Post-infusion predictors of car t-cell therapy response

Abstract

Disclosed herein is a novel set of cellular markers which can be used to rapidly analyze blood samples taken at early timepoints from patients treated with commercial CAR- T to predict risk of CAR-T failure in the long term. Subjects with predicted CAR-T failure can be treated with alternative therapies without waiting for a poor clinical outcome.

Description

TH Docket No.321502-2150 POST-INFUSION PREDICTORS OF CAR T-CELL THERAPY RESPONSE CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims benefit of U.S. Provisional Application No.63 / 567,100, filed March 19, 2024, which is hereby incorporated herein by reference in its entirety. STATEMENT OF GOVERNMENT INTEREST

[0002] This invention was made with Government Support under Grant No. CA260858 awarded by the National Institutes of Health. The Government has certain rights in the invention. BACKGROUND OF THE INVENTION

[0003] CAR-T cell therapy (CAR-T) directed against CD19 (CAR19) is standard of care (SOC) for patients with relapsed / refractory (R / R) B-cell non-Hodgkin’s lymphoma (NHL) (Neelapu SS, et al. N Engl J Med.2017377(26):2531-2544; Schuster SJ, et al. N Engl J Med.2019380(1):45-56; Abramson JS, et al. Lancet.2020396(10254):839-852; Locke FL, et al. N Engl J Med.2022386(7):640-654; Kamdar M, et al. Lancet.2022399(10343):2294- 2308; Jacobson CA, et al. Lancet Oncol.202223(1):91-103; Fowler NH, et al. Nat Med. 202228(2):325-332; Wang M, et al. N Engl J Med.2020382(14):1331-1342). Axicabtagene ciloleucel (axi-cel) and brexucabtagene autoleucel (brexu-cel) are commercially available CAR19 products containing a CD28 co-stimulatory domain (CD28-CAR19) used to treat R / R NHL. CD28-CAR19 products historically have resulted in complete response (CR) rates of 50%-65% at 6 months, after which, disease progression is uncommon (Locke FL, et al. N Engl J Med.2022386(7):640-654; Wang M, et al. N Engl J Med.2020382(14):1331-1342; Nastoupil LJ, et al. J Clin Oncol.202038(27):3119-3128; Locke FL, et al. Lancet Oncol. 201920(1):31-42; Jacobson CA, et al. J Clin Oncol.202038(27):3095-3106). However, a significant proportion of patients still experience failure CAR19. Multiple studies have identified clinical risk factors for CAR-T failure including high disease burden, extranodal disease, poor performance status, and increased baseline inflammatory markers (Vercellino L, et al. Blood Adv.20204(22):5607-5615; Locke FL, et al. Blood Adv.20204(19):4898- 4911; Jain MD, et al. Blood.2021137(19):2621-2633). However, patients with multiple clinical risk factors can still experience success with CAR19, and patients with low risk still experience failure.

[0004] Prior studies focusing on commercial CAR-T cells have described features that correlate with clinical outcomes. More naïve-like and memory like CAR-T cells present in leukapheresis products and CAR19 infusion products have been correlated with increased response rates while increased populations of exhausted CD8+CAR-T cells correlated with worse outcomes (Locke FL, et al. Blood Adv.20204(19):4898-4911; Deng Q, et al. NatTH Docket No.321502-2150 Med.202026(12):1878-1887; Monfrini C, et al. Clin Cancer Res.202228(15):3378-3386). Post-infusion peak expansion of CD28-CAR19 CAR-T cells relative to tumor burden has been correlated with improved outcomes (Locke FL, et al. Blood Adv.20204(19):4898- 4911), however other studies reveal a weak or no association between CAR-T expansion and outcomes (Garcia-Calderon CB, et al. Front Immunol.202314:1152498; Good Z, et al. Nat Med.202228(9):1860-1871).

[0005] Additionally, biomarkers to predict severe (Grade 3 or higher) immune effector cell associated neurotoxicity syndrome (ICANS) have been difficult to quantify for CD28-CAR19 products in NHL. Increased CAR-T expansion and higher baseline and peak inflammatory markers have been shown to correlate with severe ICANS in some studies, but not in others (Neelapu SS, et al. N Engl J Med.2017377(26):2531-2544; Locke FL, et al. Lancet Oncol.201920(1):31-42; Locke FL, et al. Blood Adv.20204(19):4898-4911; Strati P, et al. Journal of Clinical Oncology.202240(16_suppl):7567-7567). In acute lymphoblastic leukemia (ALL), higher pre-treatment disease burden also correlates with ICANS, but less evidence of this has been found for NHL (Santomasso BD, et al. Cancer Discov.2018 8(8):958-971). A previous study has identified lower levels of CAR+Tregs post-infusion correlates with more severe ICANS (Good Z, et al. Nat Med.202228(9):1860-1871); however, no other features of potential direct mediators of ICANS (ex. CD8+T cells) have been found. Thus, we sought to identify more robust predictive factors identifying patients at high risk of CAR19 failure and of developing high grade ICANS in order to improve management and the clinical outcomes of patients receiving CAR-T.. SUMMARY OF THE INVENTION

[0006] Disclosed herein is a set of cellular markers which can be used to rapidly analyze blood samples taken at early timepoints from patients treated with commercial CAR- T to predict risk of CAR-T failure in the long term.

[0007] CAR T-cell therapy (CART) directed against CD19 (CAR19) is standard of care (SOC) for certain patients (pts) with B-cell Non-Hodgkin’s Lymphoma (NHL). Commercially manufactured CAR T-cell products are used in the majority of cases and are now approved as second line therapy for certain patients with NHL, the most common kind of lymphoma. Prior studies have identified clinical risk factors for CART failure including high disease burden, extranodal disease, poor performance status, and increased baseline inflammatory markers. However, patients with multiple clinical risk factors can still experience success with CAR19, and patients with low risk still experience failure. Often, the exact failure mechanism is not known and novel biomarkers which may predict failure are of great interest.

[0008] In some embodiments, the method involves first identifying CD8+T cells in post-infusion blood that have been transduced with the CAR molecule. Multiple strategiesTH Docket No.321502-2150 can be utilized to identify CAR T-cells contained within the blood of patient treated with commercial CAR-T products. The method next involves using various biomarkers to identify the following subtypes of CD8 CAR+T-cells that can predict outcomes: PD1+CAR+CD8+T- cells, PD1+TCF1+CAR+CD8+T-cells, PD-1+TOX-CAR+CD8+T-cells, and PD1+Tim3+CAR+CD8+T-cells (e.g. PD1+Tim3+Tbet+GZMB+CAR+CD8+T-cells). The relative percentage of these subtypes in the subject’s blood post-infusion can then be compared to non- responder control values to predict therapeutic outcomes.

[0009] The disclosed compositions and methods have notable advantages compared to previously utilized assays. The method has been characterized at the day 14 post infusion timepoint (with appropriate intervals provided to allow for difficulty obtaining sample). However, in some embodiments, the blood sample is taken 5 to 30 days post- infusion, including 10 to 21 days post-infusion, such as day 5, 6, 7, 8, 9 , 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30 post-infusion. When a 5 to 30 day post-infusion blood sample is used, the disclosed method can predict long-term outcomes to CAR-T cell therapy, including response rates at 6 months and longer term progression free survival. It's important to note that response at 6 months is commonly used as a surrogate for longer term outcomes in commercial CAR-T for Non-Hodgkins Lymphoma (NHL) given the low rates of relapse after this timepoint. These timepoints are earlier post infusion than previously described risk stratification methods including: PET imaging used at Day 30, and minimal residual disease (MRD) analysis used at Day 28. Additionally, MRD analysis (by Next Generation Sequencing, ex. Clonoseq), used to predict outcomes in NHL post CAR-T, is extremely expensive and requires complicated sample collection techniques and burdensome navigation of a commercial online portal. percentage of patients will have expanded their CAR T-cells by this timepoint (range 5-14 days for max expansion) and thus circulating CAR T-cells will be easier to detect and presumably outcome prediction have improved sensitivity. Additionally, these markers outperformed the quantification of the expansion of CAR T-cells, and the analysis of clinical parameters which both have traditionally been used to predict clinical outcomes with CAR-T. Thus, the disclosed compositions and methods have a multitude of advantages over previously described methods used to predict outcomes with CAR-T therapy.

[0010] Also disclosed herein is a flow cytometry kit comprising antibodies to detect the disclosed biomarkers and associated required reagents and protocols. This would include a surface antibody cocktail (comprising the Viability assay, CD45, CD3, CD4, CD8, PD1, Tim3, and CAR19 Detection Reagents), an intracellular antibody cocktail (comprising TCF1, Tbet, and GZMB), Fc blocking reagent, and appropriate buffers to perform both surface and intracellular (ICS) incubations, as well as subsequent flow analysis. This kit could also contain an appropriately detailed protocol such that a sufficiently skilledTH Docket No.321502-2150 technician, with access to adequate samples, could analyze samples and predict outcomes with relative ease. A method such as this could be used to rapidly and cheaply analyze a patient’s post CAR-T infusion samples in real time in order to quantify patient’s risk of CAR-T failure. Such a flow kit, provided to an institution with the appropriate expertise and infrastructure, could be used to build a CLIA certified assay which can be utilized by clinical flow labs to test patient samples at specific time intervals post infusion of CAR-T to predict outcomes. Such a product could be also used by companies seeking to develop send out assays for the prediction of outcomes with CART (ex. Mayo Clinic, LabCorp). Expert consultation from our team can be provided to such entities in order to assist with kit optimization.

