Summary

Колоректального рака на поверхности клеток белков профилировки с Microarray антитела и флуоресценции мультиплексирования

Published: September 25, 2011
doi:

Summary

Мы описали процедуру разбивки колоректального рака (КРР) для получения жизнеспособных отдельных клеток, которые затем захвачен на индивидуальные микрочипов антител признании поверхностных антигенов (DotScan CRC микрочипов). Суб-популяции клеток, связанных с микрочипов можно профилировать по флуоресценции мультиплексирования с использованием моноклональных антител помеченные флуоресцентными красителями.

Abstract

The current prognosis and classification of CRC relies on staging systems that integrate histopathologic and clinical findings. However, in the majority of CRC cases, cell dysfunction is the result of numerous mutations that modify protein expression and post-translational modification1.

A number of cell surface antigens, including cluster of differentiation (CD) antigens, have been identified as potential prognostic or metastatic biomarkers in CRC. These antigens make ideal biomarkers as their expression often changes with tumour progression or interactions with other cell types, such as tumour-infiltrating lymphocytes (TILs) and tumour-associated macrophages (TAMs).

The use of immunohistochemistry (IHC) for cancer sub-classification and prognostication is well established for some tumour types2,3. However, no single ‘marker’ has shown prognostic significance greater than clinico-pathological staging or gained wide acceptance for use in routine pathology reporting of all CRC cases.

A more recent approach to prognostic stratification of disease phenotypes relies on surface protein profiles using multiple ‘markers’. While expression profiling of tumours using proteomic techniques such as iTRAQ is a powerful tool for the discovery of biomarkers4, it is not optimal for routine use in diagnostic laboratories and cannot distinguish different cell types in a mixed population. In addition, large amounts of tumour tissue are required for the profiling of purified plasma membrane glycoproteins by these methods.

In this video we described a simple method for surface proteome profiling of viable cells from disaggregated CRC samples using a DotScan CRC antibody microarray. The 122-antibody microarray consists of a standard 82-antibody region recognizing a range of lineage-specific leukocyte markers, adhesion molecules, receptors and markers of inflammation and immune response5, together with a satellite region for detection of 40 potentially prognostic markers for CRC. Cells are captured only on antibodies for which they express the corresponding antigen. The cell density per dot, determined by optical scanning, reflects the proportion of cells expressing that antigen, the level of expression of the antigen and affinity of the antibody6.

For CRC tissue or normal intestinal mucosa, optical scans reflect the immunophenotype of mixed populations of cells. Fluorescence multiplexing can then be used to profile selected sub-populations of cells of interest captured on the array. For example, Alexa 647-anti-epithelial cell adhesion molecule (EpCAM; CD326), is a pan-epithelial differentiation antigen that was used to detect CRC cells and also epithelial cells of normal intestinal mucosa, while Phycoerythrin-anti-CD3, was used to detect infiltrating T-cells7. The DotScan CRC microarray should be the prototype for a diagnostic alternative to the anatomically-based CRC staging system.

Protocol

Рисунок 1. Набор операций для приготовления суспензии живых клеток от хирургического образца о правах ребенка. 1. Клинический пример разбивки Все образцы были собраны из Королевской больницы Принца Альфр…

Discussion

В этом видео показано, как DotScan микрочипов антитела могут быть использованы в простых, полуколичественный способ изучения профилей поверхностного антигена для популяции клеток из ткани КПР.

Получение жизнеспособных суспензии отдельных клеток из ткани имеет решающее з…

Disclosures

The authors have nothing to disclose.

Acknowledgements

Мы благодарим сотрудников Анатомические лаборатории патологии Королевский Принца Альфреда и Согласия Репатриация Больницы для сбора свежих образцов КПР и нормальной слизистой оболочки кишечника. Работа финансировалась института рака Нового Южного Уэльса Поступательное Программа грантов.

