Assessing NAD metabolism in engineering of therapeutic lymphocyte manufacture

Abstract

The disclosure describes methods of assessing NAD biosynthesis as a biochemical hub for the TCR affinity-dependent metabolome. Through this central anabolic role, NAD biosynthesis governs a quiescence exit checkpoint, pacing proliferation. Normalizing cellular NAD(P)H likewise normalizes proliferation across affinities and enhancing NAD biosynthesis permits expansion of lower affinity clones. Furthermore, single-cell differences in NAD(P)H predict division potential for both T- and B-cells, prior to the first division, unmixing proliferative heterogeneity. This supports a broader paradigm in which complex signaling networks converge on metabolic pathways to control single-cell behavior.

Description

[0001] DESCRIPTION ASSESSING NAD METABOLISM IN ENGINEERING OF THERAPEUTIC LYMPHOCYTE MANUFACTURE PRIORITY CLAIM This application claims benefit of priority to U.S. Provisional Application Serial No. 63 / 582,577, filed September 14, 2023, the entire contents of which are hereby incorporated by reference. GOVERNMENT SUPPORT CLAUSE This invention was made with government support under Grant No. GM138085 awarded by the National Institutes of Health. The government has certain rights in the invention. BACKGROUND I. FIELD The present disclosure relates generally to the fields of molecular biology, oncology, medicine and immunology. More specifically, it provides improved methods for selecting and engineering lymphocytes in the engineering of chimeric antigen receptor (CAR) T cell therapeutics and monoclonal antibodies and their use in treating solid cancers. II. RELATED ART Cancer is the second leading cause of death in the world, accounting for one in six deaths. Current treatment options, including surgery, chemotherapy, radiotherapy and target therapy, can lead to complete remission. However, most of patients still did not respond or experienced tumor progression after therapy, calling for new therapeutic strategies in cancer treatment. Adoptive chimeric antigen receptor (CAR) T cell therapy has shown durable complete remissions in leukemia and lymphoma, thus revolutionizing clinical guidelines in hematologic malignancies. Protective adaptive immune responses require the selective expansion of high affinity antigen-specific lymphocyte clones. The affinity of the antigen receptor (TCR or BCR) to cognate antigen determines the magnitude of the primary response as well as the rate at which naive lymphocytes exit quiescence (Chapman et al., 2019). During this exit from quiescence,

[0002] 14894-1903-2290, v. 1 naive lymphocytes reprogram their transcriptome and proteome, while at the same time remodeling cellular metabolism to meet the demands of rapid proliferation (Geltink et al., 2018; Heinzel et al., 2018; Allison et al., 2016; Conley et al., 2020; Gallagher et al., 2021; Gett et al., 2003; Man et al., 2013; Price et al., 2005; Richard et al., 2018). Multiple signaling and transcriptional effectors sensitive to activating signal strength are known to converge on metabolic reprogramming (e.g., Myc, mTOR, IRF4) (Gett et al., 2003; Richard et al., 2018; Solouki et al., 2020; Finlay et al., 2012; Guy et al., 2013; Heinzel et al., 2017; Hukelmann et al., 2016; Marchingo et al., 2020; Pollizzi et al., 2015; Pollizzi et al., 2016; Preston et al., 2015; Ron-Harel et al., 2016; Tan et al., 2017; Verbist et al., 2016; Wang et al., 2011; Yang et al., 2011; Yang et al., 2013; Sinclair et al., 2019; Sinclair et al., 2013; Nakaya et al., 2014; Rathmell et al., 2003; Chapman et al., 1983). Despite this, it remains unclear whether components of the resulting metabolome are similarly sensitive to affinity and work in concert with canonical signaling and gene networks to coordinate the rapid changes in cell cycle biology controlled by antigen receptors. The ability to identify lymphocytes and CAR T cells that will provide the most robust responses would therefore be of great value in the more efficient implementation of this powerful therapeutic tool.

[0003] 24894-1903-2290, v. 1 SUMMARY The present disclosure provides a method of selecting a lymphocyte from a population of lymphocytes comprising (a) providing a population of lymphocytes; (b) assessing NAD levels or biosynthesis in said population of lymphocytes; and (c) selecting one or more lymphocytes based on higher than populational average NAD(P)H. Also provided is a method of selecting a lymphocyte from a population of lymphocytes comprising (a) providing a population of lymphocytes; (b) assessing NAD levels or biosynthesis in said population of lymphocytes; and (c) selecting one or more lymphocytes based on lower than populational average NAD(P)H. The higher or lower than populational average may be the top or bottom quartile, respectively. Step (b) may comprise assessing NAD(P)H autofluorescence. Step (c) may comprise flow cytometry cell sorting. The population of lymphocytes may be a T lymphocyte population, such as a chimeric antigen receptor (CAR) T lymphocyte population. The one or more selected lymphocytes may be a T lymphocyte and said method further comprises engineering of the one or more selected lymphocytes to express a chimeric antigen receptor (CAR). The population of lymphocytes may be a B lymphocyte population. The one or more selected lymphocytes may be cultured and expanded following step (c). The method may further comprise obtaining the population of lymphocytes from a subject prior to step (a). The lymphocyte population may be a mammalian lymphocyte population, such as a human lymphocyte population. Steps (a)-(c) may be performed in about 18-24 hours, such as in about 18 hours, about 20 hours, or about 24 hours. Steps (b)-(c) may be performed a second time on the selected one more lymphocytes of step (c). In another embodiment, there is provided a lymphocyte or lymphocytes prepared according to the methods described herein. In yet another embodiment, there is provided a lymphocyte or lymphocytes exhibiting a higher or lower than populational average of NAD levels or biosynthesis, wherein the reference population is a lymphocyte population from which the lymphocyte or lymphocytes is / are obtained, wherein the higher or lower than populational average is the top or bottom quartile, respectively. The the lymphocyte or lymphocytes may be T lymphocyte(s), CAR T lymphocyte(s) or B lymphocyte(s). In a further embodiment, there is a provided a method of treating cancer, autoimmunity or fibrosis comprising administering to a subject in need thereof a T lymphocyte, a chimeric antigen receptor (CAR) T lymphocyte, or an antibody produced by a B lymphocyte, wherein

[0004] 34894-1903-2290, v. 1 (a) the T lymphocyte, CAR T lymphocyte or B lymphocyte is produced according to the method of any one of claims 1-15; and / or (b) (i) the T lymphocyte, CAR T lymphocyte or B lymphocyte exhibits a higher than populational average of NAD levels or biosynthesis, wherein the reference population is a lymphocyte population from which the lymphocyte or lymphocytes is / are obtained, or (ii) the T lymphocyte, CAR T lymphocyte or B lymphocyte exhibits a lower than populational average of NAD levels or biosynthesis, wherein the reference population is a lymphocyte population from which the lymphocyte or lymphocytes is / are obtained, such as wherein the higher or lower than populational average is the top or bottom quartile, respectively. In still a further embodiment, there is provided method of treating an infectious disease comprising administering to a subject in need thereof an antibody produced by a B lymphocyte, wherein the B lymphocyte (a) (i) exhibits a higher than populational average of NAD levels or biosynthesis, wherein the reference population is a lymphocyte population from which the lymphocyte or lymphocytes is / are obtained, or (ii) exhibits a lower than populational average of NAD levels or biosynthesis, wherein the reference population is a lymphocyte population from which the lymphocyte or lymphocytes is / are obtained, wherein the higher or lower than populational average is the top or bottom quartile, respectively.; and / or (b) is produced according to a method described herein. The use of the word “a” or “an” when used in conjunction with the term “comprising” in the claims and / or the specification may mean “one,” but it is also consistent with the meaning of “one or more,” “at least one,” and “one or more than one.” The word “about” means plus or minus 5% of the stated number. It is contemplated that any method or composition described herein can be implemented with respect to any other method or composition described herein. Other objects, features and advantages of the present disclosure will become apparent from the following detailed description. It should be understood, however, that the detailed description and the specific examples, while indicating specific embodiments of the disclosure, are given by way of illustration only, since various changes and modifications within the spirit and scope of the disclosure will become apparent to those skilled in the art from this detailed description.

[0005] 44894-1903-2290, v. 1 BRIEF DESCRIPTION OF THE DRAWINGS The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee. The following drawings form part of the present specification and are included to further demonstrate certain aspects of the present disclosure. The disclosure may be better understood by reference to one or more of these drawings in combination with the detailed description of specific embodiments presented herein. FIGS. 1A-M: Identification of NAD biosynthesis as a core component of an affinity-dependent metabolome. (FIG.1A) Schematic of high (N4) and low (G4) affinity OT- I T cell ligand system. (FIG. 1B) OT-I T cellS were stimulated with 2µg / mL of N4 or G4 peptide and 2µg / mL of plate bound anti-CD28 antibody and Seahorse was performed 24 hours post-activation. (FIG.1C) OT-I T-cells were stimulated with 2µg / mL of N4 or G4 peptide and 2µg / mL of plate bound anti-CD28 antibody in the 10mM glucose or 0.03mM glucose media with dialyzed serum. Following 24 hours, the frequency of cells in the cell cycle (Ki67+) and (FIG. 1D) Myc gMFI of G1 cells was evaluated. OT-I T-cells were stimulated for 24 hours with 1µg / mL of either G4, T4, Q4, N4 and analyzed by LC-MS. (FIG.1E) PCA plot generated from metabolite abundance. (FIG. 1F) Heatmap of named peaks plotted as log2-fold change above G4, ranked based on the degree of linearity between log transformed metabolite abundance and log transformed peptide affinity, using affinity values generated by Daniels et al. Next to the heatmap is a table of top 15 most affinity-sensitive compounds identified, listing calculated slope and R2. (FIG. 1G) Fit analysis of all metabolites. R2 and p-value for significance of non-zero slope are plotted. (FIG. 1H) Cellular NAD quantification by cycling assay of OT-I T cells stimulated with N4 or G4 peptide 24 hours post-activation. (FIG. 1I) Schematic of NAD biosynthesis pathways. (FIG.1J) Peptide stimulated OT-I were treated with 100 nM FK866 K) in the presence of either Trp, NA, or NR 24 hours-post activation. (FIG. 1K) NAD(P)H autofluorescence was measured by flow cytometry in CD69+ OT-I T-cells, 24 hours post N4 or G4 peptide stimulation. T cells were activated with titrated amounts of plate bound anti-CD3e antibody, in the presence or absence of anti-CD28 antibody. After 24 hours of stimulation, (FIG. 1L) Nampt transcript was analyzed by qPCR (normalized to Pol2ra). (FIG.1M) OT-I T cells were stimulated for 24 hours with 1µg / mL of either N4 or G4 peptides. Flow cytometry was performed, analyzing NAD(P)H autofluorescence and CD69. (FIGS.1B- D, J-M) Representative data are shown from experiments that were repeated at least 3 times,

[0006] 54894-1903-2290, v. 1 with each data point plotted as the mean of triplicate wells with error bars representing the standard deviation (SD). FIGS.2A-L: Cellular NAD levels pace cell cycle kinetics to control affinity-driven T-cell expansion dynamics. (FIG.2A) CD8+ T-cells from Namptfl / fl x CD8a-cre x OT-I mice or Cre negative controls were transferred into CD45.1 recipients. Recipient mice were then infected with Lm-Ova and the relative number of recoverable transferred cells was quantified at day 7 post-infection (Students T test). Results from 2 independent experiments are shown. WT or Nampt Tg x CD8a-Cre mice were infected with Lm-Ova. Spleens were harvested at day 7 post-infection. (FIG. 2B) the gMFI of SIINFEKL-H2-Kb tetramer was quantified by flow cytometry and then normalized to TCRb gMFI and (FIG.2C) The number of cells stained with SIINFEKL-H2-Kb tetramer were quantified. Statistical significance was determined using a Student’s T test. Results from 3 independent experiments are shown. The mean of WT conditions was determined in each independent experiment (Student’s T test). (FIG. 2D) Schematic of experimental design for FIGS.2E-I. CD8 T-cells were activated and treated with 100 nM FK866 or vehicle control for 24 or 48 hours from the indicated time points. Cells were analyzed at the end of each treatment window for (FIG.2E cell number and proliferation after 48-hour treatment windows and (FIG. 2F) cell cycle entry after 24-hour treatment windows. CD8 T-cells were activated and treated with 100 nM FK866 or vehicle control for 24 hours from either day 0-1 or 3-4. Following a day of treatment, (FIG. 2G) NAD(P)H FLIM was performed to quantify NAD(P)H fluorescence lifetime in the mitochondria and cytoplasmic / nuclear compartments (plotted data is relative lifetime in FK866 versus vehicle treated cells). Data are quantified as an average of 3 separate experiments. CD8 T-cells were activated and treated with 100 nM FK866 or vehicle control for 24 hours from either day 0-1 or 1-2. Following a day of treatment, SeaHorse analysis was performed and (FIG. 2H) basal ECAR and OCR were measured. Multiple comparisons T test was performed using the Holm- Sidak correction. (FIG.2I) Schematic of experimental design for J-L. OT-I T-cells were labeled with CTY and stimulated with 2 µg / mL of N4 or G4 peptide and 2 µg / mL of anti-CD28 antibody. Cells were treated at the time of activation with 100 nM FK866 + / - NR at the indicated concentration. Flow cytometry was performed at the indicated time points post- activation to quantify (FIG. 2J) the number of KI67+ cells and (FIG. 2K) Myc gMFI in G1 cells. (FIG. 2L) Seahorse mitochondrial stress analysis was performed 24 hours post- stimulation WT CD8+ T treated with 100nM FK866 and NR at the indicated concentrations. (FIGS.2E-F, J-L) Representative data are shown from experiments that were repeated at least

[0007] 64894-1903-2290, v. 1 3 times, with each data point plotted as the mean of triplicate wells with error bars representing the standard deviation (SD). FIGS.3A-N: NAD biosynthesis governs a quiescence exit checkpoint in activated CD8 T-cells through its control of central carbon metabolism. (FIG. 3A) Schematic of “delayed NAD rescue” assay. (FIG. 3B) OT-I T-cells were stimulated with N4 peptide and 2µg / mL of plate bound anti-CD28 antibody and were treated for 24 hours with 100nM FK866 and were then acutely supplemented with 100µM NR (hereafter referred to as “delayed NAD rescue assay”). Following NR treatment, flow cytometry was performed to evaluate the frequency of Ki67+ cells at the indicated time points. The delayed NAD rescue assay was performed on OT-I T-cells stimulated with either N4 or G4 peptide, supplementing with either 0.01 µM or 100 µM NR at 24 hours post-activation. Following NR treatment, flow cytometry was performed at the indicated time points to evaluate (FIG.3B and FIG.3C) the frequency of KI67+ cells and (FIG. 3D) Myc gMFI. (FIG. 3E) Representative plots of Myc protein expression are shown. (FIG. 3F) OT-I T cells were activated in the presence of FK866. After 24 hours, cells were re-plated in SeaHorse assay plates. SeaHorse analysis was performed to measure ECAR and OCR and NR released into the wells of the assay plate at 36 min during the assay. Untargeted LC-MS was performed on delayed NAD rescue assay. LC-MS was performed to quantify relative metabolite abundance pre and post NR supplementation (30, 60, 240 minutes post NR). Peak areas were normalized to an internal standard. (FIG.3G) Percent of detected metabolites from Clusters 1 and 2 as defined in FIG. 1F that were sensitive to FK866 treatment and rescued with NR at any analysis time point. Significance in either comparison was determined with multiple comparisons with adjusted p<0.05. (FIG. 3H) Schematic of glycolysis shown above graphs plotting the abundance of the bolded metabolites during the delayed NAD rescue assay. (FIG. 3I) Schematic of delayed NAD rescue assay in limiting glucose conditions. OT-I T cells were activated in either control media or media containing 0.03 mM glucose and subjected to the delayed NAD rescue assay. After 24 hours, cultures were supplemented with NR and limiting glucose cultures were supplemented with 10 mM glucose. Flow cytometry was performed at the indicated time points post-NR supplementation and (FIG. 3J) cell cycle entry and (FIG. 3K) Myc gMFI were quantified. Dotted line marked at vehicle control levels at the time of NR addition. (FIG. 3L) Schematic of delayed NAD rescue with drug pre-treatment. OT-I T- were subjected to the delayed NAD rescue assay and were treated with the indicated inhibitors 10 minutes prior to NR supplementation. Flow cytometry was performed at the indicated time points post-NR supplementation and (FIG. 3M) the frequency of KI67+ cells and (FIG. 3N) Myc gMFI were

[0008] 74894-1903-2290, v. 1 quantified. (FIGS. 3B-F, J, K, M, N) Representative data are shown from experiments that were repeated at least 2 times, with each data point plotted as the mean of triplicate wells with error bars representing the standard deviation (SD). FIGS. 4A-J: Single-cell differences in NAD(P)H underly heterogeneity in lymphocyte proliferative responses. OT-I T-cells were stimulated with peptide for 24hrs and then CD8+CD69+ cells were sorted by NAD(P)H autofluorescence. (FIG. 4A) Schematic of sort scheme and example gating strategy. (FIG.4B) Basal ECAR and OCR of NAD(P)H high and low cells one day post sort. (FIG.4C) N4 stimulated OT-I T-cells were sorted by quartiles of NAD(P)H autofluorescence and evaluated for cell cycle 12 hours post-sort or (FIG. 4D) evaluated for proliferative capacity by CTY dilution 24 hours post-sort. WT CD8 T-cells were stimulated with 5 µg / mL of plate bound anti-CD3e antibody and 2 µg / mL anti-CD28 antibody and sorted by NAD(P)H autofluorescence at ~20 hours post stimulation and subsequently cultured. 3 days post-sort, cells were restimulated with PMA / ionomycin for 4.5 hours and stained for intracellular cytokines. (FIG. 4E) Representative FACs plots. (FIG. 4F) Representative FACs plots showing proliferation (CTY) and IFNg production. (FIGS. 4G-H) CD45.1 and CD45.2 OT-I T-cells were activated with either N4 or T4 peptide, respectively. After 24 hours, cells were mixed and CD8+CD69+ cells were sorted by NAD(P)H autofluorescence, using the same gate to capture both CD45.1 and CD45.2 cells to normalize NAD(P)H levels between cultures. Proliferation was then assessed 24 hours post-sort. WT CD4 T-cells or B cells were stimulated with anti-CD3e and anti-CD28 plate bound antibodies or LPS respectively. Cells were sorted ~20 hours post stimulation based on NAD(P)H autofluorescence and placed back in culture. Proliferation was calculated by flow cytometry (Cell Trace Yellow) of (FIG.4I) CD4 T-cells and (FIG.4J) B cells plotted at the indicated time points. Representative plots are shown. Representative data are shown from experiments that were repeated at least 3 times, data points in line graphs are plotted as the mean of duplicate or triplicate wells with error bars for each plot representing the standard deviation (SD). FIGS. 5A-C: NAD(P)H low sorted cells exhibit enhanced durability and killing capacity. (FIG. 5A) 45.1 OT-I T cells were stimulated with N4 peptide for 24 hours and then sorted by NAD(P)H. Cells were adoptively transferred to Lm-Ova infected, congenically marked recipients on day 1 post-infection. At days 7 and 35, the number of transferred splenic OT-I T cells were quantified. Human T cells were activated for 24 hours and then sorted into the top (NADH high) and bottom (NADH low) 20% cells based on by NAD(P)H autofluorescence. Sorted cells were then transduced with HA.28z CAR containing virus the following day. (FIG. 5B) Cell numbers were quantified through the the initial expansion and

[0009] 84894-1903-2290, v. 1 then after re-challenge with 143b osteosarcoma target cells at a 1:1 effector:target ratio. (FIG. 5C) At day 15 post-transduction, CAR T cells were challenged with 143b osteosarcoma target cells at the indicated effector:target (E:T) ratios. Killing was quantified following 24 hours of co-culture. FIGS. 6A-D: NAD(P)H autofluorescence identifies antigen-specific, high affinity B cells following immunization. CD57.B6 / J mice were immunized with PR8 HA mRNA- LNP vaccine. After 12 days, animals were euthanized and draining lymphnodes were harvested and immediately analyzed by flow cytometry. (FIG. 6A) Quantification of the frequency of HA-specific B cells using a recombinant HA-tetramer probe in either total B cells, B cells in the bottom 90% of NAD(P)H autofluorescent cells, or B cells in the top 2% of NAD(P)H autofluorescent cells. (FIG. 6B) Representative flow cytometry plots showing the average frequency of HA-specific B cells in each population, gated on CD19+cells. (FIG. 6C) Quantification of B cell affinity as measured by the mean fluorescent intensity (MFI) of HA- tetramer probe in HA-specific B cells amongst either total B cells, B cells in the bottom 90% of NAD(P)H autofluorescent cells, or B cells in the top 2% of NAD(P)H autofluorescent cells. (FIG.6D) Representative flow cytometry histograms showing HA-tetramer probe binding for each population, gated on HA-tetramer probe+cells FIGS. S1A-I: OT-I T cell were stimulated with 2µg / mL of N4 or G4 peptide and 2µg / mL of plate bound anti-CD28 antibody. (FIG. S1A) percent KI-67+, FIG. S1B) Proliferation (Cell Trace Yellow dilution), FIG. S1C) Representative histograms of total Myc protein are shown FIG. S1D) Percent Myc+ and FIG. S1E) gMFI of Myc gated on G1 cells (KI-67+, 2N DAPI) were measured by flow cytometry at the indicated times. FIG. S1F) Naive OT-I T-cells were plated in a SeaHorse assay plate and delivered N4 or G4 peptide stimulation acutely during the assay. FIG. S1G) OT-I T-cells stimulated with 2µg / mL of N4 or G4 peptide with 2µg / mL of plate bound CD28. Percent CD69 was measured at the indicated times. OT-I T-cells were stimulated with 2µg / mL of N4 and 2µg / mL of plate bound anti-CD28 antibody in dialyzed serum media with glucose levels as indicated. After 24 hours, FIG. S1H) the percent KI67 and (FIG. S1I) Myc gMFI of G1 cells were quantified. FIGS. S2A-H: Cellular NAD quantification by cycling assay. (FIG. S2A) WT CD8 T-cells stimulated with 5 µg / mL of plate bound anti-CD3e antibody, 2 µg / mL anti-CD28 antibody and 10 ng / mL rhIL-2 or the indicated titrated amounts of a single stimuli. (FIG. S2B) CD8 T-cells were activated for 24 hours and NAD+ and NADH were measured by cycling assay. (FIG. S2C) Targeted LC-MS quantification of cellular NAD, NAM, NMN, NAMN, and NAAD in CD8+ T-cells stimulated with anti-CD3e antibody. WT CD8 T cells were stimulated

