Supplementary Materials for · using RNeasy Maxi Kit (Qiagen). Recombinant Cas9 protein Cas9...

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science.sciencemag.org/cgi/content/full/science.aba7365/DC1 Supplementary Materials for CRISPR-engineered T cells in patients with refractory cancer Edward A. Stadtmauer,*† Joseph A. Fraietta,* Megan M. Davis, Adam D. Cohen, Kristy L. Weber, Eric Lancaster, Patricia A. Mangan, Irina Kulikovskaya, Minnal Gupta, Fang Chen, Lifeng Tian, Vanessa E. Gonzalez, Jun Xu, In-young Jung, J. Joseph Melenhorst, Gabriela Plesa, Joanne Shea, Tina Matlawski, Amanda Cervini, Avery L. Gaymon, Stephanie Desjardins, Anne Lamontagne, January Salas-Mckee, Andrew Fesnak, Donald L. Siegel, Bruce L. Levine, Julie K. Jadlowsky, Regina M. Young, Anne Chew, Wei-Ting Hwang, Elizabeth O. Hexner, Beatriz M. Carreno, Christopher L. Nobles, Frederic D. Bushman, Kevin R. Parker, Yanyan Qi, Ansuman T. Satpathy, Howard Y. Chang, Yangbing Zhao, Simon F. Lacey,* Carl H. June*† *These authors contributed equally to this work. †Corresponding author. Email: [email protected] (E.A.S.); [email protected] (C.H.J.) Published 6 February 2020 on Science First Release DOI: 10.1126/science.aba7365 This PDF file includes: Materials and Methods Supplementary Text Figs. S1 to S10 Tables S1, S2, S3, S5, and S6 Caption for Table S4 References Other Supporting Online Material for this manuscript includes the following: (available at science.sciencemag.org/cgi/content/full/science.aba7365/DC1) Table S4 (Excel)

Transcript of Supplementary Materials for · using RNeasy Maxi Kit (Qiagen). Recombinant Cas9 protein Cas9...

Page 1: Supplementary Materials for · using RNeasy Maxi Kit (Qiagen). Recombinant Cas9 protein Cas9 recombinant protein derived from . Streptococcus pyogenes. was TrueCut Cas9 v2 (Catalogue

science.sciencemag.org/cgi/content/full/science.aba7365/DC1

Supplementary Materials for CRISPR-engineered T cells in patients with refractory cancer

Edward A. Stadtmauer,*† Joseph A. Fraietta,* Megan M. Davis, Adam D. Cohen, Kristy L. Weber, Eric Lancaster, Patricia A. Mangan, Irina Kulikovskaya, Minnal Gupta,

Fang Chen, Lifeng Tian, Vanessa E. Gonzalez, Jun Xu, In-young Jung, J. Joseph Melenhorst, Gabriela Plesa, Joanne Shea, Tina Matlawski, Amanda Cervini, Avery L. Gaymon, Stephanie Desjardins, Anne Lamontagne, January Salas-Mckee, Andrew Fesnak,

Donald L. Siegel, Bruce L. Levine, Julie K. Jadlowsky, Regina M. Young, Anne Chew, Wei-Ting Hwang, Elizabeth O. Hexner, Beatriz M. Carreno, Christopher L. Nobles,

Frederic D. Bushman, Kevin R. Parker, Yanyan Qi, Ansuman T. Satpathy, Howard Y. Chang, Yangbing Zhao, Simon F. Lacey,* Carl H. June*†

*These authors contributed equally to this work.†Corresponding author. Email: [email protected] (E.A.S.); [email protected] (C.H.J.)

Published 6 February 2020 on Science First Release DOI: 10.1126/science.aba7365

This PDF file includes:

Materials and Methods Supplementary Text Figs. S1 to S10 Tables S1, S2, S3, S5, and S6 Caption for Table S4 References

Other Supporting Online Material for this manuscript includes the following: (available at science.sciencemag.org/cgi/content/full/science.aba7365/DC1)

Table S4 (Excel)

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Materials and Methods Experimental design

The clinical protocol is listed at trial ClinicalTrials.gov NCT03399448. Protocol #1604-1524 “Phase I Trial of Autologous T Cells Engineered to Express NY-ESO-1 TCR and Gene Edited to Eliminate Endogenous TCR and PD-1” was reviewed and approved by the U.S. National Institutes of Health Recombinant DNA Advisory Committee on June 21, 2016. See Figure S1B for clinical trial design. Patient demographics are shown in Table 1. A list of adverse events is depicted in Table 2. Clinical summaries of subjects

Subject 25416-07 (UPN07) was first diagnosed with ISS stage 1 kappa light chain multiple myeloma manifested by bone marrow plasmacytosis, serum monoclonal protein and lytic bone lesions with plasmacytomas at age 53 in 2009. She was first treated with lenalidomide and dexamethasone followed by high-dose melphalan and ASCT followed by consolidation therapy with 4 cycles of lenalidomide, bortezomib and dexamethasone followed by lenalidomide maintenance therapy. She progressed after 3 years and over the course of the next 5 years received 5 lines of therapy including various combinations of lenalidomide, bortezomib, dexamethasone, carfilzomib, pomalidomide, daratumumab and a second ASCT. Her most recent therapy was an investigational anti-CD38 directed immunoconjugate with progression. She underwent steady state T cell harvest and a cycle of chemotherapy with cyclophosphamide, doxorubicin, etoposide and dexamethasone (D-ACE) and palliative radiation to a thoracic vertebra plasmacytoma prior to fludarabine and cyclophosphamide lymphodepleting chemotherapy before NYCE T cell infusion. NYCE T cells were successfully manufactured and she underwent lymphodepleting chemotherapy and a single infusion of NYCE T cells 8/5/19 (day 1) without infusion related complications. She did experience pancytopenia felt to be related to the lymphodepleting chemotherapy and was placed on prophylactic levofloxin and required 2 transfusion of platelets and 4 units of packed red blood cells. She experienced no CRS or neurotoxicity. By day 28 she had resolution of symptoms and staging evaluation revealed progressive disease. Since then she received one cycle of D-ACE with transient response and prolonged hospitalization, selinexor, bortezomib and dexamethasone and expired day 141 from progressive disease and gram negative sepsis without new or ongoing study related adverse events.

Subject 25416-27 (UPN27) was first diagnosed with synovial sarcoma in her left lower

extremity in 2006 at age 23. She was first treated with neoadjuvant doxorubicin chemotherapy, radiation and limb salvage surgical resection. She did well for a decade when she developed recurrence with pleural based lung masses and malignant pleural effusion. Over the next 2 years, she received 4 lines of chemotherapy with various combinations of ifosfamide, doxorubicin, etoposide and trabectedin and resection of the pleural mass with progression but no active therapy for 9 months prior to T cell harvest and lymphodepleting chemotherapy and NYCE T cell infusion. NYCE T cells were successfully manufactured but she developed rapid clinical progression with inadequate respiratory function and performance status and she was taken off study before lymphodepleting chemotherapy and cell infusion. She expired on hospice care.

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Subject 25416-35 (UPN35) was first diagnosed with ISS stage 2 IgG kappa multiple myeloma manifested by bone marrow plasmacytosis, serum monoclonal protein and lytic bone lesions at age 52 in 2004. She was first treated with pulse dexamethasone with response and then cyclophosphamide and filgrastim stimulated peripheral hematopoietic stem cell transplantation (ASCT). She progressed and over the course of the next 9 years, she received 8 lines of therapy including various combinations of bortezomib, lenalidomide, pomalidomide, carfilzomib, cyclophosphamide, doxorubicin, etoposide, panobinostat, daratumumab and a third ASCT. Her most recent therapy was cycles of daratumumab, pomalidomide and dexamethasone (DARA/POM/DEX) with progression. She underwent steady state T cell harvest and another cycle of DARA/POM/DEX prior to fludarabine and cyclophosphamide lymphodepleting chemotherapy before NY-ESO-1 transduced CRISPR 3X Edited (NYCE) T cell infusion. NYCE T cells were successfully manufactured and she underwent lymphodepleting chemotherapy and a single infusion of NYCE T cells 1/7/19 (day 1) without infusion related complications. She experienced upper respiratory symptoms and sinus congestion without fever treated symptomatically for likely viral syndrome. She experienced no CRS or neurotoxicity. By day 28 she had resolution of symptoms and staging evaluation revealed stable disease. By day 60 she had progressive disease and was begun on elotuzumab, pomalidomide and dexamethasone with response but progression within 3 months. She received an investigational BCMA bispecific antibody which she tolerated well but progressed and then was replaced on elotuzumab, pomalidomide and dexamethasone once again with initial response. She remains alive without new or ongoing study related adverse events day 294 from NYCE T cell infusion.

Subject 25416-39 (UPN39) was first diagnosed with myxoid liposarcoma at age 59 in

2012. He first received doxorubicin and ifosfamide neoadjuvant chemotherapy and resection of a left pelvic tumor followed by adjuvant involved field radiation. He developed local recurrence twice in 2015 and 2017 treated with resection including left nephrectomy and partial sigmoid resection. After resection he received trabectedin and gemcitabine and taxol with progression followed by palliative left pelvis radiation with continued progression. He had not received active therapy for 9 months prior to T cell harvest and lymphodepleting chemotherapy and NYCE T cell infusion. NYCE T cells were successfully manufactured and he underwent lymphodepleting chemotherapy and a single infusion of NYCE T cells 3/18/19 (day 1) without infusion related complications. He did experience pancytopenia felt to be related to the lymphodepleting chemotherapy and was placed on prophylactic levofloxin and required one transfusion of platelets and 1 unit of packed red blood cells. He experienced no CRS or neurotoxicity. By day 28 he had recovery of blood counts and staging evaluation showed mixed response, stable disease by the RESIST criteria. By day 120 he met criteria for progression and was begun on liposomal doxorubicin. He remains alive with progression without new or ongoing study related adverse events day 274 from NYCE T cell infusion.

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Guide RNAs (gRNA)

The genomic gRNA target sequences with PAM in bold were: TRAC1 and TRAC2: 5’-TGTGCTAGACATGAGGTCTATGG-3’, TRBC: 5’-GGAGAATGACGAGTGGACCCAGG-3’, and PDCD1: 5’-GGCGCCCTGGCCAGTCGTCTGGG-3. In vitro transcribed gRNA was prepared from linearized DNA (Aldevron) using Bulk T7 Megascript 5X (Ambion) and purified using RNeasy Maxi Kit (Qiagen). Recombinant Cas9 protein

Cas9 recombinant protein derived from Streptococcus pyogenes was TrueCut Cas9 v2 (Catalogue # A36499, ThermoFisher). Cas9 RNP was made by incubating protein with gRNA at a molar ratio of 1:1 at 25°C for 10 minutes immediately prior to electroporation. Lentiviral vector manufacturing

The 8F TCR recognizes the HLA-A*0201 SLLMWITQC epitope on NY-ESO-1 and LAGE-1. The 8F TCR was isolated from a T cell clone obtained from patient after vaccination with NY-ESO-1 peptides as described (51-53). The TCR sequences were cloned into a transfer plasmid that contains the EF-1α promoter, a cPPT sequence, a rev response element and a woodchuck hepatitis virus posttranscriptional regulatory element (WPRE) as shown in Figure S1B. Plasmid DNA was manufactured at Puresyn, Inc. Lentiviral vector was produced at the University of Pennsylvania Center for Advanced Retinal and Ocular Therapeutics using transient transfection with four plasmids expressing the transfer vector, Rev, VSV-G and gag/pol, in 293T cells. NYCE T cell manufacturing

NY-ESO-1 TCR transduced 3X CRISPR-edited (NYCE) T cells are autologous T cells that have been engineered to express an HLA-A*0201-restricted NY-ESO-1 (SLLMWITQC)-specific TCR by lentiviral transduction. Engineered T cells were manufactured at the Clinical Cell and Vaccine Production Facility at the University of Pennsylvania. An overview of the manufacturing process is shown in Figure S1A. On day-5, autologous T cells were obtained by apheresis. On day -4 the fresh apheresis product was elutriated and washed to enrich for lymphocytes and seeded in static culture in medium supplemented with recombinant human IL-7 and IL-15 (Miltenyi Biotec.) On day -2, ribonucleoprotein (RNP) complexes containing wild-type Cas9 (ThermoFisher) and in vitro transcribed gRNA sequences for TRAC, TRBC and PDCD1 were added to the cells and the cell mixture was electroporated (Maxcyte) and then placed in culture at 30C in medium supplemented with IL-7 and IL-15. On day 0 the temperature was shifted to 37C and the cells were activated and expanded using anti-CD3/CD28 antibody–conjugated paramagnetic microbeads (Life Technologies). On day 1 the cells were transduced with lentiviral vector containing 8F NY-ESO-1 TCR genes and maintained in static culture in media supplemented with IL-7 and IL-15. On day 5 the cells were transferred to the Wave Bioreactor System (GE Healthcare) with daily perfusion and cultures were allowed to continue expansion until harvest day. On day 11, the cells were harvested, the beads were removed, cells washed, formulated and cryopreserved in infusible cryomedia. Small-scale cultures were included for mock electroporated

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controls, potency controls and iGUIDEseq analysis (33). Absolute cell counts were obtained during large-scale culture using a Coulter Counter (Beckman Coulter). Cell lines

