Feeds:
Posts
Comments

Archive for the ‘CANCER BIOLOGY & Innovations in Cancer Therapy’ Category

Guidelines for the welfare and use of animals in cancer research.

via Guidelines for the welfare and use of animals in cancer research.

 

Reported by: Dr. V. S. Karra, Ph.D.

We dedicate these Guidelines to Professor Lloyd Kelland and Dr Peter Twentyman, who made important contributions to these Guidelines and/or previous published versions, and who have now sadly passed away.

P Workman1, E O Aboagye2, F Balkwill3, A Balmain4, G Bruder5, D J Chaplin6, J A Double7, J Everitt8, D A H Farningham9,18, M J Glennie10, L R Kelland11, V Robinson12, I J Stratford13, G M Tozer14, S Watson15, S R Wedge16, S A Eccles1 and An ad hoc committee of the National Cancer Research Institute19

  1. 1Cancer Research UK Centre for Cancer Therapeutics, The Institute of Cancer Research, Cotswold Road, Sutton, Surrey SM2 5NG, UK
  2. 2Comprehensive Cancer Imaging Centre, Imperial College London Faculty of Medicine, Hammersmith Hospital Campus, Du Cane Road, London W12 ONN, UK
  3. 3Centre for Cancer & Inflammation, Barts and The London School of Medicine and Dentistry, John Vane Science Centre, Charterhouse Square, London EC1M 6BQ, UK
  4. 4Helen Diller Family Comprehensive Cancer Center, University of California San Francisco 1450 3rd Street, San Francisco, CA 94158, USA
  5. 5Paterson Institute for Cancer Research, University of Manchester, Wilmslow Road, Manchester M20 4BX, UK
  6. 6OXiGENE Inc., 701 Gateway Boulevard, San Francisco, CA 94080, USA
  7. 7University of Bradford, Richmond Road, Bradford BD7 1DP, UK
  8. 8GlaxoSmithkline Pharmaceutical R&D, PO Box 13398, Five Moore Drive, N2.2210.2B, Research Triangle Park, NC 27709-3398, USA
  9. 9Cancer Research UK, Clare Hall Laboratories, Blanche Lane, South Mimms, Herts EN6 3LD, UK
  10. 10Tenovus Laboratory, Cancer Sciences Division, Southampton University School of Medicine, General Hospital, Southampton SO16 6YD, UK
  11. 11Cancer Research Technology Development Laboratories, Wolfson Institute for Biomedical Research, University College London, Gower Street, London WC1E 6BT, UK
  12. 12National Centre for the Replacement, Refinement and Reduction of Animals in Research 20, Park Crescent, London W1B 1AL, UK
  13. 13School of Pharmacy and Pharmaceutical Sciences, University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, UK
  14. 14Department of Oncology, K Floor, School of Medicine, University of Sheffield, Beech Hill Road, Sheffield S10 2RX, UK
  15. 15Division of Pre-Clinical Oncology & PRECOS, D Floor West Block, Queen’s Medical Centre, University Hospital, Nottingham NG7 2UH, UK
  16. 16Cancer Bioscience, AstraZeneca, Mereside, Alderley Park, Macclesfield, Cheshire SK10 4TG, UK
  17. 17The Home Office, ASPD (mail point 1B), 1st floor Seacole Building, 2 Marsham Street, London W1P 4DF, UK
  18. 18Current address: Medical Research Council, 20 Park Crescent London W1B 1AL, UK

Correspondence: Professor P Workman and Dr SA Eccles, E-mail: Paul.Workman@icr.ac.uk and Sue.Eccles@icr.ac.uk

19The National Cancer Research Institute (NCRI) is a partnership of 21 organisations from the government, charity and commercial sectors who support cancer research in the UK. Further information about NCRI can be found at http://www.ncri.org.uk

*Observers: V Navaratnam and S Ryder17

Received 5 March 2010; Accepted 15 March 2010.

Abstract

Animal experiments remain essential to understand the fundamental mechanisms underpinning malignancy and to discover improved methods to prevent, diagnose and treat cancer. Excellent standards of animal care are fully consistent with the conduct of high quality cancer research. Here we provide updated guidelines on the welfare and use of animals in cancer research. All experiments should incorporate the 3Rs: replacement, reduction and refinement. Focusing on animal welfare, we present recommendations on all aspects of cancer research, including: study design, statistics and pilot studies; choice of tumour models (e.g., genetically engineered, orthotopic and metastatic); therapy (including drugs and radiation); imaging (covering techniques, anaesthesia and restraint); humane endpoints (including tumour burden and site); and publication of best practice.

Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the author

Keywords:

animal welfare; cancer research; fundamental and translational research; replacement, reduction and refinement (3Rs); pilot studies; tumour models; genetically engineered mouse models; human tumour xenografts; orthotopic models; metastatic models; therapy; imaging; pharmocokinetic, pharmacodynamic and efficacy studies; drugs; radiation therapy; imaging techniques; anaesthesia; restraint; humane endpoints; tumour burden; clinical signs; publication; best practice

Background and scope

Over the last decade there has been an extraordinary increase in our knowledge of the fundamental molecular processes that are involved in the development of cancer and its response to treatment (Hanahan and Weinberg, 2000Vogelstein and Kinzler, 2004Stratton et al, 2009). The public rightfully expect this explosion in basic research understanding to be translated into rapid improvements in prevention, diagnosis and treatment, particularly for the more common cancers and indeed for any malignant disease where there is still clearly an unmet need for more effective therapies. In recent years the identification of the genes and pathways that give rise to cancer dependencies and vulnerabilities has taken us further towards the development of individualised, molecularly targeted therapies (Sawyers, 2004Collins and Workman, 2006;Workman and de Bono, 2008).

Along with growth in fundamental knowledge and greater translational insight has come the development of new in vitro and ex vivo methodologies and research techniques that should further extend our still incomplete genetic, molecular and holistic understanding of cancer, and in addition should help to ensure that improved methods for diagnosis, therapy and prevention will be developed more effectively for patient benefit. Nevertheless, we are still some way from the point where all of the necessary information that is required to introduce a new drug into the clinic in terms of safety and efficacy could be gained without the use of animals in research. Moreover, animals remain essential to extend our understanding of the mechanisms responsible for cancer and to identify, for example, new targets and biomarkers.

It is clearly important that the welfare of animals in cancer research is protected, both from an ethical point of view and also because it is widely acknowledged to be entirely consistent with good science (Osborne et al, 2009). Under the earlier sponsorship of the former United Kingdom Coordinating Committee for Cancer Research (UKCCCR), two sets of guidelines have been published previously (Workman, 1988Workman et al, 1998). Although these guidelines were well received, and are still widely used and cited, it is over 10 years since they were last revised, in which time the science has moved on appreciably. The main aim of this article is to provide new guidelines for the cancer research community concerning the use of experimental animals in oncology, with a major emphasis on their welfare. We focus on rodents as these are predominantly used for cancer research: in 2008, for example, the UK government Home Office statistics showed that 96.8% of animals used in cancer research were mice (http://scienceandresearch.homeoffice.gov.uk/animal-research/publications-and-reference/statistics/index.html). While development of medicines may require testing in other species, use of animals in regulatory toxicology is outside the scope of this review.

The present guidelines should be applied to studies focused on all aspects of cancer research, including experiments aimed at understanding fundamental cancer biology as well more translational work, and should be used in conjunction with more general guidelines for the care and welfare of animals (see examples below and Additional information). It is expected that animal housing will be maintained according to the highest standards, including environmental enrichment (Tsai et al, 2006), and that local ethical review will precede any experimental animal studies. In addition, these guidelines should be used in conjunction with appropriate national legislation: UK Animals (Scientific Procedures) Act 1986; USA Institute for Laboratory Animal Research (ILAR) Guide for the Care and Use of Laboratory Animals (http://dels.nas.edu/Laboratory); EU webpage on laboratory animals (http://ec.europa.eu/environment/chemicals/lab_animals/home_en.htm); Public Health Service Policy on Humane Care and Use of Laboratory Animals (Office of Laboratory Animal Welfare, National Institutes of Health, 2002); http://grants.nih.gov/grants/olaw/references/phspol.htm. A complementary key recent publication, coordinated by the UK’s National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3R), is also recommended (Biotechnology and Biological Sciences Research Council; Department for Environment, Food and Rural Affairs; Medical Research Council; Natural Centre for the Replacement, Refinement and Reduction of Animals in Research; Natural Environment Research Council; Wellcome Trust, 2008). We also feel it is important that the public is made fully aware of the current justification for the use of animals in cancer research and the genuine concern for their welfare by researchers involved with their use. To help with this, a lay summary of the guidelines is also provided on page 1555. A glossary of terms can be found at the end of this article. Finally, it is important to emphasise that high standards of animal care and welfare should be fully consistent with, and helpful to, the conduct of high-quality cancer research (Osborne et al, 2009).

General recommendations

The use of animals raises scientific and ethical challenges. In 1959, Russell and Burch published The Principles of Humane Experimental Technique in which they stated that all animal experiments should incorporate, as far as possible, the 3Rs: replacement (of animals with alternative methods), reduction (in the numbers of animals used to achieve scientific objectives) and refinement (of methods to minimise animal suffering) (Russell and Burch, 1959). These principles underpin the legislation, guidelines and working practices concerning the use of animals in scientific procedures. Consideration of the 3Rs must be an integral part of planning cancer research using animals and the 3Rs need to be implemented throughout the lifetime of the study. Funding bodies and scientific journals (Osborne et al, 2009) should encourage scientists to use humane methods, to supply information on how the principles of the 3Rs are implemented and to publish improvements in experimental design and animal models for the benefit of the research community (www.nc3rs.org.uk/reportingguidelines). Details on the application of the 3Rs in cancer research are provided in Box 1 for ease of reference, together with information on implementation and monitoring in Box 2. Examples of tumour models, experimental design and procedures are provided throughout these guidelines. However, it is emphasised that these are intended to act as a guide only, and each study should be tailored to the specific experimental objectives.

Topof page

Tumour models

Preclinical cancer studies fall into two broad categories: those using tumour cell transplantation (Tables 1Aand B), and those in which tumours arise or are induced in the host (Tables 2A and B). The choice of animal model depends on the scientific question being investigated, but the mildest possible procedure should always be used. An example of the type of illustrative aid that can be used to facilitate the rational choice of appropriate models is shown in Figure 1. Cellular interactions and immune responses require immunocompetent animals and syngeneic systems, whereas cancer development or chemoprevention studies may use transgenic models or chemically induced tumours. In the case of translational studies designed, for example, to discover and develop therapies to exploit oncogenic abnormalities, the tumours should have the appropriate molecular genetic defect. Furthermore, real-time optical imaging will require engineered bioluminescent/fluorescent tumour models.

Figure 1.

Figure 1 - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the authorAn illustrative process for tumour model selection and use. This representative schema provides an illustration of factors to be considered when designing an animal study. In this particular example, all the factors listed at a given stage (and potentially others) should be considered before moving down, stepwise, to the next stage. Here, an initial consideration is that the choice of model may be based on the relevant molecular status, clinical tumour type or in vitro studies. At the next stage, the animal host will be dictated by the need for, say, a human tumour xenograft versus a genetically engineered mouse model, which have advantages discussed in the text. Considerations of tumour environment and site then follow, after which, in therapy studies, are dosing and endpoint aspects. Note that this schema is illustrative and not prescriptive and that each study must be tailored to the specific scientific question and experimental objectives, with appropriate humane endpoints always applied and pilot studies carried out as needed.

Full figure and legend (318K)

Transplantation tumour models

These normally involve the transplantation of mouse or rat tumour cells into a host of the same (syngeneic) species and strain. Growth of human (xenogeneic) tumour cells can be achieved using immunodeficient (e.g., nude or SCID) mice to prevent rejection (Table 1A). Most transplantable tumours are established subcutaneously. These subcutaneous (s.c.) tumours are simple to initiate but may lack relevance in terms of stromal/vascular interactions and metastasis. More complex models may involve orthotopic transplantation at appropriate primary sites, or inoculation of tumour cells through routes which maximise the chance of metastatic spread (Table 1B). There is an increasing trend to establish xenograft tumours directly from human cancers, to avoid artificial selection of cells in tissue culture and changes in gene expression and phenotype, which this may induce. Such transplants may better model the principal facets of clinical cancer, for example, maintenance of tumour architecture, heterogeneity, expression of certain targets and response to therapy (Dong et al, 2010), but can be less reproducible (especially as primary grafts) and slower growing than well-established models (Neale et al, 2008Rubio-Viqueira and Hidalgo, 2009). Detailed molecular and genetic characterisation, facilitated by modern high-throughput technologies (e.g., seehttp://www.sanger.ac.uk/genetics/CGP), is now available for human cancer cell lines used for xenografts (Masters et al, 2001Park et al, 2010) and is important to understand the biology of these models and to select the most appropriate for each study.

Autochthonous tumour models

There are two broad categories: those arising in outbred or inbred rodents (Table 2A), or those from animals harbouring genetic changes that alter tumour susceptibility (Table 2B). Certain mouse or rat strains are susceptible to spontaneous development of tumours. More commonly, tumours are induced by chemical carcinogens, radiation, viruses or bacteria. Such models may mimic some of the aetiological events in human cancer development; exposure to such agents may induce systemic effects that are difficult to replicate in genetically engineered models.

Major advances have been made in the development of sophisticated mouse models of cancer that mimic many of the genetic and biological characteristics of human malignancies, although the host genetic background may affect tumour incidence and/or malignant potential (Lifsted et al, 1998Winter and Hunter, 2008). A range of technologies now allows the inducible expression of oncogenes or inactivation of tumour-suppressor genes in vivo in a precisely controlled manner in virtually any tissue or cell type. (Chen et al, 2004Christophorou et al, 2006Sharpless and DePinho, 2006). Such genetically engineered mouse models (GEMMs) provide excellent experimental systems to develop a deeper understanding of cancer biology in vivoand are increasingly being used for preclinical testing of molecularly targeted therapies, as they depend on or are ‘addicted’ to the specific molecular abnormalities and biochemical pathways engineered to drive the malignant process.

Routine use of GEMMs for preclinical testing of anticancer therapies can be hampered by variable tumour latency, incomplete penetrance and complicated breeding schemes. The full potential of such mouse models is yet to be realised and further work is required to derive maximum benefit for cancer patients from these initiatives (Frese and Tuveson, 2007). Newer models (e.g., exploiting double or multiple genetic abnormalities) have resulted in enhanced tumorigenicity and metastatic capacity, and some studies have shown that mouse cancer models with relevant human gene mutations respond to appropriate targeted therapies (Politi et al, 2006), and also may develop common secondary mutations associated with acquired resistance (Politi et al, 2010). As an example of target validation, reversible, systemic expression of a dominant-negative mutant Myc oncogene in transgenic Ras-induced lung carcinoma model caused the tumours to regress, whereas effects on normal regenerating tissue were well tolerated and reversible (Soucek et al, 2008). To overcome heterogeneity issues, transplantation of transgenic tumours can provide higher throughput models, for example, for testing therapeutics (Varticovski et al, 2007). Commonly used GEMMs include mammary carcinomas induced by the viral oncogene polyoma virus middle T (Guy et al, 1992Fluck and Haslam, 1996;Marcotte and Muller, 2008) or by the human or rat Her2/neu oncogene (Chan et al, 1999Quaglino et al, 2008), or colon adenomas and carcinomas induced by inactivation of the adenomatous polyposis coli (APC) tumour-suppressor gene (Taketo, 2006). Space constraint does not allow a full description or listing of the many more sophisticated, patient-like models now available, examples of which are shown in Table 2B. The reader is referred to the more complete information available at http://emice.nci.nih.gov/mouse_models.

A key question that continues to be debated is whether human cancer xenografts or murine transgenic models best reflect the human disease in terms of biology and predictions of efficacy of therapeutic agents (Becher et al, 2006Dennis, 2006Garber, 2006Sausville et al, 2006Sharpless and DePinho, 2006). Some GEMMs have shown patterns of sensitivity to chemotherapeutic agents and development of resistance that are similar to their human tumour counterparts (Rottenberg and Jonkers, 2008). The predictive value of neither type of model has been fully established; however, there is agreement that molecular characterisation of all tumours is required to underpin the choice of model.

Selection and optimisation of experimental systems

As mentioned, selection of tumour models should be based on both molecular characteristics, for example, expression or mutation of a target of interest or other relevant molecular pathology, either endogenously or through transfection/transgenic technology, together with desired properties such as the rate and reproducibility of growth, metastatic potential and chemosensitivity.

Cell line verification and molecular characterisation

Given the frequency of misidentification and cross-contamination (Nardone, 2007Lacroix, 2008) it is essential that all cell lines are rigorously checked for their provenance and genetic identity (Parodi et al, 2002Yoshino et al, 2006). It is also important that cell lines are free from contamination with infectious agents such as mycoplasma, which can influence their biological behaviour and present a risk to handlers and animals (Ishikawa et al, 2006Sung et al, 2006Harlin and Gajewski, 2008). Regardless of origin, detailed characterisation of tumours should be performed and checked periodically to ensure that desired properties are maintained and are commensurate with the molecular pathology of the corresponding human malignancy (Santarius et al, 2010). A thorough literature review should establish their reported tumorigenic and immunogenic properties, with special attention paid to the selection of the correct host animal strain and sub-strain. Residual immune responses to xenografted tumours in nude/SCID mice may occur and the sex of the host should be considered, particularly for hormone-responsive tumours such as breast and prostate.

Pilot studies and optimisation

Pilot tumour growth studies using small numbers of animals (5–10) are recommended to establish that patterns of local and metastatic growth are reproducible. They also show any adverse effects associated with tumour progression and enable humane endpoints to be identified. The data derived should feed into group numbers used for definitive studies (e.g., therapy experiments) in order for experimental time frames and statistically significant endpoints to be established. Use of a relevant positive control treatment may be useful at this stage to ensure that tumour growth/responsiveness is as expected. This can be dictated by a variety of factors, including the site of growth. Subcutaneous tumours may grow rapidly and some are prone to developing haemorrhagic areas, which can cause rapid expansion and ulceration (e.g., human A2780 ovarian carcinoma and AR42J pancreatic carcinoma xenografts).

For tumours growing as a suspension in the peritoneal cavity, it is important to establish clear criteria to ensure that studies are terminated before animal welfare is compromised. This site is only appropriate for models where ascites is a feature of the natural progression of the human cancer (e.g., ovarian carcinoma, peritoneal mesothelioma, gastrointestinaI tumour carcinomatosis). Similar criteria apply to other sensitive specialised sites such as muscle or brain. For metastatic models, pilot experiments should define the extent and time course of dissemination to internal organs.

Pilot studies should include sequential analysis of animals to determine the time course required to achieve scientific goals. Termination of studies at the earliest possible point will minimise adverse effects on the animal. Where possible, use of biomarkers (e.g., serum levels of prostate-specific antigen, PSA) and real-time imaging are highly recommended. It is also possible to measure circulating tumour cells using fluorescence and PCR-based techniques (Glinskii et al, 2003Komatsubara et al, 2005). For spontaneously arising tumours, including those in transgenic animals, particular attention should be paid to the time course of tumour development and issues relating to the development of multiple tumours. Progression may be unpredictable and involve rapid dissemination and subsequent deterioration in clinical condition, in which case careful and frequent monitoring is required.

Refinement and welfare issues

Subcutaneous implantation of tumour material should use a trochar or surgical formation of a small s.c. pocket. Appropriate anaesthetics must be used and post-implantation analgesia is also strongly recommended. Veterinary advice should be sought to ensure that the agents selected reflect contemporary best practice. Anaesthesia/analgesia is also required for implantation of ‘hollow fibres’ or slow release devices such as osmotic mini-pumps. Hormone pellets (oestrogen/testosterone) may be required to support hormone-dependent tumours, but first-time use in a particular strain will require pilot experiments with different doses/exposures to assess tolerance, especially with oestrogen pellets where urinary tract side effects may be encountered (Pearse et al, 2009).

For injection of cell suspensions, the minimum number of cells in the smallest volume should be used, consistent with the properties of the tumour. For s.c. sites, 1–5 million cells in 100 μl is typical. For orthotopic sites, this should be reduced to avoid excessive tissue damage or leakage (e.g., 50 000 cells in 30 μl into the prostate, or 10–50 000 cells in 5 μl into the brain). Intramuscular tumours in the leg can affect mobility, and this site should only be used if there is special justification (e.g., for tumours which naturally develop in this tissue). Similarly, footpad injection, which has been traditionally used to potentiate lymphatic dissemination, is unacceptable without exceptional scientific justification and should then only involve a single paw.

Surgical removal of a primary tumour may be justified, for example, from s.c. sites, mammary fat pad or removal of the spleen following intrasplenic injection, to allow time for outgrowth of any secondary deposits. Surgery must be performed using sterile techniques with appropriate post-operative monitoring and control of any pain and inflammation/infection.

Cell lines should be checked regularly for contaminating microorganisms to avoid infection of host animals. This is especially important if tumours are routinely passaged between animals, which may be justified for those that are difficult to establish from cell cultures. Asymptomatic infection of experimental animals may affect tumour properties, for example, metastasis (Rodriguez-Cuesta et al, 2005). Procedures can be used to improve tumour take rate. For example, moderate doses of whole-body irradiation may further enhance engraftment of tumour cells in athymic mice (Baersch et al, 1997Nijmeijer et al, 2001Li et al, 2006), although the added stress and risk to the animal must be considered. Co-administration of human tumour cells with allogeneic bone marrow transplantation may reduce graft-vs-host activity but preserve graft-vs-tumour effects in allogeneic leukaemia models (Prigozhina et al, 2002Giver et al, 2004).

Transplanted tumours (especially xenografts) may not develop with an incidence, growth rate or malignant potential required; however this can often be enhanced by selection of tumorigenic/metastatic variants (Bruns et al, 1999Nguyen et al, 2009a). In addition, co-injection of tumour cells with extracellular matrix proteins and/or angiogenic factors (Collado et al, 2007), cancer-associated fibroblasts (Noel et al, 1993;Orimo et al, 2005) or mesenchymal stem cells (Karnoub et al, 2007Spaeth et al, 2009) can increase tumorigenicity, better recapitulate the human tumour microenvironment and enhance metastatic potential. Cells may be transfected with fluorescent or bioluminescent markers allowing serial imaging of internal tumours/metastatic spread. However, such tagged cell lines should be profiled to establish that their biological characteristics are unchanged and consideration should be given to the dependence of luminescence/fluorescence on factors in the tumour microenvironment, for example. molecular oxygenation, necrosis, or ascites fluid from peritoneal tumours (Condeelis and Segall, 2003).

Topof page

Therapy

Preclinical discovery and development of therapeutics

There is a concerted effort to identify and develop small-molecule drugs or biopharmaceuticals (e.g., antibodies, protein therapeutics, vaccines, gene therapy) targeted against cancer cells or associated host cells (Sawyers, 2004Collins and Workman, 2006Workman and de Bono, 2008). A representative ‘test cascade’ for discovering new small-molecule inhibitors of cancer targets is shown in Figure 2. As a consequence of extensive in vitro testing, comparatively small numbers of prioritised compounds progress to examination in vivo (Collins and Workman, 2006). In vivo studies use sequential, discriminatory tests to prioritise compounds at each stage. Different tests may need to be applied to biopharmaceuticals, such as antibodies and vaccines, as they may work by recruiting host effectors (e.g., cytotoxic leukocytes). Epitope specificity can also require the development of an antibody or vaccine initially using anti-rodent reagents (before switching to the clinical form) or use of a genetically modified mouse model. In addition, agents directed against the tumour microenvironment (e.g., angiogenesis, tumour-promoting stromal or inflammatory cells) will require appropriate specialised assays. A range of technical platforms are used preclinically to define responses to therapy, the most informative of which are adopted for use in patients (Figure 3). Careful assessment of a therapy’s safety profile (outside the scope of this review) is also required for regulatory submission.

Figure 2.

Figure 2 - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the authorExample of a drug discovery test cascade for identifying small-molecule antitumour drugs. A representative test cascade for identifying a potential small-molecule drug against a given target is shown. A subset of a compound library is initially screened vsthe target in vitro, in recombinant protein or cellular assays, using high-throughput automation to identify ‘hits’. Subsequent leads are examined in more detail by assessing their effect on downstream molecular events in cells and their selectivity vsother proteins. A battery of additional in vitro tests is also used for measurement or prediction of physical properties and pharmacokinetic parameters. Only compounds with a promising balance of features are progressed to in vivo testing, usually in mice. Pharmacokinetic (PK) studies, used to understand drug exposure, may initially involve co-inoculation of low doses of compounds (‘cassette dosing’) to minimise animal usage. The tolerability of leads with favourable PK is then assessed at higher doses, before evaluating their pharmacodynamic (PD) effect on tumour and normal tissues at well-tolerated doses. Compounds that do not meet the anticipated level of performance at any stage may result in subsequent rounds of iterative medicinal chemistry to generate improved leads. Selected leads are progressed to efficacy testing to determine the link between target inhibition and the effect on tumour growth or spread (metastasis). Safety studies on late-stage leads are also required before a candidate drug can be selected for examination in cancer patients (not covered here). The application of the test cascade means that compounds are filtered by the earlier stage assays so that a smaller number of compounds, and only those of higher quality, are taken into later stage in vivo assays in animals.

