Identification of genes that regulate t cell fitness using an in VIVO screening platform

Abstract

Provided herein is a screen to identify genes that enhance T cell fitness in vivo. Also provided herein are methods for identifying genetically modified T cells with modulated anti-tumor T cell function. Also provided herein are populations of cells comprising the genetically modified T cells disclosed herein. Also provided are methods of treating cancer comprising administering the genetically modified T cells disclosed herein to a subject with cancer.

Description

PATENT Atorney Docket No.: 081906-1534113-261420PC SF-2024-187-2-PCTIDENTIFICATION OF GENES THAT REGULATE T CELL FITNESS USING AN IN VIVO SCREENING PLATFORMCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority benefit of U.S. Provisional Application No.63 / 761,785 filed February 21, 2025, and U.S. Provisional Application No. 63 / 853,286, filed July 29, 2025, which are incorporated by reference in their entirety for all purposes.BACKGROUND OF THE DISCLOSURE

[0002] Although adoptive cellular therapies (ACT) have achieved success in certain hematologic malignancies, solid tumors have not responded as well, likely due in part to many obstacles in the solid tumor microenvironment (TME).1For instance, T cells must traffic to the tumor and then infiltrate the tumor mass, which is often challenging due to several physical, chemical, and biological barriers. These include repulsive chemokine cues, dense fibrotic stroma, an abnormal extracellular matrix (ECM), disorganized tumor vasculature, elevated interstitial fluid pressure, and immunosuppressive fibroblasts. It has also become increasingly clear that cellular metabolism intrinsically affects T cell function, and metabolic barriers in the TME are important drivers of ACT failure in solid tumors.2The success of T cell therapies hinges on the capacity for robust T-cell proliferation, differentiation, cytokine production, cytotoxicity, and persistence.3These processes all require substantial metabolic input and are thus compromised within the hypoxic and nutrient-scarce TME where metabolically aggressive tumor cells consume nutrients and oxygen excessively.4Recent work shows that highly glycolytic tumors display more resistance to ACT due to glucose competition by tumor cells within the TME restricting T cell function and infiltration,5and hypoxia impairs CAR T cell function.6As another example, T cells encounter many suppressive cues in the TME, that can be in the form of immune checkpoint ligands, suppressive cytokines, suppressive cells, suppressive metabolites, and other molecules. Overcoming these barriers to adoptive T-cell therapies requires innovative strategies to engineer T cells to be capable of navigating the hostile conditions in solid tumors.

[0003] Large-scale CRISPR screens are a powerful tool to investigate intricate cellular systems in high throughput, providing the ability to rapidly test hundreds of thousands of genetic perturbations in parallel. However, most human T cell screens have occurred in simplified conditions in vitro. In vitro CRISPR screen conditions often include nutrient rich media, buffered acidity levels, and in some cases a reductionist approach to modeling few aspects of the suppressive TME. It has become apparent that when for assessing new T cell therapies, in vitro performance may not always be an adequate predictor of in vivo performance.BRIEF SUMMARY OF CERTAIN ASPECTS OF THE DISCLOSURE

[0004] Performing large-scale CRISPR screens in primary human T cells in tumor-bearing NSG mice has been a significant challenge due to the limited numbers of T cells that can be recovered from tumors in these models.7This disclosure is based, at least in part, on development of a screening system that allows for genome-wide CRISPR screens in primary human T cells in tumor-bearing mice. This system can achieve genome-wide screen scale with relatively few mice, which reduces a major barrier in the field and provides the ability to rapidly identify target genes that can enhance T cell fitness in vivo.

[0005] In one aspect, the disclosure features a method of identifying genetically modified T cells with modulated anti-tumor T-cell function, the method comprising:inoculating a mouse with cancer cells genetically modified to express an anti-CD3 scFv, wherein the anti-CD3 scFv is encoded by a polynucleotide construct comprising a polynucleotide encoding a leader sequence, an anti-CD3 heavy chain variable region (VH) sequence, a linker sequence, an anti-CD3 light chain variable region (VL) sequence, a CD8 hinge sequence, and a CD8 transmembrane domain sequence, wherein the polynucleotide is operably linked to an EF-loc promoter, wherein the cancer cells express the anti-CD3 scFv at a level no more than 10% higher than a negative control;inoculating the mouse with a library of genetically modified T cells; and identifying members of the library that exhibit modulated anti-tumor T-cell activity compared to unmodified control T cells.In some embodiments, the cancer cells are from a melanoma, breast cancer, prostate cancer, colon cancer, ovarian cancer, lung cancer, pancreatic cancer, head and neck cancer, liver cancer, kidney cancer, glioblastoma, or a neuroblastoma cell line. In some embodiments, the library of genetically modified T cells is a genome wide CRISPR knockout library, a genomewide CRISPR activation library, a genome wide base editing library, or a CRISPR library comprising T cells in which a first gene is knocked out and a second gene is activated. In some embodiments, the identifying step further comprises identifying a gene that when knocked out in a member of the library of genetically modified T cells enhances T cell fitness in the member of the library of genetically modified T cells. In some embodiments, one or more of the following activities are assayed: proliferation, production of cytokines that mediate anti-tumor activity of T cells, differentiation, ability to overcome the effects of suppressive metabolites and / or other suppressive factors in the tumor microenvironment (TME), ability to persist and maintain activity in a TME, or tumor infiltration.

[0006] In a further aspect, the disclosure features a genetically modified T cell that comprises at least one genetic modification to a gene that negatively regulates T-cell fitness, wherein the genetic modification inhibits expression or activity of the polypeptide product encoded by the gene, wherein the gene is selected from the group consisting of SPTLC2, STT3B, PPIAL4D, LRIG3, GNA13, STUB1, GN AS, FAM76A, ALDH3B1, JMJD8, FBXO45, FDXR, H2AFB3, PPP6C, GOLGA1, NFKBIA, ALG3, DPEP2, CLTC, MBNL3, ERF, SYNDIG1L, Cllorf57, GTF2A2, CSNK2A1, GBE1, GNB2, HIST1H2AI, INPPL1, NT5C2, FRMD3, GARS, SIKE1, EDC4, SOCS1, EBF2, PPARG, BICC1, MDGA2, KAT8, PTPN2, CHRNB2, BRWD3, MAP4K1, REV3L, P2RY8, NR1H2, FAM3A, ADPRHL1, DUSP9, PTGER4, SATB1, RBF0X2, ZC3H12A, C12orf66, TCHH, WNT9A, MAF, SIGLEC12, MMP3, SPINK6, SOX18, PLEKHB1, CIC, TMEM127, MAP4K1, COL1A2, USP22, FAM179A, BRINP1, RORB, RGS7BP, MEF2D, FAM170A, CUTC, ZNF513, TFAP2E, CMTM4, CYP3A5, PPP1R3G, WWTR1, LRRC61, ZNF772, ADGRL4, TMCC2, SOS2, ACTA1, ANO4, B3GAT1, MSI2, C15orf61, SLC30A1, S1PR1, GNA13, PTGER4, BASP1, KCNA5, ZNF835, FKBP1A, POU5F1B, ADPRHL1, PRR19, ESRRA, SLX1A, ATF5, TMEM43, CUTC, SLC6A8, KRTAP8-1, P2RY8, MAN2C1, PDLIM7, CEBPB, CT47A2, CST7, C15orf56, F0XI2, SUN1, SHISA3, OR10A7, MUSTN1, ZNF227, CCNY, RORB, CALML3, GPR132, KLHL14, SOX30, USP49, SLC35E4, SOX11, WNT9A, GALNT11, PPM1H, PP2D1, PCGF2, FAM216A, and ADGRL4, wherein inhibition increases production of cytolytic cytokines and / or enhances tumor infiltration compared to an unmodified control T cell. In some embodiments, the gene is selected from the group consisting of PTLC2, STT3B, PPIAL4D, LRJG3, GNA13, STUB1, GN AS, FAM76A, ALDH3B1, JMJD8, FBXO45, FDXR, H2AFB3, PPP6C, GOLGA1, NFKBIA, ALG3, DPEP2, CLTC, MBNL3, ERF, SYNDIG1L, Cllorf57, GTF2A2, CSNK2A1, GBE1, GNB2, HIST1H2AI, INPPL1, NT5C2,FRMD3, GARS, SIKE1, EDC4, S0CS1, EBF2, PPARG, BICC1, MDGA2, KAT8, PTPN2, CHRNB2, BRWD3, MAP4K1, and REV3L, and the T cell expresses increased amount of interferon-gamma compared to the unmodified control T cell. In some embodiments, the gene is selected from the group consisting of P2RY8, NR1H2, FAM3A, ADPRHL1, DUSP9, PTGER4, SATB1, RBF0X2, ZC3H12A, C12orf66, TCHH, WNT9A, MAF, SIGLEC12, MMP3, SPINK6, S0X18, PLEKHB1, CIC, TMEMI27, MAP4K1, COL1A2, USP22, FAM179A, BRINP1, RORB, RGS7BP, MEF2D, FAM170A, CUTC, ZNF513, TFAP2E, CMTM4, CYP3A5, PPP1R3G, WWTR1, LRRC61, ZNF772, ADGRL4, TMCC2, SOS2, ACTA1, AN04, B3GAT1, MSI2, C15orf61, SLC30A1, S1PR1, GNA13, PTGER4, BASP1, KCNA5, ZNF835, FKBP1A, P0U5F1B, ADPRHL1, PRR19, ESRRA, SLXIA, ATF5, TMEM43, CUTC, SLC6A8, KRTAP8-1, P2RY8, MAN2C1, PDLIM7, CEBPB, CT47A2, CST7, C15orf56, F0XI2, SUN1, SHISA3, OR10A7, MUSTN1, ZNF227, CCNY, RORB, CALML3, GPR132, KLHL14, SOX30, USP49, SLC35E4, S0X11, WNT9A, GALNT11, PPM1H, PP2D1, PCGF2, FAM216A, and ADGRL4,' and the T cell exhibits enhanced tumor infiltration compared to the unmodified control T cell. In some embodiments, inhibition of expression of the gene in a population of T cells results in enrichment of the population of T cells in a tumor compared to spleen. In some instances, the T cell is a CD8+ T cell or CD4+ T cell. In some embodiments, the gene that negatively regulates T cell fitness is inhibited using a clustered, regularly interspaced, short palindromic repeats (CRISPR) system; or using a transcription activator-like effector nuclease (TALEN) system; or using a zinc finger nuclease system; or using a meganuclease system. In some embodiments, the gene that negatively regulates T cell fitness is inhibited using inhibitory RNA. In some embodiment the gene is inhibited using shRNA, siRNA, microRNA, or an antisense RNA. In some instances the T cell is modified to express a chimeric antigen receptor (CAR). In some embodiments, the T cell expresses an HLA-Independent TCR-based Chimeric Antigen Receptor, a T cell receptor fusion construct (TRuC), a synthetic T cell receptor and antigen receptor (STAR), an antibody-T cell receptor (AbTCR) or a T cell antigen coupler (TAC).

[0007] In some embodiments, a genetically modified T cell comprises modifications to at least two genes to inhibit expression or activity of the target genes. For examples, in some instances, a gene that plays a role in the P2RY8-Gal3-ARHGEF1 signaling axis that enhances tumor infiltration may be targeted and a gene that preserves T cell effector function may be targeted. In some embodiments, the genetically modified T cell comprises amodification to a P2RY8 gene that inhibits or inactivates the gene and a modification to a GNAS gene that inhibits or inactivates the gene.

[0008] In further aspects, the disclosure provides a population of cells comprising the genetically modified T cell of the disclosure, e.g., as described in the preceding paragraphs; and methods of treating cancer using such T cell populations.Terminology

[0009] As used herein, the singular forms "a", "an", and "the" are also intended to refer to the plural unless the context clearly dictates otherwise.

[0010] The terms “polynucleotide” and “nucleic acid” are used interchangeably to refer to a polymeric form of nucleotides of any length, either deoxyribonucleotides or ribonucleotides. The terms include RNA, DNA, and synthetic forms and mixed polymers of the above. In particular embodiments, a nucleotide refers to a ribonucleotide, deoxynucleotide or a modified form or analog of either type of nucleotide, and combinations thereof. In addition, a polynucleotide may include either or both naturally occurring and modified nucleotides linked together by naturally occurring and / or non-naturally occurring nucleotide linkages. The nucleic acid molecules may be modified chemically or biochemically or may contain non-natural or derivatized nucleotide bases. Such modifications include, for example, labels, substitution of one or more of the naturally occurring nucleotides with an analogue, internucleotide modifications such as uncharged linkages (e.g., methyl phosphonates, phosphotriesters, phosphoramidates, carbamates, etc.), charged linkages (e.g., phosphorothioates, phosphorodithioates, etc.), and modified linkages (e.g., alpha anomeric nucleic acids, etc.). The terms “polynucleotide” and “nucleic acid” are also intended to include any topological conformation, including single-stranded, double-stranded, partially duplexed, triplex, hairpinned, circular and padlocked conformations. A reference to a nucleic acid sequence encompasses its complement unless otherwise specified. Thus, a reference to a nucleic acid molecule having a particular sequence should be understood to encompass its complementary strand, with its complementary sequence. Reference to a “polynucleotide” or “nucleic acid” that encodes a polypeptide sequence also includes codon-optimized nucleic acids and nucleic acids that comprise alternative codons that encode the same polypeptide sequence.

[0011] As used herein, the term “complementary” or “complementarity” refers to specific base pairing between nucleotides or nucleic acids. Base pairing may be perfectly complementary or partially complementary.

[0012] The term “gene” can refer to the segment of DNA involved in producing or encoding a polypeptide chain. It may include regions preceding and following the coding region (leader and trailer) as well as intervening sequences (introns) between individual coding segments (exons). Genes disclosed herein, e.g., T cell gene targets, are defined by symbol and nomenclature for the human gene as assigned by the HUGO Gene Nomenclature Committee. Illustrative guide nucleotide sequences that target negative regulators of T cell fitness disclosed herein are provided in Tables 1-3.

[0013] A “promoter” is defined as one or more a nucleic acid control sequences that direct transcription of a nucleic acid. As used herein, a promoter includes necessary nucleic acid sequences near the start site of transcription. A promoter also optionally includes distal enhancer or repressor elements, which can be located as much as several thousand base pairs from the start site of transcription.

[0014] The term “inhibiting expression” refers to inhibiting or reducing the expression of a gene or a protein. To inhibit or reduce the expression of a gene (i.e., a gene encoding a transcription factor, or a gene regulated by a transcription factor), the sequence and / or structure of the gene may be modified such that the gene would not be transcribed (for DNA) or translated (for RNA), or would not be transcribe or translated to produce a functional protein (e.g., a transcription factor). Various methods for inhibiting or reducing expression of a gene are described in detail further herein. Some methods may introduce nucleic acid substitutions, additions, and / or deletions into the wild-type gene. Some methods may also introduce single or double strand breaks into the gene. To inhibit or reduce the expression of a protein e.g., a protein encoded by a gene that negatively regulates T cell fitness), one may inhibit or reduce the expression of the gene or polynucleotide encoding the protein, as described above. In other embodiments, one may target the protein directly to inhibit or reduce the protein’s expression using, e.g., an antibody or a protease. “Inhibited” expression refers to a decrease by at least 20%, or at least 30%, or at least 40%, or at least 50%, or preferably at least 60%, or at least 70%, or at least 80%, or at least 90% or higher, up to and including a 100% decrease (i.e. absent level as compared to a reference sample). As used herein, the term "inactivated" refers to preventing expression of a polypeptide productencoded by the gene. Inactivation can occur at any stage or process of gene expression, including, but not limited to, transcription, translation, and protein expression, and inactivation can affect any gene or gene product including, but not limited to, DNA, RNA, such a mRNA, and polypeptides. In some embodiments, “inhibited expression” reflects inactivation in a percentage of cells that are modified, e.g., at least 20%, or at least 30%, or at least 40%, or at least 50%, or at least 60%, or at least 70%, or at least 80%, or at least 90% or greater of the cells in a population that also comprises cells in which the target gene is not inactivated.

[0015] The term “genetic modification” as used herein refers to any modification to a cell to alter expression of a gene. Such modifications include modifications to the genome as well as modifications to introduce inhibitory sequences, such as inhibitory RNAs, into the cell.

[0016] As used herein, the phrase “modifying” in the context of modifying a genome of a cell refers to inducing a structural change in the sequence of the genome at a target genomic region. For example, the modifying can take the form of inserting a nucleotide sequence into the genome of the cell. For example, a nucleotide sequence encoding a polypeptide can be inserted into the genomic sequence encoding an endogenous cell surface protein in the T cell. The nucleotide sequence can encode a functional domain or a functional fragment thereof. Such modifying can be performed, for example, by inducing a double stranded break within a target genomic region, or a pair of single stranded nicks on opposite strands and flanking the target genomic region. Methods for inducing single or double stranded breaks at or within a target genomic region include the use of a nuclease domain, e.g.yCas9, or a derivative thereof, and a guide, e.g, guide RNA, directed to the target genomic region.

[0017] The terms “patient,” “subject,” “individual,” and the like are used interchangeably herein, and refer to any animal, e.g, a mammal, such as a primate. In certain non-limiting embodiments, the patient, subject or individual is a human.

[0018] The terms "treatment", "treating", and the like are used herein to generally mean obtaining a desired pharmacologic and / or physiologic effect. The effect may be prophylactic, in terms of completely or partially preventing a disease, condition, or symptoms thereof, and / or may be therapeutic in terms of a partial or complete cure for a disease or condition and / or an adverse effect, such as a symptom, attributable to the disease or condition.

[0019] " Treatment" as used herein covers any treatment of a disease or condition of a subject and includes: (a) preventing the disease or condition from occurring in a subject which may be predisposed to the disease or condition but has not yet been diagnosed as having it; (b) inhibiting the disease or condition (e.g., arresting its development); or (c) relieving the disease or condition (e.g., causing regression of the disease or condition, providing improvement in one or more symptoms).BRIEF DESCRIPTION OF THE FIGURES

[0020] FIG. 1 : Plasmid map and illustrative generation strategy of lenti-anti-CD3 scFv plasmid.

[0021] FIG. 2: Mouses platform for genome-wide in vivo CRISPR screens in primary human T cells. (A) Diagram of overexpressing anti-CD3 scFv on cancer cells. (B) Workflow depicting the generation of anti-CD3 scFv overexpressing A375 single cells. (C) Flow cytometric analysis of anti-CD3 scFv expression on anti-CD3 scFv overexpressing A375 single cells. (D) Incucyte assay demonstrating T cell killing function towards A375 single cells with varying expression levels of anti-CD3 scFv. (E) Schematic of tumor model workflow. (F) Image of final tumor sizes in (E), NSG mice were implanted with tumor cells that exhibiting low (A357_low), medium (A357_medium) and high (A375_high) response to human primary T cell killing, and then were treated with same dose of human T cells. (G, H) FACS gates for NY-ESO1 TCR-T cells isolated from A375 wildtype tumors and spleen in NSG mice (G) versus polyclonal T cells isolated from anti-CD3 scFv expressing A375_low tumors and spleen (H). (I) T cell number that we can isolate from per A375_low tumor and spleen. (I) Distribution of CD4+ and CD8+ T cells in A375_low tumors and spleen of NSG mouse.

