Topological analysis of the tumour microenvironment to study Neuroblastoma

Solid tumours and their tumour microenvironment (TME) can be considered as complex networks whose elements are in constant physical stress. All the elements of the TME, including tumour cells, stromal cells, immune and stem cells, blood/lymphatic vessels, nerve fibers and extracellular matrix components, belong to a highly balanced compressiontension molecular and cellular structure. Through mechanical signals, each element could affect its surroundings modulating tumour growth and migration. The analysis of these complex interactions and the understanding of the structural organization of a tumour requires the collaboration of different disciplines. In this thesis, we focus on a particular solid tumour: Neuroblastoma, a rare type of cancer, originated during the embryo development. We apply computational and mathematical tools to analyse the topology of vitronectin, a glycoprotein of the extracellular matrix, in neuroblastoma tumours. Vitronectin has a particular interest in tumour biology where it is associated with cell migration, angiogenesis, and matrix degradation. Still, its role in Neuroblastoma is not clear. Here, we study the organization of vitronectin within the TME considering Neuroblastoma patient prognosis and tumoral aggressiveness. Combing graph theory and image analysis, we characterize histopathological images taken, from a human sample, by analysing different topological features that capture the organizational cues of vitronectin. By means of statistical analyses, we find that two topological features (Euler number and branching), related to the organization of the existing vitronectin within and surrounding the cells (territorial), correlates with risk pre-stratification group and genetic instability criterion. We interpret that a large amount of recently synthesized VN would create tracks to aid malignant neuroblasts to invade other organs, pinpointed by both topological features, which in turn would change, dramatically, the constitution and mechanics of the extracellular matrix, increasing tumour aggressiveness and worsen patient outcomes. Further studies will be required to assess the true potential of vitronectin as a future therapeutic target of neuroblastoma.Los tumores sólidos y su microambiente tumoral (TME) pueden ser vistos como redes complejas cuyos elementos están en constante estrés físico. Todos los elementos del TME, incluidas células tumorales, células del estroma, células inmunes y células troncales, vasos sanguíneos o linfáticos, fibras nerviosas y componentes de la matriz extracelular, pertenecen a una maquinaria molecular y celular de tensión-compresión altamente equilibrada. A través de señales mecánicas, cada elemento podría afectar su entorno modulando el crecimiento tumoral y la migración. El análisis de estas interacciones complejas y la comprensión de la organización estructural de un tumor requiere la colaboración de diferentes disciplinas. En esta tesis, nos centramos en un tumor sólido particular: el neuroblastoma, un cáncer considerado como ‘raro’, que se origina durante el desarrollo del embrión. Aplicando herramientas computacionales y matemáticas, analizamos la topología de la vitronectina, una glicoproteína de la matriz extracelular, en tumores de neuroblastoma. La vitronectina tiene un interés particular en la biología tumoral, ya que está asociada con migración celular, angiogénesis y degradación de la propia matriz. Aún así, su papel en el neuroblastoma no está claro. En este trabajo, estudiamos la organización de la vitronectina dentro del microambiente tumoral, considerando el pronóstico del paciente con neuroblastoma y su agresividad tumoral. Combinando la teoría de gráficos y el análisis de imagen, caracterizamos las imágenes histopatológicas tomadas de una muestra humana, mediante el análisis de diferentes características topológicas que capturan la organización de la vitronectina. Mediante análisis estadísticos, encontramos que dos características topológicas (número de Euler y ‘ramificación’), relacionadas con la organización de la vitronectina existente dentro y alrededor de las células (territorial), se correlacionan con el grupo de pre-estratificación de riesgo y la inestabilidad genética del paciente. En consecuencia, interpretamos que una gran cantidad de VN, sintetizada recientemente, crearía una especia de ‘caminos’ para ayudar a los neuroblastos malignos a invadir otros órganos, que a su vez cambiarían dramáticamente la constitución y la mecánica de la matriz extracelular, aumentando la agresividad del tumor y empeorando el pronóstico del paciente. Futuros estudios serán requeridos para evaluar el verdadero potencial de la vitronectina como una diana terapéutica del neuroblastoma a largo plazo