Full figure and legend (167K)

Figure 3.

Figure 3 - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the authorExamples of technologies used in animals for therapeutic cancer research. In vivotumour models have an essential role in the development of new cancer medicines, enabling the temporal and quantitative effects of treatment to be examined on tumour and normal tissues in the intact organism. Methods used include those to examine (clockwise from far left) molecular determinants of sensitivity to treatment (initially in vitro, corroborated in vivo) such as (a) gene mutations by sequencing, or (b) gene amplification by fluorescent in situ hybridisation; detection of target phospho-epitopes and their inhibition in tumour tissue as determined by: (c) immunohistochemistry or (d) western blotting of cell lysates; (e) tumour vascular density and maturation by fluorescent immunohistochemistry; (f) tumour mRNA expression by gene array analysis with hierarchical clustering of information; (g) imaging techniques such as dynamic contrast-enhanced MRI to measure tumour haemodynamics; and (h) pharmacokinetic analysis of drug concentrations in plasma by mass spectrometry.

Full figure and legend (300K)

Defining tolerable doses for efficacy studies

An investigational treatment should be examined at a potential therapeutic dose level and using a relevant dosing regimen that covers the longest duration anticipated. These parameters can, for example, be estimated from consideration of mechanism of action, in vitro potency, pharmacokinetics, protein binding and pharmacodynamic biomarker data. Studies typically use two mice per dose level with a doubling dose-escalation or dose-halving de-escalation design. For studies involving a single dosing event, an interval of 24 h should be used before an alternative dose level is examined, to allow any acute adverse effects to be seen. For more chronic administration schedules (e.g., daily for 21–28 days) this interval should be at least 5 days. Animals should be examined at least twice daily (see humane endpoints below). Note that presence of a tumour may reduce host tolerance to therapy. Studies of mice may be used to predict dose requirements in other species through allometric scaling of pharmacokinetic parameters (Freireich et al, 1966).

Combination studies

There is a strong rationale to study combinations of agents in vivo to guide clinical studies. Relevant prior in vitro studies such as Combination Index or isobologram analyses to discriminate additive, synergistic or antagonistic interactions should be completed to guide the selection of combinations and schedules. Compounds are added to tumour cells in culture over a range of concentrations, alone or in combination, and the changes in sensitivity are observed. Compounds may also be added sequentially as the order of administration may significantly influence responses (Chou, 2006). Care needs to be taken with in vivo studies in addressing the choice of individual drug doses and scheduling, particularly if overlapping toxicities are likely. Pilot experiments must assess tolerability (see above), and pharmacokinetic data (see below) should also be generated to determine whether interpretation of efficacy data is affected by pharmacokinetic interactions (Siim et al, 2003).

Pharmacokinetic studies

In vitro and in silico methods are useful to predict absorption, distribution, metabolism and elimination (ADME) properties and to help prioritise compounds for evaluation in animals (Table 3Singh, 2006). However, at present such methods are unable to predict accurately the full pharmacokinetic profile of an agent. Pharmacokinetic studies should use a validated and sufficiently sensitive detection method, ideally avoiding the need to pool separate blood samples, thereby minimising animal usage. Typical experiments on mice use a single dose and 5–8 time points (2–3 mice per point) over 24–48 h with small molecules (usually administered p.o., i.v. or i.p. at doses of 0.5–100 mg kg−1) and over 1–21 days with biopharmaceuticals (administered i.v., i.p. or s.c. at doses ranging from 10 to 1000 μg per mouse).

More recently, repeat sampling of small volumes of blood from a superficial vein in mice over a series of time points has been established to reduce animal numbers. This can be employed either for isolation of plasma and analysis by sensitive liquid chromatography–mass spectrometry/mass spectrometry (LC/MS-MS or tandem MS) instrumentation (Abatan et al, 2008), or by spotting microlitre volumes of whole blood onto specialised paper cards, which are then dried and extracted before analysis (Barfield et al, 2008). In rats, a 5–8 time-point pharmacokinetic profile may be generated using 2–6 animals in total, through repeated blood sampling. ‘Cassette dosing’, which involves administration of low doses of compound mixtures, should also be considered initially as this can reduce animal usage (Watanabe et al, 2006Smith et al, 2007). Wherever possible, computational compartmental kinetic modelling should be used to predict optimal doses or multiple dosing protocols, to facilitate more limited sampling (Rowland and Tozer, 1995). It is noteworthy that the plasma half-life of monoclonal antibodies is frequently extended in immunocompromised mice, which are deficient in IgG production (Bazin et al, 1994).

Pharmacodynamic biomarkers

Initial studies of investigational therapies using tumour-bearing animals should aim to determine whether the target, or an appropriate downstream pathway or phenotype, is modulated by using suitably validated pharmacodynamic biomarkers (Collins and Workman, 2006). Typically, animals are humanely killed at intervals to determine the extent and duration of pharmacodynamic changes and to investigate biomarkers in tumour and normal tissues (e.g., blood or skin) that may be relevant to clinical development (Banerji et al, 2005). In vaccine studies, responses are assessed by changes in immune status, including evidence of tumour-infiltrating leukocytes by immunohistochemistry, and specific cellular or humoral immunity (Gajewski, 2000). It should be possible to use much smaller group sizes of 3–5 in pharmacodynamic studies in comparison to those in efficacy studies (see below). Simultaneous measurement of drug concentrations and mechanistic biomarkers is recommended to reduce animal numbers and establish a pharmacokinetic–pharmacodynamic relationship. Judicious application of such studies in a drug discovery test cascade should be used to prioritise agents before entry into efficacy studies.

Efficacy determinations

All relevant information should be used to guide the design of tumour efficacy studies. Such studies generally involve examination of treatment effects over a 2- to 4-week period and establish how the therapeutic response relates to pharmacokinetic and pharmacodynamic parameters. Typically, with treatments delivered by an appropriate route of administration (Table 4), response is determined in 6–10 animals per study group (vs a control group) either by direct twice-weekly calliper measurement of superficial tumours (Kelland, 2004), counting lung or liver metastases ex vivo, or using imaging methodologies (Edinger et al, 2002Hoffman and Yang, 2005Brindle, 2008McCann et al, 2009Yang et al, 2009). Alternatively, post-treatment excision of tumours for in vitro determination of clonogenic survival, or determination of the dose required to inhibit tumour growth by 50% (tumour control dose-TCD50) may be appropriate (see Radiation therapy section below). Methods are available to determine sample sizes for single- and combination-agent studies and to allow for incomplete data sets (Tan et al, 2005). For certain targets, alternative, surrogate in vivo efficacy models in non-tumour-bearing animals may be used, such as assessment of anti-oestrogenic activity by determining the effect on hypothalamic function (Kato et al, 1968).

Administration of experimental agents

Various sources are available for advice on well-tolerated injection volumes and recommended administration schedules. It is important to note that, from an animal welfare point of view, frequency and duration of dosing are as important as the volume and composition of the injected solution. Some commonly used examples are given in Table 4 and the following references: Diehl et al (2001)Morton et al (2001). More frequent dosing would need to be justified by pharmacokinetic or pharmacodynamic data. As an illustration of standard procedures, for oral/i.p. or i.v. dosing in mice, volumes of 10 and 5 ml kg−1, respectively (equating to 200 and 100 μl for a 20 g mouse), are widely accepted. However, the smallest volume that can be accurately and safely administered must always be used.

Where possible, compounds should be administered in an aqueous solution (sterile water for injections, 0.9%saline or 5% dextrose/saline) that is as close to physiological pH as possible, as highly acidic or basic solutions can be an irritant. If organic solvents (like dimethylsulphoxide, DMSO) are necessary, these should not exceed 5 ml kg−1 or 10% of the injected volume. Detergents (such as Tween), solubilisers or emulsifiers should not exceed 20% of the injected volume. Cyclodextrins should not exceed 2 ml kg−1 or 45% of the injected volume, and where used at >20% of the injected volume, animals need to be rehydrated within 2–4 h.

Experimental design including statistics

To maximise the scientific integrity of data generated while at the same time using the minimum number of animals, statistical expertise should be applied to all experimental design and analyses (Festing, 2002Festing and Altman, 2002Festing et al, 2002; see Boxes 3 and 4).

Chemoprevention

These studies routinely use either carcinogen-induced rat tumours (e.g., azoxymethane-induced colorectal cancer) or mouse genetic models of carcinogenesis (e.g., ApcMin colorectal; Corpet and Pierre, 2003Cai et al, 2009). Generally, animals receive the putative chemopreventive agent in the diet or drinking water over an extended period at innocuous doses. Tumour development is measured at the end of the study and compared with animals on a relevant control diet. Relatively large numbers of rodents (e.g.; greater than or equal to14 per group; Cai et al, 2009) may be required for the observed differences between the intervention and control groups to be robust. Mechanistic and pharmacodynamic endpoints should also be included (Yang et al, 2001Corpet and Pierre, 2003).

Radiation therapy

External beam radiotherapy is primarily used for local tumour irradiation, which requires lead shielding to minimise normal tissue exposure. Typically, s.c. tumours are used and combination treatment with a novel therapy is tested. Endpoints include local control, growth delay and in vivo–in vitro clonogenic survival (TCD50). Time to re-growth is preferred to a single time point analysis. Local tissue toxicity is usually manifest as skin erythema but should be minimised by restricting localised doses to less than 30 Gy (single dose). Exploration of better tolerated, clinically relevant fractionated doses (e.g., 2–5 Gy per fraction over 1–2 weeks) is encouraged. Should moist desquamation occur, this should not be allowed to persist for more than 24 h. Irradiated s.c. tumours can show ulceration, which may reflect tumour response. However, if there is evidence of infection and/or no signs of tissue repair the animal should be humanely killed. The acute and late effects of radiation treatment may also be examined in a relevant organ, particularly when studying new combination paradigms. A common endpoint has been the development of fibrosis in lung tissue, although more recently measurement of breathing rate has been implemented to detect symptoms before they become distressful to the animal (Jackson et al, 2010).

Radiotherapy can also be delivered in the form of targeted radionuclides (normally attached to antibodies; e.g., Martensson et al, 2005). Normal tissue toxicity will depend on antigen expression on tissues relative to the tumour and the nature of the emitter. Whole-body irradiation can also be used to suppress the immune response of an animal, for example, or to treat disseminated disease. Selected doses should not manifest toxicity over the duration of the experiment, for example, gut toxicity within 5 days or haematological toxicity within 30 days.

UV radiation (UVR)

The response of mouse skin to UVR may be used, for example, to study the aetiology of non-melanoma skin cancer (van Kranen and de Gruijl, 1999Hedelund et al, 2006). Generally, experiments are performed with hairless (Skh-hr2) mice. As mouse skin does not show signs of burning, it is important to use a biologically relevant, non-burning dose of 0.2–0.3 MED (minimal erythema dose; 50% skin thickening=0.5 MED). Skin thickness should be measured 2–3 times weekly after increasing the dose of UVR until 20–30% thickening has occurred. If hyperplasia is maintained over 12–15 weeks skin tumours may form. A protective mouse restrainer should be used as UV radiation is damaging to eyes and ears.

Topof page

Imaging

General considerations

Imaging techniques now have a principal role in translational cancer research, enabling sequential analysis of biological endpoints in the same animal, with obvious welfare benefits. The main utility of small-animal imaging is for monitoring deep-seated tumours and metastases with or without treatment. Applications include studies of basic biological processes and of tissue pharmacokinetics and pharmacodynamic responses to treatment (Paulmurugan et al, 2002Galbraith et al, 2003Pillai et al, 2008Tennant et al, 2009Nguyen et al, 2009b). However, animal numbers may not be reduced if, for example, full endpoint analysis requires surgical intervention such as cannulation of blood vessels or when contrast agents have a long half-life. Here, sequential imaging may not be possible and alternative techniques involving tissue excision may provide more information (usually at higher spatial resolution) from the same number of animals.

There is an increasing clinical need for pharmacodynamic imaging with molecularly targeted cancer therapeutics. However, interpretation of imaging signals is often difficult and animal models have an important role in rigorous validation of new techniques. This needs to be accompanied by consideration of unique animal welfare issues. Use of external imaging techniques on small animals is not completely non-invasive as some form of anaesthesia or physical restraint is necessary and surgery or administration of contrast agents may be required.

Imaging techniques

The applications, advantages and disadvantages of commonly used imaging technologies are summarised inTable 5 and have also been reviewed recently (Workman et al, 2006Brindle, 2008Weissleder and Pittet, 2008). Whole-body optical imaging is relatively simple and cost-effective (Edinger et al, 2002). Tumour cells are genetically modified to constitutively or inducibly express a fluorescent protein (e.g., eGFP, dsRed) or an enzyme that activates an exogenously administered substrate to a bioluminescent molecule (usually luciferase for activation of a luciferin). The whole animal is imaged using sensitive optical detectors, which may or may not incorporate a tomographic facility (Figure 4). The potential influences of genetic modification and/or substrate administration on immunogenicity and response to treatment, as well as animal welfare, must be considered (Tuchin, 1993Dennis, 2002Condeelis and Segall, 2003Wells et al, 2006).

Figure 4.

Figure 4 - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the authorExamples of in vivo imaging in pre-clinical cancer research. (A) Optical surface bioluminescence imaging of orthotopically xenografted human PC3 prostate carcinoma cells transfected with luciferase (PC3luc2a). Mice were imaged using a Charged Coupled Device (CCD) camera, which is super-cooled to enhance detection sensitivity and image resolution. The images shown were taken after systemic administration of luciferin, with ‘intensity of luminescence’ shown as ‘heat’ maps and red as maximum intensity. The scale shows the number of photons detected. Top panel: Untreated mice at day 8–41 after transplantation; bottom panel: before and after treatment with 5 mg kg−1 taxotere on day 10. This technique is useful for monitoring treatment effects in deep-seated tumour sites. Light scattering through tissues makes precise quantitation difficult. (B) PET imaging of tumour cell proliferation using 18F-3′-fluoro-3′-deoxy-l-thymidine (FLT). Transverse and coronal (0.5 mm) images of HCT116 tumour-bearing mice 24 h before treatment and after 4 daily treatments with the histone deacetylase inhibitor LAQ842 at 25 mg kg−1. 30- to 60-min summed images from a dynamic scan are presented. Numerous radiotracers are available for investigating specific biochemical pathways in vivo, if specialised facilities are available. The scale shows the intensity of radiotracer uptake. (C) Intravital imaging of tumour vasculature of the P22 rat sarcoma growing in a dorsal skin flap window chamber. The image was obtained by multi-photon fluorescence microscopy after i.v. administration of 70 kDa FITC–dextran. High spatial resolution is obtained but surgical intervention is required.

Full figure and legend (276K)

Intravital microscopy uses a wide variety of optical imaging techniques, often incorporating fluorescent or bioluminescent genetic reporters or markers, including nano-particles (Hoffman, 2005). It has particular animal welfare issues because it involves surgery to provide optical clarity and visualisation on a microscope stage or using fibre-optic light guides (Weissleder and Pittet, 2008). Some intravital microscopy techniques (e.g., tumours growing in the intestinal mesentery) require laparotomy with deep anaesthesia, so that imaging is only possible for a few hours under terminal anaesthesia. Surgical implantation of ‘window’ chambers for tumour implantation enables imaging to be performed over days to weeks (Dewhirst et al, 1987Lehr et al, 1993Brown et al, 2001Reyes-Aldasoro et al, 2008). Here, general anaesthesia is only essential for the initial surgery and imaging may be performed with restrained animals. Strict aseptic technique and good post-operative care and analgesia are essential (Richardson and Flecknell, 2005Flecknell, 2008).

Most physical imaging techniques require use of exogenous contrast agents and only positron emission tomography (PET) and single photon emission computed tomography (SPECT) are sufficiently sensitive to allow use at true tracer levels; so possible pharmacological effects of contrast agents need to be carefully considered. The same procedures for tolerability testing should apply to imaging agents as for new drugs. Some magnetic resonance imaging (MRI) techniques use inherent properties of tissues to provide endogenous imaging contrast. For instance, BOLD (blood-oxygen-level-dependent) MRI allows assessment of tissue oxygenation. These techniques avoid the use of pharmacological agents but results may be difficult to interpret.

Contrast-enhanced CT has the highest spatial resolution of all clinically applicable imaging techniques and is amenable to rapid kinetics. However, depending on the operating parameters and scan length, this may involve considerable ionising radiation dose per scan (0.02–0.6 Gy; typically 0.1–0.3 Gy) (Boone et al, 2004;Carlson et al, 2007Brindle, 2008). Doses should be minimised to avoid compromising experimental results through interaction of ionising events with the biological processes of interest, as well as welfare issues; as a guide, total radiation dose >1 Gy can affect tumour growth and whole-body doses >6 Gy are generally lethal to small rodents. Users of fused PET–CT or SPECT–CT systems should note that the radiation dose from the PET or SPECT can be as large as the CT dose. In addition, iodine-based contrast agents are nephrotoxic and, if required for repeat studies, well-tolerated doses should be established.

Anaesthesia and restraint for imaging

Physical restraint and/or general anaesthesia are required for small-animal imaging. Both procedures can affect animal well-being and introduce experimental artefacts. Body temperature must be maintained and monitored during general anaesthesia using thermostatically controlled heating pads, microwaveable gels or warm air blowers. Light general anaesthesia using an inhalational anaesthetic such as isofluorane or a short-lived i.v. injectable such as propafol should be used for pharmacological restraint, wherever possible. Deleterious effects of physical restraint can be minimised by appropriate design of restrainers, provision of black-outs and acclimatisation (Warden et al, 2000Narciso et al, 2003King et al, 2005). Preferred methods will depend on the species, imaging modality and device used. Where general anaesthesia is not appropriate, sedation with use of gentle physical restraint is encouraged, taking account of veterinary advice. Acclimatisation needs to be thorough, as a short period of training can induce more stress (Warden et al, 2000Narciso et al, 2003).

Length of imaging sessions

If applicable, animals should be transported to imaging facilities in suitable transport boxes, with food and water provided before imaging. The length, total number of imaging sessions and intervals between them depend on factors such as time required to acquire images, tolerance to restraint or general anaesthesia, half-life of the contrast agent and whether cannulation is required. Consideration also needs to be given to exposure of immune-deprived animals to a non-pathogen-free environment, as well as monitoring and control of animal physiology during imaging. If animals have no access to water, an imaging session should typically last no more than 2 h and total imaging time should not exceed 2–3 h in a 24-h period. Use of un-anaesthetised animals restrained for more than 2 h must be avoided except where there is exceptional justification, for example, for animals recovering from general anaesthesia after cannulation of superficial vessels before imaging. In this case, use of local analgesia around the cannulation site is essential. Animals anaesthetised for more than 2 h should be rehydrated if recovery is prolonged, for example, by injection of dextrose/saline. If animals need to be anaesthetised more than once per day, they must be fully recovered, eating and drinking before being re-anaesthetised. On completion of a session, animals should either be killed or kept warm until full recovery from anaesthesia or until the next analysis session. Analysis may be repeated on the same animal but typically this should not exceed five sessions within a 1- to 2-week period and typically no more than one imaging session per day.

Topof page

Humane endpoints

There are ethical, scientific and legal reasons for ensuring that adverse effects are minimised. Choice of appropriate humane endpoints provides significant opportunities for refinement, and should be developed in tandem with the requirements for a valid scientific outcome. Early endpoints reduce non-specific systemic effects and so may increase the precision of the results obtained. Pilot studies, including autopsy to determine the full extent of tumour growth, will facilitate the definition of robust and refined endpoints. Endpoints for particular models must also take account of the known pathogenesis of the particular tumour model in question and should be regularly reviewed in the light of experience.

The endpoints proposed are based on animal models in widespread use (for examples see Tables 1 and 2); however, each study should be considered on its own merits. For example, tumorigenicity studies can be terminated as soon as progressive tumour growth is evident. By contrast, carcinogen-induced skin papillomas, for example, undergo malignant transformation late in their development and may require later endpoints. Imaging techniques facilitate the development of more defined endpoints for some tumour models. Every effort should be made to identify factors allowing scientific decisions to be made at the earliest stage possible, while taking into account the total burden of procedures on animal welfare. The intentional use of death as an endpoint is unacceptable and animals should not be allowed to become moribund.

The choice of site for solid tumours will influence the maximum acceptable tumour load and the appropriate humane endpoints. Sites such as the footpad, tail, eye or bone are likely to be painful or distressing and require special justification and earlier endpoints. Similarly, tumours that metastasise to sensitive sites need great care. If brain tumours can be justified (e.g., to increase understanding of their biology and to develop therapies for this area of unmet clinical need), body weight loss is reportedly a sensitive endpoint (Redgate et al, 1991) and MRI or bioluminescent imaging (BLI) techniques can be very useful (van Furth et al, 2003Ragelet al, 2008McCann et al, 2009). Intramuscular tumours are painful and only justified where there is a strong case for orthotopic studies, for example, for sarcomas.

In genetically modified animals, particular care is needed to ensure detection of unexpected sites of tumour development. As with all internal tumour sites, this includes clinical examination, measurement of body weight, abdominal palpation and loss of condition. Humane endpoints, specialist care and interventions should reflect best practice and be discussed and agreed between researchers, veterinarians and animal care staff before commencement of the experiment. Development and publication of appropriate experimental analyses (e.g., pharmacodynamic determinations, functional imaging) to capture detailed phenotypic information assists rational determination of endpoints.

Tumour burden

Tumour burden should always be limited to the minimum required for a valid scientific outcome. For example, efficacy studies should be terminated once durable, statistically significant therapeutic effects can be shown. Therapeutic studies should be designed to avoid the need for control tumours to become excessively large. The size of any tumours should be limited when they are used simply for routine transplantation or as a source of tumour tissue. In all cases the general health and condition of an animal remains the overriding determinant. Adverse effects on the animal will depend on the biology, site, mode of growth of the tumour and any additional procedures or treatments. Despite the caveats, estimation of tumour size and burden is an important consideration in determining endpoints.

Assessment of the size of superficial tumours using callipers (usually of two diameters at right angles) is an easy and definable method. Measurement variations can be minimised by ensuring that the same well-trained technician is involved for the duration of the study. Response to therapy may be measured by changes in tumour growth rate, re-growth delay, cell survival (measured by clonogenic assay) or an appropriate surrogate marker. Excising and weighing tumours at the end of a study can provide an additional objective endpoint, which avoids errors due to variations in tumour shapes and estimations of volume or mass. For an animal carrying a single tumour, the mean diameter should not normally exceed 1.2 cm in mice or 2.5 cm in rats, or 1.5 and 2.8 cm, respectively, for therapeutic studies. Where two tumours per animal are grown, for example, in contralateral flanks, the size should be correspondingly less and should not exceed the maximum burden of a single tumour. Multiple tumours may develop in genetically modified animals (e.g., mammary tumours in polyoma virus middle T transgenic mice; Guy et al, 1992) or in the skin of animals subjected to UVR (El-Abaseri and Hansen, 2007) or chemical carcinogens (Johansen et al, 2009), for which similar limits should be observed. Exceptions to these advised size limits would require rigorous scientific justification.

Determining the tumour burden of internal orthotopic cancers, systemic lymphoreticular tumours or metastatic disease is challenging. Pilot experiments using small numbers of animals are important to allow characterisation of the kinetics and patterns of spread, to predict clinical signs and to define humane endpoints. Biomarkers or circulating cancer cells may be used as surrogates for assessing the burden of lymphomas and leukaemias, and real-time imaging is a valuable adjunct. Appropriate biochemical and pathological indicators or use of engineered reporter systems or imaging techniques should be used to determine the onset of disease. Reliance must also be placed on the general condition of the animal, together with assessment of palpable tumours and specific signs such as hind-limb weakness or paralysis.

Clinical signs

In general the clinical signs shown in Box 5 are principal indicators of rare but severe symptoms of potential adverse effects, which should be avoided. Where any one sign is present the animal should immediately be humanely culled and vigilance increased for the remainder of the cohort.

With solid tumours, scoring of ulceration, distension of covering tissues and cachexia (severe body weight loss) should be incorporated into the endpoints. Ulceration is a lesion typified by necrosis of superficial tissues, which may be dry, suppurating or exudative. Necrosis resulting in skin breakdown or exudation persisting beyond 48 h is grounds for termination. Some tumours, such as those grown in sensitive sites or that develop extensive necrosis, may be painful, although objective criteria are lacking for mice. Further research is required to enable better assessment of pain and to assist in formulating the most appropriate endpoints.

In all cases endpoints must provide for action to be taken to terminate animals humanely when the degree of suffering cannot be justified by the scientific objective, when the objective has been achieved or cannot be realised, or when the quality of the results has been compromised.