[0022] FIG. 3: Characterization of human T cells isolated from NSG mice bearing low OKT3 anti-CD3 scFv expressing A375 tumors and spleens. Flow cytometric analysis for T cell exhaustion, activation, proliferation, differentiation and cytokine production, seahorse analysis of the metabolic states and Incucyte assay for T cell killing function between splenic T cells and TILs.

[0023] FIG. 4: In vivo competition assay shows this screening platform can detect the expansion and persistence advantage of Regnase-l-KO T cells. To directly compare the relative T cell expansion and persistence in the same microenvironment, we transferred a mixture of 50:50 (control AAVS1 :Regnase-l-KO T cells) T cells into tumor bearing mice(A), and 14 days later these T cells were isolated from spleens and tumors of these mice for analysis (B). Regnase-l-KO T cells is a positive control given its known role as a loss-of-function target that enhances in vivo expansion in T cells. Regnase-1 KO T cells outcompete the control T cells in a competition assay in vivo.

[0024] FIG. 5: Sort-based strategies for in vivo genome-wide CRISPR screens. (A) TILs sorted by CD39 levels show differences in ex vivo tumor cell killing. (B) Schema for illustrative in vivo screens using markers for cell states / effector function such as CD39 & TNF-a for sort-based readouts.

[0025] FIG. 6: In vivo genome-wide CRISPR loss-of-function screens. (A) Screen schemas. (B) Volcano plot for T cell abundance screens and IFN-gamma production screens. (C) Data from T cell abundance screens displayed based on LFC of sgRNAs in the tumor vs the spleens compared to the LFC of the tumor vs the input (left panel). Data from T cell abundance screens displayed based on LFC of sgRNAs in the spleens vs the input compared to the LFC of the tumor vs the input (right panel).

[0026] FIG. 7: In vivo efficacy and safety of GNAS KO CAR-T cells. CD19-specific CAR-T cells edited for a control AAVS1 sgRNA, versus KO for GNAS, were injected into NSG mice bearing A375 tumors that express CD19. Data shows tumor volume and Kaplan-Meier survival curves. We demonstrated that GNAS KO markedly enhances tumor-killing activity in vivo across multiple CAR T and TCR T cell models: CD19-targeted CAR T cells, GNAS KO led to dramatically enhanced tumor-killing against CD19-expressing A375 solid tumors (A) and CD19-expressing A549 lung solid tumors (B). In CLDN18.2-targeted CAR T cells, GNAS KO significantly improved tumor clearance against OE19 gastroesophageal cancer in vivo (C). In NY-ESO-1 TCR T cells, GNAS KO resulted in enhanced tumor-killing activity against A375 solid tumors in vivo (D). In B7H3-targeted CAR T cells, GNAS KO CAR T cells showed a clear tumor clearance advantage in NSG mice implanted with MES-SA uterine sarcoma (E). GNAS deletion in CD 19 CAR-T cells showed a clear tumor clearance advantage in NSG mice implanted with AsPCl pancreatic cancer cells that were previously engineered to express CD 19 (F). GNAS KO CAR-T treated mice that cleared CD 19-expressing A375 tumors were rechallenged with CD19-positive A375 cells and CD19-negative A375 tumor cells in opposite flanks 60 days after the 1sttumor challenge. GNAS KO CD 19 CAR-T cells had persistent memory for CD19+tumor cells and continued to control tumor growth, but did not control CD19-negative A375 (G). In B7H3-targeted CART cells, GNAS KO conferred a clear tumor clearance advantage in NSG mice bearing MES-SA uterine sarcoma, as shown in (E), and in the A549 lung metastasis model, as shown in (H), with no evidence of weight loss or signs of poor health observed in the GNAS KO group (data not shown). In AAV-engineered CLDN18.2-targeted CAR T cells, GNAS knockout significantly enhanced in vivo tumor clearance in the OE19 gastroesophageal cancer model (I).

[0027] FIG. 8: GNAS KO dramatically increases T cell concentration per cancer cell and reduces exhaustion. GNAS KO CD19 CAR-T cell isolated from A375-CD19 tumors are more abundant and less exhausted compared to control AAVS1 CAR-T cells (A). RNAseq data of B7H3 CAR T cells isolated from the in vivo MES-SA uterine sarcoma model showed GNAS KO significantly reduces CAR T cell exhaustion (B).

[0028] FIG. 9: GNAS knockout CAR T cells maintain long-term safety in preclinical models. GNAS KO T cells do not survive cytokine withdrawal and do not recognize antigennegative cells (A and B). RNA-seq data demonstrate that upon activation under steady state, GNAS knockout does not substantially alter the T cell gene expression profile, whereas under suppressive tumor microenvironment conditions (suppressive GPCR ligands) GNAS knockout induces distinct transcriptional changes (C). GNAS knockout CAR T cell-treated mice remained healthy, showing no body weight loss or off-tumor T cell infiltration after tumor clearance (D-G).

[0029] FIG. 10: GNAS KO tumor-infiltrating T cells from patients demonstrate robust tumor cell control especially under combined suppressive signals (the suppressive GPCR ligands) from both tumors and immunosuppressive cells.

[0030] FIG. 11 : CD 19 CAR-T cells edited for a number of different target genes that emerged from our screen were tested in parallel in NSG mice engrafted with A549 non-small cell lung cancer cells. Disruption of these targets, to varying degrees, enhanced overall CAR-T cell tumor control in this model.

[0031] FIG. 12: Genes involved in germinal center migration pathways enriched in T cells in tumors. (A) Data from CRISPR KO screen for T cell abundance displayed based on LFC of sgRNAs in the tumor vs the spleens compared to the LFC of the tumor vs the input. (B) Highlighting a B cell migration pathway that involves multiple top enriched genes from our tumor abundance screen in T cells. (C) Competition migration / infiltration assay in vivo. BFP+P2RY8 KO vs GFP+AAVS1 control antigen-specific T cells were mixed at a 50:50 ratio andinjected into mice bearing the relevant target tumors. 2 days later T cells were harvested from tumors and spleens to assess the BFP:GFP ratios in the tumors vs spleens. On the left is the resulting data for the CLDN18.2-specific CAR-T cells injected into NSG mice bearing CLDN18.2+ gastric cancer, and on the right are the data for the NY-ESO-1 TCR-T cells injected into A375-bearing mice.

[0032] FIG. 13: Tumor growth curves for mice treated with CD 19 CAR-T cells with individual or combined P2RY8 and GNAS gene KOs. CD19-expressing A549 non-small cell lung cancer cells were subcutaneously engrafted into NSG mice, followed by intravenous infusion of CD 19 CAR-T cells. The experimental timeline (top), tumor growth curves (bottom left), and tumor size at day 90 post CAR-T cell treatment (bottom right) are shown (n=6 mice per group). All experimental conditions for these figure panels were performed together as a concurrent experiment and some plots are shown elsewhere for narrative clarity. P values were determined by two-tailed unpaired Student’ s t-test. *P < 0.05, **P < 0.01, *** < 0.001, and **** < 0.0001. n.s, not significant. Data are presented as mean ± s.e.m.DETAILED DESCRIPTION OF THE DISCLOSUREGenes that negatively regulate T cell fitness

[0033] In one aspect, the disclosure provides engineered T cells, e.g., primary T cells, that exhibit enhanced fitness in vivo for killing tumor cells compared to unmodified counterpart T cells. As used herein, T-cell “fitness” refers to the ability to perform tumor cell killing, including such characteristics as the ability to proliferate, produce cytokines that mediate anti-tumor activity of T cells, ability to differentiate, the ability to overcome the effects of suppressive metabolites and / or other suppressive factors in the TME, and the ability to persist and maintain activity in a TME.

[0034] In one aspect of the present disclosure, T cells, e.g., primary T cells, are genetically modified to inhibit expression of a gene that negatively regulators T-cell fitness, i.e., a negative regulatory gene that plays a role in one or more pathways, including, but not limited to, proliferation, T cell persistence, resistance to suppressive factors in a TME, tumor infiltration and migration, and pathways mediating anti-tumor activity, e.g., production of cytokines that enhance human T-cell cytotoxicity. Inhibition or knockout of one or more genes of the present disclosure that negatively regulate T-cell fitness enhances one or more properties that contribute to enhanced fitness compared to control counterpart T cells,including, but not limited to, one or more of: persistent T cell function in the context of chronic tumor stimulation; enhanced proliferation; enhanced tumor infiltrating activity, enhanced production of cytokines, e.g. human T cell production of cytolytic cytokines such as IFN-y, granzyme B, and TNFoc; enhanced resistance to tumor suppressive factors such as metabolites. Thus, T cells harboring a genetic modification that knocks out a target T-cell gene as described herein, or a genetic modification to the gene that inhibits function, have enhanced T cell effector function compared to unmodified controls.

[0035] Any T cell can be modified to inhibit expression of a gene that negatively regulates T-cell fitness. In some embodiments, a T cell modified in accordance with the invention is a CD8+ T cell. In some embodiments, the T cell is a CD4+ T cell, or gamma delta T cell. In further embodiments, the T cell is a stem memory T cell, an effector memory T cell, a central memory T cell, or a naive T cell. Review of T cell subsets are provided, e.g., in Sallusto et al., Annual Rev. Immunol. 22745-763, 2004; Mueller et al., Annual Rev. Immunol 31 : 137- 161, 2013; and for memory stem T-cells, Gattinoni, et al., Nature Med. 23:18-27, 2018.Descriptions of subsets by markers are available in the OMIP Wiley Online Library (see, e.g., Wingender and Kronenberg, OMIP-030: Characterization of human T cell subsets via surface markers Cytometry Part A 87A: 1067-1069, 2015.

[0036] Expression of the target gene can be inhibited or, in some embodiments, inactivated, such that the gene does not express an active protein product. In some embodiments, a population of cells can be enriched for cells in which the gene is inactivated. In some embodiments, the gene is inactivated by a complete or partial deletion of the gene, e.g., using a gene editing systems such as CRISPR / Cas, base editing, or a site-directed nuclease such as TALEN, zinc finger nuclease, or meganuclease.

[0037] In some embodiments, a target T cell is modified to inhibit expression of one or more of the following genes: SPTLC2, STT3B, PPIAL4D, LRIG3, GNA13, STUB1, GN AS, FAM76A, ALDH3B1, JMJD8, FBXO45, FDXR, H2AFB3, PPP6C, GOLGA1, NFKBIA, ALG3, DPEP2, CLTC, MBNL3, ERF, SYNDIG1L, Cllorf57, GTF2A2, CSNK2A1, GBE1, GNB2, HIST1H2AI, INPPL1, NT5C2, FRMD3, GARS, SIKE1, EDC4, SOCS1, EBF2, PPARG, BICC1, MDGA2, KAT8, PTPN2, CHRNB2, BRWD3, MAP4K1, REV3L, P2RY8, NR1H2, FAM3A, ADPRHL1, DUSP9, PTGER4, SATB1, RBF0X2, ZC3H12A, C12orf66, TCHH, WNT9A, MAF, SIGLEC12, MMP3, SPINK6, SOX18, PLEKHB1, CIC, IMEM127, MAP4K1, COL1A2, USP22, FAM179A, BRINP1, RORB, RGS7BP, MEF2D, FAM170A,CUTC, ZNF513, TFAP2E, CMTM4, CYP3A5, PPP1R3G, WWTR1, LRRC61, ZNF772, ADGRL4, TMCC2, S0S2, ACTA1, AN04, B3GAT1, MSI2, C15orf61, SLC30A1, S1PR1, GNA13, PTGER4, BASP1, KCNA5, ZNF835, FKBP1A, P0U5F1B, ADPRHL1, PRR19, ESRRA, SLX1A, ATF5, TMEM43, CUTC, SLC6A8, KRTAP8-1, P2RY8, MAN2C1, PDLIM7, CEBPB, CT47A2, CST7, C15orf56, F0XI2, SUN1, SHISA3, OR10A7, MUSTN1, ZNF227, CCNY, RORB, CALML3, GPR132, KLHL14, SOX30, USP49, SLC35E4, S0X11, WNT9A, GALNT11, PPM1H, PP2D1, PCGF2, FAM2I6A, or ADGRL4.

[0038] T cell function following inhibition of a gene can be assessed using any number of assays to compare the activity of the genetically modified T cell to a counterpart, e.g., an unmodified control T cell or a control T cell that does not contain the genetic modification(s) to inhibit the gene that negatively regulate T cell fitness. A T cell modified as described herein is considered to have improved fitness when there is an increase in T-cell activity of at least 20%, or at least 25%, or at least 30%, at least 35%, at least 40%, at least 45%, or at least 50%, or at least 60% or greater, compared to an unmodified control T cell.

[0039] In some instances, cytotoxicity against a target tumor cell is assessed. Thus, in some instances, a human T cell, e.g., a CD8+ T cell, modified to inhibit at least one gene selected from SPTLC2, STT3B, PPIAL4D, LRJG3, GNA13, STUB1, GNAS, FAM76A, ALDH3B1, JMJD8, FBXO45, FDXR, H2AFB3, PPP6C, GOLGA1, NFKBIA, ALG3, DPEP2, CLTC, MBNL3, ERF, SYNDIG1L, Cllorf57, GTF2A2, CSNK2A1, GBE1, GNB2, HIST1H2AI, INPPL1, NT5C2, FRMD3, GARS, SIKE1, EDC4, SOCS1, EBF2, PPARG, BICC1, MDGA2, KAT8, PTPN2, CHRNB2, BRWD3, MAP4K1, and REV3L is considered to have improved fitness when there is an increase in tumor cell killing of at least 20%, or at least 25%, or at least 30%, at least 35%, at least 40%, at least 45%, or at least 50% or greater compared to cell killing of the an unmodified control T cell or a control T cell lacking the genetic modification. Tumor cell killing can be assessed using various assays, including for example using a live-imaging system.

[0040] In some instances, a T cell modified to inhibit at least one gene selected from SPTLC2, STT3B, PPIAL4D, LRIG3, GNA13, STUB1, GNAS, FAM76A, ALDH3B1, JMJD8, FBXO45, FDXR, H2AFB3, PPP6C, GOLGA1, NFKBIA, ALG3, DPEP2, CLTC, MBNL3, ERF, SYNDIG1L, Cllorf57, GTF2A2, CSNK2A1, GBE1, GNB2, HIST1H2AI, INPPL1, NT5C2, FRMD3, GARS, SIKE1, EDC4, SOCS1, EBF2, PPARG, BICC1, MDGA2, KAT8, PTPN2, CHRNB2, BRWD3, MAP4K1, and REV3L is considered to have improved fitnesswhen expression of cytokines such as IFNgamma or TNF alpha are increased by at least 20% or at least 25%, or at least 30%, at least 35%, at least 40%, at least 45%, least 50% or greater, at least 70%, or at least 80% or greater compared to an unmodified control T cell.

[0041] In some instances, a T cell is genetically modified to inhibit and / or knockout a gene that negatively regulates T cell fitness as described herein expresses lower levels of T cell exhaustion markers such as PD1, TIM3, LAG3, and CD39, e.g, at least 25%, or at least 30%, at least 35%, at least 40%, at least 45%, or at least 50% or lower levels of such markers compared to an unmodified control T cell.

[0042] In some embodiments, a target T cell is modified to inhibit expression of one or more of the following genes: GNA13, P2RY8, NR1H2, FAM3A, ADPRHL1, DUSP9, PTGER4, SATB1, RBF0X2, ZC3H12A, C12orf66, TCHH, WNT9A, MAF, SIGLEC12, MMP3, SPINK6, SOX18, PLEKHB1, CIC, IMEM127, MAP4K1, COL1A2, USP22, FAM179A, BRINP1, RORB, RGS7BP, MEF2D, FAM170A, CUTC, ZNF513, TFAP2E, CMTM4, CYP3A5, PPP1R3G, WWTR1, LRRC61, ZNF772, ADGRL4, TMCC2, SOS2, ACTA1, ANO4, B3GAT1, MSI2, C15orf61, or SLC30AP In some embodiments, such a modified T cell is considered to have improved fitness when there is an increase of at least 20% or at least 25%, or at least 30%, at least 35%, at least 40%, at least 45%, or at least 50% or greater in the number of T cells present in a tumor compared to the number of counterpart control cells that are present in a tumor, i.e., that infiltrate a tumor.

[0043] In additional embodiments, a target T cell is modified to inhibit expression of one or more of the following genes: S1PR1, GNA13, PTGER4, BASP1, KCNA5, ZNF835, FKBP1A, POU5F1B, ADPRHL1, PRR19, ESRRA, SLX1A, ATF5, TMEM43, CUTC, SLC6A8, KRTAP8-1, P2RY8, MAN2C1, PDLIM7, CEBPB, CT47A2, CST7, C15orf56, F0XI2, SUN1, SHISA3, OR10A7, MUSTN1, ZNF227, CCNY, RORB, CALML3, GPR132, KLHL14, SOX30, USP49, SLC35E4, SOX11, WNT9A, GALNT11, PPM1H, PP2D1, PCGF2, FAM216A, or ADGRL4. In some embodiments, such a modified T cell is considered to have improved fitness when there is at least 20% or at least 25%, or at least 30%, at least 35%, at least 40%, at least 45%, or at least 50% or greater enrichment of the T cell present in a tumor compared to spleen.

[0044] Another way to assess effects of inhibition of a negative regulator of T cell fitness as described herein is assessed through in vivo experiments. For example, gene editing can be performed with TCR-T and / or CAR-T cells to knock out or inhibit a target gene. The cells are then injected into tumor-bearing mice. Tumor burden can be measured, e.g., by calipermeasure of tumor size or bioluminescent imaging, to assess effects on tumor growth over time, where a decrease in tumor burden by at least 20%, or at least 30% is indicative of improved function obtained by knockout / inhibition of the target gene. Survival in each cohort can also be tracked to assess for significant differences based on a Kaplan-Meier survival analysis.

[0045] In some embodiments, a gene that negatively regulates T cell fitness is inactivated by a gene deletion. As used herein, "gene deletion" refers to removal of at least a portion of a DNA sequence from, or in proximity to, a gene. In some embodiments, the sequence subjected to gene deletion comprises an exonic sequence of a gene. In some embodiments, the sequence subjected to gene deletion comprises a promoter sequence of the gene. In some embodiments, the sequence subjected to gene deletion comprises a flanking sequence of a gene. In some embodiments, a portion of a gene sequence is removed from a gene. In some embodiments, the complete gene sequence is removed from a chromosome. In some embodiments, the host cell comprises a gene deletion as described in the any of the embodiments herein. In some embodiments, the gene is inactivated by deletion of at least one nucleotide or nucleotide base pair in a gene sequence results in a non-functional gene product. In some embodiments, the gene is inactivated by a gene deletion, wherein deletion of at least one nucleotide to a gene sequence results in a gene product that no longer has the original gene product function or activity or exhibits aberrant function. In some embodiments, the gene is inactivated by a gene addition or substitution, wherein addition or substitution of at least one nucleotide or nucleotide base pair into the gene sequence results in a non-functional gene product. In some embodiments, the gene is inactivated by a gene inactivation, wherein incorporation or substitution of at least one nucleotide to the gene sequence results in a gene product that no longer has the original gene product function or activity; or exhibits aberrant function. In some embodiments, the gene is inactivated by an addition or substitution, wherein incorporation or substitution of at least one nucleotide into the gene sequence results in a gene product having aberrant activity. In some embodiments, the host cell comprises a gene deletion as described in the any of the embodiments herein.

