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Genetic, transcriptional and post-translational regulation of the programmed death protein ligand 1 in cancer: biology and clinical correlations


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The programmed death protein 1 (PD-1) and its ligand (PD-L1) represent a well-characterized immune checkpoint in cancer, effectively targeted by monoclonal antibodies that are approved for routine clinical use. The regulation of PD-L1 expression is complex, varies between different tumor types and occurs at the genetic, transcriptional and post-transcriptional levels. Copy number alterations of PD-L1 locus have been reported with varying frequency in several tumor types. At the transcriptional level, a number of transcriptional factors seem to regulate PD-L1 expression including HIF-1, STAT3, NF-κΒ, and AP-1. Activation of common oncogenic pathways such as JAK/STAT, RAS/ERK, or PI3K/AKT/MTOR, as well as treatment with cytotoxic agents have also been shown to affect tumoral PD-L1 expression. Correlative studies of clinical trials with PD-1/PD-L1 inhibitors have so far shown markedly discordant results regarding the value of PD-L1 expression as a marker of response to treatment. As the indications for immune checkpoint inhibition broaden, understanding the regulation of PD-L1 in cancer will be of utmost importance for defining its role as predictive marker but also for optimizing strategies for cancer immunotherapy. Here, we review the current knowledge of PD-L1 regulation, and its use as biomarker and as therapeutic target in cancer.
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Genetic, transcriptional and post-translational regulation of the
programmed death protein ligand 1 in cancer: biology and clinical
Ioannis Zerdes1Alexios Matikas1,2 Jonas Bergh1,2 George Z. Rassidakis1,3 Theodoros Foukakis 1,2
Received: 29 January 2018 / Revised: 27 March 2018 / Accepted: 13 April 2018
? The Author(s) 2018. This article is published with open access
The programmed death protein 1 (PD-1) and its ligand (PD-L1) represent a well-characterized immune checkpoint in cancer,
effectively targeted by monoclonal antibodies that are approved for routine clinical use. The regulation of PD-L1 expression
is complex, varies between different tumor types and occurs at the genetic, transcriptional and post-transcriptional levels.
Copy number alterations of PD-L1 locus have been reported with varying frequency in several tumor types. At the
transcriptional level, a number of transcriptional factors seem to regulate PD-L1 expression including HIF-1, STAT3, NF-
κΒ, and AP-1. Activation of common oncogenic pathways such as JAK/STAT, RAS/ERK, or PI3K/AKT/MTOR, as well as
treatment with cytotoxic agents have also been shown to affect tumoral PD-L1 expression. Correlative studies of clinical
trials with PD-1/PD-L1 inhibitors have so far shown markedly discordant results regarding the value of PD-L1 expression as
a marker of response to treatment. As the indications for immune checkpoint inhibition broaden, understanding the
regulation of PD-L1 in cancer will be of utmost importance for de?ning its role as predictive marker but also for optimizing
strategies for cancer immunotherapy. Here, we review the current knowledge of PD-L1 regulation, and its use as biomarker
and as therapeutic target in cancer.
Cancer development and progression raises a strong anti-
tumor immune response through which the immune system
can eliminate cancer cells. This immunosurveillance theory
describes the complex interactions between immune and
cancer cells, divided in three distinct but often overlapping
stages: elimination, equilibrium, and evasion. Thus, tumors
can suppress immunity and escape eradication; evading
immune destruction has been characterized as a hallmark of
cancer [1,2].
Programmed death protein 1 (PD-1) and its ligand (PD-
L1) have been recognized as inhibitory molecules that cause
impaired immune response against cancer cells. Therapeutic
antibodies targeting PD-1/PD-L1 have been introduced into
clinical practice, leading to better patient outcomes [3].
Immune checkpoint regulation has been under intense
investigation over the last decades, however, the underlying
mechanisms regulating the PD1 and PD-L1 expression are
not fully understood; several oncogenic signaling pathways,
epigenetic modi?cations, and genetic variations have been
suggested. The aim of this review is to summarize the
current knowledge on PD-L1 regulation and its emerging
role as a target in cancer immunotherapy.
Immune surveillance: the role of PD-1/PD-L1
axis as immune checkpoint
PD-1 (CD279) is a transmembrane protein, member of the
CD28 family. It is mainly expressed on activated T cells but
it can also be detected in other cells such as B- and natural
killer (NK) cells upon induction [4]. PD-1 has two ligands,
PD-L1 (CD274, B7-H1) and PD-L2 (CD273, B7-DC),
*Theodoros Foukakis
1Department of Oncology-Pathology, Cancer Centrum Karolinska,
Karolinska Institutet, Stockholm, Sweden
2Department of Oncology, Radiumhemmet, Karolinska University
Hospital, Stockholm, Sweden
3Department of Pathology and Cytology, Karolinska University
Hospital, Stockholm, Sweden
Table 1 Copy number alterations (CNAs) of CD274 gene in cancer
Tumor type(s) No. of
Method(s) % of gains (n) % Ampli?cations (n) Association with IHC (PD-L1
Comments Ref
Solid tumors
NSCLC 221 FISH 5 (11/221) NR PD-L1 protein overexpression in all
cases with gains
Slight predisposition of CNAs in SCCs [13]
SNP arrays
NR 1.9 (4/210) High PD-L1 expression in the cases
with focal and high-level
Susceptibility of this tumor subset to immune
checkpoint blockade
SCC of vulva and
12.5 (cervical-NGS)
44 (cervical-FISH)
17 (vulvar-FISH)
23 (cervical-FISH)
26 (vulvar -FISH)
Highest PD-L1 expression in co-
ampli?ed cases, whereas lowest PD-
L1 expression in cases with disomy
Detection of cogain or coampli?cation in both
PD-L1 and PD-L2 genes
TNBC 183 FISH 8.7 (16/183) NR High PD-L1 protein expression in
patients with copy number gains
Prolonged disease-speci?c OS in patients with
high PD-L1 basal-like tumors or with gene
copy number gains
BC 1980 aCGH 3.3 (65/1980) 0.25 (5/1980) High PD-L1 protein expression in the
three examined cases with
Classi?cation as IntClust 10 subtype:
?Four out of ?ve (80%) cases with
?37/65 (57%) of the tumors with copy number
BC 3145 aCGH 5 (163/3145) 1 (39/3145) NR ?Basal subtype: 74% of the ampli?ed cases
and more gains than other subtypes
?Losses: 4% (134/3145)
?Correlation of gains with elevated PD-L1
Colon carcinomas
NR 29 (12/41)
4.5 (2/44)
2.9 (2/68)
NR In TNBC patients with the PDJ amplicon:
worse DFS and OS and correlation of amplicon
with high mRNA expression of PD-L1 and
SCC of the oral
80 FISH Restriction to tumor
Absence in the
in?ammatory cell
15 (12/80): high-level
4 (3/80): low-level
PD-L1 positivity in 73% of the
ampli?ed cases
Mostly HPV-negative SCCs
16/80 (20%) cases with polysomy
49/80 (61%) cases with disomy
SCCs and ADCs
159 FISH 13.7 (21/159): high
gains (mean 4)
20.3 (33/159): gains
(mean 2.5)
8.8 (14/159) PD-L1 positivity (1%) in:
86% (12/14) of ampli?ed cases
29.6% (16/54) of cases with gains
Identi?cation of 9 (5.7%) JAK2 ampli?ed
cases, 7 of which with PD-L1 expression
?11/14 (9%) of ampli?ed tumors: ADC
?3/14 (6%): SCC
Hematological and lymphoid tumors
DLBCL 190 RNA-seq
12 3 Correlation with elevated PD-L1
expression in cases with cytogenetic
Detection of translocations (4%) in PD-L1/PD-
L2 locus. Higher frequency of CNAs in the
non-GCB subtype
cHL 108 FISH 56 (61/108) 36 (39/108) [21]
I. Zerdes et al.
Table 1 (continued)
Tumor type(s) No. of
Method(s) % of gains (n) % Ampli?cations (n) Association with IHC (PD-L1
Comments Ref
Correlation of genetic alterations with
PD-L1 expression (especially in
disomic cases)
Correlation of gene ampli?cation with reduced
PFS. Higher ampli?cation frequency in patients
with advanced stage disease
HL 10 FISH 60 40 Correlation with PD-L1 increased
expression in all cases with CNAs
Association with activation of JAK/
STAT3 signaling pathway
qPCR NR 38 (6/16)
63 (26/41)
Association with PD-L1 protein
expression in NSHL ampli?ed cases
Association of JAK2 ampli?cation with
elevated PD-L1 transcription
Correlation of PMBCL cases with increased
PD-L1 transcript
Primary B-cell
67 Oligonucleotide
capture sequencing
NR NR Signi?cant association between
rearrangements and PDL protein
Detection of 36 novel rearrangements (17
inversions/deletions/duplications and 19
PMBCL 125 FISH 26 29 NR Correlation of genetic alterations with increased
PDL transcripts (especially in break-apart
positive cases)
HD-SNP 67/63 (EBV+/EBV-
NR Increased PD-L1 expression in copy
number gain(+) cases
Translocations in 6% of EBV- PCNSLs and 4%
of PTLs
NSCLC non-small cell lung carcinoma, SCLC small-cell lung carcinoma, SCC squamous cell carcinoma, BC breast cancer, TNBC triple-negative breast carcinoma, PDA pancreatic ductal
adenocarcinomas, PDJ amplicon the loci for PD-L1, PD-L2, and JAK2, DLBCL diffuse large B-cell lymphoma, cHL classical Hodgkin lymphoma, NSHL nodular sclerosing Hodgkin lymphoma,
NHL non-Hodgkin lymphoma, PMBCL primary mediastinal B-cell lymphomas, PCNSLs primary central nervous system lymphomas, PTLs primary testicular lymphomas, EBV EpsteinBarr
virus, IHC immunohistochemistry, NR not reported, OS overall survival, PFS progression-free survival, DFS disease-free survival, non-GCB non-germinal center B-cell-like cell, FISH ?uorescent
in-situ hybridization, qPCR quantitative polymerase chain reaction, SNP single-nucleotide polymorphism,NGS next-generation sequencing, FC ?ow cytometry, aCGH oligonucleotide array-
based comparative genomic hybridization, RNA-seq RNA-sequencing, WGS whole-genome sequencing, MCHL mixed cellularity Hodgkin lymphoma, HD-SNP high-density single-nucleotide
polymorphism arrays, CN copy number, ADC adenocarcinomas
Genetic, transcriptional and post-translational regulation of the programmed death protein ligand 1 in. . .
which belong to the B7-CD28 protein family [5]. PD-L1 is
expressed on tumor cells but it can also be present on the
surface of other cell types including T cells, B cells, den-
dritic cells, macrophages, mesenchymal stem cells, epithe-
lial, endothelial cells, and as recently shown, brown
adipocytes [6]. PD-L2 is typically expressed in antigen-
presenting cells (APCs). PD-L1 is expressed upon stimu-
lation of cytokine interferon-γ(IFNg), secreted by activated
T cells [7,8].
PD-L1 and PD-L2 are encoded by the CD274 and
PDCD1LG2 genes, respectively, located on chromosome
9p.24.1, whereas PD-1 is encoded by the PDCD1 gene
located on chromosome 2q37.3 [4].
PD-1/PD-L1 axis plays an important role in the regula-
tion of T-cell immunity and has been also implicated in
autoimmunity and infection [9]. The PD-1/PD-L1 interac-
tion has been characterized as an immune checkpointdue
to its impact on the orchestration of immune response
against tumor antigens. Along with cytotoxic T-
lymphocyte-associated protein 4 (CTLA-4, CD152), they
represent immunological brakesthat modulate T-cell
activation leading to an impaired immunosurveillance.
T-cell activation involves a two signal-model; APCs
require a ?rst signal from T-cell receptor (TCR), which
recognizes the antigen along with the major histocompat-
ibility complex (MHC) presented on the surface of APC.
The second signal includes the co-stimulatory interaction
between CD28 on the surface of T cells and CD80 (B7.1) or
CD86 (B7.2) on the surface of APC [10,11].
