Kdm6b Regulates the Generation of Effector CD8+ T Cells by Inducing Chromatin Accessibility in Effector-Associated Genes.

The transcriptional and epigenetic regulation of CD8+ T cell differentiation is critical for balancing pathogen eradication and long-term immunity by effector and memory CTLs, respectively. In this study, we demonstrate that the lysine demethylase 6b (Kdm6b) is essential for the proper generation and function of effector CD8+ T cells during acute infection and tumor eradication. We found that cells lacking Kdm6b (by either T cell-specific knockout mice or knockdown using short hairpin RNA strategies) show an enhanced generation of memory precursor and early effector cells upon acute viral infection in a cell-intrinsic manner. We also demonstrate that Kdm6b is indispensable for proper effector functions and tumor protection, and that memory CD8+ T cells lacking Kdm6b displayed a defective recall response. Mechanistically, we identified that Kdm6b, through induction of chromatin accessibility in key effector-associated gene loci, allows for the proper generation of effector CTLs. Our results pinpoint the essential function of Kdm6b in allowing chromatin accessibility in effector-associated genes, and identify Kdm6b as a potential target for therapeutics in diseases with dysregulated effector responses.

ACE2 Expression Is Increased in the Lungs of Patients With Comorbidities Associated With Severe COVID-19.

Patients who died from COVID-19 often had comorbidities, such as hypertension, diabetes, and chronic obstructive lung disease. Although angiotensin-converting enzyme 2 (ACE2) is crucial for SARS-CoV-2 to bind and enter host cells, no study has systematically assessed the ACE2 expression in the lungs of patients with these diseases. Here, we analyzed over 700 lung transcriptome samples from patients with comorbidities associated with severe COVID-19 and found that ACE2 was highly expressed in these patients compared to control individuals. This finding suggests that patients with such comorbidities may have higher chances of developing severe COVID-19. Correlation and network analyses revealed many potential regulators of ACE2 in the human lung, including genes related to histone modifications, such as HAT1, HDAC2, and KDM5B. Our systems biology approach offers a possible explanation for increased COVID-19 severity in patients with certain comorbidities.

Prediction of Poor Response to Neoadjuvant Chemoradiation in Patients With Rectal Cancer Using a DNA Repair Deregulation Score: Picking the Losers Instead of the Winners.

