tumor- and neoantigen-reactive t-cell receptors can...

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Tumor- and neoantigen-reactive T-cell receptors can be identified based on

their frequency in fresh tumor

Anna Pasetto1, Alena Gros1, Paul F Robbins1, Drew C Deniger1, Todd D Prickett1, Rodrigo

Matus-Nicodemos2,3, Daniel C Douek3, Bryan Howie4, Harlan Robins4,5, Maria R Parkhurst1,

Jared Gartner1, Katarzyna Trebska-McGowan1, Jessica S Crystal1, Steven A Rosenberg1*

1Surgery Branch, National Cancer Institute, National Institutes of Health (NIH), Bethesda,

Maryland, USA

2Immunology Laboratory, Vaccine Research Center, National Institute of Allergy and Infectious

Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD 20892, USA

3Human Immunology Section, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892,

USA

4Adaptive Biotechnologies, Seattle, WA 98102, USA

5Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA

Running Title: Tumor and neoantigen-reactivity of high-frequency TILs

Keywords: TCRB sequencing, TCRA-TCRB pairs, neoantigen, melanoma, TCR-gene therapy

Financial support: This research was supported by the Intramural Research Program of the NIH

at the National Cancer Institute.

Corresponding author: Steven A Rosenberg

National Cancer Institute

10 Center Drive MSC 1201

CRC Room 3-3940

Bethesda, MD 20892

on May 22, 2018. © 2016 American Association for Cancer Research. cancerimmunolres.aacrjournals.org Downloaded from

Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on June 28, 2016; DOI: 10.1158/2326-6066.CIR-16-0001

http://cancerimmunolres.aacrjournals.org/

Phone: 301-496-4164, email: [email protected]

Competing financial interests. H.R. has salary, equity ownership, patents, and royalties with

Adaptive Biotechnologies and he is an inventor on the filed patent no. WO/2013/188831;

PCT/US2013/045994, titled "Uniquely tagged rearranged adaptive immune receptor genes in a

complex gene set."; B.H. has employment and equity ownership with Adaptive Biotechnologies.

All the other authors declare no competing financial interests.




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ABSTRACT

Adoptive transfer of T cells with engineered T-cell receptor (TCR) genes that target tumor-

specific antigens can mediate cancer regression. Accumulating evidence suggests that the

clinical success of many immunotherapies is mediated by T-cells targeting mutated

neoantigens unique to the patient. We hypothesized that the most frequent TCR clonotypes

infiltrating the tumor were reactive against tumor antigens. To test this, we developed a

multi-step strategy that involved TCRB deep sequencing of the CD8+PD-1+ T-cell subset,

matching of TCRA-TCRB pairs by pairSEQ and single cell RT-PCR, followed by testing of

the TCRs for tumor-antigen specificity. Analysis of 12 fresh metastatic melanomas revealed

that in 11 samples, up to 5 tumor-reactive TCRs were present in the 5 most frequently

occurring clonotypes, which included reactivity against neoantigens. These data

demonstrate the feasibility of developing a rapid, personalized, TCR-gene therapy

approach that targets the unique set of antigens presented by the autologous tumor without

the need to identify their immunologic reactivity.

INTRODUCTION

The presence of lymphocytes infiltrating into the tumor stroma (tumor infiltrating lymphocytes;

TIL) has been associated with a favorable prognosis in melanoma (1) and other cancer types

including ovarian (2), colon (3) and breast cancer (4). In melanoma, in vitro analysis of expanded

TIL revealed a broad specificity of antigen recognition including melanoma/melanocyte shared

differentiation antigens (5-7), cancer germline antigens (8,9), and mutated neoantigens unique to

each patient’s tumor (10-12).




Adoptive cell therapy using autologous TIL is an immunotherapeutic approach capable of

inducing complete durable regression in 20% of patients with metastatic melanoma (13).

However TIL used for treatment undergo extensive in vivo and in vitro expansion, becoming

highly differentiated cells with limited additional proliferative potential (13,14). Control over

which T-cell clonotypes expand in vitro is limited, so the TCR clonotypic repertoire present in

the tumor can be altered, potentially leading to decreased frequencies of tumor-reactive

clonotypes.

To overcome these problems, we focused our attention on the TCR clonotypes present in

the tumor before any in vitro expansion. In melanoma, tumor-specific clonotypes are highly

enriched in the fresh CD8+PD-1+ TIL subset (15,16), which we hypothesize could be due to the

oligoclonal expansion that occurs when T-cells encounter their specific antigen in the tumor

microenvironment in vivo (17), leading to the presence of predominant clonotypes within this

population. Thus the frequency of a clonotype within the TIL repertoire may indicate its tumor

reactivity. To test this, we analyzed the TCR repertoire of TIL in freshly resected tumors from 12

patients with metastatic melanoma and found that many of the most frequent TCR clonotypes

present in the CD8+PD-1+ TIL subset recognized the autologous tumor and either mutated or

non-mutated tumor antigens. Thus, it may be possible to efficiently identify tumor-reactive TCRs

based solely on their frequency and PD-1 expression in the tumor. This can provide an efficient

means to obtain tumor reactive TCRs that can be genetically engineered into autologous cells

with high proliferative potential for use in cell therapy.

