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Transforming treatment and improving survival for ovarian cancer patients Laura Shawver, PhD Founder Applications of genomic profiling for real time decisions.

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Presentation on theme: "Transforming treatment and improving survival for ovarian cancer patients Laura Shawver, PhD Founder Applications of genomic profiling for real time decisions."— Presentation transcript:

1 Transforming treatment and improving survival for ovarian cancer patients Laura Shawver, PhD Founder Applications of genomic profiling for real time decisions in cancer treatment

2 Overview Ovarian Cancer statistics and treatment Clearity Foundation: mission and process Clearity profiling panel and results interpretation Incorporating profiling in clinical trial designs

3 22,280 new cases and 15,500 deaths estimated in the US in 2012 ~75% diagnosed at stage III/IV Most treated with surgical cytoreduction followed by adjuvant platinum- taxane based chemotherapy Most patients recur within 2 years and receive multiple rounds of subsequent chemotherapy 27% survive >10 years Ovarian cancer statistics and standard of care

4 Multiple choices for recurrent disease Can we inform the treatment decision? NCCN Guidelines for Epithelial Ovarian Cancer/Fallopian Tube Cancer/Peritoneal Cancer

5 Bring molecular profiling to the forefront of ovarian cancer diagnosis and treatment Assist doctors in identifying therapy informed by their patients tumor molecular profile Expedite the clinical development of novel targeted agents for ovarian cancer Increase the probability of success by utilizing molecular profiling to select patients for clinical trials The Clearity Foundation launched as a non- profit organization in 2008 to:

6 Leading advisors and scientific presentations 6 Mol Cancer Ther; 11(2) February 2012: Treatment-related protein biomarker expression differs between primary and recurrent ovarian carcinomas DA Zajchowski, BY Karlan and LK Shawver ASCO 2011: Expression Profiles in Matched Primary and Recurrent Ovarian Carcinomas DA Zajchowski, BY Karlan and LK Shawver, AACR 2011: Molecular Profiling in Recurrent Ovarian Cancer Patients DA Zajchowski, C Bentley, J Gross, BY Karlan and LK Shawver AACR 2010: Selecting Patients for Ovarian Cancer Clinical Trials by Profiling Tumors against a Broad Panel of Molecular Markers DA Zajchowski, J Gross, BY Karlan, K Bloom, D Loesch, A Alarcon and LK. Shawver

7 Ovarian cancers are molecularly heterogeneous Any one genomic alteration is found in only a small fraction of patient tumors One drug will not be effective for the population Drugs must be developed for specific molecular tumor types Profiling of individual tumors is essential A broad profiling panel is necessary Serous ovarian cancer Data provided by Dr. D. Levine Genomic alterations observed in nearly every chromosome 7

8 How Clearity works Patient and medical team using molecular profiles to prioritize therapeutic options Oncologists and Patients 8 Clearity Profiling Services: Physician and patient education Testing coordination Secure data analysis Results reported to patient

9 Use tumor molecular profiles to inform choice of chemotherapy and/or clinical trial Chemotherapy Marker Panel Targeted Therapy Marker Panel Select chemo for combination with targeted agent in clinical trial Select chemotherapy for next treatment Select clinical trial with targeted agent 9

10 Key take away messages Chemotherapy agents are targeted cytotoxic treatments Chemotherapy will continue to play an important role but molecular targeted agents, on an individualized basis, will become increasingly important Molecular profiling is available to help prioritize treatments and will be increasingly utilized – for chemotherapy agents – for molecular targeted agents – for clinical trials Clinical trials should be considered early in the treatment process

