ARTICLE
Received 9 Aug 2015 | Accepted 21 Dec 2015 | Published 17 Feb 2016
DOI: 10.1038/ncomms10501
OPEN
Adaptive resistance to therapeutic PD-1 blockade is
associated with upregulation of alternative immune
checkpoints
Shohei Koyama1,2,*, Esra A. Akbay2,3,*, Yvonne Y. Li2,3,*, Grit S. Herter-Sprie2,3, Kevin A. Buczkowski3,
William G. Richards4, Leena Gandhi3, Amanda J. Redig3, Scott J. Rodig5, Hajime Asahina2,3, Robert E. Jones6,
Meghana M. Kulkarni6, Mari Kuraguchi6, Sangeetha Palakurthi6, Peter E. Fecci7, Bruce E. Johnson2,3,
Pasi A. Janne2,3, Jeffrey A. Engelman8, Sidharta P. Gangadharan9, Daniel B. Costa9, Gordon J. Freeman1,2,
Raphael Bueno4, F. Stephen Hodi2,3, Glenn Dranoff1,2, Kwok-Kin Wong2,3,6 & Peter S. Hammerman2,3,10
Despite compelling antitumour activity of antibodies targeting the programmed death 1
(PD-1): programmed death ligand 1 (PD-L1) immune checkpoint in lung cancer, resistance to
these therapies has increasingly been observed. In this study, to elucidate mechanisms
of adaptive resistance, we analyse the tumour immune microenvironment in the context of
anti-PD-1 therapy in two fully immunocompetent mouse models of lung adenocarcinoma.
In tumours progressing following response to anti-PD-1 therapy, we observe upregulation of
alternative immune checkpoints, notably T-cell immunoglobulin mucin-3 (TIM-3), in PD-1
antibody bound T cells and demonstrate a survival advantage with addition of a TIM-3
blocking antibody following failure of PD-1 blockade. Two patients who developed adaptive
resistance to anti-PD-1 treatment also show a similar TIM-3 upregulation in blocking
antibody-bound T cells at treatment failure. These data suggest that upregulation of TIM-3
and other immune checkpoints may be targetable biomarkers associated with adaptive
resistance to PD-1 blockade.
1 Department of Medical Oncology and Cancer Vaccine Center, Dana Farber Cancer Institute, Boston, Massachusetts 02215, USA. 2 Depatment of Medicine,
Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA. 3 Department of Medical Oncology, Dana Farber Cancer
Institute, Boston, Massachusetts 02215, USA. 4 Department of Thoracic Surgery, Brigham and Women’s Hospital, Boston, Massachusetts 02115, USA.
5 Department of Pathology, Brigham and Women’s Hospital, Boston, Massachusetts 02115, USA. 6 Belfer Institute for Applied Cancer Science, Dana Farber
Cancer Institute, Boston, Massachusetts 02215, USA. 7 Division of Neurosurgery, Department of Surgery, Duke University Medical Center, Durham, North
Carolina 27710, USA. 8 Massachusetts General Hospital Cancer Center, Boston, Massachusetts 02114, USA. 9 Beth Israel Deaconess Medical Center, Boston,
Massachusetts 02215, USA. 10 Cancer Program, Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA. * These authors equally
contributed to this work. Correspondence and requests for materials should be addressed to G.D. (email: glenn_dranoff@dfci.harvard.edu) or to K.-K.W.
(email: kwong1@partners.org) or to P.S.H. (email: peter_hammerman@dfci.harvard.edu).
NATURE COMMUNICATIONS | 7:10501 | DOI: 10.1038/ncomms10501 | www.nature.com/naturecommunications
1
ARTICLE
NATURE COMMUNICATIONS | DOI: 10.1038/ncomms10501
P
rogrammed death 1 (PD-1): Programmed death ligand 1
(PD-L1) immune checkpoint blockade has been demonstrated to be efficacious in a number of cancer types,
including melanoma, renal cell carcinoma, bladder cancer,
hematologic malignancies and non-small cell lung cancer
(NSCLC)1–3 and anti-PD-1 antibodies have recently been
approved for use in the United States and Asia. Anti-PD-1
therapeutic antibodies function through binding to PD-1 on
tumour-reactive T cells and inhibiting the PD-1:PD-L1
interaction, thereby reinvigourating the anti-tumour T-cell
response4–6. Expression of PD-L1 in tumour cells and
infiltrating immune cells and PD-1 in tumour-infiltrating
T cells has been associated with responsiveness to blockade of
this immune checkpoint1,7–10; however, mechanisms of both
de novo and adaptive resistance to therapy are unclear.
NSCLC is the leading cause of cancer-related mortality worldwide. While its treatment has been dramatically improved in
patients who harbour targetable genomic alterations including
epidermal growth factor receptor (EGFR) mutations and
anaplastic lymphoma kinase (ALK) fusions11, it remains the
case that only a minority of NSCLC patients benefit from
these targeted agents. Conversely, immunotherapy approaches,
specifically PD-1:PD-L1 blockade, appear to be broadly
efficacious in NSCLC patients12–14. Although the mechanisms
of resistance to targeted kinase inhibitors have been extensively
studied15,16, there have been no studies reported to date of
resistance to PD-1:PD-L1 blockade. We previously reported that a
fully immunocompetent mouse model of lung cancer driven
by expression of mutated EGFR demonstrates responsiveness to
PD-1 blockade associated with augmentation of an anti-tumour
T-cell response17.
Here we have extended these studies using two genetically
engineered mouse models of lung adenocarcinomas corresponding to the two most common oncogene drivers in human lung
adenocarcinoma, Kirsten rat sarcoma viral oncogene homologue
(KRAS) and EGFR. The EGFR and Kras models were treated with
a therapeutic anti-PD-1 antibody until tumours demonstrated
progression by magnetic resonance imaging (MRI) and evaluated
immune profiles. We identified that upregulation of other
immune checkpoints, most notably TIM-3, on therapeutic
antibody-bound T cells as a marker of treatment resistance.
To determine whether blockade of TIM-3 at the time of resistance
might be therapeutically efficacious, we performed TIM-3blocking treatment in these mice and demonstrated a clinical
benefit. To extend these results and determine their applicability
to patients treated with anti-PD-1 antibodies, we analysed
specimens from two patients who showed an initial response to
PD-1 blockade but ultimately developed progressive disease.
