Thermo Fisher Scientific • 5791 Van Allen Way • Carlsbad, CA 92008 • www.thermofisher.comFor Research Use Only. Not for use in diagnostic procedures. The content provided herein may relate to products that have not been officially released and is subject to change without notice.

G Lowman1, T Looney2, E Linch1, L Miller1, D Topacio-Hall1, A Pankov2, J Zheng2, R Hartberg3, H Almåsbak3, T E Stav-Noraas3, A Kullmann3, F Hyland2, M Andersen1

(1) Thermo Fisher Scientific, Carlsbad, CA, USA (2) Thermo Fisher Scientific, South San Francisco, CA, USA (3) Thermo Fisher Scientific, Oslo, Norway

Insights into the tumor microenvironment and therapeutic T cell manufacture revealed by long amplicon immune repertoire sequencing

ABSTRACTTCRβ immune repertoire analysis by next-generation sequencing is emerging as a valuable tool for research studies of the tumor microenvironment and potential immune responses to cancer immunotherapy1-4. Here we describe a multiplex PCR-based TCRβ sequencing assay (Ion AmpliSeqTM Immune Repertoire Assay Plus – TCRβ) that leverages Ion AmpliSeq library construction chemistry and the long read capability of the Ion S5 530TM chip to provide coverage of all three CDR domains of the human TCRβ chain. We demonstrate use of the assay to evaluate tumor-infiltrating T cell repertoire features and monitor manufacture of therapeutic T cells.

CONCLUSIONSThese results demonstrate: (1) The accuracy and versatility of immune repertoire sequencing using the Ion AmpliSeqTM

Immune Repertoire Assay Plus – TCRβ, (2) The benefit of combining targeted gene expression and repertoire profiling for studies of the tumor microenvironment, (3) The utility of repertoire sequencing covering all CDR regions in monitoring the manufacture of therapeutic T cells.

REFERENCES1. Robins, H. S. et al. Blood 114:19 (2009)2. Carlson, C. S. et al. Nat. Commun. 4, 2680 (2013)3. Li, B. et al. Nature Genetics 48, 725–732 (2016)4. Sheikh, N. et al. Cancer Res. 76:13 (2016)5. Sandberg et al. Leukemia 21:2 (2007) 6. Liu, X. et al. PLOS One 11:3 (2016)7. Thompson, J.R. et al. Nucleic Acids Res. 30:9 (2002)8. Qiu, X. et al. App. and Env. Microbiology 67:2 (2001)9. Wang, G. et al. App. and Env. Microbiology 63:12 (1997)

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19 NSCLC biopsies

Number of input T cells (log10)

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Sequencing of Counted T cells

Repressive Tumor Microenvironment

Permissive Tumor Microenvironment

Inhibits T cell responses to tumorPermits T cell expansion and

anti-tumor activity

High T cell evenness Low T cell evenness

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T cell clone evenness during in vitro expansionvia anti-CD3/CD28 beads

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57 copies

566 copies

5,655 copies

56,552 copies

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30plasmidspike-in

Detection of reference rearrangement spike-ins

Plasmid Input (pg)

Figure 1. Ion AmpliSeq Immune Repertoire Assay Plus – TCRβMultiplex AmpliSeq primers target the framework region 1 (FR1) and constant (C) regions of the TCRβ producing a ~330bp amplicon which covers the entire variable gene and the CDR3 region. The assay utilizes RNA input from blood leukocytes, fresh-frozen tissue, or sorted T cells and has a flexible input range between 10ng and 1μg.

INTRODUCTIONTo evaluate assay accuracy we sequenced libraries derived from 30 well-studied T cell lymphoma rearrangements5,6, then compared our results with those reported by another commercially available immune repertoire sequencing technology. We next used the assay to profile tumor infiltrating T cell repertoires for a cohort of 19 individuals with non-small cell lung cancer. We correlate repertoire features with gene expression profiling data. We then harnessed the long read capability of the assay to profile T cells at various stages of the therapeutic T cell manufacturing process.

ASSAY ACCURACYLong read TCRβ sequencing of 30 reference T cell lymphoma rearrangements cloned into plasmids in a background of PBL yielded strong linearity in detection of clonal frequencies in reference spike-in experiments. We further demonstrate the quantitative nature of the assay by studying populations of counted T cells.

