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
Srisairam Achuthan, Ph.D.
Senior Scientific Programmer, Research Informatics Division, Department of Information Sciences, City of Hope, CA, USA
Applying Machine learning for Automated Identification of Patient Cohorts
Srisairam Achuthan, Mike Chang, Ajay Shah, Joyce Niland
Patient cohorts for a clinical study are typically identified based on specific selection criteria. In most cases considerable time and effort are spent in finding the most relevant criteria that could potentially lead to a successful study. For complex diseases, this process can be more difficult and error prone since relevant features may not be easily identifiable. Additionally, the information captured in clinical notes is in non-coded text format. Our goal is to discover patterns within the coded and non-coded fields and thereby reveal complex relationships between clinical characteristics across different patients that would be difficult to accomplish manually. Towards this, we have applied machine learning techniques such as artificial neural networks and decision trees to determine patients sharing similar characteristics from available medical records. For this proof of concept study, we used coded and non-coded (i.e., clinical notes) patient data from a clinical database. Coded clinical information such as diagnoses, labs, medications and demographics recorded within the database were pooled together with non-coded information from clinical notes including, smoking status, life style (active / inactive) status derived from clinical notes. The non-coded textual information was identified and interpreted using a Natural Language Processing (NLP) tool I2E from Linguamatics.
Pandiaraj Manickam, Niroj Kumar Sethy, Kalpana Bhargava, Vepa Kameswararao and Karunakaran Chandran
Designing electrochemical label free immunosensors for cytochrome c using nanocomposites functionalized screen printed electrodes
Release of cytochrome c (cyt c) from mitochondria into cytosol is a hallmark of apoptosis, used as a biomarker of mitochondrial dependent pathway of cell death (Kluck et al. 1997; Green et al. 1998). We have previously reported cytochrome c reductase (CcR) based biosensors for the measurement of mitochondrial cyt c release (Pandiaraj et al. 2013). Here, we describe the development of novel label-free, immunosensor for cyt c utilizing its specific monoclonal antibody. Two types of nanocomposite modified immunosensing platforms were used for the immobilization of anti-cyt c; (i) Self-assembled monolayer (SAM) functionalized gold nanoparticles (GNP) in conducting polypyrrole (PPy) modified screen printed electrodes (SPE) (ii) Carbon nanotubes (CNT) incorporated PPy on SPE. The nanotopologies of the modified electrodes were confirmed by scanning electron microscopy (SEM). Cyclic voltammetry, electrochemical impedance spectroscopy (EIS) were used for probing the electrochemical properties of the nanocomposite modified electrodes. Method for cyt c quantification is based on the direct electron transfer between Fe3+/Fe2+-heme of cyt c selectively bound to anti-cyt c modified electrode. The Faradaic current response of these nanoimmunosensor increases with increase in cyt c concentration. The procedure for cyt c detection was also optimized (pH, incubation times, and characteristics of electrodes) to improve the analytical characteristics of immunosensors. The analytical performance of anti-cyt c biofunctionalized GNP-PPy nanocomposite platform (detection limit 0.5 nM; linear range: 0.5 nM–2 μM) was better than the CNT-PPy (detection limit 2 nM; linear range: 2 nM-500nM). The detection limits were well below the normal physiological concentration range (Karunakaran et al. 2008). The proposed method does not require any signal amplification or labeled secondary antibodies contrast to widespread ELISA and Western blot. The immunosensors results in simple and rapid measurement of cyt c and has great potential to become an inexpensive and portable device for conventional clinical immunoassays.
Shrikant Anant, Ph.D.
The Department of Molecular & Integrative Physiology, Kansas University Medical Center, USA
Cancer Stem Cells: Target Colon Cancers
Shrikant Anant, Deep Kwatra and Dharmalingam Subramaniam
Colon cancer is a leading cause of cancer related deaths in the US, and its rate is increasing at an alarming rate in lndia. Recent studies have suggested the drug resistance role for a mall number of cells within a tumor called cancer stem cells. We identified the colon cancer stem cell marker DCLK1, a member of the protein kinase superfamily and the doublecortin family. The protein encodes a Cterminal serinethreonine protein kinase domain, which shows substantial homology to Ca2calmodulindependent protein kinase. Our current studies have been to identify compounds that can either affect DCLK1 expression or inhibits its activity as a way to inhibit cancer stem cells. Honokiol is a biphenolic compound that has been used in the traditional Chinese Medicine for treating various ailments. In vitro kinase assays with recombinant DCLK1 demonstrated that honokiol inhibits its kinase activity in a dose dependent manner. We therefore determined the effect of honokiol on stem cells. One method to look at effects on stem cells is perform a spheroid assay, where spheroids formation is suggested to maintain stemlike characteristic of cancer cells. Honokiol significantly suppressed colonosphere formation of two colon cancer cell lines HCT116 and SW480. Flow cytometry studies confirmed that honokiol reduced the number of DCLK1cells. A critical signaling pathway known to modulate intestinal stem cell proliferation is the Hippo signaling pathway, and deregulation of the pathway leads to tumor development. DCLK1cells had high levels of YAP1, the nuclear target of Hippo signaling. We determined the effect of honokiol on components of the hipposignaling pathway. Honokiol reduced the phosphorylation of Mst1/2, Lats1/2 and YAP1. Furthermore, honokiol treatment resulted in downregulation of YAPTEAD complex protein TEAD-1. Ectopic expression of the TEAD-1 partially rescued the cells from honokiol mediated growth suppression. To determine the effect of honokiol on tumor growth in vivo, nude mice harboring HCT116 tumor xenografts in their flanks were administered the compound intraperitoneally every day for 21 days. Honokiol treatment significantly inhibited tumor xenograft growth. Western blot and immunohistochemistry analyses demonstrated significant inhibition in the expression of stem marker and Hippo signaling proteins in the honokioltreated xenograft tissues. Taken together, these data suggest that honokiol is a potent inhibitor of colon cancer that targets DCLK1 stem cells by inhibiting Hippo signaling pathway.
Rustom Mody, Ph.D.
Head R & D Lupin Ltd., Pune
Biosimilars are follow-on biologics also known as Similar Biologics – terms used to describe officially approved subsequent versions of innovator biopharmaceutical products made by rDNA technology when made by a different sponsor following patent expiry on the innovator product. These products are drawing global attention as a large number of block buster biopharmaceuticals have expired and many will soon seize to have patent protection in the coming years, opening the doors for the entry of biosimilars. However, the regulatory landscape is getting complex across the globe. The talk focuses on opportunities and challenges in the field of biosimilars and the future of biosimilar companies in India.