Shotgun proteomics identifies serum fibronectin as a candidate diagnostic biomarker for inclusion in future multiplex tests for ectopic pregnancy

Untargeted Metabolomic Biomarker Discovery for the Detection of Ectopic Pregnancy

Ectopic pregnancy (EP) is the leading cause of maternal morbidity and mortality in the first trimester. Using an untargeted metabolomic approach, we sought to identify putative plasma biomarkers using tandem liquid chromatography-mass spectrometry for the detection of tubal EP. This case-control study included the prospective recruitment of 50 tubal EP cases and 50 early intrauterine pregnancy controls. To avoid over-fitting, logistic regression models were developed in a randomly selected discovery group (30 cases vs. 30 controls) and validated in the test group (20 cases vs. 20 controls). In total, 585 mass spectral features were detected, of which 221 molecular features were significantly altered in EP plasma (p < 0.05). Molecular networking and metabolite identification was employed using the Global Natural Products Social Molecular Networking (GNPS) database, which identified 97 metabolites at a high confidence level. Top significant metabolites include subclasses of sphingolipids, carnitines, glycerophosphocholines, and tryptophan metabolism. The top regression model, consisting of D-erythro-sphingosine and oleoyl-carnitine, was validated in a test group and achieved an area under receiving operating curve (AUC) (95% CI) = 0.962 (0.910-1) with a sensitivity of 100% and specificity of 95.9%. Metabolite alterations indicate alterations related to inflammation and abnormal placentation in EP. The validation of these metabolite biomarkers in the future could potentially result in improved early diagnosis.

An intrauterine genomic classifier reliably delineates the location of nonviable pregnancies

OBJECTIVE

To compare the intrauterine gene expression signatures of women with surgically confirmed ectopic pregnancy (ECT) and those of women with miscarriage to inform the development of a genomic classifier for the reliable delineation of pregnancy location in women with clinically nonviable pregnancies of unknown location (NV-PULs).

DESIGN

Discovery-based prospective cohort study.

SETTING

Academic medical center.

PATIENT(S)

Women with clinically nonviable early pregnancy to include abnormal intrauterine pregnancy (AIUP), ECT, or NV-PUL.

INTERVENTION(S)

Endometrial (EM) pipelle sampling of the uterus was conducted at the time of scheduled surgery for clinically nonviable early pregnancy (dilation and curettage, manual vacuum aspiration, or laparoscopy). All pregnancy locations were surgically and/or histologically confirmed as intrauterine or ectopic.

MAIN OUTCOME MEASURE(S)

Gene expression profiles as determined by array hybridization, quantitative real-time polymerase chain reaction, and nCounter technology.

RESULT(S)

Intrauterine samples were obtained by EM pipelle from 27 women undergoing surgery for a clinically nonviable early pregnancy. Comparison of array-based global gene expression signatures from women with histologically confirmed ECT versus AIUP revealed 61 differentially expressed genes from which the 5 most informative were included in the pregnancy location classifier. All 5 genes (C20orf85, LRRC46, RSPH4A, WDR49, and ZBBX) were cilia-associated and showed increased expression in pipelle samples from women with ECT relative to expression in samples from women with AIUP. The 5-gene classifier demonstrated an average area under the receiver operator characteristic curve of 0.97 for the detection of ECT. In an external test set composed of publicly available EM pipelle-based gene expression data from a study with similar ECT and AIUP cohorts (n = 19), the classifier revealed an average area under the receiver operator characteristic curve of 0.84.

CONCLUSION(S)

Consistently increased expression of cilia-associated genes in the uterine cavity of women with ECT provides a reliable molecular signal for the delineation of pregnancy location in women with clinically assessed NV-PUL. A classifier consisting of the 5 most informative cilia-associated genes demonstrated 91% (42/46) accuracy in predicting the pregnancy location.

Metabolomic identification of novel diagnostic biomarkers in ectopic pregnancy

INTRODUCTION

Ectopic pregnancy (EP) is a potentially life-threatening condition and early diagnosis still remains a challenge, causing a delay in management leading to tubal rupture.

OBJECTIVES

To identify putative plasma biomarkers for the detection of tubal EP and elucidate altered biochemical pathways in EP compared to intrauterine pregnancies.

