This is the 2010 "Science News" Section:
Targeting uremic toxicity as a strategy to prevent cardiovascular complications of the Chronic Kidney Disease
by Andrea E. Stinghen Ph.D.1, Roberto Pecoits-Filho Ph.D.2 and Lia S. Nakao Ph.D.1,*
1Basic Pathology Department, Universidade Federal do Paraná, Curitiba, Brazil
2Center for Health and Biological Sciences, Pontifícia Universidade Católica do Paraná, Curitiba, Brazil
Chronic kidney disease (CKD) is a relatively frequent result of systemic diseases, such as hypertension and diabetes mellitus. The mortality rate of CKD patients is extremely high and is usually associated with cardiovascular diseases (CVD) (1). Inflammation and oxidative stress are known processes associated with CVD development, and recent findings have pointed that uremic toxins, which accumulate in CKD patients’ circulation in the progression of kidney dysfunction, have an important impact on vascular inflammation and oxidative stress (2). However, the relationships between vascular inflammation, oxidative stress and uremia are not well understood and some questions remain unanswered: Does uremia trigger inflammation and oxidative stress? Or do inflammation and oxidative stress contribute to the uremic status? Or is oxidative stress a result of inflammation? The vascular endothelium, due to its regulatory functions, plays a pivotal role both as target and amplifier of the inflammatory and oxidative response (3). Indeed, exposure of the endothelium to uremic toxins leads to changes in cellular phenotype, including the expression of pro-inflammatory molecules (4-6). In agreement with those data, a recent proteomic approach showed that the most prominent differentially expressed proteins from endothelial cells cultured in uremic serum were related to inflammation and oxidative stress (7). Interestingly, a single uremic toxin, indoxyl sulfate, which is one of the most abundant uremic toxins (8), is able to induce the same effects in vascular cells as those triggered by the uremic serum (9). Studies developed in our laboratory have shown that uremic medium increased the expression of cytokines and adhesion molecules, such as MCP-1, IL-8, sICAM- 1 and sVCAM-1 (6), and activates the production of reactive oxygen species (ROS) (10) by endothelial cells. In fact, some researchers speculate if this hostile environment contributes to epigenetic changes (11) to endothelial cells, up regulating the expression of these molecules. Although uremic toxins are key elements in the inflammation and oxidative stress found in CKD complications, the identification of “who is the chicken or the egg” in this field needs to be clarified to guide the understanding of the vascular mechanisms of uremic toxicity and lead to more efficient therapeutic strategies.
(1) Stenvinkel P.,Carrero J.J., et al. Emerging biomarkers for evaluating cardiovascular risk in the chronic kidney disease patient: how do new pieces fit into the uremic puzzle? Clin J Am Soc Nephrol, v.3, p.505-21. 2008.
(2) Himmelfarb J. Uremic toxicity, oxidative stress, and hemodialysis as renal replacement therapy. Semin Dial, v.22, p.636-43. 2009.
(3) Diaz-Buxo J.A., Woods H.F. Protecting the endothelium: a new focus for management of chronic kidney disease. Hemodyal Int, v.10, p.42-48. 2006.
(4) Serradell M., Diaz-Ricart M., et al. Uraemic medium causes expression, redistribution and shedding of adhesion molecules in cultured endothelial cells. Haematologica, v.87, p.1053-61. 2002.
(5) Segal M. S., Baylis C., et al. Endothelial health and diversity in the kidney. J Am Soc Nephrol, v.17, p.323-4. 2006.
(6) Stinghen A. E., Goncalves S.M., et al. Increased plasma and endothelial cell expression of chemokines and adhesion molecules in chronic kidney disease. Nephron Clin Pract, v.111, p.c117-26. 2009.
(7) Carbo C., Arderiu G., et al. Differential expression of proteins from cultured endothelial cells exposed to uremic versus normal serum. Am J Kidney Dis, v.51, p.603-12. 2008.
(8) Kikuchi K., Itoh Y., et al. Metabolomic analysis of uremic toxins by liquid chromatography/electrospray ionization-tandem mass spectrometry. Chromatogr B Analyt Technol Biomed Life Sci, v. 878, p.1662-8. 2010.
(9) Niwa T. Uremic toxicity of indoxyl sulfate. Nagoya J Med Sci, v. 72, p.1-11. 2010.
(10) Werneck M.L., França K., et al. Increased reactive oxygne species formation in endothelial cells induced by uremic serum. J Am Soc Nephrol, v.17, p.27A-27A. 2006.
