Background: Colorectal cancer is the third most common cancer and cause of related deaths worldwide. Early colorectal cancer diagnosis is vital in reducing incidence and mortality. There is a need for the development of non-invasive screening tools for enhancing the detection of the disease. Cancer specific peptides are useful cancer targeting agents that can be used to specifically improve early detection strategies. Several cancer targeting peptides have been identified. Previous work investigated the specific binding of three of these peptides (p.C, p.L and p.14) conjugated to quantum dots and were found to bind to colorectal cancer cell lines (HT-29 and Caco-2). However, their uptake, localization and biodistribution in an in vitro and in vivo colorectal cancer model have not been determined. This is essential in gaining an understanding for future diagnostic or therapeutic based applications. Primary Aim: The aim of this study was investigate the localization of three selected peptides p.C, p.L and p.14 conjugated to gold nanoparticles in an in vitro and in vivo colorectal cancer model using HRTEM. Methodology: The AuNP/peptide conjugates were characterized by HRTEM and DLS. For in vitro studies; HT-29, Caco-2 and C3A cells were exposed to the AuNP-p.C, AuNP-p.L and AuNP-p.14, collected and processed for HRTEM to assess targeting and localization. For in vivo studies; the establishment of a colorectal cancer model using the AOM/DSS model 1 and 2 was conducted. Wistar rats were assigned to 6 groups, five experimental and 1 control group. Group 1 received AOM/DSS method 1 and was treated with AuNP-p.L. Group 2 and 3 received AOM/DSS method 2 and were treated with AuNP-p.C and AuNP-p.14. Group 4 and 5 remained healthy and treated with AuNP-p.C and AuNP-p.14. Group 6 remained healthy receiving no nanoparticle treatment. After treatment, rats were sacrificed and tissue was processed for HRTEM. Tissue chosen for HRTEM analysis included: Group 1 (inflamed colon, rectum, pancreatic and kidney), Group 4 (kidney) and Group 5 (liver). Results: results obtained from nanoparticle characterization suggested that nanoparticles were conjugated to their respective peptides and were stable in dispersion. For in vitro studies, results suggested no AuNP targeting and localization in HT-29 cell lines. For in vivo studies, no colorectal cancer tumours were induced. TEM micrographs did not indicate the presence of nanoparticles in colon, rectum, pancreatic, kidney and liver tissue. However, AuNPs were found in the kidney tissue (group 4). Conclusion: Although the overall objectives were not met, this study provided insight into TEM cell preparation and optimization for future nanoparticle cell interaction research. This study also demonstrated the absence of AuNPs in healthy tissue and the presence of AuNPs in healthy kidney tissue through renal clearance, a favourable quality for diagnostic or therapeutic applications.

According to U.S. Breast Cancer Statistics, about 1 in 8 U.S. women will develop invasive breast cancer during their lifetime. Chemotherapeutics that are used on patients currently often lead to tumor resistance, bone marrow suppression and cachexia. This study evaluated a novel combination of three non-mutagenic compounds for their effectiveness against mammary tumor cells, toxicity towards immune cells, ability to provoke the expression of immunogenic cell death (ICD) markers, and killing in 3D tumor models. Methotrexate (MTX), 2-deoxyglucose (2DG), and wogonin (WGN) were combined at doses well below their EC50 values yet effectively killed human and mouse breast cancer cells. The combination inhibited cancer cell colony formation and induced a high degree of cell death in multiple malignant tumor cell lines. Importantly, the combination did not significantly inhibit the viability of peripheral-blood mononuclear cells (PBMCs), even when employed at 3X the concentration that killed cancer cells. In marked contrast, low-dose doxorubicin, a common therapeutic for breast cancers, significantly decreased PBMC viability and increased the percentage of cell death. Our novel combinatorial therapy (Trifecta) elicited the significant expression of three ICD hallmarks: calreticulin surface expression, ATP secretion, and HMGB-1 release. In all cases, Trifecta elicited an equal or greater degree of ICD-marker expression compared to doxorubicin, a known inducer of ICD. We show significant efficacy of Trifecta against human and mouse mammary 3D tumor models grown in Matrigel® ECM-complex containing culture medium, and reaffirm the marked resistance of tumorspheres towards the conventional chemotherapeutic doxorubicin. The effectiveness of Trifecta in an acceptable surrogate model for mouse studies bodes well for translation of our findings to the clinic. In conclusion, Trifecta has proven highly effective against tumor cells grown either as monolayers or tumorspheres, without significant cytotoxic effects towards proliferating immune cells. Furthermore, treatment with this combination elicits ICD, which has the potential to prime an adaptive immune response against tumor cells and prevent future relapse. The drugs chosen for our combination target metabolic pathways that cancer cells are heavily dependent upon and do not interact with or induce mutations in DNA. These properties place Trifecta at the forefront of developing anticancer therapies. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2020. / FAU Electronic Theses and Dissertations Collection

