Prediction and Prevention of Preterm Birth: A Prospective, Randomized Intervention Trial.

OBJECTIVE: The study aimed to determine if a program of mid-trimester serum proteomics screening of women at low risk for spontaneous preterm birth (sPTB) and the use of a PTB risk-reduction protocol in those whose results indicated an increased risk of sPTB would reduce the likelihood of sPTB and its sequelae. STUDY DESIGN: Prospective comparison of birth outcomes in singleton pregnancies with mid-trimester cervical length ≥2.5 cm and at otherwise low risk for sPTB randomized to undergo or not undergo mid-trimester serum proteomics screening for increased risk of sPTB (NCT03530332). Screen-positive women were offered a group of interventions aimed at reducing the risk of spontaneous PTB. The primary outcome was the rate of sPTB <37 weeks, and secondary outcomes were gestational age at delivery, total length of neonatal stay, and NICU length of stay (LOS). Unscreened and screen-negative women received standard care. The adaptive study design targeted a sample size of 3,000 to 10,000 women to detect a reduction in sPTB from 6.4 to 4.7%. Due to limited resources, the trial was stopped early prior to data unblinding. RESULTS: A total of 1,191 women were randomized. Screened and unscreened women were demographically similar. sPTB <37 weeks occurred in 2.7% of screened women and 3.5% of controls (p = 0.41). In the screened compared with the unscreened group, there were no between-group differences in the gestational age at delivery, total length of neonatal stay, and NICU LOS. However, the NICU LOS among infants admitted for sPTB was significantly shorter (median = 6.8 days, interquartile range [IQR]: 1.8-8.0 vs. 45.5 days, IQR: 34.6-79.0; p = 0.005). CONCLUSION: Mid-trimester serum proteomics screening of women at low risk for sPTB and the use of a sPTB risk-reduction protocol in screen-positive patients did not significantly reduce the rate of sPTB compared with women not screened, though the trial was underpowered thus limiting the interpretation of negative findings. Infants in the screened group had a significantly shorter NICU LOS, a difference likely due to a reduced number of infants in the screened group that delivered <35 weeks. KEY POINTS: · Mid-trimester serum proteomics screening of women at low risk for sPTB and the use of a sPTB risk-reduction protocol in screen-positive patients did not significantly reduce the rate of sPTB, though the trial was underpowered.. · NICU LOS following sPTB was significantly shortened among women who underwent screening and risk-reduction management.. · The use of serum biomarkers may contribute to a practical strategy to reduce sPTB sequelae..

Clinical and economic evaluation of a proteomic biomarker preterm birth risk predictor: cost-effectiveness modeling of prenatal interventions applied to predicted higher-risk pregnancies within a large and diverse cohort.

OBJECTIVES: Preterm birth occurs in more than 10% of U.S. births and is the leading cause of U.S. neonatal deaths, with estimated annual costs exceeding $25 billion USD. Using real-world data, we modeled the potential clinical and economic utility of a prematurity-reduction program comprising screening in a racially and ethnically diverse population with a validated proteomic biomarker risk predictor, followed by case management with or without pharmacological treatment. METHODS: The ACCORDANT microsimulation model used individual patient data from a prespecified, randomly selected sub-cohort (N = 847) of a multicenter, observational study of U.S. subjects receiving standard obstetric care with masked risk predictor assessment (TREETOP; NCT02787213). All subjects were included in three arms across 500 simulated trials: standard of care (SoC, control); risk predictor/case management comprising increased outreach, education and specialist care (RP-CM, active); and multimodal management (risk predictor/case management with pharmacological treatment) (RP-MM, active). In the active arms, only subjects stratified as higher risk by the predictor were modeled as receiving the intervention, whereas lower-risk subjects received standard care. Higher-risk subjects' gestational ages at birth were shifted based on published efficacies, and dependent outcomes, calibrated using national datasets, were changed accordingly. Subjects otherwise retained their original TREETOP outcomes. Arms were compared using survival analysis for neonatal and maternal hospital length of stay, bootstrap intervals for neonatal cost, and Fisher's exact test for neonatal morbidity/mortality (significance, p < .05). RESULTS: The model predicted improvements for all outcomes. RP-CM decreased neonatal and maternal hospital stay by 19% (p = .029) and 8.5% (p = .001), respectively; neonatal costs' point estimate by 16% (p = .098); and moderate-to-severe neonatal morbidity/mortality by 29% (p = .025). RP-MM strengthened observed reductions and significance. Point estimates of benefit did not differ by race/ethnicity. CONCLUSIONS: Modeled evaluation of a biomarker-based test-and-treat strategy in a diverse population predicts clinically and economically meaningful improvements in neonatal and maternal outcomes.

