T cell–based therapies have induced cancer remissions, though most tumors ultimately progress, reflecting inherent or acquired resistance including antigen escape. Better understanding of how T cells eliminate tumors will help decipher resistance mechanisms. We used a CRISPR/Cas9 screen and identified a necessary role for Fas–FasL in antigen-specific T-cell killing. We also found that Fas–FasL mediated off-target “bystander” killing of antigen-negative tumor cells. This localized bystander cytotoxicity enhanced clearance of antigen-heterogeneous tumors in vivo, a finding that has not been shown previously. Fas-mediated on-target and bystander killing was reproduced in chimeric antigen receptor (CAR-T) and bispecific antibody T-cell models and was augmented by inhibiting regulators of Fas signaling. Tumoral FAS expression alone predicted survival of CAR-T–treated patients in a large clinical trial (NCT02348216). These data suggest strategies to prevent immune escape by targeting both the antigen expression of most tumor cells and the geography of antigen-loss variants.
This study demonstrates the first report of in vivo Fas-dependent bystander killing of antigen-negative tumors by T cells, a phenomenon that may be contributing to the high response rates of antigen-directed immunotherapies despite tumoral heterogeneity. Small molecules that target the Fas pathway may potentiate this mechanism to prevent cancer relapse.
This article is highlighted in the In This Issue feature, p. 521
T cell–based immunotherapies—including adoptive transfer of engineered T cells, bispecific antibodies, and checkpoint blockade—have revolutionized cancer treatment. However, even with the remarkably high response rates of chimeric antigen receptor (CAR)-T–treated patients, most either progress or relapse within one year (1–3). Microenvironmental factors contributing to T-cell priming (4–6) and T cell–intrinsic factors (7, 8) both influence antitumor immunity, but tumor cell–intrinsic factors have the most abundant clinical evidence for contributing to treatment potency and failures.
The clearest such mechanism is target antigen (Ag) modulation—expression downregulation, lineage switching, or emergence of splice variants—which is the most common cause of relapse following CAR-T therapy for B-cell acute lymphoblastic leukemia (B-ALL; ref. 9). Similar mechanisms of Ag escape have also been noted in CAR-T therapy for non-Hodgkin lymphoma (NHL; ref. 9), multiple myeloma (10), and glioblastoma multiforme (11). Although downregulation of target Ag is a well-characterized occurrence, comparable rates of Ag+ relapses (12) that are unresponsive to CAR-T reinfusion (13–15) also indicate the presence of other immune evasion mechanisms in tumor cells such as suppression of apoptotic pathways.
The majority of preclinical and clinical data suggest that the tumoricidal effects of murine and human T cells are perforin- and granzyme-mediated (16–18). Consequently, expression of these and other effector molecules (e.g., IFNγ and TNFα) is the primary focus of clinical biomarker studies across T cell–based therapies (19–22). However, equal efficacy of adoptive cell therapy (23) and checkpoint blockade (24) in perforin-deficient murine models, as well as recent evidence of death receptor signaling gene signatures correlating with CAR-T efficacy (25), supports the notion that other mechanisms may have an underappreciated role in T-cell cytotoxicity and warrant further investigation.
Additionally, even with optimal Ag-specific tumor clearance, emergence of preexisting Ag-null variants is an expected mechanism of rapid relapse. Thus, the frequency of durable immunotherapy remissions despite tumoral Ag heterogeneity is surprising. A majority of patients with B-ALL harbor >1% CD19− cells at diagnosis (26), though only ∼20% of patients relapse with CD19− disease after CD19-directed therapy (9). Similarly, response rates of CAR-T therapy for NHL are comparable between subgroups with high and low/negative tumoral CD19 expression (27). Just as puzzling is that subclonal loss of β2m, effectively abolishing antigen presentation to CD8 T cells, in MSI-H colorectal tumors has no apparent effect on PD-1 blockade efficacy (28). These data are all highly suggestive of bystander cytotoxicity mediating clearance of Ag− cancer subclones. However, there are no published studies identifying tumor cell mechanisms of how this occurs in vivo despite its enormous therapeutic potential.
To dissect these mechanisms and address these important knowledge gaps, we performed a CRISPR/Cas9 screen using a targeted library of genes highly expressed by the A20 murine lymphoma cell line and identified the death receptor Fas as crucial to T-cell cytotoxicity. For the first time, we demonstrate that Fas-mediated bystander killing enhances in vivo control of heterogeneous tumors. We also demonstrate that pretreatment tumoral FAS expression is an even better predictor of long-term CAR-T therapy outcomes than expression of the target molecule, which may suggest that homogeneity of Ag expression is not needed to achieve full efficacy of Ag-directed therapies. Finally, we present evidence and rationale for combination strategies that augment both on-target and bystander cytotoxic pathways in order to prevent both Ag+ and Ag− relapses after adoptive T-cell therapies.
Fas Is a Critical T-Cell Effector Molecule
Using a reductionist 3-cell system comprising GFP-specific (JEDI) CD8 T cells (29, 30), Ag+ A20-GFP cells, and Ag− A20-mCherry cells (Fig. 1A), we exerted strong iterative Ag-specific T-cell selection pressure on the GFP+ population (Supplementary Fig. S1A) and sequenced surviving cells to measure changes in the frequency of targeted genes (Supplementary Fig. S1B). The 291 genes targeted in the screen (Supplementary Table S1) were manually curated for high expression in our cancer model and enriched for immune-related functional annotations. Significant deviations from the expected frequency of targeted genes in the GFP+ cells were internally controlled by the measured frequency in mCherry+ cells (Supplementary Fig. S1C). As expected, knockout clones of B2m and Tap1 (Supplementary Fig. S1D and S1E), genes crucial to Ag presentation, became highly enriched following selection (P < 1e−14; Fig. 1B; Supplementary Fig. S1C). Enrichment of Ag+ cells that had lost MHC class I expression was confirmed at the protein level (Supplementary Fig. S1F and S1G), in addition to the expected relative loss of PD-L1–deleted cells (Supplementary Fig. S1F and S1H). Surprisingly, knockout clones of Fas became equally enriched (P < 1e−14; Fig. 1B; Supplementary Fig. S1C and S1I), a finding unique in our model system compared with other recent T cell–based screens (31–34). For validation, we created polyclonally derived stable Fas-knockout lines of A20 lymphoma as well as 4T1 breast cancer (Fig. 1C) that had no measurable surface Fas protein expression (Supplementary Fig. S2A) and were resistant to Fas-induced cell death (Supplementary Fig. S2B). Although wild-type (WT) GFP+ cells were depleted by JEDI, both Fas-negative lymphoma (Fig. 1D; quantified in Supplementary Fig. S2C) and breast cancer (Fig. 1E; quantified in Supplementary Fig. S2D) demonstrated resistance to killing under the same conditions, despite robust T-cell proliferation, granzyme B production, and degranulation in both conditions (Fig. 1F). Similarly, superantigen-induced cytotoxicity by both CD8 and CD4 T cells—mediated by bacterial toxins that nonspecifically bind MHC molecules to T-cell receptors—was also highly dependent on Fas expression (Supplementary Fig. S2E), whereas irradiation-induced apoptosis was not (Supplementary Fig. S2F), demonstrating specificity to T cell–mediated killing.