The parental Nalm-6 cell line was obtained from DSMZ (Braunschweig). Nalm-6 cells were transduced with lentiviruses encoding the NY-ESO-1 antigen, click beetle green luciferase (CBG) and/or green fluorescent protein (GFP). These cells were selected based on GFP expression (>99% GFP-positive), expanded and authenticated by the University of Arizona (USA) Genetics Core based on criteria established by the International Cell Line Authentication Committee. Cells were cultured in complete RPMI media (RPMI 1640 supplemented with 10% fetal calf serum, 100 U/mL penicillin, 100 μg/mL streptomycin sulfate) and periodically monitored for transgene expression. Banks of the above engineered Nalm-6 cells were also screened and confirmed to be free of mycoplasma contamination. Peptides

Two sub-pools of 170 peptides (15mers with 11 amino acid overlap) each corresponding to full-length CRISPR-associated endonuclease Cas9/Csn1 (Swiss-Prot ID: Q99ZW2) of Streptococcus pyogenes serotype M1 were purchased from JPT Peptide Technologies (Catalogue # PM-STRP1-CAS9). Pool-3 was pooled from 38 peptides (Proimmune), which were the top ranked epitopes for HLA-A*02:01 according to (54). All peptides were reconstituted to a concentration of 625 mg/mL in 100% DMSO. Flow cytometry

Cryopreserved T cells were thawed and washed twice with phosphate-buffered saline (PBS). Cells were then stained with fixable Live/Dead Aqua (Invitrogen) for 10 minutes at room temperature. Cells were then washed with FACS buffer (PBS + 3% fetal bovine serum [FBS]) twice, and then incubated for 20 minutes at room temperature with surface antibody cocktail. The Foxp3 staining Buffer Set (Catalogue # 00-5523-00, ThermoFisher) was used for intracellular staining. Briefly, T cells were resuspended in permeabilization/fixation buffer and incubated for 30 minutes at room temperature, followed by washing in permeabilization/wash buffer. Cells were then stained with an antibody cocktail for 30 minutes at room temperature. Following staining, cells were washed twice and resuspended in 200 lFACS buffer for acquisition on a LSR Fortessa flow cytometer (BD Biosciences). Data was analyzed with FlowJo version 10 software (FlowJo, LLC). The following antibodies were used:

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Marker Fluorochrome Vendor Catalogue # HLA-A*0201 / SLLMWITQV

Dextramer APC Immunodex WB3247-APC

Live/Dead Aqua Invitrogen L34965 Vbeta8.1 PE BioLegend 348104

CCR7 PE-CF594 BD 562381 CD27 V711 BioLegend 302834 CD27 PE-CY7 BioLegend 356412 CD28 APC Invitrogen 17-0289-42 CD3 BV605 BioLegend 317322 CD3 APC-H7 BD 560176 CD4 BV785 BioLegend 317441

CD45RA BV570 BioLegend 304132 CD45RO BV570 BioLegend 304226

CD8 APC-H7 BD 561423 CD8 PE-CY5.5 Invitrogen 35-0088-42

LAG-3 PE-Cy7 Invitrogen 25-2239-42 PD-1 BV421 BioLegend 329920

TIM-3 BV650 BioLegend 345028 CTLA-4 PE-Cy5 BD 555854 EOMES FITC Invitrogen 11-4877-42

Analysis of CRISPR/Cas9-mediated TRAC, TRBC and PDCD1 disruption

Duplex TaqMan probe-based PCR assays were designed for each of the three target genes: one to quantify the sequence (locus) within the gene targeted by the guide RNA used in the CRISPR/Cas9 system, and another to quantify a reference sequence within the same gene that was not affected by editing. For each sample/gene combination the copy number of target and reference sequence were measured in a single duplex digital PCR employing two primer/probe sets. Target and reference amplicons were distinguished by different dyes labeling the two probes. The primers/probes were as follows: TRAC target sequence; Forward 5'-TTGTTGCTCCAGGCCACAG-3', Reverse 5'-TGTGTCACAAAGTAAGGATTCTGATGT-3’, Probe 5'-6FAM-TAGACCTCATGTCTAGCACA-3'; TRAC control sequence; Forward 5'-TGCCGGCACATGAATGC-3', Reverse 5'-CCCCTCATCTGACTTTTTAATTCC-3’, Probe 5’-6VIC-CCAGGTGTTGAAGTGG-3'. TRBC target sequence; Forward 5'-GGGCAAAGTGGAGAGAGAG-3', Reverse 5'-TCCGCTGTCAAGTCCAGTTCT-3’, Probe 5'-6FAM-GGGTCCACTCGTCATTCTCC-3' TRBC control sequence; Forward 5'-TCGCTGTGTTTGAGCCATCA-3', Reverse 5'-CACCAGTGTGGCCTTTTGG -3’, Probe 5'-VIC-AAGCAGAGATCTCC-3'. PDCD1 target sequence; Forward 5'- ACACCTGACCGCCGACC -3', Reverse 5'- CTGCTCCAGGCATGCAGAT -3’, Probe 5'-6FAM-CA+G+A+C+GAC+TGG-3', PDCD1 control sequence; Forward 5'- CCCTCAAAGCTTCCACCTTGT -3', Reverse 5'-CATCACACGGTGGAAAGATCTG-3’,

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Probe5'-6VIC-ATGGCCTCACACCATG-3'. The “+” symbol in probe sequences indicates linked bases. The Applied Biosystems (ABI) digital PCR system that was used for this study partitions the PCR mix into approximately 20,000 individual reactions on a microfluidic chip and amplifies the target and reference sequences in an end-point PCR on a ProFlex PCR system 9700 (ABI). Fluorescent signals from two dyes are read in the QuantStudio® 3D instrument and the results analyzed using QuantStudio® 3D AnalysisSuite™ Cloud Software. The final data from the digital PCR system was expressed as the number of copies of each sequence, and the degree of disruption of the T cell receptor alpha gene calculated as the ratio of the difference between reference and target copy number to the reference copy number, multiplied by 100 in order to convert this ratio to percentage disruption. Cytotoxicity of NYCE T cell infusion products Nalm-6/NY-ESO-/CBG/GFP cells were plated at 1 × 104 cells/well into 96-well round bottom plates. NYCE T cell infusion products (denoted as NYCE), patient-matched T cells expressing the NY-ESO-1 TCR without TRAC, TRBC and PDCD1 editing (denoted as NY-ESO-1 TCR) or patient-matched untransduced T cells with CRISPR edits (denoted as CRISPR) were added to Nalm-6 cells at effector to target ratios ranging from 10:1 to 1:10. The input of effectors for the NYCE and NY-ESO-1 TCR conditions was based on the number of NYCE TCR-transduced T cells (i.e., the 10E:1T ratio condition had 1 × 105 TCR+ T cells: 1 × 104 tumor targets based on %Vβ8 expression by flow cytometry at the time of dose harvest and formulation, and the total number of T cells per well varied due to different transduction efficiencies). The input of effectors for the untransduced CRISPR control condition used total T cells as effectors (i.e., for the 10E:1T ratio, 1 × 105 total effector cells and 1 × 104 tumor targets were used), since they do not express the the NY-ESO-1 TCR.

Nalm-6 cells treated with 1% Triton X-100 (complete lysis) or media alone (spontaneous lysis) served as experimental controls. Following a 24-hour co-culture, cell extracts were made using the Bright-Glo Luciferase Assay System (Promega Corporation) and substrate was added according to the manufacturer’s instructions. Luciferase measurements were taken on a SpectraMax luminescence microplate reader (Molecular Devices), and specific lysis was calculated using the following equation: (experimental lysis - spontaneous lysis) ×100/(complete lysis - spontaneous lysis). IFN-based NYCE T cell product potency assay NYCE T cell infusion products or the above patient-matched controls were co-cultured at a 2:1 ratio of T cells to Nalm-6 tumor targets and supernatants were collected 24 hours later. Cytokine levels were measured in harvested supernatants using the Human IFN DuoSet ELISA Kit (R&D Systems), according to the manufacturer’s instructions. Samples were analyzed on a FLUOstar Omega Multi-Mode Microplate Reader with 530 nm excitation and 590 nm emission channels. Data were analyzed using Omega Data Analysis Software (BMG LabTech). Detection of residual Cas9 protein in NYCE T cell infusion products An in-house ELISA to measure residual Cas9 content in the cell products was built and validated for specificity, accuracy, intra-assay and inter-assay precision and range. The DuoSet

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Ancillary Reagent Kit (R&D Systems) was used for assay establishment, according to the manufacturer’s instructions. The substrate solution for this assay consisted of a 1:1 mixture of Color Reagent A (H2O2) and Color Reagent B (Amplex™ Red at 100 M, ThermoFisher). Substrate color was developed for 15 minutes and samples were analyzed as described above. Measurement of NYCE T cell product humoral immunogenicity

An ELISA assay was created to measure human serum antibodies against Cas9 proteins. Briefly, for each ELISA plate, columns 1 to 6 were coated with 100 l/well of 2000 ng/ml TrueCut™ Cas9 Protein v2 (ThermoFisher) diluted in PBS, while columns 7 to 12 were coated with 1% BSA (10 mg/ml) in PBS at 100 l/well. Each human serum sample was tested at 1:100 and 1:500 dilutions in reagent diluent (RD, 1% BSA in PBS). Each diluted serum sample at 100 l/well was incubated with two wells coated with Cas9 protein (Cas9 signal) and two wells coated with 1% BSA (BSA signal) at room temperature (RT) for 1 hour. After washing plates twice with wash buffer, 100 l/well of anti-human IgG-HRP conjugate (ThermoFisher) diluted 1:1000 in RD was added to each well and incubated at RT for 30 minutes. Plates were processed as described above. There was no standard curve for this assay. Anti-Cas9-specific signal was calculated in relative fluorescence units (RFU) by subtracting the average BSA signal from the corresponding average Cas9 signal. Evaluation of post-infusion NY-ESO-1-specific T cell responses

Short-term exvivo expanded T cell lines were generated from PBMC cultured in Optimizer CTS T cell expansion media (ThermoFisher) containing 5% human AB-serum with 10 g/mL NY-ESO-1 9V peptide (SLLMWITQCV) and IL-2 (50U/mL). On day 10, cells were harvested, counted and re-stimulated with HLA-A*02:01 / 41BB-L artificial antigen presenting cells (aAPC, K562) for an additional period of 10 days. To assess V8.1 TCR frequency in expanded cultures, cells were stained with PE-anti-VB8.1 antibody (Biolegend) and APC-anti-CD8 antibody (ThermoFisher) for 20 minutes at 4oC. Staining was performed in cultures collected after peptide (primary) and aAPC plus peptide (secondary) stimulations. Thirty thousand events collected in the CD8+ gate were acquired and analyzed by FlowJo software. To evaluate functionality, cell lines A375, Nalm-6 and Nalm-6 A2+/ NY-ESO-1+ were labeled with 25uCi 51Cr for 1 hour, washed and tested as targets in a standard 4-hour cytotoxicity assay. Effectors were cells derived from secondary PBMC cultures generated as described above. Assays were set up in triplicates and results are shown as average plus standard deviation (SD). Assessing baseline cellular immunogenicity to Cas9 protein

Cryopreserved human PBMCs or apheresis products were thawed in complete RPMI media and 0.5 U/ml of Benzonase (MilliporeSigma), and incubated at 37°C in 5% CO2 for 30 minutes. Cells were then resuspended with complete media without Benzonase and rested at 37°C for 2 hours. Following the resting period, 0.5 × 106 cells were cultured with one of three Cas9 peptide pools described above at a concentration of 2 g/ml of each peptide in 100l of medium containing co-stimulatory antibodies (αCD28 and αCD49d, 1 μg/mL; BD Biosciences), GolgiStop (2 μL/mL; BD Biosciences), GolgiPlug (1 μg/mL; Sigma-Aldrich), and an anti-CD107 antibody (BioLegend) for 6 hours at 37°C. Cells incubated with peptide diluent (0.03% DMSO) served as the negative

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control, while PMA/Ionomycin (Sigma-Aldrich) stimulation served as a positive control. Following incubation, cells were washed with PBS and stained with LIVE/DEAD Fixable Aqua (ThermoFisher), washed, and incubated with surface antibodies to CD3, CD14, CD19, (BD Biosciences), CD4 (BioLegend), and CD8a (ThermoFisher) for 20 minutes, followed by 2 washes. The cells were fixed with Cytofix/Cytoperm Buffer (BD Biosciences) according to the manufacturer’s instructions. Following fixation, cells were washed twice in Perm/Wash Buffer and stained with antibodies against intracellular cytokines (TNF, IFN, GM-CSF and IL-2) for 20 minutes. After staining, cells were resuspended in PBS and analyzed on a BD LSRFortessa flow cytometer. Analysis of NY-ESO-1 TCR transgene persistence