The engagement of PD-1 with its ligands leads to the
inhibition of T-cell activation and response, via mechanisms
that include blocking of proliferation, induction of apopto-
sis, and regulatory T-cell differentiation and therefore
immune inhibition [11]. Blocking the PD-1/PD-L1 axis
with potent monoclonal antibodies may reverse the
impaired anticancer immunity and thus represents an
appealing target of cancer immunotherapy [12].
The genetic basis of PD-L1 expression in
The genetic aberrations of the PD-L1/PD-L2 gene loci
represent a key mechanism of PD-L1 expression both in
solid and hematologic tumors. Studies of copy number
alterations (CNAs) have been reported in several tumor
types (Table 1). The highest frequencies of CNAs have
been seen in squamous cell carcinomas of vulva and cervix
and triple-negative breast cancer (TNBC), as well as in
classical Hodgkin lymphoma (cHL) and primary mediast-
inal B-cell lymphoma (PMBCL). Contrary, low or absent
CNAs have been reported in small and non-small cell lung
cancer (NSCLC) and in diffuse large B-cell lymphomas
(DLBCL). In general, copy number gains and especially
ampli?cations are well correlated with the protein levels of
PD-L1. Given the challenges in determining the protein
levels of PD-L1 as detailed below, detection of CNAs is an
attractive alternative for identifying patients who could
bene?t from treatment with checkpoint inhibitors. Table 1
summarizes the current literature of the genetic regulation of
PD-L1 [1328]. In addition to these individual studies, a
large in silico analysis of CNAs in PD-L1 has been con-
ducted using the Cancer Genome Atlas datasets (22 cancer
types, 9771 tumors). Interestingly, deletions of 9p24.1 were
more common than gains in this analysis and were found
mostly in melanoma and NSCLC, with gains occurring
frequently in ovarian, head and neck, bladder, and cervical
carcinomas [29].
Furthermore, a novel genetic regulatory mechanism of
PD-L1 gene expression involving the disruption of its 3
untranslated region (3-UTR) has been shown in multiple
tumor types including T-cell leukemia/lymphoma, DLBCL,
and gastric adenocarcinoma. Through interruption of PD-L1
3-UTR by structural variation, a deviant increase in PD-L1
transcripts occurs leading to immune escape in murine EG7-
OVA cancer cells, which in turn can be reversed by PD-L1/
PD-1 inhibition [30].
PD-L1 regulation via oncogenic signaling
The mitogen-activated protein kinase (MAPK) pathway is
crucial for various functions in normal cells, including
growth and differentiation. Its role is also important in
carcinogenesis because its activation leads to cancer
development [31]. The ERK-MAPK pathway has been
shown to regulate PD-L1 expression in different cancer
types. Both pharmacologic inhibition of mitogen-activated
protein kinase (MEK) and small interfering RNA (siRNA)
knockdown of ERK1/2 resulted in decreased levels of PD-
L1 in melanoma cells resistant to BRAF inhibition [32].
Interestingly, in TNBC cells, MEK inhibition resulted in
upregulation of MHC II and PD-L1 expression both in vitro
and in vivo, whereas combined MEK/PD-1 inhibition
increased the effectiveness of antitumor immunity [33].
MAPK signaling pathway was also responsible for the
ectopic expression of PD-L1 in v-Ki-ras2 Kirsten rat sar-
coma viral oncogene homolog (KRAS)-mutant NSCLC cell
lines, as revealed by the decrease in PD-L1 levels after both
MEK and extracellular signal-regulated MAP kinase (ERK)
abrogation [34]. In another study, Toll-like receptor 4
activation resulted in upregulation of PD-L1 in bladder
cancer cells. The use of both ERK and JNK inhibitors
I. Zerdes et al.
abrogated PD-L1 expression, further supporting the con-
tribution of MAPK signaling in PD-L1 regulation [35].
Moreover, the interaction of tyrosine kinase receptor c-Met
with its ligand hepatocyte growth factor (HGF) induced Ras
activation. Ablation of Ras effect led to downregulation of
c-Met-mediated expression of PD-L1 in renal cancer cells
KRAS activation may also induce PD-L1 expression, as
it resulted in stabilization of PD-L1 mRNA transcript
assessed through Adenylate-uridylate-rich elements identi-
?cation in its 3-UTR in lung cancer cell lines. Additionally,
MEK and Phosphoinositide 3-kinase (PI3K) inhibition led
to decreased PD-L1 levels and enhanced effectiveness of
antitumor immunity in vivo [37].
PI3K/PTEN/Akt/mTOR pathway
The PI3K/Akt/mTOR signaling represents another pathway
that affects immune surveillance through the regulation of
PD-L1. Its activation by either oncogenic PIK3CA muta-
tions (catalytic subunit alpha of PI3K) or by loss-of-
function mutations of its negative regulator, phosphatase
and tensin homolog (PTEN) modulates immune responses
contributing to a survival bene?t of cancer cells [38]. In
human gliomas, loss of PTEN and activation of PI3K
pathway enhanced PD-L1 expression [39]. In TNBC,
knockdown of PTEN by short hairpin RNA resulted in
elevated levels of both PD-L1 protein expression and
mRNA transcripts, whereas inhibition of Akt and
mechanistic target of rapamycin (mTOR) decreased PD-L1
expression [40]. In a murine model of lung SCC, concurrent
inactivation of PTEN and Lbk1 resulted in increased levels
of PD-L1 [41]. PI3K inhibition, resulted in PD-L1 down-
regulation in different cancer types including renal cell
carcinoma through HGF/c-Met [36], KRAS- or EGFR-
mutated NSCLC [42] and melanoma [32]. Conversely,
LY294002 did not abrogate PD-L1 expression in bladder
cancer cells [35]. Moreover, mTOR inhibition with rapa-
mycin reduced levels of PD-L1, both in human cell lines
and in murine models of NSCLC and combined treatment
with rapamycin and anti-PD-1 antibody inhibited tumor
growth in mice [42].
Epidermal growth factor receptor (EGFR)
EGFR is commonly mutated in NSCLC and has been
associated with PD-L1 upregulation in these tumors [43].
PD-L1 was overexpressed in EGFR-mutant murine lung
cancer, whereas treatment with an anti-PD-1 antibody
restrained tumor growth. Forced ectopic expression of
mutant EGFR on bronchial epithelial cells resulted in PD-
L1 upregulation, whereas this effect was abolished upon
treatment with EGFR tyrosine kinase inhibitors [44,45].
The EGFR-mediated regulation of PD-L1 in EGFR mutant
NSCLC was dependent on MAPK pathway activation.
Inhibition of ERK1/2/c-Jun resulted in reduced PD-L1
levels in PD-L1 overexpressing lung cancer cells [46]. In
another more recent study, EGFR was shown to regulate the
Fig. 1 Transcriptional and post-
transcriptional control of PD-L1
in cancer. Regulation of PD-L1
is complex and occurs at
different levels. Several
signaling pathways are involved
including RAS/RAF/MEK/
Akt/mTOR. Their activation by
oncogenic and/or loss-of-
function mutations can lead
either to direct action on target
genes or to the activation of
transcription factors. Such
molecules as STAT3, STAT1, c-
Jun, HIFs, or NF-κB can shuttle
into the nucleus, bind to speci?c
sites on PD-L1 gene promoter
and induce its expression. PD-
L1 is also regulated post-
transcriptionally by microRNAs,
which bind to mRNA and lead
to its translational repression or
Genetic, transcriptional and post-translational regulation of the programmed death protein ligand 1. . .
expression of PD-L1 through the activation of Interleukin-6
(IL-6)/Janus Kinase (JAK)/signal transducer and activator
of transcription 3 (STAT3) pathway in EGFR-driven
NSCLC [47].
PD-L1 upregulation has been observed in patients with
NSCLC harboring the anaplastic lymphoma kinase (ALK)
and echinoderm microtubule-associated protein like-4
(EML4) chromosomal rearrangement. Activation of
EML4-ALK was associated with increased PD-L1 expres-
sion; furthermore, treatment with either the ALK inhibitor
alectinib or ALK gene silencing with siRNA abrogated this
effect. Notably, PD-L1 upregulation was dependent on
MAPK/ERK/MEK and PI3K/Akt signaling pathways [48].
In another study using pulmonary adenocarcinoma cell
lines, EML4-ALK transcriptionally regulated PD-L1 via
STAT3 and HIF-1a [49]. These studies indicate the differ-
ent ways in which this chimeric protein can regulate the
expression of PD-L1 and thus reveal the complexity of
signaling pathways and their downstream targets. The var-
ious crosstalks in the cellular level can in?uence anticancer
immunity and at the same time offer possible appealing
therapeutic targets.
Transcriptional control of PD-L1
The transcriptional regulation of PD-L1 is summarized in
Fig. 1.
The JAK/STAT pathway
STAT3 plays a key role in promoting cancer cell survival
and proliferation, as well as creating immunosuppressive
and thus pro-carcinogenic conditions in the tumor micro-
environment (TME) [50]. Furthermore, STAT3 is involved
in PD-L1 regulation in various cancer types. In
nucleophosmin-anaplastic large-cell lymphoma kinase
(NPM-ALK) positive anaplastic large-cell lymphoma
(ALCL), STAT3 is activated by NPM-ALK oncoprotein
through JAK3 activation, binds physically to the PD-L1
gene promoter, and induces its expression in vitro and
in vivo [51]. This STAT3-mediated transcriptional regula-
tion of PD-L1 has been recently shown in another T-cell
lymphoma, namely the ALK-negative ALCL. STAT3 gene
silencing led to decreased PD-L1 levels in ALK-ALCL [52]
and also in KRAS-mutant NSCLC cell lines [34]. By con-
trast, chromatin immunoprecipitation analysis did not show
active binding of STAT3 directly on the promoter of PD-L1
in melanoma cells, despite the presence of putative binding
sites of STAT3 on the promoter identi?ed in silico.
Abrogation of STAT3 resulted in enhancement of PD-L1
construct activity mediated by IFNg [53]. PD-L1 was also
induced by latent membrane protein-1 in EpsteinBarr virus
(EBV)-associated nasopharyngeal carcinomas (NPC)
through JAK3/STAT3 activation [54].
Another STAT family member, STAT1, is considered to
be a tumor suppressor that reduces proliferation, induces
apoptosis, and enhances cancer immunosurveillance [55].
Accumulating evidence indicates the emerging role of
STAT1 in tumor growth, immune suppression, and ther-
apeutic resistance [56]. Upon stimulation with IFNg,
STAT1 activation resulted in PD-L1 upregulation and in
reduction of NK-cell activity against tumor cells in multiple
myeloma, acute myeloid leukemia (AML), and acute lym-
phoblastic leukemia (ALL) [57]. Similarly, STAT1 inhibi-
tion led to decreased PD-L1 levels in myeloma cells and
thus suppressed the antitumor function of cytotoxic T cells
[58]. PD-L1 upregulation was JAK2/STAT1-dependent in
head and neck cancer with wild-type EGFR, whereas JAK2
inhibition resulted in both basal and EGF-mediated down-
regulation of PD-L1. Moreover, knockdown of STAT1
gene abolished both IFNg- and EGF-mediated upregulation
of PD-L1. Of note, EGFR activation promotes phosphor-
ylation of STAT1, which in turn binds to the promoter of
PD-L1 and controls its expression [59]. Although putative
binding sites for STAT1 on PD-L1 promoter have been
postulated, active binding of STAT1 on PD-L1 gene pro-
moter could not be demonstrated in melanoma cells [53].
Interferon regulatory factor 1 (IRF1) is a downstream
effector of STAT1 upon IFNg stimulation. Its role is crucial
in both constitutive and IFNg-mediated upregulation of PD-
L1. Inhibition of IRF1 activity or expression resulted in
decreased PD-L1 levels in human lung cancer cells [60].
The key role of IRF1 and interferon receptor pathway in the
regulation of PD-L1 has also been implied in melanoma,
where putative binding sites for IRF1 have been identi?ed
in the PD-L1 promoter and abrogation of IRF1 site resulted
in reduced PD-L1 levels [53,61]. Recently, another novel
mechanism of PD-L1 regulation by DNA double-strand
breaks (DSBs) was unveiled. This DSB-dependent PD-L1
upregulation was mediated by the activation of STAT1/
STAT3 phosphorylation and IRF1 [62].
