Vural Özdemir Ph.D.
Sanjeeva Srivastava Ph.D.
Sanjeeva Srivastava, Ph.D.
Assistant Professor, Proteomics Lab, IIT-Bombay, India
Identification of Potential Early Diagnostic Biomarkers for Gliomas and Various Infectious Diseases using Proteomic Technologies
The spectacular advancements achieved in the field of proteomics research during the last decade have propelled the growth of proteomics for clinical research. Recently, comprehensive proteomic analyses of different biological samples such as serum or plasma, tissue, CSF, urine, saliva etc. have attracted considerable attention for the identification of protein biomarkers as early detection surrogates for diseases (Ray et al., 2011). Biomarkers are biomolecules that can be used for early disease detection, differentiation between closely related diseases with similar clinical manifestations as well as aid in scrutinizing disease progression. Our research group is performing in-depth analysis of alteration in human proteome in different types of brain tumors and various pathogenic infections to obtain mechanistic insight about the disease pathogenesis and host immune responses, and identification of surrogate protein markers for these fatal human diseases.
Applying 2D-DIGE in combination with MALDI-TOF/TOF MS we have analyzed the serum and tissue proteome profiles of glioblastoma multiforme; the most common and lethal adult malignant brain tumor (Gollapalli et al., 2012) (Figure 1). Results obtained were validated by employing different immunoassay-based approaches. In serum proteomic analysis we have identified some interesting proteins like haptoglobin, ceruloplasmin, vitamin-D binding protein etc. Moreover, proteomic analysis of different grades (grade-I to IV) of gliomas and normal brain tissue was performed and differential expressions of quite a few proteins such as SIRT2, GFAP, SOD, CDC42 have been identified, which have significant correlation with the tumor growth. While proteomic analysis of cerebrospinal fluid from low grade (grade I & II) vs. high grade (grade III & IV) gliomas revealed modulation of CSF levels of apolipoprotein E, dickkopf related protein 3, vitamin D binding protein and albumin in high grade gliomas. The prospective candidates identified in our studies provide a mechanistic insight of glioma pathogenesis and identification of potential biomarkers. We are also studying the role of JAK/STAT interactome and therapeutic potential of STAT3 inhibitors in gliomas using proteomics approach. Several candidates of the JAK/STAT interactome were identified with altered expression and a significant correlation was observed between STAT3 and PDK1 transcript expression level.
We have also investigated the changes in human serum proteome in different infectious diseases including falciparum and vivax malaria (Ray et al., 2012a; Ray et al., 2012b), dengue (Ray et al., 2012c) and leptospirosis (Srivastava et al., 2012). Although, quite a few serum proteins were found to be commonly altered in different infectious diseases and might be a consequence of inflammation mediated acute phase response signaling, uniquely modulated candidates were identified in each pathogenic infection indicating the some inimitable responses. Further, a panel of identified proteins consists of six candidates; serum amyloid A, hemopexin, apolipoprotein E, haptoglobin, retinol-binding protein and apolipoprotein A-I was used to build statistical sample class prediction models employing PLSDA and other classification methods to predict the clinical phenotypic classes and 91.37% overall prediction accuracy was achieved (Figure 2). ROC curve analysis was carried out to evaluate the individual performance of classifier proteins. The excellent discrimination among the different disease groups on the basis of differentially expressed proteins demonstrates the potential diagnostic implications of this analytical approach.
Keywords: Diagnostic biomarkers, Gliomas, Infectious Diseases, Proteomics, Serum proteome
Acknowledgments: This disease biomarker discovery research was supported by Department of Biotechnology, India grant (No. BT/PR14359/MED/30/916/2010), Board of Research in Nuclear Sciences (BRNS) DAE young scientist award (2009/20/37/4/BRNS) and a startup grant 09IRCC007 from the IIT Bombay. The active support from Advanced Center for Treatment Research and Education in Cancer (ACTREC), Tata Memorial Hospital (TMH), and Seth GS Medical College and KEM Hospital Mumbai, India in clinical sample collection process is gratefully acknowledged.
References :
- Ray S, Reddy PJ, Jain R, Gollapalli K. Moiyadi A, Srivastava S. Proteomic technologies for the identification of disease biomarkers in serum: advances and challenges ahead. Proteomics 11: 2139-61, 2011.
- Gollapalli K, Ray S, Srivastava R, Renu D, Singh P, Dhali S, Dikshit JB, Srikanth R, Moiyadi A, Srivastava S. Investigation of serum proteome alterations in human glioblastoma multiforme. Proteomics 12(14): 2378-90, 2012.
- Ray S, Renu D, Srivastava R, Gollapalli K, Taur S, Jhaveri T, Dhali S, Chennareddy S, Potla A, Dikshit JB, Srikanth R, Gogtay N, Thatte U, Patankar S, Srivastava S. Proteomic investigation of falciparum and vivax malaria for identification of surrogate protein markers. PLoS One 7(8): e41751, 2012a.
