scholarly journals High Expression of PPFIA1 Is Associated With Tumor Progression and a Poor Prognosis in Esophageal Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Hongdian Zhang ◽  
Ran Jia ◽  
Yueyang Yang ◽  
Zhilin Sui ◽  
Wanyi Xiao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Histological Grade ◽  
Cdna Array ◽  
Enrichment Analysis ◽  
Clinical Value ◽  
Node Metastasis

Abstract Background: PTPRF interacting protein alpha 1 (PPFIA1) is reportedly related to the occurrence and progression of several types of malignancies. However, its role in esophageal squamous cell carcinoma (ESCC) remains unknown. We aimed to investigate the expression and clinical value of PPFIA1 in ESCC.Methods: The Oncomine, Gene Expression Profiling Enrichment Analysis (GEPIA), and Gene Expression Omnibus (GEO) databases were utilized to explore PPFIA1 mRNA expression in esophageal cancer. The associations of PPFIA1 expression with clinicopathological variables and prognosis were evaluated in the GSE53625 dataset and verified in quantitative real-time polymerase chain reaction (qRT-PCR)-based cDNA array and immunohistochemistry (IHC)-based tissue microarray (TMA) datasets. The interactions between PPFIA1 and other genes based on the protein-protein interaction (PPI) network was analyzed via the STRING website.Results: PPFIA1 expression was obviously upregulated in ESCC tissues versus adjacent normal tissues according to online database analyses (all P<0.05). High PPFIA1 expression was significantly associated with several clinicopathological features, including tumor size, histological grade, tumor invasion depth, lymph node metastasis, and tumor-node-metastasis (TNM) stage. High PPFIA1 expression was related to worse outcomes and was identified as an independent prognostic indicator of overall survival (OS) in ESCC patients GSE53625 dataset, P=0.004; cDNA array dataset, P<0.001; TMA dataset, P=0.039). PPI analysis demonstrated that PPFIA1 was highly correlated with multiple genes, including UNC13B, RAB3A, PTPRD, and SYT1.Conclusion: PPFIA1 may be associated with ESCC progression and could be used as a biomarker for prognostic evaluation in ESCC patients.

scholarly journals A multi-lncRNA signature for suvival prediction in esophageal squamous cell carcinoma (ESCC) patients

2020 ◽  
Author(s):  
Lan zhang ◽  
Pan Li ◽  
Chenju Xing ◽  
Di Zhu ◽  
Jianying Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Prognostic Marker ◽  
Squamous Cell ◽  
Cox Regression ◽  
Risk Groups ◽  
Validation Dataset ◽  
Clinical Value

Abstract Background: The aim of this study was to identify prognostic long non-coding RNAs (lncRNAs) and develop a multi-lncRNA signature for suvival prediction in esophageal squamous cell carcinoma (ESCC) patients.Methods: The clinical and gene expression data from 301 ESCC patients were downloaded, including a corhort used as training set from Gene Expression Omnibus database (GSE53624, n=119), another cohort of 98 paired ESCC tumor and normal tissues as test set and an independent validation cohort including 84 ESCC tissues. Survival analyses, Cox regression and Kaplan–Meier analysis were used.Results: we screened a prognostic marker of ESCC from the GSE53624 dataset and named it as the five-lncRNA signature including AC007179.1, MORF4L2-AS1, RP11-488I20.9, RP13-30A9.2, RP4-735C1.6, which could classify patients into high- and low-risk groups with significantly different survival(median survival: 1.75 years vs. 4.01 years, log rank P<0.05). Then test dataset and validation dataset confirmed that the five-lncRNA signature can determine the prognosis of ESCC patients. Predictive independence of the prognostic marker was proved by multivariable Cox regression analyses in the three datasets (P<0.05). In addition, the signature was found to be better than TNM stage in terms of prognosis.Conclusion: The five-lncRNA signature could be a good prognostic biomarker for ESCC patients and has important clinical value.

scholarly journals Prognostic value of a five-lncRNA signature in esophageal squamous cell carcinoma

2020 ◽  
Author(s):  
Lan Zhang ◽  
Pan Li ◽  
Enjie Liu ◽  
Chenju Xing ◽  
Di Zhu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Prognostic Marker ◽  
Squamous Cell ◽  
Cox Regression ◽  
Risk Groups ◽  
Validation Dataset ◽  
Clinical Value

