Published OnlineFirst January 16, 2020; DOI: 10.1158/1078-0432.CCR-19-3323
CLINICAL CANCER RESEARCH | REVIEW
Targeting PD-1 or PD-L1 in Metastatic Kidney Cancer:
Combination Therapy in the First-Line Setting
David H. Aggen1, Charles G. Drake2, and Brian I. Rini3
ABSTRACT
◥
Recent FDA approvals of regimens targeting programmed
death 1 (PD-1) in combination with anti-CTLA-4 or with VEGF
tyrosine kinase inhibitors are reshaping front-line therapy for
metastatic kidney cancer. In parallel, therapeutics specific for
programmed death ligand 1 (PD-L1), one of the two major
ligands for PD-1, are under continued investigation. Surprisingly,
not all PD-1 and PD-L1 agents lead to similar clinical outcomes,
potentially due to biological differences in the cellular expression
Introduction
The discovery of programmed death 1 (PD-1) and programmed
death ligand 1 (PD-L1) as a mechanism of peripheral T-cell tolerance
spurred the development of multiple therapeutics blocking their
critical interaction (1). In the context of kidney cancer, the PD-1–
specific therapies nivolumab (2, 3) and pembrolizumab (4), as well as
the PD-L1 antibody avelumab (5) are FDA-approved in combination
with other therapies for metastatic renal cell carcinoma (RCC). In the
past 14 months, four phase III trials have tested the hypothesis that
immunotherapy (I/O)-based combinations are efficacious as first-line
therapy in metastatic RCC (Table 1). Combination therapies based on
anti-PD-1 antibodies, pembrolizumab plus axitinib and nivolumab
plus ipilimumab, have improved overall (OS) relative to sunitinib (3, 4).
In contrast, combination therapies with anti-PD-L1 antibodies including avelumab plus axitinib (Javelin-101; ref. 5) or atezolizumab plus
bevacizumab (ImMotion 151; ref. 6) have not yet demonstrated an
overall survival benefit. Overall survival data in these anti-PD-L1
combination trials are still immature, and ultimately a survival benefit
might be observed with further follow-up. Despite this finding, it is
notable that occasional complete responses were reported with both
anti-PD-1 and anti-PD-L1 combination regimens. Caution should be
exercised in cross-trial comparison due to potential differences in
baseline patient characteristics. However, the OS benefits documented
in anti-PD-1 combination therapy trials, but not in anti-PD-L1
immunotherapy studies, highlights potential advantages to targeting
PD-1 as compared with PD-L1 in specific clinical contexts.
1
Memorial Sloan Kettering Cancer Center, New York, New York. 2Herbert Irving
Cancer Center, New York-Presbyterian/Columbia University Medical Center,
New York, New York. 3Division of Hematology/Oncology, Vanderbilt University
Medical Center, Nashville, Tennessee.
Note: Supplementary data for this article are available at Clinical Cancer
Research Online (http://clincancerres.aacrjournals.org/).
Corresponding Author: David H. Aggen, Memorial Sloan Kettering Cancer
Center, New York, NY 10065. Phone: 646-422-4679; Fax: 646-227-2417; E-mail:
aggend@mskcc.org
Clin Cancer Res 2020;26:2087–95
doi: 10.1158/1078-0432.CCR-19-3323
2020 American Association for Cancer Research.
and regulation of these targets. Here, we review current clinical
data on combination immune checkpoint inhibitor therapy in
metastatic kidney cancer and discuss the relevant biology of PD-1
and PD-L1. The design of future rational combination therapy
trials in metastatic renal cell carcinoma will rely upon an
understanding of this biology, along with an evolving understanding of immune cell populations and their functional states
in the tumor microenvironment.
Observations in other tumor types support the concept of nonequivalence between PD-1 and PD-L1 targeted therapeutics. In bladder cancer, the anti-PD-1 agent pembrolizumab showed an OS benefit
compared with second-line treatment in Keynote-045 (7), whereas the
anti-PD-L1 antibody atezolizumab did not show an OS benefit when
compared with second-line chemotherapy in a similar patient population in the IMVigor211 trial (8). In NSCLC, the anti-PD-1 antibody
pembrolizumab improved OS relative to second-line chemotherapy in
Keynote-010 (9), whereas the anti-PD-L1 antibody avelumab failed to
improve OS in a similar cohort of patients (10). Notwithstanding the
limitations of cross-trial comparisons, the discrepancies in clinical
outcome between PD-1 and PD-L1 antibodies beg a lingering question:
are these therapeutics equivalent?
Fundamental differences in the biologic mechanisms of anti-PD-1
and anti-PD-L1 may underlay these potentially disparate clinical
outcomes; thus, understanding these nuances is critical to the design
of next-generation combinatorial strategies. Herein, we describe some
key distinctions in PD-1 and PD-L1 biology in terms of cell type–
specific expression, differential regulation, and the physiologic effects
of blockade. The relative contribution of antibody directed cell cytotoxicity (ADCC) for PD-L1 therapeutics is also discussed. Finally, we
summarize ongoing clinical activity using these therapeutics in combination regimens.
The PD-1/PD-L1 Interaction Attenuates
a T-Cell Response
T-cell activation is initiated by the engagement of a T-cell receptor
(TCR) with its cognate peptide-MHC complex—along with an appropriate costimulatory signal (Signal 2). In this setting, the primary
biologic function of PD-1 is to maintain a desirable range of T-cell
activation so as to prevent rampant autoimmunity (11). Upon T-cell
activation, PD-1 is upregulated within 12 to 36 hours and its interaction with PD-L1 and/or PD-L2 downmodulates T-cell proliferation
and effector function (Fig. 1; ref. 12). Biochemically, PD-1 binding to
either PD-L1 or PD-L2 (13) activates the tyrosine phosphatase SHP-2
in the PD-1–expressing cell; this directly dampens T-cell activation by
dephosphorylating the TCR and costimulatory molecules like
CD28 (14). In the setting of chronic antigen stimulation, PD-1
preserves T-cell clones that might otherwise undergo activationinduced cell death. As a consequence of its biology, PD-1 expression
is both a marker of initial T-cell activation as well as a marker of several
AACRJournals.org | 2087
Downloaded from clincancerres.aacrjournals.org on January 13, 2022. © 2020 American Association for Cancer Research.
Published OnlineFirst January 16, 2020; DOI: 10.1158/1078-0432.CCR-19-3323
Aggen et al.
Table 1. Summary of completed phase III trials in metastatic RCC evaluating combination immune therapies.
Trial
N
PD-L1þ (%)a
PD-L1 assay/cutoff
Risk category
Favorable
Intermediate
Poor
Liver metastases (%)
Median follow-up (months)
ORRb
CRb
PFS (months)
Combination arm
Sunitinib arm
HR (CI)
OS (months)
Combination arm
Sunitinib arm
HR (CI)
Nivolumab þ Ipilimumab
Pembrolizumab þ Axitinib Avelumab þ Axitinib
Atezolizumab þ Bevacizumab
CheckMate 214
1,096
23.0%
Dako 28-8 (1% TC)
Keynote 426
861
59.3%
Dako 22C-3 (CPS 1%)
Javelin 101
1,096
61.0%
Ventana SP263 (1% IC)
ImMotion 151
915
40.0%
Ventana SP-142 (>1% IC)
23.0%
61.0%
17.0%
24.5%
32.4
41.0%
11.0%
31.9%
55.1%
13.0%
15.0%
12.8
59.3%
5.8%
21.3%
61.3%
16.3%
NR
12.0
51.4%
3.4%
20.0%
69.0%
12.0%
17.0%
24.0
37.0%
5.0%
9.7
15.1
9.7
11.1
0.85 (95.0% CI, 0.73–0.98) 0.69 (95% CI, 0.57–0.84)
13.8
11.2
8.4
8.4
0.69 (95.0% CI, 0.56–0.84) 0.83 (95.0% CI, 0.70–0.97)
NR
37.9
0.71 (95.0% CI, 0.59–0.86)
NR
NR
0.78 (95% CI, 0.55–1.08)
NR
NR
0.53 (95% CI, 0.38–0.74)
33.6
34.9
0.93 (95% CI, 0.76–1.14)
Note: HR with statistically significant confidence intervals are in bold.
