<i>P4HA3</i> is Epigenetically Activated by Slug in Gastric Cancer and its Deregulation is Associated With Enhanced Metastasis and Poor Survival

Hu, Song; Liu, Lingling; Song, Zhaoquan; Ren, Yuying; Li, Chao; Huo, Jiege

doi:10.1177/1533033818796485

Cited by 35 publications

(27 citation statements)

References 44 publications

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“…Prolyl 4-Hydroxylase Subunit Alpha 3 (P4HA3) is a critical enzyme in maintaining the stability of newly synthesized collagen. Song H et al indicated that P4HA3 is upregulated in gastric cancer and epigenetically activated by slug 28 . In the present study, we demonstrated that P4HA3 is upregulated in ccRCC, and that its high expression reflected poor outcome.…”

Section: Discussionmentioning

confidence: 99%

A cluster of metabolism-related genes predict prognosis and progression of clear cell renal cell carcinoma

Liu

Pan

Xiao

et al. 2020

Sci Rep

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Clear cell renal cell carcinoma (ccRCC) has long been considered as a metabolic disease characterized by metabolic reprogramming due to the abnormal accumulation of lipid droplets in the cytoplasm. However, the prognostic value of metabolism-related genes in ccRCC remains unclear. In our study, we investigated the associations between metabolism-related gene profile and prognosis of ccRCC patients in the Cancer Genome Atlas (TCGA) database. Importantly, we first constructed a metabolism-related prognostic model based on ten genes (ALDH6A1, FBP1, HAO2, TYMP, PSAT1, IL4I1, P4HA3, HK3, CPT1B, and CYP26A1) using Lasso cox regression analysis. The Kaplan-Meier analysis revealed that our model efficiently predicts prognosis in TCGA_KIRC Cohort and the clinical proteomic tumor analysis consortium (CPTAC_ccRCC) Cohort. Using time-dependent ROC analysis, we showed the model has optimal performance in predicting long-term survival. Besides, the multivariate Cox regression analysis demonstrated our model is an independent prognostic factor. The risk score calculated for each patient was significantly associated with various clinicopathological parameters. Notably, the gene set enrichment analysis indicated that fatty acid metabolism was enriched considerably in low-risk patients. In contrast, the high-risk patients were more associated with nonmetabolic pathways. In summary, our study provides novel insight into metabolism-related genes' roles in ccRCC. Clear cell renal cell carcinoma (ccRCC), the most common renal cell carcinoma (RCC) subtype, exhibits global health issues due to its growing incidence, extreme heterogeneity among patients and high mortality. It is estimated that 90% of the ccRCC patients died of tumor-specific recurrence and metastasis 1. Regarding this, considerable research efforts have focused on developing a model to predict the prognosis of ccRCC patients; however, these prognosis tools still require improvements to attain a high degree of accuracy 2-4. Therefore, novel and robust prognostic models are urgently needed in clinical practice. Metabolism is fundamental in maintaining all the biological processes necessary for life 5. Tumors are typified by metabolic abnormalities as proliferating cells rewire their mechanism to sustain growth 6. Notably, the rapidly proliferating cells in malignancies take up abundant glucose and glutamine to generate the proteins, lipids, and nucleic acids to support cell growth 7. RCC is regarded as a metabolic disease with diabetes, obesity, and atherosclerosis considered as the risk factors 8,9. CcRCC is a unique RCC subtypes based on the abnormally accumulated lipid droplets in the cytoplasm with research evidence implicating the lipid accumulation in disease progression 10,11. Nevertheless, the underlying mechanism and the prognostic role of these metabolic genes remain largely unknown. In the present study, we screened the differentially expressed metabolism-related genes and evaluated their clinical value based on the cancer genome atlas (TCGA) kidney renal clear ...

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Section: Discussionmentioning

confidence: 99%

A cluster of metabolism-related genes predict prognosis and progression of clear cell renal cell carcinoma

Liu

Pan

Xiao

et al. 2020

Sci Rep

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“…Another study based on the bioinformatic analysis in The Cancer Genome Atlas (TCGA) found that P4HA3 upregulation is highly correlated with genes representing ECM production in breast cancer, and higher P4HA3 expression is associated with a worse prognosis [27]. Meanwhile, Song et al found that P4HA3 was significantly overexpressed in gastric cancer tissues compared with adjacent tissues, and which was associated with gastric cancer cell metastasis [28]. However, the role and mechanism of P4HA3 in the malignant tumors was largely unknown.…”

Section: Discussionmentioning

confidence: 99%

“…Statistical significance was identified as FDR adjusted P values ≤ 0.05. We used “pathview” package [28] to display the enriched pathways and deregulated genes.…”