MATERIALS AND METHODS

Tumor samples




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Twelve metastatic melanoma samples were obtained from patients that were not undergoing

therapy at the time of sample collection. Patients had undergone a wide range of prior therapies,

including surgery, chemotherapy, radiotherapy, immunotherapy, or none of the above. PBLs

were obtained by either leukapheresis or venipuncture, prepared over Ficoll-Hypaque gradient

(LSM; ICN Biomedicals Inc.), and cryopreserved until analysis. After surgical resection, tumor

specimens were processed as previously described (18). Briefly, tumor specimens were minced,

enzymatically digested overnight at room temperature or for several hours at 37°C (RPMI-1640

with l-glutamine [Lonza], 1 mg/ml collagenase IV [Sigma-Aldrich], 30 U/ml DNAse

[Genentech], and antibiotics) and the tissue was separated mechanically using gentleMACS

(Miltenyi Biotech). Tumor single-cell suspensions were cryopreserved.

Whole-exome sequencing and RNA sequencing

Genomic DNA purification, library construction, exome capture of approximately 20,000 coding

genes and next-generation sequencing of fresh tumor embedded in O.C.T. (Sakura Finetek,

Tokyo, Japan) and a matched normal pheresis sample were performed as previously described

(19). An mRNA sequencing library was prepared from fresh tumors using Illumina TruSeq

RNA library prep kit, as previously described (20). Putative non-synonymous mutations are

defined by ≥3 exome variant reads, ≥ 8% variant allele fraction (VAF) in the exome, ≥ 10 reads

in the matched normal sample. Putative mutations with a variant allele frequency (VAF) >10%

in the tumor exome, as well as mutations that were identified in both transcriptome and exome

analysis are initially selected for screening. For some samples (e. i. 3903), the mutations selected

based on exome only were prioritized by selecting those with >10 variant reads to increase the

confidence of mutation calling.




Antibodies, flow cytometry, and cell sorting

Fluorescently conjugated antibodies were purchased from eBioscience [MIH-4, Anti-Human

CD279 conjugated to allophycocyanin (APC) and anti-mouse TCRβ-fluorescein isothiocyanate

(FITC)], Miltenyi (4B4-1, anti-human CD137-PE or -APC), BioLegend [anti-human CD8-

phycoerythrin (PE)-Cy7, anti-human CD3-APC-Cy7]. For phenotypic characterization and cell

sorting of CD8+/-, CD8+PD-1+/- T-cells tumor samples were thawed and rested overnight without

cytokines (15). The T-cells were sorted by flow cytometry with a modified FACSAria instrument

or a BD Jazz instrument (BD Biosciences), gates were set according to isotype and fluorescence

minus one (FMO) controls. The sorting strategy is shown for two representative fresh melanoma

samples (3903 and 3998) in Supplementary Fig. S1.

Sample preparation for ImmunoSEQ TCRB deep sequencing and pairSEQ

The T-cells were sorted by flow cytometry in comparable numbers for each subset: 100,000 cells

for the tumor single cell suspension bulk TIL, 10,000 cells for the CD8+ and CD8- subsets and

1,000 to 3,000 cells for the CD8+PD-1+ and CD8+PD-1- subsets. The cells were pelleted and snap

frozen. The samples were sent to Adaptive Technologies for genomic DNA extraction and

ImmunoSEQ TCRB survey sequencing. Tumor samples were sent to Adaptive Technologies for

pairSEQ (21), 1 x 106 total cells from tumor single cell suspension were pelleted in a table top

centrifuge at 6000 rpm for 30 min, re-suspended in 200 μl of RNAlater (Invitrogen) and snap

frozen.

Single cell sorting and single cell RT-PCR




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Single-cell sorting was performed using a modified FACSAria instrument or BD Jazz instrument

(BD Biosciences) on CD8+PD-1+ TIL; for samples 1913, 2650, 3713 and 3784 CD8+ expanded

TIL were used due to limited availability of tumor samples. TCR sequences from the sorted

single cells were obtained by a series of 2 nested PCR reactions. Cells were sorted into RT-PCR

buffer. For the first reverse transcription and amplification reaction were performed with a One-

Step RT-PCR kit (Qiagen) using multiplex PCR with multiple Vα and Vβ region primers and

one primer for Cα and Cβ regions each (final concentration of each primer is 0.6 μM). The RT-

PCR reaction was performed accordingly to manufacturer's instructions using the following

cycling conditions: 50 °C 15 min; 95 °C 2 min; 95 °C 15 s, 60 °C 4 min × 18 cycles; 4 °C. For

the second amplification reaction 4 μl from the first RT-PCR were used as a template in total 25

μl PCR mix using HotStarTaq DNA polymerase (Qiagen) and multiple internally nested Vα and

Vβ region primers and 1 internally nested primer for Cα and Cβ regions each (final concentration

of each primer is 0.6 μM). The cycling conditions were 95 °C 15 min; 94 °C 30 s, 50 °C 30 s, 72

°C 1 min × 50 cycles; 72 °C 10 min; 4 °C. The PCR products were purified and sequenced by

Sanger method with an internally nested Cα and Cβ regions primers by Beckmann Coulter. All

primers are listed in Supplementary Table S1.