Abbreviations: CPS, combined positive score calculated as the number of (total PD-L1 þ TC and IC)/divided by total number of TC x 100; IC, immune Cells; NR, not
reported; TC, tumor cells.
a
Percent PD-L1 positive in combination I/O arm. PD-L1 cutoff and compartment evaluated differs in each trial.
b
ORR and CR rate in combination I/O arm.
states of functional exhaustion. Those states are defined in part by the
coexpression of additional immune checkpoint molecules like LAG-3
and TIM-3 (15). Consequently, not all PD-1–expressing T cells behave
as functionally exhausted T cells, and additional cell surface markers
and epigenetic signatures are required to more completely define
immune cell subsets with diminished effector capacity (recently
reviewed in detail; ref. 16).
PD-1 and PD-L1 Protein Expression:
Shared but Distinct Cellular
Compartments
In general, PD-1 is expressed on activated/exhausted CD8 and CD4
T cells, although expression has been reported on a number of other
populations including B cells and macrophages (17). PD-L1 may be
expressed on both tumor cells or other cells in the TME, including
dendritic cells, macrophages, and other myeloid populations (18).
Controversy exists regarding the most important PD-L1 expressing
population—with some studies suggesting that tumor expression is
most critical (19, 20) and other studies highlighting expression on
myeloid populations (21, 22). The second major PD-1 ligand, PD-L2,
has a more restricted expression pattern with predominant expression
on endothelial cells, monocytes, and dendritic cells. In a study evaluating PD-L2 expression in seven distinct tumor types, RCC had
among the lowest level of tumor PD-L2 expression with relatively high
stromal and endothelial cell expression of this ligand (23). The
expression of PD-L2 in the TME is in general under-appreciated,
especially as PD-1 has a higher binding affinity for PD-L2 than for PDL1 (24). Indeed, the potential of PD-L2 to promote T-cell tolerance
provides one potential explanation for the lack of OS benefit with PDL1 combination therapies in kidney cancer.
2088 Clin Cancer Res; 26(9) May 1, 2020
PD-1 and PD-L1 Are Dynamically
Regulated by Cell Extrinsic and Intrinsic
Factors
As described above, PD-1 expression is initiated by T-cell
activation. Expression is further modulated by a number of signals
in the TME including TGFb (25), and IFNa, which promote
upregulation of PD-1 on both T cells and macrophages (26).
PD-1 biology is somewhat complex, with at least 10 transcriptional
factor complexes that function in modulating PD-1 activity dependent on the state of T-cell activation (reviewed in detail elsewhere;
ref. 27). In acute infection, antigen clearance leads to eventual
downregulation of PD-1, whereas in the context of cancer and
chronic viral infection persistent antigen exposure drives continued
PD-1 expression on antigen-specific T cells (28).
PD-L1 expression on immune and tumor cell subsets is largely
induced by TH1 cytokines like IFNg. Following IFNg exposure,
tumor and immune cells upregulate PD-L1 through a transcriptional program involving the JAK1/STAT signaling pathway (29).
Clinically, this is important, because mutations in the JAK/STAT
pathway and antigen presentation machinery have been implicated
in primary and acquired resistance to PD-1 therapy in melanoma (30). At the genomic level, copy-number alterations (CNA) in
the PD-L1 gene in tumor cells may also lead to increased levels of
PD-L1 expression. CNA in PD-L1 at chromosome 9p24 are associated with increased tumor mutation burden (31) and are enriched
in a rare but unique RCC subset with sarcomatoid pathologic
features (32). The latter is of keen interest as gene signatures
associated with sarcomatoid RCC pathology were enriched in
patients responding to atezolizumab and bevacizumab in IMMotion
151 (33). Subgroup analysis of patients with sarcomatoid pathologic
features from Checkmate 214 (nivolumab þ ipilimumab; ref. 34)
CLINICAL CANCER RESEARCH
Downloaded from clincancerres.aacrjournals.org on January 13, 2022. © 2020 American Association for Cancer Research.
Published OnlineFirst January 16, 2020; DOI: 10.1158/1078-0432.CCR-19-3323
Combination PD-1 and PD-L1 Immunotherapy for Kidney Cancer
CD8 T cell
PD-L2
TAM
DC
PD-1
TCR
VEGF
PepMHC
B7.1/2
CTLA4
Anti-CTLA4
lpilimumab
Tremelimumab
Anti-PD-1
Pembrolizumab
Nivolumab
Spartalizumab
PD-1
B7.1/2
CD28
PD-L1
Anti-PD-L1
Avelumab
Atezolizumab
Durvalumab
Pep
MHC
TCR
CD4
Tumor
cell
VEGF
Bevacizumab
VEGF TKIs
Axitinib
Cabozantinib
Sunitinib
Pazopanib
Tivozanib
Sitravatinib
Lenvatinib
Figure 1.
PD-1/PD-L1 targeted therapeutics in renal cell carcinoma. Overview of current immunotherapy targets in renal cell carcinoma. The PD-1 antibodies pembrolizumab,
nivolumab, and spartalizumab prevent interaction with PD-L1 and PD-L2. In contrast, the PD-L1 antibodies avelumab, atezolizumab, and durvalumab prevent PD1
ligation, but leave PD-1 and PD-L2 ligation unopposed.
and Keynote 426 (pembrolizumab þ axitinib; ref. 35) also demonstrated improved ORR and OS relative to sunitinib.
Additional tumor intrinsic factors may also drive PD-L1 expression
to promote immune tolerance and tumor immune evasion. In clear cell
RCC, HIF2a activation secondary to Von Hippel Landau (VHL)
deficiency promotes PD-L1 expression in vitro (36, 37). However,
clinical data supporting this association are not yet available. VHL
inactivation is estimated to occur in >90% of patients with RCC either
through direct mutation or promoter hyper-methylation, and one
would anticipate the number of PD-L1 expressing tumor samples in
RCC would be dramatically higher if this association were absolute (38). For example, in Checkmate 214, only 20% to 30% of patients
with RCC had PD-L1 positive tumor cells (3). Similarly, in the
COMPARZ trial evaluating pazopanib versus sunitinib, 36% of
patients had PD-L1–positive specimens (39). As a consequence, the
association between PD-L1 expression and VHL deficiency certainly
requires additional investigation.
Metabolic and Epigenetic Programs
Modulated by the PD-1/PD-L1 Axis
PD-1 ligation with PD-L1 or PD-L2 induces T cell functional
exhaustion by causing distinct metabolic changes within the T cell.
PD-1 binding switches the T cell energy source to fatty acid oxidation
AACRJournals.org
with concomitant attenuation of glycolysis (40). This metabolic switch
assists in determination of T cell effector versus memory cell fates and
promotes the maintenance of functional CD8 exhaustion. Similarly,
attenuation of glycolysis in CD4 T cells, which may or may not be
independent of PD-1 signaling, promotes regulatory T cell commitment (41). Thus PD-1 and additional costimulatory molecules, such as
4-1BB, are implicated in driving immune cell metabolic programs that
lead to T cell dysfunction.
Ongoing PD-1 engagement with its cognate ligands also results in
epigenetic reprogramming of T cells, which may prevent effective
rescue by immune checkpoint blockade. These observations were
initially based on murine studies utilizing the LCMV virus that mimics
chronic antigen stimulation as is observed in cancerous states (42). In
LCMV murine models, functionally exhausted T-cell remained in a
PD-1HI exhausted state even after clearance of antigen, demonstrating
that epigenetic mechanisms likely underlie long-lived functional
exhaustion and PD-1 expression (43).