Topof page

Summary and concluding remarks

This set of guidelines is designed to update and enhance the second edition (Workman et al, 1998). Information is provided on the more complex, molecularly defined and biologically relevant models now available, including genetically engineered, orthotopic and metastatic tumour systems. These more ‘patient-like’ models require sophisticated methods of evaluation; hence a detailed section on the different imaging modalities that are now used has been added. Tables 1 and 2 provide examples of some widely used experimental models. Figure 1 offers an example of the type of illustrative aid that can be used to facilitate the rational choice of appropriate models in a given study. Examples of tumour models, experimental design and procedures are provided throughout. However, it is emphasised that these are intended to act as a guide only, and each study should be tailored to the specific experimental objectives. There is renewed emphasis on continuing applications of the 3Rs – replacement (of animals with alternative methods), reduction (in the numbers of animals used to achieve scientific objectives) and refinement (in experimental design, techniques and husbandry to minimise adverse effects and improve welfare). There is an expectation that the highest animal welfare standards will be demanded from grant-awarding bodies and scientific journals. It is also emphasised that there is a responsibility for researchers to publish improved models and methodology for the benefit of the research community worldwide. A comprehensive bibliography is included to cover all of the principal topics and links to other, online resources are also provided. It is to be stressed that animal welfare considerations are not only important for ethical and legal reasons, but also should be fully consistent with the highest standards of scientific investigation. It is anticipated that the appropriate use of animal models will make an important contribution to increasing further our fundamental understanding of cancer and will enhance our growing ability to diagnose, treat and prevent it.

Topof page

Notes

Additional information

Committee to Update Science, Medicine, and Animals, National Research Council (2004) Sciences, Medicine, and Animals: National Research Council of The National Academies. The National Academies Press: Washington, DC, USA

Dennis C (2006) Cancer: off by a whisker. Nature 17: 739–741

Garber K (2006) Realistic rodents? Debate grows over new mouse models of cancer. J Natl Cancer Inst 98:1176–1178

Guidelines for the Care and Use of Mammals in Neuroscience and Behavioural Research. Committee on Guidelines for the Use of Animals in Neuroscience and Behavioural Research, (Institute for Laboratory Animal Research, Washington, D.C. 2003). National Research Council

Flecknell P (2008) Analgesia from a veterinary perspective. Br J Anaesth 101: 121–124

Richardson CA, Flecknell PA (2005) Anaesthesia and post-operative analgesia following experimental surgery in laboratory rodents: are we making progress? Altern Lab Anim 33: 119–127

Roughan JV, Flecknell PA, Davies BR (2004) Behavioural assessment of the effects of tumour growth in rats and the influence of the analgesics carprofen and meloxicam. Lab Anim 38: 286–296

The Royal Society (2004) The Use of Non-human Animals in Research: a Guide for Scientists. Science Advice Section, The Royal Society: London, UK

Useful weblinks

http://scienceandresearch.homeoffice.gov.uk/animal-research/publications-and-reference/statistics/

http://www.sanger.ac.uk/genetics/CGP

http://emice.nci.nih.gov/mouse_models

http://dels.nas.edu/ilar_n/ilarhome/reports.shtml

http://ec.europa.eu/environment/chemicals/lab_animals/home_en.htm

http://www.iasp-pain.org/AM/Template.cfm?Section=Animal_Research

http://ec.europa.eu/european_group_ethics/docs/opinion7_en.pdf

http://conventions.coe.int/treaty/en/treaties/html/123.htm

http://www.ecopa.eu/

http://caat.jhsph.edu/

http://www.imm.ki.se/sft/pdf/OECD19.pdf

http://oacu.od.nih.gov/ARAC/index.htm

http://www.research.psu.edu/arp/health/endpoints.html

http://www.nc3rs.org.uk/news.asp?id=759

http://ddgs.utu.fi/request.php?4

http://www.lal.org.uk/index.php?option=com_content&view=article&id=56&Itemid

http://www.nc3rs.org.uk

GLOSSARY

Allometric scaling: Calculation of doses of drugs to be administered to animals according to their relative sizes where the relationship of a biological variable to body mass is non-linear. For example, drug dosage can be linearly related to body surface area rather than to body weight.

Ascites: Cells/fluid in the peritoneal cavity.

Autochthonous tumours: Tumours originating within the host animal, either spontaneously, or due to genetic or pharmacological intervention.

Cachexia: Severe loss of weight and muscle mass that cannot be reversed nutritionally. Can be caused by release of biologically active molecules (cytokines) from certain tumours.

Cassette dosing: Administration of multiple compounds to an individual animal followed by individual measurements in the same blood sample.

Clinically equivalent dose: A dose of a drug, which results in blood/tissue levels that reflect those that are achieved in patients.

Clonogenic assay: Measuring the effect of treatments on the ability of tumour cells to proliferate expansively. Treatment may be in vitro or initiated in vivo and the clonogenic ability of explanted cells testedin vitro.

Desquamation: Loss of skin integrity. Moist desquamation can be a consequence of exposure to ionising radiation (UV or X-rays) where the skin thins and then begins to weep tissue fluid as the epithelial cells lose their barrier function.

Distension: Stretched beyond normal dimensions.

Ectopic: Site of growth different from the tissue of origin, for example, s.c. transplantation of tumours derived from internal organs.

Erythema: Skin reddening and thickening in response to UV irradiation, as in mild sunburn.

Factorial design: Involves the inclusion of two or more variables and measuring the response to each variable and interactions between variables.

Genetically engineered mouse models (GEMMs): Animals in which the genetic material has been altered. For example, introduction of a mutation in cells of a particular organ may result in the development of benign or malignant tumours.

Hyperplasia: Refers to the proliferation of cells within an organ or tissue beyond that which is ordinarily seen. Microscopically cells resemble normal cells but are increased in numbers. It is a benign condition, unlike neoplasia, which is malignant.

Intravital microscopy: A technique, which allows direct observation of small blood vessels within the organs of anesthetised animals.

Maximum Tolerated Dose (MTD): The highest dose of a drug in which the clinical condition of the experimental animal is maintained.

Metastasis: The spread of tumour cells from a primary site to distant sites in the body, usually through the blood or lymph. The term ‘experimental metastasis’ is sometimes used to describe the colonisation of organs after injection of cells directly into the peripheral circulation.

Oncogenesis: The process of malignant transformation resulting in tumour development.

Orthotopic: Anatomically correct site (opposite of ectopic), for example, transplantation of renal tumour cells into the kidney or mammary carcinoma cells into the mammary fat pad.

Pharmacodynamics: The study of the action of and the duration of effects of agents in the body, including confirmation of mechanism of action through identification of relevant biomarkers of activity.

Pharmacokinetics: The study of the process by which agents are absorbed, distributed, metabolized and eliminated by the body, including measurement of the rate of excretion, metabolism, blood and tissue concentrations.

Syngeneic tumour models: Cells transplanted between animals of the same inbred strain.

Ulceration: An inflamed lesion on the skin or internal surface involving tissue destruction.

Xenogeneic tumour models: Cells transplanted between species (e.g., human to mouse). Requires recipients that cannot mount an immune response and reject the foreign tissue graft such as athymic mice which lack T-lymphocytes, or severe combined immunodeficient (SCID) mice.

