scholarly journals Development of a novel miR-3648-related gene signature as a prognostic biomarker in esophageal adenocarcinoma

2021 ◽  
Vol 9 (22) ◽  
pp. 1702-1702
Author(s):  
Donglei Zhang ◽  
Hang Yin ◽  
Thomas L. Bauer ◽  
Michael P. Rogers ◽  
Jeffrey B. Velotta ◽  
...  
Keyword(s):  
Esophageal Adenocarcinoma ◽  
Prognostic Biomarker ◽  
Gene Signature ◽  
Related Gene

Identification of a 15 DNA Damage Repair–Related Gene Signature as a Prognostic Predictor for Lung Adenocarcinoma

2021 ◽  
Vol 24 ◽  
Author(s):  
Linping Gu ◽  
Yuanyuan Xu ◽  
Hong Jian
Keyword(s):  
Prognostic Model ◽  
Molecular Subtypes ◽  
Prognostic Biomarker ◽  
Gene Signature ◽  
Supplementary Information ◽  
Related Gene ◽  
Accurate Evaluation ◽  
Damage Repair ◽  
Related Feature ◽  
Cluster 2

Background: Lung Adenocarcinoma (LUAD) is a common malignancy with a poor prognosis due to the lack of predictive markers. DNA Damage Repair (DDR)-related genes are closely related to cancer progression and treatment. Introduction: To identify a reliable DDR-related gene signature as an independent predictor of LUAD. Methods: DDR-related genes were obtained using combined analysis of TCGA-LUAD data and literature information, followed by the identification of DDR-related prognostic genes. The DDR-related molecular subtypes were then screened, followed by Kaplan–Meier analysis, feature gene identification, and pathway enrichment analysis of each subtype. Moreover, Cox and LASSO regression analyses were performed for the feature genes of each subtype to construct a prognostic model. The clinical utility of the prognostic model was confirmed using the validation dataset GSE72094 and nomogram analysis. Results: Eight DDR-related prognostic genes were identified from 31 DDR-related genes. Using consensus cluster analysis, three molecular subtypes were screened. Cluster 2 had the best prognosis, while cluster 3 had the worst. Compared to cluster 2, clusters 1 and 3 consisted of more stage 3 – 4, T2–T4, male, and older samples. The feature genes of clusters 1, 2, and 3 were mainly enriched in the cell cycle, arachidonic acid metabolism, and ribosomes. Furthermore, a 15-feature gene signature was identified for improving the prognosis of LUAD patients. Conclusion: The 15 DDR-related feature gene signature is an independent and powerful prognostic biomarker for LUAD that may improve risk classification and provide supplementary information for a more accurate evaluation and personalized treatment. Conclusion: The 15 DDR-related feature gene signature is an independent and powerful prognostic biomarker for LUAD that may improve risk classification and provide supplementary information for a more accurate evaluation and personalized treatment.

scholarly journals A Liquid-Liquid Phase Separation-Related Gene Signature as Prognostic Biomarker for Epithelial Ovarian Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Yan Qiu ◽  
Min Pan ◽  
Xuemei Chen
Keyword(s):  
Ovarian Cancer ◽  
Phase Separation ◽  
Prognostic Biomarker ◽  
Risk Group ◽  
Risk Index ◽  
Gene Signature ◽  
Related Gene ◽  
Data Set ◽  
Test Set ◽  
Liquid Liquid Phase Separation

ObjectiveThe aim of the present study was to construct and test a liquid-liquid phase separation (LLPS)-related gene signature as a prognostic tool for epithelial ovarian cancer (EOC).Materials and MethodsThe data set GSE26712 was used to screen the differentially expressed LLPS-related genes. Functional enrichment analysis was performed to reveal the potential biological functions. GSE17260 and GSE32062 were combined as the discovery to construct an LLPS-related gene signature through a three-step analysis (univariate Cox, least absolute shrinkage and selection operator, and multivariate Cox analyses). The EOC data set from The Cancer Genome Atlas as the test set was used to test the LLPS-related gene signature.ResultsThe differentially expressed LLPS-related genes involved in several cancer-related pathways, such as MAPK signaling pathway, cell cycle, and DNA replication. Eleven genes were selected to construct the LLPS-related gene signature risk index as prognostic biomarker for EOC. The risk index could successfully divide patients with EOC into high- and low-risk groups. The patients in high-risk group had significantly shorter overall survival than those with in low-risk group. The LLPS-related gene signature was validated in the test set and may be an independent prognostic factor compared to routine clinical features.ConclusionWe constructed and validated an LLPS-related gene signature as a prognosis tool in EOC through integrated analysis of multiple data sets.

scholarly journals A glycolysis-related gene signature predicts prognosis of patients with esophageal adenocarcinoma

Aging ◽  
2020 ◽  
Author(s):  
Huafeng Kang ◽  
Nan Wang ◽  
Xuan Wang ◽  
Yu Zhang ◽  
Shuai Lin ◽  
...  
Keyword(s):  
Esophageal Adenocarcinoma ◽  
Gene Signature ◽  
Related Gene

scholarly journals Predicting the Prognosis of Esophageal Adenocarcinoma by a Pyroptosis-Related Gene Signature

