Targeted therapy in Cancer
S. AgelakiDept of Medical Oncology
University Hospital of Iraklion
Introduction
The concept of targeted Tx was originally described by the bacteriologist Paul Ehrlich in the late 1800s
He used the term ‘magic bullet’ to describe a chemical with the ability to specifically targetmicroorganisms
Classic anti-cancer Tx targets the loss of cell-cycle control and the genetic instability of cancer cells
Cancer cells suffer from genetic instability that results from loss of chromosome maintenance or DNA repair mechanisms
Traditional anticancer Tx mostly rely on agents (drugs and ionizing radiation) that damage DNA and the machinery that maintains chromosomal integrity
Such treatments preferentially kill certain kinds of cancer cells because these mutants have a diminished ability to survive the damage
Cytotoxicagents
Cell cycle and Cell cycle and cytotoxic cytotoxic opportunitiesopportunities
CELLCELLDIFFERENTIATIONDIFFERENTIATION
CELLCELLLIFE CYCLELIFE CYCLE
TIMETIME
CELLCELLDIVISIONDIVISION
GG22 PERIODPERIOD
(CHROMOSOME REPLICATION) (CHROMOSOME REPLICATION) SS--PHASEPHASE
GG11 PERIODPERIOD
Effects of Effects of RadiationRadiation TxTx on normal and cancer cellson normal and cancer cells
Cancer cells lack an ability to arrest the cell cycle and make the necessaryrepairs. Unfortunately, the same genetic defects may render some cancer cellsresistant to radiation treatment, as they may also be less prone at activatingapoptosis in the face of DNA damage.
CANCER CELLSCANCER CELLS NORMAL CELLSNORMAL CELLS
Loss of contact inhibitionIncrease in growth factor secretionIncrease in oncogene expressionLoss of tumor suppressor genesNeovascularization
Oncogene expression is rare
Intermittent or coordinatedgrowth factor secretion
Presence of tumor suppressor genes
Frequentmitoses
Nucleus
Blood vessel
Abnormalheterogeneous cells
Normalcell
Fewmitoses
Cancer cells are different from normalcells
The malignant genotypeActivated oncogenes
Down-regulated suppressor genes
Signal transduction/cell-cycle/apoptosis genes
These alterations result in– ↑ proliferation– ↑ angiogenesis– ↓ adhesion– ↑ invasion– ↓ apoptosis – ↑ survival
What is a “targeted” therapy?
Targeted therapy is a therapy directed at the molecular or physiologic concomitants of malignancy
This implies a DRUG acting on a MOLECULAR TARGET(necessary but not sufficient)
What makes a “drug”?
Nature Rev. Drug Discovery 4:161, 2005
What makes a MOLECULAR TARGET an IDEAL therapeutic target?
the MOLECULAR TARGET should be present in the majority of patients
the MOLECULAR TARGET should have a causative link with tumorigenesis
the MOLECULAR TARGET should have an essential function in tumor but not in normal cells
the MOLECULAR TARGET should be measurable in the clinic
measurement of the MOLECULAR TARGET should have a predictive impact on the therapy
Specific molecular targetsSignal transduction
Inhibition of tyrosine kinases (HER1, HER2, bcr-abl)Targeting of mutant oncogenes (Ras)Targeting of proteins that mediate the function of oncogenes (Raf)
Tumor supressor genes (p53, p16)
Cell cycle control (cyclin-dependent kinases)
Apoptosis regulators (Bcl-2)
Angiogenesis and metastasis (VEGF, VEGFR2, MMPs)
Targeted Cancer TxAdvantages
Selective: targets tumor cellsFewer systemic toxicities predictedDosing can be adjusted to biologicactivity of the drug May improve quality of lifeduring treatmentDramatic responses in select subsetsof patients
Approaches to block target activity
Gene therapy
Nucleus
Immuneeffectorcell
BispecificAbs
Anti-ligandMAbs
Ligand-toxinconjugates scFv-toxin
conjugates
Anti-receptorMAbs
ATP and substratecompetitors
