Genomic Profiling in Early Stage Breast Cancer. James V. Pellicane, MD, FACS Director of Breast Oncology Bon Secours Cancer Institute Richmond, VA

Transcription

1 Genomic Profiling in Early Stage Breast Cancer James V. Pellicane, MD, FACS Director of Breast Oncology Bon Secours Cancer Institute Richmond, VA 1

2 Disclosures Speakers Bureau Agendia Focal Therapeutics 2

3 Disclosures (cont d) Surgeon NY GIANTS Fan 3

4 4 Go?

5 Go Vikings Go Packers Go Chiefs Go Bears Go Broncos Go Rams Who to root for?? 5

6 6 Go Hawkeyes

7 7 Go Cyclones

8 8 Go Panthers

9 9 Go Bulldogs

10 10 Go Bandits

11 11 Go Crush

12 Goals Development of Genomic Profiling Tests Oncotype Dx Mammaprint Prosigna Clinical Utility Strengths and Weakness Predictive Assays/Mutational Analysis Molecular Intelligence Testing Foundation One Paradigm Molecular Subtyping Pam 50 Blueprint 12

13 BREAST CANCER - SURVIVAL Kaplan-Meier Survival Curves Which Breast Cancers Return? 13

14 The question: Who to treat and with what? Historically we ve relied on clinical factors 14

15 Genomic Profiling in Small Tumors Diagnosis Small tumors are regarded low risk time Diagnosis 15

16 We have begun to rely on a growing collection of increasingly precise tools 2000 Who is at risk? Is Chemotherapy Necessary? 2010 Which genomic pathway? 2020 Enhance predictive accuracy? 16

17 Breast cancer clinical care represents the most extensive exploitation of genomics in oncology Patients are doing much better Cossetti et al JCO

18 18 Genomic Assays

19 Oncotype Dx Knowledge Driven Approach 21 Genes Well Validated ER positive, Her-2 negative only Ternary Result Assumes 5 years of Anti Estrogen Therapy Predictive Component 19

20 Oncotype DX Selection Process RT-PCR Technology 250 candidate genes derived from the available literature 21 genes: 16 known functions 5 reference genes All with known functions 20

21 Oncotype DX (RT-PCR Technology) 16 Cancer and 5 Reference Genes PROLIFERATION Ki-67 STK15 Survivin Cyclin B1 MYBL2 INVASION Stromolysin 3 Cathepsin L2 HER2 GRB7 HER2 CD68 ESTROGEN ER PR Bcl2 SCUBE2 GSTM1 BAG1 REFERENCE Beta-actin GAPDH GUS RPLPO TFRC RS Weighting: x HER2 Group x ER Group x Proliferation Group x Invasion Group x CD x GSTM x BAG1 Category RS (0 100) Low risk RS < 18 Intermediate risk RS 18 and < 31 High risk RS 31 21

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23 23 Oncotype Continuous Variable

24 24 Patient Age

25 25 Tumor Size

26 26 Ki-67

27 27 Tumor Grade

28 Grade 1 Tumor Grade Grade 2 Grade 3 28 Low risk 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Intermediate Grade 1 Grade 2 Grade 3 70-gene high risk 70-gene low risk High risk

29 Histopathologic Variables Predict Oncotype DX Recurrence Score Melina B Flanagan1, David J Dabbs1, Adam M Brufsky2, Sushil Beriwal3 and Rohit Bhargava1 1 Department of Pathology, Magee-Women s Hospital of University of Pittsburgh Medical Center, Pittsburgh, PA, USA; 2 Department of Medical Oncology, Magee-Women s Hospital of University of Pittsburgh Medical Center, Pittsburgh, PA, USA and 3 Department of Radiation Oncology, Magee- Women s Hospital of University of Pittsburgh Medical Center, Pittsburgh, PA, USA Although the Oncotype DX Recurrence Score holds potential, further validation of its independent value beyond that of histopathologic analysis is necessary before it can be implemented in clinical decision making. Modern Pathology (2008) 21, ; doi: /modpath 29

30 30 Predictiveness

31 31

32 Predictiveness Does it Really Matter? 32

33 33 Depends on who you ask!

