Orientadores: Eduardo Tavares Costa, Paulo José Cecílio / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-24T11:03:55Z (GMT). No. of bitstreams: 1 Biazotto_Bruna_M.pdf: 4075478 bytes, checksum: 077630eb4f66ca28ec46de7251c31e3f (MD5) Previous issue date: 2013 / Resumo: A experiência clínica em tratamentos radioterápicos de neoplasia de próstata baseia-se no cálculo de doses em meios homogêneos. Entretanto, o feixe de radiação atravessa tecidos de densidades eletrônicas diferentes como os ossos, que alteram a distribuição de dose. Com o advento da tomografia computadorizada e de algoritmos mais avançados que modelam o feixe de radiação, as heterogeneidades entre os tecidos podem ser incorporadas nos planejamentos de tratamentos radioterápicos. Todavia, não há consenso se as alterações na dose por correções de heterogeneidade são significativas. Por tais razões, pretendeu-se no presente trabalho avaliar a necessidade das correções de heterogeneidade em planejamentos de tratamentos radioterápicos de câncer de próstata. Para isso, analisaram-se as médias das diferenças percentuais nas doses em volume alvo e órgãos de risco obtidas em cálculos com e sem correções de heterogeneidade utilizando imagens tomográficas reais de pacientes que trataram dessa neoplasia. Essa avaliação foi realizada para dois métodos de tratamentos diferentes. O primeiro é o conformacional tridimensional (25 casos), algoritmos de cálculo Convolution, Superposition e Fast Superposition do sistema de planejamento XiO/Elekta, feixes de 6 e 10 MV e 4 campos em box. O segundo por intensidade modulada (14 casos), algoritmo de cálculo Pencil Beam Convolution do sistema de planejamento Eclipse/Varian com dois métodos de correção Batho Modificado e Razão Tecido-Ar Equivalente, feixe de 6 MV e geometria de 5 campos oblíquos. As diferenças percentuais médias resultantes nos volumes estudados foram menores que a incerteza aceita atualmente no cálculo de dose de 3% para as duas modalidades de tratamento. Apesar disso, a variabilidade na anatomia dos pacientes, geometria de campos e energia dos feixes apontam para a necessidade de tais correções e a utilização de métodos ainda mais exatos para a diminuição dessa incerteza no futuro / Abstract: Clinical experience in radiotherapy treatments for prostate cancer is based on the calculation of doses in homogeneous media. However, the radiation beam traverses different electron densities in tissues such as bone, altering the dose distribution. With the advent of computed tomography and more advanced algorithms that model the radiation beam, the heterogeneity between tissues can be incorporated in the planning of radiotherapy treatments. However, there is no consensus whether changes in dose for inhomogeneity corrections are significant. For these reasons, this study intended to evaluate the need for inhomogeneity corrections in treatment planning for radiotherapy of prostate cancer. We have analyzed the average percentage differences in doses in the target volume and organs at risk obtained by calculations with and without heterogeneity corrections using actual CT images of patients treated for this cancer. This evaluation was performed for two different methods of treatments. The first is the three-dimensional conformational (25 cases), calculation algorithms Convolution, Superposition and Fast Superposition from the computerized planning system XiO/Elekta, beams of 6 and 10 MV and 4 fields in box. The second by intensity modulated (14 cases), calculation algorithm Pencil Beam Convolution from the computerized planning system Eclipse/Varian with two correction methods Modified Batho and Equivalent Tissue-Air Ratio, 6 MV beam and geometry of 5 oblique fields. The resulting average percentage differences in volumes studied were smaller than the currently accepted uncertainty in the dose calculation of 3% for both treatment modalities. Nevertheless, variability in anatomy of patients, geometry and field energy beams brings the need for these corrections and the use of more accurate methods to reduce this uncertainty in the future / Mestrado / Engenharia Biomedica / Mestra em Engenharia Elétrica

