RESUMEN
MicroRNAs have been established as key regulators of tumor gene expression and as prime biomarker candidates for clinical phenotypes in epithelial ovarian cancer (EOC). We analyzed the coexpression and regulatory structure of microRNAs and their co-localized gene targets in primary tumor tissue of 20 patients with advanced EOC in order to construct a regulatory signature for clinical prognosis. We performed an integrative analysis to identify two prognostic microRNA/mRNA coexpression modules, each enriched for consistent biological functions. One module, enriched for malignancy-related functions, was found to be upregulated in malignant versus benign samples. The second module, enriched for immune-related functions, was strongly correlated with imputed intratumoral immune infiltrates of T cells, natural killer cells, cytotoxic lymphocytes, and macrophages. We validated the prognostic relevance of the immunological module microRNAs in the publicly available The Cancer Genome Atlas data set. These findings provide novel functional roles for microRNAs in the progression of advanced EOC and possible prognostic signatures for survival.
Asunto(s)
Perfilación de la Expresión Génica , Regulación Neoplásica de la Expresión Génica , MicroARNs/genética , Neoplasias Glandulares y Epiteliales/genética , Neoplasias Glandulares y Epiteliales/inmunología , Neoplasias Ováricas/genética , Neoplasias Ováricas/inmunología , Adulto , Anciano , Anciano de 80 o más Años , Carcinoma Epitelial de Ovario , Demografía , Femenino , Humanos , Células Asesinas Naturales/metabolismo , Macrófagos/metabolismo , MicroARNs/metabolismo , Persona de Mediana Edad , Estadificación de Neoplasias , Neoplasias Glandulares y Epiteliales/patología , Neoplasias Ováricas/patología , ARN Mensajero/genética , ARN Mensajero/metabolismo , Reproducibilidad de los Resultados , Análisis de Supervivencia , Linfocitos T Citotóxicos/metabolismoRESUMEN
OBJECTIVE: To establish whether the analysis of whole-blood gene expression is useful in predicting or monitoring response to anti-tumor necrosis factor (anti-TNF) therapy in patients with rheumatoid arthritis (RA). METHODS: Whole-blood RNA (using a PAXgene system to stabilize whole-blood RNA in the collection tube) was obtained at baseline and at 14 weeks from 3 independent cohorts, consisting of a combined total of 240 RA patients who were beginning therapy with anti-TNF. We used an approach to gene expression analysis that is based on modular patterns of gene expression, or modules. RESULTS: Good and moderate responders according to the European League Against Rheumatism criteria exhibited highly significant and consistent changes in multiple gene expression modules after 14 weeks of therapy, as demonstrated by hypergeometric analysis. Strikingly, nonresponders exhibited very little change in any modules, despite exposure to TNF blockade. These patterns of change were highly consistent across all 3 cohorts, indicating that immunologic changes after TNF treatment are specific to the combination of both drug exposure and responder status. In contrast, modular patterns of gene expression did not exhibit consistent differences between responders and nonresponders at baseline in the 3 study cohorts. CONCLUSION: These data provide evidence that using gene expression modules related to inflammatory disease may provide a valuable method for objective monitoring of the response of RA patients who are treated with TNF inhibitors.