METHODS

This case-control study included prospective recruitment of 39 tubal EP cases and 89 early intrauterine pregnancy controls. Plasma samples were biochemically profiled using proton nuclear magnetic resonance spectroscopy (¹H NMR). To avoid over-fitting, datasets were randomly divided into a discovery group (26 cases vs 60 controls) and a test group (13 cases and 29 controls). Logistic regression models were developed in the discovery group and validated in the independent test group. Area under the receiver operating characteristics curve (AUC), 95% confidence interval (CI), sensitivity, and specificity values were calculated.

RESULTS

In total 13 of 43 (30.3%) metabolite concentrations were significantly altered in EP plasma (p < 0.05). Metabolomic profiling yielded significant separation between EP and controls (p < 0.05). Independent validation of a two-metabolite model consisting of lactate and acetate, achieved an AUC (95% CI) = 0.935 (0.843-1.000) with a sensitivity of 92.3% and specificity of 96.6%. The second metabolite model (D-glucose, pyruvate, acetoacetate) performed well with an AUC (95% CI) = 0.822 (0.657-0.988) and a sensitivity of 84.6% and specificity of 86.2%.

CONCLUSION

We report novel metabolomic biomarkers with a high accuracy for the detection of EP. Accurate biomarkers could potentially result in improved early diagnosis of tubal EP cases.

The potential value of activin B and fibronectin for the triage of pregnancies of unknown location and prediction of first trimester viability

Aim

We have assessed the potential predictive ability of the biomarkers activin B and fibronectin (FN1) alone and when added to established markers for triaging patients as being at low or high risk of ectopic pregnancy (EP). We also assessed their use as predictors of viability at 12 weeks gestation.

Methods

Exploratory secondary analysis of a prospective study including all women classified as a pregnancy of known location (PUL) based on transvaginal ultrasonography between January and December 2007 at the early pregnancy unit of St Georges' Hospital (London). We used multinomial logistic regression to assess the diagnostic potential of the biomarkers to triage PUL at high risk of complications (EP or persistent PUL), and standard binary logistic regression to predict first trimester viability at 12 weeks.

Results

For discriminating high-risk (n = 16) from low-risk PUL (n = 93), the area under the receiver operating characteristic curve (AUC) was 0.75 (95% confidence interval 0.60-0.85) for activin B and 0.55 (0.41-0.68) for FN1. Adding activin B to a multinomial logistic regression model incorporating β-hCG ratio and initial progesterone yielded odds ratios of 0.16 (0.05-0.55) for failing vs high-risk PUL and 0.29 (0.07-1.19) for intrauterine vs high-risk PUL and increased the model's AUC from 0.84 to 0.89. At a risk threshold of 5% for high-risk PUL, sensitivity increased from 84% to 87% and specificity from 48% to 64%. For discriminating viable (n = 28) from non-viable (n = 81) pregnancies at 12 weeks, both markers had an AUC of 0.54.

Conclusions

Our results suggested that activin B may be a promising marker to improve PUL triage in addition to established markers.

Synthesis of stable isotopically labeled peptides with filter-assisted enzymatic labeling for the diagnosis of hepatitis B virus infection utilizing mass spectrometry-based proteomics strategy

A facile method for the preparation of stable isotopically labeled peptides was developed by means of filter-assisted tryptic ¹⁶O/¹⁸O water labeling, which could be directly applied to the determination of hepatitis B virus infection from human serum with tandem mass spectrometry. Tryptic peptides of hepatitis B surface antigen or hepatitis B e antigen from different subtypes of hepatitis B virus were synthesized with traditional solid-phase peptide synthesis as potential biomarkers. Trypsin catalyzed oxygen-18 exchange at their amidated c-terminus of arginine or lysine residue. The protease catalyzed oxygen-18 to oxygen-16 back exchange reaction was eliminated due to the complete removal of trypsin by the centrifugal filter containing a thin membrane associated with molecular weight cut-off of 10 KDa. The synthetic isotopic peptides were spiked into trichloroacetic acid/acetone precipitated human serum as internal standards and were selectively detected with multiplexed parallel reaction monitoring on a hybrid quadrupole-orbitrap mass spectrometer. The limit of detection for all synthetic peptides were in the range of 0.09 fmol-1.13 fmol. The results indicated that the peptide YLWEWASVR derived from hepatitis B surface antigen was quantified approximately 200 fmol per μl serum and may serve as a diagnostic biomarker for the detection of hepatitis B virus infected disease.