Magister Scientiae (Medical Bioscience) - MSc(MBS) / The prostate is prone to three pathological processes that include inflammation, benign prostate hyperplasia (BPH) and tumors. According to the center for Disease and Control 1999-2012 report, prostate cancer is the second leading cause of death in the United States. Scientific evidence suggests that up to 30% of men in the general population aged from 50 years and above, irrespective of geographic origin, have foci of prostate neoplastic growth. Unbalanced ROS production and a dysregulated antioxidant defence system have been implicated in prostate cancer development. The transformation of a normal cell into cancer takes a very long period. This observation provides the advantage of using nutraceuticals to prevent, arrest or reverse the cellular and molecular processes of carcinogenesis. Based on scientifically observed positive health roles of green tea (Cameli sinensis) and rooibos (Aspalathus linearis) on major diseases like atherosclerosis, hepatitis and certain types of cancer, this thesis evaluated the effects of these two teas on benign (RPWE 1) and malignant (LNCaP) prostate cells. This was done through the quantification of reactive oxygen species (ROS) using a fluorescence dye 5,6 CM-H2DCFDA, total prostate specific antigen (PSA) levels using a PSA ELISA kit, cell viability using the MTT assay, apoptosis using Tali annexin V stain and cell imaging studies using a Zeiss axiovert 200M inverted fluorescence microscope. Statistical analysis was done using graphpad prism. The findings of this study show that aqueous extracts of green and black tea, fermented and unfermented rooibos and their active compounds epigallocatechin gallate (EGCG) and aspalatin, respectively, are cytotoxic in malignant (LNCaP) prostate cells but exert protective effects in benign (RPWE 1) prostate cells. This thesis implicates the pro-oxidant and anti-oxidant properties of the plant extracts, respectively, for the above mentioned effects. In this regard, tea and rooibos promoted ROS production in malignant (LNCaP) prostate cells, which subsequently promoted cell death of the malignant cells through apoptosis and necrosis. Further to this, tea and rooibos used in this thesis, protected normal prostate cells from the adverse effects of ROS. In this regard, fluorescence microscope photographs showed RPWE 1 cells with low DCF fluorescence compared to the malignant prostate cells. Low magnification light microscope photographs showed RPWE 1 cells with flat polygonal shapes and increased adherence both at low and high concentrations of tea and rooibos. On the contrary, high concentrations of tea and rooibos on malignant (LNCaP) prostate cells induced stress, which made the cells attain irregular shapes and as the stress levels increased, cells became detached and appeared dead. Flow cytometry confirmed the presence of apoptotic and necrotic cell in malignant (LNCaP) prostate cells. In this thesis, EGCG and aspalathin were responsible for the high rates of apoptosis observed whereas green tea and unfermented rooibos induced the highest rate of necrosis. Further to this, tea and rooibos and the main active compounds EGCG and aspalathin, respectively, significantly promoted the reduction of total serum prostate specific antigen (PSA) in malignant prostate cells. In normal prostate cells, these plant extracts maintained the total serum PSA at its basal physiological level. In this thesis, to the best of our knowledge, we report for the first time the cell-specific effects of fermented rooibos, unfermented rooibos and their main active component aspalathin, on prostate cancer cells. We showed that rooibos and aspalathin exert pro-oxidant effects on malignant LNCaP cells and anti-oxidant effects on benign RPWE 1 cells. In conclusion, tea (C. sinensis) and rooibos (A. linearis) and their respective main active compounds, epigallocatechin gallate and aspalathin, are cytotoxic to malignant prostate cells whereas in normal prostate cells, they have protective effects against ROS induced stress. The pro-oxidant and anti-oxidant effects are responsible for the aforementioned effects respectively. The decrease in total serum PSA demonstrate the strong therapeutic effects that tea and rooibos have on malignant (LNCaP) prostate cells. / Malawi Government: Department of Human Resources Development and Management

Magister Scientiae (Medical Bioscience) - MSc(MBS) / Prostate cancer is one of the heterogeneous groups of neoplastic diseases originating from the reproductive system of the male naming, the prostate gland. In the west, prostate cancer is the most common cancer affecting African men in older age (over the age of 55) and usually with a family history of the disease. The initiation and progression of this disease is thought to result from the genetic alterations of gene expression in the prostate epithelial cells. Prostate cancer has a very slow progression. This observation provides the advantage of early detection and the notion for using diet to prevent the cellular and molecular processes of carcinogenesis. Epidemiological research has documented a positive health role for red palm oil on atherosclerosis, arterial thrombosis and several types of cancers. This thesis focuses on investigating the effect of different concentrations of the red palm oil (0.1, 1, 10, 100, 500, 1 000 μg/ml) on malignant (LNCaP) prostate cells and benign (PWR-1E) prostate cells over 24 and 72- hours. The following parameters were investigated: cell morphology and viability (using MTT assay), the expression of androgen receptors and prostate-specific antigen (PSA) via RT-PCR and/or PSA ELISA kit. The results of this study demonstrate that red palm oil has significant cytotoxic effects on malignant (LNCaP) prostate cells but caused only a slight decrease in cell viability of benign (PWR- 1E) prostate cells. Morphologically, we noted a clear increase in detachment and cell death in malignant (LNCaP) cells as the concentrations of red palm oil increased. Moreover, the viability decreased significantly in both 24 and 72-hour treatment of red palm oil. Further to this, red palm oil significantly promoted the reduction of total PSA concentration in malignant (LNCaP) prostate cells whereas in benign (PWR-1E) prostate cells the Red Palm Oil maintained the total serum PSA at its basal physiological level. In conclusion, red palm oil is significantly cytotoxic to malignant (LNCaP) prostate cells whereas weakly cytotoxic effect toward benign (PWR-1E) prostate cells. The potent inhibition to mitochondrial dehydrogenase activity is responsible for the aforementioned effects respectively. The decrease in total serum PSA demonstrate the strong therapeutic effects that red palm oil has on malignant (LNCaP) prostate cells

