Рак молочної залози. Від молекулярної біології до персонифікованої терапії.

Автор(и)

  • I. N. Bondarenko ГУ «Днепропетровская медицинская академия МЗ Украины», Ukraine
  • Mohammad H. Elhajj ГУ «Днепропетровская медицинская академия МЗ Украины», Ukraine
  • A. V. Prokhach ГУ «Днепропетровская медицинская академия МЗ Украины», Ukraine
  • V. F. Zavizion ГУ «Днепропетровская медицинская академия МЗ Украины», Ukraine
  • K. O. Chebanov Городская многопрофильная клиническая больница №4, г. Днепропетровск, Ukraine

DOI:

https://doi.org/10.26641/1997-9665.2016.1.18-25

Ключові слова:

рак молочної залози, молекулярна біологія, молекулярні підтипи, гетерогенність, персоніфіковане лікування

Анотація

Досягнення молекулярної біології принципово змінили підходи до системного лікування раку молочної залози. Клінічні рішення щодо вибору оптимальних схем лікування приймаються на основі імуногістохімічної та молекулярно-генетичних класифікацій. Це призвело до переходу від емпіричного до індивідуалізованого і персоніфікованого лікування. Основою для таких підходів є знання про особливості молекулярної епідеміології, гетерогенності, експресійних молекулярних підтипів, прогностичних і предиктивних біомаркерів раку молочної залози, що обговорюються в даному огляді.

Посилання

Siegel R, Naishadham D, Jemal A. Cancer statistics. CA: a cancer journal for clinicians. 2013;63(11):1.

Parkin DM, Bray F, Ferlay J, Pisani P. Global cancer statistics. CA: a cancer journal for clinicians. 2005;55:74-108.

Quinn M, Wood H, Cooper N, authors. Can-cer Atlas of the United Kingdom and Ireland 1991–2000. London: ONS; 2005. 68 p.

Jemal A, Siegel R, Ward E. Cancer statistics. CA Cancer J Clin. 2008;58(2): 71-96.

Perou CM, Sorlie T, Eisen MB. Molecular portraits of human breast tumours. Nature. 2000;406:747-52.

Sorlie T, Perou CM, Tibshirani R. Gene ex-pression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A. 2001;98:10869-74.

Mishra A, Verma M. Cancer Biomarkers: Are We Ready for the Prime Time? Cancers. 2010;2 (1):190-208.

Chekhun VF, Buchinska LG, Glushenko LG. [Features of functional onkogene as the foundation of modern diagnosis and treatment of patients with malignant tumors]. Oncologya. 2009; 11 (1): 55–8. Ukrainian.

McPherson K, Steel CM, Dixon JM ABC of breast diseases. Breast cancer-epidemiology, risk factors, and genetics. BMJ. 2010; 321: 624-8.

Dunning, AM, Healey CS, Pharoah PD, Teare MD, Ponder BA, Easton DF. A systematic review of genetic polymorphisms and breast cancer risk. Cancer Epidemiol Biomarkers Prev. 1999;8: 843-54.

Chekhun VF, Zhylchuk VE, Lukyanova NY. Expression of drug resistance proteins in triple-receptor-negative tumors as the basis of individual-ized therapy of the breast cancer patients. Exp Oncol. 2009; 31 (2):123–4.

Letyagin VP, Visotska VP, Legkov AA, Pogodina EM, authors. [Treatment of malignant and non-malignant diseases of breast]. Moscow: Rondo; 1997. 287 p. Russian.

Fritz AG, editor. 3rd. Geneva: World Health Organization. International Classification of Diseases for Oncology: ICD-O; 2010. 48 p.

Eheman CR, Shaw KM, Ryerson AB, Miller JW. The changing incidence of in situ and invasive ductal and lobular breast carcinomas: United States, 1999–2004. Cancer Epidemiol. Biomarkers Prev. 2005;18 (6): 1763–9.

Lakhani S, Ellis I, Schnitt S, authors. WHO Classification of Tumours of the Breast 4th. Lyon: IARC Press; 2012. 52 p.

Tavassoli FA, Devilee P, editors. Pathology and Genetics of Tumours of the Breast and Female Genital Organs. Lyon: IARC Press; 2003. 53 p.

Elston CW, Ellis IO. Pathologic prognostic factors in breast cancer. The value of histological grades in breast cancer. Experience from a large study with long-term follow-up. Histopathology. 1991;19:403-10.

