scholarly journals A Novel Ferroptosis-Related Biomarker Signature to Predict Overall Survival of Esophageal Squamous Cell Carcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Jiahang Song ◽  
Yanhu Liu ◽  
Xiang Guan ◽  
Xun Zhang ◽  
Wenda Yu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Risk Model ◽  
Expression Profiles ◽  
Gene Signature ◽  
Immune Checkpoints ◽  
Related Gene

Esophageal squamous cell carcinoma (ESCC) accounts for the main esophageal cancer (ESCA) type, which is also associated with the greatest malignant grade and low survival rates worldwide. Ferroptosis is recently discovered as a kind of programmed cell death, which is indicated in various reports to be involved in the regulation of tumor biological behaviors. This work focused on the comprehensive evaluation of the association between ferroptosis-related gene (FRG) expression profiles and prognosis in ESCC patients based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). ALOX12, ALOX12B, ANGPTL7, DRD4, MAPK9, SLC38A1, and ZNF419 were selected to develop a novel ferroptosis-related gene signature for GEO and TCGA cohorts. The prognostic risk model exactly classified patients who had diverse survival outcomes. In addition, this study identified the ferroptosis-related signature as a factor to independently predict the risk of ESCC. Thereafter, we also constructed the prognosis nomogram by incorporating clinical factors and risk score, and the calibration plots illustrated good prognostic performance. Moreover, the association of the risk score with immune checkpoints was observed. Collectively, the proposed ferroptosis-related gene signature in our study is effective and has a potential clinical application to predict the prognosis of ESCC.

scholarly journals A glycolysis-based three-gene signature predicts survival in patients with lung squamous cell carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Guichuan Huang ◽  
Jing Zhang ◽  
Ling Gong ◽  
Yi Huang ◽  
Daishun Liu
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Cox Regression ◽  
Lung Squamous Cell Carcinoma ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Related Gene ◽  
Cox Regression Analysis

Abstract Background Lung cancer is one of the most lethal and most prevalent malignant tumors worldwide, and lung squamous cell carcinoma (LUSC) is one of the major histological subtypes. Although numerous biomarkers have been found to be associated with prognosis in LUSC, the prediction effect of a single gene biomarker is insufficient, especially for glycolysis-related genes. Therefore, we aimed to develop a novel glycolysis-related gene signature to predict survival in patients with LUSC. Methods The mRNA expression files and LUSC clinical information were obtained from The Cancer Genome Atlas (TCGA) dataset. Results Based on Gene Set Enrichment Analysis (GSEA), we found 5 glycolysis-related gene sets that were significantly enriched in LUSC tissues. Univariate and multivariate Cox proportional regression models were performed to choose prognostic-related gene signatures. Based on a Cox proportional regression model, a risk score for a three-gene signature (HKDC1, ALDH7A1, and MDH1) was established to divide patients into high-risk and low-risk subgroups. Multivariate Cox regression analysis indicated that the risk score for this three-gene signature can be used as an independent prognostic indicator in LUSC. Additionally, based on the cBioPortal database, the rate of genomic alterations in the HKDC1, ALDH7A1, and MDH1 genes were 1.9, 1.1, and 5% in LUSC patients, respectively. Conclusion A glycolysis-based three-gene signature could serve as a novel biomarker in predicting the prognosis of patients with LUSC and it also provides additional gene targets that can be used to cure LUSC patients.

scholarly journals A glycolysis-based three-gene signature predicts survival in patients with lung squamous cell carcinoma

2020 ◽  
Author(s):  
Guichuan Huang ◽  
Jing Zhang ◽  
Ling Gong ◽  
Yi Huang ◽  
Daishun Liu
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Cox Regression ◽  
Lung Squamous Cell Carcinoma ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Related Gene ◽  
Cox Regression Analysis

Abstract Background: Lung cancer is one of the most lethal and most prevalent malignant tumors worldwide, and lung squamous cell carcinoma (LUSC) is one of major histological subtypes. Although, numerous biomarkers were found to be associated with prognosis in LUSC, the prediction effect of a single gene biomarker is not sufficient, especially for glycolysis-related genes. Therefore, we aimed to develop a novel glycolysis-related gene signature to predict survival of patients with LUSC.Methods: The mRNA expression files and clinical information of LUSC were obtained from The Cancer Genome Atlas (TCGA) dataset.Results: Based on Gene set enrichment analysis (GSEA), we found 5 glycolysis-related gene sets were significantly enriched in LUSC tissues. Univariate and multivariate Cox proportional regression models were conducted to choose prognostic-related gene signature. Based on Cox proportional regression model, a risk score of three-gene signature (including HKDC1, ALDH7A1, and MDH1) was established to divide patients into high-risk and low-risk subgroups. We found that a risk score of three-gene signature was an independent of prognostic indicator in LUSC using multivariate Cox regression analysis. Additionally, based on the cBioPortal database, the rate of alterations in HKDC1, ALDH7A1, and MDH1 genes were 1.9%, 1.1%, and 5% in LUSC patients, respectively. Conclusion: In conclusion, a glycolysis-based three-gene signature could serve as a novel biomarker in predicting prognosis of patients with LUSC, which provided more gene targets to cure LUSC patients.

