product

Abstract

The invention relates to improving the efficiency of adoptive cell therapy with T cells.

Description

[0001] PRODUCT

[0002] Field of invention

[0003] The invention relates to T cells, methods of preparing T cells, and uses thereof.

[0004] *ound of the invention

[0005] Adoptive cell therapy (ACT) with ex vzvo-derived T cells is a promising approach to treat human malignancies such as cancer and autoimmune disorders.

[0006] Despite the successes, there remains much to be improved in ACT as durable responses are still difficult to achieve with some patients (Restifo et al., 2016 Nat Rev Cancer 16: 121-126; Borcoman et al., 2019 Ann Oncol 30: 385-396). Beyond tumour heterogeneity and microenvironments, much of the shortcomings of the current cell therapies can be attributed to the ‘quality’ (i.e. the state) of the initial and expanded T cells used, as this can impact their proliferation and differentiation, as well as their eventual homing, persistence, and cytotoxicity (Fraietta et al., 2018 Nat Med 24: 563-571). Improving T-cell state during the manufacturing process is therefore a key consideration for improved treatment efficacy.

[0007] Current approaches to improve T cell quality for ACT utilize different starting subpopulations, or chemical and genetic modification during ex vivo expansion. It is thought that T cell subsets with less differentiated cell states (i.e. naive, central memory or memory stem cells) have functional advantages and are considered a better source of starting material rather than more differentiated cells (Hinrichs et al., 2011 Blood 117: 808-814; Klebanoff et al., 2012 J Immunother 35: 651-660; Xu et al., 2014 Blood 123: 3750-3759; Busch et al., 2016 Semin Immunol 28: 28-34). Less differentiated cells, however, are harder to genetically manipulate and so protocols have been developed to use chemical inhibition of signalling pathways (e.g., p38 Kinase or AKT signalling) to allow efficient transduction and expansion of minimally differentiated human T cells (Klebanoff et al., 2017 JC1 Insight 2). Genetically improved T cells have also been achieved by expressing chimeric antigen receptors (CARs) for tailored specificity and downstream signaling through knockout / loss of function of proteins such as PD-1, RASA2, PTPN2, SOCS1, and gain of function through CRISPRa approaches (Gurusamy et al., 2020 Cancer Cell 37: 818-833. e9). As a cell’s state is determined by systemic changes in transcription factor expression and activity, modifying transcription factor (TF) activity in T cells during their ex vivo manufacturing could be an alternative approach to improve T cell quality and provide tailored function for ACT.

[0008] It is an object of the invention to provide further and improved T cells.

[0009] Summary of preferred embodiments

[0010] The inventors have discovered that T cell activation and T cell cytotoxicity can be improved by modifying a T cell to express or overexpress one or more proteins(s) selected from the group consisting of FOSL1, FASLG, STAT3, RAS, RAF, MAP4K, MEKK2 / 3, MEK5 and ERK5, or a functional fragment thereof. In particular, the inventors have found that cells which were modified to express or overexpress one or more of these protein(s) showed greatly improved cytotoxicity and T cell activation. In this respect, a T cell of the invention may comprise a higher amount of the protein or the functional fragment of the protein compared to a T cell which has not been modified to express the protein or a functional fragment thereof. A T cell of the invention may show improved T cell activation and / or T cell cytotoxicity compared to a T cell which has not been modified to express the protein or a functional fragment thereof . It will be understood that the comparison in protein levels between a T cell of the invention and a control cell will be for the same protein, e.g. FOSL1.

[0011] FOSL1 is particularly preferred as the inventors have shown that modifying a T cell to express or overexpress this protein resulted in greatly improved T cell activation and cytotoxicity.

[0012] In some embodiments, the invention provides a T cell which has been modified to express one more protein(s) having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to any one of SEQ ID NOs 1, 3, 5, 7, 9, 11, 13, 15, 17 and / or 19. Most preferably, the protein has at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 1.

[0013] In preferred embodiments, the T cell is genetically modified to express or overexpress the one or more protein(s). For example, the T cell may comprise one or more transgene(s) for expressing the one or more protein(s) selected from the group consisting of FOSL1, FASLG, STAT3, RAS, RAF, MAP4K, MEKK2 / 3, MEK5 and ERK5, or a functional fragment thereof. Most preferably, the T cell comprises a transgene for the expression or overexpression of FOSL1.

[0014] The T cell may also be modified to comprise one or more vector(s) comprising one or more transgene(s) for expressing the one or more protein(s) selected from the group consisting of FOSL1, FASLG, STAT3, RAS, RAF, MAP4K, MEKK2 / 3, MEK5 and ERK5, or a functional fragment thereof. The vector may be a human artificial chromosome.

[0015] The transgene may have a sequence having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to any one of SEQ ID NOs 2, 4, 6, 8, 10, 12, 14, 16, 18 and / or 20; most preferably SEQ ID NO: 2.

[0016] The T cell may be recombinantly modified ex vivo. It may also be modified in vivo as discussed, for example, in Wakao and Shiba (Front Med (Lausanne). 2023 Apr 17:10:1141880).

[0017] In some embodiments, the T cell may have enhanced cytotoxic T cell activity during normal expansion compared to a T cell which has not been modified or a modified T cell which does not overexpress a protein according to the invention. Normal expansion in this context refers to the proliferation of T cells in response to an antigen (also known as clonal expansion in the art).

[0018] In some embodiments, the T cell may have enhanced therapeutic potential, for example through improved homing, persistence, and activation readiness compared to a T cell which has not been modified or a modified T cell which does not overexpress a protein according to the invention. Methods for determining a T cell’s potential for homing, persistence, and activation readiness will be known to a skilled person.

[0019] Where a comparison is made relative to a cell which does not overexpress a protein according to the invention, a skilled person will understand that said comparison is done relative to a cell which is not modified to overexpress the specific protein the T cell of the invention overexpresses. For example, where the T cell overexpress FOSL1 the control cells will not overexpress FOSL1. In some embodiments, the T cell is produced by exogenous addition of the protein, preferably FOSL1. In a preferred embodiment a T cell of the inventon is obtained through lentiviral delivery of the protein, for example FOSL1. This is preferred because the inventors have found that lentiviral FOSL1 expression results in stable and reproducible reprogramming of the T cell phenotype.

[0020] A T cell obtained through lentiviral delivery can be distinguished through the presence of lentiviral DNA in the T cell. For example, a T cell of this aspect of the invention may comprise lentiviral DNA, such as a lentiviral promoter. Lentiviral vectors are well known in the art and so a skilled person can determine easily whether a T cell comprises lentiviral DNA for example through sequence comparison.

[0021] A T cell of the invention may show increased expression of CD62L, CCR7, CD27 and CD25. It may also show and unchanged or low expression of CD69, PD1, and TIM3. Said expression levels will be assessed relative to a T cell which has not been modified or a modified T cell which does not overexpress a protein according to the invention. “Unchanged” in this context may mean that the expression levels differ by no more than 5% or no more than 10% when assessed through a quantitative assay, such as qPCR, ELISA etc.

[0022] The CD62L protein may have the sequence of SEQ ID NO:22 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:22.

[0023] The CCR7 protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:2L

[0024] The CCR7 protein may have the sequence of SEQ ID NO:24 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:24.

[0025] The CCR7 protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:23. The CD27 protein may have the sequence of SEQ ID NO:26 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:26.

[0026] The CD27 protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:25.

[0027] The CD25 protein may have the sequence of SEQ ID NO:28 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:28.

[0028] The CD25 protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:27.

[0029] The CD69 protein may have the sequence of SEQ ID NO:30 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:30.

[0030] The CD69 protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:29.

[0031] The PD1 protein may have the sequence of SEQ ID NO: 32 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:32.

[0032] The PD1 protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:31.

[0033] The TIM3 protein may have the sequence of SEQ ID NO:34 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:34. The TIM3 protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:33.

[0034] The CD45RA+ protein may have the sequence of SEQ ID NO:36 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:36.

[0035] The CD45RA+ protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:35.

[0036] In some embodiments, the T cell may have increased expression of one or more memory and lymphoid homing markers compared to a T cell which has not been modified or a modified T cell which does not overexpress a protein according to the invention. The one or more memory or lymphoid homing markers may be selected from a group consisting of CD62L, CCR7 and / or CD27. The T cell may be a less differentiated (e.g. they are not terminal effector cells or terminally exhausted) and / or lymphoid-trafficking- competent phenotype. Such a phenotype is associated with improved persistence and recall capacity in vivo.

[0037] In some embodiments, the T cell may maintain increased expression of the one or more memory and lymphoid homing markers when subjected to repeated stimulation. In some embodiments, the T cell may maintain increased expression when stimulated two or more times. Suitable methods for stimulating T cells are known in the art and include, for example, cytokine-driven stimulation and antibody-mediated stimulation, for example through the use of one or more antibodies that bind CD3 and / or CD28 cell surface ligands. Suitable stimulation agents are also available commercially, for example ImmunoCult™ (Stemcell, Catalog number 10971). In some embodiments, the T cell may be stimulated in the presence or absence of tumour co-culture.

[0038] In some embodiments, the T cell may display increased CD25 without concurrent CD69 upregluation compared to a T cell which has not been modified or a modified T cell which does not overexpress a protein according to the invention. The T cell may have a primed but non-acutely activated state. In some embodiments, the T cell may maintain increased CD25 without concurrent CD69 upregluation when subjected to repeated stimulation. In some embodiments, the T cell may maintain increased expression when stimulated two or more times. Suitable methods for stimulating T cells are known in the art and include, for example, cytokine-driven stimulation and antibody-mediated stimulation, for example through the use of one or more antibodies that bind CD3 and / or CD28 cell surface ligands. Suitable stimulation agents are also available commercially, for example ImmunoCult™ (Stemcell, Catalog number 10971). In some embodiments, the T cell may be stimulated in the presence or absence of tumour co-culture.

[0039] In some embodiments, the T cell may have reduced or similar PD-1 and TIM3 levels compared to a T cell which has not been modified or a modified T cell which does not overexpress a protein according to the invention.

[0040] In some embodiments, the T cell may have a CD45 isoform profile which favours CD45RA+subsets. In some embodiments, the T cell may have increased expression of CD45RA+compared to a T cell which has not been modified or a modified T cell which does not overexpress a protein according to the invention. The T cell may have stem-like or naive-like state. In some embodiments, the T cell may maintain increased expression of CD45RA+when subjected to repeated stimulation. In some embodiments, the T cell may be stimulated two or more times. In some embodiments, the stimulation is cytokine-driven stimulation. In some embodiments, the T cell is stimulated with ImmunoCult™ (Stemcell, Catalog number 10971). In some embodiments, the T cell is stimulated in the presence or absence of tumour co-culture.

[0041] In some embodiments, the T cell is compatible with tumour co-culture. The T cell of the invention may have enhanced therapeutic potential. In particular it may show improved homing, persistence, and activation readiness.

[0042] The T cell of the invention is stable across multiple stimulation and tumour engagement contexts, which provides a stable and reproducible product profile. For example, the inventors were able to achieve stability with inter alia stimulation using soluble activation reagents (immunocult) or by engaging directly with tumour using a bispecific molecule. Lentiviral F0SL1 expression results in stable and reproducible reprogramming of the T cell phenotype which is indicated by the increased expression of CD62L, CCR7, CD27 and CD25 and unchanged or low expression of CD69, PD1, and TIM3.

[0043] The invention also provides a population of T cells comprising or consisting of T cells according to the invention. The population of T cells may be allogeneic, syngeneic, or autologous.

[0044] Further provided is the use of a T cell or a population of T cells of the invention in medicine. The T cells and populations of T cells of the invention are particularly suitable for use in therapy of diseases for which T cell therapy has been shown to be effective.

[0045] In some embodiments, the T cell or population of T cells may be used in the treatment of cancer.

[0046] The cancer may be a solid tumour. It may be selected from the group consisting of bone cancer, breast cancer, pancreatic cancer, skin cancer, cancer of the head or neck, cutaneous or intraocular malignant melanoma, uterine cancer, ovarian cancer, prostate cancer, rectal cancer, cancer of the anal region, colon cancer, stomach cancer, testicular cancer, uterine cancer, carcinoma of the fallopian tubes, carcinoma of the endometrium, carcinoma of the cervix, carcinoma of the vagina, carcinoma of the vulva, cancer of the esophagus, cancer of the small intestine, cancer of the endocrine system, cancer of the thyroid gland, cancer of the parathyroid gland, cancer of the adrenal gland, sarcoma of soft tissue, cancer of the urethra, cancer of the penis, pediatric tumours, cancer of the bladder, cancer of the kidney or ureter, carcinoma of the renal pelvis, neoplasm of the central nervous system (CNS), primary CNS lymphoma, tumour angiogenesis, spinal axis tumour, brain stem glioma, glioblastoma, pituitary adenoma, Kaposi's sarcoma, epidermoid cancer and squamous cell cancer, or selected from the group consisting of neuroblastoma, glioblastoma, CNS tumour (in particular recurrent or refractory HER2 positive), sarcoma (in particular HER2 -positive), osteosarcoma (in particular metastatic HER2-positive), and liver tumours (in particular GPC3-positive paediatric tumours).

