immune escape after adoptive t cell therapy for malignant ......2020/08/11 · introduction...
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Immune escape after adoptive T cell therapy for malignant gliomas Tyler J. Wildes1, Kyle A. Dyson1, Connor Francis1, Brandon Wummer1, Changlin Yang1, Oleg Yegorov1, David Shin1, Adam Grippin1, Bayli DiVita Dean1, Rebecca Abraham1, Christina Pham1, Ginger Moore1, Carmelle Kuizon1, Duane A. Mitchell1, Catherine T. Flores1* 1University of Florida Brain Tumor Immunotherapy Program, Preston A. Wells, Jr. Center for Brain Tumor Therapy, Lillian S. Wells Department of Neurosurgery, McKnight Brain Institute, University of Florida, Gainesville, Florida, USA. Running Title: Glioma immune escape after immunotherapy Keywords: Glioma, Immune escape, Immunotherapy, Adoptive cellular therapy (ACT), Immune Checkpoint Blockade, Tumor escape Acknowledgments: This research was supported by the University of Florida Health Cancer Center Predoctoral Award (T. Wildes); American Brain Tumor Association Research Collaboration Grant (C. Flores); Alex’s Lemonade Stand Young Investigator Grant (C. Flores); Florida Center for Brain Tumor Research Grant (C. Flores); Wells Foundation; and University of Florida Clinical and Translational Sciences Award (UL1TR001427). *Corresponding author: Catherine T. Flores, Ph.D., University of Florida Brain Tumor Immunotherapy Program, Preston A. Wells, Jr. Center for Brain Tumor Therapy, Lillian S. Wells Department of Neurosurgery, McKnight Brain Institute, PO Box 100265, Gainesville, FL 32610; (352) 294-5269; [email protected] Conflict of interest: CTF and DAM have patents related to material disclosed in this publication that have been licensed to iOncologi, Inc. CTF and DAM hold interests in iOncologi, Inc., a biotechnology company focused on immuno-oncology. TJW, KAD, CF, BW, CY, OY, DS, AG, BD, RA, CP, GM, and CK declare no conflicts of interest. Clinical Cancer Research Translational Relevance: 150. Current: 145 Abstract limit: 250. Current: 212 Text limit: 5000. Current: 5052 Figures limit: 6 main text figures, Current: 6+4+1
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Translational Relevance
Tumor escape from immunotherapy remains a problem. While research in
peripheral cancers has identified common mechanisms of escape, escape mechanisms
in brain tumors remain unclear. Herein, we investigated tumor escape after tumor-
specific adoptive T cell immunotherapy. We developed an immune-escaped tumor
model system to study escape mechanisms as well as secondary immunotherapy
treatment. These studies revealed multiple mechanisms of escape including a shift in
immunogenic tumor antigens, downregulation of MHC-I, and upregulation of checkpoint
molecules. Despite these changes, a new population of escape variant-specific
polyclonal T cells could be generated to target immune-escaped tumors through using
tumor escape variant RNA. These T cells were more specific for the escaped tumors
when compared to primary gliomas and were unique to each escape variant. When
applied in a treatment model with checkpoint blockade, tumor-specific adoptive T cell
therapy significantly prolonged survival of immune-escaped and primary glioma-bearing
mice.
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Abstract
Purpose: Immunotherapy has been demonstrably effective against multiple cancers,
yet tumor escape is common. It remains unclear how brain tumors escape
immunotherapy and how to overcome this immune escape.
Experimental Design: We studied KR158B-luc glioma-bearing mice during treatment
with adoptive cellular therapy (ACT) with polyclonal tumor-specific T cells. We tested
the immunogenicity of primary and escaped tumors using T cell restimulation assays.
We used flow cytometry and RNA profiling of whole tumors to further define escape
mechanisms. To treat immune-escaped tumors, we generated escape variant-specific T
cells through the use of escape variant total tumor RNA and administered these cells as
ACT. Additionally, PD-1 checkpoint blockade was studied in combination with ACT.
Results: Escape mechanisms included a shift in immunogenic tumor antigens,
downregulation of major histocompatibility complex (MHC) class I, and upregulation of
checkpoint molecules. Polyclonal T cells specific for escape variants displayed greater
recognition of escaped tumors than primary tumors. When administered as ACT, these
T cells prolonged median survival of escape variant-bearing mice by 60%. The rational
combination of ACT with PD-1 blockade prolonged median survival of escape variant
glioma-bearing mice by 110% and was dependent upon NK cells and T cells.
Conclusions: These findings suggest that the immune landscape of brain tumors are
markedly different post-immunotherapy yet can still be targeted with immunotherapy.
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Introduction
Immunotherapy has revolutionized cancer care [1, 2]. However, tumor escape is
common and poorly understood [2-4]. Herein, we studied tumor escape variants after
immunotherapy to draw meaningful insights about escape mechanisms. We then
applied that information to study secondary immunotherapy based on escape variant
total tumor RNA to treat tumor escape variants.
Gliomas are resistant to chemotherapy, radiation, surgical resection, and even
recent developments in immunotherapy, yet glioma escape mechanisms remain poorly
understood [5-14]. One of the hypothesized methods of brain tumor escape is
immunoediting, or the elimination of cells expressing targetable epitopes, the
equilibration of remaining tumor, and the outgrowth of tumor escape variants. In
peripheral tumors, immunoediting is amplified in the presence of IFN- and Fas-
mediated targeting of tumor, two primary components of T cell-mediated killing [15, 16].
Furthermore, it was also recently demonstrated that programmed cell death protein-1
(PD-1) checkpoint blockade can promote T-cell immunoediting of tumors in the
periphery [14, 17, 18]. The expectation is that once the immunogenic antigens are
deleted during immunoediting the optimal opportunity to target immunogenic tumor
antigens has largely passed [12, 17, 19].
