From pathology research to stratified medicine trials. JB... · “Stratified medicine requires...

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From pathology research to stratified medicine trials 1 Dr. John Bartlett Program Director Transformative Pathology C CCTG Breast Group Steering Committee ASCO-CAP HER2 Panel “As is your Pathology, so is your Medicine.” Sir William Osler. 1849-1919.

Transcript of From pathology research to stratified medicine trials. JB... · “Stratified medicine requires...

Page 1: From pathology research to stratified medicine trials. JB... · “Stratified medicine requires stratified diagnostics” Failure to improve diagnostic pathology, both in the quantity

From pathology research

to stratified medicine

trials

1

Dr. John BartlettProgram Director Transformative Pathology C

CCTG Breast Group Steering CommitteeASCO-CAP HER2 Panel

“As is your Pathology, so is your Medicine.” Sir William Osler. 1849-1919.

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San Antonio Breast Cancer Symposium, December 9-13, 2014

Cancer = “the big C”?

1950-70s Cancer as 1 diseaseDNA structure discovered 1953

1970-80s Cancer as “site specific”

“one size fits all”

1990-2000sCancer “subtypes”

Herceptin – targeted treatments

2010s: Molecular complexity and Heterogeneity

Genomic data overload –

4.1Million mutations in 1000 cancers..

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ONTARIO INSTITUTE FOR CANCER RESEARCH

Cancer Treatment: 20th century

Surgery

Radiotherapy

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Pan Cancer projects: Unlocking cancer

genomic data

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Information at the pathway level

Version: 26Apr2012

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Insights into global cancer processes

• Mutation vs CNAs

– a fork in the cancer

genome road map?

• “M” vs “C” class cancers?

– Mutations and CNAs

represent fundamentally

different aspects of cancer.

– Most cancers are “mixed”

with low numbers of

alterations– Ciriello G, et al, Nat Genetics 2013

45:1127-1133

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7Nature Genetics 45, 1127–1133 (2013)

M-Class Cancers

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C-Class Cancers

Nature Genetics 45, 1127–1133 (2013)

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The challenge posed by ICGC:

Cancers are heterogeneous:

Between patient heterogeneity – requires stratified

treatment approaches;

Within tumour heterogeneity – target multiple clones –

requires combination/multi-agent targeted therapy;

Selection of resistant clones during treatment requires

adaptive therapies.

NB Cancer has not changed – our understanding has

improved – current treatments are effective in the context of

molecular heterogeneity.

ICGC puts widely recognized and existing therapeutic and

treatment challenges in a molecular context – enabling a rational targeted therapeutic approach.

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Cancer Paradoxes or cancer successes?

TCGA colorectal cancer

4 molecular subgroups

ULTRA mutated cancers

Genetically unstable, multiple driver mutations

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ONTARIO INSTITUTE FOR CANCER RESEARCH

Cancer Paradoxes or cancer successes?

Version: 26Apr2012

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PIK3CA mutations: One gene –two results

0 100 200 300 400 500 600 700

0.0

0.2

0.4

0.6

0.8

1.0

Time, days

EVE.PIK3CA.WT

EVE.PIK3CA.Alt

PBO.PIK3CA.WT

PBO.PIK3CA.Alt

Pro

bab

ilit

y o

f

Pro

gre

ssio

n-F

ree S

urv

ival

In early breast cancer PIK3CA mutation is linked to good outcome, in metastatic

breast cancer PIK3CA is linked to poor outcome – what changed?

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The challenge of Context:

It is not enough to model gene function in isolation.

Treatment of different cancers, even with similar

molecular drivers, varies.

Molecular drivers, viewed in isolation, may have

different impacts at different stages of disease.

The relationship between the molecular make up

of a cancer and outcome for a patient reflects a

complex integration of multiple treatment and

response variables.

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ONTARIO INSTITUTE FOR CANCER RESEARCH

Cancer is highly complex.

10,048 cancers

An average of 400 mutations per cancer

Over 100 different druggable mutations

9.3x10157

permutations!

If only 10% are

present =

3.6x106

permutations

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To summarize….

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Personalised medicine –

progress to date

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HER2 – the test that came in from the

cold:

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HER2 – selective for Herceptin Benefit (2005!)

