Targeting serotonin transporter (SERT) for cancer immunotherapy

Abstract

The invention provides methods for the induction of the serotonin transporter (SERT) gene in solid tumor-infiltrating cytotoxic CD8 T cells. In solid tumors, CD8 T cells secrete serotonin, which stimulates their antitumor reactivities, while SERT functions as a negative regulator by depleting intratumoral serotonin. Discoveries presented herein show that the inhibition of SERT using clinically approved selective serotonin reuptake inhibitors (SSRIs), a popular class of antidepressants, can significantly enhance CD8 T cell-mediated antitumor responses in various preclinical mouse syngeneic and human xenograft tumor models. Importantly, SSRI treatment exhibited significant therapeutic synergy with anti-PD-1 therapy, and clinical data correlation studies negatively associated intratumoral SERT expression with patient survival in a range of cancers.

Description

[0001] TARGETING SEROTONIN TRANSPORTER (SERT) FOR CANCER IMMUNOTHERAPY

[0002] CROSS REFERENCE TO RELATED APPLICATIONS

[0003] This application claims the benefit under 35 U. S. C. Section 119(e) of copending and commonly-assigned U. S. Provisional Patent Application No. 63 / 778,258, filed March 26, 2025, entitled “TARGETING SEROTONIN TRANSPORTER (SERT) FOR CANCER IMMUNOTHERAPY”, which application is incorporated by reference herein.

[0004] TECHNICAL FIELD

[0005] The present invention relates to methods and materials for treating cancers.

[0006] BACKGROUND OF THE INVENTION

[0007] Immune checkpoint blockade (ICB) is a potent strategy of cancer immunotherapy that combats the immunosuppressive nature of tumors by antagonizing negative immune regulators and enhancing the host antitumor response13. By 2023, eleven ICB antibody therapies were approved by the FDA for solid tumors, targeting cytotoxic T-lymphocyte antigen 4 (CTLA-4), programmed cell death protein 1 (PD-1) and programmed cell death ligand 1 (PD-L1), or lymphocyte activation gene 3 (LAG-3)4 8. Despite highly impressive cases of complete remission in some patients9, ICB efficacy is limited by the specific characteristics of each patient, as not every checkpoint is relevant to the conditions of every tumor4 10 11. ICB therapies only have an effect in about 15-25% of treated patients, and the majority of those responders suffer tumor relapse5 12. While some progress has been made in combining existing ICB treatments to enhance efficacy12,13, identification of additional, nonredundant, immunomodulatory molecules that reshape the TME in a way that better supports a potent immune response remains a key focus of ongoing ICB research14,15.

[0008]

[0009] 5-hydroxytryptamine (5-HT), commonly referred to as serotonin, is a signaling molecule with diverse functions throughout the body16 l8. The majority of the body’s serotonin is produced by enterochromaffin cells (ECs) in the gut and subsequently transported by platelets to peripheral tissues such as the liver19-21, where it acts as both an extra- and intracellular signaling molecule. However, in the brain, where it plays a key role in sleep, mood, and behavioral regulation, serotonin is produced locally by 5-HT neurons22'23. Though the molecular machinery is the same as that used in the gut, this neuronal serotonin axis is independent from that regulated by ECs and platelets. While these two serotonin axes are the most commonly studied, the machinery necessary for the synthesis, transport, reception, and degradation of serotonin is present in many immune cells24'25. In the immune system, serotonin is believed to play a critical role in activating functions of dendritic cells (DCs) and macrophages under inflammatory conditions and there is evidence for its function as a mitogenic and immunostimulatory signal in effector T cells26-29. Furthermore, through the uptake of serotonin from activated T cells, DCs can transport serotonin to naive T cells, thereby modulating T cell activation in a manner similar to serotonin neurons in the brain30. However, the exact functions of this inflammatory serotonin are not well characterized.

[0010] The molecular network regulating serotonin and its biology, or the “serotonin axis”, involves TPH1 and MAO-A, enzymes responsible for synthesis and degradation of serotonin, respectively; the 5-HT receptors (5-HTRs), responsible for detecting serotonin and transmitting signals; and the serotonin transporter (SERT), responsible for serotonin uptake from the extracellular to the intracellular environment, thereby regulating local-tissue and cross-tissue serotonin concentrations25,31. Due to the impact that serotonin axis dysregulation in the brain has on many forms of clinical depression, various antidepressants target proteins in the serotonergic system14. The most popular class of antidepressants are selective serotonin reuptake inhibitors (SSRIs), which block SERT function and increase extracellular serotonin, greatly increasing the incidence of 5-HTR agonism32-35.

[0011]

[0012] These drugs, which include fluoxetine (trade name Prozac), citalopram (trade name Celexa), and sertraline (trade name Zoloft), have gained popularity with the boom in antidepressant usage and prescription due to their favorable safety profile compared to predecessors and alternatives32,33’36.

[0013] Unlike its well-defined role in the brain, the role of the serotonin axis regarding immune cells, especially their antitumor immunity, is poorly understood14,36. Our recent studies explored this field and found MAO-A to be a potent regulator of immune activity in the TME15,37. MAO-A inhibitors (MAOIs) were shown to both increase autocrine CD8 T cell serotonin signaling and de-polarize immunosuppressive tumor associated macrophages (TAMs)14,15,37

[0014] There is a need in the art the identification of new immune checkpoints and the associated development of materials and methods useful in new therapeutic regimens. In particular, identifying new immune checkpoint molecules hindering antitumor T cell responses and devising new therapeutic blockades are key to the development of next-generation cancer immunotherapies.

[0015] SUMMARY OF THE INVENTION

[0016] The invention disclosed herein is based upon the discovery that the serotonin transporter (SERT) gene, a molecule best known for its role in regulating serotonin neurotransmission in the brain, is induced in solid tumor-infiltrating cytotoxic CD8 T cells. In particular, we discovered that in solid tumors, CD8 T cells secrete serotonin, which stimulates their antitumor reactivities, while SERT functions as a negative regulator by depleting intratumoral serotonin. Building upon this discovery, we further demonstrate that the inhibition of SERT using clinically approved selective serotonin reuptake inhibitors (SSRIs), a popular class of antidepressants, significantly suppressed tumor growth and enhanced CD8 T cell-mediated antitumor responses in various preclinical mouse syngeneic and human xenograft tumor models. Importantly, SSRI treatment exhibited significant therapeutic synergy with anti-PD-1 therapy, and clinical data correlation studies negatively associated intratumoral SERT expression

[0017]

[0018] with patient survival in a range of cancers. These findings highlight the significance of the intratumoral serotonin axis and identify SERT as a novel immune checkpoint, positioning SSRIs as promising candidates for next-generation combination cancer therapies.

[0019] Embodiments of the invention include methods of modulating the physiology of a tumor-infiltrating CD8 T cell by introducing a SSRI in the environment in which the CD8 T cell is disposed; wherein amounts of the SSRI introduced into the environment are selected to be sufficient to modulate the physiology of the tumorinfiltrating CD8 T cell. Typically, in these embodiments, modulation of the physiology of the tumor-infiltrating CD8 T cell comprises at least one of: enhanced tumor immunoreactivity; enhanced secretion of serotonin; increased expression of IFN-Y; increased expression of Granzyme B; or decreased expression of PD-1. In certain embodiments of the invention, the tumor-infiltrating CD8 T cell is disposed in an individual diagnosed with cancer (e g. a lymphoma or a skin, breast, ovarian, prostate, colorectal or lung cancer), for example a cancer patient undergoing a therapeutic regimen comprising the administration of an immunotherapeutic agent such as an immune checkpoint inhibitor. Optionally, the SSRI comprises at least one of citalopram, escitalopram, fluoxetine, paroxetine, and sertraline, for example one or more of these compounds disposed within a nanoparticle.

[0020] The methods of the invention can further utilize a SSRI in combination with a variety of different immunotherapeutic / chemotherapeutic agents. Optionally for example, a method of the invention uses an SSRI in combination with at least one immune checkpoint inhibitor immunotherapeutic agent, such as one selected to affect CTLA-4 or a PD-1 / PD-L1 blockade. In certain embodiments, the checkpoint inhibitor comprises a CTLA-4 blocking antibody, an anti-PD-1 blocking antibody and / or an anti-PD-Ll blocking antibody. In other embodiments, the chemotherapeutic agent comprises carboplatin, cisplatin, paclitaxel, doxorubicin, docetaxel, cyclophosphamide, etoposide, fluorouracil, gemcitabine, methotrexate,

[0021]

[0022] erlotinib, imatinib mesylate, irinotecan, sorafenib, sunitinib, topotecan, vincristine, vinblastine or the like.

