Neurodegenerative disease pathways are perturbed in patients with cancer who self-report cognitive changes and anxiety: A pathway impact analysis.

BACKGROUND: Cancer-related cognitive impairment (CRCI) and anxiety co-occur in patients with cancer. Little is known about mechanisms for the co-occurrence of these two symptoms. The purposes of this secondary analysis were to evaluate for perturbed pathways associated with the co-occurrence of self-reported CRCI and anxiety in patients with low versus high levels of these two symptoms and to identify potential mechanisms for the co-occurrence of CRCI and anxiety using biological processes common across any perturbed neurodegenerative disease pathways. METHODS: Patients completed the Attentional Function Index and the Spielberger State-Trait Anxiety Inventory six times over two cycles of chemotherapy. Based on findings from a previous latent profile analysis, patients were grouped into none versus both high levels of these symptoms. Gene expression was quantified, and pathway impact analyses were performed. Signaling pathways for evaluation were defined with the Kyoto Encyclopedia of Genes and Genomes database. RESULTS: A total of 451 patients had data available for analysis. Approximately 85.0% of patients were in the none class and 15.0% were in the both high class. Pathway impact analyses identified five perturbed pathways related to neurodegenerative diseases (i.e., amyotrophic lateral sclerosis, Huntington disease, Parkinson disease, prion disease, and pathways of neurodegeneration-multiple diseases). Apoptosis, mitochondrial dysfunction, oxidative stress, and endoplasmic reticulum stress were common biological processes across these pathways. CONCLUSIONS: This study is the first to describe perturbations in neurodegenerative disease pathways associated with CRCI and anxiety in patients receiving chemotherapy. These findings provide new insights into potential targets for the development of mechanistically based interventions.

Perturbations in inflammatory pathways are associated with shortness of breath profiles in oncology patients receiving chemotherapy.

PURPOSE: One plausible mechanistic hypothesis is the potential contribution of inflammatory mechanisms to shortness of breath. This study was aimed to evaluate for associations between the occurrence of shortness of breath and perturbations in inflammatory pathways. METHODS: Patients with cancer reported the occurrence of shortness of breath six times over two cycles of chemotherapy. Latent class analysis was used to identify subgroups of patients with distinct shortness of breath occurrence profiles (i.e., none (70.5%), decreasing (8.2%), increasing (7.8%), high (13.5%)). Using an extreme phenotype approach, whole transcriptome differential gene expression and pathway impact analyses were performed to evaluate for perturbed signaling pathways associated with shortness of breath between the none and high classes. Two independent samples (RNA-sequencing (n = 293) and microarray (n = 295) methodologies) were evaluated. Fisher's combined probability method was used to combine these results to obtain a global test of the null hypothesis. In addition, an unweighted knowledge network was created using the specific pathway maps to evaluate for interconnections among these pathways. RESULTS: Twenty-nine Kyoto Encyclopedia of Genes and Genomes inflammatory signaling pathways were perturbed. The mitogen-activated protein kinase signaling pathway node had the highest closeness, betweenness, and degree scores. In addition, five common respiratory disease-related pathways, that may share mechanisms with cancer-related shortness of breath, were perturbed. CONCLUSIONS: Findings provide preliminary support for the hypothesis that inflammation contribute to the occurrence of shortness of breath in patients with cancer. In addition, the mechanisms that underlie shortness of breath in oncology patients may be similar to other respiratory diseases.

Torch-eCpG: a fast and scalable eQTM mapper for thousands of molecular phenotypes with graphical processing units.

BACKGROUND: Gene expression may be regulated by the DNA methylation of regulatory elements in cis, distal, and trans regions. One method to evaluate the relationship between DNA methylation and gene expression is the mapping of expression quantitative trait methylation (eQTM) loci (also called expression associated CpG loci, eCpG). However, no open-source tools are available to provide eQTM mapping. In addition, eQTM mapping can involve a large number of comparisons which may prevent the analyses due to limitations of computational resources. Here, we describe Torch-eCpG, an open-source tool to perform eQTM mapping that includes an optimized implementation that can use the graphical processing unit (GPU) to reduce runtime. RESULTS: We demonstrate the analyses using the tool are reproducible, up to 18 × faster using the GPU, and scale linearly with increasing methylation loci. CONCLUSIONS: Torch-eCpG is a fast, reliable, and scalable tool to perform eQTM mapping. Source code for Torch-eCpG is available at https://github.com/kordk/torch-ecpg .

