CANCER RESEARCH | TUMOR BIOLOGYAND IMMUNOLOGY

ICOS Is an Indicator of T-cell–Mediated Response toCancer Immunotherapy A C

Zunyu Xiao1,2, Aaron T. Mayer1,3, Tomomi W. Nobashi1, and Sanjiv S. Gambhir1,3,4,5,6,7

ABSTRACT◥

Immunotherapy is innovating clinical cancer management. Nev-ertheless, only a small fraction of patient's benefit from currentimmunotherapies. To improve clinical management of cancerimmunotherapy, it is critical to develop strategies for responsemonitoring and prediction. In this study, we describe inducibleT-cell costimulator (ICOS) as a conserved mediator of immuneresponse across multiple therapy strategies. ICOS expression wasevaluated by flow cytometry, 89Zr-DFO-ICOS mAb PET/CT imag-ing was performed on Lewis lung cancer models treated withdifferent immunotherapy strategies, and the change in tumor vol-ume was used as a read-out for therapeutic response. ImmunoPETimaging of ICOS enabled sensitive and specific detection of activatedT cells and early benchmarking of immune response. A STING(stimulator of interferon genes) agonistwas identified as a promising

therapeutic approach in this manner. The STING agonist gen-erated significantly stronger immune responses as measured byICOS ImmunoPET and delayed tumor growth compared withprogrammed death-1 checkpoint blockade. More importantly,ICOS ImmunoPET enabled early and robust prediction of ther-apeutic response across multiple treatment regimens. These datashow that ICOS is an indicator of T-cell–mediated immuneresponse and suggests ICOS ImmunoPET as a promising strategyfor monitoring, comparing, and predicting immunotherapy suc-cess in cancer.

Significance: ICOS ImmunoPET is a promising strategy tononinvasively predict and monitor immunotherapy response.

See related commentary by Choyke, p. 2975

IntroductionThe field of cancer therapy has benefited greatly from recent

breakthroughs in immuno-oncology, most notably the role of theprogrammed death-1 (PD-1) signaling axis in mediating immuno-suppression. PD-1 and programmed death ligand-1 (PD-L1) immunecheckpoint inhibitors have been approved by the FDA for the treat-ment ofmany cancers, including non—small cell lung cancer (NSCLC)and have shown promising outcomes in clinical trials (1). Generally,these immunotherapy agents activate the host immune system toattack and destroy malignant cells. Due to disease heterogeneity andcomplex tumor escape mechanisms, the response rates of checkpointinhibitors in NSCLC vary from 19% to 45% across different phases ofclinical trials (1–3). To improve clinical outcomes for patients diag-nosed with cancer, there is an urgent need for tools that enable theassessment of new immunotherapies and accurate monitoring ofpatient response.

The current gold standards for therapy assessment and responsemonitoring in the clinic are RECIST and immune-related responsecriteria (irRC) based on CT and MRI (4, 5). These imaging modalitiesprovide remarkably detailed anatomic information, but fail to capturemolecular information or underlying immune response. In fact, it hasbeen well documented that these criteria often fail in the immuno-oncology setting due to pseudoprogression caused by tumor immunecell infiltration (6, 7). Another limitation of these approaches isthe long lag between treatment initiation and response assessment.Typically, at least 9–12 weeks pass before following up and assessmentof therapeutic efficacy.

Due to the shortcomings of these conventional approaches, researchefforts have intensified to identify robust biomarkers of response toimmunotherapy. Tumor mutational load, gene expression profiling,T-cell repertoire sequencing, and PD-L1 IHC represent several exam-ples of novel biomarkers that have been reported to show efficacy inpredicting patient response to immune checkpoint blockade (8–11).Despite the promise of these approaches, they all require invasivebiopsies. A recent report examining heterogeneity in patients withNSCLC demonstrated that these classes of metrics were inconsistentamong repeated biopsies taken from 17 of 42 tumors in the study (12).

PET represents a theoretically ideal solution. PET has the ability todynamically and noninvasively quantify molecular information fromthe whole human body. The most classic PET radiotracer, 2-deoxy-2-(18F)fluoro-D-glucose (18F-FDG), has been widely used in lung cancerdiagnosis and patient management in the clinic. Some have evenproposed 18F-FDG for monitoring immunotherapy response in clin-ical trials (13, 14), but the biggest challenge is the lack of specificity.Because 18F-FDG reports on aberrant metabolic processes, it detectsboth tumors and proliferative immune cells and it has been technicallydifficult to deconvolve the signals arising from the two scenarios. Othermetabolic radiotracers such as 30-deoxy-30[18F]-fluorothymidine(18F-FLT), 1-(20-deoxy-20-[18F]fluoro-b-D-arabinofuranosyl) cytosine(18F-AraC), and 20-deoxy-20-[18F]fluoro-9-b-D-arabinofuranosylguanine (18F-AraG) have all faced the same issue as 18F-FDG whenapplied in the immuno-oncology setting (15, 16).

1Department of Radiology, Stanford University School of Medicine, Stanford,California. 2Molecular Imaging Research Center of Harbin Medical University,Harbin, Heilongjiang, China. 3Department of Bioengineering, Stanford Univer-sity, Stanford, California. 4Department of Materials Science and Engineering,Stanford University, Stanford, California. 5Molecular Imaging Program at Stan-ford, Stanford University School of Medicine, Stanford, California. 6CanaryCenter at Stanford for Cancer Early Detection, Stanford University School ofMedicine, Stanford, California. 7Bio-X Program at Stanford, Stanford University,Stanford, California.

Note: Supplementary data for this article are available at Cancer ResearchOnline (http://cancerres.aacrjournals.org/).

Z. Xiao and A.T. Mayer contributed equally to this article.

Corresponding Author: Sanjiv S. Gambhir, Stanford University, 318 CampusDrive, James H. Clark Center, Room E150A, CA 94305. Phone: 650-725-2309;Fax: 650-724-4948; E-mail: sgambhir@stanford.edu

Cancer Res 2020;80:3023–32

doi: 10.1158/0008-5472.CAN-19-3265

�2020 American Association for Cancer Research.

AACRJournals.org | 3023

on August 8, 2021. © 2020 American Association for Cancer Research. cancerres.aacrjournals.org Downloaded from

Published OnlineFirst March 10, 2020; DOI: 10.1158/0008-5472.CAN-19-3265

ImmunoPET tracers specifically targeting immune cell biomarkershave the potential to sensitively assess patient-specific immuneresponse. The first reports of PD-1 and PD-L1 ImmunoPET imagingin mice and humans have demonstrated the technique to be feasibleand safe in predicting patient response to immune checkpointblockade (17–19). In fact, PD-L1 ImmunoPET significantly outper-formed PD-L1–based IHC and RNA measurements in the smallcohort of patients tested thus far (20). Additional ImmunoPETtracers in development are geared for more general use for imaginga variety of immune cell phenotypes including CD3, CD4, CD8, andCD20 (21–24). While these tracers have been demonstrated to accu-rately quantify immune cell type and distributionwithin the body, theyhave failed in most settings to predict or correlate with immunother-apy response at early timepoints.

