scholarly journals Identification of Key Genes and Pathways Associated With Paclitaxel Resistance in Esophageal Squamous Cell Carcinoma Based on Bioinformatics Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhimin Shen ◽  
Mingduan Chen ◽  
Fei Luo ◽  
Hui Xu ◽  
Peipei Zhang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Differential Expression Analysis ◽  
Biological Significance ◽  
The Cancer Genome Atlas ◽  
Paclitaxel Resistance ◽  
Bioinformatics Analyses ◽  
Key Genes

Esophageal squamous cell carcinoma (ESCC) ranks as the fourth leading cause of cancer-related death in China. Although paclitaxel has been shown to be effective in treating ESCC, the prolonged use of this chemical will lead to paclitaxel resistance. In order to uncover genes and pathways driving paclitaxel resistance in the progression of ESCC, bioinformatics analyses were performed based on The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database including GSE86099 and GSE161533. Differential expression analysis was performed in TCGA data and two GEO datasets to obtain differentially expressed genes (DEGs). Based on GSE161533, weighted gene co-expression network analysis (WGCNA) was conducted to identify the key modules associated with ESCC tumor status. The DEGs common to the two GEO datasets and the genes in the key modules were intersected to obtain the paclitaxel resistance-specific or non-paclitaxel resistance-specific genes, which were subjected to subsequent least absolute shrinkage and selection operator (LASSO) feature selection, whereby paclitaxel resistance-specific or non-paclitaxel resistance-specific key genes were selected. Ten machine learning models were used to validate the biological significance of these key genes; the potential therapeutic drugs for paclitaxel resistance-specific genes were also predicted. As a result, we identified 24 paclitaxel resistance-specific genes and 18 non-paclitaxel resistance-specific genes. The ESCC machine classifiers based on the key genes achieved a relatively high AUC value in the cross-validation and in an independent test set, GSE164158. A total of 207 drugs (such as bevacizumab) were predicted to be alternative therapeutics for ESCC patients with paclitaxel resistance. These results might shed light on the in-depth research of paclitaxel resistance in the context of ESCC progression.

scholarly journals Biological Significance of Tumor Heterogeneity in Esophageal Squamous Cell Carcinoma

Cancers ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1156 ◽  
Author(s):  
Lehang Lin ◽  
De-Chen Lin
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Tumor Heterogeneity ◽  
Three Dimensional ◽  
Biological Significance ◽  
Molecular Characteristics ◽  
Tumor Evolution ◽  
Evolutionary Trajectories

Esophageal squamous cell carcinoma (ESCC) is a common and aggressive malignancy, with hitherto dismal clinical outcome. Genomic analyses of patient samples reveal a complex heterogeneous landscape for ESCC, which presents in both intertumor and intratumor forms, manifests at both genomic and epigenomic levels, and contributes significantly to tumor evolution, drug resistance, and metastasis. Here, we review the important molecular characteristics underlying ESCC heterogeneity, with an emphasis on genomic aberrations and their functional contribution to cancer evolutionary trajectories. We further discuss how novel experimental tools, including single-cell sequencing and three-dimensional organoids, may advance our understanding of tumor heterogeneity. Lastly, we suggest that deciphering the mechanisms governing tumor heterogeneity holds the potential to developing precision therapeutics for ESCC patients.

scholarly journals Autophagy-Related Three-Gene Prognostic Signature for Predicting Survival in Esophageal Squamous Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Heyang Cui ◽  
Yongjia Weng ◽  
Ning Ding ◽  
Chen Cheng ◽  
Longlong Wang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Discovery Cohort ◽  
Cox Regression Analysis

Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive malignant tumors in China, and its prognosis remains poor. Autophagy is an evolutionarily conserved catabolic process involved in the occurrence and development of ESCC. In this study, we described the expression profile of autophagy-related genes (ARGs) in ESCC and developed a prognostic prediction model for ESCC patients based on the expression pattern of ARGs. We used four ESCC cohorts, GSE53624 (119 samples) set as the discovery cohort, The Cancer Genome Atlas (TCGA) ESCC set (95 samples) as the validation cohort, 155 ESCC cohort, and Oncomine cohort were used to screen and verify differentially expressed ARGs. We identified 34 differentially expressed genes out of 222 ARGs. In the discovery cohort, we divided ESCC patients into three groups that showed significant differences in prognosis. Then, we analyzed the prognosis of 34 differentially expressed ARGs. Three genes [poly (ADP-ribose) polymerase 1 (PARP1), integrin alpha-6 (ITGA6), and Fas-associated death domain (FADD)] were ultimately obtained through random forest feature selection and were constructed as an ARG-related prognostic model. This model was further validated in TCGA ESCC set. Cox regression analysis confirmed that the three-gene signature was an independent prognostic factor for ESCC patients. This signature effectively stratified patients in both discovery and validation cohorts by overall survival (P = 5.162E-8 and P = 0.052, respectively). We also constructed a clinical nomogram with a concordance index of 0.713 to predict the survival possibility of ESCC patients by integrating clinical characteristics and the ARG signature. The calibration curves substantiated fine concordance between nomogram prediction and actual observation. In conclusion, we constructed a new ARG-related prognostic model, which shows the potential to improve the ability of individualized prognosis prediction in ESCC.

