Targeting RAS-ERK pathway alterations with MEK inhibitors to improve chemosensitivity in high grade serous ovarian cancers.

OBJECTIVE: Assess if MEK inhibitor blockade of RAS-ERK pathway adaptive response in high grade serous ovarian cancers (HGSOC) improves platinum sensitivity. METHODS: Three HGSOC cell lines and three patient derived organoid (PDOs) samples from ascites of platinum resistant HGSOC patients were collected. Cell lines and PDOs were exposed to carboplatin and MEK inhibitors cobimetinib or trametinib. Cytotoxic effects of MEK inhibitors alone or combined with carboplatin were established. Western blots demonstrated RAS-ERK pathway blockage after MEK inhibitor treatment. RNA sequencing assessed gene expression after MEK inhibitor treatment. Cell line NF1 gene knockdown was performed with corresponding chemosensitivity levels. RESULTS: High carboplatin IC50 levels indicated platinum resistance in cell lines and PDOs. Cobimetinib induced cytotoxicity in cell lines and PDOs, while trametinib was less effective. Western blot confirmed MEK-ERK pathway blockage at minimal concentrations of MEK inhibitors in cell lines and PDOs. Phosphorylated-ERK levels of untreated cells indicated higher levels of RAS-ERK pathway activation in OVSAHO and OVCAR7 compared to OVCAR3. OVSAHO harbors a NF1 mutation and had highest levels of RAS-ERK activation. Cotreatment with carboplatin and MEK inhibitors showed varying synergistic cytotoxic effects at different combinations. Synergistic effect was most prominent in the OVSAHO carboplatin and cobimetinib combination. RNA sequencing identified downregulation of c-MYC and FOXM1 gene expression after MEK inhibitor treatment. NF1 gene knockdown showed an acquired increased IC50 compared to parental cells. CONCLUSION: MEK inhibitors block RAS-ERK pathways in platinum resistant HGSOC cells and PDOs. MEK inhibitors with carboplatin have select synergistic effects which may indicate a strategy to improve platinum sensitivity.

Dynamic evaluation of blood immune cells predictive of response to immune checkpoint inhibitors in NSCLC by multicolor spectrum flow cytometry.

Introduction: Immune checkpoint inhibitors (ICIs) only benefit a subset of cancer patients, underlining the need for predictive biomarkers for patient selection. Given the limitations of tumor tissue availability, flow cytometry of peripheral blood mononuclear cells (PBMCs) is considered a noninvasive method for immune monitoring. This study explores the use of spectrum flow cytometry, which allows a more comprehensive analysis of a greater number of markers using fewer immune cells, to identify potential blood immune biomarkers and monitor ICI treatment in non-small-cell lung cancer (NSCLC) patients. Methods: PBMCs were collected from 14 non-small-cell lung cancer (NSCLC) patients before and after ICI treatment and 4 healthy human donors. Using spectrum flow cytometry, 24 immune cell markers were simultaneously monitored using only 1 million PBMCs. The results were also compared with those from clinical flow cytometry and bulk RNA sequencing analysis. Results: Our findings showed that the measurement of CD4+ and CD8+ T cells by spectrum flow cytometry matched well with those by clinical flow cytometry (Pearson R ranging from 0.75 to 0.95) and bulk RNA sequencing analysis (R=0.80, P=1.3 x 10-4). A lower frequency of CD4+ central memory cells before treatment was associated with a longer median progression-free survival (PFS) [Not reached (NR) vs. 5 months; hazard ratio (HR)=8.1, 95% confidence interval (CI) 1.5-42, P=0.01]. A higher frequency of CD4-CD8- double-negative (DN) T cells was associated with a longer PFS (NR vs. 4.45 months; HR=11.1, 95% CI 2.2-55.0, P=0.003). ICIs significantly changed the frequency of cytotoxic CD8+PD1+ T cells, DN T cells, CD16+CD56dim and CD16+CD56- natural killer (NK) cells, and CD14+HLDRhigh and CD11c+HLADR + monocytes. Of these immune cell subtypes, an increase in the frequency of CD16+CD56dim NK cells and CD14+HLADRhigh monocytes after treatment compared to before treatment were associated with a longer PFS (NR vs. 5 months, HR=5.4, 95% CI 1.1-25.7, P=0.03; 7.8 vs. 3.8 months, HR=5.7, 95% CI 169 1.0-31.7, P=0.04), respectively. Conclusion: Our preliminary findings suggest that the use of multicolor spectrum flow cytometry helps identify potential blood immune biomarkers for ICI treatment, which warrants further validation.

