Indian Journal of Cancer
Home  ICS  Feedback Subscribe Top cited articles Login 
Users Online :1521
Small font sizeDefault font sizeIncrease font size
Navigate here
  Search
 
 » Next article
 » Previous article 
 » Table of Contents
  
Resource links
 »  Similar in PUBMED
 »  Search Pubmed for
 »  Search in Google Scholar for
 »Related articles
 »  [PDF Not available] *
 »  Citation Manager
 »  Access Statistics
 »  Reader Comments
 »  Email Alert *
 »  Add to My List *
* Registration required (free)  

 
  In this article
 »  Abstract
 »  Introduction
 »  Basics of TMA co...
 »  TMA types, desig...
 »  Advantages, vali...
 »  Potential of TMA...
 »  Final word
 »  References
 »  Article Figures

 Article Access Statistics
    Viewed4668    
    Printed138    
    Emailed3    
    PDF Downloaded4    
    Comments [Add]    
    Cited by others 2    

Recommend this journal

 


 
REVIEW ARTICLE
Year : 2005  |  Volume : 42  |  Issue : 1  |  Page : 9-14
 

Tissue microarrays: Potential in the Indian subcontinent


1 Department of Pathology, Loyola University Medical Center, Maywood, IL60153, USA
2 Department of Preventive Medicine, Robert H.Lurie Cancer Center, Northwestern University Feinberg School of Medicine, Chicago IL60611, USA

Correspondence Address:
Girish Venkataraman
Department of Pathology, Loyola University Medical Center, Maywood, IL60153
USA
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0019-509X.15094

Rights and Permissions

 » Abstract 

Tissue microarrays (TMAs) are a means of combining hundreds of specimens of tissue on to a single slide for analysis simultaneously. The evolution of this technology to validate the results of cDNA microarrays has impacted tremendously in accurately identifying prognostic indicators significant in determining survival demographics for patients. TMAs can be generated from archival paraffin blocks, combined with sophisticated image analysis software for reading TMA immunohistochemistry, and a staggering amount of useful information can be generated in terms of the biomarkers useful in predicting patient outcome. There is a wide range of uses for the TMA technology including profiling of specific proteins in cancerous tissues and non-cancerous tissues. Given the wide variety of tissue resources available in India, investment in a dedicated TMA facility will be of immense use in the research arena in India. This review article discusses the basics of TMA construction, design, the software available for the analysis of this technology and its relevance to Indian scientists. A potential workflow structure for setting up a TMA facility is also included.


Keywords: Tissue microarrays, histopathology


How to cite this article:
Venkataraman G, Ananthanaranayanan V. Tissue microarrays: Potential in the Indian subcontinent. Indian J Cancer 2005;42:9-14

How to cite this URL:
Venkataraman G, Ananthanaranayanan V. Tissue microarrays: Potential in the Indian subcontinent. Indian J Cancer [serial online] 2005 [cited 2019 Aug 18];42:9-14. Available from: http://www.indianjcancer.com/text.asp?2005/42/1/9/15094



 » Introduction Top




In the current world of proteomics, the use of high density Tissue Microarrays (TMAs)-also called "tissue chips"-has been progressively increasing in the last decade ever since its inception in 1998. Arguably, it might be touted as the most noteworthy development in histopathology techniques in the last decade.[1],[2] While DNA microarrays permit expression analysis of thousands of genes from one tissue specimen on a single array, TMAs make it possible to analyze hundreds or thousands of tissue specimens in a single experiment using a single gene or antibody probe. Given the tremendous pace at which novel genes implicated in cancer are being discovered using gene chips and expression microarrays, TMAs hold an immense potential to validate this genomic data across multiple tumor types in a limited time frame. Many pathology institutions across the world have taken advantage of this fact and incorporated TMA facilities exclusively for this purpose. A thorough understanding of the potential advantages of this technology coupled with a unified system for generating TMA blocks using paraffin blocks from high-histopathology-volume institutions in India will help in establishing a good tissue database for the Indian pathologists. The basics of TMA construction, hardware involved and scoring options available are discussed here.