Recent evidence in human trials has shown evidence of immunoediting including
widespread loss of single antigen targets in gliomas and other cancers after monoclonal
chimeric antigen receptor (CAR) T-cell therapy [4, 6-9]. While some preclinical studies
have indicated that this single antigen loss may not affect anti-tumor immunity [20],
conclusions from these recent human studies recommend employing cell therapies with
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multiple antigen targets and the use of combinatorial therapies to activate host immunity
and overcome the immunosuppressive tumor microenvironment [7, 21]. Given these
findings and similar evidence in the periphery, there is now an expectation that
treatments focused on single or limited antigen pools may have limited long-term
success and may even promote immunoediting and formation of tumor escape variants.
Additional tumor escape mechanisms implicated in peripheral tumors include
loss of major histocompatibility complex class I (MHC-I) and upregulation of immune
checkpoint molecules [3, 18]. MHC-I is required for CD8+ cytotoxic T-cell targeting and
killing of cells that present the T-cell’s cognate antigen. Tumor cells can evade T-cell
targeting by downregulation or deletion of MHC-I [18, 22]. In this setting, natural killer
(NK) cells possess cytotoxic capacity against MHC-Ilo tumors since MHC-I is a key
inhibitory ligand for NK immunoglobulin-like receptors (KIRs) [23]. While various
regimens of lymphokine-activated killer (LAK) cells have been investigated for the
treatment of brain tumors, convincing demonstrations of NK cell anti-tumor efficacy
remain elusive [24-28]. It also remains unclear if NK cells provide any role during
adoptive cellular therapy (ACT) for brain tumors.
Our group developed an ACT platform that targets multiple tumor antigens with
one infusion and is demonstrably efficacious in multiple murine models of brain
malignancies [29-31]. ACT employs bone marrow-derived DCs pulsed with total tumor
RNA to ex vivo activate a polyclonal population of tumor-specific T-cells [29, 31]. These
cells are adoptively transferred into tumor-bearing hosts following host conditioning and
hematopoietic stem and progenitor cell (HSPC) transplant and anti-tumor immunity is
maintained with weekly tumor RNA-pulsed DC vaccines (Fig. 1A). This combinatorial
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strategy strongly modulates the tumor microenvironment and promotes continued
intratumor T-cell activation [29-32].
ACT prolongs median survival and mediates ~30% long-term cures in malignant
brain tumor-bearing hosts. However, ~70% of treated animals succumb to disease for
unknown reasons [31]. We hypothesized, based on our previous data highlighting the
ACT-mediated upregulation of Ifng and Fasl, that brain tumors are primed for
immunoediting during ACT [15, 16, 31]. While investigation of viable human brain tumor
tissue after failure of immunotherapy is limited due to a small number of biopsies post-
progression, mouse brain tumor tissue is readily available after escape of
immunotherapy. Therefore, we isolated treatment-resistant tumor escape variants from
mice that succumbed to disease after initial suppression of tumor growth and eventual
escape from ACT (termed TOGA). We used these immune-escaped models and in vitro
T-cell functional assays, flow cytometry, and RNA analysis to investigate mechanisms
of immune escape. These studies revealed that escape mechanisms include a shift in
the immunogenic tumor antigens, downregulation of MHC-I on tumor, and upregulation
of checkpoint molecules on tumors, NK cells, and T-cells.
To evaluate the retreatment of escape variants with immunotherapy, we
developed escape variant-specific T-cells that were primed and expanded using DCs
pulsed with tumor escape variant total tumor RNA. This polyclonal population of escape
variant-specific T-cells demonstrated heightened ability to target TOGA tumors
compared to primary glioma-specific T-cells. When administered with DC vaccines, host
conditioning, and HSPC transplant to TOGA-bearing animals, TOGA-ACT prolonged
median survival by 60% compared to untreated animals. When we introduced PD-1
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blockade during ACT administration, TOGA-ACT+PD-1 blockade prolonged median
survival by 110% compared to untreated animals. When CD8+ T-cells or NK1.1+ NK
cells were depleted during TOGA-ACT+PD-1 therapy, the therapeutic benefit was
significantly ablated. With this flexible combinatorial approach, ACT+PD-1 blockade can
be employed to immunologically reject primary and recurrent gliomas.
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Materials and Methods
Mice
Female six- to eight-week-old C57BL/6 mice (Jackson Laboratories, 000664),
transgenic DsRed mice (Jackson Laboratories, 006051), transgenic GFP mice (Jackson
Laboratories, 004353) and GREAT mice (Jackson Laboratories, 017580) were used.
The facilities at the University of Florida Animal Care Services are fully accredited by
the American Association for Accreditation of Laboratory Animal Care, and all studies
were approved by the University of Florida Institutional Animal Care and Use
Committee.
Bioluminescent imaging
Imaging was performed as previously described using the IVIS system [29].
RNA isolation
Total tumor RNA was isolated from two sources: either in vitro cell lines or
directly post-excision. Qiagen RNAeasy kit (Qiagen, 74104) was utilized for all
extractions. Manufacturer’s guidelines were followed.
RNA-seq
Untreated KR158B and GL261 tumors were harvested 3 weeks post-implantation
and 6-week old C57BL/6 mouse brains were harvested for transcriptome analysis.
cDNA preparation and sequencing for these 9 samples were described previously [33].
TOGA1.1 tumor was harvested at humane endpoint at 63 days post-tumor implantation.
For this sample, RNA-Seq libraries were generated using the SMARTerTM Ultra Low
input RNA Kit and KAPA LTP Library Preparation Kit Illumina platforms following the
manufacturers recommended protocols (Clontech cat. #634935 and KAPA Biosystems
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cat. #KK8230). Analysis for all RNASeq samples was preformed on University of
Florida High Performance Cluster (HiPerGator). Briefly, low quality reads and adaptors
of fastq data were trimmed by trim_galore [34] then aligned to Ensembl 91 mouse
genome by RSEM to extract sample gene expression [35, 36]. This algorithm allows us
to align reads from different library preparation on transcript-level and normalized gene
expression by TPM (Transcripts Per Kilobase Million) which makes samples more
comparable among different groups. TPM were compared among the groups.