[0047] The cancer may also be a haematological malignancy, such as a cancer selected from the group consisting of: leukaemias (such as acute myeloid leukaemia (AML), acute promyelocytic leukaemia, acute lymphoblastic leukaemia (ALL), acute mixed lineage leukaemia, chronic myeloid leukaemia (CML), chronic lymphocytic leukaemia (CLL), hairy cell leukaemia and large granular lymphocytic leukaemia, myelodysplastic syndrome (MDS), myeloproliferative disorders (polycythemia vera, essential thrombocytosis, primary myelofibrosis and CML), lymphomas, multiple myeloma, monoclonal gammopathy of undetermined significance (MGUS) and similar disorders, Hodgkin's lymphoma, non-Hodgkin lymphoma (NHL), primary mediastinal large B-cell lymphoma, diffuse large B-cell lymphoma, follicular lymphoma, transformed follicular lymphoma, splenic marginal zone lymphoma, lymphocytic lymphoma, T-cell lymphoma, and a B cell cancer (such as a B-cell lymphoma).

[0048] In some embodiments, the T cell or population of T cells may be used in the treatment of an autoimmune disorder. The autoimmune disorder may be selected from the group consisting of rheumatoid arthritis, systemic lupus erythematosus (lupus), inflammatory bowel disease (IBD), such as Crohn’s disease or ulcerative colitis, multiple sclerosis (MS), Type 1 diabetes mellitus, Guillain-Barre syndrome, chronic inflammatory demyelinating polyneuropathy, psoriasis, Graves' disease, Hashimoto's thyroiditis, myasthenia gravis and vasculitis.

[0049] In some embodiments, the T cell or population of T cells may be used in the treatment or prevention of an infection. The infection may be by human immunodeficiency virus (HIV), human T-lymphotropic virus (HTLV), hepatitis A (HAV), hepatitis B (HBV), hepatitis C (HCV), Epstein-Barr virus (EBV), human papillomavirus (HPV), Kaposi's sarcoma herpes virus (KSHV), Lassa virus, cytomegalovirus (CMV), coronavirus, such as CO VID-19, Aspergillus fumigatus or tuberculosis. The infection may be a chronic infection.

[0050] Brief description of the figures

[0051] Figure 1: In vitro stimulated CD8+ T cells recapitulate physiological T-cell states. (A) PCA of naive CD8 T cells activated using CD3 / CD28 beads over the course of 17 days; (B) PCA of catalog of T-cell subsets integrated with in vitro stimulated cells; (C) Distance matrix -based hierarchical clustering of the integrated dataset; (D) Heatmap of the expression of marker genes defining different T-cell subsets. Figure 2: Gene expression trajectories of CD8+ T-cells over the course of 17 days. (A) Gene regulatory network of CD8+ T-cells generated using GENIE3. Fold change values compared to naive state are overlaid on the network; (B) Pathway enrichment for genes enriched at each time-point compared to the naive state; (C) 11 distinct gene expression patterns represented in the time course dataset. Specific transcription factors belonging to each cluster are highlighted. (D) List of transcription factors that are differentially expressed over the time course.

[0052] Figure 3: CellOracle predicts the key transcription factors important in early TCR signalling. (A) Developmental trajectory of naive and memory T cells stimulated with anti- CD3 / anti-CD28 beads. (B) PS score distribution of TFs in memory and naive CD8+ T cells perturbed using in-silico modeling using CellOracle. (C) PS-scores for TFs important for regulation of activation of memory and naive T cells. (D) Dynamic expression patterns as reported by bulk RNA-seq for genes identified from CellOracle as being important for T- cell development for both memory and naive T-cell development. (E) Active TFs predicted by CollecTRI during the different stages of ex vivo expansion of T cells. (F) Schematic of JUN / FOS leucine zippers (top panel). Dynamic expression patterns as reported by bulk RNA-seq for genes in the API family (bottom panel). (G) Gene regulatory network of CD8+ T-cells generated using GENIE3. Fold change values at 3 hours compared to naive state are overlaid on the network.

[0053] Figure 4: FOSL1 regulates CD8+ T-cell effector function. (A) Schematics of twocell assay used to study the activation of Jurkat T-cells; (B) Frequency of Jurkat cells expressing CD69 post coculture with stimulator cells. TCS and TCS-CD86 are used as stimulator cells; (C) Z-scores from RNA-seq of genes that are identified as differentially expressed between the comparisons made for cells overexpressing FOSL1 vs matched parental controls with or without stimulation. Key genes are marked; (D) Log-fold change comparisons between cells overexpressing FOSL1 and parental controls in stimulation or non-stimulation conditions; (E) Pathway enrichment for genes overexpressed in FOSL1 overexpressing cell lines compared to parental cell lines under stimulation condition; (F) Volcano plot depicting differentially expressed genes in primary CD8+ T cells overexpressing FOSL1 compared to matched donors. (G) Killing assay for primary CD8+ T cells. Stimulated and unstimulated refers to the conditions in which the primary T-cells were either loaded with the bispecific antibody or left unloaded. The loss of integrated fluorescence indicates killing of target cells (A375) expressing mOrange. (H) Levels of CD25 expression on cells from (G) post-killing.

[0054] Figure 5: FOSL1 expression promotes a central-memory-like, non-exhausted T cell phenotype under resting conditions. Flow cytometry histograms showing expression of surface markers associated with memory (CD62L, CCR7), activation (CD25, CD69), and exhaustion (PD1, TIM3) in unstimulated T cells 7 days post-transduction with either control or FOSLl-expressing lentivirus, from two independent donors. FOSL1 -expressing cells (magenta) display increased expression of CD62L, CCR7, and CD25, with low expression of CD69, PD1, and TIM3, indicative of a central-memory-like, pre-activated but non-exhausted phenotype.

[0055] Figure 6: FOSL1 sustains memory-associated markers and limits exhaustion following repeated stimulation and tumour co-culture. (Top panel) Schematic of experimental timeline. Primary human T cells were activated with ImmunoCult™ (Stemcell, Catalog number 10971) and transduced with FOSL1 or control lentivirus on Day 3. Cells were either rested or restimulated and subjected to tumour co-culture for 3 days beginning on Day 10, followed by an additional rest or continued stimulation. On Day 19, surface phenotypes were assessed by flow cytometry. (Bottom panel) Median fluorescence intensity (MFI) of key phenotypic markers on Day 19 across different treatment conditions (stimulated or unstimulated; tumour-exposed or not). Each line represents an individual sample from one of two donors. FOSL1 expression promoted sustained expression of memory markers CD62L and CD27, and reduced expression of CD45RO, CD69, TIM3, and PD1. CD25 remained elevated in FOSLl-expressing cells regardless of stimulation history. Blue lines indicate previously tumour co-cultured cells; gray lines represent tumour-naive cells.

[0056] Detailed description of the preferred embodiments

[0057] T cells

[0058] In one aspect, the invention provides a T cell with improved properties. In some aspects, the T cell of the invention shows improved cytotoxicity and / or has improved

[0059] T cell activation. The T cell of the invention may also show improved proliferation. These advantageous properties are achieved by modifying the T cell to express or overexpress one or more protein(s) selected from the group consisting of FOSL1, FASLG, STAT3, RAS, RAF, MAP4K, MEKK2 / 3, MEK5 and ERK5, or a functional fragment thereof. Preferably the T cell is modified to overexpress the one or more protein(s). It will be understood that the improvement is relative to a control T cell which has not been modified to express one or more protein(s) according to the invention.

[0060] Preferably the T cell is genetically modified to express or overexpress the one or more protein(s). The invention thus provides a T cell comprising one or more transgene(s) encoding one or more protein(s) selected from the group consisting of FOSL1, FASLG, STAT3, RAS, RAF, MAP4K, MEKK2 / 3, MEK5 and ERK5, or a functional fragment thereof. Preferably the genetically modified T cell overexpresses the one or more protein(s). In a most preferred embodiment, the genetically modified T cell comprises a transgene for expressing or overexpressing FOSL1.

[0061] The T cell may also be modified to comprise one or more vector(s) comprising one or more transgene(s) for expressing the one or more protein(s) selected from the group consisting of FOSL1, FASLG, STAT3, RAS, RAF, MAP4K, MEKK2 / 3, MEK5 and ERK5, or a functional fragment thereof. The vector will be retained, at least temporarily, extrachromosomally.

[0062] The transgene may be expressed constitutively. It may also be expressed transiently. Suitable ways of expressing a transgene transiently in a T cell will be known to a skilled person and include, for example, the Syn-notch approach described inter alia in Allen et al. (Science. 2022 Dec 16;378(6625))

[0063] A T cell of the invention may also have been modified by other means to express the one or more protein(s). For example, the T cell may comprise a small molecule that controls the expression of the one or more protein(s). Suitable small molecules will be known to a skilled person.

[0064] T cells which have been produced by exogenous addition of the protein, preferably through lentiviral delivery, are preferred. This is preferred because the inventors have found that lentiviral FOSL1 expression results in stable and reproducible reprogramming of the T cell phenotype, yielding a novel population with: Elevated expression of memory and lymphoid homing markers, including CD62L, CCR7, and CD27;

[0065] Increased CD25 without concurrent CD69 upregulation, indicating a primed but (non-acutely) activated state;

[0066] Resistance to exhaustion, with low and unchanged PD-1 and TIM3 levels, even after tumour co -culture;

[0067] A shift in CD45 isoform profile favouring CD45RA+subsets, suggesting stem-like or naive-like characteristics;

[0068] Maintenance of this state across multiple stimulation and tumour engagement contexts, indicating a stable and reproducible product profile;

[0069] Sustained functional capacity, including tumour killing, achieving a “super-killer” like transcriptional state, and cytokine responsiveness over multiple challenges.

[0070] The identification of this phenotype required systematic testing and functional characterization, as demonstrated by the present inventors. Many transcription factors enhance cytokine expression without producing a memory-like or exhaustion-resistant phenotype — and in some cases, may actually promote terminal differentiation or dysfunction.

[0071] WO2024 / 097418 discusses a CRISPR activation screen and alleges that increased interferon-gamma activation can be observed in said screen. However, mere cytokine induction in such a CRISPR activation screen is not indicative of the broader cell fate transformation demonstrated by the present inventors.

[0072] A T cell of the invention may show increased expression of CD62L, CCR7, CD27 and CD25 and unchanged or low expression of CD69, PD1, and TIM3. Said expression levels will be assessed relative to a T cell which has not been modified or a modified T cell which does not overexpress a protein according to the invention.

[0073] In some embodiments, a T cell according to the invention may comprise a functional endogenous gene encoding the endogenous protein selected from the group consisting of FOSL1, FASLG, STAT3, RAS, RAF, MAP4K, MEKK2 / 3, MEK5 and ERK5. In other embodiments, the endogenous gene may be deleted or modified to reduce expression of the endogenous protein.

[0074] A T cell which has been modified to express FOSL1 is particularly preferred. As shown in the examples, the inventors have demonstrated that cells that are modified to express FOSL1 showed increased T cell activation and increased production of cytokines and surface receptors such as FASLG, which translated into improved killing of target cells. Accordingly, in a preferred embodiment, the invention provides a T cell which has been modified to express or overexpress FOSF1.

[0075] FOSF1 expression is regulated directly by STAT3 and inflammatory cytokines and mitogens within the MAPK / ERK pathway (including RAS, RAF, MAP4K, MEKK2 / 3, MEK5 and ERK5). FOSE1 expression is directly regulated by STAT3 protein with STAT3 overexpression increasing the levels of FOSE1 mRNA in a cell (Moon Y.M. et al., Front Immunol. 2017 Dec 18:8:17932017). The expression of STAT3 is therefore expected to increase FOSE1 expression so cells expressing STAT3 are expected to have similar beneficial properties. Thus, in one embodiment, the invention provides a T cell which has been modified to express or overexpress STAT3.

[0076] FOSE1 expression has also been shown to be influenced by the MAPK / ERK pathway, which increases the transcription and expression of FOSL1. In one embodiment, the invention thus provides a T cell which has been modified to overexpress RAS, RAF, MAP4K, MEKK2 / 3, MEK5 and / or ERK5.

[0077] The inventors also discovered that T cells modified to express FOSE1 exhibited increased production of cytokines and surface receptors such FASLG, which translated into improved killing of target cells. In one embodiment, the invention provides a T cell which has been modified to express FASLG.