To predict response at the earliest stages, biomarkers of immune cellactivation are requisite. Upon successful immunotherapy, immunecells are activated and then home to the tumor tissue where they canexert their effector function. The secreted markers, IFNg and gran-zyme b (25, 26), have shown promising results both for responsemonitoring and assessment of therapeutic strength. However, thesesecreted biomarkers pose challenges for imaging including half-lifeand dilution. These particular biomarkers also fundamentally repre-sent later stages of activation, once a T cell has already reached thetumor and begun to kill. In a previous study, we have successfullydemonstrated that OX40, a T-cell surface costimulatory receptor thatis only activated upon antigen-specific recognition, represents acompelling paradigm for detecting the earliest stages of activation inthe tumor-draining lymph nodes (TDLN), all the way through to thelate stages in the tumor, of T-cell–mediated immune response (27).

Here we investigate inducible T-cell costimulatory receptor (ICOSor CD278), a member of the CD28 superfamily, as a new potentialbiomarker of T-cell–mediated immunotherapy response. As reportedbefore, ICOS is mainly expressed on activated cytotoxic T cells,memory T cells, and regulatory T cells. The initiation of the ICOSpathway begins through ligation of ICOS and its ligand (ICOSL),which is expressed on B cells, macrophages, and dendritic cells.Ligation triggers a downstream pathway that regulates T-cell prolif-eration and survival, as well as secretion of IL4, IL10, and IFN (28, 29).OX40 and ICOS cooperate in a nonredundant manner to maximizeand sustain Th cell immune responses (30). Although OX40 expres-sion has been reported on both CD4 and CD8 cell subsets, inmost models it is skewed toward CD4 expression. In contrast, wedemonstrate here in a model of Lewis lung cancer that ICOS is highlyupregulated on both activated CD4 and CD8 T-cell subsets andmay represent an even more sensitive detection paradigm. Based onthis compelling evidence, we developed 89Zr-DFO-ICOS mAb as ameans to noninvasively quantify activated CD4 and CD8 T-cellresponses targeting lung cancer. Utilizing this approach, we gaininsights into the lack of therapeutic efficacy of PD-1 immune check-point inhibitors in a model of Lewis lung carcinoma, as well as identifySTING (stimulator of interferon genes) agonists as a novel and potenttreatment strategy. Overall, we demonstrate that ICOS ImmunoPET isa promising strategy for predicting and monitoring T-cell–mediatedimmune response to cancer immunotherapy.

Materials and MethodsStudy design

The aim of this study was to evaluate ICOS as a candidate biomarkerfor early prediction and monitoring of immunotherapy responsebased on noninvasive ImmunoPET imaging. ICOS expression on both

resting and activated phorbol 12-myristate 13-acetate/ionomycin(PMA/IONO) T cells was first tested by FACS, then 89Zr-DFO-ICOS mAb was synthesized, followed by characterization and celluptake studies. For animal experiments, Lewis lung carcinoma LLC1cell line (obtained fromATCC) and C57BL/6J (Jackson Lab) were usedfor establishment of themouse xenograftmodels; Lewis lung cancer cellline was cultured in T75 flask and in DMEM media (Thermo FisherScientific) supplemented with 10% FBS (Thermo Fisher Scientific)and 1% antibiotic-antimycotic, when grows to 90% confluence, cellswill be passaged, to avoid the contamination of Mycoplasma, Myco-plasma testing was performed once every month, no extra cell authen-tication was conducted. PBS, 200 mg anti-mouse PD-1 antibody, 50 mg2030-cGAMP (STING agonist) or 2030-cGAMP plus 200 mg anti-mousePD-1 antibody were administered intraperitoneally (i.p.) or intratu-morally (i.t.) to randomized cohorts of mice-bearing Lewis lungtumors. Tumor volume was measured every other day after treatmentinitiation. 89Zr-DFO-ICOS mAb PET imaging was used for ICOSdetection after treatment. A separate group of treated mice wasanalyzed by FACS to verify ICOS expression levels [FACS antibodies:anti-mouse CD4(APC/cy7, clone: GK1.5 BioLegend), anti-mouse CD8(APC, clone: 53-6.7, BioLegend), anti-human/rat/mouse ICOS(PerCP/Cy5.5, clone: 398.4A,BioLegend), anti-mouseOX40 (PE, clone:OX-86,BioLegend), anti-mouseCD25 (PE/Cy7, clone: PC61, BioLegend), anti-mouse PD-1 (BV711, clone: 29F.1A12, BioLegend), anti-mouse Foxp3(Pacific blue, clone:MF-14 BioLegend), anti-humanCD3 (FITC, clone:HIT3a, BD Pharmingen), and Live/Dead (LIVE/DEAD Fixable AquaDead Cell Stain Kit, Thermo Fisher Scientific)]. All reported data arerepresentative of at least two independent experiments.

PMA/IONO activation and FACS analysis of ICOS expression onboth naïve and activated T cells

C57BL/6J mouse spleens were collected after euthanasia. Mouse T-cell isolation was performed according to the manufacturer's protocol(EasySep Mouse T-cell Isolation Kit). T cells were seeded in a 96-wellplate at a density of 200,000 cells/well. To confirm ICOS expression onhuman-activated T cells, human peripheral blood mononuclear cells(PBMC) were seeded in a 96-well plate, 200,000/well. For T-cellactivation, PMA and IONO mixture was added to each well at a finalconcentration of 10 and 100 ng/mL, respectively. Both resting andactivated T cells were collected after 72 hours of activation. FACSstaining of mouse CD4 (APC/cy7, BioLegend), mouse CD8 (APC,BioLegend), human/rat/mouse ICOS(PerCP/Cy5.5, BioLegend),human CD3 (FITC, BD Pharmingen), and Live/Dead(LIVE/DEADFixable Aqua Dead Cell Stain Kit, Thermo Fisher Scientific) wereperformed and ICOS expression was analyzed by flow cytometry (BDLSRII). Compensation was performed in all experiments utilizing AbCTotal Antibody Compensation Bead Kit (Thermo Fisher Scientific).

DFO conjugationFor desferoxamine (DFO) conjugation, ICOS mAb (clone:

7E.17G9), or isotype control (clone: LTF-2) and DFO (p-SCN-Bn-Deferoxamine) were purchased from Bio-X-cell and Macrocyclics,respectively. 1 mg of the unconjugated mAb was maintained in 1 mLPBS (pH¼ 7.4), then buffer exchanged with pH 8.8–9.0 PBS solution.After the recovery, 10-fold excess DFO was added to mAb solution.After 1-hour incubation under 37�C, the mixture was bufferexchanged/washed by PBS (pH ¼ 7.4) using vivaspin2, 50K cut-offcentrifugal concentrator (three washes, 4,000 g, 9 minutes/wash).About 200 mL DFO-ICOS mAb or isotype control solution wasrecovered, and the concentration was determined by Thermo FisherScientific NanoDrop One Microvolume UV-Vis Spectrophotometer.

