Balancing the efficacy and safety of chimeric antigen receptor T-cell therapy by affinity combination

Domain: neuroscience
Published: 2026-04-10
Editorial outcome: major_revision

Abstract
Recent studies suggest that Chimeric Antigen Receptor (CAR) binding affinity to its ligand affects CAR-T-cell functionality. Affinity engineering towards lower binding strengths might mitigate therapeutic side effects arising from intense CAR-T-cell activation as well as tumor relapse due to antigen-escape or limited persistence of CAR-T cells during sustained activation via high-affinity receptors. Here we characterize a broad range of CARs with varying affinities to the same target epitope and leverage the insights we gain to design a combined high- and low-affinity CAR product. While CAR affinity impacts in vitro functionality minimally, it strongly correlates with tumor control in vivo. Low-affinity binders cause only mild cytokine release syndrome (CRS) in humanized mouse models at the expense of anti-tumour efficiency. In mixtures with low-affinity CARs, high-affinity CARs maintain strong functionality while showing reduced signs of exhaustion and monocyte-induced cytokine production, compared to high-affinity CAR-T cells alone. In long term in vitro and in vivo settings, low-affinity CAR-T cells dominate over time, proving more resilience to chronic antigen exposure. Overall, our findings demonstrate that affinity combination represents a promising strategy to generate more effective CAR-T-cell products with an improved therapeutic index, beyond affinity engineering alone.

Introduction
Adoptive cell therapy (ACT) with patient-derived T cells engineered with tumor-specific transgenic receptors emerged as a beacon of hope in the cancer field. T cells equipped with chimeric antigen receptors (CAR) have demonstrated remarkable success, in particular in refractory and relapsed B-cell malignancies expressing CD19 or BCMA1–6, leading to the FDA approval of currently seven CAR-T-cell products. Nevertheless, durable responses remain limited, motivating ongoing clinical investigation of novel approaches, including the use of fully human single-chain variable fragments (scFv) to minimize anti-CAR immune responses directed against murine scFvs7. The success of these therapies is now being extended to severe autoimmune indications with very promising first clinical data8,9.

However, initial therapeutic efficacy comes at the cost of acute side effects, namely cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). While CRS and ICANS are usually reversible, they occur frequently10–14 and must be managed accordingly to circumvent complications15,16. Even though CAR-T-cell activation represents the initial trigger, a broader part of the immune system is engaged, and monocyte-derived interleukin 6 (IL-6) and interleukin 1 (IL-1) are the main drivers of CRS pathophysiology17,18. Moreover, recent studies have demonstrated a correlation between the severity of CRS and the extent of hematotoxicity over-time19. Notably, prolonged cytopenia may persist beyond the resolution of CRS, posing a significant risk of infection and an increased likelihood of hemorrhagic complications.

Additionally, the effectiveness and wider use of current CAR-T-cell products are limited due to the common occurrence of disease relapses4,20,21. Being derived from antibodies, the affinities of scFvs selected for CAR-T-cell generation22 are typically 100 to 1000-fold higher than the physiological binding strength of natural T-cell receptors (TCR) towards their cognate antigens (CAR KD: 10−6-10−9 M versus TCR KD: 1–200 µM)23,24. The resulting ‘supra-physiological’ T-cell activation via high-affinity antigen binding is associated with accelerated exhaustion and reduced persistence of the transferred cells, as described for nearly all commercially available products25–27. High CAR binding affinity can also enhance the selection towards antigen loss or downregulation variants28. Besides these more commonly observed immune evasion mechanisms, recent studies also highlight the role of transient and short-term antigen escape, protein transfer and antigen depletion for the occurrence of disease relapses29. For example, trogocytosis—an intercellular contact-dependent material transfer—has lately been described as a mechanism interfering with CAR-T-cell efficacy. In particular, high-affinity CAR-T cells can exert strong trogocytosis, which can alter tumor recognition by reducing antigen density; in addition, antigen transfer to the CAR-T cells themselves can confer susceptibility to fratricide and affect their in vivo persistence28,30. These limitations spark an urgent need for the design of CAR-T-cell products with more effective properties.

Hence, multiple alternatives to commercially used CAR engineering approaches have been developed with the focus on bringing the synthetic receptor closer to physiological TCR characteristics31–34. These approaches include adjustments of the CAR antigen-binding affinity towards significantly lower affinities. For conventional T-cell responses, it is well established that T-cell functionality can be differentially affected by receptor affinity. Acute protective immunity is usually mediated by the recruitment of highly polyclonal T-cell populations with a broad spectrum of TCR-target antigen affinities. Out of these, T cells possessing higher TCR affinities for cognate epitope: major histocompatibility complex (MHC) ligands are more strongly expanded and confer superior in vivo target cell recognition and efficacy. Too high TCR affinities—beyond a not very well-defined threshold—do not further improve efficacy and are less dominant in vivo35–37. During chronic antigen exposure, high-affinity T cells are more prone to exhaustion and immune senescence. Therefore, T cells with lower-affinity TCRs can become more dominant and potentially also more relevant for long-term protection38–41. In line with these observations from normal T-cell responses, recent studies with lower-affinity CAR-T cells demonstrated comparable or even augmented cytotoxic activity42,43, while developing milder side effects25. These data have received increasing attention, since they indicate that optimal receptor binding affinity design could be used for both the reduction of side effects as well as the improvement of CAR-T-cell function and maintenance. However, determining an optimal affinity remains a demanding task, potentially requiring case-by-case optimization for each CAR:antigen pair as well as further adjustment to tumor characteristics (e.g., tumor burden and heterogeneity).

This study systematically examines how variations in CAR affinity influence the functional efficacy and safety profile of CAR-T cells and, more importantly, how integrating receptors of differing affinities can produce CAR-T-cell products with a more favorable therapeutic balance. We generate and comprehensively characterize CAR-T cells spanning a wide range of affinities down to TCR-like binding strengths and observe that while in vitro activation and cytotoxicity remain largely unaffected, in vivo anti-tumor efficacy strongly correlates with CAR affinity. Notably, low-affinity CAR-T cells substantially attenuate treatment-associated toxicity, and a combination of high- and low-affinity receptors enhances efficacy while limiting exhaustion and adverse events commonly associated with single-receptor high-affinity CAR-T-cell products.

Overall, our work highlights affinity combination as a practical approach to enhance CAR-T-cell efficacy while maintaining safety, paving the way for more balanced and widely applicable next-generation therapies.

Results
In vitro characterization of high- and low-affinity CAR-T cells
In order to systematically explore the effect of receptor affinity on CAR-T-cell characteristics, we selected two anti-human CD19 scFvs: JCAR017, which is derived from the high-affinity murine FMC63 antibody and is the central component of most commercially approved anti-CD19 CAR-T-cell products, and JCAR021, which is a fully humanized anti-CD19 CAR. We also employed the anti-CD19 scFv of the recently published CAT CAR as a reference for an affinity-reduced receptor with enhanced functionality25. To determine affinity, all scFvs were expressed as recombinant proteins conjugated to a Twin-Strep-tag (Fig. 1a), enabling their immobilization on a StrepTactin-coated surface for surface plasmon resonance (SPR) measurements. Using an engineered stable version of the extracellular domain (ECD) of the recombinant CD19 protein44, we confirmed the high affinity of JCAR017 (KD = 2.7 × 10−9 M). In comparison, JCAR021 showed a reduced affinity (KD = 1.4 × 10−7 M) closer to, but still slightly lower than the published CAT scFv (KD = 5.5 × 10−8 M) (Figs. 1b and S1a)25. Moreover, we observed that the differences in KD values were primarily driven by the dissociation kinetics (koff), rather than the association rate (kon) (Fig. 1b), consistent with other reports25. The epitope position within the three-dimensional structure of an antigen can affect CAR accessibility and, consequently, the functions of engineered T cells. Notably, our chosen scFvs recognize the same conformational epitope of CD19. This is evidenced by the lack of ECD CD19 binding to immobilized low-affinity JCAR021 in the presence of the high-affinity JCAR017 scFv (Fig. 1c, d).

To assess the impact of receptor affinity on T-cell functionality, we introduced the scFvs into a second-generation CAR backbone. The scFvs were linked via a CD28 transmembrane domain to the intracellular signaling domains CD3ζ and 4-1BB. An inert truncated epidermal growth factor receptor (EGFRt) was incorporated into the construct and utilized to track the efficiency of T-cell engineering45–47, while a triple repeat sequence of Strep-tag II (STII)46,48 was attached to the extracellular hinge domain to verify surface expression of the CAR construct (Fig. 1a). The vectors could be efficiently delivered with stable CAR surface expression (Fig. 1e). To examine how CAR affinity affects T-cell activation, we introduced the various CARs into a Nur77-tdTomato-Jurkat reporter cell line49. Within this reporter system, the fluorescent protein tdTomato is co-expressed with the early gene of TCR signaling Nur77, thus enabling a fast determination of CAR-T-cell sensitivity after antigen encounter50. Receptor affinity did not impact the activation strength (functional avidity) in this in vitro assay (Fig. 1f). We then introduced the described CARs into primary human T cells and observed that both high- and low-affinity CAR-T cells showed similar functionality in terms of cytokine production and cytotoxicity when co-cultured with CD19-expressing tumor cells (Figs. 1g, h and S1b, c), even at low effector-to target ratios and with CD19-low-expressing target cells (Fig. S1d, e).

Overall, we did not observe any significant impact on the in vitro functionality of CAR-T cells even when we reduced the CAR affinity by 50-fold.

Ligand binding affinity has only scarce impact on in vitro functionality of CAR-T cells
As the above investigated affinity range left in vitro functionality apparently unaffected but was still an order of magnitude higher than physiological TCR binding strengths, we explored the possibility of reducing the range of CAR affinities even down to physiological TCR:pMHC interactions. We used educated exchanges of 32 individual residues into the low-affinity binder JCAR021, which harbored a high probability to reduce the scFv affinity without compromising epitope specificity (Fig. 2a and Tab. S1). As the scFv dissociation kinetics (koff-rates) were the main determinant of the overall KD in our previous measurements (Fig. 1b), we adapted our flow cytometry-based TCR:ligand koff-rate technique51–53 to screen the library of mutated scFvs for potential changes in dissociation kinetics. Besides increased throughput compared to SPR, this method enables the monitoring of monomeric ligand dissociations under most physiological conditions (e.g., cell surface distribution and/or endogenous expression of the respective target antigen). For this purpose, mutated scFvs were double tagged in frame with a Strep-tag and a Tub-tag sequence (scFv Flexamer) (Fig. 2a). The tags enable the multimerization of monomeric scFvs on a StrepTactin backbone (scFv StrepTamer) and the site-specific conjugation of a fluorescent dye54 (Fig. 2b). scFv StrepTamers were used to stain PBMC-derived target CD19+ B cells. The administration of D-biotin leads to the displacement of the StrepTactin backbone due to its higher affinity compared to the Strep-tag, leaving monomeric scFvs attached to the target cells. The monomeric scFvs dissociate from cognate epitopes according to their intrinsic affinity, and the decay of the fluorescent signal can be translated into the koff-rate (Figs. 2b and S2a). The individual labeling of B cells with distinct fluorescence-conjugated anti-CD45 antibodies enabled multiplexed koff-rate measurements of up to 16 different scFvs simultaneously (Fig. S2b). In line with the SPR measurements, we observed a much slower dissociation kinetics for the JCAR017 scFv in comparison to the JCAR021 scFv. Quantitatively, JCAR017 and JCAR021 scFvs possessed koff-rates in a similar range as measured via SPR (JCAR017: SPR koff = 5.6 × 10−4 s−1 vs flow cytometry koff = 2.3 × 10−4 s−1; JCAR021: SPR koff = 2.1 × 10−2 s−1 vs flow cytometry koff = 4.1 × 10−2 s−1), thus validating the reliability of the flow cytometry-based measurement of scFv dissociation kinetics. For 26 JCAR021 scFv mutants, we were able to determine robust and highly reproducible koff-rate values and these demonstrated coverage of a broad range of distinct dissociation kinetics for individual amino acid exchanges (Figs. 2c and S2c). The remaining six mutants showed either an overall loss (H36P, F113P, W116E, Y174G) or largely reduced and variable (W116P, L184D) CD19 ligand binding (Figs. 2c and S2d), which precluded robust koff-rate measurements. By comparing the binding strength landscape of virus-specific TCRs55 with the JCAR021 mutants (these experiments had to be performed at lower temperatures (4°C) to allow measurement of fast TCR:pMHC dissociation kinetics), we could demonstrate that some JCAR021 mutants with the fastest koff-rates fell indeed within the range of TCR affinities (Fig. 2d). Notably, the temperature did not qualitatively alter the dissociation kinetics of either interaction (Fig. S2e).

We introduced the JCAR021 mutant scFvs into the same second-generation backbone as before (Fig. 2a). As stable receptor surface expression is one determining parameter for target recognition and CAR-T-cell functionality, we evaluated the efficacy of vector delivery and CAR surface expression via the transduction marker EGFRt and the CAR expression marker STII. Most of the mutants preserved an optimal CAR surface expression, as indicated by the correlation between STII and EGFRt, highly comparable to JCAR017 and JCAR021 (21/32, 66%, referred to as CARmfunct indicated in green). In contrast, the transgenic receptor was barely detectable at the cell surface of the remaining CAR-T cells (11/32, 34%, referred to as CARmlowfunct indicated in yellow), for which we observed either weak co-expression of the CAR and EGFRt markers, or transduction rates below 20% (Figs. 2e and S3a). Of note, the two CAR variants with EGFRt/STII co-expression levels apparently comparable to those of the CARmfunct group—namely F113L and W116E—exhibited little CAR surface expression.

Next, we re-expressed the JCAR021 mutant library into the Nur77-tdTomato-Jurkat reporter cell line49. The functional activation pattern among T cells engineered with JCAR017, JCAR021, and CARmfunct mutants was very similar despite the strong variations in antigen-binding affinity. In contrast, CARmlowfunct-T cells showed a drastically reduced activation pattern (Figs. 2f and S3b). Furthermore, when re-expressed in primary human T cells, CARmfunct-engineered T cells closely resembled cytokine production (IFN-γ, TNF-α and IL-2) and cytotoxicity as compared to the high-affinity binder JCAR017 or the original JCAR021. CARmlowfunct-engineered T cells, instead, showed a reduction in cytokine production or did not respond to the CD19 stimulus at all. Moreover, these T cells were predominantly unable to control target cell growth at low effector to target ratios (Figs. 2g, h and S3c, d). More challenging effector-to-target ratios and the use of CD19-high- and low-expressing target cell lines did not improve resolution with respect to the dependence of in vitro target cell killing on CAR affinity, except for the ultra-low, TCR-like-affinity CAR mutants (Fig. S4). Furthermore, we investigated the extent of interaction with the target cell membrane (trogocytosis) of selected mutants in comparison to JCAR017 and JCAR021 (Fig. S5a). As expected, the extent of trogocytosis decreased along with CAR ligand binding affinity (Fig. S5b, c), in line with recently published studies28,29.

In summary, surface expression of the CAR appears to have a greater impact on measurable in vitro functionality than the binding affinity of the scFv (Fig. 2i). Among the stable CAR constructs within the CARmfunct group, functional differences were observed only at ultra-low affinity levels—within the physiological range of functional TCRs (e.g. V236W and V236F). These variants showed slight reductions in cytokine production, notable differences in trogocytosis and reduced target cell killing at low effector-to-target ratios and low antigen density. Overall, these findings demonstrate that the threshold of CAR binding strength that still translates into effective in vitro functionality is remarkably low, even reaching down to low-affinity interactions with extremely fast koff-rates (t1/2 = 50 s at 20°C).

CAR ligand binding affinity influences recruitment, activation and anti-tumor efficacy in vivo
Within CARs with preserved and very similar surface expression, we observed comparable in vitro functionality irrespective of antigen-binding affinities, except when we analyzed CAR-ligand interactions as low as TCR-like binding affinities. Next, we assessed whether these similarities in functionality were also preserved in vivo. For this purpose, we selected the JCAR017 and JCAR021 CARs alongside three additional mutants that cover a broad affinity spectrum. The mutant L237W (t1/2 = 96 s) exhibited lower affinity than JCAR021 (t1/2 = 167 s), despite preserved in vitro functionality. We detected mutant M35A to be positioned at the threshold of in vitro functional CARs (t1/2 = 64 s) with further reduced affinity. Finally, mutant V236W harbored one of the fastest koff-rates (t1/2 = 43 s) and displayed reduced functionality compared to other CARmfunct even in vitro. Notably, the three selected mutants belonged to the CARmfunct group with stable surface expression, therefore attributing potential differences in CAR performance primarily to the scFv affinity.

We initially assessed in vivo functionality using an immunocompromised mouse model with implanted CD19+ Raji lymphoma cells (Fig. 3a). These cells were additionally modified to express firefly luciferase for bioluminescence imaging and green fluorescent protein (GFP) for peripheral detection. The T-cell products of the five CAR constructs demonstrated comparable levels of CAR expression with a strong correlation between EGFRt and STII (Figs. 3b and S6a), an equal distribution of CD8+ and CD8− T cells (Fig. 3c) and a similar ex vivo phenotype (Fig. 3d) prior to infusion. Eleven days after T-cell transfer, the majority of mice treated with non-transduced T cells (mock) had to be sacrificed due to rapid tumor progression, while the ultra-low-affinity mutant V236W provided minor survival benefits. Mice treated with the low-affinity CARs JCAR021, L237W and M35A demonstrated improved survival. However, in contrast to our results observed in vitro, lower-affinity CARs were less effective in controlling tumor progression as the high-affinity JCAR017-T cells (Figs. 3e, f and S6b).

