scholarly journals Identification of a Hypoxia-Related Gene Signature and Establishment of a Nomogram for Predicting Prognosis in Esophageal Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Wanyi Xiao ◽  
Peng Tang ◽  
Zhilin Sui ◽  
Xianxian Wu ◽  
Yueyang Yang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Gene Signature ◽  
Related Gene

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 Construction and Validation of an Immune-Related Gene Prognostic Index for Esophageal Squamous Cell Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Qinghua Ji ◽  
Yingying Cai ◽  
Sachin Mulmi Shrestha ◽  
Duo Shen ◽  
Wei Zhao ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Index ◽  
Enrichment Analysis ◽  
Response To Therapy ◽  
Gene Set Enrichment Analysis ◽  
Related Gene ◽  
Immune Related Gene

Immune checkpoint inhibitor (ICI) therapy may benefit patients with advanced esophageal squamous cell carcinoma (ESCC); however, novel biomarkers are needed to help predict the response of patients to treatment. Differentially expressed immune-related genes within The Cancer Genome Atlas ESCC dataset were selected using the weighted gene coexpression network and lasso Cox regression analyses. Based on these data, an immune-related gene prognostic index (IRGPI) was constructed. The molecular characteristics of the different IRGPI subgroups were assessed using mutation information and gene set enrichment analysis. Differences in immune cell infiltration and the response to ICI therapy and other drugs were also analyzed. Additionally, tumor and adjacent control tissues were collected from six patients with ESCC and the expression of these genes was verified using real-time quantitative polymerase chain reaction. IRGPI was designed based on CLDN1, HCAR3, FNBP1L, and BRCA2, the expression of which was confirmed in ESCC samples. The prognosis of patients in the high-IRGPI group was poor, as verified using publicly available expression data. KMT2D mutations were more common in the high-IRGPI group. Enrichment analysis revealed an active immune response, and immune infiltration assessment showed that the high-IRGPI group had an increased infiltration degree of CD8 T cells, which contributed to the improved response to ICI treatment. Collectively, these data demonstrate that IRGPI is a robust biomarker for predicting the prognosis and response to therapy of patients with ESCC.

scholarly journals A Novel Glycolysis-related Gene Signature for Survival Prediction in Patients with Head and Neck Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Haimei Qin ◽  
Junli Wang ◽  
Biyun Liao ◽  
Zhonglin Liu ◽  
Rong Wang
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Poor Prognosis ◽  
Risk Group ◽  
Gene Signature ◽  
Neck Squamous Cell Carcinoma ◽  
Related Gene ◽  
Cancer Subtypes

Abstract Background: Head and neck squamous cell carcinoma (HNSCC) is most diagnosed at an advanced stage with poor prognosis. Single gene biomarkers cannot have enough predictive ability in HNSCC. Glycolysis participating in cancers was verified. Thus, this study aimed to identify glycolysis-related gene signature predict the outcome of HNSCC. Methods: The mRNA expression data of HNSCC downloaded The Cancer Genome Atlas (TCGA) project was analyzed by Gene Set Enrichment Analysis (GSEA). We use the Cox proportional regression model to construct a prognostic model. Kaplan–Meier and receiver operating characteristic (ROC) curves were employed to estimate the signature. We also analyzed the relationship of the signature and cancer subtypes. Results: We identified nine glycolysis-related genes including G6PD, EGFR, ALDH2, GPR87, STC2, PDK3, ELF3, STC1 and GNPDA1 as prognosis-related genes signature in HNSCC. HNSCC patients were divided into high and low risk group according to the signature. High risk group showed more poor prognosis and the risk score can precisely predict the prognosis of HNSCC. Additionally, the signature also can be used in cancer subtypes. Conclusion: This study established the 9-mRNA glycolysis signature which may serve as a prospective biomarker for prognosis and novel treatment target in HNSCC.

scholarly journals Development and Validation of an E2F-Related Gene Signature to Predict Prognosis of Patients With Lung Squamous Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Cailian Wang ◽  
Xuyu Gu ◽  
Xiuxiu Zhang ◽  
Min Zhou ◽  
Yan Chen
Keyword(s):  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Decision Tree ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Lung Squamous Cell Carcinoma ◽  
Gene Signature ◽  
Related Gene ◽  
Risk Patients

BackgroundLung squamous cell carcinoma (LUSC) generally correlates with poor clinical prognoses due to the lack of available prognostic biomarkers. This study is designed to identify a potential biomarker significant for the prognosis and treatment of LUSC, so as to provide a scientific basis for clinical treatment decisions.MethodsGenomic changes in LUSC samples before and after radiation were firstly discussed to identify E2 factor (E2F) pathway of prognostic significance. A series of bioinformatics analyses and statistical methods were combined to construct a robust E2F-related prognostic gene signature. Furthermore, a decision tree and a nomogram were established according to the gene signature and multiple clinicopathological characteristics to improve risk stratification and quantify risk assessment for individual patients.ResultsIn our investigated cohorts, the E2F-related gene signature we identified was capable of predicting clinical outcomes and therapeutic responses in LUSC patients, besides, discriminative to identify high-risk patients. Survival analysis suggested that the gene signature was independently prognostic for adverse overall survival of LUSC patients. The decision tree identified the strong discriminative performance of the gene signature in risk stractification for overall survival while the nomogram demonstrated a high accuracy.ConclusionThe E2F-related gene signature may help distinguish high-risk patients so as to formulate personalized treatment strategy in LUSC patients.

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