Xiao et al.

Cancer Res; 80(14) July 15, 2020 CANCER RESEARCH3024

on August 8, 2021. © 2020 American Association for Cancer Research. cancerres.aacrjournals.org Downloaded from

Published OnlineFirst March 10, 2020; DOI: 10.1158/0008-5472.CAN-19-3265

89Zr-DFO-ICOS mAb radiosynthesis, AF594-ICOS mAbconjugation

89Zr-oxalic acid was adjusted to a pH range of 7.1–7.8 by adding1mol/L Na2CO3 solution and subsequently added to DFO-ICOSmAbstock solution. Themixture was incubated under 37�C for 1 hour, thenpurified by Zeba SpinDesalting Columns, 7KMWCO, 0.5mL, 1,000 g,1 minute. To test the stability of the tracer, 50 mCi of 89Zr-DFO-ICOSmAb was added to 1 mL PBS or 1 mL mouse serum, and kept in ashaker under 37�C. The radiochemical purity was tested at differenttime points. Alexa Fluor 594 NHS ester (Invitrogen, Thermo FisherScientific) was dissolved inDMSO to a final concentration of 10mg/mL,followed by addition to 200 mg ICOS mAb in PBS. The solution wasincubated at room temperature for 1 hour, and purified by vivaspin2,50K cut-off centrifugal concentrator.

Cell uptake studyFor cell uptake studies, 3 mCi 89Zr-DFO-ICOS mAb were added to

500,000K PMA/IONO activated, resting or blocked (activated T-celltreated by 100 mg cold ICOS mAb) T cells, and incubated for 1 hourunder 37�C in Iscove Modified Dulbecco Media. After three washeswith 200 mL PBS, cells were collected and the activity accumulated incells was determined by a gamma counter. For AF594-ICOS mAb celluptake, the probe was firstly diluted to a certain concentration from10�9 to 10�6 mol/L, and added to 200,000K PMA/IONO activated,resting or blocked (activated T cell treated by 100 mg cold ICOS mAb)T cells, and incubated for 1 hour under 37�C. After three washes with200 mL PBS, cells were collected, stained for viability, and tested forfluorophore probe binding by flow cytometry.

Animal model establishment and treatmentAll research involving animal subjects was approved by the Admin-

istrative Panel on Laboratory Animal Care. 5� 105 Lewis cells in 50mLPBS were injected subcutaneously in the right shoulder of 6–8 weeksold female C57BL/6 mice. After 7–9 days of inoculation, when thetumor volume reached a range of 40–100 mm3, mice received eitherPBS, 200 mg anti-mouse PD-1 antibody, 50 mg 2030-cGAMP Vacci-Grade (STING i.t.) or 50 mg 2030-cGAMPVacciGrade plus 200mg anti-mouse PD-1 antibody (Combo) via i.t. or i.p. injection. The originalday of treatment was denoted as day 0, and the treatment was given onday 0, 2, 4, and/or 6. Tumor volumes were recorded every other day bycalipers and tumor volumes were calculated using the formula (pi/6)�length � width � height.

PET/CT imaging and biodistribution studyAll PET scans were performed on Siemens Inveon MM-PET/CT.

After anesthetization by 1.5%–2% isoflurane gas, 50 mCi (1 mCi/mL)89Zr-DFO-ICOS mAb or isotype control was administered viamouse tail vein on day 0 right after the treatment. On days 1, 2,5, and day7/8, a 15-minute static PET scan was acquired right afterCT imaging, which was used for providing an anatomic referenceand PET signal attenuation correction. Region of interest (ROI) ofPET images was drawn using a three dimensional (3D) volumemode. No partial volume correction was applied. For validation ofthe ROI data, after the last PET scan on day 7/8, Lewis lung cancerbearing mice were euthanized, and blood, tumor, tumor-draininglymph node, spleen, heart, liver, left kidney, small intestine, largeintestine, lung, and muscle were collected and weighed. An auto-matic gamma counter was used for determining the activity indifferent organs. Both ROI and biodistribution data were normal-ized to %ID/g, while tumor-draining lymph nodes’ biodistributiondata were normalized to %ID.

Statistical analysisAll the data analysis was performed on PRISM 5 (GraphPad) and R

studio. One- or two-way ANOVA and unpaired two-tailed student ttest were used for data analysis where appropriate. P values less than0.05 were considered as statistically significant. R square and P valuewere used for evaluation of 2D or 3D linear regression fits.

ResultsDevelopment of an ICOS probe for sensitive and specificdetection of activated CD4 and CD8 T cells

To confirm reports of ICOS as a candidate biomarker for activatedT cells, we performed PMA/IONO activation assays on both murineT cells and human PBMCs, followed by antibody staining 72 hourslater. Flow cytometry revealed ICOS to be strongly upregulatedon activated compared with resting murine T cells (Fig. 1A and Bleft, P < 0.0001). Importantly, the same statistically significant resultwas observed for human PBMCs (Fig. 1B right, P < 0.0001). We nextsynthesized fluorescent and radiolabeled probes for sensitive andspecific ICOS detection. Our candidate ICOS probe was successfullylabeled via amine conjugation of anAlexaFluor 594NHS ester dye (31).We tested the probe to ensure the labeling did not interfere with theactive binding site of the antibody scaffold. In an ICOS binding assayutilizing serial dilutions of the probe, we observed AF594-ICOS mAbto have significantly higher uptake in activated T cells compared withICOS mAb blocked or resting controls and a limit of detection on theorder of 10�6 (P < 0.001) to 10�7 (P < 0.01) molar (Fig. 1C). Theradioactive version of the probe was also generated via an amineconjugation strategy, this time utilizing a DFO macrocyclic chelatorand 4-isothiocyanatophenyl cross-linking. Zirconium89 was selectedas the optimal radiometal due to its favorable half-life (78.4 hours)pairing with mAbs and its increasing clinical usage. To confirmsensitive and specific binding of the radioactive ICOS probe, celluptake studies were performed. Significantly higher uptake of 89Zr-DFO-ICOS mAb was observed for activated T cells as compared withICOS blocked or resting controls (Fig. 1D, P < 0.0001). Radiolabelingresulted in high radiochemical yield (>70%), purity (>99%), andspecific activity (�28 GBq/mmol) determined from averaging fourvalidation runs (Fig. 1E; Supplementary Table S1). The radioactiveprobe remained stable in both serum and PBS, measured out to 6 days(Supplementary Fig. S1).