To gain a clearer understanding of the factors contributing to the reduced in vivo efficacy of lower-affinity CARs, we examined the proliferative capacity and activation of transferred cells. JCAR017-T cells were significantly stronger expanded in peripheral blood as early as seven days post-transfer and continued to expand throughout the observation period. In contrast, the lower-affinity CARs reached higher numbers compared to JCAR017 in peripheral blood at day 14 post CAR-T-cell transfer. The only exception was the ultra-low mutant V236W-treated cohort, in which CAR-T cells were detectable at an early time point, similar to the JCAR017 cohort (Fig. 3g). Nevertheless, the quantity of circulating T cells does not necessarily reflect their impact on combating the disease, so we further investigated the CAR-T presence at the tumor site. Recent studies have shown that low-functional T cells can be enriched in the peripheral circulation rather than at the tumor site in cancer patients39. Therefore, we assessed T-cell infiltration into the bone marrow, the primary site of Raji cell localization, and the spleen, which is only minimally invaded by tumor cells unless there is an extremely high burden (Fig. S6c). Although CAR-T cells from all groups successfully engrafted, we observed significantly higher numbers of EGFRt+ cells in the bone marrow of mice treated with high-affinity JCAR017-T cells (Fig. 3h). T-cell infiltration was generally similar for the low-affinity CAR-T cells, except for the ultra-low-affinity clone V236W, which showed lower abundance. Conversely, the CAR-T-cell quantity in the spleen was equivalent in all treated mice (Fig. 3h), suggesting a preferential spatial distribution of T cells within the tumor based on receptor affinity.

Additionally, we observed a correlation between the activation status of CAR-T cells and their receptor affinity in both blood and tissues. Specifically, the frequency of activated PD-1+ HLA-DR+ cells was significantly reduced in both compartments of M35A and V236W-treated mice compared to the high-affinity JCAR017 (Fig. 3i). Furthermore, JCAR017-T cells maintained a higher frequency of memory cells (CD45RA−), whereas lower-affinity CARs displayed a more differentiated phenotype (CD45RA+ CD62L−), likely due to the increasing tumor burden. Notably, the ultra-low-affinity V236W CAR-T cells retained a more naïve/stem-like phenotype, indicating less activation or recruitment into the tumor response. We did not observe these variabilities within the spleen, where we identified predominantly central or effector memory differentiated populations among the EGFRt+ CAR-T cells (Fig. 3j).

Finally, we investigated whether escalating CAR-T-cell doses could rescue the in vivo anti-tumor efficacy of low-affinity CAR-T cells (Fig. S7a, b). Low doses of JCAR017-CAR-T cells were sufficient to ensure survival of all treated mice, even though residual tumor burden correlated with CAR-T-cell doses and expansion (Fig. S7c–g). Increasing doses of low-affinity CARs increased survival rates but resulted only in a dose-dependent delay of tumor progression despite the high levels of circulating CAR-T cells (Fig. S7c–g).

Overall, we revealed that scFv affinity plays a pivotal role in determining effective in vivo anti-tumor activity by driving proper CAR-T-cell activation and recruitment to the tumor site. Large numbers of low-affinity CAR-T cells only delayed tumor progression in a dose-dependent manner.

CAR-T-cell-associated toxicities are influenced by T-cell dose and receptor affinity
In order to investigate whether binding affinity also affects CAR-T-cell-related toxicities, we reconstituted a human-like immune compartment in immunocompromised triple transgenic NSG-SGM3 (NSG-S) mice with cord blood-derived CD34+ hematopoietic stem cells (HSCs) as described by Norelli et al.18. The transgenic expression of human stem cell factor, granulocyte/macrophage colony-stimulating factor (GM-CSF), and IL-3 supports the maintenance and differentiation of HSCs, especially within the myeloid cell lineages, which are key mediators for CRS18. We recently improved this model by reducing CD34+ HSC doses to produce cohorts of humanized mice derived from a single cord blood donor, thereby improving reproducibility and reliability of humanization56.

To recapitulate the clinical situation, we established a system that allows the use of CD19+ tumor cell lines (Raji or Nalm-6) and healthy donor-derived PBMCs as CAR-T-cell source (Fig. 4a). We observed successful humanization within eight weeks after CD34+ HSC engraftment, indicated by the CD45+ chimerism in the blood of treated NSG-S mice. During the humanization process all model relevant human immune compartments were reconstituted—including hCD19+ B cells, hCD33+ macrophages and hCD14+ monocytes (Figs. 4b, c and S8a, b).

Firstly, we assessed the feasibility of the model in inducing CRS by infusing escalating doses of JCAR017-T cells into humanized tumor-bearing NSG-S mice (hNSG-S). As expected, the anti-tumor activity and peripheral CAR-T-cell expansion correlated with CAR-T-cell doses (Fig. S8c–i). Importantly, CAR-T-cell-treated mice exhibited clinical symptoms of CRS, including weight loss and elevated serum cytokine levels (Fig. S8j, k), which were proportional to the administered T-cell dose. Symptoms were reversible in most cases, except in a certain proportion of mice (33%) treated with the highest T-cell dose (Fig. S8l).

Next, we evaluated the side effects induced by the low-affinity JCAR021. Therefore, JCAR017 and JCAR021 CAR-T cells with comparable characteristics in terms of receptor expression as well as CD8+/CD8− distribution were transferred into tumor-bearing hNSG-S mice (Fig. S9a–c). All CAR-T-cell-treated mice developed clinical symptoms of CRS (Fig. S9d–e). Nevertheless, mice treated with JCAR021-T cells experienced a significantly milder extent of weight loss, which also peaked at earlier time points compared to JCAR017-T-cell-treated mice, thereby allowing a faster recovery (Fig. S9d). Additionally, elevated levels of circulating INF-γ, IL-10, and IL-6 cytokines were observed in both treated groups, but at lower levels in JCAR021-T-cell-treated mice (Fig. S9e). The observed pattern of CRS development was in line with the differences in in vivo functionality for the two CAR-T-cell products. Indeed, consistent with the non-humanized NSG-S model, JCAR017-T cells exhibited superior antitumor activity, greater expansion potential and faster systemic depletion of CD19+ B cells than JCAR021-T cells in the acute phase 7 days post injection (Fig. S9f–l). This more robust expansion may account for, and potentially drive, the severity of the observed toxicity.

Next, we wanted to assess the dose effect of JCAR021-T cells when compared with JCAR017. To this end, we administered high- and low-doses of the two CAR-T cells into hNSG-S mice applying the same experimental procedure as previously described (Fig. 4d, e). All CAR-T-cell-treated mice developed clinical signs of CRS, with variability depending on both the receptor affinity and T-cell dose (Fig. 4f, g). JCAR017-T cells displayed a dose-dependent increase in CRS severity. In contrast, low-affinity JCAR021-T cells treated mice displayed only intermediate CRS severity irrespective of the applied dose levels (Fig. 4f). Similarly, when we analyzed serum cytokine levels, we observed a clear dose-dependent effect for the high-affinity CAR but not for the lower-affinity CAR-T treated mice (Fig. 4g). Regarding anti-tumor effects, both doses of JCAR017-T cells successfully eradicated the tumor, with faster response rates at the highest dose, while low-affinity CAR-T cells were less effective. Nevertheless, a high dose did provide a noticeable benefit compared to untreated mice, as observed before (Fig. 4h, i). We identified that CRS development and cytokine production aligned with the degree of T-cell expansion at early time points (day five). JCAR017-T cells displayed the strongest expansion in a dose-dependent manner, followed by the high- and low-doses of JCAR021-T cells (Fig. 4j).

In summary, lowering the binding strength of the CAR can reduce the severity of CRS, although at the cost of functionality. Remarkably, CAR-T-cell doses seems to correlate with the toxicity profile of high-affinity but not low-affinity receptors.

High-affinity CAR-T cells show fewer signs of toxicities and exhaustion when combined with low-affinity CARs in vitro
Next, we explored the possibility of creating a CAR-T-cell product with improved characteristics by combining the potency of high-affinity receptors with the safety profile and longevity of lower-affinity receptors. For this purpose, we evaluated the cytokine release of affinity-combined CAR-T-cell products composed of an equal amount of the high-affinity JCAR017-T cells and lower-affinity CAR-T cells (JCAR021, S168C or S227K) after co-culture with CD19+ target cells and donor-matched monocytes. These mixed products were compared with two JCAR017-T-cell controls: one matched for the total CAR-T-cell dose and one matched for the number of JCAR017-T cells present in the affinity-combined product. (Fig. 5a). To distinguish between CAR constructs, an Ametrine fluorescent protein was co-expressed with the JCAR017-CAR. After 24 h of co-culture, absolute cell numbers of CAR-T cells were comparable among the different groups (Fig. 5b), with a balanced composition of the high- and low-affinity CAR-T cells in the combined products (Fig. 5c). While all CAR groups showed similar CD19-specific target lysis, the mixed products induced significantly lower levels of CRS-associated cytokines than the same total dose of JCAR017-T cells alone and exhibited cytokine release comparable to the half-dose JCAR017 control (Fig. 5d, e). These observations indicate that adding lower-affinity CAR-T cells does not increase toxicity beyond what is expected from reducing high-affinity CAR T-cell numbers.

We then aimed to investigate the potential benefits of an affinity-combined CAR-T-cell product after prolonged antigen exposure. To do this, we performed chronic antigen stimulation assays and assessed expansion and longevity potential of the individual CARs compared to the affinity-combined T-cell products (Fig. 5f). The combined-affinity products expanded similarly to high- and lower-affinity CAR-T cells alone (Fig. 5g). Notably, lower-affinity CAR-T cells showed higher expansion kinetics under chronic stimulation regardless of the supplementation of high-affinity CAR-T cells, thus reaching the majority in the combined cell product (Fig. 5h, i). We then examined the expression of PD-1, Lag3, TIM3, and TIGIT to assess the level of exhaustion. All four markers showed significantly higher levels in the high-affinity JCAR017-T cells compared to both the lower-affinity and combined T-cell products (Fig. 5j). Remarkably, the proportion of TIGIT+ TIM3+ and TIGIT+ PD-1+ cells was reduced in JCAR017-T cells when used in combination with lower-affinity T cells, as opposed to when JCAR017-T cells were used individually (Fig. 5k). Finally, we assessed whether the affinity-combined product can retain similar anti-tumor activity to high-affinity CAR-T cells alone. We therefore focused on the two ultra-low-affinity variants (V236W and V236F) that exhibited impaired in vitro cytotoxicity under condition of low E:T ratios and low antigen density (Fig. S4). Notably, the combined products rescued the suboptimal cytotoxic capacity observed with low-affinity CAR-T cells alone, achieving levels of target cell killing comparable to the same dose of high-affinity CAR-T cells but exceeding those of the 0.5× dose JCAR017 control, particularly under stringent conditions of low E:T ratios and low antigen density (Fig. S10). To extend our findings, we evaluated an additional pair of high- and low-affinity CARs recognizing the same epitope on the human ROR1 antigen—CAR R12 (high-affinity, KD = 0.11 nM) and CAR R12v20 (lower-affinity, KD = 0.98 nM)57 (Fig. S11a). Similar to the CD19 model, a 50:50 combination of high- and low-affinity CAR-T cells achieved cytotoxicity comparable to full-dose high-affinity R12 CAR-T cells while outperforming lower-affinity R12v20 CAR-T cells (Fig. S11b, c), and exhibited significantly lower exhaustion levels than high-affinity CAR-T cells after chronic stimulation (Fig. S11d).

Overall, the affinity-combined cell product mitigated CRS severity, limited exhaustion in high-affinity CAR-T cells, and preserved functionality, with particular resilience against functionality loss when targeting cells with low antigen expression.

High-affinity CAR-T cells show superior functionality and fewer signs of exhaustion when administered with low-affinity CARs in vivo
We next explored the potential of an affinity-combined CAR-T-cell product in vivo. We first evaluated whether the suboptimal tumor control observed with low-dose high-affinity CAR-T cells could be rescued by higher doses of low-affinity CAR-T cells (Fig. S12a). This strategy was designed to minimize CRS, as CRS severity correlated with the dose of high-affinity—but not low-affinity—CAR-T cells (Fig. 4). While JCAR017-T cells alone delayed tumor growth, the combination with JCAR021-T cells produced a dose-dependent reduction in tumor burden. Nevertheless, a significant effect emerged only at particularly high doses of JCAR021-T cells (16-fold higher than JCAR017) (Fig. S12b, c), indicating the importance of maintaining adequate levels of high-affinity CAR-T cells for achieving effective anti-tumor responses.

Furthermore, we conducted experiments applying constant cell doses, consisting of either equal amounts or varying ratios of high- and low-affinity CARs (Figs. 6a and S13a). As observed in our previous experiments, survival did depend on the transfer of even low doses of JCAR017-T cells (Fig. 6b). Residual tumor burden further decreased based on the quantity of transferred JCAR017-T cells (Figs. 6c and S13b). Remarkably, a 1:1 ratio of JCAR017 to JCAR021 exhibited a more rapid anti-tumor response compared to JCAR017 alone (Figs. 6c and S13b), which we validated in an independent experiment (Fig. S12d, e).

While JCAR017-T cells exhibited dose-dependent expansion kinetics, the same dose (0.8×106 cells) expanded differently depending on whether it was administered alone or in combination with low-affinity CAR-T cells, with JCAR017-T cells expanding and infiltrating the bone marrow less when combined with JCAR021-T cells (Figs. 6d and S13c). These findings indicate that the observed faster tumor clearance mediated by the affinity-combined product is likely attributable to a synergistic interaction between the high- and low-affinity CAR-T cells, rather than the overall higher T-cell dose. Our data also demonstrate that the behavior of high-affinity CAR-T cells can be modulated by addition of lower-affinity CAR-T cells, even when the high-affinity CAR-T-cell dose remains at high numbers.

To explore this further, we isolated the transferred CAR-T cells 30 days after infusion to ensure sufficient antigen exposure to capture relevant differences in the transcriptomic profile of JCAR017-T cells. Remarkably, the transcriptomic profiles of JCAR017-T cells strongly differed depending on whether the cells were administered individually or in combination with low-affinity CARs. CAR-T cells isolated from mice treated with JCAR017 alone were predominantly represented in cluster 1, whereas high-affinity JCAR017-T cells of the combined cell products were in cluster 0 and 6 (Figs. 6e and S13d, e). Genes overexpressed in JCAR017-T cells within the affinity-combined products collectively suggested active migration toward inflammatory sites and tissue residency (CXCR6 and ITGA1)58, together with sustained pro-inflammatory/cytotoxic responses (ALOX5AP, KLRD1, STAT, and JAK3). Along these lines, we further observed upregulation of genes related to increased energy demand and activation (MT-CO3 and FKBP1)59,60. In contrast, JCAR017-T cells alone exhibited traits of impaired memory T-cell formation and survival (downregulation of CD27, KLF2, and TNFSF4), metabolic shifts towards glycolysis (lower CMC1)61 and an enhanced effector phenotype (reduced IL10RA, and SIRPG)62–64. Altogether, this profile indicated highly activated effector T cells prone to an immediate response rather than sustaining long-lived memory cells (Fig. 6f). Notably, when considering a set of 262 genes linked to T-cell exhaustion and dysfunction65,66, JCAR017-T cells administered alone showed higher levels of several exhaustion-related genes compared with the affinity-combined cohorts, which displayed upregulation of only a few exhaustion-associated genes and showed a profile more similar to the lower-affinity CAR-T cells (Fig. 6g). Interestingly, the shift toward a less exhausted phenotype in high-affinity JCAR017-T cells became progressively more pronounced from the 10:90 to the 50:50 combination ratios. This trend is likely attributable to increased antigen pressure on JCAR017-T cells when delivered at lower doses, as further supported by the higher residual tumor burden observed under these conditions (Fig. 6c). Accordingly, key exhaustion-associated genes, such as CCL5 and TOX, were expressed at significantly lower levels in JCAR017-T cells from the 50:50 combination (Fig. 6h). Conversely, the expression of genes implying greater cytotoxic potential (KLRD1, SCML4 and GZMB) was increased in affinity-combined JCAR017-T cells (Fig. 6i), resulting in reduced exhaustion and dysfunctional scores, most notably in the 50:50 dosing condition (Fig. 6j). These data were in line with in vitro observations (Fig. 5j, k).

Overall, our findings suggest that the enhanced tumor clearance observed with the affinity-combined product could be driven by a synergistic interaction between high- and low-affinity CAR-T cells, rather than by the overall higher T-cell dose. Our data also demonstrate that the behavior of high-affinity CAR-T cells can be modulated by the addition of lower-affinity CAR-T cells, even when the high-affinity CAR-T-cell dose remains at high numbers. Collectively, our data demonstrate that low-affinity CAR-T cells augment the anti-tumor efficacy of high-affinity CAR-T cells by preserving their functional state and mitigating terminal differentiation and exhaustion.

Methods
All experiments were conducted in accordance with all relevant ethical regulations. The study protocol involving human samples was approved by the local Institutional Review Board (Ethikkommission der Medizinischen Fakultät der Technischen Universität München). The conducted animal experiments were approved by the local authorities especially the district government of Upper Bavaria (Department 5—Environment, Health and Consumer Protection ROB-55.2-2532.Vet_02-18-162).

Cell culture
Cell lines (Raji-ffluc-GFP, Nur77-Jurkat kindly provided by Juno Therapeutics GmbH, a Bristol Myers Squibb company; Nalm6-ffluc-GFP, RD114, HEK293T cells kindly provided by the Stanley Riddell laboratory at the Fred Hutchinson Cancer Research Center, Jeko-1 ffluc and A549 ffluc cells kindly provided by the Michael Hudecek laboratory at the Department of Internal Medicine II, University Hospital Würzburg) were cultivated in Gibco RPMI 1640 medium (Thermo Fisher Scientific) or Gibco DMEM (Thermo Fisher Scientific) at 37°C, 5% CO2, and 95% humidity. Both media were supplemented with 10% fetal bovine serum (FBS; Sigma Aldrich), 0.025% L-glutamine (Gibco BRL), 0.1% HEPES (Gibco BRL), 0.001% gentamycin (Gibco BRL) and 0.002% streptomycin (Gibco BRL) (“complete medium”, cRPMI or cDMEM).