Background and Aim: Prostate cancer (PCa) is the leading cancer diagnosis amongst South African men. The incidence of PCa is 68.0 per 100 000 Age Standardized Rate (ASR) and the mortality rates are 27.9 per 100 000 ASR; Globocan 2018. Diagnosis of PCa is based on a combination of digital rectal examination, prostate-specific antigen (PSA) and histology. Several biomarkers have been used to increase the sensitivity and specificity of PSA in distinguishing patients with PCa from those with benign prostatic hyperplasia (BPH). These include fractionated PSA, free/total PSA ratio, −2proPSA, prostate cancer antigen 3 and prostate health index amongst others. Biomarkers are needed to differentiate BPH from PCa due to a lack of specificity of these markers with PSA levels above 4.0 ng/ml. The aim of this study is to investigate gene expression patterns of South African men in 9 PCa and 10 BPH patients in order to distinguish between the two groups. Methods: Ethical approval was obtained (HREC 454/2012). Patients scheduled for transurethral resection of the prostate were recruited from the Western Cape. RNA was extracted from prostate tissue using the AllPrep DNA/RNA/miRNA Universal Kit (Qiagen). Complementary DNA was synthesized from RNA using the SuperScript IV VILO Master Mix (Thermo Fischer Scientific). Gene expression was analyzed with the Human Prostate Cancer RT2 Profiler PCR Array and SYBR Green Master Mix. Data were analyzed with the GeneGlobe RT2 and miScript PCR Array Data Analysis Centre from Qiagen. Results: The cohort included patients from different ethnic groups namely, Caucasians, Mixedand African ancestry. The PCa group has an age range from 56 to 75 years (mean 65) while the BPH group was slight older ranging from 60 to 76 years (mean 68). PSA levels range from 24 to 5000 ng/ml (mean 1252 ng/ml, median 185) for the PCa group and 11 to 58 ng/mL (mean 25 ng/ml, median 22) for the BPH group. The following genes were downregulated 2-fold in the PCa group with p values s <0.05; IGF1, PTEN, GSTP1, SOCS3, EGR3, GPX3, TIMP3, ZNF185, DKK3, PTGS2, FOXO1, ARNTL, TNFRSF10D, CCND1, and DLC1, upregulated genes included; CDH1, MKI67, TMPRSS2, ERG, CDKN2A, FASN, and AR but were not statistically significant. At a fold change threshold of 1.5, the following additional genes were downregulated in the PCa group with p values <0.05; DAXX, EGFR, RASSF1, SOX4, and TIMP2, upregulated genes were ACACA, AR, CDKN2A, ERG and FASN but were also not statistically significant. The study shows similarly differentially expressed genes as seen in international studies. Of note PTEN, MKI67 and FASN which are associated with poor prognosis. EGR3 was downregulated in our study and this has been associated aggressive disease and predict relapse after PCa treatment. This could explain the high mortality demonstrated in South African epidemiological studies. Conclusion: We identified a group of differentially expressed genes that have potential in distinguishing PCa and BPH patients with PSA values above 10 ng/ml. A larger population study is needed to further evaluate the clinical significance of our findings.

