Identification of a glycolysis-related lncRNA prognostic signature for clear cell renal cell carcinoma

Ma, Wei; Zhong, Manli; Liu, Xiaowu

doi:10.1042/bsr20211451

Cited by 12 publications

(10 citation statements)

References 57 publications

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“…By using expression analysis and correlation analysis, the most potential upregulated lncRNAs AC026401.3 was identified ( Figure 4D , 4E ). Glycolysis based AC026401.3 have important value in survival prediction of renal cell carcinoma patients [ 23 ], but their specific roles in tumors are unclear and deserve further exploration [ 33 ].…”

Section: Discussionmentioning

confidence: 99%

High expression of CCNB1 driven by ncRNAs is associated with a poor prognosis and tumor immune infiltration in breast cancer

Wang

et al. 2022

Aging

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Backgrounds: Breast cancer (BC) is the most frequent cancer diagnosed in women throughout the world. The purpose of this study was to explore new biomarkers for breast cancer diagnosis. CyclinB1 (CCNB1) is found in abundance in a wide range of human malignancies. Material and Methods: We evaluated the transcriptional, survival data and expression levels in tissue data of CCNB1 in patients with breast cancer from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), The Human Protein Atlas (THAP) and Genome Tissue Expression (GTEx) database. A series of in silico analyses were used to investigate at noncoding RNAs (ncRNAs), gene ontology (GO) annotation analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG), and the Protein-Protein Interaction (PPI) network. A quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate CCNB1 in BC cell lines. Results: CCNB1 expression was higher in BC tissues than in normal breast tissues. It was significantly related to survival time, tumor mutation burden (TMB), methylated, immune cell infiltration, and the expressed in estrogen receptor (ER) (−), lymphnode (+), and p53 (+) groups in BC. Moreover, The AC026401.3/CCNB1-miR-139-5p axis was discovered as the most promising upstream ncRNA-related pathway of CCNB1 in BC. Conclusion: CCNB1 can be used as an independent predictive factor for BC, indicating that this would be a target for highly precise therapy and a biomarker for the disease.

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Section: Discussionmentioning

confidence: 99%

High expression of CCNB1 driven by ncRNAs is associated with a poor prognosis and tumor immune infiltration in breast cancer

Wang

et al. 2022

Aging

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“…LncRNAs could also be used to predict the prognosis of diseases. Ma et al found that the 7 identified glycolysis-related lncRNAs constitute a lncRNA signature with prognostic value for clear cell renal cell carcinoma and provide potential therapeutic targets for the treatment of clear cell renal cell carcinoma patients [ 38 ]. The ROC curve results showed that lncRNA NEAT1_1 in peripheral blood of STB patients had satisfactory sensitivity, specificity, and AUC in predicting the outcome of STB, which suggested that RNA in peripheral blood might be used to predict prognosis of STB.…”

Section: Discussionmentioning

confidence: 99%

Expression and Clinical Significance of lncRNA NEAT1 in Patients with Spinal Tuberculosis

et al. 2022

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Background. Spinal tuberculosis (STB) often leads to irreversible neurological injury, resulting in serious social and economic problems. With the emergence of drug resistance, the management becomes even more challenging, given the treatment courses are generally longer for skeletal than pulmonary tuberculosis (PTB). The development and validation of nonsputum biomarkers for diagnosis and tailoring of treatment duration to enable personalized and evidence-based management of such diseases to improve treatment outcomes is being called for globally. Studies have demonstrated that lncRNA NEAT1 was highly expressed in pulmonary tuberculosis (TB) and was related to its progression and recovery. However, the expression and clinical significance of lncRNA NEAT1 in STB remains unclear. Methods. The relative expression of lncRNA NEAT1 was quantified by relative real-time reverse transcription PCR (RT-PCR). The prognostic value was assessed by receiver-operating characteristic (ROC) curve analysis. Pearson and Spearman correlation coefficient and chi-square test were used to analyze the correlation between the lncRNA NEAT1 expression and the clinical characteristics. Univariate and multivariate logistic regression analyses were used to analyze independent predictors of STB recurrence. Results. Compared with normal healthy individuals, the expression level of lncRNA NEAT1 in peripheral blood and granulomatous tissues of STB patients was significantly increased. The results of the in vitro Mycobacterium tuberculosis- (Mtb-) infected cell model showed that the expression level of lncRNA NEAT1 was significantly upregulated in macrophages infected with Mtb, and the difference was statistically significant compared with Mtb-uninfected group. The expression level of lncRNA NEAT1 in granulomatous tissue of STB was significantly higher than that in peripheral blood. The expression of lncRNA NEAT1 was related to segments of the lesions, paraspinal abscesses, anti-TB treatment, drug resistance, interleukin-6 (IL-6), C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR). Multivariate analysis results showed that relatively high expression of lncRNA NEAT1_1, the shorter transcript of the NEAT1 gene, was an independent prognostic factor of STB outcome. Conclusion. LncRNA NEAT1 was highly expressed in peripheral blood mononuclear cells (PBMCs) and granulomatous tissue from patients with STB, as well as in Mtb-infected THP-1 cell lines. LncRNA NEAT1 expression was significantly associated with clinical characteristics (paraspinal abscesses, segments of the lesions and anti-TB treatment, IL-6, CRP, and ESR) of patients in STB. Increased expression of lncRNA NEAT1_1 predicted good prognosis of STB and might become a prognostic biomarker for STB.