[0078] A “modified” T cell in the context of this disclosure is a T cell in which the expression level or expression pattern of a gene is altered compared to an unmodified (control) T cell so that the overall amount of the protein in the cell is increased compared to the control cell. This is usually achieved by transduction of a cell with one or more nucleic acid(s) that encode the protein of interest. It will be understood that this increase may be seen during all stages of T cell manipulation including the activation and expansion stages. It may also be found only during some of these stages, for example where the endogenous gene is downregulated following activation.

[0079] The T cell which has been modified may express the protein at a higher level compared to a T cell which has not been modified to express the protein. For example, a T cell of the invention may express the protein at a level which is at least 5%, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 100%, at least 150%, at least 200%, at least 250%, or at least 300% higher compared to a T cell which has not been modified to express the protein. Methods for comparing expression and protein levels are well known in the art and include, for example, methods that measure the levels of nucleic acids (such as quantitative real-time PCR (qPCR), digital PCR (dPCR), and next generation sequencing (NGS)) and methods that quantify protein levels (such as Western Blot or mass spectrometry).

[0080] In addition, or alternatively to the expression at a higher level, a T cell of the invention may also have a different expression pattern for the protein compared to a T cell which has not been modified to express the protein. For example, the inventors found that FOSL1 expression from naive cells rapidly increases upon stimulation of cells and as the stimulation time increases the expression of FOSL1 decreases. A T cell of the invention may thus show an expression pattern for a protein which differs from the expression pattern of the protein in a cell which has not been modified to express the protein. For example, the protein may be constitutively expressed in the T cell following activation whereas the wildtype gene would normally be downregulated following T cell activation. Thus, a T cell of the invention may show higher expression of the protein following activation of the T cell compared to a T cell which has not been modified to express the protein. In some embodiments, a T cell according to the invention expresses the protein, e.g. FOSL1, constitutively and may be expressed constitutively following T cell activation.

[0081] The protein may also be expressed transiently.

[0082] A T cell of the invention may express a functional fragment of a protein selected from the group consisting of FOSL1, FASLG, STAT3, RAS, RAF, MAP4K, MEKK2 / 3, MEK5 and ERK5. A skilled person will be able to ascertain which fragments of a given protein are functional. Such fragments will generally retain the conserved domains of the full-length protein, such as, for example, the basis leucine zipper domain found in FOSL1. In addition, a skilled person can easily determine the functionality of the fragment, for example by testing whether a T cell modified to express a given fragment has improved T cell cytotoxicity and / or T cell activation compared to a control cell which has not been modified to express the fragment. Suitable assays will be known to a skilled person.

[0083] Longer fragment are preferred. For example, the fragment may span at least 70%, at least 75%, at least 80%, at least 85%, at least 90, or at least 95% of the length of the full length protein. As discussed above, it preferably comprises at least one domain of the full length protein.

[0084] A T cell of the invention may be a T lymphocyte. The T cell may be an inflammatory T lymphocyte, a cytotoxic T lymphocyte, a regulatory T lymphocyte, or a helper T lymphocyte. The T lymphocyte may be a CD4+ T lymphocyte. The T lymphocyte may be a CD8+ cytotoxic T lymphocyte. The T cell may be a natural killer (NK) cell. The T cell may be a gamma / delta (y5) cell.

[0085] The T cell may additionally comprise a TCR specific to a target antigen of interest. The T cell may have been selected for expression of said TCR of interest prior to modulation of the modulated factor, or the TCR of interest may have been transduced into the T cell prior to or following modulation of the modulated factor.

[0086] The T cell is preferably suitable for use in adoptive T cell transfer therapy (ACT). The T cell retains the T cell’s suitability for ACT.

[0087] In preferred embodiments, the cell is modified to express FOSL1. FOSL1 is a transcription factor which plays an important role in cell differentiation and tumourigenesis. FOSL1 protein is often considered a subunit of the transcriptional complex API.

[0088] The FOSL1 protein may have the sequence of SEQ ID NO:1 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 1. The F0SL1 protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:2.

[0089] The TNFL6 protein may have the sequence of SEQ ID NO: 3 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 3.

[0090] The TNFL6 protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 4.

[0091] The STAT3 protein may have the sequence of SEQ ID NO: 5 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 5.

[0092] The STAT3 protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 6.

[0093] The K-RAS protein may have the sequence of SEQ ID NO: 7 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 7.

[0094] The K-RAS protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 8.

[0095] The RAFI protein may have the sequence of SEQ ID NO: 9 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 9.

[0096] The RAFI protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 10. The MEKK2 protein may have the sequence of SEQ ID NO: 11 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 11.

[0097] The MEKK2 protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 12.

[0098] The MEKK3 protein may have the sequence of SEQ ID NO: 13 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 13.

[0099] The MEKK3 protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 14.

[0100] The MEK5 protein may have the sequence of SEQ ID NO: 15 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 15.

[0101] The MEK5 protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 16.

[0102] The ERK5 protein may have the sequence of SEQ ID NO: 17 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 17.

[0103] The ERK5 protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 18.

[0104] The MAP4K protein may have the sequence of SEQ ID NO: 19 or may have at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 19. The MAP4K protein may be encoded by a nucleic acid having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO: 20.

[0105] Generally, a T cell according to the invention will have been modified, for example by introducing a transgene suitable for expressing a protein according to the invention into the T cell. Thus, a T cell according to the invention will comprise a nucleic acid encoding a protein according to the invention in addition to the endogenous wildtype coding sequence. In some embodiments a T cell according to the invention may also have had the endogenous coding sequence replaced with an exogenous coding sequence or it may have been inactivated, for example by mutating the coding sequence.

[0106] Preferably the T cell is modified ex vivo.

[0107] Methods of preparing the T cells of the invention

[0108] A T cell of the invention may be prepared by modifying a T cell to express a protein according to the invention. This can be achieved by introducing an expression construct encoding a protein according to the invention into a T cell. The invention thus provides a method of preparing a T cell of the invention comprising a step of introducing one or more nucleic acid(s) encoding one or more protein(s) selected from the group consisting of FOSL1, FASLG, STAT3, RAS, RAF, MAP4K, MEKK2 / 3, MEK5 and ERK5 into a T cell. Preferably, the protein is FOSE1. Said introduction may be by any method known in the art, most preferably by transduction.

[0109] The methods of the invention may additionally comprise a step of introducing a T-cell receptor (TCR) or chimeric antigen receptor (CAR) of interest into the T cell in order to further improve the efficacy of the T cell. Said introduction may be by any method known in the art, for example by transduction. Said introduction may be performed before or after transduction of the cell with the transgene of the invention. Said introduction may be performed simultaneously, for example by introducing the TCR or CAR and a transgene in the same transduction step, optionally in the same vector, optionally on the same expression construct. Methods for the transduction of a T cell are known in the art and include, for example, transduction using viral vectors (such as lenti viral vectors), transfection and electroporation.

[0110] T cell transduction using viral vectors is the most common approach to prepare a modified T cell. Conventional viral based expression systems could include retroviral, alpha-retroviral, lentivirus, adenoviral, adeno-associated (AAV) and herpes simplex virus (HSV) vectors for gene transfer. The use of lentiviral vectors is particularly preferred. Non-viral transduction vectors include transposon-based systems including PiggyBac™ and Sleeping Beauty™ systems. Methods for producing and purifying such vectors are known in the art. T cells may be transduced using any method known in the art. Transduction may be in vitro or ex vivo.

[0111] The T cell may be modified prior to activation. It may also be modified during the expansion stage, e.g. 1 day, 2 days, 3 days, 5 days, 1 weeks, 2 weeks or more than 2 weeks post expansion.

[0112] The term “transfection” may be used to describe non- virus-mediated nucleic acid transfer. The T cells may be transfected using any method known in the art. Transfection may be in vitro or ex vivo. Any vector capable of transfecting T cells may be used, such as conventional plasmid DNA or RNA transfection, preferably mRNA transfection. A human artificial chromosome and / or naked RNA may be used to transfect the cell with the nucleic acid sequence or nucleic acid construct. Human artificial chromosomes are described in e.g. Kazuki et al., Mol. Ther. 19(9): 1591-1601 (2011), and Kouprina et al., Expert Opinion on Drug Delivery 11(4): 517-535 (2014). Alternative non-viral delivery systems include DNA plasmids, naked nucleic acid, and nucleic acid complexed with a delivery vehicle, such as a liposome. Methods of non-viral delivery of nucleic acids include lipofection, microinjection, biolistics, virosomes, liposomes, immunoliposomes, polycation or lipidmucleic acid conjugates, naked DNA, naked RNA, artificial virions, and agent- enhanced uptake of DNA.

[0113] Nanoparticle delivery systems may be used to transfect the T cell with the nucleic acid sequence. Such delivery systems include, but are not limited to, lipid-based systems, liposomes, micelles, microvesicles and exosomes. With regard to nanoparticles that can deliver RNA, see, e.g., Alabi et al., Proc Natl Acad Sci U S A. 2013 Aug 6; 110(32): 12881- 6; Zhang et al. NAR Genom Bioinform 2: lqaa078, Adv Mater. 2013 Sep 6;25(33):4641-5; Jiang et al., Nano Lett. 2013 Mar 13; 13(3): 1059-64; Karagiannis et al., ACS Nano. 2012 Oct 23;6(10):8484-7; Whitehead et al., ACS Nano. 2012 Aug 28;6(8):6922-9 and Lee et al., Nat Nanotechnol. 2012 Jun 3;7(6):389-93. Lipid Nanoparticles, Spherical Nucleic Acid (SNA™) constructs, nanoplexes and other nanoparticles (particularly gold nanoparticles) are also contemplated as a means for delivery of a nucleic acid or vector of the invention.

[0114] The immune effector cell may be transfected by electroporation. The electroporation may be mRNA electroporation.

[0115] Also provided is a method, such as an ex vivo method, of preparing a population of T cells for adoptive cell therapy. The method may comprise culturing a T cell of the invention. The method may comprises preparing one or more T cells as provided herein and expanding said T cells. Also provided is a population of T cells produced according to methods herein.

[0116] The methods of the invention may additionally comprise a step of introducing a TCR of interest into the T cell. Said introduction may be by any method known in the art, for example by transduction. Said introduction may be performed before or after modifying the T cell to express a protein according to the invention. Said introduction may be performed simultaneously with the protein according to the invention, for example by introducing the TCR and the protein in the same transduction step, optionally in the same vector, optionally on the same expression construct.

[0117] Nucleic acids, vectors and host cells

[0118] Also provided is / are one or more isolated nucleic acid(s) encoding one or more protein(s) of the invention. In some cases, the nucleic acid is collectively present on more than one nucleic acid, but collectively together they are able to encode a protein of the invention.

[0119] Nucleic acid(s) which encode a protein of the invention can be obtained by methods well known to those skilled in the art. For example, DNA sequences coding for part or all of the protein(s) may be synthesised as desired from the corresponding amino acid sequences.

[0120] The nucleic acid may be a DNA sequence. The nucleic acid may be an RNA sequence, such as mRNA. A vector may comprise the nucleic acid.

[0121] The vector may be a viral vector. Conventional viral based expression systems could include retroviral, alpha-retroviral, lentivirus, adenoviral, adeno-associated (AAV) and herpes simplex virus (HSV) vectors for gene transfer. Lentiviral vectors are most commonly used and are thus preferred. Non- viral transduction vectors include transposon based systems including PiggyBac™ and Sleeping Beauty™ systems. Methods for producing and purifying such vectors are known in the art.

[0122] The vector may be a cloning vector or an expression vector. A suitable vector may be any vector which is capable of carrying a sufficient amount of genetic information, and allowing expression of a polypeptide of the invention.

[0123] The vector is preferably an RNA vector. Suitable RNA vectors include the RNA vectors as described in Schutsky, Keith, et al., Oncotarget 6.30 (2015): 28911 and Beatty, Gregory L., et al., Gastroenterology 155.1 (2018): 29-32.

[0124] General methods by which the vectors may be constructed, transfection methods and culture methods are well known to those skilled in the art. In this respect, reference is made to “Current Protocols in Molecular Biology”, 1999, F. M. Ausubel (ed), Wiley Interscience, New York and the Maniatis Manual produced by Cold Spring Harbor Publishing.

[0125] A nucleic acid may be provided in the form of an expression cassette, which includes control sequences operably linked to the inserted sequence, thus allowing for expression of a protein of the invention in vivo. Hence, also provided is one or more expression cassette(s) encoding the one or more nucleic acid(s) that encode a protein of the invention. These expression cassettes, in turn, are typically provided within vectors (e.g. plasmids or recombinant viral vectors). Hence, also provided is a vector encoding a protein of the invention. Further provided are vectors which collectively encode a protein of the invention. The vector may be a human artificial chromosome. Human artificial chromosomes are described in e.g. Kazuki et al., Mol. Ther. 19(9): 1591-1601 (2011), and Kouprina et al., Expert Opinion on Drug Delivery 11(4): 517-535 (2014).