[0046] Methods and techniques for inhibiting or inactivating a gene as described herein to enhance T cell fitness, include, but are not limited to, small interfering RNA (siRNA), small hairpin RNA (shRNA; also referred to as a short hairpin RNA), clustered, regularly interspaced, short palindromic repeats (CRISPR), transcription activator-like effectornuclease (TALEN), zinc-finger nuclease (ZFN), homologous recombination, nonhom ologous end-joining, meganuclease, base editing and the like.Inhibitory RNA

[0047] In some embodiments, the gene is inactivated by a small interfering RNA (siRNA) system. siRNA sequences to inactivate a target gene can be identified using considerations such as length of siRNA, e.g., 21-23 nucleotides, or fewer; avoidance of regions with 50-100 nucleotides of the start codon and termination codon, avoidance of intron regions; avoidance of stretches of four or more of the same nucleotide; avoidance of regions with GC content that is less than 30% or greater than 60%; avoidance of repeats and low sequence complexity region; avoidance of single nucleotide polymorphic sites, and avoidance of sequences that are complementary to sequences in other off-target genes (see, e.g., Rules of siRNA design for RNA interference, Protocol Online, May 29, 2004; and Reynolds etal., Nat Biotechnol, 22:3236-3302004).

[0048] In some embodiments, the siRNA system comprises a siRNA nucleotide sequence that is about 10 to 200 nucleotides in length, or about 10 to 100 nucleotides in length, or about 15 to 100 nucleotides in length, or about 10 to 60 nucleotides in length, or about 15 to 60 nucleotides in length, or about 10 to 50 nucleotides in length, or about 15 to 50 nucleotides in length, or about 10 to 30 nucleotides in length, or about 15 to 30 nucleotides in length. In some embodiments, the siRNA nucleotide sequence is approximately 10-25 nucleotides in length. In some embodiments, the siRNA nucleotide sequence is approximately 15-25 nucleotides in length. In some embodiments, the siRNA nucleotide sequence is at least about 10, at least about 15, at least about 20, or at least about 25 nucleotides in length. In some embodiments, the siRNA system comprises a nucleotide sequence that is at least about 80%, at least about 85%, at least about 90%, at least about 95%, or 100% complementary to a region of the target mRNA molecule. In some embodiments, the siRNA system comprises a nucleotide sequence that is at least at least about 80%, at least about 85%, at least about 90%, at least about 95%, or 100% complementary to a region of the target pro-mRNA molecule. In some embodiments, the siRNA system comprises a double stranded RNA molecule. In some embodiments, the siRNA system comprises a single stranded RNA molecule. In some embodiments, the host cell comprises a siRNA system as described in the any of the embodiments herein. In some embodiments, the host cell comprises a pro-siRNA nucleotide sequence that is processed intoan active siRNA molecule as described in the any of the embodiments herein. In some embodiments, the host cell comprises a siRNA nucleotide sequence that is at least about 80%, at least about 85%, at least about 90%, at least about 95%, or 100% complementary to a region of the target mRNA molecule. In some embodiments, the host cell comprises an expression vector encoding a siRNA molecule as described in the any of the embodiments herein. In some embodiments, the host cell comprises an expression vector encoding a prosiRNA molecule as described in the any of the embodiments herein.

[0049] In some embodiments, the siRNA system comprises a delivery vector. In some embodiments, the host cell comprises a delivery vector. In some embodiments, the delivery vector comprises the pro-siRNA and / or siRNA molecule.

[0050] In some embodiments, the gene is inactivated by a small hairpin RNA (shRNA; also referred to as a short hairpin RNA) system. Gene inactivation by shRNA systems are available. In some embodiments, the shRNA system comprises a nucleotide sequence that is about 10 to 200 nucleotides in length, or about 10 to 100 nucleotides in length, or about 15 to 100 nucleotides in length, or about 10 to 60 nucleotides in length, or about 15 to 60 nucleotides in length, or about 10 to 50 nucleotides in length, or about 15 to 50 nucleotides in length, or about 10 to 30 nucleotides in length, or about 15 to 30 nucleotides in length. In some embodiments, the shRNA nucleotide sequence is approximately 10-25 nucleotides in length. In some embodiments, the shRNA nucleotide sequence is approximately 15-25 nucleotides in length. In some embodiments, the shRNA nucleotide sequence is at least about 10, at least about 15, at least about 20, or at least about 25 nucleotides in length. In some embodiments, the shRNA system comprises a nucleotide sequence that is at least about 80%, at least about 85%, at least about 90%, at least about 95%, or 100% complementary to a region of a gene mRNA molecule. In some embodiments, the shRNA system comprises a nucleotide sequence that is at least about 80%, at least about 85%, at least about 90%, at least about 95%, or 100% complementary to a region of a pro-mRNA molecule. In some embodiments, the shRNA system comprises a double stranded RNA molecule. In some embodiments, the shRNA system comprises a single stranded RNA molecule. In some embodiments, the host cell comprises a shRNA system as described in the any of the embodiments herein. In some embodiments, the host cell comprises a pre-shRNA nucleotide sequence that is processed in an active shRNA nucleotide sequence as described in any of the embodiments herein. In some embodiments, the pro-shRNA molecule composed of DNA. In some embodiments, the pro-shRNA molecule is a DNA construct. In some embodiments, thehost cell comprises a shRNA nucleotide sequence that is at least about 80%, at least about 85%, at least about 90%, at least about 95%, or 100% complementary to a region of the gene mRNA molecule. In some embodiments, the host cell comprises an expression vector encoding a shRNA molecule as described in the any of the embodiments herein. In some embodiments, the host cell comprises an expression vector encoding a pro-shRNA molecule as described in the any of the embodiments herein.

[0051] In some embodiments, the shRNA system comprises a delivery vector. In some embodiments, the host comprises a delivery vector. In some embodiments, the delivery vector comprises the pro-shRNA and / or shRNA molecule. In some embodiments, the delivery vector is a virus vector. In some embodiments, the delivery vector is a lentivirus. In some embodiments, the delivery vector is an adenovirus. In some embodiments, the vector comprises a promoter.CRISPR

[0052] In some embodiments, inhibiting expression of a gene that negatively regulates T cell fitness is accomplished using CRISPR / CAS methodology. Illustrative methods of using the CRISPR / Cas system to reduce gene expression are described in various publications, e.g., U.S. Patent Application Publication No. 2014 / 0170753. A CRISPR / Cas system includes a Cas protein and at least one to two ribonucleic acids that hybridize to a target motif in the gene and direct the Cas protein to the target motif. Any CRISPR / Cas system that is capable of altering a target polynucleotide sequence in a cell can be used. In some embodiments, the CRISPR Cas system is a CRISPR type I system, in some embodiments, the CRISPR / Cas system is a CRISPR type II system. In some embodiments, the CRISPR / Cas system is a CRISPR type V system.

[0053] The Cas protein used in the invention can be a naturally occurring Cas protein or a functional derivative thereof. A “functional derivative” includes, but are not limited to, fragments of a native sequence and derivatives of a native sequence polypeptide and its fragments, provided that they have a biological activity in common with a corresponding native sequence polypeptide. A biological activity contemplated herein is the ability of the functional derivative to hydrolyze a DNA substrate into fragments. The term “derivative” encompasses both amino acid sequence variants of polypeptide, covalent modifications, and fusions thereof such as derivative Cas proteins. Suitable derivatives of a Cas polypeptide or afragment thereof include but are not limited to mutants, fusions, covalent modifications of Cas protein or a fragment thereof.

[0054] There are three main types of Cas nucleases (type I, type II, and type III), and 10 subtypes including 5 type I, 3 type II, and 2 type III proteins (see, e.g., Hochstrasser and Doudna, Trends Biochem Sci, 2015:40(l):58-66). Type II Cas nucleases include Casl, Cas2, Csn2, and Cas9. These Cas nucleases are known to those skilled in the art. For example, the amino acid sequence of the Streptococcus pyogenes wild-type Cas9 polypeptide is set forth, e.g., in NBCI Ref. Seq. No. NP_269215, and the amino acid sequence of Streptococcus thermophilus wild-type Cas9 polypeptide is set forth, e.g., in NBCI Ref. Seq. No.WP 011681470. Some CRISPR-related endonucleases that may be used in methods described herein are disclosed, e.g., in U.S. Application Publication Nos. 2014 / 0068797, 2014 / 0302563, and 2014 / 0356959. Non-limiting examples of Cas nucleases include Casl, CaslB, Cas2, Cas3, Cas4, Cas5, Cas6, Cas7, Cas8, Cas9 (also known as Csnl and Csxl2), CaslO, Csyl, Csy2, Csy3, Csel, Cse2, Cscl, Csc2, Csa5, Csn2, Csm2, Csm3, Csm4, Csm5, Csm6, Cmrl, Cmr3, Cmr4, Cmr5, Cmr6, Csbl, Csb2, Csb3, Csxl7, Csxl4, CsxlO, Csxl6, CsaX, Csx3, Csxl, Csxl5, Csfl, Csf2, Csf3, Csf4, homologs thereof, variants thereof, mutants thereof, and derivatives thereof.

[0055] Cas9 homologs are found in a wide variety of eubacteria, including, but not limited to bacteria of the following taxonomic groups: Actinobacteria, Aquificae, Bacteroidetes-Chlorobi, Chlamydiae-Verrucomicrobia, Chlroflexi, Cyanobacteria, Firmicutes, Proteobacteria, Spirochaetes, and Thermotogae. An exemplary Cas9 protein is the Streptococcus pyogenes Cas9 protein. Additional Cas9 proteins and homologs thereof are described in, e.g., Chylinksi, et al., RNA Biol. 2013 May 1; 10(5): 726-737; Nat. Rev.Microbiol. 2011 June; 9(6): 467-477; Hou, et al., Proc Natl Acad Sci USA. 2013 Sep 24;110(39):15644-9; Sampson et al., Nature. 2013 May 9; 497(7448):254-7; and Jinek, et al., Science. 2012 Aug 17;337(6096):816-21. Variants of any of the Cas9 nucleases provided herein can be optimized for efficient activity or enhanced stability in the host cell. Thus, engineered Cas9 nucleases are also contemplated. Cas 9 from Streptococcus pyogenes contains 2 endonuclease domains, including an RuvC-like domain that cleaves target DNA that is noncomplementary to crRNA, and an HNH nuclease domain that cleave target DNA complementary to crRNA. The double-stranded endonuclease activity of Cas9 also involves a short conserved sequence, (2-5 nucleotides), known as a protospacer-associated motif (PAM), which follows immediately 3 '- of a target motif in the target sequence

[0056] Additionally, Cas nucleases, e.g., Cas9 polypeptides, can be derived from a variety of bacterial species including, but not limited to, Veillonella atypical, Fusobacterium nucleatum, Filifactor alocis, Solobacterium moorei, Coprococcus cams. Treponema demicola, Peptoniphilus duerdenii, Catenibacterium mitsuokai, Streptococcus mutans, Listeria innocua, Staphylococcus pseudintermedius, Acidaminococcus intestine, Olsenella uli, Oenococcus kitaharae, Bifidobacterium bifidum, Lactobacillus rhamnosus, Lactobacillus gasseri, Finegoldia magna, Mycoplasma mobile, Mycoplasma gallisepticum, Mycoplasma ovipneumoniae, Mycoplasma canis, Mycoplasma synoviae, Eubacterium rectale, Streptococcus thermophilus, Eubacterium dolichum, Lactobacillus coryniformis subsp.Torquens, Ilyobacter polytropus, Ruminococcus albus, Akkermansia muciniphila, Acidothermus cellulolyticus, Bifidobacterium longum, Bifidobacterium dentium, Corynebacterium diphtheria, Elusimicrobium minutum, Nitratifractor salsuginis, Sphaerochaeta globus, Fibrobacter succinogenes subsp. Succinogenes, Bacteroides fragilis, Capnocytophaga ochracea, Rhodopseudomonas palustris, Prevotella micans, Prevotella ruminicola, Flavobacterium columnare, Aminomonas paucivorans, Rhodospirillum rubrum, Candidatus Puniceispirillum marinum, Verminephrobacter eiseniae, Ralstonia syzygii, Dinoroseobacter shibae, Azospirillum, Nitrobacter hamburgensis, Bradyrhizobium, Wolinella succinogenes, Campylobacter jejuni subsp. Jejuni, Helicobacter mustelae, Bacillus cereus, Acidovorax ebreus, Clostridium perfringens, Parvibaculum lavamentivorans, Roseburia intestinalis, Neisseria meningitidis, Pasteurella multocida subsp. Multocida, Sutterella wadsworthensis, proteobacterium, Legionella pneumophila, Parasutterella excrementihominis, Wolinella succinogenes, and Francisella novicida.

[0057] Other RNA-mediated nucleases include Cpfl (See, e.g., Zetsche etal., Cell, Volume 163, Issue 3, p759-771, 22 October 2015) and homologs thereof.

[0058] As used herein, the term “Cas9 ribonucleoprotein” complex and the like refers to a complex between the Cas9 protein and a guide RNA, the Cas9 protein and a crRNA, the Cas9 protein and a trans-activating crRNA (tracrRNA), or a combination thereof (e.g., a complex containing the Cas9 protein, a tracrRNA, and a crRNA guide RNA). It is understood that in any of the embodiments described herein, a Cas9 nuclease can be subsitututed with another RNA-mediated nuclease, e.g., an alternative Cas protein or a Cpfl nuclease.

[0059] In some embodiments, the Cas protein is introduced into T cells in polypeptide form. Thus, for example, in certain embodiments, the Cas proteins can be conjugated to orfused to a cell-penetrating polypeptide or cell-penetrating peptide that is well known in the art. Non-limiting examples of cell-penetrating peptides include those provided in Milletti F, “Drug Discov. Today 17: 850-860, 2012, the relevant disclosure of which is hereby incorporated by reference in its entirety. In some cases, T cells may be genetically engineered to produce the Cas protein.

[0060] In some embodiments, a Cpfl nuclease or the Cas9 nuclease and the gRNA are introduced into the cell as a ribonucleoprotein (RNP) complex.

[0061] In some embodiments, the RNP complex may be introduced into about 1 x 105to about 2 * 106cells (e.g., 1x105cells to about 5 x io5cells, about 1 x io5cells to about 1 x 106cells, 1 x 105cells to about 1.5 x io6cells, 1 x io5cells to about 2 x io6cells, about 1 x 106cells to about 1.5 x io6cells, or about 1 x io6cells to about 2 x io6cells). In some embodiments, the cells are cultured under conditions effective for expanding the population of modified cells. Also disclosed herein is a population of cells, in which the genome of at least 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, 99% or greater of the cells comprises a genetic modification or heterologous polynucleotide that inhibits expression of a gene that negatively regulates T cell fitness as described herein. In some embodiments, the population comprises subpopulations of cells each of which subpopulations have a different genetic modification to inhibit expression of the gene as described herein.

[0062] In some embodiments, the RNP complex is introduced into the T cells by electroporation. Methods, compositions, and devices for electroporating cells to introduce a RNP complex are available in the art, see, e.g., WO 2016 / 123578, WO / 2006 / 001614, and Kim, J. A. etal. Biosens. Bioelectron. 23, 1353-1360 (2008). Additional or alternative methods, compositions, and devices for electroporating cells to introduce a RNP complex can include those described in U.S. Patent Appl. Pub. Nos. 2006 / 0094095; 2005 / 0064596; or 2006 / 0087522; Li, L.H. etal. Cancer Res. Treat. 1, 341-350 (2002); U.S. Patent Nos.:6,773,669; 7,186,559; 7,771,984; 7,991,559; 6,485,961; 7,029,916; and U.S. Patent Appl. Pub. Nos: 2014 / 0017213; and 2012 / 0088842; Geng, T. etal., J. Control Release 144, 91-100 (2010); and Wang, J., etal. Lab. Chip 10, 2057-2061 (2010).

[0063] In some embodiments, the Cas9 protein can be in an active endonuclease form, such that when bound to target nucleic acid as part of a complex with a guide RNA or part of a complex with a DNA template, a double strand break is introduced into the target nucleic acid. In the methods provided herein, a Cas9 polypeptide or a nucleic acid encoding a Cas9polypeptide can be introduced into the T cell. The double strand break can be repaired by HDR to insert the DNA template into the genome of the T cell. Various Cas9 nucleases can be utilized in the methods described herein. For example, a Cas9 nuclease that requires an NGG protospacer adjacent motif (PAM) immediately 3’ of the region targeted by the guide RNA can be utilized. Such Cas9 nucleases can be targeted to a region in exon 1 of the TRAC or exon 1 of the TRAB that contains an NGG sequence. As another example, Cas9 proteins with orthogonal PAM motif requirements can be used to target sequences that do not have an adjacent NGG PAM sequence. Exemplary Cas9 proteins with orthogonal PAM sequence specificities include, but are not limited to those described in Esvelt et al., Nature Methods 10: 1116-1121 (2013).

[0064] In some cases, the Cas9 protein is a nickase, such that when bound to target nucleic acid as part of a complex with a guide RNA, a single strand break or nick is introduced into the target nucleic acid. A pair of Cas9 nickases, each bound to a structurally different guide RNA, can be targeted to two proximal sites of a target genomic region and thus introduce a pair of proximal single stranded breaks into the target genomic region, for example exon 1 of a TRAC gene or exon 1 of a TRBC gene. Nickase pairs can provide enhanced specificity because off-target effects are likely to result in single nicks, which are generally repaired without lesion by base-excision repair mechanisms. Illustrative Cas9 nickases include Cas9 nucleases having a D10A or H840A mutation (See, for example, Jinek et al., Science 337:816-821, 2012; Qi et al., Cell, 152(5): 1173-1183, 2012; Ran et al., Cell 154: 1380-1389, 2013). In one embodiment, the Cas9 polypeptide from Streptococcus pyogenes comprises at least one mutation at position D10, G12, G17, E762, H840, N854, N863, H982, H983, A984, D986, A987 or any combination thereof. Descriptions of such dCas9 polypeptides and variants thereof are provided in, for example, International Patent Publication No. WO 2013 / 176772. The Cas9 enzyme may contain a mutation at D10, E762, H983, or D986, as well as a mutation at H840 or N863. In some instances, the Cas9 enzyme may contain a D10A or DION mutation. In further embodiments, the Cas9 enzyme may contain a H840A, H840Y, or H840N. In some embodiments, the Cas9 enzyme may contain D10A and H840A; D10A and H840Y; D10A and H840N; DION and H840A; DION and H840Y; or DION and H840N substitutions. The substitutions can be conservative or non-conservative substitutions to render the Cas9 polypeptide catalytically inactive and able to bind to target DNA.

