Identification of an immune-based mRNA–lncRNA signature for overall survival in cervical squamous cell carcinoma

2021 ◽  
Author(s):  
Yifang Mao ◽  
Run Chen ◽  
Meng Xia ◽  
Peng Guo ◽  
Feitianzhi Zeng ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Cervical Squamous Cell Carcinoma ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Rna Sequences ◽  
Immune Infiltration

Aim: To better predict the survival of cervical squamous cell carcinoma (CESC) patients, we aimed to construct a signature according to different immune infiltration. Methods: We downloaded the RNA sequences of CESC patients from the Cancer Genome Atlas database. By using single-sample gene set enrichment analysis, we separated the samples into high- and low-immunity groups. Then we separated the samples into training and testing datasets and performed the following analyses: univariate, least absolute shrinkage and selection operator analysis, multivariate Cox regression analyses and weighted gene coexpression network analysis using R software. Gene ontology and Kyoto Encyclopedia of Genes and Genomes studies were performed using the Database for Annotation, Visualization and Integrated Discovery website. Results & conclusion: We finally identified a signature with three mRNAs and two lncRNAs: ADGRG5, HSH2D, ZMAT4, RBAKDN and LINC00200. In short, our study constructed an mRNA–lncRNA signature related to immune infiltration to better predict the survival of CESC patients.

scholarly journals Human sperm-associated antigen 4 as a potential prognostic biomarker of lung squamous cell carcinoma

2021 ◽  
Vol 49 (7) ◽  
pp. 030006052110328
Author(s):  
Yongheng Wang ◽  
Yao Tang ◽  
Jianhui Li ◽  
Danfang Wang ◽  
Wenhan Li
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Malignant Tumors ◽  
Lung Squamous Cell Carcinoma ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Tissue Samples

Objective Lung cancer (LC) is one of the most prevalent malignant tumors worldwide. As a subtype of LC, lung squamous cell carcinoma (LUSC) has a 5-year survival rate of less than 15%. In this study, we aimed to evaluate the prognostic value of a glycolysis-related gene signature in LUSC patients. Methods We obtained RNA-Seq data from The Cancer Genome Atlas (TCGA) database. Prognosis-related genes were screened out by Gene Set Enrichment Analysis (GSEA) and Cox proportional regression models. Quantitative reverse transcription polymerase chain reaction (RT-qPCR) was used to verify the mRNA expression levels in relevant tissues. Results We found that sperm-associated antigen 4 (SPAG4) overexpression was an independent risk factor for overall survival (OS) in LUSC. Patients with high-risk scores had higher mortality rates than those with low-risk scores. Moreover, by using RT-qPCR, we validated that SPAG4 mRNA was overexpressed in LUSC tissue samples compared with their paired para-cancerous histological normal tissues. Conclusions Analysis of aberrantly overexpressed SPAG4 may provide a further useful approach to complement existing methods and predict prognosis in LUSC patients.

scholarly journals Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of esophageal squamous cell carcinoma

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Mingdi Liu ◽  
Faping Li ◽  
Bin Liu ◽  
Yongping Jian ◽  
Dan Zhang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Risk Model ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment

Abstract Background As a complex system participating in tumor development and progression, the tumor microenvironment was poorly understood in esophageal cancer especially squamous cell carcinoma (ESCC). Methods ESTIMATE algorithm is used to investigate tumor-infiltrating immune cells and prognostic genes which were associated with the tumor microenvironment in ESCC. Results Based on the immune and stromal scores, ESCC samples were divided into high and low score groups and 299 overlapping differentially expressed genes were identified. Functional enrichment analysis showed that these genes were mainly involved in muscle-related function. Prognostic genes including COL9A3, GFRA2, and VSIG4 were used to establish a risk prediction model using Cox regression analyses. Then multivariate analysis showed that COL9A3 was an independent discriminator of a better prognosis. Kaplan–Meier survival analysis showed that the expression of COL9A3 was significantly correlated with the overall survival of ESCC patients. The area under the curve for the risk model in predicting 1- and 3- year survival rates were 0.660 and 0.942, respectively. The risk score was negatively correlated with plasma cells, while positively correlated with the proportions of activated CD4 memory T cells, M1 Macrophages and M2 Macrophages (p < 0.001 for each comparison). Gene set enrichment analysis suggested that both immune response and immune system process gene sets were significantly enriched in high-risk group. Conclusions Our study provided a comprehensive understanding of the TME in ESCC patients. The establishment of the risk model is valuable for the early identification of high-risk patients to facilitate individualized treatment and improve the possibility of immunotherapy response.

