Bioinformatics analysis of gene expression profiles of esophageal squamous cell carcinoma

2017 ◽  
Vol 30 (5) ◽  
pp. 1-8 ◽  
Author(s):  
Y. He ◽  
J. Liu ◽  
Z. Zhao ◽  
H. Zhao
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles

scholarly journals Review and screening of key genes in esophageal squamous cell carcinoma

2021 ◽  
Author(s):  
Xizi Sun
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Expression Omnibus ◽  
P53 Signaling

Abstract Esophageal squamous cell carcinoma (ESCC) is the most common type of human esophageal cancer with high mortality due to late stage diagnosis. Efforts have been made to figure out the genetic events underlying its carcinogenesis and progression, but the molecular mechanisms of these processes remain elusive. To identify the candidate genes involved in ESCC, literature about significantly mutated genes (SMGs) was extensively reviewed and gene expression profiles of GSE161533, GSE20347 and GSE77861 were downloaded from the Gene Expression Omnibus (GEO) database. Following the identification of 230 differentially expressed genes (DEGs), hub gene identification was performed by the plug-in MCODE in Cytoscape software. 14 hub genes were identified which were enriched in cell cycle, DNA replication and p53 signaling pathway. In summary, genes mentioned in this study may provide potential targets for treatment and diagnosis of ESCC and help us better understand the pathogenesis and progression of ESCC from genetic perspective.

scholarly journals A comparative Analysis by SAGE of Gene Expression Profiles of Esophageal Adenocarcinoma and Esophageal Squamous Cell Carcinoma

2008 ◽  
Vol 30 (1) ◽  
pp. 63-75
Author(s):  
Jantine W. P. M. van Baal ◽  
Francesco Milana ◽  
Agnieszka M. Rygiel ◽  
Carine M. T. Sondermeijer ◽  
C. Arnold Spek ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Esophageal Adenocarcinoma ◽  
Squamous Cell ◽  
Squamous Epithelium ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Annexin A10

Esophageal adenocarcinoma (EA) and esophageal squamous cell carcinoma (ESCC) are the two main types of esophageal cancer. Despite extensive research the exact molecular basis of these cancers is unclear. Therefore we evaluated the transcriptome of EA in comparison to non-dysplastic Barrett’s esophagus (BE), the metaplastic epithelium that predisposes for EA, and compared the transcriptome of ESCC to normal esophageal squamous epithelium. For obtaining the transcriptomes tissue biopsies were used and serial analysis of gene expression (SAGE) was applied. Validation of results by RT-PCR and immunoblotting was performed using tissues of an additional 23 EA and ESCC patients. Over 58,000 tags were sequenced. Between EA and BE 1013, and between ESCC and normal squamous epithelium 1235 tags were significantly differentially expressed (p < 0.05). The most up-regulated genes in EA compared to BE were SRY-box 4 and Lipocalin2, whereas the most down-regulated genes in EA were Trefoil factors and Annexin A10. The most up-regulated genes in ESCC compared to normal squamous epithelium were BMP4, E-Cadherin and TFF3. The results could suggest that the BE expression profile is closer related to normal squamous esophagus then to EA. In addition, several uniquely expressed genes are identified.

scholarly journals Identification of tumor-infiltrating lymphocyte subpopulations correlated with patient prognosis in esophageal squamous cell carcinoma

2021 ◽  
Vol 49 (5) ◽  
pp. 030006052110162
Author(s):  
Lin Peng ◽  
Wenwu He ◽  
Feng Ye ◽  
Yane Song ◽  
Xinying Shi ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Suppressor Cells ◽  
Enrichment Analysis ◽  
Postoperative Chemotherapy ◽  
Th2 Cells

Objective To identify biomarkers related to esophageal squamous cell carcinoma (ESCC) prognosis by analyzing genetic variations and the infiltration levels of tumor-infiltrating lymphocytes (TILs) in patients. Methods The clinical features of 61 patients with ESCC were collected. DNA panel sequencing was performed to screen differentially expressed genes (DEGs). Transcriptome sequencing was performed to identify gene expression profiles, and subsequent enrichment analysis of DEGs was conducted using Metascape. Results We identified 488 DEGs between patients with ESCC with distinct prognoses that were mainly enriched in the human immune response, fibrinogen complex, and protein activation cascade pathways. Among patients with ESCC treated with postoperative chemotherapy, those with a high infiltration level of myeloid-derived suppressor cells (MDSCs) had longer overall survival (OS), and OS was positively correlated with the infiltration level of T helper type 2 (Th2) cells among patients treated without chemotherapy after surgery. Additionally, in the case of MDSCs >0.7059 or Th2 cells <0.6290, patients receiving postoperative chemotherapy had a longer OS than those treated without chemotherapy following surgery. Conclusion The level of MDSCs or Th2 cells can be used as a biomarker for assessing the prognosis of patients with ESCC treated with or without postoperative chemotherapy, respectively.

scholarly journals Weighted gene expression profiles identify diagnostic and prognostic genes for lung adenocarcinoma and squamous cell carcinoma

2019 ◽  
Vol 48 (3) ◽  
pp. 030006051989383 ◽  
Author(s):  
Xing Wu ◽  
Linlin Wang ◽  
Fan Feng ◽  
Suyan Tian
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Squamous Cell Carcinoma ◽  
Lung Adenocarcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Prognostic Signature ◽  
Diagnostic Signature

Objective To construct a diagnostic signature to distinguish lung adenocarcinoma from lung squamous cell carcinoma and a prognostic signature to predict the risk of death for patients with nonsmall-cell lung cancer, with satisfactory predictive performances, good stabilities, small sizes and meaningful biological implications. Methods Pathway-based feature selection methods utilize pathway information as a priori to provide insightful clues on potential biomarkers from the biological perspective, and such incorporation may be realized by adding weights to test statistics or gene expression values. In this study, weighted gene expression profiles were generated using the GeneRank method and then the LASSO method was used to identify discriminative and prognostic genes. Results The five-gene diagnostic signature including keratin 5 ( KRT5), mucin 1 ( MUC1), triggering receptor expressed on myeloid cells 1 ( TREM1), complement C3 ( C3) and transmembrane serine protease 2 ( TMPRSS2) achieved a predictive error of 12.8% and a Generalized Brier Score of 0.108, while the five-gene prognostic signature including alcohol dehydrogenase 1C (class I), gamma polypeptide ( ADH1C), alpha-2-glycoprotein 1, zinc-binding ( AZGP1), clusterin ( CLU), cyclin dependent kinase 1 ( CDK1) and paternally expressed 10 ( PEG10) obtained a log-rank P-value of 0.03 and a C-index of 0.622 on the test set. Conclusions Besides good predictive capacity, model parsimony and stability, the identified diagnostic and prognostic genes were highly relevant to lung cancer. A large-sized prospective study to explore the utilization of these genes in a clinical setting is warranted.

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