[0126] The vector may be a non- viral delivery system, such as DNA plasmids, naked nucleic acid (e.g. naked RNA), and nucleic acid complexed with a delivery vehicle, such as a liposome.

[0127] The nucleic acids, expression cassettes or vectors described herein may be introduced transiently into the T cell.

[0128] Also provided is a kit suitable for transforming and / or transfecting T cell to generate a T cell or population of T cells of the invention. The kit comprises a nucleic acid or vector described herein. The kit may comprise further agents such as those discussed herein that improve transfection or transformation efficacy.

[0129] Pharmaceutical composition

[0130] The invention provides a composition comprising a T cell or population of T cells of the invention. The T cell or population of T cells may be at least 1% of the total cells in the composition, such as at least 5%, at least 10%, at least 15% at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99% or at least 99.9% of the total cells in the composition. The total cells in the composition may consist or consist essentially of the T cell or population of T cells of the invention, i.e. no other cells are detectable in the composition.

[0131] The composition may be a pharmaceutical composition. The pharmaceutical composition may comprise a pharmaceutically acceptable carrier. Suitable pharmaceutically acceptable carriers comprise aqueous carriers, diluents or excipients. Examples of suitable carriers include all aqueous and non-aqueous isotonic sterile injection solutions which may contain anti-oxidants, buffers and solutes, which render the composition isotonic with the blood of the intended recipient; aqueous and non-aqueous sterile suspensions, which may include suspending agents and thickening agents, dispersion media, antifungal and antibacterial agents, isotonic and absorption agents and the like. It will be understood that compositions of the invention may also include other supplementary physiologically active agents.

[0132] The carrier is typically pharmaceutically “acceptable” in the sense of being compatible with the other ingredients in the composition and not injurious to the subject. Compositions include those suitable for parenteral administration, including subcutaneous, intramuscular, intravenous and intradermal administration. The compositions may conveniently be presented in unit dosage form and may be prepared by any method well known in the art of pharmacy. Such methods include preparing the carrier for association with the isolated T cells. In general, the compositions are prepared by uniformly and intimately bringing into association any active ingredients with liquid carriers.

[0133] The composition may be suitable for parenteral administration. In another embodiment, the composition is suitable for intravenous administration. Compositions suitable for parenteral administration include aqueous and non- aqueous isotonic sterile injection solutions which may contain anti-oxidants, buffers, bactericides and solutes, which render the composition isotonic with the blood of the intended recipient; and aqueous and non-aqueous sterile suspensions which may include suspending agents and thickening agents.

[0134] The composition of the invention may be prepared in a manner known in the art. The composition may comprise about IxlO6to about IxlO12, about IxlO6to about IxlO11, about IxlO6to about IxlO10, about IxlO6to about IxlO9, or about IxlO7to about IxlO9T cells. In preferred embodiments the composition comprises between IxlO7to about IxlO9T cells.

[0135] The T cell or population of T cells may be administered with one or more additional therapy, such as one or more additional therapeutic agents. The additional therapeutic agent may be an anti-tumour agent. The additional therapeutic may be an additional immune effector cell.

[0136] Combined administration of the T cell or population of T cells with the additional therapeutic agent may be achieved in a number of different ways. All the components may be administered together in a single composition. Each component may be administered separately as part of a combined therapy. For example, the T cell or population of T cells of the invention may be administered before, after or concurrently with the additional therapeutic agent. The additional therapy may be chemotherapy, radiotherapy and / or surgery.

[0137] For example, in the treatment of cancer it is contemplated that the composition of the present invention may be administered in combination with an alkylating agent (such as mechlorethamine, cyclophosphamide, chlorambucil, ifosfamidecysplatin, or platinum- containing alkylating agents such as cisplatin, carboplatin and oxaliplain), and antimetabolite (such as a purine or pyrimidine analogue or an anti-folate agent, such as azathioprine and mercaptopurine), an anthracycline (such as daunorubicin, doxorubicin, epirubicin idarubicin, valrubicin, mitoxantrone or anthracycline analog), a plant alkaloid (such as a vinca alkaloid or a taxane, such as vincristine, vinblastine, vinorelbine, vindesine, paclitaxel or doestaxel), a topoisomerase inhibitor (such as a type I or type II topoisomerase inhibitor), a podophyllotoxin (such as etoposide or teniposide), a tyrosine kinase inhibitor (such as imatinib mesylate, nilotinib or dasatinib), an adenosine receptor inhibitor (such as A2aR inhibitors, SCH58261, CPI-444, SYN115, ZM241385, FSPTP or A2BR inhibitors such as PSB-1115), adenosine receptor agonists (such as CCPA, IB- MECA and CI-IB-MECA), a checkpoint inhibitor, including those of the PDL-1:PD-1 axis, nivolumab, pembrolizumab, atezolizumab, BMS-936559, MEDI4736, MPDL33280A or MSB0010718C), an inhibitor of the CTLA-4 pathway (such as ipilimumab and tremelimumab), an inhibitor of the TIM- 3 pathway or an agonist monoclonal antibody that is known to promote T cell function (including anti-OX40, such as MED 16469; and anti-4- BB, such as PF-05082566).

[0138] Prior to administration of the T cell or population of T cells of the invention, the subject may undergo lymphodepletion. Lymphodepletion may be achieved via administration to the subject with fluradabine, cyclophosphamide and / or bendamustine. Lymphodepletion may be carried out for at least about one day, such as about 2 days or about 3 days.

[0139] The T cell or population of T cells may be administered as a single dose. The T cell or population of T cells may be administered in a multiple dose regimen. For example, the initial dose may be followed by administration of a second or plurality of subsequent doses. The second and subsequent doses may be separated by an appropriate time. For example, the doses between doses may be administered once about every week, once about every 2 weeks, once about every 3 weeks, once about every four weeks, or once about every month.

[0140] The invention also provides a kit or article of manufacture including a pharmaceutical composition as described above.

[0141] The invention also provides a kit for use in a therapeutic application mentioned above, the kit comprising: (a) a pharmaceutical composition of the invention; and (b) a label or package insert with instructions for use.

[0142] Suitable containers include, for example, bottles, vials, syringes, blister pack, etc. The containers may be formed from a variety of materials such as glass or plastic. The container holds a therapeutic composition which is effective for treating the condition and may have a sterile access port (e.g, the container may be an intravenous solution bag or a vial having a stopper pierceable by a hypodermic injection needle). The label or package insert indicates that the therapeutic composition is used for treating the condition of choice. In an embodiment, the label or package insert includes instructions for use and indicates that the therapeutic or prophylactic composition can be used to treat a cancer or other condition described herein.

[0143] The kit may further comprise a further container comprising a pharmaceutically - acceptable buffer, such as bacteriostatic water for injection (BWFI), phosphate-buffered saline, Ringer's solution and dextrose solution. It may further comprise other materials desirable from a commercial and user standpoint, which would be known to persons skilled in the art, suitable examples of which include other buffers, diluents, filters, needles, and syringes.

[0144] Therapeutic uses

[0145] The invention provides the use of a T cell or population of T cells of the invention in medicine.

[0146] The T cell or population of T cells is / are particularly useful for the treatment of diseases which benefit from T cell therapy. The T cell or population of T cells of the invention may be used in a method of treating cancer, an autoimmune condition or an infection in a subject. A T cell of the invention is also useful for targeting the process of cellular senescence.

[0147] The cancer may be any cancer that is susceptible to treatment with a T cell or T cell population of the invention.

[0148] The cancer may be a solid tumour. Examples of suitable cancers to be treated include bone cancer, breast cancer, pancreatic cancer, skin cancer, cancer of the head or neck, cutaneous or intraocular malignant melanoma, uterine cancer, ovarian cancer, prostate cancer, rectal cancer, cancer of the anal region, colon cancer, stomach cancer, testicular cancer, uterine cancer, carcinoma of the fallopian tubes, carcinoma of the endometrium, carcinoma of the cervix, carcinoma of the vagina, carcinoma of the vulva, cancer of the esophagus, cancer of the small intestine, cancer of the endocrine system, cancer of the thyroid gland, cancer of the parathyroid gland, cancer of the adrenal gland, sarcoma of soft tissue, cancer of the urethra, cancer of the penis, pediatric tumours, cancer of the bladder, cancer of the kidney or ureter, carcinoma of the renal pelvis, neoplasm of the central nervous system (CNS), primary CNS lymphoma, tumour angiogenesis, spinal axis tumour, brain stem glioma, glioblastoma, pituitary adenoma, Kaposi's sarcoma, epidermoid cancer and squamous cell cancer. Solid cancers that are currently the subject of clinical trials using adoptive cell immunotherapies include neuroblastoma, glioblastoma, CNS tumour (in particular recurrent or refractory HER2 positive), sarcoma (in particular HER2-positive), osteosarcoma (in particular metastatic HER2-positive), liver tumours (in particular GPC3-positive paediatric tumours), and the T cells of the invention may be particularly useful for treating these cancers.

[0149] The cancer may be a haematological malignancy, such as a cancer selected from the list consisting of: leukaemias (such as acute myeloid leukaemia (AML), acute promyelocytic leukaemia, acute lymphoblastic leukaemia (ALL), acute mixed lineage leukaemia, chronic myeloid leukaemia (CML), chronic lymphocytic leukaemia (CLL), hairy cell leukaemia and large granular lymphocytic leukaemia, myelodysplastic syndrome (MDS), myeloproliferative disorders (polycythemia vera, essential thrombocytosis, primary myelofibrosis and CML), lymphomas, multiple myeloma, monoclonal gammopathy of undetermined significance (MGUS) and similar disorders, Hodgkin's lymphoma, non-Hodgkin lymphoma (NHL), primary mediastinal large B-cell lymphoma, diffuse large B-cell lymphoma, follicular lymphoma, transformed follicular lymphoma, splenic marginal zone lymphoma, lymphocytic lymphoma, T-cell lymphoma, and other B- cell malignancies.

[0150] The cancer may be a B cell cancer, such as a B-cell lymphoma.

[0151] The autoimmune condition may be rheumatoid arthritis, systemic lupus erythematosus (lupus), inflammatory bowel disease (IBD), such as Crohn’s disease or ulcerative colitis, multiple sclerosis (MS), Type 1 diabetes mellitus, Guillain-Barre syndrome, chronic inflammatory demyelinating polyneuropathy, psoriasis, Graves' disease, Hashimoto's thyroiditis, myasthenia gravis or vasculitis.

[0152] The infection may be an infection by human immunodeficiency virus (HIV), human T-lympho tropic virus (HTLV), hepatitis A (HAV), hepatitis B (HBV), hepatitis C (HCV), Epstein-Barr virus (EBV), human papillomavirus (HPV), Kaposi's sarcoma herpes virus (KSHV), Lassa virus, cytomegalovirus (CMV), coronavirus, such as CO VID- 19, Aspergillus fumigatus or tuberculosis. The infection may be a chronic infection.

[0153] Treatment may comprise administering to the subject an effective amount of a T cell, or population of T cells of the invention. Hence, the invention also provides a T cell, population of T cells, polynucleotide(s), vector(s), expression cassette(s), or a pharmaceutical composition of the invention for use in a method of treating cancer, an autoimmune condition or an infection. The invention also provides the use of a T cell or population of T cells, or a pharmaceutical composition of the invention for the manufacture of a medicament for the treatment of cancer, an autoimmune condition or an infection. The invention also provides the use of a T cell, population of T cells, polynucleotide(s), vector(s), expression cassette(s), or a pharmaceutical composition of the invention to treat cancer, an autoimmune condition or an infection.

[0154] The invention also provides the use of a T cell, population of T cells, or a pharmaceutical composition of the invention for the manufacture of a medicament for the treatment or prevention of an inflammatory disease.

[0155] The invention also provides the use of a T cell, population of T cells, polynucleotide(s), vector(s), expression cassette(s), or a pharmaceutical composition of the invention to treat or prevent an inflammatory disease. The inflammatory disease may be an autoimmune disease.

[0156] Also provided is a method of performing adoptive cell therapy in a subject, the method comprising administering to the subject an effective amount of a T cell or a population of T cells of the invention.

[0157] Hence, the invention also provides a T cell, population of T cells, or a pharmaceutical composition for use in adoptive cell therapy. The invention also provides the use of a T cell, population of T cells, or a pharmaceutical composition of the invention for the manufacture of a medicament for adoptive cell therapy.

[0158] The invention also provides the use of a T cell, population of T cells, or a pharmaceutical composition of the invention in adoptive cell therapy.

[0159] The therapeutic uses and methods may comprise administering a therapeutically effective amount of the T cell or population of T cells.

