1 / 87

Highlights in the Management of Breast Cancer Roma, 10 Maggio 2013

Highlights in the Management of Breast Cancer Roma, 10 Maggio 2013. Molecular tools for decision making in adjuvant therapy.

stasia
Download Presentation

Highlights in the Management of Breast Cancer Roma, 10 Maggio 2013

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Highlights in the Management of Breast Cancer Roma, 10 Maggio 2013 Molecular tools for decision making in adjuvant therapy Enrico Ricevuto & Valentina Cocciolone Oncologia Medica Ospedale San Salvatore Università degli Studi di L’Aquila

  2. Adjuvant Breast Cancer TreatmentKey issues Patients selection according to biomarkers Selection of appropriate treatment 2

  3. Adjuvant Breast Cancer TreatmentMolecular Tools for decision-making Biomarkers ER/PR HER2 Topoisomerase II BRCA1/BRCA2 KI67 Multi-Genes expression profiles (GEPs) Circulating Tumoral Cells (CTCs)

  4. BC Prevalence according to ER/PR and HER2

  5. Hormone receptor status: prognostic potential • Patients with ER-positive/PgR-positive and ER-positive/PgR-negative BC had significantly better prognoses than patients with ER-negative/PgR-negative disease. • Patients with ER-positive/PgR-negative tumors tended to have slightly worse disease-free and overall survival than patients with ER-positive/PgR-positive tumors, but the differences did not achieve statistical significance (P .05) Bordou et al. J Clin Oncol 2003; 21:1973-1979

  6. Hormone receptor status: predictive potential • multivariate analyses confirmed that both ER and PgR are independent significant predictors of DFS and OS among patients who received adjuvant endocrine therapy; • the reduction in RR of recurrence was 53% for ER-positive/PgR-positive patients and 25% for ER-positive/PgR-negative patients (P .0001); • patients whose tumors are positive for both receptors have the greatest reduction of RR of death compared with patients whose tumors are ER-negative and PgR-negative. Bordou et al. J Clin Oncol 2003; 21:1973-1979

  7. Her2 status: prognostic potential Pritchard et al. N Engl J Med 2006;354:2103-11

  8. Her2 status: predictive potential Pritchard et al. N Engl J Med 2006;354:2103-11

  9. BC Prevalence according to ER/PR and HER2 9

  10. Topoisomerase II and responsiveness to adjuvant Anthracyclines amplified or deleted TOPO2A CEF normal TOPO2A CMF CEF CMF 10 O’Malley et al. J Natl Cancer Inst 2009;101:644-650

  11. Topoisomerase II and responsiveness to adjuvant Anthracyclines amplified or deleted TOPO2A CEF CMF normal TOPO2A CMF CEF 11 O’Malley et al. J Natl Cancer Inst 2009;101:644-650

  12. TOPO2A HR 0.53 for RFS (p 0.09) HR 0.38 for OS (p 0.02) Topoisomerase II and responsiveness to adjuvant Anthracyclines Adjusted test for interaction: HER2 • HR 0.40 for RFS (p 0.008) • HR 0.44 for OS (p 0.02) 12 O’Malley et al. J Natl Cancer Inst 2009;101:644-650

  13. Topoisomerase II and responsiveness to adjuvant Anthracyclines 13 Slamon et al. N Engl J Med 2011;365-1273-83

  14. BRCA1-ness in TNBC 14

  15. BRCA1, BRCA2 predisposition carriersBreast Cancer prognosis BRCA1+ BRCA2+ Non carriers Pts 93 71 1550 Risk recurrence (CI) 1.19 (.74-1.89) 1.63 (1.02-2.60) p .47 .04 Risk death (CI) 1.43 (.91-2.23) 1.81 (1.15-2.86) p .12 .01 15 Goodwin et al, JCO’12: 30; 19-26

  16. Ki67: prognostic role in EBC Despite some limitations, this meta-analysis supports the prognostic role of Ki-67 in early BC, by showing a significant association between its expression and the risk of recurrence and death in all populations considered and for both outcomes, DFS and OS. de Azambuja et al. Br J Cancer 2007;96:1504-13

