Non-Coding Mutations in Urothelial Bladder Cancer: Biological and Clinical Relevance and Potential Utility as Biomarkers

Abstract

BACKGROUND & OBJECTIVE: Whole genome sequencing has identified recurrent non-coding mutations that may be important in carcinogenesis. We investigate the frequency of 5 such non-coding mutation hotspots in urothelial bladder cancers (UBCs) and assess their potential for UBC detection and prognostication. METHODS: DNA extracted from 302 UBCs was subjected to targeted next generation sequencing of non-coding mutation hotspots in GPR126, PLEKHS1, TBC1D12, LEPROTL1 and WDR74. The frequency of mutations, and associations with stage, grade, age, gender, smoking status, clinical outcomes, mutation signatures and gene expression were analysed using χ 2 tests, logistic regression and Cox proportional hazards models. RESULTS: Non-coding mutations were common across all stages and grades of UBC. The frequencies were: GPR126 53.0%, PLEKHS1 38.7%, TBC1D12 25.5%, LEPROTL1 23.8% and WDR74 17.2%. There was an average of 1.6 mutations per UBC, and 74% of UBCs harboured at least one mutation. They frequently co-occur, and commonly accompany an APOBEC mutational signature. The mutations are not strongly associated with clinical parameters and are, most likely, early events in the development of UBC. CONCLUSIONS: Mutations at these 5 non-coding hotspots are common in UBC. Due to their high frequency across stages and grades of disease, they should be included in UBC diagnostic biomarker panels.

Non-Coding Mutations in Urothelial Bladder Cancer: Biological and Clinical Relevance and Potential Utility as Biomarkers

“…Building on previous studies to provide evidence for the inclusion of non-coding elements as potential biomarkers for urothelial bladder cancer (UBC) [2][3][4][5][6], Jeeta et al [1] recently identified clinically relevant non-coding mutations in five genes (TBC1D12, GPR126, PLEKHS1, LEPROTL1 and WDR74). Clinical relevance was assessed by performing analyses of mutation frequencies across disease stages, association with clinical outcomes, distribution of mutations relative to one another, relative to mutational signatures, their effects on gene expression, and isoform usage.…”

“…Substantiated by χ2 tests, logistic regression, and Cox proportional-hazards models, all of these analyses were informative. However, with regard to mutation frequencies, a more direct calculation of their cancer effect size-which accounts for underlying rates of mutation at each site and quantifies 1 (https://orcid.org/0000-0002-3548-5912) 2 (https://orcid.org/0000-0001-9306-6065) * Correspondence to: Jeffrey Townsend, Department of Biostatistics, Yale School of Public Health, 135 College Street, New Haven, CT 06510, USA. Tel.…”

Urine tumor DNA detection of minimal residual disease in muscle-invasive bladder cancer treated with curative-intent radical cystectomy: A cohort study

“…Notably, utDNA analysis from urine was performed without prior sequencing of tumor tissue (i.e., tumor-naive approach). We used a focused MRD gene panel encompassing 49 consensus driver genes frequently mutated in bladder cancer [ 36 – 40 ] ( S2 Table ). For SNV calling from urine, we utilized the CAPP-Seq with iDES pipeline [ 20 , 21 , 28 ] and filtered out any mutation also detected in the matched germline DNA sample.…”

“…Silent mutations included the following: exonic synonymous mutations, intronic mutations (except in PLEKHS1 ), promoter mutations (except in TERT ), 5′ UTR mutations (except in TBC1D12 ), and 3′ UTR mutations. Non-silent mutations included the following: exonic nonsynonymous mutations, splicing mutations, stop codon mutations, and the aforementioned exceptions based on evidence in the literature [ 28 , 36 , 38 ]. Overall utDNA levels were finally quantified as the highest variant allele fraction among non-silent mutations with duplex support detected by CAPP-Seq per urine sample.…”

An integrated multi-omics analysis identifies clinically relevant molecular subtypes of non-muscle-invasive bladder cancer

“…Unpublished cohort 4 provided by Richard Bryan : RNA-Seq based analysis of 85 tumors from the West Midlands Bladder Cancer Prognosis Programme (BCPP, ethics approval 06/MRE04/65), as previously described 78 . RNA libraries were prepared using the Truseq Stranded Total RNA with Ribo-zero Gold kit (Illumina) and 2 × 100 bp PE sequenced (Hiseq, n=26) or 2 × 75 bp PE sequenced (Nextseq, n=52).…”