(11) Stenvinkel P., Ekstrom TJ. Does the uremic milieu affect the epigenotype? J Ren Nutr, v. 19, p. 82-5. 2009.
Links of interest:
Infectious Causes of Human Cancers: The Risk Factor Unveiled
by Lara Termini, Ph.D. & Enrique Boccardo, Ph.D.*
Ludwig Institute for Cancer Research, São Paulo, Brazil
Despite the great progress that has been made in the treatment of cancer, prevention and early diagnosis are still the most powerful weapons against human tumors. However, a constant failure to identify the main risk factors associated to cancer has hampered the efforts to prevent many common human malignancies such as non-hereditary breast cancer as a way to avoid the development of this deadly disease. An important exception to this rule has been the identification of chronic and long-term infections by highly prevalent viruses, bacterias and trematodes as a major cause of human malignancies. Examples include the Gram-negative bacterium Helicobacter pylori, the Epstein-Barr virus (EBV), the hepatitis B virus (HBV), the hepatitis C virus (HCV), the human T-cell lymphotropic virus type 1 (HTLV-1), the immunodeficiency virus type 1 (HIV-1) and several human papillomavirus types (including types 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59 and 66), as well as the trematodes Opisthorchis viverrini, Clonorchis sinensis and Schistosoma haematobium. Due to their proven causative role in specific human cancers these agents have been classified as group 1 carcinogens by the International Agency for Research in Cancer (IARC). Moreover, HPV68 has been classified as putative (group 2A carcinogens); on the other hand, several other agents such HIV type 2, other HPV types (including types 26, 30, 34, 53, 66, 67, 69, 70, 73, 82, 85 and 97) and Schistosoma japonicum are considered as possible (group 2B carcinogens) carcinogens to humans. Altogether, infections by these agents constitute a major burden for human populations since they are estimated to account for more than 20% of all human malignancies. Importantly, the recent identification of a new polyomavirus, the Merkel Cell Polyomavirus (MCPyV), an its detection in the majority of Merkel cell carcinomas clearly indicates that the role of infectious agents in the etiology of human tumors is still underestimated. Moreover, the occasional detection of others viruses in different human tumors remains a topic of constant discussion in the scientific community. Prevention and control of infection by these agents could dramatically reduce the incidence of some prevalent cancers and, consequently, have a great impact on public health. The introduction of antibiotics therapy to control Helicobacter pylori and prevent gastric tumors as well as the widespread use of HBV and of the recently approved HPV vaccines to prevent hepatocellular carcinoma and cervical cancer, respectively, are important examples of preventive therapies against tumors and are changing the way we fight cancers. The future is promising in this area of research and more breakthroughs associating infectious agents with different types of cancer are expected. This will aid in the development of better and more efficient preventive therapies.
Boccardo E, Villa LL. Viral origins of human cancer. Curr Med Chem. 14 (24): 2526-2539, 2007.
Bouvard V, et al. WHO International Agency for Research on Cancer Monograph Working Group. A review of human carcinogens--Part B: biological agents. Lancet Oncol. 10 (4): 321-322, 2009.
Butel JS. Viral carcinogenesis: revelation of molecular mechanisms and etiology of human disease. Carcinogenesis. 21(3): 405-426, 2000.
Zur Hausen H. The search for infectious causes of human cancers: where and why. Virology. 392 (1):1-10, 2009.
Links of interest:
Cancer vaccines: a new way to fight cancer?
by Paulo Cesar Maciag, MD, Ph.D.
