towards personalized p immunotherapy of cancer
TRANSCRIPT
NCT Conference 2013
New Cancer Targets
Towards personalized pimmunotherapy of cancer
Hans-Georg Rammensee
Interfakultäres Institut für ZellbiologieAbteilung ImmunologieProf. Dr. Hans‐Georg Rammensee
Towards patient-specific tumor antigen selection for
i tivaccination.
Rammensee HG, Weinschenk T, Gouttefangeas C, Stevanović S.
I l R 188 164 76 2002Immunol Rev 188:164-76, 2002
1. MHC, peptides, and cancer
2. Our strategy to identify cancer associated peptides
3 Cli i l t di3. Clinical studies
4. Why mutated antigens should be the better targetsy g g
5. Problems
protein fragmentthis can be recognized by T cells
This is true for all
Antigen presentation
p g
= peptidThis is true for all proteins inside a cell, also for tumor Antigen presentation
by HLA moleculeassociated changes, including mutations
Antigen processingAntigen processing
Cancer cells differ from normal cellsfrom normal cellseg., in gene expression
This can be sensed by T cells - no matter which cellular compartment is affected by the changea ected by t e c a ge
3 classes of tumor antigens
Limited to few cancer entities
We know plenty of such antigens; immune responses tend to be weak but stronger immune responses may lead
This is our vision
but stronger immune responses may lead to autoimmunity
Isolation of Naturally Presented HLAIsolation of Naturally Presented HLA--LigandsLigandsIsolation of Naturally Presented HLAIsolation of Naturally Presented HLA LigandsLigands
07.07.2011Lab Meeting Daniel Kowalewski
Peptide preparationGeneral survey
Andy Weinzierl
y
• Protein A affinity chromatography i W6/32 tib dusing W6/32-antibody
• elution with citrate buffer, pH 3
Technological progress
HLA ligandome analysis, next generation
Daniel Kowalewski
D
Daniel Kowalewski
D
Technological advance: lt HPLCultraHPLC
Comparative HLA ligandome analysis
Off‐the‐shelf vaccines: Allele‐specific target identification (A*02)p g ( )
6000+ peptides exclusively identifiedin A*02+ tumor ligandomes
362 peptides identifiedin ≥ 50 % of A*02+ tumor ligandomestumor ligandomes
Department ofImmunology
OncologyHematologyImmunology
Rheumatology
Ligandomics in leukemia
Juliane Stickel
HLA ligand isolation
ells
g
igna
nt c
e
Purification Affinity Chromatography
sM
ali
Leukemia Patient
Cell lysate HLA antibody
id l i
PB
MC
s Acid elution Ultrafiltration 10 kDa
Isolated peptidesLC-MS/MS
Healthy donor
100
%
od_70521_28 1 (0.019) Sm (Mn, 2x3.00) TOF MSMS 497.93ES+ 9.45183.17
86.15
171.17
112 14
685.73
193.16
572.60
402.40211.19 367.33253.25
292.27270.31
310.28
385.38
515.53
440.48
458.53
498.54
555.54
516.55
573.62
628.69671.69
686.69
100
%
od_70521_28 1 (0.019) Sm (M n, 2x3.00) TO F MSM S 497.93ES+ 9.45183.17
86.15
171.17
112 14
685.73
193.16
572.60
402.40211.19 367.33253.25
292.27270.31
310.28
385.38
515.53
440.48
458.53
498.54
555.54
516.55
573.62
628.69671.69
686.69
Healthy donor
Peptide sequences & Source protein annotation50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950
m /z0
72.14
112.14
165.13
157.17
212.18
349.29
403.44574.63
625.65
654.65784.79687.77
688.76749.76 786.84
50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950m /z0
72.14
112.14
165.13
157.17
212.18
349.29
403.44574.63
625.65
654.65784.79687.77
688.76749.76 786.84
Overall comparison HLA Ligandome
HLA ligandome comparison CLLHLA ligandome comparison CLL
30 CLL Patient PBMC (n = 20) Healthy Volunteer PBMC (n = 31)
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1732 CLL exclusive proteins
Num 0
HLA ligandome comparison AML HLA ligandome comparison AML
5
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1545 AML exclusive proteins
AML20
Peptide-specific CD8-T-cells after “recall” stimulation in AML patientsAML20
P1• APLP2• DKGZ
HIV A*03 HIV A*03 P1 P1 P2 P2
DKGZ• FAF1• MITCH 2P2
KLF2• KLF2• MET7A• VCIP 1• WIPI 1
P4 P4 PBMCs PHAWIPI 1
HIV A*03 P2P1
FΥ+
2,4%
FΥ+
FΥ+
1,5%0%
INF
INF
INF
CD8+CD8+CD8+
Peptide-based Immunotherapy for LeukemiaLeukemia patient
n“
Exome sequencing Immunoprecipitation
rd th
erap
yon
indu
ctio
n
Mutations +Idiotype sequences
Epitope prediction
LC/MS analysisPeptide sequences,
Source protein annotation
Sta
ndar
„ rem
issi
o
Mutated HLA-Ligands + Idiotype HLA Ligands
SYFPEITHI Source protein annotation, Comparison to healthy tissue
Leukemia associated HLA ligands
Check for immunogenicity Check for immunogenicity
P ti t ifi i ti tidPatient specific vaccination peptides
Peptide vaccination = maintenance therapy
AcknowledgmentsAcknowledgmentsgg
• Prof. L. Kanz
• Prof H Salih
• Prof. H.-G. Rammensee
• Prof S StevanovicProf. H. Salih Prof. S. Stevanovic
• Juliane Stickel
• Daniel Kowalewski
• Heiko Schuster• Heiko Schuster
• Claudia Berlin
fortüne Programm
Clinical studies
immatics
Nature Medicine 2012Nature Medicine, 2012
Multipeptidvakzinierung beim Nierenzellkarzinom
28RCC phase 2 trial (IMA901-202) European multicenter study (10 countries, 50 centers)
Cyclophosphamide(300 mg/m2 assingle infusion)
Advanced RCC (N=68)-HLA-A*02-positive-1 previous line of therapy- Measurable lesion(s)
Documented progression
IMA901 plus GM-CSF (i.d.)
