Dissertations / Theses on the topic 'Prediction Of Malignant'

Oral cancer may be proceeded by dysplastic PMDs mainly presenting as leukoplakia or erythroplakia and which can carry an increased risk of malignant transformation. Therefore, early recognition of PMDs with a high potential for cancer development is important to improve patient outcome. 100 patients with dysplastic PMDs presenting in Newcastle underwent a standardised interventional management protocol based on risk factor assessment, laser excision of dysplastic lesions and long-term clinical follow-up at regular intervals. This patient cohort was studied in detail to examine the clinicopathological features that may influence disease progression. Single dysplastic PMDs were mainly observed in the floor of mouth, with 92% presenting as leukoplakia and 8% as erythroplakia. Follow-up revealed that 62% of patients remained disease-free following laser surgery, 17% showed recurrent-disease, 14% new-site dysplasia, with 5% malignant transformation and 2% developed OSCC at a site distant from the primary dysplasia. Clinical appearance, high grade dysplasia, larger sized PMDs, high risk sites and positive excision margins were shown to increase the risk of unfavourable clinical outcome. Malignant transformation was mainly seen in non-smokers and non-alcohol users, whilst new-site OSCC was only seen in non-smokers and light drinkers. The use of Raman spectroscopy in the detection and classification of dysplasia within the human oral tissue was investigated. Currently, histopathology is considered the diagnostic gold standard. Consensus opinion on dysplasia grading of individual PMD lesions using two classification systems (WHO and binary grading) was obtained and a spectral diagnostic model then correlated with the results. The ability of Raman spectroscopy to differentiate between dysplasia and morphologically normal tissue was shown, with an 81% sensitivity and specificity. This supports the suitability of the Raman system in clinical use to distinguish morphologically normal from dysplastic tissue. This work has also shown the efficacy of Raman spectroscopy in identifying early biochemical changes in epithelial dysplastic tissue before morphological/histological change becomes apparent.

Malignant melanoma (MM) is the deadliest skin cancer with an ever-increasing incidence. New treatments have improved the prognosis for patients with advanced MM. Still, most patients do not respond, and the side effects can be severe, underlining the need for better therapies. The overall aim of this thesis was to evaluate new means to improve the treatment for patients with advanced MM. Immunostimulatory gene therapy (AdCD40L) was evaluated in a clinical study and BRAF-inhibitory treatment in rare cases of BRAF-mutated MM. Due to its immunogenicity, MM is an attractive target for immunostimulatory gene therapy. AdCD40L is an adenovirus carrying the human gene for CD40 ligand, which in different ways can stimulate the immune system to combat cancer. We conducted a Phase I/IIa study with AdCD40L in patients with metastatic MM having received established treatments. In cohort 1 (n=6), four weekly, intratumoural AdCD40L injections were given. In cohort 2 (n=9), low dose cyclophosphamide was added to increase the immune response. Since irradiation may act synergistically with immunotherapy, patients in cohort 3 (n=9) also received a single fraction of radiotherapy (8 Gy). This fraction was given towards the lesion selected for injections. The primary objectives were to assess the feasibility and safety of AdCD40L-treatment and secondarily its anti-tumour effects. Patients were thoroughly assessed for toxicity. The anti-tumour response was evaluated by imaging techniques (FDG-PET/CT, DW-MRI scans), tumour biopsies and blood tests. Plasma protein markers were measured with a multiplex platform. Another objective was to evaluate the potential of DW-MRI and FDG-PET/CT for prediction of AdCD40L treatment response, in terms of overall survival (OS). AdCD40L was well tolerated with mild transient reactions. Local and distant responses in PET/CT scans along with a significantly better 6-month survival in the cohorts that received cyclophosphamide conditioning were observed. Effector lymphocyte responses were elicited. All patients had an increased T effector/T regulatory-cell ratio and death receptors were significantly up-regulated post therapy. Inflammatory cytokines and other plasma proteins were altered in favourable ways by the AdCD40L treatment. The analyses support that the functional DWI parameters may be better early predictors of OS than the established metabolic and morphologic criteria of FDG-PET/CT and CT/MRI, respectively. In conclusion, the stimulation of the CD40 pathway to initiate anti-tumour immunity is a promising treatment alternative for MM patients. However, further studies with developed treatment schemes are warranted. In the first report ever on treatment of a pregnant patient with a BRAF-inhibitor, the therapy was initiated in the second trimester. The treatment with vemurafenib enabled prolonged gestation, hence reducing the risk of immaturity-related complications. Further, we report the first case worldwide of a patient with metastatic conjunctival melanoma who benefitted from treatment with vemurafenib. Additional studies are needed to assess the efficacy of BRAF -inhibitors in the different subtypes of ocular melanoma.

Glioma is the most common and aggressive type of primary intracranial tumors. The poor prognosis of glioma patients has not changed since decades despite the advancements in diagnostic tools and treatment strategies. The inability to accurately predict the survival and response to anticancer therapy emerges from several factors including the high heterogeneity of the tumor and the inadequacy of the currently applied world-health organization (WHO) classification system. Both factors result in high variability in the clinical outcome due to variable sensitivity to treatment. Thus, molecular classification represents an important strategy for better categorization of glioma patients and for their stratification to anticancer therapy. Our high-throughput screening analysis for the identification of genetic aberrations in the glioma study population revealed high frequency of chromosomal instabilities in glioma specimens. This indicates that DNA-repair mechanisms are defective which may have contributed to gliomagenesis and progression. Furthermore, DNA-repair represents an integral interplayer in the determination of glioma response to anti-neoplastic agents due to the fact that the majority of the currently applied agents possess their cytotoxicity via DNA-damaging actions. TDP1 has been implicated in the resistance to various types of anticancer agents in vitro, including radiation and topoisomerase poisons due to its ability to repair various types of DNA lesions. Moreover, it has been found to be overexpressed in different kinds of cancers, however, its relevance in glioma has not yet been studied. In this work we show that TDP1 is overexpressed in patients with malignant glioma compared with non-tumor cases. An ascending increase of TDP1 protein expression with a correlation with glioma grade is evidenced in the astrocytic lineage and glioblastoma multiforme samples expressed the highest levels. Moreover, we show an association between high TDP1 transcript levels and the poor prognosis of glioma patients. These findings suggest that TDP1 plays an important role in gliomagenesis; however, the underlying molecular mechanisms need to be identified. For an exploration of the predictive value of TDP1 in malignant glioma the correlation between TDP1 level and the sensitivity of malignant glioma cell lines to anticancer therapy has been investigated. We show that manipulating TDP1 level alone in malignant glioma cell lines is not sufficient to modulate their response to treatment. TDP1 overexpression or knockdown resulted in changes in the transcript levels of several DNA-repair genes including MGMT, topoisomerases and the base excision repair genes PARP-1, PNKP and XRCC1. This hindered the ability to characterize the role of TDP1 to modulate the in vitro sensitivity of malignant glioma cell lines to topoisomerase poisons and temozolomide. Nonetheless, this emphasizes the importance of the comprehensive role of several DNA-repair genes for a finalized DNA-repair process to determine the sensitivity of tumor cells to DNA-damaging anticancer agents. Finally, we tested the ability of inhibiting TDP1 enzyme activity to potentiate or synergize the cytotoxicity of topoisomerase poisons using small-molecule ligands. We show that treatment of malignant glioma cell lines with a combinational therapy of a small-molecule TDP1 inhibitor and a topoisomerase poison enhances their sensitivity to the latter drug but with minimal efficacy. As a conclusion, the characterization of TDP1 in glioma is a novel finding that can aid in enhancing the diagnosis and prognosis of patients. However, its role as a predictive biomarker for better stratification of patients to therapy needs further investigation.

Background - Current guidelines suggest that all cancer patients with venous thrombosis be treated with long-term low molecular weight heparin. Whether treatment strategies should vary according to clinical characteristics remains unknown. // Systematic review - A systematic review was performed to determine current understanding of the association between malignancy characteristics in patients with cancer-associated VTE and the risk of VTE recurrence. Four retrospective and 6 prospective studies were included. They suggest that lung cancer, metastases, and adenocarcinomas confer an increased the risk of recurrence and breast cancer a low risk. // Survey - I performed survey to evaluate thrombosis experts’ opinion about the low risk of VTE recurrence they would consider acceptable for patients with cancer- associated thrombosis 103 specialists participated. 80% of respondents agreed that a risk of recurrent VTE during anticoagulation below 7% is low enough. 92% agreed that a CPR that categorizes risk of recurrence is relevant. // Retrospective Study - I performed a single retrospective cohort study to assess the feasibility of derivation of a CPR that stratifies VTE recurrence risk in patients with cancer–associated thrombosis. The study included 543 patients. A multivariate analysis selected female, lung cancer and prior history of VTE as high risk predictors and breast cancer and stage I disease as low risk. // Conclusion - Patients with cancer-associated thrombosis do have varying risks of recurrent VTE depending on clinical characteristics.

