Information

20.6: Drugs - Biology


Testing New Drugs

Thousands of chemicals, both synthetic and extracted from "natural" sources, are being examined in the hope of finding new drugs with which to combat human and veterinary diseases. The first step is to use laboratory tests to find if these substances have a significant effect on, for example:

  • cells growing in tissue culture
  • laboratory animals such as rats and mice.

If the drug achieves the desired effect in laboratory animals, without killing them in the process, the drug developer applies to the U. S. Food and Drug Administration for an IND, an investigational new drug application. Granting of an IND allows testing in humans to begin. This occurs in three phases.

Phase I

A small group (20–100) of healthy volunteers is given the drug to see

  • if it is safe
  • how quickly it is absorbed, metabolized, and excreted from the body

Phase II

A group (up to several hundred) of volunteer patients with the disease are given the drug to see

  • how effective it is against the signs and symptoms of the disease
  • what doses are best
  • what side effects may occur

A control group of similar size is given a dummy drug (placebo). Ideally the trials are "blinded" with neither the subjects (nor the investigator) knowing which pill a subject is receiving.

Phase III

Hundreds to thousands of patients with the disease are given the drug to get more reliable data on its

  • effectiveness
  • safety
  • best dose
  • rare side effects

all compared with the drug(s) that are currently used for the disease.

If all goes well, the drug manufacturer applies to the Food and Drug Administration for an NDA, a new drug application. If it is granted, the generic name of the drug is replaced by a brand name chosen by the manufacturer. For example, one of the first drugs used against AIDS was azidodideoxythymidine (AZT). When placed on the market, this name was replaced by the brand name Retrovir®.


Synthorx Gets $131M in Upsized IPO for Synthetic Biology Drugs

Synthorx, which is working to develop cancer and autoimmune therapies using technology that allows it to expand the genetic alphabet, raised $131 million in an upsized IPO on Thursday.

The company sold more than 11.9 million shares at $11 apiece. Nearly 1.8 million additional shares are available for its underwriters to purchase.

Synthorx, headed by president and CEO Laura Shawver, had planned to sell 9.1 million shares for between $10 and $12 each. The company’s shares are expected to start trading on the Nasdaq today under the stock symbol “THOR.”

Synthorx’s IPO continues the prolonged positive run for initial biotech stock offerings, which began in 2013 and has yet to slow down. Healthcare overall has been the most active sector of a hot IPO market this year with 76 total IPOs, according to IPO research firm Renaissance Capital. As of Thursday, a total of 188 IPOs had priced in 2018󈟤.5 percent more than on the same date the year prior, according to the Renaissance data. Proceeds were up 30.4 percent year over year to $45.7 billion.

Cash continued to flow to newly minted public biotechs on Thursday night. Synthorx’s IPO was preceded Thursday by Cambridge, MA-based Moderna’s $604.3 million initial stock offering—by far the largest ever for a biotech.

At Synthorx, reseachers are developing enhanced versions of proteins called cytokines, which regulate immune and inflammatory responses. The company uses technology licensed from The Scripps Research Institute (TSRI) in 2014 to insert a new DNA base pair into E. coli bacteria and make a variety of synthetic amino acids. It calls these “optimized” biologics Synthorins, which it believes could improve upon existing treatments for cancer and autoimmune diseases.

The discoveries that underpin its investigatory products were made in Floyd Romesberg’s lab at TSRI.

Synthorx says it will use the IPO proceeds to fund development of its lead product candidate, THOR-707, which is meant to be a better version of interleukein-2, an approved treatment for multiple forms of cancer. The drug is in early stage clinical testing, and Synthorx hopes to develop other similar products as well.

In the prospectus, the 25-person company said it plans to study THOR-707 as a treatment for solid tumor cancers on its own and in combination with an immunotherapy known as a checkpoint inhibitor. It plans to file paperwork in the second quarter of 2019 to start human testing, and subsequently launch a phase 1/2 clinical trial.

Synthorx is based at COI (for Community of Innovation) Pharmaceuticals, an incubator in the San Diego community of La Jolla that provides shared facilities and management for portfolio companies of Avalon Ventures, a founding investor of Synthorx.

Avalon (and its affiliated entities) was the company’s largest stockholder before the IPO, owning nearly one-third of its shares. Boston’s RA Capital Management (and affiliated entities) and New York private equity firm OrbiMed were the next two largest shareholders, with about 28 percent and 22 percent, respectively. Correlation Ventures, also a founding investor, had about 6 percent.

The company raised $63 million in April in a round led by OrbiMed and joined by Medicxi and Osage University Partners. Avalon and Correlation Ventures, another founding investor, also joined the round, along with earlier investor RA Capital.

Synthorx spent about $15.7 million on R&D since the start of 2016 through Sept. 30, according to its prospectus. As of Sept. 30, the company had $20.6 million in cash.

Sarah de Crescenzo is an Xconomy editor based in San Diego. You can reach her at [email protected] Follow @sarahdc


Publications

Levin, M., (2021), Life, death, and self: Fundamental questions of primitive cognition viewed through the lens of body plasticity and synthetic organisms, Biochemical and Biophysical Research Communications, 564: 114-133
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Levin, M., (2021), Unlimited Plasticity of Embodied, Cognitive Subjects: a new playground for the UAL framework, Biology and Philosophy, in press

Levin, M., (2021), Bioelectric Signaling: Reprogrammable Circuits Underlying Embryogenesis, Regeneration, and Cancer, Cell, in press

Bongard, J., and Levin, M., (2021), Living things are not (20th Century) machines: updating mechanism metaphors in light of the modern science of machine behavior, Frontiers in Ecology and Evolution, in press

