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.

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..

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.

Assessment of roles for the Rho-specific guanine nucleotide dissociation inhibitor Ly-GDI in platelet function: a spatial systems approach.

On activation at sites of vascular injury, platelets undergo morphological alterations essential to hemostasis via cytoskeletal reorganizations driven by the Rho GTPases Rac1, Cdc42, and RhoA. Here we investigate roles for Rho-specific guanine nucleotide dissociation inhibitor proteins (RhoGDIs) in platelet function. We find that platelets express two RhoGDI family members, RhoGDI and Ly-GDI. Whereas RhoGDI localizes throughout platelets in a granule-like manner, Ly-GDI shows an asymmetric, polarized localization that largely overlaps with Rac1 and Cdc42 as well as microtubules and protein kinase C (PKC) in platelets adherent to fibrinogen. Antibody interference and platelet spreading experiments suggest a specific role for Ly-GDI in platelet function. Intracellular signaling studies based on interactome and pathways analyses also support a regulatory role for Ly-GDI, which is phosphorylated at PKC substrate motifs in a PKC-dependent manner in response to the platelet collagen receptor glycoprotein (GP) VI-specific agonist collagen-related peptide. Additionally, PKC inhibition diffuses the polarized organization of Ly-GDI in spread platelets relative to its colocalization with Rac1 and Cdc42. Together, our results suggest a role for Ly-GDI in the localized regulation of Rho GTPases in platelets and hypothesize a link between the PKC and Rho GTPase signaling systems in platelet function.

DLK1-DIO3 genomic imprinted microRNA cluster at 14q32.2 defines a stemlike subtype of hepatocellular carcinoma associated with poor survival.

Hepatocellular carcinoma (HCC) is a heterogeneous and highly aggressive malignancy, for which there are no effective cures. Identification of a malignant stemlike subtype of HCC may offer patients with a dismal prognosis a potential targeted therapy using c-MET and Wnt pathway inhibitors. MicroRNAs (miRNAs) show promise as diagnostic and prognostic tools for cancer detection and stratification. Using a TRE-c-Met-driven transgenic HCC mouse model, we identified a cluster of 23 miRNAs that is encoded within the Dlk1-Gtl2 imprinted region on chromosome 12qF1 overexpressed in all of the isolated liver tumors. Interestingly, this region is conserved among mammalian species and maps to the human DLK1-DIO3 region on chromosome 14q32.2. We thus examined the expression of the DLK1-DIO3 miRNA cluster in a cohort of 97 hepatitis B virus-associated HCC patients and identified a subgroup (n = 18) of patients showing strong coordinate overexpression of miRNAs in this cluster but not in other cancer types (breast, lung, kidney, stomach, and colon) that were tested. Expression levels of imprinted gene transcripts from neighboring loci in this 14q32.2 region and from a subset of other imprinted sites were concomitantly elevated in human HCC. Interestingly, overexpression of the DLK1-DIO3 miRNA cluster was positively correlated with HCC stem cell markers (CD133, CD90, EpCAM, Nestin) and associated with a high level of serum α-fetoprotein, a conventional biomarker for liver cancer, and poor survival rate in HCC patients. In conclusion, our findings suggest that coordinate up-regulation of the DLK1-DIO3 miRNA cluster at 14q32.2 may define a novel molecular (stem cell-like) subtype of HCC associated with poor prognosis.

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.

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 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.

RNA-induced silencing complex-bound small interfering RNA is a determinant of RNA interference-mediated gene silencing in mice.

Deeper knowledge of pharmacokinetic and pharmacodynamic (PK/PD) concepts for RNA therapeutics is important to streamline the drug development process and for rigorous selection of best performing drug candidates. Here we characterized the PK/PD relationship for small interfering RNAs (siRNAs) targeting luciferase by examining siRNA concentration in plasma and liver, the temporal RNA-induced silencing complex binding profiles, mRNA reduction, and protein inhibition measured by noninvasive bioluminescent imaging. A dose-dependent and time-related decrease in bioluminescence was detected over 25 days after a single treatment of a lipid nanoparticle-formulated siRNA targeting luciferase messenger RNA. A direct relationship was observed between the degree of in vivo mRNA and protein reduction and the Argonaute2 (Ago2)-bound siRNA fraction but not with the total amount of siRNA found in the liver, suggesting that the Ago2-siRNA complex is the key determinant of target inhibition. These observations were confirmed for an additional siRNA that targets endogenously expressed Sjögren syndrome antigen B (Ssb) mRNA, indicating that our observations are not limited to a transgenic mouse system. Our data provide detailed information of the temporal regulation of siRNA liver delivery, Ago2 loading, mRNA reduction, and protein inhibition that are essential for the rapid and cost-effective clinical development of siRNAs therapeutics.

MicroRNA-like off-target transcript regulation by siRNAs is species specific.

siRNAs mediate sequence-specific gene silencing in cultured mammalian cells but also silence unintended transcripts. Many siRNA off-target transcripts match the guide-strand "seed region," similar to the way microRNAs match their target sites. The extent to which this seed-matched, microRNA-like, off-target silencing affects the specificity of therapeutic siRNAs in vivo is currently unknown. Here, we compare microRNA-like off-target regulations in mouse liver in vivo with those seen in cell culture for a series of therapeutic candidate siRNAs targeting Apolipoprotein B (APOB). Each siRNA triggered regulation of consistent microRNA-like off-target transcripts in mouse livers and in cultured mouse liver tumor cells. In contrast, there was only random overlap between microRNA-like off-target transcripts from cultured human and mouse liver tumor cells. Therefore, siRNA therapeutics may trigger microRNA-like silencing of many unintended targets in vivo, and the potential toxicities caused by these off-target gene regulations cannot be accurately assessed in rodent models.

microRNA-122 as a regulator of mitochondrial metabolic gene network in hepatocellular carcinoma.

