scholarly journals A novel prognostic prediction model based on seven immune-related RNAs for predicting overall survival of patients in early cervical squamous cell carcinoma

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Rui Qin ◽  
Lu Cao ◽  
Cong Ye ◽  
Junrong Wang ◽  
Ziqian Sun
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Cox Regression ◽  
Risk Groups ◽  
Cervical Squamous Cell Carcinoma ◽  
Regression Analyses ◽  
Prognostic Prediction ◽  
Immune Related Genes

Abstract Background In this study, we aimed to mine immune-related RNAs expressed in early cervical squamous cell carcinoma to construct prognostic prediction models. Methods The RNA sequencing data of 309 cervical squamous cell carcinoma (CSCC) cases, including data of individuals with available clinical information, were obtained from The Cancer Genome Atlas (TCGA) database. We included 181 early-stage CSCC tumor samples with clinical survival and prognosis information (training dataset). Then, we downloaded the GSE44001 gene expression profile data from the National Center for Biotechnology Information Gene Expression Omnibus (validation dataset). Gene ontology annotation and the Kyoto Encyclopedia of Genes and Genomes pathway analyses were used to analyze the biological functions of differentially expressed immune-related genes (DEIRGs). We established protein–protein interactions and competing endogenous RNA networks using Cytoscape. Using the Kaplan–Meier method, we evaluated the association between the high- and low-risk groups and the actual survival and prognosis information. Our univariate and multivariate Cox regression analyses screened for independent prognostic factors. Results We identified seven prognosis-related signature genes (RBAKDN, CXCL2, ZAP70, CLEC2D, CD27, KLRB1, VCAM1), the expression of which was markedly associated with overall survival (OS) in CSCC patients. Also, the risk score of the seven-gene signature discripted superior ability to categorize CSCC patients into high-risk and low-risk groups, with a observablydifferent OS in the training and validation datasets. We screened two independent prognostic factors (Pathologic N and prognostic score model status) that correlated significantly by univariate and multivariate Cox regression analyses in the TCGA dataset. To further explore the potential mechanism of immune-related genes, we observed associated essential high-risk genes with a cytokine–cytokine receptor interaction. Conclusions This study established an immune-related RNA signature, which provided a reliable prognostic tool and may be of great significance for determining immune-related biomarkers in CSCC.

scholarly journals A multi-lncRNA signature for suvival prediction in esophageal squamous cell carcinoma (ESCC) patients

2020 ◽  
Author(s):  
Lan zhang ◽  
Pan Li ◽  
Chenju Xing ◽  
Di Zhu ◽  
Jianying Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Prognostic Marker ◽  
Squamous Cell ◽  
Cox Regression ◽  
Risk Groups ◽  
Validation Dataset ◽  
Clinical Value

Abstract Background: The aim of this study was to identify prognostic long non-coding RNAs (lncRNAs) and develop a multi-lncRNA signature for suvival prediction in esophageal squamous cell carcinoma (ESCC) patients.Methods: The clinical and gene expression data from 301 ESCC patients were downloaded, including a corhort used as training set from Gene Expression Omnibus database (GSE53624, n=119), another cohort of 98 paired ESCC tumor and normal tissues as test set and an independent validation cohort including 84 ESCC tissues. Survival analyses, Cox regression and Kaplan–Meier analysis were used.Results: we screened a prognostic marker of ESCC from the GSE53624 dataset and named it as the five-lncRNA signature including AC007179.1, MORF4L2-AS1, RP11-488I20.9, RP13-30A9.2, RP4-735C1.6, which could classify patients into high- and low-risk groups with significantly different survival(median survival: 1.75 years vs. 4.01 years, log rank P<0.05). Then test dataset and validation dataset confirmed that the five-lncRNA signature can determine the prognosis of ESCC patients. Predictive independence of the prognostic marker was proved by multivariable Cox regression analyses in the three datasets (P<0.05). In addition, the signature was found to be better than TNM stage in terms of prognosis.Conclusion: The five-lncRNA signature could be a good prognostic biomarker for ESCC patients and has important clinical value.