- Ray S, Kamath KS, Srivastava R, Raghu D, Gollapalli K, Jain R, Gupta SV, Ray S, Taur S, Dhali S, Gogtay N, Thatte U, Srikanth R, Patankar S, Srivastava S. Serum proteome analysis of vivax malaria: An insight into the disease pathogenesis and host immune response. J Proteomics 75(10): 3063-80, 2012b.
- Srivastava R, Ray S, Vaibhav V, Gollapalli K, Jhaveri T, Taur S, Dhali S, Gogtay N, Thatte U, Srikanth R, Srivastava S. Serum profiling of leptospirosis patients to investigate proteomic alterations. J Proteomics 76: 56-68, 2012.
- Ray S, Srivastava R, Tripathi K, Vaibhav V, Srivastava S. Serum proteome changes in dengue virus-infected patients from a dengue-endemic area of India: towards new molecular targets? OMICS 16(10): 527-36, 2012c.
* Correspondence: Dr. Sanjeeva Srivastava, Department of Biosciences and Bioengineering, IIT Bombay, Mumbai 400 076, India: E-mail: sanjeeva@iitb.ac.in; Phone: +91-22-2576-7779, Fax: +91-22-2572-3480
Rajasekhar Chekkara, Venkata Reddy Gorla and Sobha Rani Tenkayala
Pharmacophore modeling, atom-based 3D-QSAR and molecular docking studies on Pyrimido[5,4-e][1,2,4]triazine derivatives as PLK 1 inhibitors
Polo-like kinase 1 (PLK1) is a significant enzyme with diverse biological actions in cell cycle progression, specifically mitosis. Suppression of PLK1 activity by small molecule inhibitors has been shown to inhibit cancer, being BI 2536 one of the most potent active inhibitor of PLK1 mechanism. Pharmacophore modeling, atom-based 3D-QSAR and molecular docking studies were carried out for a set of 54 compounds belonging to Pyrimido[5,4-e][1,2,4]triazine derivatives as PLK1 inhibitors. A six-point pharmacophoremodel AAADDR, with three hydrogen bond acceptors (A), two hydrogen bond donors (D) and one aromatic ring (R) was developed by Phase module of Schrdinger suite Maestro 9. The generated pharmacophore model was used to derive a predictive atom-based 3D quantitative structure-activity relationship analysis (3D-QSAR) model for the training set (r2 = 0.88, SD = 0.21, F = 57.7, N = 44) and for test set (Q2 = 0.51, RMSE = 0.41, PearsonR = 0.79, N = 10). The original set of compounds were docked into the binding site of PLK1 using Glide and the active residues of the binding site were analyzed. The most active compound H18 interacted with active residues Leu 59, Cys133 (glide score = −10.07) and in comparison of BI 2536, which interacted with active residues Leu 59, Cys133 (glide score = −10.02). The 3D-QSAR model suggests that hydrophobic and electron-withdrawing groups are essential for PLK1 inhibitory activity. The docking results describes the hydrogen bond interactions with active residues of these compounds. These results which may support in the design and development of novel PLK1 inhibitors.
Bodo Eickhoff, Ph.D.
Senior Vice-President, Head of Sales and Marketing for Roche Applied Science, Germany
New paths for treatment of complex diseases: target combinatorial drug therapy
Several types of diseases show a complex pathogenesis and require targeted as well as combinatorial drug treatment. A classical example, Tuberculosis, was thought for decades to be managable by triple therapy, however now requiring new therapeutic approaches due to multi drug resistant strains. HIV and AIDS can only be kept under control by combinations of specific, virus-protein targeted drugs, requiring constant monitoring of resistance patterns and modulation of drug combinations during life-long therapy. As a third example, Cancer in all its different variations, requires detailled molecular understanding to enable targeted therapy. New technologies provide more and in depths molecular insights into pathomechanisms and resulting treatment options. However, is there an alternative way to approach complex diseases by holistic models? Can restoring of apoptosis-capabilities of transformed cells be an example of such an alternative path? How do we in future adress major unresolved topics like increasing drug resistance in bacterial infections, lack of anti-viral drugs, treatment of parasite diseases like Malaria, and newly emerging infectious diseases in research and fast translation of these results into diagnosis and treatment?
Aswath Balakrishnan, Kapaettu Satyamoorthy and Manjunath B Joshi
Introduction
Insulin resistance is a hall mark of metabolic disorders such as diabetes. Reduced insulin response in vasculature leads to disruption of IR/Akt/eNOS signaling pathway resulting in vasoconstriction and subsequently to cardiovascular diseases. Recent studies have demonstrated that inflammatory regulator interleukin-6 (IL-6), as one of the potential mediators that can link chronic inflammation with insulin resistance. Accumulating evidences suggest a significant role of epigenetic mechanisms such as DNA methylation in progression of metabolic disorders. Hence the present study aimed to understand the role of epigenetic mechanisms involved during IL-6 induced vascular insulin resistance and its consequences in cardiovascular diseases.
