Genetic mouse models as in vivo tools for cholangiocarcinoma research

Cholangiocarcinoma (CCA) is a genetically and histologically complex disease with a highly dismal prognosis. A deeper understanding of the underlying cellular and molecular mechanisms of human CCA will increase our current knowledge of the disease and expedite the eventual development of novel therapeutic strategies for this fatal cancer. This endeavor is effectively supported by genetic mouse models, which serve as sophisticated tools to systematically investigate CCA pathobiology and treatment response. These in vivo models feature many of the genetic alterations found in humans, recapitulate multiple hallmarks of cholangiocarcinogenesis (encompassing cell transformation, preneoplastic lesions, established tumors and metastatic disease) and provide an ideal experimental setting to study the interplay between tumor cells and the surrounding stroma. This review is intended to serve as a compendium of CCA mouse models, including traditional transgenic models but also genetically flexible approaches based on either the direct introduction of DNA into liver cells or transplantation of pre-malignant cells, and is meant as a resource for CCA researchers to aid in the selection of the most appropriate in vivo model system

FOSL1 promotes cholangiocarcinoma via transcriptional effectors that could be therapeutically targeted

Understanding the molecular mechanisms involved in cholangiocarcinoma (bile duct cancer) development and progression stands as a critical step for the development of novel therapies. Through an inter-species approach, this study provides evidence of the clinical and functional role of the transcription factor FOSL1 in cholangiocarcinoma. Moreover, we report that downstream effectors of FOSL1 are susceptible to pharmacological inhibition, thus providing new opportunities for therapeutic intervention

Revisiting the epidemiology of bloodstream infections and healthcare-associated episodes: results from a multicentre prospective cohort in Spain (PRO-BAC Study)

PROBAC REIPI/GEIH-SEIMC/SAEI Group.The epidemiology of bloodstream infections (BSIs) is dynamic as it depends on microbiological, host and healthcare system factors. The aim of this study was to update the information regarding the epidemiology of BSIs in Spain considering the type of acquisition. An observational, prospective cohort study in 26 Spanish hospitals from October 2016 through March 2017 including all episodes of BSI in adults was performed. Bivariate analyses stratified by type of acquisition were performed. Multivariate analyses were performed by logistic regression. Overall, 6345 BSI episodes were included; 2510 (39.8%) were community-acquired (CA), 1661 (26.3%) were healthcare-associated (HCA) and 2056 (32.6%) hospital-acquired (HA). The 30-day mortality rates were 11.6%, 19.5% and 22.0%, respectively. The median age of patients was 71 years (interquartile range 60–81 years) and 3656 (58.3%; 95% confidence interval 57.1–59.6%) occurred in males. The proportions according to patient sex varied according to age strata. Escherichia coli (43.8%), Klebsiella spp. (8.9%), Staphylococcus aureus (8.9%) and coagulase-negative staphylococci (7.4%) were the most frequent pathogens. Multivariate analyses confirmed important differences between CA and HCA episodes, but also between HCA and HA episodes, in demographics, underlying conditions and aetiology. In conclusion, we have updated the epidemiological information regarding patients’ profiles, underlying conditions, frequency of acquisition types and aetiological agents of BSI in Spain. HCA is confirmed as a distinct type of acquisition.This work was financed by grants from Plan Nacional de I+D+i 2013–2016, Instituto de Salud Carlos III, Subdirección General de Redes y Centros de Investigación Cooperativa, Ministerio de Ciencia, Innovación y Universidades [PI16/01432] and the Spanish Network for Research in Infectious Diseases (REIPI) [RD16/0016/0001; RD16/0016/0008], co‐financed by the European Development Regional Fund ‘A way to achieve Europe’, Operative program Intelligent Growth 2014–2020

Identification of novel oncogene dependencies in mutant KRAS-driven epithelial tumours: the role of the transcription factor FOSL1