[0023] A related embodiment of the invention is a method of treating a cancer (e.g. a lymphoma or a skin, breast, ovarian, prostate, colorectal or lung cancer) in an individual comprising administering to the individual a SSRI; wherein amounts of the SSRI administered to the individual are selected to be sufficient to modulate the physiology of tumor-infiltrating CD8 T cells in the individual (e.g. wherein modulation of the physiology comprises enhanced tumor immunoreactivity; enhanced secretion of serotonin; increased expression of IFN-y; increased expression of Granzyme B; decreased expression of PD-1 or the like). Optionally, the SSRI comprises at least one of citalopram, escitalopram, fluoxetine, paroxetine, and sertraline, for example one of these compounds disposed within a nanoparticle. In certain embodiments, the individual is undergoing a therapeutic regimen comprising the administration of at least one immunotherapeutic agent, such as one selected to affect a CTLA-4 or a PD-1 / PD-L1 blockade. Optionally for example, a method of the invention includes administering a SSRI to the individual in combination with at least one immune checkpoint inhibitor immunotherapeutic agent selected to affect CTLA-4 or a PD-1 / PD-L1 blockade. In certain embodiments, the checkpoint inhibitor comprises a CTLA-4 blocking antibody, an anti-PD-1 blocking antibody and / or an anti-PD-Ll blocking antibody. In other embodiments of the invention, the chemotherapeutic agent comprises carboplatin, cisplatin, paclitaxel, doxorubicin, docetaxel, cyclophosphamide, etoposide, fluorouracil, gemcitabine, methotrexate, erlotinib, imatinib mesylate, irinotecan, sorafenib, sunitinib, topotecan, vincristine, vinblastine or the like.

[0024] Embodiments of the invention also include compositions of matter comprising a therapeutic agent; a SSRI; and a pharmaceutically acceptable carrier. Typically, in these embodiments, a SSRI is present in the composition in such that amounts of SSRI available for CD8 T cells in an individual administered the composition are sufficient to modulate the physiology of the CD8 T cells (e.g. wherein modulation of

[0025]

[0026] the physiology comprises enhanced tumor immunoreactivity; enhanced secretion of serotonin; increased expression of IFN-y; increased expression of Granzyme B; decreased expression of PD-1 or the like). In certain embodiments of the invention, a SSRI in the composition comprises at least one of: citalopram, escitalopram, fluoxetine, paroxetine, and sertraline. Optionally, the SSRI is disposed within a nanoparticle; for example, a nanoparticle comprising a lipid or the like. The compositions of the invention can include a variety of different immunotherapeutic / chemotherapeutic agents. Optionally for example, a composition of the invention includes at least one immune checkpoint inhibitor immunotherapeutic agent selected to affect CTLA-4 or a PD-1 / PD-L1 blockade. In certain embodiments, the checkpoint inhibitor comprises a CTLA-4 blocking antibody, an anti-PD-1 blocking antibody and / or an anti-PD-Ll blocking antibody. In other embodiments, the chemotherapeutic agent comprises carboplatin. cisplatin, paclitaxel, doxorubicin, docetaxel, cyclophosphamide, etoposide, fluorouracil, gemcitabine, methotrexate, erlotinib, imatinib mesylate, irinotecan, sorafenib, sunitinib, topotecan, vincristine, vinblastine or the like.

[0027] Other objects, features and advantages of the present invention will become apparent to those skilled in the art from the following detailed description. It is to be understood, however, that the detailed description and specific examples, while indicating some embodiments of the present invention, are given by way of illustration and not limitation. Many changes and modifications within the scope of the present invention may be made without departing from the spirit thereof, and the invention includes all such modifications.

[0028] BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1. SERT blockade suppresses tumor growth and enhances cytotoxic CD8 T cell antitumor responses in multiple syngeneic mouse tumor models (A) RT-qPCR analyses of Sert mRNA expression in tumor-infiltrating CD8 T cell subsets (gated as CD45.2+TCRβ+CD8+PD-1loor CD45.2+TCRβ+CD8+PD-1hi)

[0030]

[0031] isolated from day 14 B16-0VA tumors grown in wild-type B6 mice (n = 3). Naive CD8 T cells (gated as TCR CD8 CD44loCD62Lhi) sorted from the spleen of tumor-free B6 mice were included as a control (n = 3). (B) Schematic showing the “intratumoral serotonin axis” in analogy to the serotonin axis in the brain. In a T cell, TPH1 converts Trp into 5-HT, which is secreted into the TME and stimulates the T cell by binding to its surface 5-HTR. SERT depletes 5-HT from the TME by transporting it back into the T cell, where it is degraded by MAO-A into 5-HIAL. SSRIs can inhibit SERT activity, increasing extracellular 5-HT and preventing degradation. TPH1, Tryptophan hydroxylase 1; Trp, tryptophan; 5-HT, 5-hydroxytryptamine; TME, tumor microenvironment; 5-HTR, 5-HT receptor; SERT, serotonin transporter; MAO-A, monoamine oxidase A; 5-HIAL, 5-hydroxyindolealdehyde; SSRIs, selective serotonin reuptake inhibitors; TCR, T cell receptor; MHC, major histocompatibility complex; DC, dendritic cell; TAM, tumor associated macrophage. (C and D) SSRI treatment in tumor prevention experiments. (C) Experimental design. Six syngeneic mouse tumor models and two SSRIs (FLX and CIT) were used. D) Tumor growth and survival (n = 5). NT, non-treatment vehicle control; FLX, fluoxetine; CIT, citalopram. (E-H) SSRI treatment in tumor therapy experiments. (E) Experimental design. Two syngeneic mouse tumor models (B16-OVA and MC38) and two SSRIs (FLX and CIT) were used. (F) Tumor growth and survival (n = 5). (G and H) FACS analysis of intracellular IFN-y (G) and Granzyme B (H) production in tumor-infiltrating CD8 T cells isolated from B16-OVA tumors at day 14 (n = 4). MFI, mean fluorescence intensity. (I and J) SSRI and anti-PDl combination treatment in tumor therapy experiments. (I) Experimental design. Two syngeneic mouse tumor models (B16-0VA and MC38) and one SSRI (FLX) were used. (J) Tumor growth and survival (n = 5). Iso, Isotype control; aPDl, anti-PD-1. Representative of two (A, D, G, and H) or three (F and J) experiments. Data are presented as the means ± SEM. *P < 0.05, **P < 0.01, and ***p < 0.001 by one-way ANOVA (A, G, and H) or by log rank (Mantel-Cox) test (D, F, and J).

[0032]

[0033] Figure 2. SERT blockade enhances antitumor CD8 T cell effector and proliferating gene profiles (A) Schematic overview of the scRNA-seq experimental design. CD45+TILs were sorted from day 10 B 16-OVA tumors and then subjected to scRNA-seq analysis. Three experimental groups were included: NT (non-treatment vehicle control), FLX (fluoxetine-treated), and aPDl (anti-PD-1 treated). 10 tumors were combined for each group. Tils, tumor-infiltrating immune cells. (B) UMAP plot showing the formation of nine cell clusters from total CD45+TILs. Each dot represents a single cell and is colored according to its cell cluster assignment. UMAP, Uniform Manifold Approximation and Projection. (C) Combined UMAP plot showing the formation of three major cell clusters of antigen-experienced (CD44+) tumorinfiltrating CD8 T cells. Gene signature profiling analysis identified cluster 1 cells to be effector / proliferating CD8 T cells, cluster 2 cells to be progenitor exhausted CD8 T cells, and cluster 3 cells to be terminally exhausted CD8 T cells. (D) Individual UMAP plots showing the formation of three major cell clusters in the indicated treatment group. (E) Bar graphs showing the cell cluster proportions from (D). (F) Violin plots showing the expression distribution of the indicated genes signatures in each treatment group. (G) Dot plots displaying the expression of representative genes selected from the indicated signatures in (F). Color saturation indicates the strength of averaged gene expression. The dot size indicates the percentage of cells expressing the indicated genes. (H) RNA-velocity analysis of three major cell clusters in the indicated treatment group. Arrows represent the estimates of local average velocity, showing the path (indicated by arrow orientation) and pace (indicated by arrow length) of cell transition. (I) Venn diagram representing numbers of genes upregulated by FLX or aPDl treatment. (J) Bar plots showing the fold enrichment of indicated pathways up-regulated in tumor-infiltrating CD8 T cells treated with FLX or aPDl. Experiment was performed once; P value was calculated by Kruskal-Wallis test with Dunn's test as a post-hoc test (F).

