Cell mixing induced by myc is required for competitive tissue invasion and destruction

Cell-cell intercalation is used in several developmental processes to shape the normal body plan. There is no clear evidence that intercalation is involved in pathologies. Here we use the proto-oncogene myc to study a process analogous to early phase of tumour expansion: myc-induced cell competition. Cell competition is a conserved mechanism driving the elimination of slow-proliferating cells (so-called 'losers') by faster-proliferating neighbours (so-called 'winners') through apoptosis and is important in preventing developmental malformations and maintain tissue fitness. Here we show, using long-term live imaging of myc-driven competition in the Drosophila pupal notum and in the wing imaginal disc, that the probability of elimination of loser cells correlates with the surface of contact shared with winners. As such, modifying loser-winner interface morphology can modulate the strength of competition. We further show that elimination of loser clones requires winner-loser cell mixing through cell-cell intercalation. Cell mixing is driven by differential growth and the high tension at winner-winner interfaces relative to winner-loser and loser-loser interfaces, which leads to a preferential stabilization of winner-loser contacts and reduction of clone compactness over time. Differences in tension are generated by a relative difference in F-actin levels between loser and winner junctions, induced by differential levels of the membrane lipid phosphatidylinositol (3,4,5)-trisphosphate. Our results establish the first link between cell-cell intercalation induced by a proto-oncogene and how it promotes invasiveness and destruction of healthy tissues.

Proton therapy versus intensity modulated x-ray therapy in the treatment of prostate cancer: Estimating secondary cancer risks

External beam radiation therapy is used to treat nearly half of the more than 200,000 new cases of prostate cancer diagnosed in the United States each year. During a radiation therapy treatment, healthy tissues in the path of the therapeutic beam are exposed to high doses. In addition, the whole body is exposed to a low-dose bath of unwanted scatter radiation from the pelvis and leakage radiation from the treatment unit. As a result, survivors of radiation therapy for prostate cancer face an elevated risk of developing a radiogenic second cancer. Recently, proton therapy has been shown to reduce the dose delivered by the therapeutic beam to normal tissues during treatment compared to intensity modulated x-ray therapy (IMXT, the current standard of care). However, the magnitude of stray radiation doses from proton therapy, and their impact on this incidence of radiogenic second cancers, was not known. ^ The risk of a radiogenic second cancer following proton therapy for prostate cancer relative to IMXT was determined for 3 patients of large, median, and small anatomical stature. Doses delivered to healthy tissues from the therapeutic beam were obtained from treatment planning system calculations. Stray doses from IMXT were taken from the literature, while stray doses from proton therapy were simulated using a Monte Carlo model of a passive scattering treatment unit and an anthropomorphic phantom. Baseline risk models were taken from the Biological Effects of Ionizing Radiation VII report. A sensitivity analysis was conducted to characterize the uncertainty of risk calculations to uncertainties in the risk model, the relative biological effectiveness (RBE) of neutrons for carcinogenesis, and inter-patient anatomical variations. ^ The risk projections revealed that proton therapy carries a lower risk for radiogenic second cancer incidence following prostate irradiation compared to IMXT. The sensitivity analysis revealed that the results of the risk analysis depended only weakly on uncertainties in the risk model and inter-patient variations. Second cancer risks were sensitive to changes in the RBE of neutrons. However, the findings of the study were qualitatively consistent for all patient sizes and risk models considered, and for all neutron RBE values less than 100. ^

Characterization of the dose distribution in the halo region of a clinical proton pencil beam using emulsion film detectors

Proton therapy is a high precision technique in cancer radiation therapy which allows irradiating the tumor with minimal damage to the surrounding healthy tissues. Pencil beam scanning is the most advanced dose distribution technique and it is based on a variable energy beam of a few millimeters FWHM which is moved to cover the target volume. Due to spurious effects of the accelerator, of dose distribution system and to the unavoidable scattering inside the patient's body, the pencil beam is surrounded by a halo that produces a peripheral dose. To assess this issue, nuclear emulsion films interleaved with tissue equivalent material were used for the first time to characterize the beam in the halo region and to experimentally evaluate the corresponding dose. The high-precision tracking performance of the emulsion films allowed studying the angular distribution of the protons in the halo. Measurements with this technique were performed on the clinical beam of the Gantry1 at the Paul Scherrer Institute. Proton tracks were identified in the emulsion films and the track density was studied at several depths. The corresponding dose was assessed by Monte Carlo simulations and the dose profile was obtained as a function of the distance from the center of the beam spot.

