A comparative proteomic analysis for non-invasive early prediction of hypoxic-ischemic injury in asphyxiated neonates.

AIM: Hypoxic Ischemic Encephalopathy (HIE) is one of the principal causes of neonatal mortality and long-term morbidity worldwide. The neonatal signs of mild cerebral injury are subtle, making an early precise diagnosis difficult. Delayed detection, poor prognosis, and lack of specific biomarkers for the disease are increasing mortality rates. In this study, we intended to identify specific biomarkers using comparative proteomic analysis to predict the severity of perinatal asphyxia so that its outcome can also be prevented. EXPERIMENTAL DESIGN: A case-control study was conducted on 38 neonates, and urine samples were collected within 24 and 72 h of life. A tandem mass spectrometry-based quantitative proteomics approach, followed by validation via sandwich ELISA, was performed. RESULTS: The LC-MS/MS-based proteomics analysis resulted in the identification of 1201 proteins in urine, with 229, 244, and 426 being differentially expressed in HIE-1, HIE-2, and HIE-3, respectively. Axon guidance, Diseases of programmed cell death, and Detoxification of reactive oxygen species pathways were significantly enriched in mild HIE versus severe HIE. Among the differentially expressed proteins in various stages of HIE, we chose to validate four proteins - APP, AGT, FABP1, and FN1 - via sandwich ELISA. Individual and cumulative ROC curves were plotted. AGT and FABP1 together showed high sensitivity, specificity, and accuracy as potential biomarkers for early diagnosis of HIE. CONCLUSION: Establishing putative urinary biomarkers will facilitate clinicians to more accurately screen neonates for brain injury and monitor the disease progression. Prompt treatment of neonates may reduce mortality and neurodevelopmental impairment.

A computational workflow for predicting cancer neo-antigens.

Neo-antigens presented on cell surface play a pivotal role in the success of immunotherapies. Peptides derived from mutant proteins are thought to be the primary source of neo-antigens presented on the surface of cancer cells. Mutation data from cancer genome sequencing is often used to predict cancer neo-antigens. However, this strategy is associated with significant false positives as many coding mutations may not be expressed at the protein level. Hence, we describe a computational workflow to integrate genomic and proteomic data to predictpotential neo-antigens.

A network map of netrin receptor UNC5B-mediated signaling.

UNC-5 Homolog B (UNC5B) is a member of the dependence receptor family. This family of receptors can induce two opposite intracellular signaling cascades depending on the presence or absence of the ligand and is thus capable of driving two opposing processes. UNC5B signaling has been implicated in several cancers, where it induces cell death in the absence of its ligand Netrin-1 and promotes cell survival in its presence. In addition, inhibition of Netrin-1 ligand has been reported to decrease invasiveness and angiogenesis in tumors. UNC5B signaling pathway has also been reported to be involved in several processes such as neural development, developmental angiogenesis and inflammatory processes. However, literature pertaining to UNC5B signaling is scarce and scattered. Considering the importance of UNC5B signaling, we developed a resource of signaling events mediated by UNC5B. Using data mined from published literature, we compiled an integrated pathway map consisting of 88 UNC5B-mediated signaling events and 55 proteins. These signaling events include 27 protein-protein interaction events, 33 catalytic events involving various post-translational modifications, 9 events of UNC5B-mediated protein activation/inhibition, 27 gene regulation events and 2 events of translocation. This pathway resource has been made available to the research community through NetPath ( http://www.netpath.org /), a manually curated resource of signaling pathways (Database URL: http://www.netpath.org/pathways?path_id=NetPath_172 ). The current resource provides a foundation for the understanding of UNC5B-mediated cellular responses. The development of resource will serve researchers to explore the mechanisms of UNC-5B signaling in cancers.