87%85%

67%

75%

%

HR=0.48,2P=3x10-12

AC TH

AC T

Years From Randomisation

Herceptin/Trastuzumab:

“Humanised” mouse antibody

Targets BRCA driver gene HER2

Reverses poor outcome in some

“HER2 positive” BRCA (15%)

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Successful personalised drug development

Rapid identification of potential targets

For “druggable” targetsInterval from target to clinical candidate is shorter

For clinically important targetsInterval from FIH to drug approval is short

Chin L et al. Nature Medicine 17: 297-303, 2011

FD

A A

pp

ro

val

20

11

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Personalized medicine?

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In 2015 the FDA

Approved 15 new therapeutic agents

Approved 11 new applications of existing

therapeutic agents

Approved one new diagnostic test

for existing EGFr mutation detection

“As is your Pathology, so is your Medicine.” Sir

William Osler. 1849-1919.

“As is your molecular pathology – so is your

molecular medicine” - David Huntsman

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CDK/CCND pathway

CDK4/CCND1 –

amplified 15-20% breast

cancer

Luminal ER+ BC cells

sensitive to CDK4/6

inhibitor palbociclib

Palbociclib + letrozole

approved for ER+/HER2-

breast cancer

No biomarkers to select

patients for treatment

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PI3K/AKT/mTOR pathway

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Most commonly altered

pathway in BC

PIK3CA mutated in 35-

40% ER+ BC

AKT1 2-4% ER+ BC

PTEN 29-44% ER+ BC

Resistance to endocrine

therapy

Everolimus +

exemestane approved

for ER+/HER2- breast

cancer

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5-15% benefit from therapy

benefit from therapy

do not benefit try alternate therapyIdentify new target

Current paradigm

response to therapy no response to therapy

Treat

Test

F4LBC Dream Team

Don’t Treat

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5-15% benefit from therapy

benefit from therapy

do not benefit

Current reality

Test

F4LBC Dream Team

Treat

Treat

response to therapy no response to therapy

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Multiple targets - multiple opportunities

F4LBC Dream Team

Zardavas D, et al. Nat Rev Clin Oncol. 2013;10(4):191-210.

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How do we treat breast cancer

Stage

BiologyRisk

Chemotherapy benefit estimate from proportional hazards

Grade + receptors

NPI Adjuvant!

Assumes that breast cancer is a single disease (One size fits all)

Assumes that chemotherapy benefit is present in ALL

cancer subtypes. Biology

Endocrine therapyHER2-targeted therapy

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How should we treat cancer?

5-15% benefit from therapy

Current therapy

Alternate therapies

Treat

Don’t treat

TEST Less therapy

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Lack of Personalised Medicine:

One Size Fits All

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15

Bre

as

t C

an

ce

r M

orta

lity (%

)

Years

None

Tamoxifen (5yrs)

3.6%

7.9%

9.2% Benefit from

TamoxifenTreat 11 – “benefit” 1.

25% exhibit or acquireTamoxifen/endocrineresistanceNEW TREATMENT

65% “cured” by surgery/RxREDUCE TREATMENT

For each treatment “success”3 patients experience resistance7 patients are treated unnecessarily<10% of patients gain benefit

ALL risk side effects

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Reducing treatment:

Integrate risk and reduce

treatment for low risk patients

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Oncotype DX: RS as Continuous

Predictor in tam treated patients

0%

5%

10%

15%

20%

25%

30%

35%

40%

0 5 10 15 20 25 30 35 40 45 50

Dis

tan

t R

ecu

rre

nce

at

10

Ye

ars

Recurrence Score

Low-Risk Group High-Risk Group Intermediate-

Risk Group

Data from NSABP B14: Paik NEJM 2004, 351:2817

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B-20 Results: Relative benefit of chemo on 10 Year DDFS

Paik et al. J Clin Oncol. 2006.

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Optimal Personalised Treatment of early breast

cancer usIng Multi-parameter Analysis

Objectives1. To establish a method of selecting patients with hormone sensitive

primary breast cancer who are likely to benefit or not benefit from post-operative chemotherapy.