TCR pairs reconstruction, cloning into expression vectors and TCR expression evaluation

In both pairing methods (single cell RT-PCR and pairSEQ) cDNA is used as template for

multiplex PCR using TCRA and TCRB gene-specific primers. The resulting PCR product

contains the 3’ end of the variable region and the full CDR3 region of matching TCRA and

TCRB genes. These partial TCR sequences were analyzed with IMGT/V-Quest tool

(http://www.imgt.org/IMGT) which identified the TRAV and TRBV families with the highest




likelihood to contain the segment found with our pairing methods. Utilizing the IMGT database

we reconstructed the full length TRAV and TRBV regions for each pairs. In regards to the

constant regions we used modified murine TRAC and TRBC sequences to improve stability and

avoid mismatches with the endogenous human TCR after transduction into human T-cells (22).

Full TCR genes were synthetized and a 2A peptide (23) was introduced between the TCRB and

TCRA chain to ensure a comparable expression efficiency of the 2 chains. The resulting TCRB-

TCRA gene blocks were cloned into either a gamma-retroviral expression vector (24,25) or for

the following TCR pairs: 2650-1, 2650-3, 2650-4, 2650-5, 2650-6, 2650-7, 2650-9, 3903-3A1,

3903-3A2, 3992-1, 3992-2, 3992-3, 3992-4, 3992-5 and 3998-1 into a non-viral Sleeping Beauty

transposon system (26,27). The expression of the TCRB was evaluated with an anti-murine

TCRB Ab.

Target cell preparation

Melanoma tumor cell line (TC) (TC 1913, TC 2630, TC 2650, TC 3678, TC 3713, TC 3759, TC

3784, TC 3903, TC 3922, TC 3926, TC 3977, TC 3992, TC 3998) were established from tumor

fragments or from mechanically or enzymatically separated tumor cells and cultured in RPMI

1640 plus 10% FBS (Sigma-Aldrich) supplemented with 100 U/ml penicillin and 100 μg/ml

streptomycin at 37°C in 5% CO2. COS-7 cells and COS-7 cells stably transduced with HLA

molecules were maintained in DMEM containing 10% FBS (Sigma-Aldrich) supplemented with

100 U/ml penicillin and 100 μg/ml streptomycin at 37°C in 5% CO2. TC 1913 and 1913 tumor-

specific neoantigens recognition were previously reported (28). Generation of tandem minigenes

(TMG) constructs and autologous antigen presenting cells (dendritic cells and CD40L stimulated

B-cells) was done as previously described (11, 29). Briefly, up to 14 non-synonymous mutations




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identified by whole exome sequencing and RNAseq, each flanked by 12 amino acids of non-

mutated protein, were genetically fused together to generate a tandem minigenes (TMG)

construct. These constructs were codon optimized, synthesized and cloned into pcDNA3.1/V5 by

Genescript. Autologous antigen presenting cells were peptide pulsed for 2h with 1 μg/ml short

peptides (9-10 mers) and overnight with 10 μg/ml of long peptides (25 mers) before co-culture.

Target cell recognition functional assay

CD137 up-regulation was used to measure target recognition by transduced T cells. CD137 is

upregulated transiently in response to TCR stimulation, regardless of the effector cytokines

produced or the differentiation state of the cell (30). We used the co-expression of murine TCR

constant chain (identified as mTCR) and CD137 to identify the population of transduced antigen-

reactive T-cells (to be considered reactive the CD137 up-regulation had to be greater than 1%, 3

times the background and inhibited at least 50% by pan MHC-I blocking antibody, clone W6-

32). Cells were stained with anti-CD3, anti-CD8, anti–CD137 and anti-murine TCRB antibodies

after co-culture and acquired by Fortessa (BD Biosciences). Data were analyzed with FlowJo

software (Treestar).

Statistical analysis

Wilcoxon signed-rank test was used to determine the statistical significance of the data. P values

of 0.05 or less were considered significant. Statistical calculations were performed with Prism

program 6.0 (GraphPad Software Inc).

Study approval




All patient samples were obtained in the course of a National Cancer Institute Institutional

Review Board–approved clinical trial. Patients provided informed consent.

RESULTS

CD8+PD-1+ TIL clonotypes are oligoclonal compared to CD8+PD-1- TIL

To characterize the TIL TCR clonotypic repertoire and identify tumor-reactive TCRs, we

developed a multi-step strategy (Fig. 1A). We first assessed the composition of TIL from 12

fresh metastatic melanoma lesions by flow cytometry (Table 1). The samples varied considerably

in the frequency of CD8+ and CD8- lymphocytes (P = 0.15), although the frequency of PD-1

expression, which is a marker for T-cell activation (16, 31), was usually higher on the CD8+ TIL

(P = 0.003). TCRB deep sequencing is a robust method for quantifying the frequency of each T-

cell clonotype present in different sample types (32-34), which we used to determine whether the

CD8+PD-1+ TIL subset displayed evidence of clonal expansion. Genomic DNA extracted from

bulk melanoma TIL and from sorted subsets (CD8+, CD8-, CD8+PD-1+ and CD8+PD-1-) was

deep sequenced to determine the number of unique productive (35) TCRB CDR3 sequences that

do not contain stop codons or frame-shifts (Fig. 1B) in the 10 patients from which all samples

were available. These unique sequences represent a single, unique clonotype independent of its

frequency in the samples. Different samples can thus have comparable numbers of total reads

(Fig. 1C), but it is the different number of unique sequences that determines the level of clonality

of each sample. We found a significantly lower number of unique productive sequences present

in the CD8+ compared to the CD8- subsets (P = 0.002, Fig. 1B). Within the CD8+ lymphocytes,

the PD-1+ population contained a lower number of unique productive sequences compared to