Levin, M., Keijzer, F., Lyon, P., and Arend, D., (2021), Uncovering cognitive similarities and differences, conservation and innovation, Philosophical Transactions of the Royal Society B, 375 (1820): 20200458
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Lyon, P., Keijzer, F., Arendt, D., and Levin, M., (2021), Reframing cognition: getting down to biological basics, Philosophical Transactions of the Royal Society B, 376 (1821): 20190750
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Pezzulo, G., Lapalme, J., Durant, F., and Levin, M., (2021), Bistability of Somatic Pattern Memories: Stochastic Outcomes in Bioelectric Circuits Underlying Regeneration, Philosophical Proceedings of the Royal Society B, 375: 20190765
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Fields, C., and Levin, M., (2020), How Do Living Systems Create Meaning?, Philosophies, 5(4): 36
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Fields, C., and Levin, M., (2020), Why isn't sex optional? Stem-cell competition, loss of regenerative capacity, and cancer in metazoan evolution, Communicative & Integrative Biology, 13(1): 170-183
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Shah, D., Yang, B., Kriegman, S., Levin, M., Bongard, J., and Kramer-Bottiglio, R., (2020), Shape changing robots: bioinspiration, simulation, and physical realization, Advanced Materials, in press
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Levin, M., (2020), How Groups of Cells Cooperate to Build Organs and Organisms,
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Fields, C., and Levin, M., (2020), Does evolution have a target morphology?, Organisms, 4(1): 57-76
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Kuchling, F., Friston, K., Georgiev, G., and Levin, M., (2020), Integrating Variational Approaches to Pattern Formation into a Deeper Physics: Reply to comments on "Morphogenesis as Bayesian Inference: A Variational Approach to Pattern Formation and Manipulation in Complex Biological Systems", Physics of Life Reviews, 33:125-128
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Hoel, E., and Levin, M., (2020), Emergence of Informative Higher Scales in Biological Systems: a computational toolkit for optimal prediction and control, Communicative & Integrative Biology, 13(1): 108-118
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Levin, M., Bongard, J., and Lunshof, J.E, (2020), Applications and ethics of computer-designed organisms, Nature Reviews Molecular Cell Biology, 21: 655–656
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Levin, M., (2020), Opinion: Use the Pandemic to Expand the Lab to the Home,
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Gawne, R., McKenna, K., and Levin, M., (2020), Competitive and Coordinative Interactions between Body Parts Produce Adaptive Developmental Outcomes, BioEssays, 42: 1900245
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Fields, C., and Levin, M., (2020), Scale-Free Biology: Integrating Evolutionary and Developmental Thinking, BioEssays, 42: 1900228
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Cervera, J., Levin, M., Mafe, S., (2020), Bioelectrical Coupling of Single-Cell States in Multicellular Systems, J. Phys. Chem. Lett. 11, XXX, 3234-3241,
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Levin, M., (2020), Revisiting Burr and Northrop's 'The Electro-Dynamic Theory of Life', Biological Theory, 15:83–90
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Fields, C., and Levin, M., (2020), Does regeneration recapitulate phylogeny?, Communicative and Integrative Biology, 13(1): 27-38
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Srivastava, P., Kane, A., Harrison, C., and Levin, M., (2020), A Meta-Analysis of Bioelectric Data in Cancer, Embryogenesis, and Regeneration, Bioelectricity, 3(1): 42-67
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Davison, A., McDowell, G. S., Holden, J. M., Johnson, H. F., Wade, C. M., Chiba, S., Jackson, D. J., Levin, M., and Blaxter, M. L., (2020), Formin, an opinion, Development, 147: dev187427
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Tung, A., and Levin, M., (2020), Extra-genomic instructive influences in morphogenesis: A review of external signals that regulate growth and form, Developmental Biology,
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Healy, D., Faber, C., Lapalme, J., and Levin, M., (2020), Post-SSRI Sexual Dysfunction: a bioelectric mechanism?, Bioelectricity,
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Levin, M., (2020), The Biophysics of Regenerative Repair Suggests New Perspectives on Biological Causation, BioEssays, 42: 1900146
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Fields, C., Bischof, J., and Levin, M., (2020), Morphological Coordination: A Common Ancestral Function Unifying Neural and Non-Neural Signaling, Physiology, 35: 16-30
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Levin, M., Selberg, J., and Rolandi, M., (2019), Endogenous Bioelectrics in Development, Cancer, and Regeneration: Drugs and Bioelectronic Devices as Electroceuticals for Regenerative Medicine, iScience, 22: 519–533
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Finkelstein J., McLaughlin K., Levin M. (2019), Interdisciplinary Approach Needed to Crack Morphogenesis, , December 2019
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Levin, M., (2019), The Computational Boundary of a 'Self': Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition, Frontiers in Psychology, 10:2688, doi: 10.3389/fpsyg.2019.02688
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Levin, S., and Levin, M., (2019), Managing Ideas, People, and Projects: Organizational Tools and Strategies for Researchers, iScience, 20: 278–291
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Payne, S. L., Levin, M., and Oudin, M. J., (2019), Bioelectric control of metastasis in solid tumors, Bioelectricity, 1(3): 114-130
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Fields, C., and Levin, M., (2019), Somatic Multicellularity as a Satisficing Solution to the Prediction-Error Minimization Problem, Communicative & Integrative Biology, 12(1): 119-132
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Whited, J., and Levin, M., (2019), Bioelectrical controls of morphogenesis: from ancient mechanisms of cell coordination to biomedical opportunities, Current Opinion in Genetics & Development, 57: 61-69
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Levin, M., and Martinez-Arias, A., (2019), Reverse-engineering growth and form in Heidelberg, Development, 146: dev177261
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Cervera, C., Pai, V. P., Levin, M., and Mafe, S., (2019), From non-excitable single-cell to multicellular bioelectrical states supported by ion channels and gap junction proteins: electrical potentials as distributed controllers, Progress in Biophysics and Molecular Biology, 149: 39-53
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Bonzanni, M., Rouleau, N., Levin, M., and Kaplan, D., (2019), On the generalization of habituation: how discrete biological systems respond to repetitive stimuli, BioEssays, 41(7): 1900028
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Kuchling, F., Friston, K., Georgiev, G., and Levin, M., (2019), Morphogenesis as Bayesian Inference: a Variational Approach to Pattern Formation and Control in Complex Biological Systems, Physics of Life Reviews, in press
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Manicka, S., and Levin, M., (2019), The Cognitive Lens: a primer on conceptual tools for analysing information processing in developmental and regenerative morphogenesis, Philosophical Transactions of the Royal Society B, 374: 20180369
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Bizzari, M., Brash, D., Briscoe, J., Grieneisen, V., Stern, C. D., and Levin, M., (2019), A Call for a Better Understanding of Causation in Cell Biology, Nature Reviews Molecular Cell Biology, 20(5): 261-262
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Levin, M., Pietak, A., and Bischof, J., (2019), Planarian Regeneration as a Model of Anatomical Homeostasis: Recent Progress in Biophysical and Computational Approaches, Seminars in Cell and Developmental Biology, 87: 125-144
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Berard, A., Levin, M., Sadler, T., Healy, D., (2019), Selective Serotonin Reuptake Inhibitor Use During Pregnancy and Major Malformations: The Importance of Serotonin for Embryonic Development and the Effect of Serotonin Inhibition on the Occurrence of Malformations, Bioelectricity, 1(1): 18-29
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Kamm, R. D., Bashir, R., Arora, N., Dar, R. D., Gilette, M. U., Griffith, L. G., Kemp, M. L., Kinlaw, K., Levin, M., Martin, A. C., McDevitt, T. C., Nerem, R. M., Powers, M. J., Saif, T. A., Sharpe, J., Takayama, S., Takeuchi, S., Weiss, R., Ye, K., Yevick, H. G., and Zaman, M. H., (2018), Perspective: the promise of multi-cellular engineered living systems, APL Bioengineering, 2(4): 040901
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Pezzulo, G., and Levin, M., (2018), Embodying Markov blankets. Comment on 'Answering Schrödinger's question: A free-energy formulation' by Maxwell James Désormeau Ramstead et al., Physics of Life Reviews, 24: 32-36
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Cervera, J., Pietak, A., Levin, M., and Mafe, S., (2018), Bioelectrical coupling in multicellular domains regulated by gap junctions: a conceptual approach, Bioelectrochemistry, 123: 45-61
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Pietak, A., and Levin, M., (2018), Bioelectrical control of positional information in development and regeneration: a review of conceptual and computational advances, Progress in Biophysics and Molecular Biology, 137: 52-68
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Mathews, J., and Levin, M., (2018), The Body Electric 2.0: Recent Advances in Developmental Bioelectricity for Regenerative and Synthetic Bioengineering, Current Opinion in Biotechnology, 52: 134-144
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Monsoro-Burq, A.H., and Levin, M., (2018), Avian models and the study of invariant asymmetry: how the chicken and the egg taught us to tell right from left, International Journal of Developmental Biology, 62(1-3): 63-77
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Fields, C., and Levin, M., (2018), Are planaria individuals? What regenerative biology is telling us about the nature of multicellularity, Evolutionary Biology,
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Levin, M., and Martyniuk, C. J., (2018), The bioelectric code: An ancient computational medium for dynamic control of growth and form, BioSystems, 164: 76-93
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Herrera-Rincon, C., and Levin, M., (2018), Booting up the organism during development: pre-behavioral functions of the vertebrate brain in guiding body morphogenesis, Communicative & Integrative Biology, 11(1): e1433440
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Vallverdu, J., Castro, O., Mayne, R., Talanov, M., Levin, M., Baluska, F., Gunji, Y., Dussutour, A., Zenil, H., and Adamatzky, A., (2018), Slime mould: the fundamental mechanisms of biological cognition, BioSystems, 165: 57-70
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Fields, C., and Levin, M., (2018), Multiscale Memory And Bioelectric Error Correction In The Cytoplasm-Cytoskeleton-Membrane System, Wiley Interdisciplinary Reviews: Systems Biology and Medicine, 10(2): e1410
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Tuszynski, J., Tilli, T. M., and Levin, M., (2017), Ion channel and neurotransmitter modulators as electroceutical approaches to the control of cancer, Current Pharmaceutical Design, 23(32): 4827-4841
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McLaughlin, K. A., and Levin, M., (2017), Bioelectric Signaling in Regeneration: Mechanisms of Ionic Controls of Growth and Form, Developmental Biology, 433(2): 177–189
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Adams, D. S., Tseng. A-S., and Levin, M., (2017), Using optogenetics in vivo to stimulate regeneration, in K. Appasani (Ed.), Optogenetics: From Neuronal Function to Mapping and Disease Biology, Cambridge University Press: Cambridge, UK, p. 66-76

Mathews, J., and Levin, M., (2017), Gap Junctional Signaling in Pattern Regulation: physiological network connectivity instructs growth and form, Developmental Neurobiology, 77(5): 643-673
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Levin, M., Pezzulo, G., and Finkelstein, J. M., (2017), Endogenous Bioelectric Signaling Networks: Exploiting Voltage Gradients for Control of Growth and Form, Annual Review of Biomedical Engineering, 19: 353-87
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Blackiston, D. J., and Levin, M., (2017), Reversals of bodies, brains, and behavior: quantitative analysis of laterality and its disturbance in model species, in L. J. Rogers and G. Vallortigara (Eds.), Lateralized Brain Functions: Methods in Human and Non-human Species, "Neuromethods", W. Walz (Ed.), 122: 667-694
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Levin, M., and Adams, D. S., (2016), Ahead of the Curve: Hidden Breakthroughs in the Biosciences, Vol. 1, IOP Publishing: Bristol, UK

Levin, M., Klar, A. J. S., Ramsdell, A., (2016), Introduction to provocative questions in Left-Right asymmetry, Philosophical Transactions B, 371: 20150399
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McDowell, G., Rajadurai, S., and Levin, M., (2016), From cytoskeletal dynamics to organ asymmetry: a nonlinear, regulative pathway underlies left-right patterning, Philosophical Transactions B, 371: 20150409
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Pezzulo, G., and Levin, M., (2016), Top-down models in biology: explanation and control of complex living systems above the molecular level, Journal of the Royal Society Interface, 13: 20160555
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Herrera-Rincon, C., Guay, J., and Levin, M., (2016), Bioelectrical coordination of cell activity toward anatomical target states: an engineering perspective on regeneration, Chapter 4 in D. Gardiner (Ed.), Regenerative Engineering and Developmental Biology: Principles and Applications, CRC Press: Boca Raton, FL, p. 55-112
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Neuhof, M., Levin, M., and Rechavi, O., (2016), Vertically and horizontally-transmitted memories – the fading boundaries between regeneration and inheritance in planaria, Biology Open, 5, 1177-1188
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Baluska, F., and Levin, M., (2016), On Having No Head: Cognition throughout Biological Systems, Frontiers in Psychology, 7: 902, doi: 10.3389/fpsyg.2016.00902
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Sullivan, K. G., Emmons-Bell, M., and Levin, M., (2016), Physiological Inputs Regulate Species-Specific Anatomy During Embryogenesis And Regeneration, Communicative and Integrative Biology, 9:4, e1192733
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Edelstein, L., Fuxe, K., Levin, M., Popescu, B., and Smythies, J., (2016), Telocytes in their context with other intercellular communication agents, Seminars in Cell and Developmental Biology, 55:9–13
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Durant, F., Lobo, D., Hammelman, J., and Levin, M., (2016), Physiological controls of large-scale patterning in planarian regeneration: a molecular and computational perspective on growth and form, Regeneration, 3(2): 78-102
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Pezzulo, G., and Levin, M., (2015), Re-membering the body: applications of computational neuroscience to the top-down control of regeneration of limbs and other complex organs, Integrative Biology, 7: 1487-1517
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Lobo, D., and Levin, M., (2016), Computing a worm: reverse-engineering planarian regeneration, Advances in Unconventional Computing, Andrew Adamatzky ed., Vol. 2, Springer, p. 637-654