Indiana University-Purdue University Indianapolis (IUPUI) / Cancer treatment-related fatigue (CTRF) is recognized as a prevalent and bothersome symptom for patients with cancer. In a model of the CTRF experience, CTRF representation, or the beliefs, thoughts and emotions surrounding the experience of CTRF, is believed to mediate the relationship between CTRF intensity and CTRF distress. To date, there is no reported measure of CTRF representation. The purpose of this descriptive, cross-sectional study guided by Leventhal’s Common Sense Model of Self-Regulation was to evaluate an instrument designed to measure CTRF representation, the CTRF Representation scale (CTRFRep), based on an existing measure, the Illness Perception Questionnaire (IPQ-R). The study included 47 patients (mean age=57.7 years) receiving radiation therapy for cancer interviewed one month post-treatment. 77% of patients had fatigue during treatment. Three content experts and one theory expert assessed content validity of the CTRFRep. The content experts included three behavioral oncology nurse researchers whose focus is on symptom management and/or fatigue. The theory expert was a nurse researcher who is an expert in the area of self-regulation theory. As tested, the CTRFRep consisted of 105 items in 10 subscales addressing beliefs about the Identity, Timeline (Acute vs. Chronic/Cyclical), Consequences (positive/negative), Cause, Control (Treatment/Personal), Symptom Coherence, and Emotional Representation of CTRF. When evaluating psychometrics, the Identity and Cause subscales are analyzed independent of the other subscales. For the Identity subscale, symptoms most reported as related to CTRF were lack of energy, loss of strength, and feeling blue. For the Cause subscale, the most common beliefs regarding causes of CTRF were cancer treatment(s), having cancer, and stress or worry. Results indicate adequate reliability in six of eight remaining subscales (α>=0.70); the item N in those subscales was reduced from 56 to 34. To address construct validity, logistic regression assessed whether CTRFRep mediated the relationship between CTRF intensity and CTRF distress. After controlling for negative affect, the Identity and Consequences subscales were significant mediators – the Acute vs. Chronic Timeline and Emotional Representation scales were partial mediators – of the relationship between CTRF intensity on CTRF distress. These findings indicate fatigue is a problem for people undergoing treatment for cancer, and the CTRFRep may be a reliable and valid measure of CTRF representation for patients undergoing radiation treatment for cancer. Small sample size prevented successful factor analysis of the CTRFRep. Further research of the CTRFRep is warranted.

Poor dose optimization in cancer trials leads to poor patient outcomes in tumor suppression and drug tolerance as well as failures in the drug development process. Most phase I clinical cancer trials still use traditional dose-finding methods, which are inadequate for evaluating novel cancer therapies, such as molecularly targeted agents and immunotherapies. Traditional approaches include using rule-based designs instead of model-based designs, assuming one dose should be recommended to all patients, and assuming the higher the dose, the better. This dissertation aims to address each of the inefficiencies that exist in phase I trials to optimize patient and trial outcomes in oncology, specifically in settings where the patient population is heterogeneous, i.e., settings where eligibility criteria have been expanded or settings evaluating a therapy that targets multiple tumor types and mutations. In the first part of this work, we address the inefficiencies of rule-based designs and the barrier to implementation of model-based designs. We use published phase I trials that used the most common rule-based method, the 3+3 design, and compare the trial outcomes to those obtained with novel model-based designs. In the second part of the work, we propose a broadened eligibility dose-finding design to address the situation of unknown patient heterogeneity in phase I cancer trials where eligibility is expanded, and multiple eligibility criteria could potentially lead to different optimal doses for patient subgroups. Lastly, we address patient heterogeneity in efficacy by developing a dose-optimization design that accounts for patient-specific characteristics, toxicity, pharmacokinetic data, and efficacy to identify the target population and inform the optimal dose for each subpopulation. The findings in each work highlight the advantages of model-based designs, particularly when tailored for the therapy and patient population in question. Using published dose-finding trials, we show that novel designs would recommend different doses about 40% of the time and confirm the advantages of these designs compared with the 3 + 3 design, as suggested previously by simulation studies. When accounting for heterogeneity in toxicity, the broadened eligibility design identified when the expanded subpopulation should be recommended a lower dose due to their tolerance and identified the criteria affecting toxicity at least 60% of the time in simulation studies. The dose-optimization design, focusing on heterogeneity in efficacy, demonstrated that a model-based approach to identifying the target population can be effective. Further, in the presence of heterogeneity, patient characteristics relating to molecular tumor characteristics were identified correctly, and a different optimal dose was recommended for each identified target subpopulation. The simulation studies of all proposed designs show that accounting for heterogeneity, even when the source of heterogeneity is unknown, is beneficial. In addition, the simulation studies highlight the poor performance of a naive method that recommends one dose for all. Our findings in this dissertation reveal the large proportion of the patient population that will be incorrectly dosed if inappropriate dose-finding designs are used. While we cannot directly understand the effect of dose selection on cancer trial outcomes, it is likely that not handling characteristics of novel cancer therapies early on contributes to the high attrition rates of cancer trials and the toxicity burden encountered in later trials and post-approval studies.