More recent data suggest that distinct epigenetic profiles define
states of functional T-cell exhaustion (16). Elegant work identified
the nuclear transcription factor TOX as a central regulator of
epigenetic and transcriptional programs driving T-cell exhaustion (44, 45). TOX expression increases following chronic antigen
stimulation, leading to a decrease in markers of self-renewal in T
cells—including the key transcription factor TCF1 (46). Conversely,
Clin Cancer Res; 26(9) May 1, 2020
Downloaded from clincancerres.aacrjournals.org on January 13, 2022. © 2020 American Association for Cancer Research.
2089
Published OnlineFirst January 16, 2020; DOI: 10.1158/1078-0432.CCR-19-3323
Aggen et al.
deletion of TOX restored CD8 T-cell function and differentiation to
effector and memory phenotypes. Taken together, these studies
show that that TOX is a critical driver of early T-cell exhaustion.
Advancements in single-cell analysis (47) and epigenetic profiling
will be critical in further defining the functional and phenotypic
heterogeneity within these exhausted states, and clinical interventions aimed at altering the epigenetic phenotype of T cells remains
an area of active interest (48–50).
Functional Consequences of
PD-1/PD-L1 Blockade in the Clinic
Anti-PD-1 agents can restore the functionality of exhausted T
cells through direct ligation of PD-1 on CD4 and CD8 T lymphocytes, and based on that principle may rescue an immune response
relatively independent of tumor PD-L1 expression (Fig. 2A). Direct
T-cell binding by an anti-PD-1 therapeutic may afford significant
advantages relative to an anti-PD-L1 treatment, potentially via
more rapid T-cell expansion. In patients with melanoma treated
with anti-PD-1, peripheral blood profiling showed that expansion
of a PD-1þ effector T-cell pool after immune checkpoint blockade
correlated with clinical response (51). Relevant neoadjuvant studies
illustrate peripheral occupancy of PD-1, with peripheral blood
responses detected within 3 weeks on therapy (52). Peripheral
blood profiling also shows that anti-PD-1 therapeutics rapidly
stimulate T cells in the periphery, enabling tumor cell lysis,
relatively independent of tumor volume/burden. The kinetics of
T-cell expansion mediated by direct engagement of PD-1 on
effector T cells may not be achievable with anti-PD-L1 agents
A Prevents PD-L1 interaction
B Prevents PD-1 interaction
targeting tumor and immune cells. With adoption of immunotherapy into the neoadjuvant setting in clinical trials of kidney cancer
including PROSPER-RCC (53), we will gain further insights into
the mechanistic and kinetic differences in PD-1 and PD-L1 occupancy and immune blockade. Similarly, adjuvant trials for high-risk
RCC evaluating atezolizumab (NCT03024996) and pembrolizumab
(NCT03142334) have completed accrual, and peripheral blood
studies from these trials will enhance our understanding of the
relative benefit of perioperative PD-L1 and PD-1 blockade.
PD-L1–targeted therapies, in contrast, can induce immune
tumor rejection through multiple mechanisms (summarized
in Fig. 2B–D). First, anti-PD-L1 therapies prevent ligation with
PD-1 on immune cells like anti-PD-1 therapeutics. PD-L1 blockade
also prevents ligation with the costimulatory molecule B7.1 (CD80)
either in cis or in trans, which may provide a secondary mechanism
for T-cell reinvigoration (54). Second, anti-PD-L1 therapeutics may
also drive direct tumor cell killing through antibody-dependent
cellular cytotoxicity (ADCC), in this case via PD-L1 expressed on
tumor cells (Fig. 2C). In murine models, anti-PD-L1 that bind Fc
receptors that mediate ADCC led to tumor regression, whereas a
similar effect was not observed with anti-PD-1 therapies in those
models (55).
Despite these theoretical advantages, there are now two randomized
phase III trials in metastatic RCC using anti-PD-L1 therapeutics that
have not yet shown an OS benefit (Table 2). OS data in these trials is
still immature and longer follow-up is awaited. Although the mechanisms underlying this difference may be challenging to dissect, one
possibility is that interaction between PD-1 and PD-L2 is unaffected by
PD-L1 blockade, such that interactions between PD-L2 in the TME
C ADCC on tumor cell
PD-1 Blockade
Direct T-cell engagement
Direct tumor engagement
= Anti-PD-1
T cell
D ADCC on immune cell
PD-L1 blockade
Direct tumor engagement
= Anti-PD-L1
T cell
Direct T-cell engagement
= Anti-PD-L1
= Anti-PD-L1
TAM
B7.1
(CD80)
PD-1
TCR
pep
MHC
PD-1
PD-L2
PD-L1
DC
Tumor
cell
• Allows metabolic and
epigenetic reprogramming
of T cells
• Blocks interaction between
PD-1 and PD-L1/PD-L2
TCR
pep
MHC
PD-1
PD-L1
TAM
Fc
receptor
PD-1
PD-L2
DC
Tumor
cell
• Blocks interaction with PD-1 on
immunocytes and B7.1 (CD80)
• Does not interact directly with T
cells
Lytic enzymes
Peforin
Granzymes
TNF
pep
MHC
Fc
receptor
TCR
Lytic enzymes
Peforin
Granzymes
TNF
PD-L1
T cell
Tumor
cell
• Anti-PD-L1 binds to tumor
cells expressing PD-L1
• Tumor cell killing via Fc-receptor
mediated antibody-dependent
cellular cytotoxicity
• Anti-PD-L1 binds to immune
cells expressing PD-L1
• Potential for immune cell
killing and depletion of either
immunosuppressive cells (M2like TAMs, MDSCs)
Figure 2.
Mechanisms of PD-1 and PD-L1 targeting immunotherapy. A, PD-1 blockade exerts direct effects on immune cells upon ligation by driving distinct metabolic and
epigenetic programs that reverse T-cell dysfunction. B, PD-L1 blockade on immune cells masks PD-1 ligation. PD-1 can bind PD-L2. C, ADCC from PD-L1 ligation on
tumor cells permits tumor cell killing. D, PD-L1 expression on T cells permits ADCC of immune cells overexpressing PD-L1.
2090 Clin Cancer Res; 26(9) May 1, 2020
CLINICAL CANCER RESEARCH
Downloaded from clincancerres.aacrjournals.org on January 13, 2022. © 2020 American Association for Cancer Research.
Published OnlineFirst January 16, 2020; DOI: 10.1158/1078-0432.CCR-19-3323
Combination PD-1 and PD-L1 Immunotherapy for Kidney Cancer
Table 2. Prospects and limitations of anti-PD-1 and anti-PD-L1 immunotherapies for combination therapy in RCC.
Advantages
Anti-PD-1
*
*
*
*
Anti-PD-L1
*
*
*
Targets T cells directly
Distinct metabolic and epigenetic changes upon PD-1
binding reverse T-cell exhaustion
Does not require tumor PD-L1 expression for activity
PD-1 occupancy on T cells observed within 3 weeks on
treatment
Targets tumor cells directly
May permit ADCC of tumor cells
May also target immunosuppressive TAMs that express PDL1 in the TME
Disadvantages
*
*
*
*
*
*
*
*
and PD-1 on T cells provides some level of ongoing suppression. A
second theoretical concern involves binding to nontumor cell expressing isoforms of PD-L1, sequestering antibody that might be important
in blocking the PD-1/PD-L1 interaction. Accordingly, relevant data
suggest that PD-L1 expression on exosomes (56) and secreted variants
of PD-L1 (57) may suppress anti-PD-L1 responses. A final potential
mechanism of interest is that expression of PD-L1 on immune cells
might deplete immune effector cells through ADCC in certain circumstances (Fig. 2D, reviewed below).