Analysis of DNA methylation at birth and in childhood reveals changes associated with season of birth and latitude.

BACKGROUND: Seasonal variations in environmental exposures at birth or during gestation are associated with numerous adult traits and health outcomes later in life. Whether DNA methylation (DNAm) plays a role in the molecular mechanisms underlying the associations between birth season and lifelong phenotypes remains unclear. METHODS: We carried out epigenome-wide meta-analyses within the Pregnancy And Childhood Epigenetic Consortium to identify associations of DNAm with birth season, both at differentially methylated probes (DMPs) and regions (DMRs). Associations were examined at two time points: at birth (21 cohorts, N = 9358) and in children aged 1-11 years (12 cohorts, N = 3610). We conducted meta-analyses to assess the impact of latitude on birth season-specific associations at both time points. RESULTS: We identified associations between birth season and DNAm (False Discovery Rate-adjusted p values < 0.05) at two CpGs at birth (winter-born) and four in the childhood (summer-born) analyses when compared to children born in autumn. Furthermore, we identified twenty-six differentially methylated regions (DMR) at birth (winter-born: 8, spring-born: 15, summer-born: 3) and thirty-two in childhood (winter-born: 12, spring and summer: 10 each) meta-analyses with few overlapping DMRs between the birth seasons or the two time points. The DMRs were associated with genes of known functions in tumorigenesis, psychiatric/neurological disorders, inflammation, or immunity, amongst others. Latitude-stratified meta-analyses [higher (≥ 50°N), lower (< 50°N, northern hemisphere only)] revealed differences in associations between birth season and DNAm by birth latitude. DMR analysis implicated genes with previously reported links to schizophrenia (LAX1), skin disorders (PSORS1C, LTB4R), and airway inflammation including asthma (LTB4R), present only at birth in the higher latitudes (≥ 50°N). CONCLUSIONS: In this large epigenome-wide meta-analysis study, we provide evidence for (i) associations between DNAm and season of birth that are unique for the seasons of the year (temporal effect) and (ii) latitude-dependent variations in the seasonal associations (spatial effect). DNAm could play a role in the molecular mechanisms underlying the effect of birth season on adult health outcomes.

Multiomic Single Cell Sequencing Identifies Stemlike Nature of Mixed Phenotype Acute Leukemia and Provides Novel Risk Stratification.

Mixed phenotype acute leukemia (MPAL) is a leukemia whose biologic drivers are poorly understood, therapeutic strategy remains unclear, and prognosis is poor. We performed multiomic single cell (SC) profiling of 14 newly diagnosed adult MPAL patients to characterize the immunophenotypic, genetic, and transcriptional landscapes of MPAL. We show that neither genetic profile nor transcriptome reliably correlate with specific MPAL immunophenotypes. However, progressive acquisition of mutations is associated with increased expression of immunophenotypic markers of immaturity. Using SC transcriptional profiling, we find that MPAL blasts express a stem cell-like transcriptional profile distinct from other acute leukemias and indicative of high differentiation potential. Further, patients with the highest differentiation potential demonstrated inferior survival in our dataset. A gene set score, MPAL95, derived from genes highly enriched in this cohort, is applicable to bulk RNA sequencing data and was predictive of survival in an independent patient cohort, suggesting utility for clinical risk stratification.

Prediction of morning fatigue severity in outpatients receiving chemotherapy: less may still be more.