Bladder cancer is currently the 6th most common cancer in the United States, resulting in 17,000 deaths annually. Clinically, bladder cancers are mostly urothelial carcinoma, classified as either non-muscle invasive bladder cancer (NMIBC) or muscle-invasive bladder cancer (MIBC), with the latter having a 5-year survival rate of merely 50%. With recent advances in next-generation sequencing, several international consortia have elucidated molecular subtypes of MIBC. The two major subtypes of MIBCs are basal and luminal; the basal subtype frequently exhibits hallmarks of squamous differentiation and highly expressed basal markers (CD44, KRT14, KRT6A, KRT6B). Tumors of the luminal subtype have papillary morphology and highly express differentiation-associated luminal markers (e.g., KRT20, PPARG, UPKs, and FOXA1). Notably, the transcription factor Peroxisome Proliferator Activated Receptor Gamma (PPARG) gene is frequently amplified in luminal MIBC. And recurrent activating mutations have been reported for its obligatory functional partner Retinoic X Receptor (RXR). In addition, the basal subtype is immune-infiltrated and is postulated as more likely to respond to immunotherapies. In contrast, the luminal subtype is immune-cold. Despite these advances in recent years, the molecular driver of subtype determination, specifically in luminal MIBC, remains poorly understood. Furthermore, subtype-specific targeted therapy for MIBCs is still in its infancy. Our previous work determined that Pparg activation can drive luminal tumor formation. We generated a novel Krt5CreERT2; VP16;Pparg transgenic mouse model, where Pparg expression is constitutively active in basal urothelial cells upon tamoxifen induction. During homeostasis, constitutive Pparg promoted luminal differentiation and cell cycle exit in basal cells but did not produce tumors. However, increased Pparg signaling in activated basal cells following 1-month exposure to bladder-specific carcinogen BBN produced luminal tumors. These tumors are similar both in morphology and molecular markers to human luminal MIBCs. The resulting VP16;Pparg luminal tumors have reduced Nf-kb expression and are immune cold compared to basal tumors. These findings suggest that Pparg is a driver of luminal tumor formation and a suppressor of immune infiltration in bladder cancer. In Chapter 2 of the thesis, I focus on the therapeutic potential of activating Pparg in basal MIBC. We treated mice bearing BBN-induced, Pparg-negative basal tumors with synthetic Pparg ligand - Rosiglitazone (Rosi) and Mek1/2 inhibitor Trametinib (Tram), both of which have been shown to induce Pparg signaling in vitro and in vivo. The combined RosiTram treatment induced apoptosis and significantly reduced tumor burden. The post-treatment urothelium appeared similar in morphology to a healthy urothelium. RosiTram treatment also restored normal urothelial differentiation and generated resident cell types (e.g., superficial cells, intermediate cells, Keratin5+ (K5), basal cells, and Keratin14+ (K14) basal cells) that are normally seen in a healthy urothelium. In contrast, basal tumors are almost entirely composed of K14-Basal cells. Mechanistically, RosiTram treatment partially restores differentiation through retinoic acid signaling and Ezh2 inhibition. Together, our study established targeted transcriptionally and epigenetically reprogramming as a promising differentiation therapeutic approach for basal bladder tumors.

No description available.