Antibody Isotype Effects on Clinical
Activity
An underappreciated aspect of immune checkpoint blockade is
the relative contribution of T-cell–mediated tumor killing versus
the potential for ADCC or complement-dependent cytotoxicity. In
ADCC, FC gamma receptors (primarily FcgRIII) on the surface of
macrophages and NK cells bind to the Fc portion of antibodies
resulting in depletion of tumor or subsets of immune cells (Fig. 2C
and D). Specific IgG subtypes are more likely to promote ADCC,
with IgG1 and IgG3 antibody subtypes with a higher binding
affinity for Fc receptors (Supplementary Table S1; ref. 58). Thus,
anti-PD-L1 antibodies of the IgG1 isotype may lead to depletion of
both tumor and immune cells. Indeed, avelumab, an IgG1 isotype
antibody, can mediate ADCC and lead to effective direct tumor cell
killing. In theory, ADCC can also occur on PD-L1–positive CD8
effector cells leading to elimination of immune effectors. However,
no definitive evidence of the latter phenomena has been appreciated
clinically. Importantly, recently presented subgroup analysis from
the Javelin-101 showed no difference in activity of combination
avelumab plus axitinib treatment in patients with FcgRIII polymorphisms, demonstrating that ADCC may be only a minor
mechanism in anti-PD-L1 immunotherapy (59).
Ongoing efforts are focused on improving the efficiency of antibody-induced cellular cytotoxicity with immune checkpoint blockade
antibodies. Through modification of glycosylation and fucosylation
sites, antibodies can be engineered to have differential effects on ADCC
and cellular depletion (60). To promote ADCC, an Fc-modified (nonfucosylated version) of anti-CTLA-4 is in early-phase clinical trials
with the goal of regulatory T-cell depletion (NCT#03110107). Future
AACRJournals.org
No direct tumor effects from antibody
In vitro VEGF TKIs increase PD-1 expression on immune cells providing a
potential resistance mechanism
Does not block PD-1 binding to PD-L2
PD-L1 exists on exosomes and in soluble forms which may act as a “decoy”
receptor for antibody therapy
VEGF TKI treatment permits PD-L1 upregulation on tumor cells providing a
potential resistance mechanism
Limited engagement of anti-PD-L1 with PD-L1þ tumor T cells allows for
continued T cell dysfunction
Potential for ADCC and elimination of PD-L1þ positive immune cells subsets
(NK cells, DCs, antitumor TAM)
Kinetics of PD-L1 occupancy are not yet defined and complete saturation to
block PD-1 ligation may not be possible
immunotherapy combination approaches may leverage the ability to
selectively deplete immunosuppressive cell subsets and potentiate
antitumor responses.
PD-1 Versus PD-L1 in Combination with
VEGF TKIs
In RCC, the addition of a VEGF TKI to an anti-PD-1 or PD-L1
antibody exploits a number of potentially synergistic mechanisms.
VEGF in the tumor ecosystem promotes immunosuppression
by decreasing T-cell trafficking to tumors, increasing immunosuppressive cytokines and initially increasing regulatory T cells. Treatment with anti-angiogenic therapies mitigates a number of the
immunosuppressive effects of VEGF in preclinical models (61, 62).
For example, the use of sunitinib in a preclinical RCC model
decreases immunosuppressive myeloid-derived suppressor cells
(MDSC), a potential mechanism of adaptive immune resistance to
PD-1 immunotherapy (63). More recent preclinical data with
axitinib showed antitumor efficacy not only through vascular
remodeling but also through depletion of tumor-promoting mast
cells and tumor-associated macrophages (64). In human RCC
specimens, treatment with antiangiogenic therapy increased infiltration of CD4 and CD8 effector T cells, supporting the hypothesis
that VEGF inhibition might potentiate the response to immune
checkpoint blockade by promoting T-cell infiltration (65). Clearly,
the immune effects of VEGF TKIs support nonredundant mechanisms of immune activation distinct from the PD1/PD-L1 axis,
with TKI immune remodeling affecting the myeloid and T-cell
compartment.
Although the MDSC-specific effects of TKIs provide a good rationale for combining anti-PD-L1 with VEGF therapy, there are
some data suggesting that VEGF TKIs may dampen a T-cell response
to cancer. Chronic inhibition of VEGF with TKIs can induce a hypoxic
state within the TME with a concomitant accumulation of HIF1a (66).
Multiple studies show that HIF1a accumulation induces a compensatory immunosuppressive state through recruitment of MDSCs (67),
tumor-associated macrophages (68, 69), and Tregs (70). In addition,
accumulation of HIF1a alters PD-L1 expression on immune
cell subsets (71). That observation is supported by data from human
RCC samples showing that TKIs may decrease PD-L1 expression,
Clin Cancer Res; 26(9) May 1, 2020
Downloaded from clincancerres.aacrjournals.org on January 13, 2022. © 2020 American Association for Cancer Research.
2091
Published OnlineFirst January 16, 2020; DOI: 10.1158/1078-0432.CCR-19-3323
Aggen et al.
rendering anti-PD-L1 blockade more challenging. Of note, ontreatment biopsies from patients treated with pazopanib or sunitinib
showed transient decreases in PD-L1 expression by IHC (72).
In some model systems, VEGF TKIs also decrease immune cell PD1 expression (73). The decrease in PD-1 expression, however, is not
absolute, and blockade of remaining PD-1 on T cells with anti-PD-1
therapeutics may explain the improved OS noted with combination
anti-PD-1 with VEGF TKIs. Taken together, these collected observations lend support to a hypothesis that limited or intermittent VEGF
TKI therapy in combination regimens might allow an even greater
immune response, but at present all TKI combinations in the phase III
setting have been taken continuously. Further, HIF1 inhibition may be
a therapeutic approach to enhance the clinical benefit of VEGF TKIbased combinations.
Consensus First-Line Therapy
Approaches in Metastatic RCC
Both nivolumab plus ipilimumab and pembrolizumab plus axitinib
are now consensus first-line treatments for metastatic RCC. At present,
the choice of first-line therapy for a given patient is not driven by a
randomized, comparative trial, but rather by treatment side-effect
profile, prognostic risk group, perceived benefits of complete and
overall response rate and MD/patient preference. Avelumab plus
axitinib is also FDA approved for first-line RCC, but so far, an OS
benefit relative to sunitinib has not been documented. Finally, the FDA
application for drug approval of atezolizumab plus bevacizumab was
withdrawn by the manufacturer, although there may in fact be
subgroups of patients with specific gene signatures that benefit from
Table 3. On-going immunotherapy trials in RCC.
Therapy
First-line metastatic RCC trials
Pembrolizumab þ Lenvatinib or Everolimus þ Lenvatinib vs. Sunitinib (CLEAR)
Nivolumab þ Ipilimumab Followed by Nivolumab Cabozantinib (PDIGREE)
Nivolumab þ Ipilimumab Cabozantinib (COSMIC-313)
Nivolumab þ Cabozantinib vs. Sunitinib
Nivolumab þ bempegaldesleukin (CD122 agonist) vs. Cabozantinib or Sunitinib
Nivolumab þ Ipilimumab vs. Nivo/IDO vs. Nivo/Anti-Lag3 (Relatlimab) vs.