Labyrinthin Expression Is Associated with Poor Prognosis in Patients with Non-Small-Cell Lung Cancer.

To determine Labyrinthin (LAB) expression in non-small-cell lung cancer (NSCLC), we immunostained and scored for LAB immunohistochemistry (IHC) expression on sections of tissue microarrays (TMAs) prepared from 256 archival tissue blocks of NSCLC. Propensity-score-weighted Kaplan-Meier curves and weighted Cox models were used to associate LAB expression with overall survival. LAB mRNA expression was assessed in The Cancer Genome Atlas (TCGA) and correlated with clinical phenotype and outcome. Positive LAB IHC expression (>5% of tumor cells) was detected in 208/256 (81.3%) of NSCLC samples, and found in both lung adenocarcinomas (LUAD) and lung squamous cell cancer (LUSC). LAB positivity was associated with poor overall survival (HR = 3.56, 95% CI: 2.3-5.4; p < 0.0001) and high tumor differentiation grade or metastasis compared with negative LAB expression. Univariant and multivariate survival analyses demonstrated LAB expression as an independent prognostic factor for NSCLC patients. LAB RNA expression in TCGA-LUAD was higher in primary and advanced-stage tumors than in normal tissue, and was associated with poorer overall survival. No significant differences or associations were found with LAB RNA expression in TCGA-LUSC. The LAB IHC assay is being used to identify candidate cancer patients for the first-in-human phase I trial evaluating the LAB vaccines (UCDCC#296, NCT051013560).

Longitudinal profiling in patients undergoing cardiac surgery reveals postoperative changes in DNA methylation.

BACKGROUND: Cardiac surgery and cardiopulmonary bypass induce a substantial immune and inflammatory response, the overactivation of which is associated with significant pulmonary, cardiovascular, and neurologic complications. Commensurate with the immune and inflammatory response are changes in the heart and vasculature itself, which together drive postoperative complications through mechanisms that are poorly understood. Longitudinal DNA methylation profiling has the potential to identify changes in gene regulatory mechanisms that are secondary to surgery and to identify molecular processes that predict and/or cause postoperative complications. In this study, we measure DNA methylation in preoperative and postoperative whole blood samples from 96 patients undergoing cardiac surgery on cardiopulmonary bypass. RESULTS: While the vast majority of DNA methylation is unchanged by surgery after accounting for changes in cell-type composition, we identify several loci with statistically significant postoperative changes in methylation. Additionally, two of these loci are associated with new-onset postoperative atrial fibrillation, a significant complication after cardiac surgery. Paired statistical analysis, use of FACS data to support sufficient control of cell-type heterogeneity, and measurement of IL6 levels in a subset of patients add rigor to this analysis, allowing us to distinguish cell-type variability from actual changes in methylation. CONCLUSIONS: This study identifies significant changes in DNA methylation that occur immediately after cardiac surgery and demonstrates that these acute alterations in DNA methylation have the granularity to identify processes associated with major postoperative complications. This research also establishes methods for controlling for cell-type variability in a large human cohort that may be useful to deploy in other longitudinal studies of epigenetic marks in the setting of acute and chronic disease.

DNA Methylation-Based Prediction of Post-operative Atrial Fibrillation.