Materials

Name of reagent or equipment Company Catalogue number Comments
Hanks’ balanced salt solution Sigma-Aldrich H6136-10X1L Buffered with 25 mM Hepes (Sigma #H3375)
Airpure biological safety cabinet class II Westinghouse 1687-2340/612  
Surgical blades Livingstone 090609 Pack of 100
RPMI 1640 with 2 mM Hepes Sigma-Aldrich R4130-10X1L  
Collagenase type 4 Worthington 4188  
Deoxyribonuclease 1 Sigma-Aldrich DN25-1G  
Terumo Syringe (10 mL) Terumo SS+10L Box of 100
Filcon filter (200 μm) BD Biosciences 340615  
Filcon filter (50 μm) Filcon filter (50 μm) Filcon filter (50 μm) Filcon filter (50 μm) 340603  
Fetal calf serum Gibco/Invitrogen 10099-141  
Centrifuge 5810 R Eppendorf 7017  
Dimethyl sulphoxide Sigma-Aldrich D2650  
Trypan blue Sigma-Aldrich T8154  
Hemocymeter Technocolor Neubar Hirschmann not available  
Light microscope Nikon Nikon TMS  
Cyrovial tubes Greiner bio-one 121278  
Cryo freezing contrainer Nalgene 5100-0001  
DotScan antibody microarray kit Medsaic not available  
DotScan microarray wash tray Medsaic not available  
KimWipes Kimberly-Clark 4103  
Formaldehyde 37% Sigma-Aldrich F1635-500ML  
DotReaderTM Medsaic not available  
Bovine serum albumin Sigma-Aldrich A9418-10G  
Heat-inactivated AB serum 2% Invitrogen 34005100  
Phycoerythrin-conjugated CD3 Beckman Coulter ET386  
AlexaFluor647-conjugated EpCAM BioLegend 324212  
Typhoon FLA 9000 GE Healthcare 28-9558-08 532 nm laser, 580 BP30 emission filter for PE. 633 nm laser and 670 BP30 emission filter for Alexa647
MultiExperiment Viewer v4.4 TM4 Microarray Software Suite Open – source software (Ref 11)  

References

  1. Steinert, R., Buschmann, T., vander Linden, M., Fels, L. M., Lippert, H., Reymond, M. A. The role of proteomics in the diagnosis and outcome prediction in colorectal cancer. Technol. Cancer. Res. Treat. 1, 297 (2002).
  2. Eifel, P., Axelson, J. A., Costa, J., Crowley, J., Curran, W. J., Deshler, A., Fulton, S., Hendricks, C. B., Kemeny, M., Kornblith, A. B., Louis, T. A., Markman, M., Mayer, R., Roter, D. National Institutes of Health Consensus Development Conference Statement: adjuvant therapy for breast cancer. J. Natl. Canc. Inst. 93, 979 (2001).
  3. Swerdlow, S. H., Campo, E., Harris, H. L., Jaffe, E. S., Pileri, S. A., Stein, H., Thiele, J., Vardiman, J. W. WHO classification of tumour of haematopoietic and lymphoid tissues. IARC WHO Classification of Tumours. 2, (2008).
  4. Xiao, G. G., Recker, R. R., Deng, H. W. Recent advances in proteomics and cancer biomarker discovery. Clin. Med. Oncol. , (2008).
  5. Belov, L., Mulligan, S. P., Barber, N., Woolfson, A., Scott, M., Stoner, K., Chrisp, J. S., Sewell, W. A., Bradstock, K. F., Bandall, L., Pascovici, D. S., Thomas, M., Erber, W., Huang, P., et al. Analysis of human leukaemias and lymphomas using extensive immunophenotypes from an antibody microarray. Br. J. Haematol. 135, 184 (2006).
  6. Belov, L., Huang, P., Barber, N., Mulligan, S. P., Christopherson, R. I. Identification of repertories of surface antigens on leukemias using an antibody microarray. Proteomics. 3, 2147 (2003).
  7. Zhou, J., Belov, L., Huang, P. Y., Shin, J., Solomon, M. J., Chapuis, P. H., Bokey, L., Chan, C., Clarke, C., Clarke, S. J., Christopherson, R. I. Surface antigen profiling of colorectal cancer using antibody microarrays with fluorescence multiplexing. J. Immunol. Methods. 355 (1-2), 40-51 (2010).
  8. Ellmark, P., Belov, L., Huang, P., Lee, C. S., Solomon, M. J., Morgan, D. K., Christopherson, R. I. Multiplex detection of surface molecules on colorectal cancers. Proteomics. 6, 1791 (2006).
  9. Pearson, J. P., Allen, A., Hutton, D. A. Rheology of mucin. Methods Mol. Biol. 125, 99 (2000).
  10. Yang, Y. H., Dudoit, S., Luu, P., Lin, D. M., Peng, V., Ngai, J., Speed, T. P. Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Res. 30, 15 (2002).
  11. Al Saeed, ., et al. TMA: A free, open-source system for microarray data management and analysis. BioTechniques. 34, 374-378 (2003).

Play Video

Cite This Article
Zhou, J., Belov, L., Solomon, M. J., Chan, C., Clarke, S. J., Christopherson, R. I. Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing. J. Vis. Exp. (55), e3322, doi:10.3791/3322 (2011).

View Video