Resistance to granzyme-secreting T cells was surprising given its recognition as a dominant pathway for killing transformed cells (35). Using an in vivo adoptive transfer model with tetramer-sorted GFP-specific CD8 T cells, we observed earlier recurrence of Fas−/− GFP+ tumors compared with the WT counterparts (Fig. 1G; individual curves in Supplementary Fig. S2G), validating our in vitro findings. Significantly decreased activation of the extrinsic apoptosis mediator caspase-8 in the dying Fas−/− tumor cells despite comparable T-cell infiltration confirmed a role for Fas-mediated cytotoxicity in situ (Fig. 1H and I). At the same time, higher staining intensity for GFP in Fas−/− tumors when challenged with T cells (Fig. 1I), but not in control mice (Supplementary Fig. S2H and S2I), confirmed increased survival of Fas−/− tumor cells. Taken together, these data validate Fas as an important mediator of cytotoxicity in Ag-specific T cell–based immunotherapy, even in conditions with abundance of other mediators, e.g., granzymes.
Fas Mediates T-Cell Bystander Killing
Although our model system showed clear protection of Fas−/− Ag+ cells, it also demonstrated a significant, T cell–dependent increase in the GFP+/mCherry+ ratio (Supplementary Fig. S2C), indicating either increased proliferation of the Fas−/− GFP+ (Ag+) cells or increased clearance of the mCherry+ (Ag−) cells. Measurement of absolute cell counts confirmed the latter and demonstrated a surprising depletion of Ag− cells—in the setting of only partial protection for Fas−/− Ag+ cells—that was concealed by using the ratio as a surrogate for measuring cytotoxicity (Supplementary Fig. S3A). A close T-cell dose titration revealed that conditions were possible in which the killing of mCherry+ cells could overtake the killing of GFP+ cells (Supplementary Fig. S3A), resulting in an increase of the GFP+/mCherry+ ratio. This phenomenon of Ag− tumor cell death—herein referred to as bystander killing—was observed even at very low effector:target cell ratios in the WT setting and only in the presence of Ag-specific (tetramer-sorted) T cells but not with preactivated nonspecific T cells (Fig. 2A). A role for MHC class II–mediated killing was ruled out by the lack of CD4 T-cell contamination in our system (Supplementary Fig. S3B). Transwell assays confirmed that this bystander killing was contact mediated and required colocalized Ag+ cells (Fig. 2B, purple highlight; quantified in Supplementary Fig. S3C) to induce bystander apoptosis in Ag− cells. Given our observation of Fas-dependent Ag-specific cytotoxicity, we hypothesized that it may play a role in this bystander cytotoxicity as well. Coculturing GFP(WT) with mCherry(Fas−/−) cells in the presence of JEDI T cells completely abrogated the depletion of the Ag− population observed with mCherry(WT) cells, confirming that this bystander effect was Fas-mediated (Fig. 2C, left). Notably, mCherry(B2m−/−) cells were equally susceptible to bystander killing, ruling out Ag cross-reactivity or exogenous loading of MHC class I as possible explanations (Fig. 2C, left). Bystander killing was also nullified in the presence of GFP(B2m−/−) cells, demonstrating that local T-cell receptor (TCR)–peptide–MHC activation by Ag+ cells is needed for T cells to exert contact-mediated cytotoxicity against Ag− cells (Fig. 2C, right). The lack of bystander apoptosis despite the presence of preactivated JEDI in the chamber with Ag− cells confirmed that concurrent and local activation of the T cells was necessary (Fig. 2B, orange highlight; Supplementary Fig. S3C), consistent with the strict regulation of surface FasL activity (36) as well as ruling out distant delivery of active FasL via microvesicles (37) or exosomes (38).
To assess off-target killing in vivo, we inoculated mixed tumors of GFP(WT) cells with either mCherry(WT) or mCherry(Fas−/−) cells in Rag1−/− mice lacking endogenous T cells, followed by adoptive transfer of GFP-specific T cells. Although tumors in both cohorts comprised equal numbers of Ag+ target cells, tumors with Fas−/− bystander cells demonstrated a blunted response to the therapy (Fig. 2D, 50.6% vs. 71.2% peak reduction in tumor volume; individual curves in Supplementary Fig. S3D) and quicker recurrence, confirming that Ag-specific T cells were capable of exerting Fas-dependent bystander tumor clearance in vivo. Depletion studies ruled out a role for natural killer cells in this phenomenon (Supplementary Fig. S3E).
We next used a two-tumor model to determine whether this bystander effect was systemic or required the presence of local Ag+ cells as in our in vitro transwell experiments. In addition to the same mixed GFP+/mCherry+ tumors used in the prior model, which we now call the primary tumor (Fig. 2E, right flank on schema), we also inoculated a distant tumor on the opposite side (Fig. 2E, left flank on schema) comprising only mCherry+ cells of the corresponding WT or Fas−/−genotype. Lack of regression in these Ag− distant tumors, even while the primary tumors were rapidly shrinking in response to GFP-specific T-cell transfer, demonstrated that bystander cytotoxicity was geographically restricted and dependent on colocalized Ag− and Ag+ tumor cells (Supplementary Fig. S3F). Imaging over a large area exhibited a corresponding lack of caspase-8–mediated tumor cell death in these distant tumors (Fig. 2E, left; Supplementary Fig. S3G and S3H). Immunofluorescence of the primary tumors from the same mice, however, demonstrated widespread active caspase-8 activity in response to the transferred T cells (Fig. 2E, right). Higher power images of the mixed primary tumors confirmed colocalization of active caspase-8 with mCherry(WT) cells (Fig. 2F) whereas mCherry(Fas−/−) cells appeared completely protected despite being surrounded by Ag+ tumor cells undergoing on-target killing (Fig. 2G). Quantification of the staining revealed that more than four times as many mCherry(WT) tumor cells were undergoing apoptosis compared with mCherry(Fas−/−) cells at days 6 to 8 when the tumors had just begun regressing (Fig. 2H). This in situ evidence of mCherry+ bystander cell apoptosis correlates with and reasonably accounts for the Fas-dependent differences in macroscopic tumor responses to T-cell transfer (Fig. 2D).