Whole-blood samples were collected in lavender top (K2EDTA) Vacutainer tubes (BD). Genomic DNA was isolated from whole blood or marrow using QIAamp DNA blood mini kits (Qiagen) and established laboratory standard operating procedures (SOPs), quantified by spectrophotometry and stored until testing at −80°C. qPCR analyses were performed in bulk using ABI Taqman technology and a validated assay to detect the WPRE sequence present in the lentiviral vector backbone, using three replicates of 200 ng genomic DNA per time-point for peripheral blood and marrow samples and using previously described methodology (54), including normalization for amplification of input DNA using amplifications with the CDKN1A primer/probe set (NF). The reference plasmid dilution series standard was quantitated by digital PCR methodology. WPRE primers were as follows: 5′ WPRE.227. Forward: 5′ CGCAACCCCCACTGGTT 3′ (nt. 227–244 of the WPRE gene) an antisense primer with the sequence: WPRE.289.R: 5′AAAGCGAAAGTCCCGGAAA 3′ (nt. 270–289 of the WPRE gene). These primers amplify a 62-nt. long sequence from the WPRE coding sequence that can be detected using the FAM labeled probe 5′ FAM-TTGCCACCACCTGTC 3′. Values from this analysis are reported as average transgene copies per cell, calculated as: average transgene copies/cell = copies plasmid detected by qPCR/input DNA (ng) × 0.0063 ng DNA/cell × CDKN1A NF × EF. The limit of detection for the assay is <50 copies/μg genomic DNA. The white blood cell count was used as an amplifier to calculate the number of gene modified cells in the peripheral blood. An assumption of 1 vector copy per cell was based upon the multiplicity of infection of 1 used for cell transduction; however, the gene modified cell population is likely to contain subset of cells with multiple integration events. Mapping of CRISPR edit sites using iGUIDE

The locations of nuclease cleavage sites were mapped using iGUIDE (34), a modification of the GUIDESeq method (35). Briefly, T cells from each subject were exposed to the sgRNA/Cas9 reagents in addition to a protected double stranded oligodeoxynucleotide (dsODN). Cells were grown for 9-13 days, then harvested and DNA isolated as described in the qPCR analysis section. DNA was cleaved by sonication, adaptors ligated to free DNA ends, then PCR carried out using primers that annealed to the adaptor and the dsODN. PCR products were analyzed by Illumina sequencing, and reads mapped onto the human genome (hg38). Reads resulting from mispriming were identified and filtered out by requiring the presence of a flanking diagnostic dsODN sequence (a refinement of the iGUIDE method). Software used in the iGUIDE analysis is

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available at GitHub@cnobles/iGUIDE. Sequences of oligonucleotides used in this analysis are in the following table:

Oligo_Name Sequence (IDT format) * Denotes phosphothioate bond, /5Phos/ denotes 5' Phosphate addition

Ref.

dsODN oligos

iGUIDE_dsODN_sense

/5Phos/G*C*TCGCGTTTAATTGAGTTGTCATATGTTAATAACGGTATACGC*G*A

(34)

iGUIDE_dsODN_antisense

/5Phos/T*C*GCGTATACCGTTATTAACATATGACAACTCAATTAAACGCGA*G*C

(34)

Adapter Oligos

adapter_common_oligo

/5Phos/GATCGGAAGAGC*C*A

A01 AATGATACGGCGACCACCGAGATCTACACTAGATCGCNNWNNWNNACACTCTTTCCCTACACGACGCTCTTCCGATC*T

(35)

A02 AATGATACGGCGACCACCGAGATCTACACCTCTCTATNNWNNWNNACACTCTTTCCCTACACGACGCTCTTCCGATC*T

(35)

A03 AATGATACGGCGACCACCGAGATCTACACTATCCTCTNNWNNWNNACACTCTTTCCCTACACGACGCTCTTCCGATC*T

(35)

A04 AATGATACGGCGACCACCGAGATCTACACAGAGTAGANNWNNWNNACACTCTTTCCCTACACGACGCTCTTCCGATC*T

(35)

A05 AATGATACGGCGACCACCGAGATCTACACGTAAGGAGNNWNNWNNACACTCTTTCCCTACACGACGCTCTTCCGATC*T

(35)

A06 AATGATACGGCGACCACCGAGATCTACACACTGCATANNWNNWNNACACTCTTTCCCTACACGACGCTCTTCCGATC*T

(35)

A07 AATGATACGGCGACCACCGAGATCTACACAAGGAGTANNWNNWNNACACTCTTTCCCTACACGACGCTCTTCCGATC*T

(35)

A08 AATGATACGGCGACCACCGAGATCTACACCTAAGCCTNNWNNWNNACACTCTTTCCCTACACGACGCTCTTCCGATC*T

(35)

A09 AATGATACGGCGACCACCGAGATCTACACGACATTGTNNWNNWNNACACTCTTTCCCTACACGACGCTCTTCCGATC*T

(35)

A10 AATGATACGGCGACCACCGAGATCTACACACTGATGGNNWNNWNNACACTCTTTCCCTACACGACGCTCTTCCGATC*T

(35)

A11 AATGATACGGCGACCACCGAGATCTACACGTACCTAGNNWNNWNNACACTCTTTCCCTACACGACGCTCTTCCGATC*T

(35)

A12 AATGATACGGCGACCACCGAGATCTACACCAGAGCTANNWNNWNNACACTCTTTCCCTACACGACGCTCTTCCGATC*T

(35)

A13 AATGATACGGCGACCACCGAGATCTACACCATAGTGANNWNNWNNACACTCTTTCCCTACACGACGCTCTTCCGATC*T

(35)

A14 AATGATACGGCGACCACCGAGATCTACACTACCTAGTNNWNNWNNACACTCTTTCCCTACACGACGCTCTTCCGATC*T

(35)

A15 AATGATACGGCGACCACCGAGATCTACACCGCGATATNNWNNWNNACACTCTTTCCCTACACGACGCTCTTCCGATC*T

(35)

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A16 AATGATACGGCGACCACCGAGATCTACACTGGATTGTNNWNNWNNACACTCTTTCCCTACACGACGCTCTTCCGATC*T

(35)

Adapter Primers

P5_1 AATGATACGGCGACCACCGAGATCTA (35) P5_2 AATGATACGGCGACCACCGAGATCTACAC (35)

(35) dsODN Primers

GSP1_neg_Nuc_off

GGATCTCGACGCTCTCCCTGTTTAATTGAGTTGTCATATGTTAATAAC

(35)

GSP2_neg_Nuc_off

CCTCTCTATGGGCAGTCGGTGATTTGAGTTGTCATATGTTAATAACGGTA

(35)

(35)

Barcoded dsODN Tiered Primers

P701 CAAGCAGAAGACGGCATACGAGATTCGCCTTAGTGACTGGAGTCCTCTCTATGGGCAGTCGGTGA

(35)

P702 CAAGCAGAAGACGGCATACGAGATCTAGTACGGTGACTGGAGTCCTCTCTATGGGCAGTCGGTGA

(35)

P703 CAAGCAGAAGACGGCATACGAGATTTCTGCCTGTGACTGGAGTCCTCTCTATGGGCAGTCGGTGA

(35)

P704 CAAGCAGAAGACGGCATACGAGATGCTCAGGAGTGACTGGAGTCCTCTCTATGGGCAGTCGGTGA

(35)

P705 CAAGCAGAAGACGGCATACGAGATAGGAGTCCGTGACTGGAGTCCTCTCTATGGGCAGTCGGTGA

(35)

P706 CAAGCAGAAGACGGCATACGAGATCATGCCTAGTGACTGGAGTCCTCTCTATGGGCAGTCGGTGA

(35)

P707 CAAGCAGAAGACGGCATACGAGATGTAGAGAGGTGACTGGAGTCCTCTCTATGGGCAGTCGGTGA

(35)

P708 CAAGCAGAAGACGGCATACGAGATCCTCTCTGGTGACTGGAGTCCTCTCTATGGGCAGTCGGTGA

(35)

MiSeq Sequencing Primers

Index1_Seq_Primer

ATCACCGACTGCCCATAGAGAGGACTCCAGTCAC (35)

Read2_Seq_Primer

GTGACTGGAGTCCTCTCTATGGGCAGTCGGTGAT (35)

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Detection of chromosomal translocations in CRISPR-Cas9edited NYCE T cells

A panel of TaqMan qPCR assays was designed to detect the results of monocentromeric translocations and rearrangements between all combinations of TRAC, TRBC1, TRBC2 and PDCD1. These 12 translocations may be designated as, PDCD1:TRAC, PDCD1:TRBC1, PDCD1:TRBC2, TRAC:PDCD1 and so forth. An additional four assays (PDCD1-PDCD1, TRAC-TRAC, TRBC1-TRBC1, TRBC2-TRBC2) represented amplicons generated from non-translocated target genes, serving as positive controls and to quantitate the number of copies of each gene in target DNA. A single synthetic plasmid template was designed to be used as a positive control for all these monocentromeric translocation products. This template has tandem sequences for the 4 forward primers and for the 4 reverse primers flanking an array of sequences corresponding to the 4 probes. A fifth probe sequence not found in the human genome allowed the design of a primer-probe set that could be used to quantitate the synthetic plasmid against a background of human genomic DNA and to facilitate making the standards. The plasmid standard was quantitated using digital PCR to give an objectively validated number of copies per volume of stock solution. The table below shows the sequences of the primers and probes. Each of the 16 primer/probe combinations was used on a dilution series of the synthetic template in parallel during qualification to generate 16 standard curves in triplicate. These standard curves were then compared for slope, linearity and Y-intercept and found to be very similar. We therefore calculated the mean of the slopes, the mean of the Y-intercepts and the mean of the R2 and used the Linear Regression formula to derive the number of copies for each detected translocation based on the demonstrated linearity of all Standard Curves. The equation used was 𝑦 𝑚𝑥 𝑏, where y is Exponential Amplification Value, m is a slope, b is the Y-intercept and x is the number of copies. The Exponential Amplification Value for PCR 𝑦 10 / . From those formulas the number of copies, 𝑥 10 / . The assays were performed on genomic DNA extracted from cell products or from whole blood in the case of post-infusion samples.

PRIMERS SEQUENCE PD-1_tr_Forward GTGAAAGGTCCCTCCAGAC TRAC_tr_Forward GGGCAAAGAGGGAAATGAGA TRBC1_tr_Forward AAAGTGGAGAGAGAGCAACAG TRBC2_tr_Forward GGGATGGACAGACAATGGG PD-1_tr_Reverse CACTGCCTCTGTCACTCTC TRAC_tr_Reverse CATTCCTGAAGCAAGGAAACAG TRBC1_tr_Reverse GCTGAGAATCTGGGAGAAGAAT TRBC2_tr_Reverse GCTTTGCTGACCCTGTGA

PROBES PD-1-ds AGGTGAGCGGAAGGGAAACTGTC TRAC-ds TGCAAACGCCTTCAACAACAGCAT TRBC1-ds ACCATGAAGGAGAATTGGGCACCT TRBC2-ds AGAAAGCCAGAGTGGACAAGGTGG Synthetic DNA specific ACGCACGAGACCATCTGCTGAG

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Monocentromeric Synthetic DNA Control sequence (551 bp): AGTTCATGGAGGATCCGAATTCAAGCTTGGTACCGTCGACTGAGAGTGAAAGGTCCCTCCAGACCCCTCGGTTGGGGCAAAGAGGGAAATGAGATCATGGGGGCAAAGTGGAGAGAGAGCAACAGACACTACTGGGGGATGGACAGACAATGGGCAGTGTAGACGCACATCTCGTAGATCTCGTGATCGTACAACACGCACGAGACCATCTGCTGAGACAACGCGTGATAATGCCACAGGATCTCGTGAAACTAGGGCGGAGGTGAGCGGAAGGGAAACTGTCCCAGGGCATGTGCAAACGCCTTCAACAACAGCATTATTCCGCACACCATGAAGGAGAATTGGGCACCTGTGGTCCAGAAGAAAGCCAGAGTGGACAAGGTGGGATGATGGGCGAGAGTGACAGAGGCAGTGCTGGGGCAGGCTGTTTCCTTGCTTCAGGAATGGCCAGGGTTCATTCTTCTCCCAGATTCTCAGCCCAACAAGGTTCACAGGGTCAGCAAAGCACGGTGGATCCGAATTCAAGCTTGGTACCGTCGACAGTTCATGGA Measurement of NY-ESO-1 and LAGE-1 target antigen levels

Total RNA was isolated directly from whole marrow using Ribopure TM blood kits (Ambion), and cDNA synthesis was performed using iScript cDNA synthesis kits (Bio-Rad). cDNA was used directly in qPCR assays to detect and quantify the relative abundance of NY-ESO-1 (Hs00265824) and LAGE-1 (Hs00535628_m1) transcripts using the inventoried and recommended ABI-based primers-probes (indicated in parentheses). Each data point was evaluated in triplicate with a positive Ct value in 2/3 replicates and % CV less than 15%. A parallel amplification reaction to control for the quality and quantity of interrogated cDNA was performed using a primer-probe combination specific for the housekeeping gene GUS-B, and an inventoried ABI Taqman assay (HS99999908_m1). cDNA generated using RNA isolated from the melanoma cell line, A375 (ATCC) was used as a reference sample. Data were reported as a relative quantity (RQ) value.

Single-cell RNA-sequencing methods Cell Sorting

Cells were thawed at 37C and resuspended in media (RPMI 1640 with 10% FBS). Cells were stained for 15 minutes on ice with the following antibodies: CD4-PE (Tonbo Biosciences, 50-0048, 1:200), CD8-Pacific Blue (Thermo Fisher, MHCD0828, 1:200 dilution), as well as propidium iodide (PI). Live single cells that were either CD4 or CD8 positive were sorted. Approximately50,000 – 200,000 cells per condition were sorted. Single-cell RNA-sequencing

Single-cell RNA-sequencing libraries were generated with the 10x Genomics 5’ scRNA-seq kit following the standard 10x protocol unless otherwise noted. Briefly, sorted cells were washed once using 0.04% BSA in PBS, resuspended, and counted; and 16,500 cells were loaded onto the Chromium instrument with the intention of capturing 10,000 cells. To enrich for detection of the TRAC mRNA, 2 pmol of primer (5’-AAGCAGTGGTATCAACGCAGAGTACCGTCATGAGCAGATTAAACC-3’) directed against TRAC and containing a common overhang sequence allowing cDNA amplification was spiked into the reverse transcription mix (i.e., in addition to the standard poly-dT primer) during droplet encapsulation.

