نازنین حبیبی

Today, cancer is considered as a major health problem and affects the health of society. Breast cancer is the second leading cause of cancer death in women after lung cancer. According to epidemiological studies, cancer is the second most common cause of death after cardiovascular disease worldwide and the third leading cause of death after cardiovascular disease and accidents in less developed countries. Cancer occurs as a result of uncontrolled cell division, which is the result of environmental factors and genetic disorders. The four key genes involved in cancer cell development include oncogenes, tumor suppressor genes, DNA repair genes, and programmed death genes. The prevalence of breast cancer varies from about 8 to 12 women in different communities. About 30% of all monogenic breast cancers are due to mutations in the BRCA breast cancer genes, which will eventually lead to breast cancer with a dominant inheritance pattern. Repair genes naturally make proteins and enzymes that repair damaged genes. When these genes are mutated, they cannot repair the defects of other genes. One of the repairing genes is BRCA-1 gene, which has a hereditary role in the production and growth of cancer cells in female breasts when it has a mutation.MicroRNAs are a group of short, single-stranded (between 19 and 23 nucleotides) and non-coding conserved RNAs that act as post-transcriptional regulators of gene expression in a wide range of animals, plants, and viruses. The FOXO1 gene is one of the targets of miR-183, which is involved in the maturation of lymphocytes, and increased expression of miR-183 in cancer patients will interfere with immune function. Studies on miR-183-3p in breast cancer have shown that this microRNA is a Tumor suppressor-mir (Ts-mir) that prevents tumor formation and differentiation and has an inhibitory role. Another feature is the inhibition of cell proliferation and metastasis and stops the cell cycle in the G1 stage. miR-183 can play a role in other cancers in addition to breast cancer, depending on the type of target and location of activity. The aim of this study was to evaluate the expression changes of miR-183 in nuclear nuclei of breast cancer patients.

The study was performed on 60 samples including two groups of patients and healthy people. All actions and tests performed in this research and sampling have been approved by the work instructions of the ethics committee of Qom branch of the Azad University (ethics code: IR.IAU.QOM.REC.1397.010). Study steps include: extraction of peripheral blood mononuclear cells (PBMCs), extraction of RNA from PBMCs obtained from patients, design of specific primers for target genes, synthesis of cDNA from RNAs obtained, quality control of cDNA synthesized with Use of beta-actin and 5SrRNA housekeeping genes and ensure cDNA health, Real Time PCR to study changes in FOXO1 gene expression, changes in miR-183 and finally statistical analysis. In this study, the results obtained from Real-time PCR (Ct) were analyzed using LinReg software by examining the amount of fluorescence read by the device for each sample and the efficiency of each sample, the Ct of the reference gene and the target gene in both patient and healthy groups The data were then used and analyzed by Rest 2009 to determine whether the P-value was less than 0.05.

The results of analysis of data obtained from Real time-PCR show that the expression of FOXO1 gene in peripheral blood cells significantly decreases in samples of breast cancer patients compared to healthy individuals (P < 0.05). While in the expression of miR-183 gene, a significant increase was observed in the samples of people with breast cancer compared to the group of healthy people (P <0.001).

Decreased expression of FOXO1 gene reduces the maturation of lymphocytes and this function weakens and suppresses the immune system, which results in the proliferation and differentiation of cancer cells and tumor spread, which can be used as a biomarker. Limitations of the study include the small number of patients, the lack of classification of patients based on markers such as Her2nue, BRCA-1 and other diagnostic markers.

In the current economy and entrepreneurship situation in developing countries, experts maintain that establishing startup companies proves an efficient and promising approach. In spite of the fact, many startup companies are failed. However, there are key factors, which can help such companies follow the path to success. This research aims to identify the factors, which led to success of startup companies in Iran. Accordingly, one of the important roles of data mining is exploring the relationship between datasets, and getting the result of a series of association-based rules for identifying the strong relations between business activities. The data of this study is collected from a total of 165 Iranian startup companies. The feature's columns included 41 success factors of startup companies addressed in domestic and foreign studies. For the prediction phase, we use the help of support vector machine algorithm, decision tree and k-nearest neighboring to classification. The feature selection technique in order to come up with the most efficient success factor of startup companies is Cuckoo search. Finally, rules are extracted by means of Apriori Algorithms. The results indicate that factors such as, namely, entrepreneurship experience, working duration, skills, type of service or product, target market, Blue Ocean or Red Ocean strategy, flexibility, scalability, customer loyalty, presence or lack of presence in an accelerator, and first-stage of investor are the most important factors that have the greatest effects in a startup's success. Moreover, the extracted results reveal that flexibility, and scalability are considered as two key factors contributing to success of Iranian startup companies.