Topof page

References

  1. Abatan OI, Welch KB, Nemzek JA (2008) Evaluation of saphenous venipuncture and modified tail-clip blood collection in mice. J Am Assoc Lab Anim Sci 47: 8–15 | ChemPort |
  2. Aguirre AJ, Bardeesy N, Sinha M, Lopez L, Tuveson DA, Horner J, Redston MS, DePinho RA (2003) Activated Kras and Ink4a/Arf deficiency cooperate to produce metastatic pancreatic ductal adenocarcinoma. Genes Dev 17: 3112–3126 | Article | PubMed | ISI | ChemPort |
  3. Ahsan H, Aziz MH, Ahmad N (2005) Ultraviolet B exposure activates Stat3 signaling via phosphorylation at tyrosine705 in skin of SKH1 hairless mouse: a target for the management of skin cancer? Biochem Biophys Res Commun 333: 241–246 | Article | PubMed | ChemPort |
  4. Alsheikhly AR, Zweiri J, Walmesley AJ, Watson AJ, Christmas SE (2004) Both soluble and membrane-bound forms of Flt3 ligand enhance tumor immunity following ‘suicide’ gene therapy in a murine colon carcinoma model. Cancer Immunol Immunother 53: 946–954 | Article | PubMed | ISI | ChemPort |
  5. Artandi SE, Chang S, Lee SL, Alson S, Gottlieb GJ, Chin L, DePinho RA (2000) Telomere dysfunction promotes non-reciprocal translocations and epithelial cancers in mice. Nature 406: 641–645 | Article | PubMed | ISI | ChemPort |
  6. Artursson P, Palm K, Luthman K (2001) Caco-2 monolayers in experimental and theoretical predictions of drug transport. Adv Drug Deliv Rev 46: 27–43 | Article | PubMed | ISI | ChemPort |
  7. Baersch G, Mollers T, Hotte A, Dockhorn-Dworniczak B, Rube C, Ritter J, Jurgens H, Vormoor J (1997) Good engraftment of B-cell precursor ALL in NOD-SCID mice. Klin Padiatr 209: 178–185 | Article | ChemPort |
  8. Balansky RM, Ganchev G, D’Agostini F, De Flora S (2002) Effects of N-acetylcysteine in an esophageal carcinogenesis model in rats treated with diethylnitrosamine and diethyldithiocarbamate. Int J Cancer98: 493–497 | Article | ChemPort |
  9. Banerji U, Walton M, Raynaud F, Grimshaw R, Kelland L, Valenti M, Judson I, Workman P (2005) Pharmacokinetic–pharmacodynamic relationships for the heat shock protein 90 molecular chaperone inhibitor 17-allylamino, 17-demethoxygeldanamycin in human ovarian cancer xenograft models. Clin Cancer Res 11: 7023–7032 | Article | PubMed | ISI | ChemPort |
  10. Barfield M, Spooner N, Lad R, Parry S, Fowles S (2008) Application of dried blood spots combined with HPLC–MS/MS for the quantification of acetaminophen in toxicokinetic studies. J Chromatogr B Analyt Technol Biomed Life Sci 870: 32–37 | Article | ChemPort |
  11. Bazin R, Boucher G, Monier G, Chevrier MC, Verrette S, Broly H, Lemieux R (1994) Use of hu-IgG-SCID mice to evaluate the in vivo stability of human monoclonal IgG antibodies. J Immunol Methods 172: 209–217 | Article | ChemPort |
  12. Biotechnology and Biological Sciences Research Council; Department for Environment, Food and Rural Affairs; Medical Research Council; National Centre for the Replacement, Refinement and Reduction of Animals in Research; Natural Environment Research Council; Wellcome Trust (2008) Responsibility in the use of animals in bioscience research: expectations of the major research council and charitable funding bodies. National Centre for the Replacement, Refinement and Reduction of Animals in Research, London.http://www.nc3rs.org.uk/downloaddoc.asp?id=719 (Accessed date 30 March 2010)
  13. Becher OJ, Holland EC, Sausville EA, Burger AM (2006) Genetically engineered models have advantages over xenografts for preclinical studies. Cancer Res 66: 3355–3359 | Article | PubMed | ISI | ChemPort |
  14. Becker JC, Pancook JD, Gillies SD, Mendelsohn J, Reisfeld RA (1996) Eradication of human hepatic and pulmonary melanoma metastases in SCID mice by antibody-interleukin 2 fusion proteins. Proc Natl Acad Sci USA 93: 2702–2707 | Article | PubMed | ChemPort |
  15. Bergers G, Javaherian K, Lo KM, Folkman J, Hanahan D (1999) Effects of angiogenesis inhibitors on multistage carcinogenesis in mice. Science 284: 808–812 | Article | PubMed | ISI | ChemPort |
  16. Bignell GR, Greenman CD, Davies H, Butler AP, Edkins S, Andrews JM, Buck G, Chen L, Beare D, Latimer C, Widaa S, Hinton J, Fahey C, Fu B, Swamy S, Dalgliesh GL, Teh BT, Deloukas P, Yang F, Campbell PJ, Futreal PA, Stratton MR (2010) Signatures of mutation and selection in the cancer genome. Nature463: 893–898 | Article | ChemPort |
  17. Blouin S, Basle MF, Chappard D (2008) Interactions between microenvironment and cancer cells in two animal models of bone metastasis. Br J Cancer 98: 809–815 | Article | ChemPort |
  18. Boone JM, Velazquez O, Cherry SR (2004) Small-animal X-ray dose from micro-CT. Mol Imaging 3: 149–158 | Article | PubMed
  19. Brindle K (2008) New approaches for imaging tumour responses to treatment. Nat Rev Cancer 8: 94–107 | Article | PubMed | ChemPort |
  20. Brown EB, Campbell RB, Tsuzuki Y, Xu L, Carmeliet P, Fukumura D, Jain RK (2001) In vivo measurement of gene expression, angiogenesis and physiological function in tumors using multiphoton laser scanning microscopy. Nat Med 7: 864–868 | Article | PubMed | ISI | ChemPort |
  21. Bruneau P, McElroy NR (2006) logD7.4 modeling using Bayesian Regularized Neural Networks. Assessment and correction of the errors of prediction. J Chem Inf Model 46: 1379–1387 | Article | ChemPort |
  22. Bruns CJ, Harbison MT, Kuniyasu H, Eue I, Fidler IJ (1999) In vivo selection and characterization of metastatic variants from human pancreatic adenocarcinoma by using orthotopic implantation in nude mice. Neoplasia 1: 50–62 | Article | PubMed | ChemPort |
  23. Cai H, Sale S, Schmid R, Britton RG, Brown K, Steward WP, Gescher AJ (2009) Flavones as colorectal cancer chemopreventive agents – phenol-o-methylation enhances efficacy. Cancer Prev Res (Phila PA)2: 743–750
  24. Carlson SK, Classic KL, Bender CE, Russell SJ (2007) Small animal absorbed radiation dose from serial micro-computed tomography imaging. Mol Imaging Biol 9: 78–82 | Article
  25. Chan R, Muller WJ, Siegel PM (1999) Oncogenic activating mutations in the neu/erbB-2 oncogene are involved in the induction of mammary tumors. Ann N Y Acad Sci 889: 45–51 | Article | ChemPort |
  26. Chen D, Livne-bar I, Vanderluit JL, Slack RS, Agochiya M, Bremner R (2004) Cell-specific effects of RB or RB/p107 loss on retinal development implicate an intrinsically death-resistant cell-of-origin in retinoblastoma. Cancer Cell 5: 539–551 | Article | PubMed | ISI | ChemPort |
  27. Chen X, Yang G, Ding WY, Bondoc F, Curtis SK, Yang CS (1999) An esophagogastroduodenal anastomosis model for esophageal adenocarcinogenesis in rats and enhancement by iron overload.Carcinogenesis 20: 1801–1808 | Article | PubMed | ISI | ChemPort |
  28. Chou TC (2006) Theoretical basis, experimental design, and computerized simulation of synergism and antagonism in drug combination studies. Pharmacol Rev 58: 621–681 | Article | PubMed | ChemPort |
  29. Christophorou MA, Martin-Zanca D, Soucek L, Lawlor ER, Brown-Swigart L, Verschuren EW, Evan GI (2005) Temporal dissection of p53 function in vitro and in vivo. Nat Genet 37: 718–726 | Article | PubMed | ISI | ChemPort |
  30. Christophorou MA, Ringshausen I, Finch AJ, Swigart LB, Evan GI (2006) The pathological response to DNA damage does not contribute to p53-mediated tumour suppression. Nature 443: 214–217 | Article | PubMed | ISI | ChemPort |
  31. Colclough N, Hunter A, Kenny PW, Kittlety RS, Lobedan L, Tam KY, Timms MA (2008) High throughput solubility determination with application to selection of compounds for fragment screening. Bioorg Med Chem 16: 6611–6616 | Article | ChemPort |
  32. Collado B, Carmena MJ, Clemente C, Prieto JC, Bajo AM (2007) Vasoactive intestinal peptide enhances growth and angiogenesis of human experimental prostate cancer in a xenograft model. Peptides 28: 1896–1901 | Article | PubMed | ChemPort |
  33. Collins I, Workman P (2006) New approaches to molecular cancer therapeutics. Nat Chem Biol 2: 689–700 | Article | PubMed | ISI | ChemPort |
  34. Comstock KE, Hall CL, Daignault S, Mandlebaum SA, Yu C, Keller ET (2009) A bioluminescent orthotopic mouse model of human osteosarcoma that allows sensitive and rapid evaluation of new therapeutic agents in vivo. In Vivo 23: 661–668 | ChemPort |
  35. Condeelis J, Segall JE (2003) Intravital imaging of cell movement in tumours. Nat Rev Cancer 3: 921–930 | Article | PubMed | ISI | ChemPort |
  36. Corpet DE, Pierre F (2003) Point: from animal models to prevention of colon cancer. Systematic review of chemoprevention in min mice and choice of the model system. Cancer Epidemiol Biomarkers Prev 12: 391–400 | PubMed | ISI |
  37. De Fabo EC (2006) Initial studies on an in vivo action spectrum for melanoma induction. Prog Biophys Mol Biol 92: 97–104 | Article | PubMed | ChemPort |
  38. Decker S, Hollingshead M, Bonomi CA, Carter JP, Sausville EA (2004) The hollow fibre model in cancer drug screening: the NCI experience. Eur J Cancer 40: 821–826 | Article | PubMed | ChemPort |
  39. Dennis C (2006) Cancer: off by a whisker. Nature 17: 739–741 | Article | ChemPort |
  40. Dennis Jr MB (2002) Welfare issues of genetically modified animals. Ilar J 43: 100–109 | PubMed | ChemPort |
  41. Dewhirst MW, Gustafson C, Gross JF, Tso CY (1987) Temporal effects of 5.0 Gy radiation in healing subcutaneous microvasculature of a dorsal flap window chamber. Radiat Res 112: 581–591 | Article | ChemPort |
  42. Dickson PV, Hamner B, Ng CY, Hall MM, Zhou J, Hargrove PW, McCarville MB, Davidoff AM (2007) In vivobioluminescence imaging for early detection and monitoring of disease progression in a murine model of neuroblastoma. J Pediatr Surg 42: 1172–1179 | Article
  43. Diehl KH, Hull R, Morton D, Pfister R, Rabemampianina Y, Smith D, Vidal JM, van de Vorstenbosch C (2001) A good practice guide to the administration of substances and removal of blood, including routes and volumes. J Appl Toxicol 21: 15–23 | Article | PubMed | ISI | ChemPort |
  44. Dohta Y, Yamashita T, Horiike S, Nakamura T, Fukami T (2007) A system for LogD screening of 96-well plates using a water-plug aspiration/injection method combined with high-performance liquid chromatography-mass spectrometry. Anal Chem 79: 8312–8315 | Article | ChemPort |
  45. Dong X, Guan J, English JC, Flint J, Yee J, Evans K, Murray N, Macaulay C, Ng RT, Gout PW, Lam WL, Laskin J, Ling V, Lam S, Wang Y (2010) Patient-derived first generation xenografts of non-small cell lung cancers: promising tools for predicting drug responses for personalized chemotherapy. Clin Cancer Res16: 1442–1451 | Article | ChemPort |
  46. Du-Cuny L, Huwyler J, Wiese M, Kansy M (2008) Computational aqueous solubility prediction for drug-like compounds in congeneric series. Eur J Med Chem 43: 501–512 | Article | ChemPort |
  47. Edinger M, Cao YA, Hornig YS, Jenkins DE, Verneris MR, Bachmann MH, Negrin RS, Contag CH (2002) Advancing animal models of neoplasia through in vivo bioluminescence imaging. Eur J Cancer 38: 2128–2136 | Article | PubMed | ISI | ChemPort |
  48. El-Abaseri TB, Hansen LA (2007) EGFR activation and ultraviolet light-induced skin carcinogenesis. J Biomed Biotechnol 2007: 97939
  49. Felsher DW, Bishop JM (1999) Reversible tumorigenesis by MYC in hematopoietic lineages. Mol Cell 4: 199–207 | Article | PubMed | ISI | ChemPort |
  50. Festing M, Overend P, Gaine Das R, Cortina Borja M, Berdoy M (2002) The design of Animal Experiments: Reducing the Use of Animals in Research Through Better Experimental Design. Royal Society of Medicine Press: London
  51. Festing MF (2002) The design and statistical analysis of animal experiments. ILAR J 43: 191–193 | ChemPort |
  52. Festing MF, Altman DG (2002) Guidelines for the design and statistical analysis of experiments using laboratory animals. ILAR J 43: 244–258 | PubMed | ChemPort |
  53. Flecknell P (2008) Analgesia from a veterinary perspective. Br J Anaesth 101: 121–124 | Article | ChemPort |
  54. Fluck MM, Haslam SZ (1996) Mammary tumors induced by polyomavirus. Breast Cancer Res Treat 39: 45–56 | Article | ChemPort |
  55. Freireich EJ, Gehan EA, Rall DP, Schmidt LH, Skipper HE (1966) Quantitative comparison of toxicity of anticancer agents in mouse, rat, hamster, dog, monkey, and man. Cancer Chemother Rep 50: 219–244 | PubMed | ChemPort |
  56. Frese KK, Tuveson DA (2007) Maximizing mouse cancer models. Nat Rev Cancer 7: 645–658 | Article | PubMed | ChemPort |
  57. Gajewski TF (2000) Monitoring specific T-cell responses to melanoma vaccines: ELISPOT, tetramers, and beyond. Clin Diagn Lab Immunol 7: 141–144 | ChemPort |
  58. Galbraith SM, Maxwell RJ, Lodge MA, Tozer GM, Wilson J, Taylor NJ, Stirling JJ, Sena L, Padhani AR, Rustin GJ (2003) Combretastatin A4 phosphate has tumor antivascular activity in rat and man as demonstrated by dynamic magnetic resonance imaging. J Clin Oncol 21: 2831–2842 | Article | PubMed | ISI | ChemPort |
  59. Garber K (2006) Realistic rodents? Debate grows over new mouse models of cancer. J Natl Cancer Inst98: 1176–1178
  60. Giovannini M, Robanus-Maandag E, van der Valk M, Niwa-Kawakita M, Abramowski V, Goutebroze L, Woodruff JM, Berns A, Thomas G (2000) Conditional biallelic Nf2 mutation in the mouse promotes manifestations of human neurofibromatosis type 2. Genes Dev 14: 1617–1630 | PubMed | ISI | ChemPort |
  61. Giver CR, Li JM, Hossain MS, Lonial S, Waller EK (2004) Reconstructing immunity after allogeneic transplantation. Immunol Res 29: 269–282 | Article | PubMed | ISI | ChemPort |
  62. Glass B, Uharek L, Zeis M, Loeffler H, Mueller-Ruchholtz W, Gassmann W (1996) Graft-versus-leukaemia activity can be predicted by natural cytotoxicity against leukaemia cells. Br J Haematol 93: 412–420 | Article | PubMed | ISI | ChemPort |
  63. Glinskii AB, Smith BA, Jiang P, Li X-M, Yang M, Hoffman RM, Glinsky GV (2003) Viable circulating metastatic cells produced in orthotopic but not ectopic prostate cancer models. Cancer Res 63: 4239–4243 | PubMed | ISI | ChemPort |
  64. Golay J, Cittera E, Di Gaetano N, Manganini M, Mosca M, Nebuloni M, van Rooijen N, Vago L, Introna M (2006) The role of complement in the therapeutic activity of rituximab in a murine B lymphoma model homing in lymph nodes. Haematologica 91: 176–183 | ChemPort |
  65. Graf MR, Sauer JT, Merchant RE (2005) Tumor infiltration by myeloid suppressor cells in response to T cell activation in rat gliomas. J Neurooncol 73: 29–36 | Article
  66. Graff BA, Benjaminsen IC, Melas EA, Brurberg KG, Rofstad EK (2005) Changes in intratumor heterogeneity in blood perfusion in intradermal human melanoma xenografts during tumor growth assessed by DCE-MRI. Magn Reson Imaging 23: 961–966 | Article | ChemPort |
  67. Guy CT, Cardiff RD, Muller WJ (1992) Induction of mammary tumors by expression of polyomavirus middle T oncogene: a transgenic mouse model for metastatic disease. Mol Cell Biol 12: 954–961 | PubMed | ISI | ChemPort |
  68. Ha WS, Kim CK, Song SH, Kang CB (2001) Study on mechanism of multistep hepatotumorigenesis in rat: development of hepatotumorigenesis. J Vet Sci 2: 53–58 | ChemPort |
  69. Han Y, Chen XP, Huang ZY, Zhu H (2005) Nude mice multi-drug resistance model of orthotopic transplantation of liver neoplasm and Tc-99m MIBI SPECT on p-glycoprotein. World J Gastroenterol 11: 3335–3338
  70. Hanahan D, Weinberg RA (2000) The hallmarks of cancer. Cell 100: 57–70 | Article | PubMed | ISI | ChemPort |
  71. Harlin H, Gajewski TF (2008) Diagnosis and treatment of mycoplasma-contaminated cell cultures. Curr Protoc Cytom Appendix 3: Appendix 3C
  72. Harris JC, Gilliam AD, McKenzie AJ, Evans SA, Grabowska AM, Clarke PA, McWilliams DF, Watson SA (2004) The biological and therapeutic importance of gastrin gene expression in pancreatic adenocarcinomas. Cancer Res 64: 5624–5631 | Article | PubMed | ISI | ChemPort |
  73. Hawariah A, Stanslas J (1998) Antagonistic effects of styrylpyrone derivative (SPD) on 7,12-dimethylbenzanthracene-induced rat mammary tumors. In Vivo 12: 403–410 | ChemPort |
  74. Hedelund L, Lerche C, Wulf HC, Haedersdal M (2006) Carcinogenesis related to intense pulsed light and UV exposure: an experimental animal study. Lasers Med Sci 21: 198–201 | Article | ChemPort |
  75. Hingorani SR, Wang L, Multani AS, Combs C, Deramaudt TB, Hruban RH, Rustgi AK, Chang S, Tuveson DA (2005) Trp53R172H and KrasG12D cooperate to promote chromosomal instability and widely metastatic pancreatic ductal adenocarcinoma in mice. Cancer Cell 7: 469–483 | Article | PubMed | ISI | ChemPort |
  76. Hirayama T, Honda A, Matsuzaki Y, Miyazaki T, Ikegami T, Doy M, Xu G, Lea M, Salen G (2006) Hypercholesterolemia in rats with hepatomas: increased oxysterols accelerate efflux but do not inhibit biosynthesis of cholesterol. Hepatology 44: 602–611 | Article | ChemPort |
  77. Hirose Y, Hata K, Kuno T, Yoshida K, Sakata K, Yamada Y, Tanaka T, Reddy BS, Mori H (2004) Enhancement of development of azoxymethane-induced colonic premalignant lesions in C57BL/KsJ-db/db mice. Carcinogenesis 25: 821–825 | Article | PubMed | ChemPort |
  78. Hoffman RM (2005) The multiple uses of fluorescent proteins to visualize cancer in vivo. Nat Rev Cancer5: 796–806 | Article | PubMed | ISI | ChemPort |
  79. Hoffman RM, Yang M (2005) Dual-color, whole-body imaging in mice. Nat Biotechnol 23: 790; author reply 791 | Article | ChemPort |
  80. Houston JB, Carlile DJ (1997) Prediction of hepatic clearance from microsomes, hepatocytes, and liver slices. Drug Metab Rev 29: 891–922 | Article | PubMed | ChemPort |
  81. Howard ML, Hill JJ, Galluppi GR, McLean MA (2010) Plasma protein binding in drug discovery and development. Comb Chem High Throughput Screen 13: 170–187 | Article | ChemPort |
  82. Huxham LA, Kyle AH, Baker JH, Nykilchuk LK, Minchinton AI (2004) Microregional effects of gemcitabine in HCT-116 xenografts. Cancer Res 64: 6537–6541 | Article | PubMed | ISI | ChemPort |
  83. Ihle NT, Lemos Jr R, Wipf P, Yacoub A, Mitchell C, Siwak D, Mills GB, Dent P, Kirkpatrick DL, Powis G (2009) Mutations in the phosphatidylinositol-3-kinase pathway predict for antitumor activity of the inhibitor PX-866 whereas oncogenic Ras is a dominant predictor for resistance. Cancer Res 69: 143–150 | Article | PubMed | ChemPort |
  84. Ishikawa Y, Kozakai T, Morita H, Saida K, Oka S, Masuo Y (2006) Rapid detection of mycoplasma contamination in cell cultures using SYBR Green-based real-time polymerase chain reaction. In Vitro Cell Dev Biol Anim 42: 63–69 | Article | ChemPort |
  85. Jackson IL, Vujaskovic Z, Down JD (2010) Revisiting strain-related differences in radiation sensitivity of the mouse lung: recognizing and avoiding the confounding effects of pleural effusions. Radiat Res 173: 10–20 | Article | ChemPort |
  86. Johansen C, Vestergaard C, Kragballe K, Kollias G, Gaestel M, Iversen L (2009) MK2 regulates the early stages of skin tumor promotion. Carcinogenesis 30: 2100–2108 | Article | ChemPort |
  87. Johnson L, Mercer K, Greenbaum D, Bronson RT, Crowley D, Tuveson DA, Jacks T (2001) Somatic activation of the K-ras oncogene causes early onset lung cancer in mice. Nature 410: 1111–1116 | Article | PubMed | ISI | ChemPort |
  88. Jonkers J, Meuwissen R, van der Gulden H, Peterse H, van der Valk M, Berns A (2001) Synergistic tumor suppressor activity of BRCA2 and p53 in a conditional mouse model for breast cancer. Nat Genet 29: 418–425 | Article | PubMed | ISI | ChemPort |
  89. Karnoub AE, Dash AB, Vo AP, Sullivan A, Brooks MW, Bell GW, Richardson AL, Polyak K, Tubo R, Weinberg RA (2007) Mesenchymal stem cells within tumour stroma promote breast cancer metastasis.Nature 449: 557–563 | Article | PubMed | ISI | ChemPort |
  90. Kato J, Kobayashi T, Villec CA (1968) Effect of clomiphene on the uptake of estradiol by the anterior hypothalamus and hypophysis. Endocrinology 82: 1049–1052 | Article | PubMed | ChemPort |
  91. Kelland LR (2004) Of mice and men: values and liabilities of the athymic nude mouse model in anticancer drug development. Eur J Cancer 40: 827–836 | Article | PubMed | ISI | ChemPort |
  92. Kenerson H, Dundon TA, Yeung RS (2005) Effects of rapamycin in the Eker rat model of tuberous sclerosis complex. Pediatr Res 57: 67–75 | Article | PubMed | ISI | ChemPort |
  93. Kennel SJ, Boll R, Stabin M, Schuller HM, Mirzadeh S (1999) Radioimmunotherapy of micrometastases in lung with vascular targeted 213Bi. Br J Cancer 80: 175–184 | Article | ChemPort |
  94. Kim EJ, Shin M, Park H, Hong JE, Shin HK, Kim J, Kwon DY, Park JH (2009) Oral administration of 3,3′-diindolylmethane inhibits lung metastasis of 4T1 murine mammary carcinoma cells in BALB/c mice. J Nutr139: 2373–2379 | Article | ChemPort |
  95. King JA, Garelick TS, Brevard ME, Chen W, Messenger TL, Duong TQ, Ferris CF (2005) Procedure for minimizing stress for fMRI studies in conscious rats. J Neurosci Methods 148: 154–160 | Article
  96. Koehl GE, Gaumann A, Geissler EK (2009) Intravital microscopy of tumor angiogenesis and regression in the dorsal skin fold chamber: mechanistic insights and preclinical testing of therapeutic strategies. Clin Exp Metastasis 26: 329–344 | Article
  97. Komatsubara H, Umeda M, Ojima Y, Minamikawa T, Komori T (2005) Detection of cancer cells in the peripheral blood and lung of mice after transplantation of human adenoid cystic carcinoma. Kobe J Med Sci 51: 67–72 | ChemPort |
  98. Kragh M, Hjarnaa PJ, Bramm E, Kristjansen PE, Rygaard J, Binderup L (2003) In vivo chamber angiogenesis assay: an optimized Matrigel plug assay for fast assessment of antiangiogenic activity. Int J Oncol 22: 305–311 | ChemPort |
  99. Krimpenfort P, Quon KC, Mooi WJ, Loonstra A, Berns A (2001) Loss of p16Ink4a confers susceptibility to metastatic melanoma in mice. Nature 413: 83–86 | Article | PubMed | ISI | ChemPort |
  100. Lacroix M (2008) Persistent use of ‘false’ cell lines. Int J Cancer 122: 1–4 | Article | PubMed | ChemPort |
  101. Lee PH, Ayyampalayam SN, Carreira LA, Shalaeva M, Bhattachar S, Coselmon R, Poole S, Gifford E, Lombardo F (2007) In silico prediction of ionization constants of drugs. Mol Pharm 4: 498–512 | Article | ChemPort |
  102. Lehr HA, Leunig M, Menger MD, Nolte D, Messmer K (1993) Dorsal skinfold chamber technique for intravital microscopy in nude mice. Am J Pathol 143: 1055–1062 | PubMed | ISI | ChemPort |
  103. Li M, Huang X, Zhu Z, Wong M, Watkins S, Zhao Q, Herberman R, Gorelik E (2001) Immune response against 3LL Lewis lung carcinoma potentiates the therapeutic efficacy of endostatin. J Immunother 24: 472–481 | Article | ChemPort |
  104. Li Z, Chen Z, Lu J, Cen J, He J, Chen S, Xue Y, Guo L (2006) Establishment of a nude mice model of human monocytic leukemia with CNS and multiorgan extramedullary infiltration. Eur J Haematol 77: 128–133 | Article
  105. Liem NL, Papa RA, Milross CG, Schmid MA, Tajbakhsh M, Choi S, Ramirez CD, Rice AM, Haber M, Norris MD, MacKenzie KL, Lock RB (2004) Characterization of childhood acute lymphoblastic leukemia xenograft models for the preclinical evaluation of new therapies. Blood 103: 3905–3914 | Article | ChemPort |
  106. Lifsted T, Le Voyer T, Williams M, Muller W, Klein-Szanto A, Buetow KH, Hunter KW (1998) Identification of inbred mouse strains harboring genetic modifiers of mammary tumor age of onset and metastatic progression. Int J Cancer 77: 640–644 | Article | PubMed | ISI | ChemPort |
  107. Lock RB, Liem NL, Papa RA (2005) Preclinical testing of antileukemic drugs using an in vivo model of systemic disease. Methods Mol Med 111: 323–334 | ChemPort |
  108. Mahteme H, Lovqvist A, Graf W, Lundqvist H, Carlsson J, Sundin A (1998) Adjuvant 131I-anti-CEA-antibody radioimmunotherapy inhibits the development of experimental colonic carcinoma liver metastases. Anticancer Res 18: 843–848 | ChemPort |
  109. Mannhold R, Poda GI, Ostermann C, Tetko IV (2009) Calculation of molecular lipophilicity: state-of-the-art and comparison of log P methods on more than 96,000 compounds. J Pharm Sci 98: 861–893 | Article | ChemPort |
  110. Marcotte R, Muller WJ (2008) Signal transduction in transgenic mouse models of human breast cancer – implications for human breast cancer. J Mammary Gland Biol Neoplasia 13: 323–335 | Article | PubMed
  111. Martensson L, Wang Z, Nilsson R, Ohlsson T, Senter P, Sjogren HO, Strand SE, Tennvall J (2005) Determining maximal tolerable dose of the monoclonal antibody BR96 labeled with 90Y or 177Lu in rats: establishment of a syngeneic tumor model to evaluate means to improve radioimmunotherapy. Clin Cancer Res 11: 7104s–7108s | Article | ChemPort |
  112. Martinsen TC, Kawase S, Hakanson R, Torp SH, Fossmark R, Qvigstad G, Sandvik AK, Waldum HL (2003) Spontaneous ECL cell carcinomas in cotton rats: natural course and prevention by a gastrin receptor antagonist. Carcinogenesis 24: 1887–1896 | Article | ChemPort |
  113. Masimirembwa CM, Thompson R, Andersson TB (2001) In vitro high throughput screening of compounds for favorable metabolic properties in drug discovery. Comb Chem High Throughput Screen 4: 245–263 | ChemPort |
  114. Masters JR et al (2001) Short tandem repeat profiling provides an international reference standard for human cell lines. Proc Natl Acad Sci USA 98: 8012–8017 | Article | PubMed | ChemPort |
  115. McCann CM, Waterman P, Figueiredo JL, Aikawa E, Weissleder R, Chen JW (2009) Combined magnetic resonance and fluorescence imaging of the living mouse brain reveals glioma response to chemotherapy.Neuroimage 45: 360–369 | Article
  116. Mitra SK, Lim ST, Chi A, Schlaepfer DD (2006) Intrinsic focal adhesion kinase activity controls orthotopic breast carcinoma metastasis via the regulation of urokinase plasminogen activator expression in a syngeneic tumor model. Oncogene 25: 4429–4440 | Article | PubMed | ChemPort |
  117. Miyazaki K, Koshikawa N, Hasegawa S, Momiyama N, Nagashima Y, Moriyama K, Ichikawa Y, Ishikawa T, Mitsuhashi M, Shimada H (1999) Matrilysin as a target for chemotherapy for colon cancer: use of antisense oligonucleotides as antimetastatic agents. Cancer Chemother Pharmacol 43Suppl: S52–S55 | Article | ChemPort |
  118. Morton DB, Jennings M, Buckwell A, Ewbank R, Godfrey C, Holgate B, Inglis I, James R, Page C, Sharman I, Verschoyle R, Westall L, Wilson AB (2001) Refining procedures for the administration of substances. Report of the BVAAWF/FRAME/RSPCA/UFAW Joint Working Group on Refinement. British Veterinary Association Animal Welfare Foundation/Fund for the Replacement of Animals in Medical Experiments/Royal Society for the Prevention of Cruelty to Animals/Universities Federation for Animal Welfare. Lab Anim 35: 1–41 | Article | ChemPort |
  119. Nakai M, Mundy GR, Williams PJ, Boyce B, Yoneda T (1992) A synthetic antagonist to laminin inhibits the formation of osteolytic metastases by human melanoma cells in nude mice. Cancer Res 52: 5395–5399 | ChemPort |
  120. Nakatsugawa S, Okuda T, Muramoto H, Koyama K, Ishigaki T, Tsuruoka T, Hosokawa M, Kobayashi H (1999) Inhibitory effect of ND2001 on spontaneous multiple metastasis of NC 65 tumors derived from human renal cancer cells intradermally transplanted into nude mice. Anticancer Drugs 10: 229–233 | Article | ChemPort |
  121. Narciso SP, Nadziejko E, Chen LC, Gordon T, Nadziejko C (2003) Adaptation to stress induced by restraining rats and mice in nose-only inhalation holders. Inhal Toxicol 15: 1133–1143 | ChemPort |
  122. Nardone RM (2007) Eradication of cross-contaminated cell lines: a call for action. Cell Biol Toxicol 23: 367–372 | Article | PubMed
  123. Neale G, Su X, Morton CL, Phelps D, Gorlick R, Lock RB, Reynolds CP, Maris JM, Friedman HS, Dome J, Khoury J, Triche TJ, Seeger RC, Gilbertson R, Khan J, Smith MA, Houghton PJ (2008) Molecular characterization of the pediatric preclinical testing panel. Clin Cancer Res 14: 4572–4583 | Article | ChemPort |
  124. Nguyen DX, Bos PD, Massague J (2009a) Metastasis: from dissemination to organ-specific colonization.Nat Rev Cancer 9: 274–284 | Article | PubMed | ChemPort |
  125. Nguyen QD, Smith G, Glaser M, Perumal M, Arstad E, Aboagye EO (2009b) Positron emission tomography imaging of drug-induced tumor apoptosis with a caspase-3/7 specific [18F]-labeled isatin sulfonamide.Proc Natl Acad Sci USA 106: 16375–16380 | Article
  126. Nijmeijer BA, Mollevanger P, van Zelderen-Bhola SL, Kluin-Nelemans HC, Willemze R, Falkenburg JH (2001) Monitoring of engraftment and progression of acute lymphoblastic leukemia in individual NOD/SCID mice. Exp Hematol 29: 322–329 | Article | PubMed | ISI | ChemPort |
  127. Noel A, De Pauw-Gillet MC, Purnell G, Nusgens B, Lapiere CM, Foidart JM (1993) Enhancement of tumorigenicity of human breast adenocarcinoma cells in nude mice by Matrigel and fibroblasts. Br J Cancer 68: 909–915 | PubMed | ISI | ChemPort |
  128. Nordsmark M, Maxwell RJ, Wood PJ, Stratford IJ, Adams GE, Overgaard J, Horsman MR (1996) Effect of hydralazine in spontaneous tumours assessed by oxygen electrodes and 31P-magnetic resonance spectroscopy. Br J Cancer Suppl 27: S232–S235 | ChemPort |
  129. Orimo A, Gupta PB, Sgroi DC, Arenzana-Seisdedos F, Delaunay T, Naeem R, Carey VJ, Richardson AL, Weinberg RA (2005) Stromal fibroblasts present in invasive human breast carcinomas promote tumor growth and angiogenesis through elevated SDF-1/CXCL12 secretion. Cell 121: 335–348 | Article | PubMed | ISI | ChemPort |
  130. Osborne NJ, Payne D, Newman ML (2009) Journal editorial policies, animal welfare, and the 3Rs. Am J Bioeth 9: 55–59
  131. Ottaviani G, Martel S, Carrupt PA (2006) Parallel artificial membrane permeability assay: a new membrane for the fast prediction of passive human skin permeability. J Med Chem 49: 3948–3954 | Article | ChemPort |
  132. Park ES, Rabinovsky R, Carey M, Hennessy BT, Agarwal R, Liu W, Ju Z, Deng W, Lu Y, Woo HG, Kim SB, Cheong JH, Garraway LA, Weinstein JN, Mills GB, Lee JS, Davies MA (2010) Integrative analysis of proteomic signatures, mutations, drug responsiveness in the NCI 60 cancer cell line set. Mol Cancer Ther 9: 257–267 | Article | ChemPort |
  133. Parodi B, Aresu O, Bini D, Lorenzini R, Schena F, Visconti P, Cesaro M, Ferrera D, Andreotti V, Ruzzon T (2002) Species identification and confirmation of human and animal cell lines: a PCR-based method.Biotechniques 32: 432–434, 436, 438–40 | ChemPort |
  134. Patel S, Turner PR, Stubberfield C, Barry E, Rohlff CR, Stamps A, McKenzie E, Young K, Tyson K, Terrett J, Box G, Eccles S, Page MJ (2002) Hyaluronidase gene profiling and role of hyal-1 overexpression in an orthotopic model of prostate cancer. Int J Cancer 97: 416–424 | Article | PubMed | ISI | ChemPort |
  135. Paulmurugan R, Umezawa Y, Gambhir SS (2002) Noninvasive imaging of protein–protein interactions in living subjects by using reporter protein complementation and reconstitution strategies. Proc Natl Acad Sci USA 99: 15608–15613 | Article | PubMed | ChemPort |
  136. Pearse G, Frith J, Randall KJ, Klinowska T (2009) Urinary retention and cystitis associated with subcutaneous estradiol pellets in female nude mice. Toxicol Pathol 37: 227–234 | Article | ChemPort |
  137. Pelengaris S, Littlewood T, Khan M, Elia G, Evan G (1999) Reversible activation of c-Myc in skin: induction of a complex neoplastic phenotype by a single oncogenic lesion. Mol Cell 3: 565–577 | Article | PubMed | ISI | ChemPort |
  138. Pillai RG, Forster M, Perumal M, Mitchell F, Leyton J, Aibgirhio FI, Golovko O, Jackman AL, Aboagye EO (2008) Imaging pharmacodynamics of the alpha-folate receptor-targeted thymidylate synthase inhibitor BGC 945. Cancer Res 68: 3827–3834 | Article | ChemPort |
  139. Politi K, Fan PD, Shen R, Zakowski M, Varmus H (2010) Erlotinib resistance in mouse models of epidermal growth factor receptor-induced lung adenocarcinoma. Dis Model Mech 3: 111–119 | Article
  140. Politi K, Zakowski MF, Fan PD, Schonfeld EA, Pao W, Varmus HE (2006) Lung adenocarcinomas induced in mice by mutant EGF receptors found in human lung cancers respond to a tyrosine kinase inhibitor or to downregulation of the receptors. Genes Dev 20: 1496–1510 | Article | PubMed | ISI | ChemPort |
  141. Poller B, Gutmann H, Krahenbuhl S, Weksler B, Romero I, Couraud PO, Tuffin G, Drewe J, Huwyler J (2008) The human brain endothelial cell line hCMEC/D3 as a human blood–brain barrier model for drug transport studies. J Neurochem 107: 1358–1368 | Article | ChemPort |
  142. Prigozhina TB, Gurevitch O, Morecki S, Yakovlev E, Elkin G, Slavin S (2002) Nonmyeloablative allogeneic bone marrow transplantation as immunotherapy for hematologic malignancies and metastatic solid tumors in preclinical models. Exp Hematol 30: 89–96 | Article | PubMed | ISI
  143. Qian CN, Furge KA, Knol J, Huang D, Chen J, Dykema KJ, Kort EJ, Massie A, Khoo SK, Vanden Beldt K, Resau JH, Anema J, Kahnoski RJ, Morreau H, Camparo P, Comperat E, Sibony M, Denoux Y, Molinie V, Vieillefond A, Eng C, Williams BO, Teh BT (2009) Activation of the Pl3K/AKT pathway induces urothelial carcinoma of the renal pelvis: identification in human tumors and confirmation in animal models. Cancer Res 69: 8256–8264 | Article | ChemPort |
  144. Quaglino E, Mastini C, Forni G, Cavallo F (2008) ErbB2 transgenic mice: a tool for investigation of the immune prevention and treatment of mammary carcinomas. Curr Protoc Immunol Chapter 20: Unit 20 9 1–Unit 20 9–10
  145. Radaelli E, Ceruti R, Patton V, Russo M, Degrassi A, Croci V, Caprera F, Stortini G, Scanziani E, Pesenti E, Alzani R (2009) Immunohistopathological and neuroimaging characterization of murine orthotopic xenograft models of glioblastoma multiforme recapitulating the most salient features of human disease.Histol Histopathol 24: 879–891 | ChemPort |
  146. Ragel BT, Elam IL, Gillespie DL, Flynn JR, Kelly DA, Mabey D, Feng H, Couldwell WT, Jensen RL (2008) A novel model of intracranial meningioma in mice using luciferase-expressing meningioma cells. Laboratory investigation. J Neurosurg 108: 304–310 | Article
  147. Redgate ES, Deutsch M, Boggs SS (1991) Time of death of CNS tumor-bearing rats can be reliably predicted by body weight-loss patterns. Lab Anim Sci 41: 269–273 | ChemPort |
  148. Reilly KM, Loisel DA, Bronson RT, McLaughlin ME, Jacks T (2000) Nf1;Trp53 mutant mice develop glioblastoma with evidence of strain-specific effects. Nat Genet 26: 109–113 | Article | PubMed | ISI | ChemPort |
  149. Reyes-Aldasoro CC, Wilson I, Prise VE, Barber PR, Ameer-Beg M, Vojnovic B, Cunningham VJ, Tozer GM (2008) Estimation of apparent tumor vascular permeability from multiphoton fluorescence microscopic images of P22 rat sarcomas in vivo. Microcirculation 15: 65–79 | Article | ChemPort |
  150. Richardson CA, Flecknell PA (2005) Anaesthesia and post-operative analgesia following experimental surgery in laboratory rodents: are we making progress? Altern Lab Anim 33: 119–127 | ChemPort |
  151. Riley RJ, Martin IJ, Cooper AE (2002) The influence of DMPK as an integrated partner in modern drug discovery. Curr Drug Metab 3: 527–550 | Article | ChemPort |
  152. Robanus-Maandag E, Dekker M, van der Valk M, Carrozza ML, Jeanny JC, Dannenberg JH, Berns A, te Riele H (1998) p107 is a suppressor of retinoblastoma development in pRb-deficient mice. Genes Dev12: 1599–1609 | Article | PubMed | ISI | ChemPort |
  153. Rodriguez-Cuesta J, Vidal-Vanaclocha F, Mendoza L, Valcarcel M, Gallot N, Martinez de Tejada G (2005) Effect of asymptomatic natural infections due to common mouse pathogens on the metastatic progression of B16 murine melanoma in C57BL/6 mice. Clin Exp Metastasis 22: 549–558 | Article
  154. Rottenberg S, Jonkers J (2008) Modeling therapy resistance in genetically engineered mouse cancer models. Drug Resist Updat 11: 51–60 | Article | ChemPort |
  155. Roughan JV, Flecknell PA, Davies BR (2004) Behavioural assessment of the effects of tumour growth in rats and the influence of the analgesics carprofen and meloxicam. Lab Anim 38: 286–296 | Article | ChemPort |
  156. Rowland M, Tozer TN (1995) Clinical Pharmacokinetics: Concepts and Applications. 3rd edn., Chapter 7, pp 83–105. Williams and Wilkins (now Lippincott, Williams and Wilkins): Philadelphia, USA
  157. Rubio-Viqueira B, Hidalgo M (2009) Direct in vivo xenograft tumor model for predicting chemotherapeutic drug response in cancer patients. Clin Pharmacol Ther 85: 217–221 | Article | PubMed | ChemPort |
  158. Rusciano D, Lorenzoni P, Burger M (1994) Murine models of liver metastasis. Invasion Metastasis 14: 349–361
  159. Russell PJ, Ho Shon I, Boniface GR, Izard ME, Philips J, Raghavan D, Walker KZ (1991) Growth and metastasis of human bladder cancer xenografts in the bladder of nude rats. A model for intravesical radioimmunotherapy. Urol Res 19: 207–213 | Article | ChemPort |
  160. Russell WMS, Burch RL (1959) The Principles of Humane Experimental Technique. Methuen: London
  161. Santarius T, Shipley J, Brewer D, Stratton MR, Cooper CS (2010) A census of amplified and overexpressed human cancer genes. Nat Rev Cancer 10: 59–64 | Article | ChemPort |
  162. Sausville EA, Burger AM, Becher OJ, Holland EC (2006) Contributions of human tumor xenografts to anticancer drug development 10.1158/0008-5472.CAN-05-3627. Cancer Res 66: 3351–3354 | Article | PubMed | ISI | ChemPort |
  163. Sawyers C (2004) Targeted cancer therapy. Nature 432: 294–297 | Article | PubMed | ISI | ChemPort |
  164. Serganova I, Moroz E, Vider J, Gogiberidze G, Moroz M, Pillarsetty N, Doubrovin M, Minn A, Thaler HT, Massague J, Gelovani J, Blasberg R (2009) Multimodality imaging of TGFbeta signaling in breast cancer metastases. FASEB J 23: 2662–2672 | Article | ChemPort |
  165. Sharkey RM, Weadock KS, Natale A, Haywood L, Aninipot R, Blumenthal RD, Goldenberg DM (1991) Successful radioimmunotherapy for lung metastasis of human colonic cancer in nude mice. J Natl Cancer Inst 83: 627–632 | Article | PubMed | ChemPort |
  166. Sharpless NE, DePinho RA (2006) The mighty mouse: genetically engineered mouse models in cancer drug development. Nat Rev Drug Discov 5: 741–754 | Article | PubMed | ISI | ChemPort |
  167. Shibata H, Toyama K, Shioya H, Ito M, Hirota M, Hasegawa S, Matsumoto H, Takano H, Akiyama T, Toyoshima K, Kanamaru R, Kanegae Y, Saito I, Nakamura Y, Shiba K, Noda T (1997) Rapid colorectal adenoma formation initiated by conditional targeting of the Apc gene. Science 278: 120–123 | Article | PubMed | ISI | ChemPort |
  168. Shibata MA, Shibata E, Morimoto J, Eid NA, Tanaka Y, Watanabe M, Otsuki Y (2009) An immunocompetent murine model of metastatic mammary cancer accessible to bioluminescence imaging.Anticancer Res 29: 4389–4395
  169. Siim BG, Lee AE, Shalal-Zwain S, Pruijn FB, McKeage MJ, Wilson WR (2003) Marked potentiation of the antitumour activity of chemotherapeutic drugs by the antivascular agent 5,6-dimethylxanthenone-4-acetic acid (DMXAA). Cancer Chemother Pharmacol 51: 43–52 | Article | PubMed | ISI | ChemPort |
  170. Singh SS (2006) Preclinical pharmacokinetics: an approach towards safer and efficacious drugs. Curr Drug Metab 7: 165–182 | Article | PubMed | ISI | ChemPort |
  171. Sinn E, Muller W, Pattengale P, Tepler I, Wallace R, Leder P (1987) Coexpression of MMTV/v-Ha-ras and MMTV/c-myc genes in transgenic mice: synergistic action of oncogenes in vivo. Cell 49: 465–475 | Article | PubMed | ISI | ChemPort |
  172. Smith NF, Raynaud FI, Workman P (2007) The application of cassette dosing for pharmacokinetic screening in small-molecule cancer drug discovery. Mol Cancer Ther 6: 428–440 | Article | ChemPort |
  173. Soucek L, Whitfield J, Martins CP, Finch AJ, Murphy DJ, Sodir NM, Karnezis AN, Swigart LB, Nasi S, Evan GI (2008) Modelling Myc inhibition as a cancer therapy. Nature 455: 679–683 | Article | PubMed | ChemPort |
  174. Spaeth EL, Dembinski JL, Sasser AK, Watson K, Klopp A, Hall B, Andreeff M, Marini F (2009) Mesenchymal stem cell transition to tumor-associated fibroblasts contributes to fibrovascular network expansion and tumor progression. PLoS One 4: e4992 | Article | PubMed | ChemPort |
  175. Stambolic V, Tsao MS, Macpherson D, Suzuki A, Chapman WB, Mark TW (2000) High incidence of breast and endometrial neoplasia resembling human Cowden syndrome in pten+/− mice. Cancer Res 60: 3605–3611 | PubMed | ISI | ChemPort |
  176. Stratton MR, Campbell PJ, Futreal PA (2009) The cancer genome. Nature 458: 719–724 | Article | PubMed | ChemPort |
  177. Sung H, Kang SH, Bae YJ, Hong JT, Chung YB, Lee CK, Song S (2006) PCR-based detection of mycoplasma species. J Microbiol 44: 42–49 | ChemPort |
  178. Takeda N, Diksic M (1999) Relationship between drug delivery and the intra-arterial infusion rate of SarCNU in C6 rat brain tumor model. J Neurooncol 41: 235–246 | Article | ChemPort |
  179. Taketo MM (2006) Mouse models of gastrointestinal tumors. Cancer Sci 97: 355–361 | Article | PubMed | ISI | ChemPort |
  180. Tan M, Fang HB, Tian GL, Houghton PJ (2005) Repeated-measures models with constrained parameters for incomplete data in tumour xenograft experiments. Stat Med 24: 109–119 | Article
  181. Tanaka T, Konno H, Matsuda I, Nakamura S, Baba S (1995) Prevention of hepatic metastasis of human colon cancer by angiogenesis inhibitor TNP-470. Cancer Res 55: 836–839 | ChemPort |
  182. Tennant DA, Frezza C, MacKenzie ED, Nguyen QD, Zheng L, Selak MA, Roberts DL, Dive C, Watson DG, Aboagye EO, Gottlieb E (2009) Reactivating HIF prolyl hydroxylases under hypoxia results in metabolic catastrophe and cell death. Oncogene 28: 4009–4021 | Article | ChemPort |
  183. Tsai PP, Stelzer HD, Schraepler A, Hackbarth H (2006) Importance and effects of enrichment on physiology, behaviour and breeding performance in mice. Altex 23 (Suppl): 96–98
  184. Tuchin VV (1993) Laser light scattering in biomedical diagnostics and therapy. J Laser Appl 5: 43–60 | ChemPort |
  185. Ullman-Cullere MH, Foltz CJ (1999) Body condition scoring: a rapid and accurate method for assessing health status in mice. Lab Anim Sci 49: 319–323 | PubMed | ISI | ChemPort |
  186. van Furth WR, Laughlin S, Taylor MD, Salhia B, Mainprize T, Henkelman M, Cusimano MD, Ackerley C, Rutka JT (2003) Imaging of murine brain tumors using a 1.5 Tesla clinical MRI system. Can J Neurol Sci30: 326–332 | PubMed |
  187. van Kranen HJ, de Gruijl FR (1999) Mutations in cancer genes of UV-induced skin tumors of hairless mice. J Epidemiol 9: S58–S65 | ChemPort |
  188. Varticovski L, Hollingshead MG, Robles AI, Wu X, Cherry J, Munroe DJ, Lukes L, Anver MR, Carter JP, Borgel SD, Stotler H, Bonomi CA, Nunez NP, Hursting SD, Qiao W, Deng CX, Green JE, Hunter KW, Merlino G, Steeg PS, Wakefield LM, Barrett JC (2007) Accelerated preclinical testing using transplanted tumors from genetically engineered mouse breast cancer models. Clin Cancer Res 13: 2168–2177 | Article | PubMed | ISI | ChemPort |
  189. Verheul HM, Hammers H, van Erp K, Wei Y, Sanni T, Salumbides B, Qian DZ, Yancopoulos GD, Pili R (2007) Vascular endothelial growth factor trap blocks tumor growth, metastasis formation, and vascular leakage in an orthotopic murine renal cell cancer model. Clin Cancer Res 13: 4201–4208 | Article | ChemPort |
  190. Vogelstein B, Kinzler KW (2004) Cancer genes and the pathways they control. Nat Med 10: 789–799 | Article | PubMed | ISI | ChemPort |
  191. Warden SJ, Bennell KL, McMeeken JM, Wark JD (2000) A technique for restraining rodents during hindlimb interventions. Contemp Top Lab Anim Sci 39: 24–27 | ChemPort |
  192. Watanabe H, Uesaka T, Kido S, Ishimura Y, Shiraki K, Kuramoto K, Hirata S, Shoji S, Katoh O, Fujimoto N (1999) Gastric tumor induction by 1,2-dimethylhydrazine in Wistar rats with intestinal metaplasia caused by X-irradiation. Jpn J Cancer Res 90: 1207–1211 | ChemPort |
  193. Watanabe T, Schulz D, Morisseau C, Hammock BD (2006) High-throughput pharmacokinetic method: cassette dosing in mice associated with minuscule serial bleedings and LC/MS/MS analysis. Anal Chim Acta 559: 37–44 | Article | PubMed | ChemPort |
  194. Watson SA, Michaeli D, Morris TM, Clarke P, Varro A, Griffin N, Smith A, Justin T, Hardcastle JD (1999a) Antibodies raised by gastrimmune inhibit the spontaneous metastasis of a human colorectal tumour, AP5LV. Eur J Cancer 35: 1286–1291 | Article | ChemPort |
  195. Watson SA, Morris TM, Varro A, Michaeli D, Smith AM (1999b) A comparison of the therapeutic effectiveness of gastrin neutralisation in two human gastric cancer models: relation to endocrine and autocrine/paracrine gastrin mediated growth. Gut 45: 812–817 | ChemPort |
  196. Weiss WA, Aldape K, Mohapatra G, Feuerstein BG, Bishop JM (1997) Targeted expression of MYCN causes neuroblastoma in transgenic mice. EMBO J 16: 2985–2995 | Article | PubMed | ISI | ChemPort |
  197. Weissleder R, Pittet MJ (2008) Imaging in the era of molecular oncology. Nature 452: 580–589 | Article | PubMed | ChemPort |
  198. Wells DJ, Playle LC, Enser WE, Flecknell PA, Gardiner MA, Holland J, Howard BR, Hubrecht R, Humphreys KR, Jackson IJ, Lane N, Maconochie M, Mason G, Morton DB, Raymond R, Robinson V, Smith JA, Watt N (2006) Assessing the welfare of genetically altered mice. Lab Anim 40: 111–114 | Article | PubMed | ChemPort |
  199. Wetmore C, Eberhart DE, Curran T (2001) Loss of p53 but not ARF accelerates medulloblastoma in mice heterozygous for patched. Cancer Res 61: 513–516 | PubMed | ISI | ChemPort |
  200. Winter SF, Hunter KW (2008) Mouse modifier genes in mammary tumorigenesis and metastasis. J Mammary Gland Biol Neoplasia 13: 337–342 | Article
  201. Wood PJ, Stratford IJ, Sansom JM, Cattanach BM, Quinney RM, Adams GE (1992) The response of spontaneous and transplantable murine tumors to vasoactive agents measured by 31P magnetic resonance spectroscopy. Int J Radiat Oncol Biol Phys 22: 473–476 | ChemPort |
  202. Workman P, Balmain A, Hickman JA, McNally NJ, Rohas AM, Mitchison NA, Pierrepoint CG, Raymond R, Rowlatt C, Stephens TC, Wallace J (1988) UKCCCR guidelines for the welfare of animals in experimental neoplasia. Br J Cancer 58: 109–113 | PubMed |
  203. Workman P, Aboagye EO, Chung YL, Griffiths JR, Hart R, Leach MO, Maxwell RJ, McSheehy PM, Price PM, Zweit J (2006) Minimally invasive pharmacokinetic and pharmacodynamic technologies in hypothesis-testing clinical trials of innovative therapies. J Natl Cancer Inst 98: 580–598 | PubMed | ChemPort |
  204. Workman P, de Bono J (2008) Targeted therapeutics for cancer treatment: major progress towards personalised molecular medicine. Curr Opin Pharmacol 8: 359–362 | Article | PubMed | ChemPort |
  205. Workman P, Twentyman P, Balkwill F, Balmain A, Chaplin D, Double J, Embleton J, Newell D, Raymond R, Stables J, Stephens T, Wallace J (1998) UKCCCR guidelines for the welfare of animals in experimental neoplasia (Second Edition). Br J Cancer 77: 1–10 | ISI |
  206. Xu X, Wagner KU, Larson D, Weaver Z, Li C, Ried T, Hennighausen L, Wynshaw-Boris A, Deng CX (1999) Conditional mutation of Brca1 in mammary epithelial cells results in blunted ductal morphogenesis and tumour formation. Nat Genet 22: 37–43 | Article | PubMed | ISI | ChemPort |
  207. Yang L, Mao H, Cao Z, Wang YA, Peng X, Wang X, Sajja HK, Wang L, Duan H, Ni C, Staley CA, Wood WC, Gao X, Nie S (2009) Molecular imaging of pancreatic cancer in an animal model using targeted multifunctional nanoparticles. Gastroenterology 136: 1514–1525; e2 | Article | ChemPort |
  208. Yang M, Reynoso J, Jiang P, Li L, Moossa AR, Hoffman RM (2004) Transgenic nude mouse with ubiquitous green fluorescent protein expression as a host for human tumors. Cancer Res 64: 8651–8656 | Article | PubMed | ChemPort |
  209. Yang W, Velcich A, Mariadason J, Nicholas C, Corner G, Houston M, Edelmann W, Kucherlapati R, Holt PR, Augenlicht LH (2001) p21(WAF1/cip1) is an important determinant of intestinal cell response to sulindac in vitro and in vivo. Cancer Res 61: 6297–6302 | PubMed | ISI | ChemPort |
  210. Yoshino K, Iimura E, Saijo K, Iwase S, Fukami K, Ohno T, Obata Y, Nakamura Y (2006) Essential role for gene profiling analysis in the authentication of human cell lines. Hum Cell 19: 43–48 | Article
  211. Zavaleta CL, Goins BA, Bao A, McManus LM, McMahan CA, Phillips WT (2008) Imaging of 186Re-liposome therapy in ovarian cancer xenograft model of peritoneal carcinomatosis. J Drug Target 16: 626–637 | Article | ChemPort |
  212. Zhau HE, Li CL, Chung LW (2000) Establishment of human prostate carcinoma skeletal metastasis models. Cancer 88: 2995–3001 | Article | PubMed | ChemPort |
  213. Zheng Q, Chen XY, Shi Y, Xiao SD (2004) Development of gastric adenocarcinoma in Mongolian gerbils after long-term infection with Helicobacter pylori. J Gastroenterol Hepatol 19: 1192–1198 | Article
  214. Zhu JS, Song MQ, Chen GQ, Li Q, Sun Q, Zhang Q (2007) Molecular mechanisms of paclitaxel and NM-3 on human gastric cancer in a severe combined immune deficiency mice orthotopic implantation model.World J Gastroenterol 13: 4131–4135 | ChemPort |
  215. Zisman A, Pantuck AJ, Bui MH, Said JW, Caliliw RR, Rao N, Shintaku P, Berger F, Gambhir SS, Belldegrun AS (2003) LABAZ1: a metastatic tumor model for renal cell carcinoma expressing the carbonic anhydrase type 9 tumor antigen. Cancer Res 63: 4952–4959 | ChemPort |
  216. Zuber J, Radtke I, Pardee TS, Zhao Z, Rappaport AR, Luo W, McCurrach ME, Yang MM, Dolan ME, Kogan SC, Downing JR, Lowe SW (2009) Mouse models of human AML accurately predict chemotherapy response. Genes Dev 23: 877–889 | Article | PubMed | ChemPort |