Nivolumab þ CCR2/CCR5 dual agonist (BMS936558) FRACTION-RCC
Nivolumab þ Cabozantinib Ipilimumab
Nivolumab þ Ipilimumab or Pazopanib or Sunitinib (BIONIKK Biomarker Guided Trial)
Nivolumab with Salvage Nivolumab þ Ipilimumab
Nivolumab þ Bempegaldesleukin (CD122 agonist) Ipilimumab
Pembrolizumab þ Cabozantinib
Advanced (second-line or later) metastatic RCC trials
Arginase Inhibitor (INCB001158) þ Pembrolizumab
TLR 7/8 agonist (NKTR 262) þ bempegaldesleukin Nivolumab
Anti-CD73 (CPI-006) A2AR Antagonist or Pembrolizumab
Glutaminase Inhibitor (CB-839) þ Nivolumab
Anti-TIM3 (MBG453) Spartalizumab (Anti-PD1)
Durvalumab Tremelimumab or Savolitinib
ApoE Agonist (RGX104) þ Nivolumab
Anti-CSF1R (Cabiralizumab) þ Anti-CD40 (APX005M) Nivolumab
HIF-2a Inhibitor (PT2977) þ Cabozantinib
Axitinib þ Nivolumab
Sitravatinib þ Nivolumab
Angiopoietin-2 inhibitor (Trebananib) þ Pembrolizumab
Anti-IL1b (Gevokizumab) þ Cabozantinib
Guadecitabine þ Durvalumab
177Lu-J591 Anti-PSMA Radiolabeled Antibody
Anti-CD25 pyrrolobenzodiazepine toxin conjugate (Camidanlumab Tesirine)
IL-2 (Aldesleukin) þ Pembrolizumab
Perioperative (neoadjuvant RCC trials)
Nivolumab – PROSPER RCC
MSKCC
Royal Marsden
Avelumab þ Axitinib
Durvalumab Tremelimumab
Nivolumab þ Sitravatinib
Anti-IL1b (Canakinumab) þ Spartalizumab (anti-PD1)
Adjuvant RCC immunotherapy trials
Durvalumab vs. Durvalumab/Tremelimumab vs. Observation
Pembrolizumab vs. Observation
Nivolumab þ Ipilimumab vs. Observation
Atezolizumab vs. Observation
2092 Clin Cancer Res; 26(9) May 1, 2020
Number
Phase
Trial ID
Estimated
completion date
1,050
1,046
676
638
600
200
III
III
III
III
III
Ib/II
NCT02811861
NCT03793166
NCT03937219
NCT03141177
NCT03729245
NCT02996110
February 2021
September 2021
November 2021
May 2024
June 2024
January 2022
152
150
120
90
55
I
II
II
Ib/II
Ib/II
NCT02496208
NCT02960906
NCT03117309
NCT02983045
NCT03149822
Early 2020
May 2020
February 2021
June 2021
June 2020
424
393
378
299
250
195
150
120
118
98
60
60
60
58
50
50
27
Ib/II
Ib/II
Ib/II
Ib/II
Ib/II
II
Ib/II
Ib/II
II
Ib/II
Ib/II
Ib/II
Ib
Ib/II
I
I
I
NCT02903914
NCT03435640
NCT03454451
NCT02771626
NCT02608268
NCT02819596
NCT02922764
NCT03502330
NCT03634540
NCT03172754
NCT03015740
NCT03239145
NCT03798626
NCT03308396
NCT00967577
NCT03621982
NCT03260504
January 2020
December 2023
December 2023
Early 2020
Early 2020
Early 2020
Early 2020
October 2024
September 2022
April 2024
April 2023
August 2024
December 2023
December 2020
December 2019
July 2021
March 2021
805
29
19
40
45
25
14
III
Pilot
Pilot
Pilot
Ib
II
Pilot
NCT03055013
NCT02595918
NCT02446860
NCT03341845
NCT02762006
NCT03680521
NCT04028245
November 2023
August 2020
Late 2019
August 2025
January 2020
December 2019
2021
III
III
III
III
NCT03288532
NCT03142334
NCT03138512
NCT03024996
December 2037
December 2025
July 2023
April 2024
1,750
950
800
778
CLINICAL CANCER RESEARCH
Downloaded from clincancerres.aacrjournals.org on January 13, 2022. © 2020 American Association for Cancer Research.
Published OnlineFirst January 16, 2020; DOI: 10.1158/1078-0432.CCR-19-3323
Combination PD-1 and PD-L1 Immunotherapy for Kidney Cancer
this combination (74). Taken together, these data support the use of a
PD-1–based immunotherapy combination, either with pembrolizumab plus axitinib or nivolumab plus ipilimumab for first-line therapy
of metastatic RCC.
Future Combination Therapy
Approaches for Metastatic RCC
The impressive response rates and OS for patients treated with
combination anti-PD-1 plus anti-CTLA-4 or anti-PD-1 plus VEGF
TKI therapy with a favorable side-effect profile and tolerability begs the
question of utilizing a triplet therapy in the first-line setting (75).
Combination nivolumab, ipilimumab, and cabozantinib has been
administered safely across GU malignancies, and the activity of this
triplet will be tested in a phase II expansion cohort and a randomized,
phase III trial (76). Triplet therapy, however, likely over treats some
patients, such that biomarker-based strategies to select patients for the
appropriate mechanism and intensity of therapy is an unmet need.
One additional combination for first-line treatment, pembrolizumab
þ lenvatinib, is currently being tested in large phase III trials. Table 3
provides a complete listing of trials currently accruing for RCC.
A potential approach to mitigate the toxicities of I/O–I/O combinations is to incorporate other anti-inflammatory medications into the
first-line treatment regimens. To this end, clinical trials are on-going
exploring cytokine targets including anti-IL1b (NCT04028245), antiIL6, and anti-IL8 (NCT03400332; ref. 77) to augment the immune
response and potentially improve regimen tolerability. Another potential approach might be to block TNFa in the combination therapy
setting. A recent publication in animal models highlighted this
approach, demonstrating increased activity of combination immunotherapy when TNFa blockade was added to anti-PD-1 plus antiCTLA-4 (78). The wealth of treatment options available for RCC also
raises the questions of optimal therapeutic sequencing which will be
addressed in an upcoming trial (79). In contemporary cohorts of
patients with metastatic RCC, nearly 50% of patients will not receive a
second line treatment due to either disease progression or declining
performance status (80). In real-world data sets, it is estimated that
>80% of patients do not receive any second-line treatment (80, 81). As
a consequence, maximizing the efficacy of first-line therapy is of
utmost importance.
Conclusions
There are now three FDA-approved combination immunotherapies for the treatment of first-line kidney cancer, but only anti-PD1-based combinations to date have illustrated an OS benefit.
Blockade of PD-1 permits direct reprogramming of T cells, whereas
anti-PD-L1 exerts those effect in an indirect fashion and permits
binding between PD-1 and PD-L2. Although in contemporary
models, the activity of anti-PD-1 þ VEGF TKI appears to be
additive, the remarkable gains in ORR, PFS, and OS will likely
necessitate that anti-PD-1 therapeutics remain the backbone of
first-line treatment for renal cell carcinoma. For the foreseeable
future, the selection of first-line treatment will be guided by sideeffect profile, risk group, and patient preference, whereas the next
generation of first-line therapies may require clinically validated
biomarkers to select the appropriate treatment regimen.
Disclosure of Potential Conflicts of Interest
D.H. Aggen is a paid consultant for Boehringer Ingelheim. C.G. Drake is a paid
consultant for AstraZeneca, Bristol-Myers Squibb, Roche/Genentech, Merck, Novartis, and Pfizer, and reports receiving speakers bureau honoraria from Bristol-Myers
Squibb. B.I. Rini is a paid consultant for Pfizer, Merck, and Bristol-Myers Squibb, and
reports receiving commercial research grants from Pfizer, Merck, Roche, BristolMyers Squibb, and AstraZeneca. No other potential conflicts of interest were
disclosed.
Received October 9, 2019; revised December 6, 2019; accepted January 13, 2020;
published first January 16, 2020.
References
1. Topalian SL, Drake CG, Pardoll DM. Immune checkpoint blockade: a common
denominator approach to cancer therapy. Cancer Cell 2015;27:450–61.
2. Motzer RJ, Escudier B, McDermott DF, George S, Hammers HJ, Srinivas S, et al.
Nivolumab versus everolimus in advanced renal-cell carcinoma. N Engl J Med
2015;373:1803–13.
3. Motzer RJ, Tannir NM, McDermott DF, Aren Frontera O, Melichar B, Choueiri
TK, et al. Nivolumab plus ipilimumab versus sunitinib in advanced renal-cell
carcinoma. N Engl J Med 2018;378:1277–90.