KRAS representa el oncogén más frecuentemente mutado en varios tumores sólidos como el adenocarcinoma de pulmón (ACP), el adenocarcinoma ductal pancreático (ADP) y el carcinoma de vías biliares o colangiocarcinoma (CCA), donde se asocia con mal pronóstico por falta de opciones curativas. En este trabajo se ha identificado, mediante una nueva estrategia multimodal que integra transcriptómica inter-especies y una aproximación bioinformática de datos clínicos de múltiples tipos tumorales dirigidos por KRAS, una huella de genes críticamente convergentes y necesarios para la homeostasis tumoral (Vallejo y cols., Nature Communications, 2017). La disección funcional-mecanística identificó a FOSL1 como una vulnerabilidad en tumores de ACP, ADP y CCA dirigidos por la mutación de KRAS. FOSL1 (Fos-like antigen 1) o FRA1 (Fos-related antigen 1) pertenece una familia de factores de transcripción que forma dímeros con miembros de la familia JUN para constituir el complejo transcripcional AP1, lo que conlleva la regulación de distintas funciones celulares. El presente trabajo muestra que la inhibición tanto in vitro como en modelos de ratón xenotransplantados, perjudica preferencialmente a la proliferación de las células KRAS mutantes de ACP y de CCA, retrasando y disminuyendo la formación y proliferación de los tumores. Su efecto está asociado a un arresto en fase G2/M del ciclo celular y un aumento de la apoptosis. Además, la depleción de FOSL1 en Modelos de Ratón Modificados Genéticamente de ACP y CCA aumenta la supervivencia global y reduce la carga tumoral de los ratones. A nivel funcional, FOSL1 regula la expresión de factores de transcripción (FOXM1) y de quinasas centrales (AURKA y PLK1) de la progresión G2-M en tumores de pulmón y páncreas con KRAS mutado. En CCA, FOSL1 regula además el metabolismo celular a través del control de genes implicados en la síntesis de colesterol y mevalonato (HMGCS1). La inhibición in vitro de los diferentes efectores de FOSL1 reduce la proliferación de las células KRAS mutantes de ACP y de CCA, demostrando la relevancia funcional de FOSL1 en este tipo de tumores. Finalmente, el trabajo muestra cómo la inhibición farmacológica concomitante de efectores aguas arriba y aguas abajo de FOSL1 como AURKA y MEK en células de ACP KRAS-mutantes presenta efectos antitumorales sinérgicos in vitro. Además, su combinación en modelos xenoinjertados de ratón con células de ACP de pulmón KRAS-mutantes induce una mayor reducción del volumen tumoral comparado con la administración individual de cada inhibidor. En resumen, el trabajo aporta información funcional y mecanística que podría ser transladada para el tratamiento de pacientes de ACP y CCA con mutaciones en el oncogén KRAS

Identification of novel oncogene dependencies in mutant KRAS-driven epithelial tumours: the role of the transcription factor FOSL1

KRAS representa el oncogén más frecuentemente mutado en varios tumores sólidos como el adenocarcinoma de pulmón (ACP), el adenocarcinoma ductal pancreático (ADP) y el carcinoma de vías biliares o colangiocarcinoma (CCA), donde se asocia con mal pronóstico por falta de opciones curativas. En este trabajo se ha identificado, mediante una nueva estrategia multimodal que integra transcriptómica inter-especies y una aproximación bioinformática de datos clínicos de múltiples tipos tumorales dirigidos por KRAS, una huella de genes críticamente convergentes y necesarios para la homeostasis tumoral (Vallejo y cols., Nature Communications, 2017). La disección funcional-mecanística identificó a FOSL1 como una vulnerabilidad en tumores de ACP, ADP y CCA dirigidos por la mutación de KRAS. FOSL1 (Fos-like antigen 1) o FRA1 (Fos-related antigen 1) pertenece una familia de factores de transcripción que forma dímeros con miembros de la familia JUN para constituir el complejo transcripcional AP1, lo que conlleva la regulación de distintas funciones celulares. El presente trabajo muestra que la inhibición tanto in vitro como en modelos de ratón xenotransplantados, perjudica preferencialmente a la proliferación de las células KRAS mutantes de ACP y de CCA, retrasando y disminuyendo la formación y proliferación de los tumores. Su efecto está asociado a un arresto en fase G2/M del ciclo celular y un aumento de la apoptosis. Además, la depleción de FOSL1 en Modelos de Ratón Modificados Genéticamente de ACP y CCA aumenta la supervivencia global y reduce la carga tumoral de los ratones. A nivel funcional, FOSL1 regula la expresión de factores de transcripción (FOXM1) y de quinasas centrales (AURKA y PLK1) de la progresión G2-M en tumores de pulmón y páncreas con KRAS mutado. En CCA, FOSL1 regula además el metabolismo celular a través del control de genes implicados en la síntesis de colesterol y mevalonato (HMGCS1). La inhibición in vitro de los diferentes efectores de FOSL1 reduce la proliferación de las células KRAS mutantes de ACP y de CCA, demostrando la relevancia funcional de FOSL1 en este tipo de tumores. Finalmente, el trabajo muestra cómo la inhibición farmacológica concomitante de efectores aguas arriba y aguas abajo de FOSL1 como AURKA y MEK en células de ACP KRAS-mutantes presenta efectos antitumorales sinérgicos in vitro. Además, su combinación en modelos xenoinjertados de ratón con células de ACP de pulmón KRAS-mutantes induce una mayor reducción del volumen tumoral comparado con la administración individual de cada inhibidor. En resumen, el trabajo aporta información funcional y mecanística que podría ser transladada para el tratamiento de pacientes de ACP y CCA con mutaciones en el oncogén KRAS

