Aberrant promoter methylation is known to silence tumor-suppressor genes in prostate cancer. Using a quantitative real-time PCR assay(MethyLight), I determined promoter methylation levels of APC, RASSF1A, CYP26A1 and TBX15 in 219 radical prostatectomies diagnosed between 1998-2001, examined their correlation with clinicopathological follow-up data including Gleason Pattern(GP), Gleason Score(GS) and pathological stage, and explored their potential in predicting biochemical recurrence(BR) using univariate and multivariate analyses. I demonstrated that methylation status of all four genes could accurately differentiate normal from cancerous tissues. Quantitative methylation levels of APC and TBX15 correlated strongly with GP, GS, and pathological stage. Both APC and TBX15 methylation levels could significantly predict BR in univariate analysis(p-value=0.028 and 0.003, respectively). The methylation profiles of APC and TBX15 combined could discriminate patients into high, intermediate, and low risk groups of BR(p-value=0.005). My project demonstrated that quantitative increase in promoter methylation levels of APC and TBX15 were associated with PCa progression.

Shortcomings of current methods of prostate cancer detection draw attention to a need for improved biomarkers. The TMPRSS2:ERG gene fusion leads to the overexpression of ERG, an ETS family transcription factor, and is the most prevalent genetic lesion in prostate cancer, but its clinical utility remains to be defined. Two radical prostatectomy samples were analysed by next-generation whole transcriptome sequencing. The chosen samples differed in fusion gene status, as previously determined by RT-PCR. The involvement of novel and previously reported prostate cancer-related transcripts, Wnt signalling, p53 effector loss and several ETS-regulated pathways was identified in the prostate cancer cases examined. ERG was found to directly transactivate RhoGDIB, a gene associated with fusion-positive prostate cancer. Overexpression of RhoGDIB elicited spindle-shaped morphology, faster cell migration and increased cell proliferation, phenotypic changes suggestive of cancer progression. The present findings confirm the value of comprehensive sequencing for biomarker development and indicate avenues of future study.

Localized prostate cancer (LPC) is predominantly a tumor among older men, and few patients will get symptoms from the disease. All methods to treat LPC with a curative intent have different types and degrees of side effects. It is therefore very important to evaluate the side effects thoroughly to make sure that treatment complications will not decrease the quality of life more than the disease would have done. In search for new and better treatments, complications has to be registered and evaluated in relation to quality of life (QOL) for the patients. Few validated self-assessment questionnaires for evaluation of external radiotherapy (EBRT) induced side effects has yet been developed. The present project focus on the development of the PC-specific questionnaire, QUFW94, and evaluation of symptoms in patients treated with EBRT and un-treated (watchful waiting) patients with a LPC. In the newly developed LPC-specific questionnaire a reliability and responsiveness test was performed. Both the inter-rater test and the test-retest show high correlation coefficients (ICC), above 0.60 for all scales. The internal reliability exceeded the lower acceptable limit (Cronbach a >0.70). The questionnaire was proven to be valid for the evaluations of EBRT side effects in LPC patients. Late side effects were evaluated 4 years after treatment in 181 LPC patients, treated with conventional large field EBRT, and compared with 141 age-matched PC disease free men. The most prominent urinary side effects were urgency and leakage which were doubled in the patient group. A ten fold increase was seen in comparison to controls at the most prominent intestinal problems, blood, mucus and leakage. The results support the use 3-D conformai therapy to decrease irradiation dose to the rectum and the bladder and thereby decreased side effects. A prospective additional evaluation 8 years after EBRT did not show any changes in urinary problems between 4 and 8-yr follow-up in the patients or the controls. EBRT of LPC is also accompanied by disturbances in sexual function. These problems were therefore evaluated, 4 years after EBRT, in relation to the function in PC free men. Patients treated with EBRT indicated higher levels of sexual dysfunction than age-matched controls. No erection was reported from 12% of the control subjects, 56% of the patients who had only received radiotherapy (RT) and 87% of the RT+castration (RT+A) patients. The extended evaluation 8 years after EBRT show similar sexual function in all groups. QOL and late side effects/symptoms were evaluated in the first and only randomized trial between RT and deferred treatment (DT) and compared to age-matched controls. QOL was evaluated with the general QOL formula, EORTC's QLQ-C30 (+3), and LPC specific side effects with QUFW94 in 108 randomized patients with LPC 3 years after diagnosis. Social functioning was the only QOL scale where a significant difference was found between the two patient groups and in comparison with the control group. Multivariate regression analysis showed that hematuria, incontinence, mucus, and planning of the daily activities due to intestinal problems caused this decrease in QOL in the RT group. In conclusion, the LPC specific QUFW94 questionnaire was proven to be valid for evaluation of side effects and showed increased intestinal problems in the patients treated with conventional large field EBRT in comparison to untreated LPC patients. No difference in urinary and intestinal late side effects or sexual function was seen between a 4 year vs. 8 year follow-up. / digitalisering@umu