34 Prosigna Utilizes Pam 50 (Molecular Subtyping) Uses Tumor size and Proliferation ER positive, Her 2 negative only Post menopausal Assumes 5 years of Anti Estrogen Therapy Ternary results 34

35 35

36 36 Prosigna vs Oncotype Dx

37 Mammaprint Biology Driven Approach 70 Genes Well Validated Has Observational Outcomes Data Her 2 Positive and ER Negative Patients Binary Result Untreated Patients Some Predictive Data 37

38 MammaPrint developed using unbiased gene selection based on patient outcomes LOW RISK No distant metastasis within 5 years Full human genome 25K Untreated tumor samples with up to 20 year follow-up Ranking 70 most significant genes predictive of recurrence risk were identified Distant metastasis within 5 years HIGH RISK Full human genome 25K 38

39 Patients MammaPrint provides true binary results Clinical classification threshold set by determination of largest population of Low Risk patients that can withhold CT and not suffer adverse consequence. MP INDEX +1.0 LOW RISK NO INTERMEDIATE RESULTS 0.0 HIGH RISK Genes Buyse et al., Jrnl of the NCI. 2006;98(17):

40 TransBIG validation results: Show significant survival difference between MammaPrint Low and High Risk results n = 302 p = Low Risk ~10% chance (95% CI 4-15) of cancer recurrence within 10 years without any adjuvant treatment, either hormonal therapy or chemotherapy High Risk ~29% chance (95% CI 22-35) of cancer recurrence within 10 years without any adjuvant treatment, either hormonal therapy or chemotherapy Buyse et al., Jrnl of the NCI. 2006;98(17): Delayahe et al., Personalized Medicine. 2013; 10(8),

41 41 MammaPrint Adjuvant Predictive Data

42 Chemotherapy benefit in MammaPrint HIGH RISK patients (n=289) There is sufficient benefit to adopt advice of MammaPrint assay DDFS: MammaPrint LOW RISK (n=252) DDFS: MammaPrint HIGH RISK (n=289) 99% 93% 88% 76% PERCENT SURVIVAL ET+CT (n=78, 31%) ET (n=174, 69%) HR.0.26( ) p=0.20 PERCENT SURVIVAL ET+CT (n=148, 51%) ET (n=141, 49%) HR.0.35( ) p=0.01 TIME IN YEARS TIME IN YEARS 12% absolute benefit 50% relative benefit 42 Knauer et al., Breast Cancer Res Treat, 2010 Feb

43 43 Probability of pcr for MammaPrint Index

44 Probability of pcr for MammaPrint Index Compelling figure suggesting that MammaPrint is predictive of pcr pcr correlates to therapy response (in early stage breast cancer, the goal of neoadjuvant chemotherapy is to shrink tumors or obtain a pcr) In the neoadjuvant setting, results from the NBRST trial suggest that the MammaPrint Index is predictive of response to therapy (pcr) 44

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46 RASTER Prospective Outcome-Based Study First and only 5-Year prospective outcome-based data for any prognostic breast cancer risk of recurrence assay 16 Centers/427 Patients Enrollment (31%) Low Risk 295 (69%) High Risk 219 (51%) Low Risk 208 (49%) High Risk Traditional Clinical Parameters* MammaPrint 46 Drukker et al. Int J Cancer; 2013

47 RASTER Prospective Outcome-Based Study As judged appropriate by doctors and patients, MammaPrint Low Risk patients may safely forego chemotherapy and not compromise outcome MammaPrint identified 20% more Low Risk patients than traditional clinical parameters(n=87) 132 (31%) Low Risk 87 (20%) 219 (51%) Low Risk 15% adjuvant chemotherapy MammaPrint Low Risk were > 97% disease-free at 5 years 295 (69%) 208 (49%) 81% adjuvant chemotherapy High Risk High Risk MammaPrint High Risk were > 91% disease-free at 5 years Traditional Clinical Parameters* MammaPrint 47 Drukker et al. Int J Cancer; 2013

