Genomic Profiling of Tumors and Loco-Regional Recurrence

Transcription

1 1 Genomic Profiling of Tumors and Loco-Regional Recurrence Terry Mamounas, M.D., M.P.H., F.A.C.S. Medical Director, Comprehensive Breast Program UF Health Cancer Center at Orlando Health Professor of Surgery, University of Central Florida College of Medicine Clinical Professor of Clinical Sciences, Florida State University College of Medicine

2 Rationale for Evaluating Genomic Profiling and Molecular Subtyping for Predicting LRR 2 Genomic profiling and molecular subtyping are useful tools for assessing risk of distant recurrence in early-stage breast cancer Risk of LRR and distant recurrence are tightly correlated Hypothesis: Molecular subtyping would significantly predict risk of loco-regional recurrence

3 DRFS 21-Gene RS and Distant Recurrence 3 PROLIFERATION Ki-67 STK15 Survivin Cyclin B1 MYBL2 INVASION Stromelysin 3 Cathepsin L2 GSTM1 CD68 ESTROGEN ER PR Bcl2 SCUBE2 HER2 GRB7 HER2 REFERENCE GENES Beta-actin, GAPDH, RPLPO GUS, TFRC BAG1 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% NSABP B-14 Validation Study: Node(-)/ER (+) Low Risk (RS <18) Intermediate Risk (RS 18-30) High Risk (RS 31) Years Paik S, et al: N Engl J Med, 2005

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5 Rate of LRR % NSABP B-14/B-20: 10-Year LRR Rates by RS Category Tamoxifen (n=895) Tamoxifen + Chemo (n=424) RS < 18 RS RS >31 P< Time in Years RS < 18 RS RS >31 P= Time in Years Mamounas EP, et al: J Clin Oncol 2010

6 NSABP B-28: RS and LRR To evaluate the association between the 21-gene RS and risk of LRR in node (+), ER (+) patients treated with adjuvant chemo-endocrine therapy To evaluate the potential for combining the 21-gene RS with traditional clinico-pathologic factors in order to derive an improved algorithm for prediction of LRR risk Identify subgroups of ER-positive patients with 1-3 or 4 or more positive nodes who do/do not need chest wall and regional nodal XRT after mastectomy or regional nodal XRT after breast conserving surgery + breast XRT Mamounas et al: SSO 2013

7 Cumulative Incidence Rate RS in B-28: Primary Endpoint: Cumulative Incidence of LRR by RS Risk Groups RS Low RS Intermediate RS High N LRR Events P-value < % 7.2% 3.3% Time in Years Mamounas et al: SSO 2013

8 Multivariate Regression Analysis for LRR Variables Subdistribution HR (95% CI) P-value RS (1.54, 5.31) <0.001 AC+P vs. AC 0.83 (0.53, 1.30) 0.42 Age 50 vs. < (0.51, 1.33) 0.43 >4 + nodes vs (1.32, 3.27) Mastectomy vs. Lumpectomy 0.82 (0.52, 1.28) 0.38 Tumor size (cm) (1.04, 1.53) Rescaled with a range from 0 to An upper threshold was imposed at 5cm. Mamounas et al: SSO 2013

9 Cumulative Incidence Rate Cumulative Incidence Rate RS in B-28: Secondary Endpoint: Cumulative Incidence of LRR by RS And Nodal Status 1-3 Positive Nodes (N=722) > 4 Positive Nodes (N=343) RS Low RS Intermediate RS High N LRR Events RS Low RS Intermediate RS High N LRR Events P-value = 0.12 P-value = % 7.9% 11.6% 5.1% 3.2% 3.5% Years Years Mamounas et al: SSO 2013

10 Cumulative Incidence Rate RS in B-28: LRR in Patients with Mastectomy 1-3 Positive Nodes (N=386) >4 Positive Nodes (N=218) RS Low RS Intermediate RS High N LRR Events RS Low RS Intermediate RS High N LRR Events P-value = 0.64 P-value = % 6.0% 4.1% 2.4% 9.6% 5.5% Time in Years Time in Years Mamounas et al: SSO 2013