Research lines in Hyperthermia at the Bioinstrumentation Laboratory of the Centre for Biomedical Technology

The Bioinstrumentation Laboratory belongs to the Centre for Biomedical Technology (CTB) of the Technical University of Madrid and its main objective is to provide the scientific community with devices and techniques for the characterization of micro and nanostructures and consequently finding their best biomedical applications. Hyperthermia (greek word for “overheating”) is defined as the phenomenon that occurs when a body is exposed to an energy generating source that can produce a rise in temperature (42-45ºC) for a given time [1]. Specifically, the aim of the hyperthermia methods used in The Bioinstrumentation Laboratory is the development of thermal therapies, some of these using different kinds of nanoparticles, to kill cancer cells and reduce the damage on healthy tissues. The optical hyperthermia is based on noble metal nanoparticles and laser irradiation. This kind of nanoparticles has an immense potential associated to the development of therapies for cancer on account of their Surface Plasmon Resonance (SPR) enhanced light scattering and absorption. In a short period of time, the absorbed light is converted into localized heat, so we can take advantage of these characteristics to heat up tumor cells in order to obtain the cellular death [2]. In this case, the laboratory has an optical hyperthermia device based on a continuous wave laser used to kill glioblastoma cell lines (1321N1) in the presence of gold nanorods (Figure 1a). The wavelength of the laser light is 808 nm because the penetration of the light in the tissue is deeper in the Near Infrared Region. The first optical hyperthermia results show that the laser irradiation produces cellular death in the experimental samples of glioblastoma cell lines using gold nanorods but is not able to decrease the cellular viability of cancer cells in samples without the suitable nanorods (Figure 1b) [3]. The generation of magnetic hyperthermia is performed through changes of the magnetic induction in magnetic nanoparticles (MNPs) that are embedded in viscous medium. The Figure 2 shows a schematic design of the AC induction hyperthermia device in magnetic fluids. The equipment has been manufactured at The Bioinstrumentation Laboratory. The first block implies two steps: the signal selection with frequency manipulation option from 9 KHz to 2MHz, and a linear output up to 1500W. The second block is where magnetic field is generated ( 5mm, 10 turns). Finally, the third block is a software control where the user can establish initial parameters, and also shows the temperature response of MNPs due to the magnetic field applied [4-8]. The Bioinstrumentation Laboratory in collaboration with the Mexican company MRI-DT have recently implemented a new research line on Nuclear Magnetic Resonance Hyperthermia, which is sustained on the patent US 7,423,429B2 owned by this company. This investigation is based on the use of clinical MRI equipment not only for diagnosis but for therapy [9]. This idea consists of two main facts: Magnetic Resonance Imaging can cause focal heating [10], and the differentiation in resonant frequency between healthy and cancer cells [11]. To produce only heating in cancer cells when the whole body is irradiated, it is necessary to determine the specific resonant frequency of the target, using the information contained in the spectra of the area of interest. Then, special RF pulse sequence is applied to produce fast excitation and relaxation mechanism that generates temperature increase of the tumor, causing cellular death or metabolism malfunction that stops cellular division

Mejoras en el procesamiento de imágenes de TC para el tratamiento con radioterapia adaptativa del cáncer de próstata

