scholarly journals Detection of differentially expressed genes and association with clinicopathological features in laryngeal squamous cell carcinoma

2012 ◽  
Vol 4 (6) ◽  
pp. 1354-1360 ◽  
Author(s):  
RONG SHENG NI ◽  
XIAOHUI SHEN ◽  
XIAOYUN QIAN ◽  
CHENJIE YU ◽  
HAIYAN WU ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Squamous Cell ◽  
Laryngeal Squamous Cell Carcinoma ◽  
Clinicopathological Features ◽  
Differentially Expressed

scholarly journals Differentially expressed genes and lincRNAs throughout oral squamous cell carcinoma development

2012 ◽  
Vol 26 (S1) ◽  
Author(s):  
João Paulo Oliveira-Costa ◽  
Alex Fiorini Carvalho ◽  
Silvia Vanessa Lourenco ◽  
Luiz Paulo Kowalski ◽  
Dirce Maria Carraro ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Squamous Cell ◽  
Differentially Expressed

scholarly journals A Novel Signature Derived from Metabolism-Related Genes GPT and SMS to Predict Prognosis of Laryngeal Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Yujie Shen ◽  
Qiang Huang ◽  
Yifan Zhang ◽  
Chi-Yao Hsueh ◽  
Liang Zhou
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Laryngeal Squamous Cell Carcinoma ◽  
Cox Regression ◽  
External Validation ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Clinical Samples ◽  
Prognostic Signature

Abstract Background A growing body of evidence has suggested the involvement of metabolism in the occurrence and development of tumors. But the link between metabolism and laryngeal squamous cell carcinoma (LSCC) has rarely been reported. This study seeks to understand and explain the role of metabolic biomarkers in predicting the prognosis of LSCC. Methods We identified the differentially expressed metabolism-related genes (MRGs) through RNA-seq data of TCGA (The Cancer Genome Atlas) and GSEA (Gene set enrichment analysis). After the screening of protein-protein interaction (PPI), hub MRGs were analyzed by least absolute shrinkage and selection operator (LASSO) and Cox regression analyses to construct a prognostic signature. Kaplan–Meier survival analysis and the receiver operating characteristic (ROC) was applied to verify the effectiveness of the prognostic signature in four cohorts (TCGA cohort, GSE27020 cohort, TCGA-sub1 cohort and TCGA-sub2 cohort). The expressions of the hub MRGs in cell lines and clinical samples were verified by quantitative reverse transcriptase PCR (qRT-PCR). The immunofluorescence staining of the tissue microarray (TMA) was carried out to further verify the reliability and validity of the prognostic signature. Cox regression analysis was then used to screen for independent prognostic factors of LSCC and a nomogram was constructed based on the results. Results Among the 180 differentially expressed MRGs, 14 prognostic MRGs were identified. A prognostic signature based on two MRGs (GPT and SMS) was then constructed and verified via internal and external validation cohorts. Compared to the adjacent normal tissues, SMS expression was higher while GPT expression was lower in LSCC tissues, indicating poorer outcomes. The risk score proved the prognostic signature as an independent risk factor for LSCC in both internal and external validation cohorts. A nomogram based on these results was developed for clinical application. Conclusions Differentially expressed MRGs were found and proven to be related to the prognosis of LSCC. We constructed a novel prognostic signature based on MRGs in LSCC for the first time and verified via different cohorts from both databases and clinical samples. A nomogram based on this prognostic signature was developed.

Development of an immunogenomics-based prognostic index model of laryngeal squamous cell carcinoma

2020 ◽  
Author(s):  
Yujie Shen ◽  
Han Zhou ◽  
Shikun Dong ◽  
Meiping Lu ◽  
Weida Dong ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Laryngeal Squamous Cell Carcinoma ◽  
Cox Regression ◽  
Prognostic Index ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Cox Regression Analysis

Abstract Background: The immune system greatly affects the prognosis of various malignancies. Studies on differentially expressed immune-related genes (IRGs) in the immune microenvironment of laryngeal squamous cell carcinoma (LSCC) have rarely been reported.Methods: In this paper, the prognostic potentials of IRGs in LSCC were explored. The RNAseq dataset containing differentially expressed IRGs and corresponding clinical information of LSCC patients was obtained from The Cancer Genome Atlas (TCGA). A total of 371 up-regulated and 61 down-regulated IRGs were identified. Subsequent functional enrichment analysis revealed that the pathway of IRGs was mainly enriched in the cytokine-cytokine receptor interaction. Then, 30 IRGs with prognostic potentials in LSCC were screened out, and the regulatory network induced by relevant transcription factors (TFs) were constructed.Results: Finally, multivariate Cox regression analysis was conducted to assess the prognostic potential of 15 IRGs after adjustment of clinical factors and LSCC patients were classified into 2 subgroups based on different outcomes. The gene expression of the model was verified by other independent databases. Nomogram including the 15 IRGs signature was established and shown some clinical net beneft. Intriguingly, B cells were significantly enriched in the low-risk group. Conclusion:These findings may contribute to the development of potential therapeutic targets and biomarkers for the new-immunotherapy of LSCC.

Sign in / Sign up

Export Citation Format

Share Document