Diapositiva 1 - eso values in the fM to pM range •Serial killing of tumour cells, activity at low...

13th ESO Colorectal Cancer Observatory: Innovation and care in the next 12 months

Wednesday 29th June 2016, 19:00 – 20:30

Panellists:

Josep Tabernero, ES Roberto Labianca, IT

Barbara Moss, UK Eric Van Cutsem, BE Heinz-Josef Lenz, US

Nadir Arber, IL

Chair: Mario Dicato, LU Co-Chair: Jola Gore-Booth, UK

13th ESO Colorectal Cancer Observatory : Innovation and care in the next 12 months

Roberto Labianca

Ospedale Papa Giovanni XXIII

Bergamo, Italy

View of a Medical Oncologist

Adjuvant therapy of colorectal cancer

2016 NEW PERSPECTIVE

«..the addition of adjuvant chemotherapy for patients with regional (node-positive) disease has been demonstrated to reduce longer-term mortality…»

Welch GH and Robertson DJ: Colorectal cancer on the decline-Why screening

can’t explain it all. NEJM, April 28, 2016

Colon Cancer: stage II

In clinical practice stage II patients will receive adjuvant CT only if “high-risk”, according to clinico-pathological criteria 2016 emerging biological criteria: CDX2 (Malerba et al, NEJM, January 21) Immunoscore (Galon et al, ASCO) Circulating DNA (Tie et al, ASCO) Any of them ready for prime time ? NOT YET

Presented By Jerome Galon at 2016 ASCO Annual Meeting

Presented By Jeanne Tie at 2016 ASCO Annual Meeting

Colon Cancer: stage III

• FOLFOX or XELOX for 6 months will remain the standard treatment for patients up to 70 (75) years

• Oxaliplatin benefit confined to a single subtype? (Pogue-Geile, ASCO 2016)

• In elderly patients: fluoropyrimidine alone is still an acceptable choice

• Duration COULD decrease to 3 months (IDEA data expected in 2017), with better tolerability (TOSCA, IDEA France, ACHIEVE)

Presented By Kay Pogue-Geile at 2016 ASCO Annual Meeting

• Lifestyle intervention (diet, physical exercise, smoking cessation…) YES

• Aspirin (Bains SJ, JCO May 2016…) PROBABLY YES

• Immunotherapy TO BE ASSESSED

• Other interventions TO BE IDENTIFIED

• Role of Adjuvant! Online (ACCENT, in press 2016) TO BE REFINED IN ELDERLY

Colon cancer: new avenues

Rectal Cancer In preoperative setting: fluoropyrimidine alone (capecitabine or 5FU) will remain the standard, without a clear role for oxaliplatin (STAR, ASCO 2016) In postoperative setting: adjuvant chemotherapy (fluoropyrimidine + oxaliplatin) will be more frequently used in clinical practice (see also: Expert Discussion at WCG IC 2015) Through better neoadjuvant treatment: more sphincter saving surgery Biological/genomic characterization: not ready for use

Barbara Moss Patient Advocate

”The patient’s perspective”

View of an Advocate Representative


THE PATIENT EXPERIENCE: Power through Empowerment 13th ESO Colorectal Cancer Observatory

Barcelona, 29th June 2016

Barbara Moss Chair EPAG, EuropaColon

Every cancer patient has a journey........

I was now fully involved in my cancer journey

Being informed gave me the

opportunity to work with my

doctor.

How do we see empowerment?

Our vision is to see patients….

• as joint partners in their care and treatment

• to be self-aware and health-aware

• to participate in decision making if they wish

• to be recognised by clinicians as a key partner in care

What could make a difference to other patients?

Empowerment is intangible.

It helps us to keep control of our lives

Patients and caregivers should be helped with suitable knowledge

Patient groups should monitor and support change

Patient Empowerment is a Process

What needs to change?

Let me know if

you want to

know why I am

here

We should design care around patient needs

Only the patient sees the whole journey

Services that meet the needs of patients require the patient to be involved

A healthcare system for the patient…WITH the patient

And patient organisations to be involved at higher and policy level

How many more people can we encourage to stand up?