El cáncer de próstata es el tipo de cáncer con mayor prevalencia entre los hombres del mundo occidental y, pese a tener una alta tasa de supervivencia relativa, es la segunda mayor causa de muerte por cáncer en este sector de la población. El tratamiento de elección frente al cáncer de próstata es, en la mayoría de los casos, la radioterapia externa. Las técnicas más modernas de radioterapia externa, como la radioterapia modulada en intensidad, permiten incrementar la dosis en el tumor mientras se reduce la dosis en el tejido sano. Sin embargo, la localización del volumen objetivo varía con el día de tratamiento, y se requieren movimientos muy pequeños de los órganos para sacar partes del volumen objetivo fuera de la región terapéutica, o para introducir tejidos sanos críticos dentro. Para evitar esto se han desarrollado técnicas más avanzadas, como la radioterapia guiada por imagen, que se define por un manejo más preciso de los movimientos internos mediante una adaptación de la planificación del tratamiento basada en la información anatómica obtenida de imágenes de tomografía computarizada (TC) previas a la sesión terapéutica. Además, la radioterapia adaptativa añade la información dosimétrica de las fracciones previas a la información anatómica. Uno de los fundamentos de la radioterapia adaptativa es el registro deformable de imágenes, de gran utilidad a la hora de modelar los desplazamientos y deformaciones de los órganos internos. Sin embargo, su utilización conlleva nuevos retos científico-tecnológicos en el procesamiento de imágenes, principalmente asociados a la variabilidad de los órganos, tanto en localización como en apariencia. El objetivo de esta tesis doctoral es mejorar los procesos clínicos de delineación automática de contornos y de cálculo de dosis acumulada para la planificación y monitorización de tratamientos con radioterapia adaptativa, a partir de nuevos métodos de procesamiento de imágenes de TC (1) en presencia de contrastes variables, y (2) cambios de apariencia del recto. Además, se pretende (3) proveer de herramientas para la evaluación de la calidad de los contornos obtenidos en el caso del gross tumor volumen (GTV). Las principales contribuciones de esta tesis doctoral son las siguientes: _ 1. La adaptación, implementación y evaluación de un algoritmo de registro basado en el flujo óptico de la fase de la imagen como herramienta para el cálculo de transformaciones no-rígidas en presencia de cambios de intensidad, y su aplicabilidad a tratamientos de radioterapia adaptativa en cáncer de próstata con uso de agentes de contraste radiológico. Los resultados demuestran que el algoritmo seleccionado presenta mejores resultados cualitativos en presencia de contraste radiológico en la vejiga, y no distorsiona la imagen forzando deformaciones poco realistas. 2. La definición, desarrollo y validación de un nuevo método de enmascaramiento de los contenidos del recto (MER), y la evaluación de su influencia en el procedimiento de radioterapia adaptativa en cáncer de próstata. Las segmentaciones obtenidas mediante el MER para la creación de máscaras homogéneas en las imágenes de sesión permiten mejorar sensiblemente los resultados de los algoritmos de registro en la región rectal. Así, el uso de la metodología propuesta incrementa el índice de volumen solapado entre los contornos manuales y automáticos del recto hasta un valor del 89%, cercano a los resultados obtenidos usando máscaras manuales para el registro de las dos imágenes. De esta manera se pueden corregir tanto el cálculo de los nuevos contornos como el cálculo de la dosis acumulada. 3. La definición de una metodología de evaluación de la calidad de los contornos del GTV, que permite la representación de la distribución espacial del error, adaptándola a volúmenes no-convexos como el formado por la próstata y las vesículas seminales. Dicha metodología de evaluación, basada en un nuevo algoritmo de reconstrucción tridimensional y una nueva métrica de cuantificación, presenta resultados precisos con una gran resolución espacial en un tiempo despreciable frente al tiempo de registro. Esta nueva metodología puede ser una herramienta útil para la comparación de distintos algoritmos de registro deformable orientados a la radioterapia adaptativa en cáncer de próstata. En conclusión, el trabajo realizado en esta tesis doctoral corrobora las hipótesis de investigación postuladas, y pretende servir como cimiento de futuros avances en el procesamiento de imagen médica en los tratamientos de radioterapia adaptativa en cáncer de próstata. Asimismo, se siguen abriendo nuevas líneas de aplicación futura de métodos de procesamiento de imágenes médicas con el fin de mejorar los procesos de radioterapia adaptativa en presencia de cambios de apariencia de los órganos, e incrementar la seguridad del paciente. I.2 Inglés Prostate cancer is the most prevalent cancer amongst men in the Western world and, despite having a relatively high survival rate, is the second leading cause of cancer death in this sector of the population. The treatment of choice against prostate cancer is, in most cases, external beam radiation therapy. The most modern techniques of external radiotherapy, as intensity modulated radiotherapy, allow increasing the dose to the tumor whilst reducing the dose to healthy tissue. However, the location of the target volume varies with the day of treatment, and very small movements of the organs are required to pull out parts of the target volume outside the therapeutic region, or to introduce critical healthy tissues inside. Advanced techniques, such as the image-guided radiotherapy (IGRT), have been developed to avoid this. IGRT is defined by more precise handling of internal movements by adapting treatment planning based on the anatomical information obtained from computed tomography (CT) images prior to the therapy session. Moreover, the adaptive radiotherapy adds dosimetric information of previous fractions to the anatomical information. One of the fundamentals of adaptive radiotherapy is deformable image registration, very useful when modeling the displacements and deformations of the internal organs. However, its use brings new scientific and technological challenges in image processing, mainly associated to the variability of the organs, both in location and appearance. The aim of this thesis is to improve clinical processes of automatic contour delineation and cumulative dose calculation for planning and monitoring of adaptive radiotherapy treatments, based on new methods of CT image processing (1) in the presence of varying contrasts, and (2) rectum appearance changes. It also aims (3) to provide tools for assessing the quality of contours obtained in the case of gross tumor volume (GTV). The main contributions of this PhD thesis are as follows: 1. The adaptation, implementation and evaluation of a registration algorithm based on the optical flow of the image phase as a tool for the calculation of non-rigid transformations in the presence of intensity changes, and its applicability to adaptive radiotherapy treatment in prostate cancer with use of radiological contrast agents. The results demonstrate that the selected algorithm shows better qualitative results in the presence of radiological contrast agents in the urinary bladder, and does not distort the image forcing unrealistic deformations. 2. The definition, development and validation of a new method for masking the contents of the rectum (MER, Spanish acronym), and assessing their impact on the process of adaptive radiotherapy in prostate cancer. The segmentations obtained by the MER for the creation of homogenous masks in the session CT images can improve significantly the results of registration algorithms in the rectal region. Thus, the use of the proposed methodology increases the volume overlap index between manual and automatic contours of the rectum to a value of 89%, close to the results obtained using manual masks for both images. In this way, both the calculation of new contours and the calculation of the accumulated dose can be corrected. 3. The definition of a methodology for assessing the quality of the contours of the GTV, which allows the representation of the spatial distribution of the error, adapting it to non-convex volumes such as that formed by the prostate and seminal vesicles. Said evaluation methodology, based on a new three-dimensional reconstruction algorithm and a new quantification metric, presents accurate results with high spatial resolution in a time negligible compared to the registration time. This new approach may be a useful tool to compare different deformable registration algorithms oriented to adaptive radiotherapy in prostate cancer In conclusion, this PhD thesis corroborates the postulated research hypotheses, and is intended to serve as a foundation for future advances in medical image processing in adaptive radiotherapy treatment in prostate cancer. In addition, it opens new future applications for medical image processing methods aimed at improving the adaptive radiotherapy processes in the presence of organ’s appearance changes, and increase the patient safety.