[0010] 94894-1903-2290, v. 1 for 24 hours and NAMPT protein was measured by western blot following stimulation with (FIG. S2D) anti-CD3e antibody at the indicated concentration and (FIG. S2E) with or without 2 µg / mL anti-CD28 antibody (or at the indicated concentration) and 10 ng / mL rhIL-2. (FIG. S2F) CD8 T-cells were activated with anti-CD3e and anti-CD28 antibody. Immediately prior to flow cytometry analysis cells were treated with rotenone or FCCP and NAD(P)H autofluorescence was measured. (FIG. S2G) OT-I T cells were stimulated with either N4 or G4 peptide at the indicated concentration for 24 hours. The gMFI of the NAD(P)H autofluorescence is reported. (FIG. S2H) Representative plots of NAD(P)H autofluorescence relative to FSC and in Myc-GFP OT-I T-cells. FIGS. S3A-C: (FIG. S3A) Nampt transcript from CD8 T cells in either C57BL / 6 or Namptfl / fl x CD8a-cre mice either naive or following 24 hours of stimulation (normalized to Pol2ra). (FIG. S3B) Frequency of T-cells in the blood of OT-I or Namptfl / fl x CD8a-cre x OT- I mice. (FIG. S3C) WT or NamptTg CD8 T cells were stimulated for 4 days in vitro. Nampt transcript is plotted at the indicated time post stimulation (normalized to Pol2ra). FIGS. S4A-H: CD8 T-cells were activated and treated with 100 nM FK866 or vehicle control for 24 or 48 hours from the indicated time points. Following each treatment window, cells were analyzed for (FIG. S4A) cell cycle and (FIG. S4B) viability after 48-hour treatment windows (FIG. S4C) Proliferation and (FIG. S4D) Myc expression after 24 hours treatment windows. (FIG. S4E) NAD was quantified by cycling assay in CD8 T-cells treated with FK866 for 24 hours from either day 0-1 or 4-5 post-activation. CD8 T-cells were activated and treated with 100 nM FK866 or vehicle control for 24 hours from either day 0-1 or 1-2. Following a day of treatment, SeaHorse analysis was performed. (FIG. S4F) ECAR and (FIG. S4G) OCR traces are plotted and (FIG. S4H) spare respiratory capacity (SRC) was quantified. OT-I T-cells were labeled with CTV and stimulated with 2 µg / mL of N4 or G4 peptide and 2 µg / mL of anti-CD28 antibody. FIGS. S5A-H: (FIG. S5A) Experimental schematic used in FIGS. S5B-G. Cells were treated at the time of activation with 100 nM FK866 + / - NR at the indicated concentration. Flow cytometry was performed at the indicated time points post-activation to quantify: (FIG. S5B) cell number, (FIG. S5C) cell viability, (FIG. S5D) the slope of %KI-67+ cells versus time was calculated and plotted for each dose of NR used. (FIG. S5E) Number of cells in G1 and G224 hours post-activation, in cells treated with FK866 and 0.41 µM NR or vehicle control. (FIG. S5F) The number of cells in G2 or percent divided cells 28 hours post-activation, in cells treatment with FK866 and 1.23 µM NR or vehicle control. (FIG. S5G) The number of cells in each division at 52 hours post stimulation. (FIG. S5H) pS6 / S6 gMFI at 24 hours

[0011] 104894-1903-2290, v. 1 poststimulation. Representative plots are shown. Representative data are shown from experiments that were repeated at least 3 times. FIGS. S6A-L: Validation of cell activation. (FIG. S6A) CD69 and (FIG. S6B) Myc were quantified by flow cytometry at 12 hours post activation and FK866 treatment. (FIG. S6C) Schematic of experimental design in FIGS. S6D-G. OT-I T-cells were stimulated with N4 peptide and treated for 24 hours with 100nM FK866 and were then supplemented with 100 µM NR (hereafter referred to as "delayed NAD rescue assay”). Following NR supplementation, (FIG. S6D) proliferation was quantified (CTY dilution). (FIG. S6E) pS6 gMFI was quantified by flow cytometry at the indicated time points. (FIG. S6F) The delayed NAD rescue assay was performed in cells that were treated with torin (500 nM) 10 minutes before NR supplementation. At the indicated time points, flow cytometry was performed to measure (FIG. S6F) the frequency of G1 cells and (FIG. S6G) Myc gMFI. (FIG. S6H) Representative plots of Myc expression in E are shown. (FIG. S6I) Experimental schematic for FIGS. S6J-L. WT CD8 T-cells were stimulated with plate bound anti-CD3e and anti-CD28 antibody in the presence of 100 nM FK866. After 24 hours, cells were either left on antibody coated plates or removed from stimulation and subsequently treated with 100 µM NR. Flow cytometry was performed prior to (1 day post activation) and 24 hours (2 days post activation) post NR-treatment to measure the (FIG. SJ) frequency of KI-67+ cells, (FIG. S6K) proliferation capacity (with representative plots at 24 hours post rescue), and (FIG. S6L) Myc gMFI. FIGS. S7A-C: LC-MS was performed to quantify relative metabolite abundance during the course of the delayed NAD rescue assay, pre- and post-NR supplementation (30, 120, 240 minutes post NR). Peak areas were normalized to an internal standard. (FIG. S7A) The -fold change from pre rescue was plotted as a heatmap. (FIG. S7B) OT-I cells were activated with N4 peptide for 24 hours and then treated with FK866 and PARP (10 µM Rucaparib), Sirtuin (50 µM EX527), or CD38 (65 µM 78c) inhibitors. (FIG. S7C) Cellular NAD was quantified by cycling assay at the indicated time points post-drug treatment to calculate the impact of each class of NAD consuming enzymes on the NAD half-life. (FIG. S7D) The delayed NAD rescue assay was performed, with cells 10 minutes prior to NR supplementation with either an inhibitor of Parp (10µM Rucaparib), Sirt (50µM EX527), or CD38 (65µM 78c) or vehicle control. Flow cytometry was performed to assay cell cycle entry at the indicated time points. FIGS. S8A-I: (FIG. S8A) the percent of IFNg, TNFa, and IL-2 are quantified and (FIG. S8B) percent of polyfunctional T-cells post stimulation (IFNg, TNFa, and IL-2 in NAD(P)H sorted cells at 3 days post sort. (FIG. S8C) NAD measurements by enzymatic cycling assay in

[0012] 114894-1903-2290, v. 1 CD4 T-cells following 24 hours of stimulation with anti-CD3e (5µ g / mL), anti-CD28 (2 µg / mL), and IL-2 (10 ng / mL) or as indicated. (FIGS. S8D-E) CD4 T cells were stimulated for 24 hours in the presence of 100uM FK866 and treated with NR at the indicated concentration. (FIG. S8D) The percent KI-67+ and (FIG.S 8E) gMFI of Myc are plotted. NAD measurements in B cells stimulated with (FIG. S8F) anti-IgM or (FIG. S8G) LPS at indicated concentrations. B cells were stimulated with LPS for 24 hours in the presence of 100 µM FK866 and treated with NR at the indicated concentration. (FIG. S8H) The percent KI-67+ and (FIG. S8I) gMFI of Myc are plotted.

[0013] 124894-1903-2290, v. 1 DETAILED DESCRIPTION The curative potential of chimeric antigen receptor (CAR) T cell-based cancer immunotherapies has been widely established but remains to be fully utilized due to the inability to identify the strongest CAR-T candidates. This is time-consuming and laborious undertaking that is hindered by the large number of potential problems due to the relatively small number of high-quality agents with the properties necessary for development into bona fide therapeutic reagents. In the present disclosure, the inventors tested their hypothesis that TCR signaling relays antigen affinity to a discrete set of metabolic pathways responsible for supporting clonal dynamics. Using both unbiased and targeted approaches, they identify NAD biosynthesis as a biochemical hub for TCR affinity-driven metabolic remodeling. While T cells are known to increase cellular NAD levels following activation and require NAD biosynthesis for long term survival, the specific cellular functions supported by NAD biosynthesis have remained unclear and its activity as affinity-tuned metabolite is undefined (Bruzzone et al., 2009; Wang et al., 2021; Rongvaux et al., 2008; Drijvers et al., 2021; Gerner et al., 2020; Carbone et al., 1992). The inventors identify an NAD biosynthesis-dependent quiescence exit checkpoint, in which TCR affinity tunes the magnitude of cellular NAD increase and the concurrent rate of cell cycle entry. They demonstrate that while mitogenic signaling sets maximal lymphocyte proliferative potential, cellular NAD levels and biochemistry, it facilitates control of the rate cells divide within these bounds. Highlighting NAD biosynthesis as a central node for TCR-driven T-cell expansion dynamics, the inventors show that normalizing cellular NAD(P)H levels is sufficient to normalize proliferation rate between low and high affinity ligand stimulated cells and enhancing NAD biosynthesis can permit the expansion of lower affinity clones in vivo. Based on these observations, the inventors sorted T lymphocytes into NAD(P)H high and low populations shortly after activation and identified cells with disparate functional and expansion potential. They find that NAD(P)H high sorted cells divide rapidly and quickly acquire effector T cell function (FIGS. 4C-F), indicating this population contains robust effector lymphocytes. In contrast, NAD(P)H low sorted cells are enriched for cells with greater durability and memory-like properties. In vivo, the inventors have shown that NAD(P)H low sorted cells persist longer than NAD(P)H high cells at memory timepoints following infection (FIG. 5A). They have further shown that sorting NAD(P)H low human T cells purifies cells for CAR T cell manufacturing with high tumor cytotoxicity, increased longevity, slower growth (which can reduce toxicity), and resistance to “exhaustion” (a process of cellular

[0014] 134894-1903-2290, v. 1 dysfunction) (FIGS. 5B-C). Importantly, as these NAD(P)H low cells grow more slowly than their NAD(P)H high counterparts, they are outcompeted and under-represented during status quo manufacturing, thus this method is uniquely positioned to capture and expand these cells. While this provides an example of this application in CAR T cell manufacturing, this concept could be applied to any adoptive lymphocyte cell therapy, be used to identify optimal populations for cell engineering, and be leveraged to isolate cells with desired properties for delivering a drug or engineered cargo or for the large scale synthesis of proteins. To this end, NAD(P)H high sorted cells would be attractive in instances where isolating cells with high proliferative and biosynthetic potential. These NAD(P)H high cells would also be advantageous when it is attractive to have a population of cells rapidly deliver a payload before contracting. Alternatively, as memory cells are defined by their longevity, stem-like properties, and greater expansion and functional capacity upon recall, NAD(P)H low sorting will be beneficial in any manufacturing process in which those are beneficial features. Given the general role we discovered for NAD(H) in lymphocyte biology at large, this method can separate any lymphocyte type within a day of activation into populations with distinct biological and functional properties. Thus, NAD(P)H sorting can be tailored to purify cells with desired biology fitting the needs of a given biomanufacturing or cell engineering pipeline. To formally test the contribution of single-cell NAD levels to T-cell proliferative kinetics, the inventors provided a uniform stimulus across a population of cells and then sorted activated T-cells based on NAD(P)H autofluorescence prior to the first division. The inventors show that initial NAD(P)H levels are sufficient to predict cell cycle kinetics, the number of future divisions they undergo, and the rate they acquire effector function. Finally, they find that this relationship between mitogenic signaling, NAD biosynthesis, and quiescence exit holds true across T and B-lymphocytes. Altogether, these data illustrate how mitogenic signaling converges on a single metabolic process that scales with signal strength, ensuring cell cycle demands are met with a commensurate anabolic program. Accordingly, variation in this one parameter is sufficient to predict how individual cells within a population behave, both for their metabolic and proliferative capacity. The inventors believe this provides a broader model for understanding how signaling networks regulate cell behavior through single-cell variations in metabolism. These and other aspects of the disclosure are set out in detail below.

[0015] 144894-1903-2290, v. 1 I. Definitions Unless otherwise defined, scientific and technical terms used herein shall have the meaning that are commonly understood by those of ordinary skill in the art. Further, unless otherwise required by context, singular terms shall include pluralities and plural terms shall include the singular. Generally, nomenclatures utilized in connection with, and techniques of, antibodies and related molecules, cell and tissue culture, molecular biology, and protein and oligo- or polynucleotide chemistry and hybridization described herein are those well-known and commonly used in the art. Standard techniques are used for recombinant DNA, oligonucleotide synthesis, and cell culture and transformation (e.g., electroporation, lipofection). Enzymatic reactions and purification techniques are performed according to manufacturer’s specifications or as commonly accomplished in the art or as described herein. The foregoing techniques and procedures are generally performed according to conventional methods well known in the art and as described in various general and more specific references that are cited and discussed throughout the present specification. See, e.g., B. Perbal, A Practical Guide to Molecular Cloning, John Wiley and Sons (1984); J. Sambrook et al., Molecular Cloning: A Laboratory Manual, Cold Spring Harbour Laboratory Press (1989); T.A. Brown (editor), Essential Molecular Biology: A Practical Approach, Volumes 1 and 2, IRL Press (1991); D.M. Glover and B.D. Hames (editors), DNA Cloning: A Practical Approach, Volumes 1-4, IRL Press (1995 and 1996); and F.M. Ausubel et al., (editors), Current Protocols in Molecular Biology, Greene Pub. Associates and Wiley-Interscience (1988, including all updates until present); Ed Harlow and David Lane (editors) Antibodies: A Laboratory Manual, Cold Spring Harbor Laboratory (1988); and J.E. Coligan et al., (editors) Current Protocols in Immunology, John Wiley & Sons (including all updates until present). The description and definitions of variable regions and parts thereof, immunoglobulins, antibodies and fragments thereof herein may be further clarified by the discussion in Kabat Sequences of Proteins of Immunological Interest, National Institutes of Health, Bethesda, Md. (1987 and 1991); Bork et al., J Mol. Biol.242, 309-320 (1994); Chothia and Lesk J. Mol Biol. 196:901-917 (1987), Chothia et al., Nature 342, 877-883 (1989), and / or or Al-Lazikani et al., J Mol Biol 273, 927-948 (1997). As used herein, “antigen-binding site” shall be taken to mean a structure formed by a protein that is capable of binding or specifically binding to an antigen, such as an antibody. The antigen-binding site need not be a series of contiguous amino acids, or even amino acids in a single polypeptide chain. For example, in a Fv comprising two different polypeptide chains

[0016] 154894-1903-2290, v. 1 from an antibody, the antigen-binding site is made up of a series of amino acids of a VLand a VHthat interact with the antigen and that are generally, however not always in one or more of the CDRs in each variable region. In some embodiments, the antigen-binding site is an antigen- binding site of an antibody. In such embodiments, the antigen-binding site may comprise one or more complementarity-determining regions or “CDRs”. In some embodiments, the antigen- binding site of an antibody comprises at least part of a VHor a VLor a Fv. 2.5F is a small, engineered peptide of ∼3.5 kDa, conformationally constrained cystine knot peptide, that binds with high affinity and unique specificity to αvβ1, αvβ3, αvβ5, αvβ6 and α5β1integrins. The cystine knot structural family, also known as knottins, consists of small polypeptides (30–50 amino acids) linked by at least three interwoven disulfide bonds, creating a rigid molecular “knot” that confers high chemical, thermal, and proteolytic stability. EETI 2.5F, which is based on the Ecballium elaterium trypsin inhibitor-II, was identified via high- throughput screening of yeast-displayed knottin libraries (Kimura et al., Proteins 77(2):359- 369, 2009). See also U.S. Patent 9,913,878. As used herein the phrase “chimeric antigen receptor (CAR)” refers to a recombinant or synthetic molecule which combines antibody-based specificity for a desired antigen with a T cell receptor-activating intracellular domain to generate a chimeric protein that exhibits cellular immune activity to the specific antigen. As used herein the phrase “T Cell Receptor” or “TCR” refers to soluble and non-soluble forms of recombinant T-cell receptor. As used herein, a “T-cell receptor (TCR) fusion protein” or “TFP” includes a recombinant polypeptide derived from the various polypeptides comprising the TCR that is generally capable of i) binding to a surface antigen on target cells and ii) interacting with other polypeptide components of the intact TCR complex, typically when co-located in or on the surface of a T-cell. As used herein a “T Cell Receptor-like antibody (TCRL” or “peptide-centric CAR (PC- CAR)” refers to an antibody which binds an MHC displaying an HLA-restricted peptide antigen. Binding of the TCRL to its target typically has an MHC-restricted specificity: the TCRL does not bind the MHC in the absence of the complexed peptide, and the TCRL does not bind the peptide in an absence of the MHC. TCRLs are characterized by affinity sufficient to permit specific binding to a tumor antigen even when the TCRL is provided in a soluble, rather than membrane-bound, form. TCRLs are being developed as a new therapeutic class for targeting tumor cells and mediating their specific killing. In addition, TCRLs are valuable

[0017] 164894-1903-2290, v. 1 research reagents enabling the study of human class I peptide-MHC ligand presentation and TCR-peptide-MHC interactions. As used herein the phrase “MHC (or HLA)-restricted peptide” refers to a peptide which is potentially presented on an MHC molecule. Such peptides may be identified by laboratory procedures such as Mass-Spectrometry, reverse-immunology or by in-silico analysis. An MHC (or HLA)-presented peptide refers to a peptide which is confirmed in vitro or in vivo as being presented by an MHC molecule. The term “cancer” as used herein is defined as a disease characterized by the rapid and uncontrolled growth of aberrant cells. Cancer cells can spread locally or through the bloodstream and lymphatic system to other parts of the body. The terms “normoxia” and “hypoxia” are generally known to those of skill in the art. In general, oxygen levels in tumors range from about 0.3 to 4.2% oxygen but are mostly below 2%, whereas oxygen levels in normal tissues range from about 3.4 to 6.8% oxygen, mostly above 4%. See McKeown S., Br. J. Radiol. 87(1035), 2014. For the purposes of this application, normoxia is defined as 3.0% or higher oxygen while hypoxia is lower than 3.0% oxygen. A “compound” refers to any molecule including small molecules, polypeptides, and other macromolecules. In some embodiments, a compound is a small molecular weight compound with a molecular weight of less than about 2000 Daltons. The term “naturally occurring” (or “native”) as used herein as applied to an object refers to the fact that an object can be found in nature. For example, a polypeptide or polynucleotide sequence that is present in an organism (including viruses) that can be isolated from a source in nature and which has not been intentionally modified by man in the laboratory or otherwise is naturally occurring. The term “operably linked” as used herein refers to positions of components so described that are in a relationship permitting them to function in their intended manner. For example, a control sequence “operably linked” to a coding sequence is connected in such a way that expression of the coding sequence is achieved under conditions compatible with the control sequences. The term “protein” shall be taken to include a single polypeptide chain, i.e., a series of contiguous amino acids linked by peptide bonds or a series of polypeptide chains covalently or non-covalently linked to one another (i.e., a polypeptide complex). For example, the series of polypeptide chains can be covalently linked using a suitable chemical linker or a disulphide

[0018] 174894-1903-2290, v. 1 bond, for example. Examples of non-covalent bonds include hydrogen bonds, ionic bonds, Van der Waals forces, and hydrophobic interactions. The term “polypeptide” or “polypeptide chain” will be understood from the foregoing paragraph to mean a series of contiguous amino acids linked by peptide bonds. The term “polynucleotide” as referred to herein means a polymeric form of nucleotides of at least 10 bases in length, either ribonucleotides or deoxynucleotides or a modified form of either type of nucleotide, or RNA-DNA hetero-duplexes. The term includes single and double stranded forms of DNA. The term “sequence identity” means that two polynucleotide or amino acid sequences are identical (i.e., on a nucleotide-by-nucleotide or residue-by-residue basis) over the comparison window. The term “percentage of sequence identity” is calculated by comparing two optimally aligned sequences over the window of comparison, determining the number of positions at which the identical nucleic acid base (e.g., A, T, C, G, U, or I) or amino acid residue occurs in both sequences to yield the number of matched positions, dividing the number of matched positions by the total number of positions in the comparison window (i.e., the window size), and multiplying the result by 100 to yield the percentage of sequence identity. The terms “substantial identity” as used herein denotes a characteristic of a polynucleotide or amino acid sequence, wherein the polynucleotide or amino acid comprises a sequence that has at least 85 percent sequence identity, preferably at least 90 to 95 percent sequence identity, more preferably at least 99 percent sequence identity, as compared to a reference sequence over a comparison window of at least 18 nucleotide (6 amino acid) positions, frequently over a window of at least 24-48 nucleotide (8-16 amino acid) positions, wherein the percentage of sequence identity is calculated by comparing the reference sequence to the sequence which may include deletions or additions which total 20 percent or less of the reference sequence over the comparison window. The reference sequence may be a subset of a larger sequence. As used herein, the twenty conventional amino acids and their abbreviations follow conventional usage. See Immunology - A Synthesis (2ndEdition, E.S. Golub and D.R. Gren, Eds., Sinauer Associates, Sunderland, Mass. (1991)). The term “epitope” includes any protein determinant capable of specific binding to an immunoglobulin or T-cell receptor. Epitopic determinants usually consist of chemically active surface groupings of molecules such as amino acids or sugar side chains and may, but not always, have specific three-dimensional structural characteristics, as well as specific charge characteristics.

