supplementary materials for · 2015. 12. 23. · supplementary materials and methods absolute...

Supplementary Materials for

Tracking genetically engineered lymphocytes long-term reveals the

dynamics of T cell immunological memory

Giacomo Oliveira, Eliana Ruggiero, Maria Teresa Lupo Stanghellini, Nicoletta Cieri,

Mattia D’Agostino, Raffaele Fronza, Christina Lulay, Francesca Dionisio,

Sara Mastaglio, Raffaella Greco, Jacopo Peccatori, Alessandro Aiuti,

Alessandro Ambrosi, Luca Biasco, Attilio Bondanza, Antonio Lambiase,

Catia Traversari, Luca Vago, Christof von Kalle, Manfred Schmidt, Claudio Bordignon,

Fabio Ciceri, Chiara Bonini*

*Corresponding author. E-mail: [email protected]

Published 9 December 2015, Sci. Transl. Med. 7, 317ra198 (2015)

DOI: 10.1126/scitranslmed.aac8265

The PDF file includes:

Materials and Methods

Fig. S1. CD4-CD8 distribution among long-term persisting TK+ cells.

Fig. S2. CD95 expression on TK+ cells.

Fig. S3. Purification of TK+ cells from T cell subsets.

Fig. S4. Functionality of TK suicide gene in long-term persisting gene-modified T

cells.

Fig. S5. TCR gene usage among gene-modified T cells.

Fig. S6. TK+ cell kinetics and persistence after GCV treatment.

Fig. S7. Long-term persistence of TK+ cells correlates with early in vivo

expansion.

Fig. S8. Phenotype of infused TK+ cells in relation to their in vivo expansion.

Fig. S9. Phenotype of infused cells in relation to long-term persistence.

Fig. S10. Phenotype of infused cells in relation to TK+ cell AUC.

Fig. S11. Tracking CMV-specific T cells by dextramers in TK patients.

Fig. S12. Tracking Flu-specific T cells by dextramers in TK patients.

Fig. S13. Clonal distribution of TK+ cell clones after ex vivo manipulation and

purification.

Fig. S14. Memory phenotype of TK+ cell clones after ex vivo manipulation and

purification.

www.sciencetranslationalmedicine.org/cgi/content/full/7/317/317ra198/DC1

Fig. S15. Gene mapping of retroviral IS retrieved in long-term persisting

dominant TK+ cell clones.

Fig. S16. Analysis of the distribution of TK+ cell clones among memory T cell

subsets.

Fig. S17. Differential gene marking of clones after transduction.

Table S1. Characteristics of TK patients.

Table S2. Immunological parameters of TK patients.

Table S3. Variables affecting long-term immune reconstitution after

haploidentical HSCT.

Table S4. Quantification and isolation of long-term persisting TK+ cells.

Table S5. Proliferation of TK+ and TK− cells in TK patients.

Table S6. CD4-CD8 distribution among TK+ and TK− cells.

Table S7. Phenotypic characterization of TK+ and TK− cells circulating in TK

patients.

Table S8. Number of unique sequences of TK+ cells.

Supplementary Materials and Methods

Absolute counts

Absolute quantification of NK cells (CD56+), B cells (CD19+), γδ T cells (TCRγδ+), αβ

helper T cells (TCRαβ+ CD3+ CD4+) and αβ cytotoxic T cells (TCRαβ+ CD3+ CD8+) were

determined using Flow-Count technology (Beckman Coulter). Anti-human TCRγδ-APC, CD19-

PE-Cy7, CD56-Pacific Blue, CD8-PerCP-Cy5.5, CD3-Brilliant Violet 510, (Biolegend), CD4-

PE-Texas-Red (Invitrogen) and TCRαβ-FITC (BD Biosciences) antibodies were added to 50 µl

of EDTA-treated whole blood, previously diluted in a 1:3 ratio with in-house produced Fc-block

(2.4G2 hybridoma, ATCC), and incubated for 15 minutes at RT. Subsequently, red blood cells

were lysed with ACK (Ammonium-Chloride-Potassium) lysis buffer for 10 minutes at RT. After

centrifugation to remove cell debris, 25 µl of Flow-Count Fluorospheres (Beckman Coulter)

were added. Samples were immediately acquired using a Navios cytometer (Beckman Coulter)

and analyzed with Kaluza software (Beckman Coulter). Absolute quantification of subsets

amongst TK+ cells and T-cell subsets was obtained by multiplying CD3+, CD4+, CD8+ cell

counts with the frequencies of TK+ cells or T-cell subpopulation detected from multiparametic

flow cytometry analysis.

Gating strategy for flow-cytometric analyses

For all the flow-cytometry analyses, we applied the gating strategy reported hereafter

(PBMCs from UPN#10 at long-term follow-up is used as example). TK+ cells were identified as

CD3+ lymphocytes expressing LNGFR surface marker (plot 3). LNGFR Fluorescence minus

one (FMO) staining was use to set TK+-cell gate (plot 3’). The analysis of TK+-cell

differentiation phenotype was performed only if the sample contained a reliable population of

gene-modified T cells (TK+ cells / total lymphocytes > 0.01%). Specifically, to define the T-cell

subset distribution using CD45RA and CD62L, quadrants were set on CD4+ or CD8+ TK-

lymphocytes (plots 4, 5 and 6) and then applied to TK+ cells (plots 7, 8 and 9) or to total CD4+ or

CD8+ T-cell populations. To determine CD95 positivity within the CD45RA+ CD62L+

population, CD95 gate was set based on FMO negative controls (histograms, grey curve) on TEM

lymphocytes (that represent internal positive controls, being all CD95+). The gate was then

applied to the CD45RA+ CD62L+ TK+ or TK- populations to discriminate between TN and TSCM.