PD-1- cells (P = 0.002, Fig. 1B). We also compared the levels of clonal diversity [measured by




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Shannon entropy (36)] for the samples studied and we found more diversity in the CD8- subset

compared to the CD8+ (P = 0.002) and within the CD8+ lymphocytes more diversity in the PD1-

cells compared to the PD1+ (P = 0.002, Supplementary Fig. S2A). We also compared the number

of non-synonymous mutations to the percent of CD8+PD-1+ TIL and TCR clonal diversity in

different TIL subsets (Supplementary Fig. 2B-E), but found no significant correlation. Each

highly expressed individual clonotype in the CD8+PD-1+ subset was much less frequent in the

PD-1- group (P = 0.0003, Supplementary Fig. S3A), confirming that PD-1 is a marker that

separates TIL into two separate subsets with different TCR repertoires (15). The same clonotypes

that were highly expressed in the CD8+PD-1+ subset were found at low frequency in the total

CD8+ subset (Supplementary Fig. S3B, P = 0.001). The highest expressers in the PD-1+ subset

though, were often also high ranked in the bulk TIL (Supplementary Table S2).

Identification and reconstruction of TCR pairs for the most frequent CD8+PD-1+ TIL

clonotypes

To reconstruct a functional TCR, the most frequent TCRB chains present in the CD8+PD-1+ TIL

must be paired with the appropriate TCRA chains. One possible approach was to match the most

frequent TCRB clonotype with the most frequent TCRA clonotype. However, in the 6 patient

samples for which we ultimately matched the correct TCRA with the most frequent TCRB and

determined their functionality, the most frequent TCR chains paired together in 3 cases, the 1st

TCRB in the other 3 cases paired with the 7th, 18th and 47th TCRA (Supplementary Table S3).

Tumor recognition by the 1st TCRB with the 1st TCRA occurred in the 3 cases in which the 1st

TCRB clonotype was present in >20% of the PD-1+ population. Discordance of pairing based on

frequency of the TCRA was likely due to the presence of more than 1 α-chain in some cells (37)




as well as the variable efficiency of primers used in the TCRA sequencing. Thus we decided to

identify the productive TCR pairs with 2 different approaches. After identifying the most

frequent TCRBs in the CD8+PD-1+ population, we identified the corresponding TCRA with

single cell RT-PCR on CD8+PD-1+ FACS sorted TIL or CD8+ TIL expanded in vitro.

Alternatively we used the pairSEQ approach (21) on single cell suspensions from unsorted fresh

tumors. The efficiency of the single cell RT-PCR was between 26% and 90%, depending on the

sample. Using this method, we identified a median value of 29 (range 9-43) unique TCRA-

TCRB pairs, in each of the CD8+ or CD8+PD-1+ samples. Using pairSEQ on unsorted fresh

tumors we identified a median value of 217 (range 11-883) unique pairs for each sample. A total

of 93 (median value 6, range 0-21) TCRA-TCRB pairs from 12 metastatic melanoma patients

were identified using both methods (congruent pairs in Table 2, method of identification for each

pair in Supplementary Table S4). We generated expression vector constructs encoding the 83 of

these pairs ranked within the top 10 CD8+PD-1+ clonotypes and linked them to murine constant

chain sequences, to improve stability and avoid mismatches with endogenous human TCRs (22),

and then introduced them into fresh PBLs. The frequency of T-cells that expressed the

recombinant TCRs after either retroviral transduction or transfection with a Sleeping Beauty

transposon construct ranged between 24.4 and 97.6% (Supplementary Table S5).

High frequency CD8+PD-1+ clonotypes display tumor and mutation reactivity

We then evaluated the anti-tumor activity of T cells expressing those 83 TCRA-TCRB pairs

(Table 2). The TCRs obtained from 10 of the 12 patients were evaluated for response to

candidate neo-epitopes identified by whole-exome sequencing of autologous tumor (TCRs from

samples 2650 and 3977 were only evaluated against the TC line) (Table 1). All the TCR pairs




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were also tested against autologous or HLA-matched antigen presenting cells transfected with

full-length RNA encoding the melanoma/melanocyte shared differentiation antigens MART-1,

gp100, and tyrosinase (TYR) and the cancer-germline antigens NY-ESO-1, MAGEA3, and

SSX2.

Evaluation of response against the corresponding autologous TC and/or autologous

antigen presenting cells that had either been pulsed with mutated tumor-specific neoantigen

minimal epitopes or transfected with tandem minigene (TMG) (10-12) constructs provided

evidence for tumor antigen reactivity in 11 of the 12 patients that were evaluated.