[0019] 184894-1903-2290, v. 1 The term “agent” is used herein to denote a chemical compound, a mixture of chemical compounds, a biological macromolecule, or an extract made from biological materials. All publications and patents mentioned herein are hereby incorporated by reference in their entirety as if each individual publication or patent was specifically and individually indicated to be incorporated by reference. In case of conflict, the present application, including any definitions herein, will control. However, mention of any reference, article, publication, patent, patent publication, and patent application cited herein is not, and should not be taken as an acknowledgment, or any form of suggestion, that they constitute valid prior art or form part of the common general knowledge in any country in the world. In the present description, any concentration range, percentage range, ratio range, or integer range is to be understood to include the value of any integer within the recited range and, when appropriate, fractions thereof (such as one tenth and one hundredth of an integer), unless otherwise indicated. The term “about”, when immediately preceding a number or numeral, means that the number or numeral ranges plus or minus 10%. It should be understood that the terms “a” and “an” as used herein refer to “one or more” of the enumerated components unless otherwise indicated. The use of the alternative (e.g., “or”) should be understood to mean either one, both, or any combination thereof of the alternatives. The term “and / or” should be understood to mean either one, or both of the alternatives. As used herein, the terms “include” and “comprise” are used synonymously. The section headings used herein are for organizational purposes only and are not to be construed as limiting the subject matter described. II. Lymphocytes and Methods for Assaying the Same A lymphocyte is a type of white blood cell (leukocyte) in the immune system of most vertebrates. Lymphocytes include T cells (for cell-mediated, cytotoxic adaptive immunity), B cells (for humoral, antibody-driven adaptive immunity), and Innate lymphoid cells (ILCs) ("innate T cell-like" cells involved in mucosal immunity and homeostasis), of which natural killer cells are an important subtype (which functions in cell-mediated, cytotoxic innate immunity). They are the main type of cell found in lymph, which prompted the name "lymphocyte" (with cyte meaning cell). Lymphocytes make up between 18% and 42% of circulating white blood cells. The three major types of lymphocytes are T cells, B cells and natural killer (NK) cells. Lymphocytes can be identified by their large nucleus. T cells (thymus cells) and B cells (bone marrow- or bursa-derived cells[a]) are the major cellular components of the adaptive immune response. T cells are involved in cell-mediated

[0020] 194894-1903-2290, v. 1 immunity, whereas B cells are primarily responsible for humoral immunity (relating to antibodies). The function of T cells and B cells is to recognize specific "non-self" antigens, during a process known as antigen presentation. Once they have identified an invader, the cells generate specific responses that are tailored maximally to eliminate specific pathogens or pathogen-infected cells. B cells respond to pathogens by producing large quantities of antibodies which then neutralize foreign objects like bacteria and viruses. In response to pathogens some T cells, called T helper cells, produce cytokines that direct the immune response, while other T cells, called cytotoxic T cells, produce toxic granules that contain powerful enzymes which induce the death of pathogen-infected cells. Following activation, B cells and T cells leave a lasting legacy of the antigens they have encountered, in the form of memory cells. Throughout the lifetime of an animal, these memory cells will "remember" each specific pathogen encountered, and are able to mount a strong and rapid response if the same pathogen is detected again; this is known as acquired immunity. NK cells are a part of the innate immune system and play a major role in defending the host from tumors and virally infected cells. NK cells modulate the functions of other cells, including macrophages and T cells, and distinguish infected cells and tumors from normal and uninfected cells by recognizing changes of a surface molecule called MHC (major histocompatibility complex) class I. NK cells are activated in response to a family of cytokines called interferons. Activated NK cells release cytotoxic (cell-killing) granules which then destroy the altered cells. They are named "natural killer cells" because they do not require prior activation in order to kill cells which are missing MHC class I. A. Antibody Producing Cells / B Cells B cells, also known as B lymphocytes, are a type of white blood cell of the lymphocyte subtype. They function in the humoral immunity component of the adaptive immune system. B cells produce antibody molecules which may be either secreted or inserted into the plasma membrane where they serve as a part of B-cell receptors. When a naïve or memory B cell is activated by an antigen, it proliferates and differentiates into an antibody-secreting effector cell, known as a plasmablast or plasma cell. Additionally, B cells present antigens (they are also classified as professional antigen-presenting cells (APCs)) and secrete cytokines. In mammals, B cells mature in the bone marrow, which is at the core of most bones. B cells, unlike the other two classes of lymphocytes, T cells and natural killer cells, express B cell receptors (BCRs) on their cell membrane. BCRs allow the B cell to bind to a

[0021] 204894-1903-2290, v. 1 foreign antigen, against which it will initiate an antibody response. B cell receptors are extremely specific, with all BCRs on a B cell recognizing the same epitope. B cells develop from hematopoietic stem cells (HSCs) that originate from bone marrow. HSCs first differentiate into multipotent progenitor (MPP) cells, then common lymphoid progenitor (CLP) cells. From here, their development into B cells occurs in several stages (shown in image to the right), each marked by various gene expression patterns and immunoglobulin H chain and L chain gene loci arrangements, the latter due to B cells undergoing V(D)J recombination as they develop. B cells undergo two types of selection while developing in the bone marrow to ensure proper development, both involving B cell receptors (BCR) on the surface of the cell. Positive selection occurs through antigen-independent signalling involving both the pre-BCR and the BCR. If these receptors do not bind to their ligand, B cells do not receive the proper signals and cease to develop. Negative selection occurs through the binding of self-antigen with the BCR; if the BCR can bind strongly to self-antigen, then the B cell undergoes one of four fates: clonal deletion, receptor editing, anergy, or ignorance (B cell ignores signal and continues development). This negative selection process leads to a state of central tolerance, in which the mature B cells do not bind self-antigens present in the bone marrow. To complete development, immature B cells migrate from the bone marrow into the spleen as transitional B cells, passing through two transitional stages: T1 and T2. Throughout their migration to the spleen and after spleen entry, they are considered T1 B cells. Within the spleen, T1 B cells transition to T2 B cells. T2 B cells differentiate into either follicular (FO) B cells or marginal zone (MZ) B cells depending on signals received through the BCR and other receptors. Once differentiated, they are now considered mature B cells, or naive B cells. B cell activation occurs in the secondary lymphoid organs (SLOs), such as the spleen and lymph nodes. After B cells mature in the bone marrow, they migrate through the blood to SLOs, which receive a constant supply of antigen through circulating lymph. At the SLO, B cell activation begins when the B cell binds to an antigen via its BCR.]Although the events taking place immediately after activation have yet to be completely determined, it is believed that B cells are activated in accordance with the kinetic segregation model, initially determined in T lymphocytes. This model denotes that before antigen stimulation, receptors diffuse through the membrane coming into contact with Lck and CD45 in equal frequency, rendering a net equilibrium of phosphorylation and non-phosphorylation. It is only when the cell comes in contact with an antigen presenting cell that the larger CD45 is displaced due to the close distance between the two membranes. This allows for net phosphorylation of the BCR

[0022] 214894-1903-2290, v. 1 and the initiation of the signal transduction pathway. Of the three B cell subsets, FO B cells preferentially undergo T cell-dependent activation while MZ B cells and B1 B cells preferentially undergo T cell-independent activation. B cell activation is enhanced through the activity of CD21, a surface receptor in complex with surface proteins CD19 and CD81 (all three are collectively known as the B cell coreceptor complex). When a BCR binds an antigen tagged with a fragment of the C3 complement protein, CD21 binds the C3 fragment, co-ligates with the bound BCR, and signals are transduced through CD19 and CD81 to lower the activation threshold of the cell. B. T Cells and Chimeric Antigen Receptor (CAR) T Cells T cells play a central role in the adaptive immune response. T cells can be distinguished from other lymphocytes by the presence of a T-cell receptor (TCR) on their cell surface. T cells are born from hematopoietic stem cells, found in the bone marrow. Developing T cells then migrate to the thymus gland to develop (or mature). T cells derive their name from the thymus. After migration to the thymus, the precursor cells mature into several distinct types of T cells. T cell differentiation also continues after they have left the thymus. Groups of specific, differentiated T cell subtypes have a variety of important functions in controlling and shaping the immune response. One of these functions is immune-mediated cell death, and it is carried out by two major subtypes: CD8+ "killer" (cytotoxic) and CD4+ "helper" T cells. (These are named for the presence of the cell surface proteins CD8 or CD4.) CD8+ T cells, also known as "killer T cells", are cytotoxic – this means that they are able to directly kill virus-infected cells, as well as cancer cells. CD8+ T cells are also able to use small signalling proteins, known as cytokines, to recruit other types of cells when mounting an immune response. A different population of T cells, the CD4+ T cells, function as "helper cells". Unlike CD8+ killer T cells, the CD4+ helper T (TH) cells function by further activating memory B cells and cytotoxic T cells, which leads to a larger immune response. The specific adaptive immune response regulated by the TH cell depends on its subtype (such as T-helper1, T-helper2, T-helper17, regulatory T-cell), which is distinguished by the types of cytokines they secrete. Regulatory T cells are yet another distinct population of T cells that provide the critical mechanism of tolerance, whereby immune cells are able to distinguish invading cells from "self". This prevents immune cells from inappropriately reacting against one's own cells, known as an "autoimmune" response. For this reason, these regulatory T cells have also been

[0023] 224894-1903-2290, v. 1 called "suppressor" T cells. These same regulatory T cells can also be co-opted by cancer cells to prevent the recognition of, and an immune response against, tumor cells. All T cells originate from c-kit+Sca1+haematopoietic stem cells (HSC) which reside in the bone marrow. In some cases, the origin might be the fetal liver during embryonic development. The HSC then differentiate into multipotent progenitors (MPP) which retain the potential to become both myeloid and lymphoid cells. The process of differentiation then proceeds to a common lymphoid progenitor (CLP), which can only differentiate into T, B or NK cells. These CLP cells then migrate via the blood to the thymus, where they engraft; henceforth they are known as thymocytes, the immature stage of a T cell. The earliest cells which arrived in the thymus are commonly termed double-negative, as they express neither the CD4 nor CD8 co-receptor. The newly arrived CLP cells are CD4−CD8−CD44+CD25−ckit+cells, and are termed early thymic progenitor (ETP) cells. These cells will then undergo a round of division and downregulate c-kit and are termed double- negative one (DN1) cells. To become T cells, the thymocytes must undergo multiple DN stages as well as positive selection and negative selection. Double negative thymocytes can be identified by the surface expression of CD2, CD5 and CD7. Still during the double negative stages, CD34 expression stops and CD1 is expressed. Expression of both CD4 and CD8 makes them double positive, and matures into either CD4+ or CD8+ cells. A critical step in T cell maturation is making a functional T cell receptor (TCR). Each mature T cell will ultimately contain a unique TCR that reacts to a random pattern, allowing the immune system to recognize many different types of pathogens. This process is essential in developing immunity to threats that the immune system has not encountered before, since due to random variation there will always be at least one TCR to match any new pathogen. A thymocyte can only become an active T cell when it survives the process of developing a functional TCR. The TCR consists of two major components, the alpha and beta chains. These both contain random elements designed to produce a wide variety of different TCRs, but due to this huge variety they must be tested to make sure they work at all. First, the thymocytes attempt to create a functional beta chain, testing it against a 'mock' alpha chain. Then they attempt to create a functional alpha chain. Once a working TCR has been produced, the cells then must test if their TCR will identify threats correctly, and to do this it is required to recognize the body’s major histocompatibility complex (MHC) in a process known as positive selection. The thymocyte must also ensure that it does not react adversely to "self" antigens, called negative selection. If both positive and negative selection are successful, the TCR becomes fully operational and the thymocyte becomes a T cell.

[0024] 234894-1903-2290, v. 1 Chimeric antigen receptors (CARs) - also known as chimeric immunoreceptors, chimeric T cell receptors or artificial T cell receptors - are receptor proteins that have been engineered to give T cells the new ability to target a specific antigen. The receptors are chimeric in that they combine both antigen-binding and T cell activating functions into a single receptor. CAR T cell therapy uses T cells engineered with CARs to treat cancer. The premise of CAR T immunotherapy is to modify T cells to recognize cancer cells in order to more effectively target and destroy them. Scientists harvest T cells from people, genetically alter them, then infuse the resulting CAR T cells into patients to attack their tumors. CAR T cells can be derived either from T cells in a patient's own blood (autologously) or from the T cells of another, healthy, donor (allogeneically). Once isolated from a person, these T cells are genetically engineered to express a specific CAR, using a vector derived from an engineered lentivirus such as HIV (see Lentiviral vector in gene therapy). The CAR programs the recipient's T cells to target an antigen that is present on the surface of tumors. For safety, CAR T cells are engineered to be specific to an antigen that is expressed on a tumor but is not expressed on healthy cells. After CAR T cells are infused into a patient, they act as a "living drug" against cancer cells. When they come in contact with their targeted antigen on a cell's surface, CAR T cells bind to it and become activated, then proceed to proliferate and become cytotoxic. CAR T cells destroy cells through several mechanisms, including extensive stimulated cell proliferation, increasing the degree to which they are toxic to other living cells (cytotoxicity), and by causing the increased secretion of factors that can affect other cells such as cytokines, interleukins and growth factors. The surface of CAR T cells can bear either of two types of co- receptors, CD4 and CD8. These two cell types, called CD4+ and CD8+, respectively, have different and interacting cytotoxic effects, and it appears that therapies employing a 1-to-1 ratio of the cell types provide synergistic antitumor effects. Exemplary CARs are provided by U.S. Patent No. 8,399,645 and U.S. Patent No. 7,638,325. Other exemplary recombinant receptors, including CARs, recombinant T-cell receptors (TCRs), TCR fusion proteins (TFPs), as well as methods for engineering and introducing the receptors into cells, include those described in Int’l Pat. Appl. Nos. WO2017 / 096329, WO2000 / 14257, WO2013 / 126726, WO2012 / 129514, WO2014031687, WO2013 / 166321, WO2013 / 071154, WO2013 / 123061, and WO / 2014055668; U.S. Pat. Publn. Nos. US2002131960, US2013287748, and US20130149337; U.S. Pat. Nos. 6,451,995, 7,446,190, 7,638,325, 8,252,592, 8,339,645, 8,398,282, 7,446,179, 6,410,319, 7,070,995, 7,265,209, 7,354,762, 7,446,191, 8,324,353, and 8,479,118; European Pat. App. No.

[0025] 244894-1903-2290, v. 1 EP2537416; and Sadelain et al., Cancer Discov. April 3(4): 388-398 (2013); Davila et al., PLoS ONE 8(4): e61338 (2013); Turtle et al., Curr. Opin. Immunol. October 24(5): 633-39 (2012); and Wu et al., Cancer, March 18(2): 160-75 (2012). In an embodiment, the binding agent is a TFP as described in U.S. Serial No.15 / 419,398. C. Methods of Assessing Lymphocyte NAD Biosynthesis and Levels Existing pipelines are unable to identify high efficacy CAR T cells prior to treatment or high affinity B cells prior to end-stage production, primarily due to a high degree of heterogeneity in how they behave. Thus, by relying on scale to overcome this barrier, the cost is significant as are cell demands, manufacturing time, and ultimately the quality of the end product. In accordance with the disclosure, the inventors have developed a rapid and efficient method of selecting a lymphocyte from a population of lymphocytes that have properties best suited to become therapeutics or produce therapeutic products. The inventors have proven that they can “unmix” T and B lymphocytes from a heterogenous population using flow cytometry sorting based on NAD(P)H autofluorescence. Without need for treatment with compounds or genetic engineering, they can identify and select for cells with different functional and proliferative capacity, often within 24 hours of activation and prior to any cell division. They have further found that cellular NAD(H) levels scale proportionally with the antigen receptor affinity and can therefore also evaluate affinity simply by quantifying NAD(P)H autofluorescence. As its most basic, the method starts with a pre-obtained population of lymphocytes. These cells are then assessing NAD levels or NAD biosynthesis, and one or more candidates showing higher than populational average NAD(P)H are selected. Depending on the requirements for end use, as well as the size and quality of the lymphocyte population, the selection can be gated at the top 75% of the population, at the top 55% of the population, at the top 40% of the population, at the top 30% of the population, at the top 25% of the population, at the top 20% of the population, at the top 15% of the population, at the top 10% of the population, at the top 5% of the population, at the top 4% of the population, at the top 3% of the population, at the top 2% of the population, at the top 1% of the population, at the top 0.5% of the population, at the top 0.4% of the population, at the top 0.3% of the population, at the top 0.2% of the population, at the top 0.1% of the population, at the top 0.05% of the population, or at the top 0.01 % of the population. In a particular embodiment, the method employs NAD(P)H autofluorescence, with the selection function being provided by flow cytometry cell

[0026] 254894-1903-2290, v. 1 sorting. The following are exemplary methods to achieve these goals for various lymphocytes and are not intended to be limiting. NAD(P)H sorting protocol. First, one will prepare desired cells (see specific protocols in following slides) for sorting at room temperature, following standard flow cytometry protocols. Additionally, two extra samples are prepared for compensation controls: a) a sample of cells treated for 24 hours with 100 nM FK866, which will deplete cellular NAD(H); b) a sample of cells that is left untreated until the time of the sort, but will be treated with rotenone Cells are resuspended in 37°C phenol red-free RPMI 1640 or Tyrode’s buffer A cell sorter equipped with a UV laser (e.g. Cytek Aurora CS), pre-warmed in the sorting chamber to 37°C, is used. The sorter is set up for detection NAD(P)H as well as any other fluophores in the staining panel, if included. NAD(P)H autofluorescence is determined by signal excited from the UV laser (375 nm) and detected at 450nm. All NAD(P)H autofluorescence measurements should be done on a linear scale. Along with any other single-stain controls included in a given flow cytometry panel, the FK866 treated sample is sued as an NADH negative control. For a single-stain NADH positive control, one adds 1 μM rotenone to the second control sample immediately prior to placing the sample in the sorter for acquisition. Fluorescent compensation is performed according to standard guidelines for the given sorter. The sorting gates are set for the top and / or bottom quartiles of NAD(P)H autofluorescence. The size of the gate can be adjusted depending on the required cell number as well as how phenotypically enriched the cells need to be for the given application. The sorted cells are returned to culture for further expansion or cryopreserve as a final product in infusible media, as needed for the given application. CAR T cell application (post-CAR delivery). Peripheral blood T cells are collected for manufacturing from patients by leukapheresis and stimulate cells using beads coated with anti-CD3 and anti-CD28 antibodies. Lentivirus containing the CAR construct is administered to the cell culture within 24 hours of activation. Virus containing media is washed out on day 3 of culture. Cells are expaned on a rocking platform device (e.g., WAVE Bioreactor System) for 8 to 12 days and then re-stimulated with anti-CD3 / anti-CD28 antibody coated beads.18-24 hours post-stimulation, cells are harvested and prepared for flow cytometry-based sorting following standard protocols. Using a compatible cell sorter (e.g., Cytek Aurora CS with UV laser), cells are sorted based on NAD(P)H autofluorescence, as detailed in the NAP(H) sorting protocol above. Cells are returned to culture for further expansion or cryopreserve as a final product in infusible media.