 » Basics of TMA construction Top




TMAs are a method of relocating tissue from standard histological paraffin blocks such that tissue from multiple donor blocks can be placed on the same recipient block. Therefore, the first step in the process of creating a good TMA block is to locate the most representative area on each H/E slide and careful identification of the same area on the corresponding paraffin block of the slide. Once this is done, the block is positioned underneath the TMA puncher such that the representative area is directly under the punching pins. Thereafter, small "core needle biopsies" of these representative tissues are punched out directly from donor paraffin blocks and re-embedded onto a new recipient TMA paraffin block. Many such cores can be embedded in such a "master-arrayer" block employing this technique.[2] Using a 0.6 mm diameter puncher, nearly 600 or more tissue cores can be arrayed on a standard glass slide in a precise manner defined by X-Y coordinates. Although TMA block generation is a labor-intensive and time-consuming process, the ability of this high throughput technology to generate data from a staggering number of cases vastly improves statistical precision and power.




 » TMA types, design and data handling options Top




Having such a large number of spots on one single slide calls for a precise organization of the tissue spots at three levels-firstly, in the design and placement of the tissue cores in the TMA block; secondly, in the linking of clinical and pathological data to the correct core; and lastly, a validated means of scoring and analyzing any biomarker data so that a meaningful statistical analysis can be done.



Types of TMAs



The nature of tissues that can be used on TMAs is varied, ranging from totally normal tissues from various organs to non-neoplastic (like diabetes) and neoplastic ones and sometimes even cell lines.[3],[4] The Cooperative Human Tissue Network (CHTN), a division of the National Cancer Institute (NCI) can provide investigators with a wide range of normal tissues placed on a TMA slide so the expression profile of a single protein in many tissues can be assessed simultaneously. The information from such TMAs can provide valuable information regarding the biology of diseases in which these proteins are altered. TMAs based on neoplastic tissues also termed as tumor TMAs, are broadly classified into three types-multi-tumor arrays, progression arrays (based on stage of tumor) and prognostic arrays where tumors with known clinical end points are arrayed.[5],[6],[7]



Design of TMAs



An integral part of constructing TMAs is the design. After deciding on the optimum number of cases with sufficient clinical data, an important issue that merits consideration is the number of cores per case to put into the TMA block while evaluating any biomarker expression by immunohistochemistry. Although this number is variable, for most tumor TMAs, three to four cores/block adequately represent a biomarker's ability to predict survival outcomes.[8] Often two cores are taken from the donor block; one core is taken from the center of the donor block and the other close to the periphery of the block. It is important to include appropriate positive and negative controls besides orientation cores. It would be useful to chart out an MS Excel worksheet identifying the numbers of the various cores in the same pattern in which the cores are embedded in the TMA block. In addition, inclusion of irrelevant tissue at defined X-Y coordinates can help in accurate orientation of the cores. Often cores from tumors of same T size, stage or grade or tissue of origin can be clustered together on the TMA block. A typical low-density TMA block and slide is shown in [Figure - 1]. Last but not the least, it is important to ensure that all blocks used for TMA construction have been fixed and processed similarly because some immunohistochemical markers may not work when the tissue is fixed in a different fixative.



The technology used to generate TMA can range from manual to fully automated systems. One of the more prominent companies include Beecher Instruments (San Prairie, Wisconsin, USA), which features manual, semi-automated as well as fully automated systems. The cost can vary between $10,000 -$42,000 (USD) depending on the type of the equipment. Cost-effective alternative methods of generating TMA blocks can also be adapted if 60 or fewer number of cores are to be imprinted into the TMA block. A standard microscope fitted with a holing needle or a blunted 16G bone marrow trephine needle can be adapted to design TMA blocks at a fraction of the price of commercial instruments.[9]



Data acquisition, analysis and integration



Digital scanning and analysis



The next issue of importance is reading the TMA spots in an orderly, reproducible and reliable manner. Of course, the intuitive option would be to read one core after another manually under a bright-field microscope. Even so, keeping track of the precise position of each spot can become a painstaking process if there are more than 300 tissue spots on any single slide. Consequently, digital options are popular for analyzing biomarker expression on TMA. Systems like the BLISS Imaging (Bacus Labs, Lombard, IL) and ACIS system of Chromavision (www.chromavision.com) can scan and acquire images of all spots on the slide in one go without the user having to manually focus each spot separately before acquiring. Tracking and recording the scores from these tissue cores can be done using commercially available proprietary software. Bacus Laboratories also markets a TMA analysis software called 'TMAscore'. With this, TMA slides are scanned into virtual slides and placed on a network. Thereafter, multiple people can collaborate, and score each core manually or by using the aforementioned proprietary software.



