diagnosis. Moreover various studies can be found in medical journals dedicated to Artificial Neural Networks (ANN). In the presented study, a method was developed to learn and detect benign and malignant tumor types in contrast-enhanced breast magnetic resonance images (MRI). The backpropagation algorithm was taken as the ANN learning algorithm. The algorithm (NEUBREA) was developed in C# programming language by using Fast Artificial Neural Network Library (FANN). Having been diagnosed by radiologists, 7 cases of malignant tumor, 8 cases of benign tumor, and 3 normal cases were used as a training set. The results were tested on 34 cases that had been diagnosed by radiologists. After the comparison of the results, the overall accuracy of algorithm was defined as 92%.
During the last decades, plant extracts containing phytoestrogens have increasingly been used as an alternative to oestradiol hormone replacement therapy. The aim of the present study was to compare the effects of genistein with those of different phytoestrogen-containing plant extracts (from red clover flowers and soybeans) on the proliferation and differentiation of NIH-3T3, HaCaT and MCF-7 cells. Our results showed poor correlations between direct anti/prooxidant effects and cytotoxicity of the tested samples. In contrast, genistein showed a direct correlation between significant pro-oxidative effects at cytotoxic concentrations and almost no pro-oxidative effects at non-cytotoxic concentrations. Moreover, the tested red clover extract and genistein induced keratin-8 (luminal and prognostic marker in breast cancer) expression only in MCF-7 cells, but this effect was not seen following treatment with the soybean extract. From this point of view, the effect of consumption of phytoestrogens in oestrogen-positive breast cancer remains to be elucidated. In conclusion, our study demonstrates that various phytoestrogen-containing plant extracts and genistein are able to specifically modulate antioxidant properties and differentiation of studied cells. and Corresponding author: Peter Gál or Ivana Šušaníková
The paper presents results of GUHA analysis of proteomic data. The data are related to an oncological study on breast cancer and are given by 2D electrophoresis gels carrying expression intensity of proteins in cancer cells. The gels have been classified by a physician according to the clinical course of the tumor disease. A research task is aimed on search for significant relations between protein spot intensities and respective clinical presentation. The task was solved by the GUHA method of data mining.
Breast cancer survival prediction can have
an extreme effect on selection of best treatment protocols. Many approaches such as statistical or machine learning models have been employed to predict
the survival prospects of patients, but newer algorithms such as deep learning can be tested with the
aim of improving the models and prediction accuracy. In this study, we used machine learning and deep
learning approaches to predict breast cancer survival in 4,902 patient records from the University of
Malaya Medical Centre Breast Cancer Registry. The
results indicated that the multilayer perceptron (MLP),
random forest (RF) and decision tree (DT) classifiers
could predict survivorship, respectively, with 88.2 %,
83.3 % and 82.5 % accuracy in the tested samples.
Support vector machine (SVM) came out to be lower
with 80.5 %. In this study, tumour size turned out to
be the most important feature for breast cancer survivability prediction. Both deep learning and machine learning methods produce desirable prediction
accuracy, but other factors such as parameter configurations and data transformations affect the accuracy of the predictive model.
Psychosociálne faktory sú súčasťou komplexného funkčného postihnutia pri rôznych chronických ochoreniach. Cieľom práce bolo zistiť, ako sa líšia pacientky od zdravých žien v depresii a kvalite života a ako vzájomne súvisia funkčné poruchy, depresia a kvalita života pacientiek s diagnózou karcinóm prsníka. Skupina 35 pacientiek s karcinómom prsníka bola porovnávaná s kontrolnou skupinou 35 zdravých žien. Posudzovali sme funkčné poruchy, ktoré vychádzali z Medzinárodnej klasifikácie funkcií, dizabilít a zdravia WHO. Použili sme špecifické dotazníky ICF pre pacientov a zdravotníckych pracovníkov, kvality života (SF-36) a depresie (SDS). Štatisticky významný rozdiel sa ukázal v úrovni depresie, ako aj vo všetkých dimenziách SF-36 medzi skupinou žien s rakovinou prsníka a kontrolnou skupinou. Bol zistený signifikantný negatívny vzťah medzi skóre depresie a sumárnou psychickou subškálou SF-36, ako aj medzi ICF doménami porúch telesných funkcií a obmedzení aktivity a participácie a kvalitou života SF-36 u skúmaného súboru. Tieto výsledky je potrebné zahrnúť do konceptu komprehenzívnej rehabilitácie a psychologických intervencií. and Defects in functions, depression, and quality of life in patients with breast cancer
Psycho-social factors represent the part of complex functional handicap in different chronic diseases. The goal of the study was to assess how the patients differ from healthy women in depression and quality of life and how mutually interrelate the defects in functions, depression, and quality of life in patients with the breast cancer diagnosis. The group of 35 patients with breast cancer was compared to equivalent group of 35 healthy women. The defects in functions issued from International classification of functions, disabilities and health of WHO were assessed. Specific questionnaires ICF for patients and medical workers, quality of life (SF-36), and depression were used. A statistically significant difference was showed in depression level, as well as in all dimensions of SF-36 between the group of women with breast cancer and the control group. A negative significant relation of the depression score to summary mental subscale SF-36 was assessed as well as the relation of ICF domains of defects in body functions and restrictions on activity and participation and the quality of life SF-36 in surveyed group. These results should be taken in the concept of comprehensive rehabilitation and psychological interventions.