Associate Medical Director, Immunology
Bristol-Myers Squibb New Jersey USA
Cancer vaccines have as main purpose to activate the host immune response to help in the fight against tumors. The rationale behind this strategy is that cancer cells can be effectively recognized and eliminated by immune cells (1). Several strategies have been used to elicit T cell responses against tumor-associated antigens (TAAs), such as vaccination with peptides, whole proteins, DNA, dendritic cells and live vectors, among others. Each technology has pros and cons, but ultimately most of them are capable of inducing potent T cell responses to tumor antigens, having therapeutic properties in pre-clinical models of cancer. Unfortunately, in most cases the pre-clinical efficacy of cancer vaccines has not been translated to the clinics, where the rates of success are much lower. Several reasons may explain this disparity, including the more advanced stage of cancer in treated patients and the long-term interaction between the host immunity and cancer cells, turning the tumor in a less immunogenic “entity”. Moreover, tumors have a very immunosuppressive microenvironment that impairs effector T cell function. During tumor development, distinct immune cells are recruited to the tumor site and subverted to a phenotype that favors tumor growth. In particular, tumor-associated macrophages (TAMs) can promote tumor growth, angiogenesis and degradation of the extracellular matrix, facilitating invasiveness (2). In addition, TAMs have immunosuppressive properties and inhibit T cell responses within the tumor (2). Myeloid-derived suppressor cells also accumulate in animals and in patients as the tumors grow, leading to impairment of T cell responses (3). Regulatory T cells (Tregs) are also abundant in tumors and capable of suppressing T cell responses (4). In fact, improvement in the ratio of intra-tumoral cytotoxic T lymphocytes (CTLs) to Tregs has been associated with therapeutic responses to cancer vaccines (4). In summary, eliciting T cell responses to TAAs is not enough and many obstacles must be overcome for a successful cancer immunotherapeutic. For example, combination of cancer vaccines with potent adjuvants or other treatment modalities have shown promising results (5). In particular, the sequential combination of vaccine and chemotherapy is associated with better survival than each treatment alone for several tumors (5). Thus, cancer vaccines comprise a potential new therapeutic tool to treat cancer (6) and the recent approval of Provenge by the FDA validates this therapeutic modality, opening new avenues in this promising field.
1. Wang E, et al. Spontaneous and treatment-induced cancer rejection in humans. Expert Opin Biol Ther, 8 (3): 337-49, 2008.
2. Solinas G, et al. Tumor-associated macrophages (TAM) as major players of the cancer-related inflammation. J Leukoc Biol, 86(5):1065-73, 2009.
3. Gabrilovich DI, Nagaraj S. Myeloid-derived suppressor cells as regulators of the immune system. Nat Rev Immunol, 9(3):162-74, 2009.
4. Mougiakakos D, et al. Regulatory T cells in cancer. Adv Cancer Res, 107:57-117, 2010.
5. Arlen PM, et al. Combining vaccines with conventional therapies for cancer. Update Cancer Ther, 2(1):33-39, 2007.
6. Maciag PC, Radulovic S, Rothman J. The first clinical use of a live-attenuated Listeria monocytogenes vaccine: a phase I safety study of Lm-LLO-E7 in advanced cervical cancer patients. Vaccine, 27(30): 3975-3983, 2009.
The incidence of melanoma is increasing worldwide. Despite advances in early diagnosis, treatment outcome of advanced melanoma still remains poor (1). Absence of an effective therapy may be due to the acquired resistance of melanoma cells to chemotherapeutic drugs. Resistance may be acquired by selection of tumor cells for survival in a hostile microenvironment with low pH, nutrients and oxygenation. Altogether, these adverse conditions may activate protective mechanisms against cell death in tumor cells. Imbalanced production of reactive oxygen species (ROS), leading to oxidative stress, is a common feature of the tumor microenvironment. The intriguing fact is that normal melanocyte survival is also dependent on the adaptation to oxidative stress, which takes place during the synthesis of the pigment melanin upon UV exposure. Therefore, intermittent exposure to UV can facilitate melanocyte survival and at the same time it generates ROS (2), which in turn acts as a selective pressure for cell adaptation. Proteomic profiling of melanoma cells was already investigated and our group has shown that there was a significant reduction in the number of proteins responsible for ROS catabolism upon transformation, indicating that melanoma cells may adapt to a pro-oxidant state (3). This concept seems applicable to different tumors in advanced stages. Recently, the antioxidant N-acetylcysteine was suggested as an effective compound in the reduction of ROS production in UV-irradiated nevi in vitro, indicating a potentially simple and effective strategy for melanoma chemoprevention (4). Oxidative stress is also coupled to endoplasmic reticulum (ER) stress. Melanoma cells are able to survive under extreme ER stress induction and this resistance may be related to the accumulation of the protein chaperone GRP78 (5). The use of agents that target ER stress signaling pathways, such as the BH3 mimetic obatoclax, can overcome the resistance of melanoma cells to cell death induced by ER stress (6). Thus, the interface of both oxidative and ER stress responses are potential targets for drug development that may facilitate chemosensitization in melanoma cells. However, more studies are needed to investigate the effects of targeting these pathways in this type of cancer.
1. Hersey P, et al. Current strategies in overcoming resistance of cancer cells to apoptosis melanoma as a model. Int Rev Cytol 251, 131–158, 2006.