[0065] In some embodiments, the Cas nuclease can be a high-fidelity or enhanced specificity Cas9 polypeptide variant with reduced off-target effects and robust on-targetcleavage. Non-limiting examples of Cas9 polypeptide variants with improved on-target specificity include the SpCas9 (K855A), SpCas9 (K810A / K1003A / R1060A) (also referred to as eSpCas9(1.0)), and SpCas9 (K848A / K1003A / R1060A) (also referred to as eSpCas9(l.l)) variants described in Slaymaker et al. , Science, 351(6268) :84-8 (2016), and the SpCas9 variants described in Kleinstiver etal., Nature, 529(7587):490-5 (2016) containing one, two, three, or four of the following mutations: N497A, R661 A, Q695A, and Q926A (e.g., SpCas9-HFl contains all four mutations).

[0066] In some embodiments, the target motifs can be selected to minimize off-target effects of the CRISPR / Cas systems of the present invention. For example, in some embodiments, the target motif is selected such that it contains at least two mismatches when compared with all other genomic nucleotide sequences in the cell. In some embodiments, the target motif is selected such that it contains at least one mismatch when compared with all other genomic nucleotide sequences in the cell. Those skilled in the art will appreciate that a variety of techniques can be used to select suitable target motifs for minimizing off-target effects (e.g., bioinformatics analyses).

[0067] In some embodiments, CRISPRi is employed for sequence-specific repression of gene expression of a gene described herein. Description of CRISPRi methods is provided, e.g., in Engreitz etal., Cold Spring Harb Per spect Biol, 2019, 1 l:a035386. In some embodiments, the CRISPRi system includes a dCas9 polypeptide or a dCasl2 polypeptide operably linked to a repression domain. In some embodiments, the repression domain is selected from the group consisting of a Kriippel-associated box (KRAB) repressor domain, a NuE repressor domain, a NcoR repressor domain, a SID repressor domain, a SID4X repressor domain, an EZH2 repressor domain, a FOG repressor domain, a DNMT3 A repressor domain, and a DNMT3L repressor domain.

[0068] In some embodiments, CRISPRoff is employed to silence a gene that negatively regulates T cell fitness (see, e.g., Nunez JK, Chen J, Pommier GC, et al. Genome-wide programmable transcriptional memory by CRISPR-based epigenome editing. Cell, 2021;0(0). doi: 10.1016 / j .cell.2021.03.02.)

[0069] In some embodiments, base editing to introduce point mutations into a gene is employed to inhibit or inactivate a gene that negatively regulates T cell fitness. For example, DNA base editors comprise fusions between a catalytically impaired Cas nuclease and a base-modification enzyme, such as a cytosine deaminase that operates on single-strandedDNA (ssDNA), but not double-stranded DNA (dsDNA). Upon binding to its target locus in DNA, base pairing between a guide RNA and target DNA strand leads to displacement of a small segment of single-stranded DNA in an R loop. DNA bases within this single-stranded DNA bubble are modified by the deaminase enzyme. To improve efficiency in eukaryotic cells, the catalytically disabled nuclease also generates a nick in the non-edited DNA strand, inducing cells to repair the non-edited strand using the edited strand as a template. DNA base editors are available that can mediate all four possible transition mutations (C to T, A to G, T to C, and G to A). See, for example Rees & Liu, Nat. Rev. Genet. 19:770-788, 2008 and references cited therein.

[0070] As used throughout, a guide nucleic acid sequence, typically a guide RNA (gRNA) sequence, is a sequence that interacts with a site-specific or targeted nuclease and specifically binds to or hybridizes to a target nucleic acid within the genome of a cell, such that the gRNA and the targeted nuclease co-localize to the target nucleic acid in the genome of the cell. Each gRNA includes a DNA targeting sequence or protospacer sequence of about 10 to 50 nucleotides in length that specifically binds to or hybridizes to a target DNA sequence in the genome. For example, the targeting sequence may be about 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, or 50 nucleotides in length. In some embodiments, the gRNA comprises a crRNA sequence and a transactivating crRNA (tracrRNA) sequence. In some embodiments, the gRNA does not comprise a tracrRNA sequence.

[0071] The sgRNAs can be selected depending on the particular CRISPR / Cas system employed, and the sequence of the target polynucleotide, as will be appreciated by those skilled in the art. As indicated above, in some embodiments, the one to two ribonucleic acids can also be selected to minimize hybridization with nucleic acid sequences other than the target polynucleotide sequence. In some embodiments, the one to two ribonucleic acids hybridize to a target motif that contains at least two mismatches when compared with all other genomic nucleotide sequences in the cell. In some embodiments, the one to two ribonucleic acids hybridize to a target motif that contains at least one mismatch when compared with all other genomic nucleotide sequences in the cell. In some embodiments, the one to two ribonucleic acids are designed to hybridize to a target motif immediately adjacent to a deoxyribonucleic acid motif recognized by the Cas protein. In some embodiments, each of the one to two ribonucleic acids are designed to hybridize to target motifs immediately adjacent to deoxyribonucleic acid motifs recognized by the Cas protein which flank a mutantallele located between the target motifs. Guide RNAs can also be designed using software that are readily available, for example, at the website crispr.mit.edu. The one or more sgRNAs can be transfected into T cells in which Cas protein is present by transfection, according to methods known in the art.

[0072] In some cases, the DNA targeting sequence can incorporate wobble or degenerate bases to bind multiple genetic elements. In some cases, the 19 nucleotides at the 3’ or 5’ end of the binding region are perfectly complementary to the target genetic element or elements. In some cases, the binding region can be altered to increase stability. For example, nonnatural nucleotides, can be incorporated to increase RNA resistance to degradation. In some cases, the binding region can be altered or designed to avoid or reduce secondary structure formation in the binding region. In some cases, the binding region can be designed to optimize G-C content. In some cases, G-C content is preferably between about 40% and about 60% (e.g., 40%, 45%, 50%, 55%, 60%).

[0073] In some embodiments, the sequence of the gRNA, or a portion thereof is designed to complement (e.g., perfectly complement) or substantially complement (e.g., 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% complement) the target region in the gene. In some embodiments, the portion of the gRNA that complements and binds the targeting region in the polynucleotide is, or is about, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39 or 40 or more nucleotides in length. In some cases, the portion of the gRNA that complements and binds the targeting region in the polynucleotide is between about 19 and about 21 nucleotides in length. In some cases, the gRNA may incorporate wobble or degenerate bases to bind target regions. In some cases, the gRNA can be altered to increase stability. For example, non-natural nucleotides, can be incorporated to increase RNA resistance to degradation. In some cases, the gRNA can be altered or designed to avoid or reduce secondary structure formation. In some cases, the gRNA can be designed to optimize G-C content. In some cases, G-C content is between about 40% and about 60% (e.g, 40%, 45%, 50%, 55%, 60%). In some cases, the binding region can contain modified nucleotides such as, without limitation, methylated or phosphorylated nucleotides.

[0074] In some embodiments, the gRNA can be optimized for expression by substituting, deleting, or adding one or more nucleotides. In some cases, a nucleotide sequence that provides inefficient transcription from an encoding template nucleic acid can be deleted orsubstituted. For example, in some cases, the gRNA is transcribed from a nucleic acid operably linked to an RNA polymerase III promoter. In such cases, gRNA sequences that result in inefficient transcription by RNA polymerase III, such as those described in Nielsen etal., Science. 2013 Jun 28;340(6140): 1577-80, can be deleted or substituted. For example, one or more consecutive uracils can be deleted or substituted from the gRNA sequence. In some cases, if the uracil is hydrogen bonded to a corresponding adenine, the gRNA sequence can be altered to exchange the adenine and uracil. This “A-U flip” can retain the overall structure and function of the gRNA molecule while improving expression by reducing the number of consecutive uracil nucleotides.

[0075] In some embodiments, the gRNA can be optimized for stability. Stability can be enhanced by optimizing the stability of the gRNAmuclease interaction, optimizing assembly of the gRNAmuclease complex, removing or altering RNA destabilizing sequence elements, or adding RNA stabilizing sequence elements. In some embodiments, the gRNA contains a 5’ stem -loop structure proximal to, or adjacent to, the region that interacts with the gRNA-mediated nuclease. Optimization of the 5’ stem-loop structure can provide enhanced stability or assembly of the gRNAmuclease complex. In some cases, the 5’ stem-loop structure is optimized by increasing the length of the stem portion of the stem-loop structure.

[0076] gRNAs can be modified by methods known in the art. In some cases, the modifications can include, but are not limited to, the addition of one or more of the following sequence elements: a 5’ cap e.g., a 7-methylguanylate cap); a 3’ polyadenylated tail; a riboswitch sequence; a stability control sequence; a hairpin; a subcellular localization sequence; a detection sequence or label; or a binding site for one or more proteins.Modifications can also include the introduction of non-natural nucleotides including, but not limited to, one or more of the following: fluorescent nucleotides and methylated nucleotides.

[0077] Also provided herein are expression cassettes and vectors for producing gRNAs in a host cell. The expression cassettes can contain a promoter (e.g., a heterologous promoter) operably linked to a polynucleotide encoding a gRNA. The promoter can be inducible or constitutive. The promoter can be tissue specific. In some cases, the promoter is a U6, Hl, or spleen focus-forming virus (SFFV) long terminal repeat promoter. In some cases, the promoter is a weak mammalian promoter as compared to the human elongation factor 1 promoter (EFl A). In some cases, the weak mammalian promoter is a ubiquitin C promoter or a phosphoglycerate kinase 1 promoter (PGK). In some cases, the weak mammalianpromoter is a TetOn promoter in the absence of an inducer. In some cases, when a TetOn promoter is utilized, the host cell is also contacted with a tetracycline transactivator. In some embodiments, the strength of the selected gRNA promoter is selected to express an amount of gRNA that is proportional to the amount of Cas9 or dCas9. The expression cassette can be in a vector, such as a plasmid, a viral vector, a lentiviral vector, etc. In some cases, the expression cassette is in a host cell. The gRNA expression cassette can be episomal or integrated in the host cell.Modifications using alternative targeted nuclease systems

[0078] In some embodiments, a targeted nuclease that is employed in modifying a T cell to inhibit expression of a gene is a transcription activator-like effector nuclease (TALEN), a zinc finger nuclease (ZFN) or a megaTAL (See, for example, Merkert and Martin “Site-Specific Genome Engineering in Human Pluripotent Stem Cells,” Int. J. Mol. Sci. 18(7): 1000 (2016)).Zinc-finger nuclease to inhibit T-cell negative regulators of T-cell fitness

[0079] In some embodiments, modified T cells comprising a gene-targeted alteration are produced by inhibiting expression using ZFN. Methods of using the ZFNs to reduce gene expression are described, e.g., in U.S. Patent No. 9,045,763, and also in Durai etal., Nucleic Acid Research 33:5978-5990, 2005; Carroll etal. Genetics Society of America 188: 773-782, 2011; and Kim etal. Proc. Natl. Acad. Sci. USA 93: 1156-1160.

[0080] A ZFN comprises a FokI nuclease domain (or derivative thereof) fused to a DNA-binding domain. In the case of a ZFN, the DNA-binding domain comprises one or more zinc fingers. A zinc finger is a small protein structural motif stabilized by one or more zinc ions. A zinc finger can comprise, for example, Cys2His2, and can recognize an approximately 3-bp sequence. Various zinc fingers of known specificity can be combined to produce multi-finger polypeptides which recognize about 6, 9, 12, 15 or 18-bp sequences. Various selection and modular assembly techniques are available to generate zinc fingers (and combinations thereof) recognizing specific sequences, including phage display, yeast one-hybrid systems, bacterial one-hybrid and two-hybrid systems, and mammalian cells.

[0081] A ZFN dimerizes to cleave DNA. Thus, a pair of ZFNs are used to target non-palindromic DNA sites. The two individual ZFNs bind opposite strands of the DNA with their nucleases properly spaced apart (see, e.g., Bitinaite et al. , Proc. Natl. Acad. Sci. USA 95:10570-5, 1998). A ZFN can create a double-stranded break in the DNA, which can create a frame-shift mutation if improperly repaired, leading to a decrease in the expression and level of expression of the target gene in a cell in a cell.TALENs to inhibit a T cell gene that negatively regulates T cell function

[0082] In some embodiments, T cells that comprise a targeted alteration are produced by inhibiting the desired gene that negatively regulates T-cell fitness with transcription activatorlike effector nucleases (TALENS). TALENs are similar to ZFNs in that they bind as a pair around a genomic site and direct a non-specific nuclease, e.g., FoKI, to cleave the genome at a specific site, but instead of recognizing DNA triplets, each domain recognizes a single nucleotide. Methods of using TALENS to reduce gene expression are disclosed, e.g., in U.S. Patent No. 9,005,973; Christian et al. “Genetics 186(2): 757-761, 2010; Zhang et al. 2011 Nature Biotech. 29: 149-53, 2011; Geibler et al. 2011 PLoS ONE 6: el9509, 2011; Boch et al. 2009 Science 326: 1509-12; Moscou et al. 2009 Science 326: 3501.

[0083] To produce a TALENT, a TALE protein is typically fused to a FokI endonuclease, which can be a wild-type or mutated FokI endonuclease. Several mutations to FokI have been made for its use in TALENs; these, for example, improve cleavage specificity or activity. Cermak et al, Nucl. Acids Res. 39:e82, 2011; Miller et al, Nature Biotech. 29:143-8, 2011; Hockemeyer et al., Nature Biotech. 29:731-734, 2011; Wood et al., Science 333:307, 2011; Doyon et al, Nature Methods 8:74-79, 2010; Szczepek etal., Nature Biotech.25:786-793, 2007; and Guo etal., J. Mol. Biol. 200:96, 2010.

[0084] The FokI domain functions as a dimer and typically employ two constructs with unique DNA binding domains for sites in the target genome with proper orientation and spacing. Both the number of amino acid residues between the TALE DNA binding domain and the FokI cleavage domain and the number of bases between the two individual TALEN binding sites appear to be important parameters for achieving high levels of activity, (e.g., Miller et al., 2011, supra).Meganucleases

[0085] “Meganucleases” are rare-cutting endonucleases or homing endonucleases that can be highly specific, recognizing DNA target sites ranging from at least 12 base pairs in length, e.g., from 12 to 40 base pairs or 12 to 60 base pairs in length. Meganucleases can be modular DNA-binding nucleases such as any fusion protein comprising at least one catalytic domainof an endonuclease and at least one DNA binding domain or protein specifying a nucleic acid target sequence. The DNA-binding domain can contain at least one motif that recognizes single- or double-stranded DNA. The meganuclease can be monomeric or dimeric.

[0086] In some embodiments of the methods described herein, meganucleases may be used to inhibit the expression of a gene as described herein. In some instances, the meganuclease is naturally-occurring (found in nature) or wild-type, and in other instances, the meganuclease is non-natural, artificial, engineered, synthetic, or rationally designed. In certain embodiments, the meganucleases that may be used in methods described herein include, but are not limited to, an I-Crel meganuclease, I-Ceul meganuclease, I-Msol meganuclease, I-Scel meganuclease, variants thereof, mutants thereof, and derivatives thereof.

[0087] Detailed descriptions of useful meganucleases and their application in gene editing are found, e.g., in Silva et al., Curr Gene Ther, 2011, 11(1): 11-27; Zaslavoskiy et al., BMC Bioinformatics, 2014, 15:191; Takeuchi et al., Proc Natl Acad Sci USA, 2014, 111(11):4061-4066, and U.S. Patent Nos. 7,842,489; 7,897,372; 8,021,867; 8,163,514; 8,133,697; 8,021,867; 8,119,361; 8,119,381; 8,124,36; and 8,129,134.

[0088] Efficiency of the inhibition of expression of a T cell gene using a method as described herein can be assessed by measuring the amount of mRNA or protein using methods well known in the art, for example, quantitative PCR, western blot, flow cytometry, etc and the like. In some embodiments, the level of protein is evaluated to assess efficiency of inhibition efficiency. In certain embodiments, the efficiency of reduction of target gene expression is at least 5%, at least 10%, at least 20%, at least 30%, at least 50%, at least 60%, or at least 80%, or at least 90%, or greater, as compared to corresponding cells that do not have the targeted modification. In certain embodiments, the efficiency of reduction is from about 10% to about 90%. In certain embodiments, the efficiency of reduction is from about 30% to about 80%. In certain embodiments, the efficiency of reduction is from about 50% to about 80%. In some embodiments, the efficiency of reduction is greater than or equal to about 80%.

[0089] In some embodiments, a T cell modified as described herein to inhibit a gene that negatively regulates T-cell fitness comprises one or more additional genetic modifications to tailor T-cell activity. In some embodiments, a T cell that is modified to inhibit expression of a negative regulator of T-cell fitness is further modified to express a synthetic chimeric receptor construct containing an extracellular binding domain, e.g., a variable region from anantibody that binds to an antigen and an intracellular signaling domain. In some embodiments, the synthetic T-cell receptor-based construct is a CAR (chimeric antigen receptor), which comprises an extracelluar binding domain that targets an antigen and an intracellular signaling domain that can activate or stimulate an immunoresponsive cell upon engagement of the extracellular domain with a target antigen. In certain embodiments, the CAR also comprises a transmembrane domain. In some embodiments, the chimeric receptor is a TCR like fusion molecule. Examples of such TCR fusion molecules include an HLA-Independent TCR-based Chimeric Antigen Receptor (also known as “HIT-CAR”, e.g., those disclosed in International Patent Application No. PCT / US19 / 017525), T cell receptor fusion constructs (TRuCs) (e.g., those disclosed in Baeuerle et al., “Synthetic TRuC receptors engaging the complete T cell receptor for potent anti-tumor response,” Nature Comm. 10: 2087 (2019), synthetic T cell receptor and antigen receptors (STARs) (e.g., those disclosed in Liu et al. Science Translational Medicine 13(586):eabb5191, 2021), antibody-T-cell receptor (AbTCR) (e.g., those disclosed in Xu et al. Cell Discovery (2018) 4:62), and T cell antigen coupler (TAC) (e.g., those disclosed in Helsen et al. Nature Communications (2018);9:3049).Treatment Methods and Compositions

[0090] Any of the methods described herein may be used to modify T cells obtained from a human subject. T cells modified in accordance with the invention may be used to treat any number of cancers, including solid tumors.Methods of Treating Cancer

[0091] In some embodiments, T cells are modified to decrease expression of one or more genes that negatively regulate T cell fitness as described herein. In some embodiments, a gene that is modified is SPTLC2, STT3B, PPIAL4D, LRTG3, GNA13, STUB1, GNAS, FAM76A, ALDH3B1, JMJD8, FBXO45, FDXR, H2AFB3, PPP6C, GOLGA1, NFKBIA, ALG3, DPEP2, CLTC, MBNL3, ERF, SYNDIG1L, Cllorf57, GTF2A2, CSNK2A1, GBE1, GNB2, HIST1H2AI, INPPL1, NT5C2, FRMD3, GARS, SIKE1, EDC4, SOCS1, EBF2, PPARG, BICC1, MDGA2, KAT8, PTPN2, CHRNB2, BRWD3, MAP4K1, REV3L, P2RY8, NR1H2, FAM3A, ADPRHL1, DUSP9, PTGER4, SATB1, RBF0X2, ZC3H12A, C12orf66, TCHH, WNT9A, MAF, SIGLEC12, MMP3, SPINK6, SOX18, PLEKHB1, CIC, TMEM127, MAP4K1, COL1A2, USP22, FAM179A, BRINP1, RORB, RGS7BP, MEF2D, FAM170A, CUTC, ZNF513, TFAP2E, CMTM4, CYP3A5, PPP1R3G, WWTR1, LRRC61, ZNF772, ADGRL4, TMCC2, SOS2, ACTA1, ANO4, B3GAT1, MSI2, C15orf61, SLC30A1, S1PR1,GNA13, PTGER4, BASP1, KCNA5, ZNF835, FKBP1A, P0U5F1B, ADPRHL1, PRR19, ESRRA, SLX1A, ATF5, TMEM43, CUTC, SLC6A8, KRTAP8-1, P2RY8, MAN2C1, PDLIM7, CEBPB, CT47A2, CST7, C15orf56, F0XI2, SUN1, SHISA3, OR10A7, MUSTN1, ZNF227, CCNY, RORB, CALML3, GPR132, KLHL14, SOX30, USP49, SLC35E4, S0X11, WNT9A, GALNT11, PPM1H, PP2D1, PCGF2, FAM216A, or ADGRL4. Thus, in some embodiments, provided herein is a method of treating cancer in a human subject comprising: a) obtaining T cells, e.g., CD8+ cells, from the subject; b) modifying the T cells using any of the methods provided herein to decrease expression of a negative regulator of T cell fitness as described herein; and c) administering the modified T cells to the subject.