Moreover the same gate was applied to total TK+ cells to verify their complete memory

phenotype. This gating strategy was applied to all time-points and on samples of the batches

infused for each patient. In selected experiments, the same gating strategy was applied to

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1. Singlets 2. Lymphocytes 3. TK+ / TK- 3’. LNGFR FMO

4.TK- CD4/CD8

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antigen-specific T cells.

Antigen-specific cells were detected within patients or donors’ lymphocytes trough

dextramers statining. PBMCs from UPN#9 at long-term follow-up is shown as example. Virus-

specific cells were identified on TK+ or TK- T cells and expressed as fraction of total TK+ or TK-

cells. When necessary, dextramers carrying the same restriction element but loaded with an

irrelevant peptide were used to set the gate and distinguish rare antigen-specific cells from

background. Samples with antigen-specific populations below 0.01% dextramer-positive cells in

total TK+ or TK- T cells were considered negative.

Proliferating cells were identified trough Ki-67 intracellular staining. CD4+ or CD8+ T

lymphocytes were identified as previously described and divided into Naïve (CD95-) or Memory

cells (CD95-) according to CD95 expression. Ki-67 positivity was assessed based on FMO

controls. CD8+ lymphocytes PBMCs from a healthy control are shown as representative plots.

The same analysis was performed gated on TK+ cells and on Naïve or Memory TK- cells.

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Ganciclovir sensitivity

Ganciclovir sensitivity of pure TK+ cells isolated from T-cell subsets at long-term follow-up

was tested to assess expression and function of the suicide gene. After purification, TK+ cells

were polyclonally activated with PHA (1mg/mL, Sigma Aldrich), IL-2 (600 UI/mL) and

irradiated LCL EBV cell lines (0.4x106 cells/mL). At day 2, medium was washed, 0.2x106 cells

were plated in 96 well plates and GCV (Recordati) was added at scalar concentrations (500, 100,

10, 1, 0.1, 0.01, 0 μM). After 4 days of culture (day 6), cells were labeled with CD3 and LNGFR

antibodies and remaining TK+ cells were FACS counted using Flow-Count Fluorospheres

(Beckman Coulter). Inhibition was calculated normalizing the number of cells detected in each

condition on the number of cells detected in the absence of GCV. TK- cells isolated from each

specific subset were tested in parallel. Ex vivo gene-modified TK+ cells or mock transduced TK-

cells generated from PBMCs of 3 healthy subjects were used as positive and negative controls

respectively.

IFN-γ release assay

Cytomegalovirus (CMV) specific-T-cells were quantified in selected CMV-seropositive

patients and healthy donors by interferon-γ (IFN-γ) Enzyme-Linked Immunosorbent Spot

(ELISpot) assay, as previously described (14). Briefly, IFN-γ spots released by 105 PBMCs were

quantified upon 24-hour incubation with a polyclonal (PHA, 2mg/mL, Sigma Aldrich), or

antigen-specific (CMV antigens extracted from infected fibroblasts) stimulus. Incubations with

autologous irradiated (30Gy) PBMCs or in the absence of stimuli (mock) were set as negative

controls. IFN-γ spots were counted using a KS-ELISpot Reader (Zeiss), and specific release was

calculated as the number of spots observed in the presence of a stimulus, minus those observed

in the mock condition. Results were then normalized on the number of plated CD3+ lymphocytes

and finally on the number of circulating CD3+ cells (detected by FACS) to ultimately calculate

the number of IFN-γ spots produced per μL of peripheral blood.

qPCR for sjTREC and VCN quantification

Real-time qPCR for single joint T-cell Receptor Excision Circles (sjTRECs) was performed

as previously described (16), using glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as a

control to standardize DNA content. Briefly, amplification reactions were performed in a final

volume of 25 μl containing 50 ng of genomic DNA isolated from PBMCs, TaqMan universal

PCR master mix (Perkin Elmer Applied Biosystem), and the appropriate primers and probes. The

amount of sjTREC per 100 ng of DNA was determined on the basis of a standard curve

developed in-house by cloning the sequence of α1 circles from human cord blood genomic DNA

into a plasmid vector, and diluting the plasmid into human DNA from a cell line devoid of

TRECs (K562), with a lower limit of detection of 3 copies/100 ng of genomic DNA.

Quantification of transduced cells by real time PCR was performed on 50 ng of genomic

DNA, directly isolated from PBMCs, using primers and probes specific for LTR vector sequence

as previously described (11). Telomerase reference gene was amplified using the following

primers and probes: primer forward 5’-GGCACACGTGGCTTTTCG-3’; primer reverse

5’ GGTGAACCTCGTAAGTTTATGCAA-3’; probe (VIC) 5'-

TCAGGACGTCGAGTGGACACGGTG-3' (TAMRA). Vector Copy Number, expressed as the

frequency of cells containing the specific vector sequence, was calculated on the basis of a

standard curve of integrants diluted in untransduced cells.

Analysis of clonal distribution amongst TK+ cells

TK+-cell clones were identified by unique IS or unique CDR3α and CDR3β nucleotide

sequences detected within each sample of sorted memory TK+-cell subsets. As mentioned,

clonotypes with read count equal to 1 were discarded. The frequency of a clone within a sample

was calculated by dividing clone-specific reads with the total number of reads higher than 1

detected within each sample of memory T-cell subset. The final frequency of each clonotype

amongst total TK+-cell population was reconstructed by weighing intra-subset clonal frequency

with the proportion of TK+ cells detected (and FACS sorted) within each memory subset. The

distribution of unique clones amongst T-cell subpopulations was then analyzed in order to

identify sequences shared between 2 or 3 memory subsets and subset-specific clonotypes. Clonal

distribution within memory subsets was assessed by dividing the number of clones of a given

subpopulation (shared amongst 3 subsets, shared amongst 2 subsets, TSCM-specific, TCM-specific

or TEM/EFF-specific) with the total number of clones detected within a time-point. Clonal

distribution was then combined with clonal frequency to assess the actual portion of total TK+-

cell population occupied by clones belonging to a given subpopulation.

