scholarly journals Autophagy-Related Three-Gene Prognostic Signature for Predicting Survival in Esophageal Squamous Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Heyang Cui ◽  
Yongjia Weng ◽  
Ning Ding ◽  
Chen Cheng ◽  
Longlong Wang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Discovery Cohort ◽  
Cox Regression Analysis

Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive malignant tumors in China, and its prognosis remains poor. Autophagy is an evolutionarily conserved catabolic process involved in the occurrence and development of ESCC. In this study, we described the expression profile of autophagy-related genes (ARGs) in ESCC and developed a prognostic prediction model for ESCC patients based on the expression pattern of ARGs. We used four ESCC cohorts, GSE53624 (119 samples) set as the discovery cohort, The Cancer Genome Atlas (TCGA) ESCC set (95 samples) as the validation cohort, 155 ESCC cohort, and Oncomine cohort were used to screen and verify differentially expressed ARGs. We identified 34 differentially expressed genes out of 222 ARGs. In the discovery cohort, we divided ESCC patients into three groups that showed significant differences in prognosis. Then, we analyzed the prognosis of 34 differentially expressed ARGs. Three genes [poly (ADP-ribose) polymerase 1 (PARP1), integrin alpha-6 (ITGA6), and Fas-associated death domain (FADD)] were ultimately obtained through random forest feature selection and were constructed as an ARG-related prognostic model. This model was further validated in TCGA ESCC set. Cox regression analysis confirmed that the three-gene signature was an independent prognostic factor for ESCC patients. This signature effectively stratified patients in both discovery and validation cohorts by overall survival (P = 5.162E-8 and P = 0.052, respectively). We also constructed a clinical nomogram with a concordance index of 0.713 to predict the survival possibility of ESCC patients by integrating clinical characteristics and the ARG signature. The calibration curves substantiated fine concordance between nomogram prediction and actual observation. In conclusion, we constructed a new ARG-related prognostic model, which shows the potential to improve the ability of individualized prognosis prediction in ESCC.

scholarly journals Development and Validation of a Ferroptosis-Related Gene Signature and Nomogram for Predicting the Prognosis of Esophageal Squamous Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Jiecheng Ye ◽  
Yining Wu ◽  
Heyuan Cai ◽  
Li Sun ◽  
Wanying Deng ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Prognostic Value ◽  
Cox Regression ◽  
Risk Group ◽  
Clinical Variable ◽  
Cox Regression Analysis

Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor with high mortality and poor prognosis. Ferroptosis is a newly discovered form of cell death induced by iron-catalyzed excessive peroxidation of polyunsaturated fatty acids (PUFAs). However, the prognostic value of ferroptosis-related genes (FRGs) for ESCC remains unclear. Based on the ESCC dataset from the Gene Expression Omnibus (GEO) database, we identified 39 prognostic FRGs through univariate Cox regression analysis. After LASSO regression and multivariate Cox regression analyses, a multigene signature based on 10 prognostic FRGs was constructed and successfully divided ESCC patients into two risk groups. Patients in the low-risk group showed a significantly better prognosis than patients in the high-risk group. In addition, we combined the risk score with clinical predictors to construct a nomogram for ESCC. The predictive ability of the nomogram was further verified by ROC curves and calibration plots in both the training and validation sets. The predictive power of the nomogram was demonstrated to be better than that of either the risk score or clinical variable alone. Furthermore, functional analysis revealed that the 10-FRG signature was mainly associated with ferroptosis, differentiation and immune response. Connectivity map analysis identified potential compounds capable of targeting FRGs in ESCC. Finally, we demonstrated the prognostic value of SRC gene in ESCC using the clinical samples and found that SRC inhibition sensitized ESCC cells to ferroptosis inducers by in vitro experiments. In conclusion, we identified and verified a 10-FRG prognostic signature and a nomogram, which provide individualized prognosis prediction and provide insight into potential therapeutic targets for ESCC.

scholarly journals The Value of Complete Blood Count For The Prognosis Analysis of Esophageal Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Xiang Lv ◽  
Songtao Han ◽  
Bin Xu ◽  
Yuqin Deng ◽  
Feng Yangchun
Keyword(s):  
Squamous Cell Carcinoma ◽  
Regression Analysis ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Blood Count ◽  
Cox Regression ◽  
Complete Blood Count ◽  
Analysis Model ◽  
Cox Regression Analysis

