Association between SNP rs527616 in lncRNA AQP4-AS1 and susceptibility to breast cancer in a southern Brazilian population

Marchi, Rafael; Mathias, Carolina; Reiter, Gabriel A. K.; Lima, Rubens Silveira de; Kuroda, Fusakuni; Urban, Cı́cero de Andrade; Souza, Ricardo Lehtonen Rodrigues de; Ribeiro, Enilze Maria de Souza Fonseca; Cavalli, Iglenir João; Oliveira, Jaqueline Carvalho de

doi:10.1590/1678-4685-gmb-2020-0216

Cited by 12 publications

(9 citation statements)

References 23 publications

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“…In our study, the predictive model was established based on the 9 FRGs-lncRNAs (AQP4-AS1, DANCR, LINC00460, LINC00892, LINC00996, MED4-AS1, SNHG7, UCA1, and WWC2-AS2). Aquaporin 4 antisense RNA 1 (AQP4-AS1) transcribes a lncRNA with unknown function, which was found related to the risk of gastric [31] and breast cancer [32]. We found that AQP4-AS1 act as a protector factor in NSCLC.…”

Section: Discussionmentioning

confidence: 95%

Identification of the Ferroptosis-Related Long Non-Coding RNAs Signature to Improve the Prognosis Prediction in patients with NSCLC

Li¹,

Zhang²,

Fan³

et al. 2021

Preprint

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Background: Non-small cell lung cancer (NSCLC) is the most prevalent type of lung carcinoma with an unfavorable prognosis. Ferroptosis, a novel iron-dependent programmed cell death, is involved in the development of multiple cancers. Of note, the prognostic value of ferroptosis-related lncRNAs in NSCLC remains uncertain. Methods: Gene expression profiles and clinical information of NSCLC were retrieved from the TCGA database. Ferroptosis-related genes (FRGs) were explored in the FerrDb database and ferroptosis-related lncRNAs (FRGs-lncRNAs) were identified by the correlation analysis and the LncTarD database. Next, The differentially expressed FRGs-lncRNAs were screened and FRGs-lncRNAs associated with the prognosis were explored by univariate Cox regression analysis and Kaplan-Meier survival analysis. Then, an FRGs-lncRNAs signature was constructed by the Lasso-penalized Cox model in the training cohort and verified by internal and external validation. Finally, the potential correlation between risk score, immune response, and chemotherapeutic sensitivity was further investigated.Results: 129 lncRNAs with a potential regulatory relationship with 59 differentially expressed FRGs were found in NSCLC and 10 FRGs-lncRNAs associated with the prognosis of NSCLC were identified (P<0.05). 9 prognostic-related FRGs-lncRNAs (AQP4-AS1, DANCR, LINC00460, LINC00892, LINC00996, MED4-AS1, SNHG7, UCA1, and WWC2-AS2) were used to construct the prognostic model and stratify patients with NSCLC into high- and low-risk groups. Kaplan-Meier analysis demonstrated a worse outcome in patients with high risk (P<0.05). Moreover, a good predictive capacity of this signature in predicting NSCLC prognosis was confirmed by the ROC curve analysis. Additionally, 45 immune checkpoint genes and 8 m6A-related genes were found differentially expressed in the two risk groups, and the sensitivity of 28 chemotherapeutics were identified to be correlated with the risk score. Conclusion: A novel FRGs-lncRNAs signature was successfully constructed, which may contribute to improving the management strategies of NSCLC.

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Section: Discussionmentioning

confidence: 95%

Identification of the Ferroptosis-Related Long Non-Coding RNAs Signature to Improve the Prognosis Prediction in patients with NSCLC

Li¹,

Zhang²,

Fan³

et al. 2021

Preprint

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“…Meanwhile, we conducted both internal and external validation to evaluate the accuracy of the signature. Of these prognostic CRlncRNAs, LINC00205 was identified as promoting malignant tumors of LUAD by sponging miR-185-5p ( 45 ); OGFRP1 constitutes an oncogene in NSCLC through the miR-4640-5p/eIF5A axis, and downregulation of OGFRP1 inhibited the progression of NSCLC ( 46 ); MIR31HG could be confirmed as a poor prognostic biomarker and a new therapeutic target for NSCLC patients through activation of the Wnt/β−catenin SP ( 47 ); AQP4-AS1 is downregulated in breast cancer tissues, and its over-expression is related to better prognoses ( 48 ); however, for the first time, LINC00592, TFAP2A-AS1 and CADM3-AS1 were unveiled in lung cancer and could represent new therapeutic targets. The LUAD patients were then classified into low-and high-risk groups according to the median risk score for subsequent analysis.…”