11 * DNA amplification Growth Factors/ Receptors EGFR*Her2*IGF1Rc-Met*VEGFPDGFR Cytoplasmic Signal Transducers and Apoptosis Regulators K-ras**B-raf**PIK3CA**PTENBcl-2SurvivinCox-2 Nuclear Signaling Proteins Hormone Receptors/Transcription FactorsCell Cycle ERARPRKi67p16Rb Chemotherapy Resistance Markers Drug TransportersDNA Repair/ ModificationDNA Synthesis/Cell Division BCRPMRP1MDR1/PGPERCC1MGMTRRM1TSTUBB3 ** DNA mutational analysis Chemotherapy Sensitivity Markers DNA Synthesis/TranscriptionECM TLE3Topo1Top2ASPARC Current panel of IHC tests 11

12 *200 patients; March 15, 2012 (n=242; Aug 15, 2012) Data stored and analyzed in Diane Barton Database

13 Data collected as histoscores Histoscore = % tumor stained x Intensity =92

14 Marker expression in all patients provides basis for interpretation of individual results Box, inter-quartile range; line, median; whiskers, maximum and minimum values

15 Clinical research evidence for biomarkers is used to interpret results

16 Low: 75 th percentile Low RRM1 Gemzar High Topo II Doxorubicin, etoposide High PGP No Taxane, no doxil High Topo I Irinotecan, topotecan High SPARC nab-Paclitaxel Chemotherapy selection uses published evidence and expression cut-offs derived from current database Low TS Fluoropyrimidines High BCRP No Topotecan

17 17 Case Study: profile for patient diagnosed in 3/2005 with stage IIIB papillary serous carcinoma

18 18 Case Study: profile for patient diagnosed in 3/2005 with stage IIIB papillary serous carcinoma High EGFR (98 th percentile) EGFR inhibitors have been ineffective in clinical trials although benefit seen in individual patients Mutations can predict sensitivity and resistance to EGFR inhibitors in lung cancer Follow up mutation analysis conducted; patient was wt

19 19 Case Study: profile for patient diagnosed in 3/2005 with stage IIIB papillary serous carcinoma High ER Anti-estrogens and aromatase inhibitors utilized in ovarian cancer patients but not approved due to lack of efficacy in clinical studies

20 20 Case Study: profile for patient diagnosed in 3/2005 with stage IIIB papillary serous carcinoma High SPARC Clinical trial for nab-paclitaxel (none at the time) or off-label use patient had long history of taxane treatment

21 21 Case Study: profile for patient diagnosed in 3/2005 with stage IIIB papillary serous carcinoma Low TS Fluoropyrimidines and pemetrexed considered as a reasonable option

22 22 Case Study: profile for patient diagnosed in 3/2005 with stage IIIB papillary serous carcinoma Low RRM High RRM1 associated with resistance to gemcitabine Gemcitabine is an approved agent in recurrent ovarian cancer

23 RRM1 is gemcitabines target and efficacy biomarker For information on each marker, visit 23

24 Ge,zar 24 Case Study: profile for patient diagnosed in 3/2005 with stage IIIB papillary serous carcinoma Gemcitabine Gemzar (3/2010) 9/2011: NED

25 Topo II inhibitors Gemcitabine Topo I inhibitors Pemetrexed, capecitabine Often, only one of the commonly used agents to treat recurrent ovarian cancer is prioritized by the profile Teal, tumor marker expression met quartile cutpoint criterion: RRM1, TS 75 th percentile. 150/196 (76%) can be assigned to one of these agents. 25

26 Biopsy of recurrent disease is needed to obtain relevant profiling information 26 Mol Cancer Ther; 11(2) February % 3+; 255 5% 2+; 10 PrimaryRecurrence EGFR

27 Marker expression differences in patient-matched primary and recurrent samples

28 Molecular characterization of ovarian tumors reveals new means for targeting and stratifying patients Advances in methods for genomic characterization of tumor samples (next-gen sequencing in CLIA setting) Increase in the number of molecularly targeted agents entering trials for ovarian cancer Our knowledge and ability to rationally target ovarian cancer has evolved since

29 Low frequency of specific genetic aberrations in primary high grade serous ovarian carcinoma > extensive genomic interrogation necessary to characterize tumors From TCGA study: Nature 474, (2011) 29