For example, for patient 3998 we initially evaluated the reactivity of some of the top

eight most frequent TCR pairs based on the frequency of TCRB (3998-1, 3998-2, 3998-3A1,

3998-3A2, 3998-4, 3998-6, 3998-7, and 3998-8) against the autologous TC (Fig. 2A and C). Six

of the TCR pairs tested (3998-1, 3998-2, 3998-4, 3998-6, 3998-7, and 3998-8) showed MHC-

restricted recognition of the autologous tumor. The TCRB clonotype ranking 3rd in frequency in

the CD8+PD-1+ TIL was associated with two productive TCRA chains but none of the two

combinations (3998-3A1 and 3998-3A2) were tumor reactive. For tumor sample 3998, 345 non-

synonymous mutations were identified (Table 1). We next evaluated the reactivity of the 6 TCR

pairs (3998-1, 3998-2, 3998-4, 3998-6, 3998-7, and 3998-8) against 115 mutated antigens

encoded by seven TMGs (Fig. 2B) and six shared melanoma/melanocyte differentiation antigens

and cancer-germline antigens (MART-1, gp100, SSX2, TYR, NY-ESO-1, MAGEA3)

(Supplementary Fig. S4A and B). The 115 mutated antigens were selected for screening from the

345 non-synonymous mutations based on RNAseq data of their expression. Two TCR pairs

(3998-7 and 3998-8) were reactive to TMG-1 (Fig. 2B). Further testing identified MAGEA6E168K

as the specific mutation recognized within the antigens encoded by TMG-1 (Fig. 2D and




Supplementary Fig. S4C). Reactivity against one shared antigen (NY-ESO-1) was found for

TCR pair 3998-5 (Table 3 and Supplementary Fig. S4B).

Figure 3 summarizes the findings of all 12 samples. Representative cocultures for all of

the tumor samples are shown in Supplementary Figs. S4-S15. For example, in sample 1913 the

TCRB ranking 2, 3, and 4 were specific for the autologous TC line, and the clonotypes ranking 2

and 4, as previously found (15, 28), also recognized a mutation in the HLA-11 gene (Table 3).

Moreover the most frequent TCR clonotype was found to be tumor reactive for seven samples

(2650, 3759, 3903, 3922, 3926, 3977 and 3998). For all but patient 3992, up to five tumor-

reactive TCRs were found among the five most frequently expressed TCRs in the CD8+PD-1+

TIL. Reactivity against autologous neoantigens was found in five of the 10 patients whose TCRs

were screened against putative autologous mutations. In summary we found that 36 TCR pairs

were reactive against autologous tumor and 11 were directed against mutated tumor-specific

neoantigens. This indicates that it is possible to identify tumor-reactive TCR pairs in the majority

of melanoma samples simply based on their frequency in the CD8+PD-1+ TIL compartment.

DISCUSSION

We have shown that adoptive cell therapy with TIL that appeared to predominantly recognize

patient-specific tumor neoantigens (11,12) or T cells genetically engineered to express TCRs

targeting cancer-germline antigens (8) can mediate complete response in patients with metastatic

melanoma (10,12) and in a patient with metastatic cholangiocarcinoma (29). Those studies used

a labor-intensive screening approach using tandem minigenes or long peptides representing all

known mutations and could identify T cells with reactivity against mutated neoantigens. Tumor

reactive TCRs expressed by mutation-reactive T cells can be isolated, cloned into expression




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vectors and can potentially be transferred into autologous cells with high proliferative capacity

(13,38) for use in cell transfer therapy. Here we demonstrate the identification of tumor and

mutation-reactive TCRs from fresh melanoma samples, based on PD-1 expression and on TCRB

frequencies as a guide to tumor reactivity.

The development of next generation TCRB sequencing has allowed a study of the total TCR

repertoire in different T-cell compartments in healthy individuals (32) as well as in tumor

samples from colorectal (33) and ovarian carcinomas (34). In the present study we have analyzed

the TCR diversity in different subsets of TIL from freshly resected human metastatic melanomas

and attempted to determine whether the rank frequency of TCRs was related to their ability to

recognize the autologous cancer. This strategy can be used to prospectively identify tumor

reactive TCRs without the prior need to know their antigen specificity.

The major obstacle encountered in the evaluation of the anti-tumor reactivity of

individual TCRs in the fresh tumor prior to in vitro expansion, was the technical difficulty in

pairing each high frequency TCRB chain with the correct TCRA. In the present study we utilized

two independent approaches to identify the TCRA-TCRB pairs, single cell RT-PCR on a specific

subset (CD8+PD-1+ TIL or CD8+ expanded TIL) and pairSEQ on unsorted tumors. The single

cell RT-PCR allowed us to directly extract cDNA from single cells and sequence the TCR gene

after several rounds of PCR with specific primers using the Sanger method (39), followed by

TOPO TA cloning in the event the T-cell expressed two different TCRA chains at the same time.

This technique, based on a 96 well platform, has also been successful when applied to MHC-

multimer sorting on antigen-specific cells (40, 41), although MHC-multimer sorting is only

feasible when the HLA restriction element and the minimal epitope of interest are known. In our

study we used a different approach that does not require the knowledge of antigen specificity by




sorting specific TIL subsets. Other higher throughput approaches have been proposed such as

emulsion PCR (42) and “TCR gene capture” that utilizes an RNA-bait library to specifically

target the genomic sequence encoding TCR genes (43). Recently, pairSEQ (21), a new high

throughput technology for pairing TCRA and TCRB sequences has become available and we

tested its feasibility in fresh, unsorted, melanoma samples. PairSEQ utilized a statistical model

for pairing TCRA and TCRB chains and, since it is based on next generation sequencing, no

extra steps are required (such as TOPO TA cloning) to identify two different TCRA genes

expressed by the same cell. Combining the single cell RT-PCR on specific TIL subsets and

pairSEQ on unsorted tumors, we successfully identified the majority, but not all, of the top 10

most frequent TIL CD8+PD-1+ TCR pairs in 12 patients and tested them against autologous

