Identification of DEP domain-containing proteins by a machine learning method and experimental analysis of their expression in human HCC tissues

Liao, Zhijun; Wang, Xinrui; Zeng, Yeting; Zou, Quan

doi:10.1038/srep39655

Cited by 20 publications

(19 citation statements)

References 95 publications

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“…Moreover, Charos et al utilized ChIP-seq to obtain PPARGC1A binding sites across the genome in hepatoma cells HepG2 [ 10 ]. Conserved motif analysis [ 39 , 40 , 41 ] showed that the majority of PPARGC1A binding sites are located in multiple regulatory factor binding regions including RNAPII. Additionally, these regions are frequently located at the promoter of target genes, such as genes CEBPB [ 42 ].…”

Section: Discussionmentioning

confidence: 99%

MiR-93-5p Promotes Cell Proliferation through Down-Regulating PPARGC1A in Hepatocellular Carcinoma Cells by Bioinformatics Analysis and Experimental Verification

Wang

Liao

Bai

et al. 2018

Genes

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Peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PPARGC1A, formerly known as PGC-1a) is a transcriptional coactivator and metabolic regulator. Previous studies are mainly focused on the association between PPARGC1A and hepatoma. However, the regulatory mechanism remains unknown. A microRNA associated with cancer (oncomiR), miR-93-5p, has recently been found to play an essential role in tumorigenesis and progression of various carcinomas, including liver cancer. Therefore, this paper aims to explore the regulatory mechanism underlying these two proteins in hepatoma cells. Firstly, an integrative analysis was performed with miRNA–mRNA modules on microarray and The Cancer Genome Atlas (TCGA) data and obtained the core regulatory network and miR-93-5p/PPARGC1A pair. Then, a series of experiments were conducted in hepatoma cells with the results including miR-93-5p upregulated and promoted cell proliferation. Thirdly, the inverse correlation between miR-93-5p and PPARGC1A expression was validated. Finally, we inferred that miR-93-5p plays an essential role in inhibiting PPARGC1A expression by directly targeting the 3′-untranslated region (UTR) of its mRNA. In conclusion, these results suggested that miR-93-5p overexpression contributes to hepatoma development by inhibiting PPARGC1A. It is anticipated to be a promising therapeutic strategy for patients with liver cancer in the future.

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Section: Discussionmentioning

confidence: 99%

MiR-93-5p Promotes Cell Proliferation through Down-Regulating PPARGC1A in Hepatocellular Carcinoma Cells by Bioinformatics Analysis and Experimental Verification

Wang

Liao

Bai

et al. 2018

Genes

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“…Identification of novel amyloid proteins is laborious and time-consuming, but bioinformatic predictions in combination with recently developed proteomic approaches [ 72 , 73 , 74 , 75 ] are useful in this regard. In addition, future development of novel, more efficient bioinformatic algorithms based on the machine learning, which is actively using now for protein analysis [ 76 , 77 ], could also contribute to the progress in the proteomics of amyloids.…”

Section: Discussionmentioning

confidence: 99%

Predicting Amyloidogenic Proteins in the Proteomes of Plants

Antonets

Nizhnikov

2017

IJMS

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Amyloids are protein fibrils with characteristic spatial structure. Though amyloids were long perceived to be pathogens that cause dozens of incurable pathologies in humans and mammals, it is currently clear that amyloids also represent a functionally important form of protein structure implicated in a variety of biological processes in organisms ranging from archaea and bacteria to fungi and animals. Despite their social significance, plants remain the most poorly studied group of organisms in the field of amyloid biology. To date, amyloid properties have only been demonstrated in vitro or in heterologous systems for a small number of plant proteins. Here, for the first time, we performed a comprehensive analysis of the distribution of potentially amyloidogenic proteins in the proteomes of approximately 70 species of land plants using the Waltz and SARP (Sequence Analysis based on the Ranking of Probabilities) bioinformatic algorithms. We analyzed more than 2.9 million protein sequences and found that potentially amyloidogenic proteins are abundant in plant proteomes. We found that such proteins are overrepresented among membrane as well as DNA- and RNA-binding proteins of plants. Moreover, seed storage and defense proteins of most plant species are rich in amyloidogenic regions. Taken together, our data demonstrate the diversity of potentially amyloidogenic proteins in plant proteomes and suggest biological processes where formation of amyloids might be functionally important.

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“…Total RNA content was extracted from the tissues by using Trizol Reagent (Invitrogen, CA, USA) and reversely transcribed into cDNA by using the PrimeScript RT reagent Kit (TaKaRa, Tokyo, Japan) according to manufacturer's instructions. The relative expression levels of mRNA (normalized to β-actin) was analyzed by the 2 −ΔΔCt relative quanti cation method, the relative circRNA expression was calculated with the 2 −ΔCt method [19]. QPCR were performed using SYBE Green qPCR kit (TOYOBO, Tokyo, Japan) in the StepOne PCR system (Applied Biosystems).…”

Section: Rna Extraction and Quantitative Pcr (Qpcr)mentioning

confidence: 99%

Construction and Investigation of a circRNA-Associated ceRNA Regulatory Network in Tetralogy of Fallot

Wang

Cao

2020

Preprint

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Abstract Background: As the most frequent type of cyanotic congenital heart diseases (CHD), Tetralogy of Fallot (TOF) has a relatively poor prognosis without the corrective surgery. Circular RNA (circRNA) represents a novel class of endogenous noncoding RNAs that regulate target gene expression post-transcriptionally in heart development. Here, we investigate the potential role of ceRNA network in the pathogenesis of TOF. Methods: To identify circRNAs expression profiles in Tetralogy of Fallot, microarrays were used to screen the differentially expressed circRNA between 3 TOF and 3 control human myocardial tissue samples. Then, a dysregulated circRNA- associated ceRNA network was constructed via using the established multi-step screening strategy.Results: In summary, total 276 differentially expressed circRNAs were identified, including 214 up-regulated and 62 down-regulated ones in TOF samples. By constructing the circRNA-associated ceRNA network based on the bioinformatics data, a total of 19 key circRNAs, 9 key miRNAs and 34 key mRNAs were further screened. Moreover, by enlarging the samples size, the qPCR results validated that the positive correlations between hsa_circ_0007798 and HIF1A.Conclusions: The findings in this study provide a comprehensive understanding of the ceRNA network involved in TOF biology, such as hsa_circ_0007798/miR-199b-5p/HIF1A signal axis, and may offer candidate diagnostic biomarkers or potential therapeutic targets for TOF. In addtion, we propose that the ceRNA network regulates TOF progression.

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Identification of DEP domain-containing proteins by a machine learning method and experimental analysis of their expression in human HCC tissues

Cited by 20 publications

References 95 publications

MiR-93-5p Promotes Cell Proliferation through Down-Regulating PPARGC1A in Hepatocellular Carcinoma Cells by Bioinformatics Analysis and Experimental Verification

MiR-93-5p Promotes Cell Proliferation through Down-Regulating PPARGC1A in Hepatocellular Carcinoma Cells by Bioinformatics Analysis and Experimental Verification

Predicting Amyloidogenic Proteins in the Proteomes of Plants

Construction and Investigation of a circRNA-Associated ceRNA Regulatory Network in Tetralogy of Fallot

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