Read Full Post »

SDS-PAGE with Taq DNA Polymerase. SDS-PAGE is ...

SDS-PAGE with Taq DNA Polymerase. SDS-PAGE is an useful technique to separate proteins according to their electrophoretic mobility. (Photo credit: Wikipedia)

Proteomics and Biomarker Discovery

Reporter: Larry H. Bernstein, MD, FCAP

 

 

Advanced Proteomic Technologies for Cancer Biomarker Discovery

Sze Chuen Cesar Wong; Charles Ming Lok Chan; Brigette Buig Yue Ma; Money Yan Yee Lam; Gigi Ching Gee Choi; Thomas Chi Chuen Au; Andrew Sai Kit Chan; Anthony Tak Cheung Chan

Published: 06/10/2009

This report is extracted from the article above with editing and shortening as much as possible for the reader, and updated from LCGCNA Aug 12,  2012; 8
www.chromatographyonline.com

Part I

Abstract

This review will focus on four state-of-the-art proteomic technologies, namely 2D difference gel electrophoresis, MALDI imaging mass spectrometry, electron transfer dissociation mass spectrometry and reverse-phase protein array. The major advancements these techniques have brought about biomarker discovery will be presented in this review. The wide dynamic range of protein abundance, standardization of protocols and validation of cancer biomarkers, and a 5-year view of potential solutions to such problems is discussed.

English: Public domain image from cancer.gov h...

English: Public domain image from cancer.gov http://visualsonline.cancer.gov/details.cf?imageid=3483. TECAN Genesis 2000 robot preparing Ciphergen SELDI-TOF protein chips for proteomic  analysis. (Photo credit: Wikipedia)

Introduction

A common method used for isolating and identifying cancer biomarkers involves the use of serum or tissue protein identification. Unfortunately, currently used tumor markers have low sensitivities and specificities.[2] Therefore, the development of novel tumor markers might be helpful in improving cancer diagnosis, prognosis and treatment.

The rapid development of proteomic technologies during the past 10 years has brought about a massive increase in the discovery of novel cancer biomarkers. Such biomarkers may have broad applications, such as for the detection of the presence of a disease, monitoring of disease clearance and/or progression, monitoring of treatment response and demonstration of drug targeting of a particular pathway and/or target. In general, proteomic approaches begin with the collection of biological specimens representing two different physiological conditions, cancer patients and reference subjects. Proteins or peptides are extracted and separated, and the protein or peptide profiles are compared against each other in order to detect differentially expressed proteins. Commonly, quantitative proteomics is mainly performed by protein separation using either 2DE- or liquid chromatography (LC)-based methods coupled with protein identification using mass spectrometry (MS). Limitations include inability to obtain protein profiles directly from tissue sections for correlation with tissue morphology, limited ability to analyze post-translational modifications (PTMs) and low capacity for high-throughput validation of identified markers. Progress in proteomic technologies has led to the development of 2D DIGE, MALDI imaging MS (IMS), electron transfer dissociation (ETD) MS, and reverse-phase protein array (RPA).

2D Difference Gel Electrophoresis

The 2DE method has been one of the mainstream technologies used for proteomic investigations.[3,4] In this method, proteins are separated in the first dimension according to charge by isoelectric focusing, followed by separation in the second dimension according to molecular weight, using polyacrylamide gel electrophoresis. The gels are then stained to visualize separated protein spots,[5] separating up to 1000 protein spots in a single experiment and  protein spots are then excised and identified using mass spectrometry (MS).[6,7]

We previously used a 2DE approach to compare the proteomic profiles to identify differentially expressed proteins that may be involved in the development of nasopharyngeal cancer, [8]   as well as proteins that were responsive to treatment with the chemotherapeutic agent 5-fluorouracil (5FU) in the colorectal cancer SW480 cell line. Briefly, cell lysates from SW480 cells that were either treated with 5FU or were controls were separated using 2DE. After staining and analysis of the gels, differentially expressed protein spots were excised and identified using MS. The upregulation of heat-shock protein (Hsp)-27 and peroxiredoxin 6 and the downregulation of Hsp-70 were successfully validated by immunohistochemical (IHC) staining of SW480 cells.[9]

The 2D DIGE method improved the 2DE technique. Figure 1 shows how two different protein samples (e.g., control and disease) and, optionally, one reference sample (e.g., control and disease pooled together) are labeled with one of three spectrally different fluorophores: cyanine (Cy)2, 3 or 5. They have the same charge, similar molecular weight and distinct fluorescent properties, allowing their discrimination during fluorometric scanning.[10-12]  The minimal dye causes minimal change in the electrophoretic mobility pattern of the protein, whereas the saturation dye labels all available cysteine residues but causes a shift in electrophoretic mobility labeled proteins.[13]  The same pooled reference sample used for all gels within an experiment is an internal reference for normalization and spot matching.[12] The gel is scanned at three different wavelengths yielding images for each of the different samples, and variation between gels is minimized and difficulties are reduced in correctly matching of protein spots across different gels.[10,11]  Significant advantages of the DIGE technology includes a dynamic range of over four orders of magnitude and full compatibility with MS.  However, careful validations of identified markers using alternative techniques are still needed.

In a study that compared three commonly used DIGE analysis software packages, Kang et al. concluded that although the three softwares performed satisfactorily with minimal user intervention, significant improvements in the accuracy of analysis could be achieved .[14] Moreover, it was suggested that results concerning the magnitude of differential expression between protein spots after statistical analysis by such softwares must be examined with care.[14]

Figure 1.  Procedures for performing a 2D DIGE experiment. CY: Cyanine; DIGE: Differential in gel electrophoresis.

The choice of appropriate statistical methods for the analysis of DIGE data has to be considered. Statistical methodological error can be addressed by the use of statistical methods that apply a false-discovery rate (FDR) for the determination of significance. In this method, q-values are calculated for all protein spots. The q-value of each spot corresponds to the expected proportion of false-positives incurred by a change in expression level of that protein spot found to be significant.

Despite the ease of use and enabling the researcher to select an appropriate FDR according to study requirements, this approach was found to be only applicable to DIGE experiments using a two-dye labeling scheme, as a three-dye labeling approach violated the assumption of data independence required for statistical analysis.[16] Other statistical tests that have been applied for the analysis of DIGE results include significance analysis of microarrays,[7] principal components analysis[17,18] and partial least squares discriminant analysis.[18,19] Detailed discussions of the different statistical approaches applicable to proteomic research are beyond the scope of this review and readers may refer to[18,20] for further reading.

Using 2D DIGE, Yu et al. successfully identified biomarkers that were associated with pancreatic cancer.[21] In the study, 24 upregulated and 17 downregulated proteins were identified by MS. Among those proteins, upregulation of apolipoprotein E, α-1-antichymotrypsin and inter-α-trypsin inhibitor were confirmed by western blot analysis. Furthermore, the association of those three proteins with pancreatic cancer was successfully validated in another series of 20 serum samples from pancreatic cancer patients. Using a similar approach, Huang et al. identified and confirmed the upregulation of transferrin in the sera of patients with breast cancer.[22] When Sun et al. compared the proteomic profiles between malignant and adjacent benign tissue samples from patients with hepatocellular carcinoma, they proved 2D DIGE is not limited to serum or plasma samples.[23] In their study, overexpression of Hsp70/Hsp90-organizing protein and heterogenous nuclear ribonucleoproteins C1 and C2 were identified by 2D DIGE coupled with MS analysis, and the findings were successfully validated by both western blotting and IHC staining. Next, Kondo et al. applied 2D DIGE to laser-microdissected cells from fresh patient tissues.[13] Using this protocol, a 1-mm area of an 8-12-µm-thick tissue section was shown to be sufficient. These examples demonstrate the high sensitivity and broad applicability of 2D DIGE for proteomic investigations using various types of patient samples and provide evidence that 2D DIGE is a powerful technique for biomarker discovery.

MALDI Imaging Mass Spectrometry

A deeper understanding of the complex biochemical processes occurring within tumor cells and tissues requires a knowledge of the spatial and temporal expression of individual proteins. Currently, such information is mainly obtained by IHC staining for specific proteins in patient tissues.[8,24,25] Nevertheless, IHC has limited use in high-throughput proteomic biomarker discovery because only a few proteins can be immunostained simultaneously. MALDI IMS allows researchers to analyze proteomic expression profiles directly from patient tissue sections.[26-28] The protocol begins with mounting a tissue section onto a sample plate (Figure 2). MALDI matrix is then applied onto the tissue sample, which is analyzed by MALDI MS in order to obtain mass spectra from predefined locations across the entire patient tissue section. The mass spectrum from each location is a complete proteomic profile for that particular area. All acquired mass spectra from the entire tissue are then compiled to create a 2D map for that tissue sample. This map could then be compared with those from other tissue samples to identify changes in protein or peptide expression or comparisons of the maps from different areas within the same tissue section could be performed. This technology  importantly allows the high-throughput discovery of novel protein markers. In addition, correlations between protein expression and tissue histology can also be studied easily.

Most studies using MALDI IMS have been performed on frozen tissue sections ranging from 5 to 20 µm in thickness.[26,27,29] After sectioning, a MALDI matrix is applied either by automated spraying or spotting. The matrix of choice is usually α-cyano-4-hydroxy-cinnamic acid for peptides and sinapinic acid (3,5-dimethoxy-4-hydroxycinnamic acid) for proteins.

Figure 2.  Procedures for MALDI imaging. IMS: Imaging mass spectrometry; MS: Mass spectrometry.