Bystander Killing Can Be Potentiated
These data introduce the idea that Ag-loss variants of tumor cells can be targeted on the basis of their geographic proximity to other Ag+ tumor cells in vivo. We hypothesized that the efficacy of immunotherapies like checkpoint inhibitors may at least partially be due to unappreciated bystander effects. As expected, PD-1 blockade enhanced on-target apoptosis of GFP+ cells in our model (Fig. 3A, left), but surprisingly also nearly doubled bystander apoptosis of mCherry+ cells (Fig. 3A, right). This increased bystander cell death was perhaps partly due to the significant upregulation of Fas protein levels on the cell surface (Fig. 3B, top, column 2). In contrast, neutralization of interferon gamma (IFNγ) blunted Fas expression relative to the untreated condition (Fig. 3B, top, column 3) and decreased bystander apoptosis nearly 2-fold (Fig. 3A, right). These results suggest that levels of Fas may be contributing to sensitivity to off-target killing, consistent with its role in other settings of Fas-mediated apoptosis (39, 40). We speculate that FasL expression on the T cells is also being modulated in these conditions and may be contributing to the effects as well, given the prominent roles of the PD-1 pathway and the cytokine IFNγ on CD8 T-cell activation. All bystander apoptosis was nullified by treatment with a caspase-8 inhibitor or with mCherry(Fas−/−) cells, confirming that the observed killing was mediated by extrinsic apoptotic pathway machinery e.g., Fas–FasL (Fig. 3A).
A critical difference between granzyme/perforin- and death receptor–mediated apoptosis is the well-characterized signaling of the latter and thus the potential to target downstream pathways (41). We therefore screened select families of proteins with known modulatory activity within the Fas pathway and identified small-molecule inhibitors that augmented Fas-mediated cell death in our system (Supplementary Fig. S4A and S4B). We hypothesized that these drugs may sensitize cancer cells to on-target and bystander T-cell killing. Using cocultures of Ag+ or Ag− and WT or Fas−/− lymphoma cells, treatment with the histone deacetylase inhibitor (HDACi) panobinostat induced a significant increase in tumoral Fas levels (Supplementary Fig. S4C). Concurrently, we saw increased caspase-3 cleavage in both Ag+ and Ag− populations when cultured with Ag-specific T cells, although Fas−/− populations in the same culture did not respond (Fig. 3C and D). Fas-dependent potentiation of on-target and bystander apoptosis was similarly observed after treatment with the inhibitor of apoptosis proteins antagonist (IAPi) birinapant and BCL2/xL inhibitor ABT-737 (Fig. 3D; Supplementary Fig. S4D). To ensure that various metrics support the same conclusions, we confirmed similar results with a different viability assay (Supplementary Fig. S4E). For example, 1 nmol/L panobinostat had negligible effect (<1%) on A20-GFP (columns 1 and 4) and A20-mCherry (columns 9 and 12) viability at baseline, but potentiated JEDI-induced on-target killing by 31% (columns 5 and 8) and bystander killing by 32% (columns 13 and 16). Similar effects that appeared greater-than-additive were seen with inhibitors of IAP and BCL2/xL (Supplementary Fig. S4E). Importantly, all compounds had little or no effect on the viability of the T cells in the same cocultures (Supplementary Fig. S4F), suggesting lack of Fas-mediated potentiation of T-cell fratricide (42) with these combination therapies.
Bystander Killing Is Critical to Immunotherapies
To translate these concepts to clinically relevant T-cell therapies, we obtained healthy donor human T cells and measured cytotoxicity mediated by the CD3/CD19 bispecific T-cell engager blinatumomab against on-target CD19+/+ and bystander CD19−/− Raji lymphoma cells (Supplementary Fig. S5A). As in the murine setting, we again observed potentiation of Fas-dependent killing of both on-target (Fig. 3E) and bystander (Fig. 3F) cells using inhibitors to IAP and the BCL2 family member MCL1 without inducing any toxicity against the cocultured T cells (Supplementary Fig. S5B and S5C).
To assess the relevance of these findings to CAR-T cells, which utilize activation signaling distinct from endogenous T cells that may result in different effector functionality, we tested a murine CD19-targeting CD3ζ-CD28 CAR construct (43) transduced into WT syngeneic CD8 T cells. Using cocultures of CD19+ or CD19− and WT or Fas−/− lymphoma cells, we again observed resistance of Ag+ target cells lacking surface Fas to CAR-T killing (Fig. 4A). Quantification of cell counts demonstrated that although Fas-mediated cytotoxicity played a moderate role in CAR-T on-target killing (Fig. 4B, black/gray), it contributed to nearly all measured bystander killing (Fig. 4B, red/pink). To model in vivo therapy of Ag-loss escape tumors, we inoculated homogeneous (100% CD19+) or heterogeneous (95% CD19+/5% CD19−) tumors prior to CAR-T therapy. Although untreated mice died similarly rapidly with both homogeneous and heterogeneous tumors (median 24–25 days), CAR-T therapy prolonged survival of the homogeneous tumor cohort (median 42 days) and similarly prolonged survival of the heterogeneous tumor cohort (median 41 days), suggesting some protective effect of anti-CD19 CAR-T cells against CD19− tumor (Fig. 4C, solid lines). Systemic FasL blockade severely impaired CAR-T efficacy, reaffirming the Fas–FasL dependence of on-target CAR-T cytotoxicity (Fig. 4C, dashed lines). Most notably, however, with FasL blockade the heterogeneous tumor cohort had significantly worse survival than the homogeneous tumor cohort (Fig. 4C, highlighted dashed lines; median 30.5 vs. 34 days). These findings suggest that Fas–FasL signaling is critical for CAR-T bystander cytotoxicity against Ag-loss variants implicated in disease relapse.