BACKGROUND: Patients with rectal cancer may undergo neoadjuvant chemoradiation even in early stages in an attempt to achieve complete clinical response and undergo organ preservation. However, prediction of tumor response is unavailable. In this setting, accurate identification of poor responders could spare patients with early stage disease from potentially unnecessary chemoradiation. OBJECTIVE: This study focused on development/test of a score based on DNA repair gene expression to predict response to neoadjuvant chemoradiation in patients with rectal cancer. DESIGN: Pretreatment biopsy samples from patients with rectal cancer undergoing neoadjuvant chemoradiation were collected and underwent gene expression analysis using RNA-Seq (test cohort). A score was constructed using 8 differentially expressed DNA repair genes between good (complete clinical) and poor responders (incomplete clinical) to treatment. The score was validated in 2 independent cohorts of patients undergoing similar treatment strategies and using quantitative polymerase chain reaction and microarray gene expression data. SETTINGS: This was a retrospective analysis of gene expression data from 3 independent institutions. PATIENTS: Patients with rectal cancer undergoing neoadjuvant chemoradiation (50.4-54.0 Gy and 5-fluorouracil-based chemotherapy) were eligible. Patients with complete clinical response, complete pathological response, or ≤10% residual cancer cells were considered good responders. Patients with >10% residual cancer cells were considered poor responders. The test cohort included 25 patients (16 poor responders). Validation cohort 1 included 28 patients (18 poor responders), and validation cohort 2 included 46 patients (22 poor responders). MAIN OUTCOMES MEASURES: Response was correlated with the DNA repair score calculated using the expression levels of 8 DNA repair genes. DNA repair score sensitivity, specificity, and positive and negative predictive values were determined in test and validation cohorts. RESULTS: Poor responders had significantly lower DNA repair scores when compared with good responders across all 3 cohorts, regardless of the gene expression platform used. A low score correctly predicted poor response in 93%, 90%, and 71% in test, validation 1, and validation 2 cohorts. LIMITATIONS: This study was limited by its small sample size, different gene expression platforms, and treatment regimens across different cohorts used. CONCLUSIONS: A DNA repair gene score may predict patients likely to have poor response to chemoradiation. This score may be a relevant tool to be investigated in future studies focused on chemoradiation used in the context of organ preservation. See Video Abstract at http://links.lww.com/DCR/B104. PREDICCIÓN DE RESPUESTA DEFICIENTE A LA RADIO-QUIMIOTERAPIA NEOADYUVANTE EN PACIENTES CON CÁNCER RECTAL UTILIZANDO UNA PUNTUACIÓN DE DESREGULACIÓN DE REPARACIÓN DE ADN: ESCOGER LOS PERDEDORES EN LUGAR DE LOS GANADORES: Los pacientes con cáncer rectal pueden someterse a radio-quimioterapia neoadyuvante incluso en estadios tempranos en el intento por lograr una respuesta clínica completa y permitir una preservación de órgano. Sin embargo, aun no existen herramientas disponible para la prediccion de la respuesta tumoral al tratamiento. En este contexto, la identificación precisa de los tumores con mala respuesta al tratamiento podría evitar que los pacientes con enfermedad en estadio temprano sean sometidos a radio-quimioterapia potencialmente innecesaria.Desarrollo / testeo de una puntuación basada en la expresión genes reparadores del ADN para predecir la respuesta a la nCRT en pacientes con cáncer rectal.Se recogieron muestras de biopsia de pre-tratamiento de pacientes con cáncer rectal sometidos a radio-quimioterapia neoadyuvante y se les realizó un análisis de expresión génica utilizando RNAseq (cohorte de prueba). Se construyó una puntuación utilizando 8 genes de reparación de ADN expresados diferencialmente entre buenos (respuesta clinica completa) y pobres respondedores (respuesta clinica incompleta) al tratamiento. La puntuación se validó en 2 cohortes independientes de pacientes sometidos a estrategias de tratamiento similares y utilizando qPCR y datos de expresión de genes en chips ADN (biotecnología -microarrays).Análisis retrospectivo de los datos de expresión génica de 3 instituciones independientes.Fueron incluidos aquellos pacientes con cáncer rectal sometidos a radio-quimioterapia neoadyuvante (50,4-54 Gy y quimioterapia basada en 5FU). Los pacientes con respuesta clínica completa, respuesta patológica completa o ≤10% de células cancerosas residuales se consideraron buenos respondedores. Los pacientes con> 10% de células cancerosas residuales se consideraron de respuesta deficiente. La cohorte de prueba incluyó a 25 pacientes (16 respondedores pobres). La cohorte de validación n. ° 1 incluyó a 28 pacientes (18 respondedores pobres) y la cohorte de validación n. ° 2 incluyó a 46 pacientes (22 respondedores pobres).La respuesta se correlacionó con la puntuación de reparación de ADN calculada utilizando los niveles de expresión de 8 genes de reparación de ADN. La sensibilidad del puntaje de reparación del ADN, la especificidad, los valores predictivos positivos y negativos se determinaron en las cohortes de prueba y validación.Los malos respondedores tuvieron puntuaciones de reparación de ADN significativamente más bajas en comparación con los buenos respondedores en las 3 cohortes, independientemente de la plataforma de expresión génica utilizada. Una puntuación baja predijo correctamente una respuesta pobre en el 93%, 90% y 71% en las cohortes de prueba, validación n. ° 1 y validación n. ° 2, respectivamente.Pequeño tamaño de la muestra, diferentes plataformas de expresión génica y regímenes de tratamiento en diferentes cohortes utilizadas.La puntuacion basada en genes de reparación del ADN puede predecir los pacientes con respuesta pobre a la radio-quimioterapia. Esta puntuación puede ser una herramienta relevante para investigar en futuros estudios centrados en la radio-quimioterapia utilizada en el contexto de la preservación de órganos. Consulte Video Resumen en http://links.lww.com/DCR/B104. (Traducción-Dr. Xavier Delgadillo and Dr. Laura Melina Fernandez).