Hypoxia-inducible factors (HIFs)
Hypoxia signaling represents an important pathway in
oncogenesis. HIF-1a and HIF-2a are the major components
of a transcriptional complex, through which tumor cells
adapt to hypoxic conditions. HIF stabilization leads to its
binding to speci?c regions called hypoxia response ele-
ments (HRE) on certain gene promoters [63]. High levels of
HIF-1 have been correlated with both worse outcomes and
resistance to cytotoxic therapy [64]. Intriguingly, HIF-1
I. Zerdes et al.
expression by different cellular sub-populations of the
innate and adaptive immunity can modify antitumor activity
by repressing the effective T-cell response and alter TME to
promote tumor cell survival [63]. A recent study revealed
that HIF-1αguided CD8 +T-cell migration and function,
whereas its depletion on T cells resulted in increased tumor
growth and impaired antitumor control [65]. One of the
mechanisms by which hypoxia signaling impairs T-cell
functionality is the induction of PD-L1 on myeloid-derived
suppressor cells under hypoxic conditions. Indeed, HIF-1a
transcriptionally regulates PD-L1 expression by binding on
HRE of its promoter [66]. Furthermore, PD-L1 may be a
target of HIF2a in clear cell renal cell carcinoma (ccRCC)
cells in which the tumor-suppressor pVHL was abrogated.
Upon de?ciency of pVHL increased PD-L1 levels, asso-
ciated with HIF-2a activation, were observed in vitro [67].
Similar results were obtained from ccRCC patient samples
with VHL loss-of-function mutations, where a positive
correlation was seen between PD-L1 expression, HIF-2a
expression and VHL mutations. Of note, HIF-2a tran-
scriptionally regulates PD-L1 by binding to the active HRE
of its promoter [68]. Moreover, STAT3 can cooperate with
HIF-1, but not HIF-2, in the regulation of HIF target genes
in response to hypoxia. Inhibition of STAT3 expression or
activity in breast and RCC cell lines reduced the expression
of genes targeted by HIF-1 [69]. These ?ndings support the
idea of combining HIF-targeting therapies and
The role of nuclear factor kappa B (NF-κB)
NF-κB is a master transcription factor activated in several
cancer types, promoting in?ammation, inhibiting apoptosis,
and impairing effective antitumor immunity [70]. The NF-
κB family contains seven members, with the most repre-
sentative being the p65 RelA/p50. This cytoplasmic het-
erodimer translocates to the nucleus and acts as a
transcription factor of κB upon degradation of the IκΒ-α
inhibitor [71,72]. In melanoma cells, NF-κB mediated PD-
L1 overexpression induced by IFN-γ. PD-L1 upregulation
by NF-κΒ was independent of STAT3 and c-Jun, whereas
targeting of MAPK and PI3K signaling pathways had a
minor impact on PD-L1 expression [72]. Notably, STAT3
regulates and cooperates with NF-κΒ in additional cancer
types [73]. For example, PD-L1 regulation may be depen-
dent on p65/NF-κB and mediated by LMP1 in EBV-
positive NPC, as inhibition of NF-κB activity resulted in
decreased PD-L1 levels [54].
The Myc oncogene
Myc plays a pivotal role in carcinogenesis by controlling
cell proliferation and survival in various cell systems.
Tumor regression after Myc inactivation is associated with a
not fully understood immune response, as re?ected by the
accumulation of CD4 +T cells [7476]. Furthermore, a
novel role of Myc was recently revealed in the context of
avoiding effective cancer immunosurveillance. Using a Tet-
off MYC-dependent mouse model of T-ALL (MYC T-
ALL), Casey et al. showed that Myc transcriptionally reg-
ulates PD-L1 and CD47, an inhibitory regulator of the
innate immune system [77]. Moreover, forced expression of
PD-L1 and CD47 upon Myc inactivation was correlated
with worse antitumor immune response as indicated by the
reduction of macrophages and CD4 +T cells in TME,
tumor progression, and maintenance of angiogenesis and
senescence [78]. Elucidating the role of Myc in the reg-
ulation of immune-mediated antitumor response, the
potential crosstalks with other oncogenic pathways and the
immune in?ltrate in TME may pave the way for the use of
immune checkpoint inhibitors in patients with Myc-
overexpressing tumors [79]. A recent work on ALK-
negative ALCL also supports a Myc-mediated regulation
of PD-L1, as forced expression of Myc led to PD-L1
upregulation in cell lines showing low baseline levels of
PD-L1. Similarly, both inhibition and silencing of Myc
resulted in PD-L1 downregulation in lymphoma cells [52].
The bromodomain and extraterminal (BET) protein
BET proteins modulate gene expression through enzymes
that regulate chromatin and histone modi?cation [80].
Speci?cally, the BET protein BRD4 acts through RNA
polymerase II by binding to the acetyl-lysine region of
histones [81]. Inhibition of BRD4 by the JQ1 inhibitor
decreased PD-L1 expression and tumor growth. BRD4 gene
silencing also resulted in decreased PD-L1 levels in mouse
models and in ovarian cancer cell lines. Notably, BRD4
transcriptionally regulated PD-L1 by binding on its pro-
moter [82]. Similarly, in a recent study on B-cell lym-
phoma, BET inhibitors enhanced effective antitumor
immunity through regulation of PD-L1, whereas inhibition
and genetic ablation of BRD4 resulted in suppression of
PD-L1 expression in a transcriptional, Myc-independent,
manner. Moreover, BRD4 synergized with IRF1 to regulate
PD-L1 expression induced by IFN-γ[83]. Also, another
BET inhibitor (I-BET151) was shown to abrogate NF-Κβ
activity in melanoma, both in vitro and in vivo, thus
indirectly affecting PD-L1 expression [84].
Histone deacetylases (HDACs)
The role of the epigenetic modi?ers HDACs in the mod-
i?cation of non-histone targets, including those participat-
ing in tumor-host interactions, has recently been
Genetic, transcriptional and post-translational regulation of the programmed death protein ligand 1. . .
investigated [85,86]. In a study in melanoma, both inhi-
bition and depletion of HDAC6 resulted in reduced PD-L1
levels in vitro and in vivo. PD-L1 regulation by HDAC6
was mediated by STAT3 and both HDAC6 and STAT3
were recruited to the PD-L1 gene promoter [87]. It should
be noted that HDAC have pleiotropic effects within both the
innate and adaptive immune response, and may thus affect
PD-L1 levels via interferons [88].
The role of cell cycle
Cyclin-dependent kinases (CDKs) have a key role in cell
cycle [89]. Cyclin-dependent kinase 5 (Cdk5) is a serine-
threonine kinase important in central nervous system
function [90] and other cellular functions [91,92]. In a
study of medulloblastoma, depletion of Cdk5 led to the
upregulation of interferon regulatory factor 2 and interferon
regulatory factor binding protein 2, which in turn, sup-
pressed the expression of PD-L1. Cdk5 was thus necessary
for PD-L1 upregulation after IFN-γstimulation through
STA1/IRF1 axis and its disruption led to tumor rejection in
a CD4 +T-cell-dependent manner in medulloblastoma
mouse models [93]. These data highlight Cdk5 as a novel
target for interventions in combination with immune
checkpoint blockade. Additionally, CDK4/6 inhibition has
been recently shown to enhance antitumor immunity
through increased T-cell cytotoxicity and Treg suppression
[94]. This is discussed in detail in the post-translational
regulation of PD-L1 hereunder.
The AP-1 transcription factors
c-Jun, the best known member of the AP-1 family, repre-
sents another transcription factor that is implicated in PD-
L1 gene regulation. Knockdown of c-Jun resulted in
decreased levels of PD-L1 in melanoma cells resistant to
BRAF inhibitors [32], and co-activation of STAT3 and the
subsequent formation of a transcriptional complex further
enhanced these effects [95]. Similarly, combined knock-
down of c-Jun and STAT3 genes in the same melanoma
model showed a synergistic effect on PD-L1 down-
regulation [32]. Additionally, c-Jun and JUNB have been
shown to bind AP-1 sites in the PD-L1 promoter in HL cells
[96] and in KRAS-mutant NSCLC. In lung adenocarcinoma
cell lines, the transcriptional activity was subjected to
MAPK signaling pathway [34]. MAPK/AP-1 was also
shown to contribute to LMP1-mediated upregulation of PD-
L1 in EBV-associated NPC [54].
The ambivalent role of p53
The tumor-suppressor gene p53 has been implicated in
antitumor immunity by regulating several genes involved in
the immune system. Indeed, immune checkpoint regulation
has been shown to represent a major target of p53 [97].
Paradoxically, activation of wild-type p53 using the small
molecule Nutlin-3a resulted in increased expression of PD-
L1 in human breast cancer [98] and in ALK-negative ALCL
cells [52]. In p53-mutated NSCLC, downregulation of miR-
34 resulted in increased PD-L1 levels [99], whereas an
inverse correlation between miR-34a and PD-L1 was also
con?rmed in AML [100].
MicroRNAs can bind to 3-UTR of mRNAs and lead to
their degradation or translational repression [101]. MiR-513
was shown to increase PD-L1 expression in cholangiocytes
[102], whereas mutation in the 3-UTR of PD-L1 mRNA
led to overexpression of the protein by preventing miR-570
binding in gastric cancer [103,104]. On the contrary, miR-
197 downregulated PD-L1 by affecting STAT3 in platinum-
resistant NSCLC [105], whereas miR-138-5p was asso-
ciated with decreased levels of PD-L1 in colorectal cancer
(CRC) [106]. Also in CRC, miR-20b, miR-21, and miR-
130b caused PD-L1 upregulation through attenuation of
PTEN [107].
