Ключевые слова
Как цитировать
Аннотация
Сегодня результаты развития геномных технологий меняют подход к диагностике и лечению онкологических заболеваний. Так, клинические подходы к профилактике, диагностике и лечению рака молочной железы сместились в сторону использования молекулярно-генетической и иммуногистохимической информации.
Целью настоящего обзора является описание возможностей применения различных молекулярно-генетических исследований опухолевой ткани с целью повышения эффективности лечения рака молочной железы. В обзоре обсуждаются результаты применения современных молекулярных (The Cancer Genome Atlas) и иммуногистохимических (суррогатных) маркеров, обеспечивающих разделение РМЖ по молекулярным подтипам, приведены преимущества и недостатки такого разделения. Представлены основные характеристики современных экспрессионных прогностических тестов, обсуждается целесообразность и сложности применения высокопроизводительного секвенирования, в том числе расширенных мультигенных NGS-панелей в клинической практике. Обзор предназначен для ординаторов и аспирантов, врачей-генетиков и врачей-онкологов, использующих в своей работе результаты современных молекулярно-генетических тестов.
Библиографические ссылки
International Human Genome Sequencing Consortium. Finishing the euchromatic sequence of the human genome. Nature. 2004;431(7011):931-945. https://doi.org/10.1038/nature03001.
Collins F. Cancer: a disease of the genome. Cancer Res. 2007;67(9_Supplement):PL01-01.
Bader JS. The Panorama of cancer genetics. Cancer Res. 2021;81(10):2586-2587. https://doi.org/10.1158/0008-5472.CAN-21-0885.
Johnson TM. Perspective on precision medicine in oncology. Pharmacotherapy. 2017;37(9):988-989. https://doi.org/10.1002/phar.1975.
Li MM, Drilon A, Laetsch TW. Editorial. Cancer Genet. 2022;266-267:37-38. https://doi.org/10.1016/j.cancergen.2022.06.002.
Napoli GC, Chau CH, Figg WD. Single whole genome sequencing analysis blazes the trail for precision medicine. Cancer Biol Ther. 2022;23(1):134-135. https://doi.org/10.1080/15384047.2022.2033058.
Arnold M, Morgan E, Rumgay H, et al. Current and future burden of breast cancer: Global statistics for 2020 and 2040. Breast. 2022;66:15-23. https://doi.org/10.1016/j.breast.2022.08.010.
Zdrav.Expert [Internet] [cited 2023 Jun 23]. Available from: https://zdrav.expert/index.php.
Злокачественные новообразования в России в 2021 году (заболеваемость и смертность). Под ред. А.Д. Каприна, В.В. Старинского, А.О. Шахзадовой – М.: МНИОИ им. П.А. Герцена − филиал ФГБУ «НМИЦ радиологии» Минздрава России. 2022:252 [Malignant neoplasms in Russia in 2021 (morbidity and mortality). AD Kaprin, VV Starinsky, AO Shakhzadova, eds. M.: P.A. Herzen MNIOI - a branch of FGBU "NMRC Radiology" of the Ministry of Health of Russia. 2022:252 (Russ.)].
The Cancer Genome Atlas Program [Internet]. National Cancer Institute 2022 [cited 2022 Sep 8]. Available from: https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga.
Carpten JC, Mardis ER. The era of precision oncogenomics. Cold Spring Harb Mol Case Stud. 2018;4(2):a002915. https://doi.org/10.1101/mcs.a002915.
De S, Ganesan S. Looking beyond drivers and passengers in cancer genome sequencing data. Ann Oncol. 2017;28(5):938-945. https://doi.org/10.1093/annonc/mdw677.
Yu B, O'Toole SA, Trent RJ. Somatic DNA mutation analysis in targeted therapy of solid tumours. Transl Pediatr. 2015;4(2):125-138. https://doi.org/10.3978/j.issn.2224-4336.2015.04.04.