Flavonoids are a large class of dietary polyphenols that have emerged as candidate agents for chemoprevention in prostate cancer. Despite the large number of known flavonoids (over 9000), only a few have been studied in prostate cancer to date. The work presented in this thesis describes the identification of novel anti-proliferative flavonoids, their molecular effects on cell cycle and related proliferation and survival pathways, and their chemopreventive properties in a murine model of prostate carcinogenesis. We identified several novel flavonoids with potent anti-proliferative effects in human prostate cancer cells in vitro. Non-prostate cell lines were generally resistant to the effect of these flavonoids. Two of the most potent flavonoids identified, 2,2-dihydroxychalcone (DHC) and fisetin, induced S and G2 phase cell cycle arrest in LNCaP and PC3 prostate cancer cells. Gene expression studies employing oligonucleotide microarray demonstrated profound down-regulation in gene expression of 75 key cell cycle (predominantly G2 and M phase) genes by DHC and fisetin, and the enhanced expression of 50 stress-response genes with important roles in cell proliferation and survival. DHC and fisetin induced apoptosis, but not accelerated senescence, in prostate cancer cells. The chemopreventive effect of 4 flavonoids identified from the in vitro studies was examined in an autochthonous murine model of prostate cancer (TRAMP). Mice were administered diets supplemented with 1% DHC, 1% fisetin or a combination of flavonoids (0.25% DHC, 0.25% fisetin, 0.25% quercetin, 0.25% luteolin) for 32 weeks. We demonstrated a significant reduction in genitourinary weight, and a reduction in prostate cancer grade in mice administered 1% DHC and combination diets. Flavonoid supplementation was, however, associated with gastrointestinal toxicity in some mice. Liquid chromatography-mass spectrometry demonstrated the accumulation of high levels of flavonoid in the prostates of TRAMP mice. These findings lay the foundation for further studies of flavonoids in clinical chemoprevention trials.

A North American man has approximately a one in six chance of being diagnosed with prostate cancer in his lifetime. In most cases, there is no clearly optimal treatment, so he may be invited to participate in a treatment decision between several medically reasonable options, each with potential short- and long-term side effects. Information needs are high at diagnosis and can continue to be elevated for years or decades. Many men and their families seek information online, where, due partly to the array of websites available and high variation in information preferences, it can be difficult to find personally relevant and useful websites. This research sought to address this issue by developing methods to categorize prostate cancer websites and exploring quantitative and qualitative relationships between websites, information-seekers, and individuals’ assessments of websites. The research involved a series of three studies. In the first study, 29 men with prostate cancer participated in a needs assessment involving questionnaires, an interview, and interaction with a prototype website. In the second study, a detailed classification system was developed and applied to a set of forty websites selected to be representative of the variety of prostate cancer websites available. The third (online) study collected clinical, cognitive, and psychosocial details from 65 participants along with their ratings of websites from study two. A number of hypotheses were tested. One finding was that, compared to men with greater trust, men with lower trust in their physician tended to judge commercial websites as less relevant and useful, and found websites with descriptions of personal experiences more relevant and useful. Analyses also addressed a number of exploratory questions, including whether website and individual attributes might predict preferences for websites. Using discriminant analysis on 80% of the data, two functions were identified that predicted ratings significantly better than chance. These relationships were then validated with 20% of the data held back for testing. The results are discussed in terms of their implications for information tailoring and recommender systems for prostate cancer patients searching for information online. Limitations of the current research and recommendations for future research are also presented.