Post-translational regulation of PD-L1
The role of ubiquitination
In a recent study by Lim et al., a novel regulatory
mechanism involving the ?fth protein element of
COP9 signalosome complex (CSN5), also known as Jab1,
was revealed in breast cancer. CSN5 has been associated
with increased proliferation, decreased apoptotic rates, and
survival of cancer cells [108]. Under chronic in?ammatory
conditions, tumor necrosis factor alpha (TNF-α), secreted
mostly by macrophages, led to PD-L1 stabilization and
therefore to an immunosuppressive pro?le of the tumor
environment [61]. The stabilization of PD-L1 by TNF-a was
shown to be mediated by NF-κΒ subunit RelA/p65, which
binds on the promoter of CSN5 gene and has a direct effect
on its regulation. CSN5 in turn, prevents the ubiquitination
of PD-L1, hinders its degradation and as a result enhances
tumor escape from immunosurveillance. Indeed, CSN5
inhibition or gene silencing abolished PD-L1 expression
and tumor proliferation in vivo. Curcumin, a CSN5 inhi-
bitor, induced better responses to anti-CTLA-4 treatment
in vitro, indicating the potential of combinational adminis-
tration of immune checkpoint with CSN5 inhibitors [61,
109,110]. In another in vitro study, induction of both PD-
L1 ubiquitination and PD-L1 protein levels was noted upon
treatment with epidermal growth factor. An increase of
I. Zerdes et al.
Table 2 Randomized phase 3 trials of PD-1 and PD-L1 inhibitors
Trial [Ref] NClinical setting Comparison ORR (%) PFS (months) OS (months)
Non-small cell lung cancer
KEYNOTE-024 [132] 305 First line Pembrolizumab vs platinum doublet 44.8 vs 27.8 10.3 vs 6.0, p< 0.001 HR =0.60 (0.410.89), p=0.005
CheckMate 026 [133] 541 First line Nivolumab vs platinum doublet 26 vs 33 (NS) 4.2 vs 5.9, p=0.25 14.4 vs 13.2 (NS)
KEYNOTE-010 [134] 1034 Second line Pembrolizumab (2 schedules) vs docetaxel 18 and 18 vs 9, p=0.0005
and p=0.0002
3.9 and 4.0 vs 4.0 (NS) 10.4 and 12.7 vs 8.5, p=0.0008
and p< 0.0001
CheckMate 017 [135] 272 Second line, squamous Nivolumab vs docetaxel 20 vs 9, p=0.008 3.5 vs 2.8, p< 0.001 9.2 vs 7.3, p< 0.001
CheckMate 057 [136] 582 Second line, non-
Nivolumab vs docetaxel 19 vs 12, p=0.02 2.3 vs 4.2, p=0.39 12.2 vs 9.4, p=0.002
OAK [137] 850 Second line Atezolizumab vs docetaxel 14 vs 13 (NS) 2.8 vs 4.0, p=0.49 13.9 vs 9.6, p=0.0003
PACIFIC [145] 713 Maintenance stage III Durvalumab vs placebo 28.4 vs 16.0, p< 0.001 16.8 vs 5.6, p< 0.001 Not reported
Cutaneous melanoma
KEYNOTE-006 [138] 834 First line Pembrolizumab (2 schedules) vs
33.7 and 32.9 vs 11.9, p<
HR =0.58 (0.460.72),
p < 0.001
HR =0.63 (0.470.83), p =0.0005
CheckMate 066 [139] 418 First line Nivolumab vs dacarbazine 40.0 vs 13.9, p< 0.001 5.1 vs 2.2, p< 0.001 HR =0.42 (33.050.9), p< 0.001
CheckMate 037 [140] 405 After ipilimumab Nivolumab vs dacarbazine or carboplatin/
31.7 vs 10.6 3.1 vs 3.7 (NS) 16 vs 14 (NS)
CheckMate 067 [141] 945 First line Nivolumab +ipilimumab vs nivolumab
vs ipilimumab
58 vs 44 vs 19 11.5 vs 6.9 vs 2.9 NR vs NR vs 20
CheckMate 238 [146] 906 Adjuvant Nivolumab vs ipilimumab HR for RFS 0.65 (97.56% CI, 0.510.83), p< 0.001
Urothelial bladder cancer
KEYNOTE-045 [142] 542 Second line Pembrolizumab vs paclitaxel or docetaxel
or vin?unine
21.1 vs 11.4, p=0.001 2.1 vs 3.3, p=0.42 10.3 vs 7.4, p=0.002
Imvigor 211a[147] 931 Second line Atezolizumab vs paclitaxel or docetaxel or
23.0 vs 21.6 (NS) 2.4 vs 4.2 (NS) 11.1 vs 10.6, p=0.41
Clear cell renal carcinoma
CheckMate 025 [143] 821 After 12 TKIs Nivolumab vs everolimus 25 vs 5, p< 0.001 4.6 vs 4.4, p =0.11 25.0 vs 21.8, p0.0148
CheckMate 214b[148] 1096 First line Nivolumab +ipilimumab vs sunitinib 42 vs 27, p< 0.0001 22.6 vs 8.4, p=0.0331 NR vs 32, p=0.0003
Head and neck squamous cell carcinoma
CheckMate 141 [144] 361 Nivolumab vs methotrexate or docetaxel
or cetuximab
13.3 vs 5.8 2.0 vs 2.3, p=0.32 7.5 vs 5.1, p=0.01
ORR objective response rate, PFS progression-free survival, OS overall survival, NS nonsigni?cant, NR not reached, HR hazard ratio, RFS relapse-free survival, CI con?dence interval, TKI
tyrosine kinase inhibitor
aThe results presented here concern the primary endpoint of the study in the IC2/3 group of PD-L1 expression
bThe results presented here concern the primary endpoint of the study in the intermediate and poor risk group
Genetic, transcriptional and post-translational regulation of the programmed death protein ligand 1. . .
mono- and multiubiquitination of PD-L1 was seen, an effect
that was abrogated upon inhibition of the EGFR pathway
and/or ubiquitin E1 activating enzyme [111]. Furthermore, a
recent study demonstrated a novel role of cyclin D-CDK4
and cullin 3-speckle-type POZ protein (SPOP) E3 ligase in
regulating the expression of PD-L1. Cyclin D1-CDK4 was
shown to phosphorylate SPOP and lead to ubiquitination-
mediated PD-L1 destabilization. Thus, either inhibition of
CDK4/6 or loss-of-function mutations of SPOP led to
increased levels of PD-L1 and reduced tumor-in?ltrating
lymphocytes. Additionally, treatment with a CDK4/6 inhi-
bitor and an anti-PD-1 antibody resulted in tumor regression
and improved survival in vivo [112].
Lysosomal-mediated degradation
CKLF-like MARVEL transmembrane domain containing
protein 6 (CMTM6) was recently identi?ed as a novel
regulator of PD-L1 [113,114]. CMTM6a tetraspanin
proteininteracted with PD-L1 through its transmembrane
domain and regulated PD-L1 expression in cancer and
myeloid cells, both in vitro and in vivo [115]. Depletion of
CMTM6 did not in?uence the CD274 transcript, but led to
reduction of PD-L1 protein expression and augmentation of
antitumor immunity. The mechanism of action of CMTM6
involves the avoidance of PD-L1 lysosome-mediated
degradation, probably through prevention of its ubiquiti-
nation, as these two proteins are co-localized in the plasma
membrane [116].
The role of glycosylation
N-glycosylation represents a crucial post-translational mod-
i?cation determining protein formation, functionality, and
interaction with other proteins [117]. A novel association
between procedure-glycosylation and ubiquitination in the
regulation of PD-L1 has recently been unveiled. In basal-like
breast cancer cells, N-glycosylation of PD-L1 (highly at sites
N35, N192, N200, and N219) led to protein stabilization and
avoidance of its degradation by 26S proteasome. In contrast,
non-glycosylated forms interrelated with Glycogen synthase
kinase 3 beta (GSK3β), which in turn phosphorylated PD-L1
resulting in its degradation. Inhibition of GSK3βactivity
augmented immune suppression by tumor cells both in vitro
and in vivo. Furthermore, EGFR promoted inactivation of
GSK3β, and EGFR signaling blockade reversed stabilization
of PD-L1 and led to enhanced antitumor responses [118]. In
another study, N-linked glycosylation of PD-L1 (gPD-L1)
was shown to increase PD-L1/PD-1 interaction, and conse-
quently immunosuppression in TNBC. Its targeting with
monoclonal antibodies or drug-conjugated gPD-L1 was thus
proposed as a promising target of post-translational mod-
i?cations of immune checkpoints [119].
Effect of chemotherapy in PD-L1 expression
Chemotherapeutic agents, apart from their direct cytotoxic
effects on cancer cells, can also modulate immune respon-
ses against tumors [120,121]. Treatment with paclitaxel,
etoposide and 5-?uorouracil induced PD-L1 expression in
breast cancer cell lines in a dose-dependent manner [122].
Paclitaxel was also associated with elevated levels of PD-L1
in human CRC and hepatocellular carcinoma cell lines. This
regulation was dependent on MAPK activation [123].
Likewise, cisplatin induced PD-L1 expression in hepatoma
cells in ERK1/2 phosphorylation-dependent manner [124].
In another study, doxorubicin led to PD-L1 downregulation
on cell surface and a simultaneous PD-L1 upregulation in
the nucleus of breast cancer cells. Nuclear PD-L1 expres-
sion was accompanied by nuclear AKT phosphorylation
and proved to be dependent on PI3K/AKT pathway,
whereas knockdown of PD-L1 was associated with
enhanced doxorubicin-mediated apoptosis [125].
Targeting immune checkpoint regulators:
the era of immunotherapy in cancer
The introduction of systemic cancer immunotherapy in
clinical practice signi?cantly predates the ?rst randomized
trials of immune checkpoint inhibitors. Despite the occur-
rence of rare, prolonged complete remissions in patients
with metastatic melanoma and ccRCC [126,127], the use of
high-dose IL-2 was restricted by the signi?cant, often fatal
adverse events and the need for intensive monitoring and
experience in its administration, whereas the use of IFNg in
ccRCC was characterized by its perceived low ef?cacy
[128]. The clinical application of cancer immunotherapy
had remained stagnant until the ?rst checkpoint inhibitor
received regulatory approval for use in metastatic mela-
noma, the CTLA-4 inhibitor ipilimumab. Ipilimumab
exhibits several recurring characteristics of immunotherapy:
slow induction of response, a striking disassociation
between imaging-assessed objective responses and survival,
which led to the introduction of immune-related response
criteria [129], unique patterns of toxicity termed immune-
related adverse events[130] and robust, durable
improvements in terms of patient survival [131].
Shortly after the approval of ipilimumab the ?rst trials of
PD-1 and later PD-L1 inhibitors were published. Their
results have vastly changed the treatment landscape in
multiple human malignancies, adding a new category of
effective and, compared with cytotoxic chemotherapy, less
toxic agents to the therapeutic armamentarium. The results
of the published phase 3 trials are presented in Table 2
[132148], whereas a selection of ongoing randomized
trials in an ever-expanding list of indications, both at
I. Zerdes et al.
Table 3 Selected ongoing phase 3 trials of PD-1 and PD-L1 inhibitors
Disease Trial Clinical setting
Breast cancer
TNBC KEYNOTE-119 Prior anthracycline/taxane, vs monochemotherapy NCT02555657
TNBC KEYNOTE-522 First line, chemotherapy ± pembrolizumab NCT03036488
TNBC Adjuvant in residual disease after neoadjuvant chemotherapy NCT02954874
HER2 +breast cancer First line, Paclitaxel/Trastuzumab/Pertuzumab ± pembrolizumab NCT03199885
Gastrointestinal cancer
Hepatocellular cancer KEYNOTE-394 Pretreated (sorafenib or oxaliplatin), vs placebo NCT03062358
Hepatocellular cancer KEYNOTE-240 Prior sorafenib, vs placebo NCT02702401
Gastric cancer KEYNOTE-063 Second line, vs paclitaxel NCT03019588
Esophageal cancer KEYNOTE-590 First line, cisplatin/5FU ± pembrolizumab NCT03189719
Esophageal cancer KEYNOTE-181 Second line, vs taxane or irinotecan NCT02564263
Colorectal cancer KEYNOTE-177 First line, microsatellite instability-high or mismatch repair
de?cient, chemotherapy vs pembrolizumab
Genitourinary cancer
Renal cell carcinoma KEYNOTE-564 Adjuvant, vs placebo NCT03142334
Renal cell carcinoma KEYNOTE-426 First line, pembrolizumab/axitinib vs sunitinib NCT02853331
Bladder cancer KEYNOTE-361 First line, chemotherapy vs pembrolizumab vs combination NCT02853305
Lung and head and neck cancer
NSCLC KEYNOTE-091 Adjuvant, vs placebo NCT02504372
NSCLC KEYNOTE-407 First line, squamous cell, chemotherapy ± pembrolizumab NCT02775435
NSCLC KEYNOTE-189 First line, non-squamous cell, chemotherapy ± pembrolizumab NCT02578680
SCLC KEYNOTE-604 First line, chemotherapy ± pembrolizumab NCT03066778
Mesothelioma PROMISE-Meso Second line, vs gemcitabine or vinorelbine NCT02991482
Head and neck cancer KEYNOTE-412 After chemoradiation, vs placebo NCT03040999
Head and neck cancer KEYNOTE-048 Chemotherapy vs pembrolizumab vs combination NCT02358031
Melanoma KEYNOTE-252 First line, pembrolizumab ± epacadostat NCT02752074
Melanoma Adjuvant, pembrolizumab vs ipilimumab vs interferon alfa-2B NCT02506153
Hematologic malignancies
Hodgkins lymphoma KEYNOTE-204 Relapsed/refractory disease, vs brentuximab vedotin NCT02684292
Multiple myeloma KEYNOTE-183 Relapsed/refractory disease, pomalidomide/dexamethasone ±
Multiple myeloma KEYNOTE-185 First line, lenalidomide/dexamethasone ± pembrolizumab NCT02579863
Gastrointestinal cancer
Hepatocellular cancer First line, vs sorafenib NCT02576509
Gastric cancer CheckMate 649 First line, nivolumab/ipiliumab vs nivolumab/chemotherapy vs
Esophageal and junction
CheckMate 577 Adjuvant, vs placebo NCT02743494
Esophageal cancer CheckMate 648 First line, nivolumab/ipilimumab vs nivolumab/chemotherapy vs
Esophageal cancer Second line, vs taxane NCT02569242
Genitourinary cancer
Bladder cancer CheckMate 274 Adjuvant, vs placebo NCT02632409
Bladder cancer CheckMate 901 First line, nivolumab/ipilimumab vs chemotherapy NCT03036098
Genetic, transcriptional and post-translational regulation of the programmed death protein ligand 1. . .