[0027] 264894-1903-2290, v. 1 CAR T cell application (pre-CAR delivery). Peripheral blood T cells are collected for manufacturing from patients by leukapheresis and stimulate cells using beads coated with anti-CD3 and anti-CD28 antibodies. 18-24 hours post-stimulation, cells are harvested and prepared for cell sorting following standard protocols. Using a compatible cell sorter (e.g., Cytek Aurora CS with UV laser), cells are sorted based on NAD(P)H autofluorescence, as detailed in the NAP(H) sorting protocol above. Cells are returned to culture and lentivirus containing the CAR construct is administered to the cells. Virus containing media is washed out on day 3 of culture. Cells are expanded on a rocking platform device (e.g., WAVE Bioreactor System) for 8 to 12 days. The final product is cryopreserved in infusible media. Tumor-infiltrating lymphocyte (TIL) therapy application. TIL’s are harvested from one or more lesions (primary or metastasis) surgically resected from a patient and expanded for approximately two to four weeks in the presence of interleukin-2. After initial expansion, TIL’s are then stimulated with either anti-CD3 and anti-CD28 beads, irradiated allogenic peripheral blood mononuclear cells, or other comparable activating reagents. After 18-24 hours of stimulation, cells are harvested and prepared for cell sorting following standard prtocools. Using a compatible cell sorter (e.g., Cytek Aurora CS with UV laser), cells are sorted based on NAD(P)H autofluorescence, as detailed in the NAP(H) sorting protocol above. Cells are expanded on a rocking platform device (e.g., WAVE Bioreactor System) for 10 to 14 days. The final product is then either infused intravenously into patients or cryopreserved in infusible media. Biomanufacturing and drug payload delivery application. Peripheral blood lymphocytes are collected for manufacturing from individuals by leukapheresis and stimulated cells using beads coated with anti-CD3 and anti-CD28 antibodies. 18-24 hours post- stimulation, cells are harvested and prepared for cell sorting following standard protocols. Using a compatible cell sorter (e.g., Cytek Aurora CS with UV laser), cells are sorted based on NAD(P)H autofluorescence, as detailed in the NAP(H) sorting protocol above. Cells are returned to culture and a target transgene is delivered to the cells via viral transduction, electroporation, mRNA, or other gene delivery systems. Transgene containing cells are expanded on a rocking platform device (e.g., WAVE Bioreactor System). For biomanufacturing, cells can be serially stimulated approximately every 10 to 15 days to continue expansion and protein production, then harvested at regular intervals for the purification of transgenic proteins. For drug payload delivery, cells are harvested after 8 to 10 days and the final product is cryopreserved in infusible media, whereafter they can be infused into patients.

[0028] 274894-1903-2290, v. 1 Monoclonal antibody application. The desired species is immunized for antibody production (e.g., mice), with the target antigen and the appropriate adjuvant, following the manufacturer’s internal guidelines. Any prime-boost protocol is repeated, as needed. 21-28 days following the final immunization (or as required by the manufacturers internal guidelines), animals are euthanized. Spleens are harvested and a single-cell suspension is prepared. Cells are placed into culture and stimulated with target antigen. 20-24 hours post-stimulation, cells are prepared for sorting, staining with a viability dye and an appropriate B-cell marker for the immunized species (e.g., CD19). The top 2-5% of viable, CD19+cells are sorted based on NAD(P)H autofluorescence, as detailed in the NAP(H) sorting protocol above, using a compatible cell sorter (e.g., Cytek Aurora CS with UV laser). Sorted cells are prepared for fusion following the manufacturer’s internal hybridoma production guidelines (e.g., mixing 10:1 with myeloma cells in 50% PEG). One-week post-fusion, or following internal manufacturing guidelines, hybridomas are screened for target antigen reactivity and affinity. III. Expression Constructs According to the disclosure there are provided an engineered vectors that facilitate expression of CAR constructs. Such expression vectors contain elements coding for the non- antigen binding portions of CARs along with cis-acting regulatory elements. The expression vector of some embodiments of the disclosure includes additional sequences which render this vector suitable for replication and integration in prokaryotes, eukaryotes, or preferably both (e.g., as a shuttle vector). In addition, typical cloning vectors may also contain a transcription and translation initiation sequence, transcription and translation terminator and a polyadenylation signal. The nucleic acid construct of some embodiments of the disclosure includes a signal sequence for secretion or presentation of the binding agent from a host cell in which it is placed. Preferably the signal sequence for this purpose is a mammalian signal sequence. Eukaryotic promoters typically contain two types of recognition sequences, the TATA box and upstream promoter elements. The TATA box, located 25-30 base pairs upstream of the transcription initiation site, is thought to be involved in directing RNA polymerase to begin RNA synthesis. The other upstream promoter elements determine the rate at which transcription is initiated. Preferably, the promoter utilized by the expression vector is active in the specific cell population transformed. Examples of cell type-specific and / or tissue- specific promoters include promoters such as albumin that is liver specific (Pinkert et al., Genes Dev. 1:268-277 (1987)), lymphoid specific promoters (Calame et al., Adv. Immunol. 43:235-275

[0029] 284894-1903-2290, v. 1 (1988)); in particular promoters of T-cell receptors (Winoto et al., EMBO J.8:729-733 (1989)) and immunoglobulins; (Banerji et al., Cell 33:729-740 (1983)), neuron-specific promoters such as the neurofilament promoter (Byrne et al., Proc. Natl. Acad. Sci. USA 86:5473-5477 (1989)), pancreas-specific promoters (Edlunch et al., Science 230:912-916 (1985)) or mammary gland- specific promoters such as the milk whey promoter (U.S. Pat. No. 4,873,316 and European Application Publication No. EP0264166). In the construction of the expression vector, the promoter is preferably positioned approximately the same distance from the heterologous transcription start site as it is from the transcription start site in its natural setting. As is known in the art; however, some variation in this distance can be accommodated without loss of promoter function. Enhancer elements can stimulate transcription up to 1,000-fold from linked homologous or heterologous promoters. Enhancers are active when placed downstream or upstream from the transcription initiation site. Many enhancer elements derived from viruses have a broad host range and are active in a variety of tissues. For example, the SV40 early gene enhancer is suitable for many cell types. Other enhancer / promoter combinations that are suitable for some embodiments of the disclosure include those derived from polyoma virus, human or murine cytomegalovirus (CMV), the long-term repeat from various retroviruses such as murine leukemia virus, murine or Rous sarcoma virus and HIV. See, Enhancers and Eukaryotic Expression, Cold Spring Harbor Press, Cold Spring Harbor, N.Y.1983. Polyadenylation sequences can also be added to the expression vector in order to increase the efficiency of TCRL mRNA translation. Two distinct sequence elements are required for accurate and efficient polyadenylation: GU or U rich sequences located downstream from the polyadenylation site and a highly conserved sequence of six nucleotides, AAUAAA, located 11-30 nucleotides upstream. Termination and polyadenylation signals that are suitable for some embodiments of the disclosure include those derived from SV40. In addition to the elements already described the expression vector of some embodiments of the disclosure may contain other specialized elements intended to increase the level of expression of cloned nucleic acids or to facilitate the identification of cells that carry the recombinant DNA. For example, a number of animal viruses contain DNA sequences that promote the extra chromosomal replication of the viral genome in permissive cell types. Plasmids bearing these viral replicons are replicated episomally as long as the appropriate factors are provided by genes either carried on the plasmid or with the genome of the host cell. The vector may or may not include a eukaryotic replicon. If a eukaryotic replicon is present, then the vector is amplifiable in eukaryotic cells using the appropriate selectable

[0030] 294894-1903-2290, v. 1 marker. If the vector does not comprise a eukaryotic replicon, no episomal amplification is possible. Instead, the recombinant DNA integrates into the genome of the engineered cell, where the promoter directs expression of the desired nucleic acid. Also provided are cells which comprise the polynucleotides / expression vectors as described herein. Such cells are typically selected for high expression of recombinant proteins (e.g., bacterial, plant or eukaryotic cells e.g., CHO, HEK-293 cells), but may also be host cells having a specific immune effector activity (e.g., T cells or NK cells, such as Jurkat cells) when for instance the CDRs of the TCRL are implanted in a T Cell Receptor or CAR transduced in said cells which are used in adoptive cell therapy. Next, the CAR library is introduced into mammalian host cells that are then cultured under conditions supporting expression of encoded CARs. The host cells expressing the CAR are then contacted with target antigen positive host cells exhibiting CAR activation are then identified using a variety of different approaches. Once these cells are identified, the binding region can be sequenced and further developed. IV. Treatment of Cancers, Autoimmunity and Fibrosis In accordance with the present disclosure, provided are methods of treating cancers, particularly solid cancers. The methods involve the administration of CAR T cells to a subject such at the cells are brought in proximity with a cancer cell / cancer cell environment and their therapeutic effect is delivered. These methods can also be applied to other lymphocyte-based therapies where the NAD(P)H low and high populations would have distinct benefits. In the case of CAR T and other adoptive lymphocyte therapies, the NAD(P)H low cells have a profile that is consistent with what has been seen s as therapeutically beneficial (slow dividing, long lasting, and resistant to dysregulation caused by chronic signaling). On the other hand, the NAD(P)H high cells would have benefit in situations where rapid expansion and contraction of therapeutic lymphocytes would be advantageous, such as the delivery of drug payloads using lymphocytes or in the biomanufacturing of therapeutic molecules. The administration may be performed multiple times (2, 3, 4, 5, 6, 7, 8, 9, 10 or more) to a subject as needed. The subject may be an infant, a pediatric patient, a juvenile, a young adult, and adult or a senior. The subject may be a human, male or female, or may be a non-human mammal. In certain aspects the cancer tumor is a renal cell cancer, melanoma, prostate cancer, chronic lymphocytic leukemia, bladder, blood, bone, bone marrow, brain, breast, colon, esophagus, gastrointestine, gum, head, kidney, liver, lung, nasopharynx, neck, ovary, pancreas, prostate, skin, stomach, testis, tongue, or uterus. In addition, the cancer may specifically be of

[0031] 304894-1903-2290, v. 1 the following histological type, though it is not limited to these: neoplasm, malignant; carcinoma; carcinoma, undifferentiated; giant and spindle cell carcinoma; small cell carcinoma; papillary carcinoma; squamous cell carcinoma; lymphoepithelial carcinoma; basal cell carcinoma; pilomatrix carcinoma; transitional cell carcinoma; papillary transitional cell carcinoma; adenocarcinoma; gastrinoma, malignant; cholangiocarcinoma; hepatocellular carcinoma; combined hepatocellular carcinoma and cholangiocarcinoma; trabecular adenocarcinoma; adenoid cystic carcinoma; adenocarcinoma in adenomatous polyp; adenocarcinoma, familial polyposis coli; solid carcinoma; carcinoid tumor, malignant; branchiolo-alveolar adenocarcinoma; papillary adenocarcinoma; chromophobe carcinoma; acidophil carcinoma; oxyphilic adenocarcinoma; basophil carcinoma; clear cell adenocarcinoma; granular cell carcinoma; follicular adenocarcinoma; papillary and follicular adenocarcinoma; nonencapsulating sclerosing carcinoma; adrenal cortical carcinoma; endometroid carcinoma; skin appendage carcinoma; apocrine adenocarcinoma; sebaceous adenocarcinoma; ceruminous adenocarcinoma; mucoepidermoid carcinoma; cystadenocarcinoma; papillary cystadenocarcinoma; papillary serous cystadenocarcinoma; mucinous cystadenocarcinoma; mucinous adenocarcinoma; signet ring cell carcinoma; infiltrating duct carcinoma; medullary carcinoma; lobular carcinoma; inflammatory carcinoma; paget's disease, mammary; acinar cell carcinoma; adenosquamous carcinoma; adenocarcinoma w / squamous metaplasia; thymoma, malignant; ovarian stromal tumor, malignant; thecoma, malignant; granulosa cell tumor, malignant; androblastoma, malignant; sertoli cell carcinoma; leydig cell tumor, malignant; lipid cell tumor, malignant; paraganglioma, malignant; extra- mammary paraganglioma, malignant; pheochromocytoma; glomangiosarcoma; malignant melanoma; amelanotic melanoma; superficial spreading melanoma; malig melanoma in giant pigmented nevus; epithelioid cell melanoma; blue nevus, malignant; sarcoma; fibrosarcoma; fibrous histiocytoma, malignant; myxosarcoma; liposarcoma; leiomyosarcoma; rhabdomyosarcoma; embryonal rhabdomyosarcoma; alveolar rhabdomyosarcoma; stromal sarcoma; mixed tumor, malignant; mullerian mixed tumor; nephroblastoma; hepatoblastoma; carcinosarcoma; mesenchymoma, malignant; brenner tumor, malignant; phyllodes tumor, malignant; synovial sarcoma; mesothelioma, malignant; dysgerminoma; embryonal carcinoma; teratoma, malignant; struma ovarii, malignant; choriocarcinoma; mesonephroma, malignant; hemangiosarcoma; hemangioendothelioma, malignant; kaposi's sarcoma; hemangiopericytoma, malignant; lymphangiosarcoma; osteosarcoma; juxtacortical osteosarcoma; chondrosarcoma; chondroblastoma, malignant; mesenchymal chondrosarcoma; giant cell tumor of bone; ewing's sarcoma; odontogenic tumor, malignant; ameloblastic

[0032] 314894-1903-2290, v. 1 odontosarcoma; ameloblastoma, malignant; ameloblastic fibrosarcoma; pinealoma, malignant; chordoma; glioma, malignant; ependymoma; astrocytoma; protoplasmic astrocytoma; fibrillary astrocytoma; astroblastoma; glioblastoma; oligodendroglioma; oligodendroblastoma; primitive neuroectodermal; cerebellar sarcoma; ganglioneuroblastoma; neuroblastoma; retinoblastoma; olfactory neurogenic tumor; meningioma, malignant; neurofibrosarcoma; neurilemmoma, malignant; granular cell tumor, malignant; malignant lymphoma; Hodgkin's disease; Hodgkin's lymphoma; paragranuloma; malignant lymphoma, small lymphocytic; malignant lymphoma, large cell, diffuse; malignant lymphoma, follicular; mycosis fungoides; other specified non-Hodgkin's lymphomas; malignant histiocytosis; multiple myeloma; mast cell sarcoma; immunoproliferative small intestinal disease; leukemia; lymphoid leukemia; plasma cell leukemia; erythroleukemia; lymphosarcoma cell leukemia; myeloid leukemia; basophilic leukemia; eosinophilic leukemia; monocytic leukemia; mast cell leukemia; megakaryoblastic leukemia; myeloid sarcoma; and hairy cell leukemia. A. Pharmaceutical Formulations and Routes of Administration Pharmaceutical compositions provided herein comprise an effective amount of one or more therapeutic compositions and, optionally, an additional agent dissolved or dispersed in a pharmaceutically acceptable carrier. The phrases "pharmaceutical or pharmacologically acceptable" refers to molecular entities and compositions that do not produce an adverse, allergic or other untoward reaction when administered to an animal, such as, for example, a human, as appropriate. The preparation of a pharmaceutical composition that contains a therapeutic nucleic acid construct or a therapeutic engineered cell and one or more excipients will be known to those of skill in the art in light of the present disclosure, as exemplified by Remington's Pharmaceutical Sciences, 18th Ed. Mack Printing Company, 1990, incorporated herein by reference. Moreover, for animal (e.g., human) administration, it will be understood that preparations should meet sterility, pyrogenicity, general safety and purity standards as required by FDA Office of Biological Standards. As used herein, "pharmaceutically acceptable carrier" includes any and all solvents, dispersion media, coatings, surfactants, antioxidants, preservatives (e.g., antibacterial agents, antifungal agents), isotonic agents, absorption delaying agents, salts, preservatives, drugs, drug stabilizers, gels, binders, excipients, disintegration agents, lubricants, sweetening agents, flavoring agents, dyes, such like materials and combinations thereof, as would be known to one of ordinary skill in the art (see, for example, Remington's Pharmaceutical Sciences, 18th Ed. Mack Printing Company, 1990, pp. 1289-1329, incorporated herein by reference). Except

[0033] 324894-1903-2290, v. 1 insofar as any conventional carrier is incompatible with the active ingredient, its use in therapeutic or pharmaceutical compositions is contemplated. In certain embodiments, the pharmaceutical composition may comprise different types of carriers depending on whether it is to be administered in solid, liquid or aerosol form, and whether it need to be sterile for such routes of administration as injection. In certain embodiments, pharmaceutical compositions provided herein can be administered intravenously, intradermally, intraarterially, intraperitoneally, intralesionally, intracranially, intraarticularly, intraprostaticaly, intrapleurally, intratracheally, intranasally, intravitreally, intravaginally, intrarectally, topically, intratumorally, intramuscularly, intraperitoneally, subcutaneously, subconjunctival, intravesicularlly, mucosally, intrapericardially, intraumbilically, intraocularally, orally, topically, locally, inhalation (e.g. aerosol inhalation), injection, infusion, continuous infusion, localized perfusion bathing target cells directly, via a catheter, via a lavage, in cremes, in lipid compositions (e.g., liposomes), or by other method or any combination of the forgoing as would be known to one of ordinary skill in the art (see, for example, Remington's Pharmaceutical Sciences, 18th Ed. Mack Printing Company, 1990, incorporated herein by reference). In certain embodiments, the actual dosage amount of a composition administered to a patient can be determined by physical and physiological factors such as body weight, severity of condition, the type of disease being treated, previous or concurrent therapeutic interventions, idiopathy of the patient and on the route of administration. The practitioner responsible for administration will, in any event, determine the concentration of active ingredient(s) in a composition and appropriate dose(s) for the individual subject. In certain embodiments, pharmaceutical compositions may comprise, for example, at least about 0.1% of an active compound. In other embodiments, the active compound may comprise between about 2% to about 75% of the weight of the unit, or between about 25% to about 60%, for example, and any range derivable therein. In other non-limiting examples, a dose may also comprise from about 1 microgram / kg / body weight, about 5 microgram / kg / body weight, about 10 microgram / kg / body weight, about 15 microgram / kg / body weight, about 20 microgram / kg / body weight, about 25 microgram / kg / body weight, about 30 microgram / kg / body weight, about 35 microgram / kg / body weight, about 0.04 milligram / kg / body weight, about 0.05 milligram / kg / body weight, about 0.06 milligram / kg / body weight, about 0.07 milligram / kg / body weight, about 0.08 milligram / kg / body weight, about 0.09 milligram / kg / body weight, about 0.1 milligram / kg / body weight, about 0.2 milligram / kg / body weight, to about 0.5 mg / kg / body weight or more per

[0034] 334894-1903-2290, v. 1 administration, and any range derivable therein. In non-limiting examples of a derivable range from the numbers listed herein, a range of about 0.01 mg / kg / body weight to about 0.1 mg / kg / body weight, about 0.04 microgram / kg / body weight to about 0.08 milligram / kg / body weight, etc., can be administered, based on the numbers described above. In any case, the composition may comprise various antioxidants to retard oxidation of one or more component. Additionally, the prevention of the action of microorganisms can be brought about by preservatives such as various antibacterial and antifungal agents, including but not limited to parabens (e.g., methylparabens, propylparabens), chlorobutanol, phenol, sorbic acid, thimerosal or combinations thereof. In embodiments where the composition is in a liquid form, a carrier can be a solvent or dispersion medium comprising but not limited to, water, ethanol, polyol (e.g., glycerol, propylene glycol, liquid polyethylene glycol, etc.), lipids (e.g., triglycerides, vegetable oils, liposomes) and combinations thereof. The proper fluidity can be maintained, for example, by the use of a coating, such as lecithin; by the maintenance of the required particle size by dispersion in carriers such as, for example liquid polyol or lipids; by the use of surfactants such as, for example hydroxypropylcellulose; or combinations thereof such methods. In many cases, it will be preferable to include isotonic agents, such as, for example, sugars, sodium chloride or combinations thereof. In other embodiments, one may use eye drops, nasal solutions or sprays, aerosols or inhalants in the present embodiments. Such compositions are generally designed to be compatible with the target tissue type. In a non-limiting example, nasal solutions are usually aqueous solutions designed to be administered to the nasal passages in drops or sprays. Nasal solutions are prepared so that they are similar in many respects to nasal secretions, so that normal ciliary action is maintained. Thus, in preferred embodiments the aqueous nasal solutions usually are isotonic or slightly buffered to maintain a pH of about 5.5 to about 6.5. In addition, antimicrobial preservatives, similar to those used in ophthalmic preparations, drugs, or appropriate drug stabilizers, if required, may be included in the formulation. For example, various commercial nasal preparations are known and include drugs such as antibiotics or antihistamines. Sterile injectable solutions are prepared by incorporating the active compounds in the required amount in the appropriate solvent with various of the other ingredients enumerated above, as required, followed by filtered sterilization. Generally, dispersions are prepared by incorporating the various sterilized active ingredients into a sterile vehicle which contains the basic dispersion medium and / or the other ingredients. In the case of sterile powders for the

[0035] 344894-1903-2290, v. 1 preparation of sterile injectable solutions, suspensions or emulsion, the preferred methods of preparation are vacuum-drying or freeze-drying techniques which yield a powder of the active ingredient plus any additional desired ingredient from a previously sterile-filtered liquid medium thereof. The liquid medium should be suitably buffered if necessary and the liquid diluent first rendered isotonic prior to injection with sufficient saline or glucose. The preparation of highly concentrated compositions for direct injection is also contemplated, where the use of DMSO as solvent is envisioned to result in extremely rapid penetration, delivering high concentrations of the active agents to a small area. The composition must be stable under the conditions of manufacture and storage, and preserved against the contaminating action of microorganisms, such as bacteria and fungi. It will be appreciated that endotoxin contamination should be kept minimally at a safe level, for example, less than 0.5 ng / mg protein. In particular embodiments, prolonged absorption of an injectable composition can be brought about by the use in the compositions of agents delaying absorption, such as, for example, aluminum monostearate, gelatin or combinations thereof. B. Combination Therapies In order to increase the effectiveness of a nucleic acid, polypeptide or nanoparticle complex of the present embodiments, it may be desirable to combine these compositions with other agents effective in the treatment of the disease of interest. As a non-limiting example, the treatment of cancer may be implemented with a CAR / CAR T cell of the present disclosure along with other anti-cancer agents. An “anti-cancer” agent is capable of negatively affecting cancer in a subject, for example, by killing cancer cells, inducing apoptosis in cancer cells, reducing the growth rate of cancer cells, reducing the incidence or number of metastases, reducing tumor size, inhibiting tumor growth, reducing the blood supply to a tumor or cancer cells, promoting an immune response against cancer cells or a tumor, preventing or inhibiting the progression of cancer, or increasing the lifespan of a subject with cancer. More generally, these other compositions would be provided in a combined amount effective to kill or inhibit proliferation of the cell. This process may involve contacting the cells with the CAR / CAR T cell and the other agent(s) or factor(s) at the same time. This may be achieved by contacting the cell with a single composition or pharmacological formulation that includes both agents, or