R
IMA901 plus GM CSF (i d )- Documented progression
Follow-up for OS17 vaccinations over 9 months
IMA901 plus GM-CSF (i.d.)
Stratification:1) First-line therapy: cytokine(s) vs TKI
2) Risk score: low vs intermediate [MSKCC]
Patients: mRCC patients following failure of first-line treatment (TKI and/or cytokines)
Treatment: Single infusion of cyclophosphamide as immunomodulator (300 mg/m2) prior to the 1st vaccination with IMA901 (413 g i d ) and GM CSF (75 g i d ) to the 1st vaccination with IMA901 (413 g i.d.) and GM-CSF (75g i.d.)
Endpoints: Primary EP was DCR after 6 months. Secondary EP included PFS, OS, and safety. Immunomonitoring for peptide-specific T-cells (ELISpot and MHC multimer) and Tregs
Conduct: 68 patients were randomized between 2007 and 2009 in 23 centers across 10 European countries
29
IMA901 Renal Cell Cancer Phase II Trial (N=68)Low-dose CY shows benefit only in immune respondersespo de s
Single-dose CY pre-treatment associated with survival benefit• Only in patients with vaccine-induced immune responses (HR=0.38, p=0.040)• Not in patients without immune responses, arguing against single agent effect of CY (HR=0.92,Not in patients without immune responses, arguing against single agent effect of CY (HR 0.92,
p=0.870)
Number of immune responses associated with survival
Walter, Weinschenk et al. (2012), Nature Medicine
p• (p=0.023)
IMA910 composition (colorectal carcinoma)13 tumor-associated peptides
30
TUMAP Name Function / Comments
HLA-A*02 TUMAPsC20-001 Chromosome 20 open reading
frame 42Poorly characterized, strong overexpression
CCN-001 Cyclin D1 Cell cycle regulation, frequently upregulated in many cancer types
CEA-004 Carcinoembryonic antigen-related cell adhesion molecule 5 (CEA)
Well-established TAA in CRC, cell adhesion, metastasis;
MET-001 Met proto-oncogene Proliferation, motility, adhesion, invasionMUC-001 Mucin 1 Well-established TAA in CRC, unmasking of epitope
d t lt d l l ti i tdue to altered glycosylation in tumorsNOX-001 NADPH oxidase 1 Strong overexpression, inhibition of apoptosisODC-001 Ornithine decarboxylase 1 Transformation, pro-angiogenic
PCN-001 Proliferating cell nuclear antigen Proliferation (DNA replication)g g ( p )TGFBI-001 Transforming growth factor beta-
inducedTissue remodelling, angiogenesis
TOP-001 Topoisomerase (DNA) II Proliferation (DNA replication)HLA-DR TUMAPsHLA-DR TUMAPsCEA-006 Carcinoembryonic antigen-related
cell adhesion molecule 5 (CEA)Well-established TAA in CRC, cell adhesion, metastasis
MMP-001 Matrix metallopeptidase 7 (matrilysin, uterine)
Tissue remodelling, inhibition of apoptosis(matrilysin, uterine)
TGFBI-004 Transforming growth factor beta-induced
Tissue remodelling, angiogenesis
IMA910 Colorectal Cancer Phase I/II StudyOverall survival of multi-TUMAP responders
31
100100
HR=0.590 083
HR=0.60p=0 12
OS vs. Class II responseOS vs. Class I response
50
75
surv
ival
%
50
75
l sur
viva
l %
p=0.083 p=0.12
0
250-1>=2
Ove
rall
0
25
0-1>=2
Ove
rall
N=46
N=35
N=25
N=46
100
0 100 200 300 400 500 600 700 800 900 1000 11000
0 100 200 300 400 500 600 700 800 900 1000 1100 12000
OS vs. Class I and Class II resp. Overall survival relative to Visit VC (Follow up 1). Per Protocol population
p-values from Log Rank statistics; HR from Cox prop. hazards model
days days
75
100
viva
l %
Trend for increased OS in multi-TUMAP responders• Trend for increased OS observed in Class I
HR=0.53p=0.088
25
50
OthersOve
rall
surv
oror Class II Multi-TUMAP responders
• Consistent finding: effect most pronounced in patients responding to multiple Class I
CN=47
0 100 200 300 400 500 600 700 800 900 100011000
>=2
Days
and Class II TUMAPsN=24
Active immunotherapy can work, even with self antigens
Lessons:
1 One should aim to have more multipeptide responders1. One should aim to have more multipeptide responders.
2 Single low dose of Cyclophosphamide appears to be2. Single low dose of Cyclophosphamide appears to be good.
3. Immunotherapy of this kind may have no impact on progression free survival but on overall survivalprogression free survival but on overall survival.