Variable Diversity Joining Constant

N1 N2

A. Adult IGH or TCRBeta chain rearrangement

In adult B and T cells, the process of VDJ rearrangement very often involves exonucleotide chewback of VDJ genes and the addition of non-templated bases, forming N1 and N2 regions in the B cell receptorheavy chain CDR3 and the T cell receptor Beta chain CDR3. These processes vastly increase IGH and TCRB CDR3 diversity.

Variable Diversity Joining Constant

B. Fetal IGH or TCRBeta chain rearrangement

In the fetus, the process of VDJ rearrangement often occurs withoutexonucleotide chewback of VDJ genes and addition of non-templated bases, resulting in a restricted IGH and TCRB CDR3 repertoire that is distinct from the adult repertoire.

These structural differences can be used to distinguish fetal B and T cellCDR3 receptors from maternal B and T cell CDR3 receptors in cell freeDNA present in maternal peripheral blood. In this way, fetal B and Tcell health and development may be monitored in a non-invasivemanner.

Figure 1. Structural differences between fetal and adult B and T cell receptors

Variable Diversity Joining Constant

N1 N2

A. Adult IGH or TCRBeta chain rearrangement

In adult B and T cells, the process of VDJ rearrangement very often involves exonucleotide chewback of VDJ genes and the addition of non-templated bases, forming N1 and N2 regions in the B cell receptorheavy chain CDR3 and the T cell receptor Beta chain CDR3. These processes vastly increase IGH and TCRB CDR3 diversity.

Variable Diversity Joining Constant

B. Fetal IGH or TCRBeta chain rearrangement

In the fetus, the process of VDJ rearrangement often occurs withoutexonucleotide chewback of VDJ genes and addition of non-templated bases, resulting in a restricted IGH and TCRB CDR3 repertoire that is distinct from the adult repertoire.

These structural differences can be used to distinguish fetal B and T cellCDR3 receptors from maternal B and T cell CDR3 receptors in cell freeDNA present in maternal peripheral blood. In this way, fetal B and Tcell health and development may be monitored in a non-invasivemanner.

Figure 1. Structural differences between fetal and adult B and T cell receptors

FR1 FR2 Diversity(D) Joining (J)

Constant

Variable gene (V)

CDR3

FR3

~330bp Amplicon

CDR1 CDR2

Figure 2. Detection of reference rearrangements Libraries were prepared using pools of 30 known lymphoma rearrangements at known input concentrations (calculated to equal ~50,000 to ~5 copies of RNA) in a background of 100ng of leukocyte RNA. We observe strong linearity across five orders of magnitude of control input concentration.

Figure 3. Detection of counted T cells Libraries were prepared using RNA extracted from counted populations of T cells (1,000 – 100,000). The detected clone frequency is linear and in agreement with known T cell input. Importantly, there is not evidence of a large false positive rate for clone detection.

To test the reproducibility of the assay between library replicates, we constructed 16 libraries from the peripheral blood leukocyte sample. Correlations between variable gene usage and Top 50 clone detection frequency yield minimum correlation values of r=0.97 for variable gene usage and r=0.96 for Top 50 clone detection frequency.

Tumor biopsy revealed 589 unique TCR. • Oligoclonal repertoire with a small

number of dominating clones; • Shannon diversity: 6.78

PBL revealed 45305 unique TCR.• Diverse, polyclonal repertoire with few

highly expanded T cells • Shannon diversity: 13.95

RESULTSThe Ion AmpliSeq Immune Repertoire Assay Plus TCRβ kit was applied to study the overlap between between circulating and tumor-infiltrating T cells. 100ng of total RNA derived from PBL and tumor biopsy from an individual with Stage 1B squamous cell carcinoma of lung was used as template.

Sample Types:• Blood • Fresh Frozen Tissue • Sorted T cells

Sequencing of matched TIL and peripheral blood exhibited differing repertoire features between samples. The tumor biopsy showed an oligoclonal repertoire with a small number of dominating clones and a Shannon diversity value of 6.78. The peripheral blood samples exhibited a diverse, polyclonal repertoire with few highly expanded T cells and a Shannon diversity value of 13.95. By correlating the repertoires, we observe 219 clones that are shared between samples. There are 370 clones that are unique to the tumor sample, with a subset of these clones which are highly expanded. This highly expanded set of clones unique to the tumor could potentially point to T cells responding to tumor-specific antigen.

