A hypoxia related long non-coding RNA signature could accurately predict survival outcomes in patients with bladder cancer

ABSTRACT

Hypoxia plays a significant role in tumor progression. This study aimed to develop a hypoxia-related long noncoding RNA (lncRNA) signature for predicting survival outcomes of patients with bladder cancer (BC). The transcriptome and clinicopathologic data were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate Cox regression analysis and Lasso regression analysis were used to screened lncRNAs. Ten lncRNAs were screened out and included into the hypoxia lncRNA signature. The risk score based on hypoxia lncRNA signature could accurately predict the survival outcomes of BC patients. Immune infiltration analysis showed that six types of immune cells had significant different infiltration. Tumor mutation burden (TMB) analysis showed that the risk scores between the wild types and the mutation types of TP53, FGFR3, and RB1 were significantly different. Gene Set Enrichment Analysis (GSEA) showed that cancer-associated pathways belonged to the high risk groups and immune-related signal pathways were enriched into the low risk group. Then, we constructed a predictive model with the risk score, age, and clinical stage, which showed a robust prognostic performance. An lncRNA-mRNA coexpression network was constructed, which contained 62 lncRNA-mRNA links among 10 lncRNAs and 40 related mRNAs. In summary, the hypoxia lncRNA signature could accurately predict prognosis, chemotherapy and immunotherapy response in patients with BC and was relevant to clinicopathologic parameters and immune cell infiltration.

Graphical Abstract

KEYWORDS:

• Bladder cancer
• hypoxia
• long noncoding rna
• prognosis
• TCGA

Research Highlights

1. A hypoxia 10-lncRNA signature was established to predict BC patients’ prognosis.

2. The signature could predict chemotherapy and immunotherapy response accurately.

3. Functional enrichment analysis revealed potential effects of 10 lncRNAs in BC.

Acknowledgments

We thank all the patients who participated in this study and donated samples. We also thank Yubo Yang, Yiwei Gu, and Xiaoming Wang for their language polishing.

Availability of data and materials

The datasets generated and analyzed during the current study are obtained from TCGA (https://portal.gdc.cancer.gov) and the Molecular Signatures Database (https://www.gsea-msigdb.org/gsea/msigdb/index.jsp).

Disclosure statement

The authors have declared that no competing interest exists.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This work was supported by the 1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University (ZY2016104) and Pillar Program from Department of Science and Technology of Sichuan Province (2018SZ0219)Department of Science and Technology of Sichuan Province [2018SZ0219].