Preterm birth, defined as delivery before 37 weeks' gestation, is the leading cause of illness and death in newborns. In the United States, more than 10% of infants are born prematurely, and this rate is substantially higher in lower-income, inner-city and Black populations. Prematurity associates with greatly increased risk of short- and long-term medical complications and can generate significant costs throughout the lives of affected children. Annual U.S. health care costs to manage short- and long-term prematurity complications are estimated to exceed $25 billion.Clinical interventions, including case management (increased patient outreach, education and specialist care), pharmacological treatment and their combination can provide benefit to pregnancies at higher risk for preterm birth. Early and sensitive risk detection, however, remains a challenge.We have developed and validated a proteomic biomarker risk predictor for early identification of pregnancies at increased risk of preterm birth. The ACCORDANT study modeled treatments with real-world patient data from a racially and ethnically diverse U.S. population to compare the benefits of risk predictor testing plus clinical intervention for higher-risk pregnancies versus no testing and standard care. Measured outcomes included neonatal and maternal length of hospital stay, associated costs and neonatal morbidity and mortality. The model projected improved outcomes and reduced costs across all subjects, including ethnic and racial minority populations, when predicted higher-risk pregnancies were treated using case management with or without pharmacological treatment. The biomarker risk predictor shows high potential to be a clinically important component of risk stratification for pregnant women, leading to tangible gains in reducing the impact of preterm birth.

Better Estimation of Spontaneous Preterm Birth Prediction Performance through Improved Gestational Age Dating.

The clinical management of pregnancy and spontaneous preterm birth (sPTB) relies on estimates of gestational age (GA). Our objective was to evaluate the effect of GA dating uncertainty on the observed performance of a validated proteomic biomarker risk predictor, and then to test the generalizability of that effect in a broader range of GA at blood draw. In a secondary analysis of a prospective clinical trial (PAPR; NCT01371019), we compared two GA dating categories: both ultrasound and dating by last menstrual period (LMP) (all subjects) and excluding dating by LMP (excluding LMP). The risk predictor's performance was observed at the validated risk predictor threshold both in weeks 191/7-206/7 and extended to weeks 180/7-206/7. Strict blinding and independent statistical analyses were employed. The validated biomarker risk predictor showed greater observed sensitivity of 88% at 75% specificity (increases of 17% and 1%) in more reliably dated (excluding-LMP) subjects, relative to all subjects. Excluding dating by LMP significantly improved the sensitivity in weeks 191/7-206/7. In the broader blood draw window, the previously validated risk predictor threshold significantly stratified higher and lower risk of sPTB, and the risk predictor again showed significantly greater observed sensitivity in excluding-LMP subjects. These findings have implications for testing the performance of models aimed at predicting PTB.

Targeting Xist with compounds that disrupt RNA structure and X inactivation.

Although more than 98% of the human genome is non-coding1, nearly all of the drugs on the market target one of about 700 disease-related proteins. The historical reluctance to invest in non-coding RNA stems partly from requirements for drug targets to adopt a single stable conformation2. Most RNAs can adopt several conformations of similar stabilities. RNA structures also remain challenging to determine3. Nonetheless, an increasing number of diseases are now being attributed to non-coding RNA4 and the ability to target them would vastly expand the chemical space for drug development. Here we devise a screening strategy and identify small molecules that bind the non-coding RNA prototype Xist5. The X1 compound has drug-like properties and binds specifically the RepA motif6 of Xist in vitro and in vivo. Small-angle X-ray scattering analysis reveals that RepA can adopt multiple conformations but favours one structure in solution. X1 binding reduces the conformational space of RepA, displaces cognate interacting protein factors (PRC2 and SPEN), suppresses histone H3K27 trimethylation, and blocks initiation of X-chromosome inactivation. X1 inhibits cell differentiation and growth in a female-specific manner. Thus, RNA can be systematically targeted by drug-like compounds that disrupt RNA structure and epigenetic function.