[0092] In some embodiments, T cells, e.g.,CD8+ T cells, obtained from a human subject that has cancer may be expanded ex vivo. The characteristics of the subject’s cancer may determine a set of tailored cellular modifications (e.g., selection of one or more gene targets), and these modifications may be applied to the T cells using any of the methods described herein. Modified T cells may then be reintroduced to the subject. This strategy capitalizes on and enhances the function of the subject’s natural repertoire of cancer specific T cells, providing a diverse arsenal to eliminate mutagenic cancer cells quickly.

[0093] Any cancer can be treated with genetically modified T cells as described herein. In some embodiments, the cancer is a carcinoma or a sarcoma. In some embodiments, the cancer is a hematological cancer. In some embodiments, the cancer is breast cancer, prostate cancer, testicular cancer, renal cell cancer, bladder cancer, liver cancer, ovarian cancer, cervical cancer, endometrial cancer, lung cancer, colorectal cancer, anal cancer, pancreatic cancer, gastric cancer, esophageal cancer, hepatocellular cancer, kidney cancer, head and neck cancer, glioblastoma, mesothelioma, melanoma, a chondrosarcoma, or a bone or soft tissue sarcoma. In some embodiments, the cancer is adrenocortical carcinoma, anal cancer, appendix cancer, astrocytoma, basal-cell carcinoma, bile duct cancer, bone tumor, brainstem glioma, brain cancer, cerebellar astrocytoma, cerebral astrocytoma, ependymoma, medulloblastoma, supratentorial primitive neuroectodermal tumors, visual pathway and hypothalamic glioma, or bronchial adenomas. In some embodiments, the cancer is acute lymphoblastic leukemia, acute myeloid leukemia, Burkitt's lymphoma, central nervous system lymphoma, chronic lymphocytic leukemia, chronic myelogenous leukemia, hairy cell leukemia, chronic myeloproliferative disorders, a myelodysplastic syndrome, an adult acute myeloproliferative disorder, multiple myeloma, cutaneous T-cell lymphoma, Hodgkin lymphoma, or non-Hodgkin lymphoma. In some embodiments, the cancer is desmoplasticsmall round cell tumor, ependymoma, epithelioid hemangioendothelioma (EHE), Ewing's sarcoma, extracranial germ cell tumor, extragonadal germ cell tumor, extrahepatic bile duct cancer, intraocular melanoma, retinoblastoma, gallbladder cancer, gastrointestinal carcinoid tumor, gastrointestinal stromal tumor (GIST), germ cell tumor, gestational trophoblastic tumor, gastric carcinoid, heart cancer, hypopharyngeal cancer, hypothalamic and visual pathway glioma, childhood, intraocular melanoma, islet cell carcinoma, Kaposi sarcoma, laryngeal cancer, lip and oral cavity cancer, liposarcoma, non-small cell lung cancer, smallcell lung cancer, macroglobulinemia, male breast cancer, malignant fibrous histiocytoma of bone, medulloblastoma, melanoma, Merkel cell cancer, mesothelioma, metastatic squamous neck cancer, mouth cancer, multiple endocrine neoplasia syndrome, mycosis fungoides, chronic, myxoma, nasal cavity and paranasal sinus cancer, nasopharyngeal carcinoma, neuroblastoma, oligodendroglioma, oral cancer, oropharyngeal cancer, osteosarcoma, ovarian epithelial cancer, ovarian germ cell tumor, ovarian low malignant potential tumor, paranasal sinus and nasal cavity cancer, parathyroid cancer, penile cancer, pharyngeal cancer, pheochromocytoma, pineal astrocytoma, pineal germinoma, pineoblastoma, supratentorial primitive neuroectodermal tumors, pituitary adenoma, plasma cell neoplasia, pleuropulmonary blastoma, primary central nervous system lymphoma, renal cell carcinoma, retinoblastoma, rhabdomyosarcoma, salivary gland cancer, uterine sarcoma, Sezary syndrome, non-melanoma skin cancer, melanoma Merkel cell carcinoma, small intestine cancer, squamous cell carcinoma, squamous neck cancer, throat cancer, thymoma, thyroid cancer, transitional cell cancer of the renal pelvis and ureter, trophoblastic tumor, gestational, urethral cancer, uterine cancer, vaginal cancer, vulvar cancer, Waldenstrom macroglobulinemia, or Wilms tumor.

[0094] In certain embodiments, the genetically modified T cells, or individual populations of sub-types of the genetically modified T cells, are administered to the subject at a range of about one million to about 100 billion cells, such as, e.g., 1 million to about 50 billion cells (e.g., about 5 million cells, about 25 million cells, about 500 million cells, about 1 billion cells, about 5 billion cells, about 20 billion cells, about 30 billion cells, about 40 billion cells, or a range defined by any two of the foregoing values), such as about 10 million to about 100 billion cells (e.g., about 20 million cells, about 30 million cells, about 40 million cells, about 60 million cells, about 70 million cells, about 80 million cells, about 90 million cells, about 10 billion cells, about 25 billion cells, about 50 billion cells, about 75 billion cells, about 90 billion cells, or a range defined by any two of the foregoing values), and in some cases about100 million cells to about 50 billion cells (e.g., about 120 million cells, about 250 million cells, about 350 million cells, about 450 million cells, about 650 million cells, about 800 million cells, about 900 million cells, about 3 billion cells, about 30 billion cells, about 45 billion cells) or any value in between these ranges.

[0095] In some embodiments, the dose of total cells and / or dose of individual subpopulations of cells is within a range of between at or about 104and at or about 109cells / kilograms (kg) body weight, such as between 105and 106cells / kg body weight, for example, at least about 1 x 105cells / kg, 1.5 x 105cells / kg, 2 x 105cells / kg, 5 x 105cells / kg, or 1 x 106cells / kg body weight.

[0096] The appropriate dosage may depend on the type of cancer to be treated, the severity and course of the disease, previous therapy, the subject's clinical history and response to the cells, and the discretion of the attending physician. The compositions and cells are in some embodiments suitably administered to the subject at one time or over a series of treatments.

[0097] The cells can be administered by any suitable means, for example, by bolus infusion, by injection, e.g., intravenous, parenteral, and, if desired for local treatment, intralesional administration. Parenteral infusions include intramuscular, intravenous, intraarterial, intraperitoneal, or subcutaneous administration. In some embodiments, a given dose is administered by a single bolus administration of the cells. In some embodiments, it is administered by multiple bolus administrations of the cells, for example, over a period of no more than 3 days, or by continuous infusion administration of the cells.

[0098] In some embodiments, the cells are administered as part of a combination treatment, such as simultaneously with or sequentially with, in any order, another therapeutic intervention, such as an antibody or engineered cell or receptor or agent, such as a cytotoxic or therapeutic agent. The cells in some embodiments are co-administered with one or more additional therapeutic agents or in connection with another therapeutic intervention, either simultaneously or sequentially in any order. In some contexts, the cells are co-administered with another therapy sufficiently close in time such that the cell populations enhance the effect of one or more additional therapeutic agents, or vice versa. In some embodiments, the cells are administered prior to the one or more additional therapeutic agents. In some embodiments, the cells are administered after the one or more additional therapeutic agents.Screening Platform for Identifying Additional Genes that Modulate T Cell Function

[0099] In a further aspect, the disclosure provides a screening platform that provides the ability to screen large libraries of genetically modified T cells to identify genes that positively and negatively regulate T-cell function.

[0100] The platform employs an expression construct, e.g., a lentiviral plasmid, to express anti-CD3 scFv (also referred to herein as a “CD3 scFv”) in tumor cells that confers any tumor cells with the ability to activate any polyclonal TCR repertoire. In one instance, the expression construct comprises a polynucleotide comprising a sequence encoding a CD8 signal peptide, an anti-CD3 variable heavy sequence (VH), a linker sequence, an anti-CD3 variable light sequence (VL), a CD8 hinge, and a CD8 transmembrane domain, operably linked to an EF- la core promoter. In some embodiments, the anti-CD3 VH and VL are obtained from a commercial CD3 monoclonal antibody, such as OKT3, which recognizes an epitope on the epsilon-subunit within the human CD3 complex. Additional sequences can also be present in the construction, for example, a tag or marker sequence to identify the anti-CD3scFv expressed on transduced tumor cells.

[0101] The term “OKT3” refers to the anti-CD3 antibody produced by Miltenyi Biotech, Inc., San Diego, Calif., USA) and or biosimilar or variant thereof (e.g., a humanized, chimeric, or affinity matured variant). A hybridoma that produces OKT3 is available in the American Type Culture Collection and assigned the ATCC accession number CRL 8001. The OKT3 VH and VL region-expressing cells are also available from other commercial sources. In some embodiments, the scFV comprises a VH region having at least 95% identity, or at least 96%, 97%, 98%, or 99% identity, to the illustrative OKT3 VH amino acid sequence provided herein and a VL region having at least 95% identity, or at least 96%, 97%, 98%, or 99%, to the illustrative OKT3 VL amino acid sequence provided herein, e.g., as determined using NCBI Blast. In some embodiments, the scFV comprises a VH region comprising the illustrative OKT3 VH amino acid sequence provided herein and a VL region comprising the illustrative OKT3 VL amino acid sequence provided herein. The OKT3 antibody is described in detail in U.S. Patent No. 5,929,212. Additional information regarding binding domains that bind CD3, see U.S. Pat. No. 8785604, PCT / US 17 / 42264, and / or W002051871.

[0102] In some embodiments, the scFv comprises the VH and VL from an alternative anti-CD3 antibody such as TZLS-401, TR66, UCHT1, SP34, orL2K. In some embodiments, the construct may employ an alternative signal peptide and / or an alternative hinge, and / or analternative transmembrane domain. For example, in some embodiments, the construct may comprises a CD28 hinge and / or CD28 transmembrane domain and optionally, a CD28 signal peptide.

[0103] In some embodiments, the polynucleotide encoding the polynucleotide comprising the anti-CD3 scFv construct sequence is operably linked to a promoter other that EF-la, e.g., an alternative constitutive promoter including, but not limited to, a phosphoglycerate kinase- 1 (PGKF) promoter, a beta actin promoter, e.g., human beta actin or chicken beta actin promoter or a cytomegalovirus (CMV) enhancer fused to chicken beta-actin promoter, an SV40 promoter, a CMV immediate early promoter, a human Ubiquitin C promoter (UBC), or a spleen focus forming virus (SFFV) promoter.

[0104] The linker linking the VH and VL is generally composed of small, non-polar (e.g. Gly) or polar (e.g. Ser or Thr) amino acids, but may also comprise polar amino acids such as Lys and Glu, e.g., to improve solubility. The small size of these amino acids provides flexibility, and allows for mobility of the connecting functional domains. The incorporation of Ser or Thr can maintain the stability of the linker in aqueous solutions by forming hydrogen bonds with the water molecules, and therefore reduces the unfavorable interaction between the linker and the protein moieties. In some embodiments, flexible linkers are primarily composed of stretches of Gly and Ser residues (“GS” linker). An example of the most widely used flexible linker has the sequence of (Gly-Gly-Gly-Gly-Ser)n. By adjusting the copy number “n”, the length of this GS linker can be adjusted to achieve appropriate separation of the functional domains and / or to maintain necessary inter-domain interactions such that the scFv binds to the target. Additional examples of GS linkers include those having a formula (GS)n, (GSGGS)n, (GGSGGS)n, and (GGGS)n. Besides the GS linkers, many other flexible linkers have been designed for recombinant protein expression. A variety of different linkers are commercially available and are considered suitable for use.

[0105] Any tumor cell line can be engineered to express an anti-CD3 scFv construct as described above. Such lines include, for example, the A375 melanoma, MCF-7 breast cancer, A549 lung cancer, HCT116 and HT29 colon cancer, PC-3 prostate cancer, B16 melanoma, MDS-MB 231 breast cancer and U87 glioblastoma lines; as well as U-2 OS bone, UM-UC-3 bladder, A-498 kidney, and PLC / PRF / 5 liver cancer cell lines as well as lung cancer, ovarian cancer, pancreatic cancer, and neuroblastoma tumor cell lines.

[0106] An engineered cell line is then injected into animals, typically mice, for screening of a library of modified T cells. In some embodiments, the engineered cancer cell line, e.g., an A375 melanoma cell line, expresses low levels of the CD3 scFv construct e.g., as assessed using flow cytometry. Generally, when analyzed by flow cytometry, cells with CD3 scFv expression levels no more than 10% higher than the negative non-transduced control are considered to be CD3 scFv “low” expressing cells. In some instances, however, the level of expression may be more than 10% higher, but less than 25% higher than the negative control, non-transduced counterpart cells, e.g., no more than 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 21%, 22%, 23%, or 24% higher. The CD3 scFV-expressing engineered cell line, typically a “CD3scFv Low” cell line is then injected into animals, typically mice, for screening of a library of modified T cells.

[0107] This platform can be used to screen large T-cell libraries to identify modulators of T-cell activity. Such T-cell libraries can include comprehensive genome wide-CRISPR screens, e.g., knockout libraries, transcription activation libraries, based edited T cell libraries, T cell libraries with knockout of one gene and activation of another gene, insertion libraries, e.g., libraries of promoter-driven open reading frames (ORF) to test the gain-of-function of certain genes or gene combinations, which could be delivered, for example, by lentiviral random integration or site-specific integration; libraries of various constructs, such as switch-receptors, chimeric costimulatory receptors (OCRs), inducible cytokine circuits (e.x. via Syn-notch or SNIPR circuits), and the like.EXAMPLES

[0108] The following description illustrates techniques that are used to generate a library for efficient screening of large T-cell libraries and methods of screening and evaluating genes identified using the library.Example 1

[0109] To develop an efficient, effective in vivo screening platform, we constructed a lentiviral plasmid to express anti-CD3 scFv in tumor cells that confers any tumor cells with the ability to activate any polyclonal TCR repertoire. This plasmid comprises a polynucleotide sequence encoding a CD8 signal peptide, an anti-CD3 variable heavy sequence (VH), a linker sequence, an anti-CD3 variable light sequence (VL), a CD8 hinge, and a CD8 transmembrane domain under the EF-la core promoter. The anti-CD3 VH and VL were obtained from a commercial CD3 monoclonal antibody, OKT3. Additionally, weintroduced a flag tag for the identification of anti-CD3 scFv expression on transduced cells (FIG. 1).

[0110] We engineered the A375 melanoma cell line to overexpress this anti-CD3 scFv plasmid. The anti-CD3scFv encoded by the plasmid is capable of engaging any polyclonal T cell receptor (TCR) repertoire (FIG. 2A). Notably, this strategy can be used in any tumor cell line, which is an advantage to this approach in that the screening platform can be tailored to any tumor subtype. From this pool of transduced A375 cells, we picked 70 single tumor cell clones (FIG. 2B), and we subsequently narrowed down the selection to 27 clones based on their levels of anti-CD3 scFv expression, assessed using flow cytometry. Specifically, among clones with similar expression of anti-CD3 scFv levels, only one representative clone was selected (FIG. 2C). Following this, we evaluated the ability of primary human T cells to kill these 27 single tumor cell clones (FIG. 2D) and identified three clones with varying degrees of killing capabilities (low, medium (med.), and high) by human T cells. Additionally, we engrafted these three A375 single clones with high / medium / low response to T cell killing into the flanks of NSG mice and treated them with polyclonal human T cells (FIG.2E). Our data show that these clones with different OKT3 densities generate a range of responses to human T cells kill in vivo (FIG. 2F). To closely mimic the nutrient-deprived tumor microenvironment and ensure sufficient T cell transfer coverage per mouse for large-scale in vivo screens, we selected a clone with low sensitivity to primary T cell killing (referred to as A357-low) for further experiments.

[0111] Previously, when we injected human NY-ESO-1 TCR-T cells into NY-ESO-1+ A375 tumor-bearing mice, we could only extract tens to a few hundred thousand tumor infiltrating T cells (TILs) from each mouse (FIG. 2G). Typically, the number is close to 10,000 T cells from each tumor. However, with the present system, we can now routinely isolate 2-8 million TILs from each A375 flank tumor (FIG. 2H-I). This makes what was previously completely impractical (screening in hundreds of NSG mice) into a readily achievable scale for in vivo screening (genome-wide screens in -10-20 mice). Furthermore, while the T cells engineered with a single tumor-antigen specific TCR will often favor predominantly CD8 T cell expansion, our system allows for the representation of both CD4 and CD8 T cells in the spleens and tumors of NSG mice, which more closely mimics T cell distributions in humans (FIG. 2J).

[0112] Extensive phenotypic characterization of our system revealed that the T cells extracted from the tumors are exhausted / dysfunctional compared to T cells isolated from spleens of the same mice. We demonstrate compared to the splenic T cells, the TIL from our system express higher levels of canonical surface markers of exhaustion, lower levels of activation markers, have lower capacity for proliferation, lower stem cell-like memory T cell generation, lower effector cytokine production, lower metabolic function, and reduced tumor cell killing capacity on the Incucyte live-cell imaging system (FIG. 3). These findings imply that in this model, the TIL are experiencing conditions that induce dysfunction similar to T cell states found in human TILs, suggesting that this in vivo system can be used to screen for genes that mitigate this dysfunctional state.