CancerSubtypes [37] and pheatmap [38] were used for data normalization and
visualization. The top 1000 most variable genes were extracted by CancerSubtypes and
clustered with pheatmap. Then, genes were extracted from each of 6 clusters (Fig. 1F).
In addition, gene networks were generated with stringdb's confidence mode. Principle
component analysis (PCA) were performed with pca3d and rgl [39]. (Supp. Fig.5).
Adoptive Cellular Therapy
Tumor-reactive T-cells were generated as previously described [29-31, 40]. For
TOGA T-cells used in TOGA-ACT, the same protocol was used with a different RNA
species that was isolated from immune-escaped TOGA lines. Briefly, total tumor RNA
was electroporated into DCs and tumor-specific DCs were then used to prime naïve
hosts. One week later, primed splenocytes were harvested and co-cultured with
additional tumor RNA-specific DCs and IL-2. After 5-7 days of co-culture and periodic
splitting, polyclonal, tumor-specific T-cells were harvested and utilized. Treatment of
tumor-bearing mice began with 5Gy lymphodepletion or 9Gy myeloablation on day 5
post-intracranial injection with X-ray irradiation (X-RAD 320). On day 6 post-intracranial
tumor injection, mice received a single intravenous injection with 107 autologous ex-vivo
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expanded TTRNA T-cells with either 5x104 lineage-depleted (lin-) hematopoietic stem
and progenitor cells (HSCs) (Miltenyi Biotec cat. 130-090-858). Beginning day 7 post-
tumor injection, 2.5x105 TTRNA-pulsed dendritic cells were injected intradermally
weekly for 3 weeks.
T-cell functional assays
In vitro experiments utilized IFN-γ release from T-cells in functional assays as a
measure of T-cell activity. Functional assays included effector T-cells and targets
(pulsed DCs or tumor cell lines) that are co-cultured in a 10:1 ratio in 96-well U-bottom
plates in triplicate. IFN-γ Platinum ELISAs (Affymetrix, #BMS606) were performed on
acellular media that was harvested and frozen from the supernatants after 48 hours.
The supernatant transfer system utilized the 10:1 ratio of T-cells and DCs to generate
supernatants.
Tumor models
KR158B-luc was murine glioma was used courtesy of Dr. Karlyne M. Reilly [29,
41] as previously described [31]. TOGA cell lines were isolated from excision of brain
tumors from mice after succumbing to KR158B-luc tumors post-ACT treatment
(including 9Gy irradiation, HSPC transplant, tumor-reactive T-cells, and 3 DC vaccines).
TOGA tumors were utilized identically to KR158B-luc tumors. Cell lines tested negative
for mycoplasma contamination (IDEXX, 9/26/2017).
In vivo antibodies
In vivo antibodies included anti-PD-1 monoclonal antibody (BioXcell, BE0146),
anti-CD8 depletion antibody (BioXcell, BE0223), and anti-NK1.1 depletion antibody
(BioXcell, BE0036) were administered as previously described [42]. Antibodies were
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administered according to treatment diagrams in figures.
Tissue processing
Tissue was processed as previously described [30, 31]. Brain tumor dissection
began posteriorly with a midline cut in the skull and rongeur removal of skull laterally.
Tumor resection extended to gross borders of tumor mass near the site of injection.
Tumors were dissociated mechanically with a sterilized razor blade and chemically with
papain (Worthington cat. NC9809987) for 30 minutes. Tumors were filtered with a 70μm
cell strainer (BD Biosciences cat. 08-771-2) prior to antibody incubation
RT-qPCR
Quantity of RNA was measured using NanoDrop 2000. Each reverse
transcription reaction was performed us
libraries were generated using the SMARTscribe reverse transcriptase kit from total
tumor RNA per the manufacturer’s instructions (Clontech, cat. 639537). Samples were
stored at -80°C for subsequent qPCR analyses. The CFX Connect™ Real-Time PCR
Detection System (BioRad Laboratories, 1855201), TaqMan® Universal PCR Master
Mix (Applied Biosystems, 4324018), and validated TaqMan® probes were used for
qPCR analyses. Transcriptional expression of H2k1 (cat. 4331182, Mm01612247_mH)
and Pdl1 (cat. 4331182, Mm00452054_m1) were normalized to Hprt (cat. 4331182,
Mm03024075_m1) per sample and expressed as fold-change versus untreated tumors.
well. Reagent preparation and thermal cycling parameters were followed per
manufacturer instruction. No template controls and reverse transcriptase negative
samples were included to ensure the absence of contamination and genomic DNA.
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Flow cytometry
Flow cytometry was done with the BD FACS Canto-II machine under the
management of the University of Florida Cancer Center. Cell-sorting was performed
using the BD FACS Aria-II. DsRed+ mouse-derived cells were detected in FL-2.
Analysis was performed with FlowJo version 10 (Tree Star). Results were analyzed
using isotype controls after debris and doublets were excluded and target populations
were gated on size and granularity. FACS antibodies are listed in Supplemental Table
1.
Statistical analysis
Statistical tests were performed using GraphPad Prism 8. For in vitro
experiments we utilized the unpaired Student’s t-test and for in vivo experiments we
utilized the Mann-Whitney rank sum test. Correlation studies employed Pearson’s two-
tail test for correlation. Experiments are powered to include at least 5 randomized
animals per group. For survival experiments we utilized 7 or more animals to attain
enough power to distinguish groups after analysis by Mantel-Cox log-rank test. Median
survival for KR158B-luc is 42 days and for TOGA1.1 is about 21 days. Significance was
determined as P<.05.
