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miRNome of inflammatory breast cancer.

Maltseva DV, Galatenko VV, Samatov TR, Zhikrivetskaya SO, Khaustova NA, Nechaev IN, Shkurnikov MU, Lebedev AE, Mityakina IA, Kaprin AD, Schumacher U, Tonevitsky AG - BMC Res Notes (2014)

Bottom Line: Conclusive prognostic IBC molecular biomarkers which are also providing the perspectives for targeted therapy are lacking so far.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.We found that the mRNAs and pathways likely regulated by these miRNAs are highly relevant to cancer progression.

View Article: PubMed Central - PubMed

Affiliation: SRC Bioclinicum, Ugreshskaya str 2/85, 115088 Moscow, Russia. t.samatov@bioclinicum.com.

ABSTRACT

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

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Related in: MedlinePlus

Association of a predictive set of 4 miRNAs with the TP53 mutational status. Classifier values L for TP53-mutated (Mut) and TP53 wild-type (WT) samples. Smaller bar shows the estimate of the mean value, larger bar shows a 95% confidence interval for the mean value. Vertical line shows mean value ± standard deviation.
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Fig2: Association of a predictive set of 4 miRNAs with the TP53 mutational status. Classifier values L for TP53-mutated (Mut) and TP53 wild-type (WT) samples. Smaller bar shows the estimate of the mean value, larger bar shows a 95% confidence interval for the mean value. Vertical line shows mean value ± standard deviation.

Mentions: We hypothesized that the identified set of 4 miRNAs could be associated with clinico-pathological characteristics of breast cancer patients in general. To test this hypothesis we used published miRNA dataset of 101 breast cancer patient collection with GEO accession number GSE19783 [33]. The analysis revealed significant association of miRNA set with the TP53 mutational status characterized by the p-value of 1.7 × 10-4 (Figure 2). The dataset included 64 wild-type TP53 samples and 37 samples with mutated TP53.Figure 2


miRNome of inflammatory breast cancer.

Maltseva DV, Galatenko VV, Samatov TR, Zhikrivetskaya SO, Khaustova NA, Nechaev IN, Shkurnikov MU, Lebedev AE, Mityakina IA, Kaprin AD, Schumacher U, Tonevitsky AG - BMC Res Notes (2014)

Association of a predictive set of 4 miRNAs with the TP53 mutational status. Classifier values L for TP53-mutated (Mut) and TP53 wild-type (WT) samples. Smaller bar shows the estimate of the mean value, larger bar shows a 95% confidence interval for the mean value. Vertical line shows mean value ± standard deviation.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4289319&req=5

Fig2: Association of a predictive set of 4 miRNAs with the TP53 mutational status. Classifier values L for TP53-mutated (Mut) and TP53 wild-type (WT) samples. Smaller bar shows the estimate of the mean value, larger bar shows a 95% confidence interval for the mean value. Vertical line shows mean value ± standard deviation.
Mentions: We hypothesized that the identified set of 4 miRNAs could be associated with clinico-pathological characteristics of breast cancer patients in general. To test this hypothesis we used published miRNA dataset of 101 breast cancer patient collection with GEO accession number GSE19783 [33]. The analysis revealed significant association of miRNA set with the TP53 mutational status characterized by the p-value of 1.7 × 10-4 (Figure 2). The dataset included 64 wild-type TP53 samples and 37 samples with mutated TP53.Figure 2

Bottom Line: Conclusive prognostic IBC molecular biomarkers which are also providing the perspectives for targeted therapy are lacking so far.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.We found that the mRNAs and pathways likely regulated by these miRNAs are highly relevant to cancer progression.

View Article: PubMed Central - PubMed

Affiliation: SRC Bioclinicum, Ugreshskaya str 2/85, 115088 Moscow, Russia. t.samatov@bioclinicum.com.

ABSTRACT

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Show MeSH
Related in: MedlinePlus