the challenges of measuring the response to ...mm33 veh. + pembro. low il2: tils high il2: tils high...
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THE CHALLENGES OF MEASURING THE RESPONSE TO IMMUNOTHERAPIES IN VIVO
Jonas Nilsson, PhD, professorDirector of Sahlgrenska Cancer Center
www.gu.se
Jkstudios.tv
IL-2
IFNBCG
Anti-CTLA4
Anti-PD1
Anti-TIM3 etc
TILs
NK cellsCARs
Targeted antibodies
Dendritic cellsPeptides
Immunotherapies are group of treatments
www.gu.se
Anti-PD1/PDL1
Anti-CTLA4Robert C, Paris Melanoma Conference 2013
Checkpoint immunotherapies
www.gu.se
PD1/PDL1 inhibitors are tested in >1000 trials
https://www.cancerresearch.org/scientists/immuno-oncology-landscape/pd-1-pd-l1-landscape
Wolchok et al., 2017, NEJMLong et al., 2015, Lancet
How can we make the durable responses last and convert non-responders to responders?
Immunotherapy vs targeted therapy in melanoma
• Accurately models the human disease and develop fast enough to be used to pre-screen patients before trials (Einarsdottir et al., 2014 Oncotarget; Olofsson Bagge et al., 2018 JCO-PO)
• Pre-clinical drug evaluation & Biomarker discovery• Tumor immunology
Patient-derived melanoma xenograft biobank
• Accurately models the human disease and develop fast enough to be used to pre-screen patients before trials
• Pre-clinical drug evaluation & Biomarker discovery (Gad et al. Nature 2014; Warpman-Berglund Ann Oncol 2016; Einarsdottir et al., 2018 Cell Death Dis; Muralidharan et al 2017 CDD; Xue et al., Nature Medicine 2017; Lunavat et al., 2017 PNAS)
• Tumor immunology
Patient-derived melanoma xenograft biobank
• Accurately models the human disease and develop fast enough to be used to pre-screen patients before trials
• Pre-clinical drug evaluation & Biomarker discovery• Tumor immunology (Jespersen et al., Nat Commun 2017, Forsberg et al., Cancer
Res 2019 & Ny/Rizzo et al., Annals of Oncol 2020)
Patient-derived melanoma xenograft biobank
Tumor-infiltrating lymphocytes (TIL)
Cancer immune therapy in PDX models?
Adoptive T-cell transfer (ACT)
Adapted from: Rosenberg SA, Nature Rev Immunol 2012
Tumor sample
In vitro expansion
Lymphodepletionbefore TIL transfer
(chemotherapy)
• High response rate in MM (Ph II), (>50% tumor reduction in half of patients)
• Complete and durable responses(20%, 8 years of follow-up)
• Considerable toxicities
• Labour intensive
• Expensive
IL2
+ IL-2
TIL infusion(~ 1.109 cells)
T cells fully trained to kill the tumor
= TILs (Tumor Infiltrating Lymphocytes)
In vitro expansion
+PDX
RESPONSE?(Tumor growth)
TIL infusion
PXD v2.0= PDX v2.0
RESPONSE?(Tumor growth)
• Less toxic for mice (GVHD) ?• Correlation to ACT patient data?• Marker for response?• Model for combination therapy?• Genetic manipulation of T cells?
TIL infusion
0 3 6 9 18 24 36 48 66
-80
-40
0
40
Time since TIL infusion (months)
Chan
ge in
targ
et le
sion
s fro
m b
asel
ine
(%)
1124
05
29
4604Spider plot
https://www.taconic.com/taconic-insights/oncology-immuno-oncology/new-humanized-mouse-immunotherapy.html
Transgenic expression of human IL2 enables TIL-mediated tumor eradication in NOG mice
0 10 20 30 400
200
400
Days after transplantation
Tum
or v
olum
e (m
m3 ) MM33 Veh. + Pembro.
Low IL2: TILsHigh IL2: TILsHigh IL2: TILs + Pembro.
TILs n.s.
p=0,007
0 10 20 30 40 50 60 700
100
200
300
Days after transplantation
Tum
or v
olum
e (m
m3 )
20x106 - F3,710x106 - F3,05x106 - F6,01x106 - F3,40.1x106 - F3,40 - Veh.