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.

scholarly journals Mining of prognosis-related genes in cervical squamous cell carcinoma immune microenvironment

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9627 ◽  
Author(s):  
Jiong Ma ◽  
Pu Cheng ◽  
Xuejun Chen ◽  
Chunxia Zhou ◽  
Wei Zheng
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Enrichment Analysis ◽  
Malignant Tumour ◽  
Cervical Squamous Cell Carcinoma ◽  
Hpv Infection ◽  
The Cancer Genome Atlas ◽  
Immune Microenvironment ◽  
Scoring Method

Purpose The aim of this study was to explore the effective immune scoring method and mine the novel and potential immune microenvironment-related diagnostic and prognostic markers for cervical squamous cell carcinoma (CSSC). Materials and Methods The Cancer Genome Atlas (TCGA) data was downloaded and multiple data analysis approaches were initially used to search for the immune-related scoring system on the basis of Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data (ESTIMATE) algorithm. Afterwards, the representative genes in the gene modules correlated with immune-related scores based on ESTIMATE algorithm were further screened using Weighted Gene Co-expression Network Analysis (WGCNA) and network topology analysis. Gene functions were mined through enrichment analysis, followed by exploration of the correlation between these genes and immune checkpoint genes. Finally, survival analysis was applied to search for genes with significant association with overall survival and external database was employed for further validation. Results The immune-related scores based on ESTIMATE algorithm was closely associated with other categories of scores, the HPV infection status, prognosis and the mutation levels of multiple CSCC-related genes (HLA and TP53). Eighteen new representative immune microenvironment-related genes were finally screened closely associated with patient prognosis and were further validated by the independent dataset GSE44001. Conclusion Our present study suggested that the immune-related scores based on ESTIMATE algorithm can help to screen out novel immune-related diagnostic indicators, therapeutic targets and prognostic predictors in CSCC.

scholarly journals Profiles of Immune Cell Infiltration and Immune-Related Genes in the Tumor Microenvironment of Esophageal Squamous Cell Carcinoma

2020 ◽  
Author(s):  
Mingdi Liu ◽  
Faping Li ◽  
Bin Liu ◽  
Yongping Jian ◽  
Dan Zhang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Risk Model ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment

Abstract Backgrounds: As a complex system participating in tumor development and progression, the tumor microenvironment was poorly understood in esophageal cancer especially squamous cell carcinoma (ESCC).Methods: ESTIMATE algorithm is used to investigate tumor-infiltrating immune cells and prognostic genes which were associated with the tumor microenvironment in ESCC. Results: Based on the immune and stromal scores, ESCC samples were divided into high and low score groups and 299 overlapping differentially expressed genes were identified. Functional enrichment analysis showed that these genes were mainly involved in muscle-related function. Prognostic genes including COL9A3, GFRA2, and VSIG4 were used to establish a risk prediction model using Cox regression analyses. Then multivariate analysis showed that COL9A3 was an independent discriminator of a better prognosis. Kaplan-Meier survival analysis showed that the expression of COL9A3 was significantly correlated with the overall survival of ESCC patients. The area under the curve for the risk model in predicting 1- and 3- year survival rates were 0.660 and 0.942, respectively. The risk score was negatively correlated with plasma cells, while positively correlated with the proportions of activated CD4 memory T cells, M1 Macrophages and M2 Macrophages (P<0.001 for each comparison). Gene set enrichment analysis suggested that both immune response and immune system process gene sets were significantly enriched in high-risk group.Conclusions: Our study provided a comprehensive understanding of the TME in ESCC patients. The establishment of the risk model is valuable for the early identification of high-risk patients to facilitate individualized treatment and improve the possibility of immunotherapy response.

