Aug
11
Sun
2013
Disruptive Innovation: When the past doesnot predict the future? DELSA India Workshop on Big Data and Collective Innovation @ Acharya Hall
Aug 11 @ 4:30 pm – 6:15 pm

Vural Özdemir Ph.D.

Sanjeeva Srivastava Ph.D.

Aug
12
Mon
2013
Invited Talk: Identification of Potential Early Diagnostic Biomarkers for Gliomas and Various Infectious Diseases using Proteomic Technologies @ Acharya Hall
Aug 12 @ 2:35 pm – 2:56 pm

SanjeevaSanjeeva 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 :

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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

Figure 1 (a) Differentially expressed proteins in GBM identified using 2D-DIGE. Representative 2D- DIGE image to compare serum proteome of HC and GBM patients. GBM and HC samples were labeled with Cy3 and Cy5 respectively, while the protein reference pool (internal standard) was labeled with Cy2. Graphical and 3D fluorescence intensity representations of few selected statistically significant (p < 0.05) differentially expressed proteins in GBM patients identified in biological variation analysis (BVA) using DeCyder 2D software. (b) Involvement of different essential physiological pathways with differentially expressed proteins in GBM. Members of multiple essential physiological processes including cell growth and proliferation, vitamin D metabolism, lipoprotein metabolism and transport, oxidative stress regulation, complement cascade, and platelet activation found to be modulated in the GBM patients (Gollapalli et al., Proteomics 2012).
Figure 1 (a) Differentially expressed proteins in GBM identified using 2D-DIGE. Representative 2D- DIGE image to compare serum proteome of HC and GBM patients. GBM and HC samples were labeled with Cy3 and Cy5 respectively, while the protein reference pool (internal standard) was labeled with Cy2. Graphical and 3D fluorescence intensity representations of few selected statistically significant (p < 0.05) differentially expressed proteins in GBM patients identified in biological variation analysis (BVA) using DeCyder 2D software. (b) Involvement of different essential physiological pathways with differentially expressed proteins in GBM. Members of multiple essential physiological processes including cell growth and proliferation, vitamin D metabolism, lipoprotein metabolism and transport, oxidative stress regulation, complement cascade, and platelet activation found to be modulated in the GBM patients (Gollapalli et al., Proteomics 2012).
Figure 2 (a) Western blot analysis of haptoglobin (HP), serum amyloid A (SAA), and clusterin (CLU) from serum samples of healthy control (HC) [n = 12], falciparum malaria (FM) [n = 12], vivax malaria (VM) [n = 12], Leptospirosis (Lep) [n = 6], dengue fever [DF] [n = 6] and non infectious disease control (NIDC:GBM) [n = 12]. Representative blots of the target proteins are depicted along with their respective relative abundance volumes (volume X 104). All the data are represented as mean ± SE. (b) Discrimination of malaria from dengue, leptospirosis and GBM using PLS-DA analysis. PLS-DA scores Plot for FM (blue spheres, n = 8), VM (green spheres, n = 8), DF (red spheres, n = 6), Lep (grey spheres, n = 6) and GBM (brown spheres, n = 8) samples based on 6 differentially expressed proteins (serum amyloid A, hemopexin, apolipoprotein E, haptoglobin, retinol-binding protein and apolipoprotein A-I) identified using DIGE. The axes of the plot indicate PLSDA latent variables t0-t2.
Figure 2 (a) Western blot analysis of haptoglobin (HP), serum amyloid A (SAA), and clusterin (CLU) from serum samples of healthy control (HC) [n = 12], falciparum malaria (FM) [n = 12], vivax malaria (VM) [n = 12], Leptospirosis (Lep) [n = 6], dengue fever [DF] [n = 6] and non infectious disease control (NIDC:GBM) [n = 12]. Representative blots of the target proteins are depicted along with their respective relative abundance volumes (volume X 104). All the data are represented as mean ± SE. (b) Discrimination of malaria from dengue, leptospirosis and GBM using PLS-DA analysis. PLS-DA scores Plot for FM (blue spheres, n = 8), VM (green spheres, n = 8), DF (red spheres, n = 6), Lep (grey spheres, n = 6) and GBM (brown spheres, n = 8) samples based on 6 differentially expressed proteins (serum amyloid A, hemopexin, apolipoprotein E, haptoglobin, retinol-binding protein and apolipoprotein A-I) identified using DIGE. The axes of the plot indicate PLSDA latent variables t0-t2.

 

Sanjeeva (1) Sanjeeva (2)

Aug
13
Tue
2013
Invited Talk: Nanoscale Simulations – Tackling Form and Formulation Challenges in Drug Development and Drug Delivery @ Sathyam Hall
Aug 13 @ 2:15 pm – 2:40 pm

lalithaLalitha Subramanian, Ph.D.
Chief Scientific Officer & VP, Services at Scienomics, USA


Nanoscale Simulations – Tackling Form and Formulation Challenges in Drug Development and Drug Delivery

Lalitha Subramanian, Dora Spyriouni, Andreas Bick, Sabine Schweizer, and Xenophon Krokidis Scienomics

The discovery of a compound which is potent in activity against a target is a major milestone in Pharmaceutical and Biotech industry. However, a potent compound is only effective as a therapeutic agent when it can be administered such that the optimal quantity is transported to the site of action at an optimal rate. The active pharmaceutical ingredient (API) has to be tested for its physicochemical properties before the appropriate dosage form and formulation can be designed. Some of the commonly evaluated parameters are crystal forms and polymorphs, solubility, dissolution behavior, stability, partition coefficient, water sorption behavior, surface properties, particle size and shape, etc. Pharmaceutical development teams face the challenge of quickly and efficiently determining a number of properties with small quantities of the expensive candidate compounds. Recently the trend has been to screen these properties as early as possible and often the candidate compounds are not available in sufficient quantities. Increasingly, these teams are leveraging nanoscale simulations similar to those employed by drug discovery teams for several decades. Nanoscale simulations are used to predict the behavior using very little experimental data and only if this is promising further experiments are done. Another aspect where nanoscale simulations are being used in drug development and drug delivery is to get insights into the behavior of the system so that process failures can be remediated and formulation performance can be improved. Thus, the predictive screening and the in-depth understanding leads to experimental efficiency resulting in far-reaching business impacts.

With specific examples, this talk will focus on the different types of nanoscale simulations used to predict properties of the API in excipients and also provide insight into system behavior as a function of shelf life, temperature, mechanical stress, etc.

Aug
14
Wed
2013
Plenary Address: Crowd-Funded Micro-Grants to Link Biotechnology and “Big Data” R&D to Life Sciences Innovation in India @ Acharya Hall
Aug 14 @ 9:20 am – 10:05 am

VuralVural 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*

  1. Data-Enabled Life Sciences Alliance International (DELSA Global), Seattle, WA 98101, USA;
  2. 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

Email: vural.ozdemir@alumni.utoronto.ca

Vural (1) Vural (2) Vural-Ramani