multipeptide vaccination, prostate carcinoma
Clinic for Urology, Dept. Immunology TübingenP tid b d i tiPeptide-based vaccination
of patients with prostate carcinomaDepartment of Urology
- design and schedule -• Phase I/II randomized study, start 2004• 40 HLA-A2+ patients with biochemical relapse after radical prostatectomy40 HLA A2 patients with biochemical relapse after radical prostatectomy• 14 peptides, 300 µg / peptide in 500 µl Montanide ISA51
for PSA measurement
for immunomonitoring( d l h t )
Blood samples
Peptide cocktails.c.
in Montanide
Peptide cocktails.c.
in Montanide
GM-CSF
Imiquimod
Hyperthermia(serum and lymphocytes)in Montanidein Montanide
Stabilized RNA
w/o
vaccination timepointsvaccination timepoints
monthly up to 15 vacc
1. 2. 3. 4. 5. 6. 7. 8. 9. 1week
1. 2. 3. 4. 5. 6. 7. 8. 9. 1week
up to 15 vacc.blood samplesblood samples
Peptides in the vaccination cocktail
Protein Position Sequenz HLA-Restriction
PSA 141-150 FLTPKKLQCV HLA-A*0201
146-154 KLQCVDLHV HLA-A*0201
154-163 VISNDVCAQV HLA-A*0201
PSCA 14-22 ALQPGTALL HLA-A*0201
105-113 AILALLPAL HLA-A*0201
PSMA 4-12 LLHETDSAV HLA-A*0201
711-719 ALFDIESKV HLA-A*0201
Survivin 95-104 ELTLGEFLKL HLA-A*0201
5-14 TLPPAWQPFL HLA-A*0201 5 14 TLPPAWQPFL HLA A 0201
TRP-P8 187-195 GLMKYIGEV HLA-A*0201
Prostein 31-39 CLAAGITYV HLA-A*0201
PSMA 459-473 NYTLRVDCTPLMYSL DRB1*0301,0401,0701,1101
Survivin 97-111 TLGEFLKLDRERAKN DR (Vorhersage)53
Influenza MP 58-66 GILGFVFTL HLA-A*0201
clinical observations
PSA time to next therapyPSA, time to next therapy
2 mo
No response
0,0,0,0
0time to next therapy (days after 1. vaccination)
390
Biometric analysis by Prof. K. Dietz
3 imi
Response
1,1,0,0
0time to next therapy (days after 1. vaccination)
>2908
5 mo
transient response
1,0,0,0
0
time to next therapy (days after 1. vaccination)
1117
100
120
60
80
100
NR%
R trans%
R f ll%
PSA values
0
20
40R full% values
%
imi RNA mo GM Hyp
time to next therapy or to end of observation
next therapy
no other therapy
Clinical parameters TTNT vs PSAClinical parameters TTNT vs PSA
3000
2000
3000er
apy
oron
1000
2000
o ne
xt th
ebs
erva
tio
0
1000
days
to ob
NR tR R0
Anti HLA class II T cellsAnti‐HLA class II T cells
2
I pep
tides
1
ed H
LA c
lass
I
0b o
f rec
ogni
ze
0Nb
V i 11 J 2013Version 11 June 2013Pro22 excluded, Pro3 and 4 n=1, Pro38 n.i., Pro34 n=1
Anti HLA class I T cellsAnti‐HLA class I T cells
5
6
7
gen-
deriv
ed
es
3
4
5
ed tu
mor
ant
igcl
ass
I pep
tide
0
1
2
b of
reco
gniz
eH
LA c
0Nb
V i 11 J 2013Version 11 June 2013Pro22 excluded, Pro7,24 n.i.
Immunogenicity of vaccine peptidesVersion 11 June 2013
Immunogenicity of vaccine peptides120
80
100
(ELI
SPO
T)
40
60
ing
patie
nts
0
20
% re
acti
Survivin (II) PSMA (II) Prostein PSMA 711 TRP‐P8 Survivin 95 PSA 146 PSCA 105 PSA 141 Survivin 5 PSCA 14 PSA 154 PSMA 432 25 23 22 14 9 9 7 4 0 0 0 034 35 34 34 34 34 34 34 34 34 34 34 3491,4 74,3 68 65 41 26 26 20 12 0 0 0 0
Conclusions
Multipeptide immunotherapy in prostate carcinoma patients
- is well tolerated- induces T cell responses in most patients- shows clinical benefit in a fraction of patients- gives best results with TLR7 ligands as adjuvants
some peptides are not immunogenic- some peptides are not immunogenic
Widenmeyer et al., Promiscuous survivin peptide induces robust CD4(+) T-cell responses in the majority of vaccinated cancer patients. Int J Cancer. 2011 Feyerabend et al., Novel multi-peptide vaccination in Hla-A2+ hormone sensitive patients with biochemical relapse of prostate cancer. Prostate. 2009
Why mutated antigens should be the better targetstargets
Limited to few cancer entities
We know plenty of such antigens; immune responses tend to be weak but stronger immune responses may lead
This is our vision
but stronger immune responses may lead to autoimmunity
1. T cells having left the thymus before tumor occurence should not be tolerant of tumoroccurence should not be tolerant of tumor
specific mutations N C i i d i d ll i h li l ll (BNote: Cancer testis antigens are expressed in medullary epithelial cells (Bruno
Kyewski et al.)