Background: Screening is offered to individuals who have an identified increased risk of pancreatic cancer. Such risks may be increased because of a family history or a known genetic mutation which has been shown to confer increased risk. Amongst those being screened intraductal papillary mucinous neoplasm (IPMN) of the pancreas are increasingly common entities being detected incidentally; their risk of malignancy can be as high as 85%. Consensus guidelines exist for the management of these lesions – the morbidity associated with pancreas resection is as high as 50%. We set out to identify a marker which could be used to identify those IPMN which should be resected and those which may be safely observed. Methods: Individuals were identified from the European Registry of Hereditary Pancreatitis and Familial Pancreatic Cancer (EUROPAC) or patients identified in Liverpool or Hedielberg with cystic lesions and/or pancreatic cancer. Cancer screening was performed by imaging and with molecular analysis (including mutation analysis of TP53) of pancreatic juice obtained by endoscopic retrograde cholangiopancreatography (ERCP). Matched tissue sections and frozen sections of pancreatic tissue from 73 patients who underwent resection for IPMN were assessed histologically and for mutations in TP53 status using a novel limiting dilution Next Generation Sequencing technique. Results were assessed relative to clinical outcomes. Results: Amongst those 29 individuals who were screened with ERCP, 11 had IPMN, 7 IPMN with cancer (IPMC) and 3 pancreatic ductal adenocarcinoma (PDAC). The remaining cases were benign neoplastic or inflammatory conditions. Kaplan-Meier survival analysis at 5 years found that the presence of p53 mutation in the tissue was a better prognostic marker of survival than the histological diagnosis alone (p=0.0152 vs. p=0.0819). Sensitivity and specificity of p53 mutation as a predictor of survival was calculated as 0.89 and 0.95 respectively. There was 100% correlation between the p53 mutational status of the resected tissue and the pancreatic juice obtained at ERCP. When ERCP was assessed as a method for screening, however, there was found to be an unacceptably high incidence of post-ERCP pancreatitis (PEP) 7 cases of PEP in 16 ERCPs (44%). This rate was shown to be significantly reduced to 15% (6/40) with the use of pancreatic stent and diclofenac, but the overall prevalence of PEP was 23.2% over 14 years. There were no cases of PEP amongst those individuals being screened because of hereditary pancreatitis. Of 27 IPMN cases with frozen tissue 23 individuals had TP53 mutations. Seven cases died of pancreatic cancer after resection. Kaplan-Meier survival analysis revealed that one mutation p.L264R predicted survival regardless of histology (p= < 0.0001). The mutation was present in 6 of the 7 cases who died and in none of those who survived to 5 years. Mutation specific PCR was used to validate results showing that p.L264R discriminated between survivors and IPMN cases who died of cancer (AUC = 0.79). Conclusions: IPMN continues to cause concern and uncertainty among those individuals being screened for cancer who are largely well and asymptomatic. The p.L264R mutation could be used to differentiate those IPMN which result in poor survival to facilitate potentially curative surgery. The mutation may be present in pancreatic juice which can be collected endoscopically as a screening tool. The use of prophylactic measures to reduce PEP may be considered sufficient to bring the risk of complications to an acceptable level when compared to the relative certainty of prognosis afforded by a positive test for p.L264R.

Ovarian cancer is the most lethal gynaecological malignancy; however, ovarian lesions are very common and only around 1% are malignant. Due to the large number of cases, patients are triaged by gynaecologists having a high variability in diagnostic accuracy. The aim of this study is to train and validate deep neural networks and, by comparison to subjective expert assessment, determine their potential in the triage of patients with ovarian tumours. We used a transfer learning approach on pre-trained networks (VGG16, ResNet50, MobileNet), and a post-processing calibration to better align their confidence scores with the true certainty of their predictions. Our dataset contained 3077 transvaginal ultrasound images from 758 patients with ovarian tumours, where histological outcome from surgery or long-time follow-up (> 3 years) served as diagnostic ground truth. From our dataset, 150 cases (75 benign, 75 malignant), each containing 3 images, were held out for testing, while the remaining cases were used for training and model selection. The models were assessed bases on sensitivity, specificity, and AUC, along with their corresponding 95% confidence intervals. On the test set, our final model had a sensitivity of 96.0% (0.897–0.989), specificity of 86.7% (0.776–0.929), and AUC of 0.950 (0.906–0.985). When excluding the 12.7% (0.073–0.180) of cases most difficult to classify (based on the confidence score of the model output), our model had a sensitivity of 97.1% (0.909–0.994), specificity of 93.7% (0.856–0.978), and AUC of 0.958 (0.911–0.993). As comparison, the subjective expert assessment had a sensitivity and specificity of 96.0% and 88.0% respectively. We show that neural networks can be used to predict ovarian malignancy with high diagnostic accuracy, comparable to that of human experts, and thus have potential in the triage of patients with ovarian tumours.
Äggstockscancer har högst dödlighet bland gynekologiska cancersjukdomar. Äggstocksförändringar är dock vanligt förekommande och endast omkring 1% är maligna. På grund av den höga förekomsten görs initialt en bedömning lokalt (triage) huruvida patienten skall remitteras vidare för expertbedömning, eller om uppföljning på lokal vårdinrättning är tillräcklig. Triagen utförs av gynekologer som saknar utan expertkompetens inom äggstockscancer, och därav har stor variation i diagnostisk precision. Syftet med denna studie är att, genom jämförelse med subjektiv expertbedömning, utvärdera potentialen hos artificiella neurala nätverk för triagering av kvinnor med äggstockstumörer. Vi använde transfer learning av förtränade modeller (VGG16, ResNet50, MobileNet) och en kalibreringsmetod för bättre probabilistisk överensstämmelse mellan modellernas svar och deras underliggande diagnostiska precision. Vårt bildmaterial bestod av 3077 transvaginala ultraljudsbilder från 758 kvinnor med äggstockstumörer. Samtliga fall hade säkerställd diagnos genom resultat från operation eller långvarig uppföljning (> 3 år). Av detta material lades 150 fall (75 benigna, 75 maligna) à 3 bilder åt sidan för slutgiltig validering av modellen, medan resterande fall användes till träning och val av modell. Modellerna bedömdes baserat på sensitivitet, specificitet och AUC, ihop med deras 95\% konfidensintervall. Vid validering hade vår slutgiltiga modell en sensitivitet på 96,0% (0,897–0,989), specificitet på 86,7% (0,776–0,929), och AUC på 0,950 (0,906–0,985). Vid uteslutande av 12,7% (0,073–0,180) av de fall som var svårast att klassificera hade vår modell en sensitivitet på 97,1% (0,909–0,994), specificitet på 93,7% (0,856–0,978) och AUC på 0,958 (0,911–0,993). Som jämförelse hade den subjektiva expertbedömningen en sensitivitet och specificitet på 96,0%, respektive 88,0%. Vår studie visar att artificiella neurala nätverk kan användas för differentiering av benigna och maligna äggstockstumörer med hög diagnostisk precision, jämförbar med den hos erfarna läkare på området. Således bedömer vi att det finns potential för användning av dessa modeller för triagering av kvinnor med äggstockstumörer.

The aim of this thesis was to investigate the clinical problem of the initial management of febrile neutropenia (FN) in children and young people undergoing treatment for malignant disease, to thoroughly evaluate the existing research, and to collect and synthesise this to quantify the risk of adverse clinical outcomes, through development of develop a new risk prediction model, using individual participant data (IPD). A further aim was to develop methodological approaches to IPD analysis in the development of predictive models, including the graphical display and communication of such information. The research produced five systematic reveiws of the existing medical literature in this area, and helped create a global collaboration of 19 research groups (PICNICC) which has shared data on over 5000 episodes of FN. This individual patient data was synthesised using hierarchical logistic regression meta-analysis to develop a new predictive model for MDI, which is robust to internal validation techniques (bootstrapping and leave-one-out cross-validation). The multivariable predictive model derived had six components: Tumour type, temperature, clinical description of being “severely unwell”, and the results of measurements of three elements of the full blood count: haemoglobin concentration, total white cell count and absolute monocyte count. It showed good overall fit (Brier[scaled] 4.5% discordancy), moderate discrimination (AU-ROC 0.736) and good calibration between predicted and actual estimates of the risk of MDI (calibration slope 0.95). We have demonstrated that such a data sharing project is feasible across many different jurisdictions and eras of study, and we now need to undertake a series of further projects to evaluate the model and go on to improve the management of paediatric FN across the world.