Ribozymes and antisense oligonucleotides
Estrogen Receptor as a Success StoryRecurrence and Mortality Reductions from Tamoxifen
Early Breast Cancer Trialists’ Collaborative GroupLancet 351: 1451, 1998
Targeted therapies Some newer success stories
Bcr-Abl, c-kit
Her-2
The Gold Standard of Molecular Therapeutics: Imatinib
Tyrosine Kinases (TKs)Tyrosine phosphorylation is tightly regulated and modulates the activity of target proteins
Tyrosine kinases (TKs) are a family of enzymes thatcatalyses the phosphorylation of select tyrosine residuesin target proteins
The human genome contains ~90 TK and 43 TK-likegenes
Many proteins regulated by tyrosine phosphorylation areinvolved in cell cycle progression and/or survival
Classification of TKs
Receptor tyrosine kinases: EGFR, PDGFR, FGFR, IR Non-receptor tyrosine kinases: SRC, ABL, FAK and Janus kinase
TKs as targets in cancer therapy
Many proto-oncogenes encode protein tyrosine kinases
Protein tyrosine kinases can be hyperactivated by mutation, overexpression, structural rearrangements, and/or loss of normal regulatory constraints
TKs were implicated as oncogenes more than 25 yrs ago inretroviruses - induced animal tumors
The development of TKs inhibitors as an anticancer strategyhas been accelerated by the success of imatinib mesylate inCML
Activation of TKs
Cell membrane
Ligand binding
Activated receptor
Y Y
YYP
P
P
P
Proliferation Migration
Tumour growthand metastases
Survival
Signal transduction
Tyrosine kinase receptor
Tyrosine kinase domain
Strategies to target TKs in cancertherapy
Small molecule inhibitors occupie the TK ATP-binding site
High sequence homology in the ATP binding pocket of the kinasessuggested possible lack of selectivity
The development of STI-571 provided the proof- of-principle for the valueof TK inhibitors in cancer therapy
Cellular Selectivity of Imatinib (STI571, GLIVEC) IC50mM
Kinases Inhibited Kinases Not Inhibited
v-ABL 0.1–0.3 Flt-3 >10p210Bcr-Abl 0.25 c-Fms, v-Fms >10p185Bcr-Abl 0.25 EGF receptor >100TEL-Abl 0.35 c-erbB2 >100PDGF-R 0.1 Insulin receptor >100TEL-PDGF-R 0.15 IGF-I receptor >100c-Kit 0.1 v-Src >10
JAK-2 >100
Druker BJ et al. Nat Med. 1996;2:561-566.
Imatinib: GIST GISTs
– Infrequent tumour (~0.2% of all GI tumours)– Occur primarily in stomach (60%–70%) and small intestine with
liver metastases and peritoneal seeding – ~10%–30% malignant
Therapeutic Options– Surgery was the only effective modality– 0%–5% respond to chemotherapy with short time to failure
Outcomes– For unresectable/metastatic disease
• Estimated time to progression <2 months• Estimated survival <1 year
Imatinib: GIST Origin is linked to interstitial cells of Cajal (ICC)
Gastrointestinal pacemaker cells
Evolving definition of disease Historically difficult to distinguish from soft-tissue sarcomas
Now defined immunohistochemically c-Kit gain-of-function mutation Present in 95% of patientsc-Kit (CD117) is the causative abnormality of GISTs
KIT Mutations and GIST
•In frame mutation exon 11 (52%)•Point mutation exon 13 (1%)
•In frame duplication exon 9 (3%)
TK1
TK2
JM
THE ROLE OF KIT
Transmembrane receptor with tyrosine kinase activity
Stem cell factor is the ligand
Ligand-receptor binding leads to:
Kit dimerization, TK phosphorylation/activation signal transduction to the nucleus cell proliferation
Imatinib Mesylate in GIST:Rapid Response in Primary Tumor
CT
18FDG-PET
Pre-imatinib mesylate 4 weeks of imatinib mesylate
Courtesy of Dr. G.D. Demetri and Dr. A.D. Van den Abbeele.
Imatinib Mesylate in GIST:Rapid Response in Liver Metastasis
CT
18FDG-PET
Pre-imatinib mesylate 4 weeks of imatinib mesylate
Courtesy of Dr. G.D. Demetri and Dr. A.D. Van den Abbeele.