scholarly journals Immune-Related Long Non-coding RNA Signature and Clinical Nomogram to Evaluate Survival of Patients Suffering Esophageal Squamous Cell Carcinoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Ting Zhu ◽  
Zhifeng Ma ◽  
Haiyong Wang ◽  
Desheng Wei ◽  
Bin Wang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Immune Checkpoints ◽  
Regression Analyses ◽  
Training Set ◽  
Significant Difference ◽  
Validation Set

Esophageal squamous cell carcinoma (ESCC) turns out to be one of the most prevalent cancer types, leading to a relatively high mortality among worldwide sufferers. In this study, gene microarray data of ESCC patients were obtained from the GEO database, with the samples involved divided into a training set and a validation set. Based on the immune-related differential long non-coding RNAs (lncRNAs) we identified, a prognostic eight-lncRNA-based risk signature was constructed following regression analyses. Then, the predictive capacity of the model was evaluated in the training set and validation set using survival curves and receiver operation characteristic curves. In addition, univariate and multivariate regression analyses based on clinical information and the model-based risk score also demonstrated the ability of the risk score in independently determining the prognosis of patients. Besides, based on the CIBERSORT tool, the abundance of immune infiltrates in tumor samples was scored, and a significant difference was presented between the high- and low- risk groups. Correlation analysis with immune checkpoints (PD1, PDL1, and CTLA4) indicated that the eight-lncRNA signature–based risk score was negatively correlated with PD1 expression, suggesting that the eight-lncRNA signature may have an effect in immunotherapy for ESCC. Finally, GO annotation was performed for the differential mRNAs that were co-expressed with the eight lncRNAs, and it was uncovered that they were remarkably enriched in immune-related biological functions. These results suggested that the eight-lncRNA signature–based risk model could be employed as an independent biomarker for ESCC prognosis and might play a part in evaluating the response of ESCC to immunotherapy with immune checkpoint blockade.

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 < 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 < 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 A Glycolysis-Based Three-Gene Signature Predicts Survival in Patients with Lung Squamous Cell Carcinoma

2020 ◽  
Author(s):  
Guichuan Huang ◽  
Jing Zhang ◽  
Ling Gong ◽  
Yi Huang ◽  
Daishun Liu
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Cox Regression ◽  
Lung Squamous Cell Carcinoma ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Related Gene ◽  
Cox Regression Analysis

Abstract Purpose: Lung cancer is one of the most lethal and most prevalent malignant tumors worldwide, and lung squamous cell carcinoma (LUSC) is one of major histological subtypes. Although, numerous biomarkers were found to be associated with prognosis in LUSC, the prediction effect of a single gene biomarker is not sufficient, especially for glycolysis-related genes. Therefore, we aimed to develop a novel glycolysis-related gene signature to predict survival of patients with LUSC. Material and Methods: The mRNA expression files and clinical information of LUSC were obtained from The Cancer Genome Atlas (TCGA) dataset. Results: Based on Gene set enrichment analysis (GSEA), we found 5 glycolysis-related gene sets were significantly enriched in LUSC tissues. Univariate and multivariate Cox proportional regression models were conducted to choose prognostic-related gene signature. Based on Cox proportional regression model, a risk score of three-gene signature (including HKDC1, ALDH7A1, and MDH1) was established to divide patients into high-risk and low-risk subgroups. We found that a risk score of three-gene signature was an independent of prognostic indicator in LUSC using multivariate Cox regression analysis.Conclusion: In conclusion, a glycolysis-based three-gene signature could serve as a novel biomarker in predicting prognosis of patients with LUSC, which provided more gene targets to cure LUSC patients.

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.

scholarly journals MicroRNA Expression Profiles in Superficial Esophageal Squamous Cell Carcinoma before Endoscopic Submucosal Dissection: A Pilot Study

2021 ◽  
Vol 22 (9) ◽  
pp. 4789
Author(s):  
Shintaro Fujihara ◽  
Hideki Kobara ◽  
Noriko Nishiyama ◽  
Kayo Hirose ◽  
Hisakazu Iwama ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Endoscopic Submucosal Dissection ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Mirna Expression ◽  
Expression Profiles ◽  
Normal Tissues ◽  
Mirna Expression Profiles

Esophageal squamous cell carcinoma (ESCC) has a poor prognosis when diagnosed at an advanced stage, and early detection and treatment are essential to improve survival. However, intraobserver and interobserver variation make the diagnosis of superficial ESCC difficult, and suitable biomarkers are urgently needed. Here, we compared the microRNA (miRNA) expression profiles of superficial ESCC tissues and adjacent normal tissues obtained immediately before esophageal endoscopic submucosal dissection. We found that ESCC and normal tissues differed in their miRNA expression profiles. In particular, miR-21-5p and miR-146b-5p were significantly upregulated and miR-210-3p was significantly downregulated in tumor tissues compared with normal tissues. We also detected significant associations between miRNA expression and ESCC invasion depth and lymphovascular invasion. The same differential expression of miR-21-5p, miR-146b-5p, and miR-210-3p was detected in ESCC cell lines compared with normal esophageal epithelial cells in vitro. However, transfection of ESCC cells with miR-210-3p and miR-21-5p mimics or inhibitors had partial effects on cell proliferation and invasion in vitro. These results indicate that miRNA expression is significantly deregulated in superficial ESCC, and suggest that the potential contribution of differentially expressed miRNAs to the malignant phenotype should be further investigated.

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