INTRODUCTION: Fatigue is the most common and debilitating symptom experienced by cancer patients undergoing chemotherapy (CTX). Prediction of symptom severity can assist clinicians to identify high-risk patients and provide education to decrease symptom severity. The purpose of this study was to predict the severity of morning fatigue in the week following the administration of CTX. METHODS: Outpatients (n = 1217) completed questionnaires 1 week prior to and 1 week following administration of CTX. Morning fatigue was measured using the Lee Fatigue Scale (LFS). Separate prediction models for morning fatigue severity were created using 157 demographic, clinical, symptom, and psychosocial adjustment characteristics and either morning fatigue scores or individual fatigue item scores. Prediction models were created using two regression and five machine learning approaches. RESULTS: Elastic net models provided the best fit across all models. For the EN model using individual LFS item scores, two of the 13 individual LFS items (i.e., "worn out," "exhausted") were the strongest predictors. CONCLUSIONS: This study is the first to use machine learning techniques to accurately predict the severity of morning fatigue from prior to through the week following the administration of CTX using total and individual item scores from the Lee Fatigue Scale (LFS). Our findings suggest that the language used to assess clinical fatigue in oncology patients is important and that two simple questions may be used to predict morning fatigue severity.

Torch-eCpG: A fast and scalable eQTM mapper for thousands of molecular phenotypes with graphical processing units.

Background: Gene expression may be regulated by the DNA methylation of regulatory elements in cis, distal, and trans regions. One method to evaluate the relationship between DNA methylation and gene expression is the mapping of expression quantitative trait methylation (eQTM) loci (also called expression associated CpG loci, eCpG). However, no open-source tools are available to provide eQTM mapping. In addition, eQTM mapping can involve a large number of comparisons which may prevent the analyses due to limitations of computational resources. Here, we describe Torch-eCpG, an open-source tool to perform eQTM mapping that includes an optimized implementation that can use the graphical processing unit (GPU) to reduce runtime. Results: We demonstrate the analyses using the tool are reproducible, up to 18x faster using the GPU, and scale linearly with increasing methylation loci. Conclusions: Torch-eCpG is a fast, reliable, and scalable tool to perform eQTM mapping. Source code for Torch-eCpG is available at https://github.com/kordk/torch-ecpg.

Therapeutic implications of transcriptomics in head and neck cancer patient-derived xenografts.

There are currently no clinical strategies utilizing tumor gene expression to inform therapeutic selection for patients with head and neck squamous cell carcinoma (HNSCC). One of the challenges in developing predictive biomarkers is the limited characterization of preclinical HNSCC models. Patient-derived xenografts (PDXs) are increasingly recognized as translationally relevant preclinical avatars for human tumors; however, the overall transcriptomic concordance of HNSCC PDXs with primary human HNSCC is understudied, especially in human papillomavirus-associated (HPV+) disease. Here, we characterized 64 HNSCC PDXs (16 HPV+ and 48 HPV-) at the transcriptomic level using RNA-sequencing. The range of human-specific reads per PDX varied from 64.6%-96.5%, with a comparison of the most differentially expressed genes before and after removal of mouse transcripts revealing no significant benefit to filtering out mouse mRNA reads in this cohort. We demonstrate that four previously established HNSCC molecular subtypes found in The Cancer Genome Atlas (TCGA) are also clearly recapitulated in HNSCC PDXs. Unsupervised hierarchical clustering yielded a striking natural division of HNSCC PDXs by HPV status, with C19orf57 (BRME1), a gene previously correlated with positive response to cisplatin in cervical cancer, among the most significantly differentially expressed genes between HPV+ and HPV- PDXs. In vivo experiments demonstrated a possible relationship between increased C19orf57 expression and superior anti-tumor responses of PDXs to cisplatin, which should be investigated further. These findings highlight the value of PDXs as models for HPV+ and HPV- HNSCC, providing a resource for future discovery of predictive biomarkers to guide treatment selection in HNSCC.

Venetoclax and dinaciclib elicit synergistic preclinical efficacy against hypodiploid acute lymphoblastic leukemia.

Hypodiploid acute lymphoblastic leukemia (ALL) is an aggressive blood cancer with a poor prognosis despite intensive chemotherapy or stem cell transplant. Children and adolescents with positive end-of-induction minimal residual disease have an overall survival lower than 30%. However, data regarding therapeutic alternatives for this disease is nearly nonexistent, emphasizing the critical need for new or adjunctive therapies that can improve outcomes. We previously reported on the therapeutic efficacy of venetoclax (ABT-199) in hypodiploid B-lineage ALL but with limitations as monotherapy. In this study, we set out to identify drugs enhancing the anti-leukemic effect of venetoclax in hypodiploid ALL. Using a highthroughput drug screen, we identified dinaciclib, a cyclin-dependent kinase inhibitor that worked synergistically with venetoclax to induce cell death in hypodiploid cell lines. This combination eradicated leukemic blasts within hypodiploid ALL patient-derived xenografts mice with low off-target toxicity. Our findings suggest that dual inhibition of BCL-2 (venetoclax) and CDK9/MCL-1 (dinaciclib) is a promising therapeutic approach in hypodiploid ALL, warranting further investigation to inform clinical trials in this high-risk patient population.