Randomized Phase II Trial of STI571 in Metastatic GIST
400 mg/day
Treat Dailyx 24
months
REGISTER
SCREEN
Progression
600 mg/day
STI - 571 in GIST: Pivotal Trial—Conclusions
147 patients randomized to 400 or 600 mg/d83% of patients showed a clinical benefit– 67% PR/CR– 16% stable disease (SD)
Median time to progression (TTP) was 84 weeksMedian overall survival (OS) has not been reached at median follow-up of 34 monthsImatinib mesylate has an acceptable safety profile in patients with GIST
Blanke et al. ASCO 2004 Gastrointestinal Cancers Symposium. Abstract 2.
Imatinib Mesylate in GIST Pivotal Trial — Overall Survival
100
Imatinib mesylate (pooled 400-mg +600-mg)
SWOG S8616/S9627
80
Surv
ival
(%)
60
40
20
00 1 2 3 4 5
Years after registration
• With a median follow-up of 34 months, median survival has not been reached
Blanke et al. ASCO 2004 Gastrointestinal Cancers Symposium. Abstract 2.
HER2 receptor signal transduction
Signaltransductionto nucleus
Nucleus
Binding site
Tyrosinekinase activity
Cytoplasm
Plasmamembrane
Growth factor
Gene activation CELLDIVISION
Indicators of increased HER2 production
1 = - gene copy number2 = - mRNA transcription3 = - cell surface receptor protein expression4 = - release of receptor extracellular domain
Normal Amplification/overexpression
Cytoplasm
HER2 receptorprotein
Cytoplasmicmembrane
Nucleus
HER2 DNA
HER2mRNA
1
2
3
4
Herceptin: Humanized Anti-HER2 Antibody
• Targets HER2 oncoprotein• High affinity (Kd = 0.1 nM)
and specificity• 95% human, 5% murine
- Decrease potential forimmunogenicity
- Increase potential forrecruiting immune-effector mechanisms
Scientific Rationale
Recruitment of immune cells to the tumor resulting in antibody-dependent cellular
cytotoxicity (ADCC)
First-line Herceptin®
monotherapy(H0650g)
Vogel C, et al. J Clin Oncol 2002;20:719–26
Patien
ts (%)
RR Clinical benefit rate
38
26
48
35
48
34
0
10
20
30
40
50
60 All IHC 3+ FISH+
First-line single-agent Herceptin®:
survival in all enrolled patients
1.0
0.8
0.6
0.4
0.2
00 5 10 15 20 25 30 35 40 45 50
Prob
ability
of
surv
ival
Time (months)
Median survival: 24.4 months
Vogel C, et al. J Clin Oncol 2002;20:719–26
Adding Herceptin®
to chemotherapy improves survivalSummary of results of pivotal combination therapy trial
(H0648g)
H + AC(n=143)
AC(n=138)
H + P(n=92)
P(n=96)
H + CT(n=235)
CT(n=234)
Median TTP (months) All3+
7.8* 8.1*
6.16.0
6.9*7.1*
3.03.0
7.4* 7.8*
4.64.6
Response rate (%) 56*60
4242
41*49
1717
50*56
3231
Median duration ofresponse (months)
9.1* 9.3
6.75.9
10.5* 10.9
4.54.6
9.1* 10.0
6.15.6
Median TTF (months) 7.2* 7.1
5.65.1
5.8* 6.7
2.92.8
6.9* 7.0
4.54.4
Survival (months) 26.8 31*
21.421
22.125
18.418
25.1*29*
20.320
*p<0.05All: n=4693+: n=349 Slamon D et al. N Engl J Med 2001;344;783–92
Overall survival in IHC 3+ patients
1.0
0.8
0.6
0.4
0.2
00 5 10 15 20 25 30 35 40 45 50
18 25
Time (months)
Herceptin® + paclitaxelPaclitaxel alone*
40%
Herceptin® + CT CT alone*p<0.05
1.0
0.8
0.6
0.4
0.2
020 29
0 5 10 15 20 25 30 35 40 45 50Time (months)
Prob
abili
ty o
f sur
viva
l
45%
Slamon D et al. N Engl J Med 2001;344;783–92
Prob
abili
ty o
f sur
viva
l
*~70% of patients receiving CT alonecrossed over to receive Herceptin®
upon progression
The addition of Herceptin®
to chemotherapyis associated with improved quality of life (QoL)
p=0.003 p=0.03p=0.07
p=0.08
QoL domains
No.
of p
atie
nts
impr
ovin
g (%
)
Herceptin® + CT CT alone
Global QoL Physical Role Social Emotional Fatigue0
10
20
30
40
50
60
Osoba D et al. Proc ASCO 2001;20:28a (Abstract 109)
Who benefits from Herceptin®
therapy?
