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Inferring Bladder Cancer Evolution from Mucosal field Effects by Whole-Organ Spatial Mutational, Proteomic, and Metabolomic Mapping. | LitMetric

AI Article Synopsis

Article Abstract

Multi-platform mutational, proteomic, and metabolomic spatial mapping was used on the whole-organ scale to identify the molecular evolution of bladder cancer from mucosal field effects. We identified complex proteomic and metabolomic dysregulations in microscopically normal areas of bladder mucosa adjacent to dysplasia and carcinoma . The mutational landscape developed in a background of complex defects of protein homeostasis which included dysregulated nucleocytoplasmic transport, splicesome, ribosome biogenesis, and peroxisome. These changes were combined with altered urothelial differentiation which involved lipid metabolism and protein degradations controlled by PPAR. The complex alterations of proteome were accompanied by dysregulation of gluco-lipid energy-related metabolism. The analysis of mutational landscape identified three types of mutations based on their geographic distribution and variant allele frequencies. The most common were low frequency α mutations restricted to individual mucosal samples. The two other groups of mutations were associated with clonal expansion. The first of this group referred to as β mutations occurred at low frequencies across the mucosa. The second of this group called γ mutations increased in frequency with disease progression. Modeling of the mutations revealed that carcinogenesis may span nearly 30 years and can be divided into dormant and progressive phases. The α mutations developed gradually in the dormant phase. The progressive phase lasted approximately five years and was signified by the advent of β mutations, but it was driven by γ mutations which developed during the last 2-3 years of disease progression to invasive cancer. Our study indicates that the understanding of complex alterations involving mucosal microenvironment initiating bladder carcinogenesis can be inferred from the multi-platform whole-organ mapping.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11042420PMC
http://dx.doi.org/10.21203/rs.3.rs-3994376/v1DOI Listing

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