BACKGROUND: Malignant pleural mesothelioma (MPM) is an aggressive tumor with increasing incidence in industrialized countries, because of previous widespread asbestos exposure and long latency time before symptoms appearance. Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) belongs to the tumor necrosis factor (TNF) family of death ligands; it was identified as a promising anticancer agent thanks to its property of killing cancer cells while sparing normal cells. Conflicting evidences about MPM resistance rather than sensitivity to TRAIL-induced apoptosis were previously reported. While TRAIL-dependent apoptosis is thought to be p53-independent, p53 wild type cancer cells can be sensitized to TRAIL through p53 activation. In contrast to most solid tumors, MPM cells frequently express wild type p53, thus p53 reactivation might be considered as an effective strategy to sensitize MPM cells to TRAIL-dependent apoptosis. DNA-damaging agents such as chemotherapy or radiotherapy and other agents targeting negative regulators of p53, may be considered as useful strategies to reactivate p53. Murine Double Minute 2 (MDM2) is a transcriptional target of p53: once activated, MDM2 binds p53 to the amino-terminus, targeting it for ubiquitylation and subsequent proteasomal degradation. Recently, many researchers have investigated a possible role of MDM2 in promoting tumor neoangiogenesis (Vascular Endothelial Growth Factor, VEGF; hypoxia inducible factor, HIF1alpha). Thus MDM2 might be a promising target for anticancer treatment because of its antiapoptotic and proangiogenetic role. The poor prognosis of affected patients, the lack of effective treatment options, with particular reference to biologic drugs, the absence of predictive markers for targeted treatment and the lack of knowledge about the basis of different biological and clinical behaviour of the two main histologic subtypes, epithelioid versus non-epithelioid (sarcomatoid/biphasic), constitute the rationale for the present study. AIMS: The first purpose of the study was to investigate new treatment options through preclinical evaluation of extrinsic apoptosis triggers (recombinant human Apo2L/TRAIL) in combination with intrinsic apoptosis inducers acting through the reactivation of p53, such as DNA-damaging agents (carboplatin/pemetrexed) or p53-MDM2 inhibitors (nutlin3-RG7112), both in vitro and in vivo. Moreover, the study aims to investigate new targets (MDM2, HIF1alpha, VEGF) for treatment in MPM tumor samples, testing possible different expression levels of such targets in the different histologic subtypes. Some morphological features, such as inflammation, necrosis and proliferation were quantified in the different histotypes and correlated with MDM2 and HIF1alpha. Finally, correlations between molecular data and clinical features were performed. METHODS: Anticancer effects of rhApo2L/TRAIL (Amgen, Genentech) plus chemotherapy (Carboplatin/Pemetrexed) or nutlin3-RG7112 (Roche) was evaluated in different cell lines through annexin V and caspases assay, and in a Severe Combined ImmunoDeficiency (SCID) mouse model. p53 expression levels were evaluated through western blot. TRAIL receptors were evaluated through flow cytometry. Formalin-Fixed Paraffin Embedded (FFPE) chemonaive tumor samples from MPM patients were analyzed: MDM2, VEGF and HIF1alpha mRNA and protein expression levels were investigated through RT-qPCR and immunohistochemistry (IHC) with specific antibodies, respectively. Proliferation was quantified through staining with Ki67 antibodies. Necrosis and inflammation were also quantified on histological sections using a grading score. Normal pleura samples from patients undergoing diagnostic surgery for non cancer disease were used as negative controls. Clinical data of the patients under study were collected in a password-protected database: age, gender, ECOG PS (Performance Status), EORTC score, stage, systemic treatments, surgery, radiotherapy, first progression and last follow-up date, status (alive/dead). RESULTS: In vitro and in vivo results showed a significant increase of apoptosis in cell lines and reduction of tumor volume in animal models treated with rhApo2L/TRAIL plus chemotherapy or nutlin3-RG7112 compared with those receiving single treatments. This synergistic effect was dependent on the ability of chemotherapy or nutlin3-RG7112 to increase the expression of the TRAIL receptors DR4 and DR5 in a p53 manner. Higher MDM2 and HIF1alpha IHC expression was significantly associated with sarcomatoid/biphasic histologic subtype (p=0.010 and p=0.007, respectively) with positive correlation between MDM2 and HIF1alpha expression levels (correlation coefficient=0.533; p value= 0.00626). Proliferation index was significantly higher in sarcomatoid/biphasic compared with epithelioid samples (p=0.005) and also significantly higher in tumor samples with higher MDM2 expression (p=0.008). Clinical and pathological features or biomarker did not show any correlation with prognosis, except for proliferation index and Progression Free Survival (PFS), even though the results of this exploratory analysis should be considered with caution because of the limited number of patients, the heterogeneous treatment received and the insufficient follow-up time in some patients. CONCLUSION: Our preclinical in vitro and in vivo results confirm that reactivation of p53 by chemotherapy or p53-MDM2 inhibitors effectively sensitizes to TRAIL-dependent apoptosis in malignant pleural mesothelioma. Our translational study in tumor samples from MPM patients confirmed different biological and pathological features and molecular targets expression in the two main histologic subtypes. It is tempting to speculate that MDM2 and Ki67 might be considered as further useful diagnostic tools to identify poor prognosis patients. Moreover, MDM2 and HIF1alpha might be considered as promising targets for anticancer treatment of MPM.
BACKGROUND: Il mesotelioma pleurico maligno (MPM) è una neoplasia aggressiva con incidenza in aumento nei paesi industrializzati per la pregressa esposizione ad amianto e il lungo periodo di latenza tra l’esposizione e la comparsa dei sintomi. TRAIL (Tumor necrosis factor-related apoptosis-inducing ligand) appartiene alla famiglia dei ligandi di morte apoptotica di TNF (tumor necrosis factor), ed è stato recentemente identificato come promettente agente antitumorale in considerazione della sua proprietà di uccidere le cellule tumorali, risparmiando le cellule normali. Evidenze contrastanti riportano la presenza di resistenza piuttosto che di sensibilità delle cellule di mesotelioma maligno all’apoptosi mediata da TRAIL. Sebbene l’apoptosi indotta da TRAIL (via estrinseca dell’apoptosi) sembra essere indipendente da p53, alcune cellule tumorali portatrici di p53 wild-type possono essere sensibilizzate alla morte da TRAIL attraverso l’attivazione di p53 (via intrinseca dell’apoptosi). Contrariamente alla maggior parte delle neoplasie, le cellule di mesotelioma pleurico esprimono più frequentemente p53 wild-type, e quindi la riattivazione di p53 potrebbe essere una strategia efficace per sensibilizzare le cellule di mesotelioma all’apoptosi mediata da TRAIL. Agenti in grado di danneggiare il DNA (chemioterapia, radioterapia) ed altri agenti in grado di “down-regolare” gli inibitori di p53, possono essere considerati come valide strategie per riattivare p53. Murine Double Minute 2 (MDM2) è un bersaglio dell’attività trascrizionale di p53: una volta attivata, MDM2 lega il dominio ammino-terminale di p53 e la conduce al processo di ubiquitilazione e successiva degradazione proteasomica. Negli anni recenti, molti ricercatori hanno studiato un possibile ruolo di MDM2 nella attivazione di marcatori di neoangiogenesi tumorale (Vascular Endothelial Growth Factor, VEGF; hypoxia inducible factor, HIF1alpha), pertanto MDM2 potrebbe rappresentare un promettente bersaglio per il trattamento antitumorale in considerazione della sua possibile duplice attività antiapoptotica e proangiogenetica. La prognosi infausta dei pazienti affetti, l’assenza di opzioni terapeutiche efficaci, in particolare di farmaci biologici, l’assenza di marcatori predittivi di risposta ai farmaci a bersaglio molecolare, e la scarsità di conoscenze sui meccanismi che sottendono al diverso comportamento biologico e clinico dei due principali sottotipi istologici (epitelioide versus non-epitelioide), costituiscono il razionale del presente studio. OBIETTIVI: Il primo obiettivo è stato valutare nuove opzioni terapeutiche attraverso studi preclinici in vitro ed in vivo con associazione di induttori della via estrinseca dell’apoptosi (rhApo2L/TRAIL) e induttori della via intrinseca dell’apoptosi che agiscono attraverso riattivazione di p53, come agenti danneggianti il DNA (carboplatino/pemetrexed) o inibitori del legame p53-MDM2 (nutlin3-RG7112). Secondariamente, lo studio si è proposto di ricercare l’espressione dei nuovi bersagli terapeutici (MDM2, HIF1alpha) nei campioni tumorali di pazienti affetti da mesotelioma maligno, e di valutarne la diversa espressione nei diversi sottotipi istologici. Inoltre, il progetto si è focalizzato sulla valutazione di alcuni parametri morfologici come infiammazione, necrosi ed indice proliferativo nei campioni tumorali dei diversi istotipi e sulla loro correlazione con MDM2 e HIF1alpha. Infine, sono state valutate le correlazioni tra dati molecolari e caratteristiche cliniche dei pazienti in studio. MATERIALI E METODI: l’attività antitumorale di rhApo2L/TRAIL (Amgen, Genentech) in associazione a chemioterapia (Carboplatino/Pemetrexed) o nutlin3-RG7112 (Roche) è stata valutata in diverse linee cellulari attraverso il saggio di Annessina V e delle caspasi, e in un modello di topo Severe Combined ImmunoDeficiency (SCID). I livelli di espressione di p53 sono stati analizzati attraverso western blot. I recettori di TRAIL sono stati rilevati attraverso citofluorimetria. Campioni tumorali fissati in formalina e inclusi in paraffina da pazienti chemonaive sono stati analizzati con immunoistochimica e valutando l’espressione di mRNA per MDM2 e HIF1alpha. L’indice proliferativo è stato quantificato mediante anticorpo monoclonale di Ki67. La presenza di infiammazione e necrosi è stata valutata su sezioni istologiche. Campioni di pleura normale da pazienti sottoposti a chirurgia toracica per patologia non oncologica sono stati utilizzati come controlli negativi. I dati clinici dei pazienti in studio sono stati raccolti un un database protetto da password: età, sesso, ECOG PS (Performance Status), score prognostico EORTC, stadio, trattamenti sistemici, chirurgia, radioterapia, prima progressione, data di ultimo follow-up e status (vivo/morto). RISULTATI: I risultati in vitro ed in vivo mostrano un significativo aumento di apoptosi in linee cellulari e riduzione di volume tumorale in modelli animali trattati con rhApo2L/TRAIL in associazione a chemioterapia o nutlin3-RG7112, confrontato ai singoli trattamenti. Tale effetto sinergico è correlato all’incremento di espressione dei recettori di TRAIL (DR4 e 5) conseguente alla riattivazione di p53 da chemioterapia o nutlin3-RG7112. Abbiamo poi valutato i livelli di espressione di MDM2 e del suo possibile target HIF1alpha in campioni tumorali di pazienti affetti da mesotelioma. I livelli di espressione di MDM2 e HIF1alpha erano significativamente più elevati nel sottotipo istologico sarcomatoide/bifasico (p=0.010 and p=0.007, respectively), ed è stata osservata una correlazione positiva tra i livelli di espressione di MDM2 e HIF1alpha (coefficiente di correlazione =0.533; p = 0.00626). Infine, l’indice proliferativo (Ki67) si è dimostrato significativamente più elevato nel sottotipo istologico sarcomatoide/bifasico rispetto a quello epitelioide (p=0.005) e significativamente più elevato nei campioni con iperespressione di MDM2 (p=0.008). Per quanto riguarda gli obiettivi esploratori del progetto, nessuna correlazione prognostica è stata osservata per alcun parametro clinico o patologico o per diversi livelli di espressione dei biomarcatori in studio, mentre è stata osservata una correlazione significativa tra i livelli di Ki67 e la sopravvivenza libera da progressione. I risultati di tale indagine esploratoria devono, comunque, essere considerati con cautela per la limitata dimensione campionaria, l’eterogeneità degli interventi terapeutici e l’insufficiente follow-up di alcuni pazienti. CONCLUSIONI: I risultati in vitro e in vivo di questo progetto di ricerca dimostrano che la riattivazione di p53 con chemioterapia o molecole inibitrici del legame p53-MDM2 rappresenta un’efficace strategia per sensibilizzare all’apoptosi mediata da TRAIL. Lo studio traslazionale ha invece confermato diverse caratteristiche biologiche e patologiche così come differenti livelli di espressione di nuovi bersagli terapeutici nei due sottotipi istologici di MPM. MDM2 e Ki67 possono essere considerati come importanti ausili diagnostici per una migliore caratterizzazione dell’istotipo e soprattutto per identificare i tumori a peggiore prognosi. Inoltre, MDM2 e HIF1alpha potrebbero rappresentare promettenti bersagli per il trattamento del mesotelioma pleurico maligno.