Clinical trials have taught us that accurate assessment of HER2 status is essential to ensure that eligible patients are correctly identified for Herceptin
®therapy
Patients with IHC 3+ or FISH-positive disease achieve the greatest benefit with Herceptin
®
HERA TrialPrimary management
Surgery, (neo-) adjuvant chemoTx, RTx
RANDOMIZATION
No Herceptin®
Herceptin®
q 3 weeks x 1 year
Herceptin®
q 3 weeks x 2 years
LOADING: 8mg/kg MAINTENANCE: 6mg/kg every 3 weeks
Disease-free survival (ITT)Median FU 2 yrs
Patients(%)
100
Months from randomisation12 36
1 year trastuzumab
Observation
0 186 24 30
Events HR 95% CI p value
0.64 0.54, 0.76 <0.0001
3-yearDFS
80.674.3
218321
6.3%80
60
40
20
0
1703 1591 1434 1127 742 383 1401698 1535 1330 984 639
No. at risk 334 127
1703 1627 1498 1190 794 407 146
100
80
60
40
20
0
Patients(%)
Months from randomisation
Observation
Overall survival (ITT)
1 year trastuzumab
Events HR 95% CI p value
0.66 0.47, 0.91 0.0115
3-yearOS
92.489.7
12 360 186 24 30
5990
Median FU 2 yrs
2.7%
No. at risk 1698 1608 1453 1097 711 366 139
Targeted TxChallenges (I)
Biomarkers
Resistance
Side Effects
Why focus on biomarkers ?
Biomarkers have the potential to:
Improve the probability that the drugs which enter phase 2 aresuccessful by Designing phase 1 and 2 studies to include pharmacodynamic biomarkers
(making sure the drug hits the target)
Improve the probability that the drugs which enter phase 3 aresuccessful by Designing Phase 2 studies using biomarkers which are correlated with
clinical outcome Designing phase 2 and 3 studies which enroll higher-risk patients
(identified by prognostic biomarkers) likely to have a greater treatmentrespond (predictive biomarkers)
Improve our ability to identify toxicity signals (biomarkers whichare correlated with SAEs)
Her 2 Over-expression and The Development ofHerceptin : The Importance of a Predictive
Biomarker
Simulation of Phase III Trastuzumab Data
Phase III Trialin which 100% of patientsshow a treatment effect
Trial in which 50% of patientsshow a treatment effect
Trial in which 25% of patientsshow a treatment effect
Mark Pegram, UCLA
GIST: KIT Mutation Location Predicts Imatinib Mesylate Responsiveness
100PD/NE80
% o
f tot
al SD60 PR
40
200
KIT Exon 11(n=85)
KIT Exon 9(n=23)
No mutation(n=9)
KIT mutations are predictive of response to imatinib mesylateExon 11 mutants respond best
Blanke et al. ASCO 2004 Gastrointestinal Cancers Symposium. Abstract 2.
GIST: KIT Mutations Predict Overall Survival
0 100 200 300 400 500 600 700 800Days
KIT exon 11 (n=85)
KIT exon 9 (n=23)
No kinase mutation (n=9)
0102030405060708090
100
Ove
rall
surv
ival
(%)
Heinrich et al. J Clin Oncol. 2003;21:4342. Reprinted with permission from the American Society of Clinical Oncology.
Mutational hotspots in the Abl kinase domain conferringresistance to Imatinib
Src/Abl inhibitors include Dasatinib and others.100-300x more effective than Imatinib in blocking Bcr-Abl
tyrosine kinase autophosphorylationEffects extend to point mutations of Bcr-AblBind to active form of Abl (Imatinib binds inactive form)
Curr. Pharm. Biotechnology 7:371, 2006Leukemia 20:1542, 2006
Drugs Are NOT Safe…They Offer Benefit forRisk
Cardiotoxicity of Imatinib
Cardiac Dysfunction with Herceptin
H + AC(n=143)
AC(n=135)
H + P(n=91)
P(n=95)
Single agent(n=338)
% cardiac dysfunction 27.0 8.0 13.0 1.0 4.0NYHA III/IV (initial) 16.0 3.0 2.0 1.0 3.0NYHA III/IV (post-treatment) 6.0 0.7 0 0 1.5
% death due tocardiac dysfunction 0.7 0.7 0 0 0.9
Slamon D et al. N Engl J Med 2001;344:783–92Seidman et al. J Clin Oncol 2002; 20:1215-1221
Sunitinib related toxicitySkin toxicity
Sunitinib related toxicityHair discoloration
Success stories…. BUT….