Finally identical IS, CDR3α or CDR3β sequences were tracked longitudinally in sample of

TK+ cells before infusion and at long-term time-points in order to assess the origin of long-term

persisting clones. In case of identical CDR3α or CDR3β sequences, the exact correspondence of

V, (D) and J gene usage was verified.

Supplementary Figures

Fig. S1

Fig. S1. CD4-CD8 distribution among long-term persisting TK+ cells. Frequencies of CD4+

(light blue) and CD8+ (dark blue) lymphocytes amongst TK+ cells infused (TK-DLI, n=10), TK+

(n=8) and TK- (n=10) cells detected long-term after infusion at 1st long-term follow-up, and

CD3+ cells detected in aged and sex-matched healthy controls (HC, n=30). Consistently with the

CD4-CD8 distribution of cells in infused batches, long-term circulating TK+ cells were mainly

CD8+ T lymphocytes, while newly generated TK- cells display a physiological CD4-CD8 ratio.

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CD62L+ CD45RA+TK- cells

CD62L- CD45RA-TK- cells

TK+ cells97.7%

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CD62L+ CD45RA+ CD3+ sorted T cells

CD62L- CD45RA+ CD3+ sorted T cells

CD62L- CD3+ sorted T cells

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Fig. S3

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Fig. S2

Fig. S2. CD95 expression on TK+ cells. (A) Flow cytometry plots depicting CD95 expression

on CD4+ (left panel) and CD8+ (right panel) TK+ cells (blue curves) persisting long-term in a

representative patient (UPN#8). CD95 expression on CD62L+ CD45RA+ (TN enriched

lymphocytes, light grey curves, negative control) and CD62L- CD45RA- (TEM, dark grey curves,

positive control) on TK- cells is shown. (B) CD95 frequency measured on CD4+ and CD8+

ΔNGFR+ TK+ cells in samples from infused batches (TK-DLI, n=10) and at long-term follow-up

(n=10). The homogeneous expression of the CD95 marker amongst TK+ cells demonstrates the

memory phenotype.

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CD62L- CD3+ sorted T cells

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Fig. S3

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Fig. S1

TK-DLI TK+ TK- HC0

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Fig. S3

Fig. S3. Purification of TK+ cells from T cell subsets. Flow cytometry plots showing isolation

of ΔLNGFR+ TK+ cells starting from CD3+ CD62L+ CD45RA+ (red plots), CD3+ CD62L+

CD45RA- (orange plots) and CD3+ CD62L- (blue plot) T cells sorted from PBMCs of a

representative patient (UPN#4). The expression of ΔLNGFR marker on CD3+ lymphocytes is

analyzed after a round of polyclonal stimulation (S1, light colored curves), after subsequent

ΔNGFR selection (S1+ ΔLNGFR selection, intermediate colored curves) or after 2 rounds of

stimulation ad selection (S2 + ΔLNGFR selection, dark colored curves). The percentages of

ΔLNGFR+ cells are shown. The isolation of pure TK+ cells from all sorted T-cell subsets further

demonstrate the presence of functional gene-modified cells amongst all the memory

subpopulations.

Fig. S4

Fig. S4. Functionality of TK suicide gene in long-term persisting gene-modified T cells.

GCV sensitivity of TK+ (diamonds, solid lines) or TK- (circles, dashed lines) T-cell subsets

isolated from patients (n=7). TK+ (diamonds) and TK- (circles) cells transduced with the TK-

encoding vector in vitro (black symbols, n=3) are used as controls.

Fig. S5

Fig. S5. TCR gene usage among gene-modified T cells. Heatmap depicting the usage of TCR-

genes amongst persisting TK+ memory T cell subsets. TK+ cells in samples from infused batches

(TK-DLI) and long-term persisting TK+ cells (TK-LT) from two representative patients

(A:UPN#9, 2.8 years after TK-DLI; B: A:UPN#5, 7.2 years after TK-DLI) are shown. After

sorting and ΔLNGFR purification, TCRα/β-chains were sequenced to determine the usage of

variable (V) and joining (J) TCR genes within each subset. The number of retrieved clonetypes,

identified by unique CDR3 nucleotide sequence, is shown in the right corner table. Despite the

presence of preferentially used V and J genes, long-term samples displayed a wide usage of

TCR-alpha and beta V and J families, thus demonstrating the polyclonality of the repertoire of

gene-modified cells persisting long-term after infusion.

Fig. S6

Fig. S6. TK+ cell kinetics and persistence after GCV treatment. Absolute quantification of

TK+ cells circulating in GCV-treated patients (n=3). Each colored line points the course of gene-

modified TK+ cells in a single patient after the infusion (colored arrows: TK-DLIs). Bar-headed

symbols point GCV administration.

Fig. S7

Fig. S7. Long-term persistence of TK+ cells correlates with early in vivo expansion. Positive

correlation between the area under the curve (total TK-AUC, x-axis) described by absolute

counts of TK+ cells circulating in GCV-untreated patients (n=7) and at the peak of TK+ cells

detected after infusion (y-axis). The black line denotes the best fit-line of the linear regression

analysis (p < 0.0001, R2 = 0.9687).