Abstract Objective To investigate the value of complete blood count in predicting the survival rate of patients with esophageal squamous cell carcinoma. Methods A total of 3587 patients with esophageal squamous cell carcinoma who were initially admitted to the Affiliated Cancer Hospital of Xinjiang Medical University from January 2010 to December 2017 were collected by retrospective study. The relevant clinical data were collected by the medical record system, and the patients were followed up by the hospital medical record follow-up system. The follow-up outcome was death. The survival time of all patients was obtained. The survival curve was established using the cut-off value of each index obtained by ROC curve. The Cox proportional hazards regression analysis model and nomogram were established to predict the survival prognosis of esophageal squamous cell carcinoma. The role of each index in the prognosis of patients with esophageal squamous cell carcinoma was studied Results The cut-off values of NLR, NMR, LMR, RDW and PDW in blood routine were 3.52, 10.22, 2.25, 13.85% and 12.05%, respectively. Survival curve analysis showed that patients aged < 60 years and NLR < 3.52 had survival. All indicators were divided into high and low groups according to ROC curve. Univariate Cox regression analysis model showed that RDW (≥ 13.85) and NLR (≥ 3.52) groups were risk factors for the prognosis of ESCC, with HR values of 1.099 (1.015–1.191; p = 0.020) and 1.340 (1.231–1.458; p < 0.001) compared with RDW (< 13.85) and NLR (< 3.52), respectively; multivariate Cox regression analysis model showed that NLR was significantly associated with the prognosis of ESCC, with HR of 1.342 (1.232–1.461; p < 0.001) for NLR (≥ 3.52) NLR (< 3.52). Conclusion NLR results in blood count can be used to predict the survival of patients with esophageal squamous cell carcinoma.

Prognostic value of programmed death-ligand 1 expression in patients with esophageal squamous cell carcinoma

2020 ◽  
Author(s):  
Qun Zhang ◽  
Feng Li ◽  
Peng Cai ◽  
Hongwei Li ◽  
Hongmei Yin ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Cox Regression ◽  
Tumor Resection ◽  
Programmed Death Ligand 1 ◽  
Cox Regression Analysis ◽  
Programmed Death ◽  
L1 Protein

Abstract Background To investigate the expression of PD-L1(programmed death-ligand 1)in patients with esophageal squamous cell carcinoma (ESCC) and its clinical significance. Methods The tissue expression of PD-L1 protein in 139 cases of ESCC and 50 adjacent non-malignant epithelial tissues (> 5 cm from the tumor resection margins) were identified by immunohistochemical staining. Subsequently, the relationship between expression and the observed clinical characteristics was analyzed. Results The positive expression rate of PD-L1 protein was increased in tumor tissues compared to that of adjacent noncancerous mucosa tissues (40.3% vs. 22.0%, P < 0.05). The findings also indicated that PD-L1 protein expression had no significant correlation with age, gender, tumor location, differentiation and lymph node (N) status (P > 0.05). The 91 months follow-up Kaplan-Meier survival analysis showed that patients in positively expressed PD-L1 group experienced a lower survival rate compared to their negatively expressed PD-L1 counterparts (32.1% vs. 48.2%, P < 0.05). The COX regression analysis results suggested that PD-L1 represented an independent prognosis factor for ESCC. Conclusions The findings indicated that PD-L1 plays an important role in the progression of ESCC and might represent a potential therapeutic and prognostic target for ESCC patients.

Development of an immunogenomics-based prognostic index model of laryngeal squamous cell carcinoma

2020 ◽  
Author(s):  
Yujie Shen ◽  
Han Zhou ◽  
Shikun Dong ◽  
Meiping Lu ◽  
Weida Dong ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Laryngeal Squamous Cell Carcinoma ◽  
Cox Regression ◽  
Prognostic Index ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Cox Regression Analysis

Abstract Background: The immune system greatly affects the prognosis of various malignancies. Studies on differentially expressed immune-related genes (IRGs) in the immune microenvironment of laryngeal squamous cell carcinoma (LSCC) have rarely been reported.Methods: In this paper, the prognostic potentials of IRGs in LSCC were explored. The RNAseq dataset containing differentially expressed IRGs and corresponding clinical information of LSCC patients was obtained from The Cancer Genome Atlas (TCGA). A total of 371 up-regulated and 61 down-regulated IRGs were identified. Subsequent functional enrichment analysis revealed that the pathway of IRGs was mainly enriched in the cytokine-cytokine receptor interaction. Then, 30 IRGs with prognostic potentials in LSCC were screened out, and the regulatory network induced by relevant transcription factors (TFs) were constructed.Results: Finally, multivariate Cox regression analysis was conducted to assess the prognostic potential of 15 IRGs after adjustment of clinical factors and LSCC patients were classified into 2 subgroups based on different outcomes. The gene expression of the model was verified by other independent databases. Nomogram including the 15 IRGs signature was established and shown some clinical net beneft. Intriguingly, B cells were significantly enriched in the low-risk group. Conclusion:These findings may contribute to the development of potential therapeutic targets and biomarkers for the new-immunotherapy of LSCC.