[0034]

[0035] Figure 3. SERT works as an immune cell-intrinsic factor negatively regulating CD8 T cell-mediated antitumor responses (A-D) Sert-WT and Sert-KO mice tumor challenge experiments. (A) Experimental design, s.c., subcutaneous. (B) Tumor growth (n = 4-6). (C) FACS quantification of tumor-infiltrating CD8 T cells at day 14 (n = 4). (D) FACS analyses of intracellular Granzyme B production in tumorinfiltrating CD8 T cells at day 14 (n = 4). (E-I) Bone-marrow (BM) transfer experiments. (E) Experimental design. (F) Tumor growth (n = 8-13). (G and H) FACS analyses of intracellular IFN-y (G) and Granzyme B (H) production in tumorinfiltrating CD8 T cells isolated from tumors at day 21 (n = 5). (I) FACS analyses of PD-1 expression in tumor-infiltrating CD8 T cells isolated from tumors at day 21 (n = 7-8). MFI, median fluorescence intensity. (J and K) CD8 T cell depletion experiments. (J) Experimental design. (K) Tumor growth (n = 4). αCD8, anti-CD8. (L and M) NSG immunodeficient mice tumor challenge experiments. (L) Experimental design. Two SSRIs (FLX and CIT) were used. (M) Tumor growth (n = 6). Representative of two (B-D, F-I, and M) or three (K) experiments. Data are presented as the means ± SEM. ns, not significant, *P < 0.05, **P < 0.01, and ***P < 0.001 by Student’s t test (B-D, and F-I) or one-way ANOVA (K and M).

[0036] Figure 4. SERT works as an autonomous factor negatively regulating CD8 T cell antigen responses (A-G) CD8 T cell antigen response in the absence of SERT. (A) Experimental design. Naive CD8 T cells were purified from Sert-WT and Sert-KO B6 mice and stimulated in vitro with anti-CD3 over 4 days. (B) Cell counts at day 4 (n = 4). (C-E) RT-qPCR analyses of 112 (C), Ifng (D), and Gzmb (E) expression over time (n = 4). (F and G) FACS analyses of intracellular IFN-y (F) and Granzyme B (G) production at day 3 (n = 3). (H-L) CD8 T cell antigen response under SSRI treatment. (H) Experimental design. Naive CD8 T cells were purified from Sert-WT B6 mice and stimulated in vitro with anti-CD3 over 4 days in the presence or absence of SSRI (CIT or FLX) treatment. (I) Cell counts at day 3 (n = 4). (J) RT-qPCR analyses of effector gene (i.e. 112, Ifng, Tnf, Gzmb, Prfl ) expression at day 2 (n = 4). (K and L) FACS analyses of intracellular IFN-y (K) and Granzyme B (L) production at day 3 (n

[0037]

[0038] = 3). Representative of two (B-G, and I) or three (J-L) experiments. Data are presented as the means ± SEM. *P < 0.05, **P < 0.01, and ***P < 0.001 by Student’s I test (B-G) or by one-way ANOVA (I-L).

[0039] Figure 5. SERT restrains CD8 T cell antigen responses by directly regulating autocrine serotonin signaling pathway (A) Schematic showing the proposed autocrine serotonin signaling pathway in CD8 T cells. Possible pharmacological interventions are indicated. ASE, asenapine (an antagonist of 5-HTRs). (B and C) Serotonergic gene expression in Sert-WT CD8 T cells in response to antigen stimulation. Naive CD8 T cells were purified from Sert-WT B6 mice and stimulated with anti-CD3 for 3 days. (B) RT-qPCR analyses of 5-HTR family member gene expression at day 1 (n = 4). Naive CD8 T cells were included as a control. (C) RT-qPCR analyses of Sert, Tphl, and Maoa gene expression over time (n = 4). (D-EI) Serotonergic gene expression in activated Sert-WT and Sert-KO CD8 T cells. (D) Experimental design. Naive CD8 T cells were purified from Sert-WT and Sert-KO B6 mice and stimulated in vitro with anti-CD3 for 1 day. (E-H) RT-qPCR analyses of Tphl (E), Maoa (F), Htr2b (G), and Htr7 (H) expression (n = 4). (I-O) Autocrine serotonin signaling in Sert-WT CD8 T cells. (I) Experimental design. Naive Sert-WT CD8 T cells were stimulated with anti-CD3 for 3 days, in the presence or absence of SSRI (CIT or FLX) and / or ASE treatment. (J and K) RT-qPCR analyses of 112 (J) and Ijng (K) expression in FLX-treated CD8 T cells at day 2 (n = 3). (L) ELISA analyses of IFN-y production in CIT-treated CD8 T cell cultures at day 3 (n = 3-4). (M) ELISA analyses of serotonin levels over time (n = 4). (N and O) Western blot analyses of key signaling molecules involved in the 5-HTR-MAPK (N) and TCR (O) signaling pathways. MAPK, mitogen-activated protein kinase. (P-R) Serotonin levels in Sert-WT and Sert-KO BMT mice bearing B16-OVA tumors (denoted as WT and KO, respectively). (P) Experimental design. (Q and R) HPLC analyses of serotonin levels in tumor (Q, n = 4) and serum (R, n = 5-6) at day 21. (S-U) Serotonin levels in Sert-WT mice bearing B16-OVA tumors, with or without SSRI (i.e. FLX) and / or anti-CD8 depletion antibody treatment. (S) Experimental design. (T and U) HPLC analyses of

[0040]

[0041] serotonin levels in tumor (T, n = 8) and serum (U, n = 5) at day 14. Representative of two (B, E-H, and J-O) or three (C, Q, R, T, and U) experiments. Data are presented as the means ± SEM. ns, not significant, *P < 0.05, **P < 0.01. and ***P < 0.001 by Student’s t test (B, E-H, Q, and R) or one-way ANOVA (C and M) or two-way ANOVA with Turkey’s multiple comparisons test (J-L, T, and U).

[0042] Figure 6. SERT blockade for cancer immunotherapy: human T cell and clinical data correlation studies (A-D) Studying antigen response of human CD8 T cells treated with SSRI. (A) Experimental design. Human naive CD8 T cells were sorted from healthy donor PBMCs and stimulated in vitro, in the presence or absence of SSRI (FLX or CIT) for 5 days. PBMCs, peripheral blood mononuclear cells. (B) RT-qPCR analyses of the serotonergic gene expression in the indicated CD8 T cells at day 1 (n = 3). Naive CD8 T cells were included as control. (C) Cell counts at day 3 (n = 3). (D) RT-qPCR analyses of effector genes (i.e. 1L2, IFNG. GZMB) at day 3 (n = 4). (E-J) Studying gene profde of human tumor-infdtrating CD8 T cells. (E) Experimental design. Eight scRNA-seq datasets across seven cancer types (PRJNA705464, EGAS00001004809, GSE123813, GSE164522, GSE179994, GSE181061, GSE200996, and GSE212217) were retrieved from the uTILity Human TIL scRNA-seq Database and combined for the analysis. (F) Combined UMAP plot showing the formation of six major cell clusters of human tumor-infiltrating CD8 T cells. Each dot represents a single cell and is colored according to its cell cluster assignment. CM, central memory; EM, effector memory; TEMRA, terminally differentiated effector memory; TPEX, progenitor exhausted T; TEX, exhausted T. (G) Heatmap showing gene expression in the indicated CD8 T cell clusters. (H) Violin plots showing the expression distribution of the serotonergic gene signature in each cluster. (I) Heatmap displaying the expression of representative genes selected from the serotonergic gene signature. (J) RT-qPCR analyses of the selected signature gene expression in human CD8 T cells sorted from PBMCs and stimulated in vitro with or without SSRI (FLX or CIT) for 3 days (n = 3-4). (K-P) Studying SERT blockade therapy in a human melanoma xenograft model. (K) Schematic showing a humantumor-T cell pair designated for the experiments. A375-A2-ESO-FG, human A375 melanoma cell line engineered to express an NY-ESO-1 tumor antigen, its matching MHC molecule (HLA-A2), and a dual reporter comprising a firefly luciferase and an enhanced green fluorescence protein (FG). ESO-T. human CD8 T cell engineered to express an NY-ESO-1 antigen-specific TCR. ESOp, NY-ESO-1 peptide. (L) Experimental design. (M) Tumor growth (n = 4). (N-P) FACS analyses of tumorinfiltrating human CD8 T cell numbers (N), and intracellular production of IFN-y (O) and Granzyme B (P) (n = 3). (Q) Clinical data correlation studies. Kaplan-Meier plots showing the association between SERI expression in tumor and survival of cancer patients in a melanoma cohort (GSE8401@PRECOG, n = 67), a breast cancer cohort (METABRIC, n = 233), a lung cancer cohort (TCGA, n = 484), a kidney cancer cohort (TCGA. n = 256), and a sarcoma cohort (TCGA, n = 258). Representative of two (B-D and M-P) experiments. Data are presented as the means ± SEM. *P < 0.05, **P < 0.01, and ***P < 0.001 by one-way ANOVA (C, D, and J) or by Student’s t test (B, and M-P). P value was calculated by Kruskal-Wallis test with Dunn's test as a post-hoc test (H), or two-sided Wald test in a Cox-PH regression (Q).

