Using SELDI-TOF mass spectrometry on amniotic fluid and for clinical proteomics and theranostics in disorders of pregnancy

Evaluation of the Molecular Mechanisms of Sepsis Using Proteomics

Sepsis is a complex syndrome promoted by pathogenic and host factors; it is characterized by dysregulated host responses and multiple organ dysfunction, which can lead to death. However, its underlying molecular mechanisms remain unknown. Proteomics, as a biotechnology research area in the post-genomic era, paves the way for large-scale protein characterization. With the rapid development of proteomics technology, various approaches can be used to monitor proteome changes and identify differentially expressed proteins in sepsis, which may help to understand the pathophysiological process of sepsis. Although previous reports have summarized proteomics-related data on the diagnosis of sepsis and sepsis-related biomarkers, the present review aims to comprehensively summarize the available literature concerning “sepsis”, “proteomics”, “cecal ligation and puncture”, “lipopolysaccharide”, and “post-translational modifications” in relation to proteomics research to provide novel insights into the molecular mechanisms of sepsis.

Power of proteomics in linking oxidative stress and female infertility

Endometriosis, PCOS, and unexplained infertility are currently the most common diseases rendering large numbers of women infertile worldwide. Oxidative stress, due to its deleterious effects on proteins and nucleic acids, is postulated to be the one of the important mechanistic pathways in differential expression of proteins and in these diseases. The emerging field of proteomics has allowed identification of proteins involved in cell cycle, as antioxidants, extracellular matrix (ECM), cytoskeleton, and their linkage to oxidative stress in female infertility related diseases. The aim of this paper is to assess the association of oxidative stress and protein expression in the reproductive microenvironments such as endometrial fluid, peritoneal fluid, and follicular fluid, as well as reproductive tissues and serum. The review also highlights the literature that proposes the use of the fertility related proteins as potential biomarkers for noninvasive and early diagnosis of the aforementioned diseases rather than utilizing the more invasive methods used currently. The review will highlight the power of proteomic profiles identified in infertility related disease conditions and their linkage with underlying oxidative stress. The power of proteomics will be reviewed with regard to eliciting molecular mechanisms for early detection and management of these infertility related conditions.

Multivariate adaptive regression splines analysis to predict biomarkers of spontaneous preterm birth

OBJECTIVE

To develop classification models of demographic/clinical factors and biomarker data from spontaneous preterm birth in African Americans and Caucasians.

DESIGN

Secondary analysis of biomarker data using multivariate adaptive regression splines (MARS), a supervised machine learning algorithm method.

SETTING

Analysis of data on 36 biomarkers from 191 women was reduced by MARS to develop predictive models for preterm birth in African Americans and Caucasians.

SAMPLES

Maternal plasma, cord plasma collected at admission for preterm or term labor and amniotic fluid at delivery.

METHODS

Data were partitioned into training and testing sets. Variable importance, a relative indicator (0-100%) and area under the receiver operating characteristic curve (AUC) characterized results.

RESULTS

Multivariate adaptive regression splines generated models for combined and racially stratified biomarker data. Clinical and demographic data did not contribute to the model. Racial stratification of data produced distinct models in all three compartments. In African Americans maternal plasma samples IL-1RA, TNF-α, angiopoietin 2, TNFRI, IL-5, MIP1α, IL-1β and TGF-α modeled preterm birth (AUC train: 0.98, AUC test: 0.86). In Caucasians TNFR1, ICAM-1 and IL-1RA contributed to the model (AUC train: 0.84, AUC test: 0.68). African Americans cord plasma samples produced IL-12P70, IL-8 (AUC train: 0.82, AUC test: 0.66). Cord plasma in Caucasians modeled IGFII, PDGFBB, TGF-β1 , IL-12P70, and TIMP1 (AUC train: 0.99, AUC test: 0.82). Amniotic fluid in African Americans modeled FasL, TNFRII, RANTES, KGF, IGFI (AUC train: 0.95, AUC test: 0.89) and in Caucasians, TNF-α, MCP3, TGF-β3 , TNFR1 and angiopoietin 2 (AUC train: 0.94 AUC test: 0.79).

CONCLUSIONS

Multivariate adaptive regression splines models multiple biomarkers associated with preterm birth and demonstrated racial disparity.