These cases exhibited similar upregulation of TIM-3 on
therapeutic antibody-bound tumour-infiltrating lymphocytes
(TILs). These results suggest that targeting alternate immune
checkpoints upregulated in the context of PD-1 therapy may
extend the benefit of PD-1 blockade in responsive tumours.
the original tumour size in accordance with the response
evaluation in solid tumours (RECIST) definition (Fig. 1a). We
also confirmed binding of PD-1-blocking antibody at the time of
progression (PD-1R) to exclude decreased antibody binding over
time as responsible for the loss of efficacy of PD-1 blockade
(Fig. 1b). We found a modest difference in total numbers of CD4
and CD8 T cells, resulting in significantly lower CD4/CD8 ratios
in both the EGFR TL and Kras models in resistant nodules
(Fig. 1c). There were no significant differences among untreated
and anti-PD-1 therapy-resistant samples in forkhead box P3
(FOXP3) þ CD4 þ T cells (regulatory T cells: Treg; Fig. 1c) and
two major populations of myeloid cells in the murine
models, tumour-associated alveolar macrophages (TAM:
CD11c þ CD11b CD103 ) and tumour-associated neutrophils
(TAN: CD11b þ Ly6G þ ) (Supplementary Fig. 1b). There were
also no significant differences in PD-L1 expression levels in TAM
and tumour cells (CD45 EpCAM þ ) and levels of the cytokines
IL-6 in bronchoalveolar lavage fluids (BALFs), that can promote
tumour growth18,19, between untreated (U) and PD-1 treatmentresistant mice (R) (Supplementary Fig. 1c,d) though the level of
IL-6 in BALFs showed a clear reduction in PD-1 treatmentsensitive animals (S) as we previously demonstrated in a different
EGFR mutated model17.
We next performed a global analysis of sorted T cells and
tumour cells by mRNA sequencing of anti-PD-1-resistant versus
untreated tumours. In a supervised analysis of genes suppressing
T-cell function, we observed in the TL and Kras tumours an
increase in the expression of Hepatitis A virus cellular receptor 2
(Havcr2, known as Tim3), lymphocyte-activation gene 3 (Lag3)
and programmed cell death 1 (Pdcd1; Fig. 1d) but no increase in
Foxp3, 4632428N05Rik coding V-domain Ig suppressor of T cell
activation: VISTA, or B and T lymphocyte attenuator (Btla).
In agreement with the immune profiling results, there was no
noticeable expression change in the Foxp3 expression between
treated and untreated tumours. To confirm the expression of
these genes at the protein level, we analysed these T-cell
inhibitory markers in CD4 and CD8 T cells with flow cytometry
analysis. In accordance with the findings from the mRNA
sequencing data, TIM-3, LAG-3 and CTLA-4 were expressed at
higher levels in both CD4 and CD8 T cells from PD-1 resistant as
compared with untreated EGFR TL tumours by flow cytometry
analysis. However, only TIM-3 showed a significant increase
(Fig. 1e). A significant increase of TIM-3 was also identified in
both CD4 and CD8 T cells in the Kras model (Fig. 1e). In
addition, there were significant increases in LAG-3 and CTLA-4
expression in CD8 T cells only in Kras tumours, though the
magnitude of induction was less than that observed for TIM-3
(Fig. 1e). For PD-1, we found an increasing trend in the
percentage of anti-PD-1 antibody bound cells with longer
treatment duration when comparing nodules obtained from
EGFR TL and Kras mice that had received from 2–8 weeks of
therapy (Supplementary Fig. 1e), suggesting that PD-1 blockade
could enrich for PD-1 expression on TILs.
Results
Checkpoint expression in TILs at resistance to PD-1 blockade.
We performed a therapeutic study of a PD-1 blocking antibody in
two fully immunocompetent genetically engineered mouse
models of lung cancer, EGFRT790M/L858R (TL) and KrasG12D
using the same dosing schedule as described previously17
(Fig. 1a). We first compared the lung immune cell populations
among untreated (U) and anti-PD-1 treatment-resistant tumours
(PD-1R:R) in mice with similar degrees of tumour burden
(Supplementary Fig. 1a). Resistance was defined as tumours
displaying an initial therapeutic response by MRI imaging
(regression or stable disease) followed by growth to 4120% of
TIM-3 upregulation is time dependent in TILs expressing PD-1.
To further investigate TIM-3 expression in T cells, we
systemically analysed mice at the time of resistance to PD-1
blockade. TIM-3 upregulation was only detected specifically in
T cells from tumour-bearing lungs but not mediastinal lymph
node, peripheral blood (Fig. 2a) or spleen (data not shown) and
was predominantly found on anti-PD-1 antibody bound CD4 and
CD8 T cells (Fig. 2a). We also evaluated the kinetics of TIM-3
upregulation during PD-1 blocking treatment. We previously
showed that significant T-cell activation and clinical response
could be observed in mouse models following 1 week of
2
NATURE COMMUNICATIONS | 7:10501 | DOI: 10.1038/ncomms10501 | www.nature.com/naturecommunications
ARTICLE
NATURE COMMUNICATIONS | DOI: 10.1038/ncomms10501
a
b
8–10 wks after aPD-1 ab treatment
5–6 wks
of age
aPD-1 ab
aPD-1 ab
Response
sensitive:PD-1S
10–12 wks
after induction
PD-1 (29F.1A12)
Induce
lung
tumours
PD-1R
Progression
resistant:PD-1R
1.27
1.08
0.59
0.88
67.4
30.3
58.2
40.3
Anti-rat IgG2a
c
EGFR TL
Kras
1
0
1
0
2
40
1
20
0
0
U R
U R
d
60
Untreated
Havcr2
3.3
2.1
1.5
1.3
Lag3
Pdcd1
Ctla4
2
1
60
2
30
1
0
0
U R
**
0
U R
U R
Fold
P value
change
PD-1R
Havcr2
0.001
0.009
0.001
0.01
CD4/CD8
3
1.3
1.4
1.3
Lag3
Pdcd1
0.04
0.002
0.002
Ctla4
VISTA#
Btla
–2 –1 0 1 2
Row Z-score
Foxp3
1
2
Row Z-score
Kras
***
U
***
R
CTLA-4
*
LAG-3
***
50
40
30
20
10
0
Tim-3
%
CD8 T cells
FOXP3
CTLA-4
FOXP3
0
CTLA-4
5
0
LAG-3
10
10
LAG-3
R
Tim-3
**
U
CTLA-4
15
LAG-3
30
CD4 T cells
50
40
30
20
10
0
Tim-3
20
%
40
CD8 T cells
***
%
CD4 T cells
Tim-3
–2 –1 0
Foxp3
EGFR TL
%
3
Untreated
VISTA#
Btla
20
Treg
90
Kras T cells
P value
Fold
change
PD-1R
CD8 T cells
4
U R
U R
U R
EGFR TL T cells
5
4
3
2
1
0
Count mg–1
2
***
3
x102 count mg–1
3
CD4 T cells
CD4/CD8
80
2
Count mg–1
4
Treg
x102 count mg–1
CD8 T cells
x102 count mg–1
x102 count mg–1
CD4 T cells
e
CD8 T cells
CD4 T cells
Figure 1 | Upregulation of TIM-3 in T cells at the time of acquired resistance to anti-PD-1 blockade. (a) Schematic of in vivo treatment with anti-PD-1
antibody until adaptive resistance (b) Representative flow cytometry data from anti-PD-1 resistant (PD-1R) EGFR TL mouse. PD-1 expression and anti-Rat
IgG2a (therapeutic antibody binding) were evaluated. Fluorescent conjugated anti-PD-1 antibody is the same clone (29F.1A12) as the therapeutic antibody.