EGFR
Angiogenesis
The Epidermal Growth Factor ReceptorThe Epidermal Growth Factor ReceptorTGFTGF-- ααAmphiregulinAmphiregulinEGFEGFBetacellulinBetacellulinEpiregulinEpiregulinHBHB--EGF..EGF..
LigandsLigands::
NeuregulinNeuregulinEpiregulinEpiregulinHBHB--EGFEGFBetacellulinBetacellulin
NoNoKnownKnownligands ligands NeuregulinNeuregulin
erberbB1 B1 HER1HER1EGFREGFR
erberbB2B2HER2HER2neuneu
erberbB3 B3 HER3HER3
No TKNo TKActivityActivity
erberbB4 B4 HER4HER4
Receptors:Receptors:
622 622 aaaa
22 22 aaaa
542 542 aaaa
CysteineCysteine--richrichDomainDomain
TyrosineTyrosine--KinaseKinaseDomainDomain
NeoplasticNeoplastic proliferationproliferation
EGFR expression in solid EGFR expression in solid tumorstumors
HeadHead & Neck& Neck(SCC)(SCC)
CRCCRC
NSCLCNSCLC
EGFR EGFR expressionexpression
HeadHead and Neck (SCC)and Neck (SCC) 90 90 -- 100100 %%
NSCLCNSCLC 40 40 -- 80 %80 %ProstateProstate cancercancer 40 40 -- 80 %80 %BreastBreast cancercancer 14 14 -- 91 %91 %
ColorectalColorectal cancercancer (25 ) (25 ) -- 80 %80 %
GastricGastric cancercancer 33 33 -- 74 %74 %
OvarianOvarian cancercancer 35 35 -- 70 %70 %
PancreaticPancreatic cancercancer 30 30 -- 50 %50 %
Invasive growthMetastasesAdvanced stageChemo-Resistance
EGFR expression – clinical significance
Neal (1985)PoorBladder
Sainsbury (1985)PoorBreast
Volm (1998)Veale (1993)Ohsaki (2000)Pavelic (1993)Increased
Decreased OSPoorPoor
NSCLC
Dong (1998)Yamanaka (1993)Decreased OS
PoorPancreatic
Grandis (1998)Maurizi (1996)
Decreased DFSDecreased OS
PoorHead and Neck
Mayer (1993)Hemming (1992)
IncreasedPoorColorectal
ReferencesRisk ofmetastases
SurvivalPrognosisTumor type
DFS = disease-free survival; OS = overall survival; NSCLC = non-small-cell lung cancer
© PW Dec 2002
MTTCMTTCMTTC
2-63
Gefitinib(IressaTM, ZD 1839)
Erlotinib (TarcevaTM, OSI-774)
ZD 1839OSI-774
N
HN
NOO
OO
HN
N
N
O
O
Cl
F
NO
EGFR Selective Small MoleculesTyrosine Kinase Inhibitors
EGFR tyrosine kinase activity requires ATPZD1839 and OSI-774 compete for ATP bindingReversible inhibitorsOrally bioavailable small molecules
EGFR TKIs in NSCLC
Based on promising data from phase I studies gefitinib and erlotinib were preferentially studied in NSCLC
Gefitinib 500 mg
Gefitinib 500 mg
Regimen PR Median Survival 1-yr survival
Gefitinib 250 mg
Gefitinib 250 mg19%18% 7.6 mo IDEAL1
12%9%
8.1 mo
6.1 mo6.0 mo
IDEAL 2
Trial
--------
29%
6%Best supportive care 0% 4.6 mo Shepherd Docetaxel 7.0 mo
19%29%
24%
Perez-SolerErlotinib 9.0 mo14% 40%
Combination therapy — Randomized phase III trials of EGFR TKIs
Four phase III trials trials with > 4000 NSCLC pts failed to show survival benefit when gefitinib or erlotinib were combined with standard CT
INTACT 1INTACT 2
TRIBUTE
The trials also failed to meet the secondary endpoints of RR and TTP
Erlotinib in Previously Treated NSCLCBR.21 Study Design
Erlotinib in Previously Treated NSCLCErlotinib in Previously Treated NSCLCBR.21 Study Design BR.21 Study Design
RANDOM I ZE
Erlotinib* 150mg daily
StratificationCentrePerformance status
0/1 vs 2/3Response to prior Rx(CR/PR vs SD vs PD)Prior regimens(1 vs 2)Prior platinum (yes vs no)
Placebo 150mg daily
*2:1randomisation
CR = complete response; PR = partial response; SD = stable disease; PD = progressive disease
BR.21: Οverall Survival
Tarceva (n=488)
Placebo (n=243)