Caveolin-1 and Sox-2 are predictive biomarkers of cetuximab response in head and neck cancer.

The epidermal growth factor receptor (EGFR) inhibitor cetuximab is the only FDA-approved oncogene-targeting therapy for head and neck squamous cell carcinoma (HNSCC). Despite variable treatment response, no biomarkers exist to stratify patients for cetuximab therapy in HNSCC. Here, we applied unbiased hierarchical clustering to reverse-phase protein array molecular profiles from patient-derived xenograft (PDX) tumors and revealed 2 PDX clusters defined by protein networks associated with EGFR inhibitor resistance. In vivo validation revealed unbiased clustering to classify PDX tumors according to cetuximab response with 88% accuracy. Next, a support vector machine classifier algorithm identified a minimalist biomarker signature consisting of 8 proteins - caveolin-1, Sox-2, AXL, STING, Brd4, claudin-7, connexin-43, and fibronectin - with expression that strongly predicted cetuximab response in PDXs using either protein or mRNA. A combination of caveolin-1 and Sox-2 protein levels was sufficient to maintain high predictive accuracy, which we validated in tumor samples from patients with HNSCC with known clinical response to cetuximab. These results support further investigation into the combined use of caveolin-1 and Sox-2 as predictive biomarkers for cetuximab response in the clinic.

Prediction of evening fatigue severity in outpatients receiving chemotherapy: less may be more.

BACKGROUND: Fatigue is the most common and debilitating symptom experienced by oncology patients undergoing chemotherapy. Little is known about patient characteristics that predict changes in fatigue severity over time. PURPOSE: To predict the severity of evening fatigue in the week following the administration of chemotherapy using machine learning approaches. METHODS: Outpatients with breast, gastrointestinal, gynecological, or lung cancer (N=1217) completed questionnaires one week prior to and one week following administration of chemotherapy. Evening fatigue was measured with the Lee Fatigue Scale (LFS). Separate prediction models for evening fatigue severity were created using clinical, symptom, and psychosocial adjustment characteristics and either evening fatigue scores or individual fatigue item scores. Prediction models were created using two regression and three machine learning approaches. RESULTS: Random forest (RF) models provided the best fit across all models. For the RF model using individual LFS item scores, two of the 13 individual LFS items (i.e., "worn out", "exhausted") were the strongest predictors. CONCLUSION: This study is the first to use machine learning techniques to predict evening fatigue severity in the week following chemotherapy from fatigue scores obtained in the week prior to chemotherapy. Our findings suggest that the language used to assess clinical fatigue in oncology patients is important and that two simple questions may be used to predict evening fatigue severity.

The genome-wide impact of trisomy 21 on DNA methylation and its implications for hematopoiesis.

Down syndrome is associated with genome-wide perturbation of gene expression, which may be mediated by epigenetic changes. We perform an epigenome-wide association study on neonatal bloodspots comparing 196 newborns with Down syndrome and 439 newborns without Down syndrome, adjusting for cell-type heterogeneity, which identifies 652 epigenome-wide significant CpGs (P < 7.67 × 10-8) and 1,052 differentially methylated regions. Differential methylation at promoter/enhancer regions correlates with gene expression changes in Down syndrome versus non-Down syndrome fetal liver hematopoietic stem/progenitor cells (P < 0.0001). The top two differentially methylated regions overlap RUNX1 and FLI1, both important regulators of megakaryopoiesis and hematopoietic development, with significant hypermethylation at promoter regions of these two genes. Excluding Down syndrome newborns harboring preleukemic GATA1 mutations (N = 30), identified by targeted sequencing, has minimal impact on the epigenome-wide association study results. Down syndrome has profound, genome-wide effects on DNA methylation in hematopoietic cells in early life, which may contribute to the high frequency of hematological problems, including leukemia, in children with Down syndrome.