Irreversible electroporation (IRE) is a focal ablation technique that has been shown in recent clinical trials to be effective in treating pancreatic cancer. The technique uses short, high voltage pulses to induce nanoscale pores in the target cell membranes, leading to cell death. Due to its non-thermal mechanism, IRE is particularly well suited for treating a tumor that is unresectable due to its close location to crucial structures such as blood vessels and nerves. Predicting the region of treatment is critical for optimal treatment of the tumor. The only predictive tools clinicians currently rely on for IRE treatment planning are computer tomography (CT), ultrasound (US) imaging, and real-time resistance measurement is used to monitor treatment progress. However, there is currently no method to plan optimal pulse parameters such as voltage, pulse duration, pulse number, and electrode spacing prior to treatment. Computational treatment planning models aim to perform this prediction in 3D, however, the electric field region relies on the electrical response of human tissue during IRE. This work quantifies this response for the first time and implements human tissue properties in a patient-specific, 3D treatment planning model. / Master of Science / Pancreatic cancer results in 40,000 deaths every year in the U.S, making it one of the most challenging diseases to treat. The current treatments for this disease fall short and have failed to significantly extend patient life expectancy. A technique called irreversible electroporation (IRE) has been shown in recent clinical trials to be effective in treating pancreatic cancer. IRE excels at treating tumors that are located near important blood vessels, nerves, and other important structures. However, clinicians do not have a way to visualize the region of treatment before surgery. In the research setting, 3D computational models aim to predict this area, but so far these models have been based on animal tissue, often of the incorrect organ type. This work applies IRE to human tissue samples, quantifies its electrical behavior, and implements that information in a personalized, predictive 3D model.

Patients receiving Intensity Modulated Radiation Therapy (IMRT) for late stage head and neck (HN) cancer often experience anatomical changes due to weight loss, tumor regression, and positional changes of normal anatomy (1). As a result, the actual dose delivered may vary from the original treatment plan. The purpose of this study was (a) to evaluate the dosimetric consequences of the parotid glands during the course of treatment, and (b) to determine if there would be an optimal timeframe for replanning. Nineteen locally advanced HN cancer patients underwent definitive IMRT. Each patient received an initial computerized tomography simulation (CT-SIM) scan and weekly cone beam computerized tomography (CBCT) scans. A Deformable Image Registration (DIR) was performed between the CT-SIM and CBCT of the parotid glands and Planning Target Volumes (PTVs) using the Eclipse treatment planning system (TPS) and the Velocity deformation software. A recalculation of the dose was performed on the weekly CBCTs using the original monitor units. The parameters for evaluation of our method were: the changes in volume of the PTVs and parotid glands, the dose coverage of the PTVs, the lateral displacement in the Center of Mass (COM), the mean dose, and Normal Tissue Complication Probability (NTCP) of the parotid glands. The studies showed a reduction of the volume in the PTVs and parotids, a medial displacement in COM, and alterations of the mean dose to the parotid glands as compared to the initial plans. Differences were observed for the dose volume coverage of the PTVs and NTCP of the parotid gland values between the initial plan and our proposed method utilizing deformable registration-based dose calculations. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2015. / FAU Electronic Theses and Dissertations Collection

No description available.

Thesis (MSc)--Stellenbosch University, 2015. / ENGLISH ABSTRACT: This study describes: • The UPLC-MS/MS analyses and quantification of novel 5α-reduced steroids using response factors. • The kinetic characterisation of human steroid 5α-reductase type 1 (SRD5A1), expressed in HEK-293 cells, towards 11OHA4 and 11OHT and their keto derivatives by progress curve analysis. • The subcloning, transformation and functional expression of SRD5A1 in the yeast expression system, P. pastoris. • The conversion of 11OHA4 and 11OHT and their keto derivatives by SRD5A1 expressed in P. pastoris. • The endogenous enzymatic activity in P. pastoris towards the 5α-reduced metabolites in the 11OHA4- and alternate 5α-dione pathways. • The potential application of P. pastoris as a biocatalyst in the production of 5α- reduced C19 steroids. / AFRIKAANSE OPSOMMING: Hierdie ondersoek beskryf: • Die UPLC-MS/MS analise en kwantifisering van nuut-ondekte 5α-gereduseerde steroïede met behulp van responsfaktore. • Die kinetiese karakterisering van menslike steroïed 5α-reduktase tipe 1 (SRD5A1), uitgedruk in HEK-293 selle, vir 11OHA4 en 11OHT en hul ketoderivate deur middel van progressiekurwe-analise. • Die subklonering, transformasie en funksionele uitdrukking van SRD5A1 in die gis P. pastoris. • Die omsetting van 11OHA4 en 11OHT en hul ketoderivate deur SRD5A1 uitgedruk in P. pastoris. • Die omsetting van 5α-gereduseerde steroïede in die 11OHA4 en alternatiewe 5α-dioon paaie deur endogene ensieme in P. pastoris • ‘n Ondersoek na die toepassing van die gisuitdrukkingstelsel as ‘n moontlike OR potensiële biokatalis vir die produksie van 5α-gereduseerde C19 steroïede.