Bessonov, N., Levin, M., Morozova, N., Reinberg, N., Tosenberger, A., Volpert, V., (2015), Target morphology and cell memory: a model of regenerative pattern formation, Neural Regeneration Research, 10(12): 1901-1905
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Blackiston, D. J., Shomrat, T., and Levin, M., (2015), The Stability of Memories During Brain Remodeling: a Perspective, Communicative and Integrative Biology, 8(5): e1073424
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Levin, M., (2015), Nerves read the electrical topography of their microenvironment in making growth decisions, The Node
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Friston, K., Levin, M., Sengupta B., and Pezzulo, G., (2015), 'Knowing one's place' a free energy approach to pattern regulation, Journal of the Royal Society Interface, 12: 20141383
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Levin, M., (2014), Molecular bioelectricity: how endogenous voltage potentials control cell behavior and instruct pattern regulation in vivo, Molecular Biology of the Cell, 25(24): 3835-3850
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Zhu, F., Skommer, J., Huang, Y., Akagi, J., Adams, D. S., Levin, M., Hall, C. J., Crosier, P. S., and Wlodkowic, D., (2014), Fishing on chips: up-and-coming technological advances in analysis of zebrafish and Xenopus embryos, Cytometry A, 85A: 921-932
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Mustard, J., and Levin, M., (2014), Bioelectrical mechanisms for programming growth and form: taming physiological networks for soft body robotics, Soft Robotics, 1(3): 169-191
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Hernandez-Diaz S., and Levin, M., (2014), Alteration of bioelectrically-controlled processes in the embryo: a teratogenic mechanism for anticonvulsants, Reproductive Toxicology, 47: 111-114
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Lobikin, M., and Levin, M., (2014), Endogenous bioelectric cues as morphogenetic signals in vivo, Chapter 15 in D. Fels, M. Cifra, and F. Scholkmann (Eds), Fields of the Cell, Research Signpost: Kerala, India p. 283-302
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Pai, V., and Levin, M., (2014), Bioelectric controls of stem cell function, Chapter 5 in F. Calegari and C. Waskow (Eds.), Stem Cells: From Basic Research to Therapy, Volume 1, CRC Press: Boca Raton, FL, p. 106-145
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Levin, M., (2014), Endogenous bioelectrical networks store non-genetic patterning information during development and regeneration, Journal of Physiology, 592(11): 2295–2305
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Lobo, D., Solano, M., Bubenik, G. A., and Levin, M., (2014), A linear-encoding model explains the variability of the target morphology in regeneration, Journal of the Royal Society Interface, 11(92): 20130918
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Levin, M., (2013), Remembrance of Brains Past, The Node
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Vandenberg, L. N., Lemire, J. M, and Levin, M., (2013), It's Never too Early to get it Right: A Conserved Role for the Cytoskeleton in Left-Right Asymmetry, Communicative & Integrative Biology, 6(6): e27155
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Chernet, B., and Levin, M., (2013), Endogenous voltage potentials and the microenvironment: bioelectric signals that reveal, induce, and normalize cancer, Journal of Clinical and Experimental Oncology, S1: doi:10.4172/2324-9110.S1-002
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Levin, M., (2013), Reprogramming cells and tissue patterning via bioelectrical pathways: molecular mechanisms and biomedical opportunities, Wiley Interdisciplinary Reviews: Systems Biology and Medicine, 5(6): 657-676
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Vandenberg, L. N., and Levin, M., (2013), A unified model for left-right asymmetry? Comparison and synthesis of molecular models of laterality, Developmental Biology, 379(1): 1-15
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Adams, D. S., and Levin, M., (2013), Endogenous Voltage Gradients as Mediators of Cell-Cell Communication: Strategies for Investigating Bioelectrical Signals During Pattern Formation, Cell and Tissue Research, 352(1):95-122
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Tseng, A-S., and Levin, M., (2013), Cracking the bioelectric code: probing endogenous ionic controls of pattern formation, Communicative & Integrative Biology, 6(1): e22595
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Tseng, A.-S., and Levin, M., (2012), Transducing bioelectrical signals into epigenetic pathways during tadpole tail regeneration, Anatomical Record, 295(10): 1541-1551
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Levin, M., (2012), Morphogenetic fields in embryogenesis, regeneration, and cancer: non-local control of complex patterning, BioSystems, 109(3): 243­-261
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Lobo, D., Beane, W., and Levin, M., (2012), Modeling planarian regeneration: a primer for reverse-engineering the worm, PLoS Computational Biology, 8(4): e1002481 [cover]
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Levin, M., and Stevenson, C., (2012), Regulation of Cell Behavior and Tissue Patterning by Bioelectrical Signals: challenges and opportunities for biomedical engineering, Annual Reviews in Biomedical Engineering, 14: 295-323
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Levin, M., (2012), Molecular bioelectricity in developmental biology: new tools and recent discoveries. BioEssays, 34(3): 205-217
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Levin, M. (2011), Endogenous bioelectrical signals in development, regeneration, and neoplasm, in Topical Talks: The Biomedical & Life Sciences Collection, Henry Stewart Talks Ltd, London.
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Levin, M. (2011), Left-Right Asymmetry in Embryonic Development: How epigenetic, biophysical forces and gene activity interplay to determine a major embryonic axis, in Topical Talks: The Biomedical & Life Sciences Collection, Henry Stewart Talks Ltd, London.
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Levin, M., (2011), Endogenous Bioelectric Signals as Morphogenetic Controls of Development, Regeneration, and Neoplasm, in The Physiology of Bioelectricity in Development, Tissue Regeneration, and Cancer, C. Pullar (Ed.), CRC Press: Boca Raton, FL, p. 39-89
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Levin, M., (2011), The wisdom of the body: future techniques and approaches to morphogenetic fields in regenerative medicine, developmental biology, and cancer. Regenerative Medicine, 6(6): 667-673
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Vandenberg, L. N., and Levin, M., (2010), Far from solved: a perspective on what we know about early mechanisms of left-right asymmetry. Developmental Dynamics, 239: 3131-3146
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Levin, M. (2009), Bioelectric mechanisms in regeneration: Unique aspects and future perspectives. Seminars in Cell and Developmental Biology, 20: 543-556
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Levin, M., (2009), Errors of Geometry: regeneration in a broader perspective. Seminars in Cell and Developmental Biology, 20(6): 643-645
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Levin, M., (2009), Regeneration: recent advances, major puzzles, and biomedical opportunities. Seminars in Cell and Developmental Biology, 20(5): 515-516
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Levin, M., Sundelacruz, S., Levin M., Kaplan, D. L., (2009), Role of membrane potential in the regulation of cell proliferation and differentiation, Stem Cell Reviews, 5(3): 231-46
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Blackiston, D. J., K. McLaughlin, and Levin, M., (2009), Bioelectric controls of cell proliferation: ion channels, membrane voltage, and the cell cycle, Cell Cycle, 8(21): 3527-3536
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Aw, S., and Levin, M., (2009), Is left-right asymmetry a form of planar cell polarity?, Development, 136: 355-366
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Vandenberg, L., and Levin, M., (2009), Perspectives and open problems in the early phases of left-right patterning, Seminars in Cell and Developmental Biology, 20: 456-463
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Oviedo, N., and Levin, M., (2008), Planarian regeneration model as a context for the study of drug effects and mechanisms, in Planaria: A Model for Drug Action and Abuse, R. B. Raffa & S.M. Rawls (Eds.), RG Landes Co.: Austin, p. 95-104

Nicolas, C.L., Abramson, C.I., and Levin, M. (2008), Analysis of behavior in the planarian model, in Planaria: A Model for Drug Action and Abuse, Raffa RB & Rawls SM (eds), RG Landes Co.: Austin, pp. 83-94

Aw, S., and Levin, M., (2008), What's Left in Asymmetry?, Developmental Dynamics, 237: 3453-3464
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Oviedo, N., Nicolas, C. L., Adams, D. S., and Levin, M. (2008), Planarians: a versatile and powerful model system for molecular studies of regeneration, adult stem cell regulation, aging, and behavior, in Emerging Model Organisms: A Laboratory Manual, Volume 1, Cold Spring Harbor Press: Cold Spring Harbor, NY
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Tseng, A-S., and Levin, M., (2008), Tail regeneration in Xenopus laevis as a model for understanding tissue repair, Journal of Dental Research, 87(9): 806-816
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Levin, M., Palmer, R., (2007), Left-right patterning from the inside out: widespread evidence for intracellular control, BioEssays, 29: 271-287
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Levin, M., (2007), Gap junctional communication in morphogenesis. Progress in Biophysics and Molecular Biology, 94 (1-2): 186-206
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Levin, M., (2007), Large-Scale Biophysics: Ion Flows and Regeneration. Trends in Cell Biology, 17(6): 261-270
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Ingber, D., and Levin, M. (2007), What lies at the interface of regenerative medicine and developmental biology? Development, 134: 2541-2547
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Oviedo, N., and Levin, M. (2007), Gap junctions provide new links in Left-Right patterning, Cell, 129: 645-647
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Of Minds and Embryos: Left-Right Asymmetry and the Serotonergic Controls of Pre-Neural Morphogenesis

Levin, M., Lauder, J., and Buznikov, G., (2006), Of minds and embryos: serotonin signaling as a pre-nervous morphogenetic mechanism. Developmental Neuroscience, 28:171-185
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Levin, M., (2006), Is the Early Left-Right Axis like a Plant, a Kidney, or a Neuron? The Integration of Physiological Signals in Left-Right Asymmetry. Birth Defects Research (Part C), 78: 191-223
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Levin, M., (2005), Left-right asymmetry in embryonic development: a comprehensive review. Mechanisms of Development, 122(1): 3-25
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Levin, M., (2004), The embryonic origins of left-right asymmetry. Critical Reviews in Oral Biology and Medicine, 15(4): 197-206
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Adams, D. S., and Levin, M. (2004). Early Patterning of the Left/Right Axis. in C. D. Stern (Ed.), Gastrulation: from cells to embryo Cold Spring Harbor, New York, pp. 403-417
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M. Levin, (2003), Bioelectromagnetics in morphogenesis. Bioelectromagnetics, 24(5): 295-315
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Levin, M., (2003), Motor protein control of ion flux is an early step in embryonic left-right asymmetry, BioEssays, 25(10): 1002-1010
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Levin, Michael, (2002), Isolation and community: A review of the role of gap-junctional communication in embryonic patterning. Journal of Membrane Biology, 185 (3): 177-192
PDF

M. Mercola, and M. Levin, (2001), Left-Right asymmetry determination in vertebrates. Annual Review of Cell and Developmental Biology, 17: 779-805
PDF

Levin, M., (2001), Asymmetry of Body and Brain: Embryological and Twin Studies, in N. Smelser and P. Baltes (Eds.), International Encyclopedia of the Social and Behavioral Sciences, Elsevier, Oxford, UK, pp. 853-859
PDF

Levin, Michael, (1999), Twinning and embryonic left-right asymmetry. Laterality, 4(3): 197-208
PDF

Levin, M., (1999), Left-right asymmetry in animal embryogenesis, in G. Palyi, C. Zucchi, and L. Caglioti (Eds.), Advances in Biochirality, ch. 12, pp. 137-152, Elsevier Science LTD: Oxford, UK
PDF

Levin, M., (1999), Endogenous electromagnetic fields and radiations in regeneration, development, and neoplasm, Proceedings of the First World Congress on the Effects of Electricity and Magnetism in the Natural World, Madeira, Portugal

Levin, M., (1998), Left-Right asymmetry and the chick embryo, Seminars in Cell & Developmental Biology, 9(1): 67-76
PDF

Levin, M., and Nascone, N., (1997), Two molecular models of initial left-right asymmetry generation, Medical Hypotheses, 49(5): 429-435
PDF

Levin, M., (1997), Left-right asymmetry in vertebrate embryogenesis, BioEssays, 19(4): 287-296
PDF | Link

Levin, M., (1995), Use of Genetic Algorithms to Solve Biomedical Problems, M.D. Computing, 12(3): 193-198
PDF

Levin, Michael, Current and potential applications of bioelectromagnetics in medicine, (1993), ISSEEM Journal, 4(1): 77-87
PDF


Species prevalence

While the classification of small strongyle species of horses has been the subject of some discussion, there is general agreement that more than 50 species may be involved in parasitism of horses. Identification of species is usually performed on adult rather than larval stages, although in more recent times in vitro testing based on genotype has been developed [17].