30 From TCGA study: Nature 474, (2011) 30 Genomic markers can be used to assign patients to clinical trial agents RB PI3K/RAS Notch HR Alterations/BRCAness CDK inhibitors AURK inhibitors PI3K/AKT/mTOR inhibitors MEK inhibitors Notch inhibitors PARP inhibitors

31 New emphasis for profile: clinical trial selection Chemotherapy Marker Panel Targeted Therapy Marker Panel (IHC and DNA SEQ) Select chemo for combination with targeted agent in clinical trial Select chemotherapy for next treatment Select clinical trial with targeted agent 31

32 Expanded panel provides more options for Clearity patients Taxanes Gemcitabine Doxil Topo I inh (Pemetrexed) DNA repair inhibitors Cell cycle inhibitors Proliferation/ survival signaling inhibitors Targeted Tx panel ChemoTx panel Clinical trial options IHC IHC + DNA Seq* 32 * Next-gen exon sequencing of 182+ genes

33 Frequency of hotspot mutations in PIK3CA, KRAS, BRAF, and EGFR is histology- dependent Clear cell: PIK3CA Mucinous and carcinosarcoma: KRAS

34 AMP >5-fold 5-fold SS, splice site mutation; FS, frameshift; TR, truncation Examples of gene alterations in recurrent ovarian cancer

35 Case Study: profile for patient diagnosed in 2009 with stage IIIC clear cell carcinoma 4/2009 CDDP/tax (ip) x 3 Carbo/tax (iv) x3 12/2009 recurrence Tumor profiled 1/2010 Topotecan + AMG 386* (clinical trial) 5/2011 Stable disease Topotecan

36 DNA Sequencing Results IHC Results Case Study: profile for patient diagnosed in 2009 with stage IIIC clear cell carcinoma 4/2009 CDDP/tax (ip) x 3 Carbo/tax (iv) x3 12/2009 recurrence Tumor profiled 1/2010 Topotecan + AMG 386* (clinical trial) 5/2011 Stable disease 6/2011 Surgery -- residual disease Rx Irinotecan + Everolimus Tumor profiled 9/2012 NED Irinotecan Everolimus

37 DNA Sequencing Results SUMMARY of AGENTS IHC Results IHC resultsDrug correlations Protein and DNA results are integrated into one report that highlights therapy options

38 Clearity report summarizes results from multiple labs and provides consensus interpretation Summary of relevant patient medical history Summary of agents (approved and in clinical trials) associated with clinical benefit extracted from pg 2 Compilation of data from all labs with interpretation (percentile rank, potential drugs) Individual profile compared to ovarian cancer population Contact information for help with clinical trials, lab reports. Number of patients whose data are included in Diane Barton Database 38

39 New emphasis for profile: clinical trial selection Chemotherapy Marker Panel Targeted Therapy Marker Panel (IHC and DNA SEQ) Select chemo for combination with targeted agent in clinical trial Select chemotherapy for next treatment Select clinical trial with targeted agent 39

40 Vision of an Ovarian Cancer Clinical Trials Coalition (OCCTC) Increase the probability of drug development success by utilizing molecular profiling to select patients for clinical trials Facilitate access to eligible patients through patient advocate-driven clinical trials education, outreach, and established web portal for clinical trials identification and matching Remove barriers for screening large number of patients for enrollment by testing for all drug biomarkers in every patient Reduce costs of profiling assays and make efficient use of biopsy samples Make more treatment options available for ovarian cancer patients 40

41 Summary 41 Ovarian cancer is heterogeneous and a broad profiling panel is needed to capture data relevant to each individual Commonly utilized agents for treatment of recurrent ovarian cancer can be prioritized using molecular markers Molecular profiling can help prioritize drugs being tested in clinical trials

42 Thank you! 42 To everyone who has participated in the Clearity process To our physician partners To the Clearity team Dr. Deb Zajchowski Hillary Theakston Kathleen Zajchowski And our volunteers!

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