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Tumour Heterogeneity and Liquid Biopsy

Naples, 24/05/2019

Nicola Valeri MD, PhD, FRCP

Associate Professor in Personalized Oncology

Team Leader, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK

Consultant Medical Oncologist, The Royal Marsden Hospital, London, UK

8th meeting on EXTERNAL QUALITY ASSESSMENT IN MOLECULAR PATHOLOGY

➢ Challenges

➢ Solutions

Promises and hurdles in Precision Oncology

➢ Challenges

➢ Solutions

- Logistics

- Identifying the target

- Exploiting the target

- Identifying better and more cost/effective strategies to

stratify patients


Zehir et al. Nature Medicine 2017

Promises and hurdles in Precision Oncology:

Logistics


Logistics

Moorcraft et al. Annals of Oncology 2018

➢ Challenges

➢ Solutions

- Logistics




stratify patients


Meric-Bernstam F et al. J Clin Oncol 2015; Ferté C et al. Cancer Res 2014; Le Tourneau C et al. Lancet Oncol

2015; Zehir et al. Nature Medicine 2017


Can we identify a target?

Actionable Targets by NGS 30-40%

Genotype-matched treatment 4-11%

Clinical benefit (durable PR/SD) Anecdotal

Meric-Bernstam F et al. J Clin Oncol 2015; Ferté C et al. Cancer Res 2014; Le Tourneau C et al. Lancet Oncol

2015; Zehir et al. Nature Medicine 2017



Actionable Targets by NGS 30-40

Genotype-matched treatment 4-11%

Clinical benefit (durable PR/SD) Anecdotal

DNA-Guided Precision Medicine for

Cancer: A Case of Irrational Exuberance?

Voest & Bernards. Cancer Discovery 2016

Estimation of the Percentage of US

Patients With Cancer Who Benefit From

Genome-Driven Oncology.

Marquart et al. JAMA Oncology 2018



➢ Challenges

➢ Solutions

- Logistics




stratify patients



Is patient’s selection = clinical benefit?

1st line trials of novel agents in gastroesophageal cancer since 2010Trial Regimens OS/PFS HR (95% CI) P value Months

BIOMARKER SELECTED

TOGA Cis-5FU OS 0.74 (0.60-0.91) 0.0046 11.1

Cis-5FU + trastuzumab 13.8

LOGiC CapeOXOS 0.91 (0.73-1.12) 0.35

10.5

CapeOx+lapatinib 12.2

RILOMET ECXOS 1.37 (1.06-1.78) 0.016

11.5

ECX+rilotumumab 9.6

METMab FOLFOX

Onartuzumab+FOLFOXOS 0.82 0.244 11.3

11.0

NON-BIOMARKER SELECTED

AVAGAST Cis-5FU OS 0.87 0.1001 10.1

Cis-5FU + bevacizumab 12.1

REAL-3 EOXOS 1.37 (1.07-1.76) 0.013

11.3

EOX+panitumumab 8.8

EXPAND CXPFS 1.09 (0.92-1.29) 0.32

10.7

CX+cetuximab 9.4

Bang et al. Lancet 2010; Hecht et al. J Clin Onc 2015; Cunningham et al. ASCO 2015; Shah et al. ASCO 2015;

Ohtsu et al. J Clin Onc 2011; Waddell et al. Lancet Oncol 2013; Lordick et al. Lancet Oncol 2013




FGFR2 inhibition in gastro-oesophageal cancer

a tale of two trials

RMH FGFR trial – met primary endpoint –

33% ORR

Pearson et al. Cancer Discovery 2016

AZ SHINE trial – closed for futility – no

responders (1 mixed)Van Cutsem et al. Annals of Oncology 2017

Images courtesy of Neil R Smith

Intra-patient heterogeneity of biomarker expression affects outcome even in

biomarker selected populations.


FGFR2 inhibition in gastro-oesophageal cancer

a tale of two trials


0,50

1,00

2,00

4,00

8,00

16,00

32,00

99 12 135 214 206 87 316 269 21

FG

FR

2 C

NV

pla

sm

a

FGFR2 plasma CNV (OG)

*pt no 99 = no pretreatment sample

= response


FGFR2 CNV in plasma predicts response to

AZD4547


Conclusions I: Current limitations of

personalized medicine

➢ Logistics: access to material, degraded FFPE

tissues, turnaround time, cost/effectiveness

➢Biology: cancer heterogeneity, cancer evolution

➢ Challenges

➢ Solutions

- Logistics




stratify patients


Liquid Biopsy

Invasiveness Low

Compliance High

Cost/Effectiveness High

Time 3 days

Repeated biopsy Possible

Open issuesSensitivity/

reproducibility

Promises in Precision Oncology:

Liquid biopsies

Corcoran & Chabner. NEJM 2018

Should liquid biopsies substitute solid

biopsies in clinical practice?