Information is available on the most prevalent species of cyathostomins from a number of continents [3, 5, 7, 9, 18] and from differing climatic regions within continents. Often, cyathostomins were present in the majority of horses surveyed (>70% to 100%) with multiple species present in individual animals. The number of species ranged from a few to up to 26, but there was a remarkable similarity in the predominant species, regardless of geography. For example, Cyathostomum catinatum, Cylicocyclus nassatus and Cylicostephanus longibursatus were found to be amongst the most prevalent five species in France, Ukraine, US and Australia. C. nassatus was also common in Brazil. Other species that were widely recognized included Cylicostephanus minutus, Cylicostephanus calicatus and Cyathostomum insigne. Ambient temperature does not appear to be a significant factor in species distribution, as the mix of species reported from tropical and temperate climatic zones in Australia was very similar [3, 9].

Little is understood about the relative pathogenicity of individual species, or what determines the balance of species in any mixed population. Some species are known to predominantly reside in the colon, while others seem to prefer the caecum [19]. Little is also known about individual species' lifecycles in terms of patency period, although it has been reported that those species residing in the caecum appear later in the faeces than species residing in the colon [20].


Dr. Paramita M. Ghosh, Ph.D.

Paramita Ghosh studies the signal transduction pathways involved in the development and progression of prostate cancer. Advanced prostate cancer is treated by hormonal manipulation using various drugs that affect a steroid nuclear receptor called the androgen receptor. However, patients on this treatment eventually become resistant to this treatment. The overall goal of Dr. Ghosh's lab is to find ways by which resistance to the androgen receptor inhibitors can be overcome. Based on work done in her lab, a clinical trial was recently completed by UC Davis oncologists that demonstrated how a combination of two FDA approved drugs can be used to overcome resistance to each of these drugs. Her lab uses a number of biochemical and molecular biological techniques to achieve these goals. Dr. Ghosh currently has three graduate students and will welcome volunteer undergraduate students who will be working on these projects.

Research Interests

Signal Transduction Pathways in Prostate Cancer

The pathways we study include the phosphatidylinositol 3-kinase (PI3K)/Akt pathway, the Ras/Raf/MEK/MAPK pathway and other signaling pathways both upstream and downstream of these. This includes the mammalian target of rapamycin (mTOR) pathway, and signaling by the epidermal growth factor receptor (EGFR), related receptor tyrosine kinases ErbB2 and ErbB3.

Grad Group Affiliations

  • Biochemistry, Molecular, Cellular and Developmental Biology
  • Comparative Pathology (Vet Med)
  • Pharmacology and Toxicology (PTX)

Specialties / Focus

  • Cancer Biology
  • Cell Division and the Cytoskeleton
  • Integrated Genetics and Genomics
  • Signal Transduction

Courses

  • PMI 200 Foundations in Research , Fall
  • BCB 256 Cell and Molecular Biology of Cancer, Winter
  • Postdoctoral Fellows http://www.ucdmc.ucdavis.edu/urology/research/example/example_ghosh.html
    • Salma Siddiqui
    • Maria Malvina Tsamouri (PhD student), GGIP
    • Dontrel Hairston (PhD Student), PTX
    • Thomas Steele

    Honors and Awards

    • 2000 WICR Young Investigator Scholar Award. American Association for Cancer Research
    • 1997-1999 NIH Postdoctoral Training Award. Department of Pathology, University of Texas Health Science Center at San Antonio, TX.
    • 1989-1994 Tuition Scholarship and Graduate Assistantship. Rensselaer Polytechnic Institute, Troy, NY
    • 1989 Gold Medal for Excellence, Master of Science. Department of Physics, Jadavpur University, Calcutta 700032, India
    • 1989 S.N. Bose Medal for best academic achievement. Department of Physics, Jadavpur University, Calcutta 700032, India.
    • 1983-1989 National Science Scholarship. University Grants Commission, Government of India
    • 2006 UC Davis Academic Federation Travel Award
    • 2006 Best Poster Award. International Symposium on Hormonal Carcinogenesis, Montpellier, France
    • 2010 Travel Award, 6th International Symposium on Hormonal Oncogenesis, Tokyo, Japan.
    • 2007 California Coalition to Cure Prostate Cancer Award, ($26,000) Prostate Cancer Foundation, Santa Monica, CA
    • 2013 Scientist Selected to Join Global Task Force focused on Cancer Causing Potential of Chemicals (Getting to know Cancer)
    • 2016 “Exceptional Women in Endocrine Cancer” profile, Endocrine Related Cancers, 2016.

    Professional Societies

    • American Association for Cancer Research
    • Society of Basic Urological Research
    • American Association for the Advancement of Science
    • American Society for Cell Biology

    Degrees

    • 1994 PhD Chemistry Rensselaer Polytechnic Institute
    • 1988 MS Physics Jadavpur University, Calcutta, INDIA
    • 1986 BS Physics Jadavpur University, Calcutta, INDIA

    Publications

    Martin KA, Hum NR, Sebastian A, He W, Siddiqui S, Ghosh PM, Pan CX, de Vere White R, Loots GG. Methionine Adenosyltransferase 1a (MAT1A) Enhances Cell Survival During Chemotherapy Treatment and is Associated with Drug Resistance in Bladder Cancer PDX Mice. Int J Mol Sci., 20(20): E4983, 2019.

    Jathal MK, Steele TM, Siddiqui S, Mooso BA, D'Abronzo LS, Drake CM, Whang YE, Ghosh PM. Dacomitinib, but not lapatinib, suppressed progression in castration-resistant prostate cancer models by preventing HER2 increase. British Journal of Cancer, 121(3): 237-248, 2019.

    Shih TC, Fan Y, Kiss S, Li X, Deng XN, Liu R, Chen XJ, Carney R, Chen A, Ghosh PM, Lam KS. Galectin-1 inhibition induces cell apoptosis through dual suppression of CXCR4 and Ras pathways in human malignant peripheral nerve sheath tumors. Neuro Oncol., 17(19): 6218-6228, 2019.

    Lombard AP, Liu C, Armstrong CM, D'Abronzo LS, Lou W, Chen H, Dall'Era M, Ghosh PM, Evans CP, Gao AC. Overexpressed ABCB1 Induces Olaparib-Taxane Cross-Resistance in Advanced Prostate Cancer. Translational Oncology, 12(7): 871-878, 2019.

    Steele TM, Talbott GC, Sam A, Tepper CG, Ghosh PM, Vinall RL. Obatoclax, a BH3 Mimetic, Enhances Cisplatin-Induced Apoptosis and Decreases the Clonogenicity of Muscle Invasive Bladder Cancer Cells via Mechanisms That Involve the Inhibition of Pro-Survival Molecules as Well as Cell Cycle Regulators. International Journal of Molecular Science, 20(6): E1285, 2019.

    D'Abronzo LS, Pan CX, Ghosh PM. Evaluation of Protein Levels of the Receptor Tyrosine Kinase ErbB3 in Serum. Methods in molecular biology (Clifton, N.J.). 2018 1655:319-334. PMID: 28889394

    Shih TC, Liu R, Wu CT, Li X, Xiao W, Deng X, Kiss Z, Wang T, Chen X, Carney RP, Kung HJ, Duan Y, Ghosh PM, Lam KS. Targeting Galectin-1 impairs castration-resistant prostate cancer progression and invasion. Clin Cancer Res. 2018. Sep 124(17):4319-4331. PMID: 29666302

    D'Abronzo LS, Ghosh PM. eIF4E Phosphorylation in Prostate Cancer. Neoplasia . 2018 Jun20(6):563-573. PMID: 29730477.

    Baek, HB, Lombard, AP, Libertini, SJ, Fernandez-Rubio, A, Vinall, RL, Gandour-Edwards, R., Nakagawa, R., Vidallo, K., Nishida, K., Siddiqui, S. Wettersten, H., Landesman, Y., Weiss, RH, Ghosh, PM, Mudryj, M. XPO1 inhibition by selinexor induces potent cytotoxicity against high grade bladder malignancies. Oncotarget, 2018. Oct 29(77):34567-34581 . PMID: 30349650

    Shi Y, Shu ZJ, Wang H, Barnes JL, Yeh CK, Ghosh PM, Katz MS, Kamat A. Altered Expression of Hepatic β-Adrenergic Receptors in Aging Rats: Implications for Age-Related Metabolic Dysfunction in Liver. Am J Physiol Regul Integr Comp Physiol. 2017 Dec 6:ajpregu.00372.2017. doi: 10.1152/ajpregu.00372.2017.

    Kent MS, Zwingenberger A, Westropp JL, Barrett LE, Durbin-Johnson BP, Ghosh P, Vinall RL. MicroRNA profiling of dogs with transitional cell carcinoma of the bladder using blood and urine samples. BMC Vet Res. 2017 Nov 1513(1):339. doi: 10.1186/s12917-017-1259-1.