Evolutionary 3D Image Segmentation of Curve Epithelial Tissues of Drosophila melanogaster

Analysing biological images coming from the microscope is challenging; not only is it complex to acquire the images, but also the three-dimensional shapes found on them. Thus, using automatic approaches that could learn and embrace that variance would be highly interesting for the field. Here, we use an evolutionary algorithm to obtain the 3D cell shape of curve epithelial tissues. Our approach is based on the application of a 3D segmentation algorithm called LimeSeg, which is a segmentation software that uses a particle-based active contour method. This program needs the fine tuning of some hyperparameters that could present a long number of combinations, with the selection of the best parametrisation being highly time-consuming. Our evolutionary algorithm automatically selects the best possible parametrisation with which it can perform an accurate and non-supervised segmentation of 3D curved epithelial tissues. This way, we combine the segmentation potential of LimeSeg and optimise the parameters selection by adding automatisation. This methodology has been applied to three datasets of confocal images from Drosophila melanogaster, where a good convergence has been observed in the evaluation of the solutions. Our experimental results confirm the proper performing of the algorithm, whose segmented images have been compared to those manually obtained for the same tissues.Ministerio de Ciencia, Innovación y Universidades TIN2017-88209-C2Junta de Andalucía US-1263341Junta de Andalucía P18-RT-2778Ministerio de Economía, Industria y Competitividad BFU2016-74975-PMinisterio de Ciencia e Innovación PID2019-103900GB-10

Scutoids are a geometrical solution to three-dimensional packing of epithelia

As animals develop, tissue bending contributes to shape the organs into complex three-dimensional structures. However, the architecture and packing of curved epithelia remains largely unknown. Here we show by means of mathematical modelling that cells in bent epithelia can undergo intercalations along the apico-basal axis. This phenomenon forces cells to have different neighbours in their basal and apical surfaces. As a consequence, epithelial cells adopt a novel shape that we term “scutoid”. The detailed analysis of diverse tissues confirms that generation of apico-basal intercalations between cells is a common feature during morphogenesis. Using biophysical arguments, we propose that scutoids make possible the minimization of the tissue energy and stabilize three-dimensional packing. Hence, we conclude that scutoids are one of nature's solutions to achieve epithelial bending. Our findings pave the way to understand the three-dimensional organization of epithelial organs.España Ministerio de Ciencia y Tecnología BFU2013-48988-C2-1-P and BFU2016-8079

EpiGraph: an open-source platform to quantify epithelial organization

Here we present EpiGraph, an image analysis tool that quantifies epithelial organization. Our method combines computational geometry and graph theory to measure the degree of order of any packed tissue. EpiGraph goes beyond the traditional polygon distribution analysis, capturing other organizational traits that improve the characterization of epithelia. EpiGraph can objectively compare the rearrangements of epithelial cells during development and homeostasis to quantify how the global ensemble is affected. Importantly, it has been implemented in the open-access platform Fiji. This makes EpiGraph very user friendly, with no programming skills required.España Ministerio de Economia, Industria y Competitividad BFU2016-74975-PEspaña, Programa Ramón y Cajal (PI13/ 01347

CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia

Decades of research have not yet fully explained the mechanisms of epithelial self-organization and 3D packing. Single-cell analysis of large 3D epithelial libraries is crucial for understanding the assembly and function of whole tissues. Combining 3D epithelial imaging with advanced deep-learning segmentation methods is essential for enabling this high-content analysis. We introduce CartoCell, a deep-learning-based pipeline that uses small datasets to generate accurate labels for hundreds of whole 3D epithelial cysts. Our method detects the realistic morphology of epithelial cells and their contacts in the 3D structure of the tissue. CartoCell enables the quantification of geometric and packing features at the cellular level. Our single-cell cartography approach then maps the distribution of these features on 2D plots and 3D surface maps, revealing cell morphology patterns in epithelial cysts. Additionally, we show that CartoCell can be adapted to other types of epithelial tissues

CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia

Decades of research have not yet fully explained the mechanisms of epithelial self-organization and 3D packing. Single-cell analysis of large 3D epithelial libraries is crucial for understanding the assembly and function of whole tissues. Combining 3D epithelial imaging with advanced deep-learning segmentation methods is essential for enabling this high-content analysis. We introduce CartoCell, a deep-learning-based pipeline that uses small datasets to generate accurate labels for hundreds of whole 3D epithelial cysts. Our method detects the realistic morphology of epithelial cells and their contacts in the 3D structure of the tissue. CartoCell enables the quantification of geometric and packing features at the cellular level. Our single-cell cartography approach then maps the distribution of these features on 2D plots and 3D surface maps, revealing cell morphology patterns in epithelial cysts. Additionally, we show that CartoCell can be adapted to other types of epithelial tissues.Ministerio de Ciencia e Innovación PID2019-103900GB-I00, PID2020-120367GB-I00, PID2021-126701OB-I00Junta de Andalucía US-1380953, PY18-631Ministerio de Economía y Competitividad BES-2022-07778

Clinical inertia in poorly controlled elderly hypertensive patients: a cross-sectional study in Spanish physicians to ascertain reasons for not intensifying treatment

Background Clinical inertia, the failure of physicians to initiate or intensify therapy when indicated, is a major problem in the management of hypertension and may be more prevalent in elderly patients. Overcoming clinical inertia requires understanding its causes and evaluating certain factors, particularly those related to physicians. Objective The objective of our study was to determine the rate of clinical inertia and the physician-reported rea- sons for it. Conclusion Physicians provided reasons for not intensi- fying treatment in poorly controlled patients in only 30 % of instances. Main reasons for not intensifying treatment were borderline BP values, co-morbidity, suspected white coat effect, or perceived difficulty achieving target. nJCI was associated with high borderline BP values and car- diovascular diseas

Non-productive angiogenesis disassembles Aß plaque-associated blood vessels

The human Alzheimer’s disease (AD) brain accumulates angiogenic markers but paradoxically, the cerebral microvasculature is reduced around Aß plaques. Here we demonstrate that angiogenesis is started near Aß plaques in both AD mouse models and human AD samples. However, endothelial cells express the molecular signature of non-productive angiogenesis (NPA) and accumulate, around Aß plaques, a tip cell marker and IB4 reactive vascular anomalies with reduced NOTCH activity. Notably, NPA induction by endothelial loss of presenilin, whose mutations cause familial AD and which activity has been shown to decrease with age, produced a similar vascular phenotype in the absence of Aß pathology. We also show that Aß plaque-associated NPA locally disassembles blood vessels, leaving behind vascular scars, and that microglial phagocytosis contributes to the local loss of endothelial cells. These results define the role of NPA and microglia in local blood vessel disassembly and highlight the vascular component of presenilin loss of function in AD

Computational biology and Neuroblastoma tumours

Trabajo presentado en el Seminario Programa de Neurociencias, celebrado en Sevilla el 28 de enero de 2020

The complex three-dimensional organization of epithelial tissues

Understanding the cellular organization of tissues is key to developmental biology. In order to deal with this complex problem, researchers have taken advantage of reductionist approaches to reveal fundamental morphogenetic mechanisms and quantitative laws. For epithelia, their two-dimensional representation as polygonal tessellations has proved successful for understanding tissue organization. Yet, epithelial tissues bend and fold to shape organs in three dimensions. In this context, epithelial cells are too often simplified as prismatic blocks with a limited plasticity. However, there is increasing evidence that a realistic approach, even from a reductionist perspective, must include apico-basal intercalations (i.e. scutoidal cell shapes) for explaining epithelial organization convincingly. Here, we present an historical perspective about the tissue organization problem. Specifically, we analyze past and recent breakthroughs, and discuss how and why simplified, but realistic, in silico models require scutoidal features to address key morphogenetic events.Ministerio de Ciencia e Innovación PI13/01,347, 2019-105566GB-100, PID2019-103900GB-100Ministerio de Economía y Competitividad BFU2016-74975-PJunta de Andalucía P18-FR-631Lehigh University JB-FIG-201