Transcripto‐based network analysis reveals a model of gene activation in tongue squamous cell carcinomas

Zeng, Hao; Li, Hui; Zhao, Ying; Chen, Linyan; Ma, Xuelei

doi:10.1002/hed.25952

Cited by 10 publications

(12 citation statements)

References 50 publications

(112 reference statements)

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“…Furthermore, high expression of TSHZ3 predicts poor prognosis in those two cancers. Our findings are in consistence with the previous studies [20]. Since the TSHZ3 expression levels in different cancer types remain controversial, we also conducted metaanalysis with Oncomine to provide more convinced evidence on the expression levels of TSHZ3 in different cancer types.…”

Section: Discussionsupporting

confidence: 89%

“…TSHZ3 is a driver of the 19q12 amplicon and the silencing of TSHZ3 is selectively lethal in breast cancer cells harbouring its amplification [30]. Additionally, high expression level of TSHZ3 predicts poor prognosis in tongue squamous cell carcinomas by slight correlation with immune infiltration [20]. Here, we report that TSHZ3 expression is up-regulated in many cancer types, such as STAD and BLCA.…”

Section: Discussionmentioning

confidence: 65%

“…Moreover, TSHZ3 also functions as tumor suppressor in brain glioma and ovarian cancer but as it is an oncogene in breast cancer [17][18][19]. A recent study suggests that TSHZ3 predict poor prognosis in tongue squamous cell carcinomas because it modulates the immune infiltration [20]. However, the role of TSHZ3 in other cancer growth and the underlying mechanism of action is not known.…”

Section: Introductionmentioning

confidence: 99%

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TSHZ3 is A Prognostic Biomarker with Immune Infiltration in Stomach Adenocarcinoma and Bladder Urothelial Carcinoma

Zhang

Wang

et al. 2020

Preprint

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Background: This study aimed to investigate the expressions of Teashirt zinc finger homeobox 3 (TSHZ3) in different cancer types and identify the cancers of which prognosis can be predicted by TSHZ3 expression. Furthermore, we aimed to explore the correlations between tumor-infiltrating immune cells (TIICs) and TSHZ3 expression in these cancers.Methods: TSHZ3 expression was analyzed by the Oncomine database and Gene Expression Profiling Interactive Analysis (GEPIA). We examined the influence of TSHZ3 on the clinical prognosis with Kaplan-Meier plotter and TIMER (Tumor Immune Estimation Resource). The correlations between tumor immune infiltrates and TSHZ3 expressions were investigated with TIMER and validated by GEPIA.Results: TSHZ3 expressions were significantly higher in stomach adenocarcinoma (STAD) and bladder urothelial carcinoma (BLCA) when compared to normal tissues. Survival analysis results showed that high TSHZ3 expression was correlated with poor overall survival (OS) in STAD and BLCA. The infiltrations of pro-tumorigenic TIICs (M2 macrophages, monocytes, B cells and pDCs) were positively correlated with TSHZ3 expression in STAD and BLCA. Besides, the infiltration of other pro-tumorigenic TIICs (tumor-associated macrophages (TAMs), Th2 cells and Tregs) and expression of T cell exhaustion markers (PD-1 and TIM-3) were positively correlated with TSHZ3 expression in STAD.Conclusions: TSHZ3 expression was up-regulated in STAD and BLCA. High TSHZ3 expression predicted poor prognosis of patients with STAD or BLCA. In addition, TSHZ3 expression potentially contributes to the increased infiltrations of pro-tumorigenic TIICs. TSHZ3 can be used as a prognostic biomarker for predicting prognosis and immune infiltration in STAD and BLCA.

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Section: Discussionsupporting

confidence: 89%

Section: Discussionmentioning

confidence: 65%

Section: Introductionmentioning

confidence: 99%

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TSHZ3 is A Prognostic Biomarker with Immune Infiltration in Stomach Adenocarcinoma and Bladder Urothelial Carcinoma

Zhang

Wang

et al. 2020

Preprint

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“…WGCNA is an innovative statistical tool used to cluster sets of genes with similar expression patterns and to analyze the correlation between genes and clinical features. WGCNA has been widely used in the analysis of cancer, such as lung ( 24 ), breast ( 25 ), colorectal ( 26 ), liver ( 27 ), thyroid ( 28 ), and HNSCC ( 29 – 31 ). However, WGCNA-related studies on laryngeal cancer metastasis have seldom been reported.…”