(c) Cell number of T cell subsets: CD4 T cells, CD8 T cells and regulatory T cells (Treg) and CD4/CD8 ratio. Untreated (U) EGFR TL (n ¼ 7), Kras (n ¼ 7)
and anti-PD-1 resistant (R) EGFR TL (n ¼ 9), Kras (n ¼ 9) were analysed (EGFR TL ***Po0.001, Kras **P ¼ 0.0028, student’s t-test). Data are shown as
mean±s.d. (d) Expression of six genes with an annotated role in the T-cell response in sorted T cells from EGFR models (five anti-PD-1 treated and three
untreated tumours) in EGFR models and KRAS models (five anti-PD-1 treated and five untreated tumours). For each gene, expression values across the
samples are plotted as log-transformed FPKM values (row-scaled and coloured on a blue-red scale to emphasize the difference between treated and
untreated samples). The magnitude of change between resistant and genotype-matched untreated samples are shown as fold change and P values for
differentially expressed genes (defined as having an absolute fold change greater than 1.25 and a P value o0.05 as calculated by the limma package37).
Note the gene name of VISTA is 4632428N05Rik (Gene ID: 74048). (e) Surface expression of inhibitory T cell markers: TIM-3, LAG-3, CTLA-4 and FOXP3.
Untreated (U) EGFR TL (n ¼ 7), Kras (n ¼ 7) and anti-PD-1 resistant (R) EGFR TL (n ¼ 9), Kras (n ¼ 9) were analysed (*Po0.05, **Po0.01, ***Po0.001).
Data are shown as mean±s.d.
anti-PD-1 therapy17. At this time point, there was no significant
difference in TIM-3 expression between treated and untreated
tumours in both EGFR and Kras mice; however, a significant
increase in interferon-gamma-positive CD8 T cells was observed
(Fig. 2b, Supplementary Fig. 1a,f) suggesting that TIM-3 elevation
was not simply correlated with T-cell activation. In contrast,
significant TIM-3 upregulation was detected at the time of disease
progression (PD-1R) in both models (after 2 weeks in Kras and
after 4 weeks in EGFR TL) and there were significant correlations
between TIM-3 positivity and the duration of PD-1 blocking
treatment (Fig. 2b) and the percentage of anti-PD-1 antibody
positive T cells (Fig. 2c). Together with the finding that anti-PD-1
antibody binding was increased with longer duration of PD-1
blocking treatment (Supplementary Fig. 1e), these results
suggested that therapeutic PD-1 blockade could facilitate
persistence of TILs with enrichment for therapeutic antibody
bound PD-1- and TIM-3-positive T cells. In contrast, we did not
see TIM-3 upregulation with CTLA-4 blockade.
We also investigated the expression of Galectin-9, one of the
ligands for TIM-3 receptor that is expressed on a variety of cell
NATURE COMMUNICATIONS | 7:10501 | DOI: 10.1038/ncomms10501 | www.nature.com/naturecommunications
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NATURE COMMUNICATIONS | DOI: 10.1038/ncomms10501
b
CD4 T cells
59.2
0.71
MLN
1.73
17.3
32.2
52.3
28.6
0.45
0.44
0.063
TIM-3 positive (%)
7.23
1.35
Lung
tumour
CD8 T cells
EGFR TL
CD4 T cells
15
10
5
r = 0.8013
P < 0.0001
0
CD8 T cells
TIM-3 positive (%)
a
20
Untreated
PD-1S
PD-1R
15
10
5
0
r = 0.8811
P < 0.0001
0 2 4 6 8 10
PD-1 treatment (weeks)
0 2 4 6 8 10
PD-1 treatment (weeks)
Kras
0.90
0
1.38
0.15
2.43
97.2
1.23
TIM-3
Blood
96.7
CD8 T cells
CD4 T cells
4.50
25
20
15
10
5
0
r = 0.8192
P < 0.0001
0 2 4 6 8
PD-1 treatment (weeks)
Anti-rat IgG2a
TIM-3 positive (%)
95.0
15.6
TIM-3 positive (%)
83.3
50
40
30
20
10
0
Untreated
PD-1S
PD-1R
r = 0.8467
P < 0.0001
0 2 4 6 8
PD-1 treatment (weeks)
c
CD8 T cells PD-1R
PD-1 ab binding (%)
TIM-3 positive (%)
50
40
30
20
10
0
r = 0.8156
P < 0.0001
0
20
40
60
80
100
80
60
40
0
r = 0.6173
P = 0.0063
20
TIM-3 positive (%)
CD4 T cells PD-1R
25
20
15
10
5
0
PD-1 ab binding (%)
Figure 2 | TIM-3 expression in tumour-infiltrating T cells correlates with treatment time and PD-1 antibody binding. (a) TIM-3 expression
in T cells from tumour-bearing lung, mediastinal lymph node and peripheral blood. Representative flow cytometry data from anti-PD-1 resistant
EGFR TL mouse. (b) Significant correlation was detected between TIM-3 positivity and the duration of PD-1 blocking treatment in EGFR TL mice
(untreated (0 week): n ¼ 7, anti-PD-1 sensitive (PD-1S): n ¼ 6 and resistant (PD-1R): n ¼ 9) and Kras mice (untreated: n ¼ 7, anti-PD-1 sensitive
(PD-1S): n ¼ 6, resistant (PD-1R): n ¼ 9). (c) Significant correlation was detected among TIM-3 positivity and the amount of bound therapeutic PD-1
antibody in anti-PD-1 resistant (PD-1R) EGFR TL and Kras mice (both EGFR and Kras mice were combined: n ¼ 18). Correlation was evaluated
using Pearson’s correlation coefficient.