Median survival (months) 6.7 4.7
1-year survival (%) 31 21
42.5% improvement in median survival
Surv
ival
dis
trib
utio
n fu
nctio
n
Survival time (months)
HR=0.73, p<0.001*
1.00
0.75
0.50
0.25
00 5 10 15 20 25 30
Tarceva
Placebo
Shepherd F, et al. N EnglJ Med 2005;353:123–32
*HR and p (log-rank test) adjusted for stratificationfactors at randomisation and HER1/EGFR status
EGFR inhibitors – Why are 1 in 10 like this?
Somatic Μutations in the Tyrosine-Kinase (TK) Domain of
HER1/EGFR
EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy
Paez JG, Janne PA, Lee JC, Tracy S, Greulich H, Gabriel S, Herman P, Kaye FJ, Lindeman N, Boggon TJ, Naoki K, Sasaki H, Fujii Y, Eck MJ, Sellers WR, Johnson BE, Meyerson M
Science, 29 April, 2004
Activating mutations in the epidermal growth factor receptor underlying responsiveness of non–small-cell lung cancer to gefitinib
Lynch TJ, Bell DW, Sordella R, Gurubhagavatula S, Okimoto RA, Brian BS, Brannigan W, Harris PL, Haserlat SM, Supko JG, Haluska FG, Louis DN, Christiani DC, Settleman J, Haber DA
New England Journal of Medicine, 20 May, 2004
EGFR mutations in NSCLC
Most common mutations (almost 90%)Exon 19 deletions (E746_A750)Missense mutations, exons 18 and 21 (L858R)
Challenges: EGFR in Lung Cancer
Phase III INTACT Trial
Phase II IDEAL Trial
J. Clin. Oncol. 23:8081, 2005
HER1/EGFR IHC
Scored positive if membranous staining (partial or complete) present in ≥10% of tumour cells
DAKO EGFR PharmaDxTM Kit
Disomy≤2 gene copies in >90% cells
Low Trisomy3 gene copies in >10% <40% cells
High Trisomy3 gene copies in ≥40% cells
Low Polysomy≥4 gene copies in >10% but <40% cells
High Polysomy≥4 gene copies in ≥40% cells
Gene AmplificationGene/chromosome ratio >2 or ≥15 gene copies in ≥10% cells
EGFR FISH Scoring Categories(Cappuzzo F, et al. J Natl Cancer Inst 2005;97:643–55)
The biology of EGFR mutant NSCLC Different kinetics of receptor dephosphorylation
Higher sensitivity to gefitinib inhibition
More potent stimulation of PI3K and STAT paths
Angiogenesis is required for solid tumor growth
1-2 mm3
The VEGF family are critical tumor-secreted angiogenic factors
Migration, permeability, DNA synthesis, survival
Lymphangiogenesis
– P– PP–
P–
– P– P
P–P–
– P– P
P–P–
VEGF-AVEGF-B
PlGF
VEGF receptor-1
VEGF-A
VEGF receptor-2
VEGF-CVEGF-D
VEGF receptor-3
Angiogenesis
Adapted from Ferrara N. Nat Med 2003;9:669–76
Avastin plus IFL (AVF2107g) as1st-line therapy of metastatic CRC
May receive Avastin beyond
disease progression
No Avastin beyond disease
progression
May receive Avastin beyond
disease progressionPreviously untreated
metastatic CRC(n=923)
IFL* + placebo(n=411)
IFL* + Avastin(5mg/kg, every
2 weeks)(n=402)
5-FU/LV† + Avastin(5mg/kg, every
2 weeks)(n=110)
Arm closed to enrolment
Hurwitz H, et al. N Engl J Med 2004;350:2335–42
• Primary endpoint: duration of survival*Bolus 5-FU/LV†Roswell Park regimen
Avastin plus IFL (AVF2107g): overall survival
Median survival (months)IFL + placebo: 15.6 (95% CI: 14.3–17.0) vsIFL + Avastin: 20.3 (95% CI: 18.5–24.2)HR=0.66 (95% CI: 0.54–0.81)p<0.001
1.0
0.8
0.6
0.4
0.2
00 10 20 30 40
Time (months)
IFL + Avastin
IFL + placebo
15.6 20.3
Prob
abili
ty o
f su
rviv
al
CI = confidence interval Hurwitz H, et al. N Engl J Med 2004;350:2335–42
Angiogenesis inhibitors
Are there any biomarkerscorrelated with clinical outcome?