Background: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and post-operative atrial fibrillation (POAF) is a major healthcare burden, contributing to an increased risk of stroke, kidney failure, heart attack and death. Genetic studies have identified associations with AF, but no molecular diagnostic exists to predict POAF based on pre-operative measurements. Such a tool would be of great value for perioperative planning to improve patient care and reduce healthcare costs. In this pilot study of epigenetic precision medicine in the perioperative period, we carried out bisulfite sequencing to measure DNA methylation status in blood collected from patients prior to cardiac surgery to identify biosignatures of POAF. Methods: We enrolled 221 patients undergoing cardiac surgery in this prospective observational study. DNA methylation measurements were obtained from blood samples drawn from awake patients prior to surgery. After controlling for clinical and methylation covariates, we analyzed DNA methylation loci in the discovery cohort of 110 patients for association with POAF. We also constructed predictive models for POAF using clinical and DNA methylation data. We subsequently performed targeted analyses of a separate cohort of 101 cardiac surgical patients to measure the methylation status solely of significant methylation loci in the discovery cohort. Results: A total of 47 patients in the discovery cohort (42.7%) and 43 patients in the validation cohort (42.6%) developed POAF. We identified 12 CpGs that were statistically significant in the discovery cohort after correcting for multiple hypothesis testing. Of these sites, 6 were amenable to targeted bisulfite sequencing and chr16:24640902 was statistically significant in the validation cohort. In addition, the methylation POAF prediction model had an AUC of 0.79 in the validation cohort. Conclusions: We have identified DNA methylation biomarkers that can predict future occurrence of POAF associated with cardiac surgery. This research demonstrates the use of precision medicine to develop models combining epigenomic and clinical data to predict disease.

Quinacrine Induces Nucleolar Stress in Treatment-Refractory Ovarian Cancer Cell Lines.

A considerable subset of gynecologic cancer patients experience disease recurrence or acquired resistance, which contributes to high mortality rates in ovarian cancer (OC). Our prior studies showed that quinacrine (QC), an antimalarial drug, enhanced chemotherapy sensitivity in treatment-refractory OC cells, including artificially generated chemoresistant and high-grade serous OC cells. In this study, we investigated QC-induced transcriptomic changes to uncover its cytotoxic mechanisms of action. Isogenic pairs of OC cells generated to be chemoresistant and their chemosensitive counterparts were treated with QC followed by RNA-seq analysis. Validation of selected expression results and database comparison analyses indicated the ribosomal biogenesis (RBG) pathway is inhibited by QC. RBG is commonly upregulated in cancer cells and is emerging as a drug target. We found that QC attenuates the in vitro and in vivo expression of nucleostemin (NS/GNL3), a nucleolar RBG and DNA repair protein, and the RPA194 catalytic subunit of Pol I that results in RBG inhibition and nucleolar stress. QC promotes the redistribution of fibrillarin in the form of extranuclear foci and nucleolar caps, an indicator of nucleolar stress conditions. In addition, we found that QC-induced downregulation of NS disrupted homologous recombination repair both by reducing NS protein levels and PARylation resulting in reduced RAD51 recruitment to DNA damage. Our data suggest that QC inhibits RBG and this inhibition promotes DNA damage by directly downregulating the NS-RAD51 interaction. Additionally, QC showed strong synergy with PARP inhibitors in OC cells. Overall, we found that QC downregulates the RBG pathway, induces nucleolar stress, supports the increase of DNA damage, and sensitizes cells to PARP inhibition, which supports new therapeutic stratagems for treatment-refractory OC. Our work offers support for targeting RBG in OC and determines NS to be a novel target for QC.

Systematic evaluation of transcriptomics-based deconvolution methods and references using thousands of clinical samples.