types and has a role in negatively regulating Th1-type immune
responses20,21. We confirmed a significant elevation in the
expression of lectin, galactoside-binding, soluble, 9 (Lgals9),
which encodes Galectin 9, in sorted CD45 EpCAM þ tumour
samples from the anti-PD-1-resistant Kras tumours as compared
with untreated Kras tumours at both RNA and protein level
(Supplementary Fig. 2a,b). CEACAM1 and phosphatidylserine
have also been proposed as ligands for TIM-3 (refs 22,23). We did
observe that the majority of TIM-3-positive CD8 T cells coexpressed CEACAM1 (Supplementary Fig. 3a) suggesting at the
time of resistance to PD-1 blockade that TIM-3 might function
together with CEACAM1 to suppress T cells. CEACAM1 was also
expressed in some TIM-3-negative T cells and tumour cells. The
level of CEACAM1 expression in tumour cells and positivity of
CEACAM1 in CD4 and CD8 T cells did not show a significant
difference between untreated and PD-1 treatment-resistant
tumours (Supplementary Figs 2b,3b).
TIM-3 antibody addition overcomes resistance to PD-1 blockade.
As we observed PD-1 blocking antibody on TILs as well as TIM-3
upregulation at the time of therapeutic resistance to anti-PD-1
therapy, we treated mice with an anti-TIM-3 antibody at the time
of PD-1 treatment failure to investigate whether TIM-3 blockade
could provide additional clinical benefit in tumours, which had
developed resistance to anti-PD-1 treatment. Because the clinical
response to anti-PD-1 antibody was initially more robust in the
4
EGFR TL model17 (Supplementary Fig. 4a) as compared with the
Kras model that only showed disease stability with PD-1
treatment, we utilized the EGFR model for therapeutic studies
with a TIM-3-blocking antibody. Mice were treated with a PD-1
blocking antibody until tumours progressed and, then treatment
with a TIM-3-blocking antibody was initiated when mice
appeared both clinically unwell and demonstrated progressive
disease by MRI imaging (Fig. 3a, Supplementary Fig. 4b).
Antitumour efficacy (Supplementary Fig. 4b) and a significant
survival advantage (Fig. 3b) were observed in the cohort of
mice that were treated with the TIM-3-blocking antibody with
median survival for anti-PD-1 antibody alone 5 weeks versus
PD-1 þ TIM-3 sequential treatment 11.9 weeks (Fig. 3b;
P ¼ 0.0008, log-rank test). The impact of the TIM-3-blocking
antibody on T-cell function was investigated by analysing mice at
2 weeks after adding TIM-3 blockade to anti-PD-1 antibody
therapy (sequential combination treatment sensitive:Seq combS;
Supplementary Fig. 5a). Binding of both anti-PD-1- and antiTIM-3-blocking antibodies on CD8 T cells was confirmed.
Addition of TIM-3-blocking antibody but not an isotype control
antibody (Rat IgG2a) enhanced interferon-gamma production
and cell proliferation as compared with TIM-3 þ CD8 T cells
from PD-1-resistant mice (Fig. 3c,d). Importantly, we also
detected higher levels of LAG-3 and CTLA-4 on the CD8 T
cells that were bound by the anti-PD-1 and anti-TIM-3
antibodies at the time of regrowth of lung tumour after
combination treatment (Seq combR) as compared with the time
NATURE COMMUNICATIONS | 7:10501 | DOI: 10.1038/ncomms10501 | www.nature.com/naturecommunications
ARTICLE
NATURE COMMUNICATIONS | DOI: 10.1038/ncomms10501
a
c
aPD-1 ab ±
aTIM-3 ab
8–10 wks after aPD-1 ab treatment
aPD-1 ab
10–12 wks
after induction
aPD-1 ab
Response
sensitive:PD-1S
Progression
resistant:PD-1R
CD8 T cells
PD -1R
Response or
stable disease
Seq
CombS
b
PD-1 blockade
1.66
74.3
14.1
19.1
0.26
79.6
1.03
Sequential PD-1+TIM-3 blockade
IFNγ
Percent survival
100
9.96
TIM-3
50
0
0
5
10
Weeks
d
15
20
e
0
IL-6
*
300
200
100
0
PGRN
20
*
ng ml–1
10
100
80
60
40
20
0
pg ml–1
20
% In CD8 T cells
**
30
Ki-67
*
15
PD-1R
Seq CombS
10
5
0
Se P
q DC 1R
om
bS
40
Se P
q DC 1R
om
bS
% In CD8 T cells
IFNγ
Figure 3 | Sequential anti-TIM-3 blocking displays clinical efficacy in anti-PD-1 adaptive resistant tumours. (a,b) Survival after PD-1 blockade alone
(anti-PD-1 resistant) or PD-1 and sequential TIM-3 blockade combination treatment (PD-1 alone: n=16 and sequential combination treatment: n=11)
(P=0.0008) after documented tumor burden. Treatment started at week 0. Median survival PD1 5 weeks vs PD-1+TIM-3 sequential treatment 11.9 weeks.
(c) Representative flow cytometry data of IFN-gamma expression in CD8 T cells from anti-PD-1 resistant (PD-1R) and sequential anti-PD-1 plus anti-TIM-3
combination (Seq CombS): 2 weeks0 anti-PD-1 and anti-TIM-3 combination treatment after development of resistance to PD-1 single treatment. Fluorescent
conjugated anti-TIM-3 antibody is the same clone (RMT3-23) as the therapeutic antibody. (d) IFN-gamma and Ki-67 positive CD8 T cell counts from
anti-PD-1 resistant (PD-1R) (n ¼ 6) and sequential anti-PD-1 plus anti-TIM-3 combination (Seq CombS) (n ¼ 6) (*Po0.05, **Po0.01). (e) IL-6 and PGRN
production in BALFs from PD-1R (n ¼ 6) and comb (Seq CombS: n ¼ 6) (*Po0.05). Data are shown as mean±s.d., P values are calculated using student’s
t test for all data except for the survival data.
of inhibiting lung tumour growth (Seq combS) (Supplementary
Fig. 5b,c). This result suggests that additional immune
checkpoints may be upregulated in the context of combinatorial
therapy with anti-PD-1 and anti-TIM-3 antibodies, which also
might limit therapeutic activity.