indeed, patients develop efficient T cell responses against mutations (Thomas Wölfel)
2. T cells specific for tumor specific mutations should not react to self peptidesshould not react to self peptides,
since those with crossreactivity to non-mutated peptides should have undergone
negative thymic selection.negative thymic selection.
i i d> no toxicity expected
RCC-Patient vaccination
Kidney Blood
Tumor NormalT-cellsOur new strategy for the
mRNA, DNA Peptides ImmunoA
gyidentification of tumor
Genome and t i t
MS
Assays
specific peptidestranscriptome
sequence HLA-Ligands SpecificRecognitionRecognition
candidate peptides for immunotherapy
CCC IND‐01, Genome sequencing and prediction of mutated HLA‐ligands by SYFPEITHI
KCNJ12 239E/K QLIKPRVTK, HLA-A*03, score 33
HGC6.3 128M/V VVTPTASSF, HLA-A*03, score 25
(Bold: anchor; underlined: auxillary anchor AA)
CCC IND‐01, Genome sequencing and prediction of mutated HLA‐ligands by SYFPEITHI
88 unique mutated peptide sequences in tumor tissue fitting to the patient's HLA Type:tissue fitting to the patient s HLA‐Type:
● 40 fit to HLA*A0340 fit to HLA A03
● 26 fit to HLA*B14
● 22 fit to HLA*B44
67 stem from SNV and 21 from InDel Mutations
Search for mutated peptides bySearch for mutated peptides by mass spectrometry
Bsp 1:Bsp. 1:
• In Gen: sphingosine‐1‐phosphate phosphatase (SGPP1)( )
• WT: MVGLSITF
M i MVGFSITF• Mutiert: MVGFSITF
• Position: 425
Nico Trautwein
MVGFSITF TumorMVGFSITF Tumor
y₇²⁺368.77
30
Extracted from: H:\121116_NT_HCC08_W_Tu_#1_msms6.RAW #2603 RT: 41.42 ITMS, CID, z=+2, Mono m/z=434.23788 Da, MH+=867.46849 Da, Match Tol.=0.8 Da
y₅⁺
y₆⁺637.54
y₇⁺736.32
20
Inte
nsity
[cou
nts]
b₄⁺401.08
y₂⁺267.39
580.94
200 300 400 500 600 700 800
m/z
0
10
MVGFSITF synpepMVGFSITF synpep
b₇⁺, y₇⁺‐H₂O719.30
800
900
Extracted from: H:\130128_nt_synpepmix_13012_13013_13017_1pmol_msms0.RAW #5532 RT: 77.34 ITMS, CID, z=+2, Mono m/z=442.73187 Da, MH+=884.45647 Da, Match Tol.=0.8 Da
y₄⁺ b₇⁺‐H₂O
y₂⁺267.14
y₁⁺166.20
b₆⁺618.32
300
400
500
600
700
Inte
nsity
[cou
nts]
a₇⁺‐H₂O673.16
y₆⁺638.58
y₆²⁺319.27
b₆²⁺‐H₂O300.21
a₆⁺‐H₂O572.25
y₂⁺‐H₂O249.10
b₃⁺304.14
b₅⁺505.22
y₄⁺‐H₂O449.30
b₇²⁺, y₇²⁺‐H₂O360.13
a₇²⁺346.25
a₄⁺390.29
a₂⁺219.10
b₄⁺418.20
b₆⁺‐H₂O600.31
y₄467.26 701.32
200 300 400 500 600 700 800 900
m/z
0
100
200
Bsp 2:Bsp. 2:
• Gen: Glutamate receptor, ionotropic (GRIN1)
• WT: FYRIPVLGLWT: FYRIPVLGL
• Mutiert: FYCIPVLGL
• Position: 115
FYCIPVLGL TumorFYCIPVLGL Tumor
b₈²⁺447.34
150
Extracted from: H:\121123_NT_HCC08_W_Tu_20%_195min_IncludeHCC08_5sDynExcl_#1_msms3.RAW #4711 RT: 70.29 ITMS, CID, z=+2, Mono m/z=512.78009 Da, MH+=1024.55290 Da, Match Tol.=0.8 Da
b ⁺
100
Inte
nsity
[cou
nts]
y₈⁺876.77
y₅²⁺, a₄²⁺250.11
b₆²⁺362.11 b₆⁺
722.92
y₈²⁺439.03
b₂⁺311.14
b₈⁺893.42
200 300 400 500 600 700 800 900 1000
m/z
0
50
FYCIPVLGL synpepFYCIPVLGL synpep
b₇⁺
b₄⁺527.15
40
Extracted from: D:\Nico\HCC\HCC8 komplett gemessen\Final\Synpep\130110_NT_SynPeps_HCC08_120490_120491_1pmol_msms1.RAW #3427 RT: 84.69 ITMS, CID, z=+2, Mono m/z=513.27893 Da, MH+=1025.55058 Da, Match Tol.=0.5 Da
b₈⁺894.44
b₆⁺723.43
b₃⁺414.22
b₇837.18
20
30
Inte
nsity
[cou
nts]
200 300 400 500 600 700 800 900 1000
m/z
0
10
RCC792 Tumor W6/32 Rep#1/ GVPIMLVY (B*15, A*03) RNF19B%NM_001127361@A429V
Daniel Kowalewski
RCC792 Tumor W6/32 Rep#1/ GVPIMLVY (B*15, A*03) RNF19B%NM_001127361@A429V
726.519171+b
250
Extracted from: E:\RCC792 Exhaustion & Spectral Counting\Tumor W\120608_ARDK_RCC792_Tumor_W_10%_1sDynExl_Rep#1_msms1.RAW #3522 RT: 46.38 ITMS, CID, z=+2, Mono m/z=454.25336 Da, MH+=907.49944 Da, Match Tol.=0.8 Da