    D'Abronzo LS, Pan CX, Ghosh PM. Evaluation of Protein Levels of the Receptor Tyrosine Kinase ErbB3 in Serum. Methods Mol Biol. 20181655:319-334. doi: 10.1007/978-1-4939-7234-0_22.

    D'Abronzo LS, Bose S, Crapuchettes ME, Beggs RE, Vinall RL, Tepper CG, Siddiqui S, Mudryj M, Melgoza FU, Durbin-Johnson BP, deVere White RW, Ghosh PM. The androgen receptor is a negative regulator of eIF4E phosphorylation at S209: implications for the use of mTOR inhibitors in advanced prostate cancer. Oncogene. 2017 Nov 1636(46):6359-6373. doi: 10.1038/onc.2017.233.

    Shih TC, Liu R, Fung G, Bhardwaj G, Ghosh PM, Lam KS. A Novel Galectin-1 Inhibitor Discovered through One-Bead Two-Compound Library Potentiates the Antitumor Effects of Paclitaxel in vivo. Molecular cancer therapeutics. 2017 16(7):1212-1223. NIHMSID: NIHMS867388 PMID: 28396365, PMCID: PMC5516795

    Kiss Z, Ghosh PM. Circadian rhythmicity and the influence of 'clock' genes on prostate cancer.Endocr Relat Cancer. 2016 Sep 22. pii: ERC-16-0366. [Epub ahead of print].

    Ghosh PM. From physics to cancer biology and everywhere in between. Endocr Relat Cancer. 2016 Sep 7. pii: ERC-16-0382. [Epub ahead of print]

    Vinall, R.L., Tepper, C.G., Ripoll, A.Z., Gandour- Edwards, R.F., Durbin-Johnson, B.P., Yap, S.A., Ghosh, P.M. and deVere White, R.W. Decreased expression of let-7c is associated with non-response of muscle-invasive bladder cancer patients to neoadjuvant chemotherapy. Genes & Cancer, Vol. 7 (3-4): 86-97, March 2016.

    Lombard, A. P., Mooso, B. A., Libertini, S. J., Lim, R. M., Nakagawa, R., Vidallo, K., Costanzo, N., Ghosh, P. M., Mudryj, M. miR-148a Dependent Apoptosis of Bladder Cancer Cells is Mediated in Part by the Epigenetic Modifier DNMT1. Molecular Carcinogenesis, 2016 May55(5):757-67. (PMID: 25865490)

    Chow, H., Ghosh, PM, deVere White, RW, Evans, CP, Dall’Era, MA, Yap, SA, Li, Y, Beckett, LA, Lara, PN, Pan, CX. A Phase II clinical trial of everolimus plus bicalutamide for castration-resistant prostate cancer. Cancer. 2016 Jun 15122(12):1897-904. PMID: 27019001.

    D'Abronzo LS, Ghosh PM. Medical Treatment of Urological Malignancies. Stief CG, Fizazi K, Evans CP, editors. Lisbon: International Consultation on Medical Treatment of Urological Malignancies 2015. Chapter Section X, The Akt/PI3K/PTEN pathway as a driver and therapeutic target in castration-resistant prostate cancer p.325-336.

    Pan, C.-x., Zhang, H., Tepper, C. G., Lin, T.-y., Davis, R. R., Keck, J., Ghosh, P. M., Gill, P., Airhart, S., Bult, C., Gandara, D. R., Liu, E., de Vere White, R. W. Development and characterization of bladder cancer patient-derived xenografts for molecularly guided targeted therapy. PLOS ONE. 2015 Aug 1310(8):e0134346. PMID: 26270481

    Narayanan, K.N., Ali, M., Barclay, B., Cheng, Q.S., D'Abronzo, L.S., Dornetshuber-Fleiss, R., Ghosh, P.M., et al, Disruptive environmental chemicals and cellular mechanisms that confer resistance to cell death. Carcinogenesis, 2015. ** Jun36 Suppl 1:S89-S110**. PMID: 26106145

    Goodson, W.H. III, Lowe, L., …. Ghosh, P.M., et al. Assessing the Carcinogenic Potential of Low Dose Exposures to Chemical Mixtures in the Environment: The Challenge Ahead. Carcinogenesis, 2015. ** Jun36 Suppl 1:S254-96**. PMID: 26106142

    Savoy, R.M., Chen, L., Siddiqui, S., Melgoza, F.U., Durbin-Johnson, B., Drake, C., Jathal, M.K., Bose, S., Steele, T.M., Mooso, B.A., D’Abronzo, L.S., Fry, W.H., Carraway, K.L. III, Mudryj, M. and Ghosh, P.M. Transcription of Nrdp1 by the androgen receptor is regulated by nuclear Filamin A in prostate cancer. Endocrine-related Cancer, 2015. Jun 22(3):369-86 (PMID: 25759396).

    Mooso, B.A., Vinall, R.L., Mudryj, M., Yap, S.A., deVere White, R.W., Ghosh, P.M. The Role of EGFR Family Inhibitors in Muscle-Invasive Bladder Cancer. Journal of Urology. 2015. Jan193(1):19-29.

    Ghosh P, Qiu Y, Wang LY and Kung HJ: Tyrosine kinome profiling: Oncogenic mutations and therapeutic targeting in cancer, Molecular Oncology – Causes of Cancer ad Targets for Treatment. Eds. Gelmann, E.P., Sawyers, C.L. and Rauscher, F.J. Cambridge University Press. pages 58-75. Feb 2014.

    Ghosh PM and A.C. Gao. Zoledronic acid at the time of castration prevented castration-induced bone metastasis in mice. Endocrine related Cancers. 2014. Oct21(5):C11-4

    Ghosh PM. Editorial Comments on “The impact of histological reclassification during pathology re-review--evidence of a Will Rogers effect in bladder cancer?”. J. Urology. 2013 Nov190(5):1697

    Savoy RM, Ghosh PM. The changing roles of steroid nuclear receptors with prostate cancer progression. Endocr Relat Cancer. 2013 Jul 420(4):C9-11.

    Savoy RM, Ghosh PM. Linking inflammation and neuroendocrine differentiation: the role of macrophage migration inhibitory factor-mediated signaling in prostate cancer. Endocr Relat Cancer. 2013 May 2120(3):C1-4.

    Savoy RM, Ghosh PM. The dual role of filamin A in cancer: can't live with (too much of) it, can't live without it. Endocr Relat Cancer. 2013 Nov 420(6):R341-56.

    Mooso BA, Vinall RL, Tepper CG, Savoy RM, Cheung JP, Singh S, Siddiqui S, Wang Y, Bedolla RG, Martinez A, Mudryj M, Kung HJ, Devere White RW, Ghosh PM. Enhancing the effectiveness of androgen deprivation in prostate cancer by inducing Filamin A nuclear localization. Endocr Relat Cancer. 2012 Nov 919(6):759-77.

    Ghosh, P.M., Shu, Z.J., Zhu, B., Lu, Z., Ikeno, Y., Barnes, J.L., Yeh, C.K., Zhang, B.K., Katz, M.S. and Kamat, A. β-Adrenergic Receptor Signaling Increases Lipid Accumulation In Liver During Aging. Journal of Endocrinology 2012 Jun213(3):251-61.

    Chen L, Mooso BA, Jathal MK, Madhav A, Johnson SD, van Spyk E, Mikhailova M, Zierenberg-Ripoll A, Xue L, Vinall RL, deVere White RW, Ghosh PM. Dual EGFR/HER2 inhibition sensitizes prostate cancer cells to androgen withdrawal by suppressing ErbB3. Clin Cancer Res. 2011 Oct 1 17 (19):6218-28.

    Vinall RL, Mahaffey CM, Davis RR, Luo Z, Gandour-Edwards R, Ghosh PM, Tepper CG, de Vere White RW. Dual blockade of PKA and NF-B inhibits H2 relaxin-mediated castrate-resistant growth of prostate cancer sublines and induces apoptosis. Horm Cancer. 2011 Aug 2 (4):224-38. PubMed PMID: 21789713.

    Jathal MK, Chen L, Mudryj M, Ghosh PM. Targeting ErbB3: the New RTK(id) on the Prostate Cancer Block. Immunol Endocr Metab Agents Med Chem. 2011 Jun 11 (2):131-149. PubMed PMID: 21603064

    Roy M, Kung HJ, Ghosh PM. Statins and prostate cancer: role of cholesterol inhibition vs prevention of small GTP-binding proteins. Am J Cancer Res. 2011 1 (4):542-61. PubMed PMID: 21984972.

    Ghosh PM. What controls PTEN and what it controls (in prostate cancer). Asian J Androl. 2011 Sep 26 14(1): 130-131. PubMed PMID: 21946231.

    Chen H, Libertini SJ, Wang Y, Kung HJ, Ghosh P, Mudryj M. ERK regulates calpain 2-induced androgen receptor proteolysis in CWR22 relapsed prostate tumor cell lines. J Biol Chem. Jan 22285(4):2368-74. 2010

    Chen, L, Lu, X.-H., Shi, X.-B., R., deVere White, RW, Carraway, K.L. III and Ghosh, PM. Nrdp1-mediated regulation of ErbB3 expression by the androgen receptor in androgen-dependent but not castrate–resistant prostate cancer cells. Cancer Research. 70(14):5994-6003, 2010.

    Mooso, B., Madhav, A. Johnson, S.D., Roy, M., Moore, M.E., Moy, C., Loredo, Mehta, R.G., Vaughan, A.T.M. and Ghosh, P.M. Androgen Receptor regulation of Vitamin D receptor in response of castration-resistant prostate cancer cells to 1α-Hydroxyvitamin D5 – a calcitriol analog. Genes and Cancer, 2010. Nov 161(9):927-940.

    Chen, H., Libertini, S.J., George, M., Dandekar, S., Tepper, C.G., Al-Bataina, B., Kung, H.-J., Ghosh, P.M., Mudryj, M. Genome-wide analysis of androgen receptor binding and gene regulation in two CWR22-derived prostate cancer cell lines. Endocrine-related cancers. 2010. Oct 517(4):857-73.