As we reported previously, checkpoint blockade also affected
immune suppressive cytokine production in the tumour microenvironment17. We found that IL-6 and progranulin (PGRN)
were significantly reduced with combined anti-PD-1 and antiTIM-3 treatment following anti-PD-1 antibody failure as
compared with the levels at the time of anti-PD-1 resistance
(Fig. 3e). This result suggests that TIM-3 blockade may not only
enhance T-cell function following anti-PD-1 antibody failure, but
also decrease the levels of tumour-promoting cytokines, similar to
our previous observation in naive mice treated with anti-PD-1
alone17. Unlike other models where concurrent blockade of PD-1
and TIM-3 delays tumour progression as initial therapy in the
context of high expression levels of these checkpoints24, we
observed no additional benefit of combination therapy as initial
therapy as compared with anti-PD-1 alone (Supplementary
Fig. 6a,b). Although the precise basis for this difference remains
to be clarified, low levels of TIM-3 expression at the time of
treatment initiation and the rapid development of neutralizing
anti-rat antibodies might be involved.
High TIM-3 expression in TILs is observed in patients.
To assess whether these findings in mouse models might correspond to patterns of resistance to anti-PD-1 therapy in lung
cancer patients, we analysed samples from two lung cancer
patients who were treated with anti-PD-1 antibodies and five
samples from lung cancer patients who were not treated with
immune modulating agents.
Patient #1 was a 59-year-old male with an extensive smoking
history who harboured a KRAS G12D mutated stage IV lung
adenocarcinoma with diffuse metastases. Following progression
on carboplatin, paclitaxel and bevacizumab therapy, he was
enrolled in a clinical trial of anti-PD-1 therapy at which time his
tumour was determined to be PD-L1 positive by IHC (41%
positivity). The patient achieved a partial response to this
treatment as defined by RECIST 1.1 criteria but developed
progressive disease 4 months later with a new pericardial effusion
(Fig. 4a). Patient #2 was a 72-year-old male former smoker
initially diagnosed with stage IV lung adenocarcinoma with brain
metastases. His tumour was wild type for EGFR, KRAS and ALK,
but did display MET positivity by IHC. He was treated with
carboplatin and paclitaxel, pemetrexed and erlotinib plus an antiMET antibody before enrolling on a study of anti-PD1 therapy.
His tumour displayed 450% PD-L1 positivity at the time of trial
registration. He achieved a partial response of 5 months duration
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ARTICLE
NATURE COMMUNICATIONS | DOI: 10.1038/ncomms10501
a
Patient #2: 72-year-old man, adenocarcinoma
Patient #1: 59-year-old man, adenocarcinoma
Effusion collection
Anti-PD-1
Effusion collection
Anti-PD-1
CT
CT
CXR
b
c
CD4 T cells
d
CD8 T cells
CD4 T cells
*
Pt #1
30
*** **
60
CD8 T cells
*
10
40
Pt #2
20
TIM-3
20
% of TIM-3+
Pt #2
53.9%
0
0
CE
RE
PT
Anti-human IgG
CE
RE
PT
51.8%
CD4 T cells
Pt #1
80.7%
% of TIM-3+
45.6%
CD3
CD8 T cells
Anti-human IgG
Figure 4 | Upregulation of TIM-3 in two resistant patient cases after anti-PD-1 treatment. (a) Clinical course of patient #1 and patient #2, who were
treated with PD-1 blocking antibodies. Both initially responded to treatment but subsequently developed treatment resistance with effusions. Arrow
indicates soft tissue metastasis (red arrow) and pericardial effusion (white arrow) in patient #1 and left lower lobe tumour (red arrow) and pleural effusion
(orange arrow) in patient #2. (b) Detection of therapeutic antibody (human IgG) binding in CD4 and CD8 T cells. Human IgG and isotype control are
shown in red and black, respectively. (c) Percentage of TIM-3 positive CD4 and CD8 T cells in effusions from two anti-PD-1 resistant patients (resistant
effusions: RE), NSCLC patients without PD-1 blocking treatment (control effusions: CE, n ¼ 5) and surgically resected primary tumours: PT (n ¼ 11). Mean %
of TIM-3 in T cells from RE versus CE versus PT (CD4 T cells 22.10 versus 2.52 versus 9.06 and CD8 T cells 37.85 versus 3.19 versus 17.58. In CD4 T cells,
RE versus CE ***P ¼ 0.0001, RE versus PT **P ¼ 0.0023 and CE versus PT *P ¼ 0.0247. In CD8 T cells, RE versus CE *P ¼ 0.0256. (d) TIM-3 expression
and therapeutic antibody binding (human IgG) in CD4 and CD8 T cells. Data are shown as mean±s.d., P values are calculated using one-way analysis of
variance with Tukey’s multiple comparison test.
before developing disease progression with an enlarging
parenchymal lung mass and a malignant pleural effusion
(Fig. 4a). We analysed the immune cells in the effusion samples
collected from these two patients and compared the immune
profile with effusions and surgically resected tumour samples
from different NSCLC patients who had not been treated with
anti-PD-1 antibody treatment.
At the time of disease progression, CD4 and CD8 T cells in
effusions from both anti-PD-1 treated patients showed evidence of
therapeutic antibody binding (more than 45% of CD4 and CD8 T
cells showed human IgG binding; Fig. 4b), indicating that PD-1
was still expressed by these T cells at the time of treatment failure.
On detailed analysis of other immune checkpoints (TIM-3, LAG-3
and CTLA-4) and the regulatory T cell marker FOXP3 on the T
cells, we detected upregulation of TIM-3 but no significant
changes in the other markers examined as compared with
effusions from other lung cancer patients who had not been
treated with PD-1-blocking antibodies (Fig. 4c, Supplementary
Fig. 7a). These results show a similar trend to what was observed
in mouse models (Fig. 1d). There was also an increase of CTLA-4
expression in CD8 T cells in the two resistant cases
(Supplementary Fig. 7a), but the magnitude of this change was
less than that observed for TIM-3, also consistent with the mouse
data (Fig. 1d). Although tumour-infiltrating T cells from surgically
6
resected primary NSCLCs (PT) showed variation in TIM-3
expression, the level of TIM-3 on CD4 and CD8 T cells in the
effusion specimens from the two patients who progressed on antiPD-1 therapy (resistant effusions: RE) was higher (mean of TIM-3
positivity was 22.10% and 37.85% in CD4 and CD8 T cells,
respectively) than those from other NSCLC patients (mean of
TIM-3 positivity was control effusions (CE):2.52% and PT:9.06%
in CD4 T cells and 3.54% and PT:17.58% in CD8 T cells) (Fig. 4c).
