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Giá trị dự đoán của dấu 70 gen đối với hóa trị bổ trợ trong ung thư vú giai đoạn đầu
Tóm tắt
Các xét nghiệm đa gen đã được phát triển và xác thực để xác định tiên lượng của ung thư vú. Trong nghiên cứu này, chúng tôi đánh giá giá trị dự đoán bổ sung của dấu 70 gen MammaPrint đối với lợi ích hóa trị (CT) ngoài liệu pháp nội tiết (ET) từ các chuỗi nghiên cứu hợp nhất. Đối với 541 bệnh nhân nhận ET (n = 315) hoặc ET + CT (n = 226), tỷ lệ sống sót cụ thể do ung thư vú (BCSS) và tỷ lệ sống sót không có bệnh từ xa (DDFS) ở 5 năm đã được đánh giá riêng cho các nhóm nguy cơ cao và thấp theo 70 gen. Dấu 70 gen phân loại 252 bệnh nhân (47%) là nguy cơ thấp và 289 (53%) là nguy cơ cao. Trong nhóm nguy cơ thấp 70 gen, BCSS là 97% cho nhóm ET và 99% cho nhóm ET + CT sau 5 năm với tỷ lệ rủi ro đơn biến không có ý nghĩa (HR) là 0.58 (95% CI 0.07–4.98; P = 0.62). Trong nhóm nguy cơ cao 70 gen, BCSS là 81% (nhóm ET) và 94% (nhóm ET + CT) sau 5 năm với HR có ý nghĩa là 0.21 (95% CI 0.07–0.59; P < 0.01). DDFS là 93% (ET) so với 99% (ET + CT), tương ứng, trong nhóm nguy cơ thấp 70 gen, HR 0.26 (95% CI 0.03–2.02; P = 0.20). Trong nhóm nguy cơ cao, DDFS là 76 so với 88%, HR là 0.35 (95% CI 0.17–0.71; P < 0.01). Kết quả tương tự trong phân tích đa biến cho thấy lợi ích sống sót có ý nghĩa khi thêm CT vào nhóm nguy cơ cao 70 gen. Một lợi ích có ý nghĩa và có giá trị lâm sàng đã được quan sát khi thêm hóa trị vào điều trị nội tiết ở bệnh nhân nguy cơ cao 70 gen. Lợi ích này không đáng kể ở bệnh nhân nguy cơ thấp, những người có nguy cơ tái phát và tử vong liên quan đến ung thư rất thấp, đến mức việc thêm CT dường như không có ý nghĩa lâm sàng.
Từ khóa
#ung thư vú #hóa trị #liệu pháp nội tiết #70 gen #dự đoán tiên lượngTài liệu tham khảo
Trialists’ Collaborative Group (EBCTCG) et al (2005) Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet 365(9472):1687–1717
National Comprehensive Cancer Network. Practice Guidelines in Oncology—v.1.2010. http://www.nccn.org/professionals/physician_gls/PDF/breast.pdf. 12-11-2009
Goldhirsch A, Ingle JN, Gelber RD, Coates AS, Thurlimann B, Senn HJ (2009) Thresholds for therapies: highlights of the St Gallen International Expert Consensus on the primary therapy of early breast cancer 2009. Ann Oncol 20(8):1319–1329
Dowsett M, Goldhirsch A, Hayes DF, Senn HJ, Wood W, Viale G (2007) International Web-based consultation on priorities for translational breast cancer research. Breast Cancer Res 9(6):R81
van’t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M et al (2002) Gene expression profiling predicts clinical outcome of breast cancer. Nature 415(6871):530–536
van de Vijver MJ, He YD, van’t Veer LJ, Dai H, Hart AA, Voskuil DW et al (2002) A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 347(25):1999–2009
Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M (2004) A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 351(27):2817–2826
Habel LA, Shak S, Jacobs MK, Capra A, Alexander C, Pho M et al (2006) A population-based study of tumor gene expression and risk of breast cancer death among lymph node-negative patients. Breast Cancer Res 8(3):R25
Sotiriou C, Wirapati P, Loi S, Harris A, Fox S, Smeds J et al (2006) Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 98(4):262–272
Ma XJ, Wang Z, Ryan PD, Isakoff SJ, Barmettler A, Fuller A et al (2004) A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen. Cancer Cell 5(6):607–616
Ma XJ, Salunga R, Dahiya S, Wang W, Carney E, Durbecq V et al (2008) A five-gene molecular grade index and HOXB13:IL17BR are complementary prognostic factors in early stage breast cancer. Clin Cancer Res 14(9):2601–2608
Paik S, Tang G, Shak S, Kim C, Baker J, Kim W et al (2006) Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol 24(23):3726–3734
Buyse M, Loi S, van’t Veer L, Viale G, Delorenzi M, Glas AM et al (2006) Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer. J Natl Cancer Inst 98(17):1183–1192
Bueno-de-Mesquita JM, Linn SC, Keijzer R, Wesseling J, Nuyten DS, van Krimpen C et al (2009) Validation of 70-gene prognosis signature in node-negative breast cancer. Breast Cancer Res Treat 117(3):483–495
Knauer M, Wenzl E, Rutgers EJT, Linn SC, van’t Veer LJ (2009) Gene expression profiling in breast cancer—design of a pooled database to address open questions. Eur Surg 41(5):221–227
Bueno-de-Mesquita JM, van Harten WH, Retel VP, van’t Veer LJ, van Dam FS, Karsenberg K et al (2007) Use of 70-gene signature to predict prognosis of patients with node-negative breast cancer: a prospective community-based feasibility study (RASTER). Lancet Oncol 8(12):1079–1087