4. Rini BI, Plimack ER, Stus V, Gafanov R, Hawkins R, Nosov D, et al. Pembrolizumab plus axitinib versus sunitinib for advanced renal-cell carcinoma. N Engl
J Med 2019;380:1116–27.
5. Motzer RJ, Penkov K, Haanen J, Rini B, Albiges L, Campbell MT, et al. Avelumab
plus axitinib versus sunitinib for advanced renal-cell carcinoma. N Engl J Med
2019;380:1103–15.
6. Rini BI, Powles T, Atkins MB, Escudier B, McDermott DF, Suarez C, et al.
Atezolizumab plus bevacizumab versus sunitinib in patients with previously
untreated metastatic renal cell carcinoma (IMmotion151): a multicentre, openlabel, phase 3, randomised controlled trial. Lancet 2019;393:2404–15.
7. Bellmunt J, de Wit R, Vaughn DJ, Fradet Y, Lee JL, Fong L, et al. Pembrolizumab
as second-line therapy for advanced urothelial carcinoma. N Engl J Med 2017;
376:1015–26.
8. Powles T, Duran I, van der Heijden MS, Loriot Y, Vogelzang NJ, De Giorgi U,
et al. Atezolizumab versus chemotherapy in patients with platinum-treated
locally advanced or metastatic urothelial carcinoma (IMvigor211): a multicentre,
open-label, phase 3 randomised controlled trial. Lancet 2018;391:748–57.
9. Herbst RS, Baas P, Kim DW, Felip E, Perez-Gracia JL, Han JY, et al. Pembrolizumab versus docetaxel for previously treated, PD-L1-positive, advanced non-
AACRJournals.org
10.
11.
12.
13.
14.
15.
16.
17.
small-cell lung cancer (KEYNOTE-010): a randomised controlled trial. Lancet
2016;387:1540–50.
Barlesi F, Vansteenkiste J, Spigel D, Ishii H, Garassino M, de Marinis F, et al.
Avelumab versus docetaxel in patients with platinum-treated advanced nonsmall-cell lung cancer (JAVELIN Lung 200): an open-label, randomised, phase 3
study. Lancet Oncol 2018;19:1468–79.
Baumeister SH, Freeman GJ, Dranoff G, Sharpe AH. Coinhibitory pathways in
immunotherapy for cancer. Ann Rev Immunol 2016;34:539–73.
Ishida Y, Agata Y, Shibahara K, Honjo T. Induced expression of PD-1, a novel
member of the immunoglobulin gene superfamily, upon programmed cell death.
EMBO J 1992;11:3887–95.
Latchman Y, Wood CR, Chernova T, Chaudhary D, Borde M, Chernova I, et al.
PD-L2 is a second ligand for PD-1 and inhibits T cell activation. Nat Immunol
2001;2:261–8.
Yokosuka T, Takamatsu M, Kobayashi-Imanishi W, Hashimoto-Tane A, Azuma
M, Saito T. Programmed cell death 1 forms negative costimulatory microclusters
that directly inhibit T cell receptor signaling by recruiting phosphatase SHP2.
J Exp Med 2012;209:1201–17.
Woo SR, Turnis ME, Goldberg MV, Bankoti J, Selby M, Nirschl CJ, et al. Immune
inhibitory molecules LAG-3 and PD-1 synergistically regulate T-cell function to
promote tumoral immune escape. Cancer Res 2012;72:917–27.
McLane LM, Abdel-Hakeem MS, Wherry EJ. CD8 T cell exhaustion
during chronic viral infection and cancer. Annu Rev Immunol 2019;37:
457–95.
Gordon SR, Maute RL, Dulken BW, Hutter G, George BM, McCracken MN, et al.
PD-1 expression by tumour-associated macrophages inhibits phagocytosis and
tumor immunity. Nature 2017;545:495–9.
Clin Cancer Res; 26(9) May 1, 2020
Downloaded from clincancerres.aacrjournals.org on January 13, 2022. © 2020 American Association for Cancer Research.
2093
Published OnlineFirst January 16, 2020; DOI: 10.1158/1078-0432.CCR-19-3323
Aggen et al.
18. Noguchi T, Ward JP, Gubin MM, Arthur CD, Lee SH, Hundal J, et al. Temporally
distinct PD-L1 expression by tumor and host cells contributes to immune escape.
Cancer Immunol Res 2017;5:106.
19. Lau J, Cheung J, Navarro A, Lianoglou S, Haley B, Totpal K, et al. Tumor and host
cell PD-L1 is required to mediate suppression of anti-tumour immunity in mice.
Nat Commun 2017;8:14572.
20. Juneja VR, McGuire KA, Manguso RT, LaFleur MW, Collins N, Haining WN,
et al. PD-L1 on tumor cells is sufficient for immune evasion in immunogenic
tumors and inhibits CD8 T cell cytotoxicity. J Exp Med 2017;214:895–904.
21. Lin H, Wei S, Hurt EM, Green MD, Zhao L, Vatan L, et al. Host expression of PDL1 determines efficacy of PD-L1 pathway blockade–mediated tumor regression.
J Clin Invest 2018;128:805–15.
22. Tang H, Liang Y, Anders RA, Taube JM, Qiu X, Mulgaonkar A, et al. PD-L1 on
host cells is essential for PD-L1 blockade–mediated tumor regression. J Clin
Invest 2018;128:580–8.
23. Yearley JH, Gibson C, Yu N, Moon C, Murphy E, Juco J, et al. PD-L2 expression
in human tumors: relevance to anti-PD-1 therapy in cancer. Clin Cancer Res
2017;23:3158–67.
24. Youngnak P, Kozono Y, Kozono H, Iwai H, Otsuki N, Jin H, et al. Differential
binding properties of B7-H1 and B7-DC to programmed death-1.
Biochem Biophys Res Commun 2003;307:672–7.
25. Park BV, Freeman ZT, Ghasemzadeh A, Chattergoon MA, Rutebemberwa A,
Steigner J, et al. TGF-b1-mediated SMAD3 enhances PD-1 expression on
antigen-specific T cells in cancer. Cancer Discov 2016;6:1366–81.
26. Terawaki S, Chikuma S, Shibayama S, Hayashi T, Yoshida T, Okazaki T, et al.
IFN-alpha directly promotes programmed cell death-1 transcription and limits
the duration of T cell-mediated immunity. J Immunol 2011;186:2772–9.
27. Bally APR, Austin JW, Boss JM. Genetic and epigenetic regulation of PD-1
expression. J Immunol 2016;196:2431–7.
28. LaFleur MW, Muroyama Y, Drake CG, Sharpe AH. Inhibitors of the PD-1
pathway in tumor therapy. J Immunol 2018;200:375–83.
29. Garcia-Diaz A, Shin DS, Moreno BH, Saco J, Escuin-Ordinas H, Rodriguez GA,
et al. Interferon receptor signaling pathways regulating PD-L1 and PD-L2
expression. Cell Rep 2017;19:1189–201.
30. Zaretsky JM, Garcia-Diaz A, Shin DS, Escuin-Ordinas H, Hugo W, Hu-Lieskovan S, et al. Mutations associated with acquired resistance to PD-1 blockade in
melanoma. N Engl J Med 2016;375:819–29.
31. Budczies J, Bockmayr M, Denkert C, Klauschen F, Groschel S, Darb-Esfahani S,
et al. Pan-cancer analysis of copy number changes in programmed death-ligand
1 (PD-L1, CD274)—associations with gene expression, mutational load, and
survival. Genes Chromosomes Cancer 2016;55:626–39.
32. Gupta S, Cheville JC, Jungbluth AA, Zhang Y, Zhang L, Chen YB, et al. JAK2/PDL1/PD-L2 (9p24.1) amplifications in renal cell carcinomas with sarcomatoid
transformation: implications for clinical management. Mod Pathol 2019;32:
1344–58.
