Identification of a Long Noncoding RNA <i>TRAF3IP2-AS1</i> as Key Regulator of IL-17 Signaling through the SRSF10–IRF1–Act1 Axis in Autoimmune Diseases

He, Ruirui; Wu, Songfang; Gao, Ru; Chen, Jianwen; Peng, Qianwen; Hu, Huijun; Zhu, Liwen; Du, Yanyun; Sun, Wanwei; Ma, Xiaojian; Zhang, Huazhi; Cui, Zhenzhong; Wang, Heping; Martin, Bradley N.; Wang, Yueying; Zhang, Cunjin; Wang, Chenhui

doi:10.4049/jimmunol.2001223

Cited by 21 publications

(14 citation statements)

References 57 publications

(40 reference statements)

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“…TRAF3IP2-AS1, expressed from TRAF3IP2, is a natural antisense lncRNA and has decreased expression in NONO-TFE3 translocation renal cell carcinoma, which promotes progression of tumor [ 36 ]. Besides, in IL-17-related autoimmune diseases, such as psoriasis and multiple sclerosis, TRAF3IP2-AS1 may represent attractive therapeutic targets [ 37 ]. Out results illustrated that TRAF3IP2-AS1 might predict a better prognosis in patient with pancreatic cancer.…”

Section: Discussionmentioning

confidence: 99%

Development of epithelial-mesenchymal transition-related lncRNA signature for predicting survival and immune microenvironment in pancreatic cancerwithexperiment validation

et al. 2021

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Long non-coding RNAs (LncRNAs) have crucial function in epithelial–mesenchymal transition (EMT) in pancreatic cancer. It is necessary to comprehensively analyze the potential role of EMT-related lncRNA in pancreatic cancer. In the present study, genomic data of pancreatic cancer from the TCGA database were downloaded and we found 368 EMT-related lncRNAs. According to the expression characteristics of prognostic-related lncRNAs, all samples could be divided into two clusters with different clinical outcomes and different tumor microenvironments. Moreover, an eleven EMT-related lncRNAs signature was established and verified. Patients with pancreatic cancer in the high-risk group had a shorter overall survival than those in the low-risk group and the signature could act as an independent prognostic factor. Further analysis suggested that the EMT-related lncRNAs might affect the prognosis of patients through immune mechanisms. All findings indicated that the signature and eleven lncRNAs might serve as potential prognostic biomarkers and therapeutic targets in the treatment of pancreatic cancer.

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Section: Discussionmentioning

confidence: 99%

Development of epithelial-mesenchymal transition-related lncRNA signature for predicting survival and immune microenvironment in pancreatic cancerwithexperiment validation

et al. 2021

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“…To evaluate the value of these molecules in predicting the prognosis of AML patients, we identified risk signals using LASSO regression analysis, and constructed a risk prediction model based on six lncRNAs to predict OS in AML patients, Lasso regression analysis removes redundant genes, increasing the stability of the model to prevent overfitting. Among the lncRNAs involved in model construction, TRAF3IP2-AS1 is a key regulator of interleukin-17 signaling in autoimmune diseases 64 . Low levels of expression of TRAF3IP2-AS1 promotes the development of non-O-TFE3 translocation renal cell carcinoma 65 .…”

Section: Discussionmentioning

confidence: 99%

m6A-related lncRNAs predict prognosis and indicate immune microenvironment in acute myeloid leukemia

Zhong

Yao

Cheng

et al. 2022

Sci Rep

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Acute myeloid leukemia (AML) is a complex hematologic malignancy. Survival rate of AML patients is low. N6-methyladenosine (m6A) and long non-coding RNAs (lncRNAs) play important roles in AML tumorigenesis and progression. However, the relationship between lncRNAs and biological characteristics of AML, as well as how lncRNAs influence the prognosis of AML patients, remain unclear. In this study. In this study, Pearson correlation analysis was used to identify lncRNAs related to m6A regulatory genes, namely m6A-related lncRNAs. And we analyzed their roles and prognostic values in AML. m6A-related lncRNAs associated with patient prognosis were screened using univariate Cox regression analysis, followed by systematic analysis of the relationship between these genes and AML clinicopathologic and biologic characteristics. Furthermore, we examined the characteristics of tumor immune microenvironment (TIME) using different IncRNA clustering models. Using LASSO regression, we identified the risk signals related to prognosis of AML patients. We then constructed and verified a risk model based on m6A-related lncRNAs for independent prediction of overall survival in AML patients. Our results indicate that risk scores, calculated based on risk-related signaling, were related to the clinicopathologic characteristics of AML and level of immune infiltration. Finally, we examined the expression level of TRAF3IP2-AS1 in patient samples through real-time polymerase chain reaction analysis and in GEO datasets, and we identified a interaction relationship between SRSF10 and TRAF3IP2-AS1 through in vitro assays. Our study shows that m6A-related lncRNAs, evaluated using the risk prediction model, can potentially be used to predict prognosis and design immunotherapy in AML patients.

