Pathway Analysis of Selected Circulating miRNAs in Plasma of Breast Cancer Patients: A Preliminary Study.

MicroRNAs in the circulation of breast cancer (BC) patients have great potential for the early diagnosis, treatment and monitoring of breast cancer. The aim of this preliminary study was to obtain the expression profile of selected miRNAs in the plasma of BC patients that could discriminate BC patients from healthy volunteers and may be useful in early detection of BC. Significantly deregulated miRNAs were evaluated by pathway analysis with the prediction of potential miRNA targets. The study enrolled plasma samples from 65 BC patients and 34 healthy volunteers. Selected miRNAs were screened in pilot testing by the real-time PCR (qPCR) method, and the most appropriate reference genes were selected for normalisation by the geNorm algorithm. In the final testing, we detected miR-99a, miR-130a, miR-484 and miR-1260a (p < 0.05) as significantly up-regulated in the plasma of BC patients. Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis revealed that all significantly deregulated miRNAs are involved in the Hippo and Transforming Growth Factor-beta (TGF-beta) signalling pathways. Our study confirmed a different profile of selected circulating miRNAs in the plasma of BC patients with an emphasis on some critical points in the analysis process.

Why the Gold Standard Approach by Mammography Demands Extension by Multiomics? Application of Liquid Biopsy miRNA Profiles to Breast Cancer Disease Management.

In the global context, the epidemic of breast cancer (BC) is evident for the early 21st century. Evidence shows that national mammography screening programs have sufficiently reduced BC related mortality. Therefore, the great utility of the mammography-based screening is not an issue. However, both false positive and false negative BC diagnosis, excessive biopsies, and irradiation linked to mammography application, as well as sub-optimal mammography-based screening, such as in the case of high-dense breast tissue in young females, altogether increase awareness among the experts regarding the limitations of mammography-based screening. Severe concerns regarding the mammography as the "golden standard" approach demanding complementary tools to cover the evident deficits led the authors to present innovative strategies, which would sufficiently improve the quality of the BC management and services to the patient. Contextually, this article provides insights into mammography deficits and current clinical data demonstrating the great potential of non-invasive diagnostic tools utilizing circulating miRNA profiles as an adjunct to conventional mammography for the population screening and personalization of BC management.

miRNA in a multiomic context for diagnosis, treatment monitoring and personalized management of metastatic breast cancer.

Metastatic breast cancer is characterized by aggressive spreading to distant organs. Despite huge multilevel research, there are still several important challenges that have to be clarified in the management of this disease. Therefore, recent investigations have implemented a modern, multiomic approach with the aim of identifying specific biomarkers for not only early detection but also to predict treatment responses and metastatic spread. Specific attention is paid to short miRNAs, which regulate gene expression at the post-transcriptional level. Aberrant miRNA expression could initiate cancer development, cell proliferation, invasion, migration, metastatic spread or drug resistance. An miRNA signature is, therefore, believed to be a promising biomarker and prediction tool that could be utilized in all phases of carcinogenesis. This article offers comprehensive information about miRNA profiles useful for diagnostic and treatment purposes that may sufficiently advance breast cancer management and improve individual outcomes in the near future.

Droplet digital PCR analysis of CDH13 methylation status in Slovak women with invasive ductal breast cancer.

Identifying novel epigenetic biomarkers is a promising way to improve the clinical management of patients with breast cancer. Our study aimed to determine the methylation pattern of 25 tumor suppressor genes (TSG) and select the best methylation biomarker associated with clinicopathological features in the cohort of Slovak patients diagnosed with invasive ductal carcinoma (IDC). Overall, 166 formalin-fixed, paraffin-embedded (FFPE) tissues obtained from patients with IDC were included in the study. The methylation status of the promoter regions of 25 TSG was analyzed using semiquantitative methylation-specific MLPA (MS-MLPA). We identified CDH13 as the most frequently methylated gene in our cohort of patients. Further analysis by ddPCR confirmed an increased level of methylation in the promoter region of CDH13. A significant difference in CDH13 methylation levels was observed between IDC molecular subtypes LUM A versus HER2 (P = 0.0116) and HER2 versus TNBC (P = 0.0234). In addition, significantly higher methylation was detected in HER2+ versus HER2- tumors (P = 0.0004) and PR- versus PR+ tumors (P = 0.0421). Our results provide evidence that alteration in CDH13 methylation is associated with clinicopathological features in the cohort of Slovak patients with IDC. In addition, using ddPCR as a methylation-sensitive method represents a promising approach characterized by higher precision and technical simplicity to measure the methylation of target CpGs in CDH13 compared to other conventional methods such as MS-MLPA.

Aberrantly Methylated cfDNA in Body Fluids as a Promising Diagnostic Tool for Early Detection of Breast Cancer.

Breast malignancies are the leading type of cancer among women. Its prevention and early detection, particularly in young women, remains challenging. To this end, cell-free DNA (cfDNA) detected in body fluids demonstrates great potential for early detection of tissue transformation and altered molecular setup, such as epigenetic profiles. Aberrantly methylated cfDNA in body fluids could therefore serve as a potential diagnostic and prognostic tool in breast cancer management. Abnormal methylation may lead to both an activation of oncogenes via hypomethylation and an inactivation of tumor suppressor genes by hypermethylation. We update the state of the art in the area of aberrant cfDNA methylation analyses as a diagnostic and prognostic tool in breast cancer, report on the main technological challenges, and provide an outlook for advancing the overall management of breast malignancies based on cfDNA as a target for diagnosis and tailored therapies.

Predictive accuracy of the breast cancer genetic risk model based on eight common genetic variants: The BACkSIDE study.

Breast cancer (BC) development is caused by the interaction of environmental and genetic factors. At least 90 susceptible genetic variants with different population penetration and incidence have been associated with BC. This paper therefore analysed the individual discrimination power of 8 low penetrant common genetic variants and calculated the predictive accuracy of the genetic risk model. The study enrolled 171 women with developed breast cancer (57.06 ± 11.60 years) and 146 control subjects (50.24 ± 10.69 years). The genotyping was performed by high resolution melting method (HRM) and confirmed by Sanger sequencing, and the Random Forest algorithm provided the ROC curve with AUC values. Significant association with BC was confirmed in 2 SNPs: rs2981582 FGFR2 and rs889312 MAP3K1, and the odds ratios of homozygotes with two risk alleles in both SNP's were higher than in heterozygotes with one mutant allele, as follows: FGFR2 TT: 1.953 (95%CI 1.014-3.834, p = 0.049), CT 1.771 (95%CI 1.088-2.899, p = 0.026) and MAP3K1 CC 2.894 (95%CI 1.028-9.566, p = 0.048), AC 1.760 (95%CI 1.108-2.813, p = 0.019). FGFR2 had the best discrimination ability, followed by MAP3K1 and CASP8. Discriminative accuracy of the genetic risk model distinguishing the breast cancer patients and controls explained by AUC was 0.728, with 70.6% sensitivity and 65.1% specificity. Our study results therefore confirmed polygenic breast cancer inheritance with important involvement of FGFR2, MAP3K1, LSP1 and CASP8 gene variants.