[0043] Figure 7. Working model of intratumoral serotonin axis regulation of CD8 T antitumor immunity Schematic showing the “intratumoral serotonin axis” regulating CD8 T cell antitumor immunity. In this model, SERT restrains CD8 T cell antitumor responses by inhibiting the CD8 T cell-autocrine 5-HT signaling pathway in tumors. CD8 T cell is a major producer of 5-HT (or serotonin) in the TME. Upon recognition of TA, tumor-infiltrating CD8 T cells upregulate expression of TPH1, which synthesizes 5-HT to enhance T cell activation. SERT is induced by TCR / TA recognition, which in turn downregulates T cell activities by terminating 5-HT signaling via the reuptake of extracellular T cell-derived 5-HT into tumoral CD8 T cells. Blocking SERT activity using established SSRI antidepressants depletes peripheral 5-HT; however, it increases the levels of local T cell autocrine 5-HT in the TME, which activates the 5-HTR-MAPK-NF-κB signaling pathway and enhances CD8 T cell antitumor reactivities. TA, tumor antigen.

[0044]

[0045] DETAILED DESCRIPTION OF THE INVENTION

[0046] In the description of embodiments, reference may be made to the accompanying figures which form a part hereof, and in which is shown by way of illustration a specific embodiment in which the invention may be practiced. It is to be understood that other embodiments may be utilized, and structural changes may be made without departing from the scope of the present invention. Unless otherwise defined, all terms of art, notations and other scientific terms or terminology used herein are intended to have the meanings commonly understood by those of skill in the art to which this invention pertains. In some cases, terms with commonly understood meanings are defined herein for clarity and / or for ready reference, and the inclusion of such definitions herein should not necessarily be construed to represent a substantial difference over what is generally understood in the art. Many of the aspects of the techniques and procedures described or referenced herein are well understood and commonly employed by those skilled in the art. The following text discusses various embodiments of the invention.

[0047] As discussed in detail below, we have discovered that selective serotonin reuptake inhibitors (SSRIs), a popular class of antidepressants, can be used to significantly enhance CD8 T cell-mediated antitumor responses in various preclinical mouse syngeneic and human xenograft tumor models. Moreover, SSRI treatment exhibited an unexpected therapeutic synergy’ with anti-PD-1 therapy, and clinical data correlation studies negatively associated intratumoral SERT expression with patient survival in a range of cancers. These findings demonstrate the significance of the intratumoral serotonin axis in CD8 T cells, and identify SERT as a key regulator. Building upon these discoveries, we show that SSRIs are promising agents for use in, for example, next-generation combination cancer therapies.

[0048] As shown below, the invention disclosed herein has a number of embodiments. For example, embodiments of the invention include methods of modulating a physiology of a tumor-infiltrating CD8 T cell comprising introducing a SSRI in the

[0049]

[0050] environment in which the CD8 T cell is disposed; wherein amounts of the SSRI introduced into the environment are selected to be sufficient to modulate the physiology of the tumor-infiltrating CD8 T cell (e.g. wherein modulation of the physiology comprises enhanced tumor immunoreactivity or the like so that the physiology is modulated). In certain embodiments of the invention, the tumorinfiltrating CD8 T cell is disposed in an individual diagnosed with cancer (e.g. a lymphoma or a skin, breast, ovarian, prostate, colorectal or lung cancer), for example a patient undergoing a therapeutic regimen comprising the administration of a chemotherapeutic agent. Typically, in these embodiments, modulation of the physiology of the tumor-infiltrating CD8 T cell comprises at least one of: enhanced tumor immunoreactivity; enhanced secretion of serotonin; increased expression of IFN-y; increased expression of Granzyme B; or decreased expression of PD-1. Optionally, the SSRI comprises at least one of citalopram (Celexa), escitalopram (Lexapro), fluoxetine (Prozac), paroxetine (Paxil, Pexeva), and sertraline (Zoloft), for example one of these compounds disposed within a nanoparticle. These methods of the invention can introduce a SSRI into an environment in which CD8 T cells are disposed in combination with a variety of different therapeutic agents. Optionally for example, a method of the invention introduces at least one immune checkpoint inhibitor immunotherapeutic agent selected to affect CTLA-4 or a PD-1 / PD-L1 blockade. In certain embodiments, the checkpoint inhibitor comprises a CTLA-4 blocking antibody, an anti-PD-1 blocking antibody and / or an anti-PD-L1 blocking antibody. In other embodiments, the chemotherapeutic agent comprises carboplatin, cisplatin, paclitaxel, doxorubicin, docetaxel, cyclophosphamide, etoposide, fluorouracil, gemcitabine, methotrexate, erlotinib, imatinib mesylate, irinotecan, sorafenib, sunitinib, topotecan, vincristine, vinblastine or the like.

[0051] A related embodiment of the invention is a method of treating a cancer (e.g. a lymphoma or a skin, breast, ovarian, prostate, colorectal or lung cancer) in an individual comprising administering to the individual one or more SSRIs; wherein amounts of the SSRI administered to the individual are selected to be sufficient to

[0052]

[0053] modulate the physiology of tumor-infiltrating CD8 T cells in the individual (e.g. wherein modulation of the physiology comprises enhanced tumor immunoreactivity; enhanced secretion of serotonin; increased expression of IFN-y; increased expression of Granzyme B; decreased expression of PD-1 or the like). Optionally, the SSRI comprises at least one of citalopram, escitalopram, fluoxetine, paroxetine, and sertraline, for example one of these compounds disposed within a nanoparticle. In certain embodiments, the individual is undergoing a therapeutic regimen comprising the administration of at least one therapeutic agent. Some embodiments of the invention include methods of administering SSRI to the individual in combination with an immunotherapeutic / chemotherapeutic agent. Optionally for example, a method of the invention includes administering a SSRI to the individual in combination with at least one immune checkpoint inhibitor immunotherapeutic agent selected to affect CTLA-4 or a PD-1 / PD-L1 blockade. In certain embodiments, the checkpoint inhibitor comprises a CTLA-4 blocking antibody, an anti-PD-1 blocking antibody and / or an anti-PD-Ll blocking antibody. In other embodiments of the invention, the chemotherapeutic agent comprises carboplatin, cisplatin, paclitaxel, doxorubicin, docetaxel, cyclophosphamide, etoposide, fluorouracil, gemcitabine, methotrexate, erlotinib, imatinib mesylate, irinotecan, sorafenib, sunitinib, topotecan, vincristine, vinblastine or the like.

[0054] Embodiments of the invention include compositions of matter comprising a therapeutic agent; a SSRI; and a pharmaceutically acceptable carrier. Typically, in these embodiments, a SSRI is present in the composition in such that amounts of SSRI available for CD8 T cells in an individual administered the composition are sufficient to modulate the physiology of the CD8 T cells (e.g. wherein modulation of the physiology comprises enhanced tumor immunoreactivity; enhanced secretion of serotonin; increased expression of IFN-y; increased expression of Granzyme B; decreased expression of PD-1 or the like).

[0055] In certain embodiments of the invention, a SSRI in the composition comprises at least one of: citalopram, escitalopram, fluoxetine, paroxetine, and sertraline.

[0056]

[0057] Optionally, the SSRI is disposed within a nanoparticle; for example, a nanoparticle comprising a lipid or the like. In particular, embodiments of the invention can utilize such nanocarriers to modulate the circulatory half-life of free SSRIs. Illustrative nanocarriers include lipid-coated mesoporous silica nanoparticles (“silicasomes”) as well as liposome platforms. In certain embodiments, the nanocarrier is designed to have a size, a charge, one or more surface coatings (e.g., PEG, copolymers), one or more targeting ligands (e.g., peptides) and the like: an optionally the inclusion of imaging agents and the like, with a view to obtaining colloidal stability, low opsonization, long circulatory tl / 2, and effective biodistribution post intravenous (IV) injection.

[0058] Liposomes can be synthesized using lipid biofilm, rehydration, sonication and extrusion (e.g. using membrane of 100 nm pore size) protocols. One can, for example, use a lipid bilayer that exhibits an DSPC / Cholesterol / DSPE-PEG2000 at molar ratio 3:2:0.15. For silicasome embodiments, a bare MSNP core can be constructed using a templating agent and silica precursors to make 80-90 nm particles. The particles can be produced in big batch sizes (e.g., -5 g / batch) and stably stored for 18-24 months, allowing aliquots to be removed at different project stages for carrier development. Phenelzine can be remotely imported using different trapping agents, such as triethylammmonium sucrose octasulfate, (NH4)2SO4 or citric acid. Lipid coatings can be introduced using ethanol injection method with controlled sonication power.