Tumorigenesis involves multistep genetic alterations. To elucidate the microRNA (miRNA)-gene interaction network in carcinogenesis, we examined their genome-wide expression profiles in 96 pairs of tumor/non-tumor tissues from hepatocellular carcinoma (HCC). Comprehensive analysis of the coordinate expression of miRNAs and mRNAs reveals that miR-122 is under-expressed in HCC and that increased expression of miR-122 seed-matched genes leads to a loss of mitochondrial metabolic function. Furthermore, the miR-122 secondary targets, which decrease in expression, are good prognostic markers for HCC. Transcriptome profiling data from additional 180 HCC and 40 liver cirrhotic patients in the same cohort were used to confirm the anti-correlation of miR-122 primary and secondary target gene sets. The HCC findings can be recapitulated in mouse liver by silencing miR-122 with antagomir treatment followed by gene-expression microarray analysis. In vitro miR-122 data further provided a direct link between induction of miR-122-controlled genes and impairment of mitochondrial metabolism. In conclusion, miR-122 regulates mitochondrial metabolism and its loss may be detrimental to sustaining critical liver function and contribute to morbidity and mortality of liver cancer patients.

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.

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.

Transcripts targeted by the microRNA-16 family cooperatively regulate cell cycle progression.

microRNAs (miRNAs) are abundant, approximately 21-nucleotide, noncoding regulatory RNAs. Each miRNA may regulate hundreds of mRNA targets, but the identities of these targets and the processes they regulate are poorly understood. Here we have explored the use of microarray profiling and functional screening to identify targets and biological processes triggered by the transfection of human cells with miRNAs. We demonstrate that a family of miRNAs sharing sequence identity with miRNA-16 (miR-16) negatively regulates cellular growth and cell cycle progression. miR-16-down-regulated transcripts were enriched with genes whose silencing by small interfering RNAs causes an accumulation of cells in G(0)/G(1). Simultaneous silencing of these genes was more effective at blocking cell cycle progression than disruption of the individual genes. Thus, miR-16 coordinately regulates targets that may act in concert to control cell cycle progression.

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.

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.

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

Small interfering RNA screens reveal enhanced cisplatin cytotoxicity in tumor cells having both BRCA network and TP53 disruptions.

RNA interference technology allows the systematic genetic analysis of the molecular alterations in cancer cells and how these alterations affect response to therapies. Here we used small interfering RNA (siRNA) screens to identify genes that enhance the cytotoxicity (enhancers) of established anticancer chemotherapeutics. Hits identified in drug enhancer screens of cisplatin, gemcitabine, and paclitaxel were largely unique to the drug being tested and could be linked to the drug's mechanism of action. Hits identified by screening of a genome-scale siRNA library for cisplatin enhancers in TP53-deficient HeLa cells were significantly enriched for genes with annotated functions in DNA damage repair as well as poorly characterized genes likely having novel functions in this process. We followed up on a subset of the hits from the cisplatin enhancer screen and validated a number of enhancers whose products interact with BRCA1 and/or BRCA2. TP53(+/-) matched-pair cell lines were used to determine if knockdown of BRCA1, BRCA2, or validated hits that associate with BRCA1 and BRCA2 selectively enhances cisplatin cytotoxicity in TP53-deficient cells. Silencing of BRCA1, BRCA2, or BRCA1/2-associated genes enhanced cisplatin cytotoxicity approximately 4- to 7-fold more in TP53-deficient cells than in matched TP53 wild-type cells. Thus, tumor cells having disruptions in BRCA1/2 network genes and TP53 together are more sensitive to cisplatin than cells with either disruption alone.

Designing siRNA that distinguish between genes that differ by a single nucleotide.

Small interfering RNAs (siRNAs), the guides that direct RNA interference (RNAi), provide a powerful tool to reduce the expression of a single gene in human cells. Ideally, dominant, gain-of-function human diseases could be treated using siRNAs that specifically silence the mutant disease allele, while leaving expression of the wild-type allele unperturbed. Previous reports suggest that siRNAs can be designed with single nucleotide specificity, but no rational basis for the design of siRNAs with single nucleotide discrimination has been proposed. We systematically identified siRNAs that discriminate between the wild-type and mutant alleles of two disease genes: the human Cu, Zn superoxide dismutase (SOD1) gene, which contributes to the progression of hereditary amyotrophic lateral sclerosis through the gain of a toxic property, and the huntingtin (HTT) gene, which causes Huntington disease when its CAG-repeat region expands beyond approximately 35 repeats. Using cell-free RNAi reactions in Drosophila embryo lysate and reporter assays and microarray analysis of off-target effects in cultured human cells, we identified positions within an siRNA that are most sensitive to mismatches. We also show that purine:purine mismatches imbue an siRNA with greater discriminatory power than other types of base mismatches. siRNAs in which either a G:U wobble or a mismatch is located in the "seed" sequence, the specialized siRNA guide region responsible for target binding, displayed lower levels of selectivity than those in which the mismatch was located 3' to the seed; this region of an siRNA is critical for target cleavage but not siRNA binding. Our data suggest that siRNAs can be designed to discriminate between the wild-type and mutant alleles of many genes that differ by just a single nucleotide.

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.