2. Herrling T, Jung K, Fuchs J. Measurements of UV-generated free radicals/reactive oxygen species (ROS) in skin.Spectrochim Acta A Mol Biomol Spectrosc. 63: 840-845, 2006.
3. de Souza GA, et al. Proteomic and SAGE profiling of murine melanoma progression indicates the reduction of proteins responsible for ROS degradation. Proteomics. 6: 1460-1470, 2006.
4. Goodson AG, et al. Use of oral N-acetylcysteine for protection of melanocytic nevi against UV-induced oxidative stress: towards a novel paradigm for melanoma chemoprevention. Clin Cancer Res. 15 (23): 7434-7440, 2009.
5. Zhuang L, et al. Expression of glucose-regulated stress protein GRP78 is related to progression of melanoma.Histopathology. 54 (4): 462-470. 2009.
6. Jiang CC, et al. Human melanoma cells under endoplasmic reticulum stress are more susceptible to apoptosis induced by the BH3 mimetic obatoclax. Neoplasia. 11(9): 945-955, 2009.
Virally Encoded microRNAs
by Peter McErlean, Ph.D.
Division of Allergy-Immunology
Chicago, IL USA
MicroRNAs (miRs) are a class of small (~20nt) non-coding RNAs that are involved in the post-transcriptional regulation of gene expression. miR-mediated gene regulation is carried out by a collection of proteins known as the RNA-induced silencing complex (RISC) which binds to miR specific target sequences on messenger RNAs (mRNAs) and directs either translational repression or mRNA degradation (1).miRs have been identified within and across many different species of plants and animals indicating that miR-mediated gene regulation appears to be a conserved and evolutionarily favorable process. Given the parasitic nature of viral infections and the potential benefit of viruses to regulate host gene expression to their advantage (i.e. limit the antiviral response during replication), it is of no surprise that miRs have been described in viruses (2-3). Virally encoded miRs (V-miRs) were first identified in Epstein-Bar Virus (EBV), a member of the Herpesvirus family and causative agent of mononucleosis (4). Since this initial discovery bioinformatic-based approaches have predicted the existence of other V-miRs, predominately in viruses with double stranded DNA genomes (5). Experimental validation of predicted V-miRs has so far occurred in additional Herpesviruses; Kaposi sarcoma-associated virus [KSHV], Herpes Simplex-1 and Human Cytomegalovirus; Human Adenoviruses and the simian and murine Polyomaviruses (2). Characterization of V-miRs has revealed that they are employed by viruses primarily to regulate their own viral proteins as opposed to directly targeting host cellular mRNAs that may be involved in the virus life cycle. It has also been shown that the majority of V-miRs share limited sequence homology with not only their host’s endogenous miRs, but also with V-miRs found in other members of the same virus family; a particularly unique aspect when considering miRs found within other plant and animal families remain essentially conserved (3). Interestingly, V-miRs that do share limited sequence homology to host cellular miRs (e.g. KSHV miR-K12-11 and miR-155) may be involved in similar pathways to their endogenous counterparts, although further clarifications of these interactions are needed (2). Finally, given that V-miRs have been characterized from viruses known to cause or be implicated in human diseases (e.g. EBV, KSHV and B-cell lymphomas), targeting of V-miRs during infection may prove to be of therapeutic value. MicroRNA focused studies have provided us with invaluable information about many biological processes across many different organisms. The identification of V-miRs is testament to the diverse nature of miR-mediated gene regulation and although only in its infancy, V-miR focused research has bolstered our understanding of virus biology. Indeed, future studies in this area will reveal more of the immense complexity that exists in virus-host interactions.
1. Bartel, D.P. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 116 (2): p. 281-297, 2004.
2. Gottwein, E. and B.R. Cullen. Viral and cellular microRNAs as determinants of viral pathogenesis and immunity. Cell Host Microbe. 3 (6): p. 375-387, 2008.
3. Sullivan, C.S. and D. Ganem. MicroRNAs and viral infection. Mol Cell. 20 (1): p. 3-7, 2005.
4. Pfeffer, S., et al. Identification of virus-encoded microRNAs. Science. 304 (5671): p. 734-736, 2004.
5. Pfeffer, S., et al. Identification of microRNAs of the herpesvirus family. Nat Methods. 2 (4): p. 269-276, 2005.
How close are we to resolving the genotype/phenotype map?
