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.

Molecular analysis of circulating tumor DNA from breast cancer patients before and after surgery and following adjuvant chemotherapy.

The primary aim of the present study is to provide a complex molecular profile of tumors using liquid biopsy and to monitor profile changes over time in association with surgery and administered adjuvant therapy. Our secondary aim was to compare the liquid biopsy profile with the tissue biopsy and assess concordance. A total of 27 samples of circulating tumor DNA (ctDNA) collected from 9 breast cancer patients at three different time points and their matched formalin-fixed and paraffin-embedded (FFPE) samples of primary tumor were analyzed with targeted next-generation sequencing. Somatic pathogenic variants were detected before surgery in samples from 5 patients (55.6%). The most frequently mutated genes were phosphatase and tensin homolog (4/9, 44.4%) and tumor protein 53 (4/9, 44.4%). Serial sampling of ctDNA enabled the detection of more variants compared with single-time tissue primary tumor biopsy. There were 17 ctDNA variants across all samples, but only 6 FFPE variants across all patients. In addition, the concordance between ctDNA and FFPE DNA was determined in only 1 patient, and this was connected with higher variant allele frequency. The findings of the present study suggest that liquid biopsy and tissue biopsy may be used as complementary analyses to adequately capture all tumor variants.

Comparison of Somatic Mutation Profiles Between Formalin-Fixed Paraffin Embedded Tissues and Plasma Cell-Free DNA from Ovarian Cancer Patients Before and After Surgery.

Ovarian carcinogenesis can be induced by a large number of somatic gene mutations. Circulating tumor DNA (ctDNA) released into peripheral blood can provide insights into the genomic landscape of cancer cells and monitor their dynamics. Our aim was to detect and compare the genetic profiles in tumor tissue and plasma before and after tumor resection in ovarian cancer patients. All three samples were collected from each patient. In this study, we used a commercial cancer panel to identify somatic mutations in 26 genes in seven selected patients through next-generation sequencing on the Illumina platform. Overall, 16 variants with pathogenic effect were identified in the TP53, PIK3CA, PTEN, APC, NRAS, KRAS, GNAS, and MET genes involved in important signaling pathways. The genetic alterations found in the presurgical plasma in six of seven ovarian cancer patients were no longer present in the plasma after tumor surgical removal. Identical variants in formalin-fixed paraffin embedded (FFPE) tissues and preoperative plasma specimens were observed in only two cases. These findings suggest that the detected presurgical pathogenic variants absent in postsurgery plasma are associated with the primary ovarian tumor. Finally, the low-identified concordance between FFPE and plasma can be due to various factors, but most likely to high tumor heterogeneity and low ctDNA level.

Aberrant Methylation Status of Tumour Suppressor Genes in Ovarian Cancer Tissue and Paired Plasma Samples.

Ovarian cancer is a highly heterogeneous disease and its formation is affected by many epidemiological factors. It has typical lack of early signs and symptoms, and almost 70% of ovarian cancers are diagnosed in advanced stages. Robust, early and non-invasive ovarian cancer diagnosis will certainly be beneficial. Herein we analysed the regulatory sequence methylation profiles of the RASSF1, PTEN, CDH1 and PAX1 tumour suppressor genes by pyrosequencing in healthy, benign and malignant ovarian tissues, and corresponding plasma samples. We recorded statistically significant higher methylation levels (p < 0.05) in the CDH1 and PAX1 genes in malignant tissues than in controls (39.06 ± 18.78 versus 24.22 ± 6.93; 13.55 ± 10.65 versus 5.73 ± 2.19). Higher values in the CDH1 gene were also found in plasma samples (22.25 ± 14.13 versus 46.42 ± 20.91). A similar methylation pattern with positive correlation between plasma and benign lesions was noted in the CDH1 gene (r = 0.886, p = 0.019) and malignant lesions in the PAX1 gene (r = 0.771, p < 0.001). The random forest algorithm combining methylation indices of all four genes and age determined 0.932 AUC (area under the receiver operating characteristic (ROC) curve) prediction power in the model classifying malignant lesions and controls. Our study results indicate the effects of methylation changes in ovarian cancer development and suggest that the CDH1 gene is a potential candidate for non-invasive diagnosis of ovarian cancer.

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.

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.

Association of single nucleotide polymorphisms in FGF-RAS/MAP signalling cascade with breast cancer susceptibility.

The fibroblast growth factor receptors (FGFRs) and Ras/mitogen activated protein (RAS/MAP) signalling cascades are the main molecular pathways involved in breast carcinogenesis. This study aims to determine the association between FGF10 (rs4415084 C>T), FGFR2 (rs2981582 C>T) and MAP3K1 (rs889312 A>C) gene polymorphisms and breast cancer, to analyse the discriminative ability of each SNP and to test the accuracy of the predictive breast cancer risk model which includes all SNPs. We conducted a case-control study of 170 women (57.06 ± 11.60 years) with histologically confirmed breast cancer and 146 controls (50.24 ± 10.69 years). High resolution melting (HRM) method with Sanger sequencing validation was used in analyses. We have revealed significant association of FGFR2 and MAP3K1 polymorphisms with breast cancer. The odds ratio of FGFR2 T allele was 1.897 (95% CI 1.231-2.936, p = 0.004) and MAP3K1 C allele 1.804 (95% CI 1.151-2.845, p = 0.012). FGFR2 polymorphism achieved the best discriminative ability (41.95%). The Random Forest algorithm selected FGFR2, MAP3K1 and age as important breast cancer predictors. The accuracy of this prediction model approached moderate accuracy (70%), with 35.9% sensitivity and 88.6% specificity.