Epigenetically mediated inhibition of S-adenosylhomocysteine hydrolase and the associated dysregulation of 1-carbon metabolism in nonalcoholic steatohepatitis and hepatocellular carcinoma.

The substantial rise in the prevalence of nonalcoholic steatohepatitis (NASH), an advanced form of nonalcoholic fatty liver disease, and the strong association between NASH and the development of hepatocellular carcinoma indicate the urgent need for a better understanding of the underlying mechanisms. In the present study, by using the Stelic animal model of NASH and NASH-derived liver carcinogenesis, we investigated the role of the folate-dependent 1-carbon metabolism in the pathogenesis of NASH. We demonstrated that advanced NASH and NASH-related liver carcinogenesis are characterized by a significant dysregulation of 1-carbon homeostasis, with diminished expression of key 1-carbon metabolism genes, especially a marked inhibition of the S-adenosylhomocysteine hydrolase ( Ahcy) gene and an increased level of S-adenosyl-l-homocysteine (SAH). The reduction in Ahcy expression was associated with gene-specific cytosine DNA hypermethylation and enrichment of the gene promoter by trimethylated histone H3 lysine 27 and deacetylated histone H4 lysine 16, 2 main transcription-inhibiting markers. These results indicate that epigenetically mediated inhibition of Ahcy expression may be a driving force in causing SAH elevation and subsequent downstream disturbances in transsulfuration and transmethylation pathways during the development and progression of NASH.-Pogribny, I. P., Dreval, K., Kindrat, I., Melnyk, S., Jimenez, L., de Conti, A., Tryndyak, V., Pogribna, M., Ortega, J. F., James, S. J., Rusyn, I., Beland, F. A. Epigenetically mediated inhibition of S-adenosylhomocysteine hydrolase and the associated dysregulation of 1-carbon metabolism in nonalcoholic steatohepatitis and hepatocellular carcinoma.

Medical decision support system using weakly-labeled lung CT scans.

Purpose: Determination and development of an effective set of models leveraging Artificial Intelligence techniques to generate a system able to support clinical practitioners working with COVID-19 patients. It involves a pipeline including classification, lung and lesion segmentation, as well as lesion quantification of axial lung CT studies. Approach: A deep neural network architecture based on DenseNet is introduced for the classification of weakly-labeled, variable-sized (and possibly sparse) axial lung CT scans. The models are trained and tested on aggregated, publicly available data sets with over 10 categories. To further assess the models, a data set was collected from multiple medical institutions in Colombia, which includes healthy, COVID-19 and patients with other diseases. It is composed of 1,322 CT studies from a diverse set of CT machines and institutions that make over 550,000 slices. Each CT study was labeled based on a clinical test, and no per-slice annotation took place. This enabled a classification into Normal vs. Abnormal patients, and for those that were considered abnormal, an extra classification step into Abnormal (other diseases) vs. COVID-19. Additionally, the pipeline features a methodology to segment and quantify lesions of COVID-19 patients on the complete CT study, enabling easier localization and progress tracking. Moreover, multiple ablation studies were performed to appropriately assess the elements composing the classification pipeline. Results: The best performing lung CT study classification models achieved 0.83 accuracy, 0.79 sensitivity, 0.87 specificity, 0.82 F1 score and 0.85 precision for the Normal vs. Abnormal task. For the Abnormal vs COVID-19 task, the model obtained 0.86 accuracy, 0.81 sensitivity, 0.91 specificity, 0.84 F1 score and 0.88 precision. The ablation studies showed that using the complete CT study in the pipeline resulted in greater classification performance, restating that relevant COVID-19 patterns cannot be ignored towards the top and bottom of the lung volume. Discussion: The lung CT classification architecture introduced has shown that it can handle weakly-labeled, variable-sized and possibly sparse axial lung studies, reducing the need for expert annotations at a per-slice level. Conclusions: This work presents a working methodology that can guide the development of decision support systems for clinical reasoning in future interventionist or prospective studies.

