MicroRNAs are key regulators of hepatocellular carcinoma (HCC) cell dissemination—what we learned from microRNA-494

Producción CientíficaHepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide, and it is well accepted that the poor outcome of HCC patients among others is caused by metastasis and tumor cell dissemination

Tumor cell load and heterogeneity estimation from diffusion-weighted MRI calibrated with histological data: an example from lung cancer

Producción CientíficaDiffusion-weighted magnetic resonance imaging (DWI) is a key non-invasive imaging technique for cancer diagnosis and tumor treatment assessment, reflecting Brownian movement of water molecules in tissues. Since densely packed cells restrict molecule mobility, tumor tissues produce usually higher signal (a.k.a. less attenuated signal) on isotropic maps compared with normal tissues. However, no general quantitative relation between DWI data and the cell density has been established. In order to link low-resolution clinical cross-sectional data with high-resolution histological information, we developed an image processing and analysis chain, which was used to study the correlation between the diffusion coefficient (D value) estimated from DWI and tumor cellularity from serial histological slides of a resected non-small cell lung cancer tumor. Color deconvolution followed by cell nuclei segmentation was performed on digitized histological images to determine local and cell-type specific 2d (two-dimensional) densities. From these, the 3d cell density was inferred by a model-based sampling technique, which is necessary for the calculation of local and global 3d tumor cell count. Next, DWI sequence information was overlaid with high-resolution CT data and the resected histology using prominent anatomical hallmarks for co-registration of histology tissue blocks and non-invasive imaging modalities' data. The integration of cell numbers information and DWI data derived from different tumor areas revealed a clear negative correlation between cell density and D value. Importantly, spatial tumor cell density can be calculated based on DWI data. In summary, our results demonstrate that tumor cell count and heterogeneity can be predicted from DWI data, which may open new opportunities for personalized diagnosis and therapy optimization

Genes associated with metabolic syndrome predict disease-free survival in stage II colorectal cancer patients. A novel link between metabolic dysregulation and colorectal cancer

Producción CientíficaStudies have recently suggested that metabolic syndrome and its components increase the risk of colorectal cancer. Both diseases are increasing in most countries, and the genetic association between them has not been fully elucidated. The objective of this study was to assess the association between genetic risk factors of metabolic syndrome or related conditions (obesity, hyperlipidaemia, diabetes mellitus type 2) and clinical outcome in stage II colorectal cancer patients. Expression levels of several genes related to metabolic syndrome and associated alterations were analysed by real-time qPCR in two equivalent but independent sets of stage II colorectal cancer patients. Using logistic regression models and cross-validation analysis with all tumour samples, we developed a metabolic syndrome-related gene expression profile to predict clinical outcome in stage II colorectal cancer patients. The results showed that a gene expression profile constituted by genes previously related to metabolic syndrome was significantly associated with clinical outcome of stage II colorectal cancer patients. This metabolic profile was able to identify patients with a low risk and high risk of relapse. Its predictive value was validated using an independent set of stage II colorectal cancer patients. The identification of a set of genes related to metabolic syndrome that predict survival in intermediate-stage colorectal cancer patients allows delineation of a high-risk group that may benefit from adjuvant therapy and avoid the toxic and unnecessary chemotherapy in patients classified as low risk. Our results also confirm the linkage between.Ministerio de Ciencia, Innovación y Universidades (AGL2010-21565, RyC 2008-03734, IPT-2011-1248-060000),y la Comunidad de Madrid (ALIBIRD, S2009/AGR-1469