Performance of a validated spontaneous preterm delivery predictor in South Asian and Sub-Saharan African women: a nested case control study.

OBJECTIVES: To address the disproportionate burden of preterm birth (PTB) in low- and middle-income countries, this study aimed to (1) verify the performance of the United States-validated spontaneous PTB (sPTB) predictor, comprised of the IBP4/SHBG protein ratio, in subjects from Bangladesh, Pakistan and Tanzania enrolled in the Alliance for Maternal and Newborn Health Improvement (AMANHI) biorepository study, and (2) discover biomarkers that improve performance of IBP4/SHBG in the AMANHI cohort. STUDY DESIGN: The performance of the IBP4/SHBG biomarker was first evaluated in a nested case control validation study, then utilized in a follow-on discovery study performed on the same samples. Levels of serum proteins were measured by targeted mass spectrometry. Differences between the AMANHI and U.S. cohorts were adjusted using body mass index (BMI) and gestational age (GA) at blood draw as covariates. Prediction of sPTB < 37 weeks and < 34 weeks was assessed by area under the receiver operator curve (AUC). In the discovery phase, an artificial intelligence method selected additional protein biomarkers complementary to IBP4/SHBG in the AMANHI cohort. RESULTS: The IBP4/SHBG biomarker significantly predicted sPTB < 37 weeks (n = 88 vs. 171 terms ≥ 37 weeks) after adjusting for BMI and GA at blood draw (AUC= 0.64, 95% CI: 0.57-0.71, p < .001). Performance was similar for sPTB < 34 weeks (n = 17 vs. 184 ≥ 34 weeks): AUC = 0.66, 95% CI: 0.51-0.82, p = .012. The discovery phase of the study showed that the addition of endoglin, prolactin, and tetranectin to the above model resulted in the prediction of sPTB < 37 with an AUC= 0.72 (95% CI: 0.66-0.79, p-value < .001) and prediction of sPTB < 34 with an AUC of 0.78 (95% CI: 0.67-0.90, p < .001). CONCLUSION: A protein biomarker pair developed in the U.S. may have broader application in diverse non-U.S. populations.

Clinical Validation of a Proteomic Biomarker Threshold for Increased Risk of Spontaneous Preterm Birth and Associated Clinical Outcomes: A Replication Study.

Preterm births are the leading cause of neonatal death in the United States. Previously, a spontaneous preterm birth (sPTB) predictor based on the ratio of two proteins, IBP4/SHBG, was validated as a predictor of sPTB in the Proteomic Assessment of Preterm Risk (PAPR) study. In particular, a proteomic biomarker threshold of -1.37, corresponding to a ~two-fold increase or ~15% risk of sPTB, significantly stratified earlier deliveries. Guidelines for molecular tests advise replication in a second independent study. Here we tested whether the significant association between proteomic biomarker scores above the threshold and sPTB, and associated adverse outcomes, was replicated in a second independent study, the Multicenter Assessment of a Spontaneous Preterm Birth Risk Predictor (TREETOP). The threshold significantly stratified subjects in PAPR and TREETOP for sPTB (p = 0.041, p = 0.041, respectively). Application of the threshold in a Kaplan-Meier analysis demonstrated significant stratification in each study, respectively, for gestational age at birth (p < 001, p = 0.0016) and rate of hospital discharge for both neonate (p < 0.001, p = 0.005) and mother (p < 0.001, p < 0.001). Above the threshold, severe neonatal morbidity/mortality and mortality alone were 2.2 (p = 0.0083,) and 7.4-fold higher (p = 0.018), respectively, in both studies combined. Thus, higher predictor scores were associated with multiple adverse pregnancy outcomes.

Cost-Effectiveness of a Proteomic Test for Preterm Birth Prediction.