281.250221+y
566.5985314 2938
62+b
418 3171254 208131+b
354.80437*2+b
363.527572+b
182.047611+y
627.184361+b
50
100
150
200
Inte
nsity
[cou
nts]
543.6866314.2938 418.3171254.2081
200 300 400 500 600 700 800 900
m/z
0
50
Sequence: GVPIMLVYM5‐Oxidation (15.99492 Da)Charge: +2, Monoisotopic m/z: 454.25336 Da (+1.82 mmu/+4.01 ppm), MH+: 907.49944 Da, RT: 46.38 min,
Identified with: Mascot (v1.15); IonScore:26, Exp Value:2.1E‐002, Matched Ions: 4/74Fragment Match Tolerance: 0.8 Da
Protein References (2): gnl|58|do rcc792 cegat long|RNF19B%NM 153341@A430V|‐ gnl|58|do:rcc792_cegat_long|RNF19B%NM_153341@A430V|
‐ gnl|59|do:rcc792_cegat_long|RNF19B%NM_001127361@A429V|
RCC792 Tumor W6/32 Rep#1/ GVPIMLVY (B*15, A*03)
726.519171+b
250
Extracted from: E:\RCC792 Exhaustion & Spectral Counting\Tumor W\120608_ARDK_RCC792_Tumor_W_10%_1sDynExl_Rep#1_msms1.RAW #3522 RT: 46.38 ITMS, CID, z=+2, Mono m/z=454.25336 Da, MH+=907.49944 Da, Match Tol.=0.8 Da Tumor Sample
281.250221+y 354.8043
7*2+b
72+b1
1+y627.1843
61+b
100
150
200In
tens
ity [c
ount
s]
566.5985
543.6866314.293862+b
418.3171254.208131+b 363.5275
7b182.0476
1y
200 300 400 500 600 700 800 900
m/z
0
50
727.548871+b
12
14
16
Extracted from: F:\120711_DK_SynPep_120224_IVAC792B15_labeled_5pmol_msms2.RAW #5702 RT: 139.79 ITMS, CID, z=+2, Mono m/z=454.74988 Da, MH+=908.49248 Da, Match Tol.=0.8 Da SynPep (Val7‐
15N labeled, 5 pmol
51+b182 0665
11+y 216.3578 627.3995
61+b269.2565 322.2579 420.0762396.0079
31+y355.3776
7*2+b
4
6
8
10
12
Inte
nsity
[cou
nts]
513.93555b
663.6210498.9489182.0665
200 300 400 500 600 700 800 900
m/z
0
2
Zoom‐In
354.80437*2+b
2+b182 047611+y
60
70
Extracted from: E:\RCC792 Exhaustion & Spectral Counting\Tumor W\120608_ARDK_RCC792_Tumor_W_10%_1sDynExl_Rep#1_msms1.RAW #3522 RT: 46.38 ITMS, CID, z=+2, Mono m/z=454.25336 Da, MH+=907.49944 Da, Match Tol.=0.8 Da Tumor Sample
246 3437 382.5796 408.2029 427.0581281.250221+y 336.3707
165.14271*1+y 314.2938
62+b 418.3171254.2081
31+b
363.527572+b182.0476
20
30
40
50
Inte
nsity
[cou
nts]
246.3437 382.5796
200 300 400 500m/z
0
10
Extracted from: F:\120713 DK SynPep 120224 IVAC792B15 labeled 10pmol msms1 RAW #6699 RT: 139 61
182.137511+y
80
100
ts]
Extracted from: F:\120713_DK_SynPep_120224_IVAC792B15_labeled_10pmol_msms1.RAW #6699 RT: 139.61 ITMS, CID, z=+2, Mono m/z=454.74976 Da, MH+=908.49224 Da, Match Tol.=0.8 Da
227.0332 410.9032136.0168 272.256242+y
313.992662+b
286.2734 350.41144*1+b
376.91113o1+y
395.284931+y165.0696
1*1+y 364.3462
72+b
20
40
60
Inte
nsity
[cou
n
SynPep (Val7‐15N labeled, 5 pmol
200 300 400 500m/z
0
New: Two step strategy for individualized p gyimmunotherapy:
1st step, as fast as possible (eg., right after surgery): vaccination with off the shelf peptides according to HLA-expression
2nd step, after tumor mutation analysis: vaccination with mutated peptidesmutated peptides
Our first example: RCC 792 (HLA-A2,A3,B15,B27)p ( )
A2 Nr. Sequenz Quelle HLA Note 51005 STAPPVHNV MUC-1 A*02 RCC ligand
51004 SVASTITGV ADFP 1 A*02 RCC li d
RCC 792, Two step individualized vaccination
51004 SVASTITGV ADFP-1 A*02 RCC ligand
51007 YVDPVITSI MET-1 A*02 RCC ligand
51001 LAALPHSCL RGS-2 A*02 RCC ligand
50060 FLGENISNFL APOL 1 A*02 RCC ligandHLA-A2 cocktail for RCC50060 FLGENISNFL APOL-1 A 02 RCC ligand
51003 ALADGVQKV APOL-2 A*02 RCC ligand
51006 ALFDGDPHL KIAA0367-1 A*02 RCC ligand
51002 SVFAGVVGV GUCY1A31 A*02 RCC ligand
RCC
g
50061 LLYPTEITV ITGA3-1 A*02 RCC ligand
51009 LLGATCMFV CCND1-1 A*02 RCC ligand