Human pediatric B-cell acute lymphoblastic leukemias can be classified as B-1 or B-2-like based on a minimal transcriptional signature.

The finding that transformed mouse B-1 and B-2 progenitors give rise to B-cell acute lymphoblastic leukemias (B-ALLs) with varied aggressiveness suggests that B-cell lineage might also be a factor in the initiation and progression of pediatric B-ALLs in humans. If this is the case, we hypothesized that human pediatric B-ALLs would share gene expression patterns with mouse B-1 or B-2 progenitors. We tested this premise by deriving a distinct 30-gene B-1 and B-2 progenitor signature that was applied to a microarray data set of human pediatric ALLs. Cluster analysis revealed that CRLF2, E2A-PBX1, ERG, and ETV6-RUNX1 leukemias were B-1-like, whereas BCR-ABL1, hyperdiploid, and MLL leukemias were B-2-like. Examination of the 30-gene signature in two independent data sets of pediatric ALLs supported this result. Our data suggest that common genetic subtypes of human ALL have their origin in the B-1 or B-2 lineage.

Epigenome-wide meta-analysis of blood DNA methylation in newborns and children identifies numerous loci related to gestational age.

BACKGROUND: Preterm birth and shorter duration of pregnancy are associated with increased morbidity in neonatal and later life. As the epigenome is known to have an important role during fetal development, we investigated associations between gestational age and blood DNA methylation in children. METHODS: We performed meta-analysis of Illumina's HumanMethylation450-array associations between gestational age and cord blood DNA methylation in 3648 newborns from 17 cohorts without common pregnancy complications, induced delivery or caesarean section. We also explored associations of gestational age with DNA methylation measured at 4-18 years in additional pediatric cohorts. Follow-up analyses of DNA methylation and gene expression correlations were performed in cord blood. DNA methylation profiles were also explored in tissues relevant for gestational age health effects: fetal brain and lung. RESULTS: We identified 8899 CpGs in cord blood that were associated with gestational age (range 27-42 weeks), at Bonferroni significance, P < 1.06 × 10- 7, of which 3343 were novel. These were annotated to 4966 genes. After restricting findings to at least three significant adjacent CpGs, we identified 1276 CpGs annotated to 325 genes. Results were generally consistent when analyses were restricted to term births. Cord blood findings tended not to persist into childhood and adolescence. Pathway analyses identified enrichment for biological processes critical to embryonic development. Follow-up of identified genes showed correlations between gestational age and DNA methylation levels in fetal brain and lung tissue, as well as correlation with expression levels. CONCLUSIONS: We identified numerous CpGs differentially methylated in relation to gestational age at birth that appear to reflect fetal developmental processes across tissues. These findings may contribute to understanding mechanisms linking gestational age to health effects.

Next-Generation Sequencing of Retinoblastoma Identifies Pathogenic Alterations beyond RB1 Inactivation That Correlate with Aggressive Histopathologic Features.

PURPOSE: To determine the usefulness of a comprehensive, targeted-capture next-generation sequencing (NGS) assay for the clinical management of children undergoing enucleation for retinoblastoma. DESIGN: Cohort study. PARTICIPANTS: Thirty-two children with retinoblastoma. METHODS: We performed targeted NGS using the UCSF500 Cancer Panel (University of California, San Francisco, San Francisco, CA) on formalin-fixed, paraffin-embedded tumor tissue along with constitutional DNA isolated from peripheral blood, buccal swab, or uninvolved optic nerve. Peripheral blood samples were also sent to a commercial laboratory for germline RB1 mutation testing. MAIN OUTCOME MEASURES: Presence or absence of germline RB1 mutation or deletion, tumor genetic profile, and association of genetic alterations with clinicopathologic features. RESULTS: Germline mutation or deletion of the RB1 gene was identified in all children with bilateral retinoblastoma (n = 12), and these NGS results were 100% concordant with commercial germline RB1 mutation analysis. In tumor tissue tested with NGS, biallelic inactivation of RB1 was identified in 28 tumors and focal MYCN amplification was identified in 4 tumors (2 with wild-type RB1 and 2 with biallelic RB1 inactivation). Additional likely pathogenic alterations beyond RB1 were identified in 13 tumors (41%), several of which have not been reported previously in retinoblastoma. These included focal amplifications of MDM4 and RAF1, as well as damaging mutations involving BCOR, ARID1A, MGA, FAT1, and ATRX. The presence of additional likely pathogenetic mutations beyond RB1 inactivation was associated with aggressive histopathologic features, including higher histologic grade and anaplasia, and also with both unilateral and sporadic disease. CONCLUSIONS: Comprehensive NGS analysis reliably detects relevant mutations, amplifications, and chromosomal copy number changes in retinoblastoma. The presence of genetic alterations beyond RB1 inactivation correlates with aggressive histopathologic features.

