Development and validation of a set of novel and robust 4-lncRNA-based nomogram predicting prostate cancer survival by bioinformatics analysis

Abstract

Background and objective Accumulating evidence shows that long noncoding RNAs (lncRNAs) possess great potential in the diagnosis and prognosis of prostate cancer (PCa). Therefore, this study aimed to construct an lncRNA-based signature to more accurately predict the prognosis of different PCa patients, so as to improve patient management and prognosis. Methods Through univariate and multivariate Cox regression analysis, this study constructed a 4 lncRNAs-based prognosis nomogram for the classification and prediction of survival risk in patients with PCa based on TCGA data. Then we used the data of TCGA and ICGC to verify the performance of our prediction model. The receiver operating characteristic curve was plotted for detecting and validating our prediction model sensitivity and specificity. In addition, Cox regression analysis was conducted to examine whether the signature’s prediction ability was independent of additional clinicopathological variables. Possible biological functions for those prognostic lncRNAs were predicted on those 4 protein-coding genes (PCGs) related to lncRNAs. Results Four lncRNAs (HOXB-AS3, YEATS2-AS1, LINC01679, PRRT3-AS1) were extracted after COX regression analysis for classifying patients into high and low-risk groups by different OS rates. As suggested by ROC analysis, our proposed model showed high sensitivity and specificity. Independent prognostic capability of the model from other clinicopathological factors was indicated through further analysis. Based on functional enrichment, those action sites for prognostic lncRNAs were mostly located in the extracellular matrix and cell membrane, and their functions are mainly associated with the adhesion, activation and transport of the components across the extracellular matrix or cell membrane. Conclusion Our current study successfully identifies a novel candidate, which can provide more convincing evidence for prognosis in addition to the traditional clinicopathological indicators to predict the PCa survival, and laying the foundation for offering potentially novel therapeutic treatment. Additionally, this study sheds more lights on the PCa-related molecular mechanisms.

The integration of single-cell sequencing, TCGA, and GEO data analysis revealed that PRRT3-AS1 is a biomarker and therapeutic target of SKCM

“…Similarly, Zhangxiang et al identified PRRT3-AS1 as a potential biomarker of resistance to invasive treatment for breast carcinomas (24). Moreover, PRRT3-AS1 has also been reported as a part of prognostic models for glioblastoma (25), prostate cancer (26), hepatocellular carcinoma (27), and prostate cancer (28). These findings suggest that PRRT3-AS1 may be an oncogenic biomarker.…”

“…Further, PRRT3-AS1 and AL031985.3 were identified as immune-related prognostic lncRNAs in HCC patients according to study from Liang R (25). Zhang P found that Five lncRNAs including PRRT3-AS1 were found related to focal adhesion, extracellular matrix receptor interaction, and mitogen-activated protein kinase signaling pathways in prostate cancer (26). Fan L also revealed silencing of lncRNA PRRT3-AS1 can upregulate apoptosis and autophagy downregulate migration and invasion of PC cells through the mTOR signaling pathway (28).…”

A novel cuproptosis-related LncRNA signature: Prognostic and therapeutic value for acute myeloid leukemia

“…Furthermore, expressions of AC133961.1, LINC01679 and LINC02757 were found to be significantly increased in AML patients compared to healthy controls by qPCR assay. Among the 4 cuproptosis-related lncRNA signatures, LINC01679 was initially identified in a 4 lncRNAs-based prognostic model for classification and prediction of survival in patients with prostate cancer (PCa) (26). A study (27) investigated the role of LINC01679 in PCa and found that patients with low expressions of LINC01679 had worse survival outcomes.…”

m6A‐related long noncoding RNAs predict prognosis and indicate therapeutic response in endometrial carcinoma

“…YEATS2-AS1 is differentially expressed in prostate cancer and is a high-risk factor for prostate cancer. 25 Zhang et al suggested that YEATS2-AS1 can be used as a biomarker to predict OS in sarcoma patients, providing new insights into the treatment of soft tissue sarcoma (STS). YEATS2-AS1 expression was found to be significantly higher in STS tissues than in normal tissues, and higher YEATS2-AS expression was associated with lower OS in STS patients.…”