Estimating cell type composition of blood and tissue samples is a biological challenge relevant in both laboratory studies and clinical care. In recent years, a number of computational tools have been developed to estimate cell type abundance using gene expression data. Although these tools use a variety of approaches, they all leverage expression profiles from purified cell types to evaluate the cell type composition within samples. In this study, we compare 12 cell type quantification tools and evaluate their performance while using each of 10 separate reference profiles. Specifically, we have run each tool on over 4000 samples with known cell type proportions, spanning both immune and stromal cell types. A total of 12 of these represent in vitro synthetic mixtures and 300 represent in silico synthetic mixtures prepared using single-cell data. A final 3728 clinical samples have been collected from the Framingham cohort, for which cell populations have been quantified using electrical impedance cell counting. When tools are applied to the Framingham dataset, the tool Estimating the Proportions of Immune and Cancer cells (EPIC) produces the highest correlation, whereas Gene Expression Deconvolution Interactive Tool (GEDIT) produces the lowest error. The best tool for other datasets is varied, but CIBERSORT and GEDIT most consistently produce accurate results. We find that optimal reference depends on the tool used, and report suggested references to be used with each tool. Most tools return results within minutes, but on large datasets runtimes for CIBERSORT can exceed hours or even days. We conclude that deconvolution methods are capable of returning high-quality results, but that proper reference selection is critical.

The Gene Expression Deconvolution Interactive Tool (GEDIT): accurate cell type quantification from gene expression data.

BACKGROUND: The cell type composition of heterogeneous tissue samples can be a critical variable in both clinical and laboratory settings. However, current experimental methods of cell type quantification (e.g., cell flow cytometry) are costly, time consuming and have potential to introduce bias. Computational approaches that use expression data to infer cell type abundance offer an alternative solution. While these methods have gained popularity, most fail to produce accurate predictions for the full range of platforms currently used by researchers or for the wide variety of tissue types often studied. RESULTS: We present the Gene Expression Deconvolution Interactive Tool (GEDIT), a flexible tool that utilizes gene expression data to accurately predict cell type abundances. Using both simulated and experimental data, we extensively evaluate the performance of GEDIT and demonstrate that it returns robust results under a wide variety of conditions. These conditions include multiple platforms (microarray and RNA-seq), tissue types (blood and stromal), and species (human and mouse). Finally, we provide reference data from 8 sources spanning a broad range of stromal and hematopoietic types in both human and mouse. GEDIT also accepts user-submitted reference data, thus allowing the estimation of any cell type or subtype, provided that reference data are available. CONCLUSIONS: GEDIT is a powerful method for evaluating the cell type composition of tissue samples and provides excellent accuracy and versatility compared to similar tools. The reference database provided here also allows users to obtain estimates for a wide variety of tissue samples without having to provide their own data.

Effect of the p53 P72R Polymorphism on Mutant TP53 Allele Selection in Human Cancer.

BACKGROUND: TP53 mutations occur in more than 50% of cancers. We sought to determine the effect of the intragenic P72R single nucleotide polymorphism (SNP; rs1042522) on the oncogenic properties of mutant p53. METHODS: P72R allelic selection in tumors was determined from genotype calls and a Gaussian distributed mixture model. The SNP effect on mutant p53 was determined in p53-negative cancer cell lines. RNA-sequencing, chromatin immunoprecipitation, and survival analysis were performed to describe the SNP effect. All statistical tests were 2-sided. RESULTS: Among 409 patients with germline heterozygous P72R SNP who harbored somatic mutations in TP53, we observed a selection bias against missense TP53 mutants encoding the P72 SNP (P = 1.64 x 10-13). Exogenously expressed hotspot p53 mutants with the P72 SNP were negatively selected in cancer cells. Gene expression analyses showed the enrichment of p53 pathway genes and inflammatory genes in cancer cells transduced with mutants encoding P72 SNP. Immune gene signature is enriched in patients harboring missense TP53 mutations with homozygous P72 SNP. These patients have improved overall survival as compared with those with the R72 SNP (P = .04). CONCLUSION: This is the largest study demonstrating a selection against the P72 SNP. Missense p53 mutants with the P72 SNP retain partial wild-type tumor-suppressive functions, which may explain the selection bias against P72 SNP across cancer types. Ovarian cancer patients with the P72 SNP have a better prognosis than with the R72 SNP. Our study describes a previously unknown role through which the rs1042522 SNP modifies tumor suppressor activities of mutant p53 in patients.

The P72R Polymorphism in R248Q/W p53 Mutants Modifies the Mutant Effect on Epithelial to Mesenchymal Transition Phenotype and Cell Invasion via CXCL1 Expression.