[0011] The disclosed combination of markers can be used as predictors for CAR-T outcomes in a broad array of applications. Flow cytometry is one example of an easy and simple way to analyze samples using these markers, however the same markers can be used in such applications as mass spectrometry, single cell RNA Sequencing, cite-seq, and other applications used to investigate CAR T-cells at the single cell level. Cell sorting is one important application to note, given its ability to isolate cells that may mediate response to CAR-T. The disclosed methods and the products derived from it, could then be used to isolate and analyze CAR T-cells, which could then be subjected to a host of in vitro and in vivo quality assays. Such a product could then potentially be used by companies and academic centers alike to investigate their own products, and optimize their manufacturing processes and CAR-T products.

[0012] The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims. BRIEF DESCRIPTION OF FIGURES

[0013] FIGs.1A to 1F show differentially abundant CD8+CAR+T cell clusters in CR and PD cohorts. PBMCs from the Day 14 post-CAR-T timepoint were analyzed via spectral flow cytometry. FIG.1A is a representative 2D flow cytometry plot showing gating strategy for CAR19+CD8+CAR-T cells. Healthy donor samples were utilized as negative controls. Percentages of CD3+T cells as well as CAR19+CD8+T cells are indicated. FIG.1B contains box plots of CAR19+CD8+cells as a percent of live CD45+CD3+lymphocytes in CR vs. PD cohorts (left) or absolute # of CAR19+CD8+lymphocytes in CR vs. PD cohorts (right). FIG. 1C contains contour UMAP plots of CAR19+CD8+T cells in CR vs. PD cohorts. FIG.1D is a UMAP dot plot of CAR19+CD8+T cells from the total cohort (n=26). FIG.1E shows UMAP of CAR19+CD8+T cells in CR vs. PD cohorts with clusters increased in CR (Clusters 7, 8, 9, 11, 12, 13) and clusters increased in PD (Clusters 2, 3, 4). FIG.1F contains box plots showing combined clusters percentages of CAR19+CD8+Cells. Left: Combined clusters 7,TH Docket No.321502-2150 8, 9, 11, 12, and 13 in CR vs. PD. Right: Combined clusters 2, 3 and 4 in CR vs. PD. Box plots in FIGs.1B and 1F show quartiles with bands at the median; whiskers indicate 1.5 interquartile range; all observations overlaid as dots. P values are from linear regression analysis. p < 0.05 = *; p < 0.01 = **; p < 0.001 = ***.

[0014] FIGs.2A to 2D show PD-1+CD8+CAR+T cell clusters increased in the CR cohort. FIG.2A is a clustered heatmap showing key marker expressions on differentially abundant CAR+CD8+clusters. Clusters 8 and 9: PD-1+TCF1+. Clusters 7 and 13: PD-1+TCF1lowTOX-. Clusters 11 and 12: PD-1+TIM3+T-bet+GZMB+. Clusters 2, 3 and 4: PD-1- T- bet+GZMB+. Color scale was determined by median normalization of each individual marker with blue representing low expression, white representing median expression and red representing high expression. FIG.2B contains box plots of clusters in CR vs. PD cohorts. Cluster abundance was reported as a percentage of CAR+CD8+T cells. FIG.2C shows UMAP of CAR+CD8+T cells in CR vs. PD cohorts, colored by cluster. FIG.2D contains expression plots of phenotypical and functional markers present on CAR+CD8+T cells. Expression of markers on individual cells were overlaid onto the UMAP space in CR (top) vs. PD (bottom) cohorts. Box plots show quartiles with bands at the median; whiskers indicate 1.5 interquartile range; all observations overlaid as dots. P values are from linear regression analysis. p < 0.05 = *; p < 0.01 = **; p < 0.001 = ***.

[0015] FIGs.3A to 3H show key post-infusion PD-1+CAR+CD8+T cell populations correlate with clinical outcomes.2D flow plot analysis was performed on spectral flow cytometry data from Day 14 post-CAR-T samples. FIG.3A contains representative 2D flow cytometry plots showing individual patient PD-1 and TCF1 expression in CAR+CD8+T cells and corresponding box plot quantification in CR vs. PD cohorts. FIG.3B contains representative 2D flow cytometry plots showing individual patient EOMES and CD45RO expression in CAR+CD8+PD-1+TOX- T cells and corresponding box plot quantification in CR vs. PD cohorts. FIG.3C contains representative 2D flow cytometry plots showing individual patient PD-1 and TIM3 expression in CAR+CD8+T-bet+ GZMB+ T cells and corresponding box plot quantification in CR vs. PD cohorts. FIGs.3D to 3F show Kaplan- Meier (KM) analysis used to generate PFS curves stratified by high vs. low percent of CD8+CAR-T cell populations. FIG.3D shows KM analysis of PFS for patients with high (>4%) or low (<4%) percent of this cell type; high group n=6; low group n=20. FIG.3E shows KM analysis of PFS for patients with high (>4.7%) or low (<4.7%) percent of this cell type; high group n=13; low group n=13. FIG.3F shows KM analysis of PFS for patients with high (>12%) or low (<12%) percent of this cell type; high group n=17; low group n=9. FIG.3G shows box plot of the combination of PD-1+TCF1+cells and PD-1+TIM3+T-bet+GZMB+cells in CR vs. PD (left); and KM analysis of PFS for patients with high (>24%) or low (<24%) percent of this combination of cell types; high group n=13; low group n=13 (right). FIG.3HTH Docket No.321502-2150 shows box plot of the combination of PD-1+TCF1+cells, PD-1+TOX- EOMES+CD45RO+cells, and PD-1+TIM3+T-bet+GZMB+cells in CR vs. PD (left); and KM analysis of PFS for patients with high (>25%) or low (<25%) percent of this combination of cell types (right); high group n=15; low group n=11. For all KM curves, the x-axis was time in days from date of CAR-T infusion. Dotted lines on box plots indicate separation lines between high and low percentages of CAR-T cells in each population and were selected based on optimal response separation between cohorts. Because clinical outcomes were known during patient stratification, p values need to be interpreted with caution. Box plots in FIG.3A, 3B, and 3C show quartiles with bands at the median; whiskers indicate 1.5 interquartile range; all observations overlaid as dots. P values are from linear regression analysis (cell type % changes) and log-rank tests (PFS). p < 0.05 = *; p < 0.01 = **; p < 0.001 = ***.

[0016] FIGs.4A to 4C show PD-1 expression on post-infusion CD8+CAR-T cells correlates with improved clinical outcomes. FIG.4A shows individual patient PD-1 expression on CAR+CD8+T cells was plotted in the UMAP space; CR (top) vs. PD (bottom). FIG.4B shows individual patient pre- and post-CAR-T infusion FDG-PET scans. Pre-infusion PETs were performed within 30 days of CAR-T infusion; red arrows point to site of pre- infusion lymphoma lesions. Post-infusion PETs were performed 30-60 days post-CAR-T; red arrows point to areas of resolution or progression of lymphoma. FIG.4C shows representative 2D flow cytometry plot showing PD-1 expression in CR vs. PD cohorts (top); percentages of PD-1+CAR+CD8+T cells in CR vs. PD cohorts (bottom left); KM analysis of PFS for patients with high (>57.5%) or low (<57.5%) percent of PD-1+CD8+CAR-T cells (bottom right); high group n=12; low group n=14. X-axis is time in days from date of CAR-T infusion. Dotted lines on box plots indicate separation lines between high and low percentages of CAR-T cells and were selected based on optimal response separation between cohorts. Because clinical outcomes were known during patient stratification, p values should to be interpreted with caution. Box plots show quartiles with bands at the median; whiskers indicate 1.5 interquartile range; all observations overlaid as dots. P values are from linear regression analysis (cell type % changes) and log-rank test (PFS). p < 0.05 = *; p < 0.01 = **; p < 0.001 = ***.

[0017] FIGs.5A to 5C show higher quantities of PD1+TIM3+effector-like CD8+CAR- T cells correlate with severe ICANS in CR. Patients who achieved CR (n=16) were separated into a severe ICANS (Grade 3-4) cohort (n=4) and a no / non-severe ICANS (Grade 0-2) cohort (n=12). FIG.5A shows day 14 post-infusion PBMCs were analyzed by spectral flow cytometry and dimensional reduction. Individual patient UMAPs of CAR+CD8+T cell clusters in ICANS (left) vs. no / non-severe ICANS cohorts (right) are shown, colored by cluster. Largest cross sectional tumor diameter prior to CAR-T infusion is listed underneath patient identifying numbers. Box plots in 5B and 5C compare characteristics in severeTH Docket No.321502-2150 ICANS vs. no / non-severe ICANS cohorts. FIG.5B shows combined clusters 11 and 12, reported as a percent of CAR+CD8+T cells. FIG.5C shows PD-1+TIM3+T-bet+GZMB+cells quantified by 2D flow analysis, reported as a percentage of CAR+CD8+Cells. Box plots show quartiles with bands at the median; whiskers indicate 1.5 interquartile range; all observations overlaid as dots. P values are from linear regression analysis. p < 0.05 = *; p < 0.01 = **; p < 0.001 = ***.

[0018] FIG 6 shows Kaplan-Meier analysis of overall survival and progression free survival for the total cohort (n=26). X-axis: time in days from CART infusion.

[0019] FIG.7 shows a gating strategy to identify CAR+CD8+T-cells. PBMCs from the Day 14 post-CAR-T timepoint were analyzed via spectral flow cytometry. CD45+and live cells were first gated on, followed by CD3+T-cells and then CAR+CD8+T-cells.