Perou CM, Sørlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature. 2000;406(6797):747-752. https://doi.org/10.1038/35021093.
Sørlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA. 2001;98(19):10869-10874. https://doi.org/10.1073/pnas.191367098.
Ahr A, Karn T, Solbach C, et al. Identification of high risk breast-cancer patients by gene expression profiling. Lancet. 2002;359(9301):131-132. https://doi.org/10.1016/S0140-6736(02)07337-3.
Van 't Veer LJ, Dai H, van de Vijver MJ, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature. 2002;415(6871):530-536. https://doi.org/10.1038/415530a.
Sotiriou C, Neo SY, McShane LM, 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):10393-10398. https://doi.org/10.1073/pnas.1732912100.
Lucito R, Healy J, Alexander J, et al. Representational oligonucleotide microarray analysis: a high-resolution method to detect genome copy number variation. Genome Res. 2003;13(10):2291-2305. https://doi.org/10.1101/gr.1349003.
Hicks J, Krasnitz A, Lakshmi B, et al. Novel patterns of genome rearrangement and their association with survival in breast cancer. Genome Res. 2006;16(12):1465-1479. https://doi.org/10.1101/gr.5460106.
Ciriello G, Miller ML, Aksoy BA, et al. Emerging landscape of oncogenic signatures across human cancers. Nat Genet. 2013;45(10):1127-1133. https://doi.org/10.1038/ng.2762.
Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490(7418):61-70. https://doi.org/10.1038/nature11412.
Mahdi AS, Ibrahim HH, Mohammed AA. Ki-67 expression as an indicator of invasiveness in patients with breast cancer. Medical Journal of Babylon. 2018;15(4):271-5.
Irigoyen MA, García FV, Iturriagagoitia AC, et al. Subtipos moleculares del cáncer de mama: implicaciones pronósticas y características clínicas e inmunohistoquímicas [Molecular subtypes of breast cancer: prognostic implications and clinical and immunohistochemical characteristics]. An Sist Sanit Navar. 2011;34(2):219-33. https://doi.org/10.4321/s1137-66272011000200008.
Curigliano G, Burstein HJ, Winer EP, et al. De-escalating and escalating treatments for early-stage breast cancer: the St. Gallen International Expert Consensus Conference on the Primary Therapy of Early Breast Cancer 2017. Ann Oncol. 2017;28(8):1700-1712. https://doi.org/10.1093/annonc/mdx308.
Niwińska A, Olszewski W, Murawska M, et al. Triple-negative breast cancer with brain metastases: a comparison between basal-like and non-basal-like biological subtypes. J Neurooncol. 2011;105(3):547-553. https://doi.org/10.1007/s11060-011-0616-3.
Lehmann BD, Jovanovic B, Chen X, et al. Refinement of triple-negative breast cancer molecular subtypes: implications for neoadjuvant chemotherapy selection. PLoS ONE. 2016;11(6):e0157368.
Khoury T, Kanehira K, Wang D, et al. Breast carcinoma with amplified HER2: a gene expression signature specific for trastuzumab resistance and poor prognosis. Mod Pathol. 2010;23(10):1364-1378.
Zhang X. Molecular classification of breast cancer: relevance and challenges. Archives of Pathology & Laboratory Medicine. 2023;147(1):46-51. https://doi.org/10.5858/arpa.2022-0070-RA.
Goldhirsch A, Wood WC, Coates AS, 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):1736-1747. https://doi.org/10.1093/annonc/mdr304.
Sparano JA, Gray RJ, Makower DF, et al. Adjuvant chemotherapy guided by a 21-gene expression assay in breast cancer. N Engl J Med. 2018;379(2):111-121. https://doi.org/10.1056/NEJMoa1804710.
Slodkowska EA, Ross JS. MammaPrint 70-gene signature: another milestone in personalized medical care for breast cancer patients. Expert Rev Mol Diagn. 2009;9(5):417-422. https://doi.org/10.1586/erm.09.32.