Amniotic fluid: the use of high-dimensional biology to understand fetal well-being

Our aim was to review the use of high-dimensional biology techniques, specifically transcriptomics, proteomics, and metabolomics, in amniotic fluid to elucidate the mechanisms behind preterm birth or assessment of fetal development. We performed a comprehensive MEDLINE literature search on the use of transcriptomic, proteomic, and metabolomic technologies for amniotic fluid analysis. All abstracts were reviewed for pertinence to preterm birth or fetal maturation in human subjects. Nineteen articles qualified for inclusion. Most articles described the discovery of biomarker candidates, but few larger, multicenter replication or validation studies have been done. We conclude that the use of high-dimensional systems biology techniques to analyze amniotic fluid has significant potential to elucidate the mechanisms of preterm birth and fetal maturation. However, further multicenter collaborative efforts are needed to replicate and validate candidate biomarkers before they can become useful tools for clinical practice. Ideally, amniotic fluid biomarkers should be translated to a noninvasive test performed in maternal serum or urine.

Intact protein profiling in breast cancer biomarker discovery: protein identification issue and the solutions based on 3D protein separation, bottom-up and top-down mass spectrometry

Proteomics profiling of intact proteins based on MALDI-TOF MS and derived platforms has been used in cancer biomarker discovery studies. This approach suffers from a number of limitations such as low resolution, low sensitivity, and that no knowledge is available on the identity of the respective proteins in the discovery mode. Nevertheless, it remains the most high-throughput, untargeted mode of clinical proteomics studies to date. Here we compare key protein separation and MS techniques available for protein biomarker identification in this type of studies and define reasons of uncertainty in protein peak identity. As a result of critical data analysis, we consider 3D protein separation and identification workflows as optimal procedures. Subsequently, we present a new protocol based on 3D LC-MS/MS with top-down at high resolution that enabled the identification of HNRNP A2/B1 intact peptide as correlating with the estrogen receptor expression in breast cancer tissues. Additional development of this general concept toward next generation, top-down based protein profiling at high resolution is discussed.

Advances in medical diagnosis of intra-amniotic infection

INTRODUCTION

Intrauterine infection is a global problem and a significant contributor to morbidity and perinatal death. The host response to infection causes an inflammatory state that acts synergistically with microbial insult to induce preterm birth and fetal damage. Prompt and accurate diagnosis of intra-amniotic infection in the asymptomatic stage of the disease is critical for improved maternal and neonatal outcomes.

AREAS COVERED

This article provides an overview of the most recent progress, challenges, and opportunities for discovery and clinical implementation of various maternal serum, cervicovaginal, and amniotic fluid biomarkers in pregnancies complicated by intra-amniotic infection.

EXPERT OPINION

Clinically relevant biomarkers are critical to the accurate diagnostic of intrauterine infection. Front-end implementation of such biomarkers will also translate in lower incidence of early-onset neonatal sepsis (EONS) which is an important determinant of neonatal morbidity and mortality associated with prematurity. However, of the hundreds of differentially expressed proteins, only few may have clinical utility and thus function as biomarkers. The small number of validation studies along with barriers to implementation of technological innovations in the clinical setting are current limitations.

Proteomics/diagnosis of chorioamnionitis and of relationships with the fetal exposome

Proteomics, a relatively young science, originally emerged as a complement to genomics research. By definition, the goal of proteomics is to provide a snapshot of all the proteins within an organism, tissue or biological sample at a given moment. Proteomics has the ability to single out one or more proteins (biomarkers) that change consistently in affected subjects as compared to those disease-free. From a proteomics perspective, chorioamnionitis poses both challenges and opportunities. Challenges relate to the dynamic course of the inflammatory process, and compartmentalization of the gestational sac in relation to the maternal compartment. An inability to evaluate the amniotic fluid non-invasively and repeatedly for meaningful changes in its proteome, and lack of a true gold standard for diagnosis of inflammation and/or infection, represent additional challenges. On the other hand, the unbiased and holistic nature of proteomics offers a real opportunity to improve the current diagnostic and prognostic algorithms for chorioamnionitis. Even at this current stage there are reasons to believe that proteomic biomarkers will improve the understanding of how chorioamnionitis programs or affects the fetus in utero, thus defining its exposome (sum of interactions between genetic make-up of the fetus and the intrauterine environment) of pregnancies affected by infection and/or inflammation. This review summarizes the results of proteomics studies that have aimed or reached these goals.

The role of proteomics in the diagnosis of chorioamnionitis and early-onset neonatal sepsis

Intrauterine infection is a unique pathologic process that raises the risk for early-onset neonatal sepsis (EONS). By acting synergistically with prematurity, EONS increases the risk for adverse neonatal outcomes, including intraventricular hemorrhage and cerebral palsy. Although several pathways for the pathogenesis of fetal damage have been proposed, the basic molecular mechanisms that modulate these events remain incompletely understood. Discovery of clinically and biologically relevant biomarkers able to reveal key pathogenic pathways and predict pregnancies at risk for antenatal fetal damage is a priority. Proteomics provides a unique opportunity to fill this gap.