[0036] 354894-1903-2290, v. 1 by contacting the cell with two distinct compositions or formulations, at the same time, wherein one composition includes the CAR / CAR T cell and the other includes the second agent(s). Treatment with the CAR / CAR T cell may precede or follow the other agent treatment by intervals ranging from minutes to weeks. In embodiments where the other agent and the anti-cancer peptide or nanoparticle complex are applied separately to the cell, one would generally ensure that a significant period of time did not expire between the time of each delivery, such that the agent and the anti-cancer peptide or nanoparticle complex would still be able to exert an advantageously combined effect on the cell. In such instances, it is contemplated that one may contact the cell with both modalities within about 12-24 hours of each other and, more preferably, within about 6-12 hours of each other. In some situations, it may be desirable to extend the time period for treatment significantly where several days (e.g., 2, 3, 4, 5, 6 or 7 days) to several weeks (e.g., 1, 2, 3, 4, 5, 6, 7 or 8 weeks) lapse between the respective administrations. Various combinations may be employed, where the CAR / CAR T cell therapy is “A” and the other agent is “B”: A / B / A B / A / B B / B / A A / A / B A / B / B B / A / A A / B / B / B B / A / B / B B / B / B / A B / B / A / B A / A / B / B A / B / A / B A / B / B / A B / B / A / A B / A / B / A B / A / A / B A / A / A / B B / A / A / A A / B / A / A A / A / B / A In certain embodiments, administration of the CAR / CAR T cell therapy and / or other agent(s) to a patient will follow general protocols for the administration of chemotherapeutics, taking into account the toxicity, if any, of the vector. It is expected that the treatment cycles would be repeated as necessary. It also is contemplated that various standard therapies, as well as surgical intervention, may be applied in combination with the described hyperproliferative cell therapy. Chemotherapy. Cancer therapies also include a variety of combination therapies. In some aspects, a CAR / CAR T cell therapeutic and / or an immune checkpoint inhibitor of the embodiments is administered (or formulated) in conjunction with a chemotherapeutic agent. For example, in some aspects, the chemotherapeutic agent is a protein kinase inhibitor such as a EGFR, VEGFR, AKT, Erb1, Erb2, ErbB, Syk, Bcr-Abl, JAK, Src, GSK-3, PI3K, Ras, Raf, MAPK, MAPKK, mTOR, c-Kit, eph receptor or BRAF inhibitors. Nonlimiting examples of protein kinase inhibitors include Afatinib, Axitinib, Bevacizumab, Bosutinib, Cetuximab, Crizotinib, Dasatinib, Erlotinib, Fostamatinib, Gefitinib, Imatinib, Lapatinib, Lenvatinib, Mubritinib, Nilotinib, Panitumumab, Pazopanib, Pegaptanib, Ranibizumab, Ruxolitinib, Saracatinib, Sorafenib, Sunitinib, Trastuzumab, Vandetanib, AP23451, Vemurafenib, MK-

[0037] 364894-1903-2290, v. 1 2206, GSK690693, A-443654, VQD-002, Miltefosine, Perifosine, CAL101, PX-866, LY294002, rapamycin, temsirolimus, everolimus, ridaforolimus, Alvocidib, Genistein, Selumetinib, AZD-6244, Vatalanib, P1446A-05, AG-024322, ZD1839, P276-00, GW572016 or a mixture thereof. Yet further combination chemotherapies include, for example, alkylating agents such as thiotepa and cyclosphosphamide; alkyl sulfonates such as busulfan, improsulfan and piposulfan; aziridines such as benzodopa, carboquone, meturedopa, and uredopa; ethylenimines and methylamelamines including altretamine, triethylenemelamine, trietylenephosphoramide, triethiylenethiophosphoramide and trimethylolomelamine; acetogenins (especially bullatacin and bullatacinone); a camptothecin (including the synthetic analogue topotecan); bryostatin; callystatin; CC-1065 (including its adozelesin, carzelesin and bizelesin synthetic analogues); cryptophycins (particularly cryptophycin 1 and cryptophycin 8); dolastatin; duocarmycin (including the synthetic analogues, KW-2189 and CB1-TM1); eleutherobin; pancratistatin; a sarcodictyin; spongistatin; nitrogen mustards such as chlorambucil, chlornaphazine, cholophosphamide, estramustine, ifosfamide, mechlorethamine, mechlorethamine oxide hydrochloride, melphalan, novembichin, phenesterine, prednimustine, trofosfamide, uracil mustard; nitrosureas such as carmustine, chlorozotocin, fotemustine, lomustine, nimustine, and ranimnustine; antibiotics such as the enediyne antibiotics (e.g., calicheamicin, especially calicheamicin gammalI and calicheamicin omegaI1; dynemicin, including dynemicin A; bisphosphonates, such as clodronate; an esperamicin; as well as neocarzinostatin chromophore and related chromoprotein enediyne antiobiotic chromophores, aclacinomysins, actinomycin, authrarnycin, azaserine, bleomycins, cactinomycin, carabicin, carminomycin, carzinophilin, chromomycinis, dactinomycin, daunorubicin, detorubicin, 6-diazo-5-oxo-L-norleucine, doxorubicin (including morpholino- doxorubicin, cyanomorpholino-doxorubicin, 2-pyrrolino-doxorubicin and deoxydoxorubicin), epirubicin, esorubicin, idarubicin, marcellomycin, mitomycins such as mitomycin C, mycophenolic acid, nogalarnycin, olivomycins, peplomycin, potfiromycin, puromycin, quelamycin, rodorubicin, streptonigrin, streptozocin, tubercidin, ubenimex, zinostatin, zorubicin; anti-metabolites such as methotrexate and 5-fluorouracil (5-FU); folic acid analogues such as denopterin, pteropterin, trimetrexate; purine analogs such as fludarabine, 6- mercaptopurine, thiamiprine, thioguanine; pyrimidine analogs such as ancitabine, azacitidine, 6-azauridine, carmofur, cytarabine, dideoxyuridine, doxifluridine, enocitabine, floxuridine; androgens such as calusterone, dromostanolone propionate, epitiostanol, mepitiostane, testolactone; anti-adrenals such as mitotane, trilostane; folic acid replenisher such as frolinic

[0038] 374894-1903-2290, v. 1 acid; aceglatone; aldophosphamide glycoside; aminolevulinic acid; eniluracil; amsacrine; bestrabucil; bisantrene; edatraxate; defofamine; demecolcine; diaziquone; elformithine; elliptinium acetate; an epothilone; etoglucid; gallium nitrate; hydroxyurea; lentinan; lonidainine; maytansinoids such as maytansine and ansamitocins; mitoguazone; mitoxantrone; mopidanmol; nitraerine; pentostatin; phenamet; pirarubicin; losoxantrone; podophyllinic acid; 2-ethylhydrazide; procarbazine; PSK polysaccharide complex; razoxane; rhizoxin; sizofiran; spirogermanium; tenuazonic acid; triaziquone; 2,2',2”-trichlorotriethylamine; trichothecenes (especially T-2 toxin, verracurin A, roridin A and anguidine); urethan; vindesine; dacarbazine; mannomustine; mitobronitol; mitolactol; pipobroman; gacytosine; arabinoside (“Ara-C”); cyclophosphamide; taxoids, e.g., paclitaxel and docetaxel gemcitabine; 6-thioguanine; mercaptopurine; platinum coordination complexes such as cisplatin, oxaliplatin and carboplatin; vinblastine; platinum; etoposide (VP-16); ifosfamide; mitoxantrone; vincristine; vinorelbine; novantrone; teniposide; edatrexate; daunomycin; aminopterin; xeloda; ibandronate; irinotecan (e.g., CPT-11); topoisomerase inhibitor RFS 2000; difluorometlhylornithine (DMFO); retinoids such as retinoic acid; capecitabine; carboplatin, procarbazine, plicomycin, gemcitabien, navelbine, farnesyl-protein tansferase inhibitors, transplatinum, and pharmaceutically acceptable salts, acids or derivatives of any of the above. In certain embodiments, the compositions provided herein may be used in combination with gefitinib. In other embodiments, the present embodiments may be practiced in combination with Gleevac (e.g., from about 400 to about 800 mg / day of Gleevac may be administered to a patient). In certain embodiments, one or more chemotherapeutics may be used in combination with the compositions provided herein. Radiotherapy. Other factors that cause DNA damage and have been used extensively include what are commonly known as γ-rays, X-rays, and / or the directed delivery of radioisotopes to tumor cells. Other forms of DNA damaging factors are also contemplated such as microwaves and UV-irradiation. It is most likely that all of these factors induce a broad range of damage on DNA, on the precursors of DNA, on the replication and repair of DNA, and on the assembly and maintenance of chromosomes. Dosage ranges for X-rays range from daily doses of 50 to 200 roentgens for prolonged periods of time (3 to 4 wk), to single doses of 2000 to 6000 roentgens. Dosage ranges for radioisotopes vary widely, and depend on the half- life of the isotope, the strength and type of radiation emitted, and the uptake by the neoplastic cells.

[0039] 384894-1903-2290, v. 1 The terms “contacted” and “exposed,” when applied to a cell, are used herein to describe the process by which a therapeutic composition and a chemotherapeutic or radiotherapeutic agent are delivered to a target cell or are placed in direct juxtaposition with the target cell. To achieve cell killing or stasis, both agents are delivered to a cell in a combined amount effective to kill the cell or prevent it from dividing. Immunotherapy. Immunotherapeutics, generally, rely on the use of immune effector cells and molecules to target and destroy cancer cells. The immune effector may be, for example, an antibody specific for some marker on the surface of a tumor cell. The antibody alone may serve as an effector of therapy or it may recruit other cells to actually effect cell killing. The antibody also may be conjugated to a drug or toxin (chemotherapeutic, radionuclide, ricin A chain, cholera toxin, pertussis toxin, etc.) and serve merely as a targeting agent. Alternatively, the effector may be a lymphocyte carrying a surface molecule that interacts, either directly or indirectly, with a tumor cell target. Various effector cells include cytotoxic T cells and NK cells. Immunotherapy, thus, could be used as part of a combined therapy, in conjunction with a CAR / CAR T cell therapy of the present embodiments. The general approach for combined therapy is discussed below. Generally, the tumor cell must bear some marker that is amenable to targeting, i.e., is not present on the majority of other cells. Many tumor markers exist and any of these may be suitable for targeting in the context of the present embodiments. Common tumor markers include carcinoembryonic antigen, prostate specific antigen, urinary tumor associated antigen, fetal antigen, tyrosinase (p97), gp68, TAG-72, HMFG, Sialyl Lewis Antigen, MucA, MucB, PLAP, estrogen receptor, laminin receptor, erb B and p155. Gene Therapy. In yet another embodiment, the secondary treatment is a gene therapy in which a therapeutic polynucleotide is administered before, after, or at the same time as the therapeutic composition. Viral vectors for the expression of a gene product are well known in the art, and include such eukaryotic expression systems as adenoviruses, adeno-associated viruses, retroviruses, herpesviruses, lentiviruses, poxviruses including vaccinia viruses, and papiloma viruses, including SV40. Alternatively, the administration of expression constructs can be accomplished with lipid-based vectors such as liposomes or DOTAP:cholesterol vesicles. All of these methods are well known in the art (see, e.g., Sambrook et al., 1989; Ausubel et al., 1998; Ausubel, 1996). Delivery of a vector encoding one of the following gene products will have a combined anti-hyperproliferative effect on target tissues. A variety of proteins are encompassed within the present embodiments, some of which are described below.

[0040] 394894-1903-2290, v. 1 As noted above, the tumor suppressor oncogenes function to inhibit excessive cellular proliferation. The inactivation of these genes destroys their inhibitory activity, resulting in unregulated proliferation. Genes that may be employed as secondary treatment in accordance with the present embodiments include p53, p16, Rb, APC, DCC, NF-1, NF-2, WT-1, MEN-I, MEN-II, zac1, p73, VHL, MMAC1 / PTEN, DBCCR-1, FCC, rsk-3, p27, p27 / p16 fusions, p21 / p27 fusions, anti-thrombotic genes (e.g., COX-1, TFPI), PGS, Dp, E2F, ras, myc, neu, raf, erb, fms, trk, ret, gsp, hst, abl, E1A, p300, genes involved in angiogenesis (e.g., VEGF, FGF, thrombospondin, BAI-1, GDAIF, or their receptors), MCC and other genes listed in Table IV. Apoptosis, or programmed cell death, is an essential process for normal embryonic development, maintaining homeostasis in adult tissues, and suppressing carcinogenesis (Kerr et al., 1972). The Bcl-2 family of proteins and ICE-like proteases have been demonstrated to be important regulators and effectors of apoptosis in other systems. The Bcl-2 protein, discovered in association with follicular lymphoma, plays a prominent role in controlling apoptosis and enhancing cell survival in response to diverse apoptotic stimuli (Bakhshi et al., 1985; Cleary and Sklar, Proc. Nat’l. Acad. Sci. USA, 82(21):7439-43, 1985; Cleary et al., 1986; Tsujimoto et al., 1985; Tsujimoto and Croce, 1986). The evolutionarily conserved Bcl-2 protein now is recognized to be a member of a family of related proteins, which can be categorized as death agonists or death antagonists. Subsequent to its discovery, it was shown that Bcl-2 acts to suppress cell death triggered by a variety of stimuli. Also, it now is apparent that there is a family of Bcl-2 cell death regulatory proteins which share in common structural and sequence homologies. These different family members have been shown to either possess similar functions to Bcl-2 (e.g., BclXL, BclW, BclS, Mcl-1, A1, Bfl-1) or counteract Bcl-2 function and promote cell death (e.g., Bax, Bak, Bik, Bim, Bid, Bad, Harakiri). Surgery. Approximately 60% of persons with cancer will undergo surgery of some type, which includes preventative, diagnostic or staging, curative and palliative surgery. Curative surgery is a cancer treatment that may be used in conjunction with other therapies, such as the treatments provided herein, chemotherapy, radiotherapy, hormonal therapy, gene therapy, immunotherapy and / or alternative therapies. Curative surgery includes resection in which all or part of cancerous tissue is physically removed, excised, and / or destroyed. Tumor resection refers to physical removal of at least part of a tumor. In addition to tumor resection, treatment by surgery includes laser surgery, cryosurgery, electrosurgery, and miscopically controlled surgery (Mohs’ surgery). It is further

[0041] 404894-1903-2290, v. 1 contemplated that the present embodiments may be used in conjunction with removal of superficial cancers, precancers, or incidental amounts of normal tissue. Upon excision of part of all of cancerous cells, tissue, or tumor, a cavity may be formed in the body. Treatment may be accomplished by perfusion, direct injection or local application of the area with an additional anti-cancer therapy. Such treatment may be repeated, for example, every 1, 2, 3, 4, 5, 6, or 7 days, or every 1, 2, 3, 4, and 5 weeks or every 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 months. These treatments may be of varying dosages as well. Anti-Inflammatory Agents. In certain aspects CAR / CAR T cell therapies and / or an immune checkpoint inhibitor are administered in conjuction with an anti-inflammatory agent. An anti-inflammatory agent is defined herein to refer to an agent that is known or suspected to be of benefit in the treatment or prevention of inflammation in a subject. Corticosteroids are a major class of anti-inflammatory agent. The corticosteroids may be short, medium, or long acting, and may be delivered in a variety of methods. A non-limiting list of corticosteroids contemplated in the present embodiments include the oral corticosteroids such as: cortisone, hydrocortisone, prednisone, and dexamethasone. Another major class of anti-inflammatory agents are non-steroidal anti-inflammatory agents. Non-steroidal anti-inflammatory agents include a class of drugs used in the treatment of inflammation and pain. The exact mode of action of this class of drugs is unknown. Examples of members of this class of agents include, but are not limited to, ibuprofen, ketoprofen, flurbiprofen, nabumetone, piroxicam, naproxen, diclofenac, indomethacin, sulindac, tolmetin, etodolac, flufenamic acid, diflunisal, oxaprozin, rofecoxib, and celecoxib. One of ordinary skill in the art would be familiar with these agents. Included in this category are salicylates and derivates of salicylates, such as acetyl salicylic acid, sodium salicylate, choline salicylate, choline magnesium salicylate and diflunisal. Other anti-inflammatory agents include anti-rheumatic agents, such as gold salts (e.g., gold sodium thiomalate, aurothioglucose, and auranofin), anti-rheumatic agents (e.g., chloroquine, hydroxychloroquine, and penicillamine), antihistamines (e.g., diphenhydramine, chlorpheniramine, clemastine, hydroxyzine, and triprolidine), and immunosuppressive agents (e.g., methotrexate, mechlorethamine, cyclophosphamide, chlorambucil, cyclosporine, and azathioprine). Other immunosuppressive agents contemplated by the present embodiments is tacrolimus and everolimus. Tacrolimus suppresses interleukin-2 production associated with T- cell activation, inhibits differentiation and proliferation of cytotoxic T cells. Today, it is recognized worldwide as the cornerstone of immunosuppressant therapy. One of ordinary skill

[0042] 414894-1903-2290, v. 1 in the art would be familiar with these agents, and other members of this class of agents, as well as the mechanism of actions of these agents and indications for use of these agents. Other agents. It is contemplated that other agents may be used in combination with the compositions provided herein to improve the therapeutic efficacy of treatment. These additional agents include immunomodulatory agents, agents that affect the upregulation of cell surface receptors and GAP junctions, cytostatic and differentiation agents, inhibitors of cell adehesion, or agents that increase the sensitivity of the hyperproliferative cells to apoptotic inducers. Immunomodulatory agents include tumor necrosis factor; interferon alpha, beta, and gamma; IL-2 and other cytokines; F42K and other cytokine analogs; or MIP-1, MIP-1beta, MCP-1, RANTES, and other chemokines. It is further contemplated that the upregulation of cell surface receptors or their ligands such as Fas / Fas ligand, DR4 or DR5 / TRAIL would potentiate the apoptotic inducing abililties of the compositions provided herein by establishment of an autocrine or paracrine effect on hyperproliferative cells. Increases intercellular signaling by elevating the number of GAP junctions would increase the anti- hyperproliferative effects on the neighboring hyperproliferative cell population. In other embodiments, cytostatic or differentiation agents can be used in combination with the compositions provided herein to improve the anti-hyerproliferative efficacy of the treatments. Inhibitors of cell adhesion are contemplated to improve the efficacy of the disclosed agents and methods. Examples of cell adhesion inhibitors are focal adhesion kinase (FAKs) inhibitors and Lovastatin. It is further contemplated that other agents that increase the sensitivity of a hyperproliferative cell to apoptosis, such as the antibody c225, could be used in combination with the compositions provided herein to improve the treatment efficacy. In certain embodiments, hormonal therapy may also be used in conjunction with the present embodiments or in combination with any other cancer therapy previously described. The use of hormones may be employed in the treatment of certain cancers such as breast, prostate, ovarian, or cervical cancer to lower the level or block the effects of certain hormones such as testosterone or estrogen. This treatment is often used in combination with at least one other cancer therapy as a treatment option or to reduce the risk of metastases. V. Examples The following examples are included to demonstrate particular embodiments. It should be appreciated by those of skill in the art that the techniques disclosed in the examples that follow represent techniques discovered by the inventor to function well in the practice of embodiments, and thus can be considered to constitute particular modes for its practice.

