Poor prognosis among radiation associated bladder cancer is defined by clinicogenomic features.

Radiation therapy (RT) for prostate cancer has been associated with an increased risk for the development of bladder cancer. We aimed to integrate clinical and genomic data to better understand the development of RT-associated bladder cancer. A retrospective analysis was performed to identify control (CTRL; n= 41) and RT-associated (n=41) bladder cancer patients. RT and CTRL specific features were then identified through integration and analysis of the genomic sequencing data and clinical variables. RT-associated bladder tumors were significantly enriched for alterations in KDM6A and ATM, while CTRL tumors were enriched for CDKN2A mutation. Globally, there was an increased number of variants within RT tumors, albeit at a lower variant allele frequency. Mutational signature analysis revealed three predominate motif patterns, with similarity to SBS2/13 (APOBEC3A), SBS5 (ERCC2/Smoking) and SBS6/15 (MMR). Poor prognostic factors in the RT cohort include, a short tumor latency, smoking status, the presence of the smoking and XRT mutational signatures, and CDKN2A copy number loss. Based on the clinical and genomic findings, we suggest, at least two potential pathways leading to RT-associated bladder cancer; the first, occurs in the setting of field cancerization, related to smoking or pre-existing genetic alterations and leads to the development of more aggressive bladder tumors, and the second, in which RT initiates the oncogenic process in otherwise healthy urothelium, leading to a longer latency and less aggressive disease.

Understanding variants of unknown significance and classification of genomic alterations.

Despite recent efforts to issue clinical guidelines outlining strategies to define the pathogenicity of genomic variants, there is currently no standardized framework for which to make these assertions. This review does not present a step-by-step methodology, but rather takes a holistic approach to discuss many aspects which should be taken into consideration when determining variant pathogenicity. Categorization should be curated to reflect relevant findings within the scope of the specific medical context. Functional characterization should evaluate all available information, including results from literature reviews, different classes of genomic data repositories, and applicable computational predictive algorithms. This article further proposes a multidimensional view to infer pathogenic status from many genomic measurements across multiple axes. Notably, tumor suppressors and oncogenes exhibit fundamentally different biology which helps refine the importance of effects on splicing, mutation interactions, copy number thresholds, rearrangement annotations, germline status, and genome-wide signatures. Understanding these relevant datapoints with thoughtful perspective could aid in the reclassification of variants of unknown significance (VUS), which are ambiguously understood and currently have uncertain clinical implications. Ongoing assessments of VUS examining these relevant biological axes could lead to more accurate classification of variant pathogenicity interpretation in diagnostic oncology.