scholarly journals Identification of key genes associated with progression and prognosis for lung squamous cell carcinoma

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9086 ◽  
Author(s):  
Xiaohan Ma ◽  
Huijun Ren ◽  
Ruoyu Peng ◽  
Yi Li ◽  
Liang Ming
Keyword(s):  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Characteristic Curve ◽  
Lung Squamous Cell Carcinoma ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Hub Genes ◽  
Clinical Prognosis

Background Lung squamous cell carcinoma (LUSC) is a major subtype of lung cancer with limited therapeutic options and poor clinical prognosis. Methods Three datasets (GSE19188, GSE33532 and GSE33479) were obtained from the gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) between LUSC and normal tissues were identified by GEO2R, and functional analysis was employed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool. Protein–protein interaction (PPI) and hub genes were identified via the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape software. Hub genes were further validated in The Cancer Genome Atlas (TCGA) database. Subsequently, survival analysis was performed using the Kapla–Meier curve and Cox progression analysis. Based on univariate and multivariate Cox progression analysis, a gene signature was established to predict overall survival. Receiver operating characteristic curve was used to evaluate the prognostic value of the model. Results A total of 116 up-regulated genes and 84 down-regulated genes were identified. These DEGs were mainly enriched in the two pathways: cell cycle and p53 signaling way. According to the degree of protein nodes in the PPI network, 10 hub genes were identified. The mRNA expression levels of the 10 hub genes in LUSC were also significantly up-regulated in the TCGA database. Furthermore, a novel seven-gene signature (FLRT3, PPP2R2C, MMP3, MMP12, CAPN8, FILIP1 and SPP1) from the DEGs was constructed and acted as a significant and independent prognostic signature for LUSC. Conclusions The 10 hub genes might be tightly correlated with LUSC progression. The seven-gene signature might be an independent biomarker with a significant predictive value in LUSC overall survival.

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.

scholarly journals Survival-associated N6-adenosine methyltransferase signatures in lung squamous cell carcinoma and clinical verification

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jialin Qu ◽  
Li Wang ◽  
Man Jiang ◽  
Zhimin Wei ◽  
Guangming Fu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Survival Time ◽  
Squamous Cell ◽  
Risk Index ◽  
Lung Squamous Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Roc Curve Analysis ◽  
Clinical Prognosis

Abstract Background N6-methyladenine (m6A) is the most common modification of mRNA and IncRNA in higher organisms. m6A has been confirmed to be related to the formation and progression of tumors and m6A-related genes can be used as prognostic biomarkers in a variety of tumors. However, there have been no similar studies on lung squamous cell carcinoma. The main purpose of this study was aimed to explore the differential expression of m6A-related genes in lung squamous cell carcinoma tissues and its relationship with patient clinical prognosis. Methods We integrated three m6A writers that catalyze the methylation of adenine on mRNA molecules. The training set including 501 patients with LUSC was collected from The Cancer Genome Atlas (TCGA) database and the test set including 181 patients with LUSC was collected from the Gene Expression Omnibus (GEO) database. Based on the expression level of the m6A methylase gene, we established a tumor subgroup and risk-prognosis model to quantify the risk index and long-term patient prognosis, which were confirmed by principal component analysis (PCA) and receiver operating characteristic (ROC) curve analysis. After lung squamous cell carcinoma tissue specimens were obtained during surgery, immunohistochemistry (IHC) was used to verify the results in vitro. Results The results of the study showed that the expression of the three m6A methylases in tumor tissues and normal tissues was significantly different (P < 0.05). The survival-prognostic model based on METTL3 gene expression showed better predictive performance (AUC: 0.706). Patients in the high-risk and low-risk groups exhibited significant differences in terms of survival time and 5-year and 10-year survival rates. Immunohistochemistry revealed that patients with high METTL3 expression exhibited a longer survival time than those with low METTL3 expression. Conclusions Our study showed that the molecular phenotype based on the expression of METTL3 may be an independent risk factor affecting the prognosis of lung squamous cell carcinoma. These findings not only prove the important role of m6A methylase in lung squamous cell carcinoma, but are also expected to provide more accurate prognostic assessment and individualized treatment for patients with lung squamous cell carcinoma.

scholarly journals Development and validation of an individualized immune prognostic model in stage I–III lung squamous cell carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qi-Fan Yang ◽  
Di Wu ◽  
Jian Wang ◽  
Li Ba ◽  
Chen Tian ◽  
...  
Keyword(s):  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Lung Squamous Cell Carcinoma ◽  
Risk Groups ◽  
Stage I ◽  
Tissue Samples ◽  
Mutation Burden

