LAMA4-Regulating miR-4274 and Its Host Gene SORCS2 Play a Role in IGFBP6-Dependent Effects on Phenotype of Basal-Like Breast Cancer
Inflammatory breast cancer (IBC) is an extremely malignant form of breast cancer which can be easily misdiagnosed. Conclusive prognostic IBC molecular biomarkers which are also providing the perspectives for targeted therapy are lacking so far. The aim of this study was to reveal the IBC-specific miRNA expression profile and to evaluate its association with clinicopathological parameters.
miRNA expression profiles of 13 IBC and 17 non-IBC patients were characterized using comprehensive Affymetrix GeneChip miRNA 3.0 microarray platform. Bioinformatic analysis was used to reveal IBC-specific miRNAs, deregulated pathways and potential miRNA targets.
31 differentially expressed miRNAs characterize IBC and mRNAs regulated by them and their associated pathways can functionally be attributed to IBC progression. In addition, a minimal predictive set of 4 miRNAs characteristic for the IBC phenotype and associated with the TP53 mutational status in breast cancer patients was identified.
We have characterized the complete miRNome of inflammatory breast cancer and found differentially expressed miRNAs which reliably classify the patients to IBC and non-IBC groups. We found that the mRNAs and pathways likely regulated by these miRNAs are highly relevant to cancer progression. Furthermore a minimal IBC-related predictive set of 4 miRNAs associated with the TP53 mutational status and survival for breast cancer patients was identified.
Работа посвящена математическому моделированию развития опухолевого процесса рака молочной железы. Предложена новая «объединенная матема- тическая модель роста первичной опухоли и вторичных метастазов РМЖ». Предложенная модель и реализующее ее программное средство повышает точность прогноза развития РМЖ и позволяет оптимизировать проведение диагностики вторичных отдаленных метастазов.
The search for novel parameters to predict the risk of relapse in breast cancer was conducted. Significant correlation between the risk of relapse and α-2A adrenergic receptor (ADRA2A) expression was revealed using public microarray datasets. This relationship was confirmed by validation on independent microarray dataset. It was found that when assessing the risk of BC relapse, the accuracy of prediction based solely on the expression of ADRA2A gene is close to that made using OncotypeDX and MammaPrint test systems. In this case, addition of only one or two supplemental prognostic markers (for instance, expression of SQLE gene or SQLE andDSCC1genes) to ADRA2A ensures the accuracy of prediction not inferior to reliability of these test systems.