scholarly journals Prognostic Value of Tumor Mutational Burden Related to Immune Infiltration in Cervical Squamous Cell Carcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Fang Wen ◽  
Shuai Ruan ◽  
Wenjie Huang ◽  
Xiaoxue Chen ◽  
Yulan Wang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Cox Regression ◽  
Cervical Squamous Cell Carcinoma ◽  
Immune Checkpoint Blockade ◽  
Missense Mutations ◽  
Hub Genes ◽  
Immune Infiltration

Cervical squamous cell carcinoma is one of the most common causes of female cancer deaths worldwide. At present, immunotherapy using immune checkpoint blockade (ICB) has improved the prognosis of many cancer patients, and neoantigens generated by mutations may serve as potential biomarkers for predicting the outcome of ICB therapy. In this study, we identified missense mutations as the most frequent in landscapes of gene mutation in cervical squamous cell carcinoma (CESC) samples. Patients with higher tumor mutation burden (TMB) presented higher overall survival (OS). In addition, there was a significant correlation between the high TMB group and fractions of most immune cells. Univariate and multivariate Cox regression analyses identified five hub genes (IFNG, SERPINA3, CCL4L2, TNFSF15, and IL1R1) that were used to build a prognostic model. In the prognostic model, the low-risk group achieved better OS. Mutations in the five hub genes mainly affected the infiltration level of CD8+ T cells and dendritic cells. In conclusion, our study is valuable for exploring the role of TMB and its relationship with immune infiltration in CESC. Moreover, the prognosis model may help predict the sensitivity of patients to immunotherapy and provide underlying biomarkers for personalized immunotherapy.

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 Prognostic Gene Signature for Squamous Cell Carcinoma with a Higher Risk for Treatment Failure and Accelerated MEK-ERK Pathway Activity

Cancers ◽  
2021 ◽  
Vol 13 (20) ◽  
pp. 5182
Author(s):  
Bohai Feng ◽  
Kai Wang ◽  
Esther Herpel ◽  
Michaela Plath ◽  
Wilko Weichert ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Cox Regression ◽  
Human Cancer ◽  
Cancer Cell Line ◽  
The Cancer Genome Atlas ◽  
Mek Inhibitors ◽  
Prognostic Gene

Squamous cell carcinoma (SCC) is the most prevalent histological type of human cancer, including head and neck squamous cell carcinoma (HNSCC). However, reliable prognostic gene signatures for SCC and underlying genetic and/or epigenetic principles are still unclear. We identified 37 prognostic candidate genes by best cutoff computation based on survival in a pan-SCC cohort (n = 1334) of The Cancer Genome Atlas (TCGA), whose expression stratified not only the pan-SCC cohort but also independent HNSCC validation cohorts into three distinct prognostic subgroups. The most relevant prognostic genes were prioritized by a Least Absolute Shrinkage and Selection Operator Cox regression model and were used to identify subgroups with high or low risks for unfavorable survival. An integrative analysis of multi-omics data identified FN1, SEMA3A, CDH2, FBN1, COL5A1, and ADAM12 as key nodes in a regulatory network related to the prognostic phenotype. An in-silico drug screen predicted two MEK inhibitors (Trametinib and Selumetinib) as effective compounds for high-risk SCC based on the Cancer Cell Line Encyclopedia, which is supported by a higher p-MEK1/2 immunohistochemical staining of high-risk HNSCC. In conclusion, our data identified a molecular classifier for high-risk HNSCC as well as other SCC patients, who might benefit from treatment with MEK inhibitors.