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“…Yu et al identified an m6A-related lncRNA signature for predicting the prognosis of RCC, with an AUC value of 0.80 ( Yu et al, 2021 ). Ma et al identified a glycolysis-related lncRNA prognostic signature for RCC and the AUC value was 0.82 ( Ma et al, 2021 ). Dong et al identified a redox-related lncRNA signature of RCC and the AUC value was 0.82 ( Qi-Dong et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

“…Recent studies have reported several prognostic models for RCC. However, the Area Under Curve (AUC) values were all less than 0.83 (Qi-Dong et al, 2020;Ma et al, 2021;Sun et al, 2021;Yu et al, 2021). Therefore, a more efficient model is urgently needed for predicting the prognosis of RCC.…”

Section: Introductionmentioning

confidence: 99%

Systematic Investigation of Immune-Related lncRNA Landscape Reveals a Potential Long Non-Coding RNA Signature for Predicting Prognosis in Renal Cell Carcinoma

Liu

Li²,

Ruan³

et al. 2022

Front. Genet.

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Background: Renal cell carcinoma (RCC) is the predominant type of malignant tumor in kidney cancer. Finding effective biomarkers, particularly those based on the tumor immune microenvironments (TIME), is critical for the prognosis and diagnosis of RCC. Increasing evidence has revealed that long non-coding RNAs (lncRNAs) play a crucial role in cancer immunity. However, the comprehensive landscape of immune infiltration-associated lncRNAs and their potential roles in the prognosis and diagnosis of RCC remain largely unexplored.Methods: Based on transcriptomic data of 261 RCC samples, novel lncRNAs were identified using a custom pipeline. RCC patients were classified into different immune groups using unsupervised clustering algorithms. Immune-related lncRNAs were obtained according to the immune status of RCC. Competing endogenous RNAs (ceRNA) regulation network was constructed to reveal their functions. Expression patterns and several tools such as miRanda, RNAhybrid, miRWalk were used to define lncRNAs-miRNAs-mRNAs interactions. Univariate Cox, LASSO, and multivariate Cox regression analyses were performed on the training set to construct a tumorigenesis-immune-infiltration-related (TIR)-lncRNA signature for predicting the prognosis of RCC. Independent datasets involving 531 RCC samples were used to validate the TIR-lncRNA signature.Results: Tens of thousands of novel lncRNAs were identified in RCC samples. Comparing tumors with controls, 1,400 tumorigenesis-related (TR)-lncRNAs, 1269 TR-mRNAs, and 192 TR-miRNAs were obtained. Based on the infiltration of immune cells, RCC patients were classified into three immune clusters. By comparing immune-high with immune-low groups, 241 TIR-lncRNAs were identified, many of which were detected in urinary samples. Based on lncRNA-miRNA-mRNA interactions, we constructed a ceRNA network, which included 25 TR-miRNAs, 28 TIR-lncRNAs, and 66 TIR-mRNAs. Three TIR lncRNAs were identified as a prognostic signature for RCC. RCC patients in the high-risk group exhibited worse OS than those in the low-risk group in the training and testing sets (p < 0.01). The AUC was 0.9 in the training set. Univariate and multivariate Cox analyses confirmed that the TIR-lncRNA signature was an independent prognostic factor in the training and testing sets.Conclusion: Based on the constructed immune-related lncRNA landscape, 241 TIR-lncRNAs were functionally characterized, three of which were identified as a novel TIR-lncRNA signature for predicting the prognosis of RCC.

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Identification of a glycolysis-related lncRNA prognostic signature for clear cell renal cell carcinoma

Cited by 12 publications

References 57 publications

High expression of CCNB1 driven by ncRNAs is associated with a poor prognosis and tumor immune infiltration in breast cancer

High expression of CCNB1 driven by ncRNAs is associated with a poor prognosis and tumor immune infiltration in breast cancer

Expression and Clinical Significance of lncRNA NEAT1 in Patients with Spinal Tuberculosis

Systematic Investigation of Immune-Related lncRNA Landscape Reveals a Potential Long Non-Coding RNA Signature for Predicting Prognosis in Renal Cell Carcinoma

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