  17. Breast Cancer Genomics and Clinical Classification Two different gene sets: first, a set of 476 cDNA clones previously selected to reflect intrinsic properties of the tumors and, second, a gene set that highly correlated with patient outcome. Sørlieet al. ProcNatlAcad Sci USA 2001;98:10869-74

  18. Gene expression profiling predicts clinical outcome of breast cancer Panel A shows the pattern of expression of the 70 marker genes in a series of 295 consecutive patients with breast carcinomas. Each row represents the prognostic profile of the 70 marker genes for one tumor, and each column represents the relative level of expression of one gene. The tumors are numbered from 1 to 295 on the y axis, and the genes are numbered from 1 to 70 on the x axis. Red indicates a high level of expression of messenger RNA (mRNA) in the tumor, as compared with the reference level of mRNA, and green indicates a low level of expression. The dotted line is the determined threshold between a good-prognosis signature and a poor-prognosis signature. Panel B shows the time in years to distant metastases as a first event for those in whom this occurred, and the total duration of follow-up for all other patients. Panel C shows the lymph-node status (blue marks indicate lymph-node–positive disease, and white lymph-node–negative disease), the number of patients with distant metastases as a first event (blue marks), and the number of patients who died (blue marks). Van de Vijver et al. N Engl J Med 2002;347:1999-2009

  19. Gene-expression signature is a predictor of survival in breast cancer ASSOCIATION BETWEEN CLINICAL CHARACTERISTICS AND THE PROGNOSIS SIGNATURE: • the prognosis profile was significantly associated with: • the histologic grade of the tumor (P<0.001); • the estrogen-receptor status (P<0.001); • age (P<0.001) • but not with: • the diameter of the tumor; • the extent of vascular invasion; • the number of positive lymph nodes • treatment Van de Vijver et al. N Engl J Med 2002;347:1999-2009

  20. Gene-expression signature is a predictor of DFS and OS in breast cancer Among the overall population: HR for distant metastases as a first event was 5.1 (95% confidence interval, 2.9 to 9.0; P<0.001); HR for overall survival was 8.6 (95 %confidence interval, 4 to 19; P<0.001). Van de Vijver et al. N Engl J Med 2002;347:1999-2009

  21. The St. Gallen and NIH criteria classify patients as at low risk or high risk on the basis of various histologic and clinical characteristics. This comparison shows that the prognosis profile assigned many more patients with lymph-node–negative disease to the low-risk (good-prognosis signature) group than did the traditional methods (40 percent, as compared with 15 percent according to the St. Gallen criteria and 7 percent according to the NIH criteria). Comparisonwith St. Gallencriteria and NIH ConsensusCriteria Van de Vijver et al. N Engl J Med 2002;347:1999-2009

  22. Histologic grade Simpson et al. J Clin Oncol 2000; 18:2059-2069

  23. Molecular basis of histologic grade Most genes are overexpressed in grade 3 tumors (high expression is RED) and have functions that have been previously associated with cell cycle progression and proliferation. Sotiriou et al. J Natl Cancer Inst 2006; 98:262-272

  24. Molecular basis of histologic grade Sotiriou et al. J Natl Cancer Inst 2006; 98:262-272

  25. Oncotype DX 21 Gene Recurrence Score (RS) Assay For ER-positive patients N Events 117 13 47 18 Paik S, et al. Breast Cancer Res Treat 88 (S1):A24, 2004

  26. Validation in tamoxifen-treated patients with node-negative, ER–positive breast cancer (NSABP-B14) Paik et al. N Engl J Med 2004;351:2817-26

  27. Validation in tamoxifen-treated patients with node-negative, ER–positive breast cancer Paik et al. N Engl J Med 2004;351:2817-26

  28. Validation in tamoxifen-treated patients with node-negative, ER–positive breast cancer Percentage of patients on tamoxifen with larger N0 tumors free of recurrence at 10 years varies by Recurrence Score in NSABP B14 Percentage of patients on tamoxifen with moderately/poorly differentiated tumors free of recurrence at 10 years varies by Recurrence Score in NSABP B14 Paik et al. N Engl J Med 2004;351:2817-26