Sandro S, Ankita T, Ayse E, Bin W, Terri W, Rong Hu, Chuck H, McNamara G, Schwede M. Taxonomy of breast cancer based on normal cell phenotype predicts outcome. J Clin Invest. 2014;124(2):859-70.

Rayson D, Adjei AA, Suman VJ, Wold LE, Ingle JN. Metaplastic breast cancer: prognosis and response to systemic therapy. Annals of Oncology. 1999; 10(4):413-9.

Galea MH, Blamey RW, Elston CE. The Nottingham Prognostic Index in primary breast can-cer. Breast Cancer Res Treat. 1992; 22:207-19.

Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA. 2001;98:10869-74.

Eroles P, Bosch A, Pérez-Fidalgo JA, Lluch A. Molecular biology in breast cancer: intrinsic sub-types and signaling pathways. Cancer Treat Rev. 2012; 38:698–707.

Curtis, C. et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature. 2012; 486: 346-52.

Cheang MCU, Chia SK, Voduc D. Ki67 in-dex, HER2 status, and prognosis of patients with luminal B breast cancer. J Natl Cancer Inst. 2009; 101:736-50.

Geyer FC, Reis-Filho JS. Microarray-based gene expression profiling as clinical tool for breast cancer management: are we there yet? Int J Surg Pathol. 2009; 17:285-302.

Parker JS, Mullins M, Cheang MC. Super-vised risk predictor of breast cancer based on intrin-sic subtypes. J Clin Oncol. 2009; 27:1160-7.

Makretsov NA, Huntsman DG, Nielsen TO. Hierarchical clustering analysis of tissue microarray immunostaining data identifies prognostically signif-icant groups of breast carcinoma. Clin Cancer Res. 2004;10:6143-51.

Zardavas D, Pugliano L, Piccart M. Person-alized therapy for breast cancer: a dream or a reali-ty? Future Oncol. 2013;9:1105-19.

Hu Z, Fan C, Oh DS, Marron JS, He X, Qaqish BF, Livasy C, Carey LA, Reynolds E, Dress-ler L. The molecular portraits of breast tumors are conserved across microarray platforms. BMC Ge-nomics. 2006; 7:96.

Sun J, Wei W. Associations and indications of Ki67 expression with clinicopathological parame-ters and molecular subtypes in invasive breast can-cer: A population-based study. Oncol Lett. 2015;10(3):1741-8.

Sotiriou C, Neo SY, McShane LM, Korn EL, Long PM, Jazaeri A, Martiat P, Fox SB, Harris AL, Liu ET. Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci USA. 2003; 100:10393-8.

Alymani NA, Smith MD, Williams DJ, Petty RD. Predictive biomarkers for personalised anti-cancer drug use: Discovery to clinical implementa-tion. Eur J Cancer. 2010;46:869-79.

Bernardo V, Lourenço SQ, Cruz R, Monteiro-Leal LH, Silva LE, Camisasca DR, Farina M, Lins U. Reproducibility of immunostaining quantification and description of a new digital image processing procedure for quantitative evaluation of immunohistochemistry in pathology. Microsc Microanal. 2009;15:353–65.

Fisher B, Redmond C, Fisher ER, Caplan R. Relative worth of estrogen or progesterone receptor and pathologic characteristics of differentiation as indicators of prognosis in node-negative breast can-cer patients: Findings from National Surgical Adju-vant Breast and Bowel Project Protocol B-06. J Clin Oncol. 1988;6(7):1076-87.

Clark GM, McGuire WL. Steroid receptors and other prognostic factors in primary breast can-cer. Semin Oncol. 1988;15(2):20-5.

Baselga J, Swain SM. Novel anticancer tar-gets: revisiting ERBB2 and discovering ERBB3. Nat Rev Cancer. 2009;9 (7):463-75.

Slamon DJ, Clark GM, Wong SG, Levin WJ, Ullrich A, McGuire WL. Human breast cancer: correlation of relapse and survival with amplifica-tion of the HER-2/neu oncogene. Science.1987; 235(4785):177-82.

Urruticoechea A, Smith IE, Dowsett M. Proliferation marker Ki-67 in early breast cancer. J Clin Oncol. 2005;23:7212-20.

Vogelstein B, Lane D, Levine AJ: Surfing the p53 network. Nature. 2001;408:307-10.

Done SJ, Eskandarian S, Bull S, Redston M, Andrulis IL. P53 mis- sense mutations in microdissected high-grade ductal carci- noma in situ of the breast. J Natl Cancer Inst. 2001;93:700-4.

##submission.downloads##

Номер

Розділ

Статті