Nowadays, lung cancer assessment is a complex and tedious task mainly per- formed by radiological visual inspection of suspicious pulmonary nodules, using computed tomography (CT) scan images taken to patients over time. Several computational tools relying on conventional artificial intelligence and computer vision algorithms have been proposed for supporting lung cancer de- tection and classification. These solutions mostly rely on the analysis of indi- vidual lung CT images of patients and on the use of hand-crafted image de- scriptors. Unfortunately, this makes them unable to cope with the complexity and variability of the problem. Recently, the advent of deep learning has led to a major breakthrough in the medical image domain, outperforming conven- tional approaches. Despite recent promising achievements in nodule detection, segmentation, and lung cancer classification, radiologists are still reluctant to use these solutions in their day-to-day clinical practice. One of the main rea- sons is that current solutions do not provide support to automatic analysis of the temporal evolution of lung tumours. The difficulty to collect and annotate longitudinal lung CT cases to train models may partially explain the lack of deep learning studies that address this issue. In this dissertation, we investigate how to automatically provide lung can- cer assessment through deep learning algorithms and computer vision pipelines, especially taking into consideration the temporal evolution of the pulmonary nodules. To this end, our first goal consisted on obtaining accurate methods for lung cancer assessment (diagnostic ground truth) based on individual lung CT images. Since these types of labels are expensive and difficult to collect (e.g. usually after biopsy), we proposed to train different deep learning models, based on 3D convolutional neural networks (CNN), to predict nodule malig- nancy based on radiologist visual inspection annotations (which are reasonable to obtain). These classifiers were built based on ground truth consisting of the nodule malignancy, the position and the size of the nodules to classify. Next, we evaluated different ways of synthesizing the knowledge embedded by the nodule malignancy neural network, into an end-to-end pipeline aimed to detect pul- monary nodules and predict lung cancer at the patient level, given a lung CT image. The positive results confirmed the convenience of using CNNs for mod- elling nodule malignancy, according to radiologists, for the automatic prediction of lung cancer. Next, we focused on the analysis of lung CT image series. Thus, we first faced the problem of automatically re-identifying pulmonary nodules from dif- ferent lung CT scans of the same patient. To do this, we present a novel method based on a Siamese neural network (SNN) to rank similarity between nodules, overpassing the need for image registration. This change of paradigm avoided introducing potentially erroneous image deformations and provided computa- tionally faster results. Different configurations of the SNN were examined, in- cluding the application of transfer learning, using different loss functions, and the combination of several feature maps of different network levels. This method obtained state-of-the-art performances for nodule matching both in an isolated manner and embedded in an end-to-end nodule growth detection pipeline. Afterwards, we moved to the core problem of supporting radiologists in the longitudinal management of lung cancer. For this purpose, we created a novel end-to-end deep learning pipeline, composed of four stages that completely au- tomatize from the detection of nodules to the classification of cancer, through the detection of growth in the nodules. In addition, the pipeline integrated a novel approach for nodule growth detection, which relies on a recent hierarchi- cal probabilistic segmentation network adapted to report uncertainty estimates. Also, a second novel method was introduced for lung cancer nodule classification, integrating into a two stream 3D-CNN the estimated nodule malignancy prob- abilities derived from a pre-trained nodule malignancy network. The pipeline was evaluated in a longitudinal cohort and the reported outcomes (i.e. nodule detection, re-identification, growth quantification, and malignancy prediction) were comparable with state-of-the-art work, focused on solving one or a few of the functionalities of our pipeline. Thereafter, we also investigated how to help clinicians to prescribe more accurate tumour treatments and surgical planning. Thus, we created a novel method to forecast nodule growth given a single image of the nodule. Partic- ularly, the method relied on a hierarchical, probabilistic and generative deep neural network able to produce multiple consistent future segmentations of the nodule at a given time. To do this, the network learned to model the mul- timodal posterior distribution of future lung tumour segmentations by using variational inference and injecting the posterior latent features. Eventually, by applying Monte-Carlo sampling on the outputs of the trained network, we esti- mated the expected tumour growth mean and the uncertainty associated with the prediction. Although further evaluation in a larger cohort would be highly recommended, the proposed methods reported accurate results to adequately support the ra- diological workflow of pulmonary nodule follow-up. Beyond this specific appli- cation, the outlined innovations, such as the methods for integrating CNNs into computer vision pipelines, the re-identification of suspicious regions over time based on SNNs, without the need to warp the inherent image structure, or the proposed deep generative and probabilistic network to model tumour growth considering ambiguous images and label uncertainty, they could be easily appli- cable to other types of cancer (e.g. pancreas), clinical diseases (e.g. Covid-19) or medical applications (e.g. therapy follow-up).
Avui en dia, l’avaluació del càncer de pulmó ´es una tasca complexa i tediosa, principalment realitzada per inspecció visual radiològica de nòduls pulmonars sospitosos, mitjançant imatges de tomografia computada (TC) preses als pacients al llarg del temps. Actualment, existeixen diverses eines computacionals basades en intel·ligència artificial i algorismes de visió per computador per donar suport a la detecció i classificació del càncer de pulmó. Aquestes solucions es basen majoritàriament en l’anàlisi d’imatges individuals de TC pulmonar dels pacients i en l’ús de descriptors d’imatges fets a mà. Malauradament, això les fa incapaces d’afrontar completament la complexitat i la variabilitat del problema. Recentment, l’aparició de l’aprenentatge profund ha permès un gran avenc¸ en el camp de la imatge mèdica. Malgrat els prometedors assoliments en detecció de nòduls, segmentació i classificació del càncer de pulmó, els radiòlegs encara són reticents a utilitzar aquestes solucions en el seu dia a dia. Un dels principals motius ´es que les solucions actuals no proporcionen suport automàtic per analitzar l’evolució temporal dels tumors pulmonars. La dificultat de recopilar i anotar cohorts longitudinals de TC pulmonar poden explicar la manca de treballs d’aprenentatge profund que aborden aquest problema. En aquesta tesi investiguem com abordar el suport automàtic a l’avaluació del càncer de pulmó, construint algoritmes d’aprenentatge profund i pipelines de visió per ordinador que, especialment, tenen en compte l’evolució temporal dels nòduls pulmonars. Així doncs, el nostre primer objectiu va consistir a obtenir mètodes precisos per a l’avaluació del càncer de pulmó basats en imatges de CT pulmonar individuals. Atès que aquests tipus d’etiquetes són costoses i difícils d’obtenir (per exemple, després d’una biòpsia), vam dissenyar diferents xarxes neuronals profundes, basades en xarxes de convolució 3D (CNN), per predir la malignitat dels nòduls basada en la inspecció visual dels radiòlegs (més senzilles de recol.lectar). A continuació, vàrem avaluar diferents maneres de sintetitzar aquest coneixement representat en la xarxa neuronal de malignitat, en una pipeline destinada a proporcionar predicció del càncer de pulmó a nivell de pacient, donada una imatge de TC pulmonar. Els resultats positius van confirmar la conveniència d’utilitzar CNN per modelar la malignitat dels nòduls, segons els radiòlegs, per a la predicció automàtica del càncer de pulmó. Seguidament, vam dirigir la nostra investigació cap a l’anàlisi de sèries d’imatges de TC pulmonar. Per tant, ens vam enfrontar primer a la reidentificació automàtica de nòduls pulmonars de diferents tomografies pulmonars. Per fer-ho, vam proposar utilitzar xarxes neuronals siameses (SNN) per classificar la similitud entre nòduls, superant la necessitat de registre d’imatges. Aquest canvi de paradigma va evitar possibles pertorbacions de la imatge i va proporcionar resultats computacionalment més ràpids. Es van examinar diferents configuracions del SNN convencional, que van des de l’aplicació de l’aprenentatge de transferència, utilitzant diferents funcions de pèrdua, fins a la combinació de diversos mapes de característiques de diferents nivells de xarxa. Aquest mètode va obtenir resultats d’estat de la tècnica per reidentificar nòduls de manera aïllada, i de forma integrada en una pipeline per a la quantificació de creixement de nòduls. A més, vam abordar el problema de donar suport als radiòlegs en la gestió longitudinal del càncer de pulmó. Amb aquesta finalitat, vam proposar una nova pipeline d’aprenentatge profund, composta de quatre etapes que s’automatitzen completament i que van des de la detecció de nòduls fins a la classificació del càncer, passant per la detecció del creixement dels nòduls. A més, la pipeline va integrar un nou enfocament per a la detecció del creixement dels nòduls, que es basava en una recent xarxa de segmentació probabilística jeràrquica adaptada per informar estimacions d’incertesa. A més, es va introduir un segon mètode per a la classificació dels nòduls del càncer de pulmó, que integrava en una xarxa 3D-CNN de dos fluxos les probabilitats estimades de malignitat dels nòduls derivades de la xarxa pre-entrenada de malignitat dels nòduls. La pipeline es va avaluar en una cohort longitudinal i va informar rendiments comparables a l’estat de la tècnica utilitzats individualment o en pipelines però amb menys components que la proposada. Finalment, també vam investigar com ajudar els metges a prescriure de forma més acurada tractaments tumorals i planificacions quirúrgiques més precises. Amb aquesta finalitat, hem realitzat un nou mètode per predir el creixement dels nòduls donada una única imatge del nòdul. Particularment, el mètode es basa en una xarxa neuronal profunda jeràrquica, probabilística i generativa capaç de produir múltiples segmentacions de nòduls futurs consistents del nòdul en un moment determinat. Per fer-ho, la xarxa aprèn a modelar la distribució posterior multimodal de futures segmentacions de tumors pulmonars mitjançant la utilització d’inferència variacional i la injecció de les característiques latents posteriors. Finalment, aplicant el mostreig de Monte-Carlo a les sortides de la xarxa, podem estimar la mitjana de creixement del tumor i la incertesa associada a la predicció. Tot i que es recomanable una avaluació posterior en una cohort més gran, els mètodes proposats en aquest treball han informat resultats prou precisos per donar suport adequadament al flux de treball radiològic del seguiment dels nòduls pulmonars. Més enllà d’aquesta aplicació especifica, les innovacions presentades com, per exemple, els mètodes per integrar les xarxes CNN a pipelines de visió per ordinador, la reidentificació de regions sospitoses al llarg del temps basades en SNN, sense la necessitat de deformar l’estructura de la imatge inherent o la xarxa probabilística per modelar el creixement del tumor tenint en compte imatges ambigües i la incertesa en les prediccions, podrien ser fàcilment aplicables a altres tipus de càncer (per exemple, pàncrees), malalties clíniques (per exemple, Covid-19) o aplicacions mèdiques (per exemple, seguiment de la teràpia).