Cost-effective alternatives for analysis



Given the logistics involved in using proprietary software, there is a need for exploring other economical means of doing spot scoring and analysis. Some noteworthy cost-effective software alternatives are available for recording patient data, histology details and coordinates of each core for scoring, some of which are described below. This still requires an image-capturing system to create an archived database of images for further analysis. The analysis can however be done using an 'open-source' free software available over the Internet for academic use.



In the first of these, a novel relational database for TMA analysis has recently been described using Adobe Photoshop (an imaging software) for image-editing and Microsoft Excel for recording core coordinates and performing scoring.[10] The authors of this study explain that a library of digital images of individual cores is stored in a specified folder of the computer. An Excel worksheet is created and grid locations of the cores are noted in rows and columns in the same pattern as in the TMA slide. Thereafter, hyperlinks are inserted for each grid such that clicking on the hyperlink corresponding to a specific core in the Excel worksheet will open the corresponding image of the same core for scoring. This method is especially useful if the number of cores on a slide is not going to exceed 150 cores.



For managing high-density TMAs with more than 600 cores per slide, an excellent set of software tools for high-throughput analysis has been developed at Stanford University.[11] These investigators used the BLISS System mentioned previously for generating a database of images. Immunohistochemical staining results are recorded into an MS Excel Worksheet and this Excel data is re-formatted by a program called "TMA-Deconvoluter" which converts the Excel data into a text file so that a Hierarchical Cluster Analysis can be done using the "Cluster" and "TreeView" software-this analyzes the relatedness within tumor subsets depending on the immunohistochemical biomarker profile. The TreeView software generates dendrograms akin to the ones seen with cDNA microarray data. Free access to TMA-Deconvoluter is possible at the Stanford TMA Website (http://genome-www.stanford.edu/TMA) while the other two software programs are available at the website of Michael B. Eisen's lab (http://rana.lbl.gov/EisenSoftware.htm).



Another noteworthy open-source java-based software called "TMAJ" is available from the website of the Johns Hopkins University TMA core facility (http://tmaj.pathology.jhmi.edu/). This helps in recording pathology data as well core tracking and scoring. A license is however required for users with potential commercial interests.



Data integration



As long as TMA slides are read by a single pathologist, it is possible to manage data with just MS Excel and statistical analysis software. When multiple investigators read the same slides, systematic data integration can become overwhelming. TMAs generate an immense amount of data and so collaborating pathologists analyzing the same TMAs in different institutions need to be aware that they have to record the generated data in a uniform and standardized format. This is crucial because Excel data files generated by multiple pathologists across the country scoring the same TMA slides, can be integrated for statistical analysis only if the scoring format is uniform between all the investigators. Addressing this issue, a TMA data exchange software specification language for free use has been developed in XML (eXtensible Markup Language) recently.[12],[13] The basic pre-requisite of this data integration language is that all investigators need to have their Excel data scoring files with the same column headings viz. Patient ID, Age, core ID etc in the same order. A PERL (Practical Extraction and Report Language) (another computer language) script will export all these Excel data in the final XML database accurately only if the column headings are the same in all Excel files. If XML is difficult, collaborating pathologists can also use MS Excel exclusively and configure it to concatenate data from multiple investigators for analysis.[14]




 » Advantages, validation and caveats of TMAs Top




There are a number of plus points to using TMAs instead of standard histology sections. Firstly, a large number of cases can be analyzed simultaneously and this in turn, improves the power and precision of any statistical analysis considerably. Schraml et al analyzed the oncogenes CCD1, CMYC and ERBB2 in 397 tumor spots by Fluorescent In-Situ Hybridization in just one week attesting to the rapidity with which TMAs can generate results.[15]



Secondly, immunohistochemistry on a single TMA slide is much more time-saving and economical in terms of the amount of antibodies and reagents used as compared to paraffin sections while ensuring uniform treatment of all cores on a slide-no batch to batch variability needs to be accounted for as with standard sections.[16] Van de Rijn et al have described the utility of a 29-case mini TMA of breast cancer blocks as a useful control for Estrogen Receptor. Instead of a single strong positive control slide, the TMA includes a spectrum of positivity from weak to strong.[17] As a result, any change in the strength of the detection can be easily detected. Besides, inter-laboratory quality control for immunohistochemistry can also be assessed.



