Scoring proliferating cells

Scoring the extent of proliferation is especially important in a clinical setting. The percentage of Ki67-positive cells, for example, can be used to score the severity and course of cancer. There are several scoring techniques available for use with the proliferation proteins methods, each with their own strengths and limitations. We’ve highlighted in green our recommended technique for scoring cell proliferation via IHC.

Modified from Reid et all. (2015)¹¹.

‘Eye-balling’

This involves looking at a slide under a microscope, typically at a relatively low power (x10 objective), and estimating the percentage of proliferation-positive cells. This does not involve any counting of individual cells.

While this method is widely used, quick, cheap, and advocated by some guideline papers, it remains a generally inaccurate method.

Eye counting with a microscope

This method consists of ‘real-time’ counting of proliferation -positive cells under a microscopic at an intermediate power (x20 objective), focusing on identified 'hot spots' (areas containing large amounts of proliferation-positive cells).

This method can involve the use of grids and other counting tools frequently seen in pathology labs. However, even with the aid of such tools, this method can lead to errors due to counting the same proliferation-positive cells more than once.

Manual counting of camera-captured/digital image

Like eye counting with a microscope, this is a manual process but involves looking at either a printout or a screen capture of a section previously visualized with the microscope. This is typically done under low power (x10 objective). Reviewers then manually mark proliferation-positive cells on a physical print-out, or on the screen using simple software.

Counting in this manner is very convenient and allows reviewers to easily avoid duplicate scoring.

Automated counting

This is divided into using an automated counting microscope, and using software, such as ImageJ, to analyze captured images. Both methods automatically score proliferation-positive cells from manually-selected hot spots.

Using software to manually count proliferation-positive cells requires either knowledge of plugin design (for software like ImageJ) or dependence on external programs hosted online (eg from the National Institutes of Health website).

Automatic counting microscopes can often require extensive calibration, and some struggle to score partial staining. These are also very expensive.

References

1. Breunig, J. J., Arellano, J. I., Macklis, J. D. , et al. Everything that Glitters Isn’t Gold: A Critical Review of Postnatal Neural Precursor Analyses. Cell Stem Cell 1 ,612–627 (2007)
2. Anda, S., Boye, E., Grallert, B. Cell-cycle analyses using thymidine analogues in fission yeast. PLoS One  9 ,1-9 (2014)
3. Oka, S., Uramoto, H. , Shimokawa, H., et al. The expression of Ki-67, but not proliferating cell nuclear antigen, predicts poor disease free survival in patients with adenocarcinoma of the lung. Anticancer Res.  31 ,4277–4282 (2011)
4. Mateoiu, C. , Pirici, A., Bogdan, F. L. Immunohistochemical nuclear staining for p53, PCNA, ki-67 and bcl-2 in different histologic variants of basal cell carcinoma. Rom. J. Morphol. Embryol.  52 ,315–319 (2011)
5. Salehinejad, J. , et al. Immunohistochemical detection of p53 and PCNA in ameloblastoma and adenomatoid odontogenic tumor. J. Oral Sci.  53 ,213–217 (2011)
6. Bologna-Molina, R., Mosqueda-Taylor, A., Molina-Frechero, N., et al. Comparison of the value of PCNA and Ki-67 as markers of cell proliferation in ameloblastic tumors. Med. Oral Patol. Oral Cir. Bucal  18 , (2013)
7. Carreón-Burciaga, R. G., González-González, R., Molina-Frechero, N., et al. Immunoexpression of Ki-67, MCM2, and MCM3 in Ameloblastoma and Ameloblastic Carcinoma and Their Correlations with Clinical and Histopathological Patterns. Dis. Markers ,8 pages (2015)
8. Joshi, S., et al. Digital imaging in the immunohistochemical evaluation of the proliferation markers Ki67, MCM2 and Geminin, in early breast cancer, and their putative prognostic value. BMC Cancer  15 ,546 (2015)
9. Li, L. T., Jiang, G., Chen, Q. , et al. Ki67 is a promising molecular target in the diagnosis of cancer (Review). Mol. Med. Rep.  11 ,1566–1572 (2015)
10. Szelachowska, J., et al. Mcm-2 protein expression predicts prognosis better than Ki-67 antigen in oral cavity squamocellular carcinoma. Anticancer Res.  26 ,2473–2478 (2006)
11. Reid, M. D., et al. Calculation of the Ki67 index in pancreatic neuroendocrine tumors: a comparative analysis of four counting methodologies. Mod. Pathol.  28 ,686–94 (2015)