Quantitative pathology as a tool in gynaecological pathology is fairly new. Such techniques allow greater objectivity than histological grading, typing, and residual tumour estimation. This study aims to determine: whether basic morphometry data can predict outcome and chemotherapeutic response, whether newer semi-automated methods of tumour morphometry provide similar results to older methods, and whether advanced image analysis methods can offer further tumour outcome data in ovarian carcinoma. The study was performed on a well-selected group of serous ovarian carcinomas. Tumour outcome, survival and chemotherapeutic response, were investigated in 132 patients treated with the same platinum containing regimes. Traditional clinicopathologic parameters, p53 & Bcl2, mitotic activity index MAn and angiogenesis determinants were initially investigated. Semi-automated analysis, using immunohistochemically based techniques, were applied to estimate volume percentage epithelium (VPE) and nuclear morphometric parameters. Syntactic structure analysis including, minimum spanning tree, and neighbourhood features, was also investigated. Multivariate analysis revealed residual disease status, FIGO stage, MAl, VPE, equivalent nuclear diameter, and angiogenesis parameters to be strong prognosticators for overall and disease free survival. Residual disease status, VPE, nuclear length and angiogenesis parameters were found significant predictors of chemotherapy response. Angiogenesis parameters, as determined by semi-automated image analysis techniques, were found overall to be the strongest prognosticators. Morphometric data can predict outcome and chemotherapeutic response in ovarian serous carcinoma. Semi-automated morphometry techniques provide similar results to older methods, and advanced image analysis can offer further outcome data. The rationale for the application of semi-automated and automated detection is that it may provide an unbiased sampling of a lesion and possibly a more representative estimate of areas that a human expert might label. Such determined, quantitative pathological findings were found to have important value in predicting prognosis in ovarian carcinoma and, if not to supersede, certainly to add to classical prognostic factors.