scholarly journals Bioinformatic Analysis Reveals an Immune/Inflammatory-Related Risk Signature for Oral Cavity Squamous Cell Carcinoma

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Shuang Bai ◽  
Ying-Bin Yan ◽  
Wei Chen ◽  
Ping Zhang ◽  
Tong-Mei Zhang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Cavity ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Training Dataset ◽  
High Morbidity ◽  
Biological Processes

High-throughput gene expression profiling has recently emerged as a promising technique that provides insight into cancer subtype classification and improved prediction of prognoses. Immune/inflammatory-related mRNAs may potentially enrich genes to allow researchers to better illustrate cancer microenvironments. Oral cavity squamous cell carcinoma (OC-SCC) exhibits high morbidity and poor prognosis compared to that of other types of head and neck squamous cell carcinoma (HNSCC), and these differences may be partially due to differences within the tumor microenvironments. Based on this, we designed an immune-related signature to improve the prognostic prediction of OC-SCC. A cohort of 314 OC-SCC samples possessing whole genome expression data that were sourced from The Cancer Genome Atlas (TCGA) database was included for discovery. The GSE41613 database was used for validation. A risk score was established using immune/inflammatory signatures acquired from the training dataset. Principal components analysis, GO analysis, and gene set enrichment analysis were used to explore the bioinformatic implications. When grouped by the dichotomized risk score based on the signature, this classifier could successfully discriminate patients with distinct prognoses within the training and validation cohorts (P<0.05 in both cohorts) and within different clinicopathological subgroups. Similar somatic mutation patterns were observed between high and low risk score groups, and different copy number variation patterns were also identified. Further bioinformatic analyses suggested that the lower risk score group was significantly correlated with immune/inflammatory-related biological processes, while the higher risk score group was highly associated with cell cycle-related processes. The analysis indicated that the risk score was a robust predictor of patient survival, and its functional annotation was well established. Therefore, this bioinformatic-based immune-related signature suggested that the microenvironment of OC-SCC could distinguish among patients with different underlying biological processes and clinical outcomes, and the use of this signature may shed light on future OC-SCC classification and therapeutic design.

scholarly journals Upregulated Glycolysis Correlates With Clinical and Transcriptomic Significances in Head and Neck Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Hideyuki Takahashi ◽  
Reika Kawabata-Iwakawa ◽  
Shota Ida ◽  
Ikko Mito ◽  
Hiroe Tada ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Enrichment Analysis ◽  
Janus Kinase ◽  
Gene Set Enrichment Analysis ◽  
Neck Squamous Cell Carcinoma ◽  
Tumor Type ◽  
High Group

Abstract Altered metabolism is an emerging hallmark of cancer. Cancer cells preferentially utilize glycolysis for energy production, termed “aerobic glycolysis.” In this study, we performed a comprehensive analysis of the glycolysis status in the tumor microenvironment (TME) of head and neck squamous cell carcinoma (HNSCC) using data from The Cancer Genome Atlas database. We first divided 520 patients with HNSCC into two groups based on the mRNA expression of 16 glycolysis-related genes. The glycolysis-high signature positively correlated with human papillomavirus-negative tumor type, advanced T factor, and unfavorable prognosis. The gene set enrichment analysis revealed upregulation of several pathways, including interferon-alpha response, myc targets, hypoxia, epithelial-mesenchymal transition, transforming growth factor-β signaling, and interleukin 6-Janus kinase-signal transducer and activator of transcription 3 signaling, in the glycolysis-high group. Immune cell enrichment analysis revealed decreased infiltration of T cells, dendritic cells, and B cells in the glycolysis-high group, suggesting impaired tumor antigen presentation, T cell activation, and antibody production in TME. Moreover, the expression of TGFB1, CD274, and PDCD1LG2, which facilitate immunosuppression in the TME, was upregulated in the glycolysis-high group. Collectively, these findings suggest the potential of glycolysis monitoring as a biomarker for tumor progression and immunosuppression in the TME of HNSCC.

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