Hypoxia-regulated lncRNA CRPAT4 promotes cell migration via regulating AVL9 in clear cell renal cell carcinomas

Zhang, Wenhua; Wang, Jue; Chai, Ruijuan; Zhong, Guangxin; Zhang, Cong; Cao, Wenjia; Yan, Lei; Zhang, Xiang; Xu, Zhonghua

doi:10.2147/ott.s169155

Cited by 20 publications

(15 citation statements)

References 29 publications

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“…5C; 2-0.16-1 ) functions in exocytic transport from the Golgi [83]. AVL9 knockdown resulted in abnormal mitoses associated with defective protein trafficking, and increased cell migration with development of cysts [84], but also reduced cell proliferation and migration in other studies [85]. Regardless, the yeast phenomic model together with pharmacogenomics data would predict that functional loss of AVL9 renders cells vulnerable to cytarabine.…”

Section: Resultsmentioning

confidence: 99%

A humanized yeast phenomic model of deoxycytidine kinase to predict genetic buffering of nucleoside analog cytotoxicity

Santos

Icyuz

Pound

et al. 2019

Preprint

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10Knowledge about synthetic lethality can be applied to enhance the efficacy of 11 anti-cancer therapies in individual patients harboring genetic alterations in their cancer 12 that specifically render it vulnerable. We investigated the potential for high-resolution 13 phenomic analysis in yeast to predict such genetic vulnerabilities by systematic, 14 comprehensive, and quantitative assessment of drug-gene interaction for gemcitabine 15 and cytarabine, substrates of deoxycytidine kinase that have similar molecular structures 16 yet distinct anti-tumor efficacy. Human deoxycytidine kinase (dCK) was conditionally 17 expressed in the S. cerevisiae genomic library of knockout and knockdown (YKO/KD) 18 strains, to globally and quantitatively characterize differential drug-gene interaction for 19 gemcitabine and cytarabine. Pathway enrichment analysis revealed that autophagy, 20 histone modification, chromatin remodeling, and apoptosis-related processes influence 21 gemcitabine specifically, while drug-gene interaction specific to cytarabine was less 22 enriched in Gene Ontology. Processes having influence over both drugs were DNA 23 repair and integrity checkpoints and vesicle transport and fusion. Non-GO-enriched 24 genes were also informative. Yeast phenomic and cancer cell line pharmacogenomics 25 data were integrated to identify yeast-human homologs with correlated differential gene 26 2 expression and drug-efficacy, thus providing a unique resource to predict whether 27 differential gene expression observed in cancer genetic profiles are causal in tumor-28 specific responses to cytotoxic agents. 29 30 Keywords: 31 yeast phenomics, gene-drug interaction, genetic buffering, quantitative high 32 throughput cell array phenotyping (Q-HTCP), cell proliferation parameters (CPPs), 33 gemcitabine, cytarabine, recursive expectation-maximization clustering (REMc), 34 pharmacogenomics 35 36 Introduction: 37Genomics has enabled targeted therapy aimed at cancer driver genes and 38 oncogenic addiction [1], yet traditional cytotoxic chemotherapeutic agents remain among 39 the most widely used and efficacious anti-cancer therapies [2]. Changes in the genetic 40 network underlying cancer can produce vulnerabilities to cytotoxic chemotherapy that 41 further influence the therapeutic window and provide additional insight into their 42 mechanisms of action [3,4]. A potential advantage of so-called synthetic lethality-based 43 treatment strategies is that they could have efficacy against passenger gene mutation or 44 compensatory gene expression, while classic targeted therapies are directed primarily at 45 driver genes ( Fig. 1A). Quantitative high throughput cell array phenotyping of the yeast 46 knockout and knockdown libraries provides a phenomic means for systems level, high- 47resolution modeling of gene interaction [5][6][7][8][9], which is applied here to predict cancer-48 relevant drug-gene interaction through integration with cancer pharmacogenomics 49 resources ( Fig. 1B). 50Nucleoside analogs include a diverse group of co...