Further analysis of the TIM-3 expressing T-cell population in the
patients who progressed on anti-PD-1 therapy showed that the
majority of TIM-3 expressing T cells bound the therapeutic
antibody (human IgG þ ; Fig. 4d). Since previous work has
indicated that TIM-3 þ FOXP3 þ regulatory T cells possess strong
immunosuppressive functions in mice25, we also evaluated the
PD-1 antibody binding and TIM-3 expression specifically in
FOXP3 þ CD4 T cells; TIM-3 expression in Tregs was similarly
linked to anti-PD-1 antibody binding (Supplementary Fig. 7b). In
accordance with the finding in mouse models, TIM-3 levels
correlated with PD-1 expression in tumour-infiltrating cytotoxic
CD8 T cells from surgically resected NSCLCs (Supplementary
Fig. 7c). Together, with the findings in preclinical mouse models,
our data suggest that prolonged exposure to PD-1 blocking
antibody drives increased TIM-3 expression in NSCLC patients,
which might impact overall treatment efficacy.
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We further investigated T cells and myeloid cell populations in
effusion samples. The CD4/CD8 ratio was lower in T cells at
resistance in both patients (Supplementary Fig. 7d), as it was the
case for the mouse EGFR TL and Kras lung cancer models
(Fig. 1a) In the anti-PD-1-resistant samples, we noted increased
effector memory CD8 T cells (CCR7 CD45RA ) as compared
with untreated samples (Supplementary Fig. 7d). Together with
other work6, these results suggest that PD-1-blocking treatment
prolongs T-cell survival; however, PD-1 blockade also enriches
for tumour-reactive memory CD8 T cells expressing TIM-3. Two
major myeloid cell populations (CD66b þ and CD33 þ CD66b )
did not show a significant difference between untreated and
anti-PD-1-resistant samples (Supplementary Fig. 7e). We also
evaluated PD-L1 expression levels in human monocytes
(CD33 þ CD66b CD14 þ ) and found a nonsignificant trend
towards increased PD-L1 expression in the anti-PD-1-resistant
samples (Supplementary Fig. 7f). To evaluate cytokine production
in tumour microenvironment, we also analysed supernatants
from the effusion samples. We detected comparable levels of IL-6
and PGRN in both resistant samples and untreated effusion
samples, similar to our observation in the mouse models.
(Supplementary Fig. 7g). Interestingly, Galectin-9 (ref. 20),
which was significantly increased in mouse cancer models
(Supplementary Fig. 3) was also significantly increased in both
of the PD-1-resistant patient cases as compared with untreated
samples (Supplementary Fig. 7g). Together, these results suggest
that TIM-3 blockade could be a reasonable therapeutic option in
the setting of resistance to anti-PD-1 therapy because both TIM-3
on T cells and ligand in the tumour microenvironment showed
significant increases in PD-1-resistant clinical cases.
Discussion
Previously we demonstrated that oncogenic signalling downstream of the EGFR kinase in a lung cancer mouse model and in
human cancer cell lines contributed to immune evasion through
the activation of the PD-1:PD-L1 immune checkpoint. We
functionally validated the therapeutic efficacy of PD-1 blockade in
this mouse model and showed that suppression of EGFR
signalling decreased PD-L1 expression on tumour cells17. Here,
we have extended these studies to investigate potential
mechanisms of adaptive resistance to anti-PD-1 therapy using
two fully immunocompetent genetically engineered mouse
models of lung adenocarcinomas corresponding to the two
most common oncogene drivers in human lung adenocarcinoma,
KRAS and EGFR. This study was motivated by the impressive
efficacy of anti-PD-1:PD-L1 therapy in lung cancer patients,
which has been recently approved by FDA.
Here, we showed that the therapeutic PD-1-blocking antibody
was still bound to T cells at the time of disease progression in
both EGFR and Kras mutated mouse lung tumours as well as in
human specimens. These data indicate that anti-PD-1 antibodies
are still functional at the time of resistance and maintain the
ability to prevent inhibitory signals through PD-1 in the tumour
microenvironment and suggest that mechanisms other than
PD-1:PD-L1 interaction are likely important in adaptive
resistance. This argues against failure of ongoing antibody
binding to its target as a mechanism of treatment failure. Further,
we did not observe a significant difference in the number of
tumour-associated macrophages or tumour-associated neutrophils when comparing pre-treatment and resistant specimens,
arguing against quantitative changes in myeloid cell composition
as likely resistance mechanisms. We demonstrated that TIM-3
was upregulated in CD4 and CD8 T cells from anti-PD-1resistant EGFR and Kras mutated tumours as compared with
untreated tumours. Importantly, (1) elevation of TIM-3
expression in T cells was predominantly found on the therapeutic
PD-1 antibody-bound subset, (2) upregulation of TIM-3 was only
detected in tumour-bearing lungs but not in sentinel lymph nodes
and peripheral blood, (3) TIM-3 positivity was significantly
correlated with duration of PD-1 blockade and (4) TIM-3 was not
upregulated acutely at time points when we confirmed clinical
efficacy17. Other studies in the basic Immunology and Infectious
Disease literature have shown that TIM-3 is co-expressed with
PD-1 in exhausted T cells in the context of anti-microbial
responses26–29, which support our finding of TIM-3 expression
on therapeutic anti-PD-1 antibody-bound T cells in the setting of
treatment failure. In mice lacking PD-1 systemically, T cells
express higher levels of TIM-3 in the context of AML30
supporting the notion that compensatory pathways are
upregulated in the absence of PD-1. Together, with these
studies, our results suggest that prolonged exposure to PD-1blocking antibody enriches for TIM-3 expression in therapeutic
antibody-bound T cells specifically in the tumour
microenvironment and not systemically; and additional
inhibitory signals through TIM-3 can limit tumour-reactive
T cell function in anti-PD-1-resistant tumours. Although
previous studies have reported the synergistic efficacy of
combinational anti-PD-1 plus anti-TIM-3 treatment in
xenograft and carcinogen-induced tumour models31, we provide
here the first evidence showing the efficacy of TIM-3 blockade
following anti-PD-1 therapy failure in genetically engineered
mouse model in the context of adaptive resistance, which
reproduces a more clinically relevant situation as demonstrated
by our two case vignettes1,32.