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Results
Escape from adoptive cellular therapy
ACT leads to approximately 30% long-term cures in preclinical murine models
including NSC medulloblastoma, K2 brainstem glioma, and KR158B-luc glioma [31].
Here, C57BL/6 mice received orthotopic injection of syngeneic KR158B-luc high grade
glioma and were treated with ACT as previously described [29-31]. Despite a significant
increase in median and overall survival, a proportion of glioma bearing mice treated with
ACT succumb to disease [29-31]. Bioluminescent imaging revealed that all ACT treated
mice maintain control of tumor growth up to 21 days post-ACT (p<0.0001) with a
fraction demonstrating long-term survival (Fig.1A-C).
Tumors from this experiment that escaped ACT treatment after a period of
immunological control were referred to as TOGA1.1 and TOGA1.2. When orthotopically
injected into naïve C57BL/6 mice, TOGA1.1 tumor was demonstrably more aggressive
than its primary counterpart KR158B-luc (median survival, 21.5 days vs. 41 days;
p<.0001; Fig. 1D). RNA-Seq revealed global genetic differences between the primary
KR158B-luc glioma and the escaped tumor TOGA1.1 (Fig. 1E). Gene expression of
TOGA1.1 was also compared to global gene expression of primary murine glioma cell
lines KR158B-luc, GL261 glioma, and normal brain tissue (Fig. 1E). We found that
between TOGA1.1 and primary KR158B-luc 8,487 genes are differentially expressed by
at least 2-fold, indicating that the selection process of ACT led to genetically distinct
gliomas.
Brain tumor escape variants are immunologically distinct from primary tumors
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After observing genetic differences between primary KR158B-luc and escaped
TOGA1.1, we next sought to determine if the tumors were immunologically discrete. We
hypothesized that if the escape variants were immunologically distinct, T-cells
generated from the primary tumor would no longer provide a remarkable treatment
effect. To test this, we administered serial adoptive T-cell transplants specific for the
primary KR158B-luc to KR158B-luc-bearing animals. While there was not a significant
difference in median survival, giving two serial T-cell transplants did induce a shift from
30% to 40% long-term cures (p=.2503, p=.5427; Fig. 1G, Supp. Fig. S1A). Regardless,
tumor escape persisted.
We next asked if T-cells generated against the primary KR158B-luc glioma
maintain immunological recognition of the escaped tumor TOGA1.1. To determine if
KR158B-luc-specific T-cells recognize cognate antigen on TOGA1.1, KR158B-luc-
specific T-cells were generated then used as effector cells against either KR158B-luc,
TOGA1.1, or B16-F10-OVA melanoma tumor target cells in a functionality assay (Fig.
2A). Supernatant IFN- secretion was measured as an indication of anti-tumor T-cell
reactivity. KR158B-luc T-cells secreted IFN- upon recognition of KR158B-luc but had
markedly diminished recognition of TOGA1.1 or B16-F10-OVA melanoma cells
(KR158B-luc: 2911pg/mL, TOGA1.1: 448pg/mL, p=.0767, Fig. 2A). This strongly
suggests that T-cells specific for primary tumor provide very little immune function
against escape variant tumor cells.
We next investigated whether we could regenerate a secondary T-cell therapy
that was more specific for the TOGA1.1 escape variant and could mediate significant
anti-tumor function. To do this, we generated TOGA1.1-specific T-cells by using total
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tumor RNA isolated from TOGA1.1 cells. TOGA1.1-specific T-cells were then tested in a
functionality assay to target either KR158B-luc, TOGA1.1, or B16-F10-OVA tumor cells.
TOGA1.1-specific T-cells secreted significantly more IFN- upon co-culture against
TOGA1.1 over primary KR158B-luc tumor (TOGA1.1: 3782pg/mL, KR158B-luc: 1200
pg/mL, p=.0128; Fig. 2B). Importantly, this demonstrates that the TOGA1.1 tumor,
which was outgrown from a primary KR158B-luc glioma that escaped ACT, is
immunologically distinct from its primary counterpart.
Individual tumor escape variants are immunologically distinct from each other
Our data thus far demonstrates that escape from ACT results in immunologically
distinct tumors from the primary tumor. We next sought to determine if the escaped
tumors after treatment are immunologically distinct from other escape variants
originating from the same tumor that received the same ACT treatment.
Since T-cells generated against the primary KR158B-luc glioma no longer
recognize escaped TOGA1.1 glioma, we then specifically asked if T-cells generated
against tumors that have escaped ACT recognize and target each other. Here we used
TOGA1.1 and TOGA1.2 which are escaped tumors that both originated from the same
KR158B-luc tumor which escaped the same T-cell treatment (Fig. 1D). We generated
antigen-specific T-cells against TOGA1.1 and used those to target either TOGA1.1
tumor cells or TOGA1.2 tumor cells and supernatant IFN- was measured as an
indicator of T-cell recognition of cognate tumor antigen. While IFN- was released when
TOGA1.1 T-cells were cultured with TOGA1.1, minimal IFN- was detected when
TOGA1.1 T-cells were cultured with TOGA1.2 tumor cells (TOGA1.1 vs TOGA1.2,
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p=.0224, Fig. 2C). The converse experiment was conducted when TOGA1.2-specific T-
cells were generated and used to target either TOGA1.1 or TOGA1.2 glioma cells. The
TOGA1.2 T-cells failed to recognize TOGA1.1 escaped tumor cells (TOGA1.1 vs.
TOGA1.2, p=.0313, Fig. 2D). Therefore, there was successful recognition of cognate
tumors, yet minimal cross-reactivity between T-cells and the converse tumor target (Fig.
2, C-D). This indicates that tumor escape variants were at least partly unique.