tumor tissue culture lines and autologous antigen presenting cells expressing tandem minigenes

encoding shared cancer antigens, mutated tumor neoantigens and/or pulsed with the

corresponding mutated peptides (11,29). Multiple reactive pairs could be identified in the top

ranking TCRs in 11 of 12 patients with metastatic melanoma including 11 TCRs specific for

mutated neo-epitopes (Fig. 3). We included the six most common melanoma/melanocyte and

cancer-germline antigens commonly recognized by patient TIL in our screening. With this

limited screening panel we identified two TCR pairs that were specific for MART-1 (3922-1)

and NY-ESO-1 (3998-5). For the other 25 TCR pairs we could demonstrate MHC restricted

reactivity against the autologous tumor cell line although their specificity remains undefined.

Non-reactive pairs need to be considered with caution. Our approach is based on PCR

therefore it is subjected to potential errors that could have altered the original sequence of the

TCRA-TCRB pairs. Incorrect pairing is also a possible explanation.




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Despite these limitations, we identified tumor-reactive TCRs based on their TCRB

frequency in the TIL CD8+PD-1+ population. The major advantage of this approach is the

rapidity in finding functional TCRs without the need for further screening. However, once the

high-frequency TCRs are identified, they can be tested in vitro in an overnight assay versus the

fresh tumor suspension as well as normal autologous PBL to further identify their specificity.

This finding opens the possibility for a highly personalized cell transfer cancer therapy in which

patients can be treated with autologous, genetically-engineered T-cells with high proliferative

potential. This new approach can potentially be applied to malignancies other than melanoma

and is currently under study.

ACKNOWLEDGMENTS

We thank Sanja Stevanović, Eric Tran, William Lu, Mojgan Ahmadzadeh and Cyril Cohen for

helpful discussions, Yang-Li, Mona El-Gamil and Lien Ngo for technical advice and support,

Arnold Mixon and Shown Farid for flow cytometry technical support and sorting. We also thank

the Adelson Medical Research Foundation for their generous support for this study.




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FIGURE LEGENDS

Fig. 1. Strategy overview and TIL characterization. (A) Schematic representation of the

multi-step process used to identify tumor reactive TCRs. 1) TCRB deep sequencing on bulk TIL

and sorted CD8+/– TIL and CD8+PD-1+/– TIL populations is used to determine the subset with

evidence of clonal expansion and to identify the TCRB sequences of the most dominant

clonotypes within that subset. 2) The most dominant TCRB clonotypes in CD8+PD-1+ TIL are

paired with TCRA chains identified by single cell RT-PCR and pairSEQ. 3) TCRA-TCRB pairs

are cloned into expression vectors and engineered into T cells. 4) Engineered T cells are tested

for tumor reactivity against tumor cell lines, shared tumor antigens and mutated neoantigens. (B)

Unique productive TCRB clonotypes sequences are plotted for bulk TIL and sorted TIL subsets.

Productive sequences do not contain stop codons or out of frame shifts so they are likely to be

functional. These unique sequences represent a single, unique clonotype independent of its




frequency in the samples. Wilcoxon matched-pairs signed rank test was applied (n = 10). For

samples 1913 and 3922 the CD8– subset was not available. (C) Total reads of TCRB clonotypes

sequences are plotted for melanoma bulk TIL and sorted TIL subsets. Wilcoxon matched-pairs

signed rank test was applied (n = 10). For samples 1913 and 3922 the CD8- subset was not

available.

Fig. 2. Tumor-specific target recognition assay for reconstructed TCR pairs for patient

3998. (A) CD137 up-regulation on CD8+mTCRB+ cells is shown after co-culture with

autologous tumor cell line for 8 of the TCR pairs reconstructed within the top 10 CD8+PD-1+

TIL for this tumor sample: the 1st, 2nd, 3rd (in combination with 2 TCRAs), 4th, 6th, 7th and 8th

most frequent TCRBs. Values are reported as mean ± SEM, the assay was done in duplicate. (B)

CD137 up-regulation on CD8+mTCRB+ cells is shown after co-culture with autologous B cells

transfected with tandem minigenes (TMG-1 to 7) encoding for 115 non-synonymous mutations

for 6 of the TCR pairs reconstructed (3998-1, 3998-2, 3998-4, 3998-6, 3998-7, 3998-8). Values

are reported as mean ± SEM, the assay was done in duplicate. (C) CD137 up-regulation is

inhibited by pan MHC-I antibody. MHC-I restricted DMF5 TCR is reported as positive control

and MHC-II restricted TCR MAGE-A3 is reported as negative control. * = greater than 50%

inhibition. Values are reported as mean ± SEM, the assay was done in duplicate. (D) Murine

TCRB expression and CD137 up-regulation are shown for reconstructed TCR pair 3998-8 after

co-culture with, unpulsed autologous B cells, autologous B cells pulsed with 1 μg/ml, 100 ng/ml,

10 ng/ml, 1 ng/ml, and 0.1 ng/ml of the mutated MAGEA6 peptide (KVDPIGHVY) and wild

type MAGEA6 peptide (EVDPIGHVY) respectively.