2021 ◽  
Vol 12 ◽  
Author(s):  
Ruijie Zeng ◽  
Shujie Huang ◽  
Xinqi Qiu ◽  
Zewei Zhuo ◽  
Huihuan Wu ◽  
...  
Keyword(s):  
Esophageal Adenocarcinoma ◽  
Poor Prognosis ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Validation Dataset ◽  
Related Gene ◽  
Independent Validation ◽  
Risk Patients ◽  
Cancer Genome Atlas

Esophageal adenocarcinoma (EAC) is a highly malignant type of digestive tract cancers with a poor prognosis despite therapeutic advances. Pyroptosis is an inflammatory form of programmed cell death, whereas the role of pyroptosis in EAC remains largely unknown. Herein, we identified a pyroptosis-related five-gene signature that was significantly correlated with the survival of EAC patients in The Cancer Genome Atlas (TCGA) cohort and an independent validation dataset. In addition, a nomogram based on the signature was constructed with novel prognostic values. Moreover, the downregulation of GSDMB within the signature is notably correlated with enhanced DNA methylation. The pyroptosis-related signature might be related to the immune response and regulation of the tumor microenvironment. Several inhibitors including GDC-0879 and PD-0325901 are promising in reversing the altered differentially expressed genes in high-risk patients. Our findings provide insights into the involvement of pyroptosis in EAC progression and are promising in the risk assessment as well as the prognosis for EAC patients in clinical practice.

scholarly journals Identification of the Novel Pyroptosis-Related Gene Signature in Patients with Esophageal Adenocarcinoma

2021 ◽  
Author(s):  
Ruijie Zeng ◽  
Shujie Huang ◽  
Zewei Zhuo ◽  
Huihuan Wu ◽  
Weihong Sha ◽  
...  
Keyword(s):  
Esophageal Adenocarcinoma ◽  
Poor Prognosis ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Validation Dataset ◽  
The Novel ◽  
Related Gene ◽  
Independent Validation ◽  
Cancer Genome Atlas

Esophageal adenocarcinoma (EAC) is a highly malignant type of digestive tract cancers with a poor prognosis despite therapeutic advances. Pyroptosis is an inflammatory form of programmed cell death, whereas the role of pyroptosis in EAC remains largely unknown. Herein, we identified a pyroptosis-related five-gene signature that was significantly correlated with the survival of EAC patients in The Cancer Genome Atlas (TCGA) cohort and an independent validation dataset. In addition, a nomogram based on the five-gene signature was constructed with novel prognostic values. Moreover, the genes in the pyroptosis-related signature, CASP1, GSDMB, IL1B, PYCARD, and ZBP1, might be involved in immune response and regulation of the tumor microenvironment. Our findings indicate that the five-gene signature provides insights into the involvement of pyroptosis in EAC progression, and is promising in the risk assessment as well as prognosis for EAC patients in clinical practice.

scholarly journals A Ferroptosis-Related Gene Signature Identified as a Novel Prognostic Biomarker for Colon Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Xin Qi ◽  
Rui Wang ◽  
Yuxin Lin ◽  
Donghui Yan ◽  
Jiachen Zuo ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Functional Annotation ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Gene Signature ◽  
Clinicopathological Features ◽  
Survival Prediction ◽  
Related Gene ◽  
Prognostic Signature ◽  
Cox Regression Analysis

BackgroundColon cancer (CC) is a common gastrointestinal malignant tumor with high heterogeneity in clinical behavior and response to treatment, making individualized survival prediction challenging. Ferroptosis is a newly discovered iron-dependent cell death that plays a critical role in cancer biology. Therefore, identifying a prognostic biomarker with ferroptosis-related genes provides a new strategy to guide precise clinical decision-making in CC patients.MethodsAlteration in the expression profile of ferroptosis-related genes was initially screened in GSE39582 dataset involving 585 CC patients. Univariate Cox regression analysis and LASSO-penalized Cox regression analysis were combined to further identify a novel ferroptosis-related gene signature for overall survival prediction. The prognostic performance of the signature was validated in the GSE17536 dataset by Kaplan-Meier survival curve and time-dependent ROC curve analyses. Functional annotation of the signature was explored by integrating GO and KEGG enrichment analysis, GSEA analysis and ssGSEA analysis. Furthermore, an outcome risk nomogram was constructed considering both the gene signature and the clinicopathological features.ResultsThe prognostic signature biomarker composed of 9 ferroptosis-related genes accurately discriminated high-risk and low-risk patients with CC in both the training and validation datasets. The signature was tightly linked to clinicopathological features and possessed powerful predictive ability for distinct clinical subgroups. Furthermore, the risk score was confirmed to be an independent prognostic factor for CC patients by multivariate Cox regression analysis (p < 0.05). Functional annotation analyses showed that the prognostic signature was closely correlated with pivotal cancer hallmarks, particularly cell cycle, transcriptional regulation, and immune-related functions. Moreover, a nomogram with the signature was also built to quantify outcome risk for each patient.ConclusionThe novel ferroptosis-related gene signature biomarker can be utilized for predicting individualized prognosis, optimizing survival risk assessment and facilitating personalized management of CC patients.

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.

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