Glucocorticoids paradoxically facilitate steroid resistance in T cell acute lymphoblastic leukemias and thymocytes.

Glucocorticoids (GCs) are a central component of therapy for patients with T cell acute lymphoblastic leukemia (T-ALL), and although resistance to GCs is a strong negative prognostic indicator in T-ALL, the mechanisms of GC resistance remain poorly understood. Using diagnostic samples from patients enrolled in the frontline Children's Oncology Group (COG) T-ALL clinical trial AALL1231, we demonstrated that one-third of primary T-ALLs were resistant to GCs when cells were cultured in the presence of IL-7, a cytokine that is critical for normal T cell function and that plays a well-established role in leukemogenesis. We demonstrated that in these T-ALLs and in distinct populations of normal developing thymocytes, GCs paradoxically induced their own resistance by promoting upregulation of IL-7 receptor (IL-7R) expression. In the presence of IL-7, this augmented downstream signal transduction, resulting in increased STAT5 transcriptional output and upregulation of the prosurvival protein BCL-2. Taken together, we showed that IL-7 mediates an intrinsic and physiologic mechanism of GC resistance in normal thymocyte development that is retained during leukemogenesis in a subset of T-ALLs and is reversible with targeted inhibition of the IL-7R/JAK/STAT5/BCL-2 axis.

Next-Generation Sequencing of Uveal Melanoma for Detection of Genetic Alterations Predicting Metastasis.

PURPOSE: To clinically use the UCSF500, a pancancer, next-generation sequencing assay in uveal melanoma (UM) and to correlate results with gene expression profiling (GEP) and predictive factors for metastasis. METHODS: Cohort study. Tumor samples of adult UM patients were analyzed with the UCSF500 and GEP. Main outcomes were copy number changes in chromosomes 1, 3, 6, and 8 and mutations in GNAQ, GNA11, SF3B1, EIF1AX, BAP1, SRSF2, U2AF1, and PLCB4. Chromosome 3 loss (a metastasis predictor) was tested for correlation with GEP class, tumor characteristics (largest basal diameter, thickness, ciliary body involvement, and extraocular extension), and histology (presence of epithelioid cells, closed loops, and mitotic count). RESULTS: The 62 patients had a mean age of 59 years (range, 24-89 years). Chromosome 3 loss was detected in 30 patients and was associated with larger basal tumor diameter (Wilcoxon rank sum test, P = 0.015), greater thickness (Wilcoxon rank sum test, P = 0.016) and tumor, node, metastasis stage (Fisher test, P = 0.006), epithelioid cytology (Fisher test, P < 0.001), BAP1 mutation (Fisher test, P < 0.001), and chromosome 8q gain (Fisher test, P < 0.001). Class 2 tumors were much more likely to have chromosome 3 loss than class 1 (odds ratio, 121; P < 0.001). Eleven patients developed metastatic UM, of which five died during the study. All metastatic cases had chromosome 3 loss, 8 gain, BAP1 mutation, and class 2 GEP. Five class 1 tumors had chromosome 3 loss. CONCLUSIONS: UCSF500 detects chromosomal copy number changes and missense mutations that correlate strongly with metastasis predictors, including GEP. TRANSLATIONAL RELEVANCE: Next-generation sequencing of UM should enhance survival prognostication.

Meta-analysis of epigenome-wide association studies in neonates reveals widespread differential DNA methylation associated with birthweight.