Bacterial community structure associated with white band disease in the elkhorn coral Acropora palmata determined using culture-independent 16S rRNA techniques

Culture-independent molecular (16S ribosomal RNA) techniques showed distinct differences in bacterial communities associated with white band disease (WBD) Type I and healthy elkhorn coral Acropora palmata. Differences were apparent at all levels, with a greater diversity present in tissues of diseased colonies. The bacterial community associated with remote, non-diseased coral was distinct from the apparently healthy tissues of infected corals several cm from the disease lesion. This demonstrates a whole-organism effect from what appears to be a localised disease lesion, an effect that has also been recently demonstrated in white plague-like disease in star coral Montastraea annularis. The pattern of bacterial community structure changes was similar to that recently demonstrated for white plague-like disease and black band disease. Some of the changes are likely to be explained by the colonisation of dead and degrading tissues by a micro-heterotroph community adapted to the decomposition of coral tissues. However, specific ribosomal types that are absent from healthy tissues appear consistently in all samples of each of the diseases. These ribotypes are closely related members of a group of alpha-proteobacteria that cause disease, notably juvenile oyster disease, in other marine organisms. It is clearly important that members of this group are isolated for challenge experiments to determine their role in the diseases.

Bacteria and tumours: causative agents or opportunistic inhabitants?

Associations between different bacteria and various tumours have been reported in patients for decades. Studies involving characterisation of bacteria within tumour tissues have traditionally been in the context of tumourigenesis as a result of bacterial presence within healthy tissues, and in general, dogma holds that such bacteria are causative agents of malignancy (directly or indirectly). While evidence suggests that this may be the case for certain tumour types and bacterial species, it is plausible that in many cases, clinical observations of bacteria within tumours arise from spontaneous infection of established tumours. Indeed, growth of bacteria specifically within tumours following deliberate systemic administration has been demonstrated for numerous bacterial species at preclinical and clinical levels. We present the available data on links between bacteria and tumours, and propose that besides the few instances in which pathogens are playing a pathogenic role in cancer, in many instances, the prevalent relationship between solid tumours and bacteria is opportunistic rather than causative, and discuss opportunities for exploiting tumour-specific bacterial growth for cancer treatment.

Radiotherapy Treatment Assessment using DCE-MRI

Abstract

The goal of modern radiotherapy is to precisely deliver a prescribed radiation dose to delineated target volumes that contain a significant amount of tumor cells while sparing the surrounding healthy tissues/organs. Precise delineation of treatment and avoidance volumes is the key for the precision radiation therapy. In recent years, considerable clinical and research efforts have been devoted to integrate MRI into radiotherapy workflow motivated by the superior soft tissue contrast and functional imaging possibility. Dynamic contrast-enhanced MRI (DCE-MRI) is a noninvasive technique that measures properties of tissue microvasculature. Its sensitivity to radiation-induced vascular pharmacokinetic (PK) changes has been preliminary demonstrated. In spite of its great potential, two major challenges have limited DCE-MRI’s clinical application in radiotherapy assessment: the technical limitations of accurate DCE-MRI imaging implementation and the need of novel DCE-MRI data analysis methods for richer functional heterogeneity information.