TILs
MM33
Dose dependency in levels of IL2 and number of injected TILsAnti-PD1 does not enhance
0 20 40 60 80 100 120 140106
107
108
109
1010
Days after s.c. transplantation of the primary 33-luc tumour - IL2 control mouse, tumour removed around day 40- Relapse (metastasis chest + back) observed on day 76- TILs injected (17.106) on day 84
Radi
ance
(p
h/se
c/cm
2 /sr
)
Growth of MM909.33/luc in #2821 - IL2 mouse (BLI)
#2821 Metastasis CHEST#2821 Relapse tumour BACK
#2821 Primary s.c. tumour BACK
Resection of the primary tumour
Observation of a metastasis (chest) + tumour growing again at
the initial site (back)
Injection of cryopreseved TILs
Day 129
Day 40Day 76
Metastasis
• Can the PDXv2 model be predictive of ICI therapy?• Can we achieve additional effect by combination with
other therapies?• How applicable is the PDXv2.0 method to other diagnoses
than cutaneous melanoma?
Questions arising
• Can the PDXv2 model be predictive of ICI therapy?• Can we achieve additional effect by combination with
other therapies?• How applicable is the PDXv2.0 method to other diagnoses
than cutaneous melanoma?
Questions arising
Can PDX data be predictive of therapy responses
Tumor sample
NOG mouse
hIL2-NOG mouse
• T cell activation ?• Correlation to immunotherapy patient data?• Comparison to other predictive assays?• Model for combination therapy?
• New case presentingwith high tumor load
• Normally refractory to immune therapy withipi/nivo
• BRAF mutant• No TILs, only tumor
cells!!
PDX
TILs
Lars Ny, Lisa Nilsson
Case 1
• Dabrafenib/Trametinib• CR of all except very few
lesions• One subQ lesion biopsy –
TILs grew but hardly anytumor cells
• Switched to pembrolizumab• Last lesions disappeared
PDX
TILs
Post-therapy
Lars Ny, Lisa Nilsson
Case 1
Case 1
Lars Ny, Lisa Nilsson& Larissa Rizzo
A PDX-platform for prediction of therapy responses
0 20 40 600
200
400
600
800 M608B
Time (Days)
Tum
or v
olum
e (m
m3 )
0 50 100 150 2000
200
400
600
800M612
Time (Days)
Tum
or v
olum
e (m
m3 )
0 20 40 60 80 1000
50
100
150 M503B
Time (Days)
Tum
or v
olum
e (m
m3 )
0 20 40 600
100
200
300 M111
Time (Days)
Tum
or v
olum
e (m
m3 )
0 20 40 60 800
200
400
600 M812
Time (Days)
Tum
or v
olum
e (m
m3 )
NOG hIL2-NOG
0 50 100 1500
200
400
600
Time (Days)
Tum
or v
olum
e (m
m3 ) M816
0 20 40 60 80 1000
200
400
600M315
Time (Days)
Tum
or v
olum
e (m
m3 )
0 20 40 60 80 1000
100
200
300
400
500M131
Time (Days)Tu
mor
vol
ume
(mm
3 )
0 20 40 60 800
100
200
300
400
500M817
Time (Days)
Tum
or v
olum
e (m
m3 )
0 50 100 150 2000
50
100
150
200 M626B
Time (Days)
Tum
or v
olum
e (m
m3 )
250
0 50 100 150 200 2500
50
100
150
200
250
Time (Days)
Tum
or v
olum
e (m
m3 ) M626A
0 50 100 150 2000
100
200
300 M830
Time (Days)
Tum
or v
olum
e (m
m3 )
0 50 100 150 2000
50
100
150
200
250 M214LC
Time (Days)
Tum
or v
olum
e (m
m3 )
0 50 100 150 200 2500
100
200
300
400 M128B
Time (Days)
Tum
or v
olum
e (m
m3 )
0 50 100 1500
100
200
300
400 M608A
Time (Days)
Tum
or v
olum
e (m
m3 )
0 20 40 60 800
200
400
600M919A
Time (Days)
Tum
or v
olum
e (m
m3 )
0 20 40 60 800
200
400
600 M212
Time (Days)
Tum
or v
olum
e (m
m3 )
0 20 40 60 800
200
400
600 M503A
Time (Days)
Tum
or v
olum
e (m
m3 )
0 50 100 150 2000
200
400
600 M811
Time (Days)
Tum
or v
olum
e (m
m3 )
0 50 100 150 2000
100
200
300
Time (Days)
Tum
or v
olum
e (m
m3 ) M216
Growth pattern in hIL-NOG: No growth No growth but toxicity Growth Growth but delayed Growth and toxicity
Valerio Belgrano, Lars Ny, Henrik Jespersen, Lisa Nilsson& Larissa Rizzo
A PDX-platform for prediction of therapy responses
• 11/20 patients had been treated withPD-1 therapies
• Fisher test comparing mouse responsesto survival (p=0.0152)
0 10 20 30 40 500
50
100
Survival time from start of anti-PD1
Months
Perc
ent s
urvi
val
Blue/orange
Green/black&grey
Median survivalBlue/orangeUndefined
Green/black&grey19.27
Log-rank (Mantel-Cox) testChi squaredfP valueP value summaryAre the survival curves sig different?