    Khan, IH, Zhao, J, Ghosh, PM, Ziman, M, Sweeney, C, Kung, HJ and Luciw, PA. Activation and Dimerization of Receptor Tyrosine Kinases (ErbB Family) in Breast Cancer Cells Analyzed by Multiplex Microbead Suspension Array. ASSAY and Drug Development Technologies. Feb8(1):27-36. 2010

    Ghosh P, Qiu Y, Wang LY and Kung HJ: Tyrosine kinome profiling: Oncogenic mutations and therapeutic targeting in cancer, Molecular Oncology – Causes of Cancer ad Targets for Treatment. Eds. Gelmann, E.P., Sawyers, C.L. and Rauscher, F.J. Cambridge University. 58-75. 2014

    Bedolla, RG, Asuncion, A, Chamie, K, Siddiqui, S, Troyer, DA, Mehra, R, Siddiqui, J, Chinnaiyan, AM, deVereWhite, RW, and Ghosh, PM. Nuclear vs Cytoplasmic localization of Filamin A in Prostate Cancer: Immunohistochemical Correlation with Metastases. Clinical Cancer Research, 15(3): 788-796. 2009.

    Chamie, K, Ghosh, PM, Koppie, TM, Romero, V, Troppmann, C,and deVere White, RW. The effect of sirolimus on PSA kinetics in male renal transplant recipients without prostate cancer. American Journal of Transplantation, 8(12): 2668-2673. 2008.

    Wang, Y, Mikhailova, M, deVere White, RW, and Ghosh, PM. Regulation of androgen receptor transcriptional activity by rapamycin. Oncogene, 27(56): 7106-7117. 2008

    Kamat, A., Ghosh, PM, Glover, RL, Zhu, B, Yeh, CK, Choudhury, GG and Katz, MS. Reduced Expression of Epidermal Growth Factor Receptors in. Journal of Gerontology, 63(7): 683-692. 2008

    Mikhailova, M., Wang, Y., Bedolla, R.G., Lu, X.H., Kreisberg, J.I. and Ghosh, P.M.: AKT Regulates Androgen Receptor-dependent Growth and PSA Expression in Prostate Cancer, Adv Exp Med Biol., Vol. 617, pp. 397-405. 2008.

    Wang, Y., Kreisberg, J.I. and Ghosh, P.M. Cross-talk between the Androgen Receptor and the Phosphatidylinositol 3-kinase/Akt pathway in Androgen-Independent Prostate Cancer. Current Cancer Drug Targets. 7: 591-604. 2007

    Shi, X.-B., Xue, L. Tepper, C.G., Gandour-Edwards, R., Ghosh, P., Kung, H.J. and deVere White, R.W. . The oncogenic potential of a prostate cancer-derived androgen receptor mutant. The Prostate, 67(6): 591-602. 2007.

    Bedolla R, Prihoda TJ, Kreisberg JI, Malik SN, Krishnegowda NK, Troyer DA, Ghosh PM. Determining risk of biochemical recurrence in prostate cancer by immunohistochemical detection of PTEN expression and Akt activation. Clin. Cancer Res., 13(13): 3860-3867. 2007

    Wang, Y., Kreisberg, J.I., Bedolla, R., Mikhailova, M., deVere White, R.W. and Ghosh, P.M. A 90 kDa fragment of filamin A promotes Casodex-induced growth inhibition in Casodex-resistant androgen receptor positive C4-2 prostate cancer cells. Oncogene. 2007.

    Mikhailova M, Wang Y, Bedolla RG, Lu XH, Kreisberg JI and Ghosh PM: AKT Regulates Androgen Receptor-dependent Growth and PSA Expression in Prostate Cancer, Adv Exp Med Biol, Vol. 617, pp. 397-405. 2007.

    Vinall, R.L., Hwa, K., Ghosh, P., Pan, C-X., Lara, P.N. Jr. and deVere White, R.W. Combination Treatment Of Prostate Cancer Cell Lines With Bioactive Soy Isoflavones (GCP) And Perifosine Causes Increased Growth Arrest And/Or Apoptosis. Clinical Cancer Research. 13: 6204-6216. 2007.

    Wang, Y., Kreisberg, J.I. and Ghosh, P.M. Cross-talk between the Androgen Receptor and the Phosphatidylinositol 3-kinase/Akt pathway in Androgen-Independent Prostate Cancer. Current Cancer Drug Targets. 7: 591-604. 2007

    Vinall, R.L., Hwa, K., Ghosh, P., Pan, C-X., Lara, P.N. Jr. and deVere White, R.W. Combination Treatment Of Prostate Cancer Cell Lines With Bioactive Soy Isoflavones (GCP) And Perifosine Causes Increased Growth Arrest And/Or Apoptosis. Clinical Cancer Res., 13: 6204-6216, 2007

    Ghosh, P.M., Malik, S.N., Prihoda, T.J., Bedolla, R.G., Wang, Y., Troyer, D.A. and Kreisberg, J.I. Akt mediates proliferation via both androgen-dependent and independent pathways in prostate cancer. Endocr Relat Cancer. Mar12(1):119 34. 2005

    Yeh, C. K.**, Ghosh, P.M.**, Liu, Q., Zhang, B. X., and Katz, M.S. Activation of Mitogen-activated Protein Kinase Mediates Isoproterenol-induced Salivary Cell Growth. Am J Physiol Cell Physiol. 288(6):C1357-C1366. 2005

    Ghosh, P.M., Bedolla, R., Thomas, C.A. and Kreisberg, JI. Role of Protein kinase C in Arginine Vasopressin-stimulated mesangial cell proliferation. J. Cell. Biochem., 2004 91(6):1109-29.

    Kreisberg, J.I., Malik, S.N., Prihoda, T.J., Bedolla, R.G., Troyer, D.A. Kreisberg, S. and Ghosh, P.M. Expression of phospho-AKT (Ser 473) is an excellent predictor of Poor Clinical Outcome in Prostate Cancer. Cancer Res. Aug 164(15):5232-6. 2004

    Ghosh, P.M., Malik, S. N., Bedolla, R. and Kreisberg, J.I. Akt in Prostate Cancer: Possible Role in Androgen-Independence. Current Drug Metabolism, 4(6):487-496. 2003

    Ghosh PM, Bedolla R, Mikhailova M, and Kreisberg JI. RhoA-Dependent Murine Prostate Cancer Cell Proliferation and Apoptosis: Role of PKCzeta. Cancer Res. 62(9):2630-6. 2002

    Malik, S.N., Brattain, M.G., Ghosh, P.M., Troyer, D.A., Prihoda, T., Bedolla, R. and Kreisberg, J.I. Immunohistochemical Demonstration of phospho-Akt in High Gleason Grade Prostate Cancer. Clinical Cancer Res. 8(4):1168-71. 2002

    Sawhney RS, Guo-Hao K, Humphrey LE, Ghosh P, Kreisberg JI, Brattain MG: Differences in sensitivity of biological functions mediated by epidermal growth factor receptor activation with respect to endogenous and exogenous ligands. J Biol Chem 277: 75-86. 2002


    A lots of parameters affect the protein expression besides codon bias:

    • GC content
    • CpG dinucleotides content
    • Cryptic splicing sites
    • Codon-context
    • Negative CpG islands
    • Premature PolyA sites
    • Terminal signal
    • TATA boxes
    • mRNA secondary structure
    • SD sequence
    • RNA instability motif (ARE)
    • RNA secondary structures
    • Interaction of codon and anti-codon
    • Internal chi sites and ribosomal binding sites
    • Stable free energy of mRNA

    GenScript OptimumGene™ algorithm provides a comprehensive solution strategy on optimizing all parameters that are critical to protein expression levels. It can significate increase protein expression level up to 50-fold, provided that the protein expression and purification methods are appropriately applied. More Case Studies.


    Clinical Relevance and Biology of Circulating Tumor Cells

    Most breast cancer patients die due to metastases, and the early onset of this multistep process is usually missed by current tumor staging modalities. Therefore, ultrasensitive techniques have been developed to enable the enrichment, detection, isolation and characterization of disseminated tumor cells in bone marrow and circulating tumor cells in the peripheral blood of cancer patients. There is increasing evidence that the presence of these cells is associated with an unfavorable prognosis related to metastatic progression in the bone and other organs. This review focuses on investigations regarding the biology and clinical relevance of circulating tumor cells in breast cancer.

    Introduction

    Detection of circulating tumor cells (CTCs) in peripheral blood and disseminated tumor cells (DTCs) in bone marrow of tumor patients has become an active area of translational cancer research, with numerous groups developing new diagnostic assays and more than 200 clinical trials incorporating CTC counts as a biomarker in patients with various types of solid tumors. Among these activities, breast cancer has played the most prominent role as a 'driver' of research on CTCs/DTCs. The clinical relevance of DTCs is already well-established [1,2] and has been confirmed by different large-scale studies, including a pooled analysis on almost 5,000 patients. [3] Aspirations of bone marrow, a common homing organ for many types of solid tumors, [1,4] are part of the routine screening of leukemia patients and are much less difficult to perform than biopsies of other organs (for example, lungs or liver). Nevertheless, it is still a painful and invasive procedure that is not comfortable for patients and, due to this fact, has not yet been accepted for routine diagnosis of solid tumors. In contrast, CTCs are easier to obtain by peripheral blood sampling, which can be repeated frequently, allowing real-time monitoring of metastatic progression. Thus, it seems that peripheral blood might serve as a perfect alternative source of material to diagnose cancer patients, and CTC analysis in cancer patients has thus been termed a 'liquid biopsy'. [5]

    On the other hand, detection of CTCs is hampered by the still uncertain biology of these cells, which most likely inherit a heterogeneous malignant potential to home and give rise to overt metastasis in secondary organs. Even modern technologies that have been applied to isolate and characterize CTCs still need to be improved. [6] Although recent results on significant associations between the presence of CTCs and subsequent occurrence or progression of metastases are encouraging, the clinical relevance and utility of CTCs merit further investigation and confirmation by multicenter trials.

    Developments in CTC/DTC technologies over the past few years have been impressive. This review will recapitulate the current knowledge on CTCs in breast cancer patients with a focus on the biology and clinical relevance of these cells.


    Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011144:646–74.

    Aggarwal BB, Vijayalekshmi RV, Sung B. Targeting inflammatory pathways for prevention and therapy of cancer: short-term friend, long-term foe. Clin Cancer Res. 200915:425–30.

    Balkwill FR, Mantovani A. Cancer-related inflammation: common themes and therapeutic opportunities. Semin Cancer Biol. 201222:33–40.