Section: Discussionmentioning

confidence: 99%

MYCT1 Inhibits the Adhesion and Migration of Laryngeal Cancer Cells Potentially Through Repressing Collagen VI

et al. 2021

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MYCT1, a target of c-Myc, inhibits laryngeal cancer cell migration, but the underlying mechanism remains unclear. In the study, we detected differentially expressed genes (DEGs) from laryngeal cancer cells transfected by MYCT1 using RNA-seq (GSE123275). DEGs from head and neck squamous cell carcinoma (HNSCC) were first screened by comparison of transcription data from the Gene Expression Omnibus (GSE6631) and the Cancer Genome Atlas (TCGA) datasets using weighted gene co-expression network analysis (WGCNA). GO and KEGG pathway analysis explained the functions of the DEGs. The DEGs overlapped between GSE6631and TCGA datasets were then compared with ours to find the key DEGs downstream of MYCT1 related to the adhesion and migration of laryngeal cancer cells. qRT-PCR and Western blot were applied to validate gene expression at mRNA and protein levels, respectively. Finally, the cell adhesion, migration, and wound healing assays were to check cell adhesion and migration abilities, respectively. As results, 39 overlapping genes were enriched in the GSE6631 and TCGA datasets, and most of them revealed adhesion function. Thirteen of 39 genes including COL6 members COL6A1, COL6A2, and COL6A3 were overlapped in GSE6631, TCGA, and GSE123275 datasets. Similar to our RNA-seq results, we confirmed that COL6 is a target of MYCT1 in laryngeal cancer cells. We also found that MYCT1 inhibited the adhesion and migration of laryngeal cancer cells via COL6. These indicate that COL6 is a potential target of MYCT1 and participates the adhesion and migration of laryngeal cancer cells, which provides an important clue for further study on how MYCT1 regulating COL6 in laryngeal cancer progression.

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“…In addition, TSHZ3 controls breathing and has been identified as a critical region of the heterozygous deletions at 19q12-q13.11, in development of autism spectrum disorder symptoms ( Caubit et al, 2016 ). TSHZ3 expression, as one of five genes, was high in tongue SCC ( Zeng et al, 2019 ) and TSHZ3 was duplicated in ovarian and triple negative breast cancers ( McBride et al, 2012 ), while TSHZ3, as one of ten genes, inhibited the p53 activity in multiple non-small cell lung cancer cell lines ( Van Olst et al, 2017 ). However, to date, there are no reports of aberrant expression or activities of these four genes in EAC.…”

Section: Discussionmentioning

confidence: 99%

DNA methylome and transcriptome analysis established a model of four differentially methylated positions (DMPs) as a diagnostic marker in esophageal adenocarcinoma early detection

Peng

Zhao

et al. 2021

PeerJ

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Background Esophageal carcinogenesis involves in alterations of DNA methylation and gene transcription. This study profiled genomic DNA methylome vs. gene expression using transcriptome data on esophageal adenocarcinoma (EAC) tissues from the online databases in order to identify methylation biomarkers in EAC early diagnosis. Materials and Methods The DNA methylome and transcriptome data were downloaded from the UCSC Xena, Gene Expression Omnibus (GEO), and The Cancer Genome Atlas (TCGA) databases and then bioinformatically analyzed for the differentially methylated positions (DMPs) vs. gene expression between EAC and normal tissues. The highly methylated DMPs vs. reduced gene expression in EAC were selected and then stratified with those of the corresponding normal blood samples and other common human cancers to construct an EAC-specific diagnostic model. The usefulness of this model was further verified in other three GEO datasets of EAC tissues. Result A total of 841 DMPs were associated with expression of 320 genes, some of which were aberrantly methylated in EAC tissues. Further analysis showed that four (cg07589773, cg10474350, cg13011388 and cg15208375 mapped to gene IKZF1, HOXA7, EFS and TSHZ3, respectively) of these 841 DMPs could form and establish a diagnostic model after stratified them with the corresponding normal blood samples and other common human cancers. The data were further validated in other three GEO datasets on EAC tissues in early EAC diagnosis. Conclusion This study revealed a diagnostic model of four genes methylation to diagnose EAC early. Further study will confirm the usefulness of this model in a prospective EAC cases.

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Transcripto‐based network analysis reveals a model of gene activation in tongue squamous cell carcinomas

Cited by 10 publications

References 50 publications

TSHZ3 is A Prognostic Biomarker with Immune Infiltration in Stomach Adenocarcinoma and Bladder Urothelial Carcinoma

TSHZ3 is A Prognostic Biomarker with Immune Infiltration in Stomach Adenocarcinoma and Bladder Urothelial Carcinoma

MYCT1 Inhibits the Adhesion and Migration of Laryngeal Cancer Cells Potentially Through Repressing Collagen VI

DNA methylome and transcriptome analysis established a model of four differentially methylated positions (DMPs) as a diagnostic marker in esophageal adenocarcinoma early detection

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