To evaluate the clinical relevance of these findings, we tested anti-human CD19 CD3ζ-CD28 CAR-T cell products (44) made from multiple healthy donors. Consistent with the murine data, these CAR-T cells induced cytotoxicity against both CD19+/+ and CD19−/− Raji cells when cocultured (Fig. 4D). Quantifying these effects reaffirmed the murine results: CAR-T on-target killing was moderately Fas-dependent (Fig. 4E), but CAR-T bystander killing was far more sensitive to FAS expression (Fig. 4F). Similar to the bispecific antibody results, CAR-T bystander killing against Raji could also be potentiated by inhibition of MCL1 or IAP (Supplementary Fig. S5D). Importantly, we demonstrated that MCL1 inhibition can synergistically enhance both CAR-T–mediated and blinatumomab-mediated killing of primary malignant cells from two different patients with chronic lymphocytic leukemia (CLL; Supplementary Fig. S5E), further strengthening the rationale of such combination strategies in the clinic.
To assess the impact of these concepts in patients, we analyzed pretreatment tumoral RNA-sequencing (RNA-seq) data in a subset of patients from the ZUMA-1 trial for refractory diffuse large B-cell lymphoma (DLBCL), which utilized the same CAR-T construct (3). We found that patients experiencing durable clinical responses had significantly elevated tumoral FAS expression compared with all others (Fig. 4G) despite the fact that the two cohorts had comparable tumor CD19 expression (Fig. 4H). Additionally, data from The Cancer Genome Atlas (TCGA) DLBCL cohort undergoing standard therapies demonstrated that patients with high tumor FAS expression had significantly worse survival outcomes (Fig. 4I), consistent with protumorigenic Fas signaling in low membrane-FasL environments (45, 46). By contrast, patients with high FAS expression receiving CAR-T therapy had the opposite correlation: a significantly prolonged survival relative to those with lower expression (Fig. 4J). These data provide evidence for the critical role of the Fas pathway in the efficacy of T cell–based immunotherapies and perhaps even in the context of highly variable target Ag expression (Fig. 4H).
Altogether, we present here that the Fas–FasL pathway may be an undervalued effector mechanism of Ag-specific cytotoxicity and an underrecognized mechanism of bystander cytotoxicity in T cell–based immunotherapies. To our knowledge, this is the first report using in vivo models to implicate a role for the Fas–FasL pathway in the clearance of Ag− tumor cells as well as clinical data to show the impact of tumoral FAS expression on survival after CAR-T therapy.
Prior in vitro work has suggested that T cells may exert noncanonical, indiscriminate, multidirectional killing (47–50) and that FasL-mediated cytotoxicity can be immune synapse independent (51). However, because not all in vitro observations translate (52), our in vivo data are critical evidence that tumoral factors can mediate bystander killing. Earlier findings of the importance of Fas have been downplayed by acceptance that the perforin–granzyme pathway is the dominant mechanism for killing transformed cells (35). We believe that our in vivo data validate these decades-old in vitro observations, and the mechanisms proposed here have broad implications for any Ag-directed immunotherapy against heterogeneous tumors.
Target Ag loss is a primary mechanism of immune escape after CAR-T therapy, with 9% to 25% of patients in trials demonstrating Ag modulation (12). The primary strategy being pursued to treat Ag− relapses is targeting of alternative tumor Ag; a CAR-T product targeting CD22 has already shown promise for cancers resistant to CD19-targeting CARs (53). A primary limitation of this approach is that alternative, homogeneously expressed, highly tumor-specific surface Ag cannot be identified for most tumors. Therefore, Ag-agnostic approaches to preventing relapses are preferable to sequential Ag-based therapies.
Downplayed in the interpretation of CD19–CAR-T trial data is the heterogeneity of tumors and the lack of correlation between treatment efficacy and tumoral target expression (3, 27). Our analysis of tumoral transcriptomic data from ZUMA-1 indicates that FAS expression predicts long-term outcomes of CAR-T–treated patients, even though target Ag expression does not. Accordingly, our murine CAR-T model shows that Ag heterogeneous and homogeneous tumors respond similarly only if Fas signaling is intact. We therefore propose that Fas-mediated bystander elimination of Ag-loss variants may already be occurring in CAR-T–treated patients. This mechanism lays the groundwork for a novel therapeutic approach to improving Ag-directed therapies: targeting the proximity of tumor cells to each other rather than targeting new Ag. Future studies will benefit by quantifying the distribution and spatial relationship of tumoral Fas and Ag expression with infiltrating Ag-specific T cells.
In vivo demonstration of tumorally mediated bystander killing is novel. Previous studies closely measuring in vivo T-cell killing with longitudinal imaging (54, 55) did not observe bystander killing, possibly due to the use of FasL-insensitive tumor models (56). Other reports were able to demonstrate indirect clearance of Ag-loss variants by killing Ag+ cross-presenting tumor stroma (57, 58), but these studies did not demonstrate any direct contact-mediated effects by T cells against tumor nor any potentiation of this bystander killing.
We show that surface Fas expression is upregulated by IFNγ exposure, and together with recent studies demonstrating that T cell–secreted IFNγ affects tumor cells hundreds of microns away (59, 60), our data suggest that this might augment subsequent Fas–FasL-mediated bystander killing. Additionally, we demonstrate that known sensitizers of Fas-mediated cell death, e.g., HDACi (61) and SMAC mimetics (62), can enhance T cell–mediated killing, independent of Ag expression. We propose that investigating combinations of these clinical-stage small-molecule Fas signaling modulators with T-cell therapies should be a focus of future research. These approaches may prevent—rather than treat—cancer relapse due to antigen escape by targeting both tumor cell antigens and tumor cell geography.
Protocols for the treatment of patients, as well as human sample collection and analysis, were approved by the Mount Sinai Institutional Review Board, and written informed consent was obtained from all patients in accordance with the Declaration of Helsinki. All experiments including human specimens were performed in compliance with the relevant ethical regulations.
BALB/c and BALB/c(Rag1−/−) were purchased from Jackson labs and housed at the animal facility of the Icahn School of Medicine at Mount Sinai. JEDI mice (29) were backcrossed onto the BALB/c background for eight generations in our facility. All experiments were reviewed and approved by the Institutional Animal Care and Use Committee of the Icahn School of Medicine at Mount Sinai.