  29. Validation in tamoxifen-treated patients with node-positive, ER–positive breast cancer Prognostic disease-free survival and overall survival analyses by Recurrence Score group in patients treated with TAMOXIFEN ALONE Albain et al. Lancet Oncol 2010; 11:55–65

  30. Dowsett et al. J Clin Oncol 2010; 28:1829-1834

  31. Many patients live normal life expectancy free of breast cancer recurrence after surgical treatment alone 1.3% of recurrences occurred after 20 years (3.7% of the 20-year survivors) Albain KS. Presented at SABCS 2012

  32. 10-Year Survival Rate by axillary node status for patients treated with radical mastectomy Albain KS. Presented at SABCS 2012

  33. Prediction of recurrence in NSABP-B20 (Tam vs Tam + CMF) Paik et al. J Clin Oncol 2006; 24:3726-3734

  34. NSABP-B20 Paik et al. J Clin Oncol 2006; 24:3726-3734

  35. Prediction of anthracycline-based chemotherapy benefit by RS: DFS • The RS was a strong predictive factor of CAF benefit for DFS, but degree of CAF benefit depended on the RS: • NO apparent benefit for scores <18 (p=0.97; HR=1.02) or 18–30 (p=0.48; HR=0.72); • SIGNIFICANT advantage for CAF-T compared to tamoxifen alone for patients with RS ≥31 (p=0.033; HR=0.59) Albain et al. Lancet Oncol 2010; 11:55–65

  36. Impact on clinical practice (where available) Albain et al. The Breast 2009;18: S141–S145

  37. Available tests and prospective ongoing clinical trials Goncalves and Bose. J Natl Compr Canc Netw 2013;11:174-182

  38. Theoretical spectrum of sensitivity to adjuvant systemic therapy 38 Hayes D. J Clin Oncol 2012; 30:1264-1267

  39. TAILORx trial Goncalves and Bose. J Natl Compr Canc Netw 2013;11:174-182

  40. RxPONDER trial Goncalves and Bose. J Natl Compr Canc Netw 2013;11:174-182

  41. MINDACT trial Goncalves and Bose. J Natl Compr Canc Netw 2013;11:174-182

  42. Adjuvant Breast Cancer TreatmentKey questions Patients selection according to biomarkers Selection of appropriate treatment no adjuvant treatment Chemotherapy Hormonal therapy 42

  43. Circulating Tumoral Cells in Adjuvant Therapy Three typical patterns of response observed: • Decrease >10x • MarginalChange • Increase>10x Peripherally circulating tumor cells are influenced by systemic CT An increase (even after initial response to therapy) of 10-fold or more at the end of therapy is a strong predictor of relapse and a surrogate marker for the aggressiveness of the tumor cells Pachmann et al. J Clin Oncol 2008; 26:1208-1215

  44. Circulating Tumoral Cells in Adjuvant Therapy Trastuzumab Tamoxifene

  45. Metastatic Tumors Evolution of medical treatment Markers None “One fit (unfit) all” Clinical “One fit some” (>10%) Monogene “One fit few” (<10%) Multigenes “One fit one” (<1%)

  46. Early Breast carcinoma Evolution of medical treatment Markers None “One fit (unfit) all” Clinical “One fit some” (>10%) Monogene “One fit few” (<10%) Multigenes “More fit many” (>30%) 46

  47. Renal cell carcinoma Evolution of medical treatment Parameters • None “One fit (unfit) all” • Bio-Clinical “One fit some” (>10%) • Patient fitness (age, comorbidities) • Tumor prognostic risk • Drugs prediction (safety/toxicity, efficacy)

  48. Renal cell carcinoma Evolution of medical treatment Markers • None “One fit (unfit) all” • Clinical “One fit some” (>10%) • Monogene “One fit few” (1-10%) • Other genetic alterations • Heterogeneity (tumor/metastasis)

  49. Tailor therapy for individual patients Unanswered questions Are CTCs detected in the peripheral blood released from existing micrometastases or are they the source of distant metastases after “seeding” organ sites? Are there stem cells capable of “seeding”new tumor sites in the CTC? Could theCTCs be used to assess sensitivity of resistant tumor cells to alternative agents? 50

More Related