[0160] Also provided is a method of formulating a composition for treating cancer, wherein said method comprises mixing a T cell or population of T cells of the invention with an acceptable carrier to prepare said composition.

[0161] The subject may have been previously treated for the cancer.

[0162] The therapeutic methods and uses may comprise, prior to treatment with a T cell or population of T cells of the invention, determining whether the cancer expresses a target antigen specifically targeted by the T cell or population of T cells of the invention.

[0163] The method may comprise selecting a T cell or population of T cells based on the expression of the target antigen by the cancer, so that the T cell or population of T cells is specific for the cancer. The method may comprise transfecting or transforming a T cell with a nucleic acid in response to information on the expression of the target antigen by the cancer.

[0164] The therapeutic methods and uses described herein may comprise inhibiting the disease state (e.g. the cancer), for example by arresting its development and / or causing regression of the disease state until a desired end point is reached. The therapeutic methods and uses of the invention may comprise achieving a partial response, or a full response by the cancer. The therapeutic methods and uses of the invention may achieve remission of the cancer.

[0165] The therapeutic methods and uses described herein may delay the growth of the cancer, arrest the growth of the cancer and / or reverse the growth of the cancer. The therapeutic methods and uses of the invention may reduce the size of the cancer by at least 10%, such as at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or by 100%.

[0166] Typically, the subject to be treated is a human. However, non-humans animals such as non-human mammals are also contemplated. The non-human mammals may be primates, rats, rabbits, sheep, pigs, cows, cats or dogs.

[0167] The dose of the immune effector cell or population of immune effector cells may vary depending on the age and size of a subject, as well as on the disease, conditions and route of administration. The T cell or population of T cells may be administered at a dose of about IxlO6to about IxlO12cells. The T cell or population of T cells may be administered at a dose of about IxlO5cells / kg to about IxlO11cells / kg body weight.

[0168] The T cell or population of T cells may be administered as a single dose. The T cell or population of T cells may be administered in a multiple dose regimen. For example, the initial dose may be followed by administration of a second or plurality of subsequent doses. The second and subsequent doses may be separated by an appropriate time. For example, the doses between doses may be administered once about every week, once about every 2 weeks, once about every 3 weeks, once about every four weeks, or once about every month.

[0169] The T cell or population of T cells may be administered intravenously.

[0170] The T cell or population of T cells may be administered with one or more additional therapy, such as one or more additional therapeutic agents. The additional therapeutic agent may be an anti-tumour agent. The additional therapeutic may be an additional immune effector cell.

[0171] Combined administration of the T cell or population of T cells with the additional therapeutic agent may be achieved in a number of different ways. All the components may be administered together in a single composition. Each component may be administered separately as part of a combined therapy.

[0172] For example, the T cell or population of T cells of the invention may be administered before, after or concurrently with the additional therapeutic agent. The additional therapy may be chemotherapy, radiotherapy and / or surgery.

[0173] Prior to administration of the T cell or population of T cells of the invention, the subject may undergo lymphodepletion. Lymphodepletion may be achieved via administration to the subject with fluradabine, cyclophosphamide and / or bendamustine. Lymphodepletion may be carried out for at least about one day, such as about 2 days or about 3 days.

[0174] The biological activity and / or therapeutic efficacy of the administered T cell or population of T cells may be measured by known methods. For example, the method may comprise imaging, such as magnetic resonance imaging.

[0175] Other

[0176] It is to be understood that different applications of the disclosed cytotoxic T cells, or pharmaceutical compositions of the invention may be tailored to the specific needs in the art. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments of the invention only, and is not intended to be limiting.

[0177] In addition as used in this specification and the appended claims, the singular forms “a”, “an”, and “the” include plural references unless the content clearly dictates otherwise. Thus, for example, reference to “a T cell” includes two or more “T cells”.

[0178] Furthermore, when referring to “>.r” herein, this means equal to or greater than x. When referred to “<x” herein, this means less than or equal to x.

[0179] For the purpose of this invention, in order to determine the percent identity of two sequences (such as two polynucleotide or two polypeptide sequences), the sequences are aligned for optimal comparison purposes (e.g. gaps can be introduced in a first sequence for optimal alignment with a second sequence). The nucleotide or amino acid residues at each position are then compared. When a position in the first sequence is occupied by the same nucleotide or amino acid as the corresponding position in the second sequence, then the nucleotides or amino acids are identical at that position. The percent identity between the two sequences is a function of the number of identical positions shared by the sequences (i.e., % identity = number of identical positions / total number of positions in the reference sequence x 100).

[0180] Typically the sequence comparison is carried out over the length of the reference sequence. For example, if the user wished to determine whether a given (“test”) sequence is 95% identical to SEQ ID NO: 1, SEQ ID NO: 1 would be the reference sequence. To assess whether a sequence is at least 95% identical to SEQ ID NO: 1 (an example of a reference sequence), the skilled person would carry out an alignment over the length of SEQ ID NO: 1, and identify how many positions in the test sequence were identical to those of SEQ ID NO: 1. If at least 95% of the positions are identical, the test sequence is at least 95% identical to SEQ ID NO: 1. If the sequence is shorter than SEQ ID NO: 3, the gaps or missing positions should be considered to be non-identical positions.

[0181] The skilled person is aware of different computer programs that are available to determine the homology or identity between two sequences. For instance, a comparison of sequences and determination of percent identity between two sequences can be accomplished using a mathematical algorithm. In an embodiment, the percent identity between two amino acid or nucleic acid sequences is determined using the Needleman and Wunsch (1970) algorithm which has been incorporated into the GAP program in the Accelrys GCG software package (available at http: / / www.accelrys.com / products / gcg / ), using either a Blosum 62 matrix or a PAM250 matrix, and a gap weight of 16, 14, 12, 10, 8, 6, or 4 and a length weight of 1, 2, 3, 4, 5, or 6.

[0182] All publications, patents and patent applications cited herein, whether supra or infra, are hereby incorporated by reference in their entirety.

[0183] The following examples illustrate the invention.

[0184] Example 1 - Methods and Materials

[0185] Cell culture

[0186] Previously established T-cell stimulating cells (TCS) cell lines expressing an antihuman CD3 single-chain fragment fused to human CD 14 were utilized (Leitner et al., 2010 J Immunol Methods 362: 131-141). The Jurkat T cells and TCS cells were cultured in RPMI 1640 medium (Gibco) supplemented with 10% (v / v) fetal bovine serum (FBS), 1% (v / v) Penicillin / Streptomycin / Neomycin (final concentrations of 50 U / ml Penicillin, 50 pg / ml Streptomycin, 100 pg / ml Neomycin), and 1% HEPES. HEK-293T cells for lentiviral transfection were cultured in DMEM (Gibco), with additions of the same supplements as above. CD8+ primary T cells were culture in RPMI 1640 medium supplemented with 10% (v / v) human serum, 1% (v / v) Penicillin / Streptomycin / Neomycin (final concentrations of 50 U / ml Penicillin, 50 pg / ml Streptomycin, 100 pg / ml Neomycin), and 1% HEPES, betamercaptoethanol, 200U IL2. All cells were incubated at 37°C, 5% CO2. In primary cell experiments, cells were cultured in media without IL2 for 24 hours prior to assay.

[0187] Activation of naive cells and RNA extraction

[0188] Naive CD8+ T cells were isolated from PBMCs using Naive CD8+ T Cell Isolation Kit from Miltenyi (catalog number: 130-093-244) using the manufacturer’s instructions. Approximately 1 million cells were used for activation using Dynabeads™ (anti-CD3 / anti- CD28 beads) from ThermoFisher (catalog number: 1113 ID). The bead to cell ratio was 3:1. RNA was extracted from naive or activated CD8+ T cells using RNeasy Kit (Qiagen, catalog number: 74104) following manufacturer's instructions.

[0189] Cell culture and transductions

[0190] Jurkat T cells were seeded at one million cells / well in 6-well plates, and 1ml of lentiviral supernatant was added to each well. Transduction efficiency was measured via flow cytometry and validated via western blot. FOSL1 (NM_005438.5) expression construct was purchased from Genescript and the insert was cloned into pHR lentiviral vector.

[0191] 2 Cell Assay (2CA)

[0192] The two cell assay was performed as previously described. Briefly, Jurkat T cells were co-cultured with TCS in a 2: 1 ratio. To generate different stimulation conditions, Ultra-LEAF anti-human CD86 and PD-L1 antibodies (Biolegend (Clone #IT2.2 and #29E.2A3 respectively) were added to final concentration of 1 pg / ml. Cells were harvested after 24 hours. TCS cells were stained with PE- conjugated anti-mouse CD45 antibody (Clone #13 / 2.3; BioLegend), whereas Jurkat or primary cells were stained for CD69 activation marker (Clone #FN50), followed by flow cytometric analysis. Flow cytometry was performed on an LSRFortessa using FACSDiva software. Data was analyzed using the CytoExporeR package in R. All analyses were gated on viable and single cells, which was determined according to their FCS / SCC profile.

[0193] Activation, negative TCS selection ofJurkat T cells

[0194] Jurkat T cells were seeded at 1 million cells / well in 6-well plates and were either activated with an equal number of TCS cells, or not activated. Cells were harvested after 24 hours, and all samples were treated to negatively isolated TCS cells. A final concentration of 0.5 pg / ml biotin-conjugated mCD45 antibody (clone #30-Fl l, BioLegend: 103103) was added to the cells on ice. After 15 minutes, the cells were washed with MojoSort buffer (5% (w / v) BSA, 2 mM EDTA in PBS at pH 7.2, filtered with 0.22 pm SFCA syringe fdter before use), and incubated with 2 pl MojoSort Streptavidin Nanobeads (BioLegend catalog # 480015) on ice for 15 minutes. CD45 labelled TCS cells were separated using a magnetic rack, and Jurkat cells were collected into a new tube. Purity and activation status of Jurkat T cells in the final mixture was validated via flow cytometry. RNA was extracted from Jurkat cells using the RNeasy kit (Qiagen) using manufacturer’s instructions.

[0195] Transduction of primary cells

[0196] Primary CD8+ T cells were isolated using RosetteSep™ Human CD8+ T Cell Enrichment Cocktail (Stemcell, Catalog number 15063) using manufacturer’s instructions. Cells were activated using Human T- Activator CD3 / CD28 ImmunoCult™ (Stemcell, Catalog number 10971) 2 days prior to transduction. Recombinant Human Fibronectin Fragment (RetroNectin, TakaraBio, Catalog number T100A) reagent was used to aid colocalisation of target cells and virions. 300 pl of 25 pg / mL RetroNectin diluted in sterile PBS was applied to Non-Tissue Culture Treated 24-well plates at least 24 hours prior to transduction at 4 °C, or 2 hours at room temperature. To bind virus particles, wells were blocked with 2 % BSA for 30 minutes before centrifugation at 2000g at 32 °C for 90 minutes with 1.5 mL of viral supernatant. To bind target cells, 1.4ml viral supernatant was aspirated, and 1 million activated CD8+ T cells were immediately added to each well. The plate was spun at 526g at 32°C for 2 minutes. Transduced cells expressing GFP were isolated using FACS sorter 3 days post-transduction and used in subsequent assays.

[0197] Killing Assay using effector T-cells

[0198] FOSL1 overexpressing CD8+ T cells were generated using lentiviral transduction. 48-hours post-transductions, cells expressing GFP were sorted and cultured for a further 24 hours. Melanoma cell line, A375, engineered to express mOrange were loaded with GP100 peptide for ~4 hours. Control transduced parental CD8+ T-cells and CD8+ T-cells overexpressing FOSL1 cells were added into target cells together with bispecific antibody (10‘8M) and the plate was imaged every 2 hours using the Incucyte Live-Cell Analysis System. After 16 hours, cells were harvested and stained using anti-CD25 antibody, measured using flow cytometry. Killing levels were quantified from the Incucyte by measuring the area and the intensity of ‘red’ fluorescence.

[0199] Bulk RNA-seq analysis

[0200] FASTQ files were aligned using STAR version 2.7.3a and quantified using featureCounts version 2.0.6. Ensembl Homo sapiens GRCh38.86 was used as the reference genome. Lowly expressed genes were filtered out, and gene expression distributions of each sample were normalized using edgeR version 3.42.2. Differential expression analysis was performed using limma version 3.54.2. Genes with absolute log-fold-change> 1.5 and adjusted p.value<0.05 were defined as significant.

[0201] Construction of network using GENIE

[0202] Raw count files from featureCounts were filtered using the rowSums and cpm functions to retain genes with a CPM of > 1 in at least one sample, normalized using the calcNormFactors function, and log-transformed using the cpm function in edgeR version 3.40.2. Taking the log-CPM values as input, the top 35% most highly variable genes (HVGs) were identified using the getTopHVGs function in scran version 1.26.2. The raw count values of the HVGs were fed into GENIE3 version 1.20.0 to build regulatory networks. Only transcription factors (TFs) reported in Lambert et al., 2018 were used as candidate regulators. The software yielded a list of regulatory links, each of which contains a regulator, a target gene and a weight of the link. A threshold of 0.04 was applied to filter out less significant links. The remaining links were then imported into Cytoscape, in which networks were built and visualized, providing insights into gene regulation.