Determination of a conserved role for ICOSþ T cells in multipleimmunotherapy strategies targeting lung cancer

PD-1/PD-L1 axis blockade is an immunotherapy strategy thathas been tested in various clinical trials for patients with lung cancer.To determine whether ICOSþ-activated T cells are implicated in theimmune response pathway to PD-1 blockade, we treatedmice-bearingLewis lung carcinoma tumors with 200 mg anti-mouse PD-1 antibodyor 100 mL PBS (i.p.) on a standard treatment schedule (days 0, 2, 4, and6). Subsequent changes in tumor volume were measured every otherday (Fig. 2A). After four treatments, the PD-1 group demonstratedslightly delayed tumor growth and a lower overall tumor fold change.While the treatment effect was significant (Fig. 2B, P < 0.01, two-wayANOVA), the therapeutic result was modest (PD-1: 9.61 � 3.65 foldsincrease vs. PBS: 14.73 � 6.38 folds increase). This was in line withother preclinical and clinical studies utilizing PD-1 blockade in lungcancer (32). PD-1 blockade did generate early activated T-cellresponses in lymph sitesmeasured on day 2 after just a single treatment(Fig. 2C). The frequencies of ICOSþ CD4 and ICOSþ CD8 T cells inthe TDLNwere significantly higher in the PD-1 group, compared with

ICOS ImmunoPET Detects Response to Immunotherapy

AACRJournals.org Cancer Res; 80(14) July 15, 2020 3025

on August 8, 2021. © 2020 American Association for Cancer Research. cancerres.aacrjournals.org Downloaded from

Published OnlineFirst March 10, 2020; DOI: 10.1158/0008-5472.CAN-19-3265

the PBS control (P < 0.01). Significant upregulation of ICOS could alsobe observed on CD4 T cells in the spleen following PD-1 therapy (P <0.05). t-Distributed Stochastic Neighbor Embedding (tSNE) analysisrevealed ICOS is highly restricted to CD4 and CD8 T cells. Despite theweak overall response to PD-1 blockade, ICOS expression in theTLDNand spleen were the strongest early biological correlates of futuretumor volume change, out of all the biomarkers we tested (Fig. 2D).

To confirm a ubiquitous role for ICOSþT cells in immune responsetomultiple therapy strategies targeting lung cancer, we selected a novel2030-cGAMP (CDN) stimulator of interferon genes (STING) agonistfor further investigation. This CDN ligand is known to bind directly tothe endoplasmic reticulum-resident STING receptor, which is impli-cated in spontaneous tumor antigen recognition and induction oftumor-specific T-cell responses (33, 34). Intratumoral injection ofSTING agonist has shown recent success in multiple preclinicalmodels (35–37). Here we evaluated STING agonist therapy for thefirst time, to our knowledge, in Lewis lung cancer. On days 0, 2, and 4,mice-bearing Lewis lung carcinoma tumors received either STING i.t.,PD-1 i.t., Combo, or PBS i.t. (Fig. 2E). Tumor volume changes inresponse to treatment were monitored over time (Fig. 2F). BothSTING i.t. and Combo groups demonstrated significantly delayedtumor growth compared with PBS i.t. or PD-1 i.t. alone. The STINGarmof the combo therapy accounted for themajority of the therapeuticeffect, as there was no advantage of combination therapy comparedwith STING alone at this time point (p ¼ ns). FACS analyses were

performed between PBS i.t. and STING i.t. groups on day 2 (Fig. 2G).ICOS expression was again restricted to T-cell subsets by tSNEanalysis, STING agonist was observed to generate immune responsesagainst lung cancer, with a higher frequency of ICOSþ CD8 T cellsobserved in the TDLN (P < 0.0001) and spleen (P < 0.05). We furtherphenotyped the ICOSþ cells observed in thismodel of lung cancer, andas previously reported, its expression was nonredundant with OX40(Fig. 2H). ICOS expression was notably high on both CD4 and CD8populations, whereas OX40 was restricted to CD4 alone. This obser-vation is highly relevant for a potential biomarker of response to lungcancer immunotherapy, as ICOSþCD8 cells accounted for the primarydifference between STING-treated and PBS control groups.

ImmunoPET imaging of ICOS as a biomarker of adaptiveimmune response to lung cancer

To evaluate the ability of 89Zr-DFO-ICOS mAb to detect ICOSþ-activated T cells in vivo, ImmunoPET imaging studies were performedon day 2 and 7/8 after tracer administration. To quantify the PETsignals in major organs, 3D ROIs were drawn (Fig. 3A), and the PETimages were shown in (Fig. 3B–D; Video 1–6). Time course phar-macokinetic profiles demonstrated clearance of 89Zr-DFO-ICOSmAbfrom the blood pool mediated by liver uptake and subsequent hepa-tobiliary excretion typical of an IgG antibody (Fig. 4A andB). At day 2,significant increases in PET signal in the tumor, TDLN and spleen ofthe STING i.t. and Combo-treated cohorts could be observed

Figure 1.

ICOS is a sensitive and specific biomarker expressed on activated T cells.A, 3D flow cytometry plots of ICOS expression on activated and restingmurine CD4 andCD8T cells. Scale bar, green, high ICOS expression; dark purple, low ICOS expression. B,Mean fluorescence intensity (MFI) quantification of ICOS expression on activatedand resting T cells. Left, murine T cells; right, human T cells; n¼ 3.C,Uptake of AF594-ICOSmAb in PMA/IONO activated, blocked, and restingmurine T cells at 1-hourincubation; activated, blocked, and unstained, n¼ 3; na€�ve, n¼ 2; statistical comparison shown between activated and blocked groups. D, Cell uptake of 89Zr-DFO-ICOS mAb in PMA/IONO activated, blocked, and resting murine T cells at 1-hour incubation, n ≥ 3; statistical comparison shown between activated and blocked/resting groups. E, Radio-iTLC of 89Zr-DFO-ICOSmAb and free 89Zr, mobile phase: 50mmol/L EDTA. All values represent the mean� SD unless otherwise specified.Unpaired two-tailed Student t test was used for analyses. ��, P < 0.01; ���, P < 0.001; ���� , P < 0.0001.

Xiao et al.

Cancer Res; 80(14) July 15, 2020 CANCER RESEARCH3026

on August 8, 2021. © 2020 American Association for Cancer Research. cancerres.aacrjournals.org Downloaded from

Published OnlineFirst March 10, 2020; DOI: 10.1158/0008-5472.CAN-19-3265

Figure 2.

