Predictive Molecular Biomarkers of Bladder Cancer Identified by Next-Generation Sequencing-Preliminary Data

Abstract

Background: The majority of patients with bladder cancer suffer from tumour recurrence. Identifying prognostic factors for tumour recurrence is crucial for treatment and follow-up in affected patients. The study aimed to assess the impact of somatic mutations in bladder cancer on patient outcomes and tumour recurrence. Methods: The study group comprised 46 patients with urothelial bladder cancers referred for transurethral resection of the tumour. A molecular study on tumour-derived DNA was performed using next-generation sequencing. Somatic mutations were screened in 50 genes involved in carcinogenesis. Results: We identified 81 variants in 23 genes, including 54 pathogenic mutations, 18 likely pathogenic variants, and 9 variants of unknown significance. The most frequently mutated genes were FGFR3, PIK3CA, and TP53 in 52%, 35%, and 24% of tumours, respectively. The average tumour-free survival was significantly longer in cases with mutations in the PIK3CA gene (p = 0.02), and mutations in the PIK3CA gene were associated with a decreased risk of tumour recurrence (Hazard Ratio = 0.26; 95% CI: 0.11-0.62; p = 0.018). Conclusions: The PIK3CA gene was shown to be a predictive marker of a low risk of bladder tumour recurrence. Molecular screening of bladder cancers supported predictive biomarkers of tumour recurrence and showed that tumour-free survival is molecularly determined.

Keywords: bladder cancer recurrence; disease-free survival; molecular biomarkers; somatic mutations.

Figure 1

The prevalence of variants identified in bladder tumours of studied patients.

Figure 2

Comparison of cancer-free survival between patients with somatic mutations (+) and patients without somatic mutations (−) in the PIK3CA gene: (a) recurrence-free survival in patients with mutations compared to patients without mutation; (b) impact of mutations in the PIK3CA gene on cancer-free survival probability of bladder cancer patients.

Figure 3

Hierarchical Cluster Analysis covering age of onset, cancer-free survival and a number of pathogenic mutations. Clusters differ significantly with respect to survival (p < 0.001). Blue and green lines indicate extracted clusters. The red dotted line indicates the cutoff level set at 50% of the length of the longest bond in the dendrogram and determines the number of clusters.