Primary T cells were derived from healthy donors. Written informed consent was obtained from the participants, and usage of the blood samples was approved according to national law by the local Institutional Review Board (Ethikkommission der Medizinischen Fakultät der Technischen Universität München). Blood was diluted 1:1 (whole blood) or 1:2 (buffy coat) with sterile PBS and peripheral blood mononuclear cells (PBMC) were isolated by density gradient centrifugation using Pancoll solution (density 1.077 g/mL) (PanBiotech) according to manufacturer’s protocol. For engineering, human T cells were cultured at a density of 1 × 106 cells/mL in complete RPMI and activated with 2.25 µl/mL anti-CD3/CD28 Expamer Reagent (Juno Therapeutics GmbH, a Bristol Myers Squibb company)79 as well as 360 IU/mL IL-2 (Peprotech) for 48 h. Jurkat cells were thawed and cultured for one week. For in vitro cell culture, bulk T cells were cultured at a density of 1 × 106 cells/mL in complete medium supplemented with 50 IU/mL IL-2. For rapid expansion, T cells were cultured at a density between 0.25—0.5 × 106 cells/mL in complete RPMI supplemented with 200 IU/mL IL-2, 0.5 ng/mL IL-7 and 0.5 ng/mL IL-15.

Human HSC were derived from umbilical cord blood. After cord blood mononuclear cells (CBMC) isolation via density gradient centrifugation using Pancoll solution (density 1.077 g/mL), CD34+ HSCs were enriched by magnetic cell isolation using the CD34 Microbead Kit (Miltenyi Biotech) according to the manufacturer’s protocol. All cells were stored in freezing medium (10% DMSO and 90% FBS; Sigma Aldrich) for cryopreservation at a maximum concentration of 10 × 106 cells/mL.

DNA template design for scFv periplasmic protein production and CAR transduction
scFv sequences of JCAR017 (clone: FMC63) and JCAR021 were kindly provided by Juno Therapeutics GmbH, a Bristol Myers Squibb company. scFv sequences of the clone CAT was obtained from the publicly available patent (WO 2014/184143 A1). scFvs were generated by fusing the variable regions of the heavy (VH) and light (VL) chains with a short (G4S)3 linker. DNA templates were designed in silico and synthesized by GeneArt (Thermo Fisher Scientific) or Twist Bioscience. Anti-ROR1 CARs (R12 and CDR3 mutated R12v20) were kindly provided by the Michael Hudecek laboratory at the Department of Internal Medicine II, University Hospital Würzburg. Both ROR1 were constructed using the VL and VH segments of the R12. The scFv was linked by a (G4S)3 linker, a CD28 transmembrane domain and a 4-1BB cytoplasmic domain.

For periplasmic expression, scFv sequences were linked to a Twin-Strep-tag and a Tub-tag sequence building so-called ‘scFv FLEXamers’54. For CAR constructs, the signal peptide of GM-CSF receptor subunit α, which enables the transport and integration of the receptor into the membrane, was followed by an anti-CD19 scFv. The extracellular binding domain was linked to a spacer domain comprising a triple repetitive sequence of Strep-tag II (STII)46,48 and parts of the IgG4-Fc molecule, followed by a transmembrane region originated from the CD28 chain. The following intracellular signaling domains, CD3-zeta and 4-1BB, were separated by a viral T2A peptide from a truncated version of EGFR (EGFRt) used as a marker of template integration45,47. To distinguish JCAR017 and JCAR021 in affinity combination experiments, the sequence of the fluorescent protein Ametrine and mCherry were included on the C’-terminus and connected by a T2A element.

Generation of JCAR21 scFv mutants
The three-dimensional structure of the extracellular JCAR021 scFv binding domain was modeled in silico with the ABodyBuilder software by SAbPred80, and applied to the web server mCSM-AB81 for the prediction of mutational affinity changes. The delta in Gibbs free energy (ΔΔG) of JCAR021 after binding to the extracellular domain of the CD19 protein was calculated for all possible single amino acid substitutions within the JCAR021 scFv. Out of 231, 32 were selected for further analysis of reduced receptor binding affinity, with 19 substitutions being located in the framework region and 14 in the CDRs region (Tab. S1). While amino acid exchanges within the framework region were chosen based on the alteration in Gibbs free energy, those in the CDRs were only considered when similar biochemical properties (groups: hydrophobic, polar, acidic and nonpolar) were retained to preserve CAR specificity (Tab. S1). These selected amino acid substitutions were integrated via Q5 site-directed mutagenesis PCR (New England Biolabs GmbH) and subsequently cloned into the pMP72 and pASG-IBAwt2 vectors for retroviral transduction and periplasmic protein production, respectively. The pMP72 vector was derived in-house from the pMP71 vector (a kind gift from W. Uckert, Max-Delbrück-Centrum for Molecular Medicine, Berlin).

Recombinant protein expression of soluble scFvs
scFv DNA strings were cloned into a pASG-IBAwt2 vector (IBA Lifesciences) and expressed in electrocompetent E. coli JM83 (IBA Lifesciences). Expression was induced with anhydrotetracycline (IBA Lifesciences) (AHT—1:105; IBA Lifesciences) at an OD600 of 300 for at least 3 h or as soon as OD600 values stabilized at 37°C. Bacteria were centrifuged (5000 rpm, 4°C, 12 min), and the pellets were stored at −80°C. Lysis was performed in 10 mL periplasmic lysis buffer (100 mM Tris/HCl pH 8.0—Roth, 500 mM Sucrose—Sigma Aldrich, 1 mM EDTA—Sigma Aldrich) (30 min, 4°C) followed by debris centrifugation (15,000 rpm, 4°C, 15 min), nucleic acid digestion in 125 U Benzonase (Sigma Aldrich) (1 h, 4°C, rolling) and scFv purification on Strep-Tactin superflow columns (IBA Lifesciences) according to manufacturer´s instructions. Protein concentrations were measured via spectrophotometry at 280 nm, and purity was determined via SDS-PAGE. Purified scFv protein aliquots were shock-frozen in liquid nitrogen and stored at −80°C.

Retroviral transduction
CAR DNA templates were cloned into the retroviral expression vector pMP72. The mp72 vector was generated in-house by modifying the multiple cloning site of the mp71 vector to introduce specific restriction sites. The mp71 vector was kindly provided by W. Uckert (Max-Delbrück-Centrum für Molekulare Medizin, Berlin). The RD114 packaging cell line was seeded at a density of 1 × 106 cells in 3 mL of cDMEM per well of a six-well plate and allowed to adhere for 18 h. At approximately 80% confluency, the cells were transiently transfected via calcium phosphate precipitation using 18 µg DNA template followed by a medium exchange after 6 h of incubation. After 3 days, virus-containing supernatant was harvested, filtered through a 0.45 µm filter and used directly or stored at 4°C for up to one month. Tissue-culture untreated 24-well plates were coated overnight with 300 µl RetroNectin (Takara Bio Europe, 1:100 in sterile PBS) according to the manufacturer’s protocol. 500-700 µl of virus-containing supernatant was added and centrifuged at 2000 g at 32°C for 2 h, followed by the addition of 0.5 × 105 activated cells (see ‘Cell culture” section) in 200 µl RPMI medium. Primary human T cells were supplemented with 200 IU/mL IL-2. Plates were centrifuged at 800 g, 32°C for 30 min and incubated at 37°C for 48 h before further analyses. Primary human CAR-T cells were expanded as described earlier and used no later than three weeks after generation for functional in vitro and in vivo characterization.

Lentiviral transduction
Lentiviral particles were produced in HEK293T cells using transient transfection. A total of 1 × 106 cells were seeded one day prior to transfection to reach approximately 70-80% confluency. Cells were co-transfected with the lentiviral transfer plasmids together with the packaging plasmids psPAX2 (gifted from Didier Trono; Addgene plasmid #12260) and pMD2.G (gifted from Didier Trono; Addgene plasmid #12259) using Lipofectamine (Thermo Fisher Scientific), according to the manufacturer’s protocol. Six hours after transfection, the medium was replaced with fresh cDMEM. Lentiviral supernatants were collected 48 h post-transfection, concentrated and filtered. Viral supernatants were stored at −80°C until further use.

One day prior transduction, primary human T cells were isolated from healthy donors, seeded at a concentration of 1 × 106 cells per mL (500 µL per well) in a 48-well plate and activated for 24 h as previously described. Lentiviral supernatants were thawed and mixed thoroughly prior to use. Before virus addition, 333 µL medium was removed from each well, and Polybrene was added at a final concentration of 5 ng/mL. Lentivirus was added at an MOI of 3, followed by centrifugation for 45 min at 800 × g and 32°C. After centrifugation, plates were incubated for 4 h, after which fresh cRPMI supplemented with 200 IU/mL IL-2 was added to each well. CAR-T cells were expanded as described previously and used within three weeks of generation for in vitro functional analyses.

Surface antibody staining
48-72 h after transduction, primary T cells or Nur77 Jurkat reporter cells were harvested, washed in 200 µl FACS buffer (1× PBS, 0.5% bovine serum albumin) and evaluated for CAR surface expression by flow cytometry. Up to 5 × 106 cells were stained in 50 µl mastermix containing all required fluorophore-conjugated antibodies at recommended dilutions (Tab. S2) for 20 min on ice in darkness. For live/dead discrimination, propidium iodide (PI; Life Technologies—1:100) was added during the last 3 min of incubation. Cells were washed twice and filtered with 200 µl FACS buffer prior to acquisition on a Cytoflex S flow cytometer (Beckman Coulter). Data analysis was performed with the FlowJo software v10.8.0 (Treestar).

Where cell quantification was demanded, 123count eBeads (Thermo Fisher Scientific) were added to individual samples according to the manufacturer’s protocol. Specific information is supplied with each experiment.

Fluorescent-activated cell sorting
For cell purification, CAR-engineered PBMCs were harvested and washed with 5-10 mL FACS buffer. Up to 5 × 106 cells were incubated in 50 µL antibody mastermix for 20 min in the dark at 4°C and washed at least twice with 10 mL ice-cold FACS buffer. Cell aggregates were removed by passing cells through a sterile 30 µm filter. The whole procedure was performed under sterile conditions. The PI solution was added immediately before cell sorting. CAR-T cells were sorted on a MoFlo Astrios cell sorter (Beckman Coulter) at RT and cultivated afterwards as described above.

SPR and epitope mapping
SPR experiments were performed using the Biacore T200 instrument (Cytiva). A CM5 sensor chip was pre-treated with 50 mM NaOH (3× 1 min), activated with NHS/EDC for 10 min and coated with 50 µg/mL Strep-Tactin XT (diluted in immobilization buffer, pH 4.5) for 10 min. After immobilization, inactivation of reactive ester groups was conducted by addition of 1 M ethanolamine for 10 min. All reagents originated from the Twin-Strep-tag Capture Kit (IBA Lifesciences) or the amine coupling kit (Cytiva). Twin-Strep-tagged scFv FLEXamers were captured at a concentration of 50 nM at a flow rate of 10 µL/min for 60 s. For analysis of the binding between the different scFvs and CD19, a stability-engineered variant of the CD19-ECD, termed SF-CD19, was used as the soluble interaction partner44. SF-CD19 was expressed in HEK293 6E cells, followed by cleavage of the expression tags, as described previously82. Different concentrations of SF-CD19 were injected at a flow rate of 30 µL/min in running buffer HBS-EP (Cytiva) at 25°C, followed by injection of running buffer only. The chip surface was regenerated after each cycle by injection of 3 M GuHCl for 60 s at a flow rate of 10 µL/min. Data were fitted with a 1:1 kinetic binding model using the global data analysis option available within Biacore T200 Evaluation Software (Cytiva).

Competition assays were performed in a similar setup. 50 nM of Twin-Strep-tagged scFv FLEXamers were captured for 60 s with a flow rate of 30 µL/min, followed by injection of 10 nM SF-CD19 for 180 s and a buffer injection for 360 s. The chip surface was regenerated as described before, and 50 nM of Twin-Strep-tagged scFv FLEXamers were injected again for capture on immobilized StrepTactin XT. In a second step, a mixture consisting of 10 nM SF-CD19 and 100 nM FMC63 scFv was injected. Raw binding curves were plotted after subtraction of buffer baseline.

Tubulin tyrosine ligase (TTL)-mediated functionalization
Conjugation with fluorescent dye was performed as previously described54. scFv buffer was exchanged with FPLC buffer (or MES/K if concentrations are < 1.8 mg/mL) by size-exclusion chromatography (Zeba Spin desalting columns, 7K MWCO) prior quantification. TTL-catalyzed ligation of 3-acid tyrosine to scFv FLEXamer was performed in 100 µL consisting of 20 µM scFv FLEXamers, 5 µM TTL, and 1 mM 3-acid tyrosine in TTL-reaction buffer (20 mM MES, 100 mM KCl, 10 mM MgCl2, 2.5 mM ATP, and 5 mM reduced glutathione) at 25˚C for 3 h. After buffer exchange to 20 mM Tris-HCl and 50 mM NaCl (pH 8) by Zeba Spin columns, azido-FLEXamers were directly functionalized via click chemistry. For that, 20 µM azido-FLEXamers were incubated with 200 µM DBCO-PEG4-Atto-488 at 16°C for 15 h, followed by buffer exchange to FPLC storage buffer. Functionalization efficacy and concentration were determined by SDS-PAGE. Functionalized proteins were shock-frozen in liquid nitrogen and stored as aliquots at −80°C for further usage.

Flow cytometry-based koff-rate measurement
To determine anti-CD19 CAR/CD19 dissociation kinetics (koff-rate), the flow cytometry-based platform for the measurement of TCR avidity was adapted53. Therefore, 0.2 µg Atto 488-conjugated scFv molecules were multimerized with 1 µL Strep-Tactin APC in 50 µL FACS buffer for 30 min on ice in the dark. Up to 5 × 106 isolated PBMCs were incubated with 50 µL scFv-StrepTamer for 45 min on ice in the dark. Cells were stained after 25 minutes with anti-CD20 antibody, for target B-cell distinction, and a unique combination of four anti-CD45 antibodies (conjugated with Pacific Blue, Pacific Orange, PerCP, ECD) for multiplexing, enabling the koff-rate measurement of up to 16 scFvs at once. Propidium iodide was added during the last 3 min of incubation for live/dead discrimination. Cells were washed twice in FACS buffer and filtered through a nylon mesh for further analysis. Individually stained samples were mixed in a final volume of 2.1 mL FACS buffer and acquired on a Cytoflex S flow cytometer at a flow rate of 130 µL/min under constant cooling at 4°C or 20°C. After 40 s of acquisition, 2.1 mL of 2 mM D-Biotin solution was injected, followed by an additional 30 min of acquisition. Baseline mean fluorescent intensities (MFIs), especially important for CAR scFvs with strong binding strength, were conducted via acquisition of remaining samples stored for 2 h at 4°C or RT. All measurements were performed in technical triplicates. Dissociation kinetics were analyzed using FlowJo (Treestar). Fluorescence intensities of scFv-Atto488 and the Strep-Tactin-APC of CD45+CD20+ cells were exported into GraphPad Prism (GraphPad Software). Curve fitting and calculation of dissociation kinetics were performed using a non-linear regression function. The starting value of the curve was set directly at the beginning of the dissociation of Strep-Tactin APC. Baseline values of the scFv-Atto488, which were not reached during the acquisition at 4°C, were adapted by hand using measured baseline values during the 20°C measurements.

Nur77-Jurkat reporter cell assay for antigen-specific activation
To evaluate antigen-specific activation, 5 × 104 CAR-engineered Nur77-tdTomato Jurkat cells were co-cultured with 5 × 104 CD19+ Raji-ffluc-GFP target cells in 200 µL RPMI into a 96-well U-bottom plate at 37°C. Effector cell numbers were determined based on the expression of the transduction marker EGFRt+. While CAR-transduced Nur77 Jurkat cells without target cells served as a negative control, Phorbol-mystriate-acetate (PMA—25 ng/mL) and ionomycin (1 µg/mL) (Sigma Aldrich) were used as positive controls. After 3 h of incubation, cells were harvested and stained with anti-EGFR antibody and Streptavidin. Reporter gene activation was analyzed by frequency analysis of tdTomato of EGFRt+ GFP− lymphocytes. Experiments were performed in technical duplicates and biological triplicates.

Intracellular cytokine staining
Primary CAR-T cells were rested for two days in cRPMI after interleukin stimuli. 5 × 104 EGFRt+ CAR-T cells were co-cultured with 5 × 104 (E:T 1:1) or 12.5 × 103 (E:T 1:0.25) CD19+ Raji-ffluc-GFP target cells in 200 µL cRPMI into a 96-well U-bottom plate at 37°C. CAR-T cells in medium and PMA (25 ng/mL) supplemented with Ionomycin (1 µg/ml) (Sigma Aldrich) were used as negative and positive controls, respectively. After 1 h, cytokine secretion was stopped by addition of 50 µL Brefeldin A (‘Golgi Plug’—BD Biosciences) at 1 µg/mL. After an additional 4 h, cells were harvested and incubated with ethidium-monoazide-bromide (EMA; Life Technologies, 1:1000) for 10 min on ice, exposed to bright light for live/dead discrimination. Surface staining (CD8, EGFRt, Strep-tag) was performed as described before at 4°C in the dark for 20 min. After washing in 200 µL FACS buffer twice, cells were fixed and permeabilized with Cytofix/Cytoperm (BD Biosciences) at 4°C for 20 min, according to manufacturer’s instructions. The samples were washed twice with PermWash buffer (BD Biosciences), cells were stained intracellularly with anti-IFN-γ, anti-TNF-α and anti-IL-2 antibodies on ice in the dark for 20 min (Tab. S2), followed by two additional washing steps in PermWash buffer and filtered into 200 µL FACS buffer for analysis on a flow cytometer. Experiments were performed in technical and biological triplicates.