ICOS is an early indicator of therapy response in Lewis lung cancer models and is highly restricted to T cells. A, Study design of PD-1 i.p. versus PBS i.p. study (n ≥ 5).B, Tumor volume monitoring curve of PD-1 i.p. and PBS i.p. group. C, tSNE plot and flow cytometry analysis of ICOS frequency on CD4 and CD8 T cells in tumor-draining lymph node and spleen. D, Correlogram: linear regression analysis between frequency of different biomarkers and log10 (D2 tumor volume/D0 tumorvolume). Color and circle size represent strength of Pearson correlation. Scale bar, yellow, positively correlated; purple, negatively correlated. E, Study design of theSTING agonist study (n ≥ 3). F, Tumor volumemonitoring curve of STING i.t., PD-1 i.t., PBS i.t., and Combo groups.G, tSNE plot and FACS analysis of ICOS expressionon CD4 and CD8 T cells in tumor-draining lymph node and spleen.H, Comparison of ICOS andOX40 expression on CD4 and CD8 T cells in TDLN. All values representthemean� SEM unless otherwise specified. Two-way ANOVAwas for determination of PD-1 i.p. and PBS i.p. groups tumor volume change, and unpaired two-tailedStudent t test was used for others. � , P < 0.05; �� , P < 0.01; ���� , P < 0.0001; ns, not significant.

ICOS ImmunoPET Detects Response to Immunotherapy

AACRJournals.org Cancer Res; 80(14) July 15, 2020 3027

on August 8, 2021. © 2020 American Association for Cancer Research. cancerres.aacrjournals.org Downloaded from

Published OnlineFirst March 10, 2020; DOI: 10.1158/0008-5472.CAN-19-3265

compared with PD-1 i.t. or PBS i.t. groups (Fig. 4C). This signal couldbe attributed to specific increases in ICOS, determined utilizing an89Zr-DFO-Isotype mAb control. In contrast, PD-1 intraperitoneallytreated mice only demonstrated a significant increase in PET signalcompared with PBS i.p. control in the TDLN alone (Fig. 4D), corre-sponding with our previous data suggesting PD-1 treatment leads to aweaker therapeutic immune response in the Lewis lung cancer model.By day 7/8, these trends persisted but overall signal decreases wereobserved at these sites, potentially linked with a waning immuneresponse or unbound tracer clearance (Fig. 4E and F). Ex vivobiodistribution (BioD) studies confirmed the accuracy of ourmanuallydelineated ROI measurements of PET signal from the images (Sup-plementary Figs. S2 and S3). Good concordance was observed betweenPET andBioDmeasurements acrossmajor tissue sites (Fig. 4G; tumor:r2 ¼ 0.8447, P < 0.0001; spleen: r2 ¼ 0.4885, P < 0.0001). Our PETimaging studies indicate our approach enables noninvasive and spe-cific detection of ICOSþ-activated T cells in vivo.

Evaluation of ICOS imaging for immunotherapy responseprediction in lung cancer

The final goal of this study was to assess the ability of 89Zr-DFO-ICOSmAb imaging to predict andmonitor immunotherapy response.To identify the strongest response predictors from our image ROIs, wegenerated a heatmap depicting all ROIs from our early day 2 imagingtimepoint and performed unsupervised hierarchical clustering. TheROI profiles distinguished mice treated with STING agonist or

combination therapy from the other cohorts (Fig. 5A). Furtheranalysis revealed the PET signal in the tumor and TDLN had thestrongest correlation with tumor volume response at various time-points (Fig. 5B). A multiple linear regression model utilizing both ofthese ROIs to monitor (day 7/8 PET %ID/g vs. day 7/8 log10 tumorvolumemm3 fold change, r2¼ 0.6604, P¼ 3.053e-07) or predict (day 2PET %ID/g vs. day 7/8 log10 tumor volume mm3 fold change, r2 ¼0.7675, P ¼ 2.217e-09) tumor response yielded robust fits (Fig. 5C).This predictor fit therapy response well across therapeutic cohorts(e.g., STING vs. PD-1) and within therapy cohorts (e.g., PD-1;Supplementary Fig. S4). We conclude here that ICOS imaging is afeasible and promising strategy for monitoring and predicting immu-notherapy response in lung cancer.

DiscussionImmunotherapy has brought new hope to clinical cancer treat-

ment, but due to variance in patient response and modest efficacy ofPD-1 immune checkpoint blockade in this therapeutic setting, newtools need to be explored for early assessment of immune responsein cancer and identification of new treatment paradigms. Wedemonstrate that ICOS ImmunoPET imaging can be utilized toachieve these goals in preclinical immunotherapy models of Lewislung cancer and suggest that there are compelling reasons to furthertranslate and test this approach clinically based on the evidence andrationale presented here.

Figure 3.

PET/CT imaging of 89Zr-DFO-ICOSmAb in Lewis lung cancermodels.A,Reference of 3DROI drawing.B,Day 2 PET/CT imaging of 89Zr-DFO-ICOSmAb in Lewis lungcancer models. C, Day 2 PET/CT imaging of 89Zr-DFO-ICOS mAb and 89Zr-DFO-isotype control in STING agonist i.t.-treated Lewis lung cancer models. D, Day 7/8PET/CT imaging of 89Zr-DFO-ICOS mAb in Lewis lung cancer models. All images are representative of n ¼ 3–7 mice per group.

Xiao et al.

Cancer Res; 80(14) July 15, 2020 CANCER RESEARCH3028

on August 8, 2021. © 2020 American Association for Cancer Research. cancerres.aacrjournals.org Downloaded from

Published OnlineFirst March 10, 2020; DOI: 10.1158/0008-5472.CAN-19-3265

Figure 4.

ROI and biodistribution quantification. A and B, 89Zr-DFO-ICOS mAb pharmacokinetics at all imaging time points in major organs. C and D, Day 2 PET image ROIquantification of tumor, TDLN, and spleen. E and F, Day 7/8 PET image ROI quantification of tumor, TDLN, and spleen. G, Linear regression analysis of ROI andbiodistribution at day 7/8 time point. All values represent the mean� SD unless otherwise specified. One-way ANOVA and unpaired two-tailed Student t test wereused for comparation of ROI values. � , P < 0.05; �� , P < 0.01; ��� , P < 0.001; ���� , P < 0.0001; ns, not significant.

ICOS ImmunoPET Detects Response to Immunotherapy

AACRJournals.org Cancer Res; 80(14) July 15, 2020 3029

on August 8, 2021. © 2020 American Association for Cancer Research. cancerres.aacrjournals.org Downloaded from

Published OnlineFirst March 10, 2020; DOI: 10.1158/0008-5472.CAN-19-3265

Imaging ICOS theoretically represents one of the earliest and mostsensitive methods for detecting T-cell–mediated immune response tocancer therapy. ICOS is an extracellular activation marker that isturned on following antigen recognition and costimulatory signaling,the earliest known events in the adaptive immune response cascade.Here, ICOS imaging enabled early detection of response prior tochanges in tumor volume, offering a potential clinical advantage toMR- and CT-based anatomic imaging approaches. ICOS expressionwas highly restricted to activated T cells and was expressed on bothCD4 and CD8 subsets, making ICOS both a highly sensitive andspecific biomarker. While ICOS was also expressed on regulatory Tcells, these cells represented a small fraction (<10%, SupplementaryFig. S5) of the total CD4 cell population upon treatment. The change inICOS PET signal in treated compared with control was thus primarilyattributable to an increase in ICOSþ-activated effector T cells. This ispertinent given the relatively low specificity for activated T cells ofother PET tracers in clinical testing and development (e.g., 18F-FDG,18F-FLT, 18F-AraC). ICOS demonstrated earlier correlation withtumor response than changes in CD4 and CD8 subsets. This obser-vation reinforces the hypothesis that imaging T-cell activationmarkersmay provide earlier actionable insights thanT-cell phenotypemarkers.ICOS expression was nonredundant with other T-cell activationmarkers (e.g., OX40, PD-1) and was conserved across multiple immu-notherapy strategies. ICOS expression could also be detected byImmunoPET imaging in both the tumor and TDLN, elucidating thecritical interplay between these sites in immunotherapy response.Previous studies of granzyme b and IFNg imaging (25, 26) onlyreported signal in the tumor, potentially missing early stages ofimmune response detected here in the TDLN. In fact, integratingICOS ImmunoPET signal from both the tumor and TDLN enabled the

best monitoring and prediction of eventual tumor response in thispreclinical model.