23

Fig. 3. Summary of tumor and mutation reactivity for reconstructed TCR pairs. For every

sample analyzed the graph represents the TCRB frequency of the top 10 CD8+PD-1+ clonotypes

and color-coded their reactivity against autologous TC lines, shared melanoma/melanocyte and

cancer-germline antigens, and tumor-specific mutations. All patients, except 3678, had a

corresponding autologous TC line used for testing the TCR pairs. In 11 of 12 patients up to 5

tumor-reactive TCRs were found in the 5 most frequently expressed TCRs and this included

recognition of mutated neoantigens in 5 of the patients. In 2 patients reactivity against MART-1

(3922-1) and NY-ESO-1 (3998-5) was also found. The most frequent TCR clonotype was found

to be tumor reactive for 7 patients.

Patient ID Age Sex Tumor

location lymphocytes (% of viable

cells)

CD3+ (% of

lymphocytes)

CD3+CD8+ (% of CD3+)

CD3+CD8– (% of CD3+)

CD3+CD8+ PD-1+ (% of

CD3+CD8+)

CD3+CD8– PD-1+ (% of

CD3+CD8–)

Tumor cell line (TC) available

Non-synonymous mutations a

1913 40 F subcutaneous 42.9 38.4 67.2 20.1 17.2 24.4 yes 3280

2650 56 F lymph node 9.21 8.52 36.5 62.5 12 2.38 yes 431

3678 55 F lymph node 20.7 16.1 51.0 46.5 11.3 12.7 no 504

3713 53 M lung 28.1 19.7 32.7 33.9 55.2 45.7 yes 3976

3759 21 M subcutaneous 2.06 1.42 53.4 18.4 81.0 12.3 yes 1378

3784 45 M lymph node 18.1 12 35.2 22.2 31.6 15.9 yes 662

3903 56 M liver 31.4 26.2 53.3 30.8 74.8 33.7 yes 385

3922 65 M lymph node 15.9 7.2 24.5 73.3 11.4 2.84 yes 449

3926 37 M lymph node 22.8 15.7 42.3 28.5 34.4 18.5 yes 340

3977 51 M lymph node 17.7 15.4 50.3 47 35.7 16.6 yes N/A

3992 58 F lymph node 79 16.8 36.4 28.2 15.4 9.78 yes 159

3998 30 M liver 17.7 15.8 70.2 15 61.9 11.3 yes 345

TABLES




Table 1. Characteristics of infiltrating cells in fresh tumors

a Putative non-synonymous mutations defined by ≥ 3 exome variant reads, ≥ 8% variant allele

fraction (VAF) in the exome, ≥ 10 reads in the matched normal sample.

Table 2. Unique TCR pairs identified

Sample ID

Number of Unique TCR pairs identified by

Single cell RT-PCRa

Number of Unique TCR pairs identified by

pairSEQb Number of Unique

congruent TCR pairs Number of reconstructed TCR pairs

evaluated within the top 10 CD8+PD-1+ clonotypes

1913 29 136 3 8 2650 30 21 3 7 3678 32 11 0 4 3713 21 829 21 4 3759 34 133 15 7 3784 15 883 7 9 3903 14 156 5 10 3922 9 351 3 5 3926 33 737 6 8 3977 29 21 2 8 3992 20 278 9 5 3998 43 349 19 8

a Single cell PCR was performed on sorted CD8+PD-1+ TIL and for 1913, 2650, 3713, 3784 on

sorted CD8+ expanded TIL due to limited availability of tumor samples.

b PairSEQ was performed on bulk TIL.




25

Table 3. Antigen specificity identified

TCRB rank in TIL CD8+PD-1+ 1913 2650 3678 3713 3759 3784 3903 3922 3926 3977 3992 3998

1 - TC N/A - TC - KIAA-isoM1L MART-1 TC TC - TC

2 HLA-A11F33S N/A N/A HELZ2D614

N TC N/A - - N/A N/A - TC

3 TC - N/A SRPXP55L TC TC - - TC - - -

4 HLA-A11F33S - - N/A TC - - N/A N/A N/A - TC

5 - TC FBXO21S250Y TC TC - - N/A TC N/A - NY-ESO-1

6 - - - WDR46T300

I - N/A - N/A TC TC N/A TC

7 - - FBXO21S250Y N/A N/A - - N/A TC N/A N/A MAGEA6E

168K

8 - N/A N/A TC N/A TC - - N/A - N/A MAGEA6E168K

9 - - N/A N/A N/A TC N/A - N/A - N/A N/A

10 N/A N/A N/A WDR46T300

I N/A TC N/A N/A N/A - N/A N/A

- No reactivity was found against autologous tumor cell lines (TC), tumor-specific mutations,

melanoma/melanocyte and cancer-germline antigens tested.