Table 3 (continued)
Disease Trial Clinical setting
Renal cell carcinoma CheckMate 9ER First line, nivolumab/ipilimumab vs nivolumab/cabozantinib vs
Lung and head and neck cancer
NSCLC ANVIL Adjuvant, vs placebo NCT02595944
NSCLC CheckMate 816 Neoadjuvant, nivolumab/ipilimumab vs chemotherapy NCT02998528
NSCLC Stage III, after chemoradiation vs placebo NCT02768558
NSCLC CheckMate 227 First line, nivolumab/ipilimumab vs nivolumab vs nivolumab/
chemotherapy vs chemotherapy
SCLC CheckMate 451 Maintenance after ?rst line, nivolumab/ipilimumab vs
nivolumab vs placebo
Mesothelioma CheckMate 743 First line, nivolumab/ipilimumab vs chemotherapy NCT02899299
Mesothelioma CONFIRM Pretreated, vs placebo NCT03063450
Head and neck cancer CheckMate 651 First line, nivolumab/ipilimumab vs chemotherapy NCT02741570
Melanoma CheckMate 915 Adjuvant, nivolumab/ipilimumab vs nivolumab vs ipilimumab NCT03068455
Melanoma First line BRAF V600E, dabrafenib/trametinib nivolumab/
ipilimumab vs nivolumab/ipilimumab dabrafenib/trametinib
Hematologic malignancies
Hodgkins lymphoma CheckMate 812 Relapsed/refractory disease, nivolumab/brentuximab vedotin vs
brentuximab vedotin
Multiple myeloma CheckMate 602 Relapsed/refractory disease, pomalidomide/dexamethasone ±
nivolumab vs nivolumab/pomalidomide/elotuzumab/
Other tumors
Glioblastoma CheckMate 143 Second line, nivolumab/ipilimumab vs nivolumab vs
Glioblastoma CheckMate 498 First line, radiation and temozolomide or nivolumab NCT02617589
Breast cancer
TNBC IMpassion 031 Neoadjuvant, chemotherapy ± atezolizumab NCT03197935
TNBC IMpassion 130 First line, nab-paclitaxel ± atezolizumab NCT02425891
TNBC IMpassion 131 First line, paclitaxel ± atezolizumab NCT03125902
Gastrointestinal cancer
Colorectal cancer Pretreated, atezolizumab/cobimetinib vs atezolizumab vs
Colorectal cancer Adjuvant, microsatellite instability-high or mismatch repair
de?cient, chemotherapy ± atezolizumab
Colorectal cancer First line, microsatellite instability-high or mismatch repair
de?cient, chemotherapy/bevacizumab ± atezolizumab
Genitourinary cancer
Bladder cancer IMvigor 010 Adjuvant, vs placebo NCT02450331
Renal cell carcinoma IMmotion 010 Adjuvant, vs placebo NCT03024996
Renal cell carcinoma IMmotion 151 First line, atezolizumab/bevacizumab vs sunitinib NCT02420821
Prostate cancer IMbassador 250 Castration-resistant, after anti-androgen and taxane,
enzalutamide ± atezolizumab
Ovarian cancer ATALANTE Relapsed, chemotherapy/bevacizumab vs atezolizumab/
Ovarian cancer IMagyn 050 First line, Paclitaxel/Carboplatin/Bevacizumab ± atezolizumab NCT03038100
I. Zerdes et al.
refractory disease, as well as in earlier lines of therapy or at
the adjuvant setting is presented in Table 3. The results of
these trials are eagerly awaited, because there are high
unmet needs in many of the indications that these agents are
being tested. Of interest are also hematologic malignancies;
preliminary trials report impressive response rates in
otherwise refractory disease [149], believed to be driven by
both the inherent role of the PD-1/PD-L1 axis in the evasion
of immunosurveillance in lymphoid tumors, particularly in
those with a viral etiology [150], and by the presumed
signi?cance of PDL1 and PDL2 ampli?cation in the biology
of certain neoplasms such as Hodgkin lymphoma [22]. In
Table 3 (continued)
Disease Trial Clinical setting
Lung and head and neck cancer
NSCLC IMpower 130 First line, non-squamous, chemotherapy ± atezolizumab NCT02367781
NSCLC IMpower 131 First line, squamous, chemotherapy ± atezolizumab NCT02409355
NSCLC First line, platinum ineligible, vs monochemotherapy NCT03191786
SCLC IMpower 133 First line, chemotherapy ± atezolizumab NCT02763579
Melanoma First line BRAF V600E, vemurafenib/cobimetinib ±
Genitourinary cancer
Bladder cancer First line, durvalumab/tremelimumab vs durvalumab vs
Lung and head and neck cancer
NSCLC MYSTIC First line, durvalumab/tremelimumab vs durvalumab vs
NSCLC NEPTUNE First line, durvalumab/tremelimumab vs chemotherapy NCT02542293
NSCLC CAURAL Second line, EGFR T790M +, osimertinib ± durvalumab NCT02454933
NSCLC Adjuvant, vs placebo NCT02273375
SCLC Caspian First line, durvalumab/tremelimumab/chemotherapy vs
durvalumab/chemotherapy vs chemotherapy
Head and neck cancer KESTREL First line, durvalumab/tremelimumab vs durvalumab vs
Breast cancer
TNBC A-Brave Adjuvant, vs placebo NCT02926196
Gastrointestinal cancer
Gastric cancer JAVELIN Gastric 100 Maintenance after ?rst line, vs continuation chemotherapy NCT02625610
Gastric cancer JAVELIN Gastric 300 Third line, vs irinotecan or paclitaxel NCT02625623
Genitourinary cancer
Bladder cancer JAVELIN Bladder 100 Maintenance after ?rst line, vs placebo NCT02603432
Renal cell carcinoma JAVELIN Renal 101 First line, avelumab/axitinib vs sunitinib NCT02684006
Ovarian cancer JAVELIN Ovarian 100 First line, chemotherapy vs chemotherapy/avelumab vs
chemotherapy with avelumab maintenance only
Ovarian cancer JAVELIN Ovarian 200 Platinum-resistant relapse, liposomal doxorubicin ± avelumab NCT02580058
Lung and head and neck cancer
NSCLC JAVELIN Lung 100 First line, vs chemotherapy NCT02576574
NSCLC JAVELIN Lung 200 Second line, vs docetaxel NCT02395172
Head and neck cancer JAVELIN Head and
neck 100
Chemoradiotherapy ± avelumab NCT02952586
Head and neck cancer REACH Chemoradiotherapy vs radiotherapy/cetuximab/avelumab NCT02999087
NSCLC non-small cell lung cancer, SCLC small cell lung cancer, TNBC triple-negative breast cancer, HER2 human epidermal growth factor
receptor 2
Genetic, transcriptional and post-translational regulation of the programmed death protein ligand 1. . .
contrast, the recent discontinuation of the ongoing phase 3
trials in multiple myeloma due to an increased risk of death
underscores the fact that better understanding of the
underlying immune mechanisms is still needed.
Importantly, a new generation of clinical trials has been
initiated and initial results are already available regarding a
multi-faceted attempt to improve upon the ef?cacy of PD-1/
PD-L1 inhibitors as monotherapy: their combination with
CTLA-4 inhibitors, already shown to improve outcomes in
metastatic melanoma [141] and pursued in other malig-
nancies including NSCLC and SCLC; their combination
with cytotoxic chemotherapy, based upon the premise of the
prevention of early disease progression due to the simulta-
neous administration of chemotherapy and the release of
neoantigens due to the cytotoxic effects of the combinatory
treatment, which may potentiate the activity of PD-1 inhi-
bitors, an approach that has shown promising results in
advanced NSCLC and at the neoadjuvant setting of TNBC
[151,152]; the combination of targeted agents and PD-1
axis blockade [153], with preliminary results showing that
combining immunotherapy with inhibitors of known
effectors of the axis, such as CDK4/6, results in promising
activity [154]; and ?nally, the combination with inhibitors
or stimulators of modulatory molecules such as indoleamine
2,3-dioxygenase (IDO) inhibitors, because IDO is a major
negative feedback pathway regulated by IFNg. Preliminary
results of the IDO inhibitor epacadostat with nivolumab in a
variety of tumors and with pembrolizumab in melanoma are
promising and phase 3 results are eagerly awaited [155,
In short, the current era of cancer immunotherapy could
be characterized as the end of the beginning. A variety of
agents is available for use in multiple indications and
clinical experience is accumulating. The next phase, namely
the optimization of the use of the available agents and the
exploration for novel combinations, has already begun.
Immune checkpoint regulators as novel
biomarkers: prognostic and predictive value
Taking into account the signi?cant clinical ef?cacy of PD-1/
PD-L1 blockade in a small subset of patients, the con-
siderable costs and potential for devastating immune-related
adverse events associated with the use of these inhibitors
and the robust theoretical background explaining the biol-
ogy of their mechanism of action, considerable efforts have
been undertaken in order to identify putative predictive
biomarkers. The best characterized biomarker is the
immunohistochemistry (IHC)-assessed PD-L1 expression.
The con?icting results of individual trials have been sum-
marized in meta-analyses, which indicate that increased
levels of PD-L1 expression are associated with an improved
probability for objective response [157,158]. Supporting
these results are two recently published clinical trials in the
?rst line of advanced NSCLC, KEYNOTE-024, and
CheckMate 026. In the former, overall survival (OS) in
patients selected for PD-L1 positivity 50% was improved
with pembrolizumab compared with platinum-based che-
motherapy [132]. Contrary, in the latter trial there were no
OS gains in PD-L1 5% patients treated with nivolumab
versus chemotherapy [133]. As there are no perceived dif-
ferences in the potency of these antibodies, the obvious
discrepancy in the patient population could account for the
different outcome. However, several observations hinder
the routine selection of appropriate candidates according to
PD-L1 expression. First, in addition to the modest con-
cordance rates between the various antibodies used to assess
PD-L1 expression reported in the literature, questions still
remain regarding the uncontrolled pre-analytical conditions
and the assay and inter-pathologist discrepancies [159],
which can lead to PD-L1 status misclassi?cations despite
the similar analytical performance of the available assays
[160]. Second, PD-L1 expression exhibits signi?cant
intratumoral, intertumoral and temporal heterogeneity [161,
162], putting into question the widespread practice of
assessing PD-L1 IHC expression on archival tissue. Third,
as clearly shown in individual randomized trials such as the
CheckMate 017 trial at the second line of lung SCC [135],
characterizing patients as appropriate for anti-PD-1 therapy
according to PD-L1 expression both includes patients who
do not respond to treatment and also excludes potential
responders. Fourth, in the aforementioned CheckMate 026
trial, nivolumab was not more effective than chemotherapy
even in the subgroup of 50% or higher PD-L1 expression.
As this was not a strati?cation factor, imbalances such as
the sex of the patients could have confounded the results,
implying that PD-L1 positivity by itself is not a strong
predictive biomarker [133]. Finally, the association of
objective response rates and PD-L1 expression in the trial-
level meta-analyses is of unsure clinical importance, since
checkpoint inhibitors can confer prolonged, clinically
meaningful periods of disease stabilization and because
their use beyond progression in patients deemed to derive
clinical bene?t has been found to improve outcomes in a
diverse selection of solid malignancies [163165].
Keeping in mind the shortcomings of PD-L1 expression,
other biomarkers have been explored. Following the
observation that smokers with NSCLC seem to derive
improved bene?t from anti-PD-1 agents [166], it was pos-
tulated that this effect may be a surrogate marker for an
increased mutational load and subsequent increased
neoantigen production and exposure and more effective
immune response in patients chronically exposed to a strong
mutagenic factor such as smoking. Indeed, mutational load
has been found to be a predictive factor in NSCLC [167].