The Prostate is a male gland that is located around the urethra. Prostate Cancer is the second most diagnosed malignancy in men over the age of fifty. Typically, prostate cancer is diagnosed from clinical data, medical images, and biopsy. <br /><br /> Computer Aided Diagnosis (CAD) was introduced to help in the diagnosis in order to assist in the biopsy operations. Usually, CAD is carried out utilizing either the clinical data, using data mining techniques, or using features extracted from either TransRectal UltraSound (TRUS) images or the Radio Frequency (RF) signals. <br /><br /> The challenge is that TRUS images' quality is usually poor compared to either Magnetic Resonance Imaging (MRI) or the Computed Tomography (CT). On the other hand, ultrasound imaging is more convenient because of its simple instrumentation and mobility capability compared to either CT or MRI. Moreover, TRUS is far less expensive and does not need certain settings compared to either MRI or CT. Accordingly; the main motivation of this research is to enhance the outcome of TRUS images by extracting as much information as possible from it. The main objective of this research is to implement a powerful noninvasive CAD tool that integrates all the possible information gathered from the TRUS images in order to mimic the expert radiologist opinion and even go beyond his visual system capabilities, a process that will in turn assist the biopsy operation. In this sense, looking deep in the TRUS images by getting some mathematical measures that characterize the image and are not visible by the radiologist is required to achieve the task of cancer recognition. <br /><br /> This thesis presents several comprehensive algorithms for integrated feature analysis systems for the purpose of prostate tissue classification. The proposed algorithm is composed of several stages, which are: First, the regions that are highly suspicious are selected using the proposed Gabor filter based ROI identification algorithm. <br /><br /> Second, the selected regions are further examined by constructing different novel as well as typical feature sets. The novel constructed feature sets are composed of statistical feature sets, spectral feature sets and model based feature sets. <br /><br /> Next, the constructed features were further analyzed by selecting the best feature subset that identifies the cancereus regions. This task is achieved by proposing different dimensionality reduction methods which can be categorized into: Classifier dependent feature selection (Mutual Information based feature selection), classifier independent feature selection, which is based mainly on tailoring the Artificial life optimization techniques to fit the feature selection problem and Feature Extraction, which transforms the data to a new lower dimension space without any degradation in the information and with no correlation among the transformed lower dimensional features. <br /><br /> Finally, the last proposed fragment in this thesis is the Spectral Clustering algorithm, which is applied to the TRUS images. Spectral Clustering is a novel fast algorithm that can be used in order to obtain a fast initial estimate of the cancer regions. Moreover, it can be used to support the decision obtained by the proposed cancer recognition algorithm. This decision support process is crucial at this stage as the gold standards used in obtaining the results shown in this thesis is mainly the radiologist's markings on the TRUS images. This gold standards is not considered as credible since the radiologist's best accuracy is approximately 65 %. <br /><br /> In conclusion, this thesis introduces different novel complete algorithms for automatic cancerous regions detection in the prostate gland utilizing TRUS images. These proposed algorithms complement each other in which the results obtained using either of the proposed algorithms support each other by resulting in the same classification accuracy, sensitivity and specificity. This result proves the remarkable quality of the constructed features as well as the superiority of the introduced feature selection and feature extraction methods to detect cancerous regions in the prostate gland.

The goal of this thesis is to design, implement and evaluate an automated algorithm to detect cancerous tissues and segment the malignant tumour in ultrasound images of the prostate. To accomplish this goal, first, the important image features which would lead to the optimal segmentation are identified. This work focuses on the local texture feature and spatial features. Various approaches to extract the local texture feature are explored, including grey-level co-occurrence matrix (GLCM), recurrent random-pulsed neural networks (RNN), and a novel wavelet-based filter. The spatial features are represented using conventional one dimensional fuzzy membership functions and novel multi-dimensional fuzzy membership functions. The texture and spatial features are combined using the fuzzy inference system. Two of the techniques investigated in this thesis could potentially constitute the basis for key paradigm shifts in medical imaging research. One of these is the idea that medical images in general, and ultrasound images in particular, contain information which are hidden from medical professionals due to limitations in the human visual system. This thesis shows that this information could be extracted using a computerized approach by separating the deterministic components in the image from the indeterministic components, or noise. The other idea concerns the representation of multidimensional statistical distribution information with fuzzy membership functions with the corresponding dimensions. This thesis shows that increasing the number of dimensions with which to represent the statistical distributions results in a more accurate mapping of information that relates to human anatomy, which is essentially 3D in nature. In the thesis, the natures of the various techniques are explored by testing on synthesized images. Then, these approaches are adapted to the ultrasonic prostate cancer segmentation problem and are evaluated with trans-rectal ultrasound images (TRUS). The segmentation using only texture features yields results with high sensitivity. When the spatial features are incorporated using the fuzzy inference system, the specificity of the diagnosis improves dramatically and the overall classification accuracy is also increased. Clinically, this automated diagnostic system could be used as a decision support tool for radiologists when identifying suspicious regions in the prostate from which to draw biopsy samples. The proposed system improves the consistency of the cancer detection process and could provide savings in both time and cost in the prevention and treatment of prostate cancer.