Abstract Background: The aim of this study was to identify prognostic long non-coding RNAs (lncRNAs) and develop a multi-lncRNA signature for suvival prediction in esophageal squamous cell carcinoma (ESCC). Methods: The clinical and gene expression data from Gene Expression Omnibus database (GSE53624, n=119) were obtianed as training set. A total of 98 paired ESCC tumor and normal tissues were detected by RNA sequencing and used as test set. Another 84 ESCC tissues were used for real-time quantitative PCR(qRT-PCR) and as an independent validation cohort. Survival analysis, Cox regression and Kaplan–Meier analysis were performed. Results: We screened a prognostic marker of ESCC from the GSE53624 dataset and named it as the five-lncRNA signature including AC007179.1, MORF4L2-AS1, RP11-488I20.9, RP13-30A9.2, RP4-735C1.6, which could classify patients into high- and low-risk groups with significantly different survival(median survival: 1.75 years vs. 4.01 years, log rank P<0.05). Then test dataset and validation dataset confirmed that the five-lncRNA signature can determine the prognosis of ESCC patients. Predictive independence of the prognostic marker was proved by multivariable Cox regression analyses in the three datasets (P<0.05). In addition, the signature was found to be better than TNM stage in terms of prognosis. Conclusion: The five-lncRNA signature could be a good prognostic biomarker for ESCC patients and has important clinical value.

scholarly journals Identification of Key Genes Related to the Prognosis of Esophageal Squamous Cell Carcinoma Based on Chip Re-Annotation

2021 ◽  
Vol 11 (7) ◽  
pp. 3229
Author(s):  
Meiqi Wang ◽  
Dan Liu ◽  
Yunchuanxiang Huang ◽  
Ziyi Jiang ◽  
Feng Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
Clinical Prognosis ◽  
Matrix Differential ◽  
On Chip

Esophageal cancer (EC) is one of the deadliest cancers worldwide. However, reliable biomarkers for early diagnosis, or those for the prognosis of therapy, remain unfulfilled goals for its subtype esophageal squamous cell carcinoma (ESCC). The purpose of this study was to identify reliable biomarkers for the diagnosis and prognosis of ESCC by gene chip re-annotation technique and downstream bioinformatics analysis. In our research, the GSE53624 dataset was downloaded from the GEO database. Then, we reannotated the gene expression probe and obtained the gene expression matrix. Differential expressed genes (DEGs) were found by R packages and they were subjected to Gene Ontology enrichment analysis and protein–protein interaction (PPI) network construction. As a result, a total of 28,885 mRNA probes were reannotated, among which 210 down-regulated and 80 up-regulated DEGs were screened out. By combining these genes set in clinical prognosis information and Western blot analysis, we found four genes with diagnostic and prognostic significance, including MMP134SPP1, MMP10, and COL1A1. Furthermore, markers of infiltrating immune cells exhibited different DEG-related immune infiltration patterns.

scholarly journals Prognostic value of a five-lncRNA signature in esophageal squamous cell carcinoma (ESCC)

2020 ◽  
Author(s):  
Lan Zhang ◽  
Pan Li ◽  
Chenju Xing ◽  
Di Zhu ◽  
Jianying Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Prognostic Marker ◽  
Squamous Cell ◽  
Cox Regression ◽  
Risk Groups ◽  
Validation Dataset ◽  
Clinical Value

Abstract Background The aim of this study was to identify prognostic long non-coding RNAs (lncRNAs) and develop a multi-lncRNA signature for suvival prediction in esophageal squamous cell carcinoma (ESCC). Methods The clinical and gene expression data from Gene Expression Omnibus database (GSE53624, n = 119) were obtianed as training set. A total of 98 paired ESCC tumor and normal tissues were detected by RNA sequencing and used as test set. Another 84 ESCC tissues were used for real-time quantitative PCR(qRT-PCR) and as an independent validation cohort. Survival analyses, Cox regression and Kaplan–Meier analysis were performed. Results We screened a prognostic marker of ESCC from the GSE53624 dataset and named it as the five-lncRNA signature including AC007179.1, MORF4L2-AS1, RP11-488I20.9, RP13-30A9.2, RP4-735C1.6, which could classify patients into high- and low-risk groups with significantly different survival(median survival: 1.75 years vs. 4.01 years, log rank P < 0.05). Then test dataset and validation dataset confirmed that the five-lncRNA signature can determine the prognosis of ESCC patients. Predictive independence of the prognostic marker was proved by multivariable Cox regression analyses in the three datasets (P < 0.05). In addition, the signature was found to be better than TNM stage in terms of prognosis. Conclusion The five-lncRNA signature could be a good prognostic biomarker for ESCC patients and has important clinical value.