Thank you


Josep Tabernero

Vall d’Hebron University Hospital

Barcelona, Spain


Josep Tabernero MD PhD Vall d’Hebron University Hospital

Vall d’Hebron Institute of Oncology (VHIO) Barcelona, Spain

New therapies for

colorectal cancer

Acquired capacities of cancer: phenotype

Hanahan & Weinberg, Cell 2011

Monoclonal Antibodies

GA201 (RO5083945)

GlycoOptimized GT-MAB 5.2-GEX

(Cetugex)™

Sym004

Signal Transduction

R R

K K

Ligands

New EGFR Inhibitors

In vitro

Pedersen MW et al, Cancer Res 2010;70:588-97

Skartved NJ et al, Clin Cancer Res 2011;17:5962-72

Sym004: A novel synergistic anti-EGFR Ab

mixture

Dienstmann R et al. Cancer Discov 2015

Sym004: A novel synergistic anti-EGFR Ab

mixture

EGFR-refractory mCRC: 39 pat. ORR 13%; DCR 44%

Tumor Skin

BRAF (V600E) mutated CRC

• Small population:

– 8-10% early stage

– 4-5% late stage

• BRAF V600E mutations as a biomarker?

– very poor prognosis in late stage (mCRC)

– no clear prognostic effect in early stage

– predictive: negative predictive effect for anti-EGFR MoAbs in some studies:

• Cetuximab: refractory (European cons.)1,2 & first-line setting (CRYSTAL study)3

• Panitumumab: 2nd line setting (PICCOLO study)4

• No change in the label by any regulatory authority predicted

1 Di Nicolantonio F, J Clin Oncol 2018; 2 De Roock et al, Lancet Oncol 2010; 3Van Cutsem et al, J Clin Oncol 2011; 4Seymour MT et al, Lancet Oncol 2013

Corcoran et al, Cancer Discov 2012

Prahallad et al, Nature 2012

BRAFi + EGFRi in BRAF mut CRC

Regimen N PR/CR

(%) SD (%)

mPFS (m)

Vemurafenib + Cetuximab1 27 4 69 3.7

Dabrafenib + Panitumumab2 20 10 80 3.4

Dabrafenib + Trabetinib + Panitumumab2 35 26 60 4.1

Encorafenib + Cetuximab (RP2)3 26 (42) 23 (29) 54 (53) 3.7

Encorafenib + Cetuximab + Alpelisib (RP2)3 28 (49) 32 (35) 61 (44) 4.3

Hyman D et al. NEJM 2015; Van Cutsem E et al. Proc ESMO GI 2015; Elez E et al. Proc ESMO GI 2015

BRAFi + EGFRi in BRAF mut CRC

Heracles: trastuzumab + lapatinib (HER2+)

• 46/849 (5.4%) HER2+

(KRAS ex 2 wt)

• 24 patients included

(EGFR pre-treated)

• ORR: 34%

• DCR: 78%

• mTTP: 5.5 m (3.7-

7.8+ m)

Pat

ien

t #

12

10

16

baseline Week 54 - PR +

Pat

ien

t #

12

10

23

baseline Week 24 - PR +

Siena S et al. Lancet Oncol 2016

Dual binding of Ang-2 and VEGF-A using an engineered antibody: vanucizumab

anti-VEGF-A

= bevacizumab

Knobs into

holes

CH1–CL cross over

VEGF-A Ang2

anti-Ang-2

= LC06

Vanucizumab

1L mCRC

n=140

Bevacizumab +

mFOLFOX-6*

A2V +

mFOLFOX-6*

Bevacizumab

+ 5-FU/LV

R

A2V + 5-

FU/LV

Induction

(up to 8 cycles)

Maintenance

(until PD)