Section: Methodsmentioning

confidence: 99%

COL6A6 interacted with P4HA3 to suppress the growth and metastasis of pituitary adenoma via blocking PI3K-Akt pathway

Long

Liu

et al. 2019

Aging

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The role and mechanism of collagen type VI alpha 6 (COL6A6) on tumor growth and metastasis in pituitary adenoma (PA) was determined. COL6A6 was downregulated in PA tissues and cell lines, which was negatively associated with the expression of prolyl-4-hydroxylase alpha polypeptide III (P4HA3) in the progression of PA. Overexpression of COL6A6 significantly suppressed tumor growth and metastasis capacity in PA. In addition, P4HA3 worked as the upstream of the PI3K-Akt pathway to alleviate the antitumor activity of COL6A6 on the growth and metastasis of both AtT-20 and HP75 cells. Furthermore, the inhibitory effect of COL6A6 on cell proliferation, migration and invasion, and epithelial-mesenchymal transition (EMT) was reversed by P4HA3 overexpression or activation of the PI3K-Akt pathway induced by IGF-1 addition, which provided a new biomarker for clinical PA treatment.

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“…P4HA3, encoding a component of prolyl 4-hydroxylase, can promote the proliferation and invasion of melanoma cells [32]. In addition, P4HA3 has been shown to be closely related to the poor survival outcomes of breast cancer and gastric cancer [33,34]. ETNK2 (Ethanolamine Kinase 2) is a protein Coding gene.…”

Section: Discussionmentioning

confidence: 99%

Metabolic genes show excellent prognostic ability for clear cell renal cell carcinoma

Wang

Yao

et al. 2020

Preprint

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Background Renal cell carcinoma (RCC) is one of the major malignant tumors of the urinary system, with a high mortality rate and a poor prognosis. Clear cell renal cell carcinoma (ccRCC) is the most common subtype of RCC. Although the diagnosis and treatment methods have been significantly improved, the incidence and mortality of ccRCC are high and still increasing. The occurrence and development of ccRCC are closely related to the changes of classic metabolic pathways. This article aims to explore the relationship between metabolic genes and the prognosis of patients with ccRCC. Patients and methods: Gene expression profiles of 63 normal kidney tissues and 446 ccRCC tissues from TCGA database and gene expression profiles of 39 ccRCC tissues from GEO database were used to obtain differentially expressed genes (DEGs) in ccRCC. Through the the KEGG gene sets of GSEA database, we obtained metabolic genes (MGs). Univariate Cox regression analysis was used to identify prognostic MGs. Lasso regression analysis was used to eliminate false positives because of over-fitting. Multivariate Cox regression analysis was used to established a prognostic model. Gene expression data and related survival data of 101 ccRCC patients from ArrayExpress database were used for external validation. Survival analysis, ROC curve analysis, independent prognostic analysis and clinical correlation analysis were performed to evaluate this model. Results We found that there were 479 abnormally expressed MGs in ccRCC tissues. Through univariate Cox regression analysis, Lasso regression analysis and multivariate Cox regression analysis, we identified 4 prognostic MGs (P4HA3, ETNK2, PAFAH2 and ALAD) and established a prognostic model (riskScore). Whether in the training cohort, the testing cohort or the entire cohort, this model could accurately stratify patients with different survival outcomes. The prognostic value of riskScore and 4 MGs was also confirmed in the ArrayExpress database. Results of GSEA analysis show that DEGs in patients with better prognosis were enriched in metabolic pathways. Then, a new Nomogram with higher prognostic value was constructed to better predict the 1-year OS, 3-year OS and 5-year OS of ccRCC patients. In addition, we successfully established a ceRNA network to further explain the differences in the expression of these MGs between high-risk patients and low-risk patients Conclusion We have successfully established a risk model (riskScore) based on 4 MGs, which could accurately predict the prognosis of patients with ccRCC. Our research may shed new light on ccRCC patients' prognosis and treatment management.

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P4HA3 is Epigenetically Activated by Slug in Gastric Cancer and its Deregulation is Associated With Enhanced Metastasis and Poor Survival

Cited by 35 publications

References 44 publications

A cluster of metabolism-related genes predict prognosis and progression of clear cell renal cell carcinoma

A cluster of metabolism-related genes predict prognosis and progression of clear cell renal cell carcinoma

COL6A6 interacted with P4HA3 to suppress the growth and metastasis of pituitary adenoma via blocking PI3K-Akt pathway

Metabolic genes show excellent prognostic ability for clear cell renal cell carcinoma

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