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cDNA amplification and generation of the gene expression libraries were carried out as per the standard 10x protocol. Following cDNA amplification, 5 uL of the SPRI cleanup product was used as input for the following separate PCR reactions: first-round against NY-ESO-1 TCR, TRAC, TRBC, and PDCD1. These reactions used a Forward (F) primer (5’- AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTC-3’) against the 10X bead sequence added during the template-switch reaction, and a gene-specific Reverse (R) primer: NY-ESO-1 TCR (5’- GGCTCGGGAAGAAGGTATCG-3’), TRAC (5’- TTCAAAGCTTTTCTCGACCAGC-3’), TRBC (5’- CCACAGTCTGCTCTACCC-3’), PDCD1 (5’- GAAGCTCTCCGATGTGTTGG-3’). 15 cycles of PCR were performed with an annealing temperature of 67C using NEBnext Ultra II Q5 MasterMix (M0544L) following manufacturer suggested reaction conditions. A second-round PCR reaction was used to increase specificity, with a single F primer (5’- AATGATACGGCGACCACCGAGATCT-3’) and gene-specific R primers: NYESO (5’- GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTTCATGGTGGCATTCTCCCC-3’), TRAC (5’- GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTGACCAGCTTGACATCACAGG -3’), TRBC (5’- GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTACAGTCTGCTCTACCCCAGG-3’), PDCD1 (5’- GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTCGATGTGTTGGAGAAGCTGC-3’). 5 uL of PCR1 was used as input for PCR2, with annealing at 63 degrees, again using NEBnext Ultra II Q5 MasterMix and manufacturer suggested reaction conditions. PCR2 was cleaned up using Zymo DNA Clean and Concentrator 5 columns (Zymo Research, D4004) and eluted into 30 uL. TRBC primers for both rounds were designed to amplify both TRBC1 and TRBC2. The products of these reactions were then used as input for a i7 indexing reaction following the standard 10X protocol for sample indexing of gene expression libraries, as if the target-specific PCR libraries were gene expression libraries after adapter ligation and cleanup. Unique i7 indexes were used for all 5 reactions (gene expression, NY-ESO-1 TCR, TRAC, TRBC, PDCD1) for each sample.

Libraries were quantified using the KAPA Library Quantification Kits for Illumina (Roche, KK4854) and the size distribution was analyzed using an Agilent Tapestation and/or Bioanalyzer. Libraries were sequenced using a HiSeq 4000 with a 175x125 (R1xR2) read configuration, with the exception of TRAC, which was sequenced on a MiSeq using a 26x250 read configuration. Gene expression libraries were sequenced at a depth of 20,000-50,000 reads / cell, and target (NY-ESO-1 TCR, TRAC, TRBC, PDCD1) were sequenced at a depth of 100-1,000 reads / cell. Analysis of gene expression libraries

Gene expression sequencing libraries were processed using Cellranger v3.0.2. The transgene sequence of the NY-ESO-1 TCR was added to the normal human reference genome as an additional entry in the hg38 fasta file, with the entire transgene added as a new gene in the reference gtf file. The output of this was processed using Seurat v3.1.0 using the recommended Seurat SCTransform workflow. A minimum of 250 genes detected / cell and maximum of 20% mitochondrial reads were used to exclude low-quality cells, and the effect of cell cycle, percent mitochondrial reads, and number of genes detected were regressed out at the SCTransform step. The datasets from the three time points (infusion product (IP), Day (D)10, and D113) were then

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merged using the SelectIntegrationFeatures, PrepSCTIntegration, FindIntegrationAnchors, and IntegrateData commands in Seurat.

For Figure 6D, the merged dataset was clustered in Seurat using FindNeighbors (dims=1:30) and FindClusters (resolution=.65). Then, NY-ESO-1 TCR positive cells (i.e., >= 1 UMI count) were shown, split by time point (IP, D10, or D113). Thus, clustering was performed on the entire dataset, but only the NY-ESO-1 TCR+ cells were shown. Normalized expression was shown for NY-ESO-1 TCR and TCF7 from 0 to the maximum value.

For Figure 6E, NY-ESO-1 TCR positive cells from each time point were compared against each other. For this comparison, only NY-ESO-1 TCR+ cells falling in the primary CD4+ cluster were compared. Differentially expressed genes were identified using the FindMarkers command. Ribosomal and mitochondrial genes were excluded from this analysis (any genes beginning with “RPL,” “RPS,” or “MT-“ were excluded). The top 20 upregulated and top 20 downregulated genes from each pairwise comparison (IP vs. D10, IP vs. D113, and D10 vs. D113) were then shown, and scaled gene expression data was used to generate the data show in the heat map. Single cell analysis of gene mutations

Analysis of mutations was performed using a set of custom functions written in Python. This workflow was largely designed to replicate the workflow of Cellranger, as listed on the 10x Genomics website, but specifically retaining mutational information of target genes. Briefly, reads were first read in, and reads whose beginning did not align to the target sequence were excluded. Reads were aligned against a common 20-25 base pair sequence at the start of each expected amplicon to create a common start position, and then a 25 bp region centered at the CRISPR sgRNA cut site was extracted from each read (i.e., to focus analysis on mutations specifically centered at the expected cut site). Then, reads were aggregated by cell barcode, then UMI. Barcodes that did not have an exact match in the Cellranger output were compared against the list of Cellranger-identified barcodes, and those within 1 edit distance were collapsed to that barcode to account for sequence or PCR errors. Everything was then aggregated by specific read sequence (i.e., indel sequence), and similar UMIs (within 1 edit distance) were collapsed (the likelihood of the same indel sequence having the same UMI across multiple cells is very low, so very similar UMIs are likely due to sequencing artifacts). Then, for a given indel + UMI combination, reads corresponding to similar cell barcodes (within 1 edit distance) were collapsed to the most common cell barcode for that indel + UMI combination, again to account for sequencing artifacts. The result was then re-aggregated by cell barcode, then UMI, then indel; and collapsed to UMI counts (versus raw read counts) for a given cell, such that a given cell had a list of UMI counts associated with a given indel sequence. Cells where multiple indel sequences were identified at similar abundance (i.e., presumably due to contamination or low-quality cells) were excluded. Then, for each cell, the UMI counts and particular indel sequence associated with that cell were reported, allowing classification of each cell as either wild-type or mutant, as well as the number of detected mRNA molecules supporting that classification.

There are some technical limitations to this approach. First, it is difficult to exclude the possibility that a cell in which a wild-type allele is detected does not have an undetected mutant allele, and vice versa. Second, in the case where we detect both a wild-type and mutant allele, which was in a minority of cells, cells were classified as mutant, rather than excluding the cells from analysis or designating heterozygous cells as a separate category.

For Figure 6A, only cells with reads for PDCD1, TRAC, and TRBC, that were further positive for the NY-ESO-1 TCR, are shown. As the coverage for each of the three genes is limited

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due to dropout in scRNA data, there are fewer cells with all three genes detected than cells in which any one individual gene was detected. Cells where both a mutant and wild-type allele were detected were classified as mutant for the purposes of this analysis, as well as all other similar analyses.

For Figure 6B, for each gene and time point combination, the set of cells with reads for that gene was identified. Then, the proportion of wild-type and mutant/heterozygous cells was calculated. As a result, the set of cells analyzed for TRAC, TRBC, and PDCD1 is not necessarily overlapping, due to differences in coverage. Moreover, the set of cells for which reads were obtained for all three genes is a smaller subset than for any single gene. This results in the cell proportion numbers being approximate and best estimates from the single-cell RNA-sequencing data, but are not intended to be ground-truth exact numbers. For the proportion of NY-ESO-1 TCR positive cells, all cells with high-quality gene expression data (i.e., at least 250 genes detected, and no more than 20% mitochondrial reads) were included.

For Figure 6C, the set of cells with reads for TRAC, TRBC, and PDCD1 was analyzed for the IP and D113. This set of cells was split into NY-ESO-1 TCR positive and negative subsets. Data from D10 was not reported due to low coverage of PDCD1. Importantly, due to limitations in the number of cells sampled, the lack of identified cells with a given set of mutations does not necessarily indicate that that population does not exist. Thus, for D113 NY-ESO-1 TCR+ cells, no cells with three mutations (i.e., in PDCD1, TRAC, and TRBC) were identified. This does not indicate that such a cell (i.e., with four genetic alterations) does not exist; but rather that the assay had limited power to detect such a cell. The analysis was done to maximize our ability to report on the cells with genetic alterations that we did detect. Pharmacokinetics of NYCE cells

The numbers of marked cells (per uL blood) using WBC were measured longitudinally over time as specified by the trial protocol. Thirty-eight (n = 38) observations from day of infusion were available for modelling (n = 10 for UPN07, n = 15 for UPN35, n = 13 for UPN39). A log10 transformation was applied to the measurements with 0 if no cells were detected. The log10 transformed outcomes were plotted against days since infusion (day 0) as an x-axis for each subject separately. Individual pharmacokinetics patterns were first examined using a series of subject-specific piecewise linear models assuming a linear slope for the expansion phase and a separate linear slope for the decay phase after peak values were reached at the change point. We assumed a linear model due to a limited sample size in this analysis. The change points were selected according to the peak values observed, falling between day 7 and day 21. A common change point for all subjects at day 14 was also considered. Estimated slopes before and after the change point and the estimated peak values at the change point were reported for each subject separately. Between-subject variations in the parameter estimates were reported using descriptive statistics. Time to decay ½ of the peak value on log10 scale is estimated by (estimated peak value)/(2*the slope after the change point). Time to decay ½ of the peak value on original scale (e.g., from 100 to 50 on the original is equivalent to a change from 2 to 1.699 on log10 sale) is estimated by log10(2)/(the slope after the changed point) with log10(2)=0.301. Next, we fitted a piecewise linear mixed effects model using data combined from all 3 subjects with random effects to allow individual estimates (e.g., peak values, slope before, and slope after the change point) that deviate from the population average estimates. A common change

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point at day 14 was used for the mixed effects modelling. Because the mixed model included random slopes suggested no significant random slopes (i.e., although we recognize statistical power is low to detect smaller between-subject variations with limited sample size here), we followed the parsimonious principle to consider a simpler model that contains only a random intercept. The model was parametrized in the way such that the intercept corresponds to the peak values. Parameter estimates for the random intercept only model and time-to-half decay post the estimated peak values were calculated as described above. Observed longitudinal profile of NYCE cells (per uL blood) on log10 scale for 3 subjects:

Subject-specific piecewise linear model with different change points (gray: observed values, blue: individual fitted values):

-10

12

log1

0(m

ark

ed c

ell p

er u

l blo

od)

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Parameter estimates from the subject-specific piecewise linear model with different change points:

-10

12

log1

0(m

arke

d c

ell p

er u

l blo

od)

-10

12

log1

0(m

arke

d ce

ll pe

r ul

blo

od)

Change point used: Day 21 for 07, 35 Day 7 for 39

Change point used: Day 14 for all

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UPN Day Slope before (95%CI)

Value at day (95%CI)

Slope after (95%CI)

Peak/2*slope post

(95%CI)

Log10(2)/slope post

(95%CI)

R2

25416-07

21 0.061 (0.007,0.115)

2.294 (1.536,3.051)

-0.017 (-0.036,0.001)

66.3 (18.7,113.9)

17.4 (2.2,32.6)

0.53

14 0.997 (0.035,0.165)

2.234 (1.601,2.797)

-0.015 (-0.028,-0.001)

75.4 (27.4,123.4)

20.3 (5.0,35.7)

0.67

25416-35

21 0.018 (-0.004,0.041)

0.770 (0.458,1.081)

-0.003 (-0.005,-1.4e-6)

151.1 (47.4,254.7)

119.1 (11.9,224.3)

0.30

14 0.032 (-0.001,0.064)

0.772 (0.495,1.050)

-0.002 (-0.005,-0.001)

156.2 (54.6,257.8)

121.8 (20.1,223.5)

0.38

25416-39

7 0.238 (0.120,0.356)

1.855 (1.367,2.343)

0.0001 (-0.007,0.007)

----- ----- 0.72

14 0.109 (0.035,0.184)

1.981 (1.316,2.647)

-0.001 (-0.010,0.008)

965.9 (0,8278.5)

293.5 (0,2574.9)

0.58

Descriptive statistics in the parameter estimates from the subject-specific model with the common change point at day 14:

Day Slope before Value at day Slope After

Mean (SD) 14 0.379(0.536) 1.662(0.781) -0.006(0.008) Min-Max 14 0.032 to 0.0997 0.772 to 2.234 -0.015 to -0.001

Range 14 0.965 1.462 0.014 Piecewise linear mixed effects model using combined data (black: observed values, gray: estimated population level values, blue: prediction of individual values):

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Parameter and random effects estimates for the random intercept only model:

UPN Slope before day 14 (95%CI)

Value at day 14 (95%CI)

Slope after day 14 (95%CI)

Peak/2*slope post (95%CI)

Log10(2)/slope post (95%CI)

25416-07 ----- 1.902 (1.304,2.499)

----- ----- -----

25416-35 ----- 1.073 (0.496,1.650)

----- ----- -----

25416-37 ----- 1.871 (1.287,2.454)

----- ----- -----

Population average

0.076 (0.046,0.107)

1.616 (1.088,2.142)

-0.004 (-0.007,0.001)

225.18 (49,400.94)

83.93 (15.12,152.74)

(1) Piecewise linear mixed effects model using all 3 subjects data combined. Allow individual estimates (i.e., peak values; slope before, and slope after) to deviate from the population estimates using random effects.