McCAVE trial design

Open-label safety run-in with n=6–18 patients

Primary endpoint: estimated HR for PFS

Tumour

Lymph node

Blood vessel

Therapies that might affect the cancer-immunity cycle

Chen & Mellman. 2013

Release of cancer cell antigens Chemotherapy

Radiation therapy Targeted therapy

1

Cancer antigen presentation Vaccines

IFN-α GM-CSF

Anti-CD40 (agonist) TLR agonist

2

Priming and activation Anti-PD1 Anti-PDL1

Anti-CTLA-4 Anti-CD137 (agonist) Anti-OX40 (agonist) Anti-CD27 (agonist)

IL-2 IL-12

3

Infiltration of T cells into tumours Anti-VEGF

5

Recognition of cancer cells by T cells

CARs

6

Killing of cancer cells Anti-PDL1 Anti-PD1

IDO inhibitors

7

Trafficking of T cells to tumours

4

Pembrolizumab (anti-PD1) in mismatch repair-deficient/-proficient CRC: phase II

Le DT et al. NEJM 2015

Target Therapy Phase Trial Design Trial ID

Anti-PDL1

Atezolizumab (engineered IgG1,

no ADCC)

I Solid tumours NCT01375842

Ib Solid tumours (+ bevacizumab ± FOLFOX) NCT01633970

II mCRC (+ bevacizumab + fluoropyrimidine) NCT02291289

MEDI4736 (modified IgG1,

no ADCC) II mCRC NCT02227667

Anti-PD1

Nivolumab (IgG4)

I/II mCRC (± ipilimumab) (CheckMate 142) NCT02060188

I/II Solid tumours (+INCB24360) NCT02327078

I/II Solid tumours (+ chemotherapy) NCT02423954

I/II Solid tumours (+ varlilumab) NCT02335918

Pembrolizumab (IgG4, humanised)

I Solid tumours (+ aflibercept) NCT02298959

I/II GI cancers (+mFOLFOX6) NCT02268825

I/II WT mCRC (+ cetuximab) NCT02318901

II mCRC (+ radiotherapy or ablation) NCT02437071

II mCRC (+ chemotherapy) NCT02375672

II mCRC (+ azacitidine) NCT02260440

II MSI-positive/-negative CRC NCT01876511

Examples of anti-PDL1/PD1 therapies currently under investigation in CRC*

*Recruiting studies Clinicaltrials.gov

• Very high potency with EC50 values in the fM to pM range

• Serial killing of tumour cells, activity at low effector–to-target (E:T) ratio

• T cell engagement independent of specificity, activation and differentiation status

• Mode of action may overcome most escape mechanisms that cancer cells employ to evade T cell recognition

T cell bispecific antibodies (TCBs) Highly potent molecules leading to T cell-mediated killing of tumour cells

Bacac, et al. ITOC 2014

T cell

Tumour cell

Cytotoxic

granules

Mode of action

CD3 T cell

engagement

Silent Fc for

half-life extension

High avidity binding

to tumor antigen

Format

• Simultaneous binding to tumour and T cells results in

– T cell engagement, activation and killing of tumour cells by delivery of cytotoxic granules

– T cell proliferation (expansion) at site of activation

Strong anti-tumour activity in xenograft model CEA TCB reduces tumour volume and increases the frequency of intra-tumour T cells

Bacac, et al. ITOC 2014

Tumour volume Frequency of intratumour T cells

Histology of tumours

CEA TCB

CRC subtypes

CMS1 - MSI – Immune 14%

CMS2 – Canonical 37% CMS3 – Metabolic 13%

CMS4–Mesenchymal 23%

Immune checkpoint inhibitors Immune regulators BRAF-driven strategies

Guinney J, Dienstmann R et al. Nat Med 2015

How predictive the CMS subtypes are?


Heinz- Josef Lenz

USC Center for Molecular Pathways and Drug Discovery

USC/Norris Comprehensive Cancer Center

Los Angeles, California


Cancer Back Luck or

Bad Luck and Genetics?