1.42610.2324nsNo
A PDX-platform for prediction of therapy responses
0 20 40 600
200
400
600
800 M608B
Time (Days)
Tum
or v
olum
e (m
m3 )
0 50 100 150 2000
200
400
600
800M612
Time (Days)
Tum
or v
olum
e (m
m3 )
0 20 40 60 80 1000
50
100
150 M503B
Time (Days)
Tum
or v
olum
e (m
m3 )
0 20 40 600
100
200
300 M111
Time (Days)
Tum
or v
olum
e (m
m3 )
0 20 40 60 800
200
400
600 M812
Time (Days)
Tum
or v
olum
e (m
m3 )
NOG hIL2-NOG
0 50 100 1500
200
400
600
Time (Days)
Tum
or v
olum
e (m
m3 ) M816
0 20 40 60 80 1000
200
400
600M315
Time (Days)
Tum
or v
olum
e (m
m3 )
0 20 40 60 80 1000
100
200
300
400
500M131
Time (Days)Tu
mor
vol
ume
(mm
3 )
0 20 40 60 800
100
200
300
400
500M817
Time (Days)
Tum
or v
olum
e (m
m3 )
0 50 100 150 2000
50
100
150
200 M626B
Time (Days)
Tum
or v
olum
e (m
m3 )
250
0 50 100 150 200 2500
50
100
150
200
250
Time (Days)
Tum
or v
olum
e (m
m3 ) M626A
0 50 100 150 2000
100
200
300 M830
Time (Days)
Tum
or v
olum
e (m
m3 )
0 50 100 150 2000
50
100
150
200
250 M214LC
Time (Days)
Tum
or v
olum
e (m
m3 )
0 50 100 150 200 2500
100
200
300
400 M128B
Time (Days)
Tum
or v
olum
e (m
m3 )
0 50 100 1500
100
200
300
400 M608A
Time (Days)
Tum
or v
olum
e (m
m3 )
0 20 40 60 800
200
400
600M919A
Time (Days)
Tum
or v
olum
e (m
m3 )
0 20 40 60 800
200
400
600 M212
Time (Days)
Tum
or v
olum
e (m
m3 )
0 20 40 60 800
200
400
600 M503A
Time (Days)
Tum
or v
olum
e (m
m3 )
0 50 100 150 2000
200
400
600 M811
Time (Days)
Tum
or v
olum
e (m
m3 )
0 50 100 150 2000
100
200
300
Time (Days)
Tum
or v
olum
e (m
m3 ) M216
Growth pattern in hIL-NOG: No growth No growth but toxicity Growth Growth but delayed Growth and toxicity
Valerio Belgrano, Lars Ny, Henrik Jespersen, Lisa Nilsson& Larissa Rizzo
Case 2
0 50 100 1500
200
400
600 NOGhIL2-NOG
Time point (days)
Tum
or v
olum
e (m
m3 )
0 20 40 60 80 1000
200
400
600 NOGhIL2-NOG
Time point (days)
Tum
or v
olum
e (m
m3 )
0 20 40 600
200
400
600
Days post TIL infusion (i.v.)
Tum
or v
olum
e (m
m3 ) ****
0 20 40 60 80 1000
200
400
600
Time point (days)
Tum
or v
olum
e (m
m3 )
NOGhIL2-NOG
TILs
a b
c
0 14 28 42 56 70 84 980
100
200
300
400
500
600
Days post therapy
Tum
or v
olum
e (m
m3 )
BRAFi/MEKivehicleBRAFi/MEKi-long+TILsBRAFi/MEKi-short+TILsTILs
d
eBefore After anti-PD1 therapy
0 50 100 1500
200
400
600 NOGhIL2-NOG
Time point (days)
Tum
or v
olum
e (m
m3 )
0 20 40 60 80 1000
200
400
600 NOGhIL2-NOG
Time point (days)
Tum
or v
olum
e (m
m3 )
0 20 40 600
200
400
600
Days post TIL infusion (i.v.)