It has been previously reported that spectratyping using fluorescence-activated
cell sorting (FACS) analysis of TCR V may be used to track the reactivity of specific
TCR V families towards target cells [43-45]. For validation of this method, we verified
the reactivity of TCR V 5.1, 5.2 T-cells for OVA-expressing target cells [46] (Supp. Fig.
S1, B-C). We next evaluated the proportion of TCR V families within the polyclonal
pools of KR158B-luc T-cells or TOGA1.1 T-cells belong after ex vivo expansion and
determined they were largely comparable (Supp. Fig. S1D). In a recent manuscript, we
discovered that the primary TCR V family that drives ACT response to KR158B-luc in
vivo is TCR V6 [45]. We therefore FACS-sorted TCR V6+ T-cells from the polyclonal
KR158B-luc T-cell pool. After sorting, we performed T-cell functional assays against
KR158B-luc or TOGA1.1 tumor cells. TCR V6+ KR158B-luc-specific T-cells were 8-fold
more reactive towards KR158B-luc when compared with TOGA1.1 tumor cells
(KR158B-luc: 771pg/ml, TOGA1.1: 94pg/ml, p=.0033, Fig. 3A). This indicates that TCR
V can be used to broadly demarcate specificity of T-cells between KR158B-luc T-cells
and TOGA1.1 T-cells and that TCR V6+ KR158B-luc T-cells were not as capable of
targeting epitopes that were present on TOGA1.1. We therefore tested the reactivity of
individual FACS-sorted TCRV families in vitro against their cognate tumor. This
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revealed that the T-cell TCRV families that are reactive for TOGA1.1 tumors are
largely different than those that are reactive for KR158B-luc and TOGA1.2 tumors (Fig.
3, B-C).
MHC class I is downregulated on a subset of tumor escape variants
We next investigated alternative mechanisms that could be responsible for
escape following ACT. Given the dependence of CD8+ T-cells on tumor MHC-I
expression, we investigated the potential for MHC downregulation on ACT-treated
tumors. We identified a downregulation of MHC-I by percent and MFI on the TOGA1.1
tumor compared to KR158B-luc (Fig. 4, A-B). We then investigated MHC-I expression
on tumors of a cohort of animals treated with ACT in a separate experiment (Fig. 4C). In
the KR158B-luc-bearing group, 4/7 tumors maintain expression of MHC-I after ACT, 3/7
tumors displayed a marked decrease in expression of MHC-I (p=.0289, Fig. 4, D-F).
This bifurcation in response was verified by percent expression, MFI, and PCR (Fig. 4,
D-F).
We additionally tested the impact of ACT on MHC-I expression in TOGA1.1-
bearing animals. This revealed that MHC-I was ubiquitously downregulated on
TOGA1.1 tumors after TOGA-ACT by percent expression and MFI (MHC-I+, 22.59% to
10.12%, p=.0033, Fig. 4, D, G-H). It should be noted that while only a fraction of ACT-
treated KR158B-luc-bearing hosts demonstrated downregulation of MHC-I, all ACT-
treated TOGA-bearing animals demonstrated a uniform downregulation of MHC-I by
flow cytometry. We then generated TOGA-ACT T-cells from DsRed transgenic animals
and tracked T-cells in tumors of ACT-treated hosts. At endpoint we excised tumors and
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analyzed tumor-infiltrating lymphocyte (TIL) TCR V families. The V families driving at
least partial in vitro reactivity against TOGA1.1 tumors (4, 5.1/5.2, 6, 8.1/8.2, and 8.3)
also comprised the majority of the TIL fraction of the families tested at endpoint (Supp.
Fig. S1E).
PD-L1 is upregulated on a subset of escape variant tumors
Given recent reports detailing the importance of checkpoint molecules and MHC-
I expression in determining the cytotoxic response in peripheral tumors [42], we next
investigated PD-L1 expression on tumors. We determined that ACT induces an
upregulation of PD-L1 by PCR and flow cytometry (p=.0466, p=.001; Fig. 5, A-B). PD-L1
expression was then compared with MHC-I at the gene level (Fig. 5C) and the protein
level (Fig. 5D) within each sample. Within-sample analysis revealed a strong positive
correlation between the two molecules (r=.9953, p<.0001), indicating that tumors that
escape by downregulating MHC-I are largely PD-L1lo. Additionally, in concordance with
this correlative data, TOGA-ACT treated hosts, which are low for MHC-I, remained low
for Pdl1 even after ACT (Fig. 5E). This suggests that TOGA1.1 is a variant that primarily
escapes by MHC-I downregulation and not necessarily by PD-L1 upregulation. This
may suggest distinct mechanisms of escape whereby brain tumors primarily either
upregulate PD-L1 or downregulate MHC-I in response to escape T-cell pressure.
ACT promotes activation and PD-1 expression on T-cells and NK cells
To determine if ACT induced a cellular immune response, we investigated
cytotoxic immune cell infiltration in the tumor-draining cervical lymph nodes (TDLN) and
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tumor microenvironment during ACT. For these analyses, we specifically investigated
the presence and activation of CD8+ T-cells and CD3-CD19-F4/80-Ter-119-
NK1.1+NKp46+ NK cells. We studied expression of CD107a as a marker of
degranulation of activated cytotoxic cells as well as PD-1, a marker of T-cell activation
that functions as a regulatory receptor [47-49]. These analyses revealed that ACT
induced a 22-fold increase in CD8+ T-cells and a 3-fold increase in NK cells in TDLN by
percent and absolute counts (p=.001, p=.001, Fig. 5, F-G). Importantly, NK cells are not
derived from the adoptive T-cell transfer (Supp. Fig. S2). This demonstrates an
important link between T-cell therapy and NK cell engraftment in TDLN. A concomitant
increase of both absolute number and percent of CD107a+ and PD-1+ T-cells and NK
cells were also seen with ACT (Fig. 5, H-I). ACT induced a 2.5-fold greater expression
of CD107a on T-cells and a 4.5-fold greater expression on NK cells (p=.001, p=.001,
Fig. 5, H-I). Additionally, ACT induces a 6-fold greater expression of PD-1 on T-cells
and a 5-fold greater expression on NK cells (p=.001, p=.001, Fig. 5, H-I). When we
investigated MFI expression on tumor-infiltrating T-cells and NK cells, we determined
that ACT induced greater expression of PD-1 on T-cells and NK cells (p=.001, p=.042,
Supp. Fig. S2-4) while inducing greater expression of CD107a on NK cells (p=.001,
Supp. Fig. S2-4). This data demonstrates that ACT mediates T-cell and NK cell
engraftment and activation.