Fig. S8

Fig. S8. Phenotype of infused TK+ cells in relation to their in vivo expansion. Correlation

between the peak of TK+ cells per μL of blood measured after infusion of gene-modified T

lymphocytes (x-axis) and the amount of TK+-cell subsets per Kilogram (y-axis) infused in GCV-

untreated patients (n=7). Best fit-line of the log-log regression is shown in each graph. Notably,

this association is specific for TSCM (red line, R2 = 0.9521) as no correlation is found with infused

TK+ TCM (orange line, R2 = 0.1372), TEM (light blue line, R2 = 0.0604) or TEMRA (dark blue line,

R2 = 0.6114).

Fig. S9

Fig. S9. Phenotype of infused cells in relation to long-term persistence. Correlation between

the number of TK+ cells circulating at second long-term follow-up (x-axis) and the amount of

TK+-cell subsets per Kilogram (y-axis) infused (n=7). Best fit-line of the non-linear regression in

shown in each graph. Notably, this association is specific for TSCM (red line, R2 = 0.9593) as no

correlation was found with infused TK+ TCM (orange line, R2 = 0.2275), TEM (light blue line, R2

= 0.0187) or TEMRA (dark blue line, R2 = 0.0019).

Fig. S10

Fig. S10. Phenotype of infused cells in relation to TK+ cell AUC. Correlation between total

Area Under the Curve (AUC, x-axis) described by TK+ cell counts measured in the peripheral

blood of patients after infusion and the amount of TK+ cell subsets per Kilogram (y-axis) infused

in GCV-untreated patients (n=7). Best fit-line of the linear regression is shown in each graph.

Notably, this association is specific for TSCM (red line, p = 0.0006, r2 = 0.9217) as no correlation

is found with infused TK+ TCM (orange line, p = 0.5302, r2 = 0.0833), TEM (light blue line, p =

0.4097, r2 = 0.1392) or TEMRA (dark blue line, p = 0.9066, r2 = 0.0030).

Fig. S11

Fig. S11. Tracking CMV-specific T cells by dextramers in TK patients. Cytometric

quantification of pp65, UL44 and IE1 CMV-specific CD8+ T cells amongst TK+ cells in samples

of infused batches (left column, TK-DLI), and in TK+ (middle column) and TK- (right column)

lymphocytes detected within the same samples at long-term follow-up. Blue rectangular gates

identify CMV-specific T-cell population. Each line represent a different patient positive for

donor HLA-A*0201 (UPN#3, UPN #5, UPN#9, UPN#10) or donor HLA-A*0101 and HLA-

B*0801 (UPN#4). Donor/host positivity for the relevant restriction element and CMV

serological status are shown on the left. In two out of 5 patients CMV specific TK+ cells could be

tracked before and after infusion (frequency > 0.01%).

Fig. S12. Tracking Flu-specific T cells by dextramers in TK patients. Cytometric

quantification of M1 or NP Flu-specific CD8+ T cells amongst TK+ cells in samples of infused

batches (left column, TK-DLI), and in TK+ (middle column) and TK- (right column)

lymphocytes detected within the same samples at long-term follow-up. Blue rectangular gates

identify M1-Flu specific T-cells. Each line represent a different patient positive for donor HLA-

A*0201 (UPN#3, UPN #5, UPN#9, UPN#10) or donor HLA-A*0101 (UPN#4). Donor/host

positivity for the relevant restriction element is shown on the left. In UPN#10 M1-Flu specific

TK+ cells could be tracked after infusion (frequency > 0.01%).

Fig. S12

Fig. S13

Fig. S13. Clonal distribution of TK+ cell clones after ex vivo manipulation and purification.

(A) Venn diagram showing the number of unique IS identified by LAM-PCR and sequencing of

ex vivo manipulated and purified TK+ cells or unmanipulated cells harvested from UPN#9 at 2.8

years after infusion of TK+ cells. The table summarizes the percentage of overlapping clones

among the 2 samples and the proportion occupied by these clones within TK+ cells in each

sample. (B) Correlation between clonal frequencies measured within manipulated (Y axys) and

unmanipulated (X axys) samples harvested from UPN#9. The red line depicts the best fit-line of

the linear regression analysis (p < 0.0001, r2 = 0.3595). The highly significant correlation

suggests that frequency of the majority of clones detected in both samples is conserved.

Fig. S14

Fig. S14. Memory phenotype of TK+ cell clones after ex vivo manipulation and

purification. Comparison between manipulated and unmanipulated samples retrieved from 2

representative TK-patients (UPN#9 and UPN#5). Bar plots show the percentage of clones

belonging to different T-cell subsets (black: clones shared amongst all memory subsets; grey:

clones shared amongst 2 memory subsets; red: TSCM-specific clones; orange: TCM-specific

clones; blue: TEM/EFF-specific clones). No relevant differences between the two samples are

observed.

Fig. S15

Fig. S15. Gene mapping of retroviral IS retrieved in long-term persisting dominant TK+

cell clones. The word cloud shows genes closest to retroviral IS sequenced in highly represented

TK+-cell clones (frequency > 1%) circulating in 3 analyzed patients (UPN#3, UPN#5, UPN#9).

The size of each gene is proportional to the frequency of IS measured amongst all TK+-

clonotypes detected in a patient. None of the integrations retrieved in dominant clones occurred

in oncogenes, thus confirming that clonal over-representation was not associated with cell

transformation induced by insertional genotoxicity of the retroviral vector.