[0113] To further evaluate the ability of this model system to distinguish genes that can enhance T cell competitive fitness in vivo, we performed a competition assay with a “positive control” gene edit mixed with a neutral control gene edit. A previous paper demonstrated that Regnase-1 is a strong negative regulator of T cell expansion and persistence in vivo.5To test whether our anti-CD3 scFv tumor screening system could reproduce these previous findings, we set up an in vivo competition assay to compare human T cells that were transduced with control vs ZC3H12A (Regnase-1) targeting sgRNA vectors that express distinct fluorescent proteins in the same tumor-bearing mouse (FIG. 4A). We transferred a mix of 50:50 (BFP AAVS1 control: GFP Regnase-1 KO) T cells into A375_low-tumor bearing mice and isolated T cells from spleens and tumors on day 14 after T cell infusion. Regnase-l-KO T cells showed a robust competitive advantage in tumors as well as spleens in our system (as has been shown in prior murine models), suggesting that our model can be used to distinguish gene targets that boost T cell expansion and persistence in vivo (FIG. 4B).

[0114] To further characterize T cell function, we sorted these TIL on low or high expression of the exhaustion marker, CD39,8and found that the CD39 low TIL have higher anti-tumor killing capacity (FIG. 5A). Thus, in addition to intra-tumoral guide accumulation and abundance, we can also screen using functional FACS-based readouts as endpoints (ie: an exhaustion marker (CD39) or cytokine production (TNF-a)) in this novel tumor-bearing mouse model (FIG. 5B).

[0115] Taken together, this platform paves the way for comprehensive genome-wide CRISPR screens (for instance, CRISPRn, CRISPRa, and base editor screens) in primary human T cells in vivo, allowing us to more rapidly identify genetic engineering strategies thatcan enhance T cell fitness in vivo and significantly improve T cell therapies. Prior to the development of this methodology, it was not feasible to perform a genome-wide screen in primary human T cells in tumor-bearing mice due to the fact that this would require an extremely large number of mice to isolate enough total T cells from the tumors to achieve reasonable coverage. For instance, to achieve a coverage level of the sgRNA library of 1000X, which is generally felt to be optimal in CRISPR screens, assuming a T cell recovery rate of approximately 100,000 T cell per tumor, for a typical genome-wide library (4 sgRNA per gene, -70,000 sgRNAs total) one would need to plan to pool T cells isolated from -700 NSG mice. It should be noted that in addition to CRISPR-based screens, this platform can be used to screen most libraries, for instance one could test libraries of promoter-driven open reading frames (ORF) to test the gain-of-function of certain genes or gene combinations, which could be delivered by lentiviral random integration or site-specific integration. It would also be feasible to test libraries of other constructs, such as switch-receptors, chimeric costimulatory receptors (OCRs), inducible cytokine circuits (e.x. via Syn-notch or SNIPR circuits), or production of any other inducible circuit “payloads”. In other words, this system is highly scalable and flexible for testing large libraries in a more relevant in vivo context.

[0116] We have completed Genome-wide CRISPR / Cas9 loss-of-function (LOF) screens in this screening platform and the results highlighted both genes with known roles in T cell fitness and function, as well as many novel gene targets that can be used therapeutically. For the first iteration of this CRISPR LOF screen, we first injected NSG mice with 2 million anti-CD3 scFv expressing A375 tumor cells (using the clone described in benchmarking experiments above) into the unilateral flank. The isolation of primary human T cells from human PBMCs was conducted via negative selection using the EasySep Human T Cell Isolation Kit following the manufacturer’s instructions (STEMCELL). Leukopaks from two deidentified healthy donors (STEMCELL) were used for this purpose and came with consent from donors and protocols approved by an Institutional Review Board. After isolation, T cells were activated using CTS Dynabeads Human T-Cell Activator CD3 / CD28 and cultured at a density of lx 106cells / ml in complete human T cell growth medium defined as X-Vivo-15 media (Lonza) supplemented with 5% human serum (Gemini), 50 pM 2-mercaptoethanol (Thermo Fisher), and 10 mM N-acetyl-L-cysteine (MilliporeSigma). T cells were split every 48-72 hours. Human IL-2 (20 IU each; Miltenyi) was added to this media, unless stated otherwise. 24 hours after activation, these T cells were transduced with a genome-wide sgRNA library (Brunello library sourced from Addgene) at a pre-defined titer to achieveapproximately a 50% transduction rate. This was confirmed on a small sample of the cells using puromycin selection to ensure adequate transduction. 24 hours following this transduction, the T cells were washed with PBS and electroporated with Cas9-RNP containing a non-targeting sgRNA, and subsequently cultured and expanded in media and IL2 as described above. 11 days after the NSG mice were injected with the tumor cells, mice were injected with 4 million T cells per NSG mouse, and monitored for tumor size in the subsequent days. At 4 million T cells per tumor, 18 mice sufficed to achieve 1000X library coverage at the time of T cell injection. 11 days after T cell injection, the mice were sacrificed for collection of the tumors and spleens from all mice. Tumors were digested and T cells isolated using density gradient centrifugation (Ficoll). T cells were isolated from spleens using mechanical dissociation. After isolation, T cells for each donor were pooled from all tumors, and separately from all spleens. Once T cells were pooled and genomic DNA was isolated from the cells using the NucleoSpin Blood XL kit (Macherey-Nagel). Genomic DNA concentration was quantified using Invitrogen IX dsDNA High Sensitivity assay kit (Thermo Fisher) on a Qubit Fluorometer (Invitrogen). PCR of the amplicon containing the guide sequences was carried out using Ex Taq DNA Polymerase (Takara Bio) and P5 / P7 primers (IDT). The resulting amplicons were purified using SPRIselect Beads (Beckman-Coulter) and QC was conducted using a D1000 ScreenTape assay on a TapeStation (Agilent) prior to nextgeneration sequencing. Samples were pooled and sequenced on a NovaSeq X system at The Center for Advanced Technology (CAT) at UCSF. MAGeCK52 v0.5.9.5 was used to quantify guide counts in each sample and tested for guide enrichment. Paired robust rank aggregation (RRA) analysis of guide count data from two donors was performed using the default parameters. Samples of T cells collected before infusion into mice (input) were compared to samples collected from spleens and from tumors. Guides with a read count of < 40 in the control samples were filtered out. In an additional cohort, we performed a second screen, where at the final timepoint we sorted the T cells from the tumors based on level of interferon production. In this case, after isolation from tumors, the T cells were stimulated and sorted based on gating for the top and bottom 20% of IFN-g levels by flow cytometry. After sorting, these T cells were processed as described for the prior screens. Thus, we performed screens based on abundance and persistence relying on the sgRNA frequencies detected in tumors and spleens, as well as screens based on a marker of effector function (interferon gamma production by TIL).

[0117] Volcano plots for these screens are shown in FIG. 6B. Results from both screens identified multiple genes already characterized as strong regulators of human T cell exhaustion and fitness (FIG. 6B, MYC, CD3D, TPI1, FOXO1, GAPDH, LCP2, GPI, CD3E, STAT3, IRF4, ZC3H12A, MAP4K1, IL2RA, CD3G, TNFAIP3, SOCS1, IFNG, VAV1, RASA2, AGK, SOCS3, DGKZ, CBLB, PTPN2), as well as genes shown to promote murine T cell exhaustion (FIG. 6B, NR1H2, PTGER4, SIGLEC12, SATB1, USP22, MAF, CEBPB, SBNO2, STUB1, GNAS, ID2), indicating our model was highly predictive of known biology. We also identified many new targets from the top 1% of the screens that have yet to be studied in T cells (FIG. 6B, GNA13, P2RY8, FAM3A, ADPRHL1, JMJD8, FDXR, PPP6C). We additionally analyzed the data for sgRNAs specifically enriched in tumor compared to spleens (FIG. 6C). Among these genes, we found sgRNAs for PTGER4, a receptor for prostaglandin E2 (PGE2), which was recently shown to limit expansion of murine TILs to promote cancer immune escape.9'11This is an excellent example of a gene that would not have been detected in an in vitro screen.

[0118] We also found that sgRNAs for GNAS, a downstream mediator of PGE2 signaling, were enriched in the IFNy production screen. We showed that GNAS KO in CD19-targeted CAR T cells demonstrated dramatically enhanced tumor-killing activity in vivo against CD19-expressing A375 solid tumors, which led to a dramatic survival advantage (FIG. 7A). We then demonstrated this clear advantage for disruption of the GNAS gene in therapeutic T cells in multiple preclinical tumor models in various cancer subtypes. For example, we showed that in a model of CD19 expressing A549 non-small cell lung cancer (NSCLC) cells, GNAS KO CD 19 CAR-T cells were at a clear advantage compared to the AAVS1 control CD19 CAR-T cells in terms of tumor control (FIG. 7B). We showed GNAS disruption improves CLAUDIN18.2-targeted CAR-T cells in controlling gastroesophageal cancer growth and enhancing survival, specifically the OE19 gastroesophageal cancer cells implanted in NSG mice (FIG. 7C). In addition, we showed that disruption of GNAS improves NY-ESO1 TCR T cells in controlling A375 tumor growth in NSG mice (FIG. 7D).Further, in B7H3-targeted CAR T cells, GNAS deletion showed a clear tumor clearance advantage in NSG mice implanted with MES-SA sarcoma cells (FIG. 7E), with no evidence of weight loss of signs of poor health observed in the GNAS KO group (not shown). GNAS deletion in CD 19 showed a clear advantage in NSG mice implanted with AsPCl pancreatic cancer cells that were previously engineered to express CD 19 (FIG. 7F).

[0119] In order to test effects on T cell memory and persistence, we cleared the CD 19+ A375 tumors of the mice that had been treated with GNAS KO CD19 CAR-T cells and then rechallenged these mice 60 days after the initial tumor challenge, with CD 19-positive and CD 19-negative tumor cells in opposite flanks to evaluate whether GNAS disruption can enhance functional persistence and rejection of the antigen-positive tumors. Our data indicates that GNAS KO can impart strong anti-tumor memory in these rechallenge models, as evidenced by continued rejection of antigen-positive tumors (FIG. 7G).

[0120] Additionally, we demonstrated that GNAS KO significantly enhances tumor-killing activity in vivo across multiple CAR T and TCR T cell models. In B7H3-targeted CAR T cells, GNAS KO led to dramatically enhanced tumor-killing against MES-SA uterine sarcoma (FIG. 7E) and the A549 lung metastasis model (FIG. 7H). In AAV-engineered CLDN18.2-targeted CAR T cells, GNAS knockout significantly enhanced in vivo tumor clearance in the OE19 gastroesophageal cancer model (FIG. 71).

[0121] To evaluate the effects of GNAS disruption on T cell states in vivo, we isolated the CD19 CAR-T cells from tumors of a cohort of NSG mice bearing CD19+ A375 tumor cells for flow-based analyses. Our data suggests that GNAS KO leads to significantly enhanced intra-tumoral abundance of CAR-T cells, which also express significantly lower exhaustion markers compared to the AAVS1 control CAR-T cells (FIG. 8A). Additionally, RNAseq data of B7H3 CAR T cells isolated from the in vivo MES-SA uterine sarcoma model showed GNAS KO significantly reduces CAR T cell exhaustion (FIG. 8B). These results demonstrated that by disrupting GNAS, we engineer therapeutic T cells that are resistant to suppressive effects in the TME and are able to expand, persist, and remain functional within solid tumors.

[0122] We evaluated if GNAS knockout CAR T cells maintain long-term safety in preclinical models. Our data shows GNAS KO T cells do not survive cytokine withdrawal and do not recognize antigen-negative cells (FIG. 9 A, 9B). RNA-seq data demonstrate that upon activation under steady state, GNAS knockout does not substantially alter the T cell gene expression profile, whereas under suppressive tumor microenvironment conditions (suppressive GPCR ligands) it induces distinct transcriptional changes (FIG. 9C). GNAS knockout CAR T cell-treated mice remained healthy, showing no body weight loss or off-tumor T cell infiltration after tumor clearance (FIG. 9D-9G), further supporting the potential safety of this therapy.

[0123] GNAS KO tumor-infiltrating T cells from patients demonstrate robust tumor cell control especially under combined suppressive signals (the suppressive GPCR ligands) from both tumors and immunosuppressive cells (FIG. 10). We demonstrated that GNAS KO confers remarkable resistance to cytolytic dysfunction in patient-derived tumor-infiltrating T cells under multiple tumor- suppressive conditions, providing another value for TIL therapies:

[0124] We also reviewed data from a prior in vitro genome-wide CRISPR KO screen, where we challenged T cells with either vehicle or with the adenosine (A2A) receptor agonist, CGS21680 and sorted the cells based on cell division dye levels to isolate the more proliferative cells. On this in vitro screen, sgRNAs against GNAS were modestly enriched in the CGS21680-treated compared to vehicle arms, corroborating its role in adenosine receptor signaling. However, the rank score of GNAS in the in vitro screen (928) was far less robust compared to its rank score of 11 in in vivo screen of the present application. This contrast further highlights the advantages of the in vivo screen described herein.

[0125] The GNAS gene encodes the stimulatory G protein a-subunit (Gas), a critical regulatory molecule in intracellular signaling pathways. The Gas signaling axis is activated by multiple ligand-receptor pairs on T cells in the TME that can augment T cell exhaustion-related programs, and diminish T cell proliferation, cytotoxicity, and infiltration into the tumor.12For instance, adenosine and prostaglandin E2 (PGE2) stimulate Gas-coupled receptors, A2AR (ADORA2A) and EP2 (PTGER2) and EP4 (PTGER4), respectively. In addition, acidotic environments can trigger GPR65 signaling, that also activates the Gas signaling axis, pi adrenergic receptor (pi-AR) and P2AR are also expressed on T cells and can be stimulated by adrenaline / noradrenaline to activate Gas signaling. Thus, it may be that knocking out GNAS blocks multiple suppressive pathways simultaneously. While GNAS has been studied as a molecule that can suppress T cell activity and reduce response to immune checkpoint blockade,12our data strongly suggests that the GNAS gene can be targeted genetically to enhance the efficacy of adoptive T cell therapies, which may provide a significant benefit, particularly in solid tumors with highly suppressive TMEs. In addition, CD 19 CAR-T cells edited for a number of different target genes that emerged from our screen were tested in parallel in NSG mice engrafted with A549 non-small cell lung cancer cells. Disruption of these targets, to varying degrees, enhanced overall CAR-T cell tumor control in this model. Compared to other target genes of interest, GNAS is clearly the strongest (FIG. 11).

[0126] Moreover, four top hits specifically enriched in the tumor — GNA13, S1PR1, ARHGEF1, and P2RY8 — are all components of cell migration pathways that regulate germinal center B cell migration (FIG. 12A-B). P2RY8 has been characterized as a receptor that signals through Gal 3 (GNA13) to confine B cells to the germinal center. S-Geranylgeranyl-L-glutathione (GGG) was identified as a potent ligand for P2RY8 that inhibits the chemokine-mediated migration of human germinal-center B cells. In lymph nodes, a gradient of GGG binds to P2RY8 on B cells and signals through Gal 3 to inhibit B cell migration out of the geminal center.10,13’14Our screen data suggest that KO of individual members of this pathway (P2RY8, GNA13, ARHGEF1) enhances T cell trafficking into solid tumors, which suggests that it may be involved in immune exclusion (FIG. 12A-B). We performed trafficking experiments where we knocked out P2RY8 versus an AAVS1 control with sgRNA vectors each expressing a unique fluorophore. We used either NY-ESO-1 TCR-T cells, or CLDN18.2 CAR-T cells to test two different therapeutic T cell contexts. These antigen-specific T cells were transduced with sgRNAs for either P2RY8 (BFP vector) or an AAVS1 control (GFP vector), and then these cells were mixed in a 50:50 ratio and injected into tumor-bearing NSG mice. Two days later, tumors were harvested and the T cells isolated to determine changes in the 50:50 input ratio in T cells isolated from the tumors vs the spleens. We found that there was a clear trafficking / infiltration advantage for the P2RY8-KO T cells in the tumors, while the ratios in the spleens remained close to the 50:50 input ratio (FIG. 12C)

[0127] These data suggest that P2RY8, known for regulating B cell migration in germinal centers, is also an active pathway in blocking T cell migration into tumors. Notably, P2RY8 lacks a murine ortholog, illustrating the power of our screening system to identify humanspecific genes in vivo.

[0128] Finally, as the two in vivo screening readouts highlighted gene targets that change T cell behaviors along unique and potentially complementary axes, we hypothesized that combining two gene edits in one cell product might lead to useful synergy for tumor control. The sgRNA abundance screen provided the basis for the discovery that targeting the P2RY8-Gal3-ARHGEF1 signaling axis enhances tumor infiltration, but that these cells remain susceptible to various forms of suppression inside the tumor. The IFN-y screen highlighted GNAS as a potent gene target to preserve T cell effector function by disabling suppressive signaling responses within the tumor. We reasoned that we could combine disruption ofP2RY8 and GNAS to simultaneously enhance trafficking and confer resistance to suppression.

[0129] To determine if disruption of both P2Ry8 and GNAS led to synergistic effects on tumor control, we subcutaneously engrafted NSG mice with a slow-growing, CD 19-expressing A549 NSCLC cell line, followed by intravenous infusion of CD19 CAR-T cells edited at the AAVS1 control locus, P2RY8 KO, GNAS KO, or GNAS / P2RY8 double KO. While the GNAS KO effect was quite strong, combining GNAS KO with P2RY8 KO led to an even greater improvement in overall tumor control, with more mice receiving the dual edited CAR-T cells achieving complete tumor clearance (AAVS1 : 0 / 6 complete responses (CRs), P2RY8 KO: 0 / 6 CR, GNAS KO: 1 / 6 CR, GNAS + P2RY8 KO: 4 / 6 CR) (FIG. 13).Together, these results suggest that our in vivo screens uniquely identified genetic modifications that enhance T cell trafficking into tumors and T cell resistance to immunosuppression in the TME, which can be combined to achieve a more effective CAR-T cell product for treating solid tumors.