High-grade serous carcinoma (HGSC), the most lethal subtype of epithelial ovarian cancer (EOC), is characterized by widespread TP53 mutations (>90%), most of which are missense mutations (>70%). The objective of this study was to investigate differential transcriptional targets affected by a common germline P72R SNP (rs1042522) in two p53 hotspot mutants, R248Q and R248W, and identify the mechanism through which the P72R SNP affects the neomorphic properties of these mutants. Using isogenic cell line models, transcriptomic analysis, xenografts, and patient data, we found that the P72R SNP modifies the effect of p53 hotspot mutants on cellular morphology and invasion properties. Most importantly, RNA sequencing studies identified CXCL1 a critical factor that is differentially affected by P72R SNP in R248Q and R248W mutants and is responsible for differences in cellular morphology and functional properties observed in these p53 mutants. We show that the mutants with the P72 SNP promote a reversion of the EMT phenotype to epithelial characteristics, whereas its R72 counterpart promotes a mesenchymal transition via the chemokine CXCL1. These studies reveal a new role of the P72R SNP in modulating the neomorphic properties of p53 mutants via CXCL1, which has significant implications for tumor invasion and metastasis.

The cell fate regulator NUPR1 is induced by Mycobacterium leprae via type I interferon in human leprosy.

The initial interaction between a microbial pathogen and the host immune response influences the outcome of the battle between the host and the foreign invader. Leprosy, caused by the obligate intracellular pathogen Mycobacterium leprae, provides a model to study relevant human immune responses. Previous studies have adopted a targeted approach to investigate host response to M. leprae infection, focusing on the induction of specific molecules and pathways. By measuring the host transcriptome triggered by M. leprae infection of human macrophages, we were able to detect a host gene signature 24-48 hours after infection characterized by specific innate immune pathways involving the cell fate mechanisms autophagy and apoptosis. The top upstream regulator in the M. leprae-induced gene signature was NUPR1, which is found in the M. leprae-induced cell fate pathways. The induction of NUPR1 by M. leprae was dependent on the production of the type I interferon (IFN), IFN-ß. Furthermore, NUPR1 mRNA and protein were upregulated in the skin lesions from patients with the multibacillary form of leprosy. Together, these data indicate that M. leprae induces a cell fate program which includes NUPR1 as part of the host response in the progressive form of leprosy.

Vitamin A Metabolism by Dendritic Cells Triggers an Antimicrobial Response against Mycobacterium tuberculosis.

Epidemiological evidence correlates low serum vitamin A (retinol) levels with increased susceptibility to active tuberculosis (TB); however, retinol is biologically inactive and must be converted into its bioactive form, all-trans retinoic acid (ATRA). Given that ATRA triggers a Niemann-Pick type C2 (NPC2)-dependent antimicrobial response against Mycobacterium tuberculosis, we investigated the mechanism by which the immune system converts retinol into ATRA at the site of infection. We demonstrate that granulocyte-macrophage colony-stimulating factor (GM-CSF)-derived dendritic cells (DCs), but not macrophages, express enzymes in the vitamin A metabolic pathway, including aldehyde dehydrogenase 1 family, member a2 (ALDH1A2) and short-chain dehydrogenase/reductase family, member 9 (DHRS9), enzymes capable of the two-step conversion of retinol into ATRA, which is subsequently released from the cell. Additionally, mRNA and protein expression levels of ALDH1A2 and DC marker CD1B were lower in tuberculosis lung tissues than in normal lung. The conditioned medium from DCs cultured with retinol stimulated antimicrobial activity from M. tuberculosis-infected macrophages, as well as the expression of NPC2 in monocytes, which was blocked by specific inhibitors, including retinoic acid receptor inhibitor (RARi) or N,N-diethylaminobenzaldehyde (DEAB), an ALDH1A2 inhibitor. These results indicate that metabolism of vitamin A by DCs transactivates macrophage antimicrobial responses.IMPORTANCE Tuberculosis (TB) is the leading cause of death by a single infectious agent worldwide. One factor that contributes to the success of the microbe is the deficiency in immunomodulatory nutrients, such as vitamin A (retinol), which are prevalent in areas where TB is endemic. Clinical trials show that restoration of systemic retinol levels in active TB patients is ineffective in mitigating the disease; however, laboratory studies demonstrate that activation of the vitamin A pathway in Mycobacterium tuberculosis-infected macrophages triggers an antimicrobial response. Therefore, the goal of this study was to determine the link between host retinol levels and retinoic acid-mediated antimicrobial responses against M. tuberculosis By combining established in vitro models with in situ studies of lung tissue from TB patients, this study demonstrates that the innate immune system utilizes transcellular metabolism leading to activation between dendritic cells and macrophages as a means to combat the pathogen.