Acid pH Increases SARS-CoV-2 Infection and the Risk of Death by COVID-19.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can infect a broad range of human tissues by using the host receptor angiotensin-converting enzyme 2 (ACE2). Individuals with comorbidities associated with severe COVID-19 display higher levels of ACE2 in the lungs compared to those without comorbidities, and conditions such as cell stress, elevated glucose levels and hypoxia may also increase the expression of ACE2. Here, we showed that patients with Barrett's esophagus (BE) have a higher expression of ACE2 in BE tissues compared to normal squamous esophagus, and that the lower pH associated with BE may drive this increase in expression. Human primary monocytes cultured in reduced pH displayed increased ACE2 expression and higher viral load upon SARS-CoV-2 infection. We also showed in two independent cohorts of 1,357 COVID-19 patients that previous use of proton pump inhibitors is associated with 2- to 3-fold higher risk of death compared to those not using the drugs. Our work suggests that pH has a great influence on SARS-CoV-2 Infection and COVID-19 severity.

Butyrate-containing structured lipids inhibit RAC1 and epithelial-to-mesenchymal transition markers: a chemopreventive mechanism against hepatocarcinogenesis.

Hepatocellular carcinoma (HCC) is one of the most aggressive human cancers. The rising incidence of HCC worldwide and its resistance to pharmacotherapy indicate that the prevention of HCC development may be the most impactful strategy to improve HCC-related morbidity and mortality. Among the broad range of chemopreventive agents, the use of dietary and nutritional agents is an attractive and promising approach; however, a better understanding of the mechanisms of their potential cancer suppressive action is needed to justify their use. In the present study, we investigated the underlying molecular pathways associated with the previously observed suppressive effect of butyrate-containing structured lipids (STLs) against liver carcinogenesis using a rat "resistant hepatocyte" model of hepatocarcinogenesis that resembles the development of HCC in humans. Using whole transcriptome analysis, we demonstrate that the HCC suppressive effect of butyrate-containing STLs is associated with the inhibition of the cell migration, cytoskeleton organization, and epithelial-to-mesenchymal transition (EMT), mediated by the reduced levels of RACGAP1 and RAC1 proteins. Mechanistically, the inhibition of the Racgap1 and Rac1 oncogenes is associated with cytosine DNA and histone H3K27 promoter methylation. Inhibition of the RACGAP1/RAC1 oncogenic signaling pathways and EMT may be a valuable approach for liver cancer prevention.

ACE2 Expression is Increased in the Lungs of Patients with Comorbidities Associated with Severe COVID-19.

The pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has resulted in several thousand deaths worldwide in just a few months. Patients who died from Coronavirus disease 2019 (COVID-19) often had comorbidities, such as hypertension, diabetes, and chronic obstructive lung disease. The angiotensin-converting enzyme 2 (ACE2) was identified as a crucial factor that facilitates SARS-CoV2 to bind and enter host cells. To date, no study has assessed the ACE2 expression in the lungs of patients with these diseases. Here, we analyzed over 700 lung transcriptome samples of patients with comorbidities associated with severe COVID-19 and found that ACE2 was highly expressed in these patients, compared to control individuals. This finding suggests that patients with such comorbidities may have higher chances of developing severe COVID-19. We also found other genes, such as RAB1A, that can be important for SARS-CoV-2 infection in the lung. Correlation and network analyses revealed many potential regulators of ACE2 in the human lung, including genes related to histone modifications, such as HAT1, HDAC2, and KDM5B. In fact, epigenetic marks found in ACE2 locus were compatible to with those promoted by KDM5B. Our systems biology approach offers a possible explanation for increase of COVID-19 severity in patients with certain comorbidities.