Spotting allows the precise application of matrix to areas of interest and minimizes the diffusion of analyte material across the sample, although the imaging resolution achieved by spotting is lower (~150 µm). A laser beam is then fired towards the area of interest on the tissue section to generate protein ions for analysis by a mass analyzer.[29] Among the different mass analyzers, TOF analyzers are the most commonly used owing to their high sensitivity, broad mass range and suitability for detection of ions generated by MALDI. Use of other mass analyzers such as TOF-TOF, quadrupole TOF (QTOF), ion traps (ITs) and Fourier transform-ion cyclotron resonance (FT-ICR) have also been reported in other studies.[30-33]

After obtaining the mass spectra, statistical analysis needs to be performed to identify statistically significant features that could have potential use as biomarkers. But before such analyses can be applied, there has to be background-noise subtraction, spectral normalization and spectral alignment.[34,35,34] Statistical methods used to identify significant differences in peak intensity are symbolic discriminant analysis and principal component analysis. Symbolic discriminant analysis determines discriminatory features and builds functions based on such features for distinguishing samples according to their classification.[36,37] Using this approach, Lemaire et al. found a putative proteomic biomarker from ovarian cancer tissues by MALDI IMS that was later identified to be the Reg-α protein, a member of the proteasome activator 11S.[37] This result was later successfully validated by western blot (protein expression found in 88.8% carcinoma cases vs 18.7% benign disease) and IHC (protein expression found in 63.6% carcinoma tissues vs 16.6% benign tissues).[37] On the other hand, principal component analysis reduces data complexity by transforming data based on peak intensities to information based on data variance, termed ‘principal components’, resulting in a list of significant peaks (principal components) ordered by decreasing variance.[35,38,39] Neither symbolic discriminant analysis or principal component analysis is capable of performing unsupervised classification. This aim requires the use of other methods such as hierarchical clustering.[39,40] In this method identified peaks are clustered as nodes in a pair-wise manner according to similarity until a dendogram is obtained, providing information as to the degree of association of all peak masses in a hierarchical fashion. Peaks that are capable of differentiating between different histological/pathological features could then be chosen for further validation of their value as tumor markers.[39]

In MALDI IMS, protein identification cannot be performed with confidence solely on the molecular weight. However, Groseclose et al. have developed a method using in situ digestion of proteins directly on tissue section.[41] They first used MALDI IMS to obtain a map of the protein and peptide spectra, then spotted a consecutive section of the same tissue sample with trypsin for protein digestion, and then spotted matrix solution onto the digested spots and the resulting peptides are identified directly from the tissue by MS/MS. This modification increases the confidence in protein identification. The time required for MALDI IMS analysis per tissue section is as follows: tissue sectioning, mounting and matrix application: 4-8 h; MALDI image acquisition: 1-2 days; spectral analysis: 1-2 h.[33,39]

Recently, in situ enzymatic digestion has been successfully applied for improving the retrieval of peptides directly from formalin-fixed, paraffin-embedded FFPE tissue samples.[27] Such development has greatly facilitated the application of MALDI IMS in FFPE tissues.[26,42] In fact, Stauber et al. identified the downregulation of ubiquitin, transelongation factor 1, hexokinase and neurofilament M from FFPE brain tissues of rat models of Parkinson disease using this modified technique.[42] The success of performing proteomic profiling using MALDI IMS directly on FFPE tissues opens up great possibility for using archival patient materials in high-throughput biomarker discovery. Novel cancer biomarkers identified using MALDI IMS still require validation by other techniques such as IHC.

Electron Transfer Dissociation MS

Post-translational modifications play important roles in the structure and function of proteins such as protein folding, protein localization, regulation of protein activity and mediation of protein-protein interaction. Two common forms of PTM that have been implicated in cancer development are phosphorylation and glycosylation. Previously, phosphoproteomic studies have led to the identification of novel tyrosine kinase substrates in breast cancer,[43] discovery of novel therapeutic targets for brain cancer[44] and increased understanding of signaling pathways involved in lung cancer formation.[45,46] Conversely, the identification of abnormally glycosylated proteins, such as mucins, has provided novel biomarkers and therapeutic targets for ovarian cancer.[47]

The study of PTM begins with digesting the target protein using enzymes such as trypsin,   introducing the fragments into MS for determination of the sites and types of modification and, at the same time, identification of the protein. The analysis is conventionally carried out using collision-induced dissociation (CID) MS, where peptides are collided with a neutral gas for cleavage of peptide bonds to produce b- and y-type ions (Figure 3). A complete series of peptides differing in length by one amino acid is produced, leading to identification of the protein by peptide-sequence determination. However, for phosphopeptides, the presence of phosphate groups would compete with the peptide backbone as the preferred cleavage site. The end result is a reduced set of peptide fragments, which hinders protein identification, and the exact location of the phosphate group on the peptide cannot be determined accurately when there are more than one possible phosphorylation sites.[48,49]

Figure 3.  Peptide bond-cleavage site for a-, b-, c-, x-, y– and z-type ions.

Electron transfer dissociation is a recently developed dissociation technique for the analysis of peptides by MS, utilizing radiofrequency quadrupole ion traps such as 2D linear IT, spherical IT and Orbitrap™ (Thermo Fisher Scientific Inc., MA, USA) mass analyzers.[48,49] In this technology, peptides are fragmented by transfer of electrons from anions to induce cleavage of Cα-N bonds along the peptide backbone, hence producing c- and z-type ions (Figure 3). In contrast to CID, ETD preserves the localization of labile PTM and also provides peptide-sequence information.[48] But ETD fails to fragment peptide bonds adjacent to proline, which are readily cleaved by CID.[50] A study that compared the performance of CID with that of ETD found that only 12% of the identified peptides were commonly detected between the two techniques. A study reported that CID successfully identified more peptides with charge states of +2 and below, whereas ETD was found to be better at identifying peptide ions with charge states of greater than +2.[51] Therefore, it is suggested that CID and ETD should be used together to complement each other.[52]  Han et al. successfully differentiated the isobaric amino acids isoleucine and leucine from one another by performing CID on the resulting z-ions after ETD. The presence of isoleucine residue was then confirmed by the detection of a specific 29-Da loss from the peptide.[53]  A clear advantage of using ETD for the analysis of phosphopeptides is a near complete series of c- and z-ions without loss of phosphoric acid,[48] greatly facilitating the determination of the phosphorylation sites and the identification of phosphopeptides. Recently, an analysis of yeast phosphoproteome using ETD successfully identified 1252 phosphorylation sites on 629 proteins, whose expression levels ranged from less than 50 to 1,200,000 copies per cell.[54] In another study using ETD, a total of 1435 phosphorylation sites were identified from human embryonic kidney 293T cells, of which 1141 (80%) were previously unidentified. Finally, a study by Molina et al. successfully identified 80% of the known phosphorylation sites in more than 1000 yeast phosphopeptides in one single study using a combination of ETD and CID.[55] In addition, ETD could be applied to investigate other forms of PTM, such as N-linked glycosylations.[56,57] N-linked glycans contain a common core with branched structures. These can be processed by stepwise addition or removal of monosaccharide residues linked by glycosidic bonds, producing highly varied forms of N-linked glycan structures.[58-60] A weakness of analyzing glycopeptides using CID is that cleavage of glycosidic bonds occurs with little peptide backbone fragmentation, so that only the glycan structure is available.[61]  Hogan et al. used CID and ETD together to overcome this problem determining the glycan structure and glycosylation site.[61] ICID was initially used for cleavage of glycosidic bonds that allowed the entire glycan structure to be inferred from the CID spectrum alone. ETD was later performed to dissociate the same peptide that resulted in a contiguous series of fragment ions with no loss of glycan molecules, allowing the identification of both the site of glycosylation and the identity of the glycoprotein.[61] Readers are strongly encouraged to refer to[49] and.[62] In a comprehensive comparison of CID versus ETD for the identification of peptides without PTMs, CID was found to identify 50% more peptides than ETD (3518 by CID vs 2235 by ETD), but ETD provided somewhat better sequence coverage (67% for CID vs 82% for ETD). It turns out that ETD produced more uniformly fragmented ions with intensities that were five- to ten-times lower than those produced by CID.[55] Finally, the best sequence coverage of up to 92% was achieved when consecutive CID and ETD were performed.[55]

This increase in sequence coverage using the combined approach is needed for studies requiring de novo peptide identifications. As such, this strategy is particularly suited for studies involved in the discovery, identification and characterization of novel peptides or proteins and their PTMs for biomarker use. A prerequisite of this technique is that the biological samples under investigation must undergo some form of fractionation before they are amenable to analysis by ETD or CID. This is achieved by the use of LC techniques, such as reverse-phase, strong cation exchange or strong anion exchange chromatography, and serves to reduce the complexity and wide dynamic range of protein-expression levels commonly found in biological specimens. Given the important roles of PTM in the function and activity of proteins, this technology paves the way for exploring the intricate cellular activities within a cancer cell.

References

  1. Duffy MJ, van Dalen A, Haglund C et al. Tumor markers in colorectal caner: European Group on Tumor Markers (EGTM) guidelines for clinical use. Eur. J. Cancer 43(9),1348-1360 (2007).
  2. Duffy MJ. Role of tumor markers in patients with solid cancers: a critical review. Eur. J. Intern. Med. 18(3),175-184 (2007).
  3. Bertucci F, Birnbaum D, Goncalves A. Proteomics of breast cancer: principles and potential clinical applications. Mol. Cell. Proteomics 5(10),1772-1786 (2006).
  4. Feng JT, Shang S, Beretta L. Proteomics for the early detection and treatment of hepatocellular carcinoma. Oncogene 25(27),3810-3817 (2006).
  5. Miller I, Crawford J, Gianazza E. Protein stains for proteomic applications: which, when, why? Proteomics 6(20),5385-5408 (2006).
  6. Kumarathasan P, Mohottalage S, Goegan P, Vincent R. An optimized protein in-gel digest method for reliable proteome characterization by MALDI-TOF-MS analysis. Anal. Biochem. 346(1),85-89 (2005).
  7. Meunier B, Bouley J, Piec I, Bernard C, Picard B, Hocquette JF. Data analysis methods for detection of differential protein expression in two-dimensional gel electrophoresis. Anal. Biochem. 340(2),226-230 (2005).
  8. Chan CM, Wong SC, Lam MY et al. Proteomic comparison of nasopharyngeal cancer cell lines C666-1 and NP69 identifies down-regulation of annexin II and ß2-tubulin for nasopharyngeal carcinoma. Arch. Pathol. Lab. Med. 132(4),675-683 (2008).
  9. Wong SC, Wong VW, Chan CM et al. Identification of 5-fluorouracil response proteins in colorectal carcinoma cell line SW480 by two-dimensional electrophoresis and MALDI-TOF mass spectrometry. Oncol. Rep. 20(1),89-98 (2008).
  10. Marouga R, David S, Hawkins E. The development of the DIGE system: 2D fluorescence difference gel analysis technology. Anal. BioAnal. Chem. 382(3),669-678 (2005).
  11. Timms JF, Cramer R. Difference gel electrophoresis. Proteomics 8(23-24),4886-4897 (2008).
  12. Minden J. Comparative proteomics and difference gel electrophoresis. Biotechniques 43(6),739-745 (2007).
  13. Kondo T, Hirohashi S. Application of highly sensitive fluorescent dyes (CyDye DIGE Fluor saturation dyes) to laser microdissection and two-dimensional difference gel electrophoresis (2D-DIGE) for cancer proteomics. Nat. Protoc. 1(6),2940-2986 (2007).
  14. Kang Y, Techanukul T, Mantalaris A, Nagy JM. Comparison of three commercially available DIGE analysis software packages: minimal user intervention in gel-based proteomics. J. Proteome Res. 8(2),1077-1084 (2009).
  15. Kreil DP, Karp NA, Lilley KS. DNA microarray normalization methods can remove bias from differential protein expression analysis of 2D difference gel electrophoresis results. Bioinformatics 20(13),2026-2034 (2004).
  16. Karp NA, McCormick PS, Russell MR, Lilley KS. Experimental and statistical considerations to avoid false conclusions in proteomics studies using differential in-gel electrophoresis. Mol. Cell. Proteomics 6(8),1354-1364 (2007).
  17. Kleno TG, Leonardsen LR, Kjeldal HØ, Laursen SM, Jensen ON, Baunsgaard D. Mechanisms of hydrazine toxicity in rat liver investigated by proteomics and multivariate data analysis. Proteomics 4(3),868-880 (2004).
  18. Smit S, Hoefsloot HCJ, Smilde AK. Statistical data processing in clinical proteomics. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 866(1-2),77-88 (2008).
  19. Karp NA, Griffin JL, Lilley KS. Application of partial least squares discriminant analysis to two-dimensional difference gel studies in expression proteomics. Proteomics 5(1),81-90 (2005).
  20. Grove H, Jørgensen BM, Jessen F et al. Combination of statistical approaches for analysis of 2-DE data gives complementary results. J. Proteome Res. 7(12),5119-5124 (2008).
  21. Yu KH, Rustgi AK, Blair IA. Characterization of proteins in human pancreatic serum using differential gel electrophoresis and tandem mass spectrometry. J. Proteome Res. 4(5),1742-1751 (2005).
  22. Huang H-L, Stasyk T, Morandell S et al. Biomarker discovery in breast cancer serum using 2-D differential gel electrophoresis/MALDI-TOF/TOF and data validation by routine clinical assays. Electrophoresis 27(8),1641-1650 (2006).
  23. Sun W, Xing B, Sun Y et al. Proteome analysis of hepatocellular carcinoma by two-dimensional difference gel electrophoresis. Mol. Cell. Proteomics 6(10),1798-1808 (2007).
    •• Presents a very detailed account of the procedures for 2D difference gel electrophoresis analysis.
  24. Wong SC, Chan AT, Chan JK, Lo YM. Nuclear ß-catenin and Ki-67 expression in chriocarcinoma and its pre-malignant form. J. Clin. Pathol. 59(4),387-392 (2006).
  25. Chan CM, Ma BB, Hui EP et al. Cyclooxygenase-2 expression in advanced nasopharyngeal carcinoma: a prognostic evaluation and correlation with hypoxia inducible factor 1 α and vascular endothelial growth factor. Oral Oncol. 43(4),373-378 (2007).
  26. Groseclose MR, Massion PP, Chaurand P, Caprioli RM. High throughput proteomic analysis of formalin-fixed paraffin embedded tissue microarrays using MALDI imaging mass spectrometry. Proteomics 8(18),3715-3724 (2008).
  27. Lemaire R, Desmons A, Tabet JC, Day R, Salzet M, Fournier I. Direct analysis and MALDI imaging of formalin-fixed, paraffin-embedded tissue sections. J. Proteome Res. 6(4),1295-1305 (2007).
    •• Provides a detailed account of procedures for the analysis of paraffin-embedded tissue sections using MALDI imaging mass spectrometry (MS).
  28. Meistermann H, Norris JL, Aerni HR et al. Biomarker discovery by imaging mass spectrometry: transthyretin is a biomarker for gentamicin-induced nephrotoxicity in rat. Mol. Cell Proteomics 5(10),1876-1886 (2006).
  29. Cornett DS, Reyzer ML, Chaurand P, Caprioli RM. MALDI imaging mass spectrometry: molecular snapshots of biochemical systems. Nat. Methods 4(10),828-823 (2007).
    •• Excellent review on the application of MALDI imaging MS for studying biological systems.
  30. Shimma S, Sugiura Y, Hayasaka T, Zaima N, Matsumoto M, Setou M. Mass imaging and identification of biomolecules with MALDI-QIT-TOF-based system. Anal. Chem. 80(3),878-885 (2008).
  31. Taban IM, Altelaar AFM, van der Burgt YEM et al. Imaging of peptides in the rat brain using MALDI-FTICR mass spectrometry. J. Am. Soc. Mass Spectrom. 18(1),145-151 (2007).
  32. Hsieh Y, Casale R, Fukuda E et al. Matrix-assisted laser desorption/ionization imaging mass spectrometry for direct measurement of clozapine in rat brain tissue. Rapid Commun. Mass Spectrom. 20(6),965-972 (2006).
  33. Goodwin RJA, Penington SR, Pitt AR. Protein and peptides in pictures: imaging with MALDI mass spectrometry. Proteomics 8(18),3785-3800 (2008).
  34. Chaurand P, Norris JL, Cornett DS, Mobley JA, Caprioli RM. New developments in profiling and imaging of proteins from tissue sections by MALDI mass spectrometry. J. Proteome Res. 5(11),2889-2900 (2006).
  35. Yao I, Sugiura Y, Matsumoto M, Setou M. In situ proteomics with imaging mass spectrometry and principal component analysis in the Scrapper-knockout mouse brain. Proteomics 8(18),3692-3701 (2008).
  36. Schwartz SA, Weil RJ, Thompson RC et al. Proteomic-based prognosis of brain tumor patients using direct-tissue matrix-assisted laser desorption ionization mass spectrometry. Cancer Res. 65(17),7674-7681 (2005).
  37. Lemaire R, Menguellet SA, Stauber J et al. Specific MALDI imaging and profiling for biomarler hunting and validation: fragment of the 11S proteasome activator complex, Reg α fragment, is a new potential ovary cancer biomarker. J. Proteome Res. 6(11),4127-4134 (2007).
  38. Walch A, Rauser S, Deninger SO, Höfler H. MALDI imaging mass spectrometry for direct tissue analysis: a new frontier for molecular histology. Histochem. Cell Biol. 130(3),421-434 (2008).
  39. Deninger SO, Ebert MP, Fütterer A, Gerhard M, Röcken C. MALDI imaging combined with hierarchical clustering as a new tool for the interpretation of complex human cancers. J. Proteome Res. 7(12),5230-5236 (2008).
  40. McCombie G, Staab D, Stoeckli M, Knochenmuss R. Spatial and spectral correlations in MALDI mass spectrometry images by clustering and multivariate analysis. Anal. Chem. 77(19),6118-6124 (2005).
  41. Groseclose MR, Andersson M, Hardesty WM et al. Identification of proteins directly from tissue: in situ tryptic digestions coupled with imaging mass spectrometry. J. Mass Spectrom. 42(2),254-262 (2007).
    • First report of protein identification performed directly from tissue sections.
  42. Stauber J, Lemaire R, Franck J et al. MALDI imaging of formalin-fixed paraffin-embedded tissues: application to model animals of Parkinson disease for biomarker hunting. J. Proteome Res. 7(3),969-978 (2008).
  43. Chen Y, Choong LY, Lin Q et al. Differential expression of novel tyrosine kinase substrates during breast cancer development. Mol. Cell Proteomics 6(12),2072-2087 (2007).
  44. Huang PY, Cavenee WK, Furnari FB, White FM. Uncovering therapeutic targets for glioblastoma: a systems biology approach. Cell Cycle 6(22),2750-2754 (2007).
  45. Guha U, Chaerkady R, Marimuthu A et al. Comparisons of tyrosine phosphorylated proteins in cells expressing lung cancer-specific alleles of EGFR and KRAS. Proc. Natl Acad. Sci. USA 105(37),14112-14117 (2008).
  46. Rikova K, Guo A, Zeng Q et al. Global survey of phosphotyrosine signaling identifies oncogenic kinases in lung cancer. Cell 131(6),1190-1203 (2007).
  47. Singh AP, Senapati S, Ponnusamy MP et al. Clinical potential of mucins in diagnosis, prognosis, and therapy of ovarian cancer. Lancet Oncol. 9(11),1076-1085 (2008).
  48. Syka JEP, Coon JJ, Schroeder MJ, Shabanowitz J, Hunt DF. Peptide and protein sequence analysis by electron transfer dissociation mass spectrometry. Proc. Natl Acad. Sci. USA 101(26),9528-9533 (2004).
    • First report of the application of electron transfer dissociation MS for the analysis of peptides and proteins.
  49. Wiesner J, Premsler T, Sickmann A. Application of electron transfer dissociation (ETD) for the analysis of posttranslational modifications. Proteomics 8(21),4466-4483 (2008).
  50. Hayakawa S, Hashimoto M, Matsubara H, Turecek F. Dissecting the proline effect: dissociations of proline radicals formed by electron transfer to protonated Pro-Gly and Gly-Pro dipeptides in the gas phase. J. Am. Chem. Soc. 129(25),7936-7949 (2007).
  51. Good DM, Wirtala M, McAlister GC, Coon JJ. Performance characteristics of electron transfer dissociation mass spectrometry. Mol. Cell Proteomics 6(11),1942-1951 (2007).
  52. Han H, Xia Y, Yang M, McLuckey SA. Rapidly alternating transmission mode electron-transfer dissociation and collisional activation for the characterization of polypeptide ions. Anal. Chem. 80(9),3492-3497 (2008).
  53. Han H, Xia Y, McLuckey SA. Ion trap collisional activation of c and z ions formed via gas-phase ion/ion electron-transfer dissociation. J. Proteome Res. 6(8),3062-3069 (2007).
  54. Chi A, Huttenhower C, Geer LY et al. Analysis of phosphorylation sites on proteins from Saccharomyces cerevisiae by electron transfer dissociation (ETD) mass spectrometry. Proc. Natl Acad. Sci. USA 104(7),2193-2198 (2007).
  55. Molina H, Matthiesen R, Kandasamy K, Pandey A. Comprehensive comparison of collision induced dissociation and electron transfer dissociation. Anal. Chem. 80(13),4825-4835 (2008).
    • Study comparing the characteristics of peptide fragmentation performed by collision-induced dissociation with that of electron transfer dissociation.
  56. Catalina MI, Koeleman CAM, Deelder AM, Wuhrer M. Electron transfer dissociation of N-glycopeptides: loss of the entire N-glycosylated asparagine side chain. Rapid Commun. Mass Spectrom. 21(6),1053-1061 (2007).
  57. Abbott KL, Aoki K, Lim JM et al. Targeted glycoproteomic identification of biomarkers for human breast carcinoma. J. Proteome Res. 7(4),1470-1480 (2008).
  58. Yan A, Lennarz WJ. Unraveling the mechanism of protein N-glycosylation. J. Biol. Chem. 280(5),3121-3124 (2005).
  59. Danielle H, Bertozzi CR. Glycans in cancer and inflammation – potential for therapeutics and diagnostics. Nat. Rev. Drug Discov. 4(6),477-488 (2005).
  60. Morelle W, Canis K, Chirat F, Faid V, Michalski J-C. The use of mass spectrometry for the proteomic analysis of glycosylation. Proteomics 6(14),3993-4015 (2006).
  61. Hogan JM, Pitteri SJ, Chrisman PA, McLuckey SA. Complementary structural information from a tryptic N-linked glycopeptide via electron transfer ion/ion reactions and collision induced dissociation. J. Proteome Res. 4(2),628-632 (2005).
  62. Mikesh LM, Ueberheide B, Chi A et al. The utility of ETD mass spectrometry in proteomic analysis. Biochim. Biophys. Acta 1764(12),1811-1822 (2006).

Advanced Proteomic Technologies for Cancer Biomarker Discovery

Part II

Reverse-phase Protein Array

One of the goals of proteomics is to identify protein changes associated with the development of diseases such as cancer.  Even with the rapid development of proteomic technologies during the past few years, analysis of patient samples is still a challenge. Difficulties arise from the fact that[63,64]:

  • Proteomic patterns differ among cell types;
  • Protein expression changes occur over time;
  • Proteins have a broad dynamic range of expression levels spanning several orders of magnitude;
  • Proteins can be present in multiple forms, such as polymorphisms and splice variants;
  • Traditional proteomic methods require relatively large amounts of protein
  • Many proteomic technologies cannot be used to study protein-protein interactions.

The principle of RPA is simple and involves the spotting of patient samples in an array format onto a nitrocellulose support (Figure 4). Hundreds of patient specimens can be spotted onto an array, allowing a comparison of a large number of samples at once.[65] Each array is incubated with one particular antibody, and signal intensity proportional to the amount of analyte in the sample spot is generated.[66] Signal detection is commonly performed by fluorescence, chemiluminescence or colorimetric methods. The results are quantified by scanning and analyzed by softwares such as P-SCAN and ProteinScan, which can be downloaded from[84] for free.[67,68]

Figure 4.  Principle of reverse-phase protein array.

Main advantages of RPA technology include[69-71]:

  • Various types of biological samples can be used;
  • The possibility of investigating PTMs;
  • Protein-protein interactions can be studied;
  • Labeling of patient samples with fluorescent dyes (e.g., 2D DIGE) or mass tags (e.g., isotope-coded affinity tag [ICAT]) are not required;
  • Any samples spotted as a dilution allows quantifying in the linear range of detection;
  • Quantitative measurement of any protein is possible compared to reference standards of known amounts on the same array.

