High TSTA3 Expression as a Candidate Biomarker for Poor Prognosis of Patients With ESCC

Yang, Jie; Kong, Ping; Yang, Jian; Jia, Zhiwu; Hu, Xiaoling; Wang, Zianyi; Cui, Heyang; Bi, Yanghui; Qian, Yu; Li, Hongyi; Wang, Fang; Yang, Bin; Yan, Tao; Ma, Yue; Zhang, Ling; Chen, Cheng; Song, Bin; Li, Yaoping; Xu, Enwei; Liu, Haiyan; Gao, Wei; Wang, Juan; Zhai, Yuanfang; Lu, Chin‐Song; Wang, Yi; Zhang, Yingchun; Shi, Ruyi; Liu, Jing; Wang, Qi; Cheng, Xiaolong; Cui, Yongping

doi:10.1177/1533033818781405

Cited by 12 publications

(18 citation statements)

References 39 publications

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“…The difference was also significant in 60 paired cancer tissues and adjacent normal tissues ( P = 0.000) (Figure 1 F) . Correlation analysis between protein expression and clinicopathological factors showed that the high expression of TSTA3 was also significantly associated with late clinical stage, more lymph node metastasis and poor prognosis for ESCC patients 21 . Combining with TSTA3 as a fucose synthesis related enzyme, we speculated that abnormal fucosylation might participate in the progress of ESCC and TSTA3 might serve as a novel biomarker for prognosis of ESCC patients.…”

Section: Resultsmentioning

confidence: 99%

“…A total of 508 ESCC patients with FFPE samples used for WGS were recruited from Shanxi and Xinjiang provinces in China. The description of the clinical characteristics of the 508 samples was presented in our previous study 21 . A total of 155 ESCC patients with fresh frozen tissues used for both WGS and transcriptomic sequencing were recruited from Shanxi provinces in China.…”

Section: Methodsmentioning

confidence: 99%

“…A human ESCC tissue array containing 104 primary ESCC tissues and 60 paired normal tissues was used as previously 21 . Meanwhile, we collected paraffin-embedded samples from 11 ESCC patients including primary ESCC, matched non-tumor tissues and metastatic lymph node (1-3 samples per patient).…”

Section: Methodsmentioning

confidence: 99%

“…In our previous study, we revealed that overexpression of TSTA3 protein was associated with clinical stage and lymph node metastasis in ESCC patients. Moreover, increased TSTA3 expression could independently predict poor prognosis for ESCC patients 21 . In this study, we reported the frequent amplification of TSTA3 in ESCC and promoting metastasis of TSTA3 through regulating fucosylation of LAMP2 and ERBB2 in ESCC.…”

Section: Introductionmentioning

confidence: 99%

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TSTA3 facilitates esophageal squamous cell carcinoma progression through regulating fucosylation of LAMP2 and ERBB2

et al. 2020

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Background: TSTA3 gene encodes an enzyme responsible for synthesis of GDP-L-fucose as the only donor in fucosylation. This study was designed to explore clinical value, function and underlying mechanism of TSTA3 in the development of esophageal squamous cell carcinoma (ESCC). Methods: Whole genomic sequencing data from 663 ESCC patients and RNA sequencing data from 155 ESCC patients were used to analyze the copy number variation and mRNA expression of TSTA3 respectively. Immunohistochemistry based or not based on the tissue microarrays was used to detect its protein expression. Transwell assay and in vivo metastasis assay were used to study the effect of TSTA3 on invasion and metastasis of ESCC. Immunofluorescence was used to analyze fucosylation level. N-glycoproteomics and proteomics analysis, Lens Culinaris Agglutinin (LCA) and Ulex Europaeus Agglutinin I (UEA-I) affinity chromatography, immunoprecipitation, glycosyltransferase activity kit and rescue assay were used to explore the mechanism of TSTA3. Results: TSTA3 was frequently amplified and overexpressed in ESCC. TSTA3 amplification and protein overexpression were significantly associated with malignant progression and poor prognosis of ESCC patients. TSTA3 knockdown significantly suppressed ESCC cells invasion and tumor dissemination by decreasing fucosylation level. Conversely, exogenous overexpression of TSTA3 led to increased invasion and tumor metastasis in vitro and in vivo by increasing fucosylation level. Moreover, core fucosylated LAMP2 and terminal fucosylated ERBB2 might be mediators of TSTA3-induced pro-invasion in ESCC and had a synergistic effect on the process. Peracetylated 2-F-Fuc, a fucosyltransferase activity inhibitor, reduced TSTA3 expression and fucosylation modification of LAMP2 and ERBB2, thereby inhibiting ESCC cell invasion. Conclusion: Our results indicate that TSTA3 may be a driver of ESCC metastasis through regulating fucosylation of LAMP2 and ERBB2. Fucosylation inhibitor may have prospect to suppress ESCC metastasis by blocking aberrant fucosylation.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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TSTA3 facilitates esophageal squamous cell carcinoma progression through regulating fucosylation of LAMP2 and ERBB2

et al. 2020

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“…However, it has been reported as an oncogene in hepatocellular carcinoma 35 , clear cell renal cell carcinoma 36 , triple-negative breast cancer 37 , and non-small-cell lung cancer 38 . TSTA3, also known as GFUS, participates in the pathway of transporting to the Golgi apparatus as well as metabolism 39 , and is considered an oncogene in many cancers including esophageal squamous cell carcinoma 40 . To the best of our knowledge, this is the first study to report the correlation of RALY and TSTA3 with overall survival in head and neck cancer.…”