BACKGROUND: Preterm birth (PTB) carries increased risk of short- and long-term health problems as well as higher healthcare costs. Current strategies using clinically accepted maternal risk factors (prior PTB, short cervix) can only identify a minority of singleton PTBs. OBJECTIVE: We modeled the cost-effectiveness of a risk-screening-and-treat strategy versus usual care for commercially insured pregnant US women without clinically accepted PTB risk factors. The risk-screening-and-treat strategy included use of a novel PTB prognostic blood test (PreTRM®) in the 19th-20th week of pregnancy, followed by treatment with a combined regimen of multi-component high-intensity-case-management and pharmacologic interventions for the remainder of the pregnancy for women assessed as higher-risk by the test, and usual care in women without higher risk. METHODS: We built a cost-effectiveness model using a combined decision-tree/Markov approach and a US payer perspective. We modeled 1-week cycles of pregnancy from week 19 to birth (preterm or term) and assessed costs throughout the pregnancy, and further to 12-months post-delivery in mothers and 30-months in infants. PTB rates and costs were based on >40,000 mothers and infants from the HealthCore Integrated Research Database® with birth events in 2016. Estimates of test performance, treatment effectiveness, and other model inputs were derived from published literature. RESULTS: In the base case, the risk-screening-and-treat strategy dominated usual care with an estimated 870 fewer PTBs (20% reduction) and $54 million less in total cost ($863 net savings per pregnant woman). Reductions were projected for neonatal intensive care admissions (10%), overall length-of-stay (7%), and births <32 weeks (33%). Treatment effectiveness had the strongest influence on cost-effectiveness estimates. The risk-screening-and-treat strategy remained dominant in the majority of probabilistic sensitivity analysis simulations and model scenarios. CONCLUSION: Use of a novel prognostic test during pregnancy to identify women at risk of PTB combined with evidence-based treatment is estimated to reduce total costs while preventing PTBs and their consequences.

Performance of a proteomic preterm delivery predictor in a large independent prospective cohort.

BACKGROUND: Preterm birth remains a common and devastating complication of pregnancy. There remains a need for effective and accurate screening methods for preterm birth. Using a proteomic approach, we previously discovered and validated (Proteomic Assessment of Preterm Risk study, NCT01371019) a preterm birth predictor comprising a ratio of insulin-like growth factor-binding protein 4 to sex hormone-binding globulin. OBJECTIVE: To determine the performance of the ratio of insulin-like growth factor-binding protein 4 to sex hormone-binding globulin to predict both spontaneous and medically indicated very preterm births, in an independent cohort distinct from the one in which it was developed. STUDY DESIGN: This was a prospective observational study (Multicenter Assessment of a Spontaneous Preterm Birth Risk Predictor, NCT02787213) at 18 sites in the United States. Women had blood drawn at 170/7 to 216/7 weeks' gestation. For confirmation, we planned to analyze a randomly selected subgroup of women having blood drawn between 191/7 and 206/7 weeks' gestation, with the results of the remaining study participants blinded for future validation studies. Serum from participants was analyzed by mass spectrometry. Neonatal morbidity and mortality were analyzed using a composite score by a method from the PREGNANT trial (NCT00615550, Hassan et al). Scores of 0-3 reflect increasing numbers of morbidities or length of neonatal intensive care unit stay, and 4 represents perinatal mortality. RESULTS: A total of 5011 women were enrolled, with 847 included in this planned substudy analysis. There were 9 preterm birth cases at <320/7 weeks' gestation and 838 noncases at ≥320/7 weeks' gestation; 21 of 847 infants had neonatal composite morbidity and mortality index scores of ≥3, and 4 of 21 had a score of 4. The ratio of insulin-like growth factor-binding protein 4 to sex hormone-binding globulin ratio was substantially higher in both preterm births at <320/7 weeks' gestation and there were more severe neonatal outcomes. The ratio of insulin-like growth factor-binding protein 4 to sex hormone-binding globulin ratio was significantly predictive of birth at <320/7 weeks' gestation (area under the receiver operating characteristic curve, 0.71; 95% confidence interval, 0.55-0.87; P=.016). Stratification by body mass index, optimized in the previous validation study (22

Discovery and Verification of Extracellular miRNA Biomarkers for Non-invasive Prediction of Pre-eclampsia in Asymptomatic Women.