2. To establish the cost-effectiveness of alternative test-guided treatment strategies compared to standard practise

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OPTIMA Design

Radiotherapy given according to local practise

Adequate surgery

Age ≥ 40

ER +ve, HER2 –ve

N+/ N0 & T>30mm

Central confirmation of ER

& HER2 Endocrine therapy continued to 5+ yrs

Permitted chemotherapy: FEC75-100 x 6 cyclespre-specified by patient TC x 4 cyclesbefore randomization FEC100-T

E-CMF

Permitted endocrine therapy: postmenopausal - any AI premenopausal - GnRH agonist (3 yrs) + tamoxifen

Exclusion: advanced

stage = ≥ 10 N+/ IM+

Sample size to demonstrate non-inferiority (-3%) = 1860 per arm

chemo.

endocrine

R

endocrine

chemo. endocrine

1

1 Test

Patients receiving chemotherapy blind to randomisation

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Stratified medicine – and diagnostics

5-15% benefit from therapy

Current therapy

Alternate therapies

Treat

Don’t treat

TEST Less therapy

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Use existing Phase III trial of current SOC to develop

stratified medicine approaches to breast cancer

We rarely know why patients respond to treatment;

We more often know why they do not – and it is

usually different for different patients.

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Gene Hazard Ratio 95% CI Freq(%)UPF3B 8.40 1.98-35.64 0.73CBLB 5.83 1.40-24.36 0.87ERBB2 4.60 1.64-12.87 2.04BRCA1 2.32 1.18-4.56 7.57USH2A 2.16 1.22-3.83 11.35TP53 1.93 0.96-3.91 8.01AKT1 0.77 0.18-3.15 3.78MET 0.69 0.28-1.72 9.17PIK3CA 0.66 0.37.1.18 30.1GATA3 0.61 0.08-4.46 2.91EPHA5 0.53 0.17-1.68 7.13

F4LBC Dream Team 37

TEAM trial: integrating genomics

CGH/CNV

ad

just

ed

HR

targeted sequencing mRNA profiles

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PIK3CA pathway: mutation, CNV, mRNA

CNV

PIK3CA/AKT

gain, PTEN loss

PIK3CA

AKT1

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A Functional Focus: Pathways are paramount:

Molecular alterations rarely exist in isolation

50-200 mutations/CNAs in each cancer.

Intracellular regulatory pathways have key mutational nodes

Evaluation of multiple events/nodes is essential

Mutation

Copy number change

Expression

Proteins etc etc.

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Developing novel stratified diagnostics:

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Pathway and target oriented.

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Umbrella or basket?

Biankin et al, Nature 2015

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Stratified clinical trials

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HIG

H R

ISK

BR

EAST

CA

NC

ER Arm 1: Conventional treatment

Arm 2: Experimental treatment A

Arm 3: Experimental treatment B

Arm 4: Experimental treatment C

Ran

do

mise

Mo

lecular d

iagno

stic screen

Pre-operative Neo-adjuvant Adjuvant2-3 weeks 3-4 months 3-5 years

Low risk – conventional or reduced treatment

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Stratified medicine – and diagnostics

5-15% benefit from therapy

Current therapy

Alternate therapies

Treat

Don’t treat

TEST Less therapy

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To Dream the impossible dream?

RNA

CNA

CpG

Mut

mRNA

miRNA

Mutation

CNA

CpG

Ptn

“a new era of medicine — one that delivers the right treatment at the right time, to the right patient”

“Stratified medicine requires stratified diagnostics”Failure to improve diagnostic pathology, both in the quantity and the quality of information derived will continue to restrict the development of personalised medicine.

“As is your Pathology, so is your Medicine.” William Osler 1848-1919

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“I want the country

that eliminated polio

and mapped the

human genome to

lead a new era of

medicine — one that

delivers the right

treatment at the right

time,”

President Obama 21st

Jan 2015.

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OICR Diagnostic Development:

“mi casa es su casa”

IHC and FISH:

Ventana, Dako autostainer, FISH

Light and fluorescence microscopy

Bioview (FISH), Ariol, Definiens

mRNA:

Multiplex PCR/Nanostring q-mi/mRNA

RNAseq

DNA – targeted seq/CNV MLPA etc

Preclinical – cell culture, high throughput drug screening, in vitro, invivo.

Tissue:-

Laser capture micro/manual macro – 10,000s samples

ONTARIO TUMOUR BANK 15,000 samples

Breast/Prostate tissues (20-30,000)

TMAs, frozen section, etc etc…

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Funding for the Ontario Institute for Cancer Research

is provided by the Government of Ontario

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The Tumor Ecosystem: Joan Brugge

Hypothesis: there is a limit to the number of insults that the ecosystem can withstand.

Need to identify critical set of ‘perturbants’ that push the ecosystem to point beyond its ability to adapt.

Susan Komen Lecture

The facts expressed here belong to everybody, the opinions to me. The distinction is yours to draw.