Transforming treatment and improving survival for - PowerPoint Presentation

Slide1

Transforming treatment and improving survival for ovarian cancer patients

Laura Shawver, PhDFounder

Applications of genomic profiling for real time decisions in cancer treatment Slide2

OverviewOvarian Cancer statistics and treatment

Clearity Foundation: mission and processClearity profiling panel and results interpretation

Incorporating profiling in clinical trial designsSlide3

22,280 new cases and 15,500 deaths estimated in the US in 2012~75% diagnosed at stage III/IVMost treated with surgical cytoreduction

followed by adjuvant platinum-taxane based chemotherapyMost patients recur within 2 years and receive multiple rounds of subsequent chemotherapy

27% survive >10 years Ovarian cancer statistics and standard of careSlide4

Multiple choices for recurrent disease

Can we inform the treatment decision?

NCCN Guidelines for Epithelial Ovarian Cancer/Fallopian Tube Cancer/Peritoneal Cancer 3.2012 Slide5

Bring molecular profiling to the forefront of ovarian cancer diagnosis and treatment

Assist doctors in identifying

therapy informed by their patient’s tumor molecular profileExpedite 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:Slide6

Leading advisors and scientific presentations

Scientific Advisory Board

Beth Karlan, MD, Chair

Cedars Sinai & UCLA Medical Center

Doug Levine, MD

Memorial Sloan Kettering Cancer Center

Johnathan

Lancaster, MD

Moffitt Cancer Center

Julie Cherrington, PhD

Pathway Therapeutics

Ursula Matulonis, MD

Dana Farber Cancer Center & Harvard Medical School

Deb Zajchowski, PhD

Clearity

Foundation Scientific Director

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. ShawverSlide7

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

7Slide8

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 patientSlide9

Use tumor molecular profiles to inform choice of chemotherapy and/or clinical trial

Chemotherapy Marker Panel

Targeted Therapy Marker PanelSelect chemo for combination with targeted agent in clinical trial

Select chemotherapy for next treatment

Select clinical trial with targeted agent

9Slide10

Key take away messages

Chemotherapy agents are targeted cytotoxic treatmentsChemotherapy 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 utilizedfor chemotherapy agentsfor molecular targeted agentsfor clinical trialsClinical trials should be considered early in the treatment processSlide11

* DNA amplification

Growth

Factors/ Receptors

EGFR*

Her2*

IGF1R

c-Met*

VEGF

PDGFR

Cytoplasmic

Signal Transducers and Apoptosis Regulators

K-

ras

**

B-

raf**PIK3CA**PTENBcl-2SurvivinCox-2

Nuclear Signaling Proteins

Hormone

Receptors/Transcription Factors

Cell Cycle

ER

AR

PR

Ki67

p16

Rb

Chemotherapy Resistance Markers

Drug Transporters

DNA Repair/ Modification

DNA Synthesis/Cell Division

BCRP

MRP1

MDR1/PGP

ERCC1

MGMT

RRM1

TS

TUBB3

** DNA mutational analysis

Chemotherapy Sensitivity Markers

DNA Synthesis/Transcription

ECM

TLE3

Topo1

Top2A

SPARC

Current panel of IHC tests

11Slide12

*200 patients; March 15, 2012 (n=242; Aug 15, 2012)

Data stored and analyzed in

Diane Barton DatabaseSlide13

Data collected as

histoscores

Histoscore =

% tumor stained x Intensity =92Slide14

Marker expression in all patients provides basis for interpretation of individual results

Box, inter-quartile range; line, median; whiskers, maximum and minimum valuesSlide15

http://www.clearityfoundation.org/drugs-and-biomarkers.aspxClinical research evidence for biomarkers is used to interpret resultsSlide16

Low:

<25th percentile High:

>75th percentile

Low RRM1



Gemzar

High

Topo

II 

Doxorubicin,

etoposide

High PGP  No

Taxane

, no

doxil

High Topo I  Irinotecan, topotecanHigh SPARC nab-PaclitaxelChemotherapy selection uses published evidence and expression cut-offs derived from current databaseLow TS  Fluoropyrimidines

High BCRP  No

TopotecanSlide17

17

Case Study

: profile

for patient diagnosed in 3/2005 with stage IIIB papillary serous carcinoma Slide18

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

wtSlide19

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 studiesSlide20

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 Slide21

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 optionSlide22

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 cancerSlide23

RRM1 is

gemcitabine’s

target and efficacy biomarker

For information on each marker,

visit

http://

www.clearityfoundation.org/drugs-and-biomarkers.aspx

23Slide24

Ge,zar

24

Case Study

: profile

for patient diagnosed in 3/2005 with stage IIIB papillary serous carcinoma

Gemcitabine

Gemzar

(3/2010)

9/2011: NEDSlide25

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 <25

th

percentile; TOP2A, TOP1 >75

th percentile.150/196 (76%) can be assigned to one of these agents.25Slide26

Biopsy of recurrent disease is needed to obtain relevant profiling information

26

Mol

Cancer

Ther

; 11(2) February 2012

68% 3+; 255

5% 2+; 10

Primary

Recurrence

EGFRSlide27

Marker expression differences in patient-matched primary and recurrent samplesSlide28

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 200828Slide29

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, 609- 615 (2011)

29Slide30

From TCGA study: Nature 474, 609- 615 (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

inhibitorsMEK inhibitorsNotch inhibitorsPARP inhibitorsSlide31

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

31Slide32

Expanded panel provides more options for Clearity patients

TaxanesGemcitabineDoxilTopo

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+ genesSlide33

Frequency of hotspot mutations in PIK3CA, KRAS, BRAF, and EGFR is histology-dependentClear cell: PIK3CAMucinous and

carcinosarcoma: KRASSlide34

AMP

AMP

>5-fold

≤5-fold

SS, splice site mutation; FS,

frameshift

; TR, truncation

Examples of gene alterations in recurrent

ovarian cancer Slide35

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 diseaseTopotecanSlide36

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 profiled1/2010 Topotecan + AMG 386* (clinical trial)5/2011 Stable disease6/2011 Surgery -- residual diseaseRxIrinotecan + EverolimusTumor profiled9/2012 NEDIrinotecanEverolimusSlide37

DNA Sequencing Results

SUMMARY of AGENTS

IHC Results

IHC results—Drug correlations

Protein and DNA results are integrated into one report that highlights therapy optionsSlide38

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

38Slide39

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

39Slide40

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 patientReduce costs of profiling assays and make efficient use of biopsy samplesMake more treatment options available for ovarian cancer patients

40Slide41

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 Slide42

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!Slide43

www.clearityfoundation.org