scholarly journals Predictive Value of LINC01133 for Unfavorable Prognosis was Impacted by Alcohol in Esophageal Squamous Cell Carcinoma

2018 ◽  
Vol 48 (1) ◽  
pp. 251-262 ◽  
Author(s):  
Xian-Zi Yang ◽  
Qing-Jun He ◽  
Tian-Tian Cheng ◽  
Jun Chi ◽  
Zi-Ying Lei ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Protective Factor ◽  
Cox Regression ◽  
Tnm Stage ◽  
Rank Test ◽  
Cox Regression Analysis ◽  
Drinking Status

Background/Aims: Considerable evidence indicates that long noncoding RNAs (lncRNAs) exert importantly regulatory functions during human cancer initiation and progression and are promising biotargets in the flight against cancer. Methods: In this study, we evaluated the role of the lncRNA LINC01133 in esophageal squamous cell carcinoma (ESCC). LINC01133 expression in ESCC was examined by quantitative real-time PCR. The correlations between LINC01133 expression and clinicopathological variables and survival were examined by the χ2 test, Kaplan–Meier method, log-rank test, and univariate Cox regression analysis. Results: LINC01133 expression levels were frequently lower in ESCC tissues and cell lines than in paired normal tissues and an immortalized esophageal epithelial cell line, respectively. The expression of LINC01133 decreased in a TNM stage- and lifestyle-independent manner. LINC01133 was an independent protective factor and had an anti-tumor effect in the early stage of ESCC development. More importantly, we discovered that drinking status in our cohort impaired the predictive accuracy of LINC01133 for patients with ESCC. Furthermore, a new risk model combining LINC01133 expression, drinking status, and TNM stage provided better survival discrimination compared with three other predictors. Conclusions: Our data indicate that a loss of LINC01133 expression is a potential poor prognostic biomarker and therapeutic target for ESCC and provide additional prognostic information to improve the outcomes of ESCC patients.

scholarly journals A four-hypoxia-genes-based prognostic signature for oral squamous cell carcinoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Chenguang Zhao ◽  
Yingrui Zhou ◽  
Hongwei Ma ◽  
Jinhui Wang ◽  
Haoliang Guo ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Regression Analysis ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Cox Regression ◽  
Relative Proportion ◽  
The Cancer Genome Atlas ◽  
Cox Regression Analysis

Abstract Background Oral squamous cell carcinoma (OSCC) is one of the most common maligancies of the head and neck. The prognosis was is significantly different among OSCC patients. This study aims to identify new biomarkers to establish a prognostic model to predict the survival of OSCC patients. Methods The mRNA expression and corresponding clinical information of OSCC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus. Additionally, a total of 26 hypoxia-related genes were also obtained from a previous study. Univariate Cox regression analysis and LASSO Cox regression analysis were performed to screen the optimal hypoxia-related genes which were associated with the prognosis of OSCC. to establish the predictive model (Risk Score) was established for estimating the patient's overall survival (OS). Multivariate Cox regression analysis was used to determine whether the Risk Score was an independent prognostic factor. Based on all the independent prognostic factors, nomogram was established to predict the OS probability of OSCC patients. The relative proportion of 22 immune cell types in each patient was evaluated by CIBERSORT software. Results We determined that a total of four hypoxia-related genes including ALDOA, P4HA1, PGK1 and VEGFA were significantly associated with the prognosis of OSCC patients. The nomogram established based on all the independent factors could reliably predict the long-term OS of OSCC patients. In addition, our resluts indicated that the inferior prognosis of OSCC patients with high Risk Score might be related to the immunosuppressive microenvironments. Conclusion This study shows that high expression of hypoxia-related genes including ALDOA, P4HA1, PGK1 and VEGFA is associated with poor prognosis in OSCC patients, and they can be used as potential markers for predicting prognosis in OSCC patients.

