The HER Superfamily of Receptors and Related

Pathways in Gastroesophageal Cancers

Jordan Berlin, M.D.

Ingram Associate Professor of Medicine

Vanderbilt-Ingram Cancer Center

AKA: ToGA: The starting point

Disclosures

For this talk

– Advisory board and research support: Roche/Genentech

– Advisory Board and research support: Amgen

– Research Support: Lilly/Imclone

I have a lot of relationships, but no others relevant

ToGA trial design

HER2-positiveadvanced GC

(n=584)

5-FU or capecitabinea + cisplatin(n=290)

R

aChosen at investigator’s discretion GEJ, gastroesophageal junction

5-FU or capecitabinea + cisplatin

+ trastuzumab(n=294) Stratification factors

− advanced vs metastatic − GC vs GEJ− measurable vs non-measurable− ECOG PS 0-1 vs 2− capecitabine vs 5-FU

Phase III, randomized, open-label, international, multicenter study

1Bang et al; Abstract 4556, ASCO 2009

3807 patients screened1

810 HER2-positive (22.1%)

Rationale for trastuzumab in HER2-positive GC

There is no universal standard treatment, but– fluoropyrimidine (capecitabine / 5-FU) / platinum

(cisplatin / oxaliplatin)-based chemotherapy considered as reference regimen

• epirubicin or docetaxel sometimes added• biologicals are under investigation

Unmet need for new treatment options in advanced gastric cancer

Some gastric adenocarcinomas are HER2 positive Trastuzumab is effective against HER2-overexpressing

GC cell lines in vitro and in vivo

Fujimoto-Ouchi et al 2007; Gravalos & Jimeno 2008

Primary end point: OS

Time (months)

294290

277266

246223

209185

173143

147117

11390

9064

7147

5632

4324

3016

2114

137

126

65

40

10

00

No. at risk

11.1 13.8

0.00.10.20.30.40.50.60.70.80.91.0

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36

Event

FC + TFC

Events

167182

HR

0.74

95% CI

0.60, 0.91

p value

0.0046

MedianOS

13.811.1

T, trastuzumab

Secondary end point: PFS

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34

Event

294290

258238

201182

14199

9562

6033

4117

287

215

133

93

82

62

61

61

40

20

00

5.5 6.7

No. at risk

0.00.10.20.30.40.50.60.70.80.91.0

Time (months)

FC + TFC

Events

226235

HR

0.71

95% CI

0.59, 0.85

p value

0.0002

MedianPFS

6.75.5

113

OS in IHC2+/FISH+ or IHC3+ (exploratory analysis)

1.0

0.8

0.6

0.4

0.2

0.0

363432302826242220181614121086420

Time (months)

11.8 16.0

FC + T

FC

Events

120136

HR

0.65

95% CI

0.51, 0.83

MedianOS

16.011.8

Event

0.1

0.3

0.5

0.7

0.9

218 198

40

53

124

2011

228 218

196 170

170 141

142 112

12296

10075

8453

6539

5128

10

00

No. at risk

3920

2813

CALGB 80403 / ECOG E1206: Schema

Stratification:ECOG 0-1 vs 2ADC vs. SCC

ARM A: (ECF + cetuximab); 1 cycle = 21 days

Cetuximab 400 250mg/m2 IV, weeklyEpirubicin 50 mg/m2 IV, day 1Cisplatin 60mg/m2 IV, day 1Fluorouracil 200mg/m2/day, days 1-21

ARM B: (IC + cetuximab); 1 cycle = 21 days

Cetuximab 400 250mg/m2 IV, weeklyCisplatin 30 mg/m2 IV, days 1 and 8Irinotecan 65 mg/m2 IV, days 1 and 8

ARM C: (FOLFOX + cetuximab); 1 cycle = 14 days

Cetuximab 400 250mg/m2 IV, weeklyOxaliplatin 85 mg/m2 IV, day 1Leucovorin 400 mg/m2, day 1Fluorouracil 400 mg/m2 IV bolus, day 1Fluorouracil 2400 mg/m2 IV over 46hrs (days 1-2)

Enzinger PC and Burtness B, et al. ASCO 2010

• Cetuximab: chimerized monoclonal antibody - EGFR (oropharyngeal cancer , NSCLC, and colorectal cancer)

• EGFR expression – 3/4 of ADC and SCC 1-5

• EGFR expression correlates with prognosis in esophagogastric ADC and SCC 1-5

• KRAS mutations occur in approx. 2% of esophageal cancers6

CALGB 80403 / ECOG E1206: Background

1-5 Mukaida. Cancer 1991; Itakura. Cancer 1994; Yacoub. Mod Pathol 1997; Torzewski. Anticancer Res 1997; Koyama. J Cancer Res Clin Oncol 1999; 6 Lea. Carcinogenesis 2007