[0203] CellOracle implementation

[0204] Raw count scRNA-seq files of naive and memory CD8+ T cells (0, 12, 24 h poststimulation) from Bibby et al., 2022 Cell Rep 41: 111697 were preprocessed with Scanpy version 1.9.3 and then analyzed with CellOracle version 0.12.0. Cells were filtered to retain those with gene counts 200-7,500 (naive) or 200-6,000 (memory), <15% mitochondrial counts and >65 (out of 97) housekeeping genes compiled in Tirosh et al. PMID: 27124452, 2016. Following normalization of each cell by total counts of all genes, and log transformation, HVGs were identified using the highly_variable_genes function in Scanpy. Scanorama version 1.7.3 was then applied to remove batch effects and integrate datasets across time points. Thirty principal components were used to compute a neighborhood graph of cells, and the Louvain algorithm with a resolution of 0.6 (naive) or 0.4 (memory) was used to cluster the neighborhood graph. In the naive T-cell dataset, two disjoint clusters, naive and TEMRA, were identified by the algorithm, and only the naive subset was used in the CellOracle analysis. Similarly, the memory T-cell dataset exhibited two disjoint clusters, CD8aa and CD8aP, and only the CD8aP subset was used. To infer the progression of these cells, the DPT algorithm was used to calculate pseudotime. CellOracle GRN models were constructed using the pre-built promoter base GRN for human (hg 19) as the reference genome. The models simulated changes in cell identity in response to TF perturbations. To properly interpret the simulation results, a vector recapitulating the developmental flow of the CD8+ T cells, derived from DPT pseudotime analysis, was built. Perturbation scores (PS) were then calculated by comparing this vector with the simulated perturbation vector. Positive PS suggest that the TF perturbation would promote differentiation, whereas negative PS block differentiation. To ensure that only TFs were selected, only TFs that occur in both the base GRN and Lambert et al., 2018 were used in downstream analysis.

[0205] Data integration with publicly available RNA-seq dataset

[0206] FASTQ files generated in Project PRJNA744261 were downloaded from the European Nucleotide Archive (ENA). The files were aligned using STAR version 2.7.3a and quantified using featureCounts version 2.0.6. Ensembl Homo sapiens GRCh38.86 was used as the reference genome. Lowly expressed genes were filtered out using the filterByExpr function, and gene expression distributions of each sample were normalized using the calcNormFactors function in edgeR version 3.42.2. The Combat function in sva version 3.48.0 was used to adjust for batch effects in our datasets and the publicly available datasets.

[0207] Example 2 - T cell states and transitions during a 17-day ex vivo activation and expansion time course

[0208] To achieve a comprehensive overview of cell states and transcription factor (TF) network changes across T-cell activation, we performed bulk RNA sequencing on stimulated primary CD8+ T cells over a course of 17 days. This course was chosen to reflect the activation timeline that T cells typically experience during infections in vivo, and expansion ex vivo for ACT. We used naive CD8+ T cells as a starting population to reduce heterogeneity for bulk RNA-seq measurements, and because their use as a starting population (vs. unfractionated subsets of T cells) exhibits superior capacity to expand, persist and eliminate tumours.

[0209] Naive cells were stimulated with anti-CD3 / CD28 beads for seven days with RNA extracted at defined time-points (i.e., 30 mins, 3 hours, 12 hours, 24 hours, 48 hours, 72 hours, 7 days). Beads were then removed and RNA extracted at either 2, 7, or 10 days. For each time-point we extracted total RNA and performed bulk RNA-seq in three replicates. Initial principal component analysis (PCA) examination of the activation time-course revealed six major clusters of cells according to the stimulation timepoints (Figure 1A). The naive state and 30 minutes post-activation grouped together, however, by 3 hours T cell state diverged substantially from the naive cells. The next set of four time points (12- 72 hours) grouped together but remained distinct from T cells activated after 3 hours. Cells from the 7-day time point and 7 days activation with 2 days rest diverged from each other and other stimulated conditions. Lastly, cells from the long rest timepoints (7 or 10 days rest) grouped together.

[0210] Next, we compared the transcriptomic profile of in-vitro expanded CD8+cells with the catalog of bulk-RNA seq from different T cell subsets isolated from the blood of human donors that has been previously described Giles et al., 2022 Immunity 55: 557- 574.e7. This catalog consisted of various subtypes of CD8+ T-cells, namely, naive, stem cell memory (SCM), central memory (CM), effector memory (EM), effector memory RA (EMRA), and putative exhausted T-cell (Tex). The stem cell memory was further divided into two groups based on the expression of CXCR3 (SCM-CXCR3- and SCM CXCR3+), and effector memory cells were also divided into two groups based on the expression of CD27 (EMI (CD27+) and EM2 (CD27-)). As an initial examination, we reprocessed the published dataset and integrated the two datasets post batch-correction with ComBat (Zhang et al., 2020, ComBat-seq: batch effect adjustment for RNA-seq count data. NAR Genom Bioinform 2: lqaa078). This allowed us to directly compare the gene expression profile of in vitro expanded cells with the naturally occurring different subtypes of CD8 T cells. An initial PCA examination of the integrated dataset revealed a gradient of predefined subsets along PCI with naive CD8 T cells located at one end, memory subsets (SCM and CM) in the middle, and EMRA CD8 T cells at the opposite end (Figure IB). Ex vivo expanded cells on the other hand displayed a gradient along the PC2 axis with naive cells on one end and cells stimulated for 7 consecutive days on the other. Overlay of the two samples showed the distinct T-cell states that each ex vivo expanded T-cell represented. We additionally used distance matrix clustering to assess the similarity between the expanded cells and the different T-cell subsets (Figure 1C). Naive and 30- minute cells were clustered together close to the naive cells from the catalog of T-cell subsets. By three hours, cells were transiting towards the stem cell memory cell population but were still close to the bulk naive cell population. Cells expanded for 12-24 hours were most similar to the stem cell memory subset. Further expansion of the cells pushed them closer to the CM population and eventually to the PD1 expressing putative exhausted state. Interestingly, rested cells post 7 day stimulation were distinct from the 7 day stimulated but unrested cells. Rested cells were closer to the CM and EMI populations. None of the population of ex-vivo expanded cells were similar to the EMRA population.

[0211] To further validate the T-cell states, we looked at key cell state markers previously defined by Giles et al. (2022 Immunity 55: 557-574.e7) and found the activated cells expressed effector markers such as TBX21, RORC, TNF rapidly upon stimulation followed by markers of cytotoxicity such as genes encoding for granzymes and perforins such as GZMB, GZMA, and PRF1 during the later stages as the stimulation time increased. Naive and memory markers were either expressed early or late during the stimulation time course. Genes encoding several inhibitory receptors such as PD-1, LAG-3, CTLA4, TIGIT were expressed on day 7 but their expression was downregulated upon removal of stimulation, which was consistent with them being less putatively exhausted upon resting. Altogether, this analysis showed that in vitro activation drives the formation of a succession of physiological CD8+T-cell states, each of which is, in principle, selectable.

[0212] Example 3 - Gene expression profiles and patterns across a 17 day activation time course

[0213] To further characterize the different states of in vitro expanded cells, we next examined individual genes and enriched pathways across the different stages of activation. We identified the differentially expressed genes at each point compared to the naive state and performed pathway enrichments to identify how the pathways changed over the course of the activation period (Figure 2A). Gene pathway analysis showed that at 3 hours stimulation, signaling components (e.g. T-cell receptor signaling, MAPK signaling, JAK- STAT signaling, Hippo signaling, NF-kappa B signaling) were significantly upregulated (Figure 2A). Around the peak of activation 12-72 hours, T cells entered a highly proliferative state (or expansion phase) with enrichment of pathways relating to DNA replication, ribosome biosynthesis, proteasomes, cell cycle, and metabolism. During this period, pathways relating to apoptosis and cellular senescence were also enriched, likely priming the T cells for the contraction phases normally observed after pathogen clearance. Interestingly, although genes associated with the cell cycle and DNA replication persisted through the entire time course (i.e., even once the activation stimulus was removed), the pathways relating to ribosomal biogenesis, however, was not enriched during 7-day activation and rest stages. This indicated that at day 7 activation time point cells had transitioned to a low translational and proliferative state similar to that observed for T cells in a day 8 mouse-infection model (Araki et al. (2017) Nat Immunol 18: 1046-1057) . During the rest stage, it is likely the cells entered a quiescent state, supported by the reduced enrichment of genes relating to the proteasome. To further identify distinct regulatory networks during the activation time course, we then examined changes in the gene expression networks of T-cells across activation. We extracted the 35% most variably expressed genes across all timepoints and generated a gene-regulatory network using GENIE3, a previously described algorithm for inferring gene regulatory networks from expression data (Huynh-Thu et al. (2010) PLoS One 5). The resulting network consisted of -1600 nodes and -7000 edges. We then overlaid the fold-change values from the differential gene expression analysis on the nodes to identify regions of the network that were “hot” (indicating increase in expression) and “cold” (indicating decrease in expression) compared to the naive T-cell state (Figure 2B). Consistent with the PC A analysis, the network signatures could be roughly divided into five states: naive (0-30 mins), early activation (3 hours), mid activation (12-72 hours), late activation (7 days), and post-rest (7-10 days rest; Figure 2B). Collectively, this confirmed that our approach could capture unique T cell states, characterized by distinct gene regulatory networks, throughout a 17-day time course of T-cell activation.

[0214] To generate a comprehensive picture of the expression trajectory patterns, we then used all genes among the 35% of most variable genes across all the different timepoints and clustered them by their temporal expressions. We identified 11 clusters to be the optimal for this dataset. The 11 representative clusters (referred to as ‘patterns’ from hereon) each revealed a unique set of gene expression trajectories / expression patterns over the course of 17 days. Patterns 1, 2, 3 were defined by low expression at naive state and increased expression upon activation and sustained expression on resting. They differed by the timing when the initial expression after activation was observed with genes in pattern 1 expressing late in activation (72 hours onwards), pattern 2 around 48 hours and pattern 3 as early as 3 hours. The genes in these patterns included genes essential for CD8+ effector T- cells such as BATE, CD40LG, GZMH, GZMB (Kurachi et al., 2014 Nat Immunol 15: 373-383) . Genes in patterns 4 and 5 were similar to pattern 1, 2, and 3, except at the point of resting in which the expression was moderately decreased. Activation markers such as XCL1, XCL2, IL2RA, BATF3 were included in these patterns. Pattern 6 was defined by high expression upon adding the stimulus followed by low expression immediately following removal of the stimulus on day 7. Inhibitory receptors such as PDCD1, CD200 were represented in this pattern. Pattern 7 and 8 both had high expression during the naive state and decreased expression as the stimulation was continued and upon resting. A number of API transcription factor family members had this pattern including JUN, JUNB, FOS, and FOSB. An interesting pattern that was distinct from all others was 9, which was defined by a very strong upregulation 3 hours post-stimulation. The genes with this pattern included the early growth response genes such as EGR1,2, and 3, and a FOS family member FOSL2.). The two pattern types that showed differing trends upon resting were cluster 10 and cluster 11. Both showed high expression during the early time-points followed by decreased expression upon stimulation and revert to high expression during the rest phase. A number of classical exhaustion markers such as TOX and CD244 (2B4) had these patterns.

[0215] We noted that IL2, a key cytokine that is produced by T-cells upon activation, was identified in pattern 6 together with a number of other IL family proteins such as IL3, IL13, IL21R, IL411. In fact, pattern 6 contained many markers of activation including the members of the TNF families (TNFSF4, TNF). Genes in pattern 6 showed high expression already at 3 hours so this would imply that TFs that control the activation of T-cells would have to do so within the first three hours. The most striking change in TFs in the first three hours was that of the members of pattern 9 which included the members of EGR family, NR4A family, NFATC1 and RELA, which are known to be crucial for the initial signaling response.

[0216] Using the gene-regulatory network inferred earlier, we next looked at which other TFs and target genes these initial TFs regulate. Interestingly, the EGR family were predicted to regulate NFATC1, which was in turn on genes relating to effector function such as IL21R, signalling molecules of the MAPK pathways and a key co-stimulatory molecule important for effect T-cell function TNFSF14. A number of genes in pattern 6 were also regulated by the pattern 9 genes. For example, FOSL1 was predicted to be regulated by both EGR family members and NFATC1 and was predicted to regulate a number of effector related genes including TNFSF14. This suggested that perhaps a concerted effort of TFs that differentially change in the first three hours control the initial response of the T-cells and the effector response was controlled by TFs that were expressed after the initial stimulation period. Therefore, the understudied TFs that mediated the first response and the TFs that were expressed post-stimulation (TFs listed in Figure 2D) in this subset warranted further investigation.

