AUTOMATED ANALYSIS OF CELL DENSITY IN BREAST CANCER AS AN ADDITIONAL METHOD OF INCREASING OBJECTIVITY AND ACCURACY OF BREAST CANCER PROGNOSIS

Introduction. In the last ten years, it became obvious that on the molecular level breast cancer is a group of heterogenous tumors. The current objective of routine clinical practice of treatment prescription includes accurate disease prognosis for every individual patient and conviction that the risk of breast cancer recurrence after adjuvant hormone therapy without adjuvant chemotherapy doesn’t increase.

The study objective is to evaluate how clinical use of risk associated with cell density can in practice improve prognosis of recurrence risk in patients with breast cancer after standard clinical and pathomorphological examinations.

Materials and methods. The article analyzes therapy results using data from the cumulative cancer registry of breast cancer diagnosis and treatment of the N.N. Petrov National Medical Research Oncology Center in 2000–2009. The database includes information on diagnosis, treatment, and survival of 5106 patients with breast cancer. Archived material (from 2000 to 2009) from paraffin blocks of the “targeted group” for methods of molecular and genetic profiling was poured into recipient blocks, stained with corresponding antibodies such as widely used ER, PR, HER2/neu, Ki-67 markers as well as poorly studied markers: cell density, р53, CK5/6, CK14, CD4/CD8, p63, EGFR, FOXP3, AR, FOX1.

Results. The study of 1118 patients with stage T1–2N0M0 breast cancer has shown that analysis of risk associated with cell density allows to predict disease outcome. Correlation between the marker and the grade of histological malignancy is more rare than for Ki-67 determined in this patient group. As a result, determination of cell density is an additional method to increase objectivity and accuracy of breast cancer prognosis.

Conclusions. Automated cell density analysis for breast cancer is almost fully operator-independent which increases accuracy and objectivity of the results. Cell density in breast cancer lower than 3000 cells/mm² is a favorable prognostic factor.

1. Семиглазов В.Ф., Палтуев Р.М., Манихас А.Г. и др. Клинические рекомендации РООМ по диагностике и лечению рака молочной железы. М.: АБВ-пресс, 2015. [Semiglazov V.F., Paltuev R.M., Manikhas A.G. et al. RAOM clinical guidelines on breast cancer diagnosis and treatment. Moscow: ABV-Press, 2015. (In Russ.)].

2. Семиглазов В.Ф., Палтуев Р.М., Семиглазов В.В. и др. Общие рекомендации по лечению раннего рака молочной железы St. Gallen-2015, адаптированные экспертами Российского общества онкомаммологов. Опухоли женской репродуктивной системы 2015;11(3): 43–60. [Semiglazov V.F., Paltuev R.M., Semiglazov V.V. et al. General St. Gallen-2015 guidelines for the treatment of early breast cancer (adapted by the experts of the Russian Society of Breast Oncologists).Opukholi zhenskoy reproduktivnoy sistemy = Tumors of female reproductive system 2015;11(3):43–60. (In Russ.)].

3. Семиглазов В.Ф., Семиглазов В.В., Палтуев Р.М. и др. Адъювантная химиотерапия рака молочной железы: поиск новых путей планирования. Вопросы онкологии 2014;60(1):102–8. [Semiglazov V.F., Semiglazov V.V., Paltuev R.M. et al. Adjuvant chemotherapy for breast cancer: search for new ways of planning. Voprosy onkologii = Problems in Oncology 2014;60(1):102–8. (In Russ.)].

4. Шатова Ю.С., Франциянц Е.М., Новикова И.А. и др. Локальный гормональный фон опухоли и перифокальной зоны у больных раком молочной железы: данные и перспективы их применения. Опухоли женской репродуктивной системы 2016;12(3):30–5. [Shatova Yu.S., Frantsiyants E.M., Novikova I.A. et al. The local hormonal environment of tumor and perifocal zone in patients with breast cancer: data and prospects of their application. Opukholi zhenskoy reproduktivnoy sistemy = Tumors of female reproductive system. 2016;12(3):30–35. (In Russ.)].

5. Манихас А.Г., Бабешкин Р.Н., Палтуев Р.М., Манихас Г.М. Место неоадъювантной химиотерапии трижды негативного рака молочной железы в Санкт-Петербургском городском клиническом онкологическом диспансере. Опухоли женской репродуктивной системы 2016;12(2): 26–34. [Manikhas A.G., Babeshkin R.N., Paltuev R.M., Manikhas G.M. The role of neoadjuvant chemotherapy of triple-negative breast cancer in St. Petersburg City Clinical Oncological Dispensary. Opukholi zhenskoy reproduktivnoy sistemy = Tumors of female reproductive system. 2016;12(2):26–34. (In Russ.)].

6. Perou C.M., Sorlie T., Eisen M.B. et al. Molecular portraits of human breast tumours. Nature 2000;406(6797):747–52. DOI: 10.1038/35021093. PMID: 10963602.

7. Sorlie T., Perou C.M., Tibshirani R. et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 2001;98(19):10869–74. DOI: 10.1073/pnas.191367098. PMID: 11553815.

8. Sotiriou C., Neo S.Y., McShane L.M. et al. Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci USA 2003;100(18):10393–8. DOI: 10.1073/pnas.1732912100. PMID: 12917485.

9. Carlson R.W., Brown E., Burstein H.J. et al. NCCN Task Force report: adjuvant therapy for breast cancer. J Natl Compr Canc Netw 2006;4(Suppl 1):S1–26. PMID: 16507275.

10. Goldhirsch A., Wood W.C., Coates A.S. et al. Strategies for subtypes – dealing with the diversity of breast cancer: highlights of the St. Gallen international expert consensus on the primary therapy of early breast cancer 2011. Ann Oncol 2011;22(8):1736–47. DOI: 10.1093/annonc/mdr304. PMID: 21709140.