Patch-based nonlinear image registration for gigapixel whole slide images

Producción CientíficaImage registration of whole slide histology images allows the fusion of fine-grained information-like different immunohistochemical stains-from neighboring tissue slides. Traditionally, pathologists fuse this information by looking subsequently at one slide at a time. If the slides are digitized and accurately aligned at cell level, automatic analysis can be used to ease the pathologist's work. However, the size of those images exceeds the memory capacity of regular computers. Methods: We address the challenge to combine a global motion model that takes the physical cutting process of the tissue into account with image data that is not simultaneously globally available. Typical approaches either reduce the amount of data to be processed or partition the data into smaller chunks to be processed separately. Our novel method first registers the complete images on a low resolution with a nonlinear deformation model and later refines this result on patches by using a second nonlinear registration on each patch. Finally, the deformations computed on all patches are combined by interpolation to form one globally smooth nonlinear deformation. The NGF distance measure is used to handle multistain images. Results: The method is applied to ten whole slide image pairs of human lung cancer data. The alignment of 85 corresponding structures is measured by comparing manual segmentations from neighboring slides. Their offset improves significantly, by at least 15%, compared to the low-resolution nonlinear registration. Conclusion/Significance: The proposed method significantly improves the accuracy of multistain registration which allows us to compare different antibodies at cell level

The ellagic acid derivative 4,4′-Di-O-methylellagic acid efficiently inhibits colon cancer cell growth through a mechanism involving WNT16

Producción CientíficaEllagic acid (EA) and some derivatives have been reported to inhibit cancer cell proliferation, induce cell cycle arrest, and modulate some important cellular processes related to cancer. This study aimed to identify possible structure-activity relationships of EA and some in vivo derivatives in their antiproliferative effect on both human colon cancer and normal cells, and to compare this activity with that of other polyphenols. Our results showed that 4,4′-di-O-methylellagic acid (4,4′-DiOMEA) was the most effective compound in the inhibition of colon cancer cell proliferation. 4,4′-DiOMEA was 13-fold more effective than other compounds of the same family. In addition, 4,4′-DiOMEA was very active against colon cancer cells resistant to the chemotherapeutic agent 5-fluoracil, whereas no effect was observed in nonmalignant colon cells. Moreover, no correlation between antiproliferative and antioxidant activities was found, further supporting that structure differences might result in dissimilar molecular targets involved in their differential effects. Finally, microarray analysis revealed that 4,4′-DiOMEA modulated Wnt signaling, which might be involved in the potential antitumor action of this compound. Our results suggest that structural-activity differences between EA and 4,4′-DiOMEA might constitute the basis for a new strategy in anticancer drug discovery based on these chemical modifications.Ministerio de Economía, Industria y Competitividad (AGL2013-48943-C2-2-R and IPT-2011-1248-060000)Comunidad de Madrid [Grant P2013/ABI-2728 ALIBIRD-CM

Evaluación del extracto supercrítico de romero (Rosmarinus officinalis L.) como agente antitumoral: bases genómicas de su potencial aplicación clínica

Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Ciencias, Departamento de Química-Física Aplicada. Fecha de lectura: 18-03-201

Protocolo de la Práctica de Fisiología Renal a Domicilio: PID_20_21_123_Anexo 1.pdf

La pandemia por COVID-19 ha supuesto la implantación de medidas de seguridad cuyo cumplimiento se hace especialmente difícil en el caso de las prácticas de laboratorio. Este proyecto pretende adaptar la práctica de Fisiología Renal de la asignatura de Fisiología II (2º Grado en Medicina), habitualmente realizada presencialmente, para su realización por los alumnos en su propio domicilio. La práctica pone de manifiesto los mecanismos renales que regulan el volumen, la osmolaridad y el pH de los líquidos corporales, midiendo los cambios en el flujo, pH y excreción de Na+ y K+ en la orina tras distintas sobrecargas (agua o soluciones isotónicas). En este proyecto se ha diseñado un nuevo protocolo para la adaptación de la práctica, cuya viabilidad y adecuación han sido validadas antes de su propuesta a los alumnos. Posteriormente, la práctica ha sido propuesta a los estudiantes, y se ha evaluado el porcentaje de participación y la calidad de los datos obtenidos en comparación con cursos anteriores. Los resultados indican que la práctica a domicilio ha tenido mayor aceptación por parte de los alumnos que la práctica realizada en el laboratorio. Además, los datos obtenidos por los alumnos en la realización de la práctica tienen la calidad suficiente para poner de manifiesto los mecanismos renales planteados. Se concluye que la práctica de Fisiología Renal adaptada ha resultado adecuada para el aprendizaje de los alumnos y podría ser de utilidad en la docencia de la materia, tanto de forma presencial como no presencial.Departamento de Bioquímica y Biología Molecular y Fisiologí