Materials and Methods
Human umbilical vein endothelial cells (HUVEC) and Human dermal microvascular endothelial cells (HDMEC) were used for this study. Endothelial cells were treated in presence or absence of IL-6 (20ng/ml) for 36 hours and followed by insulin (100nM) stimulation for 15 minutes. Using immunoblotting, cell lysates were stained for phosphor- and total Akt levels to measure insulin resistance. To investigate changes in DNA methylation, cells were treated with or without neutrophil conditioned medium (NCM) as a physiological source of inflammation or IL-6 (at various concentrations) for 36 hours. Genomic DNA was processed for HPLC analysis for methyl cytosine content and cell lysates were analyzed for DNMT1 (DNA (cytosine-5)-methyltransferase 1) and DNMT3A (DNA (cytosine-5)-methyltransferase 3A) levels using immunoblotting.
Results
Endothelial cells stimulated with insulin exhibited an increase in phosphorylation of Aktser 473 in serum free conditions but such insulin response was not observed in cells treated with IL-6, suggesting chronic exposure of endothelial cells to IL-6 leads to insulin resistance. HPLC analysis for global DNA methylation resulted in decreased levels of 5-methyl cytosine in cells treated with pro-inflammatory molecules (both by NCM and IL-6) as compared to untreated controls. Subsequently, analysis in cells treated with IL-6 showed a significant decrease in DNMT1 levels but not in DNMT3A. Other pro-inflammatory marker such as TNF-α did not exhibit such changes.
Conclusion
Our study suggests: a) Chronic treatment of endothelial cells with IL-6 results in insulin resistance b) Neutrophil conditioned medium and IL-6 decreases methyl cytosine levels c) DNMT1 but not DNMT3a levels are reduced in cells treated with IL-6.
Vural Özdemir, MD, Ph.D., DABCP
Co-Founder, DELSA Global, Seattle, WA, USA
Crowd-Funded Micro-Grants to Link Biotechnology and “Big Data” R&D to Life Sciences Innovation in India
Vural Özdemir, MD, PhD, DABCP1,2*
- Data-Enabled Life Sciences Alliance International (DELSA Global), Seattle, WA 98101, USA;
- Faculty of Management and Medicine, McGill University, Canada;
ABSTRACT
Aims: This presentation proposes two innovative funding solutions for linking biotechnology and “Big Data” R&D in India with artisan small scale discovery science, and ultimately, with knowledge-based innovation:
- crowd-funded micro-grants, and
- citizen philanthropy
These two concepts are new, and inter-related, and can be game changing to achieve the vision of biotechnology innovation in India, and help bridge local innovation with global science.
Background and Context: Biomedical science in the 21(st) century is embedded in, and draws from, a digital commons and “Big Data” created by high-throughput Omics technologies such as genomics. Classic Edisonian metaphors of science and scientists (i.e., “the lone genius” or other narrow definitions of expertise) are ill equipped to harness the vast promises of the 21(st) century digital commons. Moreover, in medicine and life sciences, experts often under-appreciate the important contributions made by citizen scholars and lead users of innovations to design innovative products and co-create new knowledge. We believe there are a large number of users waiting to be mobilized so as to engage with Big Data as citizen scientists-only if some funding were available. Yet many of these scholars may not meet the meta-criteria used to judge expertise, such as a track record in obtaining large research grants or a traditional academic curriculum vitae. This presentation will describe a novel idea and action framework: micro-grants, each worth $1000, for genomics and Big Data. Though a relatively small amount at first glance, this far exceeds the annual income of the “bottom one billion” – the 1.4 billion people living below the extreme poverty level defined by the World Bank ($1.25/day).
We will present two types of micro-grants. Type 1 micro-grants can be awarded through established funding agencies and philanthropies that create micro-granting programs to fund a broad and highly diverse array of small artisan labs and citizen scholars to connect genomics and Big Data with new models of discovery such as open user innovation. Type 2 micro-grants can be funded by existing or new science observatories and citizen think tanks through crowd-funding mechanisms described herein. Type 2 micro-grants would also facilitate global health diplomacy by co-creating crowd-funded micro-granting programs across nation-states in regions facing political and financial instability, while sharing similar disease burdens, therapeutics, and diagnostic needs. We report the creation of ten Type 2 micro-grants for citizen science and artisan labs to be administered by the nonprofit Data-Enabled Life Sciences Alliance International (DELSA Global, Seattle: http://www.delsaglobal.org). Our hope is that these micro-grants will spur novel forms of disruptive innovation and life sciences translation by artisan scientists and citizen scholars alike.
Address Correspondence to:
Vural Özdemir, MD, PhD, DABCP
Senior Scholar and Associate Professor
Faculty of Management and Medicine, McGill University
1001 Sherbrooke Street West
Montreal, Canada H3A 1G5