Brandão M, Pondé N, Piccart-Gebhart M. Mammaprint™: a comprehensive review. Future Oncol. 2019;15(2):207-224. https://doi.org/10.2217/fon-2018-0221.
Piccart M, van't Veer LJ, Poncet C, et al. 70‐gene signature as an aid for treatment decisions in early breast cancer: updated results of the phase 3 randomised MINDACT trial with an exploratory analysis by age. Lancet Oncol. 2021;22:476‐488. https://doi.org/10.1016/S1470-2045(21)00007-3.
Viale G, de Snoo FA, Slaets L, et al. Immunohistochemical versus molecular (BluePrint and MammaPrint) subtyping of breast carcinoma. Outcome results from the EORTC 10041/BIG 3-04 MINDACT trial. Breast Cancer Res Treat. 2018;167(1):123-131. https://doi.org/10.1007/s10549-017-4509-9.
Noordhoek I, Treuner K, Putter H, et al. Breast cancer index predicts extended endocrine benefit to individualize selection of patients with HR+ early-stage breast cancer for 10 years of endocrine therapy. Clin Cancer Res. 2021;27(1):311-319. https://doi.org/10.1158/1078-0432.CCR-20-2737.
Martin M, Brase JC, Ruiz A, et al. Prognostic ability of EndoPredict compared to research-based versions of the PAM50 risk of recurrence (ROR) scores in node-positive, estrogen receptor-positive, and HER2-negative breast cancer. A GEICAM/9906 sub-study. Breast Cancer Res Treat. 2016;156(1):81-89. https://doi.org/10.1007/s10549-016-3725-z
Martín M, Prat A, Rodríguez-Lescure A, et al. PAM50 proliferation score as a predictor of weekly paclitaxel benefit in breast cancer. Breast Cancer Res Treat. 2013;138(2):457-466. https://doi.org/10.1007/s10549-013-2416-2.
Pu M, Messer K, Davies SR, et al. Research-based PAM50 signature and long-term breast cancer survival. Breast Cancer Res Treat. 2020;179(1):197-206. https://doi.org/10.1007/s10549-019-05446-y.
Dowsett M, Sestak I, Lopez-Knowles E, et al. Comparison of PAM50 risk of recurrence score with oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy. J Clin Oncol. 2013;31(22):2783-90. https://doi.org/10.1200/JCO.2012.46.1558.
Sestak I, Filipits M, Buus R, et al. Prognostic value of endopredict in women with hormone receptor-positive, HER2-negative invasive lobular breast cancer. Clin Cancer Res. 2020;26(17):4682-4687. https://doi.org/10.1158/1078-0432.CCR-20-0260.
Xin L, Liu YH, Martin TA, et al. The era of multigene panels comes? The clinical utility of oncotype DX and MammaPrint. World J Oncol. 2017;8(2):34-40. https://doi.org/10.14740/wjon1019w
Боженко В.К., и др. Возможности типирования рака молочной железы с использованием методики ОТ-ПЦР. Сибирский онкологический журнал. 2019;18(5):61-67 [Bozhenko VK, et al. Possibilities of breast cancer typing using RT-PCR technique. Siberian journal of oncology. 2019;18(5):61-67 (In Russ).]. https://doi.org/10.21294/1814-4861-2019-18-5-61-67.
Оценка риска рецидива при раке молочной железы. [Assessment of the risk of recurrence in breast cancer. (In Russ.)]. Globalindexbc.ru [Internet] [Accessed 2022 Sep 8] Available from: http://globalindexbc.ru/.
Munkácsy G, Santarpia L, Győrffy B. Gene Expression Profiling in Early Breast Cancer-Patient Stratification Based on Molecular and Tumor Microenvironment Features. Biomedicines. 2022;10(2):248. https://doi.org/10.3390/biomedicines10020248.
Melas M, Subbiah S, Saadat S, et al. The community oncology and academic medical center alliance in the age of precision medicine: cancer genetics and genomics considerations. J Clin Med. 2020;9(7):2125. https://doi.org/10.3390/jcm9072125.