In vitro killing assay
A 96-well E-Plate was filled with 50 µL DMEM and equilibrated in the xCelligence RTCA MP Real-Time Cell Analyzer (ACEA Bioscience) for 30 min at 37°C to determine the baseline impedance signal. 100 µL of CD19+ and CD19− adherent HEK293T in cDMEM (1.5 × 104 cells) or ROR1+ A549 ffluc cells in cRPMI (1.0 × 104 cells) were added and incubated for 24 h. Impedance measurements were conducted every 15 min. 100 µL cDMEM or cRPMI were aspirated and replaced by 100 µL containing 1.5 × 104 (1:1 ratio) or 7.5 × 104 (4:1 ratio) EGFRt+ CAR-T cells. In separate experiments, 100 µL containing 4.0 × 104 (4:1 ratio), 2.0 × 104 (2:1 ratio), 1.0 × 104 (1:1 ratio) or 0.5 × 104 (0.5:1 ratio) EGFRt+ CAR-T cells were added to ROR1+ A549 ffluc cells were added. 2 % Triton-X100 solution (Biorad) and cRPMI medium without effector CAR-T served as positive and negative controls, respectively. Effector and target cells were co-incubated for 48–72 h with measurement intervals of 15 min. Cytotoxic kinetics were analyzed using the software RTCA xCelligence v2.0 (ACEA Bioscience). Cell indices were normalized to the last measurement before addition of CAR-T cells. The samples were measured in technical triplicates and biological duplicates.

Flow cytometry-based cytotoxic CAR-T-cell assay
Additionally, cytotoxic effector function of CAR-T cells was determined in a co-culturing approach with CD19+ Raji-ffluc-GFP or CD19+ Nalm6-ffluc-GFP (expressing either wild type or low antigen level) target cells. The reduction of GPF+ target cells after 24 h and 48 h served as a flow cytometry-based readout. Therefore, 2 × 105 target cells were plated in 50 µL in a 96-well U-bottom plate. Frequencies and cell numbers of EGFRt+ CAR-transduced T cells were determined as described before. Serial dilution of CAR-T cells was performed, and 150 µL with either 8 × 104, 2 × 104, 1 × 104, 0.5 × 104 or 0.25 × 104 EGFRt+ CAR-T cells were added to the target cells (E:T = 4:1, 1:1, 0.5:1, 0.25:1, 0.125:1), respectively. Non-CAR-transduced T cells (mock) derived from the same donor and target cells without T cells served as negative controls. After 24 h or 48 h, cells were harvested. 123count TM eBeads were added to extrapolate absolute cell numbers. The samples were stained with dye-conjugated anti-EGFR and anti-CD8 antibodies, as well as Streptavidin, as described before.

Target cells were discriminated by internal expression of GFP. All samples were measured in triplicate. The percentage (%) of target cell killing was calculated based on the absolute number of target cells in the mock condition. That absolute number of mock T cells was set as 100%, and the number of targets in the following T-cell conditions was expressed as a percentage of survival. The elimination index was calculated as follows: 1—(number of residual target cells in the presence of target antigen-specific CAR-T cells/number of residual target cells in the presence of mock T cells).

Chronic antigen stimulation assay
To investigate the functionality of a combined-affinity CAR-T-cell product in a chronic antigen setup, 3 × 105 CAR-T cells were co-cultured with 1.2 × 106 Nalm-6-ffluc-GFP or Jeko-1 ffluc-GFP cells in a 24-well plate format. Every second day, 100 µL cells were collected and stained as described above. Tumor elimination and CAR-T-cell expansion were evaluated based on 123count eBeads. Tumor cells were added to restore an E:T ratio corresponding to 1:4 according to absolute cell numbers. The described phenotype was observed after a minimum of four rounds of stimulation.

In vitro CRS evaluation
For the evaluation of CRS side effects in vitro, the protocol of Nouri et al. was adapted83. Therefore, 2 × 105 CAR-T cells were co-cultured with 1 × 105 CD19-expressing K562 cells and 1 × 105 monocytes for 24 h in IMDM medium (Sigma Aldrich) supplemented with 50 mL FBS and 5 mL penicillin-streptomycin. Monocytes were isolated from freshly thawed PBMCs derived from the same donor used for generating CAR-T cells through the MojoSort human CD14 monocyte isolation kit according to manufacturer’s protocol (Biolegend). Wild type K562 cells served as the negative control. After 24 h, the supernatant was collected and stored at −20°C until further usage. For the detection of CRS-associated cytokines, the ELISA MAX Deluxe Set Human IL-6 Kit (Biolegend) or the human essential immune response LegendPlex kit (Biolegend) was used according to the manufacturer’s protocol. Supernatant was diluted at least 1:20 with IMDM medium before cytokine concentrations were determined. Experiments were conducted in technical and biological triplicates.

Mouse experiments
NSG-SGM3 (NOD.Cg-Prkdcscid Il2rgtm1Wjl Tg(CMV IL3, CSF2, KITLG) 1Eav/MloySzJ; #013062) mice (male and female, 8-11 weeks old) were acquired from The Jackson Laboratory or derived from in-house breeding. All animals were group-housed under specific pathogen-free conditions at controlled ambient temperature of 20°C at our mouse facility at the Technical University Munich, Institute for Medical Microbiology, Immunology and Hygiene. A 12-hour light/dark cycle was maintained to regulate the circadian rhythm, and a relative humidity of 50–60%. The conducted animal experiments were approved by the local authorities especially the district government of Upper Bavaria (Department 5—Environment, Health and Consumer Protection ROB-55.2-2532.Vet_02-18-162).

To investigate the anti-leukemic efficacy of CAR-T cells with different antigen-binding affinities, NSG-SGM3 mice were challenged with 5 × 105 Raji-ffluc-GFP or Nalm-6-ffluc-GFP cells intravenously (i.v.). After 7 days, CAR-T cells were i.v. injected in bulk or after purification. For bulk injection, CAR-T-cell counts were calculated based on the frequency of EGFRt+ cells and adjusted accordingly. Independent mouse experiments were conducted using CAR-T cells generated from PBMCs from different donors. Tumor progression was analyzed by bioluminescence imaging weekly. Therefore, mice were intraperitoneally injected with 150 mg/kg XenoLight D-Luciferin Potassium Salt dissolved in PBS (PerkinElmer), followed by anesthesia with 2.5 % isoflurane in the RAS-4 Rodent Anesthesia system (PerkinElmer) and imaged with the IVIS Lumina Imaging System (PerkinElmer). The analysis was conducted by quantification of photon/sec/cm2/sr with the Living Image 4.5 software (PerkinElmer). CAR-T-cell expansion was evaluated by blood staining once a week. Therefore, 50–100 µL blood was collected, erythrocytes were lysed with 10 mL ACK buffer (15 M Ammonium chloride—Sigma Aldrich, 17 mM Tris-HCl—Roth) and stained accordingly. Mice were euthanized by cervical dislocation upon reaching predefined human endpoints or at the completion of the experiment, and bone marrow and spleen were subsequently harvested and analyzed 30 days after CAR-T-cell transfer. Bone marrow was isolated from femur and tibia and incubated with 3 mL ACK for 3 min. Spleens were mashed through a 100 µm cell sieve and treated with 5 mL ACK buffer for 5 min. Flow cytometry staining was performed as mentioned before. For affinity combination experiments, CAR transduction efficacies were determined based on the transduction marker EGFRt. Individual CAR proportions of the product after combination were evaluated based on the expression of fluorescent proteins as described above.

For the in vivo assessment of CAR-associated side effects, 3–4-week-old female NSG-SGM3 mice were sublethally irradiated with 1 Gy and i.v. injected with 2 × 104 CD34+ HSCs on the following day. After 8-12 weeks, the reconstitution of the human immune compartment was confirmed via blood analysis and mice were challenged with 5 × 105 Raji-ffluc-GFP followed by CAR-T-cell administration as described above. CRS intensity was evaluated based on the body weight loss, changes in temperature development and serum cytokine levels. To evaluate the concentration of inflammatory cytokines in the circulation, serum samples were collected 3 and 5 days after CAR-T-cell transfer and analyzed with the capture-bead-based LegendPlex Kit (Biolegend) according to the manufacturer’s protocol. Data was analyzed with the LEGENDplex Qognit, Inc. Software (Biolegend).

Single-cell RNA sequencing
CAR-T cells were isolated from bone marrow of NSG-SGM3 30 days after transfer. Bone marrow was harvested as described above. Up to 1 × 107 cells were stained in 100 µL antibody mix as described above. In parallel, each sample was labeled with a unique Hashtag antibody (TotalSeqTM B Barcodes Biolegend) for the following demultiplexing (Tab. S3). 1000 CAR-T cells per donor mouse were sorted for GFP−, CD19−, EGFRt+. After sorting, the supernatant was removed, and the cells were resuspended in Mastermix + 37.8 µl of water before 70 µl of the cell suspension was transferred to the Chromium next GEM chip.

The integrity of the cell pellet was checked under the microscope frequently before loading the sample on the chip. 10X experiment was conducted according to the manufacturer’s protocol (Chromium next GEM Single Cell 3’ v3.1 with dual index). Sample quality was confirmed with a High-sensitivity DNA Kit on a Bioanalyzer 2100, and libraries were quantified with the Qubit dsDNA hs assay kit. All steps were performed with RPT filter tips and Low Bind tubes.