33. Rini BI, Huseni M, Atkins MB, McDermott DF, Powles TB, Escudier B, et al.
LBA31Molecular correlates differentiate response to atezolizumab (atezo) þ
bevacizumab (bev) vs. sunitinib (sun): results from a phase III study (IMmotion151) in untreated metastatic renal cell carcinoma (mRCC). Ann Oncol 2018;
29(suppl_8): viii724.
34. McDermott DF, Choueiri TK, Motzer RJ, Aren OR, George S, Powles T, et al.
CheckMate 214 post-hoc analyses of nivolumab plus ipilimumab or sunitinib in
IMDC intermediate/poor-risk patients with previously untreated advanced renal
cell carcinoma with sarcomatoid features. J Clin Oncol 2019;37(15_suppl):4513.
35. Rini BI, Plimack ER, Stus V, Gafanov R, Hawkins R, Nosov D, et al. Pembrolizumab (pembro) plus axitinib (axi) versus sunitinib as first-line therapy for
metastatic renal cell carcinoma (mRCC): outcomes in the combined IMDC
intermediate/poor risk and sarcomatoid subgroups of the phase 3 KEYNOTE426 study. J Clin Oncol 2019;37(15_suppl):4500.
36. Ruf M, Moch H, Schraml P. PD-L1 expression is regulated by hypoxia inducible
factor in clear cell renal cell carcinoma. Int J Cancer 2016;139:396–403.
37. Messai Y, Gad S, Noman MZ, Le Teuff G, Couve S, Janji B, et al. Renal cell
carcinoma programmed death-ligand 1, a new direct target of hypoxia-inducible
factor-2 alpha, is regulated by von Hippel-Lindau gene mutation status. Eur Urol
2016;70:623–32.
38. Cancer Genome Atlas Research N. Comprehensive molecular characterization of
clear cell renal cell carcinoma. Nature 2013;499:43–9.
39. Choueiri TK, Figueroa DJ, Fay AP, Signoretti S, Liu Y, Gagnon R, et al.
Correlation of PD-L1 tumor expression and treatment outcomes in patients
with renal cell carcinoma receiving sunitinib or pazopanib: results from COMPARZ, a randomized controlled trial. Clin Cancer Res 2015;21:1071–7.
2094 Clin Cancer Res; 26(9) May 1, 2020
40. Patsoukis N, Bardhan K, Chatterjee P, Sari D, Liu B, Bell LN, et al. PD-1 alters Tcell metabolic reprogramming by inhibiting glycolysis and promoting lipolysis
and fatty acid oxidation. Nat Commun 2015;6:6692.
41. Michalek RD, Gerriets VA, Jacobs SR, Macintyre AN, MacIver NJ, Mason EF,
et al. Cutting edge: distinct glycolytic and lipid oxidative metabolic programs are
essential for effector and regulatory CD4þ T cell subsets. J Immunol 2011;186:
3299–303.
42. Wherry EJ, Ha SJ, Kaech SM, Haining WN, Sarkar S, Kalia V, et al. Molecular
signature of CD8þ T cell exhaustion during chronic viral infection. Immunity
2007;27:670–84.
43. Pauken KE, Sammons MA, Odorizzi PM, Manne S, Godec J, Khan O, et al.
Epigenetic stability of exhausted T cells limits durability of reinvigoration by PD1 blockade. Science 2016;354:1160–5.
44. Scott AC, D€
undar F, Zumbo P, Chandran SS, Klebanoff CA, Shakiba M, et al.
TOX is a critical regulator of tumour-specific T cell differentiation. Nature 2019;
571:270–4.
45. Khan O, Giles JR, McDonald S, Manne S, Ngiow SF, Patel KP, et al. TOX
transcriptionally and epigenetically programs CD8þ T cell exhaustion. Nature
2019;571:211–8.
46. Kratchmarov R, Magun AM, Reiner SL. TCF1 expression marks self-renewing
human CD8(þ) T cells. Blood Adv 2018;2:1685–90.
47. Yao C, Sun H-W, Lacey NE, Ji Y, Moseman EA, Shih H-Y, et al. Single-cell RNAseq reveals TOX as a key regulator of CD8þ T cell persistence in chronic
infection. Nat Immunol 2019;20:890–901.
48. Bengsch B, Ohtani T, Khan O, Setty M, Manne S, O'Brien S, et al. Epigenomicguided mass cytometry profiling reveals disease-specific features of exhausted
CD8 T cells. Immunity 2018;48:1029–45.
49. Miller BC, Sen DR, Al Abosy R, Bi K, Virkud YV, LaFleur MW, et al. Subsets of
exhausted CD8(þ) T cells differentially mediate tumor control and respond to
checkpoint blockade. Nat Immunol 2019;20:326–36.
50. Sen DR, Kaminski J, Barnitz RA, Kurachi M, Gerdemann U, Yates KB, et al. The
epigenetic landscape of T cell exhaustion. Science 2016;354:1165–9.
51. Huang AC, Postow MA, Orlowski RJ, Mick R, Bengsch B, Manne S, et al. T-cell
invigoration to tumor burden ratio associated with anti-PD-1 response. Nature
2017;545:60–5.
52. Huang AC, Orlowski RJ, Xu X, Mick R, George SM, Yan PK, et al. A single dose of
neoadjuvant PD-1 blockade predicts clinical outcomes in resectable melanoma.
Nat Med 2019;25:454–61.
53. Harshman LC, Puligandla M, Haas NB, Allaf M, Drake CG, McDermott DF, et al.
A phase III randomized study comparing perioperative nivolumab vs. observation in patients with localized renal cell carcinoma undergoing nephrectomy
(PROSPER RCC). J Clin Oncol 2017;35(15_suppl):TPS4596.
54. Butte MJ, Keir ME, Phamduy TB, Sharpe AH, Freeman GJ. Programmed death-1
ligand 1 interacts specifically with the B7-1 costimulatory molecule to inhibit T
cell responses. Immunity 2007;27:111–22.
55. Dahan R, Sega E, Engelhardt J, Selby M, Korman Alan J, Ravetch Jeffrey V. FcgRs
modulate the anti-tumor activity of antibodies targeting the PD-1/PD-L1 axis.
Cancer Cell 2015;28:285–95.
56. Poggio M, Hu T, Pai CC, Chu B, Belair CD, Chang A, et al. Suppression of
exosomal PD-L1 induces systemic anti-tumor immunity and memory. Cell 2019;
177:414–27.
57. Gong B, Kiyotani K, Sakata S, Nagano S, Kumehara S, Baba S, et al. Secreted PDL1 variants mediate resistance to PD-L1 blockade therapy in non-small cell lung
cancer. J Exp Med 2019;216:982–1000.
58. Vidarsson G, Dekkers G, Rispens T. IgG subclasses and allotypes: from structure
to effector functions. Front Immunol 2014;5:520.
59. Choueiri TK, Albiges L, Haanen JBAG, Larkin JMG, Uemura M, Pal SK, et al.
Biomarker analyses from JAVELIN Renal 101: avelumab þ axitinib (AþAx)
versus sunitinib (S) in advanced renal cell carcinoma (aRCC). J Clin Oncol 2019;
37(15_suppl):101.
60. O'Connell A, AlDeghaither D, Zahavi D, Weiner LM. Enhancing antibodydependent cell-mediated cytotoxicity: a strategy for improving antibody-based
immunotherapy. Antibody Ther 2018;1:7–12.
61. Ozao-Choy J, Ma G, Kao J, Wang GX, Meseck M, Sung M, et al. The novel role of
tyrosine kinase inhibitor in the reversal of immune suppression and modulation
of tumor microenvironment for immune-based cancer therapies. Cancer Res
2009;69:2514–22.
62. Shrimali RK, Yu Z, Theoret MR, Chinnasamy D, Restifo NP, Rosenberg SA.
Antiangiogenic agents can increase lymphocyte infiltration into tumor and
enhance the effectiveness of adoptive immunotherapy of cancer. Cancer Res
2010;70:6171–80.