scholarly journals The value of complete blood count for the prognosis analysis of preoperative esophageal squamous cell carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiang Lv ◽  
Songtao Han ◽  
Bin Xu ◽  
Yuqin Deng ◽  
Yangchun Feng
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Blood Count ◽  
Validation Cohort ◽  
Complete Blood Count ◽  
Training Cohort ◽  
Cox Regression Analysis

Abstract Objective To investigate the predictive value of preoperative complete blood count for the survival of patients with esophageal squamous cell carcinoma. Methods A total of 1587 patients with pathologically confirmed esophageal squamous cell carcinoma who underwent esophagectomy in the Cancer Hospital Affiliated to Xinjiang Medical University from January 2010 to December 2019 were collected by retrospective study. A total of 359 patients were as the validation cohort from January 2015 to December 2016, and the remaining 1228 patients were as the training cohort. The relevant clinical data were collected by the medical record system, and the patients were followed up by the hospital medical record follow-up system. The follow-up outcome was patient death. The survival time of all patients was obtained. The Cox proportional hazards regression model and nomogram were established to predict the survival prognosis of esophageal squamous cell carcinoma by the index, their cut-off values obtained the training cohort by the ROC curve. The Kaplan-Meier survival curve was established to express the overall survival rate. The 3-year and 5-year calibration curves and C-index were used to determine the accuracy and discrimination of the prognostic model. The decision curve analysis was used to predict the potential of clinical application. Finally, the validation cohort was used to verify the results of the training cohort. Results The cut-off values of NLR, NMR, LMR, RDW and PDW in complete blood count of the training cohort were 3.29, 12.77, 2.95, 15.05 and 13.65%, respectively. All indicators were divided into high and low groups according to cut-off values. Univariate Cox regression analysis model showed that age (≥ 60), NLR (≥3.29), LMR (< 2.95), RDW (≥15.05%) and PDW (≥13.65%) were risk factors for the prognosis of esophageal squamous cell carcinoma; multivariate Cox regression analysis model showed that age (≥ 60), NLR (≥3.29) and LMR (< 2.95) were independent risk factors for esophageal squamous cell carcinoma. Kaplan-Meier curve indicated that age <  60, NLR < 3.52 and LMR ≥ 2.95 groups had higher overall survival (p <  0.05). The 3-year calibration curve indicated that its predictive probability overestimate the actual probability. 5-year calibration curve indicated that its predictive probability was consistent with the actual probability. 5 c-index was 0.730 and 0.737, respectively, indicating that the prognostic model had high accuracy and discrimination. The decision curve analysis indicated good potential for clinical application. The validation cohort also proved the validity of the prognostic model. Conclusion NLR and LMR results in complete blood count results can be used to predict the survival prognosis of patients with preoperative esophageal squamous cell carcinoma.

scholarly journals Data Mining Identifies Six Proteins that Can Act as Prognostic Markers for Head and Neck Squamous Cell Carcinoma

2020 ◽  
Vol 29 ◽  
pp. 096368972092930
Author(s):  
Zeng-hong Wu ◽  
Yun-Tang ◽  
Qing Cheng
Keyword(s):  
Squamous Cell Carcinoma ◽  
Regression Analysis ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
High Throughput Sequencing ◽  
Cox Regression ◽  
Neck Squamous Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Cox Regression Analysis

Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor of the upper aerodigestive tract affecting the oral cavity, lips, paranasal sinuses, larynx, and nasopharynx. Proteogenomics combines proteomics and genomics and employs mass spectrometry and high-throughput sequencing technologies to identify novel peptides. The aim of this study was to identify potential protein biomarkers for clinical treatment of HNSCC. To achieve this, we utilized two sets of data, one on proteins from The Cancer Proteome Atlas (TCPA) and the other on gene expression from The Cancer Genome Atlas (TCGA) database, to evaluate dysfunctional proteogenomics microenvironment. Univariate Cox regression analysis was performed to examine the relationship between protein signatures and prognosis. A total of 19 proteins were significantly associated with overall survival (OS) of patients, of which E2F transcription factor 1 (E2F1; HR = 4.557, 95% CI = 1.810 to 11.469) and enhancer of zeste homolog 2 (EZH2; HR = 0.430, 95% CI = 0.187 to 0.984) were the most differentially expressed between patients with longer and shorter OS, respectively. Furthermore, multivariate Cox regression analysis on six proteins (ERALPHA, HER3, BRAF, P27, RAPTOR, and E2F1) was performed to build the prognostic model. The receiver operating characteristic curves were used to determine whether the expression pattern of survival-related proteins could provide an early prediction of the occurrence of HNSCC. Herein, we found an AUC of 0.720. Based on an online database, we identified novel protein markers for the prognosis of HNSCC. The findings of the present study may provide new insights into the development of new and reliable tools for precise cancer intervention.