Development of effective prevention and treatment strategies for pre-eclampsia is limited by the lack of accurate methods for identification of at-risk pregnancies. We performed small RNA sequencing (RNA-seq) of maternal serum extracellular RNAs (exRNAs) to discover and verify microRNAs (miRNAs) differentially expressed in patients who later developed pre-eclampsia. Sera collected from 73 pre-eclampsia cases and 139 controls between 17 and 28 weeks gestational age (GA), divided into separate discovery and verification cohorts, are analyzed by small RNA-seq. Discovery and verification of univariate and bivariate miRNA biomarkers reveal that bivariate biomarkers verify at a markedly higher rate than univariate biomarkers. The majority of verified biomarkers contain miR-155-5p, which has been reported to mediate the pre-eclampsia-associated repression of endothelial nitric oxide synthase (eNOS) by tumor necrosis factor alpha (TNF-α). Deconvolution analysis reveals that several verified miRNA biomarkers come from the placenta and are likely carried by placenta-specific extracellular vesicles.

Targeting RNA with Small Molecules: Identification of Selective, RNA-Binding Small Molecules Occupying Drug-Like Chemical Space.

Although the potential value of RNA as a target for new small molecule therapeutics is becoming increasingly credible, the physicochemical properties required for small molecules to selectively bind to RNA remain relatively unexplored. To investigate the druggability of RNAs with small molecules, we have employed affinity mass spectrometry, using the Automated Ligand Identification System (ALIS), to screen 42 RNAs from a variety of RNA classes, each against an array of chemically diverse drug-like small molecules (~50,000 compounds) and functionally annotated tool compounds (~5100 compounds). The set of RNA-small molecule interactions that was generated was compared with that for protein-small molecule interactions, and naïve Bayesian models were constructed to determine the types of specific chemical properties that bias small molecules toward binding to RNA. This set of RNA-selective chemical features was then used to build an RNA-focused set of ~3800 small molecules that demonstrated increased propensity toward binding the RNA target set. In addition, the data provide an overview of the specific physicochemical properties that help to enable binding to potential RNA targets. This work has increased the understanding of the chemical properties that are involved in small molecule binding to RNA, and the methodology used here is generally applicable to RNA-focused drug discovery efforts.

RNA-seq from archival FFPE breast cancer samples: molecular pathway fidelity and novel discovery.

BACKGROUND: Formalin-fixed, paraffin-embedded (FFPE) tissues for RNA-seq have advantages over fresh frozen tissue including abundance and availability, connection to rich clinical data, and association with patient outcomes. However, FFPE-derived RNA is highly degraded and chemically modified, which impacts its utility as a faithful source for biological inquiry. METHODS: True archival FFPE breast cancer cases (n = 58), stored at room temperature for 2-23 years, were utilized to identify key steps in tissue selection, RNA isolation, and library choice. Gene expression fidelity was evaluated by comparing FFPE data to public data obtained from fresh tissues, and by employing single-gene, gene set and transcription network-based regulon analyses. RESULTS: We report a single 10 µm section of breast tissue yields sufficient RNA for RNA-seq, and a relationship between RNA quality and block age that was not linear. We find single-gene analysis is limiting with FFPE tissues, while targeted gene set approaches effectively distinguish ER+ from ER- breast cancers. Novel utilization of regulon analysis identified the transcription factor KDM4B to associate with ER+ disease, with KDM4B regulon activity and gene expression having prognostic significance in an independent cohort of ER+ cases. CONCLUSION: Our results, which outline a robust FFPE-RNA-seq pipeline for broad use, support utilizing FFPE tissues to address key questions in the breast cancer field, including the delineation between indolent and life-threatening disease, biological stratification and molecular mechanisms of treatment resistance.

Effects of Selective Exclusion of Patients on Preterm Birth Test Performance.