[0020] FIG.8 shows quantity of CD3+CAR-T cells in CR and PD cohorts. PBMCs from the Day 14 post-CAR-T timepoint were analyzed via spectral flow cytometry. Left: A representative 2D flow cytometry plot with the gating strategy for CD3+CAR19+CAR-T cells is shown. Healthy donor samples were utilized as negative controls. Right: Box plot of CAR19+CD8+cells as a percent of live CD45+CD3+lymphocytes in CR vs. PD cohorts. Box plots show quartiles with bands at the median; whiskers indicate 1.5 interquartile range; all observations overlaid as dots. No significant difference found between CR and PD cohorts by linear regression analysis.

[0021] FIGs.9A and 9B show all marker and cluster heatmaps. PBMC’s from the Day 14 post-CART timepoint from the total cohort were analyzed via spectral flow cytometry, gated on CAR+CD8+T-cells and analyzed via dimensional reduction. Flowsom clustering analysis was performed. FIG.9A shows a clustered heatmap for all markers and all clusters. Color scale was determined by median normalization of each individual marker with blue representing low expression, white representing median expression and red representing high expression. FIG.9B is a heatmap depicting abundance of each cluster in the CR vs. PD cohorts. Color scale was determined by median normalization of the percent abundance of all clusters with blue representing low abundance, white representing median abundance and red representing high abundance.

[0022] FIGs.10A and 10B are 2D plots of all markers. PBMC’s from the Day 14 post-CART timepoint from the total cohort (n=26) were analyzed via spectral flow cytometry and gated on CAR+ CD8+ T-cells.2D plots from patients showing representative positive expression (FIG.10A) and negative expression (FIG.10B) of each marker were generated with FlowJo.

[0023] FIG.11 shows analysis of PD-1-T-bet+GZMB+CD45RA+cells in the CR vs. PD Cohort.2D flow plot analysis was performed on spectral flow cytometry data from Day 14 post-CART samples. Representative 2D flow cytometry plots showing individual patient PD-TH Docket No.321502-2150 1 and CD45RA expression on CAR+CD8+T-bet+GZMB+T-cells and corresponding box plot quantification in CR vs. PD cohorts. Box plots show quartiles with bands at the median; whiskers indicate 1.5 interquartile range; all observations overlaid as dots. P values are from linear regression analysis. p < 0.05 = *; p < 0.01 = **; p < 0.001 = ***. CR = complete response cohort (n=16); PD = progressive disease cohort (n=10).

[0024] FIG.12 shows UMAP with clustering analysis of individual patient CAR+CD8+T-cells in PD cohort with and without severe ICANS. PBMC’s from the Day 14 post-CART timepoint from the total cohort (n=26) were analyzed via spectral flow cytometry and dimensional reduction. UMAP of individual patient CAR+CD8+T-cells, colored by cluster. Left: Two patients with severe ICANS. Right: Eight patients with no / non-severe ICANS.

[0025] FIGs.13A and 13B show baseline and peak inflammatory markers, largest tumor diameter and absolute CD8+CAR T-cell number in severe ICANS vs. no / non-severe ICANS in CR patients. FIG.13A shows inflammatory markers (LDH, ferritin, CRP) reported as baseline (day of infusion), largest tumor diameter in cm2 prior to CART infusion and absolute # of CAR+ CD8+ Cells. Absolute # CAR+ CD8+ Cells was derived from the %CAR+ CD8+ cells as a percent of live lymphocytes*ALC (cells / ul). FIG.13B shows inflammatory markers (LDH, ferritin, CRP) reported as peak (max value within 30 days post- CART infusion). Box plots show quartiles with bands at the median; whiskers indicate 1.5 interquartile range; all observations overlaid as dots. P values are from linear regression analysis. p < 0.05 = *; p < 0.01 = **; p < 0.001 = ***.

[0026] FIG.14 shows qantity of combined cluster sub-groups in severe and non- severe ICANS in CR patients. PBMCs from the Day 14 post-CAR-T timepoint were analyzed via spectral flow cytometry and Flowsom was used for clustering analysis. Box plots showing combined clusters percentages of clusters 8 + 9, 7+13, and 2+3+4 in patients with severe and no or non-severe ICANS are shown. Box plots show quartiles with bands at the median; whiskers indicate 1.5 interquartile range; all observations overlaid as dots. P values are from linear regression analysis. p < 0.05 = *; p < 0.01 = **; p < 0.001 = ***. DETAILED DESCRIPTION

[0027] Before the present disclosure is described in greater detail, it is to be understood that this disclosure is not limited to particular embodiments described, and as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present disclosure will be limited only by the appended claims.

[0028] Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limit of that range and any other stated or intervening value in that stated range, is encompassed within the disclosure. The upper and lower limits of theseTH Docket No.321502-2150 smaller ranges may independently be included in the smaller ranges and are also encompassed within the disclosure, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the disclosure.

[0029] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. Although any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present disclosure, the preferred methods and materials are now described.

[0030] All publications and patents cited in this specification are herein incorporated by reference as if each individual publication or patent were specifically and individually indicated to be incorporated by reference and are incorporated herein by reference to disclose and describe the methods and / or materials in connection with which the publications are cited. The citation of any publication is for its disclosure prior to the filing date and should not be construed as an admission that the present disclosure is not entitled to antedate such publication by virtue of prior disclosure. Further, the dates of publication provided could be different from the actual publication dates that may need to be independently confirmed.

[0031] As will be apparent to those of skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the present disclosure. Any recited method can be carried out in the order of events recited or in any other order that is logically possible.

[0032] Embodiments of the present disclosure will employ, unless otherwise indicated, techniques of chemistry, biology, and the like, which are within the skill of the art.

[0033] The following examples are put forth so as to provide those of ordinary skill in the art with a complete disclosure and description of how to perform the methods and use the probes disclosed and claimed herein. Efforts have been made to ensure accuracy with respect to numbers (e.g., amounts, temperature, etc.), but some errors and deviations should be accounted for. Unless indicated otherwise, parts are parts by weight, temperature is in °C, and pressure is at or near atmospheric. Standard temperature and pressure are defined as 20 °C and 1 atmosphere.

[0034] Before the embodiments of the present disclosure are described in detail, it is to be understood that, unless otherwise indicated, the present disclosure is not limited to particular materials, reagents, reaction materials, manufacturing processes, or the like, as such can vary. It is also to be understood that the terminology used herein is for purposes ofTH Docket No.321502-2150 describing particular embodiments only, and is not intended to be limiting. It is also possible in the present disclosure that steps can be executed in different sequence where this is logically possible. Definitions

[0035] It must be noted that, as used in the specification and the appended claims, the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise.

[0036] The term “subject” refers to any individual who is the target of administration or treatment. The subject can be a vertebrate, for example, a mammal. Thus, the subject can be a human or veterinary patient. The term “patient” refers to a subject under the treatment of a clinician, e.g., physician.

[0037] The term “treatment” refers to the medical management of a patient with the intent to cure, ameliorate, stabilize, or prevent a disease, pathological condition, or disorder. This term includes active treatment, that is, treatment directed specifically toward the improvement of a disease, pathological condition, or disorder, and also includes causal treatment, that is, treatment directed toward removal of the cause of the associated disease, pathological condition, or disorder. In addition, this term includes palliative treatment, that is, treatment designed for the relief of symptoms rather than the curing of the disease, pathological condition, or disorder; preventative treatment, that is, treatment directed to minimizing or partially or completely inhibiting the development of the associated disease, pathological condition, or disorder; and supportive treatment, that is, treatment employed to supplement another specific therapy directed toward the improvement of the associated disease, pathological condition, or disorder.

[0038] The term “antibody” refers to natural or synthetic antibodies that selectively bind a target antigen. The term includes polyclonal and monoclonal antibodies. In addition to intact immunoglobulin molecules, also included in the term “antibodies” are fragments or polymers of those immunoglobulin molecules, and human or humanized versions of immunoglobulin molecules that selectively bind the target antigen.

[0039] The term “specifically binds”, as used herein, when referring to a polypeptide (including antibodies) or receptor, refers to a binding reaction which is determinative of the presence of the protein or polypeptide or receptor in a heterogeneous population of proteins and other biologics. Thus, under designated conditions (e.g. immunoassay conditions in the case of an antibody), a specified ligand or antibody “specifically binds” to its particular “target” (e.g. an antibody specifically binds to an endothelial antigen) when it does not bind in a significant amount to other proteins present in the sample or to other proteins to which the ligand or antibody may come in contact in an organism. Generally, a first molecule that “specifically binds” a second molecule has an affinity constant (Ka) greater than about 105TH Docket No.321502-2150 M–1(e.g., 106M–1, 107M–1, 108M–1, 109M–1, 1010M–1, 1011M–1, and 1012M–1or more) with that second molecule. Methods for Detecting CAR-T Cell Populations

[0040] Immune effector cells can be obtained from blood collected from a subject using any number of techniques know to the skilled artisan, such as Ficoll™ separation. In some embodiments, the immune effector cells are isolated from peripheral blood lymphocytes by lysing the red blood cells and depleting the monocytes, for example, by centrifugation through a PERCOLL™ gradient or by counterflow centrifugal elutriation. Immune effector cells can be further engineered to express CAR-T cells. A specific subpopulation of CAR-T cells can be further isolated by positive and negative selection techniques. For example, CAR-T cells can be isolated using a combination of antibodies directed to surface markers unique to the positively selected cells, e.g., by incubation with antibody-conjugated beads for a time period sufficient for positive selection of the desired CAR-T cells to positively select the desired immune effector cells. Alternatively, enrichment of the CAR-T cells population can be accomplished by negative selection using a combination of antibodies directed to surface markers unique to the negatively selected cells. For example, cell sorting and / or selection via negative magnetic immunoadherence or flow cytometry that uses a cocktail of monoclonal antibodies directed to cell surface markers present on the cells negatively selected. Methods for Determining Non-Responder Control Subpopulation Percentages