    Grivennikov SI, Greten FR, Karin M. Immunity, inflammation, and cancer. Cell. 2010140:883–99.

    Elyada E, Pribluda A, Goldstein RE, Morgenstern Y, Brachya G, Cojocaru G, Snir-Alkalay I, Burstain I, Haffner-Krausz R, Jung S, et al. CKIalpha ablation highlights a critical role for p53 in invasiveness control. Nature. 2011470:409–13.

    Pribluda A, Elyada E, Wiener Z, Hamza H, Goldstein RE, Biton M, Burstain I, Morgenstern Y, Brachya G, Billauer H, et al. A senescence-inflammatory switch from cancer-inhibitory to cancer-promoting mechanism. Cancer Cell. 201324:242–56.

    Medzhitov R. Origin and physiological roles of inflammation. Nature. 2008454:428–35.

    Chovatiya R, Medzhitov R. Stress, inflammation, and defense of homeostasis. Mol Cell. 201454:281–8.

    Breuer K, Foroushani AK, Laird MR, Chen C, Sribnaia A, Lo R, Winsor GL, Hancock RE, Brinkman FS, Lynn DJ. InnateDB: systems biology of innate immunity and beyond--recent updates and continuing curation. Nucleic Acids Res. 201341:D1228–33.

    Kelley J, de Bono B, Trowsdale J. IRIS: a database surveying known human immune system genes. Genomics. 200585:503–11.

    Kramer A, Green J, Pollard Jr J, Tugendreich S. Causal analysis approaches in Ingenuity Pathway Analysis. Bioinformatics. 201430:523–30.

    Doyle S, Vaidya S, O'Connell R, Dadgostar H, Dempsey P, Wu T, Rao G, Sun R, Haberland M, Modlin R, Cheng G . IRF3 mediates a TLR3/TLR4-specific antiviral gene program. Immunity. 200217:251–63.

    Sato T, Vries RG, Snippert HJ, van de Wetering M, Barker N, Stange DE, van Es JH, Abo A, Kujala P, Peters PJ, Clevers H . Single Lgr5 stem cells build crypt-villus structures in vitro without a mesenchymal niche. Nature. 2009459:262–5.

    Wolff WI, Shinya H. Definitive treatment of "malignant" polyps of the colon. Ann Surg. 1975182:516–25.

    Burn J, Gerdes AM, Macrae F, Mecklin JP, Moeslein G, Olschwang S, Eccles D, Evans DG, Maher ER, Bertario L, et al. Long-term effect of aspirin on cancer risk in carriers of hereditary colorectal cancer: an analysis from the CAPP2 randomised controlled trial. Lancet. 2011378:2081–7.

    Lasry A, Zinger A, Ben-Neriah Y. Inflammatory networks underlying colorectal cancer. Nature Immunology. 201617:230–240.

    Rothwell PM, Fowkes FG, Belch JF, Ogawa H, Warlow CP, Meade TW. Effect of daily aspirin on long-term risk of death due to cancer: analysis of individual patient data from randomised trials. Lancet. 2011377:31–41.

    Streicher SA, Yu H, Lu L, Kidd MS, Risch HA. Case–control study of aspirin use and risk of pancreatic cancer. Cancer Epidemiol Biomarkers Prev. 201423:1254–63.

    Hawiger J. Innate immunity and inflammation: a transcriptional paradigm. Immunol Res. 200123:99–109.

    Hashimoto S, Suzuki T, Dong HY, Nagai S, Yamazaki N, Matsushima K. Serial analysis of gene expression in human monocyte-derived dendritic cells. Blood. 199994:845–52.

    Hashimoto S, Suzuki T, Dong HY, Yamazaki N, Matsushima K. Serial analysis of gene expression in human monocytes and macrophages. Blood. 199994:837–44.

    Barretina J, Caponigro G, Stransky N, Venkatesan K, Margolin AA, Kim S, Wilson CJ, Lehar J, Kryukov GV, Sonkin D, et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature. 2012483:603–7.

    Barbie DA, Tamayo P, Boehm JS, Kim SY, Moody SE, Dunn IF, Schinzel AC, Sandy P, Meylan E, Scholl C, et al. Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1. Nature. 2009462:108–12.

    Aran D, Sirota M, Butte AJ. Systematic pan-cancer analysis of tumour purity. Nat Commun. 20156:8971.

    Consortium GT. The Genotype-Tissue Expression (GTEx) project. Nat Genet. 201345:580–5.

    Auerbach RK, Chen B, Butte AJ. Relating genes to function: identifying enriched transcription factors using the ENCODE ChIP-Seq significance tool. Bioinformatics. 201329:1922–4.

    Rooney MS, Shukla SA, Wu CJ, Getz G, Hacohen N. Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell. 2015160:48–61.

    Galon J, Mlecnik B, Bindea G, Angell HK, Berger A, Lagorce C, Lugli A, Zlobec I, Hartmann A, Bifulco C, et al. Towards the introduction of the 'Immunoscore' in the classification of malignant tumours. J Pathol. 2014232:199–209.

    Taylor BS, Schultz N, Hieronymus H, Gopalan A, Xiao Y, Carver BS, Arora VK, Kaushik P, Cerami E, Reva B, et al. Integrative genomic profiling of human prostate cancer. Cancer Cell. 201018:11–22.

    Petitjean A, Achatz MI, Borresen-Dale AL, Hainaut P, Olivier M. TP53 mutations in human cancers: functional selection and impact on cancer prognosis and outcomes. Oncogene. 200726:2157–65.

    Lamb J, Crawford ED, Peck D, Modell JW, Blat IC, Wrobel MJ, Lerner J, Brunet JP, Subramanian A, Ross KN, et al. The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science. 2006313:1929–35.

    Coussens LM, Werb Z. Inflammation and cancer. Nature. 2002420:860–7.

    Fraser DM, Sullivan FM, Thompson AM, McCowan C. Aspirin use and survival after the diagnosis of breast cancer: a population-based cohort study. Br J Cancer. 2014111(3):623–7.

    Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 201415:550.

    Yoshihara K, Shahmoradgoli M, Martinez E, Vegesna R, Kim H, Torres-Garcia W, Trevino V, Shen H, Laird PW, Levine DA, Van Houdt WJ, Pronk A, Van Gorp J, Siersema PD, Clevers H. Inferring tumour purity and stromal and immune cell admixture from expression data. Nat Commun. 20134:2612.

    Sato T, Stange DE, Ferrante M, Vries RG, Van Es JH, Van den Brink S, Van Houdt WJ, Pronk A, Van Gorp J, Siersema PD, Clevers H. Long-term expansion of epithelial organoids from human colon, adenoma, adenocarcinoma, and Barrett's epithelium. Gastroenterology. 2011141:1762–72.

    Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. 201112:323.

    Hanzelmann S, Castelo R, Guinney J. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinformatics. 201314:7.


    Expression of inducible NOS is indispensable for the antiproliferative and proapoptotic effect of imatinib in BCR–ABL positive cells

    Madhu Dikshit, Translational Health Science and Technology, NCR Biotech Science Cluster, 3rd Milestone, Faridabad-Gurgaon Expressway, Faridabad, Haryana 121001, India.

    Anil Kumar Tripathi, Dr. Ram Manohar Lohia Institute of Medical Sciences, Vibhuti Khand, Gomti Nagar, Lucknow, Uttar Pradesh 226010, India.

    Pharmacology Division, CSIR-Central Drug Research Institute, Lucknow, India

    Madhu Dikshit, Translational Health Science and Technology, NCR Biotech Science Cluster, 3rd Milestone, Faridabad-Gurgaon Expressway, Faridabad, Haryana 121001, India.

    Anil Kumar Tripathi, Dr. Ram Manohar Lohia Institute of Medical Sciences, Vibhuti Khand, Gomti Nagar, Lucknow, Uttar Pradesh 226010, India.

    Pharmacology Division, CSIR-Central Drug Research Institute, Lucknow, India

    Pharmacology Division, CSIR-Central Drug Research Institute, Lucknow, India

    Pharmacology Division, CSIR-Central Drug Research Institute, Lucknow, India

    Pharmacology Division, CSIR-Central Drug Research Institute, Lucknow, India

    Department of Transfusion Medicine, King George's Medical University, Lucknow, India

    Pharmacology Division, CSIR-Central Drug Research Institute, Lucknow, India

    Department of Clinical Hematology, Dr. Ram Manohar Lohia Institute of Medical Sciences, Lucknow, India

    Madhu Dikshit, Translational Health Science and Technology, NCR Biotech Science Cluster, 3rd Milestone, Faridabad-Gurgaon Expressway, Faridabad, Haryana 121001, India.

    Anil Kumar Tripathi, Dr. Ram Manohar Lohia Institute of Medical Sciences, Vibhuti Khand, Gomti Nagar, Lucknow, Uttar Pradesh 226010, India.

    Pharmacology Division, CSIR-Central Drug Research Institute, Lucknow, India

    Madhu Dikshit, Translational Health Science and Technology, NCR Biotech Science Cluster, 3rd Milestone, Faridabad-Gurgaon Expressway, Faridabad, Haryana 121001, India.

    Anil Kumar Tripathi, Dr. Ram Manohar Lohia Institute of Medical Sciences, Vibhuti Khand, Gomti Nagar, Lucknow, Uttar Pradesh 226010, India.

    Abstract

    Chronic myeloid leukemia (CML) is characterized by constitutive BCR–ABL kinase activity, an aggressive proliferation of immature cells, and reduced differentiation. Targeting tyrosine kinase activity of BCR–ABL with imatinib is an effective therapy for the newly diagnosed CML patients however, 20%–30% of the patients initially treated with imatinib eventually experience treatment failure. Therefore, early identification of these patients is of high clinical relevance. In the present study, we by undertaking a direct comparison of inducible NOS (iNOS) status in neutrophils from healthy volunteers, newly diagnosed, imatinib responder, and resistant CML patients as well as by conducting in vitro studies in K562 cells demonstrated that inhibition of BCR–ABL by imatinib or siRNA significantly enhanced NO generation and iNOS expression. Indeed, patients exhibiting treatment failure or imatinib resistance were less likely to induce NO generation/iNOS expression. Our findings further demonstrated that imatinib mediated antiproliferative and proapoptotic effect in BCR–ABL + cells associated with enhanced iNOS expression, and it was significantly prevented in the presence of L-NAME, 1400W, or iNOS siRNA. Overexpression of iNOS in K562 cells expectedly enhanced imatinib sensitivity on cytostasis and apoptosis, even at lower concentration (0.1 μM) of imatinib. Mechanistically, imatinib or BCR–ABL siRNA following deglutathionylation of NF-κB, enhanced its binding to iNOS promoter and induced iNOS transcription. Deglutathionylation of procaspase-3 however associated with increased caspase-3 activity and cell apoptosis. Taken together, results obtained suggest that monitoring NO/iNOS level could be useful to identify patients likely to be responsive or resistant to imatinib and can be used to personalized alternative therapy.