The Prostate is a male gland that is located around the urethra. Prostate Cancer is the second most diagnosed malignancy in men over the age of fifty. Typically, prostate cancer is diagnosed from clinical data, medical images, and biopsy. <br /><br /> Computer Aided Diagnosis (CAD) was introduced to help in the diagnosis in order to assist in the biopsy operations. Usually, CAD is carried out utilizing either the clinical data, using data mining techniques, or using features extracted from either TransRectal UltraSound (TRUS) images or the Radio Frequency (RF) signals. <br /><br /> The challenge is that TRUS images' quality is usually poor compared to either Magnetic Resonance Imaging (MRI) or the Computed Tomography (CT). On the other hand, ultrasound imaging is more convenient because of its simple instrumentation and mobility capability compared to either CT or MRI. Moreover, TRUS is far less expensive and does not need certain settings compared to either MRI or CT. Accordingly; the main motivation of this research is to enhance the outcome of TRUS images by extracting as much information as possible from it. The main objective of this research is to implement a powerful noninvasive CAD tool that integrates all the possible information gathered from the TRUS images in order to mimic the expert radiologist opinion and even go beyond his visual system capabilities, a process that will in turn assist the biopsy operation. In this sense, looking deep in the TRUS images by getting some mathematical measures that characterize the image and are not visible by the radiologist is required to achieve the task of cancer recognition. <br /><br /> This thesis presents several comprehensive algorithms for integrated feature analysis systems for the purpose of prostate tissue classification. The proposed algorithm is composed of several stages, which are: First, the regions that are highly suspicious are selected using the proposed Gabor filter based ROI identification algorithm. <br /><br /> Second, the selected regions are further examined by constructing different novel as well as typical feature sets. The novel constructed feature sets are composed of statistical feature sets, spectral feature sets and model based feature sets. <br /><br /> Next, the constructed features were further analyzed by selecting the best feature subset that identifies the cancereus regions. This task is achieved by proposing different dimensionality reduction methods which can be categorized into: Classifier dependent feature selection (Mutual Information based feature selection), classifier independent feature selection, which is based mainly on tailoring the Artificial life optimization techniques to fit the feature selection problem and Feature Extraction, which transforms the data to a new lower dimension space without any degradation in the information and with no correlation among the transformed lower dimensional features. <br /><br /> Finally, the last proposed fragment in this thesis is the Spectral Clustering algorithm, which is applied to the TRUS images. Spectral Clustering is a novel fast algorithm that can be used in order to obtain a fast initial estimate of the cancer regions. Moreover, it can be used to support the decision obtained by the proposed cancer recognition algorithm. This decision support process is crucial at this stage as the gold standards used in obtaining the results shown in this thesis is mainly the radiologist's markings on the TRUS images. This gold standards is not considered as credible since the radiologist's best accuracy is approximately 65 %. <br /><br /> In conclusion, this thesis introduces different novel complete algorithms for automatic cancerous regions detection in the prostate gland utilizing TRUS images. These proposed algorithms complement each other in which the results obtained using either of the proposed algorithms support each other by resulting in the same classification accuracy, sensitivity and specificity. This result proves the remarkable quality of the constructed features as well as the superiority of the introduced feature selection and feature extraction methods to detect cancerous regions in the prostate gland.