On the other hand, TMAs can be used to test new prognostic candidate biomarkers evolving from cDNA microarray studies. Natkunam et al were able to test a new marker of plasmacytic differentiation called MUM1/RF4 against 1335 different human tumors and demonstrate it to be a sensitive albeit non-specific marker to the extent that even melanocytic tumors stained positive.[18]



Yet another study has demonstrated the elegant way in which TMAs validated the results of a cDNA microarray analysis.[19] The authors screened 5184 genes and discovered 2 genes namely, IGFBP2 and HSP27 that were upregulated in xenografts of hormone refractory prostate cancer (HRPC). They followed this up with immunohistochemistry for both markers on a TMA and found that 100% of HRPC cases were positive for IGFBP2 while none of the normal prostate cores were positive for the same marker.



Criticism is often directed towards the fact that the small size of TMA cores may not adequately represent biomarkers (like ER) that are distributed heterogeneously in the tissue. Addressing this problem of spatial heterogeneity, Camp et al found that just two 0.6 mm cores from the same block provided equivalent information on ER indices as that of whole sections.[20] Thus, intra-tumoral heterogeneity will not be an issue of significant concern.



Caveats with TMAs: With TMAs, investigators also need to be able to decide if constructing a TMA in any situation is going to give additional information for the extra price being paid; if you have only 30 donor blocks of a prostatic adenocarcinoma, it might work out better doing conventional one slide-one section IHC rather than constructing a TMA. The cost-benefit ratio is high only if the array is valuable (i.e. if it contains rare to find tissues and lesions), the number of cores on the array is very high or if there is a need to assess many proteins at one time. If too many spatially close cores (>6) are marked for punching on the same block, the technologist will have a hard time locating these on the block. Lastly, it is necessary to do a Quality Assurance (QA) with every TMA slide to see if the representative tissue is present at the pre-defined X-Y coordinate on the slide. The representative tissue of interest may often get depleted in deeper sections (e.g. breast lobules or areas of HGPIN in blocks from radical prostatectomy). In such cases, an auxiliary TMA block using the same tissues should be constructed using larger tissue cores.



Resources: The National Cancer Institute (NCI, Bethesda, MD USA) has set up a Tissue Array Research Program, TARP (http://ccr.cancer.gov/tech_initiatives/tarp/) to facilitate access to multi-tumor TMA slides to investigators interested in procuring pre-designed TMA slides. There are two other divisions of the NCI namely, CBCTR and CPCTR (Central Breast/Prostate Cancer Tissue Resource databases respectively) which have a repository of pre-arrayed TMA slides. Access to TMA slides containing prostate and breast cancer cores is available from them at a nominal price after approval of the proposed intent of use.



On the other hand, commercial companies will also make TMA blocks if they are provided with the standard paraffin blocks (www.petagen.com) although the costs can get prohibitive if high-density arrays are planned. In a recent article, Mobasheri et al have provided a comprehensive list of the commercial companies constructing TMAs.[21]




 » Potential of TMA in India Top




Given the immense potential of this technology, it is clearly evident that TMAs will play a major role in the foreseeable future in the arena of evaluating potential biomarkers. There are a number of high-volume histopathology institutions within India like AIIMS, PGIMER, JIPMER and Tata Memorial Hospital. Any one of these institutes can operate a 'TMA core facility'. All other institutes could send in their blocks along with relevant clinico-pathological information for TMA construction. In return, these institutes would then have access to the TMA slides generated from the blocks at a nominal price that would hopefully cover for the pay of the technicians and computer programmers working at the core facility.



Two technical staff (one for receiving and the other for arraying blocks), one computer programmer (for computerized cataloguing of the TMA database and generating template MS Excel data files) and one pathologist for marking out areas to be punched are sufficient within such a core facility. [Figure - 2] depicts a potential hierarchy to streamline the process in our country. Sample forms that will be useful for recording array design (Form-A), clinico-pathological data of blocks received from the peripheral centers (Form-B); Form-C and D for scoring recording the clinico-pathologic data of the array. All outgoing forms can be included as multiple Excel worksheets in one single Excel file that makes data handling and integration an easier job. A useful thing for pathologists participating in such TMA facilities would be to learn to use MS Excel in a proficient manner so that they can record data efficiently. For a start, programmers can design the aforementioned Excel guide sheets based on the CHTNs Excel sheets available from their website http://faculty.virginia.edu/chtn-tma/2002N1/CHTN2002N1X.xls.