[0043] 424894-1903-2290, v. 1 However, those of skill in the art should, in light of the present disclosure, appreciate that many changes can be made in the specific embodiments which are disclosed and still obtain a like or similar result without departing from the spirit and scope of the disclosure. Example 1 – Materials and Methods Mice. C57BL / 6 (Jax #000664), OT-I (Jax #003831), CD8-Cre (Jax #008766) and B6- Ly5.1 (Jax #002014) mice (6-8 weeks old) were purchased from Jackson Laboratories and maintained in house. Namptfl / fl (Rongvaux et al., 2008) and NamptTg (Frederick et al., 2015) mice were a gift from J. Baur. All mice were housed under specific pathogen-free conditions with a 12 hour on / off light cycle at the Children’s Hospital of Philadelphia. All experiments were performed in accordance with the Institutional Animal Care and Use Committee of the Children’s Hospital of Philadelphia (IAC 21-001325). Lymphocyte cell culture. CD8+ T cells, CD4+ T cells, or B cells were isolated from the spleen and lymph nodes (inguinal, axillary, brachial and superficial cervical) of either C56BL / 6 (WT) or OT-I mice by negative selection using a EasySep Mouse Isolation kit (StemCell Technologies). Unless otherwise noted, OT-I T cells were stimulated with 1 μg / ml SIINFEKL (N4), SIIQFEKL (Q4), SIITFEKL (T4), or SIIGFEKL (G4) peptides (Anaspec), anti-CD28 (clone 37.51, BioLegend) and recombinant mouse IL-2 (BioLegend). C57BL / 6 CD8+ T and CD4+ T cells were stimulated with anti-CD3 (clone 145-2C11, BioLegend), anti- CD28, and mouse IL-2. B cells were stimulated with anti-IgM (Goat anti-mouse, Jackson Immunoresearch), CD40 (Clone FGK 4.5, BioXcell) or LPS (Sigma). For all experiments using pharmacological inhibitors or metabolite supplementation, the following doses were used, unless otherwise noted: 100 nM FK866 (Daporinad), 100 μM NR (Elysium), Tryptophan (Sigma), Nicotinic Acid (Sigma), 1 μM rotenone (Sigma), 1 μM oligomycin (Sigma), 10 mM 2-deoxy-D-glucose, 0.2 mM FCCP (Sigma), 10 μM Rucaparib (MedChemExpress), 50 μM EX527 (Selleck), 65 μM 78c (Tocris). Flow Cytometry. All flow cytometry was performed on a CytoFLEX LX or CytoFLEX S cytometer (Beckman Coulter). Data was analyzed using FlowJo software (Treestar). For dead cell exclusion, eBioscience Fixable Viability Dye eFluor 780 was used (ThermoFisher) was used. Absolute cell number in each sample was backcalculated from recorded cytometer sample volumes following calibration. Cell division was measured by labelling cells with CellTrace Violet or CellTrace Yellow (Invitrogen) before activation, and evaluated for proliferation at the indicated time points. Cell-cycle status, Myc expression, and mTORC1 signaling were determined by intracellular flow cytometry analysis of Ki67, 7AAD, anti-cMyc

[0044] 434894-1903-2290, v. 1 (Cell Signaling Technology, 5605), anti-S6 (Cell Signaling Technology, 5317), and anti- phospho-S6 (Cell Signaling Technology, 5316) at the indicated time points. NAD(P)H autofluorescence was determined by signal excited from the UV laser (375 nm) and detected at 450nm. Triplicate sample wells were run asynchronously to control for any fluctuations in the autofluorescence signal over time were controlled. Cytokine was measured by adding brefeldin A, 30 minutes after the addition of PMA (20 ng / ml) and ionomycin (20 ng / ml); 4.5 h after restimulation, cells were fixed, permeabilized and stained with anti-CD8 (Thermo), anti- IFNγ (Thermo), anti-TNFa (Thermo), and anti-IL-2 (Thermo) and analysed by flow cytometry. Tetramer staining was performed with SIINFEKL loaded H2-Kb tetramer (NIH tetramer core) for 1 hour at 4C prior to surface staining. The gMFI was calculated from live, TCRb+, CD8+, CD44+ cells and normalized to TCRb gMFI to calculate relative TCR affinity. Flow cytometric cell sorting. Cell sorting of T cells and B cells was done on a Cytek Aurora CS cell sorter. For compensation calculation, FK866 treated CD8 T-cells were used as a negative control for NAD(P)H autofluorescence. Cells were harvested approximately 20 hours after activation. After cell sorting, cells were re-cultured in lymphocyte culture medium without further stimulation. During the sort for NAD(P)H autofluorescence, the chamber was kept at 37C. The sort gates were set by a percentage of the population to capture NAD(P)H high and low cells. Seahorse analysis. Analysis was performed on cells at the noted time points post- activation. Cells were washed in complete Seahorse medium (Seahorse Bioscience) with 10 mM glucose, 1 mM sodium pyruvate and 2 mM glutamine. Cells were plated at 1 × 105 cells per well in a 96-well Seahorse assay plate, pretreated with Cell-Tak (Corning). Cells were equilibrated to 37 °C for 30 min before assay. OCR (pmoles / min) and ECAR (mpH / min) were measured as indicated upon cell treatment with oligomycin (0.5 mM), FCCP (0.2 mM), rotenone (1 μM), and antimycin A (1 μM), according to the manufacturer’s instructions. Listeria monocytogenes infection. Transgenic Listeria monocytogenes expressing ovalbumin (Lm-Ova) was a gift from H. Shen. For infection, Lm-Ova was grown to early log phase (OD600 nm 0.1) in brain heart infusion media (Becton Dickinson), washed and diluted with sterile saline, and then inoculated intravenously (104 colony-forming units per mouse). Animals were harvested at 1 week post infection to measure the peak of the T cell effector response. qPCR. RNA was extracted using the Zymo Quick-RNA MicroPrep Kit without DNase I treatment according to the manufacturer’s protocol.1 μg of total RNA was reverse transcribed into cDNA using Thermo Maxima H Minus Reverse Transcriptase, 100 U per 20 µL reaction

[0045] 444894-1903-2290, v. 1 with 25 pmol each oligo (dT)18 and random hexamer primers. RT reaction was incubated for 10 min at 25 °C, 15 min at 50 °C, and then terminated by heating for 5 min at 85 °C. cDNA was diluted 1:10 before being used in RT-qPCR with PowerTrack SYBR Green Master Mix on a Bio-Rad CFX384 real-time qPCR system. Technical triplicates were quantified using 2- ΔCt normalized to Ube2d2a. Western Blot. Two million cells were lysed with 20-35 uL of radioimmunoprecipitation assay buffer (50 mM Tris, pH 8.0, 1 mM EDTA, 150 mM NaCl, 1% NP-40, 0.5% Na-deoxycholate, and 0.1% SDS) freshly supplemented with 10 mM NaF, 1 mM Na3VO4, and EDTA-free proteinase inhibitor cocktail Complete (Roche, no. 11836170001). Lysates were boiled for 5 min at 95°C with 6x Reducing Laemmli Sample Buffer (Boston BioProducts, BP-111R). Samples were loaded into Any kD Mini-PROTEAN TGX Stain-Free Protein Gels (Bio-Rad, 456-8126). Transfer was performed using the Trans-Blot Turbo Transfer System and Trans-Blot Turbo RTA Mini LF PVDF Transfer Kit. Membranes were blocked with 5% dry nonfat dairy milk in TBS-T (0.1%) for 30-60 min. Primary antibodies were incubated in TBS + 1% Casein overnight at 4°C with shaking. 3-5 washes of 3-10 min were performed before secondary antibodies were incubated in 5% milk in TBS-T for 30-60 min at room temperature with rocking. Washes were performed before membranes were visualized using SuperSignal West Pico PLUS or Femto Chemiluminescent Substrate and the ChemiDoc MP Imaging System. Liquid chromatography high resolution-mass spectrometry (LC-HRMS) and peak analysis. Following cell culture, cells were washed with PBS, pelleted, and flash frozen. Metabolomics extraction was done by cold methanol precipitation. Briefly: to the frozen cell pellet in an Eppendorf tube, two different aliquots of internal standard mixture were added (100 ng 13C5-NAD and 50 μL of 2.5 μM labeled amino acids, both from Cambridge Isotopes Laboratory) followed by 1 mL of cold 80% methanol (MeOH) and vortexed for 30 sec. Samples were pulse-sonicated in ice with a sonic dismembranator (Fisher Scientific, Waltham, MA) for 30 sec, incubated on ice for 10 min, and then pulsed again for 30 sec. Samples were pelleted by centrifugation at 6000 x g for 5 min at room temperature. The clear supernatant was moved to a new tube and dry down under nitrogen. Dry metabolites were re-suspended in100 μL of 5% MeOH with 0.1 % formic acid. The samples were spun down at 10, 000 x g for 10 min at 4°C and only the top 50 µL were transferred to a HPLC vial for LC-HRMS analysis. A pooled sample was created by mixing 10 µL of each re-suspended sample.2 µL injections were made on each of the LC-platforms.

[0046] 454894-1903-2290, v. 1 C18-Gold LC method. Metabolites were separated using a Thermo Hypersil Gold, 150 x 2.1 mm, 1.9 μm using the UltiMate 3000 quaternary UHPLC (Thermo Scientific, Waltham, MA) equipped with a refrigerated autosampler (6℃) and column heater (55℃). Solvent A was water with 0.1% formic acid and solvent B was methanol with 0.1% formic acid. The gradient was as follows: 0.5% B at 0 min, 0.5% B at 2 min, 50% B at 6 min, 100 % B at 12 min, 100 % B at 16 min, and back to 0.5 % B at 17 min and kept for 3 more min for column re-equilibration. The flow rate was 0.45 ml / min. The Q Exactive HF (QE-HF) (Thermo Scientific, Waltham, MA) equipped with a heated electro-spray ionization (HESI) source was operated in positive mode in full scan at 120,000 resolution, AGC target, 1e6; Maximum IT, 150 ms; scan range, 90 to 950 m / z. The QC samples were used for identification also, by doing the top 20 MS / MS spectral (dd-MS2) @ 15000 were generated with AGC target = 2e5, Maximum IT=25 ms, and (N)CE / stepped NCE = 20, 30, 40v. Metabolites detection and identification was as described in data analysis. The quantification was done from the full scan mode. The ion-pairing method was performed exactly as described Frederick et all (Frederick DW, Trefely S, Buas A, Goodspeed J, Singh J, Mesaros C, Baur JA, Snyder NW. Stable isotope labeling by essential nutrients in cell culture (SILEC) for accurate measurement of nicotinamide adenine dinucleotide metabolism. Analyst. 2017 Nov 20;142(23):4431-4437.) Control extraction blanks were made in the same way using just the solvents instead of the cell homogenate. The control blanks were used for the exclusion list with a threshold feature intensity set at 1e10^5. The pool sample was run every 10 samples. The coefficient of variation of less than 10% of the pooled sample was used to assess a robust signal. For data analysis, metabolites were identified based on the exact mass + / - 5 ppm and retention time similar with the authentic standards (Sigma Metabolomics Library). Peak integration was conducted using Xcalibur 4.2 (Thermo Fisher Scientific). Metabolites were identified based on the exact mass + / - 5 ppm and retention time similar with the authentic standards (Sigma Metabolomics Library). Peak integration was conducted using Xcalibur 4.2 (Thermo Fisher Scientific). MetaboAnalystR to process the peak values. Missing values were substituted with 1 / 5th of next smallest value in the original metabolic peak information. Data for the heat maps was then normalized by pooling the G4 (FIG. 1F) or vehicle (FIG. S7A) samples, log transformed (base 10), and auto scaled (mean centered and dived by the standard deviation). PCA and pathway analysis were further performed using MetaboAnalystR. Heatmaps were generated using normalized values and clustered using Ward’s method by calculating the Euclidean distance between metabolites. For the random forest analysis, the inventors first examined how all metabolites were able to predict

[0047] 464894-1903-2290, v. 1 affinity by using a machine learning model. Data for each sample underwent an 80 / 20 split so that 80% of the data would be used to train the model and the remaining 20% of the samples were used to test the model. Finally, a 5-fold cross validation of a random forest model was performed. Data analysis. MetaboAnalystR (world-wide-web at metaboanalyst.ca / ) was used to perform analysis of LC-HRMS results. Data was processed by substituting missing values with 1 / 5th of next smallest value in the original metabolic peak information. Zeroes were also replaced with half of the next smallest value in original metabolic peak info. Data was then normalized by pooling the G4 samples, log10 transforming the normalized results, and then auto scaled (mean centered and dived by the standard deviation). PCA and pathway analysis were further performed using MetaboAnalystR. Heatmaps were generated using normalized values and clustered using Ward’s method by calculating the Euclidean distance between metabolites. NAD Cycling Assay. All reagents used in this assay were obtained from Sigma. Cells were washed with PBS, pelleted, and flash frozen. Lysates were prepared with 0.6M perchloric acid at 4 degrees centigrade. Cleared acid extracts were collected after pelleting insoluble material at 4 degrees centigrade. In the plate wells, 4 µl of NAD standards or of diluted tissue acid extracts were combined with 100ul of cycling reaction reagent consisting of 2% ethanol, 100 ug / ml alcohol dehydrogenase, 10 ug / ml diaphorase, 20 µM resazurin, 10 µM flavin mononucleotide, 10 mM nicotinamide and 0.1% BSA in 100mM phosphate buffer, pH 8.0. The cycling reaction proceeded for 20 to 30 minutes while resorufin accumulation was measured with excitation at 544nm and the counting of emitted photons at 590nm. NADH FLIM. Fluorescence lifetime imaging microscopy of NADH autofluorescence (NADH FLIM) was performed on a LSM 710 (Zeiss) using a femtosecond-pulsed two-photon laser (Coherent) as described in (Schaefer et al., 2017). In brief, cells were mounted on the microscope in a four compartment CELLview cell culture dish with a thin glass bottom (cat. #627870, Greiner) in 500 μL Tyrodes solution (135 mM NaCl, 5 mM KCl, 1.8 mM CaCl2, 20 mM HEPES (2-[4-(2-hydroxyethyl)piperazin-1-yl]ethanesulfonic acid), 5 mM D-glucose, 1 mM MgCl2, and 1 mM L-glutamine.). The temperature was kept stable at 37°C. NADH was excited at 730nm (<5mW on the sample, 1min acquisition time) and the autofluorescence was detected through a 680 shortpass and 460 / 50 bandpass emission filter. Time-correlated single photon counting was performed using a HPM-100–40 detector and the SPCM 9.81 software (both Becker and Hickl). FLIM images were analyzed by SPCImage 8.0 using a biexponential decay with Ƭ1 and Ƭ2 being fixed to 400 and 2500 ps for free and protein bound NADH. The

[0048] 474894-1903-2290, v. 1 fixed lifetime components were used to reduce the number of photons required for a valid lifetime calculation. Nuclear NADH was quantified using ROIs, averaging a minimum of 5 cells per image section. Mitochondrial NADH was quantified using the threshold function of SPCImage and verified using ROIs for individual conditions. CAR T cell assays. Cryopreserved T cells were activated with Human T-Expander CD3 / CD28 Dynabeads (Gibco) at 3:1 beads:cell ratio with 100 U / mL recombinant human IL- 2 (BioLegend) in AIMV media (Gibco) supplemented with 5% FBS, 10mM HEPES, 2mM GlutaMAX (Gibco), 100 U / mL penicillin, and 100ug / mL streptomycin. T cells were transduced with HA.28z CAR containing virus 2 days post-activation (Lynn et al., 2019). At 15 days post-transduction, cells were challenged with 143b osteosarcoma target cells stably expressing firefly luciferase at a range of effector:target ratios. Cell killing capacity was evaluated by luceriferase release 24 hours after co-culture. Cell expansion capacity in re- challenged was quantified following 1:1 effector:target culture. Immunizations. WT C57.B6 / J mice were vaccinated with 30 µg PR8 HA mRNA-LNP vaccine, injected into the quadriceps. After 12 days, animals were euthanized and draining lymph nodes were harvested. Immediately following harvest, total lymph node cells were stained with anti-CD19 (Thermo) and HA tetramer probes and then NAD(P)H was quantified through flow cytometry analysis (Margine et al., 2013). Example 2 T-cell receptor ligand affinity coordinates the kinetics of cell cycle progression and anabolic programming in CD8 T-cells. The strength of the activating TCR signal is known to dictate cell cycle entry kinetics and impact differentiation, however the extent to which metabolic programming is similarly tuned by the TCR remains to be fully elucidated. To address this, the inventors took advantage of the OT-I TCR transgenic murine model, in which all T-cells encode a TCR with high affinity for the MHC-I restricted (H-2 Kb) peptide SIINFEKL (N4), with lower affinity peptide variants (e.g., SIIGFEKL, “G4”) having been well defined (FIG.1A) (Jameson et al., 1993; Hogquist et al., 1994; Rosette et al.,2001; Daniels et al., 2006; Rabinowitz et al., 1996). Consistent with previous findings, the inventors observe that stimulation of OT-I T-cells with the higher affinity N4 peptide results in more rapid cell cycle entry Myc stabilization, and proliferation compared to the lower affinity G4 peptide (FIGS. S1A-E) (Price et al., 2005; Ron-Harel et al., 2016; Daniels et al., 2006; Auphan-Anezin et al., 2003; Malherbe et al., 2004; Denton et al., 2011; Chang et al., 2013).

[0049] 484894-1903-2290, v. 1 The inventors then assayed whether the kinetics of downstream metabolic processes were similarly controlled by peptide affinity. To this end, they stimulated OT-I T-cells with either N4 or G4 peptide and measured rates of glycolysis and respiration both 24 hours after activation and immediately following introduction of peptide. At both time points, the inventors found that N4 stimulated cells more rapidly reached higher basal glycolytic and respiration rates than G4 stimulated cells (FIG. 1B and FIG. S1H). They then asked whether these differences in affinity-driven metabolism in turn control the corresponding rates of quiescence exit. To test this, the inventors restricted glucose availability in both N4 and G4 stimulated cells. N4 stimulated cells exhibited a marked impairment of cell cycle entry and Myc expression (FIGS.1C-D and FIGS. S1I- J). Unlike N4 stimulated cells, G4 stimulation in limiting glucose conditions resulted in a more marginal reduction in cell cycle frequency and Myc protein abundance in glucose restricted conditions (FIGS. 1C-D). Thus, the strength of TCR signal sets the rate and magnitude of anabolic metabolism commensurate to the rate of quiescence exit. Identification of a NAD as a central component of the TCR affinity-dependent metabolome. Given that the kinetics of ligand affinity driven quiescence exit depends on the scale of the metabolic response, the inventors hypothesized that specific TCR-dependent metabolic pathways are responsible for these TCR-dependent proliferation dynamics. Moreover, they sought to determine if certain metabolites act as central metabolic hubs, helping to coordinate the broader landscape of metabolic remodeling in activated T-cells. While the global metabolic differences between naive and activated T-cells have been characterized, the extent to which specific metabolites are tuned in a scalable, affinity-dependent manner is undefined (Tan et al., 2017; Yang et al., 2011, Geiger et al., 2016; Ma et al., 2019; Ron-Harel et al., 2019; Edwards-Hicks et al., 2020; Puleston et al., 2021). To this end, the inventors performed LC-MS on OT-I T-cells stimulated for 24 hours with an array of peptides with decreasing affinity – N4, Q4, T4, or G4 peptide. This time point was chosen to optimally capture metabolic changes associated with the kinetics of quiescence exit, as it minimized confounding differences in activation status between the highest (N4) and lowest (G4) affinity conditions, while still proceeding the first division for all peptide stimulations (FIG. S1B and FIG. S1G). Principal component analysis revealed that the global metabolite profile was sufficient to distinguish cells based on the affinity they were stimulated with, confirming that metabolic rewiring is a central feature of affinity-driven changes during T-cell activation (FIG. 1E). The inventors then performed hierarchical clustering and found that not all metabolites were equally responsive to peptide affinity (FIG. 1F). Whereas some metabolites showed no

[0050] 494894-1903-2290, v. 1 discernable trend in their response to affinity (Clusters 3 and 4), two clusters were dose sensitive to TCR signal strength, with one cluster increasing (Cluster 1) and the other decreasing with affinity (Cluster 2) (FIG.1F). Seeing this, the inventors wanted to further test the hypothesis that metabolic changes are a defining feature of TCR signal strength and asked whether a discrete set of molecules would be sufficient to predict affinity. To do so, the inventors performed a random forest analysis with a 5-fold cross validation of the data. When this model was built using all detected metabolites, they found it had a 91.6% prediction accuracy (Table S1). When building the model using specific clusters, the inventors found that Clusters 1 and 2 had 91.6% and 100% accuracy, respectively, indicating these subsets alone perform as well or better than the full list of metabolites (Table S1). In contrast, Clusters 3 and 4 performed worse compared to the model containing all metabolites (Table S1). Thus, a discrete set of metabolites defines affinity-driven biology. Having defined the TCR affinity-dependent metabolome, the inventors sought to identify the pathways these molecules were most associated with and determine whether any specific metabolites might play a central role in coordinating this network. For this reason, they focused their analysis on Cluster 1 – metabolites that accumulate with increasing affinity. To do so, the inventors performed targeted pathway analysis using Metaboanalyst and found metabolites in Cluster 1 matched significantly to 14 pathways (Table S2). Consistent with TCR affinity’s role in cell cycle entry kinetics, Cluster 1 was most enriched for metabolites involved in purine synthesis (Table S2). In addition to nucleotide synthesis, the citric acid cycle and the malate-aspartate shuttle were shown to be among the most enriched pathways, supporting prior studies on the role of these processes in proliferation of T-cells (Table S2) (Katsyuba & Auwerx, 2017). To begin addressing whether specific metabolites might play a central coordinating role in the larger affinity-dependent metabolome, the inventors ranked metabolites in Cluster 1 by the frequency with which they were involved across all identified pathways. This approach revealed that NAD was the most represented metabolite over all significantly enriched pathways (FIG. 1G). Beyond metabolites represented in the pathway analysis, the inventors further noted NMN (an NAD precursor) as well as metabolites such as orotate and lactate, which require NAD(H) as a coenzyme for their synthesis, were among the most affinity-sensitive metabolites identified (FIG. 1F). Altogether, this led us to hypothesize that NAD functions as a central, affinity-tuned metabolic hub that coordinates the broad biochemical changes in early T-cell activation. TCR signaling tunes the NAD salvage pathway to control single-cell NAD(P)H levels. To corroborate the inventors’ metabolomics findings, they first validated that TCR

[0051] 504894-1903-2290, v. 1 stimulation strength controls the accumulation of NAD using an enzymatic NAD cycling assay. Stimulation of OT-I T-cells with either higher peptide concentration or higher peptide affinity resulted in a dose-dependent increase in cellular NAD levels, following 24 hours of stimulation (FIG. 1H). They further find that while TCR engagement is absolutely required for enhanced NAD biosynthesis, CD28 stimulation is sufficient to further enhance cellular NAD levels, while exogenous IL-2 had no impact (FIG. S2A). As NAD exists in either an oxidized (NAD+) or reduced (NADH) form, the inventors next investigated whether T-cell activation-induced NAD accumulation was due to a shift in the redox balance or an absolute increase in NAD. To assay this, they measured NAD and NADH in polyclonal CD8 T-cells activated for 24 hours with a range of anti-CD3 concentration. They observed that TCR stimulation dose dependently induces both species, indicating that an absolute increase in total NAD(H) was required rather than purely changes in cellular redox state (FIG. S2B). The inventors next sought to determine which NAD biosynthesis pathways are engaged following TCR stimulation. NAD is made in cells by 3 primary pathways: De novo from tryptophan, the Preiss Handler pathway from nicotinic acid (NA), or the NAD Salvage Pathway from nicotinamide (NAM) (FIG.1I) (Yoshino et al., 2018). The inventors performed targeted mass spectrometry to detect metabolites from each pathway and found that only NAD Salvage Pathway metabolites increased dose-dependently in response to TCR stimulation (FIG. S2C). In keeping with this and prior reports, pharmacological inhibition of the NAD Salvage Pathway with FK866, an inhibitor of the rate limiting enzyme (NAMPT) prevented the accumulation of cellular NAD following activation (FIG.1J) (Wang et al., 2021; Rongvaux et al., 2008). To more formally assay whether T-cells rely solely on the Salvage Pathway for NAD biosynthesis, the inventors attempted to rescue FK866 treatment by supplementing media with tryptophan (De Novo), NA (Preiss Handler), or nicotinamide riboside (NR), which bypasses FK866 by supporting NMN synthesis in an NAMPT-independent manner (FIG.1I) (Yoshino et al., 2018, Quinn, 3rd et al., 2020). They observed that only the NAD Salvage Pathway precursor NR was able to rescue NAD levels in the presence of FK866 (FIG.1K). Finally, as NAMPT expression has been shown to be sensitive to T-cell activation, the inventors tested whether this is regulated in a signal strength-dependent manner (Rongvaux et al., 2008). They determined that while both TCR and co-stimulation dose-dependently controlled Nampt transcript levels, TCR signaling was necessary and sufficient for increasing NAMPT protein (Fig1L, FIGS. S2D-E). Together, these data support a model in which TCR stimulation promotes NAD biosynthesis through the NAD Salvage Pathway.