scholarly journals A nomogram to predict lymph node metastasis risk for early esophageal squamous cell carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaofeng Duan ◽  
Xiaobin Shang ◽  
Jie Yue ◽  
Zhao Ma ◽  
Chuangui Chen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Squamous Cell Carcinoma ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Early Stage ◽  
Derivation Cohort ◽  
Node Metastasis

Abstract Background A nomogram was developed to predict lymph node metastasis (LNM) for patients with early-stage esophageal squamous cell carcinoma (ESCC). Methods We used the clinical data of ESCC patients with pathological T1 stage disease who underwent surgery from January 2011 to June 2018 to develop a nomogram model. Multivariable logistic regression was used to confirm the risk factors for variable selection. The risk of LNM was stratified based on the nomogram model. The nomogram was validated by an independent cohort which included early ESCC patients underwent esophagectomy between July 2018 and December 2019. Results Of the 223 patients, 36 (16.1%) patients had LNM. The following three variables were confirmed as LNM risk factors and were included in the nomogram model: tumor differentiation (odds ratio [OR] = 3.776, 95% confidence interval [CI] 1.515–9.360, p = 0.004), depth of tumor invasion (OR = 3.124, 95% CI 1.146–8.511, p = 0.026), and tumor size (OR = 2.420, 95% CI 1.070–5.473, p = 0.034). The C-index was 0.810 (95% CI 0.742–0.895) in the derivation cohort (223 patients) and 0.830 (95% CI 0.763–0.902) in the validation cohort (80 patients). Conclusions A validated nomogram can predict the risk of LNM via risk stratification. It could be used to assist in the decision-making process to determine which patients should undergo esophagectomy and for which patients with a low risk of LNM, curative endoscopic resection would be sufficient.

scholarly journals Identification of tumor-infiltrating lymphocyte subpopulations correlated with patient prognosis in esophageal squamous cell carcinoma

2021 ◽  
Vol 49 (5) ◽  
pp. 030006052110162
Author(s):  
Lin Peng ◽  
Wenwu He ◽  
Feng Ye ◽  
Yane Song ◽  
Xinying Shi ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Suppressor Cells ◽  
Enrichment Analysis ◽  
Postoperative Chemotherapy ◽  
Th2 Cells

Objective To identify biomarkers related to esophageal squamous cell carcinoma (ESCC) prognosis by analyzing genetic variations and the infiltration levels of tumor-infiltrating lymphocytes (TILs) in patients. Methods The clinical features of 61 patients with ESCC were collected. DNA panel sequencing was performed to screen differentially expressed genes (DEGs). Transcriptome sequencing was performed to identify gene expression profiles, and subsequent enrichment analysis of DEGs was conducted using Metascape. Results We identified 488 DEGs between patients with ESCC with distinct prognoses that were mainly enriched in the human immune response, fibrinogen complex, and protein activation cascade pathways. Among patients with ESCC treated with postoperative chemotherapy, those with a high infiltration level of myeloid-derived suppressor cells (MDSCs) had longer overall survival (OS), and OS was positively correlated with the infiltration level of T helper type 2 (Th2) cells among patients treated without chemotherapy after surgery. Additionally, in the case of MDSCs >0.7059 or Th2 cells <0.6290, patients receiving postoperative chemotherapy had a longer OS than those treated without chemotherapy following surgery. Conclusion The level of MDSCs or Th2 cells can be used as a biomarker for assessing the prognosis of patients with ESCC treated with or without postoperative chemotherapy, respectively.

Risk factors of lymph node metastasis in T1 esophageal squamous cell carcinoma

2008 ◽  
Vol 23 (4) ◽  
pp. 619-625 ◽  
Author(s):  
Dong Uk Kim ◽  
Jun Haeng Lee ◽  
Byung-Hoon Min ◽  
Sang Goon Shim ◽  
Dong Kyung Chang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Squamous Cell Carcinoma ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Node Metastasis
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