48 Discordant cases between MammaPrint Low and Adjuvant Online High who received no AST (n=70) There was no recurrence risk when the MammaPrint recommendation was followed CT + ET ET CT 70 No AST 48 Drukker et al. Int J Cancer; 2013

49 MammaPrint vs. Oncotype 31% High Risk 69% Low Risk genes, 465 controls Interrogates all 7 critical genomic pathways Outcomes based: Queried entire genome to identify most predictive genes for recurrence for patients with known outcomes Binary result (High / Low Risk) Comprehensive of ER+/-, HER2+/-, Node +/- Microarray platform Developed on untreated population 12% High Risk 39% Intermediates 49% Low risk genes, 5 controls Interrogates 3 of the 7 critical genomic pathways Literature based: Genes selected based on documented gene function Ternary result (High, Low, Intermediate) Limited to ER+, HER2-, N +/- PCR platform Validated with tamoxifen treated patient population MammaPrint 1. Molecular Subtyping when combined with BluePrint Oncotype van de Vijver MJ, He YD, van't Veer LJ, Dai H, Hart AA, Voskuil DW, et al. N Engl J Med 2002;347: Paik et al: N Engl J Med 351(27): Dabbs et al: ASCO 2014 poster 4. Carlson JJ, et al. Breast Cancer Res Treat.2013 Aug;141(1):

50 Oncotype Intermediate Friend or Foe? 50

51 # patients Promis Study Interim results (n=347) N=347 median ODX score is 21 MammaPrint Low Risk 165 (48%) median ODX score is 20 MammaPrint High Risk 182 (52%) median ODX score is 23 Distribution MammaPrint risk Low Risk High Risk ODX score 51

52 All depends on your perspective Over treating? Under treating? Don t have to give chemotherapy Can give chemotherapy Let s me be a doctor(???) 52

53 BREAST CANCER - SURVIVAL Kaplan-Meier Survival Curves Which Breast Cancers Return? 53

54 Molecular Profiling Mutational Analysis 54

55 Molecular Profiling Caris Molecular Intelligence Multiplatform Assay Over 50 actionable mutations Foundation One Next Gen Sequencing About 20 actionable mutations Paradigm Next Gen Sequencing-DNA and mrna Quicker turnaround time Over 60 actionable mutations Theraprint Agendia Not commercially available 55

56 Where We Started Histology Adenocarcinoma Large cell carcinoma / not otherwise specified Squamous cell carcinoma Small cell lung cancer Scagliotti, GV. Individualized therapy in lung cancer: where are we in 2012? 13th International Lung Cancer Congress; July 19-22, 2012; Huntington Beach, CA. - See more at: 56

57 Where We Have Evolved Molecular Subtypes EGFR mutants ALK ROS1 RET HER 2 B-raf K-ras. Adenocarcinoma Large cell carcinoma / not otherwise specified Squamous cell carcinoma Small cell lung cancer Adapted from Scagliotti, GV. Individualized therapy in lung cancer: where are we in 2012? 13th International Lung Cancer Congress; July 19-22, 2012; Huntington Beach, CA. - See more at:

58 How Genomics Accelerates Personalized Medicine PERSONALIZED MEDICINE EGFR mutants ALK ROS1 HER2 B-raf K-ras affiliates. 58

59 The Financial Burden of Non-Responders Avastin Rituxan Herceptin Revlimid Gleevec $3.059B $2.466B $1.526B $1.373B $1.285B Taxotere Alimta Gemzar Tarceva Femara $1.042B $975M $723M $661M $650M Erbitux Velcade Xeloda Arimidex Leuprolin $646M $598M $508M $494M $483M Responder Non-Responder $ Total Drug Sales Sources: Individual Drug Labels. US Food and Drug Administration. Market and Product Forecasts: Top 20 Oncology Therapy Brands. DataMonitor,

60 60 Molecular Subtyping

61 Identified molecular intrinsic subtypes for Invasive Ductal Carcinoma Demonstrated statistically different rates of survival as well as recurrence free survival for the different molecular subtypes. 61 Sorlie et al, PNAS 2001