On the logistic front, a manual tissue microarrayer often comes at the price of a high-end microtome and the monetary savings from using TMAs will definitely offset the initial costs of establishment, in the long run. For partial funding of core center technologists, 20% of the TMA slides from tumor arrays may be allocated to foreign researchers at a nominal price to generate revenue.



TMA slides with relevant information could be used as thesis material by PhD and post-graduate pathology residents who are required to complete a thesis work in partial fulfillment of their residency program. Currently, pathology residents often have a difficult time accessing archival paraffin blocks, slides and clinical information in the process of working on their thesis. Unfortunately, many medical and even pathology postgraduates are often ignorant about this technology. Students, faculty and technicians at all levels should be educated about TMA technology. At the medical school level, the pathology curriculum should probably try to include a chapter on recent medical technology like TMA and others that have impacted significantly on the research front. At the postgraduate level, invited talks by experts in the field at national conferences like the IAPM would be a good way to introduce this technology at all levels in the scientific community. Another potential advantage is that a single TMA slide with all possible grades of any single tumor type (like prostate cancer) will help pathology post-graduates in mastering the fine art of tumor grading. This in turn will help in reducing inter-observer variability while grading these tumors in daily surgical pathology practice.



On the other hand, there will be abundant material for the faculty to conduct research without having to use up large amounts of costly antibodies. On the research front, there will be ample opportunities to collaborate with overseas institutions where access to histology tissues is relatively difficult owing to bureaucratic issues. The ample autopsy material available within India can serve as a valuable source of tissues for TMA blocks while collaborating foreign institutions can supply primary antibodies thus pooling resources.




 » Final word Top




TMA technology is a powerful proteomic platform that plays an integral role in understanding protein expression patterns in a wide variety of normal and neoplastic tissues. The technology is highly evolved and has abundant potential to bridge the chasm between translational research and clinical therapeutics. Given the wealth of tissue resources available in our country, it only seems that the adopting this state-of-the-art technology will go a long way in benefiting students and researchers alike in the time to come.



Addendum: All the hyperlinks have been tested and the websites are accessible as of December 29, 2004.

