Regorafenib induces lethal autophagy arrest by stabilizing PSAT1 in glioblastoma

Jiang, Jingwen; Zhang, Lu; Chen, Hai‐Ning; Y, Lei; Zhang, Tao; Wang, Yuelong; Park, Jin; Jiang, Lan; Zhou, Li; Huang, Zhao; Li, Bowen; Liu, Yuan; Gao, Wei; Xie, Ke; Zhou, Liangxue; Nice, Edouard C.; Peng, Yong; Cao, Yihai; Wei, Yuquan; Wang, Kui; Huang, Canhua

doi:10.1080/15548627.2019.1598752

Cited by 109 publications

(105 citation statements)

References 61 publications

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“…The Fructose-Bisphosphatase 1 (FBP1) is a rate-limiting enzyme in gluconeogenesis, which is suppressed in kidney tumors and thus feeds ccRCC; FBP1 is associated with impaired cell proliferation, glycolysis and the pentose phosphate pathway in ccRCC in a catalytic-activity-independent manner via direct interaction with the HIF inhibitory domain 18 . PSAT1 is up-regulated in many cancers and acts as an oncogene that exerts a vital role in cancer progression and metastasis [19][20][21] . Interestingly, through mining public database and RT-qPCR, we found that PSAT1 in ccRCC patients is down-regulated compared with normal tissue.…”

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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“…Moreover, we were able to construct four PPI modules, all of which were related to critical GBM biological processes. Highly relevant nodes in the modules, including STAT3, SLC11A1, and ITGAM, have been reported to promote tumor proliferation, angiogenesis, migration, and invasiveness (73)(74)(75)(76)(77). Among the 64 genes validated, 27 (such as ALOX5, CAST, HS6ST1, ITGAM, PTPN6, SLC11A1, and SLC12A7) have been reported to be involved in the pathogenesis of GBM or critical in predicting OS.…”

Section: Discussionmentioning

confidence: 99%

Malignant Evaluation and Clinical Prognostic Values of m6A RNA Methylation Regulators in Glioblastoma

Du¹,

Hou²,

Mi³

et al. 2020

Front. Oncol.

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N6-methyladenosine (m6A) RNA methylation, the most common form of mRNA modification and regulated by the m6A RNA methylation regulators ("writers," "erasers," and "readers"), has been reported to be associated with the progression of the malignant tumor. However, its role in glioblastoma (GBM) has been poorly known. This study aimed to identify the expression, potential functions, and prognostic values of m6A RNA methylation regulators in GBM. Here, we revealed that the 13 central m6A RNA methylation regulators were firmly related to the clinical and molecular phenotype of GBM. Taking advantage of consensus cluster analysis, we obtained two categories of GBM samples and found malignancy-related processes of m6A methylation regulators and compounds that specifically targeted the malignant processes. Besides, we also obtained a list of genes with poor prognosis in GBM. Finally, we derived a risk-gene signature with three selected m6A RNA methylation regulators, which allowed us to extend the in-depth study and dichotomized the OS of patients with GBM into high-and low-risk subgroups. Notably, this risk-gene signature could be used as independent prognostic markers and accurate clinicopathological parameter predictors. In conclusion, m6A RNA methylation regulators are a type of vital participant in the malignant progression of GBM, with a critical potential in the prognostic stratification and treatment strategies of GBM.

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“…A number of studies have suggested overexpression of PSAT1 protein as a poor prognostic marker in colorectal cancer [17], esophageal squamous cell carcinoma [15], NSCLC [14] and ER(−) breast cancer [16]. However, a recent study suggested that a high level of PSAT1 protein could be a favorable prognostic marker for regorafenib-induced GBM suppression [18]. From literature review and our analyses, we conclude that the prognostic role of PSAT1 overexpression in gliomas, including LGGs and GBM, might be different from that in other cancer types.…”

Section: Discussionmentioning

confidence: 99%

“…However, the prognostic roles of these three genes in LGGs are still unknown. in Glioblastoma with regorafenib treatment [18] NAD+: an oxidized nicotinamide adenine dinucleotide.…”

Section: Phgdh Psph and Psat1 Are Important Regulators Of The Ssp Amentioning

confidence: 99%

“…PSAT1 was regarded as a poor prognostic marker in non-small cell lung cancer [14], esophageal squamous cell carcinoma [15], breast cancer [16] and colorectal cancer [17] and contributes to cancer cell proliferation and metastasis. In contrast, maintenance of PSAT1 protein at a high level has been identified as a marker for a favorable outcome in GBM with regorafenib treatment [18].…”

Section: Introductionmentioning

confidence: 99%

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Overexpression of PSAT1 Gene is a Favorable Prognostic Marker in Lower-Grade Gliomas and Predicts a Favorable Outcome in Patients with IDH1 Mutations and Chromosome 1p19q Codeletion

Huang

Chan

Lin

2019

Cancers

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Patients with lower-grade gliomas (LGGs) have highly diverse clinical outcomes. Although histological features and molecular markers have been used to predict prognosis, the identification of new biomarkers for the accurate prediction of patient outcomes is still needed. The serine synthesis pathway (SSP) is important in cancer metabolism. There are three key regulators, including phosphoglycerate dehydrogenase (PHGDH), phosphoserine phosphatase (PSPH), and phosphoserine aminotransferase 1 (PSAT1), in SSP. However, their clinical importance in LGGs is still unknown. In this study, we used the bioinformatics tool in the Gene Expression Profiling Interactive Analysis (GEPIA) website to examine the prognostic significance of PHGDH, PSPH, and PSAT1 genes in LGGs. PSAT1 gene expression was then identified as a potential biomarker candidate for LGGs. Datasets from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) were further used to explore the prognostic role of PSAT1 gene. Our results demonstrated that PSAT1 overexpression is a favorable prognostic marker of LGGs and significantly correlated with patient age ≤40, and a lower WHO histological grade, as well as mutations in IDH1, TP53 and ATRX, but not with chromosome 1p19q codeletions. More importantly, LGG patients with isocitrate dehydrogenase 1 (IDH1) mutations, chromosome 1p19q codeletions, and PSAT1 overexpression may have the best overall survival (five-year survival rate: 100%). Finally, we observed a coordinated biological reaction between IDH1 mutations and PSAT1 overexpression, and suggested overexpression of PSAT1 might enhance the function of mutant IDH1 to promote a favorable outcome in LGG patients. In conclusion, our study confirmed the importance of identifying the overexpression of PSAT1 as a favorable prognostic marker of LGGs, which may compensate for the limitation of IDH1 mutations and chromosome 1p19q codeletion in the prognostication of LGGs.

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Regorafenib induces lethal autophagy arrest by stabilizing PSAT1 in glioblastoma

Cited by 109 publications

References 61 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

Malignant Evaluation and Clinical Prognostic Values of m6A RNA Methylation Regulators in Glioblastoma

Overexpression of PSAT1 Gene is a Favorable Prognostic Marker in Lower-Grade Gliomas and Predicts a Favorable Outcome in Patients with IDH1 Mutations and Chromosome 1p19q Codeletion

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