Our results demonstrate a proof of concept for how imaging ICOSmay be utilized to streamline preclinical drug development andimprove clinical patient management. Given that early ImmunoPETimaging of ICOS correlated strongly with late therapeutic volumetrictumor response in the model systems tested here, this approach haspotential for rapid evaluation and benchmarking of new immuno-therapy strategies. For example, in this work, we demonstrate thatSTING, previously not validated in the lung cancer setting, signifi-cantly outperforms PD-1 blockade in inducing immune and thera-peutic responses. Long survival studies could be shortened, as thesedifferences were evident from ImmunoPET imaging at just 2 daysposttreatment initiation. A multiple linear regression model couldforecast the predicted tumor growth for each therapeutic cohort manydays later. Furthermore, the mechanistic insights gained from ICOSimaging into the strength of an activated immune response following anovel immunotherapy regiment are likely more informative thanchanges in tumor volume alone when evaluating drugs for translation.Based on the same results, ICOS imaging could improve clinicalpatient management by allowing the treating physician to makedecisions regarding drug dose or switching drug regiments early aftertreatment initiation. ICOS imaging thus may lead to improved patientoutcomes by enabling the identification of the optimal therapy prior totumor progression, and potentially decrease costs associated withunnecessary therapies not contributing to patient benefit.

Imaging ICOS as presented here does have limitations. For theex vivo activation assay, we chose the most common PMA/IONOactivation assay, which is quite different from ICOS biology in vivo andcan’t perfectly mimic the mechanisms in vivo. While ICOS has been

Figure 5.

Evaluation of ICOS imagingmetrics for immunotherapy response prediction in the Lewis lung cancermodel.A, Z-normalized heatmap of %ID/g tracer uptake valuesin specified ROIs. Row/column order determined by unsupervised hierarchical clustering. Side bars represent log10 (fold-change tumor volume) at day 2 (d2) orday 7/8 (d7/8) posttherapy. B, Correlogram depicting r2 Pearson correlation between %ID/g tracer uptake measured in the indicated ROI, compared with the log10(fold-change tumor volumes) at various time points. �, positive or negative correlation. Circle size and color denotes Pearson correlation strength. C, 3D linearregression of log10 (fold-change tumor volumes) at day 7/8 with %ID/g tracer uptake in TDLN and tumor at day 2 (predict) or day 7/8 (monitor).

Xiao et al.

Cancer Res; 80(14) July 15, 2020 CANCER RESEARCH3030

on August 8, 2021. © 2020 American Association for Cancer Research. cancerres.aacrjournals.org Downloaded from

Published OnlineFirst March 10, 2020; DOI: 10.1158/0008-5472.CAN-19-3265

reported as a biomarker of response in clinical studies (38, 39) andpreclinical models (35, 40), here our evaluation of ICOS as an imagingbiomarker was limited to a single subcutaneous lung cancer murinexenograft model, and there were only two immunotherapy adjuvantsemployed. Further work is needed to explore the feasibility of ICOSImmunoPET in the prediction and evaluation of immunotherapyresponse across different treatment strategies and orthotopic or spon-taneousmodels that could bettermimic the tumormicroenvironment.Studies will also need to be performed to determine the best time toassess ICOS activation posttreatment. According to our longitudinalICOS imaging studies, PET signals in the tumor and TDLN decreasedslightly over time. Further FACS characterization in the anti PD-1antibody treated group showed ICOS expression to wane on CD4 andCD8 T cells as a function of time posttreatment (SupplementaryFig. S6). Therefore, establishing the right imaging window will becritical for proper therapy response assessment. Also, ICOSþ T cellsmay not be implicated in all models or therapy types. It is for thisreason that we are developing a comprehensive Immunoimagingtoolbox (41), and evaluating the roles of multiple markers, imagingagents, and cell types, while making decisions about which candidatesare the most promising for clinical translation. This study principallyevaluated PD-1 and STINGagonist as lung cancer therapies, because ofreports that PD-1 therapy generates relatively low numbers of ICOSþ

T cells (42) while STING agonist generates relatively high numbers ofICOSþ T cells (36). These were, therefore, ideal selections given ourprimary goal to assess the feasibility of our ICOS imaging approach todetect differences in T-cell–mediated immune response. While weidentified that STING agonist approaches may be efficacious in thelung cancer setting for the first time to our knowledge, more work willneed to be done to evaluate the optimal dose and therapeutic schedule.

In this proof-of-concept work, we successfully employed an anti-body-based probe for PET imaging of ICOS. ImmunoPET imaging ofICOS offers a compelling approach for monitoring and predictingactivated T-cell immune responses. In the age of next-generationsequencing and highly multiplexed assays, ImmunoPET imaging ofa single biomarker may seem to offer a paucity of information. Inopposition to this notion, ImmunoPET gives a full body view ofimmune response and can help guide these biopsy-dependent tech-

niques, which often suffer from interlesional and intralesional het-erogeneity. In fact, ImmunoPET imaging is just beginning to realize itsfull potential. ImmunoPET imaging is now entering the clinic andbeing employed to monitor and stratify patients for cancer immuno-therapy, with recent successful reports of PD-1 and PD-L1 imaging inhumans (20, 43). Our initial data suggest ICOS imaging offers advan-tages as a general marker of T-cell activation for monitoring immu-notherapy response and merits further investigation.

Disclosure of Potential Conflicts of InterestNo potential conflicts of interest were disclosed.