scRNA-seq data analysis
The human reference GRCh38-2024-A, was used for Transcriptome annotation (CellRanger 7.0.0). To identify CAR transcripts in single cells, the complete transcript of the CAR constructs (JCAR017, JCAR021) was added to the reference genome. Data preprocessing has been performed according to the current best practice in single-cell RNA-seq analysis84,85. Data analysis was performed with SCANPY V1.9.1. In brief, single cells were annotated by their respective CAR transcripts (JCAR017, JCAR021); only cells with a unique identification of a CAR construct were annotated as JCAR017 or JCAR021, respectively. Subsequently, cells with fewer than 200 genes, as well as genes present in fewer than 20 cells were excluded. Counts were normalized per cell, logarithmized, and the variance was scaled to unit variance and zero mean. The number of counts was regressed out before highly variable genes were identified and filtered. DNA-Barcode demultiplexing was performed with HashSolo included in SCANPY. Differential gene expression analysis was performed using SCANPY and diffxpy (https://diffxpy.readthedocs.io/en/latest/index.html). Gene ontology analysis was performed using g:Profiler toolkit86. Gene set enrichment analysis was performed using GSEAPY87.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Balancing the efficacy and safety of Chimeric Antigen Receptor T cell therapy by affinity\ncombination\nIn this manuscript Warmuth, Dotsch, et.al, propose the novel concept that a combination therapy using anti-CD19 CARs with\ndifferent affinities (2.7 nM and 140 nM) could achieve comparable efficacy to high affinity CARs alone, while lowering off-\ntumor toxicity. The authors suggest this strategy has the potential to lower the risk of cytokine release syndrome (CRS) and\nimmune effector cell-associated neurotoxicity syndrome (ICANs), thereby expanding the therapeutic window of CAR T cells.\nThe authors support their hypothesis through a series of in vitro and in vivo assays, including studies in NSG and a\nhumanized mouse model, to assess both efficacy and toxicity.\nA particularly notable finding is that high affinity CARs in the bone marrow exhibit a distinct phenotype in the presence of low\naffinity CARs as determined by scRNA-seq. The authors suggest a synergistic interaction between the low- and high-affinity\nCARs, enabling a balance between therapeutic efficacy and safety.\nThe work is relevant to the field of CAR T cell immunotherapy, where achieving an optimal balance between efficacy and\ntoxicity remains a major challenge. The proposed affinity-combination approach should be of interest to the immunotherapy\ncommunity. However, the scope of the study is currently limited to CD19-directed CARs with a specific architecture (a CD28\ntransmembrane domain, a 41BB co-stimulatory domain and a CD3z signaling domain) which may constrain the broader\napplicability of the findings. While it is reasonable for the authors to stay within this defined system, expanding the study to\ninclude additional target antigens and/or other CAR architectures would substantially increase the impact of the approach.\nThe authors present affinity measurements for a well-established high affinity murine ScFv (JCAR017 based on FMC63 - 2.7\nnM) and a lower affinity humanized version (JCAR 021 - 140 nM). They then developed a collection of affinity variants by\nmutating the JCAR021 scFv and incorporating these variants into synthetic CAR constructs to evaluate performance. While\nthis provides a careful and systematic evaluation of affinity-dependent CAR function, similar studies have been previously\nreported. For example:\nHe et. al (Science Immunology, 2023) characterized several affinity variants of FMC63, including\nWT - 4.5 nM, Y261A - 682.5 nM, Y70A - 275 nM and showed functional differences in CAR T cells depending on affinity.\nhttps://www.science.org/doi/10.1126/sciimmunol.adf1426\nBarden et al (Journal for Immunotherapy of Cancer, 2024) and Liu et al have explored the relationship between ScFv affinity\nand CAR efficacy in other tumor antigens, such as HER2, with conclusions that moderate affinity cAR may outperform both\nhigh and low affinity variants under certain conditions.\nhttps://jitc.bmj.com/content/12/12/e010208\nGiven this context, the novelty of the current work lies not in the generation of affinity variants but in the combination of two\nCARs of differing affinity to enhance the therapeutic index. This concept is interesting and underexplored.\nHowever, to strengthen the affinity exploration, the authors might consider including in vitro killing assays using CD19+ targets of different densities at lower E:T. Previous work has shown in vitro differences that are affinity dependent (Fig. 4C -\nreference above). Under the current conditions, where T cell numbers are high, such differences might be masked.\nThe overall conclusions of the manuscript are promising. However, several key claims, particularly those regarding the\nmechanism of synergy or communication between high- and low-affinity CAR T cells in the combined product, would benefit\nfrom additional clarification or supporting evidence.\nSpecifically\nEfficiency of in vitro killing across a broad affinity spectrum of CAR binders\nCurrent E:T ratios used to explore differential in vitro killing across variants (Fig. 2g) show early saturation in target killing for\nmost variants. Most variants that exhibit intermediate behavior between the control curve and JCAR021 express low levels\nof CAR or do not express it at all (Suppl. Fig. 3d). More challenging E:T ratios may be able to demonstrate dependence of\nkilling dynamics on CAR affinity. Similarly, exploring how variants with different affinities kill targets with low antigen density\nwould provide another way to test differences in vitro. The authors already demonstrated a relationship between CAR affinity\nand capacity to kill low antigen density targets (Fig. 5n). Exploring affinity variants across these two axes (total antigen by\nE:T ratio or using low antigen density per cell) could help validate the claim that there are no functional differences across\nthe broad spectrum of CAR affinities.\nCAR T cell toxicity associated with affinity.\nDespite generating several affinity variants, the authors only explored the original 2 CARs based on JCAR017 and\nJCAR021. Although there is a clear correlation between CAR affinity, dose, and toxicity, it would have been interesting to\nobserve variants with intermediate affinities between these two (e.g., S168C, S227K, S50A). This is particularly relevant\nbecause Fig. 4b and 4h suggest that for JCAR017, a dose between 1M and 4M is sufficient to control tumors without\nsignificant toxicity; however, not even 8M JCAR021 can control tumors.\nRatio of low/high affinity CAR T cells over time in vivo vs in vitro -\nThe dynamics of CAR T cell populations in the 50:50 combination differ substantially between the in vitro and in vivo\nsettings. In vitro (Fig. 5g–i), the total expansion resembles the high-affinity CAR alone, but the population eventually shifts\ntoward low-affinity CAR dominance (~30:70 by day 28, Fig. 5i). In contrast, in vivo data from day 10 post-ACT (Supp. Fig.\n12c, left) show similar cell numbers for both the low-affinity and combined products across different dose levels, which\nsuggests different expansion or persistence dynamics. It would strengthen the manuscript if the authors could comment on\nthese discrepancies and discuss possible biological or experimental reasons behind them.\nThe authors propose that the high-affinity CAR T cells are protected from exhaustion in the combination setting. However,\nthe absolute numbers of high-affinity CAR T cells (JCAR017) in both the solo and combination treatments appear to decline\nsimilarly over time (Supp. Fig. 12c, middle). Would earlier time points for the high-affinity CAR alone show a more\ncomparable phenotype to that observed in the combination setting? Alternatively, could the dominant expansion of the low-\naffinity CAR population reduce the number of high-affinity CAR interactions with target cells, thereby indirectly preserving\ntheir phenotype? It would be useful if authors split the analysis of the combined JCAR021 and JCAR017 CARs for each\nindividual treatment group (0.8/0.8 and 0.2/1.4). These two groups have different tumor control profiles (Fig. 6c) and total\nnumber of cells (Suppl. Fig. 12d). It would be interesting to see if the described phenotypical differences are maintained\nwhen comparing JCAR017 alone with JCAR017 in the 50:50 ratio.\nThe current data set lacks an additional control using high-affinity CAR T cells with untransduced T cells or CARs of\nunrelated specificity at matched total cell doses. This limits the ability to conclusively attribute phenotypic shifts in the high-\naffinity CAR population to active synergy or indirect effects from the low-affinity CAR T cells. Including such controls would\nhelp determine whether the observed effects are specific to affinity combinations or merely a consequence of changes in T\ncell dose or competition.\nIt remains unclear whether the differences in CAR T cell phenotype (especially exhaustion profiles) could be influenced by\ndifferential cytokine production. Is there in vivo data on cytokine expression profiles comparing high- and low-affinity CARs,\nor in the combination product? This could help determine whether secreted factors from the low-affinity CAR T cells\ncontribute to shaping the phenotype or function of their high-affinity counterparts.\nSeveral issues could be clarified and revised to improve data interpretation. Addressing the points below would enhance\nclarity\nReplacing the labels “JCAR017” with “High affinity CAR (ScFv - 2.7 nM)” and “JCAR 021” with “ Low affinity CAR (ScFv 140\nnM)” throughout the figures would make the data more accessible and easier to follow for a broader readership, particularly\nfor those less familiar with the names/codes.\nCAT CAR T cells are only explored in Fig. 1. Although it is important that the authors benchmark their findings against other\npreviously described CARs, this could be moved to the supplementary figures, allowing the main figures to focus only on the\nhigh and low affinity CARs that are explored further (JCAR017 and JCAR021).\nFig.1g axis label reads E:T 1:4 but the Methods section for the assay description states E:T 1:0.25, which one is it?\nIntuitively, one would expect a higher fraction of cells secreting cytokines at higher target numbers. The current axis labels\nsuggest otherwise. Please, clarify\nFig. 1h More E:T conditions and antigen-densities for each construct could reveal differences in the in vitro killing behavior,\nparticularly under suboptimal T cell conditions where functional differences are more likely to emerge (see comment in\nprevious section)\nOn page 6, the phrase \"the individual label of CAR-T cells with fluorescence conjugated anti-CD45 antibodies enabled\nmultiplexing…\" seems to indicate that CAR-T cells were generated and stained, while the methods section states that target\nB cells were stained with anti-CD45 antibodies. Please clarify this discrepancy.\nThe logic of Fig. 2 is currently somewhat confusing, as it first addresses and classifies CAR T cells based on function, and\nonly later explains that many of the low-functioning CARs do not even express the receptor as a surface protein. One\nsuggestion for reorganizing the figure is to first establish the affinity of the variants, then describe their expression as CARs in\nprimary T cells, and only proceed with the functional assays for those that show clear CAR expression (based on EGFRt+\nand STII+). Additionally, binning the CARs into groups does not allow the reader to appreciate interesting cases of function\nversus affinity. The heat map in Fig. 2i is a good summary, but including some XY plots of affinity versus target lysis or\naffinity versus IL-2 secretion could help to highlight interesting cases. That would also help to feature variants that are used in\nfollowing figures, allowing a better interpretation of those results.\nFig.4 can be rearranged to improve clarity. Figure panels that showed immune reconstitution (Suppl Fig.7 c and d) could be\nmoved to main Fig.4. Also, dose titration is interesting mostly only in the context of affinity variants. Panels Fig.4 b to g can be\nmoved to supplementary, allowing a clearer focus to Panels Fig4h to k. Some panels from Suppl Fig 9 can be then\nmoved also to the main Fig. 4.\nWhich cell line is used in Fig.4 experiments (Raji or Nalm-6), please specify in figure’s legend\nMapping the mutations in the JCAR021 ScFv onto its structure and color-coding them by functional impact would add\nvaluable insight. This visualization could highlight whether key residues are localized near the CD19 binding interface or\nwhether functional “hotspots” exist in certain regions of the antibody. This may also help clarify why some affinity variants\nbehave differently than expected.\nFig. 5 would benefit from including data for all the variants mentioned in the figure. The monocyte cytokine release assay\nand the chronic stimulation assay should be performed with all the described variants, as well as their combinations.\nAdditionally, at least one variant with intermediate affinity between JCAR017 and JCAR021 should be tested (e.g., S168C,\nS227K, S50A). This would allow for better interpretation of the role of affinity in toxicity and exhaustion prevention.\nSimilarly, antigen density is an important factor to evaluate, as it may reveal differences in target killing by the various affinity\nvariants, as observed in Fig. 5n. In addition, Fig. 5n shows that target killing by the combination of CAR T cells appears to\nreach saturation at 24 hours, which does not allow for a proper evaluation of whether the effect of the combined CAR T cell\napproach is driven by phenotypic differences in the high-affinity CAR. Testing different E:T ratios could help the reader\nobserve these potential differences, such as instances where the same amount of high-affinity CAR fails to eliminate tumor\ncells while the combination, even at a lower high-affinity CAR dose, is effective. Furthermore, testing similar ratios of\nJCAR017 and JCAR021 alongside the other variants would also be informative.\nFigure 6e. Why does there seem to be much less cells for both high- and low-affinity CAR T a in the UMAP in the 50:50\ncondition than in the 90:10 condition? The absolute counts in S12c show otherwise, could you provide an explanation\nbetween the count trends in the blood and bone marrow? Similarly, as described before it would be useful if authors split the\nanalysis of the combined JCAR021 and JCAR017 CARs for each individual treatment group (0.8/0.8 and 0.2/1.4). Also,\nincluding it would be useful for the interpretation of the results to include in the comparisons in Fig. 6h an j the profile of\nJCAR021 alone and in combination.\nThe authors claim: “Our data show that lower-affinity CAR-T cells remain functionally active in the presence of high-affinity\nCAR-T cells, leading to a more controlled and sustained immune response.” However, this claim is difficult to support with\nthe current experiments. Although it can be assumed that lower quantities of JCAR017 require the presence of JCAR021 to\nachieve similar survival (Fig. 6b), effective tumor control appears to require at least 0.8 million high-affinity CAR-T cells to\nprevent tumor growth (Fig.6c). Additionally, low-affinity CAR-T cells achieve similar numbers in the bone marrow under\nconditions that differ in terms of tumor control (i.e., 1.6 million single low-affinity cells versus 0.8 million in combination)\n(Fig.6d). Including an analysis of JCAR021 from the scRNAseq data, as previously suggested, may help to substantiate this\nclaim.\nPlease clarify if the same donor T cells were used throughout the manuscript or different ones. If a single one, adding other\ndonor T cells would strengthen the results.\nMethods are mostly adequate. Extra details in some sections would help to reproduce authors’ work. Specifically:\nIn figure legends, specify the number of donors used in the experiments.\nAdd source of retroviral expression vector (Addgene?, other lab?)\nWhich number of RD114 that was seeded, in which plate/flask format, for how long before transfection.\nIn which media transfection was performed, and was media exchanged during those 72h?\nFor how long the transduced primary T cells were maintained in culture before CAR expression was analyzed. How long\nafter the transduction they were used in in vitro experiments. How long for in vivo experiments.\nFor which experiments CAR T cells were sorted? For which experiments they were not sorted. Please add this information\nto the figure legend, particularly for the in vivo experiments.\nFor the chronic restimulation assay, please describe the plate format used. Also, add how many rounds of stimulation were\nperformed.\nFor BM and spleen preps, do authors intend to write ACK buffer instead of “ACT buffer”?", "reviewer_2": "Warmuth et al. present intresting results showing that the combination of high- and low-affinity CARs targeting Cd19 antigen\ncan balance the antitumor response by reducing toxicities without compromising efficacy. The authors generated and\nthorougly tested a panel of CD19 binders and compared them to clinically used CAT. The authors evaluated T cells with\ndifferent binders alone or in combination in vitro and in vivo, including in a humanized model to assess CRS. Overall, the\nmanuscript is well presented, original, and addresses a critical question in the field. My only concern is that the study would\nbenefit from deeper mechanistic analyses to determine how low-affinity CARs mitigate high-affinity CAR exhaustion and\nexcessive stimulation. Is this achieved through transient antigen masking, reduced tumor burden, or potential cytokine\nsecretion? Addressing this question would further strengthen the authors conclusions. A minor point that should be\naddressed in the limitations section is the challenge of translating these findings to patients, given the heterogeneity both\nbetween patients and across different antigens, a limitation noted by the authors in the discussion.", "reviewer_3": "The presented manuscript elaborates the impact of receptor-affinity towards efficacy and safety of CD19 targeting CAR T\ncells. In short, the authors describe that in vivo, but not in vitro function correlates with affinity. Using improved murine CRS\nmodels, the authors show that in high, but not in low affinity CAR Ts, toxicity is correlated to dose. In a last step, the authors\nevaluate the combination of high and low affinity CAR T cells with the aim to maintain efficacy by reducing toxicities such as\nCRS.\nFor long time, CARs were preferentially generated from high affinity antibodies, whereas nowadays, scientists are becoming\naware that sometimes, lower affinity might beneficial in specific indications (e.g. Olson et al, Leukemia, 2022; Flugel et al,\nNat Rev Clin Onc, 2023). Thus, the combinatory approach presented here is of significant interest to the field and displays a\nconcept that has not been presented yet.\nMost of the conclusions and claims are sufficiently supported, however, due to the large amount of data (varying dosages\nand combinations) in the murine studies, the reader would benefit from further explanation how studies are connected to\neach other, and if and how conclusions from one experiment might have shaped the setup of the following study. From the\ndata presented, it looks like 2 Mio JCAR017 are typically curative in the used models, whereas 1Mio JCAR017 is not\nsufficient to completely eradicate the tumor. Regarding the combination of JCAR017 and JCAR021, there seem to be\ndifferent ratios that might be beneficiary, and a final conclusion on the optimal ratio is missing. Thus, a final experiment is\nmissing to fully support the main message of the manuscript: Within the CRS model, compare an optimal combination (e.g.\n1Mio +1Mio, if that is the chosen dosage) against I) a comparable dose (total cell amount =2 Mio) of high affinity CAR and II)\nsame amount of high affinity CAR as in the combination (1Mio) to make a final decision on the dose as well as to have\nsupportive data on efficacy and toxicity, preferably over long term to address toxicity as well as long term efficacy and\npotential relapse.\nStatistics should only be calculated if n ≥3 and biological (but not technical) replicates are available. Smaller datasets can\nstill be presented but should not be included in statistical analysis.\nBesides the above mentioned general comments, there are some details that should be addressed:\nIntroduction:\n• Besides JCAR017 being the “central component of most commercially approved anti CD19 CAR T products” it should be\nmentioned that also JCAR021 is being evaluated in clinical trials and results have been reported (PMID 39820359 by\nGauthier et al, 2025).¬¬¬\nFigures:\n• Fig. 1h: The wording of figure should be revised: “data was obtained from one experiment”.\n• Fig 2f: How are constructs assigned to group mfunct and mfunct low? If this assignment is based on function, there is one\nconstruct within the CARmlowfunct group that shows cytokine production after antigen spec. stimulation. Please clarify\nallocation.\n• Fig. 2h: In addition to the transduction rate, is the MFI also reduced in the mlowfunct group?\n• Fig 3f/S5b: BLI data from the one mouse surviving in the L237W group (d28) is shown in S5b, but not in 3f. Please justify\nwhy this has been excluded from the analysis.\n• Fig. 3g ff: What is the baseline of the Mock T cells? Were any Mock T cells detectable in blood, BM or spleen?\n• Fig S6: Please include average radiance analysis of the remaining mice of d24 as the final day of the experiment\n• Fig. 4: How has the murine CRS model been improved? Please indicate for each experiment which cell line was actually\nused (Nalm-6 or Raji).\n• Fig 4h-k: Even though Fig 4 is meant to demonstrate toxicity, the BLI imaging suggests that the low affinity CAR might have\nan antitumor effect at high dosage while showing a lower toxicity. Is there data available on longer observation periods\nregarding efficacy?\n• Fig: 5b: Does the ametrine fluorescent protein influence CAR expression or functionality?\n• Fig 5c: Please clarify the composition of CAR017 and JCAR021 at t=0\n• Fig 5a-e: From the presented data, it is not clear if the combination has a benefit at all. A control condition containing the\nreduced amount of JCAR017 without the addition of JCAR021 would be helpful to fully interpret the results.\n• Fig.5n: please include a condition of 0.01x10^6 JCAR017 to enable a conclusion if similar lysis would also be achieved by\nthe lower dose of JCAR017 in the complete absence of JCAR021. In the current data set, Figs. 5 and S10 do not sufficiently\nsupport the main message of the paper, as relevant controls are missing.