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Section: Resultsmentioning

confidence: 99%

A humanized yeast phenomic model of deoxycytidine kinase to predict genetic buffering of nucleoside analog cytotoxicity

Santos

Icyuz

Pound

et al. 2019

Preprint

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“…Zhang et al. revealed that under hypoxic conditions in ccRCC, lncRNA CRPAT4 promoted cell migration by regulating AVL9 ( 39 ). In the present study, we performed a co-expression analysis between hypoxia genes and differentially expressed lncRNAs through paired lncRNA and mRNA expression data in ccRCC patients from TCGA.…”

Section: Discussionmentioning

confidence: 99%

An Effective Hypoxia-Related Long Non-Coding RNAs Assessment Model for Prognosis of Clear Cell Renal Carcinoma

et al. 2021

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Hypoxia is a significant clinical feature and regulates various tumor processes in clear cell renal carcinoma (ccRCC). Increasing evidence has demonstrated that long non-coding RNAs (lncRNAs) are closely associated with the survival outcomes of ccRCC patients and regulates hypoxia-induced tumor processes. Thus, this study aimed to develop a hypoxia-related lncRNA (HRL) prognostic model for predicting the survival outcomes in ccRCC. LncRNAs in ccRCC samples were extracted from The Cancer Genome Atlas database. Hypoxia-related genes were downloaded from the Molecular Signatures Database. A co-expression analysis between differentially expressed lncRNAs and hypoxia-related genes in ccRCC samples was performed to identify HRLs. Univariate and multivariate Cox regression analyses were performed to select nine optimal lncRNAs for developing the HRL model. The prognostic model showed good performance in predicting prognosis among patients with ccRCC, and the validation sets reached consistent results. The model was also found to be related to the clinicopathologic parameters of tumor grade and tumor stage and to tumor immune infiltration. In conclusion, our findings indicate that the hypoxia-lncRNA assessment model may be useful for prognostication in ccRCC cases. Furthermore, the nine HRLs included in the model might be useful targets for investigating the tumorigenesis of ccRCC and designing individualized treatment strategies.

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“…lncRNA PCGEM1 may be used as a scaffold to form a complex with HIF-1α and transcription factor Snail homolog 1 (SNAI1) and regulate the invasion and metastasis of gastric cancer cells (67). Hypoxia-induced lncRNA CRPAT4 is regulated by HIF-1α and plays a carcinogenic role by promoting the growth and migration of cancer cells (68). The presence of siRNA targeting HIF-1α may provide a novel direction for specific treatment against HIF-1α, and it could achieve molecular therapy by inducing apoptosis and increasing the sensitivity of radiotherapy (69,70).…”

Section: Role Of Hif-1 In Non-coding Rna Associated With Cscsmentioning

confidence: 99%

Role of hypoxia inducible factor-1 in cancer stem cells (Review)

et al. 2020

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Cancer stem cells (CSCs) have been found to play a decisive role in cancer recurrence, metastasis, and chemo-, radio-and immuno-resistance. Understanding the mechanism of CSC self-renewal and proliferation may help overcome the limitations of clinical treatment. The microenvironment of tumor growth consists of a lack of oxygen, and hypoxia has been confirmed to induce cancer cell invasion, metastasis and epithelial-mesenchymal transition, and is usually associated with poor prognosis and low survival rates. Hypoxia inducible factor-1 (HIF-1) can be stably expressed under hypoxia and act as an important molecule to regulate the development of CSCs, but the specific mechanism remains unclear. The present review attempted to explain the role of HIF-1 in the generation and maintenance of CSCs from the perspective of epigenetics, metabolic reprogramming, tumor immunity, CSC markers, non-coding RNA and signaling pathways associated with HIF-1, in order to provide novel targets with HIF-1 as the core for clinical treatment, and extend the life of patients. Contents 1. Introduction 2. Structural characteristics of HIF-1 3. Role of epigenetic and post-translational modification of HIF-1 in CSCs 4. Role of HIF-1 in non-coding RNA associated with CSCs 5. Role of HIF-1 in CSC markers 6. Role of HIF-1 in tumor immunity of CSCs 7. Role of HIF-1 in metabolic reprogramming of CSCs 8. Role of HIF-1 in signaling pathways associated with CSCs 9. Potential targets for CSC therapy 10. Conclusions and perspectives

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Hypoxia-regulated lncRNA CRPAT4 promotes cell migration via regulating AVL9 in clear cell renal cell carcinomas

Cited by 20 publications

References 29 publications

A humanized yeast phenomic model of deoxycytidine kinase to predict genetic buffering of nucleoside analog cytotoxicity

A humanized yeast phenomic model of deoxycytidine kinase to predict genetic buffering of nucleoside analog cytotoxicity

An Effective Hypoxia-Related Long Non-Coding RNAs Assessment Model for Prognosis of Clear Cell Renal Carcinoma

Role of hypoxia inducible factor-1 in cancer stem cells (Review)

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