Use day 14 as the change point (black: observed values, gray: estimated population level values, blue: prediction of individual values)

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Parameter estimates (random intercept and random slopes model):

UPN Slope before day 14 (95%CI)

Value at day 14 (95%CI)

Slope after day 14

(95%CI)

Peak/2*slope post

(95%CI)

Log10(2)/slope post

(95%CI) 25416-

07 0.074 1.896(1.389,2.

403) -0.004 237.00 75.26

25416-35

0.074 1.091(0.581,1.592)

-0.004 136.38 75.26

25416-39

0.077 1.812(1.305,2.319)

-0.001 906.00 301.03

Population

average 0.075

(0.045,0.105) 1.600

(1.093,2.107) -0.003

(-0.007,0.001) 244.11

(0,536.38) 91.87

(0,205.94) Because there is no clear evidence that the 3 patients have significantly different slopes (i.e., random slopes), although statistical power is low to detect smaller between-subject variations with limited sample size here, we thus considered a simpler model (i.e., follows the parsimonious principle) that contains only random intercept. The model was parametrized in the way such that intercept corresponds to the peak values. (black: observed values, gray: estimated population level values, blue: prediction of individual values)

-10

12

log1

0(m

arke

d c

ell p

er u

l blo

od)

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Parameter estimates (random intercept model only):

UPN Slope before day 14

(95%CI)

Value at day 14

(95%CI)

Slope after day 14

(95%CI)

Peak/2*slope post

(95%CI)

Log10(2)/slope post

(95%CI)

25416-07

----- 1.902 (1.304,2.499)

----- ----- -----

25416-35

----- 1.073 (0.496,1.650)

----- ----- -----

25416-37

----- 1.871 (1.287,2.454)

----- ----- -----

Population

average

0.076(0.046,0.107)

1.616 (1.088,2.142)

-0.004 (-0.007,0.001)

225.18 (49,400.94)

83.93 (15.12,152.74)

The differences in the parameter estimates are minimal, compared to the above estimates (i.e., further supporting no random slopes are needed). Because this simpler random intercept only model estimates fewer parameters, we get a more stable model and estimates that are more precise.

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Statistical analysis Statistics for NYCE T cell product characterization data were analyzed using GraphPad Prism software (GraphPad Software, Inc.). Normality was first assessed using the D’Agostino and Pearson normality test. For comparisons between two independent conditions, statistical significance was determined using an unpaired student’s t-test. A paired student’s t-test was applied when samples from the same subject were being compared at different time points, as indicated in the figure legends. P values were considered significant if less than 0.05. Asterisks used to indicate significance correspond to P < 0.05*, P < 0.01** and P < 0.001***. Supplemental Text: iGUIDE

Here we analyzed 8 specimens from the four final products treated with the three

sgRNA/Cas9 RNPs, which recognize four genomic sites. A total of 3,399,560 reads were generated, which represent 76,265 distinct incorporated double-stranded oligo-dinucleotides (dsODNs) with associated segments of flanking DNA.

The percentage of on target gene edits can be scored in several ways. The total percent of

reads aligning near the predicted cut site can be scored (marked “Total” in the Table below), but by this measure rare and potentially artifactual reads can raise the apparent off-target cleavage frequency. In addition, a background is expected from naturally occurring double strand DNA breaks. For this reason, it is desirable to apply more stringent filtering criteria before accepting sites as genuine locations of sgRNA/Cas9 cleavage. In the Table below we consider results after applying three different filtering criteria:

- Alignment Pileups: unique alignments that overlap with each other or “pileup”, suggesting

a nearby location may be targeted for a double strand break (DSB). For this analysis, any group of 3 or more unique alignments were considered as a pileup cluster.

- Flanking Paired Alignments: alignments can be found on either side of a DSB, and

therefore identifying flanking alignments suggests a DSB could be found between the paired alignments. Flanking alignments were searched for in these data allowing up to 200 bp spacing.

- Target Matched Alignments: searching for matches to the sgRNA-targeted sequences

upstream of the incorporation site can be an indicator of targeted nuclease activity. However, sgRNAs show a variety of behaviors when annealing to target DNA, not all of which can be easily predicted. Here nucleotide sequences matching target sequences were searched for up to 100 bp upstream from the incorporation sites and required to have no more than 6 mismatches in the target sequence and/or PAM sequence.

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A comprehensive analysis of the distributions of mapped cleavage sites (dsODN positions)

is shown in Figure S4. Incorporations are shown for the positive (red) and negative (blue) orientations. The percentage in the bottom right corner of each plot is an estimate of the number of incorporations associated with the on-target site cleavage (based on pileups) captured within the allowed window of 100 bps in either direction along the genome.

Figure 4C and Figure S5 summarize major off target cleavage sites for TRAC, TRBC and

PDCD1 gRNA marked by dsODN incorporation. Potential off-target sites were filtered based on sequence similarity to the sgRNA recognition sequences within 100 bp upstream of incorporation sites, allowing six mismatches (“Matched” criteria). “Abund” indicates the total number of alignments associated with each site. “Gene ID” indicates the nearest gene. Symbols after the gene name indicate: * that the site is within the transcription unit of the gene, ~ the gene appears on the cancer-association list, ! and that the gene appears on a focused human lymphoma gene list. Gene lists used were Bushman group allOnco v3 and Human Lymphoma, available at http://www.bushmanlab.org/links/genelists .

ON TARGET

Specimen Subject Condition AlignmentsTotal

(percent)Pileup

(percent)Paired

(percent)Matched (percent)

iGSP0148 UPN27 sgRNA/CAS9 11,139 68 86.56 98.73 98.44

iGSP0149 UPN27 Mock 2,731 0 0 0 0

iGSP0150 UPN35 sgRNA/CAS9 10,061 60.58 84.66 98.86 98.43

iGSP0151 UPN35 Mock 12,280 0 0 0 0

iGSP0176 UPN39 sgRNA/CAS9 5,071 35.81 62.56 98.63 95.93

iGSP0177 UPN39 Mock 16,557 0 0 0 0

iGSP0241 UPN07 sgRNA/CAS9 11,754 71.09 86.87 98.58 98.35

iGSP0242 UPN07 Mock 6,672 0.01 0 0 4.55

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Figure S1 Figure S1. NYCE T cell manufacturing process and NY‐ESO‐1 vector map. (A) A schematic representation of the NYCE T cell manufacturing process is shown. (B) NY-ESO-1 TCR (8F) plasmid map and vector design are shown.

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Figure S2 Figure S2. Clinical trial protocol schematic. The overall protocol is shown with scheduled staging and biopsy procedures. ICD = informed consent document.

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Figure S3 Figure S3. Consort statement/diagram. An overview of the number of patients screened, enrolled and infused on the protocol is shown. Of the 32 eligible patients after screening, 16 did not express the target antigen, 4 declined for other therapy, 3 died prior to enrollment, 1 withdrew consent and 2 experienced disease progression that rendered them ineligible for infusion. IHC = Immunohistochemistry.

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Figure S4 Figure S4. iGUIDE distribution of cleavage for TRAC, TRBC and PDCD1. Distribution of inferred positions of cleavage and dsODN incorporation at an on-target loci for UPN07, UPN27, UPN35 and UPN39. Incorporations in different strand orientations are shown on the positive (red) and negative (blue) y-axis. The percentage in the bottom right corner is an estimate of the number of incorporations associated with the on-target site (based on pileups) captured within the allowed window of 100 bps.

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Figure S5 Figure S5. Abundance of on- and off-target cleavage sites for TRBC and PDCD1. Sequences of sites of cleavage and dsODN incorporation are shown for TRBC (A) and PDCD1 (B), annotated by whether they are on-target or off-target (“Target”); the total number of unique alignments associated with the site (“Abund”); and an identifier indicating the nearest gene (“Gene ID”). Symbols after the gene name indicate: * that the site is within the transcription unit of the

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named gene; and ~ the gene appears on the allOnco cancer-associated gene list. This analysis is composite pooled data from the four final manufactured products.

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Figure S6

Figure S6. Optimization of assays to detect chromosomal translocations. Translocation assay results on healthy donor DNA edited at three target loci (TRAC, TRBC, PDCD1) with variable amounts of gRNA. Grid shows primer combinations used. Symbols indicate different target DNAs. The assays were conducted in triplicate and the means plotted. Lower Ct values (y-axis) indicate more product, except for values plotted at 0, indicating no amplification.

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Figure S7

Figure S7. scRNAseq pipeline for analysis of CRISPR-edited NYCE T cells. (A) Workflow for processing NYCE T cell samples for scRNAseq is shown. (B) Process of barcoding cDNA molecules and generating target-specific libraries for next-generation sequencing

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is depicted. UMI = unique molecular identifier; TSO = template switch oligo. (C) The procedure used for classifying single cells as wild-type or mutant is listed.

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Figure S8 Figure S8. scRNAseq of PDCD1 in cells expressing NY ESO-1 TCR. Heat map of NY-ESO-1 TCR+ cells from UPN39 are shown. Reads in 52 cells at baseline (infusion product), 8 cells at Day 10, and 20 cells isolated from blood 4 months (Day 113) after infusion are shown. ~25% of the TCR+ cells at baseline had mutations in PDCD1, and this decreased to 5% at month 4. PDCD1status indicated: Blanched almond, wild-type; Red, mutant.

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Figure S9 Figure S9. NY-ESO-1 and LAGE-1 antigen expression and NYCE T cells detected in bone marrow. Transcripts for tumor antigens NY-ESO-1 and LAGE-1 were evaluated by qRT-PCR in bone marrow at baseline and then after NYCE T cell product infusion. NY-ESO-1 TCR-expressing T cells were quantified by qPCR analysis to detect the WPRE sequences present in the lentivirus backbone. UPN07 (top) and UPN35 (bottom). ND = not detected; NP = assay not performed

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Figure S10

Fig. S10. NY-ESO-1 stimulation promotes the preferential expansion of TCRV8.1 CD8+ T cells transduced with NY-ESO-1 TCR in post-infusion samples.

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(A) Schematic showing expansion of NY-ESO-1 TCR+ T cells from post-infusion patient samples. PBMC collected pre- and post-infusion were stimulated in the presence of NY-ESO-1 peptide (10ug/mL, SLLMWITQV) and cultures were supplemented with IL-2 every other day. At day 10, cells were harvested, counted and stained with anti-CD8 and anti-TCRV8.1 antibodies and analyzed by flow cytometry. Expanded T cells were tested for cytotoxicity against NY-ESO-1+ or NY-ESO-1 peptide-loaded tumor targets. (B) Level of NY-ESO-1 TCR transgene detected (i.e., by qPCR) in expansion cultures and in the peripheral blood of patients infused with CRISPR-edited NYCE T cell products.(C) Representative flow cytometry showing an increase in the frequencies of TCRV8.1-expressing cells in expanded T cellsamples.

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Table S1. NYCE T cell product release specifications.

Assay Release Specification Cell viability on sentinel vial >70% Transduction efficiency by flow cytometry (Net Vβ8.1 surface expression)

> 2%

Residual bead number < 100 beads / 3e6 cells Endotoxin Negative Mycoplasma Negative BACTEC culture No growth at day 7 IL-2 independent growth (long-term culture) No proliferation in absence of IL-2 Fungal culture No growth at day 7

Transduction efficiency for transgene integration (qPCR WPRE copy number)

> 0.02 - < 5 average copies/cell

RCL (VSVg copy number) Decreasing from day 5 to post-

harvest or < 50 average copies/ug DNA

Disruption of TRAC gene (TCR-alpha editing) Detectable disruption Disruption of TRBC gene (TCR-beta editing) Detectable disruption Disruption of PDCD1 gene Detectable disruption

Residual Cas9 protein Decreasing Cas9 concentration from day 0 to harvest

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Table S2. NYCE T cell final product characterization and dosing.

Subject ID Subject

Weight (kg) Total Number

of T cells1

NY-ESO-1 TCR

Transduction Efficiency2

Number of NY-ESO-1

TCR Transduced

Cells

CD4:CD8 Ratio

UPN07 59.9 6.00 × 109 4.5% 3.71 × 108 0.24 UPN273 93.9 9.40 × 109 2.4% 2.91 × 108 0.12 UPN35 50.1 5.00 × 109 4.1% 6.01 × 107 0.25 UPN39 63.2 6.30 × 109 1.4% 7.14 × 108 1.09

1Protocol specified dose was 1.00 × 108 cells/kg. 2Calculated by Vβ 8.1 staining, with background signal from untransduced control cells subtracted. 3Product not infused.