scholarly journals Identification of the Prognostic Value of Tumor Microenvironment-Related Genes in Esophageal Squamous Cell Carcinoma

2020 ◽  
Vol 7 ◽  
Author(s):  
Donglei Zhang ◽  
Changlin Qian ◽  
Huabing Wei ◽  
Xiaozhe Qian
Keyword(s):  
Squamous Cell Carcinoma ◽  
Tumor Microenvironment ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Prognostic Value ◽  
Cox Regression ◽  
Expression Profiles ◽  
Cox Regression Analysis

Background: Esophageal squamous cell carcinoma (ESCC) is the most prevalent histological type of esophageal cancer, but there is a lack of definite prognostic markers for this cancer.Methods: We used the ESTIMATE algorithm to access the tumor microenvironment (TME) of ESCC cases deposited in the TCGA database, and identified TME-related prognostic genes using Cox regression analysis. A least absolute shrinkage and selector operation or LASSO algorithm was used to identify key prognostic genes. Risk scores were calculated, and a clinical predictive model was constructed to evaluate the prognostic value of TME-related genes.Results: We found that high immune and stromal scores were significantly associated with poor overall survival (p &lt; 0.05). We identified a total of 1,151 TME-related differently expression genes, among which 67 were prognosis-related genes. Through the LASSO method, 13 key prognostic genes were selected, namely, ADAMTS16, LOC51089, CH25H, CORO2B, DLGAP1, GYS2, HAL, MXRA8, NPTX1, OTX1, RET, SLC24A2, and SPI1, and a 13-gene risk score was constructed. A higher score was indicative of a poorer prognosis than a lower risk score (hazard ratio = 8.21, 95% confidence interval: 2.56–26.31; P &lt; 0.001). The risk score was significantly correlated with immune/stromal scores and various types of infiltrating immune cells, including CD8 cells, regulatory T cells, and resting macrophages.Conclusion: We characterized the tumor microenvironment in ESCC, and identified the key prognosis genes. The risk score based on the expression profiles of these genes is proposed as an indicator of TME status and is instrumental in predicting patient prognosis.

scholarly journals Identifying the p65-Dependent Effect of Sulforaphene on Esophageal Squamous Cell Carcinoma Progression via Bioinformatics Analysis

2020 ◽  
Vol 22 (1) ◽  
pp. 60
Author(s):  
Sichong Han ◽  
Zhe Wang ◽  
Jining Liu ◽  
Qipeng Yuan
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Squamous Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Dependent Manner

Understanding the mechanism by which sulforaphene (SFE) affects esophageal squamous cell carcinoma (ESCC) contributes to the application of this isothiocyanate as a chemotherapeutic agent. Thus, we attempted to investigate SFE regulation of ESCC characteristics more deeply. We performed gene set enrichment analysis (GSEA) on microarray data of SFE-treated ESCC cells and found that differentially expressed genes are enriched in TNFα_Signaling_via_the_NFκB_Pathway. Coupled with the expression profile data from the GSE20347 and GSE75241 datasets, we narrowed the set to 8 genes, 4 of which (C-X-C motif chemokine ligand 10 (CXCL10), TNF alpha induced protein 3 (TNFAIP3), inhibin subunit beta A (INHBA), and plasminogen activator, urokinase (PLAU)) were verified as the targets of SFE. RNA-sequence (RNA-seq) data of 182 ESCC samples from The Cancer Genome Atlas (TCGA) were grouped into two phenotypes for GSEA according to the expression of CXCL10, TNFAIP3, INHBA, and PLAU. The enrichment results proved that they were all involved in the NFκB pathway. ChIP-seq analyses obtained from the Cistrome database indicated that NFκB-p65 is likely to control the transcription of CXCL10, TNFAIP3, INHBA, and PLAU, and considering TNFAIP3 and PLAU are the most significantly differentially expressed genes, we used chromatin immunoprecipitation-polymerase chain reaction (ChIP-PCR) to verify the regulation of p65 on their expression. The results demonstrated that SFE suppresses ESCC progression by down-regulating TNFAIP3 and PLAU expression in a p65-dependent manner.

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