 
 » References Top

1.Wan WH, Fortuna MB, Furmanski P. A rapid and efficient method for testing immunohistochemical reactivity of monoclonal antibodies against multiple tissue samples simultaneously. J Immunol Methods 1987;103:121-9.  Back to cited text no. 1  [PUBMED]  
2.Kononen J, Bubendorf L, Kallioniemi A, Barlund M, Schraml P, Leighton S, et al. Tissue microarrays for high-throughput molecular profiling of tumor specimens. Nat Med 1998;4:844-7.  Back to cited text no. 2  [PUBMED]  
3.Mobasheri A, Marples D. Expression of the AQP-1 water channel in normal human tissues: A semiquantitative study using tissue microarray technology. Am J Physiol Cell Physiol 2004;286:C529-37.  Back to cited text no. 3  [PUBMED]  [FULLTEXT]
4.Moskaluk CA, Stoler MH. Agarose mold embedding of cultured cells for tissue microarrays. Diagn Mol Pathol 2002;11:234-8.  Back to cited text no. 4  [PUBMED]  [FULLTEXT]
5.Nocito A, Kononen J, Kallioniemi OP, Sauter G. Tissue microarrays (TMAs) for high-throughput molecular pathology research. Int J Cancer 2001;94:1-5.  Back to cited text no. 5  [PUBMED]  [FULLTEXT]
6.Shergill IS, Arya M. Tissue microarrays. Expert Rev Mol Diagn 2004;4:421-3.  Back to cited text no. 6  [PUBMED]  [FULLTEXT]
7.Shergill IS, Shergill NK, Arya M, Patel HR. Tissue microarrays: A current medical research tool. Curr Med Res Opin 2004;20:707-12.  Back to cited text no. 7  [PUBMED]  [FULLTEXT]
8.Rubin MA, Dunn R, Strawderman M, Pienta KJ. Tissue microarray sampling strategy for prostate cancer biomarker analysis. Am J Surg Pathol 2002;26:312-9.  Back to cited text no. 8  [PUBMED]  [FULLTEXT]
9.Hidalgo A, Pina P, Guerrero G, Lazos M, Salcedo M. A simple method for the construction of small format tissue arrays. J Clin Pathol 2003;56:144-6.  Back to cited text no. 9  [PUBMED]  [FULLTEXT]
10.Shaknovich R, Celestine A, Yang L, Cattoretti G. Novel relational database for tissue microarray analysis. Arch Pathol Lab Med 2003;127:492-4.  Back to cited text no. 10  [PUBMED]  [FULLTEXT]
11.Liu CL, Prapong W, Natkunam Y, Alizadeh A, Montgomery K, Gilks CB, et al. Software tools for high-throughput analysis and archiving of immunohistochemistry staining data obtained with tissue microarrays. Am J Pathol 2002;161:1557-65.  Back to cited text no. 11  [PUBMED]  [FULLTEXT]
12.Berman JJ, Edgerton ME, Friedman BA. The tissue microarray data exchange specification: A community-based, open source tool for sharing tissue microarray data. BMC Med Inform Decis Mak 2003;3:5.  Back to cited text no. 12  [PUBMED]  [FULLTEXT]
13.Berman JJ, Datta M, Kajdacsy-Balla A, Melamed J, Orenstein J, Dobbin K, et al. The tissue microarray data exchange specification: Implementation by the Cooperative Prostate Cancer Tissue Resource. BMC Bioinformatics 2004;5:19.  Back to cited text no. 13  [PUBMED]  [FULLTEXT]
14.Manley S, Mucci NR, De Marzo AM, Rubin MA. Relational database structure to manage high-density tissue microarray data and images for pathology studies focusing on clinical outcome: The prostate specialized program of research excellence model. Am J Pathol 2001;159:837-43.  Back to cited text no. 14  [PUBMED]  [FULLTEXT]
15.Schraml P, Kononen J, Bubendorf L, Moch H, Bissig H, Nocito A, et al. Tissue microarrays for gene amplification surveys in many different tumor types. Clin Cancer Res 1999;5:1966-75.  Back to cited text no. 15  [PUBMED]  [FULLTEXT]
16.Milanes-Yearsley M, Hammond ME, Pajak TF, Cooper JS, Chang C, Griffin T, et al. Tissue micro-array: A cost and time-effective method for correlative studies by regional and national cancer study groups. Mod Pathol 2002;15:1366-73.  Back to cited text no. 16  [PUBMED]  
17.van de Rijn M, Gilks CB. Applications of microarrays to histopathology. Histopathology 2004;44:97-108.  Back to cited text no. 17  [PUBMED]  [FULLTEXT]
18.Natkunam Y, Warnke RA, Montgomery K, Falini B, van De Rijn M. Analysis of MUM1/IRF4 protein expression using tissue microarrays and immunohistochemistry. Mod Pathol 2001;14:686-94.  Back to cited text no. 18  [PUBMED]  
19.Bubendorf L, Kolmer M, Kononen J, Koivisto P, Mousses S, Chen Y, et al. Hormone therapy failure in human prostate cancer: Analysis by complementary DNA and tissue microarrays. J Natl Cancer Inst 1999;91:1758-64.  Back to cited text no. 19  [PUBMED]  [FULLTEXT]
20.Camp RL, Charette LA, Rimm DL. Validation of tissue microarray technology in breast carcinoma. Lab Invest 2000;80:1943-9.  Back to cited text no. 20  [PUBMED]  
21.Mobasheri A, Airley R, Foster CS, Schulze-Tanzil G, Shakibaei M. Post-genomic applications of tissue microarrays: Basic research, prognostic oncology, clinical genomics and drug discovery. Histol Histopathol 2004;19:325-35.  Back to cited text no. 21  [PUBMED]  [FULLTEXT]


    Figures

[Figure - 1], [Figure - 2]

This article has been cited by
1 How to make tissue microarrays
Mike Parsons,Heike Grabsch
Diagnostic Histopathology. 2009; 15(3): 142
[Pubmed] | [DOI]
2 How to make tissue microarrays
Parsons, M., Grabsch, H.
Diagnostic Histopathology. 2009; 15(3): 142-150
[Pubmed]



 

Top
Print this article  Email this article
Previous article Next article

    

  Site Map | What's new | Copyright and Disclaimer
  Online since 1st April '07
  © 2007 - Indian Journal of Cancer | Published by Wolters Kluwer - Medknow