a1_Proteinase-activated receptor-2 (PAR-2) is a ubiquitous surface molecule participating in many biological processes. It belongs to the family of G protein-coupled receptors activated by the site-specific proteolysis of trypsin and similar proteases. Altered function of PAR-2 has been described in different malignant tumors. In the present study, we investigated the expression of PAR-2 in breast cancer surgical specimens and the role of trypsin in breast cancer cell line MDA MB-231 proliferation and metabolism. A total of 40 surgical samples of infiltrative ductal breast cancer and breast cancer cell line were included in this study. We analyzed PAR-2 expression by immunohistochemistry, RT-PCR and western blot. Activation of PAR-2 on cell line MDA MB-231 was measured using calcium mobilization assay determined by flow cytometry. MTT cell metabolism assay and cell count analysis were used to assess the trypsin influence on breast cancer cell line MDA MB-231 proliferation. Immunohistochemical examination showed the expression of PAR-2 in all samples of breast cancer surgical specimens and high levels of cell lines which was confirmed by RT-PCR and western blot., a2_Calcium mobilization assay corroborated the activation of PAR-2 on cell line MDA MB-231 either by trypsin or by an agonistic peptide. Cell metabolism assay and cell count analysis showed significant differences of proliferative activity of breast cancer cells dependent on the presence or absence of trypsin and serum in the culture medium. PAR-2 is expressed by high levels in infiltrative ductal breast cancer tissue specimens. PAR-2 is also strongly expressed in studied breast cancer cell lines. PAR-2 is activated by trypsin and also by agonistic peptide in the model of breast cancer cell line MDA MB-231. Activation of PAR-2 in vitro influences proliferative and metabolic activity of breast cancer cell line MDA MB-231. The action of trypsin is modified by the presence of serum which is a potential source of protease inhibitors., R. Matěj, P. Manďáková, I. Netíková, P. Poučková, T. Olejár., and Obsahuje biblografii a bibliografické odkazy
Blood monocytes (BMs) from 139 subjects (70 malignant melanoma patients, 31 breast cancer patients, 38 healthy controls) were cultured for at least 7 days. The formation of multinucleated giant cells (MGCs), which was checked during the whole time of culture, was observed in all cases. By the seventh day MGCs represented 25-50 % and during the second and third month more than 90% of all cells. Lymphokines and/or concanavalin A stimulation (16-34 cases respectively) of BMs was performed as well. This stimulation greatly accelerated MGC formation. There were no differences either in spontaneous or in stimulated fusion between the different groups compared.
The aim of the present study was to introduce methods for exome sequencing of two ATP-binding cassette (ABC) transporters ABCC8 and ABCD2 recently suggested to play a putative role in breast cancer progression and prognosis of patients. We performed next generation sequencing targeted at analysis of all exons in ABCC8 and ABCD2 genes and surrounding noncoding sequences in blood DNA samples from 24 patients with breast cancer. The revealed alterations were characterized by in silico tools. We then compared the most frequent functionally relevant polymorphism rs757110 in ABCC8 with clinical data of patients. In total, the study identified 113 genetic alterations (>70 % novel ones) in both genes. Of these alterations, 83 were noncoding, 13 synonymous, 10 frameshifts and 7 were missense alterations. Four in silico programs predicted pathogenicity of two polymorphisms and four newly identified alterations. Rs757110 polymorphism in ABCC8 did not significantly associate with clinical data of the patients. In conclusion, exome sequencing identified several functionally relevant alterations in ABCC8 and ABCD2 genes that may further be used for a larger follow-up study aiming to assess their clinical significance., P. Soucek, V. Hlavac, K. Elsnerova, R. Vaclavikova, R. Kozevnikovova, K. Raus., and Obsahuje bibliografii