The need to reduce the rate of preterm delivery and the recent emergence of technologies that measure hundreds of biological analytes (eg, genomics, transcriptomics, metabolomics, proteomics; collectively referred to as "omics approaches") have led to proliferation of potential diagnostic biomarkers. On review of the literature, a concern must be raised regarding experimental design and data analysis reporting. Specifically, inaccurate performance has often been reported after selective exclusion of patients around the definition boundary of preterm birth. For example, authors may report the performance of a preterm delivery predictor by using patients who delivered early preterm compared with deliveries at 37 weeks of gestation or greater. A key principle that must be maintained during the development of any predictive test is to communicate performance for all patients for whom the test will be applicable clinically (ie, the intended-use population), which for prediction of preterm birth includes patients delivering throughout the spectrum of gestational ages, as this is what is to be predicted, and not known at the time of testing. Using biomarker data collected from the U.S.-based Proteomic Assessment of Preterm Risk clinical trial, we provide examples where the area under the receiver operating characteristic curve for the same test artifactually improves from 0.68 (for preterm delivery at less than 37 weeks of gestation) or 0.76 (for preterm delivery at less than 32 weeks of gestation) to 0.91 when patients who deliver late preterm are excluded. We review this phenomenon in this commentary and offer recommendations for clinicians and investigators going forward. FUNDING SOURCE:: Sera Prognostics.

BET bromodomain inhibition blocks the function of a critical AR-independent master regulator network in lethal prostate cancer.

BET bromodomain inhibitors block prostate cancer cell growth at least in part through c-Myc and androgen receptor (AR) suppression. However, little is known about other transcriptional regulators whose suppression contributes to BET bromodomain inhibitor anti-tumor activity. Moreover, the anti-tumor activity of BET bromodomain inhibition in AR-independent castration-resistant prostate cancers (CRPC), whose frequency is increasing, is also unknown. Herein, we demonstrate that BET bromodomain inhibition blocks growth of a diverse set of CRPC cell models, including those that are AR-independent or in which c-Myc is not suppressed. To identify transcriptional regulators whose suppression accounts for these effects, we treated multiple CRPC cell lines with the BET bromodomain inhibitor JQ1 and then performed RNA-sequencing followed by Master Regulator computational analysis. This approach identified several previously unappreciated transcriptional regulators that are highly expressed in CRPC and whose suppression, via both transcriptional or post-translational mechanisms, contributes to the anti-tumor activity of BET bromodomain inhibitors.

Intratracheal Administration of siRNA Triggers mRNA Silencing in the Lung to Modulate T Cell Immune Response and Lung Inflammation.

Clinical application of siRNA-based therapeutics outside of the liver has been hindered by the inefficient delivery of siRNA effector molecules into extra-hepatic organs and cells of interest. To understand the parameters that enable RNAi activity in vivo, it is necessary to develop a systematic approach to identify which cells within a tissue are permissive to oligonucleotide internalization and activity. In the present study, we evaluate the distribution and activity within the lung of chemically stabilized siRNA to characterize cell-type tropism and structure-activity relationship. We demonstrate intratracheal delivery of fully modified siRNA for RNAi-mediated target knockdown in lung CD11c+ cells (dendritic cells, alveolar macrophages) and alveolar epithelial cells. Finally, we use an allergen-induced model of lung inflammation to demonstrate the capacity of inhaled siRNA to induce target knockdown in dendritic cells and ameliorate lung pathology.

Maintenance of MYC expression promotes de novo resistance to BET bromodomain inhibition in castration-resistant prostate cancer.

The BET bromodomain protein BRD4 is a chromatin reader that regulates transcription, including in cancer. In prostate cancer, specifically, the anti-tumor activity of BET bromodomain inhibition has been principally linked to suppression of androgen receptor (AR) function. MYC is a well-described BRD4 target gene in multiple cancer types, and prior work demonstrates that MYC plays an important role in promoting prostate cancer cell survival. Importantly, several BET bromodomain clinical trials are ongoing, including in prostate cancer. However, there is limited information about pharmacodynamic markers of response or mediators of de novo resistance. Using a panel of prostate cancer cell lines, we demonstrated that MYC suppression-rather than AR suppression-is a key determinant of BET bromodomain inhibitor sensitivity. Importantly, we determined that BRD4 was dispensable for MYC expression in the most resistant cell lines and that MYC RNAi + BET bromodomain inhibition led to additive anti-tumor activity in the most resistant cell lines. Our findings demonstrate that MYC suppression is an important pharmacodynamic marker of BET bromodomain inhibitor response and suggest that targeting MYC may be a promising therapeutic strategy to overcome de novo BET bromodomain inhibitor resistance in prostate cancer.