Le principal effet cytotoxique du 5-fluorouracile (5fu) s'exerce par inhibition de la thymidylate synthetase (ts). La formation d'un complexe ternaire intracellulaire entre la ts, un anabolite du 5fu le fluorodeoxyuridine monophosphate (fdump) et un folate reduit, le 5,10-methylenetetrahydrofolate (ch2fh4), bloque la synthese de thymidine et donc la formation d'adn. L'acide folinique (af) potentialise l'effet du 5fu en augmentant le pool intracellulaire de ch2fh4. Une concentration optimale de ch2fh4 sous forme polyglutamatee via la folylpolyglutamate synthetase (fpgs) est necessaire pour une inhibition maximale de la ts. Le 5fu est catabolise par la dihydropyrimidine deshydrogenase (dpd), qui diminue la concentration intratumorale de fdump. Les objectifs de cette etude etaient de tester sur des lignees cellulaires tumorales et des biopsies tumorales de patients, la valeur predictive des activites ts, dpd, fpgs et du ch2fh4 vis a vis de la sensibilite au 5fu et a l'af. Dans les lignees cellulaires, la fpgs est le seul facteur predictif de la sensibilite au 5fu seul ou en presence d'af. L'effet potentialisateur de l'af sur le 5fu est d'autant plus important que le taux de ch2fh4 de base et l'activite fpgs basale sont eleves. Le ch2fh4 intratumoral n'est pas le facteur limitant de l'effet potentialisateur. Dans les tumeurs orl, les patients repondeurs au 5fu ont un taux de ch2fh4 plus eleve et une activite dpd normalisee (dpdtumorale/dpdtissu sain) plus faible que les patients resistants. Au dessus de 1,6 pmole/mg de proteine de ch2fh4, tous les patients sont repondeurs au traitement. Au dessous de 1,6 pmole/min/mg de proteine 52% des patients sont resistants au traitement. Dans le cas des metastases hepatiques de cancers colorectaux, les patients resistants au 5fu ont une activite fpgs plus faible que les repondeurs. 96% des metastases hepatiques dont l'activite fpgs < 1,1 pmole/min/mg de proteine ou dont l'activite ts > 0,32 pmole/min/mg de proteine, sont resistantes a une chimiotherapie a base de 5fu - af

L’objectif de ce travail de thèse était de proposer une approche systématique et raisonnée des outils de quantification disponibles en routine clinique et du domaine de la recherche dans la prise en charge des patients atteints d’une tumeur endocrine. Nos résultats font état des limites des paramètres semi-quantitatifs pour faire le diagnostic de malignité d’un ITf fixant au 18FDG-TEP/TDM. Nos données sur l’intérêt des paramètres de textures dans le diagnostic de malignité des tumeurs surrénaliennes nous montrent des performances excellentes de ces indices mais qui n’apparaissent cependant pas supérieures en comparaison des paramètres semi-quantitatifs conventionnels. Notre approche soulève de nouvelles hypothèses quant à l’intérêt de l’analyse de texture dans la caractérisation de certaines tumeurs surrénaliennes rares (phéochromocytomes et corticosurrenalomes) qui devront faire l’objet de futurs travaux. Enfin, notre travail sur l’approche multi-paramétrique en imagerie 68Ga-DOTATOC-TEP/TDM met en évidence la faisabilité d’une acquisition dynamique corps entier en 68Ga-DOTATOC-TEP/TDM et les possibilités de quantification de la fixation tumorale des TNE traitées par RIV sur les acquisitions TEMP/TDM post-thérapeutiques. Nos résultats ouvrent des perspectives multiples quant à la prise en charge des TNE à différents étapes de la maladie (diagnostique, pronostique et évaluation thérapeutique)
The objective of this work was to propose a systematic and reasoned approach of the quantification tools available in clinical routine and in research in the management of patients with endocrine tumors. Our results report the limitations of semi-quantitative parameters to assess the malignancy of fTI detected by 18FDG-PET / CT. Our data on the interest of textural parameters in the diagnosis of malignancy of adrenal tumors show excellent performances of these indices. However these indices do not appear superior in comparison with conventional semi-quantitative parameters.Our approach raises new hypotheses regarding the interest of texture analysis in the characterization of some rare adrenal tumors (pheochromocytomas and adrenocortical carcinoma) that will be the subject of future work. Finally, our work on the multi-parametric 68Ga-DOTATOC-PET / CT imaging highlights the feasibility of a whole-body dynamic 68Ga-DOTATOC-PET / CT acquisition and the possibilities to perform quantification of NETs uptake treated with PRRT on post-therapeutic SPECT / CT acquisitions. Our results open up multiple perspectives for the management of NETs at different stages of the disease (diagnosis, prognosis and therapeutic evaluation)

M.Tech.
To determine whether a combination of real-time B-Mode ultrasound, Doppler Color flow and Power Doppler flow mapping would be reliable in differentiating benign from malignant breast nodules in an attempt to avoid unnecessary biopsies, where after ultrasound guidelines would be formulated. A quantitative cross-sectional comparative descriptive design in a study population which consisted of 62 women over the age of 35 years who came to Klerksdorp Radiology services for mammography. Both breast ultrasound imaging and mammography was used as a routine procedure as part of the workup for the classification of breast nodules, before histologic specimens were obtained. All nodules were classified according to the ultrasonographic BI-RADS lexicon and compared with the pathologic results. Of the 63 patients, 63 breast nodules were detected and confirmed by biopsy. Thirty seven (59%) nodules were found to be malignant and 26 (41%) were benign according to biopsy results. Mammography had 87% sensitivity and ultrasound 60% sensitivity in detecting malignancy. It is recommended that B-mode, Color Doppler flow and Power Doppler flow mapping be used in combination with mammography for screening as a gold standard.

Objective: To develop a predictive model for preoperative differentiation between benign (B) and malignant (M) histology in patients with renal masses (RM) using recursive partitioning. Methods: We analyzed preoperative patient and tumour characteristics in 395 subjects who had surgery for RM suspicious for renal cell carcinoma. Results: The model predicted B vs. M histology with an overall accuracy of 89.6% (95% CI 86.2,92.5). It assigned patients with smaller tumours (<5.67cc) and a predominantly (>45%) exophytic component a high risk of B disease (52.6%). Patients with symptoms, larger tumours (>5.67cc) and larger endophytic component (>35%) have a 0% risk of B disease. Conclusion: B vs. M disease can be predicted accurately. This predictive accuracy is higher than that shown in renal biopsy series. It is hypothesized that for smaller and exophytic RMs, a biopsy is indicated. Symptomatic, larger and endophytic RMs should be removed without further investigations.

碩士
中原大學
化學工程研究所
103
Prostate cancer in 10% of prostate cancer patients are aggressive and metastatic, killing the patients within one year of the initial diagnosis. The current dominant diagnosis for the cancer is to test an elevated serum PSA level. However the diagnosis test has at least 20-25% false results; the elevated level of PSA in the serum is not always predictive of the pathologic stage of the prostate cancer or the presence of a metastatic disease. Many potential diagnostic markers for prostate cancer progression have been validated; however, most of them cannot accurately distinguish between indolent and aggressive cancers. As such, there is still an urgent need to search for a better marker for the early detection of the metastatic potential of prostate carcinomas. Previous research suggested that METCAM/MUC18 may be used as a novel diagnostic biomarker for early detection of the metastatic potential of human prostate cancer and for distinguishing the aggressive cancers from indolent ones. The purpose of my research is to test the possibility of using METCAM/MUC18 as a diagnostic biomarker for developing a reliable, cost-effective test for predicting the malignant progression of prostate cancer. We have used immunological methods, both ELISA (enzyme-linked immunosorbent assay) and Western blot (WB) analysis, to establish a standard curve by using recombinant METCAM/MUC18 proteins and then used the tests to determine METCAM/MUC18 concentrations in human serum samples. To initiate the research, we used Western blot (WB) analysis to identify an antibody to have the highest sensitivity and specificity to recognize the METCAM/MUC18 antigen and using the antibody to develop a 96-well-ELISA for quantitative analysis of the METCAM/MUC18 antigen. Four antibodies were used for the tests: our home- made chicken antibody anti-middle portion (aa#220-375), MyBioscource MBS275688 rabbit antibody against METCAM/MUC18 aa#14-234, Santa Cruz SC-28667 rabbit antibody against the C-terminus aa#586-646 of METCAM/MUC18, and Santa Cruz SC-18940 goat antibody against METCAM/MUC18 unknown internal epitopes. We found that the home-made chicken antibody anti-middle portion (aa#212-375) was the best and MyBioscource MBS275688 rabbit antibody against METCAM/MUC18 aa#14-234 the second best for ELISA. Second, we determined the best concentrations of the primary antibodies and secondary antibodies for obtaining optimal ELISA signals. Third, we established a protein standard curve for ELISA by using five recombinant proteins (antigen #1: M, antigen#2:M-GST, antigen#4: N-M-GST, antigen#5:C-terminal portion, and GST control). Finally, we used the two best primary antibodies for ELISA to determine and quantify the serum METCAMMCUC18 concentrations in 18 human serum samples obtained from normal individuals, BPH patients, and patients at different stages of prostate cancer in comparison with the protein standard curve. We found that it was possible to detect the presence of METCAM/MUC18 antigens in the clinical serum specimens by Western blot analysis and ELISA. We also found that the serum METCAM/MUC18 concentrations were linearly proportional to most of the PSA concentrations when serum PSA concentrations were at <7 ng/ml and < 25 ng.ml. However, the serum METCAM/MUC18 concentrations remained statistically similar versus most PSA concentrations when serum PSA concentrations were at between >25 and <1500 ng/ml. We also compared the results of ELISA with those of WB analysis and found that the results were similar to ELISA results except the serum METCAM/MUC18 concentrations determined by WB were higher than those by ELISA, which we did not know the exact reason. One likely reason was that the resolution of Image J, which we used for quantitative analysis, was not high enough for a more precise quantitation. We also found that serum METCAM/MUC18 concentrations appeared to be higher in prostate cancer patients than normal individuals and BPH patients. Since the survey cohort was not large enough to obtain statistically significant results, we still could not differentiate malignant prostate cancers from indolent ones and also to monitor treatment outcome of the patients. In conclusion, the preliminary results by using immunological test to determine serum METCAM/MUC18 concentrations were promising, so that in the near future we should expand our survey cohort in Taiwanese males and to simplify and increase sensitivity of our tests by exploring the use of 2D-MBLF and 3D-aerogel bio-chip. Furthermore, it may also be possible to detect the presence of METCAM/MUC18 in urine samples, because the presence of METCAM/MUC18 antigen in serum was detectable.