Dual RNA-Seq of Human Leprosy Lesions Identifies Bacterial Determinants Linked to Host Immune Response.

To understand how the interaction between an intracellular bacterium and the host immune system contributes to outcome at the site of infection, we studied leprosy, a disease that forms a clinical spectrum, in which progressive infection by the intracellular bacterium Mycobacterium leprae is characterized by the production of type I IFNs and antibody production. Dual RNA-seq on patient lesions identifies two independent molecular measures of M. leprae, each of which correlates with distinct aspects of the host immune response. The fraction of bacterial transcripts, reflecting bacterial burden, correlates with a host type I IFN gene signature, known to inhibit antimicrobial responses. Second, the bacterial mRNA:rRNA ratio, reflecting bacterial viability, links bacterial heat shock proteins with the BAFF-BCMA host antibody response pathway. Our findings provide a platform for the interrogation of host and pathogen transcriptomes at the site of infection, allowing insight into mechanisms of inflammation in human disease.

Plasticity of antimicrobial and phagocytic programs in human macrophages.

Macrophage (MΦ) polarization is triggered during the innate immune response to defend against microbial pathogens, but can also contribute to disease pathogenesis. In a previous study, we found that interleukin-15 (IL-15) -derived classically activated macrophages (M1 MΦ) have enhanced antimicrobial activity, whereas IL-10-derived alternatively activated macrophages (M2 MΦ) were highly phagocytic but lacked antimicrobial activity. Given that the ability to modulate MΦ polarization from M2 MΦ to M1 MΦ may promote a more effective immune response to infection, we investigated the plasticity of these MΦ programs. Addition of IL-10 to M1 MΦ induced M2-like MΦ, but IL-15 had little effect on M2 MΦ. We determined the set of immune receptors that are present on M2 MΦ, elucidating two candidates for inducing plasticity of M2 MΦ, Toll-like receptor 1 (TLR1) and interferonγ (IFN-γ) receptor 1. Stimulation of M2 MΦ with TLR2/1 ligand (TLR2/1L) or IFN-γ alone was not sufficient to alter M2 MΦ phenotype or function. However, co-addition of TLR2/1L and IFN-γ re-educated M2 MΦ towards the M1 MΦ phenotype, with a decrease in the phagocytosis of lipids and mycobacteria, as well as recovery of the vitamin-D-dependent antimicrobial pathway compared with M2 MΦ maintained in polarizing conditions. Similarly, treatment of M2 MΦ with both TLR2/1L and anti-IL-10 neutralizing antibodies led to polarization to the M1-like MΦ phenotype and function. Together, our data demonstrate an approach to induce MΦ plasticity that provides the potential for re-educating MΦ function in human mycobacterial disease to promote host defense and limit pathogenesis.

Epigenome-wide association in adipose tissue from the METSIM cohort.