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Table S3. Off-target gene editing in NYCE T cell infusion products identified by iGUIDE.

gRNA / Subject

ID Gene Processes

Known Disease

Association Expression Notes

PDCD1 / none

N/A N/A N/A N/A N/A No off-target genes with this sgRNA

TRAC / UPN07 UPN27

CLIC2*

Chloride intracellular channel 2

Chloride channel. This protein plays a role in inhibiting the function of ryanodine receptor 2

CLIC2 mutations associated with mental retardation, X-linked, Syndrome 32

Transcripts detected in all tissue; Cytoplasmic protein expression in several tissues, including immune cells and epithelial cells

*Site within transcription unit

TRBC / UPN07 UPN27 UPN35 UPN39

ZNF609

Zinc Finger Protein 609

Transcriptional regulator that is a positive regulator of RAG1, and possibly RAG2, transcription. (PMID: 23076336)

No known disease association

Transcripts detected in all tissues; Nuclear and cytoplasmic protein expression in most tissues.

ZFN609 also encodes a circular RNA with functions in myogenesis (PMID: 28344082). The off-target edit from TRBC gRNA disrupts an intron in the linear gene but not in the circular RNA coding sequence.

TRBC UPN07 UPN27 UPN35 UPN39

LINC00377

Long intergenic non-protein coding RNA 377

N/A

Expression associated improved prognosis in breast cancer

Low level expression in spleen

PMID:31850229

N/A = not available

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Table S4. scRNAseq Metadata Tables (S4a-c) See separate file: “20200126_Table S4_FINAL.xls”

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Table S5. Differentially expressed genes in NY-ESO-1 TCR+ T cells.

a. Day 0 Infusion Product vs. Day 10 Post-infusion b. Day 10 Post-infusion vs. Day 0 Infusion Product c. Day 0 Infusion Product vs. Day 113 Post-infusion d. Day 113 Post-infusion vs. Day 0 Infusion Product

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Gene p_val avg_logFC pct.1 pct.2 p_val_adjDYNLL1 1.05E-74 1.09711983 0.836 0.056 1.60E-70NDFIP2 1.77E-73 1.10765521 0.754 0.02 2.70E-69

TMSB4X 1.22E-66 1.27911908 1 1 1.86E-62ARPC5 4.01E-65 1.12520734 0.948 0.263 6.11E-61

S100A11 2.89E-63 1.6467516 0.993 0.809 4.41E-59STMN1 8.54E-63 2.02257849 0.776 0.082 1.30E-58RAC2 5.40E-62 1.21436636 1 0.834 8.23E-58PPIA 8.29E-62 1.21177179 1 0.997 1.26E-57

GAPDH 9.15E-62 1.28403478 1 1 1.39E-57ACTR3 1.77E-61 1.15142767 0.97 0.375 2.70E-57PRDX1 3.80E-61 1.40305621 0.955 0.352 5.80E-57

TPI1 2.55E-58 1.24206349 0.993 0.719 3.89E-54IL32 3.94E-58 1.71683716 1 0.952 6.01E-54

SELPLG 1.49E-57 1.37191503 0.881 0.255 2.27E-53ATP6V0E1 4.93E-57 0.99916527 0.918 0.273 7.53E-53HNRNPF 1.76E-56 1.21935575 0.963 0.429 2.69E-52

CST7 3.16E-56 1.08584456 0.843 0.151 4.82E-52FTL 2.05E-55 1.32610855 1 0.995 3.13E-51

ABRACL 2.19E-53 0.99664966 0.985 0.469 3.34E-49MYL6 6.74E-53 0.90782934 1 0.987 1.03E-48

MRPL51 1.17E-52 0.8573495 0.813 0.163 1.78E-48CLIC1 2.56E-52 1.00899747 1 0.842 3.90E-48CFL1 5.66E-51 0.8662298 1 0.977 8.63E-47

TRAPPC1 1.36E-50 0.93390123 0.948 0.464 2.07E-46ENO1 9.03E-50 1.12637295 1 0.778 1.38E-45TXN 3.54E-49 1.17524038 0.985 0.666 5.40E-45

CLEC2D 7.24E-49 0.94019263 0.799 0.184 1.10E-44GPR171 8.67E-49 0.69468999 0.59 0.036 1.32E-44H2AFZ 1.23E-48 1.5734975 0.985 0.653 1.88E-44BST2 3.12E-48 0.92514337 0.933 0.365 4.76E-44

ACTG1 1.11E-47 0.87804341 1 0.992 1.69E-43MYL6B 3.67E-47 0.6763553 0.627 0.059 5.60E-43CAP1 6.38E-47 0.91282133 0.948 0.52 9.73E-43

HNRNPA2B1 7.50E-47 1.06806966 0.985 0.832 1.14E-42ATP5MC3 7.83E-47 0.9309322 1 0.707 1.19E-42

SERF2 8.38E-47 0.68921873 1 0.997 1.28E-42CORO1A 1.55E-46 0.87314668 0.993 0.98 2.36E-42

CD53 6.04E-46 0.90963273 0.888 0.337 9.22E-42TRMT112 1.78E-45 0.8574319 0.925 0.408 2.72E-41

IL2RA 5.59E-45 0.97018579 0.612 0.066 8.53E-41

Table S5a. Differentially expressed genes in NY-ESO-1 TCR+ T cells (Day 0 Infusion Product vs. Day 10 Post-infusion)

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TRAF3IP3 7.75E-45 0.89856878 0.948 0.487 1.18E-40LCK 8.94E-45 0.88298419 0.978 0.635 1.36E-40RAN 1.18E-44 0.99436029 0.97 0.778 1.80E-40

PSMB9 1.50E-44 1.02156439 0.925 0.462 2.30E-40OAZ1 8.36E-44 0.83177198 0.985 0.824 1.28E-39

C14orf119 2.65E-43 0.51254283 0.47 0.01 4.04E-39TMBIM6 3.67E-43 0.89833681 0.918 0.569 5.61E-39

DBI 4.95E-43 0.88759502 0.97 0.592 7.54E-39B2M 1.97E-42 0.49288291 1 1 3.00E-38

NEDD8 3.42E-42 0.80112489 0.94 0.536 5.21E-38

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Gene p_val avg_logFC pct.1 pct.2 p_val_adjEEF1A1 5.64E-64 0.85876097 1 1 8.61E-60HLA-C 6.90E-54 0.83146851 1 1 1.05E-49

EIF1 4.53E-52 0.83517589 1 1 6.91E-48HLA-B 4.60E-47 0.66707693 1 1 7.01E-43ZFP36 3.60E-43 1.08203574 0.916 0.328 5.48E-39CIRBP 2.88E-40 0.8539347 0.957 0.604 4.39E-36PTMA 3.47E-39 0.67669319 1 0.993 5.30E-35FTH1 4.56E-39 0.93616703 0.931 0.5 6.96E-35JUN 5.55E-35 1.10281541 0.872 0.321 8.46E-31

ZFP36L1 1.78E-34 0.9499618 0.893 0.403 2.71E-30STK17A 4.81E-34 0.75198141 0.742 0.119 7.33E-30TSC22D3 4.12E-30 0.71728866 0.732 0.142 6.29E-26

TPT1 2.89E-29 0.37178075 1 1 4.40E-25CD69 4.33E-29 0.9060108 0.76 0.261 6.61E-25

PIK3IP1 5.87E-29 0.66117902 0.758 0.194 8.95E-25BTG1 1.27E-28 0.74934767 0.969 0.634 1.93E-24

PTPRCAP 2.76E-25 0.65156651 0.921 0.604 4.21E-21JUNB 1.04E-23 0.62768306 0.615 0.104 1.59E-19DDIT4 7.06E-23 0.66455696 0.842 0.433 1.08E-18

MIF 1.09E-22 0.55498378 0.962 0.724 1.67E-18EPC1 2.52E-22 0.59392187 0.806 0.381 3.85E-18CD44 4.98E-22 0.57463071 0.883 0.515 7.60E-18DDX5 4.56E-21 0.56546307 0.972 0.843 6.95E-17FAU 2.03E-20 0.2737835 1 1 3.10E-16

SNHG8 3.09E-20 0.54092989 0.781 0.396 4.71E-16ZFAND2A 4.68E-20 0.43987201 0.526 0.067 7.14E-16STK17B 2.15E-19 0.55552869 0.773 0.381 3.28E-15SARAF 2.62E-19 0.51498172 0.827 0.455 3.99E-15COX5B 3.51E-19 0.49593765 0.661 0.231 5.36E-15DDIT3 1.59E-18 0.49405167 0.515 0.082 2.43E-14CRIP1 2.28E-18 0.65432967 0.906 0.642 3.48E-14EIF3F 2.34E-18 0.4426147 0.597 0.164 3.57E-14

LEPROTL1 2.75E-18 0.54209903 0.903 0.664 4.19E-14DNAJB1 3.01E-18 0.50274108 0.628 0.209 4.59E-14CXCR4 1.12E-17 0.57363274 0.821 0.44 1.71E-13

BHLHE40 2.54E-17 0.49355396 0.679 0.269 3.88E-13TNFAIP3 3.03E-17 0.45538614 0.449 0.037 4.62E-13RBM39 3.18E-17 0.48072185 0.89 0.694 4.85E-13HAUS3 7.00E-17 0.44345553 0.423 0.03 1.07E-12USP3 7.20E-17 0.43329737 0.643 0.246 1.10E-12

Table S5b. Differentially expressed genes in NY-ESO-1 TCR+ T cells (Day 10 Post-infusion vs. Day 0 Infusion Product)

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SPOCK2 8.48E-17 0.50888535 0.865 0.597 1.29E-12RNF125 1.61E-16 0.4860712 0.551 0.157 2.46E-12

AL118516.1 2.57E-16 0.40455273 0.413 0.03 3.91E-12AC243960.1 3.57E-16 0.49452521 0.679 0.284 5.45E-12

IL7R 4.34E-16 0.41823284 0.778 0.321 6.62E-12CCNL1 5.57E-16 0.48135746 0.696 0.351 8.50E-12RGS16 6.94E-16 0.47019258 0.375 0.007 1.06E-11NOP53 8.88E-16 0.38665849 0.967 0.873 1.35E-11PCGF5 1.06E-15 0.39497795 0.497 0.104 1.61E-11

MGAT4A 1.12E-15 0.45689299 0.577 0.187 1.70E-11

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Gene p_val avg_logFC pct.1 pct.2 p_val_adjNDFIP2 1.15E-102 1.12561216 0.754 0.007 1.75E-98STMN1 1.22E-95 2.07478133 0.776 0.029 1.86E-91

TPI1 7.47E-79 1.67708606 0.993 0.423 1.14E-74TXN 8.36E-78 1.6541502 0.985 0.347 1.28E-73

SERF2 5.67E-74 1.71435331 1 0.764 8.65E-70CFL1 8.91E-73 1.64297928 1 0.88 1.36E-68MYL6 1.98E-72 1.53366822 1 0.878 3.02E-68ACTB 2.10E-72 1.69188395 0.993 0.483 3.20E-68

TMSB4X 2.86E-72 1.66861003 1 1 4.37E-68GAPDH 4.21E-72 1.96195502 1 0.987 6.43E-68RAC2 4.29E-72 1.46697798 1 0.731 6.54E-68

DYNLL1 8.51E-72 1.02813886 0.836 0.132 1.30E-67S100A11 1.02E-71 1.8689398 0.993 0.684 1.55E-67

IL32 1.12E-71 2.55620429 1 0.851 1.71E-67ENO1 1.31E-71 1.58612777 1 0.548 2.00E-67B2M 2.01E-71 1.07798724 1 1 3.06E-67PPIA 2.92E-71 1.48826184 1 0.985 4.46E-67CAPG 3.73E-71 0.94872397 0.672 0.045 5.69E-67

TMSB10 2.01E-70 1.62755898 1 0.996 3.07E-66SH3BGRL3 1.45E-69 1.43925935 1 0.955 2.21E-65

MYL6B 7.66E-69 0.70122636 0.627 0.033 1.17E-64PRDX1 1.50E-68 1.41389501 0.955 0.372 2.29E-64CD52 4.61E-67 1.40478717 1 0.956 7.03E-63

IFITM2 3.35E-66 1.47814318 0.993 0.77 5.11E-62CLIC1 1.30E-65 1.20785218 1 0.77 1.99E-61S100A4 1.78E-65 1.95752461 0.993 0.846 2.71E-61LGALS1 4.37E-65 1.95606206 1 0.63 6.67E-61ACTR3 7.96E-65 1.10602654 0.97 0.417 1.21E-60ACTG1 1.87E-64 1.30598143 1 0.976 2.86E-60

FTL 4.64E-64 1.47725108 1 0.993 7.08E-60TRAPPC1 1.48E-63 1.03401632 0.948 0.376 2.26E-59

DBI 2.70E-63 1.12338065 0.97 0.408 4.13E-59PHPT1 3.53E-63 0.77829331 0.612 0.042 5.39E-59

CORO1A 9.69E-63 1.15680022 0.993 0.92 1.48E-58ARPC5 1.05E-62 1.01656257 0.948 0.377 1.60E-58

ARHGDIB 8.50E-62 1.12322883 1 0.967 1.30E-57ARPC1B 9.06E-62 1.11681614 0.955 0.486 1.38E-57ANXA4 4.67E-61 0.53554443 0.493 0.009 7.12E-57ARPC3 6.52E-61 1.04414798 0.993 0.788 9.94E-57

ABRACL 9.88E-61 1.01924082 0.985 0.466 1.51E-56LSP1 6.93E-60 1.21490923 0.985 0.682 1.06E-55

Table S5c. Differentially expressed genes in NY-ESO-1 TCR+ T cells (Day 0 Infusion Product vs. Day 113 Post-infusion)