62 BluePrint development: Functional molecular subtyping Three classes were determined by IHC in concordance with TargetPrint microarray single gene read-out: Protein IHC/FISH Testing ER PR HER2 mrna Target Print Single Gene Expression Luminal-type = positive ER and/or PR hormone receptor status (hormone positive) Concordance HER2-type = positive HER2 status Basal-type = negative ER, PR and HER2 status (triple negative) Luminal-type HER2-type Basal-type 58 Genes 4 Genes 28 Genes 62 Dataset used: NEJM-295 Rosetta data Profile: 80 genes (overlap with Perou ~25 genes, overlap with PAM50 9 genes, overlap with MP 4 genes of 70- set, 10 genes of 231-set, overlap with TP 3 genes).

63 Intrinsic Subtypes BluePrint 48 PAM Krijgsman et al 2011 Br. Can Res. Treat

64 What are functional molecular subtypes? Molecular subtypes show which pathway drives cancer growth. Luminal-type driven by estrogen pathways HER2-type driven by HER2 pathways Basal-type lack of expression of ER/PR/HER2 There is ~20% discordance between molecular subtypes and subtyping with IHC (Nielsen et al., 2010) 64

65 Clinical subtyping limitations Example: ER+ patients by clinical subtyping IHC ER+ RESPONDING TO THERAPY Ta m ox i fe n NOT RESPONDING TO THERAPY Tamoxifen Therapy 65

66 Protein expression does not indicate pathway is functioning Three ways to measure Estrogen Receptor Activity (Luminal activation) ER Gene TOOL MEASUREMENT TargetPrint mrna ERmRNA IHC Protein ER protein BluePrint ER Function 66

67 Functional molecular subtyping with MammaPrint and BluePrint Low Risk Luminal-type Low Risk Luminal-type A High Risk Luminal-type B HER2-type Low Risk HER2-type High Risk HER2-type High Risk Basal-type High Risk Basal-type 67

68 The importance of molecular subtypes for treatment St Gallen guidelines, 2013 St. Gallen Subtype IHC Subtype Functional Molecular Subtype Luminal A-like Luminal B-like (HER2 negative) Luminal B-like (HER2 positive) HER2 positive (non-luminal) Triple negative (ductal) HR+/HER2-/Ki67 low HR+/HER2-/Ki67 high HR+/HER2+ HR-/HER2+ HR-/HER2- Low Risk Luminal (A) High Risk Luminal (B) Low Risk HER2-type High Risk HER2-type High Risk Luminal-type (B) High Risk HER2-type High Risk Basal-type The panel recognized the superior accuracy and reproducibility of multi-gene molecular assays, but recognized that these assays are not available in all parts of the world. 68 Goldhirsch et al., Ann Oncol 2013: St Gallen guidelines

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70 Molecular reclassification by MammaPrint and BluePrint ER-positive HER2 Basal Total HER2-positive 7 36 Triple Negative (n) Glück, et al. BCRT 2013

71 Chemosensitivity and 5yr DMFS by MammaPrint and BluePrint molecular subtyping BluePrint Subtyping Chemosensitivity pcr (%) 5yr DMFS by Response Luminal-type A 5/90 (6%) pcr 75% no pcr 94% Luminal-type B 16/154 (11%) pcr 85% no pcr 72% HER2-type 33/69 (48%) pcr 91% no pcr 64% Basal-type 45/122 (37%) pcr 91% no pcr 54% p p p p Basal-type and HER2-type show significantly higher pcr rates 71 Glück, et al. BCRT 2013

72 5 Year Neo-Adjuvant Evidence 93% DDFS BluePrint Clinical Molecular Subtyping Subtyping by IHC Distant Disease-Free Disease-free Survival Results Low Risk Luminal A 6% pcr yet 93% DDFS Separates ER+ patients accurately into Luminal A from B Luminal B patients have a comparable survival to HER2+ patients HR+HER2- (n=204) Low Risk Luminal (n=90) High Risk Luminal (n=154) HER2 (n=70) Basal (n=123) P< % 81% 77% 74% 68% Glück, et al. BCRT 2013