I. Zerdes et al.
Table 4 Examples of studies reporting a correlation of PD-1/L1 status and prognosis
Tumor type PD-1/L1 status Correlation with outcome Reference
Breast cancer
All PD-L1 expression Unfavorable [174,178,219]
All PD-L1 expression Favorable [175]
HER2+PD-L1 expression Unfavorable [179]
TNBC PD-L1 expression Favorable [176]
TNBC PD-L1 ampli?cation Unfavorable [16]
Residual after neoadjuvant PD-L1 expression Unfavorable [177]
Gastrointestinal cancer
All digestive tumors PD-L1 expression Unfavorable [183]
Hepatocellular cancer PD-L1/2 expression Unfavorable [180,181]
Colorectal cancer PD-L1 expression Favorable [186,209]
Colorectal cancer PD-L2 expression Unfavorable [187]
Gastric cancer PD-L1 expression Unfavorable [184,185]
Cholangiocarcinoma PD-L1 expression Unfavorable [217]
Esophageal cancer PD-L1 expression Favorable [214]
Pancreatic cancer PD-1 expression Favorable [182]
Genitourinary cancer
Clear cell renal PD-L1/2 expression Unfavorable [195197]
Non-clear cell renal PD-L1 expression Unfavorable [194]
Papillary renal PD-L1 expression Unfavorable [193]
Chromophobe renal PD-L2 expression Unfavorable [192]
Bladder cancer PD-L1 expression Unfavorable [191,218]
Prostate cancer PD-1 expression Unfavorable [190]
Prostate cancer PD-L1 expression Unfavorable [189]
Ovarian cancer PD-L1 expression Favorable [188,210]
Lung and head and neck cancer
NSCLC PD-L1 expression Favorable [211,213]
NSCLC PD-L1 expression Unfavorable [202206]
NSCLC PD-L1 expression Not predictive [202]
NSCLC PD-L1 ampli?cation Unfavorable [200]
SCLC PD-L1 expression Unfavorable [201]
Pulmonary neuroendocrine PD-L1 expression Unfavorable [220]
Head and neck cancer PD-L1 expression Favorable [199,215]
Head and neck cancer PD-L1 expression Unfavorable [198]
Melanoma and sarcoma
Melanoma PD-L1 expression Favorable [212]
Melanoma PD-L1 expression Unfavorable [208]
Soft tissue sarcoma PD-L1 expression Unfavorable [207]
Hematologic malignancies
Hodgkins lymphoma PD-1 expression Unfavorable [222]
Hodgkins lymphoma PD-1/L-1 co-expression Unfavorable [225]
Hodgkins lymphoma PD-L1 ampli?cation Unfavorable [121]
DLBCL PD-L1 expression Unfavorable [216,227]
NK/T-cell lymphoma PD-L1 expression Unfavorable [226]
Multiple myeloma Soluble PD-L1 Unfavorable [223,224]
All tumor types
Meta-analyses PD-L1 expression Unfavorable [221,228,229]
HER2 human epidermal growth factor receptor, TNBC triple-negative breast cancer, NSCLC non-small cell lung cancer, SCLC small cell lung
cancer, DLBCL diffuse large B-cell lymphoma, NK natural killer cells
Genetic, transcriptional and post-translational regulation of the programmed death protein ligand 1. . .
Supporting this association is the observation that mismatch
repair defective, and thus hypermutated tumors, are exqui-
sitely sensitive to PD-1 blockade [168,169]. In addition,
NSCLC harboring driver molecular aberrations such as
EGFR mutations, which exhibit lesser mutational loads
have been shown to be relatively resistant to immune
checkpoint inhibition [170], a ?nding supported by a
recently published meta-analysis on the prediction of
response in NSCLC patients. EGFR mutant and KRAS wild-
type status were associated with a lack of sensitivity to PD-
1/PD-L1 inhibition, whereas clinical factors such as smok-
ing status, histology, sex, performance status, and age did
not affect the magnitude of bene?t[171].
The quantitative and qualitative assessment of the host
immune response has also been explored as a predictor in
checkpoint inhibition. Factors such as the abundance of pre-
existing CD8 (+) T cells, a restricted (clonal) TCR reper-
toire, a TH1-type response, increased levels of IFN-γand
IL-18 and decreased levels of IL-6, among others, have
been correlated with improved responses [166,172], but
these results need to be evaluated prospectively in rando-
mized trials. The implementation of multiparametric, high-
throughput ?ow cytometry, and multiplex immunohisto-
chemical staining techniques that vastly improve the T-cell
population analysis [173] and of whole-exome sequencing
for the evaluation of the mutational load and the presence of
speci?c, predictive molecular alterations will aid in this
On the other hand, PD-1 and PD-L1 expression both at
the tissue level and on circulating tumor cells have been
evaluated in a wide variety of malignancies for their prog-
nostic impact (Table 4)[17,21,174229]. The results have
been thus far inconsistent among tumor types and somewhat
confusing, with reports supporting both an improved and a
decreased OS conferred by high expression, a phenomenon
that resonates the previously mentioned shortcomings of the
assessment of PD-L1. The biologic background of these
observations is as of yet uncertain. Moreover, as the
expansion of the indications of PD-1/PD-L1 blockade
continues with the conduct and report of clinical trials, these
associations could be affected due to the increasing use of
these agents, making their clinical utility questionable at the
Open questions for future research
Despite the progress in genetic and epigenetic regulation of
PD-L1 expression, several gaps in the literature should be
covered by intensive laboratory-based research. For
instance, the signaling transduction pathways involved in
PD-L1 regulation are only partially understood. Better
understanding of the signaling mechanisms could provide
the biologic rationale for combined targeted therapy with
immunotherapy strategies in cancer. Furthermore, little is
known about the post-translational modi?cations of PD-L1
protein including tyrosine or serine/threonine phosphoryla-
tion, acetylation, ubiquitination, and SUMOylation. It is
also largely unknown how possible post-translational
modi?cations not only regulate PD-L1 levels in the tumor
cells, but also how they might affect its physiologic function
or its interaction with the PD-1 receptor. In addition to PD-
L1, the non-genetic mechanisms underlying PD-L2
expression and function in solid tumors and hematologic
malignancies should be investigated, as both ligands com-
pete for the same receptor, PD1, and therefore the relative
levels of both proteins may impact certain immunotherapy
Regarding clinical practice, regulatory authorities both in
Europe (European Medicine Agency), and the United States
(Food and Drug Administration) have approved the use of
PD-1/PD-L1 inhibitors for a variety of malignancies
regardless of the presence or absence of predictive bio-
markers. Exceptions include the use of pembrolizumab at
the ?rst and second line of NSCLC, which requires PD-L1
expression levels of 50% and 1% respectively, as well as
the site agnostic indication for mismatch repair de?cient
tumors. In addition, the ?nancial burden of the generalized
use of these agents is considerable even in high-resource
settings [230]. Overcoming this obstacle and achieving the
personalized use of these agents requires a stepwise
approach: ?rst, taking into account the previously men-
tioned shortcomings of PD-L1 as a potential biomarker, it is
important to retrospectively identify, in the large amount of
collected tumor material from prospective studies, novel
predictive biomarkers. These would ideally be pro-
spectively validated, although the logistics of repeating
single agent trials might be prohibitive. Instead, these bio-
markers could form the basis of the next-generation com-
binatorial trials, of trials addressing the as yet unanswered
question of the optimal duration of treatment or of trials in
earlier disease settings where the overtreatment of already
cured individuals in a massive scale could pose a signi?cant
public health burden.
Despite the clinical success of immune checkpoint inhibi-
tion in many tumors through PD-L1/PD-1 blockade, rela-
tively little is known regarding the biology of these
regulators of cancer immune surveillance. Many mechan-
isms have been demonstrated to regulate the expression of
PD-L1 including signaling pathways, transcriptional fac-
tors, and post-transcriptional modulators. The oncogenic
signaling pathways such as JAK/STAT, RAS/ERK, or
I. Zerdes et al.
PI3K/AKT/MTOR are activated by gene mutations and
growth factors. At the transcriptional level, a number of
transcriptional factors seem to regulate PD-L1 expression
including HIF-1, STAT3, NF-κΒ, and AP-1. PD-L1 is
subject to post-transcriptional regulation by several miR-
NAs, CSN5, CMTM6, CDK4 and possibly other, still
unknown mechanisms. Better understanding of PD-L1
regulation may pave the way for combinational treatments
with both immune checkpoint inhibitors and targeted
therapies against kinases or transcription factors many of
which are already available for clinical use.
Acknowledgements We thank Dr. Ioannis Mantas for his help with
illustrative work.
Funding This study was supported by the Swedish Cancer Society
(CAN 2015/713 to TF); the Cancer Society in Stockholm (154132 to
TF); The Swedish Breast Cancer Association (IZ, TF); European
Society for Medical Oncology Georges Mathe?Translational Research
Fellowship (AM); and Hellenic Society of Medical Oncology (AM).
Compliance with ethical standards
Con?ict of interest Dr. Foukakis has received research grants (insti-
tutional) from P?zer and Roche; personal fees from Novartis, P?zer,
Roche and UpToDate outside the submitted work. The remaining
authors declare that they have no con?ict of interest.
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Genetic, transcriptional and post-translational regulation of the programmed death protein ligand 1. . .
... PD-L1 and PD-L2 are encoded by the CD274 and PDCD1LG2 genes, respectively, that are integral parts of chromosome 9p.24.1, while PD-1 is encoded by the PDCD1 gene on chromosome 2q37.3 (24,25). The genomic alterations of the PD-L1/PD-L2 gene loci appear to be mainly responsible for PD-L1 expression both in malignant diseases. ...
... This results in two possible ways: direct action on target genes or the activation of transcription factors like STAT3, STAT1, c-Jun, HIFs, or NF-κB which inside the nucleus links to particular sites on PD-L1 gene promoter inducing its expression. PD-L1 is also directed post-transcriptionally by microRNAs, that links to mRNA resulting in its suppression or enhancement(24,26).Activation of PD-L1 signaling pathway in the context of constitutive oncogenic signaling activation includes loss of PTEN expression, activation of different pathways including PI3K/AKT, RAS/MAPK, RAS/ERK/EMT and MAPK/ERK, inhibition of p53 signaling, upregulation of reprogramming factors (Oct4, Sox2, and c-Myc) and upregulation of ZEB1 [an inducer of epithelial-tomesenchymal transition (EMT)] (26-28). Regulation of PD-L1 expression thus is directed via the PI3K/AKT and/ or RAS/MAPK pathways in variety of cancer cell types. ...
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Abstract: Thymic epithelial tumors (TETs) include several anterior mediastinal malignant tumours: thymomas, thymic carcinomas and thymic neuroendocrine cancers. There is significant variety in the biologic features and clinical course of TETs and many attempts have been made to identify target genes for successful therapy of TETs. Next generation sequencing (NGS) represents a huge advancement in diagnostics and these new molecular technologies revealed that thymic neoplasms have the lowest tumor mutation burden among all adult malignant tumours with a different pattern of molecular aberrations in thymomas and thymic carcinomas. As for the PD-L1 expression in tumor cells in thymoma and thymic carcinoma, it varies a lot in published studies, with findings of PD-L1 expression from 23% to 92% in thymoma and 36% to 100% in thymic carcinoma. When correlated PD-L1 expression with disease stage some controversial results were obtained, with no association with tumor stage in most studies. This is, at least in part, explained by the fact that several diverse PD-L1 immunohistochemical tests were used in each trial, with four different antibodies (SP142, SP263, 22C3, and 28-8), different definition of PD-L1positivity and cutoff values throughout the studies as well. There is a huge interest in using genomic features to produce predictive genomic-based immunotherapy biomarkers, particularly since recent data suggest that certain tumor-specific genomic alterations, either individually or in combination, appear to influence immune checkpoint activity and better responses as the outcome, so as such in some cancer types they may complement existing biomarkers to improve the selection criteria for immunotherapy.