Authors’ ContributionsConception and design: Z. Xiao, A.T. Mayer, S.S. GambhirDevelopment of methodology: Z. Xiao, A.T. Mayer, S.S. GambhirAcquisition of data (provided animals, acquired and managed patients, providedfacilities, etc.): Z. Xiao, A.T. Mayer, T.W. NobashiAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): Z. Xiao, A.T. MayerWriting, review, and/or revision of the manuscript: Z. Xiao, A.T. Mayer,T.W. Nobashi, S.S. GambhirAdministrative, technical, or material support (i.e., reporting or organizing data,constructing databases): S.S. GambhirStudy supervision: A.T. Mayer, S.S. Gambhir

AcknowledgmentsThis work was supported in part by funding from the Ben and Catherine Ivy

Foundation, the Canary Foundation, and the NCI (R01 CA201719-03).The authors would like to acknowledge Drs. Tim Doyle, Frezghi Habte, and the

Stanford Center for Innovation in In-Vivo Imaging (SCI3) for their assistancewith thepreclinical imaging.We also thankmembers of the Stanford FACS facility for sharingtheir expertise. In addition, we thank Kenneth Lau for assistance with massspectrometry.

The costs of publication of this article were defrayed in part by thepayment of page charges. This article must therefore be hereby markedadvertisement in accordance with 18 U.S.C. Section 1734 solely to indicatethis fact.

Received October 17, 2019; revised January 17, 2020; accepted March 6, 2020;published first March 10, 2020.

References1. Reck M, Rodriguez-Abreu D, Robinson AG, Hui R, Csoszi T, Fulop A, et al.

Pembrolizumab versus chemotherapy for PD-L1-positive non-small-cell lungcancer. N Engl J Med 2016;375:1823–33.

2. BorghaeiH, Paz-Ares L,Horn L, Spigel DR, SteinsM, ReadyNE, et al. Nivolumabversus docetaxel in advanced nonsquamous non-small-cell lung cancer. N Engl JMed 2015;373:1627–39.

3. Brahmer J, Reckamp KL, Baas P, Crino L, Eberhardt WE, Poddubskaya E, et al.Nivolumab versus docetaxel in advanced squamous-cell non-small-cell lungcancer. N Engl J Med 2015;373:123–35.

4. Fournier L, Ammari S, Thiam R, Cuenod CA. Imaging criteria for assessingtumour response: RECIST, mRECIST, Cheson. Diagn Interv Imaging 2014;95:689–703.

5. Tazdait M, Mezquita L, Lahmar J, Ferrara R, Bidault F, Ammari S, et al. Patternsof responses in metastatic NSCLC during PD-1 or PDL-1 inhibitor therapy:comparison of RECIST 1.1, irRECIST and iRECIST criteria. Eur J Cancer 2018;88:38–47.

6. Borcoman E, Nandikolla A, Long G, Goel S, Le Tourneau C. Patterns of responseand progression to immunotherapy. Am Soc Clin Oncol Educ Book 2018;38:169–78.

7. Vrankar M, Unk M. Immune RECIST criteria and symptomatic pseudopro-gression in non-small cell lung cancer patients treated with immunotherapy.Radiol Oncol 2018;52:365–9.

8. Samstein RM, Lee CH, Shoushtari AN, Hellmann MD, Shen R, Janjigian YY,et al. Tumor mutational load predicts survival after immunotherapy acrossmultiple cancer types. Nat Genet 2019;51:202–6.

9. Jamieson NB,Maker AV. Gene-expression profiling to predict responsiveness toimmunotherapy. Cancer Gene Ther 2017;24:134–40.

10. Reuben A, Gittelman R, Gao J, Zhang J, Yusko EC, Wu CJ, et al. TCR repertoireintratumor heterogeneity in localized lung adenocarcinomas: an associationwithpredicted neoantigen heterogeneity and postsurgical recurrence. Cancer Discov2017;7:1088–97.

11. Patel SP, Kurzrock R. PD-L1 expression as a predictive biomarker in cancerimmunotherapy. Mol Cancer Ther 2015;14:847–56.

12. Rosenthal R, Cadieux EL, Salgado R, Bakir MA, Moore DA, Hiley CT, et al.Neoantigen-directed immune escape in lung cancer evolution. Nature 2019;567:479–85.

13. Sheikhbahaei S,Mena E, Yanamadala A, Reddy S, Solnes LB,Wachsmann J, et al.The value of FDG PET/CT in treatment response assessment, follow-up, andsurveillance of lung cancer. AJR Am J Roentgenol 2017;208:420–33.

14. Goldfarb L, Duchemann B, Chouahnia K, Zelek L, Soussan M. Monitoring anti-PD-1-based immunotherapy in non-small cell lung cancer with FDG PET:introduction of iPERCIST. EJNMMI Res 2019;9:8.

15. Nguyen NC, Yee MK, Tuchayi AM, Kirkwood JM, Tawbi H, Mountz JM.Targeted therapy and immunotherapy response assessment with F-18

ICOS ImmunoPET Detects Response to Immunotherapy

AACRJournals.org Cancer Res; 80(14) July 15, 2020 3031

on August 8, 2021. © 2020 American Association for Cancer Research. cancerres.aacrjournals.org Downloaded from

Published OnlineFirst March 10, 2020; DOI: 10.1158/0008-5472.CAN-19-3265

fluorothymidine positron-emission tomography/magnetic resonance imaging inmelanoma brain metastasis: a pilot study. Front Oncol 2018;8:18.

16. Ronald JA, Kim BS, Gowrishankar G, Namavari M, Alam IS, D'Souza A, et al. APET imaging strategy to visualize activated T cells in acute graft-versus-hostdisease elicited by allogenic hematopoietic cell transplant. Cancer Res 2017;77:2893–902.

17. Natarajan A,Mayer AT, Xu L, Reeves RE, Gano J, Gambhir SS. Novel radiotracerfor ImmunoPET imaging of PD-1 checkpoint expression on tumor infiltratinglymphocytes. Bioconjug Chem 2015;26:2062–9.

18. Maute RL, Gordon SR, Mayer AT, McCrackenMN, Natarajan A, Ring NG, et al.Engineering high-affinity PD-1 variants for optimized immunotherapy andimmuno-PET imaging. Proc Natl Acad Sci U S A 2015;112:E6506–14.

19. Mayer AT, Natarajan A, Gordon SR,Maute RL,McCrackenMN, Ring AM, et al.Practical immuno-PET radiotracer design considerations for human immunecheckpoint imaging. J Nucl Med 2017;58:538–46.

20. Bensch F, van der Veen EL, Lub-de Hooge MN, Jorritsma-Smit A, Boellaard R,Kok IC, et al. (89)Zr-atezolizumab imaging as a non-invasive approach to assessclinical response to PD-L1 blockade in cancer. Nat Med 2018;24:1852–8.

21. Seo JW, Tavare R, Mahakian LM, Silvestrini MT, Tam S, Ingham ES, et al. CD8(þ) T-cell density imaging with (64)Cu-labeled cys-diabody informs immuno-therapy protocols. Clin Cancer Res 2018;24:4976–87.

22. Freise AC, Zettlitz KA, Salazar FB, Lu X, Tavare R, Wu AM. ImmunoPETimaging ofmurineCD4(þ) T cells using anti-CD4 cys-diabody: effects of proteindose on T cell function and imaging. Mol Imaging Biol 2017;19:599–609.