1) Using liquid biopsies to determine RAS status

2) Using liquid biopsies to monitor response and resistance

3) Using liquid biopsies to identify vulnerabilities

Testing RAS pathway abnormalities in

metastatic colon cancer

Misale et al. Cancer Discovery 2014

Khan et al. Cancer Discovery 2018

Multi-region Sequencing and Cancer

Heterogeneity in the RAS pathway

Metastatic colorectal

cancer patientTreatment (Cetuximab EGFR inhibitor)

Blood

Tissue

biopsy

Diagnostic tissue

sampleTissue

biopsy

Tissue

biopsy

Scan Scan Scan


Longitudinal biopsies to monitor anti-EGFR

response: the PROSPECT-C Trial

Methods for cell-free (cf)DNA analysis in the

PROSPECT-C Trial

- Tiered approach: test for Individual hot-spots

- Rapid Turnaround time

- Relatively inexpensive

- 77 genes panel including APC and TP53

- Rapid Turnaround time

- Relatively expensive

Digital-droplet PCR

(Cohort I)

NGS “Avenio” panel

(Cohort II)

Limitations of a tiered approach for cfDNA

testing

Digital-droplet PCR

(Cohort I)


Testing RAS status in pre-treatment bloods

- Approximately 25% of patients who tested as RAS wild-type on archival tissues show

mutations in pre-treatment bloods

- Approximately 50% of patients harbour mutations in the RAS pathway (i.e. ERBB2)

Digital-droplet PCR

(Cohort I)

NGS “Avenio” panel

(Cohort II)


Mutations in the RAS pathway in pre-treatment

bloods are associated with no status benefit

from EGFR inhibition

NGS of post-treatment bloods identifies drivers

of resistance to EGFR inhibitors


Comparison of solid and liquid biopsies




ERBB2 CNV

validation in tissues

and bloods


Most RAS mutations detected

in blood are present at low VAF

in tissues


ERBB2 CNV

validation in tissues

and bloods

Analysis of liquid and solid biopsies confirms

that resistance to EGFR inhibition is polyclonal



Using liquid biopsies to inform clinical decisions


Using liquid biopsies to inform clinical decisions:

monitoring ctDNA to forecast evolution

Monitoring ctDNA to forecast evolution from

academic exercise to relevant tool

Sensitive

Resistant

Baseline Response Relapse

Lote, Spiteri, Ermini et al. Annals of Oncology 2017; Khan et al. Cancer Discovery 2018

Dating cancer progression and resistance

050302011 40

0.01

0.11

0.21

0.31

0.41

Mutant detected

in the blood

Predictive window

of opportunity

Relapse

Weather prediction:

Wind

Humidity

Temperature

Resistance prediction:

Frequency in the driver

Sensitivity of the method

Frequency of blood sampling


Blood-Based Prediction of Tumour Relapse: The

ctDNA Forecast

From “Precision Medicine” to “Tight Medicine”

Health/Economic implications of personalised

medicine

49

Cost of Trial without patient selection = £642.141



medicine

50

Cost of Trial without patient selection = £642.141

Estimated cost of Trial with patient selection = £437.108



medicine

Conclusions: next-generation biopsies to

improve patient’s outcomes

1. Analysis of RAS status in pre-treatment bloods

improves selection of patients candidate to anti-

EGFR treatment.

2. Frequent serial blood sampling allows to

forecast treatment failure at single patient level

and might identify vulnerabilities.

Drug Discovery Unit ICR, UK

Udai Banerji

Johann de Bono

Molecular Diagnostics RMH, UK

Michael Hubank

Paula Proszek

Sanna Hulkki

University of Padua IT

Matteo Fassan

Massimo Rugge

Beatson Institute for Cancer Research, UK

Owen Sansom

Royal Marsden NHS Trust

Khurum Khan

Francesco Sclafani

Lizzy Smyth

Shelize Khakoo

Gayathri Anandappa

Sing Yu Moorcraft

Ian Chau

Ruwaida Begum

Clare Peckitt

Naureen Starling

David Watkins

Sheela Rao

Asif Chaudry

Nina Tunariu

Dow-Mu Koh

William Allum

David Cunningham

Valeri’s Lab

Andrea Lampis

Jens Hahne

Mahnaz Darvish Damavandi

George Vlachogiannis

Hazel Lote

Somaieh Hedayat

Massimiliano Salati

Institute of Cancer Research

Andrea Sottoriva

Chiara Braconi

Anguraj Sadanandam

Steven Whittaker

Vladimir Kirkin

Sue Eccles

Simon Robinson

Paul Clarke

Rosemary Burke

Paul Workman

George Poulogiannis

Gabriela Kramer-Marek

Javier Fernandez Mateos

Inma Spiteri Sagastume

Yann Jamin

Janet Shipley

Mel Greaves

Acknowledgments

NIHR RM/ICR Biomedical Research Centre

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