[0059] Based on the growing awareness that tumor targeting and / or the activation of tumor transcytosis mechanism may generate more robust access in multiple solid tumors, we can make nanoparticles having targeting agents by introducing peptide conjugation to the LB (e.g. iRGD and tumor targeting Arg-Gly-Asp peptide), using a thiol-maleimide reaction to link the cysteine-modified peptide to DSPE-PEG2000-maleimide. All the SSRI nanocarriers can be thoroughly characterized for physicochemical properties, such as size, morphology (cryoEM), loading capacity, release profile, zeta potential, impurities, and stability in biological fluids before use. The biological activity' of SSRIs can be read out using a pre-established in vitro

[0060]

[0061] mouse T cell activation assay, by measuring SSRI regulation of T cell proliferation and IFN-γ / Granzyme B production.

[0062] In certain embodiments of the invention, the SSRI is present in the composition in specific amounts such as a dose within the range of SSRI doses that are used to treat psychiatric conditions. However, in view of the fact that different people weigh different amounts and may respond differently to a specific amount of a SSRI, those of skill in this art understand that a more precise way to describe embodiments of the invention is to include a description of what the composition does (e.g. enhances tumor immunoreactivity; enhances secretion of serotonin; increases expression of IFN-y; increases expression of Granzyme B; decreases expression of PD-1 or the like), rather than by what the composition is (e.g. 5-50 mg of a SSRI). In view of the well studied pharmacology of SSRIs, the disclosure provided herein along with the known pharmacodynamics of SSRIs (see. e.g. Clinical Handbook of Psychotropic Drugs 25th Edition, by Ric M. Procyshyn (Editor) 2023, and Handbook of Clinical Psychopharmacology7by John D. Preston PsyD ABPP, John H. O'Neal MD, et al., 2021) makes the dosing associated with a desired effect to be routine in the art.

[0063] The compositions of the invention can include a variety of different immunotherapeutic / chemotherapeutic agents. Optionally for example, a composition of the invention includes at least one immune checkpoint inhibitor immunotherapeutic agent selected to affect CTLA-4 or a PD-1 / PD-L1 blockade. In certain embodiments, the checkpoint inhibitor comprises a CTLA-4 blocking antibody, an anti-PD-1 blocking antibody and / or an anti-PD-L1 blocking antibody. In other embodiments, the chemotherapeutic agent comprises carboplatin, cisplatin, paclitaxel, doxorubicin, docetaxel, cyclophosphamide, etoposide, fluorouracil, gemcitabine, methotrexate, erlotinib, imatinib mesylate, irinotecan, sorafenib, sunitinib, topotecan, vincristine, vinblastine or the like.

[0064] The compositions of the invention comprising SSRI may be made and then systemically administered in combination with a pharmaceutically acceptable vehicle

[0065]

[0066] such as an inert diluent. For oral therapeutic administration, the compounds may be combined with one or more excipients and used in the form of ingestible tablets, buccal tablets, troches, capsules, elixirs, suspensions, syrups, wafers, and the like. For compositions suitable for administration to humans, the term "excipient" is meant to include, but is not limited to, those ingredients described in Remington: The Science and Practice of Pharmacy, Lippincott Williams & Wilkins, 21st ed. (2006) (hereinafter Remington's). Common illustrative excipients include antimicrobial agents and buffering agents.

[0067] The compositions of the invention comprising SSRI may be administered parenterally, such as intravenously or intraperitoneally by infusion or injection. Solutions of the compositions of the invention comprising SSRI can be prepared in water, optionally mixed with a nontoxic surfactant. Dispersions can also be prepared in glycerol, liquid polyethylene glycols, triacetin, and mixtures thereof and in oils. Under ordinary conditions of storage and use, these preparations can contain a preservative to prevent the growth of microorganisms.

[0068] The pharmaceutical dosage forms suitable for injection or infusion can include sterile aqueous solutions or dispersions or sterile powders comprising compounds w hich are adapted for the extemporaneous preparation of sterile injectable or infusible solutions or dispersions, optionally encapsulated in liposomes. In all cases, the ultimate dosage form should be sterile, fluid and stable under the conditions of manufacture and storage. The liquid carrier or vehicle can be a solvent or liquid dispersion medium comprising, for example, water, ethanol, a polyol (for example, glycerol, propylene glycol, liquid polyethylene glycols, and the like), vegetable oils, nontoxic glyceryl esters, and suitable mixtures thereof.

[0069] Aspects of the present invention are disclosed in Li et al., “SEROTONIN TRANSPORTER INHIBITS ANTITUMOR IMMUNITY THROUGH REGULATING THE INTRATUMORAL SEROTONIN AXIS” CELL Volume 188, Issue 14, p3823-3842. e21 (1-18), online May 21, 2025, in pnnt July 10, 2025

[0070]

[0071] (hereinafter “Li et al.”), the contents of which are incorporated herein by reference. Further aspects and embodiments of the invention are discussed below.

[0072] SERT blockade suppresses tumor growth and enhances cytotoxic CD8 T cell antitumor responses in multiple syngeneic mouse tumor models

[0073] To investigate the possible involvement of SERT in CD8 T cell antitumor responses, we first isolated tumor-infiltrating CD8 T cells from a B16-0VA mouse melanoma model and examined Serf gene expression. RT-qPCR analysis detected an overall upregulation of Serf gene expression in tumor-infiltrating CD8 T cells compared to their naive counterparts, with PD-1hitumor-infiltrating CD8 T cells showing higher induction of Sert expression than PD-1loCD8 T cells (Figure 1A). This correlation suggests that SERT may regulate antitumor responses and exhaustion status of CD8 T cells. We then asked whether SERT blockade with established SSRIs might impact the antitumor immunity, particularly the CD8 T cell antitumor responses, via modulating the intratumoral serotonin axis (Figure 1B).

[0074] To represent SSRIs, we used fluoxetine (FLX) and citalopram (CIT), two of the most-prescribed drugs of their class32,33. [The SSRI doses used in our animal studies reflect therapeutical doses in human, producing comparable serum SSRI levels58 42Safety of the SSRI treatment in our animal studies was validated by a lack of exaggerated tissue inflammation (Figure SI A in Li et al.) or induction of autoantibodies (Figure SIB in Li et al.).

[0075] Six syngeneic mouse models across two mouse strains (C57BL / 6J, or B6, and BALB / c) were used in our study, spanning melanoma (B16-F10) and ovalbuminexpressing melanoma (B16-OVA), colon cancer (MC38 and CT26), bladder cancer (MB49), and breast cancer (4T1). In a set of tumor prevention experiments, administration of FLX or CIT resulted in greatly reduced tumor growth and prolonged animal survival in all six models regardless of tumor type or mouse genetic background (Figures 1C and ID).

[0076]

[0077] Encouraged by the impressive tumor prevention efficacy of SSRIs, we next evaluated therapeutic potential of SSRIs in tumor therapy experiments employing B16-OVA melanoma and MC38 colon cancer models (Figure IE). We found that treatment with either SSRI significantly reduced tumor growth and improved animal survival in both tumor models (Figure IF). Analysis of total tumor-infiltrating CD8 T cells in day 14 B16-OVA tumors revealed an enhancement of effector functions characterized by an increased production of IFN-y (Figure 1G) and Granzyme B (Figure 1H). Further analysis of tumor antigen-specific CD8 T cells (i.e., OVA-specific T cells) showed similar results (Figures SIC and SID in Li et al.).

[0078] Next, we explored the therapeutic potential of SSRIs for combination therapy, combining FLX and anti-PD-1 treatments (Figure 1I). In both B16-0VA melanoma and MC38 colon cancer models, FLX and anti-PD-1 monotherapies similarly impeded tumor growth (Figure 1J). Combination therapy in the B16-OVA model, which is relatively insensitive to traditional ICB therapies, yielded impressive synergistic efficacy (Figure 1J). Although anti-PD-1 monotherapy resulted in robust antitumor efficacy in the MC38 tumor model, which is sensitive to anti-PD-1, combination therapy further improved the antitumor effect of anti-PD-1 treatment (Figure 1J).

[0079] Collectively, these findings demonstrate the immunotherapeutic potential of SSRIs in a broad range of cancers and suggest that SERT regulates CD8 T cell antitumor immunity through a possible "intratumoral serotonin axis” (Figure IB).

[0080] SERT blockade enhances antitumor CD8 T cell effector and proliferating gene profiles

[0081] To investigate how SERT blockade alters tumor-infiltrating CD8 T cell compartment, we isolated tumor-infiltrating immune cells (TILs) from B6 mice bearing B16-OVA tumors treated with or without FLX and conducted a single-cell RNA sequencing (scRNA-seq) study (Figure 2A). Tils from B6 mice treated with anti-PD-1 were included to compare the impact of SSRIs to a traditional checkpoint

[0082]

[0083] inhibitor (Figure 2A). Uniform Manifold Approximation and Projection (UMAP) analysis of total combined Tils showed the formation of 9 cell clusters: B cells, CD8 T cells, DCs, γδ T cells, granulocytes, monocytes / TAM, NK cells, T helper (Th) cells, and regulatory T cells (Tregs); (Figures 2B and S2A in Li et al.). Cell cluster distributions were similar between non-treated and FLX-treated Tils; notably, compared to these two groups, anti-PDl -treated Tils comprised a much higher percentage of granulocytes (Figures S2B and S2C in Li et al.), in agreement with previous reports.