It has been shown that RPA is extremely sensitive as it is capable of detecting up to zeptomole (1 x 10-21 mole) levels of target proteins with less than 10% variance. The analysis of few cell signaling events is known.[65,70,71] The assay sensitivity depends on antibody affinity, which depends upon antigen-antibody pairs.[68] Of course, only known proteins with available antibodies can be identified. Therefore, this method is more suitable for biomarker screening or validation than discovery of novel proteins. To assist researchers in selecting suitable antibodies, two open antibody databases show their western blot results using cell lysates.[72,73,85,86]

One application of RPA is to investigate the signaling pathways in human cancers. Zha et al. compared the survival signaling events between Bcl 2-positive and -negative lymphomas and found that survival signals, independent of Bcl 2 expression, were detected in follicular lymphoma and confirmed by validation with IHC.[71] In another study, patient-specific signaling pathways have been identified in breast cancers using RPA. Bayesian clustering of a set of 54 subjects successfully separated normal subjects from cancer patients based on an epithelial signaling signature. Principal component analysis was capable of distinguishing normal from cancer patient samples by using a signature composed of a panel of kinase substrates.[69] Differences in cell signaling between patient-matched primary and metastatic lesions have also been found using RPA. In the study, six patient-matched primary ovarian tumors probed with antibodies against signaling proteins, and the signaling profiles differed significantly between primary and metastatic tumors and upregulation of phosphor c-kit was capable of distinguishing five of the six metastatic tumors from the primary lesions.[70] These findings suggest that treatment strategies may need to target signaling events among disseminated tumor cells.

Reverse-phase protein array has also been used to validate mathematical models of cellular pathways. The p53-Mdm2 feedback loop is one of the most well-studied cellular-feedback mechanisms.[74] Normally, p53 activates transcription and expression of Mdm2, which, in turn, suppresses p53 activity. This negative-feedback loop ensures the low-level expression of p53 under normal conditions. Mathematical models have previously been used to investigate this negative-feedback loop.[67] Ramalingam et al. has shown, by using RPA, that part of the mechanism of the p53-Mdm2 feedback loop can be explained by current mathematical models.[75]

Another important application of RPA is for the identification of cancer specific antigens.  Using this method serum from 14 lung cancer patients, colon cancer patients and normal subjects were incubated and eight fractions of the cell lysate were recognized by the sera from four patients, while none of the sera from normal individuals was positive.[76] This study demonstrates the diagnostic potential of identifying cancer antigens that induce immune response in cancer patients by using RPA.

Expert Commentary and Five-year View

The development of 2D DIGE in the past few years has provided researchers with a more accurate method for relative quantification of proteins substantially reducing the number of replicates required for 2D gels and increased its applicability for high-throughput biomarker discovery. MALDI MS has immensely facilitated the direct discovery of biomarkers from patient tissue. Even though archival patient tissue samples are a potential source of materials for tumor marker research, high-throughput techniques for biomarker discovery using such samples has been problematic. With the development of MALDI IMS, investigators can now perform studies that aim to discover novel biomarkers directly from tissue sections and are able to correlate their expression with the histopathological changes of tumors. Previously, investigation into the sites of protein PTM has been difficult since MS-dissociation techniques, such as CID, would lead to preferential loss of PTM, but the use of ETD as a complementary peptide ion-dissociation method has allowed researchers to investigate the precise location and structure of the PTM, and to identify peptide sequence with higher confidence.

The rapid technological improvements in proteomic technologies will identify potential biomarkers for clinical use. Independent validation studies using clinical specimens must be performed before such markers can be applied clinically,. In this regard, RPA has added a potential for high-throughput screening or validation of newly found markers. Using this technique, it will be possible for researchers to quantitatively measure and validate novel markers on hundreds of patient samples simultaneously.

A big problem for proteomic researchers iincludes the abundance of proteins in biological samples. This could be partially solved by depletion of abundant proteins or by fractionation of protein samples according to characteristics. It is envisaged that, in the future, proteomic technologies will be developed to a stage that is capable of analyzing complex protein mixtures without preparatory fractionation. Such progress has recently been achieved in LC-MS, where the use of a high-field, asymmetric waveform, ion-mobility spectrometry device as an interface to an IT MS resulted in a more than fivefold increase in dynamic range without increasing the length of the LC-MS analysis.[77]

Another area that needs improvement is the standardization of protocols for patient-sample collection because results were found to be inconsistent among various studies using MS.[78] It is also considered that part of the reason for this inconsistency is due to the differences in sample-collection or sample-handling procedures.[78,79] The Human Proteome Organization previously published its findings on pre-analytical factors that affect plasma proteomic patterns and provides suggestions for sample handling.[80,81] In addition to the pre-analytical stages, it is imperative to stress that consistent and strict adherence to predefined procedures or standards, from sample collection, sample processing, experimentation, data analysis through to result validation, are of utmost importance to minimize variations and achieve consistent and reproducible results.

Any newly identified potential biomarker must also be validated using an independent cohort of patients in order to establish its clinical value, but the translation of results from the laboratory to the clinic has been slow. Consequently, it has been suggested that quantitative MS could be used for the detection of proteins.[82] The increasing availability of MS facilities to researchers worldwide will facilitate the detection, measurement and validation of protein biomarkers using quantitative MS techniques. Even after validation of such results in the laboratory, diagnostic tests will need to be developed for the marker and large-scale clinical trials would also have to be performed to confirm the results.  All these efforts require cooperation of personnel from various disciplines, such as scientists, medical professionals, pharmaceutical companies and governments. Finally, it is hoped that, through improved understanding of the protein expression as cancer progresses will lead to the discovery and development of useful cancer biomarkers for patient diagnosis, prognosis, monitoring and treatment.

Key Issues

  • 2DE coupled with mass spectrometry has been the main workhorse for the proteomic discovery of novel biomarkers in the past 10 years, and the development of 2D difference gel electrophoresis has substantially improved the quantification accuracy of 2DE.
  • MALDI imaging mass spectrometry has allowed the identification of novel proteomic features directly from patient tissue section for correlation with histopathological changes.
  • Electron transfer dissociation mass spectrometry has opened up the possibility of identifying the structure and localization of the post-translational modification and the peptide/protein.
  • Reverse-phase protein array is a powerful tool for the high-throughput validation of novel biomarkers across hundreds of patient samples simultaneously.

References

63.  States DJ, Omenn GS, Blackwell TW et al. Challenges in deriving high-confidence protein identifications from data gathered by a HUPO plasma proteome collaborative study. Nat. Biotechnol. 24(3),333-338 (2006).

64. Wulfkuhle JD, Edmiston KH, Liotta LA, Petricoin EF 3rd. Technology insight: pharmacoproteomics for cancer – promises of patient-tailored medicine using protein microarrays. Nat. Clin. Pract. Oncol. 3(5),256-268 (2006).

•• Excellent review on the clinical application of reverse-phase protein array.

65. Tibes R, Qiu Y, Lu Y et al. Reverse phase protein array: validation of a novel proteomic technology and utility for analysis of primary leukemia specimens and hematopoietic stem cells. Mol. Cancer Ther. 5(10),2512-2521 (2006).

66. LaBaer J, Ramachandran N. Protein microarrays as tools for functional proteomics. Curr. Opin. Chem. Biol. 9(1),14-19 (2005).

67. Ramalingam S, Honkanen P, Young L et al. Quantitative assessment of the p53-Mdm2 feedback loop using protein lysate microarrays. Cancer Res. 67(13),6247-6252 (2007).

68. Nishizuka S, Ramalingam S, Spurrier B et al. Quantitative protein network monitoring in response to DNA damage. J. Proteome Res. 7(2),803-808 (2008).

69. Petricoin EF 3rd, Bichsel VE, Calvert VS et al. Mapping molecular networks using proteomics: a vision for patient-tailored combination therapy. J. Clin. Oncol. 23(15),3614-3621 (2005).

70. Sheehan KM, Calvert VS, Kay EW et al. Use of reverse-phase protein microarrays and reference standard development for molecular network analysis of metastatic ovarian carcinoma. Mol. Cell Proteomics 4(4),346-355 (2005).

71. Zha H, Raffled M, Charboneau L et al. Similarities of prosurvival signals in Bcl 2-positive and Bcl 2-negative follicular lymphomas identified by reverse phase protein microarray. Lab. Invest. 84(2),235-244 (2004).

72. Major SM, Nishizuka S, Morita D et al. AbMiner: a bioinformatic resource on available monoclonal antibodies and corresponding gene identifiers for genomic, proteomic, and immunologic studies. BMC Bioinformatics 7,192 (2006).

73. Spurrier B, Washburn FL, Asin S, Ramalingam S, Nishizuka S. Antibody screening database for protein kinetic modeling. Proteomics 7(18),3259-3263 (2007).

74. Ciliberto A, Novak B, Tyson JJ. Steady states and oscillations in the p53/Mdm2 network. Cell Cycle 4(3),488-493 (2005).

75. Ma L, Wagner J, Rice JJ, Hu W, Levine AJ, Stolovitzky GA. A plausible model for the digital response of p53 to DNA damage. Proc. Natl Acad. Sci. USA 102(40),14266-14271 (2005).

76. Madoz-Gurpide J, Kuick R, Wang H, Misek DE, Hanash SM. Integral protein microarrays for the identification of lung cancer antigens in sera that induce a humoral immune response. Mol. Cell. Proteomics 7(2),268-281 (2007).

77. Canterbury JD, Yi X, Hoopmann MR, MacCoss MJ. Assessing the dynamic range and peak capacity of nanoflow LC-FAIMS-MS on an ion trap mass spectrometer for proteomics. Anal. Chem. 80(18),6888-6897 (2008).

78. Coombes KR, Morris JS, Hu J, Edmonson SR, Baggerly KA. Serum proteomics – a young technology begins to mature. Nat. Biotechnol. 23(3),291-292 (2005).

78. Hortin GL. Can mass spectrometric protein profiling meet desired standards of clinical laboratory practice? Clin. Chem. 51(1),3-5 (2005).

79. Omenn GS, States DJ, Adamski M et al. Overview of the HUPO plasma proteome project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database. Proteomics 5(13),3226-3245 (2005).

80. Rai AJ, Gelfrand CA, Haywood BC et al. HUPO plasma proteome project specimen collection and handling: towards the standardization of parameters for plasma proteome samples. Proteomics 5(13),3262-3277 (2005).

• Concise report on several pre-analytical factors that impact the results of plasma proteomic profiling.

81. Mann M. Can proteomics retire the western blot? J. Proteome Res. 7(8),3065 (2008).

Update from LC/GC North America.

Solutions for Separation Scientists. Aug 2012; 30(8).

30 years of LCGC

www.chromatographyonline.com

The key advances in separation science is covered in five areas of the discipline:

  1. sample preparation
  2. gas chromatography(GC) columns
  3. GC instrumentation
  4. liquid cheomatography (LC) columns
  5. LC instrumentation

In the first, there is automated sample preparation in kit form (QuEChERS). A short list of automated sample preparation techniques includes: supercritical fluid extraction (SFE), microwave extraction, automated solvent extraction (ASE), and solid phase extraction (SPE). A panel of experts views the bast basic method of extraction is SPE, and one uses solid phase microextraction with direct immersion and static headspace extraction, along with liquid-liquid extraction.[2] In GC incremental improvements have been made with ionic liquids, multidimentional GC, and fast GC. LC has advanced dramatically with ultra-high pressure LC and superficially porous particles. LC-MS has become standard equipment routinely used in many labs.[1]

Biomarkers have to be detected in a background of 104-106 other components of comparable concentration that also partition with the stationary phase. The partition coefficients of many species are similar, or identical to the biomarker target. The issue is how to select and resolve fewer than 100 biomarkers from a milieu of 1 million components in a complex mixture. The novel idea is to target structure instead of general properties of molecules.[3] How might this work?  A single substrate, metabolite, hormone, or toxin is identified in milliseconds by specific protein receptors. The combinatorial chemistry community has shown that synthetic polynucleotides (aptamers) can be found and amplified that have selectivities approaching antibodies.This is a method well know for years as affinity chromatography. A distinct problem has been the natural process of post translational modification (PTMs), which may create isoforms by addition of a single phosphate ester to be found in the proverbial soup.

1. Bush L. Separation Science: Past, Present and Future. LCGC NA 2012; 30(8):620.

2.McNally ME. Analysis of the State of the Art: Sample Preparation. LCGC NA 2012; 30(8):648-651.

2. Regnier FE. Plates vs Selectivity: An Emerging Issue with Complex Samples.  LCGC NA 2012; 30(8):622.

Read Full Post »

Thyroid Cancer: The Evolution of Treatment Options.

via Thyroid Cancer: The Evolution of Treatment Options.

Read Full Post »

Author and Reporter: Anamika Sarkar, Ph.D.

Today, the gold standard treatment for cancer is still chemo therapy or radiation therapy. Drugs are administered to treat patients with different doses, frequencies and combinations. It is recognized that the side effects of all these therapies lead to DNA damage responses (DDR) and their subsequent signaling alterations resulting in cellular functions. Moreover, it is well known that DDR is responsible for complex cross talks and feedback of signaling pathways for progrowth and apoptosis within intracellular as well as extracellular networks (in tissues).

Optimal combinations of drugs in respect of doses or frequencies or order of treatments of different drugs have been recognized as a powerful method of treatment of complex diseases. However, executing experiments of multiple possible combinations of drugs and cell lines can easily lead to very costly proposition. Lee et.al in their paper published in Cell (2012), titled “Sequential Application of Anticancer Drugs Enhances Cell Death by Rewiring Apoptotic Signaling Networks”, reported from experimental results that when triple negative breast cancer (TNBC) cells are treated, with a combination of drugs  – erlotinib, which is an EGFR inhibitor, at least 4 hours before of another drug, doxorubicin – the cells show higher apoptotic (cell death) responses. Other forms of treatments like, single administration of the drugs or treating the cells together with two drugs at same time, did not show any increased levels of apoptosis in TNBC cells.

They complemented their understanding of reason behind such unique behavior of TNBC cells, when exposed to time -stagger treatment of drugs, with systems level modeling. They used quantitative analysis of high throughput reverse-phase protein microarrays and quantitative western blotting of experiments. They chose to measure activation states of 35 signaling proteins at 12 time points following exposure to ertolinib and doxorubicin individually and in combinations. The authors used PLS (Partial Least Square) and PCA (Principle Component Analysis) methods for predictive analysis from data driven model.

They report from their systems level analysis that time – stagger treatment of TNBC with two drugs ertolinib and doxorubicin activate Caspase 8, a key apoptotic signaling component, which remains absent in other combinations of treatments of drugs. They hypothesized that early treatment of ertolinib, inhibits EGFR responses, which increases levels of activated Caspase 8 and gets amplified after getting exposed to the second drug doxorubicin.

Combination therapy in treating complicated diseases like cancer has many importance in making the dose and treatment efficient. However, due to complex nature of signaling pathways, it poses increasing amount of challenges. Lee et. al., address some of those challenges by bringing in synergistic collaborations among different fields – experiments and mathematical modeling, which is the future of drug development.

Sources:

http://www.ncbi.nlm.nih.gov/pubmed/22579283

Read Full Post »

Reporter: Aviva Lev-Ari, PhD, RN

Cornell Chronicle Online  
Aug. 14, 2012
Missing gene may drive more than a quarter of breast cancers
tumors

Schimenti Lab
The image shows two tumors in mice from transplanted tumor-prone mammary gland stem cells. The tumor on the left was manipulated to have a reduced amount of NF1 protein (expressed by the NF1 gene), while the one on the right has normal NF1 levels. This preliminary experiment supports a critical role for NF1 in suppressing breast cancer.

A new study shows that the lack of a certain gene occurs in almost 28 percent of human breast cancers, playing a role in some 60,000 breast cancer cases in the United States and 383,000 worldwide this year.

Recent studies have observed loss of the gene NF1 in glioblastoma (an aggressive brain cancer), lung and ovarian cancers, but the significance has been overlooked because it was thought that two copies of the gene (one from each parent) needed to be missing to cause cancer. The study, published online July 30 in the journal Genetics, reports that in most human breast cancer cases where NF1 is a factor, only one copy is missing.

The finding has important clinical implications. It suggests that several existing drugs may be effective in treating breast cancers with missing NF1; it also suggests that the commonly used breast cancer drug tamoxifen could make the disease worse in these specific cancers.

The NF1 gene negatively regulates one of the most important oncogenes — genes that when mutated or expressed at high levels contribute to turning a normal cell into a cancerous one. This oncogene, called RAS, is involved in signaling inside the cell to control growth. When NF1 is missing or depleted, RAS becomes hyperactivated and can lead to tumor formation.

In the study, Cornell researchers used a mouse model with elevated mutation rates that lead to breast cancer in 80 percent of the mice.

“These mice almost always get mammary tumors, and when we looked at their genomes, nearly all of them were missing this NF1 gene,” said John Schimenti, professor of genetics and the paper’s senior author. “There are many big cancer studies that identify the most commonly mutated genes, but they don’t prove experimentally that those genes are the drivers of cancer.”

In humans, there are many causes of breast cancer, and each patient’s cancer has a slightly different set of natural gene variants as well as new mutations in their tumors, so identifying individual genes that drive cancer can be problematic. But the model mice are inbred and get exactly the same tumor every time. “So we’ve eliminated all the noise,” allowing the researchers to identify NF1 as a driver of these tumors, said Schimenti.

In the mouse model, RAS is hyperactivated. Since RAS is one of the most important oncogenes, many drugs have been already developed to interrupt the RAS pathway to treat cancer.

“If NF1 is missing and it is causing cancer by activating RAS, then these drugs may help,” said Schimenti. “Therefore, there doesn’t need to be any more drug development to test this possibility right now,” he added.

The study also suggests that tamoxifen, one of the most common breast cancer treatments, may exacerbate the disease when the missing NF1 is the driver. Another study reported that NF1 protein depletion makes cancer cells resistant to tamoxifen, and tamoxifen-treated patients whose tumors have low NF1 levels had poorer clinical outcomes.

Schimenti and his colleagues plan to test whether they can reverse growth of tumors in mice missing the NF1 gene by inserting a replacement gene. They are also testing how effective RAS inhibitor drugs are at curbing cancer in mice. The paper shows that RAS inhibitors curb growth of these tumor cells in culture.

Marsha Wallace, a graduate student working in Schimenti’s lab, is the paper’s lead author. Researchers from the University of North Carolina and Sloan Kettering Cancer Center co-authored the study.

The study was funded by the National Institutes of Health, the Empire State Stem Cell Fund, the National Cancer Institute and the Breast Cancer Research Foundation.

 

Read Full Post »

Aspirin a Day Tied to Lower Cancer Mortality

Reporter: Aviva Lev-Ari, PhD, RN

Aspirin a Day Tied to Lower Cancer Mortality

Download Complimentary Source PDF 

Daily aspirin use is associated with a modest decrease in mortality from cancer, particularly for malignancies of the gastrointestinal tract, a large retrospective study confirmed.

Individuals who were current daily users for 5 years or more at baseline had an 8% decrease in cancer mortality compared with non-users (RR 0.92, 95% CI 0.83 to 1.02), according to Eric J. Jacobs, PhD, and colleagues from the American Cancer Society in Atlanta.

The association was stronger, with a 16% decrease for those with daily use for 5 years or more, when the analysis included data collected periodically during 2 decades of follow-up (RR 0.84, 95% CI 0.75 to 0.95), the researchers reported in the Journal of the National Cancer Institute.

A recent pooled analysis of more than 50 trials involving aspirin use for cardioprotection found a 37% reduction in deaths from cancer among users, which was considerably greater than in observational studies and trials of alternate-day aspirin.

To clarify the magnitude of the association between aspirin use and overall cancer mortality, Jacobs and colleagues analyzed data from the Cancer Prevention Study II, which began in 1992 and included 100,139 participants who completed questionnaires with information on demographics, medical history, and behavioral influences.

Beginning in 1997, participants also provided information about aspirin use, and continued to provide updates every 2 years.

The 1997 questionnaire was considered the baseline for the analysis, at which time 23.8% of participants were using either low-dose or adult-strength aspirin.

More than half of participants were older than 60 and female, and almost all were white.

During the 20 years of follow-up, there were 5,138 deaths from cancer.

Among those who reported aspirin use in 1997, three-quarters said they were still taking it in 2003, while among those who were non-users at baseline, 25% had begun doing so.

Baseline aspirin users tended to be more educated, former smokers, and obese, as well as to have a history of cardiovascular disease and diabetes.

Male users also were more likely to have a history of prostate specific antigen (PSA) testing, and women users were more likely to have a history of mammography.

Overall mortality was slightly lower even for individuals who had been users for less than 5 years (RR 0.84, 95% CI 0.76 to 0.94).

Relative risks were similar for users of low-dose and full-strength aspirin, and for those with and without a history of cardiovascular disease, ranging from 0.82 (95% CI 0.72 to 0.91) to 0.95 (95% CI 0.86 to 1.04).

Current users who had never smoked had considerably lower mortality (RR 0.68, 95% CI 0.57 to 0.81), a reduction that was not seen for former smokers (RR 0.92, 95% CI 0.82 to 1.04) or those currently smoking (RR 0.91, 95% CI 0.70 to 1.19).

Even after discounting lung cancer deaths, the only lower mortality among aspirin users was for never-smokers (RR 0.67, 95% CI 0.56 to 0.81).

A possible explanation for the lack of effect on cancers other than those in the lung among ever-smokers is that smoking may attenuate the antiplatelet activity of aspirin, and activated platelets are thought to promote tumor metastases, the researchers explained.

Aspirin use at the 1997 baseline was not significantly associated with mortality from specific cancers, but differences were seen when data through 2008 were included in the analysis:

  • Cancers within the gastrointestinal tract, RR 0.61 (95% CI 0.44 to 0.84)
  • Cancers outside the gastrointestinal tract, RR 0.88 (95% CI 0.78 to 1)
  • Colorectal cancer, OR 0.64 (95% CI 0.42 to 0.98)
  • Esophageal and stomach cancer, RR 0.56 (95% CI 0.37 to 0.86)

“The reduction in overall cancer mortality was driven by both a substantial reduction in mortality from gastrointestinal tract cancers and a small, but statistically significant, reduction in mortality from cancers outside the gastrointestinal tract,” they stated.

They noted that their study was observational, which was an important limitation, in that confounding factors could have resulted in either an underestimate or an overestimate of the effects of aspirin on mortality.

Also, the absolute risk for cancer mortality between non-users and daily long-term aspirin users — approximately 100 per 100,000 person-years for men and about 40 per 100,000 person-years for women — would represent an important benefit of aspirin use if it were causal, the authors stated.

“However, even if causal, differences in absolute rates are likely to differ between our predominantly elderly population and younger populations at much lower risk of cancer mortality,” they warned.

They concluded that the “relatively modest benefit” seen in their analysis could “meaningfully influence the balances of risks and benefits of prophylactic aspirin use.”

In an accompanying editorial, John Baron, MD, of the University of North Carolina in Chapel Hill, offered a word of caution. Baron was the lead author of the meta-analysis on aspirin use and cancer risk.

“Just because aspirin is effective does not mean it necessarily should be used,” he argued.

“Aspirin is a real drug, with definite toxicity. As for any preventative intervention, the benefits must be balanced against the risks, particularly when the benefits are delayed whereas the risks are not,” Baron stated.

The American Cancer Society funds the Cancer Prevention Study II cohort.

The authors are employees of the American Cancer Society.

Editorialist Baron has been a consultant for Bayer, and holds a use patent for aspirin chemoprevention.

Primary source: Journal of the National Cancer Institute
Source reference:
Jacobs E, et al “Daily aspirin use and cancer mortality in a large US cohort” JNCI 2012; DOI: 10.1093/jnci/djs318.

Additional source: Journal of the National Cancer Institute
Source reference:
Baron JA, et al “Aspirin and cancer: trials and observational studies” JNCI 2012; DOI: 10.1093/jnci/djs318.

Read Full Post »

Curator/Author: Aviral Vatsa PhD, MBBS

Nitric oxide is one of the smallest molecules involved in physiological functions in the body. It is a diatom and thus seeks formation of chemical bonds with its targets rather than structure-function configuration of say protein receptors. Nitric oxide can exert its effects principally by two ways:

  • Direct
  • Indirect

Direct actions, as the name suggests, result from direct chemical interaction of NO with its targets e.g. with metal complexes, radical species. These actions occur at relatively low NO concentrations (<200 nM)

Indirect actions result from the effects of reactive nitrogen species (RNS) such as NO2 and N2O3. These reactive species are formed by the interaction of NO with superoxide or molecular oxygen. RNS are generally formed at relatively high NO concentrations (>400 nM)

Credits: Nitric Oxide: Biology and Pathobiology By Louis J. Ignarro

Credits: Nitric Oxide: Biology and Pathobiology By Louis J. Ignarro

Although it can be tempting for scientists to believe that RNS will always have deleterious effects and NO will have anabolic effects, this is not entirely true as certain RNS mediated actions mediate important signalling steps e.g. thiol oxidation and nitrosation of proteins mediate cell proliferation and survival, and apoptosis respectively. As depicted in the figure above, NO concentration determines the action it exerts on different proteins. This is highlighted in the following examples from different studies:

  • Cells subjected to NO concentration between 10-30 nM were associated with cGMP dependent phosphorylation of ERK
  • Cells subjected to NO concentration between 30-60 nM were associated with Akt phosphorylation
  • Concentration nearing 100 nM resulted in stabilisation of hypoxia inducible factor-1
  • At nearly 400 nM NO, p53 can be modulated
  • >1μM NO, it nhibits mitochondrial respiration

Besides the concentration, duration of NO exposure also determines how proteins respond to NO. Hence proteins can be ‘immediate’ responders or ‘delayed’ responders. The response can be either ‘transient’ (short lived) or ‘sustained’ (prolonged). Different proteins fall into these different categories. These are not rigid categories rather a functional ‘classification’.