Heinz-Josef Lenz

Professor of Medicine and Preventive Medicine

Associate Director, Clinical Research

J Terrence Lanni Chair in Cancer Research

Co-Director, USC Center for Molecular Pathways and

Drug Discovery

USC/Norris Comprehensive Cancer Center

Los Angeles, California

Fig. 2 Stochastic (replicative) factors versus environmental and inherited factors: R-tumor versus D-tumor classification. The adjusted ERS (aERS) is indicated next to the name of each

cancer type.

Cristian Tomasetti, and Bert Vogelstein Science 2015;347:78-81

Published by AAAS

Cancer risk versus lifetime number of stem cell divisions (lscd) on a log-log scale. Each colour corresponds to a different anatomical site, The length of each coloured line represents the variance in risk due to the lifetime number of stem cell divisions for that anatomical region or tissue type, and the spacing between coloured lines represents the variation due to tissue type. Based on figures 5A and 6A of Noble et al. (2015

Stems Cells vs Mutation Rate

Proportion of drivers and passengers

Ester Borras et al. Cancer Prev Res 2016;9:417-427

Height associated with Cancer Risk in Men and Women

Stefan et al Lancet 2016

Height associated with Cancer Risk

Giannandrea et al Front. Endocrinol., 26 November 2012

If Most Cancer are Just Bad Luck

• Diagnosing early cancer by screening

• Can we quantitate bad luck by identifying surrogates in normal tissue/blood

• Can we reverse bad luck by treating the chances of more bad luck


Nadir Arber

The Tel-Aviv Sourasky Medical Center

Tel Aviv, Israel

View of a Gastroenterologist

My Financial Disclosures: Bayer Takeda GI View

Micromedic Bio View

Check-Cap Bio-Explorer

Nucleix

….cancer is definitely not a good luck…

Cancer is not Bad Luck!

Nadir Arber

The Integrated Cancer Prevention Center

Tel Aviv Medical Center

Heredity!

Environment!

Bad Luck?

It's probably a combination

of all

Variation in Cancer Risk Among Tissues can be

Explained by the Number of Stem Cell Divisions C. Tomasetti and B. Vogelstein

Science 347, 78–81; 2015

• Random mutations arising during DNA replication in normal

noncancerous stem cells = Bad Luck Cancer

• The stochastic effects of DNA replication is the major contributor

to cancer in humans

Would you like to buy

ice?

Two-thirds of Adult Cancer Incidence Across Tissues can be

Explained Primarily by “Bad Luck” Cancers due to bad luck plus

environmental and inherited factors Cancers due to bad luck

Head osteosarcoma

Glioblastoma

Medulloblastoma

Thyroid medullary

Lung (non-smokers) Esophageal

Arms osteosarcoma

Hepatocellular

Pancreas ductal

Pancreas Islet Duodenum

Gallbladder

Small intestine

Pelvis osteosarcoma Ovarian germ cells

Testicular germ cell

Osteosarcoma

Legs Osteosarcoma

Chronic lymphocytic leukemia

Acute myeloid leukemia

Head and Neck

Melanoma

Lung (smokers)

HCV hepatocellular

Colorectal

Adenocarcinoma

FAP colorectal

Lynch colorectal

Basal cell carcinoma

HPV-16 head&neck

Thyroid follicular

World cancer report 2014

Estimated Number of Cancers (all ages, both sexes)

Total- 14,090, 149

Other (4,969,278)

Bladder (429,793)

Esophagus (455,784) Cervix uteri (527,624)

Liver (782,451)

Lung (1,824,701)

Breast (1,676,633)

Colorectum (1,360,602)

Prostate (1,111,689)

Stomach (951,594)

The Role of Genes and Environment in the Development of Cancer

A. The percentage contribution of genetic and environmental factors to cancer. The contribution of genetic factors and environmental factors towards cancer risk is 5–10% and 90–95% respectively

B. Family risk ratios for selected cancers. The numbers represent familial risk ratios, defined as the risk to a given type of relative of an affected individual divided by the population prevalence

C. Percentage contribution of each environmental factor. The percentages represented here indicate the attributable-fraction of cancer deaths due to the specified environmental risk factor

