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Analysis of a Long Non-coding RNA associated Signature to Predict Survival in Patients with Bladder Cancer
Wenwen Zhong1, Hu Qu1, Bing Yao1
1Department of Urology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, CHN.
Cureus
|June 13, 2022
Summary
This study identified a nine long non-coding RNA (lncRNA) signature that accurately predicts bladder cancer survival. The developed risk score model serves as a potential biomarker for patient prognosis.
Area of Science:
- Oncology
- Genomics
- Biomarker Discovery
Background:
- Bladder cancer prognosis remains challenging.
- Identifying reliable prognostic biomarkers is crucial for effective treatment strategies.
Purpose of the Study:
- To develop a prognostic model for bladder cancer survival using long non-coding RNAs (lncRNAs).
- To analyze The Cancer Genome Atlas (TCGA) data for novel lncRNA signatures.
Main Methods:
- Downloaded and analyzed TCGA gene expression data.
- Identified differentially expressed lncRNAs (DELs) between tumor and normal tissues.
- Constructed a prognostic risk score model using multivariate Cox and lasso regression analysis on a training set.
- Validated the model in an independent testing set.
Main Results:
- Screened 169 DELs, with 13 associated with prognosis (p<0.01).
- A nine-lncRNA signature (MIR497HG, LINC00968, NALCN-AS1, LINC02321, RNF144A-AS1, MNX1-AS1, FLJ22447, LINC01956, FLJ42969) was significantly related to prognosis.
- High-risk patients exhibited significantly lower survival rates in both training and testing sets (p<0.05).
- Receiver operating characteristic (ROC) curve analysis showed model performance with areas of 0.737 (training) and 0.68 (testing).
Conclusions:
- A significant nine-lncRNA signature was identified for bladder cancer.
- The risk score Cox model demonstrates potential as a valuable biomarker for predicting bladder cancer prognosis.