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“… Shuai Yang et al (2021) investigated the inhibitory effect of the tumor growth suppressor TRAF3IP2-AS1 on the progression of NONO-TFE3-translocated renal carcinoma and found that the overexpression of TRaf3IP2-AS1 could stimulate N6-methyladenosine of PARP1 mRNA and downregulate PTEN, further inhibiting the progression of renal carcinoma. He et al (2021) showed that TRAF3IP2-AS1 may be an attractive therapeutic target for IL-17-related autoimmune diseases, such as psoriasis and multiple sclerosis. Bannon et al (2015) analyzed clinical samples and showed that TRAF3IP2-AS1 exhibits high expression in cocaine abusers, positively correlating with the opposite chain protein encoding transcript TRAF3IP2.…”

Section: Discussionmentioning

confidence: 99%

Prognostication of Pancreatic Cancer Using The Cancer Genome Atlas Based Ferroptosis-Related Long Non-Coding RNAs

Zhang

Tao

et al. 2022

Front. Genet.

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Background: Long non-coding RNAs (lncRNAs) are key regulators of pancreatic cancer development and are involved in ferroptosis regulation. LncRNA transcript levels serve as a prognostic factor for pancreatic cancer. Therefore, identifying ferroptosis-related lncRNAs (FRLs) with prognostic value in pancreatic cancer is critical.Methods: In this study, FRLs were identified by combining The Cancer Genome Atlas (TCGA) and FerrDb databases. For training cohort, univariate Cox, Lasso, and multivariate Cox regression analyses were applied to identify prognosis FRLs and then construct a prognostic FRLs signature. Testing cohort and entire cohort were applied to validate the prognostic signature. Moreover, the nomogram was performed to predict prognosis at different clinicopathological stages and risk scores. A co-expression network with 76 lncRNA-mRNA targets was constructed.Results: Univariate Cox analysis was performed to analyze the prognostic value of 193 lncRNAs. Furthermore, the least absolute shrinkage and selection operator and the multivariate Cox analysis were used to assess the prognostic value of these ferroptosis-related lncRNAs. A prognostic risk model, of six lncRNAs, including LINC01705, AC068620.2, TRAF3IP2-AS1, AC092171.2, AC099850.3, and MIR193BHG was constructed. The Kaplan Meier (KM) and time-related receiver operating characteristic (ROC) curve analysis were performed to calculate overall survival and compare high- and low-risk groups. There was also a significant difference in survival time between the high-risk and low-risk groups for the testing cohort and the entire cohort, with AUCs of .723, .753, respectively. Combined with clinicopathological characteristics, the risk model was validated as a new independent prognostic factor for pancreatic adenocarcinoma through univariate and multivariate Cox regression. Moreover, a nomogram showed good prediction.Conclusion: The signature of six FRLs had significant prognostic value for pancreatic adenocarcinoma. They may be a promising therapeutic target in clinical practice.

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Identification of a Long Noncoding RNA TRAF3IP2-AS1 as Key Regulator of IL-17 Signaling through the SRSF10–IRF1–Act1 Axis in Autoimmune Diseases

Cited by 21 publications

References 57 publications

Development of epithelial-mesenchymal transition-related lncRNA signature for predicting survival and immune microenvironment in pancreatic cancerwithexperiment validation

Development of epithelial-mesenchymal transition-related lncRNA signature for predicting survival and immune microenvironment in pancreatic cancerwithexperiment validation

m6A-related lncRNAs predict prognosis and indicate immune microenvironment in acute myeloid leukemia

Prognostication of Pancreatic Cancer Using The Cancer Genome Atlas Based Ferroptosis-Related Long Non-Coding RNAs

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