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CST7 8.01E-60 1.05331822 0.843 0.185 1.22E-55ANXA6 2.18E-59 0.89336057 0.881 0.232 3.32E-55TALDO1 3.07E-59 0.91311972 0.821 0.18 4.69E-55SLC25A5 3.41E-59 1.13773278 0.993 0.8 5.20E-55

RAN 4.58E-59 1.21681233 0.97 0.623 6.98E-55PPP1CA 1.53E-58 0.94994961 0.918 0.325 2.34E-54

ATP5MC3 2.45E-58 1.04486218 1 0.662 3.74E-54NDUFA13 4.56E-58 0.90837444 0.955 0.563 6.95E-54

OAZ1 5.14E-58 1.03380612 0.985 0.733 7.83E-54

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Gene p_val avg_logFC pct.1 pct.2 p_val_adjEEF1A1 2.30E-68 0.87232428 1 1 3.52E-64

IL7R 1.87E-61 1.51433138 0.993 0.321 2.86E-57CIRBP 3.25E-32 0.70607437 0.94 0.604 4.96E-28TPT1 7.19E-32 0.36583596 1 1 1.10E-27

LEPROTL1 5.43E-27 0.67019672 0.918 0.664 8.29E-23PDCD4 3.05E-26 0.60031333 0.782 0.306 4.65E-22PIK3IP1 4.36E-23 0.56773322 0.672 0.194 6.64E-19PABPC1 9.01E-23 0.47483896 0.998 0.985 1.37E-18PIK3R1 1.72E-22 0.57770837 0.662 0.201 2.62E-18SYTL3 6.33E-22 0.63251806 0.813 0.485 9.65E-18SNHG8 1.04E-21 0.51498137 0.802 0.396 1.58E-17PNRC1 7.59E-21 0.55026038 0.822 0.455 1.16E-16CD69 7.38E-20 0.52140713 0.684 0.261 1.13E-15

TSC22D3 1.13E-18 0.44573861 0.581 0.142 1.72E-14HLA-E 1.15E-18 0.43208808 0.998 0.918 1.76E-14

JUN 1.92E-17 0.77760188 0.686 0.321 2.93E-13BTG1 1.34E-16 0.4800704 0.938 0.634 2.05E-12

AL138963.3 2.36E-16 0.94780527 0.514 0.127 3.60E-12TCF7 5.10E-16 0.38008422 0.437 0.052 7.78E-12FOS 7.98E-16 0.64632321 0.459 0.075 1.22E-11EEF2 2.24E-14 0.27706533 1 1 3.41E-10

NOP53 1.33E-13 0.31192355 0.971 0.873 2.03E-09DDIT4 1.45E-13 0.42116127 0.75 0.433 2.21E-09TXNIP 3.58E-13 0.46549593 0.942 0.769 5.46E-09

TNFAIP3 3.70E-13 0.33958227 0.365 0.037 5.65E-09RCC1 6.05E-13 0.36760796 0.679 0.336 9.23E-09

RARRES3 8.16E-13 0.35908457 0.717 0.373 1.24E-08DDIT3 8.94E-13 0.33827838 0.41 0.082 1.36E-08

EEF1B2 1.19E-12 0.26346602 1 1 1.81E-08FTH1 1.27E-12 0.48677515 0.742 0.5 1.94E-08

PFDN5 3.29E-12 0.25078221 1 0.985 5.01E-08ATP5PO 1.21E-11 0.3024407 0.47 0.149 1.85E-07

9-Sep 1.74E-11 0.33208532 0.813 0.537 2.66E-07MATR3.1 2.05E-11 0.35609818 0.701 0.41 3.13E-07CXCR4 6.18E-11 0.44370422 0.721 0.44 9.43E-07

MGAT4A 1.64E-10 0.31672846 0.485 0.187 2.49E-06ZFAND2A 5.73E-10 0.26138266 0.338 0.067 8.75E-06

AC133644.2 6.80E-10 0.3194537 0.31 0.052 1.04E-05DUSP1 1.96E-09 0.36970115 0.437 0.164 2.99E-05

ZFP36L2 2.21E-09 0.27812949 0.383 0.112 3.37E-05

Table S5d. Differentially expressed genes in NY-ESO-1 TCR+ T cells (Day 113 Post-infusion vs. Day 0 Infusion Product)

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NFU1 5.82E-09 0.25705962 0.332 0.082 8.88E-05ATF7IP2 1.64E-08 0.26453577 0.396 0.142 0.00025041CBLL1 2.35E-08 0.25970485 0.472 0.209 0.00035846

ZFP36L1 1.14E-07 0.28884867 0.653 0.403 0.00173529C1orf162 1.89E-07 0.26801168 0.368 0.134 0.00288258

CIR1 2.10E-07 0.26554891 0.485 0.261 0.00320783CCND3 3.27E-07 0.26945516 0.681 0.455 0.00498501ABLIM1 3.44E-07 0.28611249 0.463 0.231 0.00525013NOSIP 1.52E-06 0.31675034 0.771 0.664 0.02322768IL16 2.18E-06 0.25674595 0.722 0.522 0.03325915

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Gene p_val avg_logFC pct.1 pct.2 p_val_adjPTMA 1.11E-146 1.27045053 1 0.94 1.69E-142HLA-B 5.19E-145 1.06601219 1 1 7.92E-141HLA-C 1.55E-143 1.10503337 1 0.998 2.36E-139

TMSB10 2.07E-140 1.26881291 1 0.996 3.15E-136S100A4 3.93E-138 1.59216974 0.997 0.846 6.00E-134CD52 7.86E-134 1.28510246 1 0.956 1.20E-129

HLA-A 2.25E-129 0.93928731 1 0.998 3.43E-125ACTB 4.20E-123 1.40122125 0.967 0.483 6.41E-119MIF 1.19E-121 1.11854602 0.962 0.457 1.82E-117

SERF2 4.48E-119 1.02513458 0.997 0.764 6.84E-115B2M 5.71E-116 0.58510433 1 1 8.72E-112

PTPRCAP 2.58E-115 1.10384683 0.921 0.319 3.94E-111CHCHD2 4.13E-114 0.98450313 0.964 0.528 6.30E-110H3F3A 5.40E-103 0.89185469 0.99 0.74 8.24E-99CRIP1 3.78E-101 1.10721512 0.906 0.328 5.77E-97

SH3BGRL3 1.88E-100 0.88971711 1 0.955 2.87E-96EIF1 2.04E-93 0.59449113 1 1 3.11E-89

ATP5F1E 8.51E-87 0.64910883 1 0.942 1.30E-82ZFP36 8.68E-85 0.92710756 0.916 0.499 1.32E-80

GAPDH 3.73E-83 0.67792023 1 0.987 5.69E-79NME2 1.07E-79 0.72935895 0.768 0.198 1.63E-75LY6E 3.25E-79 0.9329133 0.903 0.483 4.95E-75TMA7 1.38E-75 0.62676827 0.995 0.893 2.11E-71

S100A6 9.24E-75 0.89548197 0.964 0.757 1.41E-70CFL1 2.90E-74 0.77674948 0.977 0.88 4.43E-70

STK17A 8.39E-69 0.65082196 0.742 0.203 1.28E-64GSTK1 6.94E-68 0.64116336 0.99 0.887 1.06E-63IFITM2 1.30E-66 0.82480609 0.964 0.77 1.98E-62COX5B 1.35E-66 0.58807682 0.661 0.142 2.06E-62MYL6 4.90E-66 0.62583889 0.987 0.878 7.48E-62CD3E 7.17E-66 0.56535097 0.997 0.946 1.09E-61

COX6C 6.67E-63 0.59947144 0.967 0.748 1.02E-58SRP14 2.62E-59 0.52034681 0.982 0.875 4.00E-55

RNF125 3.54E-59 0.55623146 0.551 0.085 5.40E-55PHPT1 1.20E-58 0.49810191 0.485 0.042 1.82E-54YBX1 1.14E-56 0.61875728 0.849 0.445 1.74E-52JUNB 2.33E-56 0.59230891 0.615 0.143 3.56E-52

HMGN2 5.76E-56 0.63395216 0.77 0.348 8.79E-52ELOB 1.68E-54 0.52087066 0.944 0.751 2.56E-50ARPC3 4.58E-53 0.54583702 0.969 0.788 6.99E-49

Table S5e. Differentially expressed genes in NY-ESO-1 TCR+ T cells (Day 10 Post-infusion vs. Day 113 Post-infusion)

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HSP90AB1 1.31E-51 0.66773853 0.918 0.735 2.00E-47PPP1R2 7.35E-51 0.46993104 0.548 0.111 1.12E-46CD99 1.64E-50 0.52601355 0.648 0.201 2.51E-46

NDUFB11 2.59E-48 0.53727799 0.735 0.309 3.95E-44STK17B 3.05E-48 0.58683076 0.773 0.385 4.66E-44IFITM1 5.01E-48 0.50241594 0.997 0.985 7.63E-44

NDUFB2 2.77E-47 0.48318782 0.671 0.236 4.23E-43CDKN1A 9.34E-47 0.57591839 0.503 0.096 1.43E-42ZFP36L1 1.03E-46 0.66111313 0.893 0.653 1.56E-42

LSP1 3.46E-46 0.5693337 0.903 0.682 5.27E-42

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Gene p_val avg_logFC pct.1 pct.2 p_val_adjIL7R 5.38E-113 1.09609855 0.993 0.778 8.21E-109

SYTL3 7.47E-62 0.76613936 0.813 0.365 1.14E-57CCR7 2.70E-47 0.49585715 0.466 0.033 4.12E-43FCMR 9.27E-32 0.40402356 0.483 0.128 1.41E-27

MAT2B 3.46E-30 0.35699387 0.519 0.161 5.28E-26PDCD4 3.34E-28 0.40473588 0.782 0.503 5.10E-24TRAT1 9.63E-27 0.34027736 0.555 0.224 1.47E-22TAGAP 2.65E-26 0.36402039 0.526 0.191 4.04E-22

AC133644.2 7.13E-26 0.33282244 0.31 0.036 1.09E-21PTPRC 4.40E-25 0.42278043 0.817 0.62 6.71E-21TCF7 1.33E-24 0.34164874 0.437 0.125 2.03E-20

CCND3 1.84E-24 0.37410666 0.681 0.39 2.80E-20C12orf65 1.90E-24 0.27782632 0.338 0.059 2.89E-20RAP1A 2.10E-24 0.3306953 0.566 0.247 3.20E-20SARS 1.77E-23 0.30942967 0.575 0.247 2.71E-19

ICAM2 1.84E-23 0.31462928 0.416 0.122 2.81E-19UBE2V2 3.53E-23 0.28000302 0.368 0.087 5.39E-19GIMAP4 6.52E-23 0.3417884 0.566 0.265 9.94E-19RIPOR2 4.35E-20 0.31662635 0.655 0.367 6.64E-16TECR 6.61E-20 0.31463336 0.65 0.378 1.01E-15IFI16 9.79E-20 0.25966402 0.421 0.145 1.49E-15

SELPLG 1.91E-19 0.28734486 0.537 0.255 2.92E-15TXNIP 5.02E-19 0.41663972 0.942 0.855 7.65E-15HAX1 9.91E-19 0.26601377 0.557 0.276 1.51E-14ISG20 4.04E-18 0.33582514 0.811 0.64 6.16E-14CARS 4.33E-18 0.25129182 0.385 0.133 6.61E-14

C1orf162 5.68E-18 0.30185496 0.368 0.125 8.66E-14FOS 1.35E-17 0.49091832 0.459 0.204 2.07E-13

TRABD 1.38E-17 0.27279984 0.49 0.227 2.11E-13HLA-E 2.02E-17 0.25977668 0.998 0.985 3.08E-13ZNF638 3.17E-17 0.255007 0.37 0.128 4.83E-13PIK3R1 1.46E-16 0.3257448 0.662 0.444 2.22E-12LMAN1 2.68E-16 0.26124001 0.528 0.268 4.08E-12CLEC2D 2.69E-16 0.25852615 0.43 0.184 4.10E-12DGUOK 4.81E-16 0.25189799 0.555 0.304 7.34E-12CEP57 2.35E-15 0.25883932 0.497 0.253 3.59E-11

HNRNPF 3.89E-15 0.26283187 0.662 0.429 5.94E-11IL16 4.38E-14 0.29209494 0.722 0.546 6.68E-10

SRGN 1.15E-12 0.31756601 0.802 0.648 1.75E-08CREM 1.49E-12 0.34162438 0.492 0.288 2.27E-08

Table S5f. Differentially expressed genes in NY-ESO-1 TCR+ T cells (Day 113 Post-infusion vs. Day 10 Post-infusion)

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NEAT1 3.01E-10 0.27282146 0.621 0.454 4.59E-06PASK 1.09E-08 0.25360698 0.25 0.11 0.00016559

AL138963.3 6.05E-07 0.48491166 0.514 0.37 0.00923187

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Table S6. Longitudinal measurement of absolute levels for circulatingcytokines/chemokines/growth factors in serum and bone marrow after infusion of NYCE T cells.

a. UPN07 b. UPN35 c. UPN39 Serum samples were analyzed in triplicate, and data acquisition and analysis were done using xPONENT software (Luminex). Reported values are in pg/ml. Data quality was examined based on the following criteria: The standard curve for each analyte has a R2 value > 0.95 with or without minor fitting using xPONENT software. The results for the in house control needed to be within the 95% of CI (confidence interval) derived from historical in house control data for >25 of the tested analytes. No further tests were done on samples with results out of range low (<OOR) as they were tested without dilution. Samples with results that were out of range high (>OOR) or greater than the standard curve maximum value (SC max) were re-tested at higher dilutions.