51008 FLPSDFFPSV HBV-1 A*02 pos
Vaccination started April 2012, Med. Klinik II
Vaccination started April 2012, Med. Klinik II
50076 GILGFVFTL IMP-1 A*02 pos
50089 NPPSMVAAGSVVAAV 2CCND1-1 DR helper
50091 HSKIIIIKKGHAKDSQ 2IBP3-1 DR helper
Klinik IIKlinik II
51018 SQDDIKGIQKLYGKRS 2MMP7-1 DR helper
50097 EIHVVHLSTAFARVDEALGR 2G250-1 DR helper
HLA-A3 cocktail for RCC
Mutation analysis of RCC792
#gene transcript allele ref_pep ref_score mut_pep mut_score binder mutationZNF799 NM_001080821 B_2705_9 CGKAFIDFY 11 CRKAFIDFY 21 True G454RC2orf28 NM_080592 A_0301_9 TQCPGSVQN 12 TLCPGSVQN 22 True Q92LC2orf28 NM 001170795 A 0301 9 TQCPGSVQN 12 TLCPGSVQN 22 True Q37L_ _ _SNX27 NM_030918 A_0201_9 SAVLPGGAA 12 SAVLPGGAV 18 True A90VFAM55B NM_182495 A_0301_9 KNINDCLER 14 KIINDCLER 22 True N351ISAMM50 NM_015380 A_0201_9 IVLRLGNIA 14 IILRLGNIA 18 True V431IZNF799 NM_001080821 B_2705_9 KCGKAFIDF 15 KRGKAFIDF 25 True C453RC2orf28 NM 080592 B 1501 9 ALPEICTQC 15 ALPEICTLC 14 True Q92LC2orf28 NM_080592 B_1501_9 ALPEICTQC 15 ALPEICTLC 14 True Q92LC2orf28 NM_001170795 B_1501_9 ALPEICTQC 15 ALPEICTLC 14 True Q37LC2orf28 NM_080592 A_0201_9 LALPEICTQ 16 LALPEICTL 26 True Q92LC2orf28 NM_001170795 A_0201_9 LALPEICTQ 16 LALPEICTL 26 True Q37LC2orf28 NM_080592 A_0201_9 QCPGSVQNL 16 LCPGSVQNL 18 True Q92LC2orf28 NM_001170795 A_0201_9 QCPGSVQNL 16 LCPGSVQNL 18 True Q37LJPH2 NM_020433 A_0201_9 SVGSQRSRV 16 SVGGQRSRV 18 True S241GZNF799 NM_001080821 B_2705_9 KPYKCKCGK 17 KPYKCKCRK 19 True G454RSAMM50 NM_015380 B_2705_9 YGAGIVLRL 17 YGAGIILRL 19 True V431IPLA2G3 NM 015715 B 2705 9 VALGGSPAL 18 VALGGSPSL 19 True A23SPLA2G3 NM_015715 B_2705_9 VALGGSPAL 18 VALGGSPSL 19 True A23SCALHM2 NM_015916 A_0201_9 QLFGWLLIG 18 QLFEWLLIG 18 True G188EAP2A2 NM_012305 A_0201_9 NLVKVGGYI 18 NLVKVGDYI 18 True G500DAP2A2 NM_012305 A_0201_9 LVKVGGYIL 18 LVKVGDYIL 18 True G500DFLNA NM_001456 A_0201_9 ARRLTVSSL 18 ARCLTVSSL 18 True R2326CFLNA NM 001110556 A 0201 9 ARRLTVSSL 18 ARCLTVSSL 18 T R2334CFLNA NM_001110556 A_0201_9 ARRLTVSSL 18 ARCLTVSSL 18 True R2334CTLR8 NM_138636 A_0201_9 YTLTDKYNL 19 YTLTDKYKL 21 True N604KSHH NM_000193 B_2705_9 RLLLTAAHL 19 RMLLTAAHL 19 True L264MOR4K15 NM_001005486 A_0201_9 TLRNKEVKA 19 MLRNKEVKA 19 True T312MKIAA1211 NM 020722 A 0201 9 SAAKHKLAV 20 SAANHKLAV 20 True K158N_ _ _SETD2 NM_014159 A_0201_9 KELDSLSKV 20 NELDSLSKV 19 True K650NSAMM50 NM_015380 A_0201_9 GIVLRLGNI 21 GIILRLGNI 23 True V431ISAMM50 NM_015380 A_0301_9 VLRLGNIAR 21 ILRLGNIAR 23 True V431ISHH NM_000193 B_2705_9 TREPRERLL 21 TREPRERML 21 True L264MSAMM50 NM 015380 A 0201 9 YGAGIVLRL 21 YGAGIILRL 21 True V431I
IND
Nr Sequenz Quelle Position HLA NoteNr. Sequenz Quelle Position HLA Note121148 AQNSRIQQL ANGL4 111-119 A*02:01/B*15 ligand of 792
121172 GVPIMLVY RN19B 424-431 B*15 mutation
121164 RLDNSAANH KIA 1211 151-159 A*03:01 mutation
121150 ARCLTVSSL FLNA 2332-2340 B*27 mutation
Vaccination started Sept. 2012, Med. Klinik II (off the shelf peptides
Vaccination started Sept. 2012, Med. Klinik II (off the shelf peptides ( p pcontinued)
( p pcontinued)
RCC792: T-Zellmonitoring after 12day stimulation (16.01.13) with IND-peptide cocktailIFN- Elispot 250.000 cells/well
10% DMSO121150ARCLTVSSL
121172GVPIMLVY
121197RLDNSAANH
121148AQNSRIQQL
PHA
02.07.12
11.10.12
28.12.12
120470ARRLTVSSL
121290GVPIMLAY
120471RLDNSAAKH
02.07.12
11.10.12
02 07 2012 8 weeks before 1 V with IND‐Cocktail02.07.2012 8 weeks before 1.V with IND‐Cocktail11.10.2012 8 weeks after 1.V mit IND‐Cocktail (5V IND Cocktail)28.12.2012 4 months after 1.V mit IND‐Cocktail (8V IND‐Cocktail)