Section: Discussionmentioning

confidence: 99%

Cuproptosis-related lncRNA signatures: Predicting prognosis and evaluating the tumor immune microenvironment in lung adenocarcinoma

et al. 2023

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BackgroundCuproptosis, a unique kind of cell death, has implications for cancer therapy, particularly lung adenocarcinoma (LUAD). Long non-coding RNAs (lncRNAs) have been demonstrated to influence cancer cell activity by binding to a wide variety of targets, including DNA, RNA, and proteins.MethodsCuproptosis-related lncRNAs (CRlncRNAs) were utilized to build a risk model that classified patients into high-and low-risk groups. Based on the CRlncRNAs in the model, Consensus clustering analysis was used to classify LUAD patients into different subtypes. Next, we explored the differences in overall survival (OS), the tumor immune microenvironment (TIME), and the mutation landscape between different risk groups and molecular subtypes. Finally, the functions of LINC00592 were verified through in vitro experiments.ResultsPatients in various risk categories and molecular subtypes showed statistically significant variations in terms of OS, immune cell infiltration, pathway activity, and mutation patterns. Cell experiments revealed that LINC00592 knockdown significantly reduced LUAD cell proliferation, invasion, and migration ability.ConclusionThe development of a trustworthy prediction model based on CRlncRNAs may significantly aid in the assessment of patient prognosis, molecular features, and therapeutic modalities and may eventually be used in clinical applications.

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“…Energy stress-induced LINC01564 activated the serine synthesis pathway and facilitated hepatocellular carcinogenesis [ 33 ]. AQP4-AS1 plays a potential role in breast cancer [ 34 ]. The lncRNA PIK3CD-AS2 promoted lung adenocarcinoma progression via YBX1-mediated suppression of the p53 pathway [ 35 ].…”

Section: Discussionmentioning

confidence: 99%

Combined Transcriptomic and Metabolomic Analysis of Women with Polycystic Ovary Syndrome

Lin

Ding

et al. 2022

Disease Markers

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Background. Polycystic ovary syndrome (PCOS) is a complex class of endocrine disorders with insulin resistance, compensatory hyperinsulinemia, and obesity. However, the pathogenesis and therapies of PCOS have not been fully elucidated. Exosomal miRNAs have the potential to serve as biomarkers and therapies for a wide range of medical conditions. Method. We collected follicular fluid from 5 PCOS patients and 5 healthy people. High-throughput sequencing technology to identify differentially expressed miRNAs and untargeted metabolome identify differential metabolites in follicular fluid exosomal. RT-qPCR and AUC analysis were performed. Result. miRNA high-throughput sequencing identified 124 differential miRNAs. RT-qPCR analysis confirmed the sequencing results. These differential miRNA target genes are mainly involved in metabolic pathways. Metabolomics studies identified 31 differential metabolites. miRNA and lncRNA coexpression networks in metabolic pathways rigorously screened 28 differentially expressed miRNAs. This network would identify miRNA signatures associated with metabolic processes in PCOS. Meanwhile, the area under curve of receiver operating characteristic revealed that hsa-miR-196a-3p, hsa-miR-143-5p, hsa-miR-106a-3p, hsa-miR-34a-5p, and hsa-miR-20a-5p were potential biomarkers for the diagnosis of PCOS. Conclusion. Collectively, these results demonstrate the potential pathogenesis of PCOS, and follicular fluid exosomal miRNAs may be efficient targets for the diagnosis and treatment of PCOS in long-term clinical studies.

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Association between SNP rs527616 in lncRNA AQP4-AS1 and susceptibility to breast cancer in a southern Brazilian population

Cited by 12 publications

References 23 publications

Identification of the Ferroptosis-Related Long Non-Coding RNAs Signature to Improve the Prognosis Prediction in patients with NSCLC

Identification of the Ferroptosis-Related Long Non-Coding RNAs Signature to Improve the Prognosis Prediction in patients with NSCLC

Cuproptosis-related lncRNA signatures: Predicting prognosis and evaluating the tumor immune microenvironment in lung adenocarcinoma

Combined Transcriptomic and Metabolomic Analysis of Women with Polycystic Ovary Syndrome

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