All cell lines (A20, 4T1, and Raji) were maintained at 37°C with 5% CO2 in RPMI supplemented with 10% heat-inactivated FCS, penicillin/streptomycin, and 50 μmol/L beta-mercaptoethanol. Cell lines with stable expression of Cas9 were generated by transducing with a lentivirus encoding Cas9 (lentiCRISPRv2; Addgene plasmid #52961) and selecting for puromycin resistance. Single-gene knockout lines were generated by cloning in the specific single-guide RNA (sgRNA; Supplementary Table S1; Fas 5′-GGCGTCCCAAAGCTTACCAG-3′) as previously described (63) prior to transduction and FACS purification. To control for clonal heterogeneity, 1e6 cells from the parent line were transduced with a multiplicity of infection (MOI) of 10. After 5 days of growth, 1e6 cells negative for surface Fas expression were purified by FACS and propagated as the knockout line. Expression of Cas9 was confirmed by Western blot (anti-Cas9, clone 7A9, Millipore). A20-Cas9 cells were then transduced with GFP or mCherry lentiviral vectors at 10 MOI, and stable GFP+ or mCherry+ cells (∼10%) were purified by FACS 1 week after transduction. Cells for library screening were maintained in puromycin until 1 day before transduction with libraries. A20(CD19+) and A20(CD19−) lines were generated by FACS purification. 4T1-GFP and 4T1-mCherry cell lines were a gift from the Brown lab (Mount Sinai). Raji cells were a gift from the Dominguez-Sola lab (Mount Sinai). Cell line authentication was not performed, but Mycoplasma testing by PCR was performed annually. Cell lines were used for experiments within 2 weeks of thawing from frozen stocks.
291 target genes for screening were manually curated and selected on the basis of expression levels >1 RPKM in A20 lymphoma cells (accession ENCSR000CLV) and cross-referencing with the UniProt Knowledgebase (64) for the following annotations: secreted, membrane, immunity, inflammatory response, or cytokine. sgRNA sequences were obtained from previously described CRISPR libraries (65) and are listed in Supplementary Table S1. For increased sensitivity, target genes were separated into four separate pools for independent screening.
Library Preparation and Lentiviral Production
The custom oligonucleotide libraries were reconstituted in water to a final concentration of 0.01 pmol/μL and PCR amplified using Q5 Hot Start Polymerase (New England Biolabs). Each PCR-amplified library was then purified using a PCR purification kit (Qiagen) following the manufacturer's protocol. Subsequently, a restriction digest was performed using BbsI restriction enzyme (New England Biolabs) at 37°C overnight. The digested library was then purified by electrophoresis on a 2% agarose gel with 1× TBE running buffer and recovered using a gel extraction kit (Qiagen) following the manufacturer's protocol. The library oligonucleotides were then cloned downstream of the human U6 promoter in a lentiviral vector that also contained an NGFR transgene downstream of the human phosphoglycerate kinase promoter. The vector backbone was digested with AgeI and EcoRI, treated with FastAP Thermosensitive Alkaline Phosphatase (Thermo Scientific), and purified on a 1% agarose gel and recovered using a gel extraction kit (Qiagen). Ligation was performed using the Quick Ligase Kit (New England Biolabs). To prevent loss of library diversity, colonies were collected from fifteen 10-cm plates after transformation of NEB 10-beta electrocompetent cells (New England Biolabs). The pool of plasmids was prepared for transfection using an endotoxin-free Maxi prep kit (Qiagen). Lentiviral vectors were produced as previously described (34). Briefly, 293T cells were seeded 24 hours before Ca3PO4 transfection with third-generation VSV-pseudotyped packaging plasmids and library transfer plasmids. Supernatants were then collected, passed through a 0.22-μm filter, and purified by ultracentrifugation. Viral titer was estimated on 293T cells by limiting dilution.
To ensure that a majority of transduced cells received only one vector and that there was proper library representation, 1e6 cells were transduced for each replicate at an MOI of 10 to ensure ∼10% transduction efficiency. Transductions were done in a 12-well plate with a total volume of 500 μL in the presence of 5 μg/mL polybrene (Millipore). Five separate transductions were done for each cell type (A20-Cas9-GFP and A20-Cas9-mCherry) and each library to generate replicates. One week after the transduction, cells that received and integrated vector were purified by flow sorting for NGFR+ cells. Purified cells were expanded in culture for five more days before cryopreservation and thawed two days prior to the screening assay.
2 × 104 A20-GFP-library+ cells, 20,000 A20-mCherry-library+ cells, and 40,000 preactivated JEDI T cells (pooled from three separate mice) were cocultured per well in 96-well U-bottom plates. Each condition was done in 96 separate reactions (1 plate) and pooled together to ensure proper library representation. Each replicate consisted of one plate with (JEDI) and one plate without (Ctrl) T cells added into the culture. After two days, wells were pooled together and FACS purified for live NGFR+GFP+ cells and NGFR+mCherry+ cells. Purified cells were expanded in culture for two more days before cryopreservation for propagation into future iterations and preservation of a frozen pellet (2e6 cells) for DNA extraction.
Sequencing and Screen Analysis
Library preparation was adapted from methods previously described (66). Briefly, genomic DNA was extracted using the DNeasy Blood and Tissue Kit (Qiagen). The sgRNA sequence sites were amplified from genomic DNA as follows: in a 50-μL reaction, 25 μL Q5 High-Fidelity 2X Master Mix (NEB), 2.5 μL sense primer (5 μmol/L), 2.5 μL antisense primer (5 μmol/L), and 200 ng guide DNA from the sample. Cycling parameters were 98°C for 30 seconds, 28 cycles of 98°C for 10 seconds, 61°C for 30 seconds, 72°C for 25 seconds, and 72°C for 2 minutes. The primers used to amplify the target sites contained sequences that hybridize directly to the Illumina flow cell. Barcodes were inserted immediately following the Illumina sequencing primer binding site to allow for multiplexing. PCR-amplified libraries were purified for a 250-bp band on a 2% agarose gel using a gel extraction kit (Qiagen). Before sequencing, all purified library amplification products were analyzed on an Agilent 2100 Bioanalyzer. The prepared libraries were multiplexed and sequenced on the Illumina Hi-Seq2000.
Debarcoded raw read counts were normalized to the total number of mapped reads within each sample. For each condition, the median of five independent replicates within the GFP+ population was plotted against the paired mCherry+ population. A linear regression was performed on all 5,186 data points, and standardized residuals (Z-scores) of the observed percent reads in the GFP+ population for each target relative to the expected reads were calculated for determining significance of enrichment.