11 Cumulative Incidence Rate RS in B-28: LRR in Patients with Lumpectomy + Breast XRT 1-3 Positive Nodes (N=336) >4 Positive Nodes (N=125) RS Low RS Intermediate RS High P-value = 0.12 N LRR Events % 6.2% 3.9% RS Low RS Intermediate RS High P-value = N LRR Events % 12.8% 0.0% Time in Years Time in Years Mamounas et al: SSO 2013

12 RS in B-28: Clinical Implications These findings can help with patient selection for post-mastectomy chest wall and regional nodal XRT and post lumpectomy regional nodal XRT in node-positive, ER-positive patients treated with adjuvant chemo-endocrine therapy Mamounas et al: SSO 2013

13 P= % 5.1% 3.8% Solin et al: Breast Cancer Res Treat, 2012

14 Cheng et al: J Clin Oncol 2006 Genomic Prediction of LRR After Mastectomy 14 Unsupervised Analysis: 258 Genes in 62 Patients Kaplan-Meier LRFS in the Validation Study Low-Risk High-Risk 258 Gene Model Low-Risk High-Risk 34 Gene Model

15 Nuyten et al: Br Ca Res 2006 Genomic Prediction of LRR After BCS Wound Response Signature (GSEA) 15 Training Set Validation Set 6% 35% 5% 29%

16 Nguyen et al: J Clin Oncol 2008 LRR According to BC Subtype After BCS 16 n=793

17 Voduc KD et al: J Clin Oncol 2010 Ten-Year Local Recurrence Free Survival After Breast Conserving Surgery By Subtype 17

18 Voduc KD et al: J Clin Oncol 2010 Ten-Year Local Recurrence Free Survival After Mastectomy By Subtype 18

19 Kyndi et al: J Clin Oncol 2008 PMRT Benefit According to Tumor Subtype 19 ER+/HER2- ER+/HER2+ ER-/HER2- ER-/HER2+

20 DCIS Score 20 DCIS Score (0 100) evaluated 2 ways: - Continuous variable - 3 pre-specified risk groups: Low < 39 Intermediate High > 55 Solin et al, SABCS 2011

21 DCIS Score: Gene Selection Based on Published NSABP B-14 RS Results: TAM vs. Placebo 21 Bcl2 SCUBE2 ER PR HER2 GRB7 CTSL2 STMY3 CCNB1 Ki-67 MYBL2 STK15 SURV GSTM1 CD68 BAG ER Group HER2 Group Invasion Genes Proliferation Genes Single Genes B-14 Tam N=668 # events=109 B-14 Placebo N=355 # events=94 Paik, NEJM 2004, Supplemental materials

22 Validation of DCIS Score in E5194: 10-Yr Ipsilateral Breast Events (IBE) by Risk Group 22 Any IBE Invasive IBE Solin et al, SABCS 2011

23 DCIS Score: 10-Yr Risk of an Ipsilateral Breast Event (IBE) 23 Solin et al, SABCS 2011

24 Multivariate Models of Risk for IBE 24 Hazard Ratio (95% CI) P value Excluding the DCIS Score Tumor size 1.54 (1.14, 2.02) 0.01 Postmenopausal 0.49 (0.27, 0.90) 0.02 Including the DCIS Score DCIS Score 2.41 (1.15, 4.89) 0.02 Tumor size 1.52 (1.11, 2.01) 0.01 Postmenopausal 0.49 (0.27, 0.90) 0.02 For study cohort, surgical margins, grade, comedo necrosis, and DCIS pattern, all p > For tamoxifen, p = Solin et al, SABCS 2011

25 Summary Genomic profiling predicts risk for LRR in node (-) and node (+) BC pts treated with endocrine or chemo-endocrine therapy These findings may help tailor the extent or need for LR XRT, particularly in node-positive patients Emerging evidence suggests that ER (+) tumors may be more sensitive to the effects of XRT than Triple (-) or HER-2 (+) tumors Genomic profiling also predicts risk of in-breast recurrence in patients with DCIS and can help with decisions regarding the use of breast XRT 25