[0084] Further UMAP analysis of the antigen-experienced cytotoxic CD8 T cell (CD8+CD44+) cluster revealed three major subclusters (Figures 2C). These consisted of effector / proliferating (cluster 1), progenitor-exhausted (cluster 2), and terminally exhausted (cluster 3) CD8 T cells (Figures 2C), as identified by gene signature analysis (S2D, S2F, and S2G in Li et al.) and gene set enrichment analysis (GSEA; Figure S2E in Li et al.). Compared to the non-treatment control, the FLX-treated tumor-infiltrating CD8 T cells exhibited an enrichment in effector / proliferating (cluster 1) cells, accompanied by a reduction in exhausted (clusters 2 and 3) cells (Figures 2D and 2E).

[0085] Consistently, the gene signature analysis showed overall enhancement of the T cell effector / proliferating gene signature in CD8 T cells from FLX-treated mice (Figures 2F and 2G). FLX treatment also upregulated genes associated with mitochondrial function, which play a key role in CD8 T cell activation and persistence (i.e., mitochondrial electron transport chain genes; Figures S2F, S2H, and S2I in Li et al.). On the other hand, the anti-PD-1 treatment primarily decreased the proportion of the progenitor exhausted (cluster 2) cells (Figures 2D and 2E) and greatly reduced overall expression of progenitor exhausted CD8 T cell signature genes (Figures 2F and 2G). These interesting findings were further validated by RNA velocity analysis showing that SSRI and anti-PD-1 treatment resulted in a relative accumulation of tumor-infiltrating CD8 T cells at the effector / proliferating stage (Cluster 2) and the early exhausted stage (Cluster 3), respectively (Figure 2H).

[0086]

[0087] Venn diagram analysis revealed that there was very little overlap between the total upregulated genes in FLX-treated and anti-PD-1 -treated tumor-infiltrating CD8 T cells (21 / 432 and 21 / 110, respectively; Figure 21). Notably, the FLX treatment-induced gene set (432 genes) was significantly larger than that observed in anti-PD-1 group (110 genes; Figure 21). We then performed pathway analysis for those genes specifically upregulated by FLX treatment. FLX treatment-enriched pathways were related to cell proliferation, mitochondrial function, ATP metabolism, serotonin signaling, and glycolysis; these pathways had a substantially lower enrichment in anti-PD-1 -treated CD8 T cells (Figure 2J), suggesting SERT may regulate reactivities of tumor-infiltrating CD8 T cells via mechanisms that are distinct to those associated with PD-1.

[0088] Together, these in vivo gene profiling studies suggest SERT may play an important role in regulating the generation / persistence of antitumor effector CD8 T cells.

[0089] SERT works as an immune cell-intrinsic factor negatively regulating CD8 T cell-mediated antitumor responses

[0090] To study the role of SERT in regulating CD8 T cell antitumor responses, we utilized Sert knockout (Sert-KO) mice and included wild-type (WT) B6 mice as the Sert-WT control. Sert-KO mice carry a Sert mutant with targeted deletion of exon 2 that results in expression of nonfunctional SERT protein43. Before B16-OVA melanoma challenge, these mice contained normal numbers of CD4 and CD8 T cells in the periphery (Figure S3A in Li et al.), which displayed a typical naive phenotype (CD25loCD44loCD62Lhi) (Figures S3B and S3C in Li et al.). After tumor challenge, Sert-KO mice displayed significantly suppressed tumor growth (Figures 3A and 3B) and possessed increased numbers of tumor-infiltrating CD8 T cells (Figure 3C) exhibiting enhanced effector function (i.e. increased Granzyme B production, Figure 3D).

[0091]

[0092] Next, we performed a bone marrow transfer (BMT) experiment that confined SERT deficiency to immune cells by reconstituting B6 recipient mice with BM cells from either Sert-WT or Sert-KO donor mice, followed by B16-0VA tumor challenge (Figure 3E). Consistent with global Sert-KO mice, Sert-KO BMT mice showed dramatically delayed B16-0VA tumor growth (Figure 3F). Tumor-infiltrating CD8 T cells from Sert-KO BMT mice displayed enhanced effector function (i.e. higher IFN-y and Granzyme B production, Figure 3G and 3H) and decreased exhaustion markers (i.e. PD-1, Figure 31). Therefore, SERT can function as an immune cell-intrinsic regulator for antitumor response.

[0093] To further assess the role of CD8 T cells in SERT-mediated tumor control, we depleted CD8 T cells in Sert-WT mice challenged with B16-0VA melanoma and treated them with FLX (Figure 3J). CD8 T cell depletion abolished the FLX-induced tumor suppression effect (Figure 3K). We also grew B16-0VA tumors in immunodeficient NSG mice, which lack mature T cells, B cells and NK cells (Figure 3L). Treatment with SSRIs (FLX or CIT) did not suppress the in vivo growth of B16-OVA tumors in NSG mice (Figure 3M).

[0094] Collectively, these in vivo findings suggest SERT works as an immune cell-intrinsic factor negatively regulating antitumor immune responses, at least in part through direct regulation of antitumor CD8 T cell immunity.

[0095] SERT works as an autonomous factor negatively regulating CD8 T cell antigen responses

[0096] To assess if SERT acts as an autonomous factor directly regulating CD8 T cell antigen responses, we isolated CD8 T cells from SerLWT or 5<?rt-KO mice and stimulated these T cells with anti-CD3 (Figure 4A). < Se / 7-KO CD8 T cells showed an enhancement in cell proliferation (Figure 4B), effector cytokine expression (i.e. IL-2 and IFN-y, Figures 4C, 4D and 4F), and cytotoxic molecule expression (i.e. Granzyme B, Figures 4E and 4G). Similar results were obtained when we stimulated

[0097]

[0098] CD8 T cells with both anti-CD3 and anti-CD28 antibodies (Figures S4A-S4C in Li et al.).

[0099] To test if pharmacological inhibition of SERT in Se / 7-WT CD8 T cells can recapitulate the phenotype of -KO CD8 T cells, we isolated CD8 T cells from Sert-WT mice, followed by anti-CD3 stimulation in the presence or absence of SSRI (FLX or CIT; Figure 4H). SSRI treatments resulted in a significant enhancement in CD8 T cell proliferation (Figure 41) and expression of effector cytokines (i.e. IL-2, IFN-y, and TNF-a; Figures 4J and 4K) and cytotoxic molecules (i.e. Granzyme B and Perforin; Figures 4J and 4L). Study of SSRI-treated Sert-WT CD8 T cells stimulated with both anti-CD3 and anti-CD28 antibodies also yielded similar results (Figures S4D-S4G in Li et al.).

[0100] These in vitro studies validate SERT as an autonomous factor restraining CD8 T cell antigen responses in the presence or absence of antigen co-stimulation.

[0101] SERT restrains CDS T cell antigen responses by directly regulating autocrine serotonin signaling pathway

[0102] SERT regulates brain activity through modulating its local serotonin axis (Figure IB), where neurons synthesize and utilize serotonin for synaptic signal transmission44’45. Interestingly, T cells have these same molecular mechanisms for serotonin production, control, and reception, and stimulation of surface serotonin receptors (5-HTRs) has been linked to enhanced T activation and immune function15’27. We therefore propose a SERT-regulated intratumoral serotonin axis, wherein autocrine serotonin binds to surface 5-HTRs, acting as a cofactor enhancing antitumor immune pathways (Figure 5A).

[0103] To test this hypothesis, we first sought to characterize the serotonergic system in CDS T cells. We isolated naive CD8 T cells from B6 WT mice and stimulated them in vitro with anti-CD3 to mimic antigen reception. In a panel of all 13 mouse 5-HTR subtypes, only two subtypes (i.e. 5-Htr2b and 5-Htr7) expressed at high levels, both of which were further induced by antigen stimulation (Figure 5B). Interestingly,

[0104]

[0105] stimulation of naive 5-Htr7-KO CD8 T cells produced a markedly reduced effector phenotype (Figures S5A-S5G in Li et al.). In CD8 T cells from WT B6 mice, antigen stimulation significantly upregulated expression of Seri mRNA (Figures 5C and S6A in Li et al.), as well as mRNA for Tph1 and Maoa (Figure 5C), which encode for key proteins regulating serotonin synthesis and degradation, respectively. In line with the in vitro data, mRNA expression of these key serotonergic genes showed dramatic upregulation in PD-lhltumor-infiltrating CD8 T cells (tumor antigen-stimulated CD8 T cells. Figures 1A, and S6B-S6E in Li et al.). These findings indicate an antigen-induced induction of the entire serotonergic system in mouse CD8 T cells and suggest autocrine serotonin signaling as a positive regulator of antitumor immunity.

