RRML - Optimisation of the quantitative analysis of inflammatory cell infiltrates in breast cancer

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ISSN-L: 1841-6624

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Concept, Design & Programming
Dr. Adrian Man

Nr. 22(3)/2014 DOI:10.2478/rrlm-2014-0035

Optimisation of the quantitative analysis of inflammatory cell infiltrates in breast cancer

Optimizarea analizei cantitative a infiltratului celular inflamator în cancerul mamar

Anca-Raluca Vrânceanu, Cristina Claudia Tărniceriu, Daniela Jitaru, Cristina Terinte, Florin Zugun-Eloae, Eugen Carasevici


In this study we aimed to determine the optimal cut-off point for the quantitative analysis of inflammatory infiltrates in breast cancer, using the HistoQuest system. We used samples of tumour breast tissue which were IHC stained with CD68 and CD8 and subsequently tested with automated systems on three regions: intratumoral, invasive front and peritumoral, using the HistoQuest system. In order to delimit between positive and negative cells on histograms and scattergrams, we need to set a cut-off value. We compared 5 cut-off types for optimisation of the quantitative analysis. The results obtained statistically for the CD8 marker for all 5 types of cut-offs applied on IT, PT and IF regions did not show statistically significant differences (p > 0.05). As for the CD68 marker, we found statistically significant differences (p < 0.05) between manual cut-offs (C2 – manual and C3 – manual, arithmetic mean) and automated cut-offs placed by the software (C1 – automated, C4 – negative region, and C5 – automated, arithmetic mean), which suggests that the use of an automated cut-off should be preferred in order to remove the subjective factor. The automated cut-off setting generates objective and reproducible data and can be used in subsequent quantitative analyses.

Keywords: quantitative analysis, cut-off, inflammatory infiltrates, breast cancer

Received: 9.4.2014
Accepted: 1.9.2014
Published: 8.9.2014

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How to cite
Vrânceanu AR, Tărniceriu CC, Jitaru D, Terinte C, Zugun-Eloae F, Carasevici E. Optimisation of the quantitative analysis of inflammatory cell infiltrates in breast cancer. Rev Romana Med Lab. 2014;22(3):335-45. DOI:10.2478/rrlm-2014-0035