\n• Fig. S10: same as Fig 5. In Figure S7, it is shown that giving 2 or 4 Mio of JCAR017 does not have a significant difference\nin efficacy. Thus, the data from S7 suggest that the observed effect is caused by the reduction of the amount of JCAR017,\nbut not from the combination with the low affinity CAR.\n• Fig. S11: in contrast to the text (p.12), Fig. S11 doesn’t demonstrate increased safety, but efficacy of combined CAR T.\nIndeed, a comparison of this “optimal combination approach” to standard dosages with regards to safety and efficacy would\nstrongly support the manuscript.\n• Fig. S11a: 1M JCAR017 and 1M JCAR017 +1M JCAR021 are not shown in b/c. if these conditions were not assessed\nhere, but in a separate experiment (d/e), please delete in the experimental set up (a).\n• Fig. S11d/e is mentioned in the text in correspondence with Fig S12, maybe consider relocation.\nDiscussion:\n• The affinity variants of the CAR all target the same epitope within CD19. As one suggested mode of action is the\ncompetitive binding and availability of antigen binding sites, do you think the effects would be similar when targeting\ndifferent epitopes?", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts."}, "author_response": "Point-by-point response to the reviewer comments\nReviewer #1 (Remarks to the Author):\nBalancing the efficacy and safety of Chimeric Antigen Receptor T cell therapy by affinity\ncombination\nIn this manuscript Warmuth, Dotsch, et.al, propose the novel concept that a combination therapy\nusing anti-CD19 CARs with different affinities (2.7 nM and 140 nM) could achieve comparable\nefficacy to high affinity CARs alone, while lowering off-tumor toxicity. The authors suggest this\nstrategy has the potential to lower the risk of cytokine release syndrome (CRS) and immune\neffector cell-associated neurotoxicity syndrome (ICANs), thereby expanding the therapeutic\nwindow of CAR T cells. The authors support their hypothesis through a series of in vitro and in\nvivo assays, including studies in NSG and a humanized mouse model, to assess both efficacy\nand toxicity. A particularly notable finding is that high affinity CARs in the bone marrow exhibit a\ndistinct phenotype in the presence of low affinity CARs as determined by scRNA-seq. The authors\nsuggest a synergistic interaction between the low- and high-affinity CARs, enabling a balance\nbetween therapeutic efficacy and safety.\nThe work is relevant to the field of CAR T cell immunotherapy, where achieving an optimal balance\nbetween efficacy and toxicity remains a major challenge. The proposed affinity-combination\napproach should be of interest to the immunotherapy community. However, the scope of the study\nis currently limited to CD19-directed CARs with a specific architecture (a CD28 transmembrane\ndomain, a 41BB co-stimulatory domain and a CD3z signaling domain) which may constrain the\nbroader applicability of the findings. While it is reasonable for the authors to stay within this defined\nsystem, expanding the study to include additional target antigens and/or other CAR architectures\nwould substantially increase the impact of the approach.\nWe thank the reviewer for emphasizing the relevance of our study and for the valuable suggestion\nto extend our findings to additional target antigens. Indeed, this recommendation and consequent\nexperiments clearly increased the impact of our findings. To address this point, we evaluated an\nadditional pair of high- and low-affinity CARs recognizing the same epitope on the human ROR1\nantigen (high-affinity CAR R12 - K = 0.11 nM; lower-affinity CAR R12v20 - K = 0.98 nM)\nD D\n(Hudecek et al., Clin Cancer Res. 2013). For this CAR pair, we assessed cytotoxic activity and\nthe expression of exhaustion-related markers following chronic stimulation, using CAR-T cells\neither alone or as affinity-combined products.\nHigh-affinity R12-T cells (R12hi-T) displayed superior tumor cell killing compared with lower-affinity\nR12v20-T cells (R12lo-T). Notably, a 50:50 mixture of high- and low-affinity CAR-T cells\n(corresponding to a 0.5x dose of each CAR) achieved cytotoxic activity comparable to that of\nR12hi-T cells used alone at full dose (1x). Moreover, the affinity-combined product outperformed\nboth R12lo-T cells at full dose and R12hi-T cells at half dose, which corresponds to the high-affinity\nCAR-T cell dose present in the combined product. In chronic stimulation assays, R12hi-T cells\nexhibited higher expression of multiple exhaustion markers compared with R12low-T cells, whereas\nthe affinity-combined product displayed exhaustion levels comparable to those of the lower-affinity\nCAR-T cells. Owing to the lack of a reporter gene in the anti-ROR1 CAR constructs, it was not\npossible to discriminate between the two CAR-T cell populations within the combined product.\nIn summary, the ROR1 antigen model corroborates the observations made in the CD19 model,\ndemonstrating improved functionality and less signs of exhaustion of affinity-combined CAR-T\nproducts compared with high-affinity CAR-T cells alone also for another antigen model. These\nfindings further underline the significance of CAR mixing, and were added in Fig. S11.\nThe authors present affinity measurements for a well-established high affinity murine ScFv\n(JCAR017 based on FMC63 - 2.7 nM) and a lower affinity humanized version (JCAR 021 - 140\nnM). They then developed a collection of affinity variants by mutating the JCAR021 scFv and\nincorporating these variants into synthetic CAR constructs to evaluate performance. While this\nprovides a careful and systematic evaluation of affinity-dependent CAR function, similar studies\nhave been previously reported. For example:\nHe et. al (Science Immunology, 2023) characterized several affinity variants of FMC63, including\nWT - 4.5 nM, Y261A - 682.5 nM, Y70A - 275 nM and showed functional differences in CAR T cells\ndepending on affinity.\nhttps://www.science.org/doi/10.1126/sciimmunol.adf1426\nBarden et al (Journal for Immunotherapy of Cancer, 2024) and Liu et al have explored the\nrelationship between ScFv affinity and CAR efficacy in other tumor antigens, such as HER2, with\nconclusions that moderate affinity cAR may outperform both high and low affinity variants under\ncertain conditions.\nhttps://jitc.bmj.com/content/12/12/e010208\nGiven this context, the novelty of the current work lies not in the generation of affinity variants but\nin the combination of two CARs of differing affinity to enhance the therapeutic index. This concept\nis interesting and underexplored.\nWe agree with the reviewer that the novelty of our work lies in the combined-affinity approach to\nimprove the balance between efficacy and safety of CAR-T cell products. In order to follow the\nreviewer’s advice, we have revised the Abstract, Introduction, and Discussion to emphasize this\nparticular point. We believe that these changes, together with the addition of the suggested\nreferences, should clarify how our study corroborates prior work on affinity-dependent CAR\nfunction while providing a distinct contribution to the design of innovative and more efficient CAR-\nT cell therapies.\nHowever, to strengthen the affinity exploration, the authors might consider including in vitro killing\nassays using CD19+ targets of different densities at lower E:T. Previous work has shown in vitro\ndifferences that are affinity dependent (Fig. 4C - reference above). Under the current conditions,\nwhere T cell numbers are high, such differences might be masked.\nThe overall conclusions of the manuscript are promising. However, several key claims, particularly\nthose regarding the mechanism of synergy or communication between high- and low-affinity CAR\nT cells in the combined product, would benefit from additional clarification or supporting evidence.\nWe followed the reviewer’s recommendation and performed additional in vitro killing assays using\nlower E:T ratios. These data are discussed below in the point-by-point response. We also tried to\nfurther elucidate potential mechanisms explaining the synergy, focusing on the hypothesis that\nepitope masking by lower-affinity CAR-T cells protects high-affinity CAR-T cell function. To this\nend, we attempted to visualize interactions between effector and target cells in in vitro co-culture\nsystems using antibody blocking approaches, membrane staining/dye transfer as well as high-\nresolution microscopy. However, these assays proved technically challenging and did not provide\na better assessment of the mechanism of action, which remains beyond the scope of this\nmanuscript.\nWe revised the manuscript to ensure a usage of the term “synergistic” cautiously and only as a\npotential interpretation of the data, not as a firm conclusion.\nSpecifically – Major points\n1. Efficiency of in vitro killing across a broad affinity spectrum of CAR binders\nCurrent E:T ratios used to explore differential in vitro killing across variants (Fig. 2g) show early\nsaturation in target killing for most variants. Most variants that exhibit intermediate behavior\nbetween the control curve and JCAR021 express low levels of CAR or do not express it at all\n(Suppl. Fig. 3d). More challenging E:T ratios may be able to demonstrate dependence of killing\ndynamics on CAR affinity. Similarly, exploring how variants with different affinities kill targets with\nlow antigen density would provide another way to test differences in vitro. The authors already\ndemonstrated a relationship between CAR affinity and capacity to kill low antigen density targets\n(Fig. 5n). Exploring affinity variants across these two axes (total antigen by E:T ratio or using low\nantigen density per cell) could help validate the claim that there are no functional differences\nacross the broad spectrum of CAR affinities.\nWe followed the reviewer’s suggestion and tested more challenging E:T ratios across CARs\nspanning the full affinity spectrum in our dataset, using the same CD19⁺ tumor cell line engineered\nto express either low or high target density. We did not observe improved resolution with respect\nto the dependence of in vitro target cell killing on CAR affinity and antigen density, except for the\nultra-low, TCR-like CAR affinities. These new observations confirmed the reduced cytotoxic\ncapacity of lower-affinity CARs, particularly against low–antigen-density target cells, already\nobserved in Fig. 5n of the original manuscript. These data have been incorporated into the new\nFig. S4 of the revised manuscript.\n2. CAR T cell toxicity associated with affinity.\nDespite generating several affinity variants, the authors only explored the original 2 CARs based\non JCAR017 and JCAR021. Although there is a clear correlation between CAR affinity, dose, and\ntoxicity, it would have been interesting to observe variants with intermediate affinities between\nthese two (e.g., S168C, S227K, S50A). This is particularly relevant because Fig. 4b and 4h\nsuggest that for JCAR017, a dose between 1M and 4M is sufficient to control tumors without\nsignificant toxicity; however, not even 8M JCAR021 can control tumors.\nWe thank the reviewer for this constructive suggestion. We agree that inclusion of additional\nvariants strengthens the interpretation of affinity-dependent effects on toxicity. In response, we\nanalyzed the affinity variants S168C and S227K, which exhibit the highest affinities in our dataset\nwhile remaining substantially closer in affinity to JCAR021 than to JCAR017. T cells engineered\nwith these CARs were evaluated using the in vitro monocyte-induced cytokine release (CRS)\nassay. Both S168C- and S227K-CAR T cells produced significantly lower levels of CRS-related\ncytokines compared with JCAR017-CAR T cells, with cytokine profiles closely matching those\nobserved for JCAR021-CAR T cells.\nIn addition, we evaluated 1:1 mixtures of high-affinity JCAR017-CAR T cells with each of the newly\nanalyzed lower-affinity variants. These mixed products were compared with two JCAR017-CAR\nT-cell controls: one matched for the total CAR-T cell dose and one matched for the number of\nJCAR017-CAR T cells present in the affinity-combined product. For both S168C- and S227K-CAR\nT cells, the mixed products induced significantly lower levels of CRS-associated cytokines than\nthe same total dose of JCAR017-CAR T cells alone and exhibited cytokine release comparable to\nthe half-dose JCAR017 control. This indicates that adding lower-affinity CAR-T cells does not\nincrease toxicity beyond what is expected from reducing high-affinity CAR T-cell numbers.\nTogether, these data further support the affinity-toxicity relationship previously described in the\nmanuscript for JCAR017 and JCAR021. The new findings have been incorporated into the revised\nmanuscript as Fig. 5a–e.\n3. Ratio of low/high affinity CAR T cells over time in vivo vs in vitro –\nThe dynamics of CAR T cell populations in the 50:50 combination differ substantially between the\nin vitro and in vivo settings. In vitro (Fig. 5g–i), the total expansion resembles the high-affinity CAR\nalone, but the population eventually shifts toward low-affinity CAR dominance (~30:70 by day 28,\nFig. 5i). In contrast, in vivo data from day 10 post-ACT (Supp. Fig. 12c, left) show similar cell\nnumbers for both the low-affinity and combined products across different dose levels, which\nsuggests different expansion or persistence dynamics. It would strengthen the manuscript if the\nauthors could comment on these discrepancies and discuss possible biological or experimental\nreasons behind them.\nWe thank the reviewer for highlighting this difference and giving us the opportunity to elaborate\non these population dynamics. A major difference between the in vitro and in vivo settings lies in\nthe distinct antigenic pressures experienced by CAR-T cells. In the in vitro chronic stimulation\nmodel, target cells are repetitively added to the CAR-T cells, which are continuously and directly\nexposed to high levels of their cognate antigen. This drives constant expansion and proliferation\nwithout reaching full exhaustion. Consequently, both high- and low-affinity CAR-T cells maintain\nproliferation (Fig. 5g-h). In contrast, in the in vivo model, antigen exposure changes depending\non the efficacy of the infused CAR-T cells. In mice treated with lower-affinity JCAR021-T cells\nalone, tumors continue to grow due to poor efficacy, providing persistent antigen stimulation that\nsustains T-cell expansion. Conversely, in mice treated with high-affinity JCAR017-T cells alone or\nin combination, tumors regress markedly, leading to diminished T-cell expansion. The small\nresidual tumor burden maintains JCAR017-T cells at a steady level rather than inducing the typical\ncontraction usually seen in the peripheral circulation with complete tumor clearance (Fig. 6c and\nFig. S13c). What remains unclear is the exact underlying reason for the late expansion of the\nJCAR021-T cells also in the combined product. Future investigations will be necessary to unravel\nunderlying mechanistic insights for those proliferation dynamics; we deliberately chose not to\ninclude speculative interpretations in the manuscript.\n4. The authors propose that the high-affinity CAR T cells are protected from exhaustion in the\ncombination setting. However, the absolute numbers of high-affinity CAR T cells (JCAR017) in\nboth the solo and combination treatments appear to decline similarly over time (Supp. Fig. 12c,\nmiddle). Would earlier time points for the high-affinity CAR alone show a more comparable\nphenotype to that observed in the combination setting? Alternatively, could the dominant\nexpansion of the low-affinity CAR population reduce the number of high-affinity CAR interactions\nwith target cells, thereby indirectly preserving their phenotype?\nThe transcriptomic analyses in Fig. 6g–j clearly indicate that JCAR017-T cells display milder signs\nof exhaustion in the combined product. This is further supported by the assessment of a smaller\nset of exhaustion-related markers in Fig. 5i-j after chronic antigen exposure, demonstrating a\nconsistent phenotype across assays. In contrast, expansion and persistence data do not provide\ninsight into the functional state of the transferred cells and therefore cannot be used as surrogate\nmarkers of exhaustion. We also do not consider it necessary to determine whether high-affinity\nCAR-T cells alone would display a phenotype similar to the combination setting if analyzed at\nearlier time-points. In our view, the key and most informative finding is precisely that, under\nidentical conditions, high-affinity CAR-T cells behave differently when administered alone versus\nin combination with low-affinity CAR-T cells.\nAs noted in the Discussion, we also considered the hypothesis that competition for antigen binding\nmay be a central mechanism through which low-affinity CAR-T cells help preserve a more\nfunctional and less exhausted phenotype in the high-affinity CAR-T cell population, given\nrecognition of the same epitope. Future experiments are required to gain more detailed insights\ninto the exact consequences and dynamics of epitope competition between different CAR-T cell\npopulations (we started first live cell in vitro imaging studies to visualize and compare target\ncontact dynamics; although the data are highly interesting, we believe they are too preliminary to\ndraw sound conclusions at this stage and decided not to add them to the manuscript).\n5. It would be useful if authors split the analysis of the combined JCAR021 and JCAR017 CARs\nfor each individual treatment group (0.8/0.8 and 0.2/1.4). These two groups have different tumor\ncontrol profiles (Fig. 6c) and total number of cells (Suppl. Fig. 12d). It would be interesting to see\nif the described phenotypical differences are maintained when comparing JCAR017 alone with\nJCAR017 in the 50:50 ratio.\nWe thank the reviewer for these insightful suggestions, which substantially strengthened the\ninterpretation of the observed phenotype. We have now separated the analysis of the combined\nJCAR017 and JCAR021 treatments into the individual 50:50 and 10:90 dosing groups. This\nstratification confirms a more pronounced exhausted phenotype in high-affinity JCAR017-T cells\nwhen administered alone compared with the affinity-combined conditions. Moreover, we observed\nthat the shift toward a less exhausted phenotype in high-affinity JCAR017-T cells became\nprogressively more pronounced when moving from the 10:90 to the 50:50 mixing ratio, with\ntranscriptional profiles increasingly resembling those of low-affinity JCAR012-T cells. Notably, the\n50:50 group exhibited a markedly reduced exhaustion phenotype, characterized by significantly\nlower expression of exhaustion-associated genes (e.g., TOX and CCL5), higher expression of\ngenes linked to cytotoxic function (e.g., KLRD1, SCML4, and GZMB), and overall reduced\nexhaustion and dysfunction scores. We hypothesize that these differences reflect increased\nantigen pressure on JCAR017-T cells when delivered at lower doses, a notion further supported\nby the higher residual tumor burden observed under these conditions (Fig. 6c).\nThese new analyses have been incorporated into the revised manuscript as Fig. 6h-j.\n6. The current data set lacks an additional control using high-affinity CAR T cells with\nuntransduced T cells or CARs of unrelated specificity at matched total cell doses. This limits the\nability to conclusively attribute phenotypic shifts in the high-affinity CAR population to active\nsynergy or indirect effects from the low-affinity CAR T cells. Including such controls would help\ndetermine whether the observed effects are specific to affinity combinations or merely a\nconsequence of changes in T cell dose or competition.\nWe thank the reviewer for this suggestion. While we fully appreciate the relevance of the proposed\ncontrol groups, we believe that we have tested a sufficiently broad and diverse set of experimental\nconditions that consistently converged on similar phenotypes indicative of a beneficial effect of the\naffinity-combined products. Overall, our data indicate that the affinity-combined CAR T-cell\nproduct can achieve efficient antitumor activity together with an improved safety profile, while\npreserving a more effector-like rather than exhausted phenotype.\nThe in vivo data shown in Fig. 6 suggest a potential synergistic interaction for the following reason.\nFirst, the 50:50 affinity-combined product exhibits significantly superior antitumor activity\ncompared with JCAR017-T cells alone (Fig. 6c), despite lower expansion of JCAR017-T cells\nwithin the combined product (Fig. S13c). In other words, the improved antitumor efficacy exceeds\nwhat would be expected solely from an increased overall CAR T-cell dose (JCAR017 + JCAR021).\nSecond, the milder signs of exhaustion of JCAR017-T cells in the combined product (Fig. 6g-j)\nwere not readily anticipated.\nNevertheless, we acknowledge that these observations are not sufficient to conclusively\ndemonstrate synergism. Accordingly, we have revised the manuscript and used the term\n“synergistic” cautiously and only as a potential interpretation of the data, not as a firm conclusion.\n7. It remains unclear whether the differences in CAR T cell phenotype (especially exhaustion\nprofiles) could be influenced by differential cytokine production. Is there in vivo data on cytokine\nexpression profiles comparing high- and low-affinity CARs, or in the combination product? This\ncould help determine whether secreted factors from the low-affinity CAR T cells contribute to\nshaping the phenotype or function of their high-affinity counterparts.\nWe appreciate the reviewer interest in cytokine profiling. Circulating cytokine levels were\nmeasured in a humanized mouse model of CRS using a cytokine panel; however, cytokine\nmeasurements were not performed in the tumor-bearing NSG mice, which were instead used for\nextended evaluation of CAR-T cell functionality, persistence, and phenotype. Importantly, the\nrestricted cytokine panel available would not have been sufficient to support mechanistic\nconclusions regarding how low-affinity CAR-T cells modulate high-affinity CAR-T cells.\nWe also considered interrogating our scRNA-seq dataset for cytokine expression. However, in\naddition to the (experiment intrinsic) absence of a JCAR021-T-cell-alone control arm, cytokine\nexpression is only moderately reliable at the single-gene, single-cell level in scRNA-seq data.\nCytokine transcripts are typically low in abundance and exhibit rapid and transient transcriptional\ndynamics, resulting in sparse, noisy, and timing-dependent detection. While these limitations can\nsometimes be mitigated by aggregating large numbers of cells within the same cluster, our dataset\ndid not meet this requirement. Moreover, even under optimal conditions, transcriptional cytokine\nsignals are generally expected to be supported by complementary protein-level measurements.