[0106] Because of their correlated induction, we sought to determine whether SERT KO influenced expression of other serotonergic molecules. Comparison of mRNA transcripts from CD8 T cells isolated from Sert-WT and Sert-KO (Figure 5D) showed comparable levels of Tphl, Maoci, and the Htr2b and Htr7 serotonin receptors (Figure 5E-5H) in both Sert genotypes. Together, these data indicate that the enhancement of SERT-deficient CD8 T cell activity is not achieved by regulating the expression of other key serotonergic genes.

[0107] To examine whether T cell-produced serotonin mediates SERT regulation of CD8 T cell antigen responses, we cultured Sert-WT CD8 T cells in vitro in presence of SSRI treatment (FLX or CIT) in serotonin-depleted medium (Figure 51). Pharmacological inhibition of SERT in Sert-WT CD8 T cells resulted in the hyperactivation phenotype of CD8 T cells, characterized by increased expression of the effector cytokines IL-2 (Figure 5J) and IFN-y (Figures 5K and 5L), an effect that was eliminated in cells cultured with an added 5-HTR general antagonist, asenapine (Figures 5J-5L). Notably, the culture medium of SSRI-treated CD8 T cells contained significantly higher levels of serotonin after antigen stimulation (Figure 5M). These findings indicate that SERT controls the availability of T cell-autologous serotonin, which is important for autocrine CD8 T cell activation.

[0108]

[0109] To address how T cell autocrine serotonin enhances CD8 T cell activation, we compared the effects of SERT inhibition on the mitogen-activated protein kinase (MAPK) and T cell receptor (TCR) signaling pathways, which are the major pathways induced by serotonin signals in CD8 T cells27. We observed that SSRIs enhanced both MAPK signaling, measured by extracellular signal-regulated kinase (ERK) phosphorylation (Figure 5N), and TCR downstream signaling, measured by nuclear translocation of nuclear factor of activated T cells (NF AT), nuclear factor KB (NF-KB), and c-Jun transcription factors (Figure 5O). This enhancement was largely abrogated by blocking 5-HTRs with asenapine (Figures 5N and 5O). Collectively, these data suggest that SERT negatively regulates CD8 T cell antigen responses by modulating T cell autocrine serotonin-5-HTR-MAPK-NF-κB signaling.

[0110] To validate the autocrine CD8 T cell serotonin axis in vivo, we first measured intratumoral and peripheral serotonin levels in Sert-KO and Sert-WT BMT mice bearing B16-0VA tumors by using high-performance liquid chromatography (HPLC; Figure 5P). Sert-KO BMT mice exhibited significantly increased levels of intratumoral serotonin (Figure 5Q). In contrast, serum serotonin levels were greatly decreased in SSert-KO BMT mice (Figure 5R). Similarly. FLX-treated Sert-WT mice also showed increased levels of intratumoral serotonin (Figures 5S and 5T). Depletion of CD8 T cells in &7-WT mice eliminated FLX-induced accumulation of serotonin in tumors (Figures 5S and 5T), while FLX treatment in the presence and absence of anti-CD8 blockade similarly depleted serotonin levels in peripheral blood (Figures 5S and 5U). These data support tumor-infiltrating CD8 T cells as a major contributor to the intratumoral serotonin axis and suggest that SERT plays a key role in negatively regulating the availability of local serotonin in tumors, analogous to SERT regulation of serotonin in the brain.

[0111] Together, these in vitro and in vivo data support SERT as a negative-feedback regulator restraining CD8 T cell reactivities, at least partly through directly regulating intratumoral CD8 T cell autocrine serotonin signaling.

[0112]

[0113] SERT blockade for cancer immunotherapy: human T cell and clinical data correlation studies

[0114] To explore the translational potential of SERT blockade therapy, we studied SERT regulation of human CD8 T cell antigen responses. Human naive CD8 T cells isolated from peripheral blood mononuclear cells (PBMCs) of random and healthy donors were stimulated in vitro, in the presence or absence of SSRI (Figure 6A). Compared to naive CD8 T cells, antigen-stimulated CD8 T cells showed a significant increase in gene expression of SERT, TPH1, and MAOA (Figure 6B), which is in line with the findings in mouse counterparts. In a panel of 13 human HTR subtypes known to be functional in human cells, only the HTR4 gene w as predominantly expressed in CD8 T cells of all four donors (Figure S7A in Li et al.) and induced by antigen stimulation (Figure 6B). Of note, SSRI-treated CD8 T cells showed enhanced cell proliferation (Figure 6C) and effector phenotypes, characterized by upregulated expression of effector cytokines (e g. IL-2, IFN-y, and TNF-a; Figures 6D and S7B-S7D in Li et al.) and cytotoxic molecules (e.g. Granzyme B and Perforin; Figures 6D and S7E-S7F in Li et al.).

[0115] To further characterize the serotonergic system in human tumor-infiltrating CD8 T cells, we conducted scRNA-seq analysis by combining eight datasets of seven cancer types from the uTILity Human TIL scRNA-seq Database (Figure 6E). UMAP analysis of human CD8 TILs identified six CD8 T cell clusters (Naive-like T; TCM, central memory T; TEM, effector memory T; TEMRA, terminally differentiated effector memory T; TPEX, progenitor exhausted T; TEX, exhausted T; Figure 6F). Gene expression analysis revealed SERT gene was specifically induced in the CD8 TEMRA cells (Figure 6G), a robust effector human CD8 T cell population, which is in line with the human in vitro data. In contrast, the classic immune checkpoint genes for FDA-approved ICB therapy were only induced in the exhausted clusters (Figure 6G). The gene signature analysis showed that CD8 TEMRA cells had the enhanced expression of the serotonergic signature genes, compared to other cell clusters (Figures 6H and 61). The upregulation of the selected serotonergic genes was further

[0116]

[0117] validated in human PBMC-derived CD8 T cells treated with SSRI in vitro (Figure 6J). Thus, these findings suggest activation of the serotonergic system may be important for human CD8 T cell antitumor responses and SERT functions as a negativefeedback regulator of human tumor-infiltrating effector CD8 T cells.

[0118] To study human CD8 T cell antitumor responses in vivo using a xenograft NSG mouse model47, we engineered an A375 human melanoma cell line to co-express tumor antigen NY-ESO-147, its matching human leukocyte antigen serotype A2 (HLA-A2), as well as a firefly luciferase and an enhanced green fluorescence protein (denoted as A375-A2-ESO-FG). In addition, CD8 T cells from PBMCs of a healthy donor were engineered to express a NY-ESO-1 -specific TCR (denoted as ESO-TCR, Figure S7G in Li et al.). Thus, these CD8 T cells (denoted as ESO-T cells) specifically targeted A375-A2-ESO-FG melanoma cells (Figure 6K).

[0119] Next, we examined whether SERT blockade could enhance human CD8 T cell antitumor immunity in the xenograft model. We challenged NSG mice with A375-A2-ESO-FG tumor cells; ESO-T cells were adoptively transferred on day 7, followed by daily treatment of SSRI (e.g. FLX) (Figure 6L). FLX treatment effectively suppressed tumor progression (Figure 6M). FACS analyses detected higher numbers of human CD8 T cells in the tumor (Figure 6N) and these T cells produced significantly higher levels of IFN-y (Figure 6O), Granzyme B (Figure 6P), and Perforin (Figure S7H in Li et al.). Furthermore, tumor suppression was not observed in NSG mice that received FLX treatment without adoptive T cell transfer (Figures S71 and S7J in Li et al.). These results demonstrate that FLX treatment induces antitumor effects in a human tumor model by directly enhancing human CD8 T cell antitumor immunity7, supporting the translational potential of SERT blockade for cancer immunotherapy.

[0120] To investigate whether SERT gene expression in tumors has clinical implications in patients with cancer, we conducted the correlation of SERT gene expression in whole-tumor lysate transcriptome data with clinical outcomes of patients by using the Tumor Immune Dysfunction and Exclusion (TIDE) computational method48. We

[0121]

[0122] observed that intratumoral SERT expression levels were negatively correlated with patient survival in a broad range of solid cancers, spanning melanoma, breast cancer, lung cancer, kidney cancer, and sarcoma (Figure 6Q). TIDE also models the association of CD8 T cell dysfunction in tumors with gene expression by analyzing the interactions of three variants: (1) the intratumoral expression of a selected gene; (2) the intratumoral levels of CD8 T cells; and (3) patient survival. We found that high SERT expression negated the benefit of increased tumor-infiltrating CD8 T cells on patient survival in multiple cancer patient cohorts, including breast cancer (Figure S7K in Li et al.), brain cancer (Figure S7L in Li et al.), kidney cancer (Figure S7M in Li et al.), head and neck cancer (Figure S7N in Li et al.), leukemia (Figure S7O in Li et al.), and ovarian cancer (Figure S7P in Li et al.).