[0041] Biomarkers are crucial in the identification, characterization, and monitoring of diseases. There is a basal level of CAR-T+ cells, so the method for determining non- responder subpopulations is critical to the identification of patients that will need alternative care methods. In addition, the method for determining non-responder subpopulations must account for different subtypes of T-cells. Best practices for the separation of these two groups involve the use of optimal response separation to determine a threshold between high and low percentages of CAR T cells in each population. For a given CAR T product in a subset of patients with similar disease type, a group of responders and non-responders can be analyzed and separated based on the percent prevalence of CAR T cell sub-populations. An optimal response separation cutoff is selected based on the difference between median percent population of each CAR T cell subtype in responders and non-responders. Methods for Treating Non-Responders

[0042] Effective biomarker identification and analysis allows for the early detection of nonresponsive patients of CAR-T cell treatment. Early strategies to intervene for patients that are predicted to be nonresponsive to CAR-T cell treatment may include an immunomodulatory agents and celmods that can act to augment CART function, targeted therapy such as Bruton’s Tyrosine Kinase inhibitors that can augment CART function andTH Docket No.321502-2150 reduce the suppressive tumor microenvironment, and immunotherapy such as bi-specific antibody treatment and checkpoint inhibition. Additionally, traditional chemo-immunotherapy regimens, radiation and alternative targeted therapies that may be more detrimental to CAR T function can be used depending on the sub types identified if CAR-T treatment is predicted to be likely to result in poor outcomes.

[0043] The cancer of the disclosed methods can be any neoplasm or tumor for which radiotherapy is currently used. Alternatively, the cancer can be a neoplasm or tumor that is not sufficiently sensitive to radiotherapy using standard methods. Thus, the cancer can be a sarcoma, lymphoma, leukemia, carcinoma, blastoma, or germ cell tumor. A representative but non-limiting list of cancers that the disclosed compositions can be used to treat include lymphoma, B cell lymphoma, T cell lymphoma, mycosis fungoides, Hodgkin’s Disease, myeloid leukemia, bladder cancer, brain cancer, nervous system cancer, head and neck cancer, squamous cell carcinoma of head and neck, kidney cancer, lung cancers such as small cell lung cancer and non-small cell lung cancer, neuroblastoma / glioblastoma, ovarian cancer, pancreatic cancer, prostate cancer, skin cancer, liver cancer, melanoma, squamous cell carcinomas of the mouth, throat, larynx, and lung, endometrial cancer, cervical cancer, cervical carcinoma, breast cancer, epithelial cancer, renal cancer, genitourinary cancer, pulmonary cancer, esophageal carcinoma, head and neck carcinoma, large bowel cancer, hematopoietic cancers; testicular cancer; colon and rectal cancers, prostatic cancer, and pancreatic cancer.

[0044] In some embodiments, the subject predicted to be nonresponsive to the CART therapy can be treated with a chemotherapeutic agent that would otherwise be contraindicated with CART therapy.

[0045] In some embodiments, the chemotherapeutic agent is a thalidomide immunomodulatory derivatives (IMiDs) (e.g. lenalidomide and pomalidomide) or analog, now known as the Cereblon E3 ligase modulators (CELMoDs). These include CC-122, CC-220 and CC-885. For example, CC-885 induces degradation of the translation termination factor GSPT1, a CRL4CRBN neo-substrate. In addition, CRBN is also a target for the development of proteolysis-targeting chimaera (PROTAC) technology, which relies on linking a drug that binds to a protein of interest to IMiDs. Many CRBN-based PROTACs, including the potent BRD4 protein degrader dBET1, have been developed for the degradation of target proteins in cancer and other human diseases. Despite recent advances in the field, many questions apart from clinical efficacy of IMiDs remain unknown. For example, CRBN is required for the action of IMiDs, but CRBN protein levels do not correlate with intrinsic sensitivity or resistance to IMiDs in MM cell lines, suggesting that other factors play a critical role in regulating the mechanisms underlying sensitivity and / or resistance to IMiDs.TH Docket No.321502-2150

[0046] In some embodiments, the chemotherapeutic agent may be selected from an antimetabolite, such as methotrexate, 6-mercaptopurine, 6-thioguanine, cytarabine, fludarabine, 5-fluorouracil, decarbazine, hydroxyurea, asparaginase, gemcitabine or cladribine.

[0047] In some embodiments, the chemotherapeutic agent may be selected from an alkylating agent, such as mechlorethamine, thioepa, chlorambucil, melphalan, carmustine (BSNU), lomustine (CCNU), cyclophosphamide, busulfan, dibromomannitol, streptozotocin, dacarbazine (DTIC), procarbazine, mitomycin C, cisplatin and other platinum derivatives, such as carboplatin .

[0048] In some embodiments, the chemotherapeutic agent may be selected from an anti-mitotic agent, such as taxanes, for instance docetaxel, and paclitaxel, and vinca alkaloids, for instance vindesine, vincristine, vinblastine, and vinorelbine.

[0049] In some embodiments, the chemotherapeutic agent may be selected from a topoisomerase inhibitor, such as topotecan or irinotecan, or a cytostatic drug, such as etoposide and teniposide.

[0050] In some embodiments, the subject predicted to be nonresponsive to the CART therapy can be treated with an alternative immunotherapy. There are two distinct types of immunotherapy: passive immunotherapy uses components of the immune system to direct targeted cytotoxic activity against cancer cells, without necessarily initiating an immune response in the patient, while active immunotherapy actively triggers an endogenous immune response. Passive strategies include the use of the monoclonal antibodies (mAbs) produced by B cells in response to a specific antigen. The development of hybridoma technology in the 1970s and the identification of tumor-specific antigens permitted the pharmaceutical development of mAbs that could specifically target tumor cells for destruction by the immune system. Thus far, mAbs have been the biggest success story for immunotherapy; the top three best-selling anticancer drugs in 2012 were mAbs. Among them is rituximab (Rituxan, Genentech), which binds to the CD20 protein that is highly expressed on the surface of B cell malignancies such as non-Hodgkin’s lymphoma (NHL). Rituximab is approved by the FDA for the treatment of NHL and chronic lymphocytic leukemia (CLL) in combination with chemotherapy. Another important mAb is trastuzumab (Herceptin; Genentech), which revolutionized the treatment of HER2 (human epidermal growth factor receptor 2)-positive breast cancer by targeting the expression of HER2.

[0051] In some embodiments, the subject predicted to be nonresponsive to the CART therapy can be treated with a checkpoint inhibitor. The two known inhibitory checkpoint pathways involve signaling through the cytotoxic T-lymphocyte antigen-4 (CTLA- 4) and programmed-death 1 (PD-1) receptors. These proteins are members of the CD28-B7 family of cosignaling molecules that play important roles throughout all stages of T cellTH Docket No.321502-2150 function. The PD-1 receptor (also known as CD279) is expressed on the surface of activated T cells. Its ligands, PD-L1 (B7-H1; CD274) and PD-L2 (B7-DC; CD273), are expressed on the surface of APCs such as dendritic cells or macrophages. PD-L1 is the predominant ligand, while PD-L2 has a much more restricted expression pattern. When the ligands bind to PD-1, an inhibitory signal is transmitted into the T cell, which reduces cytokine production and suppresses T-cell proliferation. Checkpoint inhibitors include, but are not limited to antibodies that block PD-1 (Nivolumab (BMS-936558 or MDX1106), CT-011, MK-3475), PD- L1 (MDX-1105 (BMS-936559), MPDL3280A, MSB0010718C), PD-L2 (rHIgM12B7), CTLA-4 (Ipilimumab (MDX-010), Tremelimumab (CP-675,206)), IDO, B7-H3 (MGA271), B7-H4, TIM3, LAG-3 (BMS-986016).

[0052] Human monoclonal antibodies to programmed death 1 (PD-1) and methods for treating cancer using anti-PD-1 antibodies alone or in combination with other immunotherapeutics are described in U.S. Patent No.8,008,449, which is incorporated by reference for these antibodies. Anti-PD-L1 antibodies and uses therefor are described in U.S. Patent No.8,552,154, which is incorporated by reference for these antibodies. Anticancer agent comprising anti-PD-1 antibody or anti-PD-L1 antibody are described in U.S. Patent No.8,617,546, which is incorporated by reference for these antibodies.

[0053] In some embodiments, the PDL1 inhibitor comprises an antibody that specifically binds PDL1, such as BMS-936559 (Bristol-Myers Squibb) or MPDL3280A (Roche). In some embodiments, the PD1 inhibitor comprises an antibody that specifically binds PD1, such as lambrolizumab (Merck), nivolumab (Bristol-Myers Squibb), or MEDI4736 (AstraZeneca). Human monoclonal antibodies to PD-1 and methods for treating cancer using anti-PD-1 antibodies alone or in combination with other immunotherapeutics are described in U.S. Patent No.8,008,449, which is incorporated by reference for these antibodies. Anti-PD-L1 antibodies and uses therefor are described in U.S. Patent No. 8,552,154, which is incorporated by reference for these antibodies. Anticancer agent comprising anti-PD-1 antibody or anti-PD-L1 antibody are described in U.S. Patent No. 8,617,546, which is incorporated by reference for these antibodies.

