Radoslav Davidovic

The impact of PTEN tumor suppressor gene on acquiring resistance to tamoxifen treatment in breast cancer patients

Tamoxifen is a standard therapeutical treatment in patients with estrogen receptor positive breast carcinoma. However, less than 50% of estrogen receptor positive breast cancers do not respond to tamoxifen treatment whereas 40% of tumors that initially respond to treatment develop resistance over time. The underlying mechanisms for tamoxifen resistance are probably multifactorial but remain largely unknown. The primary aim of this study was to investigate the impact of PTEN tumor suppressor gene on acquiring resistance to tamoxifen by analyzing loss of heterozygosity (LOH) and immunohystochemical expression of PTEN in 49 primary breast carcinomas of patients treated with tamoxifen as the only adjuvant therapy. The effect of PTEN inactivation on breast cancer progression and disease outcome was also analyzed. Reduced or completely lost PTEN expression was observed in 55.1% of samples, while 63.3% of samples displayed LOH of PTEN gene. Inactivation of PTEN immunoexpression significantly correlated with the PTEN loss of heterozygosity, suggesting LOH as the most important genetic mechanism for the reduction or complete loss of PTEN expression in primary breast carcinoma. Most importantly, LOH of PTEN and consequential reduction of its immunoexpression showed significant correlation with the recurrence of the disease. Besides, our study revealed that LOH of PTEN tumor suppressor was significantly associated with shorter disease free survival, breast cancer specific survival and overall survival. In summary, our results imply that LOH of PTEN could be used as a good prognostic characteristic for the outcome of breast cancer patients treated with tamoxifen.

MicroRNA in breast cancer: The association with BRCA1/2

Breast cancer (BC) is a heterogeneous disease in an urgent need for developing novel research, classification, and therapy approaches. Breast cancer 1 (BRCA1) and breast cancer 2 (BRCA2) proteins are well described tumor suppressors with great potential to be the subjects of different therapies. MicroRNAs (miRNAs) are genetic elements that might be used to solve the complex BC puzzle. BRCA1 was described to be the target of up to 100 miRNAs. BRCA1 may directly repress miR-155 activity. In addition, miR-15/107/182-mediated downregulation of BRCA1 interrupt DNA repair and may change the course of BC therapy. miR-146a and miR-146-5p silencing BRCA1 may trigger formation of triple-negative and basal-like sporadic BC cases. miR-182 might effect the therapy outcome. miR-21 targeted therapy might be useful for the treatment of BRCA2 mutation carriers. miR-342 overexpression and the absence of functional BRCA1 gene might cause synthetic lethality, which might be used as a base for future therapies. The present review discusses the latest data from studies that focus on the complex network of miRNAs and BRCA1/2 related BCs, which might be important for improving the therapy within the patients with triple-negative BC (TNBC) and basal-like BC, and for understanding the formation of TNBC.

Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes

BACKGROUND The significant number of protein-protein interactions (PPIs) discovered by harnessing concomitant advances in the fields of sequencing, crystallography, spectrometry and two-hybrid screening suggests astonishing prospects for remodelling drug discovery. The PPI space which includes up to 650 000 entities is a remarkable reservoir of potential therapeutic targets for every human disease. In order to allow modern drug discovery programs to leverage this we should be able to discern complete PPI maps associated with a specific disorder and corresponding normal physiology. OBJECTIVE Here, we will review community available computational programs for predicting PPIs and web-based resources for storing experimentally annotated interactions. METHODS We compared the capacities of prediction tools: iLoops, Struck2Net, HOMCOS, COTH, PrePPI, InterPreTS and PRISM to predict recently discovered protein interactions. RESULTS We described sequence-based and structure-based PPI prediction tools and addressed their peculiarities. Additionally, since the usefulness of prediction algorithms critically depends on the quality and quantity of the experimental data they are built on, we extensively discussed community resources for protein interactions. We focused on the active and recently updated primary and secondary PPI databases, repositories specialized to the subject or species, as well as databases that include both experimental and predicted PPIs. CONCLUSION PPI complexes are the basis of important physiological processes and therefore, possible targets for cell-penetrating ligands. Reliable computational PPI predictions can speed up new target discoveries through prioritization of therapeutically relevant protein-protein complexes for experimental studies.

Methylation-specific PCR: four steps in primer design

Methylation-specific PCR (MSP) is still the method of choice for a single gene methylation study. The proper design of the primer pairs is a prerequisite for obtaining reliable PCR results. Despite numerous protocols describing the rules for MSP primer design, none of them provide a comprehensive approach to the problem. Our aim was to depict a workflow for the primer design that is concise and easy to follow. In order to achieve this goal, adequate tools for promoter sequence retrieval, MSP primer design and subsequent in silico analysis are presented and discussed. Furthermore, a few instructive examples regarding a good versus a poor primer design are provided. Finally, primer design is demonstrated according to the proposed workflow. This article aims to provide researchers, interested in a single gene methylation studies, with useful information regarding successful primer design.

Significance of β-catenin expression for the incidence of pathological fractures in giant cell tumors of bone

Aim of the study is to determine the possible roles of p53, cyclin D1, β-catenin and Ki-67 in the increase in risk of fractures in patients with giant cell tumor of bone. The study included a total of 164 patients with giant cell tumor of bone (GCTB), 21 (12.8%) with and 143 (87.2%) without fracture. The samples were analyzed immunohistochemically for expression of Ki-67, p53, cyclin D1 and β-catenin. According to the immunohistochemical expression of p53 and Ki 67 in mononuclear stromal cells, as well as of cyclin D1 in multinuclear giant cells, there was no significant association with immunopositivity and risk of fractures. However, our research revealed that patients with cytoplasmic expression of b-catenin in stromal cells had three times more frequent occurrence of pathological fractures, which was highly statistically significant (χ2 = 7.065; p = 0.008). Moreover, a highly statistically significant correlation between the nuclear expression of β-catenin in giant cells and the incidence of pathological fractures was also found (χ2 = 8.824; p = 0.003). The study showed that β-catenin expression highly correlates with the incidence of pathological fractures in patients with GCTB. Taking into account that β-catenin is closely linked to activation of the Wnt signaling pathway in GCTB pathogenesis, one could postulate that activation of the Wnt pathway is one of the contributing factors to locally destructive behavior of this tumor, as well as to the incidence of pathological fractures.