[0052] 514894-1903-2290, v. 1 While the inventors had observed a clear connection between TCR signal strength and cellular NAD(H) abundance at the population level, the assays described thus far require bulk analysis of T-cells. These approaches are thus unable to resolve how differences in anabolic state, cell size, and activation status might explain the observed changes in cellular NAD(H) levels, as all these properties are also controlled by the strength of T-cell signaling. To assay whether ligand affinity tunes cellular NAD(H) independent of these confounding factors, the inventors reasoned that since NAD and NADH proportionally increase in a TCR-dependent manner they could take advantage of the autofluorescent properties of NADH (ex: 375nm, em: 450nm) and interrogate cellular NAD(H) at the single cell level by flow cytometry. Given that NADPH has near identical autofluorescent properties as NADH, the inventors pharmacologically determined the NADH specific component of the NAD(P)H autofluorescence and confirmed that it indeed represented the majority of the TCR-induced signal (FIG. S2F). They next tested whether the per cell abundance of NAD(P)H scaled with ligand concentration and / or affinity. The inventors observed that NAD(P)H MFI dose- dependently increased over a range of peptide concentrations and was dependent on affinity, even when controlling for activation status (CD69 expression), size, or Myc expression (FIG. 1M and FIGS. S2G-H). Altogether, these findings indicate that TCR signal strength tunes cellular NAD(H) in an analog manner, independent of activation status, cell size, or the expression of Myc. Cellular NAD levels pace early cell cycle kinetics to control affinity-driven T-cell expansion dynamics. Activated T-cells have been shown to be sensitive to pharmacological NAMPT inhibition and conditional loss of Nampt disrupts thymocyte development, however the requirement for CD8 T-cell Nampt expression during an adaptive immune response is unknown (Bruzzone et al., 2009; Wang et al., 2021; Rongvaux et al., 2008; Drijvers et al., 2021; Gerner et al., 2020; Carbone et al., 1992). To confirm that NAD biosynthesis plays a biologically relevant role in a peripheral CD8 T cell response, the inventors crossed Namptfl / fl mice to CD8 -Cre, OT-I mice, resulting in peripheral CD8 T-cell-specific NAD Salvage Pathway deficient animals (FIG. S3A) (Drijvers et al., 2021). They adoptively transferred either WT or Nampt-deficient OT-I T-cells into WT recipients and then infected those animals with transgenic Listeria monocytogenes expressing ovalbumin (Lm-Ova). The inventors found that while WT OT-I T-cells expanded as expected 8 days post-infection, Nampt deficient cells failed to do so, indicating NAD biosynthesis is required for the in vivo expansion of activated T cells (FIG. 2A). Suggesting that NAMPT is required specifically in activated T cells, they

[0053] 524894-1903-2290, v. 1 found an equivalent percentage of circulating OT-I T cells between naïve WT and Nampt- deficient donor animals (FIG. S3B). To begin testing their hypothesis that NAD biosynthesis acts as a metabolic conduit for TCR affinity, the inventors asked whether globally enhancing NAD biosynthesis capacity in CD8 T-cells is sufficient to permit expansion of lower affinity T-cell clones during a polyclonal response. They thus bred mice expressing a Cre-dependent conditional Nampt overexpression transgene to CD8a-Cre animals (NamptTg) (Bailis et al., 2019). CD8 T-cells in these mice express higher basal levels of Nampt, uncoupling NAD Salvage Pathway regulation from TCR affinity (FIG. S3C). The inventors then infected NamptTg animals with Lm-Ova and measured the affinity and number of responding clones to SIINFEKL loaded H2-Kb tetramer. They found that responding clones in NamptTg mice displayed a lower normalized tetramer MFI than WT controls, suggesting that the affinity of the polyclonal response was diminished (FIG. 2B). Strikingly, the inventors found that despite NamptTg animals displaying a lower affinity response, both transgenic and WT mice had the same number of SIIFNEKL-reactive T-cells, indicating that enhancing NAD biosynthesis is sufficient to permit equitable expansion of lower affinity clones (FIG. 2C). Consistent with the inventors’ hypothesis, these data demonstrate that NAD biosynthesis is a metabolic mediator of TCR affinity-driven clonal dynamics. The data this far supports a model in which TCR affinity tunes cellular NAD levels in activated T-cells and that the NAD biosynthesis capacity of those cells modulates their ability to expand in vivo. The inventors next sought to understand the mechanism for how NAD biosynthesis controls the complex cell biology downstream of the TCR. Given cellular metabolic requirements change throughout the course of T-cell activation, they first asked whether NAD biosynthesis was required throughout T cell activation or if its role was restricted to a specific stage, (Solouki et al., 2020; Guy et al., 2013; Geiger et al., 2016; Katsyuba & Auwerx, 2017). To this end, the inventors treated activated CD8 T-cells with the NAMPT inhibitor FK866 for 48 hours, starting either at the time of TCR stimulation (day 0) or after quiescence exit, starting 2 days post-activation (FIG. 2D). They then measured viability, proliferation, and cell cycle status in each of these treatment windows. The inventors observed that cells were most sensitive to NAMPT inhibition prior to cell cycle entry (days 0-2); however, cells rapidly became insensitive to NAD biosynthesis inhibition following quiescence exit (days 2-4) (FIG. 2E and FIGS. S4A-B). To more fully elucidate the time- dependent requirements for NAD biosynthesis throughout CD8 T-cell activation, the inventors treated activated cells with a rolling 24-hour window of FK866 treatment at each day of cell

[0054] 534894-1903-2290, v. 1 culture starting at the time of activation and then evaluated cell cycle, proliferation, and Myc expression by flow cytometry the following day (FIG. 2F and FIGS. S4C-D). The inventors once again observed that cells displayed a heightened sensitivity to FK866 treatment when cells were still exiting quiescence, however this sensitivity was lost once the majority of cells were fully in the cell cycle (FIG. 2F). Suggesting that this difference was not simply due to differences in NAD levels at the time of analysis, the inventors found that NAD levels reach the limit of detection in cells treated with FK866 at both ends of the rolling window (day 0-1 and 4-5) (FIG. S4E). Together, these data suggested that quiescence exit has a uniquely high biochemical requirement for NAD biosynthesis that diminishes over the course of activation. The inventors next asked whether the change in requirement for the NAD Salvage Pathway throughout activation result from differential metabolic demands for NAD biosynthesis before and after quiescence exit. They first tested whether they could observe global differences in NAD utilization in early versus late activated CD8 T-cells using NAD(P)H fluorescence lifetime imaging microscopy (FLIM). In addition to fluorescence intensity, the fluorescence lifetime data provides information about the free (shorter lifetime) and protein bound (longer lifetime) ratio of NAD(P)H in the cell. The inventors treated activated CD8 T-cells with FK866 from the time of activation through day 1 or starting day 3 until day 4. They then measured the lifetime of NAD(P)H fluorescence in both the mitochondria and cytosol / nucleus, to evaluate how inhibiting the NAD Salvage pathway alters the availability of free (non-enzyme bound) NADH. The inventors observed that loss of NAD biosynthesis had a greater impact on fluorescence lifetime in early activated CD8 T-cells than later stage cells, indicating recently activated T-cells have a heightened requirement for NAD biosynthesis to maintain proper NAD(H) utilization throughout the cell (FIG.2G). As NAD acts as a metabolic coenzyme both for mitochondrial respiration as well as glycolysis, the inventors tested whether these two processes were differentially sensitive to NAD Salvage Pathway inhibition at the time of activation and shortly after. They treated activated CD8 T-cells with FK866 from day 0-1 post activation or from days 1-2 and then performed Seahorse analysis. The inventors found that FK866 treatment from day 0-1 resulted in a marked impairment of CD8 T-cell glycolysis (FIG. 2H and FIG. S4F). In stark contrast, FK866 treatment of T-cells after from days 1-2 resulted in no detectable differences in the rate of glycolysis. Similarly, FK866 treatment from day 0-1 almost completely abrogated mitochondrial respiration, whereas basal OCR was only marginally affected when NAD biosynthesis was inhibited starting at day 1, with spare respiratory capacity showing some sensitivity (FIG.2H and FIGS. S2G-H). These data suggest that CD8 T-cells have a heightened

[0055] 544894-1903-2290, v. 1 requirement for NAD biosynthesis to support glycolysis and mitochondrial respiration as they enter the cell cycle, which is lost shortly after. TCR signal strength is understood to control the rate of cell cycle entry and progression during the early stages of activation. The data thus far demonstrate that the magnitude of TCR signaling results in a commensurate induction of NAD biosynthesis that is required as these cells are exiting quiescence. The inventors therefore asked whether the degree of NAD biosynthesis downstream of a given TCR affinity played a direct role in regulating the cell cycle rates of those cells. To do so, they activated OT-I T-cells with either N4 or G4 peptide in the presence of FK866 and titrated NR at the time of stimulation. In the presence of FK866, NAM cannot be recycled back to NMN, leaving NMN synthesis entirely reliant on the amount of NR available in the media, enabling us to control the NAD biosynthesis capacity in these cells (FIG.2I). Using this approach, the inventors assessed how cellular NAD levels impacted T-cell expansion, viability, and cell cycle kinetics after stimulation with high and low affinity peptide. For both N4 and G4 peptides, they found that the number of T-cells generated was proportionately controlled by the concentration of NR in the culture (FIG. S5B). While the inventors also observed that NAD biosynthesis capacity-controlled T-cell viability over time, there was no effect on cell survival within the first 36 hours, which allowed us to assess the interaction of NAD with the cell cycle within this window (FIG. S5C). They found that NAD biosynthesis capacity sets the kinetics of G1-entry, G2 progression, and the time to the first division downstream of a given TCR signal strength (FIG. 2J and FIGS. S5D-F). Moreover, the inventors saw that T-cells stimulated by high and low affinity ligands displayed differential sensitivity to diminished NAD biosynthesis capacity. Whereas N4 stimulated cell proliferation at 56 hours was impaired at intermediate NR doses, G4 stimulated cells were only marginally affected at the same NR concentrations (FIG. S5G). Similar to the increased glucose requirement in higher affinity CD8 T cells (FIGS. 1C-D), these data suggest that TCR signal strength sets the cellular demand for the NAD Salvage Pathway required to sustain cell cycle kinetics downstream of a given ligand affinity. Combined, these data demonstrate that NAD biosynthesis capacity dictates the rate of quiescence exit and cell cycle progression to control expansion dynamics in activated T-cells, within the bounds set by the corresponding strength of signaling. As T-cell cell cycle entry is understood to be controlled by mTORC1 signaling and Myc expression, and central carbon metabolism, the inventors next aimed to test whether NAD biosynthesis might modulate these key anabolic regulators. To test this, they activated OT-I T- cells in the presence of FK866 and titrated doses of NR and measured mTORC1 activity and

[0056] 554894-1903-2290, v. 1 Myc protein levels by flow cytometry. The inventors observed that the phosphorylation of the mTORC1 substrate S6 as well as the kinetics of and amplitude of Myc expression were dose dependently sensitive to NR supplementation, suggesting that NAD biosynthesis capacity is limiting for both factors (FIG. 2K and FIG. S5H). The inventors next tested whether cellular NAD levels also control the metabolic capacity of these cells. They thus performed Seahorse analysis on CD8 T-cells activated in the presence of FK866 and titrated doses of NR for 24 hours. They found that NAD biosynthesis capacity dose-dependently controlled the rates of both glycolysis and mitochondrial respiration (FIG. 2L). Altogether, these findings support a model in which ligand affinity determines the NAD biosynthesis capacity of a T-cell and cellular NAD levels in turn govern the magnitude of the corresponding affinity-driven anabolic growth program. NAD biosynthesis governs a quiescence exit checkpoint in activated CD8 T-cells. The data indicated that the magnitude of NAD biosynthesis controls T-cell expansion dynamics and that T cells undergoing quiescence exit display the greatest requirement for the NAD Salvage Pathway. The inventors next asked whether the cell cycle entry arrest exhibited following NAD Salvage Pathway inhibition represented a reversable checkpoint-like phenomena or an irreversible process such as senescence and / or cell death. They thus assayed whether cells unable to undergo NAD biosynthesis at the time of activation could undergo quiescence exit if the NAD Salvage Pathway were restored in a delayed manner. To do so, the inventors activated OT-I T-cells with N4 peptide in the presence of FK866 for 24 hours and then acutely supplemented their media with NR (FIG.3A). They then evaluated the rate these cells entered the cell cycle following NR supplementation. As a control, they also assayed T- cell viability and activation prior to NR supplementation and observed no differences in FK866 treated compared to vehicle treated cells, despite the failure of FK866 treated cells to enter G1 (FIG. S5C, FIGS. S6A-B). The inventors found that delayed NR supplementation resulted in a rapid recovery of G1 entry, with the frequency of G1 cells continuing to increase back to what was observed in untreated control (FIG. 3B). Following this initial NR treatment period, they observed these “rescued” cells were then able to successfully proliferate, with nearly 100% of cells having divided 24 hours later in the N4 stimulated cells (FIG. S6D). These data indicate that NAD biosynthesis is necessary and sufficient for activated T-cell quiescence exit and the block in cell cycle entry observed upon NAD Salvage Pathway inhibition is indeed reversible. Using the delayed NAD rescue assay, the inventors next sought to test if the cell cycle kinetics set by a given TCR affinity were truly dependent on the corresponding magnitude of NAD biosynthesis generated downstream. To test this, they repeated the delayed rescue

[0057] 564894-1903-2290, v. 1 experiment in cells stimulated with either N4 or G4 peptide and treated cultures with either a low (0.1 M) or high (100 M) dose of NR at the time of rescue. The inventors then assayed the rate of cell cycle entry and Myc protein levels. They found G4 stimulated cells were similarly able to exit quiescence and elevate Myc protein expression, however they did so with a less rapid recovery kinetic than N4 stimulated cells (FIGS. 3C-E). Consistent with NAD biosynthesis being a rate-limiting factor for affinity-dependent differences in cell cycle kinetics, the inventors found that N4 stimulated cells could be induced to recover cell cycle entry and Myc protein expression at rates comparable to G4 stimulated cells when their NAD biosynthesis capacity was limited (FIGS. 3C-E). Thus, TCR affinity determines the levels of cellular NAD a T-cell will generate early in activation and this in turn paces the rate of quiescence exit downstream of that signal strength. T-cell quiescence exit is known to require mTOR activity (Verbist et al., 2016; Yang et al., 2013; Sinclair et al., 2019). The inventors next asked whether mTOR signaling was likewise essential for the NAD-dependent cell cycle entry they had observed. To address this, the inventors first assayed whether delayed NAD rescue results in the acute recovery of mTOR signaling. Similar to cell cycle entry and Myc expression, they observed that S6 phosphorylation was quickly restored after delayed NAD rescue, suggesting NAD biosynthesis is also necessary and sufficient for mTOR signaling during cell cycle entry (FIG. S6E). To test if mTOR activity was in turn required for this NAD-dependent quiescence exit checkpoint, the inventors performed the delayed NAD rescue assay as above, but treating cells with vehicle control or Torin for 15 minutes prior to NR supplementation. They found that Torin treatment resulted in minimal impact on the rate of G1 entry following delayed NAD rescue compared to control samples, while only partially abrogating Myc protein expression (FIGS. S6F-H). These results indicate that while mTOR signaling is required for optimal proliferation and Myc expression, reengagement of mTOR activity does not fully explain the effects of how NAD biosynthesis controls quiescence exit. Having found mTOR signaling was not essential for this NAD biosynthesis quiescence exit checkpoint, the inventors hypothesized that once activation has occurred, NAD might regulate quiescence exit independent of mitogenic signaling. They thus asked whether NAD- dependent quiescence exit required sustained TCR and costimulatory signaling or could occur in the absence of TCR engagement and costimulation once cells have already been activated. To test this, they activated polyclonal CD8 T-cells with plate-bound anti-CD3e and anti-CD28 antibody in the presence or absence of FK866 for 24 hours. The inventors then removed the cells antibody-coated plates and onto fresh, uncoated plates that they subsequently

[0058] 574894-1903-2290, v. 1 supplemented with NR (FIG. S6I). Regardless of whether T-cells received continuous stimulation or removed activating signals, the inventors observed that NR supplementation restored proliferative capacity and Myc expression to comparable levels (FIGS. S6J-L). Altogether, these data demonstrate that mitogenic signals poise T-cells for cell cycle entry and dictate the maximal rate for this response, however quiescence exit cannot occur until T-cells overcome an NAD biosynthesis-dependent checkpoint. Thus activated T-cell NAD levels are set in an affinity-dependent manner, after which T-cells undergo a cell cycle regulatory “hand- off” in which quiescence exit becomes NAD biosynthesis-dependent and signaling- independent after this initial patterning. NAD biosynthesis governs the rates of glycolysis and respiration to control quiescence exit. The coincidence of an NAD-dependent requirement for cell cycle entry and sustaining energetics during early CD8 T-cell activation led us to hypothesize these two processes were connected. In keeping with this, metabolic processes including glycolysis, the citric acid cycle, and oxidative phosphorylation, are known to regulate cell cycle progression in activated T-cells (Solouki et al., 2020; Guy et al., 2013; Geiger et al., 2016, Katsyuba & Auwerx, 2017). Having seen that the rate of glycolysis and mitochondrial respiration are markedly affected after inhibition of the NAD Salvage Pathway in early activated cells, the inventors first tested whether these cells directly engage these metabolic processes during the delayed NAD rescue assay. They activated OT-I T-cells for 20 hours in the presence of FK866 and subsequently measured ECAR and OCR before and after NR supplementation in a Seahorse analyzer configured to release NR into the culture wells. The inventors observed a rapid increase in both ECAR and OCR within 5 minutes of NR addition, with both readouts continuing to rise over the course of the assay, confirming that NAD biosynthesis limiting for and acutely required for glycolysis and respiration (FIG.3F). As NAD(H) regulates a large number of biochemical pathways beyond glycolysis and respiration, the inventors next aimed to more globally characterize the NAD(H)-dependent pathways engaged during T-cell quiescence exit. To do so, they performed mass-spectrometry on OT-I T-cells at 0, 30, 120 and 240 minutes post-delayed NR treatment. Validating the delayed NAD rescue assay and this approach, the inventors saw that FK866 resulted in a striking depletion of cellular NAD levels that rapidly increase throughout the assay (FIG. S7A). In turn, this loss and recovery of cellular NAD had broad and differential effects on amino acids, nucleic acids, and metabolites in central carbon metabolism (FIG. S7A). To more formally test the inventors’ hypothesis that NAD operates as a central metabolic hub for affinity, they evaluated the extent to which metabolites in the affinity-dependent metabolome