Fig. S16

Fig. S16. Analysis of the distribution of TK+ cell clones among memory T cell subsets. The

bar plots report the frequencies of clones shared between 2 (grey) or 3 (black) memory TK+ cell

subsets, or unique to each T cell subsets (TSCM in red, TCM in orange and TEM/EFF in blue, see also

venn-diagram legend). Y-axis reports the percentage of subset-specific TK+-cell clones amongst

total gene-modified cells analyzed by IS (top panel), CDR3α (middle panel) and CDR3β (bottom

panel) sequencing. Samples from infused batches (TK-DLI, left bars) and at long-term time-

points (right bars) are shown. The bar-headed line points a GCV-treated patient (UPN#3). These

data shows that long-term TK+ cell samples are characterized by an increase in the percentage of

shared clones. Of note, the lowest level of sharing at long-term follow-up is observed in the

patient treated with GCV.

Fig. S17

Fig. S17. Differential gene marking of clones after transduction. Frequency of clones

detected with IS (top panel), CDR3α (middle panel) and CDR3β (bottom panel) sequencing

within the TK+-cell batches infused in UPN#5. Light blue area highlights the most frequent

clones in the sample (frequency > 0.01%). Each dot represents a single clone shared between 2

(grey) or 3 (black) memory subsets, or unique to each T-cell subset (TSCM in red, TCM in orange

and TEM/EFF in blue, see also venn-diagram legend). Of note, highly represented clones are

predominantly unique to each T-cell subset, when analysed by IS sequencing, while they are

shared among 2 or 3 memory T-cell subsets, when studied by CDR3α and β sequencing. These

results suggest that clones with the same TCRs - but belonging to distinct memory T-cell subsets

- have been differentially labeled by retroviral integration after the transduction procedure.

Table S1. Characteristics of TK patients.

†AML = acute myeloid leukaemia; ALL = acute lymphoblastic leukaemia; sAML = secondary AML;

MDS = myelodysplasia.

GCV = ganciclovir;

CR = complete remission

Patient Sex / Age Diagnosis† Total TK+ cells

x106/Kg

(number of

infusions)

GvHD

(grade)

Days

from last

TK-DLI to

GvHD

GvHD

outcome

(days after 1st

dose of GCV)

Years from last

TK-DLI

(1st – 2nd long-

term follow-up)

Status at

last follow-

up

UPN#1 M / 45 AML M5 10 (1) - - - 12 – 14 Alive and

well

UPN#2 M / 67 AML M1 1 (1) - - - 9.4 – 10.9 Alive and

well

UPN#3 F / 35 ALL L2 10 (1) Acute (II) 19 CR (21) 9.4 – 10.6 Alive and

well

UPN#4 M / 27 ALL T 20 (2) - - - 9.1 – 10.1 Alive and

well

UPN#5 F / 65 sAML 20 (2) - - - 7.2 – 8.3 Alive and

well

UPN#6 M / 32 MDS 19.15 (2) - - - 6.5 – 7.4 Alive and

well

UPN#7 F / 53 AML M4 12,5 (2) Acute (II) 54 CR (10) 6.4 – 7.1 Alive and

well

UPN#8 M / 24 AML M4 38,6 (3) - - - 3.5 – 3.8 Alive and

well

UPN#9 M / 57 AML M4 39,5 (3) - - - 2.8 – 3.5 Alive and

well

UPN#10 F / 52 AML M1 21,6 (2) Acute (II) 20 CR (13) 1.9 – 2.2 Alive and

well

Table S2. Immunological parameters of TK patients.

Patient CD4+ T cells (cells / μL) CD8+ T cells (cells / μL)

TN TSCM TCM TEM TEMRA TN TSCM TCM TEM TEMRA

UPN#1 138.77 17.18 340.78 212.99 12.27 88.94 111.84 88.55 157.92 116.75

UPN#2 90.15 38.96 467.57 153.56 13.75 118.73 194.51 157.41 150.29 170.07

UPN#3 43.76 3.37 108.53 47.33 1.02 121.45 13.95 37.98 35.37 8.25

UPN#4 679.06 38.5 208.99 85.86 17.09 480 77.51 21.69 37.1 74.54

UPN#5 221.61 12.01 162.76 153.35 3.88 76.51 14.27 82.83 242.4 51.94

UPN#6 317.59 178.66 36.34 25.71 59.7 314.56 79.12 6.68 10.81 131.84

UPN#7 149.59 11.48 280.84 370.87 13.22 84.95 11.57 43.76 186.1 82.62

UPN#8 347.35 31.04 345.63 93.37 1.64 179.04 76.38 85.42 41.89 27.92

UPN#9 35.77 2.31 263.36 118.8 16.51 119.33 8.05 281.27 239.48 370.95

UPN#10 260.37 35.46 438.06 190.58 23.7 152.58 25.67 30.7 22.16 26.85

Median 185.6 24.11 272.1 136.08 13.49 120.39 51.025 63.295 96.09 78.58

Mean 228.4 36.9 265.29 145.24 16.28 173.61 61.29 83.63 112.35 106.17

SEM 60.63 16.37 43.95 31.35 5.348 40.46 18.9 25.98 29.26 33.58

Patient cells / μL

NK cells B cells γδT cells CD4+ αβT cells CD8+ αβT cells

UPN#1 742 372 95.59 722 564

UPN#2 812 582 130.375 764 791

UPN#3 126 245 104.73 204 217

UPN#4 446.46 379.11 26.76 1029.51 690.85

UPN#5 439.09 306.16 181.71 553.62 467.96

UPN#6 77 187 78.21 618 543

UPN#7 344 394 132.1 826 409

UPN#8 149.12 370 69.98 819.03 410.65

UPN#9 215.83 336.07 28.26 436.75 1019.08

UPN#10 266.96 896.51 25.84 948.18 257.96

Median 305.48 371 86.9 743 505.48

Mean 361.85 406.79 131.12 692.11 537.05

SEM 79.79 63.56 16.49 78.01 77.37

Patient sjTRECs / IFNγ producing spots / μL

100 ng of DNA

Mock Auto CMV Ag PHA

UPN#1 7.14 0 0.80 0.039 14.03

UPN#2 10.65 0 0.96 6.40 31.83

UPN#3 20.65 n.a. n.a. n.a. n.a.