Preparation of JEDI T Cells for Use In Vitro and In Vivo
Spleen and lymph nodes of JEDI mice were dissected, and single-cell suspensions of leukocytes were obtained by mechanical disruption and filtering through a 70-mm cell strainer. Red blood cells were lysed using ACK buffer (Lonza), and CD8+ T cells were negatively selected using the MagniSort Mouse CD8+ T Cell Enrichment Kit (Thermo Fisher Scientific) according to the manufacturer's protocol. For in vitro experiments described in the text using JEDI, cells were activated for two days with 5 μg/mL plate-bound purified hamster anti-mouse CD3e (clone 145-2C11; BD Biosciences), 1 μg/mL purified hamster anti-mouse CD28 (clone 37.51; BD Biosciences), and 20 ng/mL recombinant mouse IL2 (Gemini Bio-Products) in RPMI with 10% FBS, 100 U/mL penicillin/streptomycin/ampicillin, and 50 μmol/L 2-mercaptoethanol. For in vitro experiments described in the text using GFP-specific T cells, cells were first FACS purified using H-2Kd-HYLSTQSAL tetramer reagent produced by the NIH Tetramer Core Facility prior to activation as described above. For all in vivo experiments, freshly isolated tetramer-sorted GFP-specific T cells were used without activation.
In Vitro JEDI T-cell Killing Assays
Three-cell coculture cytotoxicity assays using A20 cancer cells were implemented with 2.5e4 A20-GFP+ cells, 2.5e4 A20-mCherry+ cells, and 5e4 JEDI T cells (2:1 T:target cell ratio) unless otherwise noted and harvested for analysis by flow cytometry after 24 or 48 hours. For 5-cell coculture experiments involving WT, Fas−/−, and/or B2m−/− target cell lines, a 2:1 T:target cell ratio was maintained unless otherwise noted. Assays using 4T1 cancer cells were similarly performed at 25:1 T:target cell ratio. When indicated, a homogeneous suspension of Precision Counting Beads (BioLegend) was uniformly added to each sample prior to analysis by flow cytometry. Normalized cell counts were calculated by dividing the number of event counts of a population of interest by the number of event counts of beads within the same sample.
Three- and four-cell coculture cytotoxicity assays were performed as described above, except with the indicated populations seeded into a transwell insert separated by a permeable membrane with 1-μm pores within a 24-well plate (Thermo Fisher Scientific). After 48 hours, the cells from the top and bottom chambers were combined before analysis by flow cytometry as one sample.
In Vitro Superantigen-Induced T-cell Killing Assays
CD4 and CD8 T cells were isolated from naïve BALB/c mice using the MagniSort Mouse CD4+ or CD8+ T Cell Enrichment Kits (Thermo Fisher Scientific) according to the manufacturer's protocol. 5e4 purified T cells were cocultured with 5e4 total A20 cells (a mixture of outlined genotypes) with 50 ng/mL staphylococcal enterotoxin B (Toxin Technology) for 48 hours before harvesting for analysis by flow cytometry.
Tumor Induction and Measurements
3e6 total cells were injected in 100 μL Hank's Balanced Salt Solution (HBSS) subcutaneously on the flank. For two-tumor models, the same number of total cells was inoculated on the contralateral flank 10 days after the first tumor in order to delay lethality from the nonresponding tumor during a critical time window of experimental observation of the responding tumor. Tumor size was determined via caliper measurements on the indicated days (length × width × height).
GFP-Specific In Vivo Tumor Models
BALB/c(Rag1−/−) mice subcutaneously inoculated with homogeneous A20-GFP (WT or Fas−/−) tumors on the right flank were adoptively transferred with 5e3 GFP-specific T cells via tail-vein injection on the indicated day. BALB/c(Rag1−/−) mice inoculated with mixed heterogeneous tumors, or two-tumor models, were adoptively transferred with 3e5 GFP-specific T cells via tail-vein injection on the indicated day. Where indicated, depletion of natural killer cells was achieved by two intraperitoneal loading doses of 50 μL anti-asialo-GM1 (Wako) 6 and 2 days prior to T-cell transfer, followed by 25 μL doses every 4 days. All tumors harvested for immunofluorescence were dissected on day 8 after T-cell transfer.
Whole tumors were dissected out, washed in PBS, and incubated in periodate-lysine-paraformaldehyde buffer (0.05M phosphate buffer containing 0.1 M L-lysine [pH 7.4], 2 mg/mL NaIO4, and 10 mg/mL paraformaldehyde) overnight at 4°C. Tissue was equilibrated sequentially in 10%, 20%, and 30% sucrose solutions for 2 hours each before embedding in OCT (Thermo Fisher Scientific) and rapidly frozen on dry ice stored at −80°C. Slides with 10-μm sections made with a cryostat were incubated in blocking buffer (2% FBS and 1% BSA in PBS) for 2 hours and then incubated with rat anti-GFP (FM264G, AlexaFluor 488; BioLegend), chicken anti-mCherry (ab205402; Abcam), rat anti-CD8 (53-6.7, AlexaFluor 647; BioLegend), rabbit anti-cleaved caspase 8 (polyclonal; Novus Biologicals), and/or rat anti-B220 (RA3-6B2, BV421; BioLegend) in 0.1× blocking buffer overnight. Slides were washed with PBS-Tween (0.1%) and incubated for 1 hour with donkey anti-rabbit (Poly4064, AlexaFluor 594 or 647; BioLegend) and/or goat anti-chicken (A32759, AlexaFluor 594; Thermo Fisher Scientific) secondary antibodies where indicated. ProLong Gold antifade (Thermo Fisher Scientific) was used as a mounting reagent, and 16-bit images were acquired on a Zeiss LSM780 confocal microscope. Images were analyzed using FIJI (67). For quantification, the mean intensity of the top 10% pixels of each channel was calculated on a standardized scale to remove background signal. For pixel colocalization analysis, Otsu and RenyiEntropy auto thresholding algorithms were applied before the Image Calculator function was used to perform logical operations on the binary images created from each channel. A total of at least 22 to 30 fields of view from 3 to 4 mice pooled from three independent experiments were included in the analysis.
Inhibition and Potentiation of Apoptosis
The following concentrations of agents were added to cocultures of T cells with target cells when indicated, except when specified differently: 100 μg/mL anti–PD-1 (RPM1-14; Bio X Cell), 100 μg/mL anti-IFNγ (XMG1.2; Bio X Cell), 25 μmol/L Z-IETD-FMK (Selleck), 1 μmol/L birinapant (APExBIO Technology), 100 nmol/L ABT-737 (Selleck), 1 nmol/L panobinostat (Selleck), and 10 nmol/L S63845 (Selleck). Other agents used during screening include venetoclax (Selleck), entinostat (Selleck), and fasentin (Sigma-Aldrich). Fas-mediated apoptosis during compound screening was induced by agonistic antibodies to mouse (Jo2, BD Biosciences; 10 ng/mL) or human (CH11, Millipore; 100 ng/mL) CD95.