[0059] 584894-1903-2290, v. 1 (Clusters 1 and 2) exhibited features of being NAD biosynthesis dependent (FIG. 1F). They found that the majority of detected metabolites in Cluster 1 and 2 were sensitive to NAD biosynthesis inhibition, with over 50% of metabolites in both clusters reversing that trend at some point within the 4 hours post NR rescue, indicating these metabolites are more directly dependent on cellular NAD levels (FIG. 3G). Thus, NAD biosynthesis plays a critical role in orchestrating the remodeling of the broader affinity-driven metabolome. Among the most striking NAD-dependent changes, the inventors observed that glycolysis was markedly sensitive during the delayed NAD rescue assay (FIG.3H). They found that FK866 treatment resulted in a buildup of metabolites in glycolysis prior to the GAPDH step and a depletion of metabolites immediately after. Reciprocally, this block was reversed immediately following NR supplementation and thereafter (FIG.3H). These data suggest that NAD biosynthesis is required to support the rapid increase in glycolysis during early T-cell activation via GAPDH. Whereas GADPH reduces NAD to NADH, the NADH oxidizing activity by LDH is understood to help recover NAD in highly glycolytic cells, as free NAD can become rate limiting for glycolysis when GAPDH activity is elevated. The inventors observed that FK866 treatment had minimal effects on lactate and pyruvate levels, but that lactate quickly accumulated after NR supplementation with pyruvate trending down over time, confirming that glycolysis is rapidly engaged after the NAD Salvage Pathway is restored (FIG. 3H). Together, these data suggest that NAD(H) levels are limiting early during CD8 T-cell activation and that NAD biosynthesis is required to sustain the high rate of GAPDH activity in these cells. While LDH activity may help recover free NAD to support this high glycolytic rate, it cannot restore redox balance sufficient for GAPDH in the absence of the NAD Salvage Pathway. The findings thus far led us to hypothesize that affinity-dependent NAD biosynthesis controls quiescence exit kinetics through its regulation of the rate of glycolysis and respiration. To begin testing this, the inventors revisited the impact glucose restriction has on cell cycle entry during T-cell activation (FIGS. S1H-I). They asked if delayed glucose supplementation could rescue quiescence exit in those conditions and in turn whether NAD biosynthesis governs the rate this occurs. The inventors therefore activated T-cells in low glucose (0.03 mM) conditions in the presence or absence of FK866. After 24 hours, cells were treated with 10 mM glucose and either rescued with NR or left in FK866 without supplementation (FIG. 3I). The inventors then tracked cell cycle entry over the following 6 hours (FIG. 3J). They found that while delayed glucose supplementation was sufficient to rapidly induce cell cycle entry and Myc expression, this was entirely dependent on the NAD biosynthesis capacity of the cells

[0060] 594894-1903-2290, v. 1 (FIGS. 3J-K). Thus, while glucose availability is necessary for cell cycle entry, it is not sufficient, as NAD biosynthesis is required for glucose utilization during quiescence exit. As NAD(H) has roles beyond its activity as a coenzyme, the inventors next sought to test the null hypothesis that rather than acting through central carbon metabolism, NAD biosynthesis primarily supports quiescence exit through its role as a substrate for NAD consuming enzymes (i.e., Sirtuins, PARP’s, and CD38) (52, 53). To demonstrate that these NAD consumption pathways are engaged in activated CD8 T-cells, treatment with pan-Sirtuin, pan-PARP, or CD38 inhibitors markedly enhanced NAD half-life (FIG. S7B). To functionally test the relative contribution of NAD’s role as a coenzyme and substrate to the NAD-dependent quiescence exit checkpoint. The inventors cultured N4 stimulated OT-I T-cells in the presence of FK866 for 20 hours and then treated these cells with either 2-deoxyglucose (2DG), oligomycin, or inhibitors of Sirtuins, PARPs, or CD38 for 15 minutes prior to NR supplementation (FIG. 3L). Whereas inhibitors targeting NAD consuming enzymes had minimal effect on cell cycle entry, the inventors found that treatment with either 2DG or oligomycin abrogated quiescence exit following their delayed NAD rescue assay (FIG. 3M, FIG. S7C). Thus, NAD most likely supports quiescence exit through its role as a coenzyme in central carbon metabolism, rather than acting as a substrate for consuming enzymes. The inventors next asked whether glycolysis and respiration were similarly required for the induction of Myc protein expression after delayed NAD rescue. They observed that while both 2DG and oligomycin abrogated Myc protein expression after NR supplementation, inhibition of glycolysis had a greater impact Myc protein expression following restoration of NAD biosynthesis (FIG.3N). These data indicate NAD biosynthesis licenses cells to pass through a quiescence exit checkpoint downstream of its role as a rate limiting factor in central carbon metabolism. Once cells have cleared this checkpoint and entered the cell cycle, the inventors further find their reliance on NAD biosynthesis starkly decreases, highlighting the distinct biochemical requirements at the time of cell cycle entry. Altogether, these data support a model in which the expression of metabolite transporters leads to the accumulation of carbon sources early in T-cell activation, however cells cannot exit quiescence until they have synthesized sufficient NAD to fuel themselves for the energetic and synthetic demands of division. As the magnitude of NAD biosynthesis is proportional to ligand affinity, NAD functions as a metabolic conduit for TCR signal strength in controlling T-cell expansion dynamics. Single-cell differences in NAD(P)H underly heterogeneity in lymphocyte proliferative responses. Thus far, the findings illustrate how TCR signal strength tunes

[0061] 604894-1903-2290, v. 1 cellular NAD levels in CD8 T-cells and licenses the biochemical remodeling required for quiescence exit. While this was found at the population level, the inventors’ NAD(P)H flow cytometry results show a broad distribution in NAD levels amongst individual T-cells responding to the same stimuli. Given that proliferation rates are not uniform across populations of identically stimulated CD8 T-cells, the inventors hypothesized that differences in single-cell NAD(H) levels were underlying this heterogeneity. To test this, they developed a flow cytometry sorting strategy that enabled us to unmix populations of cells based on their cellular NAD(P)H and then return them to culture. Using this approach, the inventors ensured that all sorted cells were activated (CD69+) and had not undergone their first cell division (CTY) (FIG. 7A). Consistent with the inventors’ findings that NAD levels support T-cell metabolic potential, 24 hours post sort, NAD(P)H high cells exhibited higher rates of glycolysis and oxygen consumption (FIG. 7B) The inventors then asked whether sorting activated CD8 T-cells based on NAD(P)H would be sufficient to predict subsequent T-cell cycle and proliferation kinetics. They thus sorted cells based on quartiles of cellular NAD(P)H and found that the magnitude of early cellular NAD(P)H was predictive of the future rate that CD8 T- cells exited quiescence, progressed through the cell cycle as early as 12 hours post-sort (FIG. 7C). Looking shortly after at 24 hours post-sort, the inventors found initial cellular NAD(P)H levels not only predicted the rate CD8 T cells underwent their first division, but also their early proliferative potential, with the number of divisions proportional to NAD(P)H levels at the time of sort (FIG. 7D). As the acquisition of effector function is known to be tightly coupled to proliferative capacity, the inventors next asked whether pre-division NAD(P)H was predictive of cytokine production early in the response. Consistent with cell division kinetics, they found observed that initial cellular NAD(P)H levels were capable of identifying CD8 T- cells that rapidly begin to produce cytokine, with NAD(P)H high cells producing more IFNγ and TNFα overall and particularly at the latest divisions (FIGS. 7E-F, FIGS. S8A-B). Consistent with this, the inventors observed that NAD(P)H high sorted cells displayed greater overall polyfunctionality compared to NAD(P)H low cells. Thus, early differences in single- cell metabolism are deterministic of the proliferative dynamics from a population of activated cells. This metabolic feature can further be used to isolate cells with discrete characteristics from an otherwise heterogenous pool. Having seen that cellular NAD(P)H could underly heterogeneity in the response to a single peptide ligand, the inventors next asked whether differences in single-cell NAD(P)H could help explain the differences in proliferative potential between high and low affinity ligand stimulated cells. To address this, they stimulated CD45.1 or CD45.2 OT-I T-cells with

[0062] 614894-1903-2290, v. 1 either N4 or T4 peptide, respectively (FIG.7G). Congenic markers were used so the inventors could separately activate each group of cells and then combine them at the time of sort so NAD(P)H levels could be gated on at the same time for both N4 and T4 stimulated cells, to control for fluctuations in NAD(P)H during the sorting procedure. In this manner, they were able to normalize cellular NAD(P)H across populations of cells activated with different ligand affinities. As expected, the inventors observed that unsorted N4 stimulated OT-I T-cells proliferated to a greater extent than T4 stimulated cells (FIG. 7H). In contrast, when cellular NAD(P)H levels were normalized across activating conditions, they found that both N4 and T4 stimulated cells proliferated to the same extent post-sort (FIG. 7H). Altogether, these data indicate that CD8 T-cell activation generates a continuum of single-cell NAD(P)H levels, with increasing ligand affinity resulting in a broader distribution and a higher median. While low and high affinity stimulated T-cells are phenotypically distinct at the population level, the inventors find that initial differences in single-cell NAD(P)H are sufficient to explain heterogeneity in proliferative potential across ligand affinities. Antigen receptor ligand affinity control of cell expansion dynamics is not unique to CD8 T-cells and is a shared feature with CD4 T-cells and B lymphocytes. The inventors therefore asked if the relationship they observed between CD8 T-cell ligand affinity, NAD biosynthesis, and cell cycle kinetics was conserved in these other lymphocyte populations. The inventors first aimed to determine if antigen receptor stimulation strength similarly sets cellular NAD levels in activated CD4 T and B cells. To do so, they stimulated CD4 T-cells and B cells with titrated amounts of anti-CD3 or anti-IgM, respectively, and then measured NAD levels following 1 day of stimulation. Similar to CD8 T-cells, antigen receptor signaling drove a dose- dependent increase of cellular NAD (FIGS. S8C and S8F). In addition to antigen receptor stimulation, B cells also exit quiescence following TLR stimulation, raising the possibility that NAD biosynthesis plays a role in response to a broad range of mitogenic signals. The inventors therefore stimulated B cells with titrated concentrations of LPS and measured NAD in these cells. As with BCR stimulation, increasing TLR stimulation was able to drive a dose-dependent increase in cellular NAD levels (FIG. S8G). They next asked whether the NAD Salvage Pathway was similarly required for cell cycle entry in CD4 T-cell and B lymphocytes. To test this, the inventors activated CD4 T-cells and B cells in the presence of FK866 and measured cell cycle status 1-day post-activation. They found that FK866 treatment abrogated G1 entry and Myc expression in CD4 T and B cells, suggesting NAD biosynthesis is a general requirement for lymphocyte quiescence exit (FIGS. S8D-E and S8H-I). Finally, the inventors aimed to determine whether differences in single-cell, pre-division cellular NAD(P)H levels

[0063] 624894-1903-2290, v. 1 could help explain heterogeneity in CD4 T and B cell proliferative responses after activation. They thus sorted activated B and CD4 T lymphocytes into NAD(P)H high and low populations, 24 hours post stimulation. Consistent with CD8 T-cell results, the inventors observed that higher pre-division NAD(P)H levels predicted faster rates through the cell cycle and time to the first division (FIGS.7I-J). Altogether, these data indicate that mitogen-driven NAD biosynthesis is a conserved feature of lymphocyte activation that regulates the rate of quiescence exit, cell cycle progression, and cell division. In turn, this distribution of single-cell NAD levels in a population of activated lymphocytes underlies the heterogeneity observed in T and B cell proliferative responses. These findings provide a new metabolic framework to explain how ligand affinity and signal strength dictate clonal lymphocyte dynamics. The inventors believe that this offers one of the first comprehensive models for how mitogenic signaling coordinates cell cycle progression via a single metabolite. These data illustrate how canonical signaling networks must work in concert with metabolic reprogramming to ensure that a newly deployed cellular program can be supported by a cell’s biochemical state. Thus, while signaling sets the limits of cellular function, single-cell differences in metabolism govern their behavior. This paradigm suggests that other aspects of cellular metabolism might similarly contribute to heterogeneity in other developmental processes and might be leveraged to rapidly identify cells with desired functional properties for cellular engineering or cell-based therapies.

[0064] 634894-1903-2290, v. 1

[0065] 4894-1903-2290, v.1 Supplementary Table 2

[0066] 654894-1903-2290, v. 1

[0067] * * * * * * * * * * * * * * * * * All of the compositions and methods disclosed and claimed herein can be made and executed without undue experimentation in light of the present disclosure. While the compositions and methods of this disclosure have been described in terms of particular embodiments, it will be apparent to those of skill in the art that variations may be applied to the compositions and methods and in the steps or in the sequence of steps of the method described herein without departing from the concept, spirit and scope of the disclosure. More specifically, it will be apparent that certain agents which are both chemically and physiologically related may be substituted for the agents described herein while the same or similar results would be achieved. All such similar substitutes and modifications apparent to those skilled in the art are deemed to be within the spirit, scope and concept of the disclosure as defined by the appended claims.

[0068] 664894-1903-2290, v. 1 VI. References The following references, to the extent that they provide exemplary procedural or other details supplementary to those set forth herein, are specifically incorporated herein by reference. Chapman et al., Nature Reviews Immunology 201920:120, 55-70 (2019). Geltink et al., annurev-immunol-042617-05301936, 461-488 (2018). Heinzel et al., Current Opinion in Immunology 51, 32-38 (2018). Allison et al., eLife 5, (2016). Conley et al., Journal of immunology (Baltimore, Md. : 1950) 205, 335-345 (2020). Gallagher et al., Proceedings of the National Academy of Sciences of the United States of America 118, e2025825118-e2025825118 (2021). Gett et al., Nature immunology 4, 355-360 (2003). Man et al., Nature immunology 14, 1155-1165 (2013). Price et al., The Journal of experimental medicine 202, 1349-1361 (2005). Richard et al., Nature Immunology 201819:819, 849-858 (2018). Solouki et al., J Immunol 205, 1217-1227 (2020). Finlay et al., J Exp Med 209, 2441-2453 (2012). Guy et al., Nat Immunol 14, 262-270 (2013). Heinzel et al., Nat Immunol 18, 96-103 (2017). Hukelmann et al., Nat Immunol 17, 104-112 (2016). Lynn et al., Nature 576(7786):293-300 (2019). Marchingo et al., eLife 9, (2020). Margine et al., J. Vis. Exp.6(81):e51112 (2013). Pollizzi et al., J Clin Invest 125, 2090-2108 (2015). Pollizzi et al., Nat Immunol 17, 704-711 (2016). Preston et al., The EMBO Journal 34, 2008-2024 (2015). Ron-Harel et al., Cell Metab 24, 104-117 (2016). Tan et al., Immunity 46, 488-503 (2017). Verbist et al., Nature 532, 389-389 (2016). Wang et al., Immunity 35, 871-882 (2011). Yang et al., Nat Immunol 12, 888-897 (2011). Yang et al., Immunity 39, 1043-1043 (2013). Sinclair et al., Elife 8, (2019).

[0069] 674894-1903-2290, v. 1 Sinclair et al., Nat Immunol 14, 500-508 (2013). Nakaya et al., Immunity 40, 692-705 (2014). Rathmell et al., Mol Cell Biol 23, 7315-7328 (2003). Chapman et al., Mechanisms of Ageing and Development 21, 157-167 (1983). Bruzzone et al., PLoS ONE 4, (2009). Wang et al., Cell Rep 36, 109516 (2021). Rongvaux et al., J Immunol 181, 4685-4695 (2008). Drijvers et al., Cancer Immunol Res 9, 184-199 (2021). Gerner et al., Leukemia 34, 1885-1897 (2020). Carbone et al., Int Immunol 4, 861-867 (1992). Jameson et al., J Exp Med 177, 1541-1550 (1993). Hogquist et al., Cell 76, 17-27 (1994). Rosette et al., Immunity 15, 59-70 (2001). Daniels et al., Nature 444, 724-729 (2006). Rabinowitz et al., Immunity 5, 125-135 (1996). Auphan-Anezin et al., J Immunol 170, 2442-2448 (2003). Malherbe et al., Immunity 21, 669-679 (2004). Denton et al., The Journal of Immunology 187, 5733-5744 (2011). Chang et al., Cell 153, 1239-1251 (2013). Geiger et al., Cell 167, 829-842.e813 (2016). Ma et al., Immunity 51, 856-870 e855 (2019). Ron-Harel et al., Cell Rep 28, 3011-3021 e3014 (2019). Edwards-Hicks et al., Metabolites 11, (2020). Puleston et al., Cell 184, 4186-4202 e4120 (2021). Katsyuba & Auwerx, EMBO J 36, 2670-2683 (2017). Yoshino et al., Cell Metab 27, 513-528 (2018). Quinn, 3rd et al., Cell Rep 33, 108500 (2020). Frederick et al., J Biol Chem 290, 1546-1558 (2015). Bailis et al., Nature 571, 403-407 (2019).

[0070] 684894-1903-2290, v. 1

Claims

WHAT IS CLAIMED:

1. A method of selecting a lymphocyte from a population of lymphocytes comprising: (a) providing a population of lymphocytes; (b) assessing NAD levels or biosynthesis in said population of lymphocytes; and (c) selecting one or more lymphocytes based on higher than populational average NAD(P)H.

2. A method of selecting a lymphocyte from a population of lymphocytes comprising: (a) providing a population of lymphocytes; (b) assessing NAD levels or biosynthesis in said population of lymphocytes; and (c) selecting one or more lymphocytes based on lower than populational average NAD(P)H.

3. The method of claim 1 or claim 2, wherein the higher or lower than populational average is the top or bottom quartile, respectively.

4. The method of any one of claims 1-3, wherein step (b) comprises assessing NAD(P)H autofluorescence.

5. The method of any one of claims 1-4, wherein step (c) comprises flow cytometry cell sorting.

6. The method of any one of claims 1-5, wherein the population of lymphocytes is a T lymphocyte population.

7. The method of claim 6, wherein the population of lymphocytes is a chimeric antigen receptor (CAR) T lymphocyte population.

8. The method of any one of claims 1-5, wherein the one or more selected lymphocytes is a T lymphocyte and said method further comprises engineering of the one or more selected lymphocytes to express a chimeric antigen receptor (CAR).

9. The method of any one of claims 1-5, wherein the population of lymphocytes is a B lymphocyte population.694894-1903-2290, v.

110. The method of any one of claims 1-9, wherein the one or more selected lymphocytes is cultured and expanded following step (c).

11. The method of any one of claims 1-10, further comprising obtaining the population of lymphocytes from a subject prior to step (a).

12. The method of any one of claims 1-11, wherein the lymphocyte population is a mammalian lymphocyte population, such as a human lymphocyte population.

13. The method of any one of claims 1-12, wherein steps (a)-(c) are performed in about 18- 24 hours.

14. The method of one of claims 1-12, wherein steps (a)-(c) are performed in about 18 hours, about 20 hours, or about 24 hours.

15. The method of any one of claims 1-14, wherein steps (b)-(c) are performed a second time on the selected one more lymphocytes of step (c).

16. A lymphocyte or lymphocytes prepared according to the method of any one of claims 1-15.

17. A lymphocyte or lymphocytes exhibiting a higher or lower than populational average of NAD levels or biosynthesis, wherein the reference population is a lymphocyte population from which the lymphocyte or lymphocytes is / are obtained, wherein the higher or lower than populational average is the top or bottom quartile, respectively.

18. The lymphocyte or lymphocytes of claim 17, wherein the lymphocyte or lymphocytes is / are T lymphocyte(s), CAR T lymphocyte(s) or B lymphocyte(s).

19. A method of treating cancer, autoimmunity or fibrosis comprising administering to a subject in need thereof a T lymphocyte, a chimeric antigen receptor (CAR) T lymphocyte, or an antibody produced by a B lymphocyte, wherein: (a) the T lymphocyte, CAR T lymphocyte or B lymphocyte is produced according to the method of any one of claims 1-15; and / or704894-1903-2290, v. 1(b) (i) the T lymphocyte, CAR T lymphocyte or B lymphocyte exhibits a higher than populational average of NAD levels or biosynthesis, wherein the reference population is a lymphocyte population from which the lymphocyte or lymphocytes is / are obtained, or (ii) the T lymphocyte, CAR T lymphocyte or B lymphocyte exhibits a lower than populational average of NAD levels or biosynthesis, wherein the reference population is a lymphocyte population from which the lymphocyte or lymphocytes is / are obtained, such as wherein the higher or lower than populational average is the top or bottom quartile, respectively.

20. A method of treating an infectious disease comprising administering to a subject in need thereof an antibody produced by a B lymphocyte, wherein the B lymphocyte: (a) (i) exhibits a higher than populational average of NAD levels or biosynthesis, wherein the reference population is a lymphocyte population from which the lymphocyte or lymphocytes is / are obtained, or (ii) exhibits a lower than populational average of NAD levels or biosynthesis, wherein the reference population is a lymphocyte population from which the lymphocyte or lymphocytes is / are obtained, wherein the higher or lower than populational average is the top or bottom quartile, respectively.; and / or (b) is produced according to the method of any one of claims 1-3 and 7-15.714894-1903-2290, v. 1

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