\nAlthough we agree that cytokine production is an important mechanism by which CAR-T cells may\nmutually modulate each other in affinity-combined products, the available datasets do not provide\nsufficient resolution or coverage to allow robust and mechanistically sound conclusions.\nTherefore, we chose not to include cytokine analyses to avoid overinterpretation.\nSeveral issues could be clarified and revised to improve data interpretation. Addressing\nthe points below would enhance clarity\n- Replacing the labels “JCAR017” with “High affinity CAR (ScFv - 2.7 nM)” and “JCAR 021” with “\nLow affinity CAR (ScFv 140 nM)” throughout the figures would make the data more accessible\nand easier to follow for a broader readership, particularly for those less familiar with the\nnames/codes.\nWe thank the reviewer for this suggestion. We have incorporated the affinity values (K ) into the\nD\nFig.1 panels to provide additional clarity. However, we have retained the original CAR names\n(JCAR017 and JCAR021) in the other figures, as these are the established terms used throughout\nthe manuscript and the field. This combination should allow the data to remain accessible while\nmaintaining consistency with literature.\n- CAT CAR T cells are only explored in Fig. 1. Although it is important that the authors benchmark\ntheir findings against other previously described CARs, this could be moved to the supplementary\nfigures, allowing the main figures to focus only on the high and low affinity CARs that are explored\nfurther (JCAR017 and JCAR021).\nWe thank the reviewer for this suggestion but respectfully disagree with it. CAT CAR, as an\neffective low-affinity CAR in a similar affinity range as JCAR021, provide an important benchmark\nfor comparison in Fig. 1. Including CAT CAR-T cells in the main figure allows readers to directly\nassess the relative effects of the high- and low-affinity CARs (JCAR017 and JCAR021) within the\nsame experimental context. Moving CAT to the supplementary figures would reduce the clarity of\nthis comparative assessment.\n- Fig.1g axis label reads E:T 1:4 but the Methods section for the assay description states E:T\n1:0.25, which one is it? Intuitively, one would expect a higher fraction of cells secreting cytokines\nat higher target numbers. The current axis labels suggest otherwise. Please, clarify\nWe thank the reviewer for bringing this to our attention. The correct effector-to-target ratio used in\nthe assay is E:T 1:0.25, as stated in the Methods section. The axis label in Fig. 1g was\ninadvertently mislabeled as “1:4” during figure preparation; mathematically, E:T 1:0.25\ncorresponds to 4:1, and this inversion led to the incorrect annotation. We have now corrected the\naxis label in Fig. 1g to accurately reflect the E:T = 1:0.25 ratio and ensure consistency with the\nMethods description.\n- Fig. 1h More E:T conditions and antigen-densities for each construct could reveal differences in\nthe in vitro killing behavior, particularly under suboptimal T cell conditions where functional\ndifferences are more likely to emerge (see comment in previous section)\nWe assessed in vitro cytotoxicity across a range of E:T ratios down to 0.125:1 using a flow-\ncytometry–based co-culture assay with the CD19-expressing target cell line Nalm6 engineered to\nexpress either wild-type or low levels of CD19. Because Nalm6 cells do not adhere optimally and\nare therefore unsuitable for xCELLigence-based killing assays, we selected a flow-cytometry–\nbased approach, which also enables higher-throughput analysis of multiple conditions in parallel.\nWhile reduced antigen density and lower E:T ratios progressively affected the magnitude and\nefficiency of cytotoxicity after 24 hours, both JCAR017 and JCAR021 exhibited a comparable,\nparallel decline in target-specific killing against wild-type and CD19-low Nalm6 cells. These data\nhave been incorporated into the revised manuscript as Fig. S1d–e.\n- On page 6, the phrase \"the individual label of CAR-T cells with fluorescence conjugated anti-\nCD45 antibodies enabled multiplexing…\" seems to indicate that CAR-T cells were generated and\nstained, while the methods section states that target B cells were stained with anti-CD45\nantibodies. Please clarify this discrepancy.\nWe thank the reviewers for pointing this out. Indeed, it is the target B cells that are specifically\nlabelled with fluorescence-conjugated anti-CD45 antibodies to enable multiplexed k -rate\noff\nmeasurements of 16 different scFvs simultaneously. We adjusted the phrasing in the Results\nsection of the revised manuscript.\n- The logic of Fig. 2 is currently somewhat confusing, as it first addresses and classifies CAR T\ncells based on function, and only later explains that many of the low-functioning CARs do not even\nexpress the receptor as a surface protein. One suggestion for reorganizing the figure is to first\nestablish the affinity of the variants, then describe their expression as CARs in primary T cells,\nand only proceed with the functional assays for those that show clear CAR expression (based on\nEGFRt+ and STII+). Additionally, binning the CARs into groups does not allow the reader to\nappreciate interesting cases of function versus affinity. The heat map in Fig. 2i is a good summary,\nbut including some XY plots of affinity versus target lysis or affinity versus IL-2 secretion could\nhelp to highlight interesting cases. That would also help to feature variants that are used in\nfollowing figures, allowing a better interpretation of those results.\nWe thank the reviewer for the helpful suggestions regarding the structure and clarity of Figure 2.\nIn line with this feedback, we have reorganized the figure to present the data in a more intuitive\nsequence. After the affinity measurements, the revised figure now continues with an assessment\nof CAR surface expression in primary T cells, followed by the functional evaluation of the variants.\nFor the functional analyses, we retained the mutants with suboptimal CAR expression for\ncompleteness, as impaired in vitro functionality in our dataset is predominantly linked to reduced\nreceptor surface expression rather than affinity. This observation underscores the importance of\nconsidering receptor expression quality when interpreting the relationship between functionality\nand affinity, and further supports grouping CAR variants based on surface expression, as it\nrepresents the main source of functional variability in in vitro assays.\nIn addition, we performed the suggested XY analyses (see below, k -rate vs. surface expression\noff\nk -rate vs. target lysis, k -rate vs. IL-2 secretion). However, these did not yield additional\noff off\nmechanistic insights or highlight specific outlier variants, presumably due to the dichotomous\nnature of the functional differences rather than a continuum of variability within our dataset.\nTherefore, we provided these analyses to the reviewers but decided not to incorporate these data\ninto the revised manuscript.\nTogether, these adjustments clarify the logic of Figure 2 and improve alignment between the\ncharacterization of CAR variants and the downstream experimental design. Corresponding\nupdates have been made to the Results section.\nPearson correlation analyses examining the relationship between scFv k -rates and CAR surface expression (a), cytotoxic capacity\noff\ndetermined as target lysis following 24 h co-culture with Raji tumor cells (b), and intracellular IL-2 production (c) in CAR-T cells.\nJCAR021 (light blu), CARmfunct variants (green) or CARmlowfunct variants (yellow).\n- Fig.4 can be rearranged to improve clarity. Figure panels that showed immune reconstitution\n(Suppl Fig.7 c and d) could be moved to main Fig.4. Also, dose titration is interesting mostly only\nin the context of affinity variants. Panels Fig.4 b to g can be moved to supplementary, allowing a\nclearer focus to Panels Fig4h to k. Some panels from Suppl Fig 9 can be then moved also to the\nmain Fig. 4.\nWe appreciate the reviewer’s thoughtful suggestion to reorganize Fig. 4 for improved clarity.\nAccordingly, we have focused Fig. 4 on the assessment of CAR affinities and varying doses in\nrelation to CRS, while relocating the dose-titration experiment of high-affinity JCAR017-T cells and\nthe initial comparison of high- and low-affinity CAR-T cells to the Supplementary Figures (Fig. S8\nand S9, respectively).\n- Which cell line is used in Fig.4 experiments (Raji or Nalm-6), please specify in figure’s legend\nFor each figure (Fig. 4, Fig. S8 and Fig. S9), we have added the corresponding experimental\nschematic, including the target tumor cell line used.\n- Mapping the mutations in the JCAR021 ScFv onto its structure and color-coding them by\nfunctional impact would add valuable insight. This visualization could highlight whether key\nresidues are localized near the CD19 binding interface or whether functional “hotspots” exist in\ncertain regions of the antibody. This may also help clarify why some affinity variants\nbehave differently than expected.\nWe appreciate the reviewer suggestion; however, mapping the mutations within the JCAR021\nscFv would be informative only if the binding interface between JCAR021 and the CD19 epitope\nwere structurally resolved. To the best of our knowledge, neither the residues of the JCAR021\nscFv that directly interact with CD19 nor the crystal structure of JCAR021 have been determined\nto date. In contrast, the binding interface between JCAR017 (FMC63 clone) and CD19 has been\nstructurally resolved (He et al., Sci Immunol 2023). Moreover, our data indicate that JCAR019 and\nJCAR021 recognize the same CD19 epitope (Fig. 1d). Still, this information alone is insufficient to\nreliably infer the CD19-interacting residues of JCAR021, beyond approximate predictions based\non sequence similarity to JCAR017 and other immunoglobulin-like interactions. Such similarity-\nbased prediction is precisely the approach implemented in the ABodyBuilder software, which\nleverages existing structural knowledge of related protein–antigen complexes to propose single–\namino acid substitutions predicted to reduce receptor affinity. Consistent with the inherent\nlimitations of purely predictive algorithms, only a subset of these mutations in our dataset\npreserved CAR expression while successfully reducing affinity.\nMoreover, the affinity-modulating mutations identified in our study are distributed across the entire\nvariable domain, encompassing both complementarity-determining regions (CDRs) and\nframework regions, without revealing a clear empirical association between mutation location and\nfunctional outcome. For example, CAR variants exhibiting the strongest affinity reductions resulted\nfrom mutations located both near the N-terminus (V48E, H38G) and near the C-terminus (V236W,\nV236F) of the primary amino acid sequence. Similarly, substitution of the same polar residue with\ndifferent non-polar amino acids produced divergent outcomes, ranging from complete loss of CAR\nexpression (Y174G) to only a modest reduction in affinity (Y174V).\nIn summary, while the reviewer suggestion is compelling and could indeed yield valuable insights\ninto the relationship between mutation position and functional consequences, addressing this\nquestion rigorously would require dedicated structural studies, beginning with the resolution of the\nCAR–antigen interaction interface.\nTo partially address this point, we have highlighted in yellow residue substitutions that resulted in\nstructural dysfunction in the existing Supplementary Table 1, which summarized the biochemical\ncharacteristics and positional context of all variable residues that were mutated.\n- Fig. 5 would benefit from including data for all the variants mentioned in the figure. The monocyte\ncytokine release assay and the chronic stimulation assay should be performed with all the\ndescribed variants, as well as their combinations. Additionally, at least one variant with\nintermediate affinity between JCAR017 and JCAR021 should be tested (e.g., S168C,\nS227K, S50A). This would allow for better interpretation of the role of affinity in toxicity and exhaustion\nprevention.\nAgain, we thank the reviewer for this constructive suggestion. As discussed above (point 3), we\nanalyzed additional JCAR021-derived CAR variants with respect to toxicity, both as single\nproducts and in combination with high-affinity JCAR017-CAR T cells. These results have been\nincluded as Fig. 5a-e of the revised manuscript and are addressed in details in the corresponding\nsection of this rebuttal (point 3).\nUsing the same receptors and experimental approach, we further extended the chronic stimulation\nassay to additional lower-affinity CARs, specifically the S168C and S227K mutants. T cells\nexpressing these lower-affinity CARs behaved similarly to JCAR021-CAR T cells. Specifically,\nS168C- and S227K-CAR T cells exhibited comparable expansion kinetics under chronic\nstimulation, regardless of the presence of high-affinity JCAR017-CAR T cells, and consequently\nbecame the dominant population within the combined cell product, as also observed for JCAR021-\nCAR T cells. Moreover, S168C- and S227K-CAR T cells expressed lower levels of the exhaustion\nmarkers PD-1, LAG-3, and TIM-3 when cultured alone and contributed to reduced expression of\nthese markers in JCAR017-CAR T cells within the affinity-combined product. These data have\nbeen incorporated into the revised manuscript as Figure 5f–j.\n- Similarly, antigen density is an important factor to evaluate, as it may reveal differences in target\nkilling by the various affinity variants, as observed in Fig. 5n. In addition, Fig. 5n shows that target\nkilling by the combination of CAR T cells appears to reach saturation at 24 hours, which does not\nallow for a proper evaluation of whether the effect of the combined CAR T cell approach is driven\nby phenotypic differences in the high-affinity CAR. Testing different E:T ratios could help the reader\nobserve these potential differences, such as instances where the same amount of high-\naffinity CAR fails to eliminate tumor cells while the combination, even at a lower high-affinity CAR\ndose, is effective. Furthermore, testing similar ratios of JCAR017 and JCAR021 alongside the\nother variants would also be informative.\nAs already discussed before (point 1), we tested more challenging E:T ratios across CARs\nspanning the full affinity spectrum in our dataset, using low and high antigen-expressing CD19⁺\ntumor cells. We did not observe improved resolution with respect to the dependence of in vitro\ntarget cell killing on CAR affinity and antigen density, except for the ultra-low, TCR-like CAR\naffinities (Fig. S4).\nWe therefore focused on the two ultra-low-affinity variants (V236W and V236F) that exhibited\nimpaired in vitro cytotoxicity under conditions of high E:T ratios and low antigen density and\ncombined them at a 1:1 ratio with high-affinity JCAR017 CAR T cells. As in the in vitro CRS model,\nthe mixed products were compared with two JCAR017-CAR T-cell control conditions matched\neither for the total CAR T-cell dose or for the number of JCAR017-CAR T cells present in the\naffinity-combined product. Notably, the combined products rescued the suboptimal cytotoxic\ncapacity observed with low-affinity CAR T cells alone, achieving levels of target cell killing that\nexceeded those of the 0.5× dose JCAR017 control, particularly under stringent conditions of high\nE:T ratios and low antigen density. These data have been incorporated into the revised manuscript\nas Fig. S10.\nFigure 6e. Why does there seem to be much less cells for both high- and low-affinity CAR T a in\nthe UMAP in the 50:50 condition than in the 90:10 condition? The absolute counts in S12c show\notherwise, could you provide an explanation between the count trends in the blood and bone\nmarrow? Similarly, as described before it would be useful if authors split the analysis of the\ncombined JCAR021 and JCAR017 CARs for each individual treatment group (0.8/0.8 and 0.2/1.4).\nAlso, including it would be useful for the interpretation of the results to include in the comparisons\nin Fig. 6h an j the profile of JCAR021 alone and in combination.\nThe UMAPs are derived from scRNA-seq analyses of bone marrow aspirates and should therefore\nbe compared with the data shown in Fig. 6d rather than Fig. S13c (revised manuscript), which\nreflects peripheral blood samples. The total cell counts in Fig. 6d indeed correlate with the relative\nabundances inferred from the UMAPs. In addition, technical factors related to sample preparation\nand data processing should be considered, as these may account for the apparently lower\nrepresentation of JCAR017-T cells in the UMAPs under the 50:50 condition.\nMice treated with JCAR021-T cells alone had to be euthanized due to excessive tumor burden\nprior to the scRNA-seq time point (Fig. 6c). Consequently, this key control was not available,\nprecluding differential gene expression analyses analogous to those performed for JCAR017-T\ncells in Fig. 6f. Nevertheless, JCAR021-T cells from the combined groups were included in the\nanalysis of exhaustion-associated gene expression (Fig. 6g), which revealed no evidence of\nexhaustion or functional impairment.\nThe authors claim: “Our data show that lower-affinity CAR-T cells remain functionally active in the\npresence of high-affinity CAR-T cells, leading to a more controlled and sustained immune\nresponse.” However, this claim is difficult to support with the current experiments. Although it can\nbe assumed that lower quantities of JCAR017 require the presence of JCAR021 to achieve similar\nsurvival (Fig. 6b), effective tumor control appears to require at least 0.8 million high-affinity CAR-\nT cells to prevent tumor growth (Fig.6c). Additionally, low-affinity CAR-T cells achieve similar\nnumbers in the bone marrow under conditions that differ in terms of tumor control (i.e., 1.6 million\nsingle low-affinity cells versus 0.8 million in combination) (Fig.6d). Including an analysis of\nJCAR021 from the scRNAseq data, as previously suggested, may help to substantiate this claim.\nWe thank the reviewer for pointing this out. Indeed, the sentence contained an error resulting from\nan inversion of the terms “lower” and “high.” The corrected sentence now reads: “Our data shows\nthat high-affinity CAR-T cells remain functionally active in the presence of lower-affinity CAR-T\ncells, leading to a more controlled and sustained immune response”. The manuscript has been\ncorrected accordingly.\nPlease clarify if the same donor T cells were used throughout the manuscript or different ones. If\na single one, adding other donor T cells would strengthen the results.\nWe appreciate the reviewer attention to donor variability. To clarify, different primary T-cell donors\nwere used for each independent mouse experiment. This approach was intentionally chosen to\nensure that in vivo outcomes were not dependent on a single donor’s T-cell biology. In cases\nwhere data from multiple experiments were pooled, the use of different donors is explicitly\nindicated in the corresponding figure legends. We agree that donor diversity strengthens the\nrobustness of the findings, and the current dataset already reflects this by incorporating multiple\nindependent donors across experiments.\nMethods are mostly adequate. Extra details in some sections would help to reproduce\nauthors’ work. Specifically:\n- Add source of retroviral expression vector (Addgene?, other lab?)\nSource is now included.\n- Which number of RD114 that was seeded, in which plate/flask format, for how long before\ntransfection.\nThis information is now included.\n- In which media transfection was performed, and was media exchanged during those 72h?\nThis information is now included.\n- For how long the transduced primary T cells were maintained in culture before CAR expression\nwas analyzed. How long after the transduction they were used in in vitro experiments. How long\nfor in vivo experiments.\nThis information is now included.\n- For which experiments CAR T cells were sorted? For which experiments they were not sorted.\nPlease add this information to the figure legend, particularly for the in vivo experiments.\nThis information is now included.\n- For the chronic restimulation assay, please describe the plate format used. Also, add how many\nrounds of stimulation were performed.\nThis information is now included.\n- For BM and spleen preps, do authors intend to write ACK buffer instead of “ACT buffer”?\nWe thank the reviewer for pointing this out. In our manuscript, the term ACT buffer was used in\nsome instances following historical usage in our laboratory protocols and German-language\ndocumentation. Functionally, ACT in our context corresponds to the RBC lysis buffer (ACK buffer)\nused for isolation of nucleated cells from blood or bone marrow.\nReviewer #2 (Remarks to the Author):\nWarmuth et al. present intresting results showing that the combination of high- and low-affinity\nCARs targeting Cd19 antigen can balance the antitumor response by reducing toxicities without\ncompromising efficacy. The authors generated and thoroughly tested a panel of CD19 binders\nand compared them to clinically used CAT. The authors evaluated T cells with different binders\nalone or in combination in vitro and in vivo, including in a humanized model to assess CRS.\nOverall, the manuscript is well presented, original, and addresses a critical question in the field.\nMy only concern is that the study would benefit from deeper mechanistic analyses to determine\nhow low-affinity CARs mitigate high-affinity CAR exhaustion and excessive stimulation. Is this\nachieved through transient antigen masking, reduced tumor burden, or potential cytokine\nsecretion? Addressing this question would further strengthen the authors conclusions. A minor\npoint that should be addressed in the limitations section is the challenge of translating these\nfindings to patients, given the heterogeneity both between patients and across different antigens,\na limitation noted by the authors in the discussion.\nWe thank the reviewer for recognizing the relevance of our study and agree on the importance of\ndeeper mechanistic analyses, which we attempted to address as outlined below.\nFirst, to extend our findings, we evaluated an additional pair of high- and low-affinity CARs\nrecognizing the same epitope on the human ROR1 antigen (high-affinity CAR R12 - K = 0.11 nM;\nD\nlower-affinity CAR R12v20 - K = 0.98 nM) (Hudecek et al., Clin Cancer Res. 2013). Similar to the\nD\nCD19 model, a 50:50 mix of high- and low-affinity CAR-T cells achieved cytotoxicity comparable\nto full-dose high-affinity R12-T cells while outperforming lower-affinity R12v20-T cells, and\nexhibited significantly lower exhaustion levels than high-affinity CAR-T cells after chronic\nstimulation (Fig. S11c-e).