ACT and ACT+PD-1 blockade prolongs survival of escape variant-bearing hosts
We next performed a series of survival experiments to test the capacity of ACT to
overcome the three described immune escape mechanisms: tumor antigen changes,
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MHC-I downregulation, and checkpoint molecule upregulation on immune cells and
tumor cells. Based on the in vitro data, we anticipated that tumor-specific ACT would
overcome the shift in immunogenic tumor antigens and allow for tumor-specific
targeting. We also anticipated MHC-I downregulation could be overcome because
tumor-specific T-cells still targeted escape variants in vitro and simultaneously
enhanced infiltration and activation of NK cells and T-cells in vivo. Lastly, we anticipated
combinatorial addition of PD-1 checkpoint blockade could prevent immune checkpoint-
mediated escape. Administration of TOGA1.1-specific ACT prolonged median survival
of TOGA1.1-bearing hosts by 60% (median survival, 24 to 33 days, p=.0003; Fig. 6, A-
B). Since we identified upregulated PD-1 on NK cells and T-cells previously during ACT,
we tested the ability of PD-1 to enhance the anti-tumor benefit of TOGA-ACT (Fig. 6C).
When we administered TOGA-ACT+PD-1 to TOGA-bearing animals, this yielded 110%
prolongation of median survival (UnTx vs. ACT+PD-1, 20 to 42 days, p=.0002, ACT vs.
ACT+PD-1, 32 to 42 days, p=.1522, Fig. 6D).
We previously demonstrated an ACT-induced engraftment and activation of NK
cells and T-cells in TDLN and tumors but had not yet investigated their impact on anti-
tumor efficacy. To test the functional impact of NK cells and T-cells during therapy, we
utilized depleting antibodies before and during TOGA-ACT+PD-1. When depleting
antibodies were administered to deplete NK1.1+ NK cells or CD8+ T-cells from animals
during ACT+PD-1 therapy, the survival benefit was significantly diminished (anti-NK1.1,
42 to 31 days, p=.0122; anti-CD8, 42 to 27 days, p=.0038, Fig. 6E). Therefore, both cell
types are required for optimal efficacy.
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In summary, brain tumor escape from ACT occurs through at least three
mechanisms including a shift in immunogenic tumor antigens, MHC-I downregulation,
and upregulation of checkpoint molecules. However, ACT promotes the infiltration of
both NK cells and T-cells, two populations that can cytotoxically target tumors
regardless of MHC-I status. When we regenerated T-cells specific for tumor escape
variants, they were more specific for their cognate escape variant tumor cells when
compared to primary glioma cells. When this escape variant-specific T-cell approach
was applied in vivo with an ACT regimen, it significantly prolonged median survival. PD-
1 blockade during ACT enhanced this benefit and depletion of NK cells and CD8+ T-
cells highlighted the requirement for both cell types for optimal efficacy.
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Discussion
This report highlights multiple mechanisms of escape during immunotherapy for
malignant gliomas including a shift in immunogenic tumor antigens, downregulation of
MHC-I, and upregulation of checkpoint molecules. This study also demonstrates a
translatable method of analyzing tumor that has escaped immunotherapy in situations
where re-biopsy is feasible. This mechanistic investigation which was done in
recalcitrant primary and recurrent murine gliomas demonstrates that tumor immunity is
complex and that single pathways are not solely responsible for escape, which is highly
relevant to cancer immunology. For instance, when tumors are targeted with antigen-
specific CAR-T cells or other single-antigen targeting modalities, antigen loss provides a
tumor escape route [4, 7, 8, 20, 50]. Alternatively, checkpoint blockade strategies may
promote anti-tumor immunity, but can encourage escape from immune surveillance [17,
51-55]. In another pathway altogether, the most advanced adaptive immunotherapy
strategy can be immobilized or stripped of activation by the network of pro-tumor
myeloid cells that are endemic to all anti-tumor immune responses [56, 57]. These are
all part of a larger coordinated immune system that self-regulates to the extent that
opportunistic tumor cells can benefit in the fray.
The role of CD8+ T-cells in anti-tumor immunity is well-established and was been
recapitulated in this report. They were required for optimal anti-tumor immunity even
against TOGA tumors, which express relatively lower MHC-I. However, the role of NK
cells in brain tumor immunity is not as well-appreciated. While much of the
immunotherapy field has focused on checkpoint molecules on T-cells, recent evidence
has also implicated checkpoint molecules on NK cells. In lymphoma models, PD-1
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checkpoint blockade can promote activation of natural killer (NK) cell-mediated
immunity, opening the possibility for simultaneous activation of T and NK cells [42].