CD3/CD19 Bispecific T-cell Engager Assays
Peripheral blood mononuclear cells (PBMC) were isolated from healthy donor blood by density gradient centrifugation using Ficoll Paque Plus (GE Healthcare), followed by red blood cell lysis using ACK buffer (Lonza). CD8+ T cells were negatively selected using the MojoSort Human CD8 T cell Isolation Kit (BioLegend) according to the manufacturer's protocol. CD8+ T cells were subsequently activated and expanded for 48 hours with 500 U/mL IL2 (R&D Systems) in RPMI with 10% FBS, 100 U/mL penicillin/streptomycin/ampicillin, and 50 μmol/L 2-mercaptoethanol. 4e4 preactivated CD8+ T cells were cocultured with 1e4 each of CD19+/+FAS+/+, CD19−/−FAS+/+, CD19+/+FAS−/−, and CD19−/−FAS−/− Raji cells in the presence of 500 U/mL IL2 and 100 pmol/L blinatumomab for 72 hours before analysis by flow cytometry. All Raji cells were labeled with CellTrace carboxyfluorescein diacetate succinimidyl ester (CFSE; Thermo Fisher Scientific), and all CD19+/+ Raji cells were also labeled with CellTrace Violet (Thermo Fisher Scientific) according to the manufacturer's protocol prior to seeding for gating purposes.
Generation of Mouse CD19-Targeting CAR-T Cells
Retroviral vector and CAR-T cells using a previously published anti-mouse CD19 CD3ζ-CD28 CAR construct (43) was generated as previously described (68) with the following adaptations. Briefly, leukocytes were isolated from spleens and lymph nodes of BALB/c mice. Single-cell suspensions were obtained by mechanical disruption and filtering through a 70-nm cell strainer. Red blood cells were lysed using ACK buffer (Lonza), and CD8+ T cells were negatively selected using the MagniSort Mouse CD8+ T Cell Enrichment Kit (Thermo Fisher Scientific) according to the manufacturer's protocol. Cells were activated in 6-well plates (1.5e6 cells per well) with 5 μg/mL plate-bound purified hamster anti-mouse CD3e (clone 145-2C11, BD Biosciences), 1 μg/mL purified hamster anti-mouse CD28 (clone 37.51, BD Biosciences), and 20 ng/mL recombinant mouse IL2 (Gemini Bio-Products) in RPMI with 10% FBS, 100 U/mL penicillin/streptomycin/ampicillin, and 50 μmol/L 2-mercaptoethanol. After one day, 1 mL/well of viral supernatant (thawed from stocks frozen at −80°C) was added to 6-well plates precoated with 15 μg/mL RetroNectin (Takara), and 2e6 cells in 1 mL complete media (supplemented with 80 ng/mL IL2) were added on top. The plates were centrifuged at 2,000 × g at 30°C for 1 hour before returning to the incubator (first spinoculation). The next day, 1 mL of media was carefully aspirated out and replaced with 1 mL new viral supernatant before centrifuging at 2,000 × g at 30°C for 1 hour again and returning to the incubator (second spinoculation). Cells were then expanded while maintaining at 1–2e6/mL in media supplemented with 20 ng/mL IL2 for 4 more days before cryopreservation.
In Vitro Mouse CAR-T Killing Assay
6e4 thawed mouse CAR-T cells were cocultured with 1.5e4 each of [CD19+ or CD19−] and [Fas+ or Fas−] A20 cells for 72 hours before analysis by flow cytometry. A homogeneous suspension of Precision Counting Beads (BioLegend) was uniformly added to each sample prior to analysis by flow cytometry. Normalized cell counts were calculated by dividing the number of event counts of a population of interest by the number of event counts of beads within the same sample, and normalized death was calculated by calculating the percentage of reduction in counts compared with the control sample.
In Vivo Mouse CAR-T Killing Assay
BALB/c mice were inoculated with homogeneous (100% A20 CD19+ cells) or heterogeneous (95% A20 CD19+/5% A20 CD19− cells) tumors immediately after 5 Gy total body irradiation (TBI). 2.5e6 CAR-T cells were adoptively transferred by tail-vein injection four days after TBI. For FasL blockade, 250 μg/mouse InVivoMab anti-mouse FasL (MFL3, Bio X Cell) was injected intraperitoneally every three days starting on the day of adoptive T-cell transfer, except for the first loading dose of 500 μg/mouse. Mice were tracked for survival every day and closely monitored for any signs of systemic disease (e.g., leg paralysis), for which they were euthanized.
In Vitro Human CAR-T Killing Assay
Human CAR-T-cell products were manufactured as described previously (44) and cryopreserved. 1e6 thawed CAR-T cells were cocultured with 5e4 each of CD19+/+FAS+/+, CD19−/−FAS+/+, CD19+/+FAS−/−, and CD19−/−FAS−/− Raji cells for six hours (unless otherwise indicated) before analysis by flow cytometry. All Raji cells were labeled with CellTrace CFSE (Thermo Fisher Scientific), and all CD19+/+ Raji cells were also labeled with CellTrace Violet (Thermo Fisher Scientific) according to the manufacturer's protocol prior to seeding for gating purposes.
In Vitro Killing Assays Using Primary CLL Cells
Patient PBMCs were collected and cryopreserved. 2e5 thawed patient cells were cocultured with 8e5 human CAR-T cells or 8e5 healthy donor CD8 T cells in the presence of 1 nmol/L blinatumomab for two days before analysis by flow cytometry. Patient cells were labeled with CellTrace Violet (Thermo Fisher Scientific) according to the manufacturer's protocol prior to seeding for gating purposes, and CD20+ cells were used for analysis of effects on malignant cells only.