Endogenously generated NO concentration ranges from 2 nM as in endothelial cell to >1 μM in a fully activated macrophage. This wide range, along with the unique chemical reactivity of NO offers immense versatility to the physiological effects that it can exert in different cellular milieu in the body.

In addition to the concentration-dependent effects, other factors that determine the local cellular/tissue milieu add to the complexities involved with signal transduction undertaken by NO. These factors are

  • rate of NO production
  • diffusion distance
  • rates of consumption
  • reactivity of RNS with molecular targets.

These kinetic determinants play vital role in physiological functions and disease states.

Although it is not possible to detail the modes of modulation of biological functions by NO in a short post, but I hope the post gives a taste of the intricacies involved with NO functions and that there are various parameters that determine the exact role of NO in a biological milieu.

Sources

http://www.pnas.org/content/101/24/8894.short

http://onlinelibrary.wiley.com/doi/10.1002/ijc.22336/full

http://cancerres.aacrjournals.org/content/67/1/289.short

http://www.sciencedirect.com/science/article/pii/S0005272806000417

http://goo.gl/eVXFh

Read Full Post »

 

Reporter: Aviva Lev-Ari, PhD, RN

A Matched Comparison of Perioperative Outcomes of a Single Laparoscopic Surgeon Versus a Multisurgeon Robot-Assisted Cohort for Partial Nephrectomy

The Journal of Urology
Volume 188, Issue 1 , Pages 45-50, July 2012

 

Department of Urology, University of Michigan, Ann Arbor, Michigan

Received 17 October 2011 published online 14 May 2012.

Purpose

Minimally invasive nephron sparing surgery is gaining popularity for small renal masses. Few groups have evaluated robot-assisted partial nephrectomy compared to other approaches using comparable patient populations. We present a matched pair analysis of a heterogeneous group of surgeons who performed robot-assisted partial nephrectomy and a single experienced laparoscopic surgeon who performed conventional laparoscopic partial nephrectomy. Perioperative outcomes and complications were compared.

Materials and Methods

All 249 conventional laparoscopic and robot-assisted partial nephrectomy cases from January 2007 to June 2010 were reviewed from our prospectively maintained institutional database. Groups were matched 1:1 (108 matched pairs) by R.E.N.A.L. (radius, exophytic/endophytic properties, nearness of tumor to collecting system or sinus, anterior/posterior, location relative to polar lines) nephrometry score, transperitoneal vs retroperitoneal approach, patient age and hilar nature of the tumor. Statistical analysis was done to compare operative outcomes and complications.

Results

Matched analysis revealed that nephrometry score, age, gender, tumor side and American Society of Anesthesia physical status classification were similar. Operative time favored conventional laparoscopic partial nephrectomy. During the study period robot-assisted partial nephrectomy showed significant improvements in estimated blood loss and warm ischemia time compared to those of the experienced conventional laparoscopic group. Postoperative complication rates, and complication distributions by Clavien classification and type were similar for conventional laparoscopic and robot-assisted partial nephrectomy (41.7% and 35.0%, respectively).

Conclusions

Robot-assisted partial nephrectomy has a noticeable but rapid learning curve. After it is overcome the robotic procedure results in perioperative outcomes similar to those achieved with conventional laparoscopic partial nephrectomy done by an experienced surgeon. Robot-assisted partial nephrectomy likely improves surgeon and patient accessibility to minimally invasive nephron sparing surgery.

Key Words:  kidney , kidney neoplasms , nephrectomy , laparoscopy , robotics

Abbreviations and Acronyms:  CLPNconventional laparoscopic partial nephrectomyEBLestimated blood losseGFR,estimated glomerular filtration rateICUintensive care unitLOSlength of stayRAPNrobot-assisted partial nephrectomy,SRMsmall renal massWITwarm ischemia time

 

Similar outcomes for robot-aided, conventional nephrectomy June 22, 2012 in Other Robot-assisted and conventional laparoscopic partial nephrectomies have similar outcomes and complication rates, according to a study published in the July issue of The Journal of Urology. (HealthDay) — Robot-assisted and conventional laparoscopic partial nephrectomies have similar outcomes and complication rates, according to a study published in the July issue of The Journal of Urology. Ads by Google Prostate Cancer Treatment – Expert Prostate Cancer Treatment & Care – View Video to Learn More! – http://www.TuftsMedicalCenter.tv Prostate Cancer Treatment – Learn about Watchful Waiting. Get a Second Opinion at BIDMC. – http://www.BIDMC.org Jonathan S. Ellison, M.D., from the University of Michigan in Ann Arbor, and colleagues compared perioperative outcomes and complications from conventional laparoscopic and robot-assisted partial nephrectomy cases from January 2007 to June 2010. Robot-assisted partial nephrectomies were performed by a heterogeneous group of surgeons, while a single experienced laparoscopic surgeon performed the conventional procedures. One hundred eight pairs of patients were matched by age, hilar nature of the tumor, approach, and R.E.N.A.L. (radius, exophytic/endophytic properties, nearness of tumor to collecting system or sinus, anterior/posterior, location relative to polar lines) nephrometry score. The researchers found that nephrometry score, age, gender, tumor side, and American Society of Anesthesia physical status classification were similar between the groups. Conventional laparoscopic partial nephrectomy had better operative time. Robot-assisted partial nephrectomy showed significant improvements in estimated blood loss and warm ischemia time compared to the conventional laparoscopic group. The postoperative complication rates and complication distributions by Clavien classification and type were similar for both groups (41.7 percent for the conventional group and 35.0 percent for the robot-assisted group). “Robot-assisted partial nephrectomy has a noticeable but rapid learning curve,” write the authors. “After it is overcome the robotic procedure results in perioperative outcomes similar to those achieved with conventional laparoscopic partial nephrectomy done by an experienced surgeon.” More information: Abstract Full Text (subscription or payment may be required) Journal reference: Journal of Urology

http://medicalxpress.com/news/2012-06-similar-outcomes-robot-aided-conventional-nephrectomy.html

 

Prostate Cancer

What does your PSA score, level, reading, test mean?

By itself, a PSA reading does not mean very much. There are many possible causes of the rise in the PSA reading. The most common of these reasons is an enlarged, inflamed, or infected prostate. So a high PSA score does not necessarily indicate prostate cancer.

Unfortunately there is no failsafe test or methods at this time that can differentiate between a high PSA level caused by inflammation of the prostate or infection of the prostate or prostate cancer. At best doctors use a statistical model, which seeks to predict your chances of having prostate cancer. But that is purely a statistical construct and does not actually predict your specific and personal situation at all.

Nonetheless, an elevated PSA reading should not be ignored. It is a good indicator, certainly the best we have, and you should take precautionary action.

If you have a high PSA reading you need to return your prostate back to good health. You need to make important changes to your diet. You also need to have regular exercise. A third and equally important part of my recommendation is to take appropriate natural supplements.

I provide a roadmap in my guide “All about the Prostate”. Most men who follow my roadmap will see their PSA levels come down. It will return their prostate to good health.

http://www.bensprostate.com/minib/psa-test-and-levels/?utm_source=bing&utm_medium=cpc&utm_campaign=bing-prostate-us-broad&utm_content=psa-2&utm_term=psa

INDICATION

ZYTIGA® (abiraterone acetate) in combination with prednisone is indicated for the treatment of patients with metastatic castration-resistant prostate cancer (mCRPC) who have received prior chemotherapy containing docetaxel.

IMPORTANT SAFETY INFORMATION

Contraindications – ZYTIGA® (abiraterone acetate) may cause fetal harm (Pregnancy Category X) and is contraindicated in women who are or may become pregnant.

Hypertension, Hypokalemia and Fluid Retention Due to Mineralocorticoid Excess –Use with caution in patients with a history of cardiovascular disease or with medical conditions that might be compromised by increases in hypertension, hypokalemia, and fluid retention. ZYTIGA® may cause hypertension, hypokalemia, and fluid retention as a consequence of increased mineralocorticoid levels resulting from CYP17 inhibition. Safety has not been established in patients with LVEF <50% or New York Heart Association (NYHA) Class III or IV heart failure because these patients were excluded from the randomized clinical trial. Control hypertension and correct hypokalemia before and during treatment. Monitor blood pressure, serum potassium, and symptoms of fluid retention at least monthly.

Adrenocortical Insufficiency (AI) – AI has been reported in clinical trials in patients receiving ZYTIGA® in combination with prednisone, after an interruption of daily steroids and/or with concurrent infection or stress. Use caution and monitor for symptoms and signs of AI if prednisone is stopped or withdrawn, if prednisone dose is reduced, or if the patient experiences unusual stress. Symptoms and signs of AI may be masked by adverse reactions associated with mineralocorticoid excess seen in patients treated with ZYTIGA®. Perform appropriate tests, if indicated, to confirm AI. Increased dosages of corticosteroids may be used before, during, and after stressful situations.

Hepatotoxicity – Increases in liver enzymes have led to drug interruption, dose modification, and/or discontinuation. Monitor liver function and modify, withhold, or discontinue ZYTIGA® dosing as recommended (see Prescribing Information for more information). Measure serum transaminases [alanine aminotransferase (ALT) and aspartate aminotransferase (AST)] and bilirubin levels prior to starting treatment with ZYTIGA®, every two weeks for the first three months of treatment, and monthly thereafter. Promptly measure serum total bilirubin, AST, and ALT if clinical symptoms or signs suggestive of hepatotoxicity develop. Elevations of AST, ALT, or bilirubin from the patient’s baseline should prompt more frequent monitoring. If at any time AST or ALT rise above five times the upper limit of normal (ULN) or the bilirubin rises above three times the ULN, interrupt ZYTIGA® treatment and closely monitor liver function.

Food Effect – ZYTIGA® must be taken on an empty stomach. Exposure of abiraterone increases up to 10-fold when abiraterone acetate is taken with meals. No food should be eaten for at least two hours before the dose of ZYTIGA® is taken and for at least one hour after the dose of ZYTIGA® is taken. Abiraterone Cmax and AUC0-∞ (exposure) were increased up to 17- and 10-fold higher, respectively, when a single dose of abiraterone acetate was administered with a meal compared to a fasted state.

Adverse Reactions – The most common adverse reactions (≥ 5%) are joint swelling or discomfort, hypokalemia, edema, muscle discomfort, hot flush, diarrhea, urinary tract infection, cough, hypertension, arrhythmia, urinary frequency, nocturia, dyspepsia, fractures and upper respiratory tract infection.

Drug Interactions – ZYTIGA® is an inhibitor of the hepatic drug-metabolizing enzyme CYP2D6. Avoid co-administration with CYP2D6 substrates that have a narrow therapeutic index. If an alternative cannot be used, exercise caution and consider a dose reduction of the CYP2D6 substrate. Additionally, abiraterone is a substrate of CYP3A4 in vitro. Strong inhibitors and inducers of CYP3A4 should be avoided or used with caution.

Use in Specific Populations – The safety of ZYTIGA® in patients with baseline severe hepatic impairment has not been studied. These patients should not receive ZYTIGA®.

 

Read Full Post »

Reporter: Aviva Lev-Ari, PhD, RN

“A Synergistic Approach towards Biowaivers & Biosimilars”. Biosimilars-2012 is scheduled on September 10-12, 2012 at Hilton San Antonio Airport, USA.

Biosimilars or Follow-on biologics
http://en.wikipedia.org/wiki/Biologic_medical_product are terms used to describe officially-approved subsequent versions of innovator biopharmaceutical http://en.wikipedia.org/wiki/Biopharmaceutical  products made by a different sponsor following patent and exclusivity expiry on the innovator product.[1] http://en.wikipedia.org/wiki/Biosimilar#cite_note-biosimilars2012-0 Biosimilars are also referred to as subsequent entry biologics (SEBs) in Canada.[2] http://en.wikipedia.org/wiki/Biosimilar#cite_note-1 Reference to the innovator product is an integral component of the approval.
 
A Biowaiver is a waiver (exemption) of clinical bioequivalence studies given to a drug product.
 

Biowaivers and Biosimilars.

The main theme of the conference is “A Synergistic Approach towards Biowaivers & Biosimilars”.

Biosimilars-2012 is scheduled on September 10-12, 2012 at Hilton San Antonio Airport, USA.

 Click here to view the downloadable Preliminary Program 

 http://sm1.mailserv.in/omicsonlinebiz/lt.php?id=eR4DBVEEUA9UUksGBlMKAU4=UQMNDAgNSllRVQgECyUNWAodUg5C

This three day conference will cover the latest trends and challenges in Biowaivers and Biosimilars.   Biosimilars-2012 highlights the following topics:   

  • Biosimilars Pathway  
  • Immunogenicity   
  • Skill Set for Biosimilars Development  
  • Biosimilar Therapeutics      
  • Biomedical informatics  
  • BCS and IVIVC based biowaivers  
  • Transgenic animals & plants  
  • In vitro & In vivo Correlations  
  • Bioequivalence Testing  
  • BCS and IVIVC based biowaivers    
  • Oral drug delivery     

Conference assets are William Velander (University of Nebraska, USA), Lisa J. Murray (Absorption Systems, PA, USA), Leandro Mieravilla (Biosimilar-Biotech Global Expert, Canada) and David Goodall (Paraytec Limited, UK) who will discuss their novel research on Biosimilars & Biowaivers.

This conference is perfect for researchers and experts, as well as those who require in-depth analysis of the latest trends, technologies, and techniques.

Confirmed Speakers Including

Tentative Scientific Program18:00-19:00Registrations Sep-09-2012

Day 1

Sep-10-2012

07:00-08:00 Registrations

08:00-08:30 Breakfast

Breakout 1

08:30-09:00 Opening Ceremony

Keynote Forum

09:00-09:05 Introduction

09:05-09:30 Lisa J. Murray, Absorption Systems, USA

09:30-09:55 Yet to be Confirmed

09:55-10:20 Yet to be Confirmed

10:20-10:45 Yet to be Confirmed

Coffee Break 10:45-11:00

Track 1: Biosimilars : Innovator Pharmaceutical Products

Track 2: Biosimilars: Regulatory Approach

Session Introduction

11:00-11:20

Title: The role of scientific justification in the nascent us biosimilars approval pathway

Ben Kaspar, MMS Holdings Inc., USA

11:20-11:40

Title: The what million dollar question: Patent litigation and strategy under the biologics

price Competition and Innovation act

Bryan J. Vogel, Robins, Kaplan, Miller & Ciresi L.L.P., USA

11:40-12:00

Title: The role of patents in biosimilars and biobetters

Brian Dorn, Barnes & Thornburg LLP, USA

12:00-12:20

Title: New patent reform litigation options for biosimilars

Paul A. Calvo, Sterne, Kessler, Goldstein & Fox P.L.L.C., USA

12:20-12:40 Title: Regulatory consideration of the assessment of biosimilar products

Jun Wang, Duke University School of Medicine, USA

Lunch Break 12:40-13:20

13:20-13:40

Title: What hath FDA wrought: The February 2012 guidance and their implications for

securing biosimilar approval

Michal Swit, Duane Morris LLP, USA

13:40-14:00

Title: The role of clinical trials in demonstrating similarity of biological medicinal

products in the European Union

Cecil Nick, PARAXEL Consulting, UK

14:00-14:20

Title: Biosimilars panel: Opportunities and challenges to be overcome in the near term

Jennifer Brice, Frost & Sullivan, UK

14:20-14:40

Title: Graphical representation of the assessment of inventive step for patents using the

Problem-Solution-Approach (PSA)

Joachim Stellmach, European Patent Office, Germany

14:40-15:00

Title: IP strategies for the biosimilar arena

Ulrich Storz, Michalski Huettermann Patent Attorneys, Germany

15:00-15:20

Title: Biosimilars in emerging countries: Argentina

Gustavo Helguera, University of Buenos Aires, Argentina

15:20-15:40

Title: Developing biosimilars: Considerations, opportunities and challenges

Ming Wang, Gan & Lee Pharmaceuticals, China

Panel Discussion 15:40-15:55

Coffee Break 15:55-16:10

Track 3: Skill Set for Biosimilars Development

Track 4: Clinical Studies for Biosimilars

Session Introduction

16:10-16:30

Title: Strategies for development and validation of immunogenicity assays to support

preclinical and clinical biosimilar programs

Kelly S. Colletti, Charles River Preclinical Services, USA

16:30-16:50

Title: Transgenic blood proteins: An abundant source for next generation therapies with

worldwide availability

William Velander, University of Nebraska, USA

16:50-17:10

Title: The Danish HNPCC-system – Biomedical support to individual health care in

hereditary colon cancer families

Inge Thomsen Bernstein, Hvidovre University Hospital, Denmark

17:10-17:30

Title: Use of human protein transgenic animal models for immunogenicity testing and

their value for comparative studies of biosimilars

Melody Sauerborn, TNO Triskelion BV, The Netherlands

17:30-17:50

Title: Application of nanotechnology in drug delivery

Rawia Khalil, National Research Centre, Egypt

Panel Discussion 17:50-18:05

18:05-19:05 Cocktails: Sponsored by Journal of Bioequivalence & Bioavailability

Day 2

Sep-11-2012

Breakout 1

Track 5: Biosimilars Therapeutics

Track 6: Commercialization or Globalization of Biosimilars

Session Introduction

09:30-09:50

Title: Development of antibody arrays for measuring biosimilar conformational

comparability at molecular level

Xing Wang, Array Bridge Inc., USA

09:50-10:20

Title: Biosimilar market overview, present and future

Leandro Mieravilla, Biosimilar-Biotech Global Expert, Canada

10:20-10:40

Title: Modified biosimilars: Potential role in the emerging global biosimilar market

Pascal Bailon, Bailon Consultants, USA

Coffee Break 10:40-10:55

10:55-11:15

Title: The application of releasable pegylation linkers to improve the pharmaceutical

properties of biosimilars and biobetters

Hong Zhao, Enzon Pharmaceuticals, USA

11:15-11:35

Title: The clinical development of monoclonal biosimilars

Cecil Nick, PARAXEL Consulting, UK

11:35-11:55

Title: Ghrelin antagonist: Advantages and side-effects

Maria Vlasova, University of Eastern Finland, Finland

11:55-12:15

Title: Biosimilar market growth trends in emerging markets

Syamala Ariyanchira, Independent Consultant, Malaysia

12:15-12:35

Title: Developing of long acting glycoprotein hormones using gene fusion and gene

transfer: From bench to clinics

Fuad Fares, University of Haifa, Israel

Lunch Break 12:35-13:15

13:15-13:35

Title: Th1 immune response induced by Ipr1-PPE68 DNA vaccine in BALB/C mice model

Yang Chun, Chongqing Medical University, China

13:35-13:55

Title: Anticancer noscapinoids: Synthesis to nanomedicine

Ramesh Chandra, University of Delhi, India

Panel Discussion 13:55-14:10

Track 7: Plant Produ ced Biosimilar Products

Track 8: Aggregation and Immunogenicity of Biosimilars

Session Introduction

14:10-14:30

Title: Biosimilars: Lessons learned from development to commercial launch

Niranjan M. Kumar, ABS Inc. USA

14:30-14:50

Title: Plant-based production and preclinical analysis of biosimilar Trastuzumab

Michael D. McLean, PlantForm Corporation, Canada

Coffee Break 14:50-15:05

15:05-15:25

Title: Immunological aspects of formation of anti-drug antibodies against aggregated

protein drugs

Melody Sauerborn, TNO Triskelion BV, The Netherlands

15:25-15:45 Speech Opportunity Available

15:45-16:05 Speech Opportunity Available

Panel Discussion 16:05-16:20

Breakout 2

16:20-19:20

Editorial Board Meeting

Poster Presentations

Scientific Partnering

Cocktails: Sponsored by Pharmaceutica Analytica Acta

Day 3

Sep-12-2012

Breakout 1

Track 9: Biowaivers

Track 10: BCS & IVIVC Based Biowaivers

Track 11: Bioequivalence Assessment

Track 12: Analytical Strategies

Session Introduction

09:30-09:50

Title: Role of process controls in mitigating the risk associated with manufacturing of

biosimilars

Indu S. Javeri, CuriRx Inc., USA

09:50-10:20

Title: Current analytical techniques for analysis of carbohydrate containing biosimilars

Parastoo Azadi, University of Georgia, USA

10:20-10:40

Title: Improving outcomes: A decade of industry and regulatory experience with BCS

based biowaivers

Lisa J. Murray, Absorption Systems, USA

Coffee Break 10:40-10:55

10:55-11:15

Title: Approach for development of w-3 phospholipid dietary supplement to potential lipid

drug

Su Chen, Chainon Neurotrophin Biotechnology Inc., USA

11:15-11:35

Title: Bioanalytical challenges in development of biosimilars

Carmine Lanni, Bioanalytical Development Services, USA

11:35-11:55

Title: Some statistical issues on the evaluation of the similarity and interchangeability of

biologics

Laszlo Endrenyi, University of Toronto, Canada

11:55-12:15

Title: Rapid characterization of formulations: Protein size, aggregate levels and viscosity

David Goodall, Paraytec Limited, UK

12:15-12:35

Title: Taylor dispersion analysis, a rapid, nanolitre method to monitor protein aggregation

behavior

Wendy Louise Hulse, University of Bradford, UK

Lunch Break 12:35-13:15

13:15-13:35

Title: Effects of drying technology and polymers on integrity and biological activity of

proteins

Amal Ali Elkordy, University of Sunderland, UK

13:35-13:55

Title: A global perspective on the challenges of GLP/GCLP-bioanalysis for biosimilars

Aparna Kasinath, Clinigene International Limited, India

13:55-14:15 Speech Opportunity Available

14:15-14:35 Speech Opportunity Available

14:35-14:55 Speech Opportunity Available

14:55-15:15 Speech Opportunity Available

Panel Discussion 15:15-15:30

Editorial Board Meeting

For Biosimilars-2012 Organizing Committee 

OMICS Group Conferences
5716 Corsa Ave., Suite110
Westlake, Los Angeles
CA91362-7354, USA
Phone:+1-650-268-9744 <tel:%2B1-650-268-9744>
Fax:+1-650-618-1414 <tel:%2B1-650-618-1414>
Email: biosimilars2012@omicsgroup.com <mailto:biosimilars2012@omicsgroup.com>
     
         

Read Full Post »

 

Reporter: Aviva Lev-Ari, PhD

Mucosal CD30-positive T-cell lymphoproliferations of the head and neck show a clinicopathologic spectrum similar to cutaneous CD30-positive T-cell lymphoproliferative disorders

Modern Pathology 25, 983-992 (July 2012) doi:10.1038/modpathol.2012.38

Andrew P Sciallis, Mark E Law, David J Inwards, Rebecca F McClure,William R Macon, Paul J Kurtin, Ahmet Dogan and Andrew L Feldman

Abstract

CD30-positive T-cell lymphoproliferative disorders are classified as cutaneous (primary cutaneous anaplastic large cell lymphoma and lymphomatoid papulosis) or systemic. As extent of disease dictates prognosis and treatment, patients with skin involvement need clinical staging to determine whether systemic lymphoma also is present. Similar processes may involve mucosal sites of the head and neck, constituting a spectrum that includes both neoplasms and reactive conditions (eg, traumatic ulcerative granuloma with stromal eosinophilia). However, no standard classification exists for mucosal CD30-positive T-cell lymphoproliferations. To improve our understanding of these processes, we identified 15 such patients and examined clinical presentation, treatment and outcome, morphology, phenotype using immunohistochemistry, and genetics using gene rearrangement studies and fluorescence in situ hybridization. The 15 patients (11 M, 4 F; mean age, 57 years) had disease involving the oral cavity/lip/tongue (9), orbit/conjunctiva (3) or nasal cavity/sinuses (3). Of 14 patients with staging data, 7 had mucosal disease only; 2 had mucocutaneous disease; and 5 had systemic anaplastic large cell lymphoma. Patients with mucosal or mucocutaneous disease only had a favorable prognosis and none developed systemic spread (follow-up, 4–93 months). Three of five patients with systemic disease died of lymphoma after 1–48 months. Morphologic and phenotypic features were similar regardless of extent of disease. One anaplastic lymphoma kinase-positive case was associated with systemic disease. Two cases had rearrangements of the DUSP22-IRF4 locus on chromosome 6p25.3, seen most frequently in primary cutaneous anaplastic large cell lymphoma. Our findings suggest mucosal CD30-positive T-cell lymphoproliferations share features with cutaneous CD30-positive T-cell lymphoproliferative disorders, and require clinical staging for stratification into primary and secondary types. Primary cases have clinicopathologic features closer to primary cutaneous disease than to systemic anaplastic large cell lymphoma, including indolent clinical behavior. Understanding the spectrum of mucosal CD30-positive T-cell lymphoproliferations is important to avoid possible overtreatment resulting from a diagnosis of overt T-cell lymphoma.

 

Read Full Post »

« Newer Posts - Older Posts »