... Cancer cells can overexpress PD-L1 upon type I interferon (IFN I) stimulation [30] to evade cytotoxic immune responses. Immune cells, including Treg, myeloidderived suppressor cells (MDSC), dendritic cells (DC) and TEC can similarly upregulate PD-L1 upon inflammatory signals (especially by IFNs) fostering an immunosuppressive TME [31]. ...
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Immunotherapy (IO) has revolutionized the therapy landscape of non-small cell lung cancer (NSCLC), significantly prolonging the overall survival (OS) of advanced stage patients. Over the recent years IO therapy has been broadly integrated into the first-line setting of non-oncogene driven NSCLC, either in combination with chemotherapy, or in selected patients with PD-L1high expression as monotherapy. Still, a significant proportion of patients suffer from disease progression. A better understanding of resistance mechanisms depicts a central goal to avoid or overcome IO resistance and to improve patient outcome.We here review major cellular and molecular pathways within the tumor microenvironment (TME) that may impact the evolution of IO resistance. We summarize upcoming treatment options after IO resistance including novel IO targets (e.g. RIG-I, STING) as well as interesting combinational approaches such as IO combined with anti-angiogenic agents or metabolic targets (e.g. IDO-1, adenosine signaling, arginase). By discussing the fundamental mode of action of IO within the TME, we aim to understand and manage IO resistance and to seed new ideas for effective therapeutic IO concepts.
... La longueur totale de PD-L1 est codée dans sept exons, ce qui correspond à une protéine de 40 kDa de 290 acides aminés ( Figure 12). Comme dans tout type de protéines, la régulation de PD-L1 est complexe et peut intervenir à de nombreux niveaux, pas seulement transcriptionnel mais aussi par des mécanismes de régulation post-transcriptionnelle ou post-traductionnelle qui doivent encore être clarifiés (Zerdes et al. 2018). ...
Malgré les nombreux progrés réalisés ces dernières années dans la prise en charge thérapeutique du cancer broncho-pulmonaire, cette pathologie reste la première cause de décès lié au cancer dans le monde. L’enjeu majeur pour cette maladie est donc de développer de nouveaux traitements et d’optimiser l’utilisation des drogues existantes, en particulier les sels de platine. Les protocoles combinant des inhibiteurs de points de contr?le immunitaire avec des sels de platine est actuellement en plein essor malgré un certain manque en études précliniques. Dans ce travail, j’ai cherché à évaluer l'impact du cisplatine sur l'expression de PD-L1 en analysant des patients ayant re?u une chimiothérapie néo-adjuvante à base de cisplatine. Le traitement d'induction augmentait considérablement le marquage PD-L1 des cellules tumorales et immunitaires du microenvironnement. Vingt-deux patients présentaient une variation positive du pourcentage de cellules tumorales PD-L1+ après chimiothérapie néoadjuvante; dont 9 (23,1%) passant de <50% à ≥50% des cellules tumorales marquées. Nous avons également confirmé la régulation positive de PD-L1 par le cisplatine, tant au niveau de l'ARNm qu’au niveau protéique, in-vitro et in-vivo sur des souris nude et des souris immunocompétentes greffées par des tumeurs expérimentales issues de lignées cellulaires de cancer du poumon A549, LNM-R ou LLC1. L’up-régulation de PD-L1 par le cisplatine fait intervenir la voie de signalisation PI3K/AKT. De plus, l'administration combinée d'anticorps anti-PD-L1 (3 mg / kg) et de cisplatine (1 mg / kg) à des souris portant un carcinome pulmonaire réduisait significativement la croissance tumorale par rapport aux traitements en monothérapie et par rapport aux contr?les. Le cisplatine augmente donc précocément et durablement l'expression de PD-L1 et pourrait donc agir de manière synergique avec un blocage de PD-1 / PD-L1 pour améliorer la réponse tumorale aux traitements. En parallèle, nous avons pu développer une thérapie ciblée anti-neurotensine permettant de bloquer ses effets paracrines stimulants la prolifération, la croissance, et les capacités d’invasion des cellules de tumeurs pulmonaires. Les anticorps anti-neurotensine amélioraient également la sensibilité au cisplatine de tumeurs préalablement résistantes par des mécanismes qui impliquent probablement l’augmentation de l’influx et la diminution de l’efflux de platine au niveau de sa cible intra-nucléaire qu’est l’ADN. L’ensemble de ces résultats apportent du rationnel à la réalisation d’essais cliniques impliquant le cisplatine et visant par différents biais à améliorer l’efficacité de traitements systémiques de cancers broncho-pulmonaires non à petites cellules.
... It is important to appreciate that tumour-immune interaction is heterogeneous, dynamic and also bidirectional. For instance, immune pressure could potentially drive tumour genomic evolution 14,34 ; in return, immune landscapes are also constantly being shaped by the tumour transcriptomic landscapes 35,36 . From our current data, the HCC TME shifted from homogenously "good" to heterogenously "bad" albeit exhausted and suppressive TME, forming a gradient of decreasing immunoselective pressure, an indication of immune landscape evolution. ...
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The clinical relevance of immune landscape intratumoural heterogeneity (immune-ITH) and its role in tumour evolution remain largely unexplored. Here, we uncovered significant spatial and phenotypic immune–ITH from multiple tumour sectors and deciphered its relationship with tumour evolution and disease progression in hepatocellular carcinomas (HCC). Immune–ITH was associated with RNA-ITH and distinct immune microenvironments. Tumours with low immune–ITH experienced higher immunoselective pressure and underwent escape mechanisms via loss of heterozygosity in human leukocyte antigens and immunoediting. Instead, the tumours with high immune-ITH were associated with a more immunosuppressive/exhausted microenvironment. This immune pressure gradient along with immune-ITH represents a hallmark of tumour evolution closely linked to the transcriptome-immune networks contributing to disease progression and immune inactivation. Remarkably, high immune-ITH and its transcriptomic signature were predictive for worse clinical outcome in HCC patients. This in-depth investigation of ITH provides novel evidence on tumour-immune co-evolution along HCC progression.
... 11 Moreover, PD-L1, one of the hot spots in current immunotherapy, was reported to be regulated by JAK/STAT signaling in many cell types, especially JAK2/STAT1 and JAK2/STAT3. 12 However, one group reported that PD-L1 was also regulated by interferon-gamma-JAK1/JAK2-STAT1/STAT2/ STAT3-IRF1 axis in melanoma cells. 13 Physiologically, JAK2/STAT3 is commonly transition activated and can be inactivated by dephosphorylation of its upstream kinase by phosphatases, including small heterodimer partners and suppressors of cytokine signaling. ...
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Background We have previously discovered a relationship between the low expression of protein tyrosine phosphatase, receptor type O (PTPRO) in tumor-infiltrating T cells and immunosuppression. The aim of the present study was to investigate the relationship between decreased PTPRO and increased programmed death ligand 1 (PD-L1) in both the peripheral monocytes and tumor-infiltrating macrophages of human hepatocellular carcinoma (HCC). Methods The expression and correlation of all the indices were explored in monocytes and tumor-infiltrating macrophages within both human and mice HCC. The mechanic regulations were studied by using both in vitro and in vivo studies. Results We found a significant decrease in PTPRO in HCC peripheral monocytes that was associated with increased PD-L1 expression in peripheral monocytes and tumor-associated macrophages (TAMs) in HCC. Monocyte PD-L1 and PTPRO therefore could serve as valuable prognostic indicators for post-surgery patients with HCC and were associated with increased T-cell exhaustion (Tim3+T cells). A depletion of PTPRO promoted PD-L1 secretion in both monocytes and macrophages through the JAK2/STAT1 and JAK2/STAT3/c-MYC pathways. Increased IL-6 expression was associated with activation of JAK2/STAT3/c-MYC and with decreased PTPRO expression through the STAT3/c-MYC/miR-25–3 p axis. Monocytes and TAMs showed significantly increased miR-25–3 p expression, which could target the 3′ untranslated region of PTPRO. The miR-25–3 p expression positively correlated with serum IL-6 levels, but inversely correlated with PTPRO in HCC monocytes. IL-6/STAT3/c-MYC activation enhanced in vitro miR-25–3 p transcription and decreased PTPRO, while further promoting PD-L1 secretion. Adoptive cell transfer of c-MYC/miR-25–3 p–modified monocytes promoted tumor growth by downregulating PTPRO and causing a PD-L1–induced immunosuppression in an orthotopic tumor transplantation model. Conclusions Increased serum IL-6 downregulated PTPRO expression in HCC monocytes and macrophages by activating STAT3/c-MYC/miR-25–3 p and by further enhancing PD-L1 expression through JAK2/STAT1 and JAK2/STAT3/c-MYC signaling.
... Several reports have demonstrated that some cytotoxic agents including fluorouracil, paclitaxel, and radiation therapy can upregulate PD-L1 expression via cell signaling pathways in GI cancer. [67][68][69] Notably, Yang et al reported that GC patients with a preferable response to chemotherapy displayed PD-L1 downregulation and showed better RFS, whereas pretreatment PD-L1 status was not associated with survival. 70 Ogura et al also demonstrated equivalent results in patients with rectal cancer who received CRT. ...
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Cancer immunotherapy has caused a paradigm shift from conventional therapies that directly target cancer cells to innovative therapies that utilize the host immune system. In particular, programmed cell death‐1 (PD‐1)/programmed death ligand‐1 (PD‐L1) inhibitors have achieved an impressive breakthrough and been approved for clinical use in several types of cancer including gastrointestinal (GI) cancer. To identify and develop predictive biomarkers for PD‐1 inhibitors is of great concern in clinical practice. Although PD‐L1 expression is considered a logical biomarker as PD‐L1 is a substantial target of the immune checkpoint inhibitors, its clinical significance in GI cancer remains unclear. In this review, we summarize the current evidence for PD‐L1 expression as a prognostic and predictive biomarker for PD‐1/PD‐L1 inhibitors in GI cancer from recent publications, and emerging evidence from recent key clinical trials on the efficacy of PD‐1/PD‐L1 inhibitors. Challenging clinical issues for PD‐L1 assessment are then discussed from the viewpoint of the methodology for PD‐L1 evaluation including the differences in PD‐L1 detection assays and evaluation criteria for PD‐L1 positivity. Moreover, we highlight the biological features of PD‐L1 expression in terms of tumor spatial and temporal heterogeneity, which suggests important implications for biomarker analysis. Finally, we describe future perspectives using liquid biopsy for better assessment of PD‐L1 status. This new information should improve our understanding of the clinical significance of PD‐L1 in GI cancer, leading to optimal patient selection and treatment strategy for the clinical use of PD‐1/PD‐L1 inhibitors in patients with GI cancer.
Cancer immunotherapy harness the body's immune system to eliminate cancer, by using a broad panel of soluble and membrane proteins as therapeutic targets. Immunosuppression signaling mediated by ligand-receptor interaction may be blocked by monoclonal antibodies, but because of repopulation of the membrane via intracellular organelles, targets must be eliminated in whole cells. Targeted protein degradation, as exemplified in proteolysis targeting chimera (PROTAC) studies, is a promising strategy for selective inhibition of target proteins. The recently reported use of lysosomal targeting molecules to eliminate immune checkpoint proteins has paved the way for targeted degradation of membrane proteins as crucial anti-cancer targets. Further studies on these molecules' modes of action, target-binding "warheads", lysosomal sorting signals, and linker design should facilitate their rational design. Modifications and derivatives may improve their cell-penetrating ability and the in vivo stability of these pro-drugs. These studies suggest the promise of alternative strategies for cancer immunotherapy, with the aim of achieving more potent and durable suppression of tumor growth. Here, the successes and limitations of antibody inhibitors in cancer immunotherapy, as well as research progress on PROTAC- and lysosomal-dependent degradation of target proteins, are reviewed.