Using Biomarkers/Surrogates which arecorrelated with clinical outcome
IFL/Placebo (n=412) RR=34.8%
IFL/Avastin (n=403)RR=44.8% p=0.004
1.0
0.8
0.6
0.4
0.2
00 10 20 30 40
Time (months)
IFL + Avastin
IFL + placebo
15.6 20.3
Prob
abili
ty o
f su
rviv
al
CI = confidence interval Hurwitz H, et al. N Engl J Med 2004;350:2335–42
Phase III MBC Trial With Avastin:Progression-free Survival
RR is not always a good biomarker though!
Cap/Placebo (n=230) RR=19.1%
Cap/Avastin (n=232)RR=30.2% p=0.006
DCE-MRI with Gadolinium: A Biomarker study for
PTK787 in Colorectal Cancer Patients
Morgan et al. JCO. 21:3955-64
Targeted therapiesChallenges (II)
Integration with other treatment regimens
Complexity in molecular targets
One specific target vs multiple targets
“Biological Effective Dose” rather than “Maximal Tolerated Dose”
Cell regulation: complex molecular interactions
WNT
Cell
ECM
Growth factors (e.g. EGF, amphiregulin TGFα)
Nuclear receptors(e.g. oestrogen)
Survival factors(e.g. IGF1)
Cytokines(e.g. ILs, IFNs)
Deathfactors
(e.g. FasL)
Anti-growth factors(e.g. TGFβ)
GPCR ligands
Frizzled Disheveled
GSK-3β
APC
Tubulin
TCF
Integrins
β-Cutenin β-Cutenin:TCFE-Cadherin
CdC42 PI3K Rac
Fak Cas CrkSrc
FynShc
NF1
RasRTK Grb2SOS Ral MEK MAPK MAPK
MEKK
PLC
PKC Mos MKKs JNKs
ELK
Myc:Max
Max:MaxFos
JUN
Abl
7-TMRCdC42 Rac Rho
G-Prol Ad Cycl PKA CREB
PKC NF-κB
NHR (e.g. ER)
NF-κB
P13K Akt Akka IKB
PTEN?
Stat 3.5
Stat 3.5
Stat 3.5
Bcl XL
Caspase 9
Cytochrome C
Jaks
Bad BidMitochondria
Bim, etc.Abnormalitysensor
Bcl 2
Cell Death(Apoptosis) Caspase 8
Fap
FADDBcl 2
Bax
ARF
p53
Mitochondria
MDM2
DNA damagesensorCell
Proliferation(cell cycle)
Changesin Gene
Expression
Cycl E:CDK2 p21
p27
E2Fs
Rb
p16
Cycl D:CDK+ p15 Smads
RTK
Cytokine R
Decoy R
Fas
SurfaceAg
TGFβR
HPVE7
Complexity
Analysis of 13,023 genes in 11 breast and 11 colorectal tumors
189 genes were significantly associated with the cancer process, affecting a wide range of cellularfunctions
An average of 11 mutant genes per tumor were cancer associated
Science 314: 268 - 274
One vs multiple targetsIn Defense of the “General” Molecular Target
Binding of Multiple Myeloma (MM)cells to bone marrow stromatriggers IL-6 release in aNF-kB dependent manner (1994)
Proteasome inhibitors inhibited NF-kB activationIn vivo inhibition of MM cells in SCID mice (1999)
Phase II trial of Bortezomib in refractory relapsed MM35% Response rates, Response duration of 14 monthsvs. 6-9 month expected survival
Approved 2003EJC Suppl. 2: 3-6, 2004
Other Targets of Proteasome Inhibitors
Nature Rev. Cancer 4: 349, 2004
Other Targets of Proteasome Inhibitors
Other “General” Molecular Targets
Histone deacetylase inhibitorsDNA methylation inhibitorsHsp90 inhibitors
How are tumor cells more sensitive to inhibition than normal cells?