Gene Expression and DNA Methylation Alterations in the Glycine N-Methyltransferase Gene in Diet-Induced Nonalcoholic Fatty Liver Disease-Associated Carcinogenesis.

Nonalcoholic fatty liver disease (NAFLD) is becoming a major etiological risk factor for hepatocellular carcinoma (HCC) in the United States and other Western countries. In this study, we investigated the role of gene-specific promoter cytosine DNA methylation and gene expression alterations in the development of NAFLD-associated HCC in mice using (1) a diet-induced animal model of NAFLD, (2) a Stelic Animal Model of nonalcoholic steatohepatitis-derived HCC, and (3) a choline- and folate-deficient (CFD) diet (CFD model). We found that the development of NAFLD and its progression to HCC was characterized by down-regulation of glycine N-methyltransferase (Gnmt) and this was mediated by progressive Gnmt promoter cytosine DNA hypermethylation. Using a panel of genetically diverse inbred mice, we observed that Gnmt down-regulation was an early event in the pathogenesis of NAFLD and correlated with the extent of the NAFLD-like liver injury. Reduced GNMT expression was also found in human HCC tissue and liver cancer cell lines. In in vitro experiments, we demonstrated that one of the consequences of GNMT inhibition was an increase in genome methylation facilitated by an elevated level of S-adenosyl-L-methionine. Overall, our findings suggest that reduced Gnmt expression caused by promoter hypermethylation is one of the key molecular events in the development of NAFLD-derived HCC and that assessing Gnmt methylation level may be useful for disease stratification.

IRE1α-XBP1 signaling in leukocytes controls prostaglandin biosynthesis and pain.

Inositol-requiring enzyme 1[α] (IRE1[α])-X-box binding protein spliced (XBP1) signaling maintains endoplasmic reticulum (ER) homeostasis while controlling immunometabolic processes. Yet, the physiological consequences of IRE1α-XBP1 activation in leukocytes remain unexplored. We found that induction of prostaglandin-endoperoxide synthase 2 (Ptgs2/Cox-2) and prostaglandin E synthase (Ptges/mPGES-1) was compromised in IRE1α-deficient myeloid cells undergoing ER stress or stimulated through pattern recognition receptors. Inducible biosynthesis of prostaglandins, including the pro-algesic mediator prostaglandin E2 (PGE2), was decreased in myeloid cells that lack IRE1α or XBP1 but not other ER stress sensors. Functional XBP1 transactivated the human PTGS2 and PTGES genes to enable optimal PGE2 production. Mice that lack IRE1α-XBP1 in leukocytes, or that were treated with IRE1α inhibitors, demonstrated reduced pain behaviors in PGE2-dependent models of pain. Thus, IRE1α-XBP1 is a mediator of prostaglandin biosynthesis and a potential target to control pain.

Unsupervised fuzzy binning of metagenomic sequence fragments on three-dimensional Barnes-Hut t-Stochastic Neighbor Embeddings.

Shotgun metagenomic studies attempt to reconstruct population genome sequences from complex microbial communities. In some traditional genome demarcation approaches, high-dimensional sequence data are embedded into two-dimensional spaces and subsequently binned into candidate genomic populations. One such approach uses a combination of the Barnes-Hut approximation and the $t -$Stochastic Neighbor Embedding (BH-SNE) algorithm for dimensionality reduction of DNA sequence data pentamer profiles; and demarcation of groups based on Gaussian mixture models within humanimposed boundaries. We found that genome demarcation from three-dimensional BH-SNE embeddings consistently results in more accurate binnings than 2-D embeddings. We further addressed the lack of a priori population number information by developing an unsupervised binning approach based on the Subtractive and Fuzzy c-means (FCM) clustering algorithms combined with internal clustering validity indices. Lastly, we addressed the subject of shared membership of individual data objects in a mixed community by assigning a degree of membership to individual objects using the FCM algorithm, and discriminated between confidently binned and uncertain sequence data objects from the community for subsequent biological interpretation. The binning of metagenome sequence fragments according to thresholds in the degree of membership opens the door for the identification of horizontally transferred elements and other genomic regions of uncertain assignment in which biologically meaningful information resides. The reported approach improves the unsupervised genome demarcation of populations within complex communities, increases the confidence in the coherence of the binned elements, and enables the identification of evolutionary processes ignored in hard-binning approaches in shotgun metagenomic studies.