Syftet med studien var att undersöka hur en gruppverksamhet vars mål är att ge psykosocialt stöd och fysisk aktivitet till män diagnostiserade med prostatacancer bör utformas och presenteras för att tilltala målgruppen. Metod: Studien hade en kvalitativ, deskriptiv ansats och baserades på fem individuella intervjuer och en fokusgruppsintervju . Samtliga intervjuer var semistrukturerade och spelades in. Huvudresultat: Innehållsanalyser av intervjuerna resulterade i följande tre kategorier; ”Presentation av gruppverksamhet”, ”Attityder” och ”Innehåll i gruppverksamhet”. Varje kategori hade även ett antal subkategorier. Tillsammans åskådliggjorde kategorierna vad män med prostatacancer ansåg att en rehabiliteringsgrupp som Rehabilitering med samtal och yoga [RSYG] ska innehålla samt hur den kan presenteras. Det mest överraskande resultatet var att av de män som tidigare inte deltagit i RSYG så var det flera som var intresserade av att delta och angav tidsbrist som främsta orsak till att de uteblivit. Slutsats: För att män skall delta i RSYG krävs inte enbart ett väl utformat flygblad eller en god synlighet, inte heller räcker det med att vårdpersonal säger åt männen att gå till RSYG, utan innehållet i Rehabilitering med samtal och yoga bör även individanpassas då alla män inte lider av samma symptom då de har och behandlas för prostatacancer. Anhöriga bör även involveras då de också påverkas av männens sjukdom och en blandning av alla dessa strategier bör därför prövas och utvärderas. / Aim: The aim of this study was to investigate how a support group, offering psychosocial support and physical activity to men diagnosed with prostate cancer, should be presented and what it should comprise of. Method: A qualitative descriptive approach was used. Five individual interviews and one focus group interview were conducted. All interviews were semi-structured and recorded. Main results: The content analysis of the interviews resulted in the following three categories; “Presentation of the support group”, “Attitudes” and “Content of the support group”. Each category had a number of subcategories assigned to them. Together, the categories described the views of men, diagnosed with prostate cancer, regarding the presentation and the content of Rehabilitation with conversation and yoga [RSYG]. The most surprising result was that several men, who had not participated in RSYG, expressed an interest in participating. Their main reason to not having participated was lack of time. Conclusion: In pursuit of more participants for RSYG, the persons in charge must not only design an appealing flyer or become more visible to the men. Nor is it enough that other health professionals, such as doctors and nurses, order the men to attend. The content of the support group must become more adaptable to the individual needs of the men since every man suffers different symptoms from prostate cancer. The spouses of the men should be included in the support group since they too get affected by the cancer. A mix of the strategies mentioned above should be tried and evaluated.

The vitamin D metabolite 1,25(OH)2D3 has long been known to inhibit growth of prostate cancer cells and this mainly through a VDR-mediated pathway controlling target gene expression, resulting in cell cycle arrest, apoptosis and differentiation. Another major way in which 1,25(OH)2D3 inhibits cell growth in prostate cancer is via membrane-initiated steroid signalling, which triggers activation of signal cascades upon steroid binding to a receptor complex, leading to induction of genes regulating cell growth, proliferation and apoptosis. The main prostate cancer inhibiting membrane-initiated route is the TGFβ signalling pathway, elicited by the protein TGFβ. Two other important proteins downstream in this cascade are Smad2 and Smad3. In this study the early effects of 1,25(OH)2D3 on activated Smad2/3 levelsin PC-3 prostate cancer cells were examined. PC-3 cells were incubated for 3, 5, 10, 30 and 60 minutes as well as 38 hours both together with 1,25(OH)2D3 of the concentrations 10-10 and 10-7 M and without. Western Blots were then performed on supernatants from the cells treated followed by treatment of the membranes with primary antibodies against phosphorylated Smad2/3 C-terminal linker regions, alkaline phosphatase conjugated secondary antibodies and finally visualization with BCIP/ NBT tablets. As the downstream cascade protein JNK is a proposed activator of Smad2/3, this procedure was also repeated with a JNK inhibitor. This is a follow-up to an earlier study which examined the influence of 1,25(OH)2D3 on TGFβ levels using the same doses and time points and which found that 1,25(OH)2D3 initially lowered the level of active TGFβ, then increased it. The results of this study indicated a 1,25(OH)2D3 mediated induction of the same pattern in the levels of active Smad2 and 3, both with and without JNK inhibitor. The results did not indicate that 1,25(OH)2D3 activates the Smad2/3 C-terminal linker region via the JNK pathway.