[0054] In some embodiments, the subject predicted to be nonresponsive to the CART therapy can be treated with a T cell agonist, which can be provided through ligation of tumor necrosis factor receptor family members, including OX40 (CD134) and 4-1BB (CD137). OX40 is of particular interest as treatment with an activating (agonist) anti-OX40 mAb augments T cell differentiation and cytolytic function leading to enhanced anti-tumor immunity against a variety of tumors.

[0055] In some embodiments, such the immunotherapy may be selected from a tyrosine kinase inhibitor, such as imatinib (Glivec, Gleevec STI571) or lapatinib.TH Docket No.321502-2150

[0056] In some embodiments, the immunotherapy may be selected from a growth factor inhibitor, such as an inhibitor of ErbBl (EGFR) (such as an EGFR antibody, e.g. zalutumumab, cetuximab, panitumumab or nimotuzumab or other EGFR inhibitors, such as gefitinib or erlotinib), another inhibitor of ErbB2 (HER2 / neu) (such as a HER2 antibody, e.g. trastuzumab, trastuzumab-DM l or pertuzumab) or an inhibitor of both EGFR and HER2, such as lapatinib).

[0057] In some embodiments, the immunotherapy may be selected from ofatumumab, zanolimumab, daratumumab, ranibizumab, nimotuzumab, panitumumab, hu806, daclizumab (Zenapax), basiliximab (Simulect), infliximab (Remicade), adalimumab (Humira), natalizumab (Tysabri), omalizumab (Xolair), efalizumab (Raptiva), and / or rituximab.

[0058] In some embodiments, the immunotherapy may be an anti-cancer cytokine, chemokine, or combination thereof. Examples of suitable cytokines and growth factors include IFNy, IL-2, IL-4, IL-6, IL-7, IL-10, IL-12, IL-13, IL-15, IL-18, IL-21, IL-23, IL-24, IL-27, IL-28a, IL-28b, IL-29, KGF, IFNa (e.g., INFa2b), IFN , GM-CSF, CD40L, Flt3 ligand, stem cell factor, ancestim, and TNFa. Suitable chemokines may include Glu-Leu-Arg (ELR)- negative chemokines such as IP-10, MCP-3, MIG, and SDF-la from the human CXC and C- C chemokine families. Suitable cytokines include cytokine derivatives, cytokine variants, cytokine fragments, and cytokine fusion proteins.

[0059] In some embodiments, the subject predicted to be nonresponsive to the CART therapy can be treated with a hormonal regulating agent, such as agents useful for anti-androgen and anti-estrogen therapy. Examples of such hormonal regulating agents are tamoxifen, idoxifene, fulvestrant, droloxifene, toremifene, raloxifene, diethylstilbestrol, ethinyl estradiol / estinyl, an antiandrogene (such as flutaminde / eulexin), a progestin (such as such as hydroxyprogesterone caproate, medroxy- progesterone / provera, megestrol acepate / megace), an adrenocorticosteroid (such as hydrocortisone, prednisone), luteinizing hormone-releasing hormone (and analogs thereof and other LHRH agonists such as buserelin and goserelin), an aromatase inhibitor (such as anastrazole / arimidex, aminoglutethimide / cytraden, exemestane) or a hormone inhibitor (such as octreotide / sandostatin).

[0060] In some embodiments, the subject predicted to be nonresponsive to the CART therapy can be treated with a radiotherapy. Radiotherapy may comprise radiation or associated administration of radiopharmaceuticals to a patient is provided. The source of radiation may be either external or internal to the patient being treated (radiation treatment may, for example, be in the form of external beam radiation therapy (EBRT) or brachytherapy (BT)). Radioactive elements that may be used in practicing such methodsTH Docket No.321502-2150 include, e.g., radium, cesium-137, iridium-192, americium-241, gold-198, cobalt-57, copper- 67, technetium-99, iodide-123, iodide-131, and indium-111. Embodiments

[0061] Embodiment 1. A method for predicting clinical outcome of a subject treated with a chimeric antigen receptor (CAR) T-cell (CAR-T) therapy, comprising assaying from a blood sample collected 5 to 30 days post-infusion for the percentage of CD8+CAR+T cells that are PD-1+, wherein an elevated percentage of PD-1+CD8+CAR-T cells compared to non- responder controls is an indication of responsiveness to the CAR-T therapy.

[0062] Embodiment 2. The method of embodiment 1, further comprising assaying the PD-1+CD8+CAR-T cells for TCF1 expression, wherein an elevated percentage of PD- 1+TCF1+CD8+stem-like CAR-T cells is an indication of responsiveness to the CAR-T therapy.

[0063] Embodiment 3. The method of embodiment 1 or 2, further comprising assaying the PD-1+CD8+CAR-T cells for TOX expression, wherein an elevated percentage of PD-1+TOX-CD8+memory-like CAR-T cells is an indication of responsiveness to the CAR- T therapy.

[0064] Embodiment 4. The method of any one of embodiments 1 to 3, further comprising assaying the PD-1+CD8+CAR-T cells for TIM3, wherein an elevated percentage of PD-1+TIM3+CD8+effector-like CAR-T cells is an indication of responsiveness to the CAR- T therapy.

[0065] Embodiment 5. The method of embodiment 4, further comprising assaying the PD-1+TIM3+CD8+effector-like CAR-T cells for Granzyme B (GZMB) and / or Tbet, wherein an elevated percentage of PD-1+TIM3+Tbet+GZMB+effector-like CAR-T cells is an indication of severe Immune effector cell-associated neurotoxicity syndrome (ICANS).

[0066] Embodiment 6. The method of any one of embodiments 1 to 5, wherein the blood sample is collected 10 to 21 post-infusion.

[0067] Embodiment 7. The method of embodiment 6, wherein the blood sample is collected 14 days post-infusion.

[0068] Embodiment 8. A method for treating a subject, comprising (a) administering to the subject a chimeric antigen receptor (CAR) T-cell therapy (CART), (b) collecting a blood sample from the subject 5 to 30 days post-infusion, and (c) detecting in the blood sample the percentage of CD8+PD-1+CAR+T cells compared to non-responder controls.

[0069] Embodiment 9. The method of embodiment 8, further comprising detecting in the blood sample the percentage of PD-1+CD8+TCF1+CAR-T cells.TH Docket No.321502-2150

[0070] Embodiment 10. The method of embodiment 8 or 9, further comprising detecting in the blood sample the percentage of PD-1+TOX-CD8+CAR-T cells.

[0071] Embodiment 11. The method of any one of embodiments 8 to 10, further comprising detecting in the blood sample the percentage of PD-1+TIM3+Tbet+GZMB+CAR-T cells.

[0072] Embodiment 12. The method of any one of embodiments 8 to 11, wherein the percentage of CD8+PD-1+CAR+T cells is elevated compared to non-responder controls, the method further comprising active observation of the subject for cancer progression.

[0073] Embodiment 13. The method of any one of embodiments 8 to 12, wherein the percentage of CD8+PD-1+CAR+T cells is not elevated compared to non-responder controls, the method further comprising treating the subject with a T cell activator, chemotherapy, or immunotherapy.

[0074] Embodiment 14. The method of any one of embodiments 8 to 13, wherein the blood sample is collected 10 to 21 post-infusion.

[0075] Embodiment 15. The method of embodiment 14, wherein the blood sample is collected 14 days post-infusion.

[0076] Embodiment 16. A kit comprising (i) CAR-T cell, (ii) antibodies for detecting the chimeric antigen receptor (CAR) of the CAR-T cells and antibodies for detecting CD8 and PD1 on the CAR-T cells; (iv) fixation and permeabilization buffer for intracellular staining; and (v) instructions containing separation cutoffs based on the difference between median percent population of each CD8+PD-1+CAR+T cell subtype in responders and non- responders.

[0077] Embodiment 17. The kit of embodiment 16, further comprising antibodies for detecting TCF1, Tim3, EOMES, CD45RO, GZMB, Tbet, and TOX.

[0078] Embodiment 18. The kit of embodiment 16 or 17, further comprising antibodies for detecting CD45, CD3, CD4, and CD28.

[0079] Embodiment 19. The kit of any one of embodiments 16 to 18, further comprising a live / dead stain.

[0080] A number of embodiments of the invention have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of the invention. Accordingly, other embodiments are within the scope of the following claims.TH Docket No.321502-2150 EXAMPLES Example 1: Post-infusion PD-1+ CD8+ CAR-T cells identify patients responsive to CD19-CAR-T therapy in non-Hodgkin’s lymphoma

[0081] In this study, we performed high-dimensional flow cytometric analysis of post- infusion CD8+CAR+T cell populations to identify features of patient’s CAR-T cells associated with achieving CR by 6 months and who developed severe ICANS. High- dimensional analysis was performed with spectral flow cytometry, a next generation platform utilizing antibody-fluorochrome conjugates to detect a significantly increased number of surface and intracellular molecules (Nolan JP, et al. Curr Protoc Cytom.2013 Chapter 1:127 21-212713). To account for variabilities in phenotype and functionality between CAR-T cell products with different constructs and co-stimulatory domains, we focused our analysis on commercial CD28-CAR19 products used for B-cell-NHL. We found that the presence of post-infusion PD-1+CD8+CAR-T cells was highly associated with achievement of CR by 6 months. Further analysis identified multiple subtypes of PD-1+CD8+CAR-T cells that correlated with improved clinical outcomes, including PD-1+TCF1+“stem-like” CAR-T cells (Siddiqui I, et al. Immunity.201950(1):195-211 e110; Escobar G, et al. Sci Immunol.2020 5(53); Koh J, et al. Eur J Cancer.2022174:10-20; Connolly KA, et al. Sci Immunol.2021 6(64):eabg7836; Yi L, et al. Front Immunol.202213:907172), and PD-1+TIM3+effector-like CAR-T cells. Additionally, we identified a subset of CD8+CAR+T cells with effector-like function that was increased in patients who achieved a CR and had severe ICANS. Here we identified robust biomarkers of response and toxicity to CD28-CAR-T and highlight the importance of PD-1 positivity in CD8+CAR-T cells post-infusion in achieving CR. Methods Patients