[0217] Example 4 - In silico perturbation using CellOracle to identify early transcriptional regulators of T cell activation.

[0218] The bulk transcriptomic allowed categorization of different TF families and their functions based on their expression patterns and up / down regulation relative to a previous T-cell state. Next, we explored whether we could do a case-study of integrating the expression information on a different dataset to further refine information of TFs to T-cell state and function. For this, we opted to use a scRNA-seq dataset from a recent study by Bibby et al. In the study, human naive and memory CD4+ and CD8+ T cells were first isolated by staining with CD45RA or CD45RO and then either left unstimulated or stimulated for 12 or 24 h via anti-CD3 and anti-CD28 antibodies. While this data only covered the first 24 hours of activation, because it used the same method of activating T- cells, it provided an appropriate approach to examine if the expression pattern information from bulk analysis could be integrated into such single cell datasets.

[0219] Initial unsupervised clustering from the single cell data revealed a gradient of cells from stimulated to activated and proliferative states as the cells were subjected to stimulation with the beads in both naive and memory cell population (Figure 3A). The existence of this dataset in which naive cells or unstimulated memory cells transition into proliferating cells allowed us to investigate the transcriptional regulation of T cell state transition using CellOracle, a recently described regulatory network inference tool (Kamimoto et al., 2023 Nature 614: 742-751). CellOracle is able to model context- specific gene regulatory networks (GRNs) from scRNA-seq data and information on ‘accessibility’ of genomic regions. Here we used a pre-curated general human TF-binding network together with this scRNA-seq data to infer a T-cell activation gene-regulatory network. Once the GRN is inferred, CellOracle can be used to simulate global downstream shifts in gene expression post-perturbation. In silico perturbation in CellOracle is visualised as a vector map on the 2D trajectory space in which perturbation scores (PS) are superimposed. A negative PS implies that TF KO delays or blocks the transition to an activated / proliferative state whereas a positive PS implies that the loss of TF function promotes differentiation (2D trajectory space in right panel Figure 3A). visualised as a vector map on the 2D trajectory space in which perturbation scores (PS) are superimposed.

[0220] To validate the use of CellOracle for inferring TF role in T-cells we first identified a set of 132 and 119 transcription factors whose expression was differentially expressed in the three timepoints of the naive and memory scRNAseq datasets, respectively. Of these 88 transcription factors were shared between the two sets. For the overlapping TFs, we systematically performed an in silico KO on the base network and calculated the summed negative perturbation scores for naive and memory cell differentiation over the course of stimulation. We then calculated the negative PS sum cut-off by first calculating PS sum scores from randomised simulation and then setting the cutoff at 99th percentile of the randomised simulation to give a cut-off at false-positive rate of 0.01 (score distributions in Figure 3B). The PS scores were then represented as a scatter plot (Figure 3C). The resulting distribution of TFs based on negative PS-scores was consistent with the known functions of many well-characterized T-cell specific TFs. For example, transcription factors that are known to be involved in activation and proliferation of T-cells API family (JUNB, FOSL2, JUN, FOSB, BATF), IRF family (IRF4, IRF8), and Early growth response family (ERG1, ERG2, ERG3), NFKB1, NFATC2, NR4 (NR4A1, NR4A3) family were located on the top right comer indicating that their KO delays early stage development in both memory and naive cell population post stimulation.

[0221] We then investigated how the expression of the genes highlighted to be important for early signalling in T-cells by CellOracle related to the bulk RNA-seq transcriptional trajectories in the dataset we generated. Interestingly, 86 / 88 TFs in this list showed dynamic expression in the first 24 hours of stimulation (IRF7 and PRDM1 from cluster 1 did not) (Figure 3D). Focusing on cluster 11 (i.e., genes with acute increase at 3 hrs stimulation), 14 / 16 TFs were also identified with a significant PS score in the CellOracle analysis reiterating the role of these genes as “first responders” during T-cell activation. Another interesting observation was the genes whose expression pattern seemingly looked similar in the first 24 hours looked different over the course of the experiment (for example with pattern 7 vs pattern 11 and pattern 3 / 4 vs pattern 6). Together this showed that it is important to study temporal gene expression information during all stages of expansion and not only during the initial activation. We then used our bulk RNA-seq readings which contained the temporal dynamic gene expression changes across the different stages of ex vivo expansion to infer transcription factor activity at different time points using the CollecTRI software (Miiller- Dott et al. (2023) Nucleic Acids Res 51: 10934-10949). CollecTRI derived regulons contain signed TF- target gene interactions compiled from 12 different resources, which aids in accurate prediction of transcription factor activity from bulk RNA-seq data (Figure 3E). This analysis showed that TF activity is markedly different depending on which activation time point the cells are in. During the early stages, the initial responder TFs are API, and NFKB family TFs, which peaks around 3 hours after which proliferation related TFs are turned on (E2F family members). API, and NFkB family members up to the point where stimulus is present (day 7) but as soon as the stimulus is removed a clear switch on activity occurs with all initial responder TFs being turned off.

[0222] Both of these analyses pointed to AP-1 being tightly regulated during the ex vivo expansion of T cells. The AP-1 complex results from dimerization between members of JUN (c-Jun, JunB, JunD), FOS (c-Fos, FosB, Fra-1, and Fra-2), ATF (Activating Transcription Factor) (ATF2, ATF3 / LRF1, B-ATF), and MAF(musculoaponeurotic fibrosarcoma) (c-MAF, MAFA, MAFB, MAFG / F / K, NRL) (schematics in Figure 3F). The API family is one of the most widely studied family of transcription factors relating to T- cell activity but the regulation of cell fate by AP-1 is a complex process where it is governed by a number of factors including the relative abundances of AP- 1 subunit, the composition of the dimer composition, quality of stimulation, cell type and cell environment (Shaulian & Karin (2002) Nat Cell Biol 4: E131-6). In the context of T-cells, components of API are comprised of both activation factors (JUNC, JUND) and exhaustion-promoting factors (JUNB, BATF, BATF3) because of which the precise mechanism of interplay between all the different components of API during the different states of T cell is still not clarified. We took a closer look into the genes represented in this family, specifically the JUN-family, the FOS-family, and the ATF family members in our bulk RNA-seq data (Figure 3F). In the FOS family, FOS, FOSB and FOSL2 all had a high expression at naive stage, which then dropped as the cells proliferated. FOSL1, however, had an opposite trend as it has a very low expression at a naive stage and an increase upon activation, which gradually decreased over time. Given the interesting pattern of expression of FOSL1, and the fact that our gene-regulatory network suggested that it was one of the key genes during the key 3 hour time point (Figure 3G) combined with little literature on FOSL1, we next focused our attention to its role in T-cell activation.

[0223] Example 5 - FOSL1 enhances effector function in primary CD8- T cells

[0224] To investigate the role of FOSL1 on T-cell function, we first generated FOSL1 overexpression and FOSL1 knock out (KO) lines in immortalized human Jurkat T cells through lentiviral transduction. These engineered lines were used in activation assays using an existing stimulation system via stimulator cells (TCS-CD86) that co-express membranebound anti-CD3-scFv (to engage the TCR) and high levels of CD86 (to engage the costimulatory molecule CD28). The TCS system provides a way to modulate signaling strengths by pre -blocking the cells with anti-CD86, creating a range of stimulation conditions (Schematics in Figure 4A). Activation level of Jurkat cells was measured by expression of CD69, which is a commonly used T-cell activation marker. Jurkat cells overexpressing FOSL1 showed a higher level of CD69 expression upon stimulation under both high (stimulation of both the TCR and CD28 with TCS-CD86) or low (stimulation of only the TCR using TCS-CD86 pre-blocked with anti-CD86 antibody) stimulation context when compared to the parental Jurkat cell lines (Figure 4B). Targeting FOSL1 in Jurkat cells did not have any impact on the expression levels of CD69. This suggested that FOSL1, when expressed in sufficient levels, could act as a positive regulator of the T-cell signalling process.

[0225] To gain a better insight into the global transcriptional changes elicited by overexpression of FOSL1 in Jurkat cells, we performed a bulk RNA-analysis of the parental and FOSL1 overexpressing Jurkat cell lines that were either left unstimulated or were stimulated using TCS alone (CD86 blocked). Interestingly, the transcriptomic profile of the cells only upon overexpression of FOSL1 was already distinct from the parental cell lines even without any stimulation (Figure 4C).

[0226] Pathway enrichment suggested that the main pathway in which these cells differed was on the expression of extracellular matrix organisation with expression of laminins LAMA3 / 5), collagens (COL5A3. COL6A3, COL24A1), and integrins (ITGA3, ITGA2B, 1TGAX, ITGAM) enriched in the FOSL1 expressing lines. Interestingly, a number of components of API transcription factor themselves including ATF3, JUN, and JUNB were downregulated in the FOSL1 overexpressing cell lines. In addition, transcripts encoding granzyme B (GZMB which is a major cytokine of cytotoxic T-cells upregulated in the unstimulated cells.

[0227] We next compared the difference between parental and FOSL1 overexpressing lines under both stimulated and unstimulated conditions (Figure 4C). We could observe a high correlation between the comparisons made for FOSL1 overexpression lines vs parental lines under unstimulated and stimulation conditions. This suggested that the gene expression difference was mostly mediated by the overexpression of FOSL1 rather than the stimulation context. Under stimulation context, the key pathways that were enriched upon overexpression of FOSL1 were IL2 / STAT5 signalling pathway, TNF-alpha Signaling via NF-kB, and pathways relating to extracellular matrix reorganisation (Figure 4D). We looked at the IL2 signalling and NF-kB signalling pathway in more detail as these were more related to T-cell effector biology and noticed that transcripts for genes encoding regulators of T-cell activation such as early activation transcription factor (NR4A2), cytokine function 1L3, 1L2RB, IL23A) were enriched in cells expressing FOSL1. Of note was also TNFSF14, a major cytokine important for T-cell proliferation, which was predicted to be regulated by FOSL1 in the initial gene-regulatory network was in fact upregulated by in the FOSL1 overexpressing line. This provided additional evidence that overexpression of FOSL1 led to an increase in signalling in T-cells.

[0228] The RNA-seq experiment on Jurkat cells suggested that cells overexpressing FOSL1 had increased gene expression of cytokines and granzymes. We then tested if these transcriptional signatures of increased activation would translate to an increase in effector function in primary cytotoxic CD8 T-cells. For this we transduced three donor CD8+ T-cells with lentivirus encoding FOSL1 and performed bulk RNA-seq to assess the transcriptional changes in the cells overexpressing FOSL1 compared to the parental donors. In a similar manner as Jurkat cells, genes relating to the IL2 pathway were again upregulated in FOSL1 overexpressing cells. Effector specific markers such as BATF, GZMH, and XCL1 were also upregulated suggesting that FOSL1 could be playing a direct role in effector function of CD8+ T cells (Figure 4F). FOSL1 overexpressing cells also had an increased expression of Fas ligand (FASLG), which is a cell surface receptor expressed on cytotoxic T-cells that can bind to Fas receptor on target cells to induce programmed cell death.

[0229] To test if increased expression of FOSL1 would increase cytokine production including granzymes which would translate to better killing of target cells, we performed target killing assays with parental and FOSL1 overexpressing donor CD8+ T cells. In the killing assay, we first pre-incubated either parental or FOSL1 overexpressing CD8 T-Cells with a bispecific molecule, which is an engineered biologic that has a GP100 specific T Cell Receptor fused to a single chain antibody fragment (scFv) against CD3. This allows CD8 T-cells to engage target cells that present the GP100 peptide. The cells were then added to mOrange expressing A375 cells that were either pre-loaded with GP100 peptide (stimulated condition) or left unloaded (unstimulated condition). The target killing was performed for 16 hours and killing dynamics was assessed by quantifying the red fluorescence intensity from the target cells. We could observe that cells overexpressing FOSL1 exhibited improved kinetics of cancer cell killing as measured by loss in red- fluorescence intensity (Figure 4G). The cells at the end of the killing assay were stained with anti-CD25 antibody to quantify the level of activation and we could observe an increase in the level of CD25 expression on stimulated cells overexpressing FOSL1 (Figure 4H).

[0230] We show that FOSL1 expression from naive cells rapidly increases upon stimulation of cells and as the stimulation time increases the expression of FOSL1 decreases. This expression pattern is common to early immediate genes, which serve as the initial response to the activation signal. Given the effect of FOSL1 in regulating effector functions, the gradual decrease in expression is presumably driven by negative feedback mechanisms to prevent uncontrolled immune response. When overexpressed, FOSL1 was able to increase T cell activation and increased production of cytokines and surface receptors such FASLG, which translated into improved killing of target cells. This highlights the efficacy of our pipeline to relate TFs to core T-cell functions and rationally engineer TF activity in T cells to improve their activity.