Bio-EdIP: An automatic approach for in vitro cell confluence images quantification.

BACKGROUND AND OBJECTIVES: Cell imaging is a widely-employed technique to analyze multiple biological processes. Therefore, simple, accurate and quantitative tools are needed to understand cellular events. For this purpose, Bio-EdIP was developed as a user-friendly tool to quantify confluence levels using cell culture images. METHODS: The proposed algorithm combines a pre-processing step with subsequent stages that involve local processing techniques and a morphological reconstruction-based segmentation algorithm. Segmentation performance was assessed in three constructed image sets, comparing F-measure scores and AUC values (ROC analysis) for Bio-EdIP, its previous version and TScratch. Furthermore, segmentation results were compared with published algorithms using eight public benchmarks. RESULTS: Bio-EdIP automatically segmented cell-free regions from images of in vitro cell culture. Based on mean F-measure scores and ROC analysis, Bio-EdIP conserved a high performance regardless of image characteristics of the constructed dataset, when compared with its previous version and TScratch. Although acquisition quality of the public dataset affected Bio-EdIP segmentation, performance was better in two out of eight public sets. CONCLUSIONS: Bio-EdIP is a user-friendly interface, which is useful for the automatic analysis of confluence levels and cell growth processes using in vitro cell culture images. Here, we also presented new manually annotated data for algorithms evaluation.

Comprehensive cancer-gene panels can be used to estimate mutational load and predict clinical benefit to PD-1 blockade in clinical practice.

Cancer gene panels (CGPs) are already used in clinical practice to match tumor's genetic profile with available targeted therapies. We aimed to determine if CGPs could also be applied to estimate tumor mutational load and predict clinical benefit to PD-1 and CTLA-4 checkpoint blockade therapy. Whole-exome sequencing (WES) mutation data obtained from melanoma and non-small cell lung cancer (NSCLC) patients published by Snyder et al. 2014 and Rizvi et al. 2015, respectively, were used to select nonsynonymous somatic mutations occurring in genes included in the Foundation Medicine Panel (FM-CGP) and in our own Institutional Panel (HSL-CGP). CGP-mutational load was calculated for each patient using both panels and was associated with clinical outcomes as defined and reported in the original articles. Higher CGP-mutational load was observed in NSCLC patients presenting durable clinical benefit (DCB) to PD-1 blockade (FM-CGP P=0.03, HSL-CGP P=0.01). We also observed that 69% of patients with high CGP-mutational load experienced DCB to PD-1 blockade, as compared to 20% of patients with low CGP-mutational load (FM-CGP and HSL-CGP P=0.01). Noteworthy, predictive accuracy of CGP-mutational load for DCB was not statistically different from that estimated by WES sequencing (P=0.73). Moreover, a high CGP-mutational load was significantly associated with progression-free survival (PFS) in patients treated with PD-1 blockade (FM-CGP P=0.005, HR 0.27, 95% IC 0.105 to 0.669; HSL-CGP P=0.008, HR 0.29, 95% IC 0.116 to 0.719). Similar associations between CGP-mutational load and clinical benefit to CTLA-4 blockade were not observed. In summary, our data reveals that CGPs can be used to estimate mutational load and to predict clinical benefit to PD-1 blockade, with similar accuracy to that reported using WES.