UPN#4 118.69 n.a. n.a. n.a. n.a.

UPN#5 18.13 n.a. n.a. n.a. n.a.

UPN#6 23.69 n.a n.a n.a n.a

UPN#7 35.62 0 0.12 4.48 28.57

UPN#8 44.15 0 0 0.46 21.36

UPN#9 8.53 0 0.96 24.02 27.69

UPN#10 6.3 n.a n.a n.a n.a

Median 19.39 0 0.80 4.48 27.69

Mean 29.36 0 0.57 7.08 24.7

SEM 10.69 0 0.21 4.40 3.16

n.e. : not evaluable; n.a. : not assessed.

Mock: response measured in the absence of stimuli; Auto: response measured against autologous

irradiated PBMCs; CMV Ag: response measured in the presence of CMV antigen; PHA:

response measured in the presence of Phytohemagglutinin.

Table S3. Variables affecting long-term immune reconstitution after haploidentical HSCT.

Conditioning: TBI Rituximab

Cell population TBI untreated

(n=11)

TBI treated

(n=21) p

Rituximab

untreated (n=4)

Rituximab treated

(n=28) p

NK cells 470.1± 336.4 244.5 ±169.1 0.0463 531.6 ± 313.4 372.7 ± 306.4 0.3405

B cells 568.7 ± 322.4 493.6 ± 305 0.5288 394.5 ± 13.3 564.1 ± 327.2 0.3199

γδT cells 163.1 ± 167.3 113 ± 79,81 0.3582 89.36 ± 44.26 154 ± 151.7 0.4097

CD4 αβT cells 694.1 ± 630.1 630.1 ± 202 0.6079 679.9 ± 345.2 671± 331.6 0.9604

CD8 αβT cells 997.4 ± 707.5 639.7 ± 321.6 0,1189 565.7 ± 250.3 939.7 ± 639.2 0.2616

CD8+ Subsets:

CD8 TN 106.8 ± 112.8 145.3 ± 97.76 0.3461 202.3 ± 185.7 107.8 ± 91.53 0.1021

CD8 TSCM 154.1 ± 171.8 77.9 ± 76,85 0.1746 99.45 ± 75.24 131.9 ± 157.6 0.6909

CD8 TCM 144.1 ± 94.5 88.98 ± 78.53 0.1083 76.41 ± 61.05 132.1 ± 94.31 0,2638

CD8 TEM 311.7 ± 249.9 175 ± 169.3 0.1151 95.17 ± 68.13 288.9 ± 237,7 0.1201

CD8 TEMRA 280.7 ± 304 207.8 ± 234.2 0.4937 92.4 ± 68.38 279 ± 291.8 0.2184

GvHD: aGvHD cGvHD

Cell population aGvHD 0-I

(n=10)

aGvHD II-IV

(n=22) p

no CGVHD

(n=21)

CGvHD

(n=11) p

NK cells 441.2± 332.7 268.1 ±189.6 0.1544 365.6 ± 237.6 443.9 ± 417.6 0.5819

B cells 517.3 ± 265.5 643.2 ± 410,5 0.3168 531.8 ± 345.6 563.9 ± 255.8 0.7887

γδT cells 156.8 ± 166.9 121.9 ± 73.29 0.5342 107.6 ± 84.01 219 ± 202.7 0.0353

CD4 αβT cells 647.6 ± 303 726 ± 388.3 0.5389 700.6 ± 304.3 617.7 ± 309.9 0.5056

CD8 αβT cells 990.6 ± 679.7 678.3 ± 385.5 0.1872 702.9 ± 447.6 1256 ± 741.4 0.0131

CD8+ Subsets:

CD8 TN 130.5 ± 126.7 95.7 ± 41.69 0.4073 137.5 ± 112.6 85.45 ± 93.61 0.1997

CD8 TSCM 160.3 ± 169.2 56.61 ± 42,63 0.0678 96.98 ± 127.1 186.9 ± 176.1 0.1068

CD8 TCM 128.9 ± 97.55 116.9 ± 82.58 0.7390 97.89 ± 82.35 177.2 ± 90.08 0.0178

CD8 TEM 258.3 ± 240.7 278.8 ± 223.7 0.8212 180.9 ± 165.2 424.6 ± 263.8 0.0031

CD8 TEMRA 312.7 ± 315.4 130.3 ± 114.2 0.0879 189.7 ± 247.5 381.7 ± 307.2 0,0646

Mean ± standard deviation of cell counts are shown within each group of patients. For all the

studied parameters, p value was calculated using an unpaired two-tale t-student test. Significant p

values are highlighted in red (p < 0.05), while bold case marks trends (p < 0.1).

Table S4. Quantification and isolation of long-term persisting TK+ cells.

