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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
5. TK- CD4+ subsets
6. TK- CD8+ subsets
FSC-A
FS
C-H
FSC-A
SS
C-A
CD3
LN
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7.TK+ CD4/CD8
8. TK+ CD4+ subsets
9. TK+ CD8+ subsets
CD8
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CD62L+ CD45RA+ CD62L- CD45RA-
CD95
SS
C
CD62L+ CD45RA+ CD62L- CD45RA-
CD95
SS
C
CD62L+ CD45RA+ CD62L- CD45RA-
CD95
SS
C
CD62L+ CD45RA+ CD62L- CD45RA-
FMO
TK- cells
FMO
TK- cells
FMO
TK+ cells
FMO
TK+ cells
Supplementary Materials and Methods
2.1
3.9
0.06
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0.44
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29.7
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6.7
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37.9
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81.8
0.002
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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Ki-67
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0.431% 3.03%0.155%
40.6%
0.99%
Supplementary Materials and Methods
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Ki-67
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40.6%
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Supplementary Materials and Methods
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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Fig. S2
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CD62L+ CD45RA+TK- cells
CD62L- CD45RA-TK- cells
TK+ cells97.7%
84%
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S2+ΔLNGFR selection
S1+ΔLNGFR selection
S1
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S1+ΔLNGFR selection
S1
S2+ΔLNGFR selection
S1+ΔLNGFR selection
S1
ΔLNGFR ΔLNGFR ΔLNGFR
CD62L+ CD45RA+ CD3+ sorted T cells
CD62L- CD45RA+ CD3+ sorted T cells
CD62L- CD3+ sorted T cells
0.364%
59.3%
99.5%
0.596%
71.1%
99.4%
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98.1%
Fig. S3
CD4
CD8
Fig. S1
TK-DLI TK+ TK- HC0
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% o
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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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DLNGFR
+ cells
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Fig. S2
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CD62L+ CD45RA+TK- cells
CD62L- CD45RA-TK- cells
TK+ cells97.7%
84%
15.5%
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94.6%
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CD95
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Gated on CD8+ T cells
B
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S1+ΔLNGFR selection
S1
S2+ΔLNGFR selection
S1+ΔLNGFR selection
S1
S2+ΔLNGFR selection
S1+ΔLNGFR selection
S1
ΔLNGFR ΔLNGFR ΔLNGFR
CD62L+ CD45RA+ CD3+ sorted T cells
CD62L- CD45RA+ CD3+ sorted T cells
CD62L- CD3+ sorted T cells
0.364%
59.3%
99.5%
0.596%
71.1%
99.4%
0.182%
5.51%
98.1%
Fig. S3
CD4
CD8
Fig. S1
TK-DLI TK+ TK- HC0
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100
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
n.e.: not evaluable.
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
TN TSCM TCM TEM TEMRA TN TSCM TCM TEM TEMRA
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.
n.e.: not evaluable.
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)
TN TSCM TCM TEM TEMRA TN TSCM TCM TEM TEMRA
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)
TN TSCM TCM TEM TEMRA TN TSCM TCM TEM TEMRA
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.