ECF-C IC-C FOLFOX-C Total N=67 N=71 N=72 N=210

Mos 95% c.i. Mos 95% c.i. Mos 95% c.i. Mos 95% c.i. OS median 11.5 (8.1,12.5) 8.9 (6.2,13.1) 12.4 (8.8,13.9) 11.0 (8.8,12.3) # dead 51 52 51 154 PFS median 5.9 (4.5,8.3) 5.0 (3.9,6.0) 6.7 (5.5,7.4) 5.8 (5.1,6.8) # dead/pd 57 64 63 184 TTF median 5.5 (3.9,7.2) 4.5 (3.6,5.6) 6.7 (4.8,7.2) 5.5 (4.5,5.9)

#dead/pd/ off forAE 58 66 64 188

CALGB 80403/ECOG 1206: Survival

So what happened? ToGA worked and there is no real signal

from ECOG/CALGB trial

– Is this a failure of the “science?”

– Does HER 2 overexpression mean something different than HER 1 (EGFR)?

Data from breast, colon and lung cancer don’t suggest they are the same. Her 2 is a driver, but HER 1 is not in most cases

– Am I reading too much into CALGB/ECOG trial?

Authors of REAL3 and EXPAND hope so

Next Steps

TOGA identified that for a small subset of GE patients, trastuzamab helps improve survival but not miraculously

We need to identify further targets, optimization of identified targets and how to combine targeted therapies

How do we select?

HER family HER 1, 2, 4 transmembrane protein with

extracellular ligand binding domains and intracellular tyrosine kinase domain

HER 3 membrane bound with ligand binding domain (neuregulin, for example) but no kinase domain

– HER 3 heterodimerization may be key effector of HER2 activation

Activation by ligand results in homo- or heter-dimerizaiton and activation of PI3k and/or MAP K pathways

www.cellsignal.com/reference/pathway/ErbB_HER.html

www.cellsignal.com/reference/pathway/ErbB_HER.html

Underlying etiology

Find a driver of cell growth such as Her 2

One place to start is with the start of the cancer

Helicobacter Pylori– Increasing evidence that CagA + H. Pylori

stimulates malignant transformation– Some data exists on methods by which H.

Pylori stimulates this process

H Pylori

CAG A + H. Pylori binds to CD 74 receptor

– This results in IL-8 production (other cytokines) through NF-kappa B activation

– Induces CD 74 expression

– MEK inhibition may decrease the IL-8 production

Beswick EJ, et al J Immunol 2005;175;171-176Sekiguchi H, et al Biosci Biotechnol Biochem. 2010;74:1018-24

What can CAG-A induce?

It has been associated with activation of – EGFR (red because it appears to come

up with all the below)MAP kinase

AKT

ERK

PI3 kinase

Nagy TA, et al J Infect Dis 2009; 199:641–5Tabassam FH, et al Cellular Micro 2009:11, 70–82Chen Y-C, et al W J Gastro 2006; 12: 5972-5977

Underlying etiology as a target

Based on this evidence, EGFR should be a key target

– Also, Ras mutations are rare (<2%)

H. Pylori is not the only etiology of gastric cancer and not the cause of esophageal cancer

– Likely more important in distal gastric cancer– ECOG/CALGB studied esophagus and GE junction

Is it possible EGFR inhibition is more relevant in H. Pylori associated disease?

Is it possible that if EGFR is an inciting event, by the time we find the cancer, it is too late to block EGFR and make a difference?

Target differences by location: Not a new concept

HER 2 overexpression by location

– GE junction: 24-32%

– Corpus/antrum: 10-18%

HER 2 overexpression by histology

– Diffuse: 2-7%

– Intestinal: 16-34%

Is it possible that activation of a kinase may have different effects in different cells?

Colon cancer and EGFR as an example:– EGFR inhibitors don’t work (and in some settings

may harm) if Ras is mutatedIs PI3 kinase irrelevant in this setting?Or is it that unbalanced stimulation of PI3K by EGFR

results in harm in some cases when Ras is also activated?