scholarly journals Prognostic value of a five-lncRNA signature in esophageal squamous cell carcinoma

2020 ◽  
Author(s):  
Lan Zhang ◽  
Pan Li ◽  
Enjie Liu ◽  
Chenju Xing ◽  
Di Zhu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Prognostic Marker ◽  
Squamous Cell ◽  
Cox Regression ◽  
Risk Groups ◽  
Validation Dataset ◽  
Clinical Value

Abstract Background: The aim of this study was to identify prognostic long non-coding RNAs (lncRNAs) and develop a multi-lncRNA signature for suvival prediction in esophageal squamous cell carcinoma (ESCC). Methods: The clinical and gene expression data from Gene Expression Omnibus database (GSE53624, n=119) were obtianed as training set. A total of 98 paired ESCC tumor and normal tissues were detected by RNA sequencing and used as test set. Another 84 ESCC tissues were used for real-time quantitative PCR(qRT-PCR) and as an independent validation cohort. Survival analysis, Cox regression and Kaplan–Meier analysis were performed. Results: We screened a prognostic marker of ESCC from the GSE53624 dataset and named it as the five-lncRNA signature including AC007179.1, MORF4L2-AS1, RP11-488I20.9, RP13-30A9.2, RP4-735C1.6, which could classify patients into high- and low-risk groups with significantly different survival(median survival: 1.75 years vs. 4.01 years, log rank P<0.05). Then test dataset and validation dataset confirmed that the five-lncRNA signature can determine the prognosis of ESCC patients. Predictive independence of the prognostic marker was proved by multivariable Cox regression analyses in the three datasets (P<0.05). In addition, the signature was found to be better than TNM stage in terms of prognosis. Conclusion: The five-lncRNA signature could be a good prognostic biomarker for ESCC patients and has important clinical value.

scholarly journals Prognostic value of a five-lncRNA signature in esophageal squamous cell carcinoma (ESCC)

2020 ◽  
Author(s):  
Lan Zhang ◽  
Pan Li ◽  
Chenju Xing ◽  
Di Zhu ◽  
Jianying Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Prognostic Marker ◽  
Squamous Cell ◽  
Cox Regression ◽  
Risk Groups ◽  
Validation Dataset ◽  
Clinical Value

Abstract Background The aim of this study was to identify prognostic long non-coding RNAs (lncRNAs) and develop a multi-lncRNA signature for suvival prediction in esophageal squamous cell carcinoma (ESCC). Methods The clinical and gene expression data from Gene Expression Omnibus database (GSE53624, n = 119) were obtianed as training set. A total of 98 paired ESCC tumor and normal tissues were detected by RNA sequencing and used as test set. Another 84 ESCC tissues were used for real-time quantitative PCR(qRT-PCR) and as an independent validation cohort. Survival analyses, Cox regression and Kaplan–Meier analysis were performed. Results We screened a prognostic marker of ESCC from the GSE53624 dataset and named it as the five-lncRNA signature including AC007179.1, MORF4L2-AS1, RP11-488I20.9, RP13-30A9.2, RP4-735C1.6, which could classify patients into high- and low-risk groups with significantly different survival(median survival: 1.75 years vs. 4.01 years, log rank P < 0.05). Then test dataset and validation dataset confirmed that the five-lncRNA signature can determine the prognosis of ESCC patients. Predictive independence of the prognostic marker was proved by multivariable Cox regression analyses in the three datasets (P < 0.05). In addition, the signature was found to be better than TNM stage in terms of prognosis. Conclusion The five-lncRNA signature could be a good prognostic biomarker for ESCC patients and has important clinical value.