[0130] In summary, the technical results described herein showcase the power of this new screening platform. Our first CRISPRKO screens demonstrated the ability of our system to identify biology and gene enhancement strategies in human T cells - such as pathways involved in resistance to suppressive cues and novel mechanisms of T cell trafficking, which would not have been uncovered by in vitro screens. In addition to the pathways we have highlighted, there are many other gene hits that we identified in our screens that are also very promising and will be the subjects of further interrogation. This platform can be used to perform additional screens to identify key genetic perturbations that enhance function in human T cells in a living organism.Example 2

[0131] The list of the top 50 ranked genes from the interferon sort-based screen (in ranked order) are listed here. We have bolded those that have been described already as key genes to edit to enhance human T cell therapies.TNFAIP3SPTLC2STT3BPPIAL4DLRIG3DGKZGNA13CBLB STUB1RASA2GNAS FAM76AALDH3B1JMJD8FBXO45FDXRH2AFB3PPP6CG0LGA1NFKBIA ALG3DPEP2CLTC MBNL3ERF SYNDIG1LCllorf57GTF2A2CSNK2A1GBE1GNB2HIST1H2AIINPPL1NT5C2FRMD3GARS SIKE1SOCS3EDC4SOCS1EBF2PPARG BICC1MDGA2KAT8PTPN2CHRNB2BRWD3MAP4K1REV3LThe list of the top 50 ranked genes from the tumor abundance-based screen (in ranked order) are listed here. We have bolded those that have been described already as key genes to edit to enhance human T cell therapies.GNA13P2RY8 TNFAIP3 NR1H2 FAM3A ADPRHL1 DUSP9 PTGER4 SOCS1 SATB1 RBF0X2 ZC3H12A C12orf66 TCHH WNT9A MAF SIGLEC12 MMP3 SPINK6 SOX18 PLEKHB1 CIC TMEM127 MAP4K1 C0L1A2 USP22 FAM179A BRINP1 RORB RGS7BP MEF2D FAM170A CUTC ZNF513 TFAP2E CMTM4 CYP3A5 PPP1R3G WWTR1 LRRC61 ZNF772 ADGRL4 TMCC2 SOS2 ACTA1 AN04 B3GAT1 MSI2 C15orf61 SLC30A1The list of the top 47 ranked genes from the tumor abundance-based screen ranked based on enrichment in tumor compared to spleen (in ranked order) are listed here.S1PR1GNA13PTGER4BASP1KCNA5ZNF835FKBP1APOU5F1BADPRHL1PRR19ESRRA SLX1AATF5TMEM43CUTC SLC6A8KRTAP8-1P2RY8MAN2C1PDLIM7CEBPB CT47A2CST7C15orf56FOXI2SUN1SHISA3OR10A7MUSTN1ZNF227CCNY RORB CALML3GPR132KLHL14SOX30USP49SLC35E4SOX11WNT9AGALNT11PPM1HPP2D1PCGF2FAM216AADGRL4References1. Anderson, K.G., Stromnes, I.M. & Greenberg, P.D. Obstacles Posed by the Tumor Microenvironment to T cell Activity: A Case for Synergistic Therapies. Cancer Cell 31, 311-325 (2017), PMC5423788.2. Arner, E.N. & Rathmell, J.C. Metabolic programming and immune suppression in the tumor microenvironment. Cancer Cell 41, 421-433 (2023), PMC10023409.3. Wang, R., et al. The transcription factor Myc controls metabolic reprogramming upon T lymphocyte activation. Immunity 35, 871-882 (2011), PMC3248798.4. DeBerardinis, R.J., Lum, J.J., Hatzivassiliou, G. & Thompson, C.B. The biology of cancer: metabolic reprogramming fuels cell growth and proliferation. Cell Metab 7 , 11-20 (2008),5. Chang, C.H., et al. Metabolic Competition in the Tumor Microenvironment Is a Driver of Cancer Progression. Cell 162, 1229-1241 (2015), PMC4864363.6. Vignali, P.D. A., et al. Hypoxia drives CD39-dependent suppressor function in exhausted T cells to limit antitumor immunity. Nat Immunol 24, 267-279 (2023),PMC 10402660.7. Belk, J. A., et al. Genome-wide CRISPR screens of T cell exhaustion identify chromatin remodeling factors that limit T cell persistence. Cancer Cell 40, 768-786 e767 (2022), PMC9949532.8. Klysz, D.D., et al. Inosine induces sternness features in CAR-T cells and enhances potency. Cancer Cell 42, 266-282 e268 (2024), PMC10923096.9. Lacher, S.B., et al. PGE(2) limits effector expansion of tumour-infiltrating stem-like CD8(+) T cells. Nature 629, 417-425 (2024), PMC 11078747.10. Morotti, M., et al. PGE(2) inhibits TIL expansion by disrupting IL-2 signalling and mitochondrial function. Nature 629, 426-434 (2024), PMC11078736.11. Punyawatthananukool, S., et al. Prostaglandin E(2)-EP2 / EP4 signaling induces immunosuppression in human cancer by impairing bioenergetics and ribosome biogenesis in immune cells. Nat Commun 15, 9464 (2024), PMC11530437.12. Wu, V.H., et al. The GPCR-Galpha(s)-PKA signaling axis promotes T cell dysfunction and cancer immunotherapy failure. Nat Immunol 24, 1318-1330 (2023), PMC 10735169.13. Lu, E., Wolfreys, F.D., Muppidi, J.R., Xu, Y. & Cyster, J.G. S-Geranylgeranyl-L-glutathione is a ligand for human B cell-confinement receptor P2RY8. Nature 567, 244-248 (2019), PMC6640153.14. Muppidi, J.R., Lu, E. & Cyster, J.G. The G protein-coupled receptor P2RY8 and follicular dendritic cells promote germinal center confinement of B cells, whereas S1PR3 can contribute to their dissemination. J Exp Med 212, 2213-2222 (2015), PMC4689170.

[0132] It is understood that the examples and embodiments described herein are for illustrative purposes only and that various modifications or changes in light thereof will be suggested to persons skilled in the art and are to be included within the spirit and purview of this application and scope of the appended claims. All publications, patents, and patent applications cited herein are hereby incorporated by reference for the contents for which they are cited.Table 1. Guide RNA sequences of top 50 genes identified in interferon sort-based screen. The “U” residues of the crRNA sequences are shown as “T” residues in the sequences provided in Table 1.Targe gene sgRNA_name crRNA sequenceTNFAIP3 sgTNFAIP3-1 CTGTCCTTCAGGGTCACCAA TNFAIP3 sgTNFAIP3-2 TATGCCATGAGTGCTCAGAG SPTLC2 sgSPTLC2-1GATATCTTCGAGATTTCTTG SPTLC2 sgSPTLC2-2CATCATGTTACACAAAATGG STT3B sgSTT3B-1 TACAGCAAAAGAGTCTACATSTT3B sgSTT3B-2 CCAGGGTTGATGATAACCGCPPIAL4D sgPPIAL4D-1CAAGCATGTGGCGTTTGGCA PPIAL4D sgPPIAL4D-2CCTGTACCCAAAGTGCTCCG LRIG3 sgLRIG3-1 AACCTAACAGAGATTACCAALRIG3 sgLRIG3-2 GGTTCAGCCAGAAACACAGTDGKZ sgDGKZ-1 G AATAAG ATGTTCTAC GC C GDGKZ sgDGKZ-1 AGGCTCCAGGAATGTCCGCG GNA13 sgGNA13-1 AGAGCATTATGGGCAGACAGGNA13 sgGNA13-2 AGAGATCAGAAAGGAAACGTCBLB sgCBLB-1 TGCACAGAACTATCGTACCACBLB sgCBLB-2 TTCCGCAAAATAGAGCCCCASTUB1 sgSTUB1-1 GGCCGTGTATTACACCAACCSTUB1 sgSTUB1-2 GGAGATGGAGAGCTATGATGRASA2 sgRASA2-1 AGATATCACACATTACAGTGRASA2 sgRASA2-1 TTAGCATCAAGGCATGCCATGNAS sgGNAS-1 CCCACCAGCATGTTTGACGTGNAS sgGNAS-2 AGATTCCAGAAGTCAGGACAFAM76A sgFAM76A-1ATTATGTTGCAATACTGACA FAM76A sgFAM76A-2CCTGAGACAGCGCCTCGAAG ALDH3B1 sgALDH3B1-1GCAGTCAGCCTTCGAGTCGG ALDH3B1 sgALDH3B1-2CTATCCGCTGAACCTGACGC JMJD8 sgJMJD8-1 TCGGGCCGACCTCACCTACGJMJD8 sgJMJD8-2 GTTCCCAGCAGGCCAAATGGFBXO45 sgFBXO45-1GTACCAGTGCTTGCACACCA FBXO45 sgFBXO45-2ACCACACTTCCCATGCATGG FDXR sgFDXR-1 CATCTTTCATCAGAGCTACGFDXR sgFDXR-2 CTGCCCACCACACAGATCTGH2AFB3 sgH2AFB3-1GTGGAGCGCAGTCTACGGGAH2AFB3 sgH2AFB3-2GGCCAAGGTCCTGGAGCTGG PPP6C sgPPP6C-1 TATCAGGAGATAAACCACCA PPP6C sgPPP6C-2 CAGTTCTGAACAGTTCACAA G0LGA1 sgG0LGA1-1CTGCTCTTGAAATTTCCGCAG0LGA1 sgG0LGA1-1CCAAAGAGAAATTGTGAGCG NFKBIA sgNFKBIA-1 GGTTGGTGATCACAGCCAAG NFKBIA sgNFKBIA-2 CTGGACGACCGCCACGACAG ALG3 sgALG3-1 CACCCTGTGAATGACCCAGA ALG3 sgALG3-2 CACACAGTTTGGCTTCCGTG DPEP2 sgDPEP2-1 AACTTGCCTACCTTTAGCCG DPEP2 sgDPEP2-2 GGACTACTGAGTGTGGTCGA CLTC sgCLTC-1 TAATAAGTTC C AG ATC AC AT CLTC sgCLTC-2 GTACTCCAGACACTATCCGT MBNL3 sgMBNL3-1 CGCAGCTGGAGATTAATGGG MBNL3 sgMBNL3-2 GTTTGCCGAGAATTTCAGCG ERF sgERF-1 GGAAGGCACCCAGATCCGGA ERF sgERF-2 CGGAAGTGGCTACCACCCGA SYNDIG1L sgSYNDIG1L-1CTCTACTCCTACCTCCTAGG SYNDIG1L sgSYNDIG1L-2GGTCCCTGGGAGGCAGCGTGC11orf57 sgC11orf57-1CAGATGGAAGATGCTTACCGC11orf57 sgC11orf57-2TTCTTCTGAGAACTCACTCG GTF2A2 sgGTF2A2-1CAGGAACAGAGTCAATTTCA GTF2A2 sgGTF2A2-2TAAGGCTATAAATGCAGCAC CSNK2A1 sgCSNK2A1-1AGACATTGTAAAAGACCCTG CSNK2A1 sgCSNK2A1-2CTAGTTGGTGAGGATAGCCA GBE1 sgGBE1-1 CGATTCTATAACAATAGCTG GBE1 sgGBE1-2 TCTTGTATCGTATTTCACCG GNB2 sgGNB2-1 GCAACACGACAGGTACCCTG GNB2 sgGNB2-1 TCTACCTCCAGATCACAGCT HIST1H2AI sgHIST1H2AI-1GGCAACTATGCGGAGCGGGT HIST1H2AI sgHIST1H2AI-2GCCGGGCTTCAGTTTCCCGT INPPL1 sglNPPL1-1 CCAGATCCGTAAGCTCCTTGINPPL1 sglNPPL1-2 TTTCAGGTAGTCGTGCGAGA NT5C2 sgNT5C2-1 GCAAAGCTGAGCAACTCCTG NT5C2 sgNT5C2-2 GAGTCACATACGGTACCTTG FRMD3 sgFRMD3-1 TAATCTTCAAGGGTTCATGT FRMD3 sgFRMD3-2 TGGGTGAGGATCCACCCCGT GARS sgGARS-1 GCTTTGTCTACGTCTACTTG GARS sgGARS-1 GAGATATTCCAACCTTCGTG SIKE1 sgSIKE1-1 ACCGGCGGGTAGCAGCTATG SIKE1 sgSIKE1-2 AATGGTTGCTAAAAAAGCGG S0CS3 sgS0CS3-1 TCAGCGTCAAGACCCAGTCT S0CS3 sgSOCS3-2 TTGAGCACGCAGTCGAAGCG EDC4 sgEDC4-1 AGAACCGAGAGTTAAAGATG EDC4 sgEDC4-2 GCAGCTCCACGATTCGTCGG S0CS1 sgS0CS1-1 AAGTGCACGCGGATGCTCGT S0CS1 sgS0CS1-2 CGGCGTGCGAACGGAATGTG EBF2 sgEBF2-1 AAACCGAAATGAGACTCCAT EBF2 sgEBF2-2 GCAGGTTGTGTTGTCAACAA PPARG sgPPARG-1 TGGCATCTCTGTGTCAACCA PPARG sgPPARG-2 TGGCATCTCTGTGTCAACCA BICC1 sgBICC1-1 AGTGCTGAGTGCAAATCACG BICC1 sgBICC1-2 GGGATGCCTACCTTGTAACA MDGA2 sgMDGA2-1 AGGGTCTACACTATCCGGGA MDGA2 sgMDGA2-2 ACAAATATTCAGCGACACCA KAT8 sgKAT8-1 TTTGCCATCAACTTCGTACA KAT8 sgKAT8-2 CCATACTTACAGTTAACCGG PTPN2 sgPTPN2-1 GCCCAATGCCTGCACTACAG PTPN2 sgPTPN2-2 CCATGACTATCCTCATAGAG CHRNB2 sgCHRNB2-1CAGTGCTGACGGCATGTACG CHRNB2 sgCHRNB2-2CCACGTACGTAGAGTCGTCG BRWD3 sgBRWD3-1TTTACTGAGAGATCCAGACC BRWD3 sgBRWD3-2AGAGCATACTCTGTTAATGG MAP4K1 sgMAP4K1-1AGGGTGTCCCAATGAAAGAG MAP4K1 sgMAP4K1-2TTCCGTTCTCCATCAGACGA REV3L sgREV3L-1 TCTAATTCACATGTACTCTG REV3L sgREV3L-2 GATTTAACTAAAACCACTCGTable 2. Guide RNA sequences of top 50 genes identified in tumor abundance-based screen. The “U” residues of the crRNA sequences are shown as “T” residues in the sequences provided in Table 2.Targe gene sgRNA_name crRNA sequenceGNA13 sgGNA13-1 AGAGCATTATGGGCAGACAGGNA13 sgGNA13-2 AGAGATCAGAAAGGAAACGTP2RY8 sgP2RY8-1 GAGATCGGTGCGCGCCAGCGP2RY8 sgP2RY8-2 GATCATGAAGATGACCGACGTNFAIP3 sgTNFAIP3-1 CTGTCCTTCAGGGTCACCAA TNFAIP3 sgTNFAIP3-2 TATGCCATGAGTGCTCAGAGNR1H2 sgNR1H2-1 CACAGACACGGCAAAGCTCGNR1H2 sgNR1H2-2 CATCTCAGTCCAGGAGATCGFAM3A sgFAM3A-1 TTTATTCGGCCACTGCACGAFAM3A sgFAM3A-2 TGTGGGTGTCACATGGATCG ADPRHL1 sgADPRHL1-1CTCCTGGCGAGAGTACGAGG ADPRHL1 sgADPRHL1-2CATGCACATCGCAACCGCCG DUSP9 sgDUSP9-1 CTGGTCGTACAGGAGCACGG DUSP9 sgDUSP9-2 CCCCGCGGCACCTACCCTGG PTGER4 sgPTGER4-1 GCCCGCGTACATGTAGGAGTPTGER4 sgPTGER4-2 CAGCGCGCAAAAGAGCACGTS0CS1 sgS0CS1-1 CGAAAAAGCAGTTCCGCTGG S0CS1 sgS0CS1-2 AAGTGCACGCGGATGCTCGT SATB1 sgSATB1-1 CATTGAATATGATTGCAAGGSATB1 sgSATB1-2 ATGCTAAGTACCTGTGAAAGRBF0X2 sgRBF0X2-1GTGTGGCACCCCATACTCTG RBF0X2 sgRBFOX2-2TATGGTCCGGAGTTATATGC ZC3H12A sgZC3H12A-1 TTCACACCATCACGACGCGT ZC3H12A sgZC3H12A-2 CAGGACGCTGTGGATCTCCG C12orf66 sgC12orf66-1GTGATAGACCTTCTCGGCCGC12orf66 sgC12orf66-2CACACCAAACTGCAGACGTG TCHH sgTCHH-1 TTGCAAAGGTCACGAAACTGTCHH sgTCHH-2 GGCAAAGCAAAGTCTACTCG WNT9A sgWNT9A-1 CGCAGGTACAGCGCTCCATG WNT9A sgWNT9A-2 CACTTGCCTTCACACCCACGMAF sgMAF-1 GATCACGGCGGACACCACGGMAF sgMAF-2 GAAGACTACTACTGGATGAC SIGLEC12 sgSIGLEC12-1CAAGGAGGAGGAATCGACCG SIGLEC12 sgSIGLEC12-2TGAACCAGGATCCATAAACAMMP3 sgMMP3-1 TACCTGAACAAGGTTCATGC MMP3 sgMMP3-2 CTGTGAGTGAGTGATAGAGT SPINK6 sgSPINK6-1 TTACTTTGGTAGGTTGACTG SPINK6 sgSPINK6-2 CGGGAATCTAACCCACACTG S0X18 sgSOX18-1 CCGTCGAACTCGGCGCCCAG S0X18 sgSOX18-2 GAACCCGGACCTGCACAACG PLEKHB1 sgPLEKHB1-1GCTGGAGGCAAACTCCACCC PLEKHB1 sgPLEKHB1-2ACTGTGAACCTACGGGAAGG CIC sgCIC-1 CTCTACCGCCCGGAAAACGT CIC sgCIC-2 ACTGTCACTAACCTACTGGT TMEM127 sgTM EM 127-1GCACAGCGCCGTGATAGACA TMEM127 sgTM EM 127-2GTGCACATAGCCCAACACGT MAP4K1 sgMAP4K1-1AGGGTGTCCCAATGAAAGAG MAP4K1 sgMAP4K1-2TTCCGTTCTCCATCAGACGAC0L1A2 sgCOL1A2-1TACTTACAGGAGGTCCAACGC0L1A2 sgCOL1A2-2CAGGGCTTAATGGGACCTAG USP22 sgUSP22-1 CCTCGAACTGCACCATAGGT USP22 sgUSP22-2 TGGGGCTCTGCATCTCACAG FAM179A sgFAM179A-1TACCTGCGGTGCTCACGTTG FAM179A sgFAM179A-2GAACCGTCACAGCTCCTGCG BRINP1 sgBRINP1-1TTGACCGTGATGGTACCATG BRINP1 sgBRNP1-2 AAGGGCTACAAGCTGTATCG RORB sgRORB-1 CACTCACGCCATCCAATACG RORB sgRORB-2 AACCTGAACAACGAGACCAG RGS7BP sgRGS7BP-1AAAAATTGGCTGCCATCTCA RGS7BP sgRGS7BP-2TAAAATCCATATGTCTGCTG MEF2D sgMEF2D-1 CAAGTACCGACGCGCCAGCG MEF2D sgMEF2D-2 GGTGAGCGAATGAGTAGACT FAM OA sgFAM170A-1TTCTGGTGGACACATCAGAG FAM VOA sg FAM 170A-2GGTACAAATGAACAAAGGTG CUTC sgCUTC-1 TATGTTCTGGTTTATCAGAG CUTC sgCUTC-2 CTGCCAGTCACTTTCCACCG ZNF513 sgZNF513-1 CTGGTCGTGGAGTACAGCAGZNF513 sgZNF513-2 GCTCGAGTAGTGGGACACGA TFAP2E sgTFAP2E-1GCAGTGGCATAGTCACGGCG TFAP2E sgTFAP2E-2GAGGCGTTGAGGCACTCGGG CMTM4 sgCMTM4-1 AAAGTAGAGGCCTTCACACG CMTM4 sgCMTM4-2 TCAGATTCCAGTTGATCTGG CYP3A5 sgCYP3A5-1TAGCACTGTTCTGATCACGT CYP3A5 sgCYP3A5-2AGATATGGGACCCGTACACA PPP1R3G sgPPP1R3G-1CAGCGTGAAGCACTTCAGCG PPP1R3G sgPPP1R3G-2GGGACCAGCGCCCTTCCGAG WWTR1 sgWWTR1-1AGGCTTACCGAGATTTGGCT WWTR1 sgWWTR1-2ACGCGGGCGACGAGTGCGAG LRRC61 sgLRRC61-1CAGCTGCTGAAGTCACGCAC LRRC61 sgLRRC61-2GGCTCCGAGACCCTTTGGCC ZNF772 sgZNF772-1 CACCAGTGAGGCAACTATGT ZNF772 sgZNF772-1 AGGTTGTTGGCATGGAATGG ADGRL4 sgADGRL4-1TGAAGCCTGCTATTGCAACA ADGRL4 sgADGRL4-2ATTTACATTAAGTCATCGAA TMCC2 sgTMCC2-1 AGGTCTCCCTTATCGACCTG TMCC2 sgTMCC2-2 GGAGGCTCGCGACGACAATG S0S2 sgS0S2-1 GAATCGGTGCCAAACATGAA S0S2 sgSOS2-2 GGCATCCCCATTATTAAAGG ACTA1 sgACTA1-1 GGGTCAGAAAGATTCCTACG ACTA1 sgACTA1-2 TCAGGTAGTCGGTGAGATCG AN04 sgAN04-1 ACAGCACAATACCTCATGCA AN04 sgANO4-2 ATAAATACTGTC CATTCATG B3GAT1 sgB3GAT1-1CCGCGCAGCTTGTAGTTGCGB3GAT1 sgB3GAT1-2TGTAGGTGGGCGTCACCACG MSI2 sgMSI2-1 AAAACTACCAACAGGCACAG MSI2 sgMSI2-2 ACCTTGGGTTGCGCTCGACG C15orf61 sgC15orf61-1CAGGCGGAGCGCGACCTCGTC15orf61 sgC15orf61-2CCGGCCAGTTGAAGTGCGAGSLC30A1 sgSLC30A1-1CCAGCACGTCCGACAGCATG SLC30A1 sgSLC30A1-2GCTGGACAACTTAACATGCGTable 3. Guide RNA sequences of top 47 genes identified in tumor abundance-based screen based on enrichment in tumor compared to spleen. The “U” residues of the crRNA sequences are shown as “T” residues in the sequences provided in Table 3.crRNA sequenceTarget gene sgRNA_nameS1PR1 sgS1PR1-1 ACAAGCTCACTCCCGCCCAGS1PR1 sgS1PR1-2 TCTGCAGTACAGAATGACGAGNA13 sgGNA13-1 AGAGCATTATGGGCAGACAGGNA13 sgGNA13-2 AGAGATCAGAAAGGAAACGTPTGER4 sgPTGER4-1 GCCCGCGTACATGTAGGAGTPTGER4 sgPTGER4-2 CAGCGCGCAAAAGAGCACGTBASP1 sgBASP1-1 GCGGAGCCCGAGAAGACGGABASP1 sgBASP1-2 AAGCCCGACCAGGACGCCGA KCNA5 sgKCNA5-1 AGATACGCTTCTACCAGCTGKCNA5 sgKCNA5-2 GGTGAACCAGATGACGCACG ZNF835 sgZNF835-1 CAAGAAGCCGTGGAAATGCG ZNF835 sgZNF835-2 CTGCGTCAGGTGCGACACCT FKBP1A sgFKBP1A-1GGCAAGCAGGAGGTGATCCG FKBP1A sgFKBP1A-2ACCGGTGTAGTGCACCACGC POU5F1B sgPOU5F1B-1GGTGGAGAGCAACTCCAATG POU5F1B sgPOU5F1B-2CCCGCCGTATGAGTTATGTG ADPRHL1 sgADPRHL1-1CTCCTGGCGAGAGTACGAGG ADPRHL1 sgADPRHL1-2CATGCACATCGCAACCGCCG PRR19 sgPRR19-1 TCCGTCGTCGGAAGACTAGGPRR19 sgPRR19-2 TCCTGAATCAGGTTCCTCCGESRRA sgESRRA-1 CTCCGGCTACCACTATGGTGESRRA sgESRRA-2 CCACAATCTCTCGGTCAAAGSLX1A sgSLX1A-1 TACGCCGCCCGCAGTTTGAGSLX1A sgSLX1A-2 GGAGCCTGAGCCAGACCAGGATF5 sgATF5-1 TCCAGAGTATCCAAGACAGGATF5 sgATF5-2 GCTCCCTATGAGGTCCTTGG TMEM43 sgTMEM43-1TGGCGCCTTACGGACATCCATMEM43 sgTMEM43-2GGCTGAGCGAGACCTCGGGT CUTC sgCUTC-1 TATGTTCTGGTTTATCAGAG CUTC sgCUTC-2 CAACACGCGTTCAAATCCCA SLC6A8 sgSLC6A8-1TGGCGCGTCCAGGTCTCGCG SLC6A8 sgSLC6A8-2GGCTGCTCACCTTTGAACAG KRTAP8-1 sgKRTAP8-1-1GGCAGCACCTACTCTCCAGT KRTAP8-1 sgKRTAP8-1-2CAGCCAACGCTATATCCCAGP2RY8 sgP2RY8-1 GAGATCGGTGCGCGCCAGCG P2RY8 sgP2RY8-2 GATCATGAAGATGACCGACG MAN2C1 sgMAN2C1-1TCCCATAGGAGTCGCCAGGT MAN2C1 sgMAN2C1-1ACTGCCACATTGATACAGGT PDLIM7 sgPDLIM7-1 CTGGGTGCAAAGGTGTACCG PDLIM7 sgPDLIM7-2 TCTGGGACCAGCGGTCGGAG CEBPB sgCEBPB-1 TCGAGCCCGCGGACTGCAAG CEBPB sgCEBPB-2 CCTCTTCTCCGACGACTACG CT47A2 sgCT47A2-1CAACTCAGCCGCCTGATGGT CT47A2 sgCT47A2-2GGCGGCCAACTTCGACTTGG CST7 sgCST7-1 CCTGGTCTTGAGCACCACTG CST7 sgCST7-2 CAAGGAGTCCCGCATCACAA C15orf56 sgC15orf56-1GCGGCGGCGAACCCAGAGCGC15orf56 sgC15orf56-2AAGCCCAGGAACGCTCGAAGF0XI2 sgFOXI2-1 CTACGCGGCCCCGAGCTACG F0XI2 sgFOXI2-2 CCCCCCGGGCTATGAGCCAG SUN1 sgSUN1-1 GAAGACCGGCTGTGAGACAG SUN1 sgSUN1-2 TGGGTTTAAACACGTCCTGG SHISA3 sgSHISA3-1 CGTGCAGGGCAACTACCACG OR10A7 sgSHISA3-2 GGGTCTCTGTCTGATAGCTG MUSTN1 sgMUSTN1-1GGGGCGCTTCTTCTTGATAG MUSTN1 sgMUSTN1-2GGTCCTCGTCCTTCACAGGG ZNF227 sgZNF227-1 GGCATATTAATGGTGAATTG ZNF227 sgZNF227-2 ATTGGGATACCATATCTGGT CONY sgCCNY-1 GGAGTCCTACCGGCCAGACA CONY sgCCNY-2 TGAATGTGCCATCGTCACCC RORB sgRORB-1 CACTCACGCCATCCAATACGRORB sgRORB-2 AACCTGAACAACGAGACCAG CALML3 sgCALML3-1GCAGGTCACAGAATTCAAGG CALML3 sgCALML3-2ACTCATCATGTCCCGCAGCT GPR132 sgGPR132-1GGTAGTGAACGATCCCGACG GPR132 sgGPR132-2GTGTACGCGCTGGAGAGTCG KLHL14 sgKLHL14-1GGTGCTCGAGTACCTCTACA KLHL14 sgKLHL14-2GCACCGAGATCTGGTCGTTG SOX30 sgSOX30-1 GCGCCGTCTGACGCTGTCGG SOX30 sgSOX30-2 GGAGCGTCAAAGGGATCCTA USP49 sgUSP49-1 GGCGGCGCGAGGTGAAACGG USP49 sgUSP49-2 CACCAAACAGGTCTTAAAGG SLC35E4 sgSLC35E4-1CAGCGAGGTGGCGTAAAGCA SLC35E4 sgSLC35E4-2GCAGCCCTGGCATGCCACCG SOX11 sgSOX11-1 GTACTTGTAGTCGGGGTAGT SOX11 sgSOX11-2 CGACCCAGACTGGTGCAAGA WNT9A sgWNT9A-1 CGCAGGTACAGCGCTCCATG WNT9A sgWNT9A-2 CACTTGCCTTCACACCCACG GALNT11 sgGALNT11-1GTCCGCGGAGGGTTCAACTG GALNT11 sgGALNT11-2TGGACAGTATGATAGTGGCA PPM1H sgPPM1H-1 ACCTACAGATAGAACGAGAG PPM1H sgPPM1H-2 CTTCCCGGCATTGATAACCC PP2D1 sgPP2D1-1 TGATGTCAACTCTGCCGCTG PP2D1 sgPP2D1-2 GCTCTCTGCCAACCCATCAT PCGF2 sgPCGF2-1 CATCGACGCCACCACTATCG PCGF2 sgPCGF2-2 AACGGCTCCAATGAGGACCG FAM216A sgFAM216A-1CAGGTAACGCTTCTGGCCTG FAM216A sgFAM216A-2AGAGCTACGCTCCGTCCAGT ADGRL4 sgADGRL4-1TGAAGCCTGCTATTGCAACA ADGRL4 sgADGRL4-2ATTTACATTAAGTCATCGAAIllustrative anti-CD3 scFV sequences encoded by an anti-CD3 scFV expression construct of the present disclosure:CD8 signal sequence:MALPVTALLLPLALLLHAARP0KT3 VH sequence (CDR sequences underlined):DIKLOQSGAELARPGASVKMSCKTSGYTFTRYTMHWVKORPGOGLEWIGYINPSRG YTNYNOKFKDKATLTTDKSSSTAYMQLSSLTSEDSAVYYCARYYDDHYCLDYWGQ GTTLTVSSLinker sequence:GGGGSGGGGSGGGGSGGGGSOKT3 VL sequence (CDR sequences underlined):DIOLTQSPAIMSASPGEKVTMTCRASSSVSYMNWYOOKSGTSPKRWIYDTSKVASG VPYRFSGSGSGTSYSLTISSMEAEDAATYYCOQWSSNPLTFGAGTKLELK(Alternative VL sequences: CDR1 SASSSVSYMN, CDR2 DTSKLAS, CDR3 QQWSSNPFTF)CD8 hinge sequence:TTTPAPRPPTPAPTIASQPLSLRPEACRPAAGGAVHTRGLDFACDCD8 transmembrane domain sequenceIYIWAPLAGTCGVLLLSLVITLYCFlag (tag) sequence:DYKDDDDK

