Dr. Eng Lo, Ph.D. from Massachussets General Hospital talks about how his team is advancing stroke research through proteomics. Collaborating with the Biomarkers Research Initiatives in Mass Spectrometry Center (BRIMS), his team is applying cutting edge mass spectrometry to identify and validate biomarkers.
Neurovascular disease is a complex multi-organ injury, encompassing a wide array of phenotypes. It involves multiple cell types of the brain, the blood–brain barrier, along with the peripheral systemic circulation, and multiple stroke subtypes. Individual confounders such as genetic variations, clinical risk factors, medication intake, and even food intake can skew the outcomes.
In the absence of appropriate clinical tools for patient selection or therapeutic follow-up, researchers advocate a systemic approach based on clinical proteomics to help understand the complex systemic effects of multi-organ neurovascular diseases and therapies. Researchers led by Drs. Ning and Lo collaborating with Dr. Lopez and Dr. Sarracino of Thermo-Fisher (BRIMS, Cambridge, MA) describe a ‘pharmaco-proteomic’ approach to improve risk stratification, widen therapeutic options, and explore novel targets in neurological disease. They review specific examples to illustrate the approach targeting three major issues: (i) thrombolytic treatment for ischemic stroke, (ii) therapeutic hypothermia for post-cardiac arrest syndrome, and (iii) treatment for patent foramen ovale (PFO) related paradoxical embolic stroke.1
Applying pharmaco-proteomic techniques enables measurements of systemic changes in plasma signaling before and after a speciﬁc intervention, minimizes confounders and helps monitor therapeutic efﬁcacy. Pharmacoproteomics has the potential to maximize beneﬁt–risk ratio in real time by delivering personalized interventions.2,3
Using “degradomics”, which measures composite protease degradation products following a specific stimulus, other researchers studied the serine protease tissue plasminogen activator (tPA) in ischemic stroke.4 Their findings suggest strong differences in protease patterns even up to 3–5 days after intravenous tPA administration, well beyond the half-life of tPA itself. The findings revealed a cascade of events in blood and systemic effects of therapy that are quantiﬁable in real time at the bedside. Clinicians are able to individualize the thrombolytic therapy by monitoring the treatment related systemic changes and signaling responses, balancing efficacy with risks of treatment related side effects such as hemorrhage and edema.
Similarly, the proteomic approach enables the study of systemic effects associated with therapeutic hypothermia (TH) in post-cardiac arrest syndrome, to improve both patient selection and prognosis. Post-cardiac arrest syndrome involves brain injury, myocardial dysfunction, and systemic ischemia/reperfusion response, following cardiac arrest. Post-translational modiﬁcations (PTM) such as glycosylation underlying hypo-metabolic state, cell signaling and recognition occur within 24 hours of TH. They mediate sepsis and coagulopathy. Glycosylation plays a key role in immune response and coagulation, TH’s major side effects. Proteomic enrichment and separation techniques can analyze the glycosylation patterns and signaling cascades in TH-treated patients with respect to clinical outcomes in real time.
The researchers next reviewed the use of proteomics in analysing the interaction between the brain and the heart in patent foramen ovale (PFO)-related embolic stroke. Patent foramen ovale (PFO) is a hole between the left and right atria of the heart that fails to close naturally soon after a baby is born. It affects more than a quarter of the world’s population. Endovascular closure of PFO using a closure device can stop right-to-left shunting immediately. Lopez et al. applied a novel quantitative two-pass discovery workﬂow using high-resolution LC-MS/MS coupled with label-free analysis to monitor protein expression in PFO patients’ blood before and after PFO closure.6 The investigators identified quantitative changes in protein expression before and after PFO closure, and also in long-term follow-up. Alterations in protein expression involve prothrombin activation, atherosclerosis signaling, acute phase response, LXR/RXR activation, and coagulation pathways. The protein expression after PFO closure was reduced in stroke-related acute inﬂammatory response and coagulation signaling. A proteomic approach for biomarker discovery might help monitor PFO closure efﬁcacy in cardiac atrial blood.
“A pharmaco-proteomic approach to obtain a ‘composite’ signature of treatment effects may help to monitor therapeutic efﬁcacy, improve patient selection, ensure more precise clinical phenotyping for clinical trials, and most importantly individualize treatment for our patients,” the researchers conclude.
- Ning, M.M., et al. (2013) “Pharmaco-proteomics opportunities for individualizing neurovascular treatment”, Neurological Research, 35(5), (pp.448-56). doi: 10.1179/1743132813Y.0000000213.
- Ning, M., Lo, E.H.(2010) “Opportunities and challenges in Omics,” Translational Stroke Research,1(4), (pp.233–237), doi: 10.1007/s12975-010-0048-y.
- Yu, L.R., (2011) “Pharmacoproteomics and toxicoproteomics: the field of dreams,” Journal of Proteomics,74(12), (pp.2549–53), http://dx.doi.org/10.1016/j.jprot.2011.10.001.
- Ning, M., et al.(2010) “ Proteomic protease substrate profiling of tPA treatment in acute ischemic stroke patients: a step toward individualizing thrombolytic therapy at the bedside”, Translational Stroke Research ,1(4), (pp.268–275), doi: 10.1007/s12975-010-0047-z.
- Cao, J., et al.(2013) “Studying extracellular signaling utilizing a glycoproteomic approach –Lectin blot surveys – A first and important step”, Methods in Molecular Biology,1013, (pp.227–33), doi: 10.1007/978-1-62703-426-5_15.
- Lopez, M.F., et al.(2012) “Heart–brain signaling in Patent Foramen Ovale related stroke: Differential Plasma Protein Expression Patterns Revealed with a Two-Pass LC-MS/MS Discovery Workflow”, Journal of Investigative Medicine, 60(8) (pp.1122–30), doi: 10.231/JIM.0b013e318276de0
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