Prognostic significance of eight immune-related genes on survival in patients with lung squamous cell carcinoma

2021 ◽  
Vol 15 (4) ◽  
pp. 295-306
Author(s):  
Hansheng Wu ◽  
Shujie Huang ◽  
Weitao Zhuang ◽  
Guibin Qiao
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Differential Expression ◽  
Squamous Cell ◽  
Lung Squamous Cell Carcinoma ◽  
Risk Groups ◽  
Related Gene ◽  
Immune Related Gene ◽  
Immune Related Genes

Aim: To build a valid prognostic model based on immune-related genes for lung squamous cell carcinoma (LUSC). Materials & methods: Differential expression of immune-related genes between LUSC and normal specimens from TCGA dataset and underlying molecular mechanisms were systematically analyzed. Constructing and validating the high-risk and low-risk groups for LUSC survival. Results: The immune-related gene-based prognostic index (IRGPI) could predict the overall survival in patients with different clinicopathological characteristics. Functional enrichment analysis of differential expression of immune-related gene signature indicated distinctive molecular pathways between high-risk and low-risk groups. Conclusion: Analysis of IRGs in LUSC enable us to stratify patients into distinct risk groups, which may help to screen LUSC patients at risk and decision making on follow-up therapeutic intervention.

scholarly journals Intravesical Therapy for Non-Muscle-Invasive Bladder Cancer: What Is the Real Impact of Squamous Cell Carcinoma Variant on Oncological Outcomes?

Medicina ◽  
2022 ◽  
Vol 58 (1) ◽  
pp. 90
Author(s):  
Guglielmo Mantica ◽  
Francesco Chierigo ◽  
Rafaela Malinaric ◽  
Salvatore Smelzo ◽  
Francesca Ambrosini ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Bladder Cancer ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Cox Regression ◽  
Disease Recurrence ◽  
Intravesical Therapy ◽  
Regression Analyses ◽  
Muscle Invasive Bladder Cancer ◽  
Muscle Invasive

Background and Objectives: To evaluate the oncological impact of squamous cell carcinoma (SCC) variant in patients submitted to intravesical therapy for non-muscle-invasive bladder cancer (NMIBC). Materials and Methods: Between January 2015 and January 2020, patients with conventional urothelial NMIBC (TCC) or urothelial NMIBC with SCC variant (TCC + SCC) and submitted to adjuvant intravesical therapies were collected. Kaplan–Meier analyses targeted disease recurrence and progression. Uni- and multivariable Cox regression analyses were used to test the role of SCC on disease recurrence and/or progression. Results: A total of 32 patients out of 353 had SCC at diagnosis. Recurrence was observed in 42% of TCC and 44% of TCC + SCC patients (p = 0.88), while progression was observed in 12% of both TCC and TCC + SCC patients (p = 0.78). At multivariable Cox regression analyses, the presence of SCC variant was not associated with higher rates of neither recurrence (p = 0.663) nor progression (p = 0.582). Conclusions: We presented data from the largest series on patients with TCC and concomitant SCC histological variant managed with intravesical therapy (BCG or MMC). No significant differences were found in term of recurrence and progression between TCC and TCC + SCC. Despite the limited sample size, this study paves the way for a possible implementation of the use of intravesical BCG and MMC in NMIBC with histological variants.

scholarly journals Prognostic Signatures Based on Ferroptosis- and Immune-Related Genes for Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma

2022 ◽  
Vol 11 ◽  
Author(s):  
Chaoqun Xing ◽  
Huiming Yin ◽  
Zhi-Yong Yao ◽  
Xiao-Liang Xing
Keyword(s):  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
Prediction Model ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Female Genital Tract ◽  
Cervical Squamous Cell Carcinoma ◽  
Assessment Model ◽  
Endocervical Adenocarcinoma ◽  
Immune Related Genes