AbstractLung squamous cell carcinoma (LUSC) possesses a poor prognosis even for stages I–III resected patients. Reliable prognostic biomarkers that can stratify and predict clinical outcomes for stage I–III resected LUSC patients are urgently needed. Based on gene expression of LUSC tissue samples from five public datasets, consisting of 687 cases, we developed an immune-related prognostic model (IPM) according to immune genes from ImmPort database. Then, we comprehensively analyzed the immune microenvironment and mutation burden that are significantly associated with this model. According to the IPM, patients were stratified into high- and low-risk groups with markedly distinct survival benefits. We found that patients with high immune risk possessed a higher proportion of immunosuppressive cells such as macrophages M0, and presented higher expression of CD47, CD73, SIRPA, and TIM-3. Moreover, When further stratified based on the tumor mutation burden (TMB) and risk score, patients with high TMB and low immune risk had a remarkable prolonged overall survival compared to patients with low TMB and high immune risk. Finally, a nomogram combing the IPM with clinical factors was established to provide a more precise evaluation of prognosis. The proposed immune relevant model is a promising biomarker for predicting overall survival in stage I–III LUSC. Thus, it may shed light on identifying patient subset at high risk of adverse prognosis from an immunological perspective.

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 UBE2D1 RNA Expression Was an Independent Unfavorable Prognostic Indicator in Lung Adenocarcinoma, but Not in Lung Squamous Cell Carcinoma

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Liyan Hou ◽  
Yingbo Li ◽  
Ying Wang ◽  
Dongqiang Xu ◽  
Hailing Cui ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Squamous Cell Carcinoma ◽  
Lung Adenocarcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Survival Data ◽  
Lung Squamous Cell Carcinoma ◽  
Prognostic Indicator ◽  
The Cancer Genome Atlas ◽  
Rna Expression

In this study, we investigated the potential prognostic value of ubiquitin-conjugating enzyme E2D1 (UBE2D1) RNA expression in different histological subtypes of non-small-cell lung cancer (NSCLC). A retrospective study was performed by using molecular, clinicopathological, and survival data in the Cancer Genome Atlas (TCGA)—Lung Cancer. Results showed that both lung adenocarcinoma (LUAD) (N=514) and lung squamous cell carcinoma (LUSC) (N=502) tissues had significantly elevated UBE2D1 RNA expression compared to the normal tissues (p<0.001 and p=0.036, respectively). UBE2D1 RNA expression was significantly higher in LUAD than in LUSC tissues. Increased UBE2D1 RNA expression was independently associated with shorter OS (HR: 1.359, 95% CI: 1.031–1.791, p=0.029) and RFS (HR: 1.842, 95% CI: 1.353–2.508, p<0.001) in LUAD patients, but not in LUSC patients. DNA amplification was common in LUAD patients (88/551, 16.0%) and was associated with significantly upregulated UBE2D1 RNA expression. Based on these findings, we infer that UBE2D1 RNA expression might only serve as an independent prognostic indicator of unfavorable OS and RFS in LUAD, but not in LUSC.

scholarly journals How Long Non-Coding RNAs and MicroRNAs Mediate the Endogenous RNA Network of Head and Neck Squamous Cell Carcinoma: a Comprehensive Analysis

2018 ◽  
Vol 50 (1) ◽  
pp. 332-341 ◽  
Author(s):  
Guomiao Zhao ◽  
Yaru Fu ◽  
Zhifang Su ◽  
Rongling wu
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Cancer Metastasis ◽  
Lung Squamous Cell Carcinoma ◽  
Neck Squamous Cell Carcinoma ◽  
Differentially Expressed ◽  
Clinical Prognosis ◽  
Non Coding Rnas