Tum
or v
olum
e (m
m3 ) ****
0 20 40 60 80 1000
200
400
600
Time point (days)
Tum
or v
olum
e (m
m3 )
NOGhIL2-NOG
TILs
a b
c
0 14 28 42 56 70 84 980
100
200
300
400
500
600
Days post therapy
Tum
or v
olum
e (m
m3 )
BRAFi/MEKivehicleBRAFi/MEKi-long+TILsBRAFi/MEKi-short+TILsTILs
d
eBefore After anti-PD1 therapy
0 50 100 1500
200
400
600 NOGhIL2-NOG
Time point (days)
Tum
or v
olum
e (m
m3 )
0 20 40 60 80 1000
200
400
600 NOGhIL2-NOG
Time point (days)
Tum
or v
olum
e (m
m3 )
0 20 40 600
200
400
600
Days post TIL infusion (i.v.)
Tum
or v
olum
e (m
m3 ) ****
0 20 40 60 80 1000
200
400
600
Time point (days)
Tum
or v
olum
e (m
m3 )
NOGhIL2-NOG
TILs
a b
c
0 14 28 42 56 70 84 980
100
200
300
400
500
600
Days post therapy
Tum
or v
olum
e (m
m3 )
BRAFi/MEKivehicleBRAFi/MEKi-long+TILsBRAFi/MEKi-short+TILsTILs
d
eBefore After anti-PD1 therapy
Valerio Belgrano, Lars Ny, Henrik Jespersen, Lisa Nilsson& Larissa Rizzo
Case 2
0 50 100 1500
200
400
600 NOGhIL2-NOG
Time point (days)
Tum
or v
olum
e (m
m3 )
0 20 40 60 80 1000
200
400
600 NOGhIL2-NOG
Time point (days)
Tum
or v
olum
e (m
m3 )
0 20 40 600
200
400
600
Days post TIL infusion (i.v.)
Tum
or v
olum
e (m
m3 ) ****
0 20 40 60 80 1000
200
400
600
Time point (days)Tu
mor
vol
ume
(mm
3 )
NOGhIL2-NOG
TILs
a b
c
0 14 28 42 56 70 84 980
100
200
300
400
500
600
Days post therapy
Tum
or v
olum
e (m
m3 )
BRAFi/MEKivehicleBRAFi/MEKi-long+TILsBRAFi/MEKi-short+TILsTILs
d
eBefore After anti-PD1 therapy
Ny/Rizzo et al., Ann Oncol In press
Jkstudios.tv
IL-2
IFNBCG
Anti-CTLA4
Anti-PD1
Anti-TIM3 etc
TILs
NK cellsCARs
Targeted antibodies
Dendritic cellsPeptides(e.g. gp100)
Potential combination immunotherapies
• Can the PDXv2 model be predictive of ICI therapy?• Can we achieve additional effect by combination with
other therapies?• How applicable is the PDXv2.0 method to other diagnoses
than cutaneous melanoma?
Questions arising
Sahlgrenska Cancer Center PDX biobank
Control TIL therapy CAR-T therapy CRISPR library
Breast cancer
Breast cancer biobank
ID TYPE Grade ER/PR HER2 LN Follow-up TILs25 IDC 3 ER+ - + Surgery (LN-) ++27 IDC 3 - - + Surgery (LN+) ++28 IDC 2 ER+PR+ + - -29 IDC (apocrine) 2 - + - -30 IDC (lobular) 2 ER+PR+ + - -32 IDC 2 - + + ++34 Skeletal met - +35 IDC 2 - - + +36 IDC 2 ER+ + - +37 DC (medullary) 3 - - - ++38 IDC 3 ER+PR+ - + +
Patients scheduled for neoadjuvant chemo for breast cancer
• PDX models can predict responses to ACT and ICI therapy• This can be useful in clinical and translational research
• Guide inclusion into trials• Inform on necessity of next-line therapy• Tools for testing new types of therapies
• Checkpoint inhibitors• Epigenetic therapies• Targeted therapies• Cell therapy (antigen-selected, engineered cells etc)• Stroma-cell directed therapies
• Challenges include• Take rate• Full immune humanization• Imaging
Summary & challenges
Solutions• Organoids• HSC transplantation• Nanoprobes
AcknowledgmentsSurgeons:Roger Olofsson Bagge, MD, PhD, assoc profPeter Naredi, MD, PhD, professor Caroline Vilhav, MD, PhD studentKian Chin, MDMedical Oncologists:Lars Ny, Assoc prof, MD, PhDHenrik Jespersen, MD, PhD student
Senior Research Fellows:Lisa Nilsson, PhD, Senior staff scientistSamuel Alsén, PhDJoakim Karlsson, PhDPost-graduate students:Elin Forsberg, MSc, PhD studentVasu Sah, MSc, PhD studentTechnical staff:Sofia Stenqvist, animal technician Carina Karlsson, research technician
Center for Cancer Immune Therapy, HerlevInge Marie Svane, MD, PhD, professorMarco Donia & Rikke Andersen, MDs/PhDs
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