Claims

1. WHAT IS CLAIMED IS:

1. A method of identifying genetically modified T cells with modulated anti-tumor T cell function, the method comprising:inoculating a mouse with cancer cells genetically modified to express an anti-CD3 scFv, wherein the anti-CD3 scFv is encoded by a polynucleotide construct comprising a polynucleotide encoding a leader sequence, an anti-CD3 heavy chain variable region (VH) sequence, a linker sequence, an anti-CD3 light chain variable region (VL) sequence, a CD8 hinge sequence, and a CD8 transmembrane domain sequence, wherein the polynucleotide is operably linked to an EF-loc promoter, wherein the cancer cells express the anti-CD3 scFv at a level no more than 10% higher than a negative control;inoculating the mouse with a library of genetically modified T cells; and identifying members of the library that exhibit modulated anti-tumor T cell activity compared to unmodified control T cells.

2. The method of claim 1, wherein the cancer cells are from a melanoma, breast cancer, prostate cancer, colon cancer, ovarian cancer, lung cancer, pancreatic cancer, head and neck cancer, liver cancer, kidney cancer, glioblastoma, or a neuroblastoma cell line.

3. The method of claim 1 or 2, wherein the library of genetically modified T cells is a genome wide CRISPR knockout library, a genome wide CRISPR transcription activation library, or a CRISPR library comprising T cells in which a first gene is knocked out and a second gene is activated.

4. The method of claim 3, wherein the library is a genome-wide CRISPR knockout library.

5. The method of claim 4, wherein the identifying step further comprises identifying a gene that when knocked out in a member of the library of genetically modified T cells enhances T cell fitness in the member of the library of genetically modified T cells.

6. The method of claim 5, wherein one or more of the following activities is assayed: proliferation, production of cytokines that mediate anti-tumor activity of T cells, differentiation, ability to overcome the effects of suppressive metabolites and / or other suppressive factors in the tumor microenvironment (TME), ability to persist and maintain activity in a TME or tumor infiltration.

7. A genetically modified T cell that comprises at least one genetic modification to a gene that negatively regulates T cell fitness, wherein the genetic modification inhibits expression or activity of the polypeptide product encoded by the gene, wherein the gene is selected from the group consisting of SPTLC2, STT3B, PPIAL4D, LRIG3, GNA13, STUB1, GNAS, FAM76A, ALDH3BI, JMJD8, FBXO45, FDXR, H2AFB3, PPP6C, G0LGA1, NFKBIA, ALG3, DPEP2, CLTC, MBNL3, ERF, SYNDIG1L, Cllorf57, GTF2A2, CSNK2AI, GBEI, GNB2, HIST1H2AI, INPPL1, NT5C2, FRMD3, GARS, SIKE1, EDC4, SOCS1, EBF2, PPARG, BICC1, MDGA2, KAT8, PTPN2, CHRNB2, BRWD3, MAP4K1, REV3L, P2RY8, NR1H2, FAM3A, ADPRHL1, DUSP9, PTGER4, SATB1, RBF0X2, ZC3H12A, C12orf66, TCHH, WNT9A, MAF, SIGLEC12, MMP3, SPINK6, S0X18, PLEKHB1, CIC, TMEM127, MAP4K1, COL1A2, USP22, FAM179A, BRINP1, RORB, RGS7BP, MEF2D, FAM170A, CUTC, ZNF513, TFAP2E, CMTM4, CYP3A5, PPP1R3G, WWTR1, LRRC61, ZNF772, ADGRL4, TMCC2, SOS2, AC TAI, AN04, B3GAT1, MSI2, C15orf61, SLC30A1, S1PR1, GNA13, PTGER4, BASP1, KCNA5, ZNF835, FKBP1A, P0U5F1B, ADPRHL1, PRR19, ESRRA, SLX1A, ATF5, TMEM43, CUTC, SLC6A8, KRTAP8-1, P2RY8, MAN2C1, PDLIM7, CEBPB, CT47A2, CST7, C15orf56, F0XI2, SUN1, SHISA3, OR10A7, MUSTN1, ZNF227, CCNY, RORB, CALML3, GPR132, KLHL14, SOX30, USP49, SLC35E4, S0X11, WNT9A, GALNT11, PPM1H, PP2D1, PCGF2, FAM216A, and ADGRL4, wherein inhibition increases production of cytolytic cytokines and / or enhances tumor infiltration compared to an unmodified control T cell.

8. The genetically modified T cell of claim 7, wherein the gene is selected from the group consisting of GNAS, SPTLC2, STT3B, PPIAL4D, LRTG3, GNA13, STUB1, FAM76A, ALDH3B1, JMJD8, FBXO45, FDXR, H2AFB3, PPP6C, G0LGA1, NFKBIA, ALG3, DPEP2, CLTC, MBNL3, ERF, SYNDIG1L, Cllorf57, GTF2A2, CSNK2A1, GBEI, GNB2, HIST1H2AI, INPPL1, NT5C2, FRMD3, GARS, SIKE1, EDC4, SOCS1, EBF2, PPARG, BICC1, MDGA2, KAT8, PTPN2, CHRNB2, BRWD3, MAP4K1, and REV3L, and the T-cell expresses an increased amount of interferon-gamma compared to the unmodified control T cell.

9. The genetically modified T cell of claim 7, wherein the gene is selected from the group consisting of P2RY8, NR1H2, FAM3A, ADPRHL1, DUSP9, PTGER4, SATB1, RBF0X2, ZC3H12A, C12orf66, TCHH, WNT9A, MAF, SIGLEC12, MMP3, SPINK6, S0X18, PLEKHB1, CIC, TMEM127, MAP4K1, COL1A2, USP22,FAM179A, BRINP1, RORB, RGS7BP, MEF2D, FAM170A, CUTC, ZNF513, TFAP2E, CMTM4, CYP3A5, PPP1R3G, WWTR1, LRRC61, ZNF772, ADGRL4, TMCC2, S0S2, ACTA1, AN04, B3GAT1, MSI2, C15orf61, SLC30A1, S1PR1, GNA13, PTGER4, BASP1, KCNA5, ZNF835, FKBP1A, P0U5F1B, ADPRHL1, PRR19, ESRRA, SLXIA, ATF5, TMEM43, CUTC, SLC6A8, KRTAP8-1, P2RY8, MAN2C1, PDLIM7, CEBPB, CT47A2, CST7, C15orf56, F0XI2, SUN1, SHISA3, OR10A7, MUSTN1, ZNF227, CCNY, RORB, CALML3, GPR132, KLHL14, SOX30, USP49, SLC35E4, S0X11, WNT9A, GALNT11, PPM1H, PP2D1, PCGF2, FAM216A, and ADGRL4,' and the T cell exhibits enhanced tumor infiltration compared to the unmodified control T cell.

10. The genetically modified T cell of claim 9, wherein inhibition of expression of the gene in a population of T cells results in enrichment of the population of T cells in a tumor compared to spleen.

11. The genetically modified T cell of any one of claims 7-19, wherein the T cell is a CD8+ T cell or CD4+ T cell.

12. The genetically modified T cell of any one of claims 7-11, wherein the gene is inhibited using a clustered, regularly interspaced, short palindromic repeats (CRISPR) system.

13. The genetically modified T cell of any one of claims 7-11, wherein the gene is inhibited using a transcription activator-like effector nuclease (TALEN) system.

14. The genetically modified T cell of any one of claims 7-11, wherein the gene is inhibited using a zinc finger nuclease system.

15. The genetically modified T cell of any one of claims 7-11 wherein the gene is inhibited using a meganuclease system.

16. The genetically modified T cell of any one of claims 7-15, wherein the genetic modification inactivates the gene.

17. The genetically modified T cell of any one of claims 7-11, wherein the gene is inhibited using inhibitory RNA.

18. The genetically modified T cell of any one of claims 7-11, wherein the gene is inhibited using shRNA, siRNA, microRNA, or an antisense RNA.

19. The genetically modified T cell of any one of claims 7-18, wherein the gene is a P2RY8 gene and the T cell further comprises a genetic modification that inhibits expression or activity of the polypeptide product encoded by a GNAS gene.

20. The genetically modified T cell of any one of claims 7-18, wherein the T cell expresses a CAR.

21. The genetically modified T cell of claim 20, wherein the T cell expresses an HLA-Independent TCR-based Chimeric Antigen Receptor, a T cell receptor fusion construct (TRuC), a synthetic T cell receptor and antigen receptor (STAR), an antibody-T-cell receptor (AbTCR) or a T cell antigen coupler (TAC).

22. A population of cells comprising the genetically modified T cell of any one of claims 7-21.

23. A method of treating cancer comprising administering the population of cells of claim 22 to a subject that has cancer.

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