Introducción: Los países de América Latina y el Caribe están luchando por responder al aumento de la morbilidad y mortalidad por las enfermedades no transmisibles crónicas. Los Ministerios de Salud, en países en vías de desarrollo como Argentina, enfrentan grandes desafíos en el cuidado de pacientes con cáncer avanzado; debido a falta de financiamiento, inequidad de recursos y servicios en la población, carencia de una atención de salud adecuada, condicionada por factores socio-económicos, geográficos, étnicos, entre otros. Por esto resulta importante avanzar en investigaciones que conduzcan a generar conocimientos en pos de la prevención y diagnóstico temprano del cáncer. El cáncer oral (CO) se caracteriza por que su prevalencia e iincidencia cambia de acuerdo al área geográfica. Objetivo: Evaluar y desarrollar modelos de predicción de riesgo para cáncer bucal de células escamosas (CBCE) a partir de variables genotípicas (polimorfismos de genes individuales o de grupos de genes ya identificados o nuevos) ajustadas por variables medio ambiente (exposición laboral de riesgo) y hábitos de riesgos (tabaco, alcohol) en pacientes adultos. Métodos: Se realizó un estudio transversal en 140 de CBCE, desordenes orales potencialmente malignos (DPM) y controles. La genotipificación de polimorfismo de nucleótido sencillo (SNP) se realizó mediante técnicas de PCR o RFLP específicas de alelo. Las variables fueron evaluadas por métodos estadísticos bivariados y multivariados, estableciendo p <0.05 para significancia estadística. Resultados: Los análisis de correspondencia múltiple mostraron que los pacientes con CBCE están agrupados con el alelo T de XRCC3 T241M y el alelo C de TP53 R72P, mientras que los pacientes con PDM están agrupados con el alelo T de NFKβ-519. El punto de corte para CBCE y DPM fue de 4.5, por lo cual puntajes mayores a los puntos de corte establecidos tendrían más riego de presentar CBCE/DPM Conclusiones: nuestros resultados mostraron que el alelo C de la variante Pro72 de TP53 está relacionado con CBCE y DPM, mientras que el alelo T de NFKβ-519 está relacionado con DPM en pacientes argentinos. Estos resultados coinciden con los estudios realizados en poblaciones caucásicas; se sabe que existe una relación de SNP con distribución geográfica. Estos estudios tienen beneficios potenciales al permitir la identificación de biomarcadores predictivos y grupos con mayor riesgo de cáncer oral y la implementación de una variedad de estrategias de atención médica. Sin embargo, los resultados de este estudio deben confirmarse en investigaciones adicionales que incluyan un mayor número de pacientes y en diferentes regiones de Argentina.
Introduction: The countries of Latin America and the Caribbean are struggling to respond to the increase in morbidity and mortality from chronic non-communicable diseases. The Ministries of Health, in developing countries like Argentina, face great challenges in the care of patients with advanced cancer; due to lack of financing, inequity of resources and services in the population, lack of adequate health care, conditioned by socio-economic, geographical, ethnic factors, among others. For this reason, it is important to advance in research that leads to the generation of knowledge for the prevention and early diagnosis of cancer. Its prevalence and incidence changing according to the geographical area characterize oral cancer. Objective: To evaluate and develop risk prediction models for oral cancer based on genotypic variables (polymorphisms of individual gene or of groups of genes already identified or new) adjusted by environmental variables (occupational risk exposure) and risk habits (tobacco, alcohol) in adult patients. Methods: A cross-sectional study was conducted in 140 patients with oral squamous cell carcinoma, potentially malignant oral disorders, and controls. SNP genotyping was performed by allele-specific PCR or RFLP techniques. The variables were evaluated by bivariate and multivariate statistical methods, establishing p <0.05 for statistical significance. Results: Multiple correspondence analyzes showed that patients with CBCE are clustered with the T allele of XRCC3 T241M and the C allele of TP53 R72P, while patients with OPDM are clustered with the T allele of NFKβ-519. The cut-off point for CO and DPM was 4.5 therefore; scores higher than the established cut-off points would have more risk of presenting CO / DPM. Conclusions: our results showed that the C allele of the Pro72 variant of TP53 is related to OSSC and DPM, while the T allele of NFKβ-519 is related to DPM in Argentine patients. These results coincide with the studies carried out in European populations. It is known that there is a relationship of SNPs with geographic distribution. These studies have potential benefits by allowing the identification of predictive biomarkers and groups at increased risk for oral cancer and the implementation of a variety of health care strategies. However, the results of this study should be confirmed by additional investigations that include a greater number of patients and in different regions of Argentina.
2023-06-28
Fil: Galindez-Costa, María Fernanda. Universidad Nacional de Córdoba. Facultad de Odontología; Argentina.

Thyroid cancer is the most prevalent endocrine cancer (1). The prevalence of palpable thyroid nodules in the general adult population is 4% to 7% (2). Ultrasound imaging detects thyroid nodules in 19%-68% of randomly selected individuals (3). The rate of thyroid cancer in nodules found on US is 4% to 15% (4). In order to evaluate thyroid nodules patients undergo thyroid ultrasonography and, if needed, a fine-needle aspiration biopsy. Of all fine-needle aspiration biopsies, 15-30% are indeterminate on cytology (5). While only 3% of these nodules are malignant on average, a much higher percentage of nodules are surgically removed in order to rule out malignancy after indeterminate FNA results. Our goal is to identify clinical and ultrasound predictors of benign results in indeterminate nodules, to assist physicians in selecting nodules for surgical removal versus monitoring with ultrasound imaging. Between October 2010 and November 2017 there were 129 patients with 134 thyroid nodules from Temple University Hospital, Jeanes Hospital, and Fox Chase Cancer Center who had a total or partial thyroidectomy after a cytology report of at least one AUS or FLUS thyroid nodule. These patients were evaluated for age, sex, BMI, TSH, fT4, tT3, nodule size, and ultrasonography features to determine if any features were predictive of a benign or malignant thyroid nodule. Additionally, we looked at whether any of these features were more likely to occur in an AUS nodule or a FLUS nodule. We found that none of the demographic factors, thyroid function tests, or ultrasound features were good predictors of malignancy in AUS or FLUS thyroid nodules. We found that AUS nodules are more likely to be malignant than FLUS nodules, and this held true when we accounted for age, sex, smoking history, and BMI. We concluded that demographic factors and thyroid function tests are unable to predict increased risk of malignancy in Bethesda category III nodules, AUS nodules are more likely to be malignant that FLUS nodules, and nodules with at least one suspicious ultrasound feature are more likely to be AUS nodules than FLUS nodules due to AUS nodules having nuclear atypia and FLUS nodules having architectural atypia.