Patient Years from last TK-DLI TK+ cells / μL

VCN Isolation of

(1st-2nd long-term follow-up) (1st-2nd long-term follow-up) TK+ cells

UPN#1 12 – 14 4 - 7.73 0.006 yes

UPN#2 9.4 – 10.9 0.08 - 0.03 0.000055 yes

UPN#3 9.4 – 10.6 2.61 - 0.51 0.002 yes

UPN#4 9.1 – 10.1 6.51 - 7.15 0.001 yes

UPN#5 7.2 – 8.3 55.32 - 24.68 0.067 yes

UPN#6 6.5 – 7.4 0.2 - 0.32 n.e. yes

UPN#7 6.4 – 7.1 0.72 - 0.9 0.000248 yes

UPN#8 3.5 – 3.8 6.04 - 6.24 0.003 yes

UPN#9 2.8 – 3.5 658.25 - 584.1 0.692 yes

UPN#10 1.9 – 2.2 5.84 - 5.29 0.006 yes

Median 4.92 - 5.77 0.003

n.e.: not evaluable

VCN: vector copy number measured at 1st long-term follow-up.

Isolation of TK+ cells was performed at either first or second long-term follow-up.

Table S5. Proliferation of TK+ and TK- cells in TK patients.

Patient % of KI-67+ cells / CD4+ T cells % of KI-67+ cells / CD8+ T cells

Naïve TK- cells Memory TK- cells TK+ cells Naïve TK- cells Memory TK- cells TK+ cells

UPN#1 0.13 1.36 n.e. 0.09 0.474 n.e.

UPN#2 n.e. n.e. n.e. n.e. n.e. n.e.

UPN#3 0.13 3.52 4.35 0.11 1.66 3.7

UPN#4 0.07 3.06 12.6 0.06 1.27 1.92

UPN#5 0.10 3.3 0 0.10 1.12 0.61

UPN#6 0.07 2.92 0 0.08 1.25 3.75

UPN#7 0.02 1.85 7.69 0.02 1.75 2.04

UPN#8 0.18 2.84 2.21 0.09 1.35 1.42

UPN#9 0.36 4.85 6.58 0.80 4.85 2.2

UPN#10 0.35 7.81 3.5 0.47 8 2.03

Mean 0.16 3.5 4.62 0.20 2.41 2.21

SEM 0.04 0.63 1.51 0.09 0.81 0.38

n.e.: not evaluable.

Table S6. CD4-CD8 distribution among TK+ and TK- cells.

Patient TK-DLI (before infusion) TK+ cells (long-term) TK- cells (long-term)

% CD4+ % CD8+ % CD4+ % CD8+ % CD4+ % CD8+

UPN#1 22.4 77.6 64.29 35.71 63.23 36.77

UPN#2 23 77 n.e. n.e 60.91 39.09

UPN#3 18.55 81.45 30.36 69.64 58.72 41.28

UPN#4 43.13 56.87 21.11 78.89 62.66 37.34

UPN#5 13.49 86.51 0.48 99.52 51.67 48.33

UPN#6 35.89 64.11 n.e. n.e. 59.4 40.6

UPN#7 39.96 60.04 53.39 46.61 69.48 30.52

UPN#8 22.44 77.56 6.05 93.95 68.06 31.94

UPN#9 26.3 73.7 10.57 89.43 49.67 50.33

UPN#10 18.55 81.45 48.07 51.93 80.74 19.26

Mean 26.37 73.63 29.29 70.71 62.45 37.55

SEM 3.14 3.14 8.40 8.40 2.83 2.83


Numbers show frequency of CD4+ or CD8+ cells detected before infusion or at 1st long-term

follow-up. Frequencies have been normalized on total CD4+ and CD8+ T cells.

Table S7. Phenotypic characterization of TK+ and TK- cells circulating in TK patients.

TK+-cell batches before infusion (TK-DLI).

Patient % / CD4+ TK+ cells % / CD8+ TK+ cells


UPN#1 0 0.5 17.6 81.3 0.6 0 4.59 20.9 71.7 2.81

UPN#2 0 8.29 25 61.3 5.41 0 12.1 10.5 56.7 20.7

UPN#3 0 2.45 29.41 67.16 0.98 0 20.2 20.2 49.22 10.38

UPN#4 0 3.36 21.67 72.89 2.08 0 12.65 10.19 64.59 12.57

UPN#5 0 5.56 40.37 51.11 2.96 0 37.2 16.75 33.39 12.66

UPN#6 0 7.03 4.72 60.9 27.35 0 7.36 1.89 49 41.75

UPN#7 0 1.45 15.4 76.8 6.35 0 11.1 9.28 53.8 25.82

UPN#8 0 8.78 57.74 31.29 2.19 0 14.56 36.57 44.79 4.08

UPN#9 0 13.67 71.8 12.9 1.63 0 75.16 6.01 10.44 8.39

UPN#10 0 33.42 40.15 22.94 3.49 0 46.21 18.08 23.99 11.72

Mean 0 8.45 32.39 53.86 5.31 0 24.11 15.04 45.76 15.09

SEM 0 3.05 6.47 7.51 2.52 0 7.05 3.11 5.88 3.68

TK+ cell circulating at long-term time-points.


TK- cell circulating at long-term time-points.

Patient

% / CD4+ TK+ cells % / CD8+ TK+ cells

(1st - 2nd long-term follow-up) (1st - 2nd long-term follow-up)


UPN#1 0 - 0 0.14 - 1.98 47.3 - 53.91 51.8 - 42.9 0.76 - 1.22 0 - 0 2.71 - 6.25 25.4 - 38.1 70.2 - 42.9 1.69 - 9.8

UPN#2 n.e. n.e. n.e. n.e. n.e. n.e. n.e. n.e. n.e. n.e.