Mardis ER. Next-generation DNA sequencing methods. Annu Rev Genomics Hum Genet. 2008;9:387-402. https://doi.org/10.1146/annurev.genom.9.081307.164359.
Oliver GR, Hart SN, Klee EW. Bioinformatics for clinical next generation sequencing. Clin Chem. 2015;61(1):124-135. https://doi.org/10.1373/clinchem.2014.224360.
Nagahashi M, Shimada Y, Ichikawa H, et al. Next generation sequencing-based gene panel tests for the management of solid tumors. Cancer Sci. 2019;110(1):6-15. https://doi.org/10.1111/cas.13837.
Imyanitov E. Sokolenko A. Integrative genomic tests in clinical oncology. Int J Mol Sci. 2022;23:13129. https://doi.org/10.3390/ijms232113129.
Vidula N, Lipman A, Kato S, et al. Detection of microsatellite instability high (MSI-H) status by targeted plasma-based genotyping in metastatic breast cancer. NPJ Breast Cancer. 2022;8(1):117. https://doi.org/10.1038/s41523-022-00490-2.
Bonneville R, Krook MA, Chen HZ, et al. Detection of microsatellite instability biomarkers via next-generation sequencing. Methods Mol Biol. 2020;2055:119-132. https://doi.org/10.1007/978-1-4939-9773-2_5.
Hempelmann JA, Scroggins SM, Pritchard CC, et al. MSIplus for Integrated Colorectal Cancer Molecular Testing by Next-Generation Sequencing. J Mol Diagn. 2015;17(6):705-14. https://doi.org/10.1016/j.jmoldx.2015.05.008.
Pritchard CC, Smith C, Salipante SJ, et al. ColoSeq provides comprehensive lynch and polyposis syndrome mutational analysis using massively parallel sequencing. J Mol Diagn. 2012;14(4):357-66. https://doi.org/10.1016/j.jmoldx.2012.03.002.
Cai Y, Wang C, Zhou S, et al. Comparison of the tumor mutation burden (TMB) analysis results between a targeted next-generation sequencing method and the conventional WES method. J Clin Oncol. 2018;36(15_suppl):e24186-e24186. http://dx.doi.org/10.1200/jco.2018.36.15_suppl.e24186.
Cordova-Delgado M, Pizarro G, Pinto MP, et al. Case report: molecular features and treatment options for small bowel adenocarcinoma. Front Oncol. 2021;11:593561. https://doi.org/10.3389/fonc.2021.593561.
Yang S, Wang X, Jiang H, et al. Effective treatment of aggressive fibromatosis with celecoxib guided by genetic testing. Cancer Biol Ther. 2017;18(10):757-760. https://doi.org/10.1080/15384047.2017.1373215.
Hou H, Zhu H, Zhao H, et al. Comprehensive molecular characterization of young chinese patients with lung adenocarcinoma identified a distinctive genetic profile. Oncologist. 2018;23(9):1008-1015. https://doi.org/10.1634/theoncologist.2017-0629.
Hou H, Yang X, Zhang J, et al. Discovery of targetable genetic alterations in advanced non-small cell lung cancer using a next-generation sequencing-based circulating tumor DNA assay. Sci Rep. 2017;7(1):14605. https://doi.org/10.1038/s41598-017-14962-0.
Hou H, Liu D, Zhang C, et al. Targeted next generation sequencing in Chinese colorectal cancer patients guided anti-EGFR treatment and facilitated precision cancer medicine. Oncotarget. 2017;8(62):105072-105080. https://doi.org/10.18632/oncotarget.21349.
Это произведение доступно по лицензии Creative Commons «Attribution-NonCommercial-NoDerivatives» («Атрибуция — Некоммерческое использование — Без производных произведений») 4.0 Всемирная.
© АННМО «Вопросы онкологии», Copyright (c) 2023