Flow Cytometry and Cell Sorting
Viability staining was performed in HBSS using fixable viability stain 450 or 780 (BD Biosciences) at 1:1,000 for 5 minutes at room temperature (RT). Surface staining of mouse leukocytes was performed in FACS blocking buffer (made in house) using monoclonal antibodies against B220 (RA3-6B2; BioLegend), CD8 (53-6.7; BioLegend), CD4 (RM4-5; BioLegend), CD19 (6D5; BioLegend), CD45.1 (A20; BioLegend), CD45.2 (104; BioLegend), CD95 (SA367H8; BioLegend), CD107a (1D4B; BioLegend), H-2Kd (SF1-1.1; BioLegend), H-2Kd-HYLSTQSAL tetramer (NIH tetramer core facility), PD-L1 (10 F.9G2; BioLegend), NGFR (C40-1457; BD Biosciences), and TCRb (H57-597; BioLegend). Surface staining of human leukocytes was performed in FACS blocking buffer (made in house) using monoclonal antibodies against CD3 (HIT3a; BD Biosciences), CD4 (RPA-T4; BD Biosciences), CD8 (RPA-T8; BD Biosciences), CD19 (HIB19; BioLegend), CD20 (2H7; BioLegend), and CD95 (DX2; BioLegend). All surface antibodies were used at a dilution of 1:400, and samples were incubated with antibodies for 15 minutes at room temperature in the dark. Hoechst 33258 (BD Biosciences), fixable viability stains (BD Biosciences), Annexin V (BioLegend), and/or 7-AAD (BioLegend) were added according to the manufacturer's protocols to analyze dead cells. For intracellular staining, surface-stained cells were fixed and permeabilized using commercial buffer sets (Invitrogen), then stained with anti-cleaved caspase-3 (C92-605.1; BD Biosciences), anti-Granzyme B (NGZB; Thermo Fisher Scientific), or anti-IFNγ (XMG1.2; BioLegend) at 1:200 dilution for 30 minutes. Samples were acquired using an LSRFortessa (BD Biosciences) or Attune (Thermo Fisher Scientific), and data were analyzed with Cytobank. Cell sorting was performed on a FACSAria (BD Biosciences).
Analysis of RNA-seq Data
TCGA gene-expression (z-scores of RSEM RNA-seq V2) and survival data were downloaded from cBioPortal (69). For ZUMA-1 data, the paired-end reads were aligned to the Genome Reference Consortium Human Build 38 using STAR aligner (70). Gene counts for each sample were generated using the featureCounts function in the R/Bioconductor package “Rsubread” (71). The R/Bioconductor package “DESeq2” was used to apply the variance stabilizing transformation (VST) normalization on the count data (72). When multiple RNA-seq samples were available for one patient, the VST-normalized expression counts were averaged. The VST-normalized counts were used for comparing the expression distribution of FAS and CD19 genes among the patients with ongoing treatments versus others using the Wilcoxon test. The box plots were generated using the R package “ggpubr.” Expression thresholds for comparing survival outcomes were selected by implementing the “surv_cutpoint” function from the “maxstat” R package (73).
Data analysis was performed using GraphPad Prism6. An unpaired two-tailed Student t test was used to compare two independent groups; one-way ANOVA with Sidak correction for multiple comparisons was used to compare multiple (>2) groups with one independent variable; two-way ANOVA with Sidak correction for multiple comparisons was used to compare multiple (>2) groups with two independent variables; one-way ANOVA with Holm–Sidak correction for multiple comparisons was used to compare multiple (>2) groups with matched data points. P values > 0.05 were considered statistically nonsignificant (ns).
Data and Materials Availability
Human CAR-T-cell products, clinical correlates data, and RNA-seq data from ZUMA-1 used in this report are courtesy of Kite Pharma. Material requests should be directed to Kite Pharma. Results shown are in part based on data generated by the TCGA Research Network (www.cancer.gov/tcga). Otherwise, all other data supporting the findings presented in this study are available from the corresponding author upon reasonable request.
A. Bot reports personal fees from Kite, a Gilead Company, outside the submitted work. J.M. Rossi reports other from Kite, A Gilead Company, outside the submitted work. M. Merad reports personal fees from Compugen, personal fees from Innate Pharma, personal fees from Morphic Therapeutic, personal fees from Myeloid Therapeutics, personal fees from Celsius Therapeutics, grants and personal fees from Genentech, grants and personal fees from Regeneron, personal fees from Boehringer, and grants and personal fees from Takeda during the conduct of the study. B.D. Brown reports a patent for EP3043641B1 issued. J.D. Brody reports non-financial support from Kite/Gilead during the conduct of the study, and grants from Merck, grants from Genentech, grants from BMS, grants from Kite/Gilead, grants from Acerta, grants from Seattle Genetics, grants from Pharmacyclics, and grants from Janssen outside the submitted work.No other disclosures were reported.
R. Upadhyay: Conceptualization, formal analysis, validation, investigation, visualization, methodology, writing–original draft, writing–review and editing. J.A. Boiarsky: Investigation, writing–review and editing. G. Pantsulaia: Validation and investigation. J. Svensson-Arvelund: Investigation. M.J. Lin: Validation and investigation. A. Wroblewska: Investigation and methodology. S. Bhalla: Formal analysis and methodology. N. Scholler: Resources and project administration. A. Bot: Resources and project administration. J.M. Rossi: Resources and project administration. N. Sadek: Investigation. S. Parekh: Supervision, writing–review and editing. A. Lagana: Supervision. A. Baccarini: Supervision, funding acquisition, investigation, writing–review and editing. M. Merad: Conceptualization, supervision, funding acquisition, writing–review and editing. B.D. Brown: Conceptualization, supervision, funding acquisition, methodology, writing–original draft, project administration, writing–review and editing. J.D. Brody: Conceptualization, supervision, funding acquisition, methodology, writing–original draft, project administration, writing–review and editing.
We thank the flow cytometry core facility, microscopy core facility, and the Center for Comparative Medicine and Surgery at Icahn School of Medicine at Mount Sinai. We also thank S. Hekmaty, G. Panda, and R. Sachidanandam for assistance with sequencing, J. Javier Bravo-Cordero for assistance with image analysis, and A. Kamphorst for critical review of the manuscript. Research reported in this article was supported by NIH P30CA196521. R. Upadhyay was supported by NIH 5T32GM007280 and 5T32AI007605. M. Merad was supported by NIH R01CA154947 and R01CA190400. B.D. Brown was supported by the Cancer Research Institute (CRI), NIH R01AT011326, R01AI113221, and R33CA223947. B.D. Brown and M. Merad were supported by NIH U19AI128949. J.D. Brody was supported by the Damon Runyon Cancer Research Foundation, Merck Investigator Studies Program, CRI, and NIH R37CA246239.
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