However, PD-1 blockade alone does not mediate remarkable efficacy in primary glioma
tumor models [30]. What we demonstrated here is that ACT+PD-1 blockade can
activate T-cells and NK cells and promote anti-tumor efficacy. We anticipate that NK
cells may follow parallel pathways of cytokine and chemokine-mediated migration and
activation that promote T-cell immunity. We previously demonstrated that HSPCs in the
tumor microenvironment release MIP-1 which promotes T-cell migration to tumors in
coordination with ACT that induces upregulation of Ccl5, Ifng, and other T-cell cytokines
and chemokines [10, 29, 31]. There are multiple reports that NK cells can migrate and
become activated through the same molecules and future investigation will explore this
further [58, 59]. Regardless, through this combined engagement of T-cells and NK cells
during ACT+PD-1, CD8+ T-cells can kill any tumor cell that has MHC-I while NK cells
can kill MHClo tumors that may appear in response to T-cell pressure. Perhaps this
encourages tumors into “escaping” into the cytotoxic snare of either NK cells or T-cells
in MHC-pliable tumors.
After ACT, some tumors displayed preferential escape through PD-L1
upregulation or MHC-I downregulation. In the within-sample analysis, there were largely
no tumor samples that expressed low MHC-I and high PD-L1 or high MHC-I and low
PD-L1. Previous experiments that demonstrated the impact of NK cells during PD-1/PD-
L1 blockade used a cell line that was MHClo and transduced with Pdl1 [42]. Then with
increased tumor Pdl1, NK cells were engaged by PD-1 or PD-L1 blockade to generate
anti-tumor efficacy against MHC-Ilo tumors. In our study, PD-L1 was only highly
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expressed when MHC-I was highly expressed. Since CD8+ T-cells rely on MHC-I and
NK cells depend on its absence, our study suggests that the PD-1/PD-L1 axis is more
relevant in the function of CD8+ T-cell immunity during ACT. This may partially explain
why PD-1 blockade did not induce significant activation of NK cells in TDLN, whereas
PD-1 blockade did induce CD8+ T-cell activation. However, NK cells and CD8+ T-cells
were both required for optimal efficacy during combined ACT+PD-1. In total, these data
indicate a potential bifurcation in the escape mechanisms of brain tumors that is
reminiscent of a mechanistic model that has been described in other tumors as
escaping by “natural selection” or “acquired resistance” [22, 60]. Future studies in brain
tumors should perform single cell analysis to longitudinally track single cells and their
pre-determined or acquired resistances.
In the cohort of tumors that escape by PD-L1 upregulation and we anticipate that
TOGA-ACT+PD-1 may provide considerable benefit and perhaps long-term tumor
control. Given recent articles on neoadjuvant PD-1 blockade in glioblastoma [61, 62],
we anticipate robust development in neoadjuvant or adjuvant ACT+PD-1 combinations
in primary and resistant tumors. With ACT inducing a subset of tumors to upregulate
PD-L1, perhaps some escaped tumors are more readily treatable with PD-1 blockade
after stratification in the PD-L1hi escape variant subtype. On the contrary, the addition of
PD-1 to TOGA-ACT in the TOGA1.1 model was beneficial but limited. We anticipate this
may be due to TOGA1.1 demonstrating a preference for MHC-I downregulation (a
potential form of “natural selection”), not PD-L1 upregulation. Even though ACT induces
considerable T-cell engraftment (22-fold increase) and significant but limited NK cell
engraftment (3-fold increase), we generated a significant survival benefit. We anticipate
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that for tumors that escape by MHC-I downregulation, additional combinatorial NK cell
activation strategies in addition to ACT+PD-1 may be beneficial. MHC-I was
downregulated on TOGA1.1, but it is important to recognize that MHC-I does not appear
completely lost on TOGA1.1. It was detectable by PCR and flow cytometry and our
functional assays indicate T-cell targeting despite lower MHC-I. However, future studies
should investigate the single cell-level kinetics of MHC-I changes and antigen
expression levels in escape variants and determine the relative requirement of MHC-I
and antigen presence for adequate T and NK cell function.
The strengths of this study include the use of multiple therapeutic brain tumor
models including the generated escape variant models. Here we laid the groundwork for
three primary mechanisms of escape in malignant gliomas. Even after escape, we
generated a significant benefit through novel generation of escape variant-specific ACT.
Future directions of these studies include the stratification and early detection of escape
variant subtypes. With that classification, future cancer regimens can be diversified and
tailored with attention to how and when specific tumors escape.
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Author Contributions: Conception or design of the work: TJW, DAM, CTF, KAD, CF, AG, and CP. The acquisition, analysis, or interpretation of data: TJW, DAM, CTF, KAD, CF, BW, CY, OY, DS, BD, RA, CP, GM, and CK. Drafted the work or substantively revised it: TJW, DAM, CTF, KAD, BW, AG, and BD. The creation of new software used in the work: n/a TJW, KAD, CF, BW, CY, OY, DS, AG, BD, RA, CP, GM, CK, DAM, and CTF approved the submitted version (and any substantially modified version that involves the author's contribution to the study). TJW, KAD, CF, BW, CY, OY, DS, AG, BD, RA, CP, GM, CK, DAM, and CTF agreed both to be personally accountable for the author's own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature.
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Figure Legends Figure 1. Adoptive cellular therapy prevents early tumor growth and promotes
long-term survival in malignant primary glioma-bearing mice. A). Treatment platform for tumor-bearing mice. B-C). Bioluminescent imaging of KR158B-luc glioma-bearing mice untreated or treated with ACT. 8/10 animals escaped ACT while 2/10 were long-term cures. D). Survival of KR158B-luc glioma-bearing mice untreated or treated with ACT. Experiment performed at least five times. E). Tumorigenicity of TOGA1.1 tumor after re-implantation into naïve hosts. Passaging of TOGA1.1 cell line remained below 5 passages. Experiment performed two times. F). Heatmap of RNA-seq of primary tumors (KR158B-luc or GL261) and recurrent immune-escaped tumor (TOGA1.1) compared to normal brain. G). Survival of KR158B-luc glioma-bearing mice treated with ACT including 1 injection of T cells or serial ACT with 2 injections of T cells (treatment platform Supp. Fig. S1). *P<.05, **P<.01, ***P<.001, ****P<.0001, by Mantel-Cox Log Rank Test for survival experiments (n≥7).