Section: Discussionmentioning

confidence: 99%

Proteomic analysis of hypopharyngeal and laryngeal squamous cell carcinoma sheds light on differences in survival

Zhu

et al. 2020

Sci Rep

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The link between differences in molecular expression and survival among advanced laryngeal (LSCC) and hypopharyngeal squamous carcinoma (HPSCC) remains unclear. Here, we applied the Surveillance, Epidemiology, and End Results (SEER) program, Isobaric tag for relative and absolute quantitation (iTRAQ) with Liquid chromatography-mass spectrometry (LC–MS/MS) proteomics data and The Cancer Genome Atlas (TCGA) related data to discover the possible disparities between HPSCC and LSCC. Our results showed a significantly worse 5-year overall-survival in HPSCC compared with LSCC before and after adjusting for clinical parameters. 240 differentially expressed proteins were enriched in molecular networks of cytoskeleton remodeling and antigen presentation. Moreover, HPSCC consisted of less T-central-memory cells, T-follicular-helper cells, TGF-β response, and CD4 + T memory resting cells, but more wound healing than LSCC. Furthermore, 9 mRNAs expression were significantly and independently correlated to overall survival in 126 HPSCC and LSCC patients, which was further validated in another cohort of head and neck cancers. These findings support that Immunity signatures as well as pathway networks that include cytoskeleton remodeling and antigen presentation may contribute to the observed differences in survival between HPSCC and LSCC.

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Establishment of prognostic risk model and drug sensitivity based on prognostic related genes of esophageal cancer

Dai

Reyimu

Sun

et al. 2022

Sci Rep

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At present, the treatment of esophageal cancer (EC) is mainly surgical and drug treatment. However, due to drug resistance, these therapies can not effectively improve the prognosis of patients with the EC. Therefore, a multigene prognostic risk scoring system was constructed by bioinformatics analysis method to provide a theoretical basis for the prognosis and treatment decision of EC. The gene expression profiles and clinical data of esophageal cancer patients were gathered from the Cancer Genome Atlas TCGA database, and the differentially expressed genes (DEGs) were screened by R software. Genes with prognostic value were screened by Kaplan Meier analysis, followed by functional enrichment analysis. A cox regression model was used to construct the prognostic risk score model of DEGs. ROC curve and survival curve were utilized to evaluate the performance of the model. Univariate and multivariate Cox regression analysis was used to evaluate whether the model has an independent prognostic value. Network tool mirdip was used to find miRNAs that may regulate risk genes, and Cytoscape software was used to construct gene miRNA regulatory network. GSCA platform is used to analyze the relationship between gene expression and drug sensitivity. 41 DEGs related to prognosis were pre-liminarily screened by survival analysis. A prognostic risk scoring model composed of 8 DEGs (APOA2, COX6A2, CLCNKB, BHLHA15, HIST1H1E, FABP3, UBE2C and ERO1B) was built by Cox regression analysis. In this model, the prognosis of the high-risk score group was poor (P < 0.001). The ROC curve showed that (AUC = 0.862) the model had a good performance in predicting prognosis. In Cox regression analysis, the comprehensive risk score can be employed as an independent prognostic factor of the EC. HIST1H1E, UBE2C and ERO1B interacted with differentially expressed miRNAs. High expression of HIST1H1E was resistant to trametinib, selumetinib, RDEA119, docetaxel and 17-AAG, High expression of UBE2C was resistant to masitinib, and Low expression of ERO1B made the EC more sensitive to FK866. We constructed an EC risk score model composed of 8 DEGs and gene resistance analysis, which can provide reference for prognosis prediction, diagnosis and treatment of the EC patients.

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High TSTA3 Expression as a Candidate Biomarker for Poor Prognosis of Patients With ESCC

Cited by 12 publications

References 39 publications

TSTA3 facilitates esophageal squamous cell carcinoma progression through regulating fucosylation of LAMP2 and ERBB2

TSTA3 facilitates esophageal squamous cell carcinoma progression through regulating fucosylation of LAMP2 and ERBB2

Proteomic analysis of hypopharyngeal and laryngeal squamous cell carcinoma sheds light on differences in survival

Establishment of prognostic risk model and drug sensitivity based on prognostic related genes of esophageal cancer

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