CLINICAL CANCER RESEARCH
Downloaded from clincancerres.aacrjournals.org on January 13, 2022. © 2020 American Association for Cancer Research.
Published OnlineFirst January 16, 2020; DOI: 10.1158/1078-0432.CCR-19-3323
Combination PD-1 and PD-L1 Immunotherapy for Kidney Cancer
63. Ko JS, Zea AH, Rini BI, Ireland JL, Elson P, Cohen P, et al. Sunitinib mediates
reversal of myeloid-derived suppressor cell accumulation in renal cell carcinoma
patients. Clin Cancer Res 2009;15:2148–57.
64. Laubli H, Muller P, D'Amico L, Buchi M, Kashyap AS, Zippelius A. The multireceptor inhibitor axitinib reverses tumor-induced immunosuppression and
potentiates treatment with immune-modulatory antibodies in preclinical
murine models. Cancer Immunol Immunother 2018;67:815–24.
65. Liu XD, Hoang A, Zhou L, Kalra S, Yetil A, Sun M, et al. Resistance to
antiangiogenic therapy is associated with an immunosuppressive tumor microenvironment in metastatic renal cell carcinoma. Cancer Immunol Res 2015;3:
1017–29.
66. Bergers G, Hanahan D. Modes of resistance to anti-angiogenic therapy. Nat Rev
Cancer 2008;8:592–603.
67. Corzo CA, Condamine T, Lu L, Cotter MJ, Youn JI, Cheng P, et al. HIF-1alpha
regulates function and differentiation of myeloid-derived suppressor cells in the
tumor microenvironment. J Exp Med 2010;207:2439–53.
68. Doedens AL, Stockmann C, Rubinstein MP, Liao D, Zhang N, DeNardo
DG, et al. Macrophage expression of hypoxia-inducible factor-1 alpha
suppresses T-cell function and promotes tumor progression. Cancer Res
2010;70:7465–75.
69. Imtiyaz HZ, Williams EP, Hickey MM, Patel SA, Durham AC, Yuan LJ,
et al. Hypoxia-inducible factor 2alpha regulates macrophage function in
mouse models of acute and tumor inflammation. J Clin Invest 2010;120:
2699–714.
70. Clambey ET, McNamee EN, Westrich JA, Glover LE, Campbell EL, Jedlicka P,
et al. Hypoxia-inducible factor-1 alpha-dependent induction of FoxP3 drives
regulatory T-cell abundance and function during inflammatory hypoxia of the
mucosa. Proc Natl Acad Sci U S A 2012;109:E2784–93.
71. Noman MZ, Desantis G, Janji B, Hasmim M, Karray S, Dessen P, et al. PD-L1 is a
novel direct target of HIF-1alpha, and its blockade under hypoxia enhanced
MDSC-mediated T cell activation. J Exp Med 2014;211:781–90.
72. Sharpe K, Stewart GD, Mackay A, Van Neste C, Rofe C, Berney D, et al. The effect
of VEGF-targeted therapy on biomarker expression in sequential tissue from
patients with metastatic clear cell renal cancer. Clin Cancer Res 2013;19:6924–34.
AACRJournals.org
73. Voron T, Colussi O, Marcheteau E, Pernot S, Nizard M, Pointet AL, et al. VEGFA modulates expression of inhibitory checkpoints on CD8þ T cells in tumors.
J Exp Med 2015;212:139–48.
74. McDermott DF, Huseni MA, Atkins MB, Motzer RJ, Rini BI, Escudier B, et al.
Clinical activity and molecular correlates of response to atezolizumab alone or in
combination with bevacizumab versus sunitinib in renal cell carcinoma.
Nat Med 2018;24:749–57.
75. Cella D, Grunwald V, Escudier B, Hammers HJ, George S, Nathan P, et al.
Patient-reported outcomes of patients with advanced renal cell carcinoma
treated with nivolumab plus ipilimumab versus sunitinib (CheckMate 214): a
randomised, phase 3 trial. Lancet Oncol 2019;20:297–310.
76. Nadal RM, Mortazavi A, Stein M, Pal SK, Davarpanah NN, Parnes HL, et al.
Results of phase I plus expansion cohorts of cabozantinib (Cabo) plus nivolumab
(Nivo) and CaboNivo plus ipilimumab (Ipi) in patients (pts) with metastatic
urothelial carcinoma (mUC) and other genitourinary (GU) malignancies. J Clin
Oncol 2018;36(6_suppl):515.
77. Bermejo IM, Jaffee EM, Davar D, Cardarelli J, Williams D, Phillips P, et al. Phase
1b/2 study of nivolumab in combination with an anti–IL-8 monoclonal antibody,
BMS-986253, in a biomarker-enriched population of patients with advanced
cancer. J Clin Oncol 2018;36(15_suppl):TPS3109.
78. Perez-Ruiz E, Minute L, Otano I, Alvarez M, Ochoa MC, Belsue V, et al.
Prophylactic TNF blockade uncouples efficacy and toxicity in dual CTLA-4
and PD-1 immunotherapy. Nature 2019;569:428–32.
79. Zhang T, Ballman KV, Choudhury AD, Chen RC, Watt C, Wen Y, et al.
PDIGREE: an adaptive phase 3 trial of PD-inhibitor nivolumab and ipilimumab
(IPI-NIVO) with VEGF TKI cabozantinib (CABO) in metastatic untreated renal
cell cancer (Alliance A031704). J Clin Oncol 2019;37(15_suppl):TPS4596.
80. Motzer RJ, Barrios CH, Kim TM, Falcon S, Cosgriff T, Harker WG, et al. Phase II
randomized trial comparing sequential first-line everolimus and second-line
sunitinib versus first-line sunitinib and second-line everolimus in patients with
metastatic renal cell carcinoma. J Clin Oncol 2014;32:2765–72.
81. Wagstaff J, Jones R, Hawkins R, Porfiri E, Pickering L, Bahl A, et al. Treatment
patterns and clinical outcomes in patients with renal cell carcinoma in the UK:
insights from the RECCORD registry. Ann Oncol 2016;27:159–65.
Clin Cancer Res; 26(9) May 1, 2020
Downloaded from clincancerres.aacrjournals.org on January 13, 2022. © 2020 American Association for Cancer Research.
2095
Published OnlineFirst January 16, 2020; DOI: 10.1158/1078-0432.CCR-19-3323
Targeting PD-1 or PD-L1 in Metastatic Kidney Cancer: Combination
Therapy in the First-Line Setting
David H. Aggen, Charles G. Drake and Brian I. Rini
Clin Cancer Res 2020;26:2087-2095. Published OnlineFirst January 16, 2020.
Updated version
Supplementary
Material
Cited articles
Citing articles
E-mail alerts
Reprints and
Subscriptions
Permissions
Access the most recent version of this article at:
doi:10.1158/1078-0432.CCR-19-3323
Access the most recent supplemental material at:
http://clincancerres.aacrjournals.org/content/suppl/2020/01/16/1078-0432.CCR-19-3323.DC1
This article cites 81 articles, 26 of which you can access for free at:
http://clincancerres.aacrjournals.org/content/26/9/2087.full#ref-list-1
This article has been cited by 3 HighWire-hosted articles. Access the articles at:
http://clincancerres.aacrjournals.org/content/26/9/2087.full#related-urls
Sign up to receive free email-alerts related to this article or journal.
To order reprints of this article or to subscribe to the journal, contact the AACR Publications Department at
pubs@aacr.org.
To request permission to re-use all or part of this article, use this link
http://clincancerres.aacrjournals.org/content/26/9/2087.
Click on "Request Permissions" which will take you to the Copyright Clearance Center's (CCC)
Rightslink site.
Downloaded from clincancerres.aacrjournals.org on January 13, 2022. © 2020 American Association for Cancer Research.