Current approaches in the clinical management of pregnancy-associated breast cancer-pros and cons.

Malignancies are one of the leading causes of mortality in women during their reproductive life. Treatment of gynecological malignant tumors during pregnancy is possible but not simple, since it creates a conflict between care of the mother and the fetus. BC is the most prevalent malignancy diagnosed in pregnancy, ranking up to 21% of all pregnancy-related malignancies. Due to its stets increasing prevalence, aggressive cancer subtype, and severe ethical and psychological aspects linked to the disease, experts raise an alarm for an acute necessity to improve the overall management of the PABC-the issue which has strongly motivated our current paper. Comprehensive research data and clinical experience accumulated in recent years have advanced our understanding of the disease complexity. PABC treatment must be individualized with an emphasis on optimal care of the mother, while observing standard treatment protocols with regard to safety of the fetus. Treatment protocols should be elaborated based on the individualized patient profile, bearing in mind the acute danger to the mother, maximizing the therapy efficacy and minimizing harmful effects to the fetus. Complex consulting on treatment options, their impacts on pregnancy and potential teratogenic effects requires tight "doctor-patient" collaboration. Complications that may arise due to the treatment of breast cancer in pregnancy require a multiprofessional expertise including oncologists, neonatologists, perinatologists, obstetricians, teratologists, and toxicologists, and an extensive psychological support throughout the pregnancy and after giving birth. Thereby, specifically psychological aspects of PABC diagnosis and follow-up are frequently neglected, being not yet adequately explored in the entire disease management approach. Herewith, we update the status quo regarding the currently available diagnostic modalities, complex treatment algorithms, and novel clinical approaches which altogether argue for an urgent necessity of a paradigm shift moving away from reactive to predictive, preventive, and personalized medical approach in the overall management of PABC meeting the needs of young populations, persons at high risk, affected patients, and families as the society at large.

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.

Breast cancer and Flammer syndrome: any symptoms in common for prediction, prevention and personalised medical approach?

An epidemic scale of the breast cancer (BC) prevalence is actually recognised as the reality of the early twenty-first century. Particularly alarming is that the sporadic BC (about 90% of all patients) creates currently unpredictable subpopulations in terms of disease predisposition, development and progression. Despite broad discussions run since years in BC area, no any plausible approach has been suggested so far to get the overall situation better controlled in the populations. Here, we present highly innovative concepts considering investigation of specific syndromes and symptoms underestimated till now in relationship with BC predisposition and development. Consequently, the purpose of our pilot project was to evaluate the prevalence of Flammer Syndrome (FS) in BC patient cohort. The results achieved here support the main hypothesis of the project clearly demonstrating the tendency of BC patients to the increased prevalence of FS symptoms compared to the disease-free individuals. Our study strongly indicates the relevance of FS symptoms for BC pathology such as feeling inadequately cold, deficient thermoregulation, altered sensitivity to different stimuli, potential dehydration, altered sleep patterns, tendency towards headache, migraine attacks and dizziness. Moreover, the symptoms' appearance is specifically linked to the individual BC subtypes. Potential mechanisms interconnecting FS with BC pathology are discussed.

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.