Karoline Laske
RCC 792 Two stepRCC 792, Two step individualized vaccination
1. Mutated peptides could not be identified by mass spectrometry
2. Patient RCC 792 appeared to be nonresponder against all class I peptides tried
But we still try, and we will try hardery, y
Interfakultäres Institut für ZellbiologieAbteilung ImmunologieProf. Dr. Hans‐Georg Rammensee
Collaboration
B b S h ib l b d R /St i l bBob Schreiber lab and Rammensee/Stevanovic lab
Heiko Schuster
Courtesy Bob Schreiber
Expansion and IFNγ treatment ofd42mt1 progressor cell line T3
1) Expansion to 500 Mio cells1) Expansion to 500 Mio cells2) IFNγ treatment to increaseMHC expression
MCA Sarcoma cell line d42mt1 ‐T3(R913L‐Spectrin‐β2 negative(R913L Spectrin β2 negative= “progressor clone”)
Isolation of H2Kb presented peptidesand subsequent LC‐MS analysis
H2Kb Affinity chromatography(specific antibody Y3)
Lysis with detergent Acidic elution and
• In total 224 different
Lysis with detergent Acidic elution andultrafiltration LC‐MS
o a d e eH2Kb presentedpeptides identified(FDR < 0 05)(FDR < 0.05)
• Identification ofmutated tumorrejection antigenLama4 VGFNFRTL
First time identification and successful validation of a mutated MHC ligandvalidation of a mutated MHC ligand
VGFNFRTLmLama4(G1254V)
V lid i i hValidation with an isotope labeledsynthetic peptideVGFNFRTLVGFNFRTL (13C6, 15N1)
Problem:
Patient individualized peptides have to be produced according to GMP conditions, like all other drugs.
GMP center for individualized substancesBau: Finanziert durch MWK und UKTBetrieb: Anfinanziert durch MWK und Med. Fak.Betrieb: Anfinanziert durch MWK und Med. Fak.
Erteilung des Zertifikats für Wi k t ff tidh t ll 7 Mä 2012Wirkstoffpeptidherstellung 7. März 2012
Antrag auf Arzneimittelherstellung aus diesenAntrag auf Arzneimittelherstellung aus diesen Wirkstoffen Mai 2012
Dritter Mängelbeseitigungsbericht geht am 19.7. 2013 ans Regierungspräsidium2013 ans Regierungspräsidium
Inspektion der (neuen) GMP-Räume am 23. und p ( )24. 9. 2013.
Problem:
What will the regulatory authorities say to an individualized study design?
Levels of personalizationConcept by CIMT
81
(A) (B) (C)
G).
Patient
sear
ch G
roup
(RR
G
? ? ? ?Tumor
MT)
Reg
ulat
ory
Res
passive personalization
active personalization
StratificationThera-nostic m
mun
othe
rapy
(CIM
(„AP“)nostic
ciat
ion
forC
ance
rIm
DrugProduct(s) S
lide
byA
ssoc
ConfidentialConfidential
Invariant DP Variant DPs Variant DPs
THE REGULATORY LANDSCAPE FOR ACTIVELY PERSONALIZED CANCER
IMMUNOTHERAPIESIMMUNOTHERAPIES
Cedrik M. Britten*1,2, Harpreet Singh-Jasuja*3, Bruno Flamion4, Axel Hoos5, Christoph Huber6, Karl-
Josef Kallen7, Samir N. Khleif8, Sebastian Kreiter1, Michaela Nielsen9, Hans-Georg Rammensee10,
U S hi 1 11 Th Hi #12 d Ul i h K li k #13Ugur Sahin1,11, Thomas Hinz#12, and Ulrich Kalinke#13
on behalf of the Association of Cancer Immunotherapy (CIMT) Regulatory Research Group (RRG)
ABSTRACT
Tumors carry multiple somatic mutations, the majority of which are unique to
individual patients Recent data imply that immunogenic tumor mutations can beindividual patients. Recent data imply that immunogenic tumor mutations can be
exploited for the treatment of cancer patients. Here we propose a development
strategy for actively personalized vaccines (APVACs) targeting multiple tumor
mutations. This strategy is based on the existing regulatory framework thus
facilitating the way towards first clinical testing.