Most epigenome-wide association studies to date have been conducted in blood. However, metabolic syndrome is mediated by a dysregulation of adiposity and therefore it is critical to study adipose tissue in order to understand the effects of this syndrome on epigenomes. To determine if natural variation in DNA methylation was associated with metabolic syndrome traits, we profiled global methylation levels in subcutaneous abdominal adipose tissue. We measured association between 32 clinical traits related to diabetes and obesity in 201 people from the Metabolic Syndrome in Men cohort. We performed epigenome-wide association studies between DNA methylation levels and traits, and identified associations for 13 clinical traits in 21 loci. We prioritized candidate genes in these loci using expression quantitative trait loci, and identified 18 high confidence candidate genes, including known and novel genes associated with diabetes and obesity traits. Using methylation deconvolution, we examined which cell types may be mediating the associations, and concluded that most of the loci we identified were specific to adipocytes. We determined whether the abundance of cell types varies with metabolic traits, and found that macrophages increased in abundance with the severity of metabolic syndrome traits. Finally, we developed a DNA methylation-based biomarker to assess type 2 diabetes risk in adipose tissue. In conclusion, our results demonstrate that profiling DNA methylation in adipose tissue is a powerful tool for understanding the molecular effects of metabolic syndrome on adipose tissue, and can be used in conjunction with traditional genetic analyses to further characterize this disorder.

Genetic Mechanisms of Immune Evasion in Colorectal Cancer.

To understand the genetic drivers of immune recognition and evasion in colorectal cancer, we analyzed 1,211 colorectal cancer primary tumor samples, including 179 classified as microsatellite instability-high (MSI-high). This set includes The Cancer Genome Atlas colorectal cancer cohort of 592 samples, completed and analyzed here. MSI-high, a hypermutated, immunogenic subtype of colorectal cancer, had a high rate of significantly mutated genes in important immune-modulating pathways and in the antigen presentation machinery, including biallelic losses of B2M and HLA genes due to copy-number alterations and copy-neutral loss of heterozygosity. WNT/ß-catenin signaling genes were significantly mutated in all colorectal cancer subtypes, and activated WNT/ß-catenin signaling was correlated with the absence of T-cell infiltration. This large-scale genomic analysis of colorectal cancer demonstrates that MSI-high cases frequently undergo an immunoediting process that provides them with genetic events allowing immune escape despite high mutational load and frequent lymphocytic infiltration and, furthermore, that colorectal cancer tumors have genetic and methylation events associated with activated WNT signaling and T-cell exclusion.Significance: This multi-omic analysis of 1,211 colorectal cancer primary tumors reveals that it should be possible to better monitor resistance in the 15% of cases that respond to immune blockade therapy and also to use WNT signaling inhibitors to reverse immune exclusion in the 85% of cases that currently do not. Cancer Discov; 8(6); 730-49. ©2018 AACR.This article is highlighted in the In This Issue feature, p. 663.

SaVanT: a web-based tool for the sample-level visualization of molecular signatures in gene expression profiles.

BACKGROUND: Molecular signatures are collections of genes characteristic of a particular cell type, tissue, disease, or perturbation. Signatures can also be used to interpret expression profiles generated from heterogeneous samples. Large collections of gene signatures have been previously developed and catalogued in the MSigDB database. In addition, several consortia and large-scale projects have systematically profiled broad collections of purified primary cells, molecular perturbations of cell types, and tissues from specific diseases, and the specificity and breadth of these datasets can be leveraged to create additional molecular signatures. However, to date there are few tools that allow the visualization of individual signatures across large numbers of expression profiles. Signature visualization of individual samples allows, for example, the identification of patient subcategories a priori on the basis of well-defined molecular signatures. RESULT: Here, we generate and compile 10,985 signatures (636 newly-generated and 10,349 previously available from MSigDB) and provide a web-based Signature Visualization Tool (SaVanT; http://newpathways.mcdb.ucla.edu/savant ), to visualize these signatures in user-generated expression data. We show that using SaVanT, immune activation signatures can distinguish patients with different types of acute infections (influenza A and bacterial pneumonia). Furthermore, SaVanT is able to identify the prominent signatures within each patient group, and identify the primary cell types underlying different leukemias (acute myeloid and acute lymphoblastic) and skin disorders. CONCLUSIONS: The development of SaVanT facilitates large-scale analysis of gene expression profiles on a patient-level basis to identify patient subphenotypes, or potential therapeutic target pathways.

Solid-phase extraction microfluidic devices for matrix removal in trace element assay of actinide materials.