23. Beckford Vera DR, Smith CC, Bixby LM, Glatt DM, Dunn SS, Saito R, et al.Immuno-PET imaging of tumor-infiltrating lymphocytes using zirconium-89radiolabeled anti-CD3 antibody in immune-competent mice bearing syngeneictumors. PLoS One 2018;13:e0193832.

24. James ML, Hoehne A, Mayer AT, Lechtenberg K, Moreno M, Gowrishankar G,et al. Imaging B cells in a mouse model of multiple sclerosis using (64)Cu-rituximab PET. J Nucl Med 2017;58:1845–51.

25. Larimer BM, Bloch E, Nesti S, Austin EE, Wehrenberg-Klee E, Boland G, et al.The effectiveness of checkpoint inhibitor combinations and administrationtiming can be measured by granzyme B PET imaging. Clin Cancer Res 2019;25:1196–205.

26. Gibson HM, McKnight BN, Malysa A, Dyson G, Wiesend WN, McCarthy CE,et al. IFNgamma PET imaging as a predictive tool for monitoring response totumor immunotherapy. Cancer Res 2018;78:5706–17.

27. Alam IS, Mayer AT, Sagiv-Barfi I, Wang K, Vermesh O, Czerwinski DK, et al.Imaging activated T cells predicts response to cancer vaccines. J Clin Invest 2018;128:2569–80.

28. Rudd CE, Schneider H. Unifying concepts in CD28, ICOS and CTLA4 co-receptor signalling. Nat Rev Immunol 2003;3:544–56.

29. Hutloff A, Dittrich AM, Beier KC, Eljaschewitsch B, Kraft R, Anagnostopoulos I,et al. ICOS is an inducible T-cell co-stimulator structurally and functionallyrelated to CD28. Nature 1999;397:263–6.

30. Tahiliani V, Hutchinson TE, Abboud G, Croft M, Salek-Ardakani S. OX40cooperates with ICOS to amplify follicular Th cell development and germinalcenter reactions during infection. J Immunol 2017;198:218–28.

31. Whitson KB, Beechem JM, Beth AH, Staros JV. Preparation and characterizationof Alexa Fluor 594-labeled epidermal growth factor for fluorescence resonanceenergy transfer studies: application to the epidermal growth factor receptor.Anal Biochem 2004;324:227–36.

32. Orillion A, Hashimoto A, Damayanti N, Shen L, Adelaiye-Ogala R, Arisa S, et al.Entinostat neutralizes myeloid-derived suppressor cells and enhances the anti-tumor effect of PD-1 inhibition in murine models of lung and renal cellcarcinoma. Clin Cancer Res 2017;23:5187–201.

33. Danilchanka O, Mekalanos JJ. Cyclic dinucleotides and the innate immuneresponse. Cell 2013;154:962–70.

34. Woo SR, Fuertes MB, Corrales L, Spranger S, Furdyna MJ, Leung MY, et al.STING-dependent cytosolic DNA sensing mediates innate immune recognitionof immunogenic tumors. Immunity 2014;41:830–42.

35. Sallets A, Robinson S, Kardosh A, Levy R. Enhancing immunotherapy of STINGagonist for lymphoma in preclinical models. Blood Adv 2018;2:2230–41.

36. Demaria O, De Gassart A, Coso S, Gestermann N, Di Domizio J, Flatz L, et al.STING activation of tumor endothelial cells initiates spontaneous and thera-peutic antitumor immunity. Proc Natl Acad Sci U S A 2015;112:15408–13.

37. Corrales L, Glickman LH, McWhirter SM, Kanne DB, Sivick KE, Katibah GE,et al. Direct activation of STING in the tumor microenvironment leads to potentand systemic tumor regression and immunity. Cell Rep 2015;11:1018–30.

38. Sharma P. Immune checkpoint therapy and the search for predictive biomarkers.Cancer J 2016;22:68–72.

39. Carthon BC, Wolchok JD, Yuan J, Kamat A, Ng Tang DS, Sun J, et al.Preoperative CTLA-4 blockade: tolerability and immune monitoring in thesetting of a presurgical clinical trial. Clin Cancer Res 2010;16:2861–71.

40. Curran MA, MontalvoW, Yagita H, Allison JP. PD-1 and CTLA-4 combinationblockade expands infiltrating T cells and reduces regulatory T and myeloid cellswithin B16 melanoma tumors. Proc Natl Acad Sci U S A 2010;107:4275–80.

41. Mayer AT, Gambhir SS. The immunoimaging toolbox. J Nucl Med 2018;59:1174–82.

42. Wei SC, Levine JH, Cogdill AP, Zhao Y, AnangNAS, AndrewsMC, et al. Distinctcellular mechanisms underlie anti-CTLA-4 and anti-PD-1 checkpoint blockade.Cell 2017;170:1120–33.

43. Niemeijer AN, Leung D, Huisman MC, Bahce I, Hoekstra OS, van Dongen G,et al. Whole body PD-1 and PD-L1 positron emission tomography in patientswith non-small-cell lung cancer. Nat Commun 2018;9:4664.

Cancer Res; 80(14) July 15, 2020 CANCER RESEARCH3032

Xiao et al.

on August 8, 2021. © 2020 American Association for Cancer Research. cancerres.aacrjournals.org Downloaded from

Published OnlineFirst March 10, 2020; DOI: 10.1158/0008-5472.CAN-19-3265

2020;80:3023-3032. Published OnlineFirst March 10, 2020.Cancer Res   Zunyu Xiao, Aaron T. Mayer, Tomomi W. Nobashi, et al.   Immunotherapy

Mediated Response to Cancer−ICOS Is an Indicator of T-cell

  Updated version

  10.1158/0008-5472.CAN-19-3265doi:

Access the most recent version of this article at:

  Material

Supplementary

  http://cancerres.aacrjournals.org/content/suppl/2020/03/10/0008-5472.CAN-19-3265.DC1

Access the most recent supplemental material at:

   

   

  Cited articles

  http://cancerres.aacrjournals.org/content/80/14/3023.full#ref-list-1

This article cites 43 articles, 14 of which you can access for free at:

  Citing articles

  http://cancerres.aacrjournals.org/content/80/14/3023.full#related-urls

This article has been cited by 8 HighWire-hosted articles. Access the articles at:

   

  E-mail alerts related to this article or journal.Sign up to receive free email-alerts

  Subscriptions

Reprints and

  .pubs@aacr.org

To order reprints of this article or to subscribe to the journal, contact the AACR Publications Department at

  Permissions

  Rightslink site. Click on "Request Permissions" which will take you to the Copyright Clearance Center's (CCC)

.http://cancerres.aacrjournals.org/content/80/14/3023To request permission to re-use all or part of this article, use this link

on August 8, 2021. © 2020 American Association for Cancer Research. cancerres.aacrjournals.org Downloaded from

Published OnlineFirst March 10, 2020; DOI: 10.1158/0008-5472.CAN-19-3265