This study aims at improving current DCE-MRI techniques and developing new DCE-MRI analysis methods for particular radiotherapy assessment. Thus, the study is naturally divided into two parts. The first part focuses on DCE-MRI temporal resolution as one of the key DCE-MRI technical factors, and some improvements regarding DCE-MRI temporal resolution are proposed; the second part explores the potential value of image heterogeneity analysis and multiple PK model combination for therapeutic response assessment, and several novel DCE-MRI data analysis methods are developed.

I. Improvement of DCE-MRI temporal resolution. First, the feasibility of improving DCE-MRI temporal resolution via image undersampling was studied. Specifically, a novel MR image iterative reconstruction algorithm was studied for DCE-MRI reconstruction. This algorithm was built on the recently developed compress sensing (CS) theory. By utilizing a limited k-space acquisition with shorter imaging time, images can be reconstructed in an iterative fashion under the regularization of a newly proposed total generalized variation (TGV) penalty term. In the retrospective study of brain radiosurgery patient DCE-MRI scans under IRB-approval, the clinically obtained image data was selected as reference data, and the simulated accelerated k-space acquisition was generated via undersampling the reference image full k-space with designed sampling grids. Two undersampling strategies were proposed: 1) a radial multi-ray grid with a special angular distribution was adopted to sample each slice of the full k-space; 2) a Cartesian random sampling grid series with spatiotemporal constraints from adjacent frames was adopted to sample the dynamic k-space series at a slice location. Two sets of PK parameters’ maps were generated from the undersampled data and from the fully-sampled data, respectively. Multiple quantitative measurements and statistical studies were performed to evaluate the accuracy of PK maps generated from the undersampled data in reference to the PK maps generated from the fully-sampled data. Results showed that at a simulated acceleration factor of four, PK maps could be faithfully calculated from the DCE images that were reconstructed using undersampled data, and no statistically significant differences were found between the regional PK mean values from undersampled and fully-sampled data sets. DCE-MRI acceleration using the investigated image reconstruction method has been suggested as feasible and promising.

Second, for high temporal resolution DCE-MRI, a new PK model fitting method was developed to solve PK parameters for better calculation accuracy and efficiency. This method is based on a derivative-based deformation of the commonly used Tofts PK model, which is presented as an integrative expression. This method also includes an advanced Kolmogorov-Zurbenko (KZ) filter to remove the potential noise effect in data and solve the PK parameter as a linear problem in matrix format. In the computer simulation study, PK parameters representing typical intracranial values were selected as references to simulated DCE-MRI data for different temporal resolution and different data noise level. Results showed that at both high temporal resolutions (<1s) and clinically feasible temporal resolution (~5s), this new method was able to calculate PK parameters more accurate than the current calculation methods at clinically relevant noise levels; at high temporal resolutions, the calculation efficiency of this new method was superior to current methods in an order of 102. In a retrospective of clinical brain DCE-MRI scans, the PK maps derived from the proposed method were comparable with the results from current methods. Based on these results, it can be concluded that this new method can be used for accurate and efficient PK model fitting for high temporal resolution DCE-MRI.

II. Development of DCE-MRI analysis methods for therapeutic response assessment. This part aims at methodology developments in two approaches. The first one is to develop model-free analysis method for DCE-MRI functional heterogeneity evaluation. This approach is inspired by the rationale that radiotherapy-induced functional change could be heterogeneous across the treatment area. The first effort was spent on a translational investigation of classic fractal dimension theory for DCE-MRI therapeutic response assessment. In a small-animal anti-angiogenesis drug therapy experiment, the randomly assigned treatment/control groups received multiple fraction treatments with one pre-treatment and multiple post-treatment high spatiotemporal DCE-MRI scans. In the post-treatment scan two weeks after the start, the investigated Rényi dimensions of the classic PK rate constant map demonstrated significant differences between the treatment and the control groups; when Rényi dimensions were adopted for treatment/control group classification, the achieved accuracy was higher than the accuracy from using conventional PK parameter statistics. Following this pilot work, two novel texture analysis methods were proposed. First, a new technique called Gray Level Local Power Matrix (GLLPM) was developed. It intends to solve the lack of temporal information and poor calculation efficiency of the commonly used Gray Level Co-Occurrence Matrix (GLCOM) techniques. In the same small animal experiment, the dynamic curves of Haralick texture features derived from the GLLPM had an overall better performance than the corresponding curves derived from current GLCOM techniques in treatment/control separation and classification. The second developed method is dynamic Fractal Signature Dissimilarity (FSD) analysis. Inspired by the classic fractal dimension theory, this method measures the dynamics of tumor heterogeneity during the contrast agent uptake in a quantitative fashion on DCE images. In the small animal experiment mentioned before, the selected parameters from dynamic FSD analysis showed significant differences between treatment/control groups as early as after 1 treatment fraction; in contrast, metrics from conventional PK analysis showed significant differences only after 3 treatment fractions. When using dynamic FSD parameters, the treatment/control group classification after 1st treatment fraction was improved than using conventional PK statistics. These results suggest the promising application of this novel method for capturing early therapeutic response.