Advances in sample nebulization and injection technology have significantly reduced the volume of solution required for trace impurity analysis in plutonium and uranium materials. Correspondingly, we have designed and tested a novel chip-based microfluidic platform, containing a 100-µL or 20-µL solid-phase microextraction column, packed by centrifugation, which supports nuclear material mass and solution volume reductions of 90% or more compared to standard methods. Quantitative recovery of 28 trace elements in uranium was demonstrated using a UTEVA chromatographic resin column, and trace element recovery from thorium (a surrogate for plutonium) was similarly demonstrated using anion exchange resin AG MP-1. Of nine materials tested, compatibility of polyvinyl chloride (PVC), polypropylene (PP), and polytetrafluoroethylene (PTFE) chips with the strong nitric acid media was highest. The microcolumns can be incorporated into a variety of devices and systems, and can be loaded with other solid-phase resins for trace element assay in high-purity metals.

Jagged1 Instructs Macrophage Differentiation in Leprosy.

As circulating monocytes enter the site of disease, the local microenvironment instructs their differentiation into tissue macrophages (MΦ). To identify mechanisms that regulate MΦ differentiation, we studied human leprosy as a model, since M1-type antimicrobial MΦ predominate in lesions in the self-limited form, whereas M2-type phagocytic MΦ are characteristic of the lesions in the progressive form. Using a heterotypic co-culture model, we found that unstimulated endothelial cells (EC) trigger monocytes to become M2 MΦ. However, biochemical screens identified that IFN-γ and two families of small molecules activated EC to induce monocytes to differentiate into M1 MΦ. The gene expression profiles induced in these activated EC, when overlapped with the transcriptomes of human leprosy lesions, identified Jagged1 (JAG1) as a potential regulator of MΦ differentiation. JAG1 protein was preferentially expressed in the lesions from the self-limited form of leprosy, and localized to the vascular endothelium. The ability of activated EC to induce M1 MΦ was JAG1-dependent and the addition of JAG1 to quiescent EC facilitated monocyte differentiation into M1 MΦ with antimicrobial activity against M. leprae. Our findings indicate a potential role for the IFN-γ-JAG1 axis in instructing MΦ differentiation as part of the host defense response at the site of disease in human leprosy.

Epigenetic changes in T-cell and monocyte signatures and production of neurotoxic cytokines in ALS patients.

We have investigated transcriptional and epigenetic differences in peripheral blood mononuclear cells (PBMCs) of monozygotic female twins discordant in the diagnosis of amyotrophic lateral sclerosis (ALS). Exploring DNA methylation differences by reduced representation bisulfite sequencing (RRBS), we determined that, over time, the ALS twin developed higher abundances of the CD14 macrophages and lower abundances of T cells compared to the non-ALS twin. Higher macrophage signature in the ALS twin was also shown by RNA sequencing (RNA-seq). Moreover, the twins differed in the methylome at loci near several genes, including EGFR and TNFRSF11A, and in the pathways related to the tretinoin and H3K27me3 markers. We also tested cytokine production by PBMCs. The ALS twin's PBMCs spontaneously produced IL-6 and TNF-α, whereas PBMCs of the healthy twin produced these cytokines only when stimulated by superoxide dismutase (SOD)-1. These results and flow cytometric detection of CD45 and CD127 suggest the presence of memory T cells in both twins, but effector T cells only in the ALS twin. The ALS twin's PBMC supernatants, but not the healthy twin's, were toxic to rat cortical neurons, and this toxicity was strongly inhibited by an IL-6 receptor antibody (tocilizumab) and less well by TNF-α and IL-1ß antibodies. The putative neurotoxicity of IL-6 and TNF-α is in agreement with a high expression of these cytokines on infiltrating macrophages in the ALS spinal cord. We hypothesize that higher macrophage abundance and increased neurotoxic cytokines have a fundamental role in the phenotype and treatment of certain individuals with ALS.-Lam, L., Chin, L., Halder, R. C., Sagong, B., Famenini, S., Sayre, J., Montoya, D., Rubbi L., Pellegrini, M., Fiala, M. Epigenetic changes in T-cell and monocyte signatures and production of neurotoxic cytokines in ALS patients.