碩士
國立臺灣大學
獸醫學研究所
94
Mammary gland tumors (MGTs) are frequently encounted neoplasm in cats, and its ratio of malignancy is higher, so easy metastases cause poor prognosis. Many prognostic factors and biomarkers are studied and reported to assist the pathology diagnosis and prognosis. Podocalyxin was isolated in 1980’s from glomerular epithelium (podocyte) in rats, and is considered a function “anti-adhesion”. The function of anti-adhesion makes cells separate with each other and basement membrane. The objective of this study is to study the expression and malignancy prediction of Podocalyxin in feline mammary gland tumors. Thirty-two feline MGTs cases were retrospectively collected for basic information analysis and immunohistochemistry (IHC) of Podocalyxin and PCNA. The mean age of MGT affected cats was 9.7 year-old, and the first and second predisposing breed were Domestic Short Hair (DSH) (53.1%, 17/32) and Persian (21.8%, 7/32). The ratio of benign tumors and malignant tumors was 1:3. The result of IHC for Podocalyxin showed significant difference between malignant/metastastic neoplastic cells to normal/ hyperplastic cells (p < 0.05). The expression of Podocalyxin also had significant difference between hyperplastic/benign and normal cells. The expression for PCNA showed no significant difference between benignancy and malignancy. Based on the result, it is hypothesized that the expression of Podocalyxin is correlated to the malignance and metastasis, and Podocalyxin has a potential to be a prognostic biomarker in feline mammary gland tumors.

碩士
國立臺灣大學
護理學研究所
100
This study aims to explore the relationship among quality of life, uncertainty and levels of hope in patients with Hematological malignancy undergoing hematopoietic stem cell transplantation. A descriptive and cross-sectional correlation design with purposive sampling from two bone marrow transplantation center in northern Taiwan medical hospital. The data were collected by mail and interviewing out-patients with hematological malignancy undergoing hematopoietic stem cell transplantation after discharge as the research object. The valid samples are 201 objects from March 2011 to June 2011.The structure questionnaires were including:(1)demographic questionnaire, (2)the Chinese version of MUIS-Adult Form,(3)the Chinese version of Herth Hope Index,(4)the traditional Chinese version of FACT-BMT,(5) the McGill Quality of Life Scale-Taiwan version).The data were analyzed by SPSS 17.0 Window and descriptive statistics, t test, ANOVA, pearson correlation and multiple regression analysis. The major finding of this study were as below: 1.The patients’ mean age was 46.4 years, the majority of patients diagnosed with leukemia (66.3%), the mean time since transplantation was 5.6±4.7 years, the personal health status was very good and great (46.2%). 2.Levels of uncertainty(55.32 ± 14.92 points) were medium, levels of hope (36.32 ± 5.37 points) were high. An average of FACT-BMT QOL total score (100.03 ± 22.09) and overall MQOL (7.57 ± 2.42) were high. Long-term quality of life in patients with Hematological malignancy undergoing hematopoietic stem cell transplantation was in the middle and upper level. 3.With stepwise regression analysis to identify the important predictors of FACT-BMT QOL were " levels of uncertainty, levels of hope, good personal health status, marital and post-transplant survival of 5-10 years",explained the total amount of (R2) to 59.5%, the important predictors of MQOL were " levels of uncertainty, levels of hope, poor personal health status, complications, annual household income, explained the total amount of (R2) to 49.5%., and were statistically significant. The conclusion: the results of this study indicated levels of uncertainty, levels of hope, personal health status were the most important factors of quality of life in patients undergoing trasplantation, FACT-BMT and MQOL questionnaires are a reliable and valid assessment for measuring the QOL of patients undergoing hematopoietic stem cell transplantation. It would strengthen the clinical nursing staffs'' role function., We hope that nursing staff will provide a continous and comprehensive nursing care to reduce uncertainty of patients and enhance levels of hope and quality of life for patients.

The motivation of this research is to propose innovative nonlinear and optimal control design algorithms, which can be used in real life. The algorithms need to be computationally efficient, should deal with control constraints and should operate under state feedback. To show the efficacy of algorithms, automatic therapy for different cancer problems is chosen to be the field of application. In this thesis, first an advanced control design technique called ’optimal dynamic in-version’ has been successfully experimented with control constraints. The proposed approach has subsequently been shown to be quite effective in proposing automatic drug delivery schemes with simultaneous application of chemo and immunotherapy drugs for complete elimination of cancer cells in melanoma (a skin cancer) as well as glioma (a brain cancer). As per the current practice, the amount of drug dosages are generally given based on some apriori statistical study with a very small sample size, which in reality may either also lead to drug toxicity (due to excessive drug) or may become ineffective (due to insufficient drug) for a particular patient. Subject to the fidelity of the mathematical model (which has been taken from published literature), it has been shown in this thesis that nonlinear control theory can be used for computation of drug dosages, which can then be used in a feedback strategy, thereby customizing the drug for the patient’s condition, to cure the disease successfully. Next, attention has been shifted to impulsive control of systems. Such impulsive con-trol systems appear in many other applications such as control of swings, control of spacecrafts and rockets using reaction control system, radiotherapy in cancer treatment and so on. Two impulsive control design philosophies are proposed in this thesis. In one approach, recently proposed model predictive static programming (MPSP) has been extended for impulsive control systems and has been named as impulsive-MPSP (I-MPSP). In other approach, another recent development, namely the Pseudospectral method has been utilized to consider both the magnitude of the control impulses as well as the time instants at which they are applied as the decision variables. It can be noted, that to the best of the knowledge of the author, the time instants of control application, being considered as decision variables is being proposed for the first time in the nonlinear and optimal control framework. Both I-MPSP and Pseudospectral methods are computationally quite efficient and hence can be used for feedback control (I-MPSP happens to be computationally more efficient than the Pseudospectral method). Applicability of the proposed extensions have been shown by solving various benchmark problems such as (i) a scalar linear problem, (ii) Van der Pol’s oscillator problem and (iii) an inverted pendulum problem. Finally the applicability of the proposed I-MPSP strategy has been shown by solving challenging problems such as radiotherapy treatment of head and neck and adenocarcimona cancers. Radio-therapy model is considered with oxygen effect, in which radiosensitivity parameters are considered in different forms. Head and neck cancer is considered with constant radiosensitivity parameters and adenocarcinoma is considered with constant, linear, quadratic and saturation model of radiosensitivity parameters. Note that toxicity constraints on normal tissue, which are nonlinear control constraints, are also successfully incorporated in this control design.

The motivation of this research is to propose innovative nonlinear and optimal control design algorithms, which can be used in real life. The algorithms need to be computationally efficient, should deal with control constraints and should operate under state feedback. To show the efficacy of algorithms, automatic therapy for different cancer problems is chosen to be the field of application. In this thesis, first an advanced control design technique called ’optimal dynamic in-version’ has been successfully experimented with control constraints. The proposed approach has subsequently been shown to be quite effective in proposing automatic drug delivery schemes with simultaneous application of chemo and immunotherapy drugs for complete elimination of cancer cells in melanoma (a skin cancer) as well as glioma (a brain cancer). As per the current practice, the amount of drug dosages are generally given based on some apriori statistical study with a very small sample size, which in reality may either also lead to drug toxicity (due to excessive drug) or may become ineffective (due to insufficient drug) for a particular patient. Subject to the fidelity of the mathematical model (which has been taken from published literature), it has been shown in this thesis that nonlinear control theory can be used for computation of drug dosages, which can then be used in a feedback strategy, thereby customizing the drug for the patient’s condition, to cure the disease successfully. Next, attention has been shifted to impulsive control of systems. Such impulsive con-trol systems appear in many other applications such as control of swings, control of spacecrafts and rockets using reaction control system, radiotherapy in cancer treatment and so on. Two impulsive control design philosophies are proposed in this thesis. In one approach, recently proposed model predictive static programming (MPSP) has been extended for impulsive control systems and has been named as impulsive-MPSP (I-MPSP). In other approach, another recent development, namely the Pseudospectral method has been utilized to consider both the magnitude of the control impulses as well as the time instants at which they are applied as the decision variables. It can be noted, that to the best of the knowledge of the author, the time instants of control application, being considered as decision variables is being proposed for the first time in the nonlinear and optimal control framework. Both I-MPSP and Pseudospectral methods are computationally quite efficient and hence can be used for feedback control (I-MPSP happens to be computationally more efficient than the Pseudospectral method). Applicability of the proposed extensions have been shown by solving various benchmark problems such as (i) a scalar linear problem, (ii) Van der Pol’s oscillator problem and (iii) an inverted pendulum problem. Finally the applicability of the proposed I-MPSP strategy has been shown by solving challenging problems such as radiotherapy treatment of head and neck and adenocarcimona cancers. Radio-therapy model is considered with oxygen effect, in which radiosensitivity parameters are considered in different forms. Head and neck cancer is considered with constant radiosensitivity parameters and adenocarcinoma is considered with constant, linear, quadratic and saturation model of radiosensitivity parameters. Note that toxicity constraints on normal tissue, which are nonlinear control constraints, are also successfully incorporated in this control design.