scholarly journals Clinical Value of Tumor Marker Index Based on Preoperative CYFRA 21-1 and SCC-Ag in the Evaluation of Prognosis and Treatment Effectiveness in Patients with Esophageal Squamous Cell Carcinoma

2020 ◽  
Vol Volume 13 ◽  
pp. 4135-4143
Author(s):  
Nanchang Yin ◽  
Wei Liu
Cancer ◽  
2000 ◽  
Vol 89 (8) ◽  
pp. 1677-1683 ◽  
Author(s):  
Hideaki Shimada ◽  
Akihiko Takeda ◽  
Miwako Arima ◽  
Shinichi Okazumi ◽  
Hisahiro Matsubara ◽  
...  

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15265-e15265
Author(s):  
Wei Peng ◽  
Jun Zhu ◽  
Delin Liu ◽  
Pudong Qian ◽  
Qin Zhang ◽  
...  

e15265 Background: Piwi-interacting RNAs (piRNAs) are a novel type of small noncoding RNAs which have important biological functions in malignant diseases. However, little is known about the clinical value of piRNAs in esophageal squamous cell carcinoma (ESCC). Hence, we demonstrated that two representative piRNAs, piR-36026 and piR-651, to dig out their clinical value in ESCC. Methods: Quantitative real-time PCR was employed to detect the levels of piR-36026 and piR-651 expression in ESCC tissues. Furthermore, the correlation between them and ESCC patients' clinicopathological characteristics were explored. Receiver operating characteristic (ROC) curves were constructed for measuring significances of piR-36026 and piR-651 for ESCC diagnosis. Results: Both of piR-36026 and piR-651 were prominently increased in ESCC tissues compared with normal. Additionally, piR-36026 was related with ESCC patients' diameter (P = 0.013), TNM stage (P = 0.027), tumor differentiation (P = 0.008) and CEA (P = 0.013); and piR-651 was associated with diameter (P = 0.005), lymph node metastasis (P = 0.002), tumor differentiation (P = 0.008) and SCC (P = 0.002). The area under the ROC curve (AUC) of piR-36026 was up to 0.8634 (95% confidence interval: 0.8171-0.9089, P < 0.05). Similarly, the AUC of piR-651 was 0.8525 (95% confidence interval: 0.7804-0.9247, P < 0.05). Conclusions: These results demonstrated that both piR-36026 and piR-651 may play a crucial role in ESCC oncogenesis; and they may be diagnostic biomarker for ESCC.


2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Fa-Min Zeng ◽  
Jian-Zhong He ◽  
Shao-Hong Wang ◽  
De-kai Liu ◽  
Xiu-E. Xu ◽  
...  

To precisely predict the clinical outcome and determine the optimal treatment options for patients with esophageal squamous cell carcinoma (ESCC) remains challenging. Prognostic models based on multiple molecular markers of tumors have been shown to have superiority over the use of single biomarkers. Our previous studies have identified the crucial role of ezrin in ESCC progression, which prompted us to hypothesize that ezrin-associated proteins contribute to the pathobiology of ESCC. Herein, we explored the clinical value of a molecular model constructed based on ezrin-associated proteins in ESCC patients. We revealed that the ezrin-associated proteins (MYC, PDIA3, and ITGA5B1) correlated with the overall survival (OS) and disease-free survival (DFS) of patients with ESCC. High expression of MYC was associated with advanced pTNM-stage (P=0.011), and PDIA3 and ITGA5B1 were correlated with both lymph node metastasis (PDIA3: P<0.001; ITGA5B1: P=0.001) and pTNM-stage (PDIA3: P=0.001; ITGA5B1: P=0.009). Furthermore, we found that, compared with the current TNM staging system, the molecular model elicited from the expression of MYC, PDIA3, and ITGA5B1 shows higher accuracy in predicting OS (P<0.001) or DFS (P<0.001) in ESCC patients. Moreover, ROC and regression analysis demonstrated that this model was an independent predictor for OS and DFS, which could also help determine a subgroup of ESCC patients that may benefit from chemoradiotherapy. In conclusion, our study has identified a novel molecular prognosis model, which may serve as a complement for current clinical risk stratification approaches and provide potential therapeutic targets for ESCC treatment.


2021 ◽  
Author(s):  
Hongdian Zhang ◽  
Ran Jia ◽  
Yueyang Yang ◽  
Zhilin Sui ◽  
Wanyi Xiao ◽  
...  

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.


2020 ◽  
Author(s):  
Lan zhang ◽  
Pan Li ◽  
Chenju Xing ◽  
Di Zhu ◽  
Jianying Zhang ◽  
...  

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.


Author(s):  
Jifeng Feng ◽  
Liang Wang ◽  
Xun Yang ◽  
Qixun Chen

We herein propose a novel integrative score based on inflammatory and nutritional score, coagulation indicator and tumor marker, named comprehensive prognostic score (CPS), to predict postoperative survival in resectable esophageal squamous cell carcinoma (ESCC). We also aimed to establish and validate a nomogram based on CPS and other clinical features for individual survival prediction. A total of 490 resectable ESCC patients were randomly divided into either a training or validation cohort at a ratio of 7:3 for retrospective analysis. The CPS, based on squamous cell carcinoma antigen (SCCA), C-reactive protein to albumin ratio (CAR), neutrophil to lymphocyte ratio (NLR), and fibrinogen (FIB), was divided into two models to verify its prognostic value. The predictive model of CPS-based nomogram was established and validated in two cohorts. Patients with CPS low group in model 1 had better 5-year cancer-specific survival (CSS) than those in CPS high group (50.7% vs. 17.8%, P<0.001). For model 2, the 5-year CSS for CPS 0, 1 and 2 were 75.0%, 38.9% and 13.3%, respectively (P<0.001). CPS was confirmed as an independent prognostic score in both models. The CPS-based nomogram can accurately and effectively predict survival in resected ESCC. The CPS is a novel, simple, and effective predictor in resectable ESCC. Moreover, CPS has a potential independent prognostic value in predicting postoperative survival, which can accurately and effectively predict individual survival in resectable ESCC.


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