[0082] Patients who received SOC axi-cel or brexu-cel for R / R NHL at the Ohio State University Comprehensive Cancer Center (OSUCCC) and who were consented to the Leukemia Tissue Bank (LTB) protocol were included in this study. Inclusion criteria: Patients with detectable CD19+ disease prior to CAR19 infusion. Exclusion criteria: Patients who had ongoing partial response (PR) which had not resolved to either CR or progressive disease (PD) at the time of final study evaluation. Patients who achieved SD as best response were included in the PD cohort. Patient samples were procured from the OSUCCC LTB after informed consent and approval by the OSU Institution Review Board (IRB) were obtained. Samples

[0083] Patients received CD28-CAR19 from February 2022-March 2023 and had blood samples collected at time of standard of care phlebotomy at or near day 14 post-CAR- T infusion. The median day post-CAR-T of sample collection was 15.5 days for the CR cohort and 16.5 days for PD Cohort. Peripheral blood mononuclear cells (PBMC’s) wereTH Docket No.321502-2150 isolated from fresh whole blood by density gradient centrifugation using Ficoll-Paque and cryopreserved. Healthy donor PBMC’s were purchased from STEMCELL Technologies.

[0084] Clinical data were obtained retrospectively from the electronic medical record under an IRB approved protocol. Treatment response was assessed radiographically according to the Lugano criteria (Cheson BD, et al. J Clin Oncol.201432(27):3059- 3068).Toxicity was evaluated by the ASTCT consensus guidelines criteria for cytokine release syndrome (CRS) and ICANS (Lee DW, et al. Biol Blood Marrow Transplant.2019 25(4):625-638). Cutoffs for lab values being defined as within normal limits(WNL) included: lactate dehydrogenase (LDH) < 190 U / L, ferritin < 322 ng / ml, and C-reactive protein (CRP) < 10 mg / L. Spectral flow cytometry

[0085] The 37-color spectral flow cytometry panel is outlined in Table 1. Post- infusion PBMC samples were thawed and analyzed simultaneously along with healthy donor PBMC’s. Cryopreserved single-cell suspensions collected were thawed and washed with RPMI-1640 (Gibco). LIVE / DEAD fixable blue (Invitrogen) was applied to stain dead cells. Cells were washed twice with FACS buffer and the surface molecule staining antibody cocktail including Fc block was applied for 45 minutes at 4°C. After incubation, cells were washed twice with FACS buffer and the FOXP3 / Transcription factor staining buffer set (eBioscience) was applied overnight. Cells were washed twice in permeabilization buffer, and the intracellular staining antibody cocktail was added. After 2 hours of incubation at room temperature, cells were washed twice with FACS buffer; data was collected using the Aurora (Cytek) 5-laser spectral flow cytometry machine. Table 1: CD8 CAR19 Specific Spectral Flow Panel Marker Fluorochrome Brand Category Number CloneTH Docket No.321502-2150 PEDAZZLE CTLA4 (ICS) 594 BioLegend 369616 BNI3 15-2239-421

[0086] Flow cytometry data was uploaded to web-based software OMIQ. Live CD45+, CD8+, and CAR+cells were gated, and UMAP (Uniform Manifold Approximation and Projection) dimension reduction and FlowSOM clustering analysis was performed. The proper number of clusters was determined using FlowSOM elbow meta-clustering analysis; FlowSOM consensus meta-clustering analysis was performed to cluster cells with unique features (Van Gassen S, et al. Cytometry A.201587(7):636-645). Characteristics of each cluster were evaluated using individual marker expressions in UMAP space and validated using clustered heatmap. For further validation, flow cytometry data was re-evaluated using FlowJo (BD) by creating 2D plots and utilizing concomitant statistical approaches. In order to quantify the amount of CAR+CD8+T cells present at the time of sample collection, live cell lymphocytes were gated followed by CD45+CD3+CD4−CD8+CAR+cells to quantify the percentage of CD8+CAR+T cells as a proportion of lymphocytes. This number was then multiplied by the clinically measured absolute lymphocyte count (ALC) in order to obtain the absolute number of CD8+CAR+T cells per μl of blood. Statistical analyses

[0087] Two-sample t-test was used for the analysis of the continuous variables and Fisher’s exact test was used for the categorical variables. Normality assumption was checked prior to analysis, and majority of the variables follow normal distribution. WilcoxonTH Docket No.321502-2150 rank sum test was used to confirm our findings. The proportion of different cell types identified by flow cytometric analysis was compared using linear regression models that accounted for patient age, gender, and tumor size; the models employed the log2- transformed proportion as the response variable and the t-distribution as the reference distribution. Spearman Correlation was used to analyze correlation between cell types and clinical variables and a multivariate regression model controlling for clinical variables was used to associate cell types with response. Kaplan-Meier analysis was used for survival outcomes, and log-rank test was utilized to evaluate statistical significance. Thresholds for separation of patient cohorts based on cell types were selected based on the optimal response separation between the groups and denoted as “high” or “low”, as was performed in previously published analyses (Good Z, et al. Nat Med.202228(9):1860-1871). Thus, p- values should be interpreted with caution. SAS 9.4 and R were used for all the data analyses. Results Patient characteristics and outcomes with commercial CD28-CAR19

[0088] Twenty-six sequential patients treated with CD28-CAR19 between February 2022 and March 2023 met inclusion criteria and had Day 14 PBMC samples analyzed simultaneously via spectral flow cytometry. Sixteen patients achieved CR by the 6-month timepoint and were included in the CR cohort. Ten patients had progression of disease within the first 6 months post-CAR-T infusion and were included in the PD cohort.

[0089] Patient and disease characteristics were for the most part well balanced between the two cohorts and were similar to those treated in real-world studies of axi-cel (Nastoupil LJ, et al. J Clin Oncol.202038(27):3119-3128; Jacobson CA, et al. J Clin Oncol. 202038(27):3095-3106). Baseline ferritin and CRP were significantly increased in the PD cohort compared to the CR cohort when analyzed as categorical variables. There were no other significant differences in clinical characteristics between the CR and PD cohorts. Toxicity, including CRS and ICANS, was not significantly different between the two cohorts (Table 2). Progression free survival (PFS) and overall survival (OS) for the entire 26 patient cohort (Figure 6) were similar to real-world studies with axi-cel (Nastoupil LJ, et al. J Clin Oncol.202038(27):3119-3128; Jacobson CA, et al. J Clin Oncol.202038(27):3095-3106). Overall, our patient cohort was found to be comparable to the majority of real-world patients treated with CD28-CAR19.TH Docket No.321502-2150 Supplemental Table 2: Toxicity and Clinical Outcomespanel to identify features of post-infusion CD8+CAR+T cells that may correlate with clinical outcomes. We targeted Day 14 samples for the analysis to ensure all patients had reached maximum expansion, as it has been shown that the range of peak expansion for CD28- CAR19 products is 5-14 days (Garcia-Calderon CB, et al. Front Immunol.202314:1152498; Locke FL, et al. Mol Ther.201725(1):285-295).

[0091] We first looked at the quantity of CD8+CAR+T cells (gating strategy shown in Figure 7). Similar to previous reports (Good Z, et al. Nat Med.202228(9):1860-1871), we observed no differences in the quantity of circulating CAR+T cells between CR and PD cohorts. This was measured as the absolute number of CD8+CAR+T cells (Figure 1A) and as the percent of CD3+(Figure 8) and CD8+CAR+T cells in circulation (Figure 1B). However, visualization of cells through contour plots revealed areas of the UMAP in which CD8+CAR+T cell events were more prevalent in the CR vs. PD cohort (Figure 1C). Single cell clustering analysis resulted in 14 clusters which were mapped back to the CD8+CAR+T cell UMAP space (Figure 1D). Clusters 7, 8, 9, 11, 12, and 13 were found to be more abundant in the CR cohort, whereas clusters 2, 3 and 4 were more abundant in PD cohort (Figure 1E). When combined and analyzed via linear regression model, the abundance of clusters 7, 8, 9, 11, 12, and 13 was significantly higher in the CR than the PD cohort, whereas the abundance of clusters 2, 3 and 4 was significantly lower in the CR than the PD cohort (Figure 1F). These results suggest that significant qualitative differences are present within CD8+CAR+T cells between CR and PD cohorts. PD-1+CD8+CAR+T cell clusters are increased in the CR cohort