Background/Aims: Long non-coding RNAs (lncRNAs) act as competing endogenous RNAs (ceRNAs) to compete for microRNAs (miRNAs) in cancer metastasis. Head and neck squamous cell carcinoma (HNSCC) is one of the most common human cancers and rare biomarkers could predict the clinical prognosis of this disease and its therapeutic effect. Methods: Weighted gene co-expression network analysis (WGCNA) was performed to identify differentially expressed mRNAs (DEmRNAs) that might be key genes. GO enrichment and protein–protein interaction (PPI) analyses were performed to identify the principal functions of the DEmRNAs. An lncRNA-miRNA-mRNA network was constructed to understand the regulatory mechanisms in HNSCC. The prognostic signatures of mRNAs, miRNAs, and lncRNAs were determined by Gene Expression Profiling Interactive Analysis (GEPIA) and using Kaplan–Meier survival curves for patients with lung squamous cell carcinoma. Results: We identified 2,023 DEmRNAs, 1,048 differentially expressed lncRNAs (DElncRNAs), and 82 differentially expressed miRNAs (DEmiRNAs). We found that eight DEmRNAs, 53 DElncRNAs, and 16 DEmiRNAs interacted in the ceRNA network. Three ceRNAs (HCG22, LINC00460 and STC2) were significantly correlated with survival. STC2 transcript levels were significantly higher in tumour tissues than in normal tissues, and the STC2 expression was slightly upregulated at different stages of HNSCC. Conclusion: LINC00460, HCG22 and STC2 exhibited aberrant levels of expression and may participate in the pathogenesis of HNSCC.

scholarly journals Pathological and Prognostic Indications of the mdig Gene in Human Lung Cancer

2021 ◽  
Vol 55 (S2) ◽  
pp. 13-28
Keyword(s):  
Lung Cancer ◽  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Lung Squamous Cell Carcinoma ◽  
Human Lung Cancer ◽  
Clinical Samples ◽  
Lung Carcinogenesis ◽  
Expression Status

Background/Aims: The mineral-dust-induced gene mdig is a lung-cancer-associated oncogene. The focus of this study is to evaluate the expression status of mdig in lung cancer and to assess its influence in predicting the patient’s overall survival. Methods: Using high-density tissue microarrays and clinical samples of synchronous multiple primary lung cancer (SMPLC), we investigated the expression of mdig through immunohistochemistry and utilized the open-access lung cancer patient databases containing genomic and transcriptomic data from the UCSC Xena and TCGA web platforms to determine the prognostic values of mdig expression status among different subtypes of lung cancer. Results: mdig is upregulated in smokers and in lung squamous cell carcinoma. High mdig expression predicted poor overall survival in lung squamous cell carcinoma and female smokers. Among tumor tissues from SMPLC patients, we not only unraveled the highest positive rate of mdig expression, but also revealed a unique cytoplasmic, rather than nuclear localization of mdig protein. Furthermore, by inspecting some pathological but not cancerous lung tissues, we believe that mdig is required for the transformation of non-cancerous lung cells to the fully-fledged cancer cells. Conclusion: These data suggested that mdig is involved in various stages of lung carcinogenesis, possibly through the epigenetic regulation on some critical cancer-associated genes, and increased mdig expression is an important prognostic factor for some types of lung cancer.

scholarly journals Identification of Cell cycle Gene Signatures Predicting Survival in Patients with Lung Squamous Cell Carcinoma

2019 ◽  
Author(s):  
Lei Zhang ◽  
Zhe Zhang ◽  
Zhenglun Yu
Keyword(s):  
Cell Cycle ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Lung Squamous Cell Carcinoma ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Test Series ◽  
Gene Signatures ◽  
Gene Set

Abstract Background:Lung cancer (LC) is one of the most important and common malignant tumors, and its incidence and mortality are increasing annually. Lung squamous cell carcinoma (LUSC) is the common pathological type of lung cancer. A small part of biomarkers have been confirmed to be related to the prognosis and survival by data excavation. However, the moderate forecast effect of a single gene biomarker is not accurate. Thus, we aimed to identify new gene signatures to better predict Lung squamous cell carcinoma ( LU SC). Methods : Using the mRNA-mining approach, we performed mRNA expression profiling in large lung squamous cell carcinoma cohorts (n= from The Cancer Genome Atlas (TCGA) database. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis(GSVA) were accomplished, and connections between genes and cell cycle were found in the Cox proportional regression model. Results : We have confirmed a set of four genes (CDKN1A, CHEK2, E2F4 and RAD21) that were importantly associated with overall survival (OS) in the test series. Based on the research of the four-gene signature, the patients in the test series could be divided into high-risk and low-risk teams. Additionally, multivariate Cox regression analysis revealed that the prognostic power of the four-gene signature is independent of the clinical factors. Conclusion : Our study demonstrated the connections between the four-gene signature and cell cycle. Novel insights into the research mechanisms of cell cycle was also revealed regarding the biomarkers of a poor prognosis for lung squamous cell carcinoma patients.

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