Interestingly, surgically resected human tumour samples show
that TIM-3 expression varies even in PD-1-high T cells in
treatment naive patients. This may suggest that expression of
immune checkpoints beyond PD-1:PD-L1 is important in
determining response to anti-PD-1 therapy. Given that only a
minority of lung cancer patients respond to anti-PD-1 (ref. 12), it
would be of interest to correlate expression of other checkpoints
at the time of treatment initiation with response to PD-1
blockade. Although we report no benefit in the EGFR TL mouse
model of concurrent PD-1 plus TIM-3 blockade, we would
caution against extrapolation of this result to human lung cancer
given that this model expresses scant TIM-3 before PD-1
treatment and develops neutralizing antibodies to therapy
which should not be the case in humans treated with
humanized therapeutic antibodies. Genetically engineered
mouse models are genetically heterogeneous and therefore
unlikely to manifest all of the potential mechanisms associated
with resistance to PD-1 blockade and specifically are not suitable
for the study of immune editing of specific tumour neoantigens or
loss of antigen presentation as potential resistance mechanisms to
anti-PD-1 therapy33, processes which will likely require
evaluation in large cohorts of primary patient specimens.
Our data suggest that targeting specific immune checkpoints
engaged by lung tumours, as identified by flow cytometry and/or
gene expression analysis, may represent a rational approach to the
selection of specific immunotherapy regimens. Given the current
clinical interest in building upon the success of anti-PD-1 therapy
in lung cancer, we feel that direct measurement of multiple
checkpoints could allow for the development of targeted
immunotherapy approaches in selected patients based on direct
analysis of immune checkpoint biomarkers. We also feel that the
specific immune checkpoints engaged will likely be impacted by
cancer therapies, as we observe with TIM-3 and LAG-3
upregulation following PD-1 blockade, and that serial measurements will be necessary to best understand the status of the
tumour immune microenvironment and to aid the selection of
appropriate immunotherapies.
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Our data also suggest, as is well known in the kinase inhibitor
field, that cancers possess the ability to evolve in the face of
immunotherapy and to escape therapy by engaging bypass
pathways. In the cases studied in this report, we observed
upregulation of not only TIM-3 on T cells but Galectin-9 on
tumour cells in the case of Kras mutant tumours, indicating that
resistance to PD-1 therapy can be driven by coordinated
interactions among the tumour and neighbouring immune cells.
When larger cohorts of patient samples are analysed, they will
very likely display heterogeneous patterns of suppressive
mechanisms at the time of resistance, possibly including changes
in the T-cell suppressive cytokines or in myeloid-derived
suppressor cells, compensatory upregulation of additional
immune checkpoints as seen here or immune editing in tumour
cell populations. Understanding the dynamics and diversity of
these mechanisms will identify therapeutic strategies that can
prolong the efficacy of immunotherapy and thereby improve
patient outcomes.
Methods
Mouse treatment studies. EGFR transgenic mice carrying tetracycline-inducible
human EGFR cDNA were previously generated34. L858R T790M mutation was
generated by site-directed mutagenesis of the pCIBA-hEGFR plasmid. The
fragment containing the whole hEGFR ORF with the Kozak site was then
subcloned into pTRE2-hyg (Clon- tech, Mountain View, CA). The constructs were
then digested to release the entire allele containing Tet-op-EGFR TL-b-globin
polyA. Transgenic mice were then generated by injection of the construct into
FVB/N blastocysts. EGFR mutant mice were crossed with CC10-RTTA mice
expressing reverse tetracycline activator from the lung Clara cell CC10 promoter,
and maintained in mixed background. Double-positive (EGFR and CC10 RTTA)
progeny were fed with a doxycycline diet starting at 5–6 weeks of age for the
induction of tumours and maintained on doxycycline throughout the study.
Kras G12D mice were given adenovirus expressing Cre recombinase (5 106 titre)
intranasally at 5 weeks of age for induction of recombination and tumour
formation35. All the mice were maintained on a mixed (C57Bl/6, FVB and S129)
background. The mice were euthanized when they reached tumour burden
euthanasia criteria determined by health condition as evaluated by veterinary
technicians upon twice daily health checks. TIM-3 antibody was added to the
treatment regimen when mice displayed clinical signs of progressive disease, which
was confirmed by MRI. All breedings and in vivo experiments were performed with
the approval of the DFCI Animal Care and Use Committee. MRI imaging was
performed using the 7 Tesla (BioSpec: Bruker BioSpin) MRI. Tumour volume
quantifications were performed using the 3D-Slicer software. PD-1-blocking
antibody (clone 29F.1A12), TIM-3-blocking antibody (clone RMT3–23: Bio X cell)
and their isotype controls (clone 2A3: Bio X cell) were injected intraperitoneally
into the mice for therapeutic treatment (three times a week, 200 mg for PD1 and
100 mg for TIM-3 per dose).
Patient sample collection. Anonymized patient samples were obtained under IRB
approved protocols 02–180 and 11–104 and BIDMC 2001-P-001089 from subjects
providing informed consent for tissue collection. Biopsies and effusions were
obtained during routine clinical procedures. All human subjects research was
performed in accordance with the above protocols approved by the Institutional
Review Boards at the Dana-Farber Cancer Institute and Beth Israel Deaconess
Medical Center.
Immune analysis for patient and mouse samples. Murine tumour and immune
cell characterization was performed as previously described17 and detailed in
Supplementary Methods. The processing for freshly resected patient lung tumour
samples was performed similarly. For freshly collected effusion samples, the cells
were treated with RBC lysis after spin and directly used for staining after cell
screening (70 mm). Isolated cells were stained with LIVE/DEAD fixable dead cell
stain kit (Invitrogen) before surface marker staining. The antibodies used for
immune analysis are listed in the Supplementary Appendix. For counting absolute
numbers of immune cell populations, AccuCheck Counting Beads (Molecular
probes) were used according to the manufacturer’s protocol. For detecting anti
PD-1 antibody binding, Rabbit anti human IgG/Rabbit isotype control IgG
(SouthernBiotech) and secondary Goat anti Rabbit IgG (SouthernBiotech) for
human and anti Rat IgG2a (r2a-21B2: eBioscience) for mice were used without
prior Fc blocking (Miltenyi Biotech and BD Biosciences), which was used for all the
other staining. All antibodies were used at 1:50 dilution. For intracellular cytokine
staining, total tumour-bearing lung cells were fractionated over cell separation
media, OptiPrep (Sigma) and buffered saline with Tricine (Sigma) as per the
manufacturer’s instructions (Axis-Shield, Application Sheet C43). Isolated
mononuclear cells were stimulated with 50 ng ml 1 PMA (Sigma) and
8
500 ng ml 1 Ionomycin (Sigma) for 4 h in the presence of Golgi plug
(BD Biosciences). Fixation/permeabilization buffers (eBioscience) or BD
Cytofix/Cytoperm buffers (BD Biosciences) were used for both mice and human
samples for intracellular staining. Acquisition of eight colour samples was
performed on a BD Canto II cytometer equipped with Diva software and analysed
using Flowjo. Antibody clone numbers for mouse are provided in Supplementary
Table 1 and for human in Supplementary Table 2.