Genetic mouse models as in vivo tools for cholangiocarcinoma research

Cholangiocarcinoma (CCA) is a genetically and histologically complex disease with a highly dismal prognosis. A deeper understanding of the underlying cellular and molecular mechanisms of human CCA will increase our current knowledge of the disease and expedite the eventual development of novel therapeutic strategies for this fatal cancer. This endeavor is effectively supported by genetic mouse models, which serve as sophisticated tools to systematically investigate CCA pathobiology and treatment response. These in vivo models feature many of the genetic alterations found in humans, recapitulate multiple hallmarks of cholangiocarcinogenesis (encompassing cell transformation, preneoplastic lesions, established tumors and metastatic disease) and provide an ideal experimental setting to study the interplay between tumor cells and the surrounding stroma. This review is intended to serve as a compendium of CCA mouse models, including traditional transgenic models but also genetically flexible approaches based on either the direct introduction of DNA into liver cells or transplantation of pre-malignant cells, and is meant as a resource for CCA researchers to aid in the selection of the most appropriate in vivo model system

Accurate prediction of kinase-substrate networks using knowledge graphs

Phosphorylation of specific substrates by protein kinases is a key control mechanism for vital cell-fate decisions and other cellular processes. However, discovering specific kinasesubstrate relationships is time-consuming and often rather serendipitous. Computational predictions alleviate these challenges, but the current approaches suffer from limitations like restricted kinome coverage and inaccuracy. They also typically utilise only local features without reflecting broader interaction context. To address these limitations, we have developed an alternative predictive model. It uses statistical relational learning on top of phosphorylation networks interpreted as knowledge graphs, a simple yet robust model for representing networked knowledge. Compared to a representative selection of six existing systems, our model has the highest kinome coverage and produces biologically valid highconfidence predictions not possible with the other tools. Specifically, we have experimentally validated predictions of previously unknown phosphorylations by the LATS1, AKT1, PKA and MST2 kinases in human. Thus, our tool is useful for focusing phosphoproteomic experiments, and facilitates the discovery of new phosphorylation reactions. Our model can be accessed publicly via an easy-to-use web interface (LinkPhinder)

Accurate prediction of kinase-substrate networks using knowledge graphs

Phosphorylation of specific substrates by protein kinases is a key control mechanism for vital cell-fate decisions and other cellular processes. However, discovering specific kinasesubstrate relationships is time-consuming and often rather serendipitous. Computational predictions alleviate these challenges, but the current approaches suffer from limitations like restricted kinome coverage and inaccuracy. They also typically utilise only local features without reflecting broader interaction context. To address these limitations, we have developed an alternative predictive model. It uses statistical relational learning on top of phosphorylation networks interpreted as knowledge graphs, a simple yet robust model for representing networked knowledge. Compared to a representative selection of six existing systems, our model has the highest kinome coverage and produces biologically valid highconfidence predictions not possible with the other tools. Specifically, we have experimentally validated predictions of previously unknown phosphorylations by the LATS1, AKT1, PKA and MST2 kinases in human. Thus, our tool is useful for focusing phosphoproteomic experiments, and facilitates the discovery of new phosphorylation reactions. Our model can be accessed publicly via an easy-to-use web interface (LinkPhinder)

FOSL1 promotes cholangiocarcinoma via transcriptional effectors that could be therapeutically targeted

Understanding the molecular mechanisms involved in cholangiocarcinoma (bile duct cancer) development and progression stands as a critical step for the development of novel therapies. Through an inter-species approach, this study provides evidence of the clinical and functional role of the transcription factor FOSL1 in cholangiocarcinoma. Moreover, we report that downstream effectors of FOSL1 are susceptible to pharmacological inhibition, thus providing new opportunities for therapeutic intervention

Discovering HIV related information by means of association rules and machine learning

Acquired immunodeficiency syndrome (AIDS) is still one of the main health problems worldwide. It is therefore essential to keep making progress in improving the prognosis and quality of life of affected patients. One way to advance along this pathway is to uncover connections between other disorders associated with HIV/AIDS-so that they can be anticipated and possibly mitigated. We propose to achieve this by using Association Rules (ARs). They allow us to represent the dependencies between a number of diseases and other specific diseases. However, classical techniques systematically generate every AR meeting some minimal conditions on data frequency, hence generating a vast amount of uninteresting ARs, which need to be filtered out. The lack of manually annotated ARs has favored unsupervised filtering, even though they produce limited results. In this paper, we propose a semi-supervised system, able to identify relevant ARs among HIV-related diseases with a minimal amount of annotated training data. Our system has been able to extract a good number of relationships between HIV-related diseases that have been previously detected in the literature but are scattered and are often little known. Furthermore, a number of plausible new relationships have shown up which deserve further investigation by qualified medical experts