Mook S, Schmidt MK, Viale G, Pruneri G, Eekhout I, Floore A et al (2009) The 70-gene prognosis-signature predicts disease outcome in breast cancer patients with 1–3 positive lymph nodes in an independent validation study. Breast Cancer Res Treat 116(2):295–302
Mook S, Schmidt MK, Weigelt B, Kreike B, Eekhout I, van de Vijver MJ et al (2009) The 70-gene prognosis signature predicts early metastasis in breast cancer patients between 55 and 70 years of age. Ann Oncol. doi:10.1093/annonc/mdp388
Glas AM, Floore A, Delahaye LJ, Witteveen AT, Pover RC, Bakx N et al (2006) Converting a breast cancer microarray signature into a high-throughput diagnostic test. BMC Genomics 7:278
Ioannidis JP (2006) Gene expression profiling for individualized breast cancer chemotherapy: success or not? Nat Clin Pract Oncol 3(10):538–539
Simmonds MC, Higgins JP, Stewart LA, Tierney JF, Clarke MJ, Thompson SG (2005) Meta-analysis of individual patient data from randomized trials: a review of methods used in practice. Clin Trials 2(3):209–217
Cardoso F, van’t Veer L, Rutgers E, Loi S, Mook S, Piccart-Gebhart MJ (2008) Clinical application of the 70-gene profile: the MINDACT trial. J Clin Oncol 26(5):729–735
Sparano JA (2006) TAILORx: trial assigning individualized options for treatment (Rx). Clin Breast Cancer 7(4):347–350
Albain KS, Barlow WE, Shak S, Hortobagyi GN, Livingston RB, Yeh IT et al (2010) Prognostic and predictive value of the 21-gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-positive breast cancer on chemotherapy: a retrospective analysis of a randomised trial. Lancet Oncol 11(1):55–65
Sotiriou C, Pusztai L (2009) Gene-expression signatures in breast cancer. N Engl J Med 360(8):790–800
Ayers M, Symmans WF, Stec J, Damokosh AI, Clark E, Hess K et al (2004) Gene expression profiles predict complete pathologic response to neoadjuvant paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide chemotherapy in breast cancer. J Clin Oncol 22(12):2284–2293
Bonnefoi H, Potti A, Delorenzi M, Mauriac L, Campone M, Tubiana-Hulin M et al (2007) Validation of gene signatures that predict the response of breast cancer to neoadjuvant chemotherapy: a substudy of the EORTC 10994/BIG 00-01 clinical trial. Lancet Oncol 8(12):1071–1078
Hess KR, Anderson K, Symmans WF, Valero V, Ibrahim N, Mejia JA et al (2006) Pharmacogenomic predictor of sensitivity to preoperative chemotherapy with paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide in breast cancer. J Clin Oncol 24(26):4236–4244
Liedtke C, Hatzis C, Symmans WF, Desmedt C, Haibe-Kains B, Valero V et al (2009) Genomic grade index is associated with response to chemotherapy in patients with breast cancer. J Clin Oncol 27(19):3185–3191
Chang JC, Wooten EC, Tsimelzon A, Hilsenbeck SG, Gutierrez MC, Elledge R et al (2003) Gene expression profiling for the prediction of therapeutic response to docetaxel in patients with breast cancer. Lancet 362(9381):362–369
Dressman HK, Hans C, Bild A, Olson JA, Rosen E, Marcom PK et al (2006) Gene expression profiles of multiple breast cancer phenotypes and response to neoadjuvant chemotherapy. Clin Cancer Res 12(3 Pt 1):819–826
Folgueira MA, Carraro DM, Brentani H, Patrao DF, Barbosa EM, Netto MM et al (2005) Gene expression profile associated with response to doxorubicin-based therapy in breast cancer. Clin Cancer Res 11(20):7434–7443
Gianni L, Zambetti M, Clark K, Baker J, Cronin M, Wu J et al (2005) Gene expression profiles in paraffin-embedded core biopsy tissue predict response to chemotherapy in women with locally advanced breast cancer. J Clin Oncol 23(29):7265–7277
Iwao-Koizumi K, Matoba R, Ueno N, Kim SJ, Ando A, Miyoshi Y et al (2005) Prediction of docetaxel response in human breast cancer by gene expression profiling. J Clin Oncol 23(3):422–431
Park S, Shimizu C, Shimoyama T, Takeda M, Ando M, Kohno T et al (2006) Gene expression profiling of ATP-binding cassette (ABC) transporters as a predictor of the pathologic response to neoadjuvant chemotherapy in breast cancer patients. Breast Cancer Res Treat 99(1):9–17
Potti A, Dressman HK, Bild A, Riedel RF, Chan G, Sayer R et al (2006) Genomic signatures to guide the use of chemotherapeutics. Nat Med 12(11):1294–1300
Thuerigen O, Schneeweiss A, Toedt G, Warnat P, Hahn M, Kramer H et al (2006) Gene expression signature predicting pathologic complete response with gemcitabine, epirubicin, and docetaxel in primary breast cancer. J Clin Oncol 24(12):1839–1845
Straver ME, Glas AM, Hannemann J, Wesseling J, van de Vijver MJ, Rutgers EJ et al (2010) The 70-gene signature as a response predictor for neoadjuvant chemotherapy in breast cancer. Breast Cancer Res Treat 119(3):551–558