The second approach of developing novel DCE-MRI methods is to combine PK information from multiple PK models. Currently, the classic Tofts model or its alternative version has been widely adopted for DCE-MRI analysis as a gold-standard approach for therapeutic response assessment. Previously, a shutter-speed (SS) model was proposed to incorporate transcytolemmal water exchange effect into contrast agent concentration quantification. In spite of richer biological assumption, its application in therapeutic response assessment is limited. It might be intriguing to combine the information from the SS model and from the classic Tofts model to explore potential new biological information for treatment assessment. The feasibility of this idea was investigated in the same small animal experiment. The SS model was compared against the Tofts model for therapeutic response assessment using PK parameter regional mean value comparison. Based on the modeled transcytolemmal water exchange rate, a biological subvolume was proposed and was automatically identified using histogram analysis. Within the biological subvolume, the PK rate constant derived from the SS model were proved to be superior to the one from Tofts model in treatment/control separation and classification. Furthermore, novel biomarkers were designed to integrate PK rate constants from these two models. When being evaluated in the biological subvolume, this biomarker was able to reflect significant treatment/control difference in both post-treatment evaluation. These results confirm the potential value of SS model as well as its combination with Tofts model for therapeutic response assessment.

In summary, this study addressed two problems of DCE-MRI application in radiotherapy assessment. In the first part, a method of accelerating DCE-MRI acquisition for better temporal resolution was investigated, and a novel PK model fitting algorithm was proposed for high temporal resolution DCE-MRI. In the second part, two model-free texture analysis methods and a multiple-model analysis method were developed for DCE-MRI therapeutic response assessment. The presented works could benefit the future DCE-MRI routine clinical application in radiotherapy assessment.

HNF1B variants associate with promoter methylation and regulate gene networks activated in prostate and ovarian cancer

Two independent regions within HNF1B are consistently identified in prostate and ovarian cancer genome-wide association studies (GWAS); their functional roles are unclear. We link prostate cancer (PC) risk SNPs rs11649743 and rs3760511 with elevated HNF1B gene expression and allele-specific epigenetic silencing, and outline a mechanism by which common risk variants could effect functional changes that increase disease risk: functional assays suggest that HNF1B is a pro-differentiation factor that suppresses epithelial-to-mesenchymal transition (EMT) in unmethylated, healthy tissues. This tumor-suppressor activity is lost when HNF1B is silenced by promoter methylation in the progression to PC. Epigenetic inactivation of HNF1B in ovarian cancer also associates with known risk SNPs, with a similar impact on EMT. This represents one of the first comprehensive studies into the pleiotropic role of a GWAS-associated transcription factor across distinct cancer types, and is the first to describe a conserved role for a multi-cancer genetic risk factor.

Evaluating deviations in prostatectomy patients treated with IMRT

Aim - To evaluate the deviations in prostatectomy patients treated with IMRT in order to calculate appropriate margins to create the PTV. Background - Defining inappropriate margins can lead to underdosing in target volumes and also overdosing in healthy tissues, increasing morbidity. Material and methods - 223 CBCT images used for alignment with the CT planning scan based on bony anatomy were analyzed in 12 patients treated with IMRT following prostatectomy. Shifts of CBCT images were recorded in three directions to calculate the required margin to create PTV. Results and discussion - The mean and standard deviation (SD) values in millimetres were −0.05 ± 1.35 in the LR direction, −0.03 ± 0.65 in the SI direction and −0.02 ± 2.05 the AP direction. The systematic error measured in the LR, SI and AP direction were 1.35 mm, 0.65 mm, and 2.05 mm with a random error of 2.07 mm; 1.45 mm and 3.16 mm, resulting in a PTV margin of 4.82 mm; 2.64 mm, and 7.33 mm, respectively. Conclusion - With IGRT we suggest a margin of 5 mm, 3 mm and 8 mm in the LR, SI and AP direction, respectively, to PTV1 and PTV2. Therefore, this study supports an anisotropic margin expansion to the PTV being the largest expansion in the AP direction and lower in SI.