To butcher Orwell,– “All pathways are equally relevant but some are

more equally relevant than others”, but which pathway is more equally relevant varies

MET activation results in activation of beta catenin pathwasy, PI3kinase pathway, STAT pathway and NOTCH pathwayMET appears to prolong Ras induction and Ras mediates MET activation

Every protein and its brother stimulates PI3K and MAPkinase pathways

C-MET I get to talk about it because they said I should talk

about all the proteins that interact with the HER family and C-MET does

Overexpressed in both gastric and esophageal cancers

– In esophageal cancer, expression increases in the pathway from metaplasia to adenocarcinoma

Can confer poor prognosis Preclinical studies show some cell lines

susceptible to MET inhibition C-MET can activate HER signaling through cross-

talk with HER family receptorsAnderson MR, et al Clin Cancer Res 2006;12:5936-5943 Arkenau H-T J Cancer Res Clin Oncol 2009;135:855–866

C-MET inhibitionC-Met inhibition has worked in

both gastric and esophageal cell lines– C-Met inhibition in esophageal cancer

In at least one cell line (Flo-1), MET increased PI3K/AKT and PI3K inhibition mimicked the effects of MET inhibition

That means that in Flo-1 cells, PI 3 kinase mediates MET activity

Annotating the cell lines may help us better understand what works and when

Watson GA, et al Neoplasia . 2006, 8:949 – 955

C-MET Inhibition

Clinically, minimal data, but not impressive– Can the lab tell us why? One example:

Took C-MET addicted cell lines and made them resistant to inhibition

– Displayed C-MET gene amplification

– Progressively developed Wt Kras amplification

– Cells became resistant to C-Met inhibition but dependent on K-Ras

– Too bad we can’t inhibit Ras

Cepero V, et al Cancer Res 2010; 70; 7580–90.

Further complexity Src: a non-receptor tyrosine kinase

– Commonly activated in gastric cancer– Induces activation of ERK and AKT– In cell lines sensitive to Src inhibition, this results in

decreased phosphorylation of ERK and AKT and increased apoptosis

In a study of 16 gastric cancer cell lines, 14 with activated Src

– Dasatinib inhibited Src activated cell lines as long as MET was not activated

– MET inhibition inhibited Src resistant cell lines with Src activation

– Neither method inhibited cell lines without Src activation

Okamoto W, et al. Mol Cancer Ther 2010;9:1188-1197

HER and MET

Studies have now shown that activation of HER family receptors confers resistance to MET inhibition

– Activation of EGFR by providing ligand or by adding mutated, constitutively activated EGFR led to AKT and MAPK activation and resistance to MET inhibition

– HER 2/HER3 upregulation conferred secondary resistance to CMET inhibition

– MET independent activation of HER family receptors reactivates MAPK and AKT phosphorylation

Bachleitner-Hoffman, et al Mol Cancer Ther 2008;7:3499–508Corso et al. Molecular Cancer 2010, 9:121

What can we learn from the limited C-MET story I’ve shown?

C-Met, like HER family has complex interactions with other signaling pathways

Upregulation of C-MET doesn’t always mean C-MET sensitivity

There are many mechanisms of resistance to C-MET

– Mutations in another pathway, – Upregulation of pathway proteins– Gene overexpression – Stimulation by ligand of another, complimentary (HER)

pathway In turn, C-MET activation can confer resistance to

inhibition of another pathway

Bringing it Back to HER

Why is trastuzamab good, but no miracle?

– Cross-talk between pathways is clearly important

– Genetic variations in the interacting pathways occur (eg AKT, PTEN, PI3kinase)

– Mutations in interacting pathways occur (Ras 2%, AKT 2%, PI3K 16%)

– All of the above can confer either primary or secondary resistance

Hildebrandt MAT, et al J Clin Oncol 2009;27:857-871.Barbi et al. Journal of Experimental & Clinical Cancer Research 2010, 29:32Soung YH, et al Oncology 2006;70:285–289

HER is at the top of the cascade, why not go to the bottom?

www.cellsignal.com/reference/pathway/ErbB_HER.html

www.cellsignal.com/reference/pathway/ErbB_HER.html

The bottom (or close to it)

Yoon, et al showed that different co-mutations led to differential responsiveness of lung cancer lines to MEK inhibition

In HER activated, MET resistant cell lines, MAPK and AKT inhibition were both required to inhibit cell growth

PI3K mutations confer resistance to MEK inhibitors, especially in presence of Ras mutation

And the list goes on

Yoon Y-K, et al MOLECULAR CARCINOGENESIS 49:353–362 (2010)

Bachleitner-Hoffman, et al Mol Cancer Ther 2008;7:3499–508Wee S, et al Cancer Res 2009;69:4286-4293

Conclusions I Cancer is “driven” to grow

The HER superfamily and its downstream effectors are drivers of many gastroesophageal cancers (and other cancers too)

Targeting this superfamily will likely yield results

But to truly win, we have to get smarter

Gettin’ Smarter Characterize our cell lines Determine which variables predict for

sensitivity to which inhibitors Test our patients for these variables

and treat based on these variables Determine mechanisms of resistance

so we are ready to adjust It’s time to split, not lump

– Challenge will be in trial design