Tumour-infiltrating T-cell sorting and RNA sequencing. Sorting of
tumour-infiltrating T cells (CD45 þ TCRb þ CD11b CD11c CD19 DX5
TER119 Ly6G ) and tumour cells (enriched epithelial cell population: CD45
EpCAM þ was utilized as tumour cells) was performed on a BD FACSAria II cell
sorter. The gating method for sorting is shown in Supplementary Fig. 8. RNA was
prepared from sorted lymphocyte populations using the Arcturus PicoPure kit
(Life Technologies) and RNA quantified using Ribo-Green (Life Technologies) per
the manufacturer’s protocol. 10 ng of total RNA was used for library preparation
using the Nugen Ovation system (Nugen) as per the manufacturer’s instructions.
Libraries were quantified and analysed using a high-sensitivity DNA chip assay
(Agilent) and by quantitative PCR. Pooled libraries were sequenced on an Illumina
HiSeq instrument to a minimum read depth of 30 million reads. RNA-seq reads
were aligned to the mm9 Ensembl transcript annotation (release 65) using the
PRADA pipeline (10.1093/bioinformatics/btu169), and FPKM expression values
were determined using Cufflinks36 with mm9 RefSeq gene annotations and
subsequently log2-transformed. Expression values of T-cell samples were
normalized to the expression value of Cd3e in each respective sample and tumour
samples were similarly normalized to Epcam. These normalized expression values
of resistant and untreated tumours were used to calculate fold change and input
into the limma package (PMID: 25605792) to calculate P values based on a
moderated t-statistic. Differentially expressed genes were defined as those
with absolute fold change over 1.25 and P value under 0.05. For heatmaps, the
log2-transformed FPKM values were row-scaled and coloured on a blue-red
scale ranging from 2 to 2. Data can be accessed with the BioProject number
PRJNA305565 at the NCBI BioProject database.
Cytokine and chemokine measurements. BALF collection was performed by
injecting 1 ml of PBS into the trachea to inflate the lungs, which were then
aspirated. Collected BALFs and supernatants of effusions were kept at 80° before
performing the ELISA. Cytokine and chemokines were measured with ELISA kits
according to the manufacturer’s protocol; mouse and human IL-6
(BD Biosciences), GRN (R&D Systems) and human Galectin-9 (R&D Systems).
Statistical analysis. All numerical data are shown as mean±s.d. Data were
analysed using two-tailed unpaired Student’s t-test for comparisons of two groups
and one-way analysis of variance with Tukey multiple comparison test for three
groups. Correlation was evaluated using Pearson’s correlation coefficient. P values
for the survival curves have been calculated using a log-rank test.
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Acknowledgements
We thank Dana-Farber flow core facility (Suzan Lazo-Kallanian, John Daley, Kristen
Cowens, Steven Paul) for help with flow cytometry anlaysis, Harvard Medical School
Rodent Pathology Core for tissue processing and Brigham and Women’s Pathology Core
and Mei Zhang for help with tissue stainings, Xiaoen Wang for help with mouse MRI,
and the Dana-Farber Center for Cancer Genome Discovery for RNA sequencing.P.S.H. is
supported by a Clinical Investigator Award from the Damon Runyon Cancer Research
Foundation, a Developmental Project Grant from NCI P50 CA090578 and the Starr
Consortium for Cancer Research. K.-K.W. is supported by NIH/NCI P01 CA120964,
5R01CA163896-04, 1R01CA195740-01, 5R01CA140594-07, 5R01CA122794-10 and
5R01CA166480-04 grants and support from Gross-Loh Family Fund for Lung Cancer
Research and Susan Spooner Family Lung Cancer Research Fund at Dana-Farber
Cancer Institute. S.K. is supported by Margaret A. Cunningham Immune Mechanisms
in Cancer Research Fellowship Award and The Kanae Foundation for the Promotion
of Medical Science Fellowship Award. G.S.H.-S. is supported by the Deutsche
Forschungsgemeinschaft (HE 6897/1-1) and the Claudia Adams Barr Program for
Innovative Cancer Research. G.J.F. is supported by NIH R01AI08995. D.B.C. is
supported by American Cancer Society grant RSG 11-186 and NCI grant CA090578.
P.S.H., K.-K.W. J.A.E. and P.A.J. are supported by a Stand Up To Cancer—American
Cancer Society Lung Cancer Dream Team Translational Research Grant (Grant Number:
SU2C-AACR-DT17-15). Stand Up To Cancer is a programme of the Entertainment
Industry Foundation.
Author contributions
S.K., E.A.A., G.D., K.-K.W. and P.S.H. designed the research studies; S.K., E.A.A., Y.Y.L.
and K.A.B. conducted the experiments and acquired and analysed the data; all the
authors contributed by providing samples and writing and reviewing the manuscript.
Additional information
Accession codes: The RNA-seq data have been deposited in the NCBI BioProject
database under accession code PRJNA305565.
Supplementary Information accompanies this paper at http://www.nature.com/
naturecommunications
Competing financial interests: G.D. received sponsored research support from
Bristol-Myers Squibb and Novartis. He is currently an employee of Novartis. F.S.H. is a
Bristol-Myers Squibb nonpaid consultant, Novartis, Merck and Genentech consultant
and receives clinical trial support to the institution from these companies. G.J.F. receives
patent royalties on the PD-1 pathway from Bristol-Myers-Squibb, Roche, Merck,
EMD-Serrono, Boehringer-Ingelheim, Amplimmune/AstraZeneca and Novartis and
patent royalties on the TIM-3 pathway from Novartis. D.B.C. is a consultant for Pfizer.
S.J.R. receives research support from Bristol-Myers Squibb and the Center for Immune
Oncology, DFCI. The remaining authors declare no competing financial interests.
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How to cite this article: Koyama, S. et al. Adaptive resistance to therapeutic PD-1
blockade is associated with upregulation of alternative immune checkpoints.
Nat. Commun. 7:10501 doi: 10.1038/ncomms10501 (2016).
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NATURE COMMUNICATIONS | 7:10501 | DOI: 10.1038/ncomms10501 | www.nature.com/naturecommunications
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