Applications of metrological techniques for clinical implementation of dosimetry and radiobiology in molecular radiotherapy

Molecular radiotherapy (MRT) is a fast developing and promising treatment for metastasised neuroendocrine tumours. Efficacy of MRT is based on the capability to selectively "deliver" radiation to tumour cells, minimizing administered dose to normal tissues. Outcome of MRT depends on the individual patient characteristics. For that reason, personalized treatment planning is important to improve outcomes of therapy. Dosimetry plays a key role in this setting, as it is the main physical quantity related to radiation effects on cells. Dosimetry in MRT consists in a complex series of procedures ranging from imaging quantification to dose calculation. This doctoral thesis focused on several aspects concerning the clinical implementation of absorbed dose calculations in MRT. Accuracy of SPECT/CT quantification was assessed in order to determine the optimal reconstruction parameters. A model of PVE correction was developed in order to improve the activity quantification in small volume, such us lesions in clinical patterns. Advanced dosimetric methods were compared with the aim of defining the most accurate modality, applicable in clinical routine. Also, for the first time on a large number of clinical cases, the overall uncertainty of tumour dose calculation was assessed. As part of the MRTDosimetry project, protocols for calibration of SPECT/CT systems and implementation of dosimetry were drawn up in order to provide standard guidelines to the clinics offering MRT. To estimate the risk of experiencing radio-toxicity side effects and the chance of inducing damage on neoplastic cells is crucial for patient selection and treatment planning. In this thesis, the NTCP and TCP models were derived based on clinical data as help to clinicians to decide the pharmaceutical dosage in relation to the therapy control and the limitation of damage to healthy tissues. Moreover, a model for tumour response prediction based on Machine Learning analysis was developed.

The FOOT experiment: Trigger and Data Acquisition (TDAQ) development and data analysis

Hadrontherapy employs high-energy beams of charged particles (protons and heavier ions) to treat deep-seated tumours: these particles have a favourable depth-dose distribution in tissue characterized by a low dose in the entrance channel and a sharp maximum (Bragg peak) near the end of their path. In these treatments nuclear interactions have to be considered: beam particles can fragment in the human body releasing a non-zero dose beyond the Bragg peak while fragments of human body nuclei can modify the dose released in healthy tissues. These effects are still in question given the lack of interesting cross sections data. Also space radioprotection can profit by fragmentation cross section measurements: the interest in long-term manned space missions beyond Low Earth Orbit is growing in these years but it has to cope with major health risks due to space radiation. To this end, risk models are under study: however, huge gaps in fragmentation cross sections data are currently present preventing an accurate benchmark of deterministic and Monte Carlo codes. To fill these gaps in data, the FOOT (FragmentatiOn Of Target) experiment was proposed. It is composed by two independent and complementary setups, an Emulsion Cloud Chamber and an electronic setup composed by several subdetectors providing redundant measurements of kinematic properties of fragments produced in nuclear interactions between a beam and a target. FOOT aims to measure double differential cross sections both in angle and kinetic energy which is the most complete information to address existing questions. In this Ph.D. thesis, the development of the Trigger and Data Acquisition system for the FOOT electronic setup and a first analysis of 400 MeV/u 16O beam on Carbon target data acquired in July 2021 at GSI (Darmstadt, Germany) are presented. When possible, a comparison with other available measurements is also reported.

Chemo-physical and biological mechanisms behind the anticancer activity of plasma activated Ringer's Lactate solution for the treatment of peritoneal carcinosis from primitive epithelial ovarian/tubular tumor

Cancer research and development of targeting agents in this field is based on robust studies using preclinical models. The failure rate of standardized treatment approaches for several solid tumors has led to the urgent need to fine-tune more sophisticated and faithful preclinical models able to recapitulate the features of in vivo human tumors, with the final aim to shed light on new potential therapeutic targets. Epithelial Ovarian Cancer (EOC) serous histotype (HGSOC) is one of the most lethal diseases in women due to its high aggressiveness (75% of patients diagnosed at FIGO III-IV state) and poor prognosis (less of 50% in 5 years), whose therapy often fails as chemoresistance sets in. This thesis aimed at using the novel perfusion-based bioreactor U-CUP that provides direct perfusion throughout the tumor tissue seeking to obtain an EOC 3D ex vivo model able to recapitulate the features of the original tumor including the tumor microenvironment and maintaining its cellular heterogeneity. Moreover, we optimized this approach so that it can be successfully applied to slow-frozen tumoral tissues, further extending the usefulness of this tool. We also investigated the effectiveness of Plasma Activated Ringer’s Lactate solution (PA-RL) against Epithelial Ovarian Cancer (EOC) serous histotype in both 2D and 3D cultures using ex-vivo specimens from HGSOC patients. We propose PA-RL as a novel therapy with local intraperitoneal administration, which could act on primary or metastatic ovarian tumors inducing a specific cancer cell death with reduced damage on the surrounding healthy tissues.

