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BMC Cancer ; 18(1): 275, 2018 03 12.
Artículo en Inglés | MEDLINE | ID: mdl-29530001

RESUMEN

BACKGROUND: Ribosomes, the organelles responsible for the translation of mRNA, are comprised of four rRNAs and ~ 80 ribosomal proteins (RPs). Although canonically assumed to be maintained in equivalent proportions, some RPs have been shown to possess differential expression across tissue types. Dysregulation of RP expression occurs in a variety of human diseases, notably in many cancers, and altered expression of some RPs correlates with different tumor phenotypes and patient survival. Little work has been done, however, to characterize overall patterns of RP transcript (RPT) expression in human cancers. METHODS: To investigate the impact of global RPT expression patterns on tumor phenotypes, we analyzed RPT expression of ~ 10,000 human tumors and over 700 normal tissues from The Cancer Genome Atlas (TCGA) using t-distributed stochastic neighbor embedding (t-SNE). Clusters of tumors identified by t-SNE were then analyzed with chi-squared and t-tests to compare phenotypic data, ANOVA to compare individual RPT expression, and Kaplan-Meier curves to assess survival differences. RESULTS: Normal tissues and cancers possess distinct and readily discernible RPT expression patterns that are independent of their absolute levels of expression. In tumors, RPT patterning is distinct from that of normal tissues, identifies heretofore unrecognized tumor subtypes, and in many cases correlates with molecular, pathological, and clinical features, including survival. CONCLUSIONS: RPT expression patterns are both tissue-specific and tumor-specific. These could be used as a powerful and novel method of tumor classification, offering a potential clinical tool for prognosis and therapeutic stratification.


Asunto(s)
Genoma Humano/genética , Neoplasias/genética , Pronóstico , Proteínas Ribosómicas/genética , Regulación Neoplásica de la Expresión Génica , Humanos , Estimación de Kaplan-Meier , Neoplasias/epidemiología , Neoplasias/patología , Proteómica
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