LIMK2 is a serine/threonine/tyrosine kinase that promotes tumor cell invasion and metastasis by phosphorylating cell proteins and altering their functions. There is a need to find tumor-specific substrates for LIMK2 in order to understand the downstream pathway of these substrates, their function, and how they are regulated by LIMK2. Recently, our labrotory identified LIMK2 as an excellent target for curing castration-resistant prostate cancer (CRPC). In this study, we identify two novel substrates for LIMK2 in CRPC: speckle-type POZ protein (SPOP), and Y-box binding protein-1 (YBX1). While LIMK2 negatively regulates SPOP, it positively regulates YBX1 − both by phosphorylation using in-vitro kinase assays. A study in our labrotory also proved that LIMK2 regulates Aurora A kinase (AURKA), where AURKA directly phosphorylates LIMK2. AURKA is a serine/threonine kinase that regulates cell cycle during mitosis; it is known to be upregulated, with uncontrolled activity, in many types of cancer, including prostate cancer. It is therefore important to identify new substrates for AURKA, especially in light of reported lethality in early embryonic mice, in association with AURKA-knockout. In other words, targeting AURKA directly may cause severe toxicity, a finding that has prevented direct inhibitors from passing Phase II clinical trials. In this study, we also identified SPOP and YBX1 as direct substrates for AURKA. Our results confirm what we know about the LIMK2/AURKA relationship: that AURKA negatively regulates SPOP and positively regulates YBX1. Targeting LIMK2 and AURKA indirectly through SPOP, YBX1 and its other substrates holds tremendous therapeutic potential in treating prostate cancer. With this, we open the door for researches to investigate the direct phosphorylation of SPOP and YBX1 in other types of cancer cells known to have overexpression in SPOP and/or YBX1.

One of the most common types of cancer among women is breast cancer. It represents one of the diseases leading to a high number of mortalities among women. On the other hand, prostate cancer is the second most frequent malignancy in men worldwide. The early detection of prostate cancer is fundamental to reduce mortality and increase the survival rate. A comparison between six types of machine learning models as Logistic Regression, Decision Tree, Random Forest, Gradient Boosting, k Nearest Neighbors, and Naïve Bayes has been performed. This research aims to identify the most efficient machine learning algorithms for identifying the most significant risk factors of prostate and breast cancers. For this reason, National Health Interview Survey (NHIS) and Prostate, Lung, Colorectal, and Ovarian (PLCO) datasets are used. A comprehensive comparison of risk factors leading to these two crucial cancers can significantly impact early detection and progressive improvement in survival. / Includes bibliography. / Thesis (P.S.M.)--Florida Atlantic University, 2021. / FAU Electronic Theses and Dissertations Collection

Prostate cancer (PCa) is the second most diagnosed cancer in men. The resistance of prostate cancer to chemotherapy has been linked to the ATP Binding Cassette (ABC)-Mediated Multidrug Resistance (MDR). This study investigated the combination of 3-Bromopyruvate (3-BPA) and the anti-inflammatory molecule SC-514 in reducing MDR in prostate cancer. The compounds were incorporated into a PLGA nanoparticles to increase delivery to target cells. To investigate the effectiveness of SC-514 and/3-BPA, cytoxicity assays including trypan blue dye exclusion, MTT tetrazolium reduction, NBT, LDH release poly caspase detection, cell titer glow assay, and ELISA were utilized. Both immunofluorescence and multidrug resistance efflux assays were utilized to estimate the number of drug resistant cells. SC-514 was encapsulated in PLGA nanoparticles via single-emulsion method. SC-514 nanoparticles were analyzed utilizing Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM). Liquid chromatography–mass spectrometry (LC–MS) was used to measure the amount of SC- 514 released from the nanoparticle. Alternative SC-514 drug release quantification methods such as colony forming assay, wound healing assay, and transwell and migration assay were explored. / Includes bibliography. / Dissertation (PhD)--Florida Atlantic University, 2021. / FAU Electronic Theses and Dissertations Collection

The oncogenic role of many of inflammatory genes in prostate cancer (PCa) remains unexplored despite the increasing association of chronic inflammation with PCa initiation, progression, and therapy resistance. The overarching goal of this project was to identify dysregulated inflammatory genes that correlate with PCa progression and seek to understand their molecular mechanisms and the therapeutic potential of targeting them. To achieve this, we utilized cutting-edge integrative (epi) genomic and transcriptomic techniques to identify and characterize inflammatory genes whose deregulation or (epi) genetic alterations correlate with PCa progression. Weighted Gene Co-expression Network Analysis and other multivariate analysis techniques identified IRAK1 as one of the inflammatory signatures found to be overexpressed in over 80% of prostate adenocarcinoma (PRAD) samples. We also explored the diagnostic and prognostic potential of IRAK1 as a biomarker using Kaplan Meier Survival Analysis and AUROC Analysis. DNA methylation analysis showed that IRAK1 is hypomethylated and found to negatively correlate with its overexpression in PRAD patients. We also found some missense and truncated mutations in some patients and reported a high level of IRAK1 gene amplification in castration-resistant and neuroendocrine PCa patients. / Includes bibliography. / Dissertation (PhD)--Florida Atlantic University, 2021. / FAU Electronic Theses and Dissertations Collection