Purpose To evaluate the effects of hepatic artery embolization (HAE) on the expression of programmed cell death 1 ligand 1 (PD-L1) in an orthotopic rat hepatocellular carcinoma (HCC) model. Materials and Methods A rat HCC model was established in Sprague–Dawley rats with the RH7777 cell line. Six animals each were assigned to receive HAE or sham treatment. Liver tissues were harvested 24 h after the procedure. Immunohistochemistry (IHC) was used to compare expression of PD-L1 and hypoxia-inducible factor (HIF)–1α in the intratumoral and peritumoral regions and normal liver tissue. In vitro cell culture study was performed for 24 h under normoxic and hypoxic conditions, and protein expression of PD-L1 and HIF-1α and the effects of HIF-1α inhibitors were assessed. Results IHC showed that PD-L1– and HIF-1α–positive areas were significantly larger in the HAE group vs the sham group in intratumoral (P = .006 and P < .001, respectively) and peritumoral regions (both P < .001). The expression of PD-L1 positively correlated with HIF-1α expression in the intratumoral region (r2 = 0.551; P < .001). In vitro cell culture study revealed that protein expression of PD-L1 and HIF-1α were significantly higher when cells were incubated under hypoxic vs normoxic conditions (P = .028 and P = .010, respectively). PD-L1 expression was suppressed significantly when the HIF-1α inhibitor rapamycin was added to the culture medium (P = .024). Conclusions HAE enhances intratumoral and peritumoral PD-L1 expression in a rat HCC model. The HIF-1α pathway is a possible mechanism underlying increased intratumoral PD-L1 expression after HAE.
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Background: Immune-checkpoint inhibitors (ICIs) have been approved as 1st line therapy and benefit patients with advanced cancer. However, still many patients fail to achieve the significant efficacy, a predictor for precise patient selection is needed. The aim of our study is to determine whether the administration of antibiotics before or at the beginning of ICIs treatment is a prognostic factor of progression-free survival (PFS) and overall survival (OS) in patients with advanced cancer. Methods: A systematic search in PubMed, Embase, Cochrane and Web of Science databases was conducted using the search terms antibiotic, PD-1, PD-L1, CTLA-4, combined with cancer, tumor, neoplasm, or carcinoma. Data extraction was performed independently. Hazard ratio (HR) for PFS and OS of antibiotics (+) group vs antibiotics (-) group were pooled according to random or fixed-effects models. HRs with 95% confidence intervals (CIs) for PFS and OS were pooled to obtain prognostic information and aggregate values. Results: Nine studies including 1163 patients were included in this meta-analysis. By PFS analysis, antibiotics administration was associated with a significantly increased risk of disease progression (HR, 1.76; 95% CI, 1.37-2.26; P< 0.01). By OS analysis, antibiotics uptake also showed an HR in favor of death (HR, 1.7; 95% CI, 1.40-2.07; P< 0.01). Conclusions: Based on the existing evidence, antibiotics administration is a prognostic factor for reduced PFS and OS in patients receiving ICIs treatment. The time interval between antibiotics administration and ICIs treatment should be considered.
Aims The advent of immune checkpoint inhibitor therapy has proven beneficial in a subset of high-grade urothelial carcinomas (HGUC) of the bladder. Although treatment selection is currently largely determined by programmed death-ligand 1 (PD-L1) status, multiple factors in the immune system may modulate the host immune response to HGUC and immunotherapy. In this pilot study, we used a transcriptomic approach to identify the immune milieu associated with PD-L1 expression to enhance our understanding of the HGUC immune evasion network. Methods The immune transcriptome of 40 HGUC cystectomy cases was profiled using the NanoString nCounter Human V.1.1 PanCancer Panel. All cases were assessed for associated PD-L1 status (SP263) using whole tissue sections. PD-L1 status was determined as high or low using 25% tumour and/or immune cell staining. Results The most significantly differentially expressed gene was PD-L1 messenger RNA ( CD274 ), which strongly correlated with protein expression (r=0.720, p<0.001). The sensitivity, specificity, positive and negative predictive values of CD274 for PD-L1 expression were 85%, 96%, 92% and 93%, respectively. The PD-L1 associated gene signature also included complement components C1QA and CD46 and NOD2 (innate immune system), proinflammatory cytokines CXCL14, CXCL16, CCL3, CCL3L1 and OSM along with the immune response mediator SMAD3, among others. Pathway analysis determined enrichment of these genes in interleukin-10 production, lymphocyte chemotaxis and aberrant IFNγ, NF-κB and ERK signalling networks. Conclusions We report key genes and pathways in the immune transcriptome and their association with PD-L1 status, which may be involved in immune evasion of HGUC and warrants further investigation.
Literature Review
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Accumulating evidence suggests that exogenous cellular stress induces PD-L1 upregulation in cancer. A DNA double-strand break (DSB) is the most critical type of genotoxic stress, but the involvement of DSB repair in PD-L1 expression has not been investigated. Here we show that PD-L1 expression in cancer cells is upregulated in response to DSBs. This upregulation requires ATM/ATR/Chk1 kinases. Using an siRNA library targeting DSB repair genes, we discover that BRCA2 depletion enhances Chk1-dependent PD-L1 upregulation after X-rays or PARP inhibition. In addition, we show that Ku70/80 depletion substantially enhances PD-L1 upregulation after X-rays. The upregulation by Ku80 depletion requires Chk1 activation following DNA end-resection by Exonuclease 1. DSBs activate STAT1 and STAT3 signalling, and IRF1 is required for DSB-dependent PD-L1 upregulation. Thus, our findings reveal the involvement of DSB repair in PD-L1 expression and provide mechanistic insight into how PD-L1 expression is regulated after DSBs.
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Treatments that target immune checkpoints, such as the one mediated by programmed cell death protein 1 (PD-1) and its ligand PD-L1, have been approved for treating human cancers with durable clinical benefit1,2. However, many cancer patients fail to respond to anti-PD-1/PD-L1 treatment, and the underlying mechanism(s) is not well understood3–5. Recent studies revealed that response to PD-1/PD-L1 blockade might correlate with PD-L1 expression levels in tumor cells6,7. Hence, it is important to mechanistically understand the pathways controlling PD-L1 protein expression and stability, which can offer a molecular basis to improve the clinical response rate and efficacy of PD-1/PD-L1 blockade in cancer patients. Here, we report that PD-L1 protein abundance is regulated by cyclin D-CDK4 and the Cullin 3SPOP E3 ligase via proteasome-mediated degradation. Inhibition of CDK4/6 in vivo elevates PD-L1 protein levels, largely by inhibiting cyclin D–CDK4-mediated phosphorylation of SPOP and thereby promoting SPOP degradation by APC/CCdh1. Loss-of-function mutations in SPOP compromise ubiquitination-mediated PD-L1 degradation, leading to increased PD-L1 levels and reduced numbers of tumor-infiltrating lymphocytes (TILs) in mouse tumors and in primary human prostate cancer specimens. Notably, combining CDK4/6 inhibitor treatment with anti-PD-1 immunotherapy enhances tumor regression and dramatically improves overall survival rates in mouse tumor models. Our study uncovers a novel molecular mechanism for regulating PD-L1 protein stability by a cell cycle kinase and reveals the potential for using combination treatment with CDK4/6 inhibitors and PD-1/PD-L1 immune checkpoint blockade to enhance therapeutic efficacy for human cancers.
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Cytotoxic T cells infiltrating tumors are thought to utilize HIF transcription factors during adaptation to the hypoxic tumor microenvironment. Deletion analyses of the two key HIF isoforms found that HIF-1α, but not HIF-2α, was essential for the effector state in CD8? T cells. Furthermore, loss of HIF-1α in CD8? T cells reduced tumor infiltration and tumor cell killing, and altered tumor vascularization. Deletion of VEGF-A, an HIF target gene, in CD8? T cells accelerated tumorigenesis while also altering vascularization. Analyses of human breast cancer showed inverse correlations between VEGF-A expression and CD8? T cell infiltration, and a link between T cell infiltration and vascularization. These data demonstrate that the HIF-1α/VEGF-A axis is an essential aspect of tumor immunity. Palazon et al. demonstrate the importance of the HIF-1α/VEGF-A axis in tumor immunity. HIF-1α, but not HIF-2α, drives CD8? T cell glycolytic metabolism, migration, and effector function, while the HIF-1α transcriptional target VEGF-A contributes to tumor vascularization.
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Programmed death ligand 1 (PD-L1) is expressed on a number of immune and cancer cells, where it can downregulate antitumor immune responses. Its expression has been linked to metabolic changes in these cells. Here we develop a radiolabeled camelid single-domain antibody (anti-PD-L1 VHH) to track PD-L1 expression by immuno-positron emission tomography (PET). PET-CT imaging shows a robust and specific PD-L1 signal in brown adipose tissue (BAT). We confirm expression of PD-L1 on brown adipocytes and demonstrate that signal intensity does not change in response to cold exposure or β-adrenergic activation. This is the first robust method of visualizing murine brown fat independent of its activation state.
Background: Abemaciclib is a selective and potent small molecule inhibitor of CDK4 and 6, with evidence of single-agent antitumor activity, and a safety profile that enables dosing on a continuous schedule. Abemaciclib demonstrated anti-tumor activity as a single agent with a 19.7% objective response rate for women with previously treated HR+, HER2- MBC1. In the phase 1b study JPBH, abemaciclib demonstrated a tolerable safety profile when combined with endocrine or HER2 targeted agents for MBC2. Abemaciclib given BID in combination with pembrolizumab also demonstrated a tolerable safety profile in phase 1b study of stage IV NSCLC3. Methods: JPCE is a multicenter, nonrandomized, open-label, phase 1b study of abemaciclib plus pembrolizumab for patients with HR+, HER2- MBC or NSCLC ( NCT02779751). The study has 3 disease-specific cohorts, each with approximately 25 patients (N=75); the HR+, HER2- MBC cohort (part C) will be presented here. The primary objective was to characterize safety of the abemaciclib and pembrolizumab combination. Secondary objectives included efficacy endpoints (objective response rate, disease control rate, duration of response, progression-free survival, and overall survival), pharmacokinetics of abemaciclib plus pembrolizumab, and changes in patient-reported pain and disease-related symptoms. Patients received 150 mg of abemaciclib orally Q12H plus pembrolizumab 200 mg as a 30-minute IV infusion on Day 1 every 21 days. Eligible patients included women with confirmed HR+, HER2- MBC who have previously received at least 1 but no more than 2 prior chemotherapy regimens for MBC; are able to provide tumor tissue at baseline and at cycle 3, day 1; have measurable disease (RECIST v.1.1), adequate organ function, ECOG PS ≤1, are able to swallow oral medications; and have not received treatment with CDK4 & 6 or PD-1/ PD-L1 inhibitors. Results: At the time of abstract submission, study JPCE part C cohort (HR+, HER2- MBC) was fully enrolled at 25 patients. Data to be presented include patient demographics, baseline disease characteristics, adverse events by frequency and by grade, and preliminary efficacy of the abemaciclib plus pembrolizumab combination in HR+, HER2- MBC. References: 1. Dickler et al, Clin Cancer Res. 2017 2. Goetz et al. poster presented at SABCS, 2015 3. Goldman et al. poster presented at IASLC 2016 Citation Format: Rugo HS, Kabos P, Dickler MN, John WJ, Smith I, Lu Y, Young S, Tolaney SM. A phase 1b study of abemaciclib plus pembrolizumab for patients with hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) metastatic breast cancer (MBC) [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P1-09-01.
Protein glycosylation provides proteomic diversity in regulating protein localization, stability, and activity; it remains largely unknown whether the sugar moiety contributes to immunosuppression. In the study of immune receptor glycosylation, we showed that EGF induces programmed death ligand 1 (PD-L1) and receptor programmed cell death protein 1 (PD-1) interaction, requiring β-1,3-N-acetylglucosaminyl transferase (B3GNT3) expression in triple-negative breast cancer. Downregulation of B3GNT3 enhances cytotoxic T cell-mediated anti-tumor immunity. A monoclonal antibody targeting glycosylated PD-L1 (gPD-L1) blocks PD-L1/PD-1 interaction and promotes PD-L1 internalization and degradation. In addition to immune reactivation, drug-conjugated gPD-L1 antibody induces a potent cell-killing effect as well as a bystander-killing effect on adjacent cancer cells lacking PD-L1 expression without any detectable toxicity. Our work suggests targeting protein glycosylation as a potential strategy to enhance immune checkpoint therapy.