_H), were prudently identified. Gene set enrichment analysis revealed that the classical oncogenic pathways, immune-related pathways, and regulation of stem cell division were active in SCE_H; ferroptosis, NK cell activation, and post-mutation repair pathways were active in SCE_L. GC stem cell subtypes could accurately predict clinical outcomes in patients, tumor microenvironment cell-infiltration characteristics, somatic mutation landscape, and potential responses to immunotherapy, targeted therapy, and chemotherapy. Additionally, a CSC typing-related RS model was established; it was strongly independent and could accurately predict the patient’s overall survival. Conclusions This study demonstrated the complex oncogenic mechanisms underlying GC. The findings provide a basis and reference for the diagnosis and treatment of GC.


PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11273
Author(s):  
Lei Yang ◽  
Weilong Yin ◽  
Xuechen Liu ◽  
Fangcun Li ◽  
Li Ma ◽  
...  

Background Hepatocellular carcinoma (HCC) is considered to be a malignant tumor with a high incidence and a high mortality. Accurate prognostic models are urgently needed. The present study was aimed at screening the critical genes for prognosis of HCC. Methods The GSE25097, GSE14520, GSE36376 and GSE76427 datasets were obtained from Gene Expression Omnibus (GEO). We used GEO2R to screen differentially expressed genes (DEGs). A protein-protein interaction network of the DEGs was constructed by Cytoscape in order to find hub genes by module analysis. The Metascape was performed to discover biological functions and pathway enrichment of DEGs. MCODE components were calculated to construct a module complex of DEGs. Then, gene set enrichment analysis (GSEA) was used for gene enrichment analysis. ONCOMINE was employed to assess the mRNA expression levels of key genes in HCC, and the survival analysis was conducted using the array from The Cancer Genome Atlas (TCGA) of HCC. Then, the LASSO Cox regression model was performed to establish and identify the prognostic gene signature. We validated the prognostic value of the gene signature in the TCGA cohort. Results We screened out 10 hub genes which were all up-regulated in HCC tissue. They mainly enrich in mitotic cell cycle process. The GSEA results showed that these data sets had good enrichment score and significance in the cell cycle pathway. Each candidate gene may be an indicator of prognostic factors in the development of HCC. However, hub genes expression was weekly associated with overall survival in HCC patients. LASSO Cox regression analysis validated a five-gene signature (including CDC20, CCNB2, NCAPG, ASPM and NUSAP1). These results suggest that five-gene signature model may provide clues for clinical prognostic biomarker of HCC.


2019 ◽  
Vol 28 (4) ◽  
pp. 439-447 ◽  
Author(s):  
Yan Jiao ◽  
Yanqing Li ◽  
Bai Ji ◽  
Hongqiao Cai ◽  
Yahui Liu

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.


2021 ◽  
Author(s):  
Zhiyuan Huang ◽  
He Wang ◽  
Min Liu ◽  
Xinrui Li ◽  
Lei Zhu ◽  
...  

Abstract Background: It has been demonstrated by studies globally that autophagy took part in the development of cervical cancer (CC). Few studies concentrated on the correlation between overall survival and CC patients. We retrieved significant autophagy-related genes (ARGs) correlated to the process of cervical cancer. They may be used as prognosis marker or treatment target for clinical application.Methods: Expressions level of genes in cervical cancer and normal tissue samples were obtained from GTEx and TCGA database. Autophagy-related genes (ARGs) were retrieved accroding to the gene list from HaDB. Differentially expressed autophagy related genes (DE-ARGs) related to cervical cancer were identified by Wilcoxon signed-rank test. ClusterProfiler package worked in R software was used to perform GO and KEGG enrichment analyses. Univariate propotional hazard cox regression and multivariate propotional hazard cox regressions were applied to identify DE-ARGs equipped with prognostic value and other clinical independent risk factors. ROC curve was drawn for comparing the survival predict feasibility of risk score with other risk factors in CC patients. Nomogram was drawn to exhibit the prediction model constructed accroding to multivariate cox regression. Correlations between Differentially expressed autophagy related genes (DE-ARGs) and other clinical features were investigated by t test or Cruskal wallis analysis. Correlation between Immune and autophagy in cervical cancer was investigated by ssGSEA and TIMER database. Results: Fifty-six differentially expressed ARGs (DE-ARGs) were retrieved from cervical cancer tissue and normal tissue samples. GO enrichment analysis showed that these ARGs involved in autophagy, ubiquitination of protein and apoptosis. Cox regression medel showed that there were six ARGs significantly associated with overall survival of cervical caner patients. VAMP7 (HR = 0.599, P= 0.033) and TP73 (HR = 0.671, P= 0.014) played protective roles in survival among these six genes. Stage (Stage IV vs Stage I HR = 3.985, P<0.001) and risk score (HR = 1.353, P< 0.001) were sorted as independent prognostic risk factors based on multivariate cox regression. ROC curve validated that risk score was preferable to predict survival of CC patients than other risk factors. Additionally, we found some of these six predictor ARGs were correlated significantly in statistic with tumor grade or stage, clinical T stage, clinical N stage, pathology or risk score (all P< 0.05). The immune cells and immune functions showed a lower activity in high risk group than low risk group which is distincted by median risk score. Conclusion: Our discovery showed that autophagy genes involved in the progress of cervical cancer. Many autophagy-related genes could probably serve as prognostic biomarkers and accelerate the discovery of treatment targets for CC patients.


2021 ◽  
Author(s):  
Junliang Li ◽  
Lingfang Zhang ◽  
Tiankang Guo

Abstract Background. Peritoneal metastatic gastric cancer (PMGC) is very common, and usually, the prognosis is poor. There is currently an absence of accurate methods for the early diagnosis and prediction of peritoneal metastasis (PM). This highlights the need to develop strategies to identify the risk of PMGC. Methods. We performed a comprehensive discovery of biomarkers to predict PM by analyzing profiling datasets from GSE62254. The prognostic PM-related genes were obtained using the univariate Cox regression analysis, followed by a least absolute shrinkage and selection operator regression (LASSO) to establish a risk score model. The gene set enrichment analysis (GSEA) was used to determine the pathway enrichment in both the high- and low-risk groups. The 1-, 3-, and 5-year overall survival (OS) rates and area under the receiver operating characteristic curve (ROC) were used to compare the predictive accuracy-based risk stratification. In addition, an unsupervised clustering algorithm was applied to divide patients into subgroups according to the PM-related genes. Results. We identified 10 genes (MMP12, TAC1, TSPYL5, PPP1R14A, TMSB15B, NPY1R, PCDH9, EPM2AIP1, TIG7, and DYNC1I1) for PMGC diagnosis. The OS rates between the high- and low-risk groups at 1-, 3-, and 5-years were significantly different in the training and validation sets. The AUCs at 1-, 3-, and 5-years in the training set were 0.71, 0.74, and 0.73, respectively. In the validation set, the AUCs at 1-, 3-, and 5-years were 0.68, 0.66, and 0.69, respectively. The 10 gene signatures were correlated with immune cell infiltration in both the high- and low-risk groups. In addition, based on the GSEA, several significant pathways were enriched in the high-risk PMGC group, such as the Wnt and transforming growth factor beta (TGF-β) signaling pathway and leukocyte transendothelial migration pathway. Furthermore, unsupervised cluster analysis showed that the model could distinguish the level of risk among patients with PMGC. Conclusions. Overall, 10 gene signatures were identified for PMGC risk prediction. These may be valuable in making clinical decisions to improve treatment outcomes in patients with PMGC.


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