Challenges in biomarker discovery with MALDI-TOF MS

MALDI-TOF MS technique is commonly used in system biology and clinical studies to search for new potential markers associated with pathological conditions. Despite numerous concerns regarding a sample preparation or processing of complex data, this strategy is still recognized as a popular tool and its awareness has risen in the proteomic community over the last decade. In this review, we present comprehensive application of MALDI mass spectrometry with special focus on profiling research. We also discuss major advantages and disadvantages of universal sample preparation methods such as micro-SPE columns, immunodepletion or magnetic beads, and we show the potential of nanostructured materials in capturing low molecular weight subproteomes. Furthermore, as the general protocol considerably affects spectra quality and interpretation, an alternative solution for improved ion detection, including hydrophobic constituents, data processing and statistical analysis is being considered in up-to-date profiling pattern. In conclusion, many reports involving MALDI-TOF MS indicated highly abundant proteins as valuable indicators, and at the same time showed the inaccuracy of available methods in the detection of low abundant proteome that is the most interesting from the clinical perspective. Therefore, the analytical aspects of sample preparation methods should be standardized to provide a reproducible, low sample handling and credible procedure.

Molecular diagnostics and therapeutics for ectopic pregnancy

Ectopic pregnancies are a serious gynaecological emergency that can be fatal. As such, prompt diagnosis and safe timely treatment is essential. Here, we review the literature on the development of molecularly targeted diagnostics and therapeutics for ectopic pregnancy. A blood-based biomarker that accurately identifies an ectopic pregnancy could be used to offer early diagnostic certainty in cases where ultrasound cannot determine the location of the embryo ('a pregnancy of unknown location'). Molecules examined so far can be broadly grouped into biological themes of relevance to reproduction: (i) Fallopian tube (dys)function, (ii) embryo/trophoblast growth, (iii) corpus luteum function, (iv) inflammation, (v) uterine function and (vi) angiogenesis. While a sensitive and specific biomarker for ectopic pregnancy has yet to be identified, it is possible that improvements in platform technologies or a multi-modal biomarker approach may yield an accurate diagnostic biomarker test. Furthermore, with the advent of better imaging technology, the need for a blood-based biomarker test may be superseded by improvements in ultrasound or magnetic resonance imaging technology. There have been some recent preclinical studies describing molecularly targeted therapeutic approaches for ectopic pregnancy. Notably, bench-to-bedside studies have examined the use of combination gefitinib (orally available epidermal growth factor receptor inhibitor) and methotrexate. Preclinical studies suggest that combination gefitinib and methotrexate is highly effective in inducing placental cell death, and is significantly more effective than methotrexate alone. In early human trials, encouraging preliminary efficacy data have shown that combination gefitinib and methotrexate can rapidly resolve tubal ectopic pregnancies, and large extra-tubal ectopic pregnancies. If a large clinical randomized controlled trial confirms these findings, combination gefitinib and methotrexate could become a new medical treatment option for ectopic pregnancy.

Identification of ENO1 as a potential sputum biomarker for early-stage lung cancer by shotgun proteomics

BACKGROUND

Lung cancer is the leading cancer killer. Early detection will reduce the related deaths. The objective of this study was to identify potential biomarkers for early-stage lung cancer in sputum supernatant.

MATERIALS AND METHODS

Using shotgun proteomics, we detected changes in protein profiles that were associated with lung cancer by analyzing sputum supernatants from 6 patients with early-stage lung cancer and 5 cancer-free controls. Using western blotting, we validated the proteomic results in 22 lung cancer cases and 22 controls. Using enzyme-linked immunosorbent assay (ELISA), we evaluated the diagnostic performance of the biomarker candidates in an independent set of 35 cases and 36 controls.

RESULTS

Proteomics identified 8 biomarker candidates for lung cancer. Western blotting validation of the candidates showed that enolase 1 (ENO1) displayed a higher expression level in patients with cancer than in cancer-free individuals (P = .015). ELISA revealed that the assessment of ENO1 expression in sputum supernatant had 58.33% sensitivity and 80.00% specificity in distinguishing patients with stage I lung cancer from cancer-free individuals.

CONCLUSION

The analysis of protein biomarkers in sputum may provide a potential approach for the early detection of lung cancer. Future validation of all the candidates defined by shotgun proteomics in a large cohort study may help develop additional biomarkers that can be added to ENO1 to provide more diagnostic efficacy for lung cancer.