Figure 2. Reactivity of tumor escape variant-specific T cells for primary and
recurrent tumors. A-B). IFN- ELISA of restimulation assay between B). KR158B-luc-T cells and KR158B-luc or TOGA1.1 tumor cells or C). TOGA1.1-T cells and KR158B-luc or TOGA1.1 tumor cells. KR158B-luc-primary glioma, TOGA1.1-immune-escaped glioma, B16-melanoma negative control. Experiment
performed twice. C-D). IFN- ELISA of restimulation assay between TOGA1.1-T
cells and TOGA1.1 or TOGA1.2 tumor cells. G). IFN- ELISA of restimulation assay between TOGA1.2-T cells and TOGA1.1 or TOGA1.2 tumor cells. All data represent the mean +/-SEM. *P<.05, **P<.01, ***P<.001, ****P<.0001, by
unpaired students t test for in vitro studies (n3).
Figure 3. TCR V families of TOGA1.1-T cells and TOGA1.2-T cells. A). IFN-
ELISA of restimulation assay performed after FACS-sorting for TCR V6+
KR158B-luc-T cells. Restimulation assay contained unsorted or V6+-sorted KR158B-luc-T cells cultured with KR158B-luc or TOGA1.1 tumor cells. B-C). IFN-
ELISA of restimulation assay performed after FACS-sorting for TCR V
families. Restimulation assay contained either B). unsorted or sorted TCR V-specific TOGA1.1-T cells with TOGA1.1 tumor cells or C). unsorted or sorted
TCR V-specific TOGA1.2-specific T cells with TOGA1.2 tumor cells. All data represent the mean +/-SEM. *P<.05, **P<.01, ***P<.001, ****P<.0001, by
unpaired students t test for in vitro studies (n3). Figure 4. MHC class I downregulation during adoptive cellular therapy. A-B). Flow
cytometry of MHC-I expression on KR158B-luc primary glioma or the isolated tumor escape variant TOGA1.1 C). Treatment plan for D-H. D). Flow cytometry MFI of MHC class I on brain tumors of mice treated untreated or treated with ACT at humane endpoint. E) Quantification of MFI and percent MHC-I expression in KR158B-luc-bearing animals. F). Correlation between % MHC-I positivity by flow cytometry and PCR expression of H2k1 for KR158B-luc-bearing animals. G). Quantification of MFI and percent MHC-I expression in TOGA1.1-bearing animals. H). Correlation between % MHC-I positivity by flow cytometry and PCR expression of H2k1 for TOGA1.1-bearing animals. All experiments performed twice and data represent the mean +/-SEM. *P<.05, **P<.01,
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***P<.001, ****P<.0001, by Mann-Whitney t test for in vivo studies (n5) and and
Pearson’s two tail test for correlation (n5). Figure 5. PD-L1 upregulation on tumors and PD-1 upregulation on T cells and NK
cells during adoptive cellular therapy. A). PCR for Pdl1 (Cd274), the gene for PD-L1 in mice, at humane endpoint in KR158B-luc-bearing hosts. B). Flow cytometry of PD-L1 of brain tumors of mice at day 23 post-T cell transplant. Experiment performed twice. C). Correlation between Pdl1 and H2k1 determined by PCR in tumors from untreated or ACT-treated animals at humane endpoint. Statistics represent Pearson’s test for ACT-treated group. D). Correlation between PD-L1 and MHC-I determined by flow cytometry in tumors from untreated or ACT-treated animals at day 23 post-T cell transplant. Experiment performed twice. Statistics represent Pearson’s test for ACT-treated group. E). PCR for Pdl1 (Cd274) at humane endpoint in TOGA1.1-bearing hosts. F). Flow cytometry of CD8+ T cells in TDLN untreated or treated with ACT at day 23 post-T cell transplant. G). Flow cytometry of NK cells in TDLN untreated or treated with ACT at day 23 post-T cell transplant. NK cell phenotype is CD3-CD19-F4/80-
Ter-119-NK1.1+NKp46+. H). Flow cytometry of markers CD107a and PD-1 on T cells in TDLN. I). Flow cytometry of markers CD107a and PD-1 on NK cells in TDLN. Data represent the mean +/-SEM. *P<.05, **P<.01, ***P<.001,
****P<.0001, by Mann-Whitney t test for in vivo studies (n5) and Pearson’s two
tail test for correlation (n5). Figure 6. Anti-tumor efficacy of ACT alone or in combination with PD-1 blockade
for immune-escaped and primary brain tumors. A). Treatment outline for Fig. 6B. B). Survival curve of TOGA-bearing animals treated with TOGA-specific ACT. Experiment performed twice. C). Treatment outline for Figure 6, D-E. D). Survival curve of TOGA-bearing animals treated with TOGA-ACT+PD-1 blockade. PD-1 blockade was administered on days 6, 11, 16, and 21 as depicted by ticks on the graph. E). Survival curve of TOGA-bearing animals depleted of NK1.1+ NK cells or CD8+ T cells during ACT+PD-1 blockade. PD-1 blockade was administered on days 6, 11, 16, and 21 as depicted by ticks on the graph. NK1.1+ NK cells or CD8+ T cells were depleted on days -2, -1, 5, 10, 15, 20, 25, and 30 as depicted by ticks on the graph. *P<.05, **P<.01, ***P<.001, ****P<.0001, by Mantel-Cox Log Rank Test for survival experiments (n≥7).
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Published OnlineFirst August 11, 2020.Clin Cancer Res Tyler J Wildes, Kyle A Dyson, Connor P Francis, et al. gliomasImmune escape after adoptive T cell therapy for malignant
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