scholarly journals Expression and biological significance of matrix metalloprofeinase inhibitor RECK gene in esophageal squamous cell carcinoma

2008 ◽  
Vol 16 (15) ◽  
pp. 1634
Author(s):  
Dong-Ling Gao ◽  
Sheng-Lei Li ◽  
Kui-Sheng Chen ◽  
Zhi-Hua Zhao ◽  
Qiu-Min Zhao ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Biological Significance

scholarly journals Single-cell transcriptomic analysis reveals the critical molecular pattern of UV-induced cutaneous squamous cell carcinoma

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Guorong Yan ◽  
Liang Li ◽  
Sibo Zhu ◽  
Yuhao Wu ◽  
Yeqiang Liu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Gene Family ◽  
Cell Carcinoma ◽  
Single Cell ◽  
Squamous Cell ◽  
Differential Expression Analysis ◽  
Cutaneous Squamous Cell Carcinoma ◽  
Gene Set Enrichment Analysis ◽  
Bioinformatics Analyses ◽  
Molecular Pattern

AbstractCutaneous squamous cell carcinoma (cSCC) is the second most common nonmelanoma skin cancer characterized by high invasiveness, heterogeneity, and mainly occurs in the ultraviolet (UV)-exposed regions of the skin, but its pathogenesis is still unclear. Here, we generated single-cell transcriptome profiles for 350 cells from six primary UV-induced cSCCs, together with matched adjacent skin samples, and three healthy control skin tissues by single-cell RNA-sequencing technology based on Smart-seq2 strategy. A series of bioinformatics analyses and in vitro experiments were used to decipher and validate the critical molecular pattern of cSCC. Results showed that cSCC cells and normal keratinocytes were significantly distinct in gene expression and chromosomal copy number variation. Furthermore, cSCC cells exhibited 18 hallmark pathways of cancer by gene set enrichment analysis. Differential expression analysis demonstrated that many members belonging to S100 gene family, SPRR gene family, and FABP5 were significantly upregulated in cSCC cells. Further experiments confirmed their upregulation and showed that S100A9 or FABP5 knockdown in cSCC cells inhibited their proliferation and migration through NF-κB pathway. Taken together, our data provide a valuable resource for deciphering the molecular pattern in UV-induced cSCC at a single-cell level and suggest that S100A9 and FABP5 may provide novel targets for therapeutic intervention of cSCC in the future.

scholarly journals Overexpression of long noncoding RNA LINC01419 in esophageal squamous cell carcinoma and its relation to the sensitivity to 5-fluorouracil by mediating GSTP1 methylation

2019 ◽  
Vol 11 ◽  
pp. 175883591983895 ◽  
Author(s):  
Jian-Liang Chen ◽  
Zhi-Xiong Lin ◽  
Yun-Sheng Qin ◽  
Yu-Qi She ◽  
Yun Chen ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Noncoding Rna ◽  
Dna Methyltransferase ◽  
The Cancer Genome Atlas ◽  
Aberrant Expression ◽  
Tissue Samples ◽  
Enhanced Sensitivity

Background: Genome-wide sequencing investigations have identified numerous long noncoding RNAs (lncRNAs) among mammals, many of which exhibit aberrant expression in cancers, including esophageal squamous cell carcinoma (ESCC). Herein, this study elucidates the role and mechanism by which LINC01419 regulates the DNA methylation of glutathione S-transferase pi 1 (GSTP1) in relation to ESCC progression and the sensitivity of ESCC cells to 5-fluorouracil (5-FU). Methods: LINC01419 and GSTP1 levels were quantified among 38 paired ESCC and adjacent tissue samples collected from patients with ESCC. To ascertain the contributory role of LINC01419 in the progression of ESCC and identify the interaction between LINC01419 and GSTP1 promoter methylation, LINC01419 was overexpressed or silenced, and the DNA methyltransferase inhibitor 5-Aza-CdR was treated. Results: Data from the GEO database (GSE21362) and the Cancer Genome Atlas displayed elevated levels of LINC01419 and downregulated levels of GSTP1 in the ESCC tissues and cells. The silencing of LINC01419 led to decreased proliferation, increased apoptosis, and enhanced sensitivity to 5-FU in ESCC cells. Notably, LINC01419 could bind to the promoter region of the GSTP1 gene, resulting in elevated GSTP1 methylation and reduced GSTP1 levels via the recruitment of DNA methyltransferase among ESCC cells, whereby ESCC progression was stimulated accompanied by reduced ESCC cell sensitivity to 5-FU. GSTP1 demethylation by 5-Aza-CdR was observed to reverse the effects of LINC01419 overexpression in ESCC cells and the response to 5-FU. Conclusion: Highly expressed LINC01419 in ESCC promotes GSTP1 methylation, which ultimately acts to promote the event of ESCC and diminish the sensitivity of ESCC cells to 5-FU, highlighting a novel potential strategy to improve 5-FU-based chemotherapy in ESCC.