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) are among the most common malignancies of the female genital tract. Ferroptosis and immunity regulate each other and play important roles in the progression of CESC. The present study aimed to screen ferroptosis- and immune-related differentially expressed genes (FI-DEGs) to identify suitable prognostic signatures for patients with CESC. We downloaded the RNAseq count data and corresponding clinical information of CESC patients from The Cancer Genome Atlas database; obtained recognized ferroptosis- and immune-related genes from the FerrDb and ImmPort databases, respectively; and screened for suitable prognostic signatures using a series of bioinformatics analyses. We identified eight FI-DEGs (CALCRL, CHIT1, DES, DUOX1, FLT1, HELLS, SCD, and SDC1) that were independently correlated with the overall survival of patients with CESC. The prediction model constructed using these eight FI-DEGs was also independently correlated with overall survival. Both the sensitivity and specificity of the prediction model constructed using these eight signatures were over 60%. The comprehensive index of ferroptosis and immune status was significantly correlated with the immunity of patients with CESC. In conclusion, the risk assessment model constructed with these eight FI-DEGs predicted the CESC outcomes. Therefore, these eight FI-DEGs could serve as prognostic signatures for CESC.

Prognostic values of lymphocyte and eosinophil counts in resectable cervical squamous cell carcinoma

2019 ◽  
Vol 15 (30) ◽  
pp. 3467-3481 ◽  
Author(s):  
Jie Zhu ◽  
Han Wang ◽  
Min-Jie Gao ◽  
Yi-Fan Li ◽  
Yue-Qing Huang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Cox Regression ◽  
Cell Cancer ◽  
Progression Free Survival ◽  
Cervical Squamous Cell Carcinoma ◽  
Analysis Model ◽  
Cox Regression Analysis ◽  
Cell Parameters

Aim: Cervical cancer is one of the leading causes of cancer mortality in women. Peripheral white blood cell parameters such as neutrophil (NE), eosinophil (EO), basophil (BA), as well as lymphocyte (LY) and monocyte (MO), are correlated with tumor outcomes. Methods: In total, 110 cervical squamous cell carcinoma patients were recruited in this study. The potential prognostic factors were evaluated by univariate and multivariate survival analysis. Results: Cox regression analysis model indicated that higher pretreatment EO level and increased post-/preradiotherapy EO ratio were independently associated with worse progression-free survival. Lower pretreatment LY or higher EO levels and increased post-/preradiotherapy EO ratio were independently associated with worse overall survival. Conclusion: LY and EO are correlated with outcomes of cervical squamous cell cancer.

scholarly journals A Novel Immune-Related Prognostic Signature in Head and Neck Squamous Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Yi Zhang ◽  
Ping Chen ◽  
Qiang Zhou ◽  
Hongyan Wang ◽  
Qingquan Hua ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Neck Squamous Cell Carcinoma ◽  
Related Gene ◽  
Gene Signatures ◽  
Immune Related Gene ◽  
Immune Related Genes

The immune response within the tumor microenvironment plays a key role in tumorigenesis and determines the clinical outcomes of head and neck squamous cell carcinoma (HNSCC). However, to date, very limited robust and reliable immunological biomarkers have been developed that are capable of estimating prognosis in HNSCC patients. In this study, we aimed to identify the effects of novel immune-related gene signatures (IRGs) that can predict HNSCC prognosis. Based on gene expression profiles and clinical data of HNSCC patient cohorts from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, a total of 439 highly variable expressed immune-related genes (including 239 upregulated and 200 downregulated genes) were identified by using differential gene expression analysis. Pathway enrichment analysis indicated that these immune-related differentially expressed genes were enriched in inflammatory functions. After process screening in the training TCGA cohort, six immune-related genes (PLAU, STC2, TNFRSF4, PDGFA, DKK1, and CHGB) were significantly associated with overall survival (OS) based on the LASSO Cox regression model. Integrating these genes with clinicopathological features, a multivariable model was built and suggested better performance in determining patients’ OS in the testing cohort, and the independent validation cohort. In conclusion, a well-established model encompassing both immune-related gene signatures and clinicopathological factors would serve as a promising tool for the prognostic prediction of HNSCC.

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