Cancer Risk Factors

• Age,

• Gender,

• Smoking,

• Alcohol,

• Ethnicity,

• Geographic location,

• Genetics,

• Overweight,

• Life style,

• Exposure to carcinogens (chemical, physical and infectious agents)

• Age at menarche, parity, hormonal status, lactation

o Emphasis on very rare cancers (e.g. osteosarcoma,

medulloblastoma) that make only a small contribution to

the total cancer burden

o No data on breast and prostate cancers

o The report excludes (lack of data) common cancers for

which incidence differs substantially between populations

and over time (stomach, cervix)

o The study focuses exclusively on the USA

The Pitfalls of the Stem Cell Theory:

o People who migrate from regions of lower to higher cancer

risk soon develop cancer at rates consistent with their new

homes, and vice versa

o Some individuals leading a healthy lifestyle and/or using

chemoprevention will still be diagnosed with cancer but on

the average they will have less cancer

o Mutations during cell division rarely build up to the point of

producing cancer, even in tissues with relatively high rates of

cell division. For some cancers 7 mutations are needed

o Many populations have experienced a doubling of cancer

incidence over past decades

• Because genetics and environment cannot explain the huge

differences in cancer rates between different populations,

individuals and organs, it does not mean that they play a

minor role in carcinogenesis

• Strong correlation at the population level, is blind to the

existence of strong differences in group

susceptibilities (environmental and hereditary) to cancer

• If most cancers were due to random errors during stem cell

replication, then one would expect to see the same cancers

with increasing probability over time. Yet, the incidence of

childhood and adolescent cancers is quite different from

those of adults

o Most humans have equal numbers of stem cells: Yet,

o the incidence for many cancers varies widely (Esophageal

cancer is common in East Africa but rare in West Africa)

o variation over time

Dramatic decrease in gastric cancer world-wide

4-fold increase in CRC in Japan (last 2 decades)

• Intrinsic stem-cell division rates and extrinsic factors are not

entirely independent

• Environmental exposures do affect stem-cell division

rates

“The mathematical model was intrinsically insensitive to

changes in 'Bad Luck' or environment? .…it depends on

the cancer… and by reanalyzed the data, it was

concluded that about 90% of cancers have environmental

contributions…”

Stem cell divisions mandate the mutation rate, but NOT

cancer incidence

Song Wu, et al (Nature. 2015;529:4347)

Debunking Mathematically the Logical Fallacy that Cancer Risk is

Just “Bad Luck” Sornette and M. Favre*

D. Sornette and M. Favre (2015), Debunking mathematically the logical fallacy that cancer risk is just “bad luck”, EPJ Nonlinear Biomedical Physics, 3 :10,

It is a very simple mathematical calculations but for you I will make it

even simpler

• Small bowel mucosa represent 90% of the GI surface

area

• Colonic tissue undergoes four times more stem cell

divisions than SB tissue in humans

• SB/GIT cancer rate = 90%:10%x4=36%

• SB cancer account for only 1% of all GI tumors

• There must be more than just stem cell division

A Simple Math Calculation

Hypermethylation

MSI

CMS1 CMS2

Chromosomal instability

Serrated adenoma Tubular adenoma

Histopathology 2013, 62, 367-386. DOI: 10.1111/his. 12055

“Concluding that ‘bad luck’ is the major cause of cancer would be misleading and may detract from efforts to identify the causes of the disease and effectively prevent it” IARC Director Dr Christopher Wild

“It is clear that the number of cell divisions increases

the risk of mutation and cancer, but the majority of

cancers, worldwide, are strongly related to

environmental and lifestyle exposures. Society should

emphasis on early detection and prevention. Half of

all cancer cases worldwide are preventable”

Cancer is not a Bad Luck

Moscow – 2005: Euro Final

This is Bad Lack….

It is all a matter of perspective I am a Man U fan……for me it was a

very fortunate luck

• All cancers are caused by a combination

of:

–environment

–heredity

–bad luck

Diapositiva 1 - eso values in the fM to pM range •Serial killing of tumour cells, activity at low...

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