Identification of biomarkers and construction of a microRNA‑mRNA regulatory network for clear cell renal cell carcinoma using integrated bioinformatics analysis

Han, Miaoru; Yan, Haifeng; Yang, Kang; Fan, Boya; Liu, Panying; Yang, Hongtao

doi:10.1371/journal.pone.0244394

Cited by 8 publications

(6 citation statements)

References 40 publications

(44 reference statements)

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“…After a series of analyses for these 23 miRNAs, miR-532-3p was identified as the most potential miRNA of PLAUR, which was negatively associated with PLAUR expression; it was overexpressed and predicted a bad outcome in KIRC. Moreover, Han et al suggested that miR-532-3p inhibited the malignant progression of KIRC by downregulating the expression of ETS1, an oncogene associated with unfavorable prognosis in KIRC (44). Subsequently, 121 upstream potential lncRNAs of the miR-532-3p-PLAUR axis were discovered.…”

Section: Discussionmentioning

confidence: 99%

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Identification of PLAUR-related ceRNA and immune prognostic signature for kidney renal clear cell carcinoma

Wang

Sun

et al. 2022

Front. Oncol.

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Kidney renal clear cell carcinoma (KIRC) represents one of the most fatal cancers, usually showing malignant progression and a high tumor recurrence rate. The urokinase-type plasminogen activator receptor (PLAUR) plays a critical role in the initiation and progression of several cancers, including KIRC. However, the function and mechanism of PLAUR in patients with KIRC are still unclear and require further investigation. In the present study, we first explored the expression profile and prognostic values of PLAUR in pan-cancer based on The Cancer Genome Atlas and Genotype-Tissue Expression databases. PLAUR was upregulated in multiple cancers and was significantly associated with poor overall survival and disease-free survival only in patients with KIRC. Subsequently, the PVT1/SNHG15-hsa-miR-532-3p axis was identified as the most potential upstream regulatory network of PLAUR in KIRC. In addition, PLAUR expression was closely associated with tumor-infiltrating immune cells, tumor immunity biomarkers, and immunomodulator expression. Furthermore, we constructed a multiple-gene risk prediction signature according to the PLAUR-related immunomodulators (PRIs). A prognostic nomogram was then developed to predict the 1-, 3-, and 5-year survival probabilities of individuals. In conclusion, our study identified the PVT1/SNHG15-hsa-miR-532-3p-PLAUR axis and a prognostic signature of PRIs, which could be a reference for future clinical research.

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Section: Discussionmentioning

confidence: 99%

“…Moreover, Han et al. suggested that miR-532-3p inhibited the malignant progression of KIRC by downregulating the expression of ETS1, an oncogene associated with unfavorable prognosis in KIRC ( 44 ).…”

Section: Discussionmentioning

confidence: 99%

Identification of PLAUR-related ceRNA and immune prognostic signature for kidney renal clear cell carcinoma

Wang

Sun

et al. 2022

Front. Oncol.

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“…Microarray technology can be reliable and useful for identifying novel targets for clinical diagnostic and therapeutic approaches. This technology can be used in pancreatic cancer and renal clear cell carcinoma for diagnosis and effective therapy [ 15 , 17 ].…”

Section: Discussionmentioning

confidence: 99%

Microarray analysis of potential biomarkers of brachial plexus avulsion caused neuropathic pain in male rat

Wang

Lao

2022

BMC Neurosci

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The present study aimed to investigate the expression of mRNA in the brachial plexus avulsion neuropathic pain model and analyze biological functions. Microarray mRNA assay and reverse transcriptase quantitative polymerase chain reaction (RT-PCR) were conducted. The whole blood was collected from two groups for Microarray mRNA analysis. The predicted mRNA targets were studied by gene ontology analysis and pathway analysis. We identified 3 targeted mRNAs, including PIK3CB, HRAS, and JUN. The results showed that PIK3CB, HRAS, and JUN gene expression was increased in the control group but decreased in the neuropathic pain group. These findings indicate that certain genes may be important biomarkers for the potential targets for the prevention and treatment of brachial plexus avulsion caused neuropathic pain.

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“…Although hsa-mir-142 and hsa-mir-3676 have not been implicated in renal cancer in the literature, our final candidate, hsa-mir-133b, has been associated with renal cancer through the JAK2/STAT3 pathway [47]. It has also been identified as a biomarker in other studies [48].…”

Section: Discussionmentioning

confidence: 99%

“…CHL1 is an ATP-dependent DNA helicase that promotes genomic stability through DNA replication, DNA repair, and ribosomal RNA synthesis [51]. CHL1 was found to be a prognostic marker for renal cancer by multiple sources [50, 52], suggesting that under-expression can lead to lower survival rates in renal cancer patients. HAPLN1 is a protein that binds hyaluronic acid with proteoglycan monomers [51].…”

Section: Discussionmentioning

confidence: 99%

Multi-omics analysis of renal clear cell carcinoma progression

Guruacharya

Golden

Garrett

et al. 2022

Preprint

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Renal clear cell carcinoma (RCC), the most common type of kidney cancer, lacks a well-defined collection of biomarkers for tracking disease progression. Although complementary diagnostic and prognostic RCC biomarkers may be beneficial for guiding therapeutic selection and informing clinical outcomes, patients currently have a poor prognosis due to limited early detection. Without a priori biomarker knowledge or histopathology information, we used machine learning (ML) techniques to investigate how mRNA, microRNA, and protein expression levels change as a patient progresses to different stages of RCC. The novel combination of big data with ML enables researchers to generate hypothesis-free models in a fraction of the time used in traditional clinical trials. Ranked genes that are most predictive of survival and disease progression can be used for target discovery and downstream analysis in precision medicine. We extracted clinical information for normal and RCC patients along with their related expression profiles in RCC tissues from three publicly-available datasets: 1. The Cancer Genome Atlas (TCGA), 2. Genotype-Tissue Expression (GTEx) project, 3. Clinical Proteomic Tumor Analysis Consortium (CPTAC). Our study found that among others, gene expression levels (mRNA) from GNG7 and BCR are potential predictors for RCC progression. For microRNA, we found hsa-mir-199a-2 and hsa-mir-129-1 to be potential predictors of RCC progression. Understanding how genes and protein expression levels change as RCC progresses will further guide the development of prognostic biomarkers and targets for RCC therapies.

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Identification of biomarkers and construction of a microRNA‑mRNA regulatory network for clear cell renal cell carcinoma using integrated bioinformatics analysis

Cited by 8 publications

References 40 publications

Identification of PLAUR-related ceRNA and immune prognostic signature for kidney renal clear cell carcinoma

Identification of PLAUR-related ceRNA and immune prognostic signature for kidney renal clear cell carcinoma

Microarray analysis of potential biomarkers of brachial plexus avulsion caused neuropathic pain in male rat

Multi-omics analysis of renal clear cell carcinoma progression

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