To further study the ability of immune repertoire sequencing to probe the tumor microenvironment (TME), we sought to correlate repertoire features with gene expression profiles derived from the OncomineTM Immune Response Research Assay (OIRRA). In a repressive TME the T cell repertoire may exhibit high evenness (with few expanded clones) due to inhibition of T cell response. In a permissive TME the repertoire may exhibit low evenness (with T cell expansion) due to T cell response to the tumor. We sought to correlate these metrics with several immune response gene expression categories.

Clone overlap for PBL and Tumor

Log10 frequency in PBL

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45086 clones unique to PBL

219 shared clones

370 clones unique to tumor

Figure 6. Correlation of T cell evenness and gene expression profile (A) Schematic illustrating T cell response in repressive/permissive tumor microenvironments. (B-C) Libraries were prepared from 19 NSCLC biopsies using the Ion AmpliSeqTM Immune Repertoire Assay Plus – TCRβ and the OncomineTM Immune Response Research Assay (OIRRA). The majority of this cohort exhibited high T cell evenness – suggesting repressive tumor microenvironments. Using a largest principle component analysis of each gene category within the OIRRA panel, we see correlation between evenness values and markers for myeloid response.

(A)

(B)Proliferation

Drug_target

Checkpoint_pathway

NK_cell_marker

T_cell_differentiation

Housekeeping

Leukocyte_inhibition

Antigen_processing

Macrophage

Type_I_interferon_signaling

Neutrophil

Lymphocyte_infiltrate

NK_activation

Dendridic_cell

Interferon_signaling

Tumor_marker,stemness

Antigen_presentation

Cytokine_signaling

Lymphocyte_development

T_cell_regulation

Chemokine_signaling

Tumor_antigen

Type_II_interferon_signaling

TCR_coexpression

Helper_T_cells

Tumor_marker

PD-1_signaling,tumor_marker

Myeloid_marker,MDSC

Leukocyte_migration

Lymphocyte_activation

Adhesion,migration

Dendridic_cell,macrophage

Apoptosis

Myeloid_marker

PD-1_signaling

T_cell_receptor_signaling

T_cell_regulation,trafficking

B_cell_marker

Innate_immune_response

B_cell_receptor_signaling

Myeloid_marker,stem_cell

Gene function correlation with clone evenness

Correlation

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Correlation with Oncomine™ Immune Response Research Assay

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(C)

Figure 7. T cell evenness measurement during therapeutic T cell manufacturing process. T cell clone evenness is tracked for two separate donors from Day 0 (PBMC pre- & post-isolation), Day 3 (pre- and post-bead removal), and after Day 10 in culture. Importantly, T cell evenness increases over time, showing that there is no bias for expansion in particular T cell populations in culture using CTSTM DynabeadsTM anti-CD3/CD28 beads and CTSTM OpTimizerTM serum-free media.

PBMC-derived T cells were subjected to in vitro expansion via CTSTM DynabeadsTM anti-CD3/CD28 beads and CTSTM

OpTimizerTM serum-free media as part of a therapeutic T cell research study. T cell expansion was measured using T cell clone evenness output by Ion ReporterTM analysis of data generated by the Ion AmpliSeq Immune Repertoire Assay Plus – TCRβ panel. There is a consistent increase in evenness with cell culture time, suggesting that anti-CD3/CD28 beads and CTS™ OpTmizer™ media promote polyclonal (unbiased) T cell expansion.

Table 2. Steps in the manufacture of therapeutic T cells. Explanation of the role of T cell repertoire sequencing in the steps involved in carrying T cells from isolation, through expansion, transduction, and introduction

Figure 5. Overlap of clones identified in matched TIL and PBL samples Plot showing clones identified and unique to peripheral blood (45,086 - along x-axis), unique to TIL (370 - along y-axis), and found in both samples (219 - middle of plot).

Figure 4. Correlation of variable gene usage and Top 50 clone frequency across 16 libraries. Plot showing correlation between 16 replicate libraries for (A) variable gene usage and (B) Top 50 clone detection frequency.