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Factor (pg/ml) 0 0 +1 +3 +7 +10 +14 +14 +21 +28 +28Blood serum Blood serum Blood serum Blood serum Blood serum Blood serum Blood serum BM serum Blood serum Blood serum BM serum

EGF 98.66 67.59 90.06 5.37 73.84 147.43 90.39 59.17 37.13 46.31 16.03FGF‐2 10.45 ND 15.34 ND 24.82 ND ND 30.29 ND ND 12.89Eotaxin 143.69 151.43 134.99 100.76 135.30 179.97 139.35 147.07 133.46 125.89 118.04sIL‐2Ra 83.40 200.53 207.76 247.65 206.87 216.59 166.62 567.16 128.42 141.65 452.40G‐CSF 35.60 35.18 47.77 95.95 178.53 223.44 48.23 40.91 40.13 44.36 57.10GM‐CSF 9.74 28.15 7.62 4.46 4.79 2.33 1.77 3.56 2.05 0.17 6.00IFN‐a2 1.66 ND ND ND ND ND ND ND ND ND NDIFN‐G 0.99 14.89 2.58 1.33 0.70 ND 0.22 0.36 0.44 0.30 0.40IL‐10 12.92 15.65 13.73 13.73 18.49 10.59 14.24 14.34 38.72 17.83 20.82IL‐12p40 ND ND ND ND ND ND ND 8.00 ND ND 16.68IL‐12p70 ND ND ND ND ND ND ND ND ND ND NDIL‐13 ND ND ND ND ND ND ND ND ND ND NDIL‐15 62.57 61.02 63.10 33.47 17.50 17.80 15.18 14.68 5.36 3.49 4.73IL‐17A 2.37 3.05 2.65 2.83 3.73 4.97 6.06 10.10 6.74 5.75 8.80IL‐1Ra 15.09 22.42 14.64 6.88 6.54 8.71 10.10 56.44 13.41 9.48 50.63HGF 407.10 590.40 417.96 339.10 396.25 446.05 551.38 3208.50 621.77 778.74 8759.04IL‐1B ND 0.01 ND 0.14 ND ND ND 0.11 ND ND 0.20CXCL9/MIG 1481.79 1527.38 1957.75 2067.82 2203.63 1971.71 2046.62 2968.36 2555.37 2528.88 3911.68IL‐2 0.46 0.41 0.46 0.24 0.25 0.33 0.21 0.81 0.39 0.16 0.98IL‐4 ND ND ND ND ND ND ND ND ND ND NDIL‐5 ND 3.39 9.14 1.80 0.71 1.45 0.67 1.23 0.23 0.25 1.19IL‐6 10.45 8.46 9.58 11.16 7.66 7.01 3.91 8.13 7.78 7.41 10.63IL‐7 10.60 8.47 8.33 2.53 ND ND ND ND ND ND NDCXCL8/IL‐8 4.38 7.18 7.89 7.57 4.55 6.71 3.32 2.25 6.85 4.06 6.75CXCL10/IP‐10 509.37 579.95 785.96 1028.79 730.95 603.28 588.70 611.01 1047.35 981.11 1160.83CCL2/MCP‐1 2837.05 3162.36 4268.15 2462.63 1028.59 1190.80 837.13 1218.44 1165.04 854.22 1188.73CCL3/MIP‐1a 9.40 12.29 10.09 3.60 2.10 ND 3.08 2.86 9.30 6.96 17.48CCL4/MIP‐1B 57.93 78.81 52.64 35.79 25.03 30.65 32.09 44.13 44.94 44.95 57.15CCL5/RANTES 3677.71 3793.54 3771.15 3038.28 4583.17 6193.74 4365.20 3820.64 3274.40 3806.30 2114.27TNF‐a 17.24 48.60 23.23 19.61 19.50 18.68 13.23 23.75 21.52 18.09 27.02VEGF 48.42 41.89 21.72 ND 21.31 21.69 14.96 26.12 ND ND 41.24

Table S6A. Longitudinal measurement of absolute levels for circulating cytokines/chemokines/growth factors in serum after infusion of NYCE cells UPN07.

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Factor (pg/ml) ‐10 to ‐6 ‐10 to ‐6 ‐5  to ‐3 ‐12  to ‐8 0 +1 +3 +7 +10 +14 +14 +21 +28 +28Blood serum BM serum Blood serum BM serum Blood serum Blood serum Blood serum Blood serum Blood serum Blood serum BM serum Blood serum Blood serum BM serum

EGF 376.91 579.27 596.90 790.53 325.73 458.35 492.86 508.88 634.27 584.62 237.49 251.08 406.99 402.40FGF‐2 ND 263.08 50.86 237.63 188.07 51.93 99.48 52.98 46.45 46.41 102.15 ND 56.40 330.59Eotaxin 101.12 112.24 138.49 240.90 127.56 181.72 175.45 219.72 201.61 190.89 193.48 180.56 132.56 127.76sIL‐2Ra 117.92 390.89 139.64 556.81 123.63 179.05 118.00 377.42 168.64 93.24 389.79 33.81 52.06 244.23G‐CSF 45.32 50.54 51.34 17.28 86.12 72.18 94.96 170.79 226.48 45.85 54.51 5.73 51.48 52.59GM‐CSF 4.88 26.38 7.04 3.89 7.17 8.09 7.57 6.45 8.02 13.79 24.98 8.02 8.93 17.28IFN‐a2 ND ND 7.58 9.88 ND ND ND ND ND ND 9.14 ND ND 14.79IFN‐G ND 0.75 0.71 1.15 0.20 0.65 0.66 0.32 0.82 1.04 3.15 ND 0.66 2.35IL‐10 10.99 21.02 8.26 17.91 6.25 6.61 5.24 10.81 9.72 6.48 7.67 4.87 4.13 35.04IL‐12p40 ND ND ND ND ND ND ND ND ND ND ND ND ND NDIL‐12p70 ND ND 0.04 0.96 ND ND ND ND ND ND ND 0.04 ND NDIL‐13 ND ND ND ND ND ND ND ND ND ND ND ND ND NDIL‐15 11.43 12.90 13.06 14.24 40.61 41.34 33.63 30.41 29.28 22.44 28.80 17.97 16.74 18.89IL‐17A 0.05 ND 0.15 0.62 0.13 0.35 0.25 2.22 1.19 0.38 0.40 0.58 ND 0.40IL‐1Ra 7.63 24.67 12.04 33.28 9.59 12.08 8.77 15.77 17.40 13.31 27.48 5.61 12.67 23.06HGF 3131.46 18100.16 3355.32 31192.99 2694.26 2942.68 2569.55 3158.55 3443.38 3287.17 11933.70 2685.32 3459.17 12349.25IL‐1B ND ND ND 0.17 ND ND ND ND ND ND ND ND ND 0.17CXCL9/MIG 1046.53 1791.38 1230.28 2498.65 1445.14 1311.29 1054.85 2272.89 1141.34 1112.13 1910.37 1132.29 932.75 1467.75IL‐2 ND 0.46 0.10 0.54 0.24 0.20 ND ND ND 0.15 0.44 ND 0.37 0.46IL‐4 ND 1.70 ND 6.82 ND ND ND ND ND ND ND ND ND NDIL‐5 0.40 0.64 0.21 0.10 2.38 3.29 1.67 0.97 1.48 0.29 1.11 0.81 0.38 0.06IL‐6 9.37 5.73 4.88 3.44 1.57 1.60 1.68 3.34 8.63 0.86 1.24 1.42 26.12 3.58IL‐7 7.43 7.60 7.45 6.57 8.89 8.89 6.72 7.83 9.06 8.05 9.18 4.81 2.85 3.88CXCL8/IL‐8 9.39 10.93 7.84 131.49 9.78 6.76 8.14 11.97 12.84 7.42 7.95 5.24 4.87 5.22CXCL10/IP‐10 187.37 160.96 192.09 283.28 277.46 338.68 276.14 276.65 231.25 247.83 258.36 284.75 280.93 276.52CCL2/MCP‐1 496.66 585.35 611.31 503.71 1331.24 1305.36 1114.53 815.07 816.59 928.75 711.25 688.24 574.73 706.78CCL3/MIP‐1a 16.93 22.77 21.25 20.64 17.04 15.06 16.16 15.52 20.54 15.95 23.03 13.38 16.32 22.18CCL4/MIP‐1B 97.42 115.16 102.89 144.53 88.26 104.81 88.30 68.14 67.18 68.40 76.54 52.78 50.48 66.56CCL5/RANTES 8974.59 15345.02 10489.53 15440.39 7543.92 7806.38 9828.06 7891.33 7624.75 6799.50 7316.78 5808.09 9097.68 10231.48TNF‐a 41.71 43.06 37.91 41.79 24.31 31.02 27.48 31.98 32.58 29.46 33.82 26.54 29.04 16.31VEGF 400.62 453.45 444.30 307.03 251.86 260.95 188.40 226.61 417.79 485.62 487.61 240.00 233.80 262.18

DAY POST INFUSION

Table S6B. Longitudinal measurement of absolute levels for circulating cytokines/chemokines/growth factors in serum after infusion of NYCE cells UPN35.

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Factor (pg/ml) ‐10 to‐6 ‐5  to ‐3 0 0 +1 +3 +7 +10 +14 +21 +28Blood serum Blood serum Blood serum Blood serum Blood serum Blood serum Blood serum Blood serum Blood serum Blood serum Blood serum

EGF 5.15 ND 11.01 7.92 ND 11.96 ND ND ND ND 7.92FGF‐2 17.82 50.10 42.69 41.43 42.69 29.98 ND 24.65 36.56 42.63 45.16Eotaxin 152.38 158.27 163.73 71.88 155.77 123.82 79.96 158.28 108.35 108.21 143.41sIL‐2Ra 413.16 414.31 537.65 338.61 940.51 515.56 1214.99 1226.16 1119.61 1172.52 1478.54G‐CSF 3.16 16.03 37.13 30.45 59.89 46.73 29.37 62.27 73.06 32.55 24.70GM‐CSF 0.63 17.35 24.12 45.73 29.11 25.99 8.96 23.48 7.27 2.69 NDIFN‐a2 ND 39.71 33.07 33.08 36.42 19.96 25.86 29.52 21.96 28.60 27.71IFN‐G 0.20 3.64 3.13 5.08 3.84 3.68 2.34 4.00 5.67 16.79 12.77IL‐10 0.57 3.99 21.43 18.49 21.39 18.36 20.48 23.80 18.59 18.55 18.80IL‐12p40 ND ND ND ND ND ND ND ND ND ND NDIL‐12p70 ND 6.85 ND ND 0.84 ND ND ND ND 3.20 0.57IL‐13 ND ND 17.24 16.69 17.65 16.74 16.60 16.69 17.15 17.15 17.61IL‐15 ND ND 57.86 35.59 68.44 41.37 27.98 24.72 24.44 26.65 24.61IL‐17A 0.10 2.69 ND ND ND ND ND ND ND ND NDIL‐1Ra 7.29 16.57 21.69 15.96 19.36 17.85 17.22 1.88 11.02 15.96 26.88HGF 318.79 330.89 342.05 279.00 366.66 422.21 695.22 497.59 286.15 311.88 446.26IL‐1B ND 2.93 ND ND ND ND ND ND ND ND NDCXCL9/MIG 1752.74 1522.71 2469.50 2790.62 2928.19 1355.53 2616.03 2368.16 2532.45 7578.43 10580.19IL‐2 0.10 2.18 15.92 15.27 15.63 15.11 15.40 15.57 15.72 15.90 16.00IL‐4 ND 15.11 13.56 6.92 12.31 9.21 8.29 10.09 15.40 15.31 15.09IL‐5 2.35 3.26 ND 13.20 32.10 30.03 33.15 14.92 16.19 37.52 21.12IL‐6 0.58 1.05 6.12 21.47 9.97 9.03 13.86 3.43 6.20 8.02 5.13IL‐7 6.42 3.72 30.42 27.93 22.70 27.93 19.67 18.95 10.06 19.68 20.01CXCL8/IL‐8 9.24 7.93 24.74 31.39 29.61 15.03 20.31 24.11 20.11 14.79 20.47CXCL10/IP‐10 285.38 400.03 739.06 1368.25 875.79 752.37 1178.03 771.83 868.46 1833.13 2025.45CCL2/MCP‐1 471.80 230.30 6480.14 1881.97 3387.13 2221.94 1275.65 2204.23 1203.12 409.82 316.02CCL3/MIP‐1a ND ND ND 8.72 ND ND ND ND ND ND NDCCL4/MIP‐1B 19.91 18.15 47.66 65.00 43.03 27.32 21.42 27.43 35.79 27.08 35.15CCL5/RANTES 4593.34 4866.70 2691.53 2576.82 2799.18 2249.27 1996.24 2354.38 2300.47 2067.79 2519.31TNF‐a 36.89 32.97 33.94 49.76 41.62 25.74 45.37 27.01 41.40 67.97 80.42VEGF 66.61 58.78 58.83 54.54 31.49 24.20 ND 3.35 9.64 19.13 25.63

DAY POST INFUSION

Table S6C. Longitudinal measurement of absolute levels for circulating cytokines/chemokines/growth factors in serum after infusion of NYCE cells UPN39.

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