Ruolo di Glutaredossina-2 nella trasformazione tumorale oncocitaria

Gli oncocitomi sono tumori epiteliali caratterizzati da un accumulo di mitocondri strutturalmente e funzionalmente compromessi, a prognosi generalmente benigna. Le cause genetiche della trasformazione oncocitaria sono tuttora sconosciute; pertanto, lo studio di oncocitomi in contesti familiari sindromici è utile nella ricerca dei determinanti genetici predisponenti il fenotipo. Diversi membri di una famiglia affetta da sindrome dell’iperparatiroidismo con tumore della mandibola (HPT-JT), dovuta ad un'ampia delezione in CDC73, hanno mostrato recidiva di tumori paratiroidei oncocitari. Il sequenziamento dell’esoma ha escluso mutazioni private della famiglia; all'interno della delezione ereditata, tuttavia, sono stati individuati elementi regolatori del gene glutaredossina 2 (GLRX2), codificante un'isoforma mitocondriale deputata alla deglutationilazione proteica reversibile -modificazione modulante l’attività di numerosi target- il cui ruolo nel cancro non è noto. La proteina è risultata assente in tutti i tumori e dimezzata nei tessuti sani dei soggetti. Per indagare se la sua assenza alteri la deglutationilazione proteica predisponendo al fenotipo oncocitario, sono stati generati modelli cellulari TPC1 e HCT116 GLRX2 KO in cui sono stati riscontrati un ridotto tasso proliferativo ed un'alterata glutationilazione proteica, particolarmente in seguito a stress ossidativo. Un esperimento pilota in vivo ha mostrato cellule KO oncocitoidi, con mitocondri morfologicamente alterati, suggerendo che l’alterazione redox innescata dall’assenza di GLRX2 possa indurre una disfunzione metabolica mitocondriale tale da mimare quelle osservate negli oncocitomi. L’analisi proteomica ha individuato diversi target di glutationilazione nei campioni KO identificando proteine del ciclo di Krebs e della catena respiratoria mitocondriale. In particolare, una marcata glutationilazione del complesso della piruvato deidrogenasi (PDHc) è stata correlata ad una ridotta sintesi di ATP dipendente da piruvato. Considerando l'importanza dello stress ossidativo nella fisiopatologia del cancro ed il ruolo del glutatione nella risposta antiossidante, GLRX2 rappresenta un potenziale candidato nella regolazione del metabolismo ossidativo nelle cellule tumorali esposte allo stress e nella modulazione del fenotipo tumorale.

A 3D biomimetic in vitro model: a novel strategy to investigate glioma biology

Gliomas are one of the most frequent primary malignant brain tumors. Acquisition of stem-like features likely contributes to the malignant nature of high-grade gliomas and may be responsible for the initiation, growth, and recurrence of these tumors. In this regard, although the traditional 2D cell culture system has been widely used in cancer research, it shows limitations in maintaining the stemness properties of cancer and in mimicking the in vivo microenvironment. In order to overcome these limitations, different three-dimensional (3D) culture systems have been developed to mimic better the tumor microenvironment. Cancer cells cultured in 3D structures may represent a more reliable in vitro model due to increased cell-cell and cell-extracellular matrix (ECM) interaction. Several attempts to recreate brain cancer tissue in vitro are described in literature. However, to date, it is still unclear which main characteristics the ideal model should reproduce. The overall goal of this project was the development of a 3D in vitro model able to reproduce the brain ECM microenvironment and to recapitulate pathological condition for the study of tumor stroma interactions, tumor invasion ability, and molecular phenotype of glioma cells. We performed an in silico bioinformatic analysis using GEPIA2 Software to compare the expression level of seven matrix protein in the LGG tumors with healthy tissues. Then, we carried out a FFPE retrospective study in order to evaluate the percentage of expression of selected proteins. Thus, we developed a 3D scaffold composed by Hyaluronic Acid and Collagen IV in a ratio of 50:50. We used two astrocytoma cell lines, HTB-12 and HTB-13. In conclusion, we developed an in vitro 3D model able to reproduce the composition of brain tumor ECM, demonstrating that it is a feasible platform to investigate the interaction between tumor cells and the matrix.