The extent to which we can satisfy the growing optimism for personalized medicine and virtual development of therapeutics is largely dependent on our ability to accurately map correlations between the genotype to the phenotype, an incredibly difficult and unresolved problem (1,2). Historically, this issue has been considered via demonstration of congruence in explaining the Baldwin effect, a population phenomenon scored through individuals that illustrates the potential of the genotype to adapt to its environment over several generations (3). The following is a brief opinion with regards the tractability of this immense problem with consideration of developments in modern techniques and the tendency of biologists to be divided between two groups, viz., “experimentalists who observe things that cannot be explained, and theoreticians who explain things that cannot be observed” - Aharon Katzir-Katchalsky (4).
Given the wide spatial and temporal range of interactions that constitute evolutionary dynamics, it is not surprising that the study of form has been recognized as a central means by which to dissect the underpinnings of morphogenesis well before the molecular era (5). This is primarily due to the inherent nature of shapes to simplify the complicated complexities operating across different levels of hierarchies through expression as qualities that are shifted to new sets of constrained typicalities and variabilities when perturbed. The impact of this realization is demonstrated by the success of phenotype-based screens that continue to affect the direction of current disease research (6).
The central goal for medical virtualization is to visualize and manipulate the dynamics of a comprehensive network on a geometrically transforming manifold (7). The challenges with which we are faced are to do this in a manner that balances accurate information with computability, that is, as more information becomes available, processing speeds are slowed. As a result, researchers are now starting to move away from trying to generate a singular globalized model to a more manageable approach that takes advantage of local communities (8), but with an eye towards eventual integration.
From an experimentalist view, resolving phenotype/gentoype correlations is being carried out through complementary high-throughput methods with more targeted means (9) in hopes of mapping networks in the mold of Waddington’s vision of the epigenetic landscape. This is necessitated by the fact that there exists a problem of being unable to assess concentration effects using high throughput methods, which can be exposed through targeted, explicit models (10) as things move towards concurrency.
Consideration of the organism as a complex adaptive system (11) naturally allows integration of diverse scientific disciplines onto a singular topic. Therefore, participating in the growth of a genotype/phenotype map offers an opportunity to shuffle and integrate existing programs into new combinations in hopes that it would lead to innovations, a lesson learned from the study of evolutionary novelties. To circumvent potential communication barriers, transparent efforts to develop user-friendly platforms (12,13) that foster exchange are constantly being updated. Such combined efforts are having an extremely positive effect on modifying education and culture of 21st century biology and engineering (14). Indeed, it is an exciting time to join this multidisciplinary endeavor!
References and links:
1. Webster G, Goodwin BC. Form and transformation: generative and relational principles in biology. Cambridge, U.K. ; New York, N.Y.: Cambridge University Press. xiv p. 287, 1996.
2. Crutchfield JP, Schuster P. Evolutionary dynamics : exploring the interplay of selection, accident, neutrality, and function. Oxford ; New York: Oxford University Press. xxxiv p. 452, 2003.
3. Fontana W. Evolvability of phenotypes.
4. Bower JM, Bolouri H. Computational modeling of genetic and biochemical networks. Cambridge, Mass, 2001.
5. Riedl R. Order in living organisms : a systems analysis of evolution. Chichester ; New York: Wiley. xx, 313, 1978.
6. Garcia-Garcia MJ, Eggenschwiler JT, Caspary T, Alcorn HL, Wyler MR, et al. Analysis of mouse embryonic patterning and morphogenesis by forward genetics. PNAS 102: 5913-5919,
7. Thom R. Structural stability and morphogenesis; an outline of a general theory of models. Reading, Mass.,: W. A. Benjamin. 348, 1975.
8. Detwiler LT, Suciu D, Franklin JD, Moore EB, Poliakov AV, et al. Distributed XQuery-Based Integration and Visualization of Multimodality Brain Mapping Data. Front Neuroinformatics 3: 2, 2009.
9. Hadjantonakis AK, Dickinson ME, Fraser SE, Papaioannou VE. Technicolour transgenics: imaging tools for functional genomics in the mouse. Nat Rev Genet 4: 613-625, 2003.
10. Lee E, Salic A, Kruger R, Heinrich R, Kirschner MW. The roles of APC and Axin derived from experimental and theoretical analysis of the Wnt pathway. PLoS Biol 1: E10, 2003.
11. Gell-Mann M, Baltimore D, Kuhn RL.
12. Cvitanovic P. http://chaosbook.org/
13. Wilensky U. Netlogo, 1999. http://ccl.northwestern.edu/netlogo/14. Ottino JM. New tools, new outlooks, new opportunities. AIChE Journal Volume 51: 1839 - 1845, 2004.
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