Fig. 1

Strategy overview

Total productive unique sequences

log

10 T

CR

B c

lon

oty

pe s

eq

uen

ces

Bulk TIL

TIL C

D8-

TIL C

D8+

TIL C

D8+

PD-1

-

TIL C

D8+

PD-1

+

2.0

2.5

3.0

3.5

4.0

4.5

5.0Bulk TIL

TIL CD8+

TIL CD8-

TIL CD8+PD-1+

TIL CD8+PD-1-

TCRB unique clonotypes

p=0.002 p=0.002

Total productive unique sequences

log

10 T

CR

B c

lon

oty

pe s

eq

uen

ces

Bulk TIL

TIL C

D8-

TIL C

D8+

TIL C

D8+

PD-1

-

TIL C

D8+

PD-1

+

5.0

5.5

6.0

6.5

7.0Bulk TIL

TIL CD8+

TIL CD8-

TIL CD8+PD-1+

TIL CD8+PD-1-

Total reads

p=0.5 p>0.9

A

B C

Metastatic

melanoma sample

Tumor cells

Tumor Infiltrating

Lymphocytes (TIL)

• Tumor cell line (TC)

• Shared tumor antigens

(MART-1, gp100, TYR,

MAGEA3, SSX2, NY-

ESO-1)

• Tumor neoantigens

Sorting of specific

populations (TIL CD8+/-,

TIL CD8+PD-1+/-)

Unsorted fresh

tumor (bulk TIL)

TCRB

ImmunoSEQ TCRB

sequencing to

identify most

dominant clonotypes

T cell receptor

(TCR)

Deep sequencing

from genomic DNA

TCRA-TCRB

pairsSingle cell RT-PCR on

TIL CD8+PD-1+TCRA TCRB

PairSEQ on

unsorted bulk TIL

High throughput

TCRA-TCRB pairs

TCRA TCRB

Expression vector

TCRA TCRB

2.

3.

1.

4.

Lo

g10 T

CR

B u

niq

ue c

lon

oty

pes

Lo

g10 T

CR

B u

niq

ue r

ea

ds




Fig. 2

A

B 3998 TMG mut SEM no 3

% C

D8

+m

TC

RB

+C

D1

37

+

3998

-1

3998

-2

3998

-4

3998

-6

3998

-7

3998

-8

0

10

20

30

40

50

60

70

TMG-1

TMG-2

TMG-3

TMG-4

irr TMG

TMG-5

TMG-6

TMG-7

TC 3998

% C

D8+

mT

CR

+C

D137

+

3998 TMG mut SEM no 3

% C

D8

+m

TC

RB

+C

D1

37

+

3998

-1

3998

-2

3998

-4

3998

-6

3998

-7

3998

-8

0

20

40

60

80

TMG-1

TMG-2

TMG-3

TMG-4

irr TMG

TMG-5

TMG-6

TMG-7

TC 3998

% C

D8+

mT

CR

+C

D137

+

3998 TC coculture version 7 SEM

% C

D8

+m

TC

RB

+C

D1

37

+

3998-

1

3998-

2

3998-

3A1

3998-

3A2

3998-

4

3998-

6

3998-

7

3998-

8

0

20

40

60

80

TC 3998

OKT-3

Mismatched TC

3998 TC coculture version 7 SEM

% C

D8

+m

TC

RB

+C

D1

37

+

3998-

1

3998-

2

3998-

3A1

3998-

3A2

3998-

4

3998-

6

3998-

7

3998-

8

0

20

40

60

80

TC 3998Mismatched TC

OKT-3

D

3998 class I block only

% C

D8

+m

TC

RB

+C

D1

37

+

3998

-1

3998

-2

3998

-4

3998

-6

DM

F5

MAGE-A

3

0

20

40

60

80

TC 3998

TC 3998 + class I block

T cells only

TC 2630 CIITA

TC 2630 CIITA + class I block

C

3998

-1

3998

-2

3998

-4

3998

-6

DM

F5

MAGE-A

3

0

5

10

15

20

60

80

3998 class I block only

% C

D8

+m

TC

RB

+C

D1

37

+

TC 3998

TC 3998 + class I block

T cells only

TC 2630 CIITA

TC 2630 CIITA + class I block%

CD

8+

mT

CR

+C

D137

+

*

*

* *

*

100 ng/ml 10 ng/ml 1 ng/ml 0.1 ng/ml B-cells only

OKT-3

CD137

mT

CR

B

MAGEA6mut peptide

MAGEA6wt peptide

1 μg/ml

100 ng/ml 10 ng/ml 1 ng/ml 0.1 ng/ml 1 μg/ml

TCR pair 3998-8




Fig. 3 L

og

10

TC

RB

clo

no

type

TCRB clonotype rank in CD8+PD-1+

Not evaluated TC and shared

Ag

reactive

TC

reactive

Mutation

reactive

(TC N/A)

Not reactive TC and Mutation

reactive

1913

0 1 2 3 4 5 6 7 8 9 100.1

1

10

100

2650

0 1 2 3 4 5 6 7 8 9 100.1

1

10

100

3678

0 1 2 3 4 5 6 7 8 9 100.1

1

10

100

3713

0 1 2 3 4 5 6 7 8 9 100.1

1

10

100

3759

0 1 2 3 4 5 6 7 8 9 100.1

1

10

100

3784

0 1 2 3 4 5 6 7 8 9 100.1

1

10

100

3903

0 1 2 3 4 5 6 7 8 9 100.1

1

10

100

3922

0 1 2 3 4 5 6 7 8 9 100.1

1

10

100

3926

0 1 2 3 4 5 6 7 8 9 100.1

1

10

100

3977

0 1 2 3 4 5 6 7 8 9 100.1

1

10

100

3992

0 1 2 3 4 5 6 7 8 9 100.1

1

10

100

3998

0 1 2 3 4 5 6 7 8 9 100.1

1

10

100




Published OnlineFirst June 28, 2016.Cancer Immunol Res Anna Pasetto, Gros Alena, Paul F Robbins, et al. identified based on their frequency in fresh tumorTumor- and neoantigen-reactive T-cell receptors can be

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