[0092] We next examined key markers of these differentially abundant clusters in CR vs. PD cohorts. Characteristics of each cluster and individual marker expression were first evaluated by a clustered heatmap (Figure 2A). We first noted that all cell clusters increasedTH Docket No.321502-2150 in the CR group were PD-1+, while clusters increased in the PD group were PD-1-. Clusters 8 and 9, increased in the CR cohort, were PD-1+TCF1+T-bet-, which is consistent with the phenotype of stem-like T cells (Siddiqui I, et al. Immunity.201950(1):195-211 e110; Escobar G, et al. Sci Immunol.20205(53); Koh J, et al. Eur J Cancer.2022174:10-20; Connolly KA, et al. Sci Immunol.20216(64):eabg7836; Yi L, et al. Front Immunol.2022 13:907172). These clusters also had high expression of other stem-like T cell markers such as CD28 and EOMES22-26. Clusters 11 and 12, increased in the CR group, were PD-1+TIM3+, and expressed high levels of effector T cell markers including GZMB and T-bet. Overall, these PD-1+TIM3+T-bet+GZMB+cells had an expression pattern similar to previously described CD8+effector-like transitory T cells (Siddiqui I, et al. Immunity.2019 50(1):195-211 e110; Escobar G, et al. Sci Immunol.20205(53); Koh J, et al. Eur J Cancer. 2022174:10-20; Connolly KA, et al. Sci Immunol.20216(64):eabg7836; Yi L, et al. Front Immunol.202213:907172; Hudson WH, et al. Immunity.201951(6):1043-1058 e1044). Clusters 7 and 13, also increased in the CR cohort, were PD-1+, TCF1low, and TOX- with a diverse expression of EOMES and CD28 and appeared to be in transition from stem-like to effector-like transitory cells. On the other hand, clusters 2, 3 and 4, increased in the PD group, were T-bet+GZMB+, but PD-1-. This is in contrast with the PD-1 positivity present on T-bet+and GZMB+cells found in clusters 11 and 12 which were increased in the CR cohort. Statistical analysis revealed the CR cohort had a significantly increased population of each PD-1+CD8+CAR-T cell sub-group (Figure 2B): PD-1+TCF1+(clusters 8 & 9), PD-1+TCF1lowTOX- (clusters 7 & 13) and PD-1+TIM3+T-bet+GZMB+(clusters 11 & 12). The PD-1- clusters 2, 3 and 4, as shown in Figure 1, were noted to be significantly increased in the PD cohort. Comparison of UMAP dot plots depicting cellular dynamics and marker expression plots overlaid in UMAP space were used to confirm these findings (Figure 2C, 2D). Expression of all markers on all clusters is shown in Figure 9A. Collectively, our data showed that at Day 14 post-CAR-T cell infusion, PD-1+CAR-T cell groups including PD-1+TCF1+stem-like T cells and PD-1+TIM3+effector-like T cells were increased in patients who achieved CR by 6 months. Identification of key CD8+CAR+T cell types that correlate with improved clinical outcomes

[0093] To further delineate the importance of PD-1+CD8+CAR-T cell clusters in patients who achieved CR, we performed a separate analysis of spectral flow data via 2D plotting and correlated this with clinical outcomes (Figures 3, 10). Similar to dimensional reduction, 2D plot analysis again clearly identified a PD-1+TCF1+population of CD8+CAR-T cells that was more prevalent in patients who achieved a CR at 6 months (Figure 3A). A population of PD-1+TOX- EOMES+CD45RO+cells was also found to be increased in the CR cohort (Figure 3B). Additionally, the population of PD-1+TIM3+T-bet+GZMB+Toxloweffector-TH Docket No.321502-2150 like CD8+CAR-T cells was also found to be more abundant in CR patients (Figure 3C). In the PD cohort, a PD-1- T-bet+GZMB+CD45RA+population of cells was noted to be increased (Figure 11). This population of cells appeared to share characteristics of T cell effector memory CD45RA re-expressors (Temras) (Lanzavecchia A, et al. Science.2000 290(5489):92-97; Sallusto F, et al. Annu Rev Immunol.200422:745-763), though PD-1 was notably absent in the majority of Temras in the PD group.

[0094] We next divided patients into cohorts based on high or low percentage of each PD-1+CD8+CAR-T cell population and assessed PFS using Kaplan-Meier analysis. Three populations were analyzed: PD-1+TCF1+, PD-1+TOX- EOMES+CD45RO+and PD-1+TIM3+T-bet+GZMB+CD8+CAR-T cells. We found that patients who had higher percentages of each individual population alone had significantly improved PFS (Figure 3D, 3E, 3F). We also found that the combined abundance of groupings of these cell types was significantly higher in the CR cohort (Figure 3G, 3H) and higher levels of these combinations of cell types correlated to increased PFS, as assessed by Kaplan-Meier analysis (Figure 3G, 3H). To investigate if tumor burden or baseline inflammation correlated with the presence of the PD- 1+, PD-1+TCF1+or PD-1+TIM3+T-bet+GZMB+CD8+CAR-T cells, we performed Spearman Correlation and multivariate regression analysis. We found no direct correlation between cell types and tumor diameter and baseline LDH. In the multivariate model (controlling for LDH, CRP, ferritin, and largest tumor diameter) we found that PD-1+CD8+CAR-T cells (though not other cell types) correlated with both patient response and tumor diameter but not baseline LDH, ferritin or CRP. When controlling for tumor burden, a higher quantity PD-1+ CD8+CAR-T cells correlated with increased chance for CR. Taken together, these results provide a basis for quantifying easily identifiable post-infusion CD8+CAR-T cell types by 2D flow and establish associations with these cell types to improved PFS for patients treated with CD28-CAR19 in NHL. PD-1 expression on post-infusion CD8+CAR-T cells correlates with improved clinical outcomes

[0095] Given PD-1 expression was present on all key clusters and cell types that correlated with improved clinical outcomes, we next analyzed whether PD-1 expression alone correlated with better clinical outcomes. Individual patient PD-1 expression plots revealed increased expression of PD-1 on CD8+CAR+T cells of patients in the CR cohort (Figure 4A). Pre- and post-infusion FDG-PET scans (Figure 4B) revealed complete responses achieved by patients with the presence of high PD-1 expression (Pt#5 and Pt#31). In comparison, PETs revealed progressive disease in patients with low PD-1 expression (Pt#6 and Pt#27). Statistical analysis of PD-1 expression on CD8+CAR+T cells revealed that PD-1+CD8+CAR+T cells were significantly increased in CR vs. PD (Figure 4C). Additionally, patients with a higher percentage of PD-1+CD8+CAR-T cells hadTH Docket No.321502-2150 increased PFS, as assessed by Kaplan-Meier analysis (Figure 4C). Analysis of PD-1 expression as a continuous variable revealed that for each 1% increase in PD-1+expression on CAR+CD8+cells at Day 14, the odds of achieving a CR increased by 5%. A 5% increase in PD-1+CD8+CAR-T cells resulted in a 28% increase in the odds of CR, and a 20% increase resulted in a 260% increase in the odds of achieving a CR. Overall, these analyses reveal that increased PD-1 expression on post-infusion CD8+CAR-T cells at Day 14 correlates with improvement in clinical outcomes. Increased PD-1+CD8+CAR+effector-like cells correlate with severe ICANS in the CR cohort

[0096] We also evaluated toxicity to investigate for factors associated with severe (Grade 3 or higher) ICANS. The rate of any grade ICANS for the total cohort was 50% and the rate of severe ICANS was 23% (Table 2), similar to real-world studies (Nastoupil LJ, et al. J Clin Oncol.202038(27):3119-3128; Jacobson CA, et al. J Clin Oncol.2020 38(27):3095-3106). We then analyzed for features present on CD8+CAR-T cells that may have correlated with severe ICANS. Six patients had severe ICANS while 20 patients had no or non-severe ICANS (Grade 0-2). Of six patients with severe ICANS, four had CR and two had PD. Utilizing individual patient UMAPs, we found that Clusters 11 and 12 were enriched in CR patients who had severe ICANS compared to those without severe ICANS (Figure 5A). These clusters were not enriched in the two PD patients with severe ICANS (Figure 12). We thus continued our analysis with a focus on CR patients and ICANS. Patient and disease characteristics in CR patients were analyzed and no clinical characteristics were found to correlate with the presence of severe ICANS (Table 3). Further analysis of baseline and peak (within 30 days post-CAR-T) inflammatory markers (LDH, ferritin, and CRP) as well as expansion of CAR-T cells at the time of sample collection revealed no correlation with severe ICANS (Figure 13). However, linear regression analysis confirmed that Clusters 11 and 12, which were previously characterized as PD-1+TIM3+T-bet+GZMB+effector-like CD8+CAR-T cells (Figure 2A), were significantly increased in patients with severe ICANS (Figure 5B). Clusters 7 and 13 were significantly increased in patients with no / non-severe ICANS while other clusters did not correlate with ICANS (Figure 14). Subsequently, 2D flow analysis confirmed that PD-1+TIM3+T-bet+GZMB+effector-like CD8+CAR-T cells were increased in the severe ICANS cohort (Figure 5C). With this analysis, we identified a CD8+effector-like CAR-T cell population present at the Day 14 timepoint that correlated with severe ICANS in patients who achieved a CR.TH Docket No.321502-2150 Table 3: ICANS and Patient and Disease CharacteristicsDiscussion

[0097] In this study, we found that post-infusion PD-1+CD8+CAR-T cells were critical for patients to achieve CR by 6 months with CD28-CAR19 for NHL. Deeper analysis identified subtypes of PD-1+CD8+CAR-T cells that correlated with improved clinical outcomes, including PD-1+TCF1+stem-like CAR-T cells and PD-1+TIM3+effector-like CAR-TTH Docket No.321502-2150 cells. Furthermore, we identified a subset of CD8+CAR+T cells with effector-like function that was increased in the CR cohort patients who had severe ICANS.

