RESUMO
Alternative transcript cleavage and polyadenylation is linked to cancer cell transformation, proliferation and outcome. This has led researchers to develop methods to detect and bioinformatically analyse alternative polyadenylation as potential cancer biomarkers. If incorporated into standard prognostic measures such as gene expression and clinical parameters, these could advance cancer prognostic testing and possibly guide therapy. In this review, we focus on the existing methodologies, both experimental and computational, that have been applied to support the use of alternative polyadenylation as cancer biomarkers.
Assuntos
Regiões 3' não Traduzidas , Biomarcadores Tumorais/genética , Processamento Alternativo , Biomarcadores Tumorais/metabolismo , Biologia Computacional , Bases de Dados de Ácidos Nucleicos , Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Neoplasias/diagnóstico , Neoplasias/genética , Neoplasias/metabolismo , Poliadenilação , Sítios de Splice de RNA , RNA Mensageiro/genética , RNA Mensageiro/metabolismo , RNA-Seq , Análise de Célula ÚnicaRESUMO
Three-dimensional structures of proteins that regulate their functions can be modelled using complex network based approaches for understanding the structure-function relationship. The six mutants of the protein Lipase A from Bacillus subtilis, harbouring 2 to 12 mutations, retain their function at higher temperatures with negligible variation in their overall three-dimensional crystallographic structures. This enhanced thermostability of the mutants questions the structure-function paradigm. In this paper, a coarse-grained complex network approach is used to elucidate the structural basis of enhanced thermostability in the mutant proteins, by uncovering small but significant local changes distributed throughout the structure, rendering stability to the mutants at higher temperatures. Community structure analysis of the six mutant protein networks uncovers the specific reorganisations among the nodes/residues that occur, in absence of overall structural variations, which induce enhanced rigidity underlying the increased thermostability. This study offers a novel and significant application of complex network analysis that proposes to be useful in the understanding and designing of thermostable proteins.