scholarly journals Competitive Endogenous RNA Network Construction and Comparison of Lung Squamous Cell Carcinoma in Smokers and Nonsmokers

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Yan Yao ◽  
Tingting Zhang ◽  
Lingyu Qi ◽  
Ruijuan Liu ◽  
Gongxi Liu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Molecular Mechanisms ◽  
Differential Expression Analysis ◽  
Lung Squamous Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cerna Network

Background. Lung squamous cell carcinoma (LUSC) is a subtype of highly malignant lung cancer with poor prognosis, for which smoking is the main risk factor. However, the underlying genetic and molecular mechanisms of smoking-related LUSC remain largely unknown. Methods. We mined existing LUSC-related mRNA, miRNA, and lncRNA transcriptome data and corresponding clinical data from The Cancer Genome Atlas (TCGA) database and divided them into smoking and nonsmoking groups, followed by differential expression analysis. Functional enrichment analysis of the unique differentially expressed mRNAs of the two groups was performed using the DAVID database. Subsequently, the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network of LUSC in smoking and nonsmoking groups was constructed. Finally, survival analyses were performed to determine the effects of differentially expressed lncRNAs/mRNAs/miRNAs that were involved in the ceRNA network on overall survival and to discover the hub genes. Results. A total of 1696 lncRNAs, 125 miRNAs, and 3246 mRNAs and 1784 lncRNAs, 96 miRNAs, and 3229 mRNAs with differentially expressed profiles were identified in the smoking and nonsmoking groups, respectively. The ceRNA network and survival analysis revealed four lncRNAs (LINC00466, DLX6-AS1, LINC00261, and AGBL1), one miRNA (hsa-mir-210), and two mRNAs (CITED2 and ENPP4), with the potential as biomarkers for smoking-related LUSC diagnosis and prognosis. Conclusion. Taken together, our research has identified the differences in the ceRNA regulatory networks between smoking and nonsmoking LUSC, which could lay the foundation for future clinical research.

scholarly journals BAG2 overexpression correlates with growth and poor prognosis of esophageal squamous cell carcinoma

2018 ◽  
Vol 13 (1) ◽  
pp. 582-588
Author(s):  
Ying-Cai Hong ◽  
Zheng Wang ◽  
Bin Peng ◽  
Li-Gang Xia ◽  
Lie-Wen Lin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Proliferation ◽  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
The Cancer Genome Atlas ◽  
Cell Counting ◽  
Migration And Invasion ◽  
Small Interference Rna

AbstractPrevious studies have suggested that Bcl2-associated athanogene 2 (BAG2) serves as a crucial regulator for tumorigenesis in multiple tumors. However, little is known about the effect of BAG2 on esophageal squamous cell carcinoma (ESCC). This study focused on investigating whether BAG2 functions as a cancer-promoting gene in ESCC. In this work, gene expression data and clinical information from the NCBI Gene Expression Omnibus (GEO), Oncomine and The Cancer Genome Atlas (TCGA) were collected and analyzed. Expression of BAG2 in ESCC was determined using quantitative reverse transcription polymerase chain reaction (qRT-PCR). BAG2 was knocked down using small interference RNA (si-RNA) approach. Cell proliferation, migration and invasion were assessed by Cell Counting Kit-8 (CCK-8) and transwell assays. Molecular mechanism was detected by western blotting assay. The expression of BAG2 both in ESCC tissues and cells was upregulated and overexpression was associated with worsened prognosis. BAG2 silencing inhibited ESCC cell proliferation, migration and invasion, which was regulated by the phosphatidylinositol-3-kinase (PI3K)/ protein kinase B (AKT) signaling pathway. These results reveal contributions of BAG2 as a predictor and potential therapeutic target in ESCC.

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