[0231] Example 6 - FOSL1 expression promotes a central-memory-like, non-exhausted T cell phenotype under resting conditions. To evaluate the phenotypic impact of FOSL1 overexpression in human T cells, we performed multiparameter flow cytometric analysis on peripheral blood T cells from two donors, comparing FOSLl-transduced (FOSL1+) cells to control cells 7 days post introducing FOSL1 into purified CD8+ T cells (Figure 5, top panel). Expression of key markers associated with differentiation, activation, and exhaustion was assessed to determine the potential of FOSL1 to modulate T cell states relevant to adoptive cell therapy.

[0232] FOSL1 overexpressing T cells exhibited a pronounced retention of a central memory-like phenotype, as evidenced by elevated expression of CD62L and CCR7 compared to controls. CD62L and CCR7 are canonical lymphoid-homing receptors whose expression is typically downregulated upon differentiation to effector states. Their preservation in FOSL1 overexpressing cells indicates a shift toward a less differentiated, lymphoidtrafficking-competent phenotype, which is associated with improved persistence and recall capacity in vivo — key attributes for effective cell therapy products.

[0233] In addition to memory- associated markers, FOSL1 overexpressing cells showed markedly increased expression of CD25 (IL-2Ra), a marker of cytokine responsiveness and early activation versus. This suggests that FOSL1 primes T cells toward a transcriptionally poised state, potentially enhancing their readiness to respond to stimulation or cytokine-driven expansion without inducing overt activation. This is consistent with the previous data from RNA-seq where we observed increased activation related genes in FOSL1 overexpressed T cells. In contrast, expression of CD69, a transient early activation marker, was unchanged or reduced in FOSL1 overexpressing cells, and exhaustion-associated markers (PD-1 and TIM3) remained low across all groups, indicating that FOSL1 does not induce tonic signaling or T cell dysfunction.

[0234] These findings support a model in which FOSL1 promotes a hybrid phenotype characterized by memory retention, homeostatic activation, and low exhaustion, aligning with attributes known to enhance the efficacy of adoptively transferred T cells. From a therapeutic perspective, maintaining CD62L+CCR7+expression is desirable for engraftment, lymphoid tissue trafficking, and recall potential, while CD25 upregulation may improve responsiveness to homeostatic cytokines such as IL-2 or IL- 15. Importantly, the absence of PD-1 or TIM3 upregulation suggests FOSL1 does not drive premature exhaustion, which is a common limitation in engineered T cells.

[0235] To assess how FOSL1 expression impacts T cell phenotype in the context of tumour exposure and cytokine-driven stimulation, we performed a staged activation assay over 19 days (Figure 6, top). Human T cells transduced with FOSL1 or control vector were cultured with ImmunoCult™ (Stemcell, Catalog number 10971) for initial activation, rested, and then either left unstimulated or re-exposed to ImmunoCulf™ (Stemcell, Catalog number 10971) in the presence or absence of tumour co-culture. On Day 19, cells were analyzed for a panel of differentiation, activation, and exhaustion markers by flow cytometry.

[0236] Across all conditions, FOSL1 -overexpressing cells maintained a memory-like phenotype characterized by higher expression of CD62L and CD27, regardless of stimulation status or tumour engagement. CD62L and CD27 are commonly downregulated during effector differentiation, and their preservation in FOSL1 overexpressing cells suggests a resistance to terminal differentiation during repeated stimulation. This effect was observed in both donors and was particularly pronounced in cells co-cultured with tumour cells.

[0237] In line with a memory-biased phenotype, FOSL1 also reduced the expression of CD45-RO and elevated CD45-RA, especially under unstimulated conditions. This pattern suggests that FOSL1 may bias T cells toward a less differentiated or stem-like state, consistent with enhanced durability and self-renewal capacity — desirable traits for adoptive T cell products. Interestingly, CD25 remained elevated in FOSL1 overexpressing cells even after repeated stimulations, indicating sustained responsiveness to IL-2 signaling. In contrast, CD69 expression was generally reduced in FOSL1 -expressing cells, consistent with observations in the earlier timepoint (Day 10). These data support the idea that FOSL1 programs a poised, non-acutely activated state.

[0238] Importantly, the expression of exhaustion-associated markers TIM3 and PD-1 did not increase in FOSL1 overexpressing cells despite chronic stimulation and tumour contact. In many conditions, TIM3 expression was slightly reduced in the FOSL1 group, and PD-1 expression remained unchanged or lower than control, particularly in cells previously co-cultured with tumour cells. This suggests that FOSL1 protects T cells from functional exhaustion, even in contexts that typically induce it, such as persistent antigen exposure. Collectively, these findings reinforce that FOSL1 expression preserves a centralmemory-like, cytokine-responsive, and non-exhausted T cell state across diverse stimulatory environments. The maintenance of CD62L+CD27+expression and resistance to exhaustion under chronic antigen exposure highlight the therapeutic potential of FOSL1- modified T cells in adoptive cell therapy, where both durability and functional resilience are critical for clinical success.

[0239] Sequence listing

Claims

Claims1. A T cell which has been modified to express one or more protein(s) selected from the group consisting of FOSL1, FASLG, STAT3, RAS, RAF, MAP4K, MEKK2 / 3, MEK5 and ERK5, or a functional fragment thereof.

2. The T cell of claim 1, wherein the T cell comprises a higher amount of the protein or the functional fragment of the protein compared to a T cell which has not been modified to express the protein or a functional fragment thereof.

3. The T cell of claim 1 or 2 wherein the protein is FOSL1 or a functional fragment of FOSL1.

4. The T cell of any preceding claim, wherein the T cell has been genetically modified to express the one or more protein(s).

5. The T cell of claim 4, wherein the T cell comprises one or more transgene(s) for expressing the one or more protein(s) selected from the group consisting of FOSL1, FASLG, STAT3, RAS, RAF, MAP4K, MEKK2 / 3, MEK5 and ERK5, or a functional fragment thereof.

6. The T cell of any preceding claim, wherein the T cell expresses FOSL1 constitutively or transiently.

7. The T cell of any preceding claim wherein the FOSL1 protein has at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity toSEQ ID NO: 1.

8. The T cell of any one of claims 1 to 7, wherein the FOSL1 protein is encoded by a transgene having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to SEQ ID NO:2.

9. A T cell which has been modified to express one or more protein(s) having at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or 100% sequence identity to any one of SEQ ID NOs 1, 3, 5, 7, 9, 11, 13, 15, 17 and / or 19.

10. The T cell of any preceding claim wherein the T cell is a CD4+, a CD8+ T cell, a gamma-delta (y5) cell or a natural killer (NK) cell.

11. The T cell of any preceding claim wherein the T cell is recombinantly modified ex vivo.

12. The T cell of any preceding claim, wherein the T cell was produced by exogenous addition of a protein selected from the group consisting of FOSL1, FASLG, STAT3, RAS, RAF, MAP4K, MEKK2 / 3, MEK5 and ERK5.

13. The T cell of claim 12 wherein the T cell is modified using a viral vector.

14. The T cell of claim 13 wherein the viral vector is a lentiviral vector or a y-retroviral vector.

15. The T cell of any one or claims 12 to 14 wherein the T cell comprises an unmodified endogenous gene encoding a protein selected from the group consisting of FOSL1, FASLG, STAT3, RAS, RAF, MAP4K, MEKK2 / 3, MEK5 and ERK5.

16. The T cell of any preceding claim, wherein the T cell has enhanced cytotoxic T cell activity during normal expansion.

17. The T cell of any preceding claim wherein the protein is FOSL1.

18. The T cell of any preceding claim, wherein the T cell has increased expression of one or more memory and lymphoid homing markers.

19. The T cell of any preceding claim, wherein the T cell expresses one or more memory or lymphoid homing markers selected from a group constisting of CD62L, CCR7 and CD27.

20. The T cell of any preceding claim, wherein the T cell has increased CD25 expression without concurrent CD69 upregulation.

21. The T cell of any preceding claim, wherein the T cell has reduced levels of PD-1 and TIM3 expression.

22. The T cell of any preceding claim, wherein the T cell has a CD45 isoform profile which favours CD45RA+subsets.

23. The T cell of any preceding claim, wherein the T cell has increased expression of CD45RA+24. The T cell of any preceding claim, wherein the T cell is compatible with tumour coculture.

25. A population of T cells comprising or consisting of a T cell according to any one of claims 1 to 24.

26. The population of T cells of claim 25 wherein the population of T cells is allogeneic, syngeneic, or autologous.

27. A T cell according to any one of claims 1 to 24 or a population of T cells according to any one of claims 25 or 26 for use in medicine.

28. A T cell according to any one of claims 1 to 24 or a population of T cells according to any one of claims 25 or 26 for use in treating cancer.

29. The T cell or the population of T cells of claim 28, wherein the cancer is a solid tumour.

30. The T cell or the population of T cells of of claim 29, wherein the cancer is selected from the group consisting of bone cancer, breast cancer, pancreatic cancer, skin cancer, cancer of the head or neck, cutaneous or intraocular malignant melanoma, uterine cancer, ovarian cancer, prostate cancer, rectal cancer, cancer of the anal region, colon cancer, stomach cancer, testicular cancer, uterine cancer, carcinoma of the fallopian tubes, carcinoma of the endometrium, carcinoma of the cervix, carcinoma of the vagina, carcinoma of the vulva, cancer of the esophagus, cancer of the small intestine, cancer of the endocrine system, cancer of the thyroid gland, cancer of the parathyroid gland, cancer of the adrenal gland, sarcoma of soft tissue, cancer of the urethra, cancer of the penis, pediatric tumours, cancer of the bladder, cancer of the kidney or ureter, carcinoma of the renal pelvis, neoplasm of the central nervous system (CNS), primary CNS lymphoma, tumour angiogenesis, spinal axis tumour, brain stem glioma, glioblastoma, pituitary adenoma, Kaposi's sarcoma, epidermoid cancer and squamous cell cancer.

31. The T cell or the population of T cells according to claim 30, wherein the cancer is neuroblastoma, glioblastoma, CNS tumour (in particular recurrent or refractory HER2 positive), sarcoma (in particular HER2-positive), osteosarcoma (in particularmetastatic HER2-positive), liver tumours (in particular GPC3-positive paediatric tumours).

32. The T cell or the population of T cells according to claim 28, wherein the cancer is a haematological malignancy; optionally wherein the haematological malignancy is a cancer selected from the group consisting of: leukaemias (such as acute myeloid leukaemia (AML), acute promyelocytic leukaemia, acute lymphoblastic leukaemia (ALL), acute mixed lineage leukaemia, chronic myeloid leukaemia (CML), chronic lymphocytic leukaemia (CLL), hairy cell leukaemia and large granular lymphocytic leukaemia, myelodysplastic syndrome (MDS), myeloproliferative disorders (polycythemia vera, essential thrombocytosis, primary myelofibrosis and CML), lymphomas, multiple myeloma, monoclonal gammopathy of undetermined significance (MGUS) and similar disorders, Hodgkin's lymphoma, non-Hodgkin lymphoma (NHL), primary mediastinal large B-cell lymphoma, diffuse large B-cell lymphoma, follicular lymphoma, transformed follicular lymphoma, splenic marginal zone lymphoma, lymphocytic lymphoma, T-cell lymphoma, and a B cell cancer (such as a B-cell lymphoma).

33. A T cell according to any one of claims 1 to 24 or a population of T cells according to any one of claims 25 or 26 for use in treating an autoimmune disorder.

34. The T cell or the population of T cells according to claim 33, wherein the autoimmune disorder is selected from the group consisting of rheumatoid arthritis, systemic lupus erythematosus (lupus), inflammatory bowel disease (IBD), such as Crohn’s disease or ulcerative colitis, multiple sclerosis (MS), Type 1 diabetes mellitus, Guillain-Barre syndrome, chronic inflammatory demyelinating polyneuropathy, psoriasis, Graves' disease, Hashimoto's thyroiditis, myasthenia gravis and vasculitis.

35. A T cell according to any one of claims 1 to 24 or a population of T cells according to any one of claims 25 or 26 for use in treating or preventing an infection.

36. The T cell or the population of T cells according to claim 35, wherein the infection is by human immunodeficiency virus (HIV), human T-lymphotropic virus (HTLV), hepatitis A (HAV), hepatitis B (HBV), hepatitis C (HCV), Epstein-Barr virus (EBV), human papillomavirus (HPV), Kaposi's sarcoma herpes virus (KSHV), Lassa virus,cytomegalovirus (CMV), coronavirus, such as COVID-19, Aspergillus fumigatus or tuberculosis, or wherein the infection is a chronic infection.

Images