73 Glück: Relevance for Today ER+ reclassified to Basal-type (11/256): Chemotherapy sensitive patients mistakenly identified as chemotherapy insensitive HER2+ reclassified to Luminal-type (43/107): Dual positive patients perhaps misrepresented as HER2 driven and may not receive any benefit from trastuzumab and chemotherapy 73 Glück, et al. BCRT 2013

74 Defined by clinical assays: ER- PR- HER2- Triple Negative Breast Cancer: What is It? Molecular assays: Heterogeneity is the norm Should one treat a Claudin-Low differently from a Basal-like? 74 Prat and Perou, Molec Oncol 2010 (Slide Courtesy of Carey Anders, MD)

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76 Reclassification of patients with MammaPrint/BluePrint 23% (156/767) of patients are classified in a different subgroup by MammaPrint/BluePrint (BP) vs conventional IHC/FISH assessment Note: Approximately half of HER2+/ER+ patients are BP Luminal 76

77 pcr with neoadjuvant CT: BluePrint vs IHC/FISH 77

78 pcr Clinically High Risk, BluePrint Luminal A response to NCT Clinically High Risk, BluePrint Luminal-type (A) patients have low response to neoadjuvant chemotherapy 15% 10% 5% Response to neoadjuvant chemotherapy IHC/FISH Molecular Subtype 0% (188) (44) HR+/HER2- Luminal A (n) = Patients 78 Whitworth et al, Ann Surg Oncol 2014

79 pcr Clinical HR+/HER2- Reclassification by functional molecular subtype 25% 20% 15% 10% IHC/FISH Molecular Subtype 5% 0% (151) (35) (36) (115) (188) (35) (n) = Patients 2 patients classified to HER2-type 79 Whitworth et al, Ann Surg Oncol 2014

80 pcr Clinical HER2+/HR+ Reclassification by functional molecular subtype 50% 40% 30% 20% IHC/FISH Molecular Subtype 10% 0% (36) (33) (36) (75) (33) (n) = Patients 6 patients classified to Basal-type 80 Whitworth et al, Ann Surg Oncol 2014

81 pcr BluePrint Basal-type patients compared to Triple Negative by IHC patients 52% more patients classified as Basal-type compared to triple negative by IHC (140 vs 92) 35 clinical HR+ patients reclassified as Basal-type with 26% pcr 50% 40% 30% 20% IHC/FISH Molecular Subtype BPBasal have a similar chemosensitivity to clinical triple negative patients 10% 0% (92) (140) (n) = Patients 11 IHC HER2+/HR- patients classified to BPBasal 6 IHC HER2+/HR+ patients classified to BPBasal 81 Whitworth et al, Ann Surg Oncol 2014

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84 Summary Multiple studies have shown superiority of Genomic Profiling over Traditional Clinical Parameters (TCP). TCP remain important but risk assessment can be augmented by utilization of Genomics. Multiple tests on the market, each with their own strengths and weaknesses typically related to the development of the assay. All tests include patients with 1-3 positive lymph nodes suggesting nodal metastasis may not be as important as once thought. Strong prognostic data is more important than weak predictive data (opinion). 84

85 Summary Multiple trials underway to use Molecular Profiling / Mutational Analysis to help guide targeted agent selection. Significant discordance between clinical subtyping and true molecular subtyping. Molecular Subtyping reclassifies over 20% of patients Molecular Subtyping has the potential to change the way we evaluate risk and determine therapy. Recent data suggests dual Her 2 therapy may overcome Herceptin resistance in Her 2 positive Luminal Subtype. 85

86 The Complexity of Therapy Continues to Increase RNA Complexity Different Subtypes within the same Cell Type Patient Response Variations within the same Subtype Dynamic Clonal Heterogeneity Immuno-evasion Cancer Stem Cells?? 86

87 Conclusions Several Genomic tests on the market None are as precise as they would like to be Some have predictive data but none of it is strong All shown to add prognostic accuracy beyond Traditional Clinical Parameters If not already utilizing, do your own due diligence, pick one and use. 87

88 88 Thank You