Cell fusion potentiates tumor heterogeneity and reveals circulating hybrid cells that correlate with stage and survival.

High lethality rates associated with metastatic cancer highlight an urgent medical need for improved understanding of biologic mechanisms driving metastatic spread and identification of biomarkers predicting late-stage progression. Numerous neoplastic cell intrinsic and extrinsic mechanisms fuel tumor progression; however, mechanisms driving heterogeneity of neoplastic cells in solid tumors remain obscure. Increased mutational rates of neoplastic cells in stressed environments are implicated but cannot explain all aspects of tumor heterogeneity. We present evidence that fusion of neoplastic cells with leukocytes (for example, macrophages) contributes to tumor heterogeneity, resulting in cells exhibiting increased metastatic behavior. Fusion hybrids (cells harboring hematopoietic and epithelial properties) are readily detectible in cell culture and tumor-bearing mice. Further, hybrids enumerated in peripheral blood of human cancer patients correlate with disease stage and predict overall survival. This unique population of neoplastic cells provides a novel biomarker for tumor staging, as well as a potential therapeutic target for intervention.

Discovery of Selective RNA-Binding Small Molecules by Affinity-Selection Mass Spectrometry.

Recent advances in understanding the relevance of noncoding RNA (ncRNA) to disease have increased interest in drugging ncRNA with small molecules. The recent discovery of ribocil, a structurally distinct synthetic mimic of the natural ligand of the flavin mononucleotide (FMN) riboswitch, has revealed the potential chemical diversity of small molecules that target ncRNA. Affinity-selection mass spectrometry (AS-MS) is theoretically applicable to high-throughput screening (HTS) of small molecules binding to ncRNA. Here, we report the first application of the Automated Ligand Detection System (ALIS), an indirect AS-MS technique, for the selective detection of small molecule-ncRNA interactions, high-throughput screening against large unbiased small-molecule libraries, and identification and characterization of novel compounds (structurally distinct from both FMN and ribocil) that target the FMN riboswitch. Crystal structures reveal that different compounds induce various conformations of the FMN riboswitch, leading to different activity profiles. Our findings validate the ALIS platform for HTS screening for RNA-binding small molecules and further demonstrate that ncRNA can be broadly targeted by chemically diverse yet selective small molecules as therapeutics.

Vitamin C Prevents Offspring DNA Methylation Changes Associated with Maternal Smoking in Pregnancy.

RATIONALE: Infants whose mothers smoked during pregnancy demonstrate lifelong decreases in pulmonary function. DNA methylation changes associated with maternal smoking during pregnancy have been described in placenta and cord blood at delivery, in fetal lung, and in buccal epithelium and blood during childhood. We demonstrated in a randomized clinical trial ( ClinicalTrials.gov identifier, NCT00632476) that vitamin C supplementation to pregnant smokers can lessen the impact of maternal smoking on offspring pulmonary function and decrease the incidence of wheeze at 1 year of age. OBJECTIVES: To determine whether vitamin C supplementation reduces changes in offspring methylation in response to maternal smoking and whether methylation at specific CpGs is also associated with respiratory outcomes. METHODS: Targeted bisulfite sequencing was performed with a subset of placentas, cord blood samples, and buccal samples collected during the NCT00632476 trial followed by independent validation of selected cord blood differentially methylated regions, using bisulfite amplicon sequencing. MEASUREMENTS AND MAIN RESULTS: The majority (69.03%) of CpGs with at least 10% methylation difference between placebo and nonsmoker groups were restored (by at least 50%) toward nonsmoker levels with vitamin C treatment. A significant proportion of restored CpGs were associated with phenotypic outcome with greater enrichment among hypomethylated CpGs. CONCLUSIONS: We identified a pattern of normalization in DNA methylation by vitamin C supplementation across multiple loci. The consistency of this pattern across tissues and time suggests a systemic and persistent effect on offspring DNA methylation. Further work is necessary to determine how genome-wide changes in DNA methylation may mediate or reflect persistent effects of maternal smoking on lung function.