Is there a single, dominant molecular pathway?Or is there partial inhibition of multiple pathways?
How do you follow this in a clinical trial?
Are multiple targets “better”?
Maximal tolerated vs biological doseRecommended phase II dose and primary reason for dose recommendation
Recommended phase II dose / Primary basis for recommendation No. of trials No. of agents
Not stated 6 6
Not recommended 2 1
RecommendedToxicity 35 19Pharmacokinetic data 11 7Other trial results (toxicity) 2 2Clinical activity* 1 1PBMC findings† 1 1Effect in tumor (target or response) 1 1Convenient dosing schedule 1 1
Total 60
Phase I trial design for solid tumor studies of targeted, non-cytotoxicAgents: Theory and practice. JNCI 96: 990, 2004
Targeted TxChallenges (III)
Consider Multiple Aspects of Tumor Progression— Cancer stem cells— Tumor dormancy— Micrometastatic disease
Consider additional steps in metastasis for therapeuticintervention
Normal stem cells:Extensive capacity for self renewal that allows maintenanceof the undifferentiated stem cell pool;Strict regulation of stem cell number;Abililty to undergo differentiation to reconstitute functional elements in the tissue
Cancer stem cell:A cancer cell that has the ability to self-renew giving rise to anothermalignant stem cells as well asundergo differentiation to give riseto phenotypically diverse nontumorigenic cancer cells
Curr. Opinion in Genetics & Development 14:43, 2004
Tumor Dormancy
B. Solitary tumor cell in liver d25
C-D. Solitary cells labeled withnanoparticles 11 w.
Cells labeled with flourescent nanospheres, which will be eliminated in 3 divisionsCells Ki-67 negativeCells can be harvested, grown in vitro, will form tumors upon re-injection
Cancer Res. 62:2162, 2002
Gross Metastases: Solitary Cells:
Breast Ca. Res. Trt. 2812-03: 1, 2003
What Steps In Metastasis Are Open for Therapeutic Intervention?
Future Cancer Treatment
20th century
Cytotoxic therapyRadiotherapy
Hormonal therapySurgery
21st century
Targeted therapy
Patient-specific therapy
Radiotherapy
Hormonal therapy Chemotherapy
Biologicaltherapies• Herceptin®
• IressaTM
• Glivec• ?
Tumour type
Disease stageTumor phenotype
Tumor genotype
Treatment
Target Discovery & ValidationAssay Development
High-Throughput Screens, Secondary and Tertiary Assays
Lead SelectionLead Optimization, Preclinical Efficacy
Preclinical Toxicity
Clinical Trial
0 1 2 3 4 5 6 7 8Years
Adapted from Nature, 2005
Drug development is getting and moreexpensive
Tufts Center for the study of Drug Development (CSDD)
Estimate of cost to develop a new drug (2003 study) –897 million in 2000 dollars
―Included in the cost are expenses of drug failuresand the impact that long development times haveon investment costs
―Estimates in prior studies was $802 million in 2001 and $231 million ($318 million in 2000 dollars) in1987
Driver for increasing costs thought to be clinical trialscosts
Declining success rates
How shall we achieve our goals towardstargeted Tx? (I)
Target identification…
The Achilles heelof cancer
How shall we achieve our goals towardstargeted Τx? (II)
Drugs that intervene in pathways mediating growth, deathmetastasis and resistance
Explore rational combinations More than limited preclinical experimentation Identification of biomarkers of efficacy
Molecularly based clinical trialsMolecular test for entryDevelop and validate biomarkers of activity
In conclusion…
Developing targeted therapyisn’t easy
The right thing for patients ismatching drugs with patients
that will benefit and not treatingthose that will not
Molecular biology should be incorporated into clinical trials
To this end
Tumor sample should be available for molecular analysis