    Supplemental Figure S1. BCR-ABL expression negatively regulates iNOS expression in leukemic cells.

    Supplemental Figure S2. Effect of imatinib and iNOS on K562 cells viability.

    Supplemental Figure S3. Expression of iNOS and mitochondrial membrane potential in iNOS knockdown or overexpressed K562 cells.

    Supplemental Figure S4. Expression of iNOS in PMNs and progenitors of CML patients.

    Supplemental Figure S5. NO generation and BCR-ABL/iNOS expression in PMNs of drug naive CML patients following in vitro treatment with imatinib.

    Supplemental Figure S6. Imatinib or BCR-ABL knockdown attenuate ROS generation in BCR-ABL + cells.

    Supplemental Figure S7. Glutathione content and Glutaredoxins expression in BCR-ABL positive cells.

    Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.


    A Systems Biology Approach to Uncovering Pharmacological Synergy in Herbal Medicines with Applications to Cardiovascular Disease

    Background. Clinical trials reveal that multiherb prescriptions of herbal medicine often exhibit pharmacological and therapeutic superiority in comparison to isolated single constituents. However, the synergistic mechanisms underlying this remain elusive. To address this question, a novel systems biology model integrating oral bioavailability and drug-likeness screening, target identification, and network pharmacology method has been constructed and applied to four clinically widely used herbs Radix Astragali Mongolici, Radix Puerariae Lobatae, Radix Ophiopogonis Japonici, and Radix Salviae Miltiorrhiza which exert synergistic effects of combined treatment of cardiovascular disease (CVD). Results. The results show that the structural properties of molecules in four herbs have substantial differences, and each herb can interact with significant target proteins related to CVD. Moreover, the bioactive ingredients from different herbs potentially act on the same molecular target (multiple-drug-one-target) and/or the functionally diverse targets but with potentially clinically relevant associations (multiple-drug-multiple-target-one-disease). From a molecular/systematic level, this explains why the herbs within a concoction could mutually enhance pharmacological synergy on a disease. Conclusions. The present work provides a new strategy not only for the understanding of pharmacological synergy in herbal medicine, but also for the rational discovery of potent drug/herb combinations that are individually subtherapeutic.

    1. Introduction

    Herbal medicine, especially traditional Chinese medicine (TCM) with the longest history in Asia, is a cost-effective system of medical practice that differs in substance, methodology, and philosophy to modern medicine, and plays an important role in health maintenance for the peoples of the world [1]. Because of their extensive use and the therapeutic effects [2, 3], there is an increasing interest and need to evaluate the mechanisms of action of herbal products rigorously.

    Herbal medicines are characterized by the use of mixtures of several herbs (multiherbs) in a single formula, in which the pharmacological activities of one single herb is either potentiated or prolonged, and/or its adverse effects reduced by addition of other herbs [4]. This thus will lead to a more favorable response for some herbal combinations than for the constituent herb used alone [2], which suggests that therapeutic effects of these herbal products may arise from synergistic actions of herbal ingredients [3, 4].

    Up to now, herbal synergism has been frequently reported [5], which may result from: (1) the potentiation of pharmacokinetics, such that one ingredient enhances the therapeutic effect of another component by regulating the drug absorption and metabolism. For examples, saponins increase absorption of corticosteroids [6] and procyanidin B2 or hyperoside in St. John’s wort increases the solubility of hypericin [7, 8] and (2) reinforcement of pharmacodynamics, thus all ingredients involved in an herbal combination direct at a similar receptor target or physiological system [4]. For instance, in the case of St. John’s wort, individually subtherapeutic effects (e.g., MAO and COMT inhibition) may combine to augment the primary pharmacological mechanism (monoamine reuptake inhibition). However, the molecular mechanism underlying such multicomponent synergy associated with the interacting targets, pathways, and even diseases remains largely uncovered. Clearly, deep understanding of the herb synergism will be not only helpful to optimize the drug combinations in multicomponent therapeutics but also critical for developing novel drug combinations that are individually subtherapeutic but efficacious in combination.

    Evaluation of synergy in multicomponent therapeutics is usually performed experimentally in a case-by-case approach [9]. For examples, Wiesner et al. demonstrated that a novel antimalarial drug fosmidomycin had both in vitro and in vivo synergic effect with clindamycin [10] Nguyen et al. reported that triple combination of amantadine, ribavirin, and oseltamivir was highly active and synergistic against drug resistant influenza virus strains in vitro [11]. However, as we know for any medicinal herb, they might contain hundreds of ingredients, thus it is unfeasible to screen all possible drug combinations for all possible indications, although high-throughput screening was possible to determine drug combinations [12], it is also much expensive. Another drawback of the existing methods is that these “blind” approaches including molecular biology are costly and time consuming. In addition, little is known about the system properties of a full drug interaction network, which hinders the understanding of mechanisms of drug combinations.

    Alternatively, computational methods, especially systems biology, that enable to investigate the complex mechanism of action of drugs and circumvent the challenges associated with experiment have recently been developed. Systems biology investigates the biological processes within the complex, physiological milieu systematically through a systems approach integrating experimental, mathematical, and computational sciences. It has the potential to further facilitate the identification and validation of the therapeutic modulation of regulatory and metabolic networks and hence help identify targets and biomarkers, as well as ‘‘off-target’’ and side effects of drug candidates (reviewed by [13]). For example, network-target based techniques were used for virtual screening synergistic drug combinations [14, 15], thereby try to explain how and why the drugs work. But they only work on small drug sets due to the computational and experimental cost. Moreover, drugs are generally combined based on their mechanisms of action, which is characterized by the properties of drugs, such as their targets and pharmacology [16]. Thus the incompleteness of molecular networks and the scarceness of the drug properties limit the application of such approaches to TCM considerably.

    In this work, we present a novel concept based on a systems biology framework for the investigation of synergy of four herbs, that is, Radix Salviae Miltiorrhiza (RSM), Radix Astragali Mongolici (RAM), Radix Puerariae lobatae (RPL), and Radix Ophiopogonis Japonici (ROJ) [17]. Among these four herbs, RSM shows diverse biological activities, such as inhibition of angiotensin converting enzyme (ACE), lowering blood pressure, dilate arteries, and decreasing blood clotting [18–20], thus is widely prescribed in different TCM formulae RAM also shows protective effects against ultraviolet A-induced photoaging in human fibroblasts [21] and on proliferation and Akt phosphorylation of breast cancer cell lines [22] isoflavones from RPL and their metabolites can inhibit growth and induce apoptosis in breast cancer cells [23] ROJ plays a role in enhancing immunity, anti-myocardial ischemia, lowering blood glucose, and antiviral activity [24]. Impressively, RSM has shown synergisms with each of the other three herbs in clinical trials for cardiovascular disease (CVD) [17], the leading cause of morbidity and mortality all over the world [25].

    2. Materials and Methods

    We have identified the potential targets of the four herbs on a proteome-wide scale and disclosed the synergistic mechanisms of action of the active ingredients by integrating both molecular and pharmacological features associated with drugs [26, 27]. Our methodology effectively and systematically extends the scope of the previously network-target concept, and is more likely to be successful in achieving the ultimate goal of providing pharmacological synergy in psychoactive herbal medicines. Our systems biology approach proceeds as follows: (1) all 3D structures of available molecules in the four herbs are collected (2) the drug-likeness (DL) and oral bioavailability (OB) of the molecules are calculated to prescreen for the bioactive molecules (3) the physicochemical properties and architecture of molecules in four herbs are revisited (4) the potential targets of these four herbs are identified on a proteome-wide scale (5) the tools of network biology and systematic information about drugs and their targets are combined to uncover the synergistic therapeutic actions of herbal ingredients. Our approach essentially explores some feature patterns enriched in known combinatorial therapies that can be predictive of new drug combinations and provide insights into the mechanisms underlying combinatorial therapy. Then these compounds and proteins are mapped to functional ontologies such as compound-target associations, compound-pathway connections, and disease-target we assessed retrospectively and prospectively network-based relationships between drugs and their targets and interrelationships between drug targets and disease-gene products. In this way, our approach has the potential to increase the rate of successful drug discovery and development.

    2.1. Database Construction and Molecular Modeling

    In order to extract the current state of the art on known chemical ingredients in these four herbs, their information was extracted from the Traditional Chinese Medicine Systems Pharmacology database and Analysis Platform (TcmSP http://tcmspnw.com/) that was recently developed in our group. The newest version of TcmSP comprises 510 effective herbal entries registered in Chinese pharmacopoeia with more than 31000 ingredients, which spread over 18 different drug classes. This is currently the most comprehensive small molecular database for systems pharmacology analysis of TCM. In this work, the 3D structures of all molecules in the database were minimized in Sybyl by using the standard Tripos force field (Tripos, Inc.). After removing the duplicated compounds, a total of 532 molecules with 209 in RSM, 95 in RAM, 113 in RPL, and 135 in ROJ were collected in this study. Glycosides in medicinal herbs are usually hydrolyzed to liberate aglycone which is then absorbed at the intestinal mucos [28], thus the corresponding aglycone chemicals were also added into the database.

    2.2. Drug-Likeness Calculation

    DL is a qualitative concept used in drug design for how ‘‘druglike’’ a substance is with respect to factors affecting pharmacodynamics and pharmacokinetics of molecules which ultimately influences their absorption, distribution, metabolism, and excretion (ADME) in human body [29]. DL between the compound structure

    and the drug molecular structure

    obtained from Drugbank was evaluated by Tanimoto coefficient defined as:


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