archives@tulane.edu / The current system for evaluating prostate cancer architecture is the Gleason Grade system, which divides the morphology of cancer into five distinct architectural patterns, labeled numerically in increasing levels of cancer aggressiveness and generates a score by summing the labels of the two most dominant patterns. The Gleason score is currently the most powerful prognostic predictor of patient outcomes; however, it suffers from problems in reproducibility and consistency due to the high intra-observer and inter-observer variability among pathologists. In addition, the Gleason system lacks the granularity to address potentially prognostic architectural features beyond Gleason patterns. We look towards persistent homology, a tool from topological data analysis, to provide a means of evaluating prostate cancer glandular architecture. The objective of this work is to demonstrate the capacity of persistent homology to capture architectural features independently of Gleason patterns in a representation suitable for unsupervised and supervised machine learning. Specifically, using persistent homology, we compute topological representations of purely graded prostate cancer histopathology images of Gleason patterns and show that persistent homology is capable of clustering prostate cancer histology into architectural groups through discrete representations of persistent homology in both two-dimensional and three-dimensional histopathology. We then demonstrate the performance of persistent homology based features in common machine learning classifiers, indicating that persistent homology can both separate unique architectures in prostate cancer, but is also predictive of prostate cancer aggressiveness. Our results indicate the ability of persistent homology to cluster into unique groups with dominant architectural patterns consistent with the continuum of Gleason patterns. In addition, of particular interest, is the sensitivity of persistent homology to identify specific sub-architectural groups within single Gleason patterns, suggesting that persistent homology could represent a robust quantification method for prostate cancer architecture with higher granularity than the existing semi-quantitative measures. This work develops a framework for segregating prostate cancer aggressiveness by architectural subtype using topological representations, in a supervised machine learning setting, and lays the groundwork for augmenting traditional approaches with topological features for improved diagnosis and prognosis. / 1 / Peter Lawson

Prostate cancer is one of the most frequently diagnosed cancers and the second leading cause of cancer-related deaths in male population. While localized prostate cancer can be successfully treated with surgery or radiation therapy, the metastatic disease has no curable options. Metastasis can be developed as a result of failed therapy of localized cancer or present at initial diagnosis. As metastasis is the most common cause of prostate cancer-related death, developing novel approaches and improving the efficiency of existing therapies for the metastatic prostate cancer treatment will significantly improve patients’ survival. <div><br><div>The first-line treatment option for metastatic prostate cancer and localized prostate cancer with high risk of recurrence is androgen deprivation therapy (ADT) that decreases androgen receptor (AR) signaling. However, targeting AR signaling inevitably leads to AR reactivation and cancer progression to the castration-resistant prostate cancer (CRPC) that has no curable treatment options. Moreover, about 30% of CRPC cases progress to neuroendocrine prostate cancer (NEPC), highly aggressive and lethal type of prostate cancer. </div><div><br></div><div>Recently my group has shown that protein arginine methyltransferase 5 (PRMT5) functions as an activator of AR expression in hormone-naïve prostate cancer (HNPC). In this dissertation, I demonstrate that PRMT5 also functions as an epigenetic activator of AR transcription in CRPC via symmetric dimethylation of H4R3 at the AR promoter. This epigenetic activation is dependent on pICln, a PRMT5 interaction partner involved in spliceosome assembly, and independent of MEP50, the canonical cofactor of PRMT5. PRMT5 and pICln, but not MEP50, were required for the expression of AR signaling pathway genes. In clinical samples of both HNPC and CRPC, nuclear PRMT5 and pICln protein expressions were highly positively correlated with nuclear AR protein expression. In xenograft tumors, targeting PRMT5 or pICln significantly decreased tumor growth and AR expression. </div><div><br></div><div>Overall, this work identifies PRMT5/pICln as a therapeutic target for HNPC and CRPC treatment that needs to be further evaluated in clinical setting. </div></div>