[0098] PD-1+TCF1+stem-like T cells are characterized by high proliferative capacity and the capacity for self-renewal. In models of chronic infection and cancer, they are responsible for providing a pool of functional CD8+T cells that mediate disease control and with immune checkpoint inhibitor (ICI) therapy the presence and frequency of stem-like T cells correlates with improved clinical outcomes (Siddiqui I, et al. Immunity.201950(1):195- 211 e110; Escobar G, et al. Sci Immunol.20205(53); Koh J, et al. Eur J Cancer.2022 174:10-20; Connolly KA, et al. Sci Immunol.20216(64):eabg7836; Yi L, et al. Front Immunol.202213:907172). To date, the presence of PD-1+TCF1+stem-like CD8+CAR-T cells and their correlation to CAR-T response has not been described. Here, we clearly show that a higher frequency of stem-like CD8+CAR-T cells correlated with better clinical outcomes with CD28-CAR19 for NHL. We also identified a PD-1+TIM3+GZMB+T-bet+Toxlowpopulation of effector-like CD8+CAR-T cells which correlated with improved outcomes. These effector-like CD8+cells, as progeny of stem-like T cells, have been found to be highly proliferative and also mediate disease control (Im SJ, et al. Nature.2016537(7620):417- 421; Utzschneider DT, et al. Immunity.201645(2):415-427; Wu T, et al. Sci Immunol.2016 1(6)).

[0099] Our study also highlights the importance of PD-1 expression on CD8+CAR+T cells post-infusion. PD-1 is often described as a marker of T-cell exhaustion, however this is only when combined with expression of other co-inhibitory receptors (ex. TIGIT, CTLA4, TIM3). PD-1 first and foremost is a marker of T-cell activation (Sharpe AH, et al. Nat Rev Immunol.201818(3):153-167). When antigen specific T-cells encounter antigen and are adequately activated, PD-1 is upregulated (Agata Y, et al. Int Immunol.19968(5):765-772; Chikuma S, et al. J Immunol.2009182(11):6682-6689; Youngblood B, et al. Immunity.2011 35(3):400-412). Thus, one might expect PD-1 upregulation to be ubiquitous on CAR-T cells post-infusion, given the abundant expression of CD19 on B-cells in circulation and lymphoma cells. However, we, along with others looking at Day +7, have shown negative, low and high PD-1 expression on CAR-T cells post-infusion (Garcia-Calderon CB, et al. Front Immunol.202314:1152498; Good Z, et al. Nat Med.202228(9):1860-1871). Poor PD- 1 upregulation by Day 14 may denote sub-optimal activation caused by intrinsic T-cell dysfunction or other influences (i.e. systemic or tumor related immunosuppression). Here we found that neither tumor burden nor LDH correlated to less PD-1+expression and when controlling for LDH or tumor burden, PD-1+expression on CD8+CAR+T cells still associated with improved response. This suggests that the lack of PD1+upregulation may not be effected by systemic inflammation or tumor burden but may be a T-cell intrinsic phenomenon directly related to a patients apheresis product or final CAR-T infusion product.TH Docket No.321502-2150

[0100] Furthermore, we found that higher PD-1 expression on post-infusion CD8+CAR-T cells at Day 14 correlated with improved longer-term outcomes. Prior studies have described the role of PD-1 in protecting T-cell longevity, proliferation, and optimal memory formation in stem-like T cell models of cancer, chronic infection and ICI therapy ((Siddiqui I, et al. Immunity.201950(1):195-211 e110; Escobar G, et al. Sci Immunol.2020 5(53); Koh J, et al. Eur J Cancer.2022174:10-20; Connolly KA, et al. Sci Immunol.2021 6(64):eabg7836; Yi L, et al. Front Immunol.202213:907172)). A knockout of PD-1 on CD8+ T-cells can lead to increased expansion, but also more rapid development of T-cell dysfunction and exhaustion, and loss of memory formation (Pauken KE, et al. Cell Rep. 202031(13):107827). Therefore, it may be that low levels of PD-1 post-infusion result in a reduced ability for CAR-T cells to maintain and mediate ongoing response; further studies are ongoing to investigate this.

[0101] Previous studies have shown that increased tumor burden, expansion, and peak inflammation, as well as lower levels CAR+Tregs post-infusion correlate with more severe ICANS (Neelapu SS, et al. N Engl J Med.2017377(26):2531-2544; Good Z, et al. Nat Med.202228(9):1860-1871; Santomasso BD, et al. Cancer Discov.20188(8):958-971; Strati P, et al. Blood Adv.20204(16):3943-3951). Here we found that a subset of post- infusion CD8+CAR+T cells with the effector-like phenotype (PD-1+TIM3+GZMB+T-bet+) was increased in patients in the CR cohort who had severe ICANS, suggesting that these effector-like CD8+CAR-T cells may potentially play a role in the development of severe ICANS. Of note, this specific population of effector-like T cells was not prevalent in PD patients, likely because the majority of effector-like cells in PD patients lacked both PD-1 and TIM3. Further analysis with larger numbers of PD patients with severe ICANS and further studies investigating the interplay between CAR+Tregs, CAR-T expansion, inflammation and effector-like CD8+CAR-T cells are required.

[0102] Some limitations of our study include it’s correlative, retrospective, and descriptive nature. In regards to the KM curve analysis for PFS, given there is no known biologically relevant value for the newly described cell types we had no pre-determined way to specify cutoffs for each value. Thus, cutoffs were determined post hoc, and p values and PFS based on these values should be interpreted with caution. We also did not report on CD4+CAR-T cell analyses here. Though there were some differences noted, our panel was focused on CD8+CAR-T cell phenotype and function and further studies with a focus on CD4+CAR-T cells are under way.

[0103] With this study, we highlight the importance of PD-1 positivity in CD8+CAR-T cells post-infusion, describe specific populations of post-infusion CAR-T cells, including stem-like and effector-like CD8+CAR-T cells, and investigate how CD8+CAR-T cell phenotype and function may play a role in outcomes to CAR-T cell therapy. These resultsTH Docket No.321502-2150 allow us to identify robust biomarkers of clinical response and toxicity to CD28-CAR19, and help further elucidate patterns of CAR-T cell population dynamics in the post-CAR-T infusion setting.

[0104] Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by one of skill in the art to which the disclosed invention belongs. Publications cited herein and the materials for which they are cited are specifically incorporated by reference.

[0105] Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific embodiments of the invention described herein. Such equivalents are intended to be encompassed by the following claims.

Claims

TH Docket No.321502-2150 CLAIMS 1. A method for predicting clinical outcome of a subject treated with a chimeric antigen receptor (CAR) T-cell (CAR-T) therapy, comprising assaying from a blood sample collected 5 to 30 days post-infusion for the percentage of CD8+CAR+T cells that are PD-1+, wherein an elevated percentage of PD-1+CD8+CAR-T cells compared to non-responder controls is an indication of responsiveness to the CAR-T therapy.

2. The method of claim 1, further comprising assaying the PD-1+CD8+CAR-T cells for TCF1 expression, wherein an elevated percentage of PD-1+TCF1+CD8+stem-like CAR-T cells is an indication of responsiveness to the CAR-T therapy.

3. The method of claim 1, further comprising assaying the PD-1+CD8+CAR-T cells for TOX expression, wherein an elevated percentage of PD-1+TOX-CD8+memory-like CAR-T cells is an indication of responsiveness to the CAR-T therapy.

4. The method of claim 1, further comprising assaying the PD-1+CD8+CAR-T cells for TIM3, wherein an elevated percentage of PD-1+TIM3+CD8+effector-like CAR-T cells is an indication of responsiveness to the CAR-T therapy.

5. The method of claim 4, further comprising assaying the PD-1+TIM3+CD8+effector-like CAR-T cells for Granzyme B (GZMB) and / or Tbet, wherein an elevated percentage of PD-1+TIM3+Tbet+GZMB+effector-like CAR-T cells is an indication of severe Immune effector cell-associated neurotoxicity syndrome (ICANS).

6. The method of claim 1, wherein the blood sample is collected 10 to 21 post-infusion.

7. The method of claim 6, wherein the blood sample is collected 14 days post-infusion.

8. A method for treating a subject, comprising (a) administering to the subject a chimeric antigen receptor (CAR) T-cell therapy (CART), (b) collecting a blood sample from the subject 5 to 30 days post-infusion, and (c) detecting in the blood sample the percentage of CD8+PD-1+CAR+T cells compared to non-responder controls.

9. The method of claim 8, further comprising detecting in the blood sample the percentage of PD-1+CD8+TCF1+CAR-T cells.

10. The method of claim 8, further comprising detecting in the blood sample the percentage of PD-1+TOX-CD8+CAR-T cells.

11. The method of claim 8, further comprising detecting in the blood sample the percentage of PD-1+TIM3+Tbet+GZMB+CAR-T cells.

12. The method of claim 8, wherein the percentage of CD8+PD-1+CAR+T cells is elevated compared to non-responder controls, the method further comprising active observation of the subject for cancer progression.TH Docket No.321502-2150 13. The method of claim 8, wherein the percentage of CD8+PD-1+CAR+T cells is not elevated compared to non-responder controls, the method further comprising treating the subject with a T cell activator, chemotherapy, or immunotherapy.

14. The method of claim 8, wherein the blood sample is collected 10 to 21 post-infusion.

15. The method of claim 14, wherein the blood sample is collected 14 days post-infusion.

16. A kit comprising (i) CAR-T cell, (ii) antibodies for detecting the chimeric antigen receptor (CAR) of the CAR-T cells and antibodies for detecting CD8 and PD1 on the CAR-T cells; (iv) fixation and permeabilization buffer for intracellular staining; and (v) instructions containing separation cutoffs based on the difference between median percent population of each CD8+PD-1+CAR+T cell subtype in responders and non- responders.

17. The kit of claim 16, further comprising antibodies for detecting TCF1, Tim3, EOMES, CD45RO, GZMB, Tbet, and TOX.

18. The kit of claim 16, further comprising antibodies for detecting CD45, CD3, CD4, and CD28.

19. The kit of claim 16, further comprising a live / dead stain.

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