\nSecond, we tried to investigate deeper the hypothesis that epitope masking by lower-affinity CAR-\nT cells may contribute to the preservation of functionality in high-affinity CAR-T cells when both\nCARs engage the same epitope. We attempted to assess by live-cell imaging microscopy whether\nlower-affinity CAR-T cells interact more frequently with target cells - presumably due to shorter\ndwell times - thereby masking antigen availability for high-affinity CAR-T cells. We also tested\nreviewer’s suggestion of receptor masking by using anti-CD19 antibody of the same clone like\nJCAR017. However, establishing appropriate experimental conditions for meaningful analyses\nproved technically very challenging.\nFinally, we considered interrogating our scRNA-seq dataset for cytokine expression (Fig.6).\nHowever, in addition to the absence of a JCAR021-T-cell-alone control arm, cytokine expression\nis only moderately reliable at the single-gene, single-cell level in scRNA-seq data. Cytokine\ntranscripts are typically low in abundance and exhibit rapid and transient transcriptional dynamics,\nresulting in sparse, noisy, and timing-dependent detection. While these limitations can sometimes\nbe mitigated by aggregating large numbers of cells within the same cluster, our dataset did not\nmeet this requirement. Moreover, even under optimal conditions, transcriptional cytokine signals\nare generally expected to be supported by complementary protein-level measurements.\nIn summary, the ROR1 antigen model corroborates the observations with the CD19 model,\ndemonstrating improved functionality and less signs of exhaustion of affinity-combined CAR-T\nproducts compared with high-affinity CAR-T cells alone. However, further experiments will be\nrequired to elucidate the mechanisms underlying the beneficial effects of affinity-combined CAR-\nT cell products, which are beyond the scope of this manuscript.\nReviewer #3 (Remarks to the Author):\nThe presented manuscript elaborates the impact of receptor-affinity towards efficacy and safety\nof CD19 targeting CAR T cells. In short, the authors describe that in vivo, but not in vitro function\ncorrelates with affinity. Using improved murine CRS models, the authors show that in high, but not\nin low affinity CAR Ts, toxicity is correlated to dose. In a last step, the authors evaluate the\ncombination of high and low affinity CAR T cells with the aim to maintain efficacy by reducing\ntoxicities such as CRS.\nFor long time, CARs were preferentially generated from high affinity antibodies, whereas\nnowadays, scientists are becoming aware that sometimes, lower affinity might beneficial in specific\nindications (e.g. Olson et al, Leukemia, 2022; Flugel et al, Nat Rev Clin Onc, 2023). Thus, the\ncombinatory approach presented here is of significant interest to the field and displays a concept\nthat has not been presented yet.\nMost of the conclusions and claims are sufficiently supported, however, due to the large amount\nof data (varying dosages and combinations) in the murine studies, the reader would benefit from\nfurther explanation how studies are connected to each other, and if and how conclusions from one\nexperiment might have shaped the setup of the following study. From the data presented, it looks\nlike 2 Mio JCAR017 are typically curative in the used models, whereas 1Mio JCAR017 is not\nsufficient to completely eradicate the tumor. Regarding the combination of JCAR017 and\nJCAR021, there seem to be different ratios that might be beneficiary, and a final conclusion on\nthe optimal ratio is missing. Thus, a final experiment is missing to fully support the main message\nof the manuscript: Within the CRS model, compare an optimal combination (e.g. 1Mio +1Mio, if\nthat is the chosen dosage) against I) a comparable dose (total cell amount =2 Mio) of high affinity\nCAR and II) same amount of high affinity CAR as in the combination (1Mio) to make a final decision\non the dose as well as to have supportive data on efficacy and toxicity, preferably over long term\nto address toxicity as well as long term efficacy and potential relapse.\nWe thank the reviewer for pointing out that our combinatorial CAR-T cell approach “is of significant\ninterest to the field and displays a concept that has not been presented yet.” We understand the\nreviewer’s confusion and questions regarding the recommended cell dose for the affinity-\ncombined product. They arise in part from the necessity of using different experimental models for\ndistinct objectives. Some studies were performed using Nalm6 cells, whereas others employed\nthe more aggressive Raji model. These models differ substantially in growth kinetics and immune\nevasion properties, which inherently influence the dose–response relationships observed across\nexperiments. In addition, CAR-T cell doses used in humanized mouse studies cannot be directly\ntranslated to non-humanized xenograft settings. Humanized mouse models require higher cell\ndoses to induce CRS and are not suitable for long-term monitoring due to xenogeneic and\nallogeneic immune interactions. Consequently, safety and functionality studies necessarily had to\nbe uncoupled.\nDespite these discrepancies, a consistent finding across models is the beneficial effect of a 50:50\ncombination of high- and low-affinity CAR-T cells compared with high-affinity CAR-T cells alone.\nThis affinity-combined product mediated reduced CRS (in vitro), protection from exhaustion of\nhigh-affinity CAR-T cells, and improved anti-tumor activity (revised Figs. 5 and 6). Notably, for\nCRS evaluation - although performed in vitro - we incorporated the reviewer’s suggestion and\ndirectly compared (i) the proposed optimal 50:50 combination dose, (ii) an equivalent total dose\nof high-affinity CAR-T cells, and (iii) the corresponding single-dose high-affinity CAR-T cell\ncondition.\nTo improve clarity, we have added a section to the study limitations describing the need of using\ndifferent dosing regimens throughout the manuscript while explicitly identifying the 50:50\ncombined-product dose as optimal for further investigation.\nStatistics should only be calculated if n ≥3 and biological (but not technical) replicates are\navailable. Smaller datasets can still be presented but should not be included in statistical analysis.\nAll in vitro data have been performed in at least three independent biological replicates, whereas\nmouse experiments include at least four mice per group (except Fig. S8), thereby fulfilling the\nstatistical requirements.\nBesides the above mentioned general comments, there are some details that should be\naddressed:\nIntroduction:\n• Besides JCAR017 being the “central component of most commercially approved anti CD19 CAR\nT products” it should be mentioned that also JCAR021 is being evaluated in clinical trials and\nresults have been reported (PMID 39820359 by Gauthier et al, 2025).\nWe thank the reviewer for bringing this to our attention. The study has been added to the\nIntroduction.\nFigures:\n• Fig. 1h: The wording of figure should be revised: “data was obtained from one experiment”.\nThe text now reads: “Each dot represents a technical replicate (n = 2-3) of one out of three\nindependent biological experiments”. The CAR-T cell cytotoxicity assay in Fig 1h was performed\nusing three independent biological replicates; however, for simplicity, only one representative\nreplicate is shown, as the same trend was observed across all biological replicates. We\nacknowledge that the reviewer’s comment may have arisen from a misinterpretation suggesting\nthat only a single experiment had been performed.\n• Fig 2f: How are constructs assigned to group mfunct and mfunct low? If this assignment is based\non function, there is one construct within the CARmlowfunct group that shows cytokine production\nafter antigen spec. stimulation. Please clarify allocation.\nThe allocation of CAR mutants into functional groups was based on the efficacy of vector delivery\nand CAR surface expression, which we assessed via the transduction marker EGFRt and the CAR\nexpression marker STII, respectively. CARmfun preserved an optimal CAR surface expression, as\nindicated by the correlation between STII and EGFRt highly comparable to JCAR017 and\nJCAR021. In contrast, CARmlowfunct displayed either weak co-expression of the CAR and EGFRt\nmarkers, or transduction rates below 20%. In the revised manuscript, we have reorganized Fig. 2\nso that surface expression is presented as the first parameter, making the rationale for group\nallocation clearer.\n• Fig. 2h: In addition to the transduction rate, is the MFI also reduced in the mlowfunct group?\nThe surface expression profiles of CARmfunct and CARmlowfunct constructs are shown in Fig. S3a.\nConstructs lacking detectable STII on the cell surface consistently exhibit reduced MFI among\nsuccessfully transduced cells. Moreover, CARmlowfunct variants with overall lower gene delivery or\nintegration efficiencies display correspondingly decreased STII MFI. As summarized in the\naccompanying figure, CARmlowfunct constructs uniformly show lower MFI values compared with\nCARmfunct, underscoring their reduced surface expression (see below).\nCAR surface expression indicated as Mean Fluorescence Intensity (MFI) for CAR-T cells expressing JCAR021 (light blu), CARmfunct\nvariants (green) or CARmlowfunct variants (yellow).\n• Fig 3f/S5b: BLI data from the one mouse surviving in the L237W group (d28) is shown in S5b,\nbut not in 3f. Please justify why this has been excluded from the analysis.\nWe appreciate the reviewer’s comment. In the original version, the data point from the single\nremaining mouse in the L237W group at day 28 was not included in Fig. 3f because this figure\ndisplays group-level summaries (mean + SD), which cannot be meaningfully calculated for n = 1.\nTo avoid implying statistical representativeness where it is not present, this individual value was\nshown only in the BLI image in the supplementary figure. For completeness and transparency, we\nhave now included the full dataset in the revised version of Fig. 3f.\n• Fig. 3g ff: What is the baseline of the Mock T cells? Were any Mock T cells detectable in blood,\nBM or spleen?\nMock T cells were indeed detectable in blood (day 7), and bone marrow (BM) and spleen at the\ncorresponding endpoints, as shown in the figure below (a = blood at day 7, b = BM and c = spleen\nat the endpoint). Mock T cells appeared at high levels during the early time course in the peripheral\nblood and in the spleen, but are barely detectable at the tumor site, which is expected given their\nlack of antigen specificity and thereby infiltration at the relevant tumor site.\nAlthough mock T cells represent an important control for survival and residual tumor burden\nanalyses, they provide limited information for assessing CAR-T cell persistence and phenotype at\nlater time points, as mock-treated mice succumb to tumor progression within 10–14 days after\ntumor injection; accordingly, this group was not included in Fig. 3g.\nQuantification of unedited (mock) or CAR-T cells adoptively transferred into tumor-bearing mice. Related to Fig.3 of the revised\nmanuscript.\n• Fig S6: Please include average radiance analysis of the remaining mice of d24 as the final day\nof the experiment\nThe average radiance values for the remaining mice at day 24 have now been included in the\nrevised analysis and are shown in Fig. S7e of the revised manuscript.\n• Fig. 4: How has the murine CRS model been improved? Please indicate for each experiment\nwhich cell line was actually used (Nalm-6 or Raji).\nTo improve the murine CRS model, we performed HSC titrations to generate larger cohorts of\nhumanized mice derived from a single cord blood donor (Schütz et al., 2025 preprint). This\napproach reduces allo- and xeno-reactive responses by limiting the number of pooled HSC\ndonors, which are commonly used in commercially available preparations. By minimizing donor\nheterogeneity, the model achieves more consistent engraftment and immune composition,\nimproving reproducibility and reliability of the experiments. We added some of these advantages\nto the revised manuscript.\nFor clarity, the specific cell line used in each experiment (Nalm-6 or Raji) is now indicated in the\nrespective figure panels.\n• Fig 4h-k: Even though Fig 4 is meant to demonstrate toxicity, the BLI imaging suggests that the\nlow affinity CAR might have an antitumor effect at high dosage while showing a lower toxicity.\nIs there data available on longer observation periods regarding efficacy?\nIndeed, the BLI signals in Fig. 4h-k of the original manuscript (now Fig. 4f-j) indicate that low-\naffinity JCAR021-T cells exert antitumor activity while maintaining a more favorable toxicity profile.\nConsistently, we previously observed a degree of antitumor activity for JCAR021-T cells in\nimmunocompromised tumor-bearing mice, as reflected by improved survival compared with\nuntreated controls (Fig. 3e–f). However, this benefit is transient, as low-affinity CARs are unable\nto efficiently control tumor growth at later stages in our experimental setting. Unfortunately, the\nused in vivo CRS model has inherent limitations that prevent extended observation periods. Due\nto donor mismatches, xenogeneic responses and allo-reactive components, mice frequently\ndevelop rejection-related complications that constrain the feasible timeframe of analysis.\nConsequently, prolonged efficacy assessments beyond the time window shown in Fig. 4 cannot\nbe reliably performed in this model, necessitating the uncoupling of toxicity evaluation from long-\nterm efficacy following CAR-T cell adoptive transfer.\n• Fig: 5b: Does the ametrine fluorescent protein influence CAR expression or functionality?\nWe appreciate the reviewer’s question. In our experiment, Ametrine was co-expressed with the\nCAR and used in vitro and in vivo without any detectable impact on CAR surface expression.\nMoreover, Ametrine+ CAR-T cells behave as expected in functional assays, as shown in Fig. 5\nand 6. Ametrine served solely as a fluorescent marker to track CAR-T cells.\n• Fig 5c: Please clarify the composition of CAR017 and JCAR021 at t=0\nAt t=0 JCAR017 and JCAR021 cell numbers were counted separately and then combined at a\n50:50 ratio to initiate the co-culture. After 24 hours, the composition remained largely stable with\nonly minor changes in the relative proportion of the two CAR populations. Any deviations from the\ndefined affinity combination were minimal, such that the initial configuration of the two products\nwas essentially maintained.\n• Fig 5a-e: From the presented data, it is not clear if the combination has a benefit at all. A control\ncondition containing the reduced amount of JCAR017 without the addition of JCAR021 would be\nhelpful to fully interpret the results.\nTo address this point, we updated Fig. 5a–e to include the reduced dose of JCAR017 alone, as\nsuggested by the reviewer. In addition, we extended the analysis to include additional JCAR021-\nderived CAR variants and their corresponding affinity-combined products with JCAR017-T cells.\nNotably, a reduced dose of JCAR017-T cells (0.5x dose) induced stronger CRS than individual\nlower-affinity CARs administered at twice the dose (1x dose). More importantly, the 0.5x dose\nhigh-affinity CAR-T cells alone triggered, to some extent, higher cytokine release than the affinity-\ncombined CAR products (0.5x JCAR017-T cells plus 0.5x lower-affinity CAR-T cells), indicating\nthat affinity combination does not exacerbate CRS despite the increased total cell number. These\ndata have been incorporated into the revised manuscript as Fig. 5a–e.\n• Fig.5n: please include a condition of 0.01x10^6 JCAR017 to enable a conclusion if similar lysis\nwould also be achieved by the lower dose of JCAR017 in the complete absence of JCAR021. In\nthe current data set, Figs. 5 and S10 do not sufficiently support the main message of the paper,\nas relevant controls are missing.\nWe agree with the reviewer on the importance of the suggested control, which was included in\nrepetition experiments. Moreover, we extended the cytotoxic analyses to more stringent effector-\nto-target ratios and the use of CD19+ target cells with high and low antigen expression. Now, the\nmixed products were compared with two JCAR017-CAR T-cell control conditions matched\neither for the total CAR T-cell dose or for the number of JCAR017-CAR T cells present in the\naffinity-combined product. Notably, the combined products rescued the suboptimal cytotoxic\ncapacity observed with low-affinity CAR T cells alone, achieving levels of target cell killing that\nexceeded those of the 0.5× dose JCAR017 control, particularly under stringent conditions of high\nE:T ratios and low antigen density. These data have been incorporated into the revised manuscript\nas Fig. S10.\n• Fig. S10: same as Fig 5. In Figure S7, it is shown that giving 2 or 4 Mio of JCAR017 does not\nhave a significant difference in efficacy. Thus, the data from S7 suggest that the observed effect\nis caused by the reduction of the amount of JCAR017, but not from the combination with the low\naffinity CAR.\nWe agree with the reviewer that the experimental setup of Fig. S10 in the original manuscript does\nnot allow the observed reduction in tumor burden to be unequivocally attributed to the combined\nproduct rather than to the total dose of 2 million JCAR-T cells, as an additional control group\nreceiving 2 million JCAR-T cells alone was missing. Accordingly, these data have been removed\nfrom the revised manuscript.\n• Fig. S11: in contrast to the text (p.12), Fig. S11 doesn’t demonstrate increased safety, but\nefficacy of combined CAR T. Indeed, a comparison of this “optimal combination approach” to\nstandard dosages with regards to safety and efficacy would strongly support the manuscript.\nWe agree with the reviewer that Fig. S11 (now Fig. S12 in the revised manuscript) demonstrates\nthe anti-tumor efficacy of affinity-combined products rather than safety outcomes. This was indeed\nthe intent of the experiment; however, we recognize that the original phrasing was suboptimal and\nled to misinterpretation.\nIn this experimental setting, we combined a fixed, suboptimal dose of high-affinity JCAR017-T\ncells - insufficient to achieve tumor clearance - with increasing doses of low-affinity JCAR021-T\ncells. The rationale was to assess whether higher doses of low-affinity CAR-T cells could rescue\nthe suboptimal anti-tumor activity of high-affinity CAR-T cells. This strategy has potential\nimplications for designing CAR-T products with an improved balance between efficacy and safety,\nas CRS severity correlates with the dose of high- but not low-affinity CAR-T cells (Fig. 4).\nHowever, we observed a beneficial anti-tumor effect of the combined product only at very high\ndoses of JCAR021-T cells (16-fold excess), indicating that this approach is not optimal and would\nbe difficult to translate into a combined product with an improved therapeutic index.\nWe have rephrased the rationale underlying this experiment accordingly and hope this clarification\naddresses the reviewer’s comment.\n• Fig. S11a: 1M JCAR017 and 1M JCAR017 +1M JCAR021 are not shown in b/c. if these\nconditions were not assessed here, but in a separate experiment (d/e), please delete in the\nexperimental set up (a).\nWe thank the reviewer to point this out. We have removed 1M JCAR017 and 1M JCAR017 + 1M\nJCAR021 from the experimental setup in panel a (Fig. S12a of the revised manuscript).\n• Fig. S11d/e is mentioned in the text in correspondence with Fig S12, maybe consider relocation.\nWe understand the reviewer’s point of view and agree that disrupting the numerical flow of figures\nand subpanels is not ideal. However, to strictly preserve the numbering sequence, Fig. S11d/e\nfrom the original manuscript would need to be placed as Fig. S13c (revised manuscript), which\nwould disrupt the internal cohesiveness of Fig. S13. Therefore, although not optimal, we chose to\nretain the original figure order.\nDiscussion:\n• The affinity variants of the CAR all target the same epitope within CD19. As one suggested mode\nof action is the competitive binding and availability of antigen binding sites, do you think the effects\nwould be similar when targeting different epitopes?\nWe thank the reviewer for this insightful comment. We were also very interested in whether epitope\nspecificity might influence the observed phenotype. To address this, we first evaluated an\nadditional affinity-tuned CAR pair targeting the same epitope to confirm the superior features of\naffinity-combined CAR-T cell products over monospecific high-affinity CAR-T cells. Specifically,\nwe analyzed CARs with variable affinities binding the same epitope on the human ROR1 antigen.\nSimilar to the CD19 model, a 50:50 mix of high- and low-affinity CAR-T cells achieved cytotoxicity\ncomparable to full-dose high-affinity CAR-T cells while outperforming lower-affinity CAR-T cells,\nand exhibited significantly lower exhaustion levels than high-affinity CAR-T cells after chronic\nstimulation. These data are presented in Fig. S11 of the revised manuscript.\nMoreover, we tried to investigate deeper the hypothesis that epitope masking by lower-affinity\nCAR-T cells may contribute to the preservation of functionality in high-affinity CAR-T cells when\nboth CARs engage the same epitope. We attempted to assess by live-cell imaging microscopy\nwhether lower-affinity CAR-T cells interact more frequently with target cells - presumably due to\nshorter dwell times - thereby masking antigen availability for high-affinity CAR-T cells. We further\nattempted to recapitulate the phenotype of affinity-combined CAR-T cell products by co-culturing\nhigh-affinity CAR-T cells with target cells in the presence of an anti-CD19 antibody of the same\nclone as that used in JCAR017. However, establishing appropriate experimental conditions for\nmeaningful analyses proved technically very challenging. Further experiments will be required to\nelucidate the mechanisms underlying the beneficial effects of affinity-combined CAR-T cell\nproducts, which are beyond the scope of this manuscript.\nReviewer #4 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is\npart of the Nature Communications initiative to facilitate training in peer review and to provide\nappropriate recognition for Early Career Researchers who co-review manuscripts.\nWe thank the reviewer for their constructive feedback, which contributed significantly to the\nrevision process and to improving the quality of the revised manuscript."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have significantly improved their manuscript. Also they have responded adequately to the questions and\ncomments. We recommend that this article is accepted for publication.\nMinor typo in page 12 of the revised manuscript, “JCAR012” perhaps the authors meant JCAR021\nRogelio A. Hernandez-Lopez\nDaniel Hoces", "reviewer_2": "The authors addressed my concerns and significantly improved the manuscript", "reviewer_3": "Thanks to the authors for the revised manuscript and the given answers. All questions have been adressed.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts."}, "author_response": ""}]

Decision letter