Birthweight is associated with health outcomes across the life course, DNA methylation may be an underlying mechanism. In this meta-analysis of epigenome-wide association studies of 8,825 neonates from 24 birth cohorts in the Pregnancy And Childhood Epigenetics Consortium, we find that DNA methylation in neonatal blood is associated with birthweight at 914 sites, with a difference in birthweight ranging from -183 to 178 grams per 10% increase in methylation (PBonferroni < 1.06 x 10-7). In additional analyses in 7,278 participants, <1.3% of birthweight-associated differential methylation is also observed in childhood and adolescence, but not adulthood. Birthweight-related CpGs overlap with some Bonferroni-significant CpGs that were previously reported to be related to maternal smoking (55/914, p = 6.12 x 10-74) and BMI in pregnancy (3/914, p = 1.13x10-3), but not with those related to folate levels in pregnancy. Whether the associations that we observe are causal or explained by confounding or fetal growth influencing DNA methylation (i.e. reverse causality) requires further research.

Epigenomic profiling of newborns with isolated orofacial clefts reveals widespread DNA methylation changes and implicates metastable epiallele regions in disease risk.

Cleft lip with or without cleft palate (CL/P) is a common human birth defect whose etiologies remain largely unknown. Several studies have demonstrated that periconceptional supplementation of folic acid can reduce risk of CL/P in offspring. In this study, we tested the hypothesis that the preventive effect of folic acid is manifested through epigenetic modifications by determining whether DNA methylation changes are associated with CL/P. To more readily observe the potential effects of maternal folate on the offspring epigenome, we focused on births prior to mandatory dietary folate fortification in the United States (i.e. birth year 1997 or earlier). Genomic DNA methylation levels were assessed from archived newborn bloodspots in a 182-member case-control study using the Illumina® Human Beadchip 450K array. CL/P cases displayed striking epigenome-wide hypomethylation relative to controls: 63% of CpGs interrogated had lower methylation levels in case newborns, a trend which held up in racially stratified sub-groups. 28 CpG sites reached epigenome-wide significance and all were case-hypomethylated. The most significant CL/P-associated differentially methylated region encompassed the VTRNA2-1 gene, which was also hypomethylated in cases (FWER p = 0.014). This region has been previously characterized as a nutritionally-responsive, metastable epiallele and CL/P-associated methylation changes, in general, were greater at or near putative metastable epiallelic regions. Gene Set Enrichment Analysis of CL/P-associated DMRs showed an over-representation of genes involved in palate development such as WNT9B, MIR140 and LHX8. CL/P-associated DNA methylation changes may partly explain the mechanism by which orofacial clefts are responsive to maternal folate levels.

Autocrine TGFß Is a Survival Factor for Monocytes and Drives Immunosuppressive Lineage Commitment.

Transforming growth factor ß (TGFß) is an effector of immune suppression and contributes to a permissive tumor microenvironment that compromises effective immunotherapy. We identified a correlation between TGFB1 and genes expressed by myeloid cells, but not granulocytes, in The Cancer Genome Atlas lung adenocarcinoma data, in which high TGFB1 expression was associated with poor survival. To determine whether TGFß affected cell fate decisions and lineage commitment, we studied primary cultures of CD14+ monocytes isolated from peripheral blood of healthy donors. We discovered that TGFß was a survival factor for CD14+ monocytes, which rapidly executed an apoptotic program in its absence. Continued exposure to TGFß in combination with granulocyte-macrophage colony stimulating factor (GM-CSF) and interleukin 6 (IL6) amplified HLA-DRlowCD14+CD11b+CD33+ myeloid-derived suppressor cells (MDSCs) at the expense of macrophage and dendritic cell (DC) differentiation. MDSCs generated in the presence of TGFß were more effective in suppressing T-cell proliferation and promoted the T regulatory cell phenotype. In contrast, inhibition of TGFß signaling using a small-molecule inhibitor of receptor kinase activity in CD14+ monocytes treated with GM-CSF and IL6 decreased MDSC differentiation and increased differentiation to proinflammatory macrophages and antigen-presenting DCs. The effect of autocrine and paracrine TGFß on myeloid cell survival and lineage commitment suggests that pharmacologic inhibition of TGFß-dependent signaling in cancer would favor antitumor immunity.