N t Bi t h l 2013 iNature Biotechnology 2013, in press
Glioma Actively Personalized Vaccine Consortium
83
GAPVAC
• Establish an actively personalized vaccinaton (APVAC) approach for treatment of glioblastoma patients
C ti ith• Consortium with14 partners fundedby EU with 6 mn EUR
• Led by Immatics(Coordinator) andBioNTech (Vice(Coordinator)
• Clinical study plannedt t t i 2014to start in 2014
• Up to 30 glioblastomapatients will receive APVACspatients will receive APVACscomposed of warehouse-selected and mutanome-derived peptides.
8484Tumor-associated peptides – shared vs. individual
Tumor 1
Tumor 2
SHAILEALATQMPDPKTFHVNDLFLQY
TUMAPs potentiallysuitable for personalized
therapy
ALRDVRQQYHQITVLHVYGLATDVQTVKLHGVNINV
LEEDSAREI
SHAILEALA
FAEGFVRALHVIDVKFLYGQFPGHNEF
GLNDETYGYLEEDSAREI
LLAERDLYL IAMATVTALLLAERDLYL
QEQSFVIRARLASYLDKV
MEDIKILIA
MQKEITAL
Off-the-shelfMulti-TUMAP
Vaccine
Tumor 3
MQKEITAL
Tumor 3
Glioma Actively Personalized Vaccine Consortium
85
GAPVAC design
To do for each patient:To do for each patient:
1. start vaccination with off-the-shelf peptides
2. select 5 - 15 peptides representing mutated ANDpatient-specific wild type HLA class I and class II ligands synthesize and formulate to a cocktail startligands, synthesize and formulate to a cocktail, start vaccination
Interfakultäres Institut für ZellbiologieAbteilung ImmunologieProf. Dr. Hans‐Georg Rammensee
87 Co-workers and Collaborators
IMA901 Chief InvestigatorsUS: Brian Rini, ClevelandEU: Tim Eisen, LondonGER: Arnulf Stenzl, Tübingen
Pfizer Inc.
COIN Study Group
University of TübingenHans-Georg RammenseeStefan Stevanovic
DiscoveryToni WeinschenkOliver Schoor
IMA910 Clinical TeamAndrea Mayer-MoklerJörg Ludwig
Cécile GouttefangeasArnulf StenzlSusan FeyerabendJörg HennenlotterJens Bedke
Norbert HilfJens FritzscheAndrea MahrNina Pawlowski
IMA910 Chief InvestigatorFrank Mayer, Tübingen
IMA950 Project LeadersOliver Schoor (CR-UK study)
BioNTechUgur SahinCedrik BrittenJohn CastleSandra Heesch
Jens BedkeGraham PawelecEvelyna Derhovanessian
University of VeronaVincenzo Bronte
ImmunologySteffen WalterDominik MaurerSabrina KuttruffR i M d k
Oliver Schoor (CR-UK study)Norbert Hilf (NCI study)
IMA950 Chief InvestigatorsRoy Rampling, Glasgow (CR-UK study)H d Fi d J h S l
Sandra HeeschSebastian Kreiter
Vincenzo Bronte
University of PadovaSusanna Mandruzzato
Regina MendrzykVerona Vass
CMCPeter Lewandrowski
Howard Fine and Joohee Sul,Bethesda (NCI study)
SAB & DSMB MembersHans-Georg Rammensee
Cancer Research UKJames RitchieLesley McGuigan
University of GenevaPierre-Yves DietrichValérie Dutoit
University of HeidelbergChristian FlohrWerner Stüber
IMA901 Clinical TeamAlexandra Kirner
gCornelius MeliefChristoph HuberPedro RomeroCraig Slingluff Jr.Christian Ottensmeier
y gSarah Halford
y gChristel Herold-MendePhilipp BeckhoveWolfgang Wick
Alexandra KirnerMaud LePriellecAnnette Schmid
Christian OttensmeierHakan Melsted
Chief Medical Officer Carsten ReinhardtChief Scientific Officer Harpreet Singh
ImmunomonitoringProficiency Panel &
Regulatory Research Group
Acknowledgements
Dept. Immunology University Hospital
Molecular immunology
Stefan Stevanovic
Urology
Arnulf Stenzl
Immunomonitoring
Cécile Gouttefangeas
Surgery
Alfred Königsrainer
Mathias Walzer
Armin Rabsteyn
Daniel Kowalewski
Jens Bedke
Susan Feyerabend
Jörg Hennenlotter
Karoline Laske
Annemarie Dröge
Melanie Widenmayer
Stefan Löb
Markus Löffler
Philipp HorvathDaniel Kowalewski
Heiko Schuster
Janet Peper
Jörg Hennenlotter
Pathology
Melanie Widenmayer
Heinrich Griesemann
Bioinformatics
Philipp Horvath
Internal Medicine II
Nico Trautwein
Christina Kyzirakos
Falko Fend
H G ti
Bioinformatics
Oliver Kohlbacher
Mathias Walzer
Lothar Kanz
Susanne Rittig
Christoph Grabenbauer
Thomas Feger
Christian Hotz
Human Genetics
Olaf Riess
Peter Bauer
immatics
Harpreet Singh
Helmut Salih
Sebastian Haen
Julia StickelChristian Hotz
Lea Prokop
Stefanie Souczek
Michael Bonin
Christopher Schröder
Harpreet Singh
Toni Weinschenk
Steffen Walter
Julia Stickel
Claudia Berlin
Rita Pfeifer Support: SFB 685, GK 794, BMBF, EU, Krebshilfe, fortüne, AKF