UPN#3 0 - 0 4.68 - 4.82 70.76 - 30.1 22.1 - 63.9 2.46 - 1.18 0 - 0 18.09 - 5.98 19.5 - 5.98 46.8 - 80.4 15.61 - 7.61

UPN#4 0 - 0 45.93 - 44.4 37.18 - 44.4 14.04 - 11.1 2.85 - 0.1 0 - 0 26.4 - 17.2 20.18 - 48.3 46.74 - 31 6.68 - 3.5

UPN#5 0 - 0 7 - 23.5 22 - 23.5 68 - 52.9 3 - 0.1 0 - 0 0.36 - 0.59 1.31 - 2.08 87.4 - 90.2 10.93 - 7.13

UPN#6 n.e. n.e. n.e. n.e. n.e. n.e. n.e. n.e. n.e. n.e.

UPN#7 0 - 0 0 - 0.909 19.6 - 22.7 80.4 - 75.5 0 - 0.89 0 - 0 2.44 - 2.56 7.38 - 11.5 87.8 - 85.9 2.38 - 0.04

UPN#8 0 - 0 2.94 - 0.87 70.56 - 65.1 26.5 - 33.6 0 - 0.43 0 - 0 1.38 - 0.83 43.6 - 53.3 54.8 - 45.5 0.22 - 0.37

UPN#9 0 - 0 0.11 - 0.19 72.1 - 73.8 27.7 - 26 0.09 - 0.01 0 - 0 19.3 - 18.5 27.4 - 41.9 37 - 31.2 16.3 - 8.4

UPN#10 0 - 0 0.07 - 0.44 51 – 50.3 48.8 – 49.2 0.13 - 0.06 0 - 0 11.6 - 13.1 43.4 – 49.3 39.7 – 31.2 5.3 – 6.4

Mean 0 - 0 7.61 - 9.64 48.81 - 43.94 42.42 - 45.91 1.16 - 0.51 0 - 0 10.28 - 7.94 23.52 - 28.67 58.81 - 56.9 7.39 - 6.12

SEM 0 - 0 5.55 - 5.68 7.57 - 6.73 8.36 - 7.63 0.48 - 0.18 0 - 0 3.54 - 2.50 5.34 - 7.04 7.24 - 8.70 2.21 - 1.55

Patient

% / CD4+ TK- cells % / CD8+ TK- cells

(1st - 2nd long-term follow-up) (1st - 2nd long-term follow-up)


UPN#1 19.22 - 22.16 2.38 - 2.74 47.2 - 42.7 29.5 - 30.8 1.7 - 1.6 15.77 - 17.29 19.83 - 4.41 15.7 - 30.6 28 - 37.9 20.7 - 3.75

UPN#2 11.8 - 7.17 5.1 - 3.23 61.2 - 62.5 20.1 - 26 1.8 - 1.1 15.01 - 5.72 24.59 - 15.08 19.9 - 35.2 19 - 35.5 21.5 - 8.5

UPN#3 32.43 - 34.19 1.07 - 2.81 31.2 - 27.7 33.1 - 33.2 2.2 - 2.1 37.6 - 38.57 1.5 - 5.16 4.51 - 5.14 32.8 - 32.6 23.59 - 18.5

UPN#4 65.96 - 61.42 3.74 - 2.18 20.3 - 25.8 8.34 - 8.27 1.66 - 2.33 69.48 - 66.44 11.22 - 5.06 3.14 - 6.69 5.37 - 8.48 10.79 - 13.33

UPN#5 51.09 - 40.17 2.31 - 1.63 27.5 - 28.5 18.2 - 29 0.9 - 0.7 29.21 - 16.97 2.39 - 2.63 10.7 - 18.4 36.4 - 50.4 21.3 - 11.6

UPN#6 51.39 - 44.75 28.91 - 21.15 5.88 - 12.6 4.16 - 11.3 9.66 - 10.2 57.93 - 43.29 14.57 - 5.41 1.23 - 4.87 1.99 - 14 24.28 - 32.43

UPN#7 15.77 - 16.28 1.43 - 0.92 32.5 - 32.8 46.6 - 46.4 3.7 - 3.6 27.72 - 29.32 4.48 - 3.08 10.6 - 10.7 42.2 - 41.9 15 - 15

UPN#8 52.35 - 52.54 0.95 - 1.06 34.8 - 35.2 10.6 -10.7 1.30 - 0.5 42.4 - 48.73 9.42 - 8.27 21.1 - 20.8 14.8 - 16.1 5.64 - 6.1

UPN#9 11.6 - 10.94 0.34 - 0.66 57.1 - 62.4 30.3 - 26 0.7 - 0 12.1 - 11.69 0.83 - 0.51 54.9 - 44.7 30.2 - 40 1.9 - 3.1

UPN#10 27.46 – 25.51 3.74 - 4.19 46.1 – 46.5 20.1 – 21.7 2.6 - 2.1 59.48 – 66.55 9.92 - 10.65 11.8 – 12.2 8.48 – 6.7 10.32 – 3.9

Mean 33.91 - 31.30 5 - 4.13 36.38 - 37.2 22.1 - 24.89 2.62 - 2.48 36.67 - 33.65 9.88 - 6.03 15.36 - 18.62 21.92 - 28.85 15.50 - 12.24

SEM 6.27 - 5.77 2.70 - 1.93 5.34 - 5.00 4.10 - 3.73 0.83 - 0.93 6.44 - 6.55 2.53 - 1.35 4.88 - 4.43 4.42 - 4.71 2.52 - 2.72

Table S8. Number of unique sequences of TK+ cells. Sample Patient IS CDR3α CDR3β

TK+-cell batches

(before infusion)

UPN#9 52675 8761 5355

UPN#5 11488 53560 50060

UPN#3 29572 18459 13351

TK+ cells

long-term

UPN#9 1158 325 175

UPN#5 169 1077 621

UPN#3 324 3775 1930

Number of unique sequences detected with read count >1 is reported.

supplementary materials for · 2015. 12. 23. · supplementary materials and methods absolute...

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