[0123] Together, the human T cell and clinical data correlation studies support our model of SERT-mediated negative regulation of human antitumor CD8 T reactivities and position a well-established class of antidepressants, SSRIs, as a promising candidate for next-generation cancer immunotherapy.

[0124] EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS

[0125] Mice

[0126] C57BL / 6J (B6), BALB / cJ (BALB / c), BGAl^CgySlcSa^W / J (&rt-KO), B

[0127]

[0128] 6A29-Htr7tmISut / i (5-Htr7-KO), and NOD. Cg- / 77u / c',: / Il2rgtmIWJll^>zA (Nod scid gamma or NSG) mice were purchased from the Jackson Laboratory’ (JAX; Bar Harbor). Ser / -KO and 5Htr7-KO mice were backcrossed with C57BL / 6J mice for more than six generations at the University of California, Los Angeles (UCLA). All animals were maintained in the animal facilities at UCLA. Eight- to 12-week-old females were used for all experiments unless otherwise indicated. All animal experiments were approved by the Institutional Animal Care and Use Committee of UCLA.

[0129] Tumor cell lines

[0130]

[0131] The B16-OVA mouse melanoma cell line and the PG13 retroviral packaging cell line were kindly provided by Dr. Pin Wang (University7of Southern California, CA, USA). The MC38 mouse colon adenocarcinoma cell line was provided by Dr. Marcus Bosenberg (Yale University. CT, USA). The MB49 mouse bladder cancer cell line was provided by Dr. Arnold Qin (University of California, Los Angeles, CA, USA). The human embryonic kidney 293T, B16-F10 mouse melanoma, CT26 mouse colon cancer, and 4T1 mouse breast cancer cell lines were purchased from the American Type Culture Collection (ATCC). The A375-A2-ESO-FG human melanoma cell line were generated by our group and previously reported47. These cell lines were cultured in Dulbecco’s modified Eagle’s medium (DMEM; catalog no.

[0132] 10013, Coming) supplemented with 10% fetal bovine serum (FBS; catalog no. F2442, Sigma-Aldrich) and 1% penicillin-streptomycin-glutamine (catalog no. 10378016, Gibco).

[0133] METHOD DETAILS

[0134] Syngeneic mouse tumor models

[0135] B16-OVA melanoma cells (1 x io6per animal). B16-F10 melanoma cells (1 x 106per animal), MC38 colon cancer cells (5 x 105per animal), MB49 bladder cancer cells (2 x 105per animal), CT26 colon cancer cells (5 x 106per animal) or 4T1 breast cancer cells (1 x 106per animal) were subcutaneously injected into experimental mice to form solid tumors. For SSRI treatment experiments, mice received intraperitoneal injection of SSRls [i.e., fluoxetine (10mg / kg / day, catalog no. abl20077, Abeam), or citalopram (30mg / kg / day, catalog no. abl20133. Abeam)] to block SERT activity. For T cell depletion experiments, mice received intraperitoneal injection of anti-mouse CD8 antibody (200 mg per animal, twice per week, catalog no. BE0061, clone 2.43, BioXCell) to deplete CD8 T cells; mice that received intraperitoneal injection of rat immunoglobulin G2b (IgG2b) isotype antibody (200 mg per animal, twice per week, catalog no. BE0090, BioXCell) were included as controls. For PD-1 blockade experiments, mice received intraperitoneal injection of anti-mouse PD-1 antibody

[0136]

[0137] (300 mg per animal, twice per week, catalog no. BE0146, clone RMP1-14, BioXCell) to block PD-1 receptor; mice that received intraperitoneal injection of rat IgG2a isotype antibody (300 mg per animal, twice per week, catalog no. BE0089, BioXCell) were included as controls. Throughout the course of experiments, tumor size was measured twice per week by using a Fisherbrand Traceable digital caliper (Thermo Fisher Scientific). Tumor volumes were calculated by formula 1 / 2 * L x W2. At the end of experiments, tumor, spleen, lymph nodes, and blood were collected for analysis of different assays.

[0138] Bone marrow (BM) transfer mouse tumor model

[0139] BM cells were collected from femurs and tibias of Sert-WT or &rt-KO donor mice and were transferred into B6 recipient mice through intravenous (i.v.) injection (10 × 106cells per recipient mouse). Recipient mice were preconditioned with wholebody irradiation (1100 Gy). After BM transfer, recipient mice were maintained on antibiotic water (Amoxil; 0.25 mg / ml) for 4 weeks. Periodic bleedings were performed to monitor immune cell reconstitution using flow cytometry. At 8 to 12 weeks after BM transfer, recipient mice were fully immune-reconstituted and were used for B16-OVA mouse melanoma challenge experiments. Tumor growth was monitored twice per week by measuring tumor size using a digital caliper; tumor volumes were calculated by formula 1 / 2 * L * W2.

[0140] Xenograft human tumor model

[0141] The A375-A2-ESO-FG human melanoma cells (10 x 106cells per animal) were subcutaneously injected into NSG mice to form solid tumors. Mice received fluoxetine treatment through intraperitoneal injection (10 mg / kg / day). In some experiments, mice received ESO-T cells through local subcutaneous injection (5 × 106cells per recipient mouse). During experiments, tumor growth was monitored twice per week by measuring tumor size using a Fisherbrand Traceable digital caliper;

[0142]

[0143] tumor volumes were calculated by formula 1 / 2 x L x W2. At the end of experiments, tumor and blood were collected for analysis of different assays.

[0144] Tumor-infiltrating immune cell (TII) ex vivo analysis

[0145] Solid tumors were harvested from experimental mice and mechanically meshed in 70-mm cell strainers (catalog no. 07-201-431, Coming) to get single cell suspensions. Single cells were washed once with T cell culture medium, resuspended in 50% Percoll (catalog no. P4937, Sigma-Aldrich), and centrifuged at 800g at 25°C for 30 min with brake off. Cell pellets enriched with Tils were then collected for further analysis.

[0146] In the experiments studying gene expression in tumor-infiltrating CD8 T cell subsets, day 14 B16-OVA tumors were harvested from B6 wild-type mice to prepare Til suspensions. Tumor-infiltrating CD8 T cells (pregated as DAPI−CD45.2+TCRb+CD8+cells) were sorted into two subsets (gated as PD-1loand PD-1hiTim-3hiLAG-3hicells) using a FACSAria II flow cytometer and then were subjected to qPCR analysis.

[0147] In the experiments studying gene expression profiling of TIIs, day 10 B16-OVA tumors were harvested from SSRI-treated and anti-PD-1 -treated mice to prepare TII suspensions. TII suspensions were then sorted using a FACSAria II flow cytometer to purify immune cells (gated as DAPI−CD45.2+cells) that were subjected to scRNA-seq analysis.

[0148] In the experiments studying status and functions of tumor-infiltrating CD8 T cells, TII suspensions were prepared and then analyzed by flow cytometry to study the expression of surface activation / exhaustion markers and intracellular effector molecules.

[0149] Histological analysis

[0150] For histological sectioning, organs (e.g. heart, lung, kidney, spleen, and liver) were harvested from the experimental mice, placed into 10% neutral-buffered

[0151]

[0152] formalin (catalog no. 5705, Richard-Allan Scientific) immediately, fixed for 18 h, and then transferred to 70% ethanol before standard paraffin embedding for sectioning (5-μm thickness), followed by hematoxylin and eosin (H& E) staining using standard procedures (UCLA Translational Pathology Core Laboratory). The sections were photographed using an upright microscope (BX-51; Olympus) and using a color charge-coupled device digital camera (Insight 4 MP; SPOT) and software (SPOT).

[0153] In vitro mouse CD8 T cell culture

[0154] Spleen and lymph node cells were harvested from WT and KO mice. Naive CD8 T cells were sorted using the Mouse Naive CD8 T Cell Isolation Kit (catalog no.

[0155] 130-096-543, Miltenyi Biotec) according to the manufacturer’s instructions or using a FACSAria II flow cytometer (gated as DAPI TCR0+CD8 CD44loCD62Lhicells). Purified mouse CD8 T cells were cultured in vitro in T cell culture medium that was made of RPMI 1640 (catalog no. 10040, Coming) supplemented with 10% FBS (catalog no. F2442, Sigma- Aldrich), 1% penicillin-streptomycin-glutamine (catalog no. 10378016, Gibco), 0.2% Normocin (catalog no. ant-nr-2, InvivoGen), 1% Minimal Essential Medium (MEM) Non-essential Amino Acid Solution (catalog no.

[0156] 11140050, Gibco), 1% HEPES (catalog no. 15630080, Gibco), 1% sodium pyruvate (catalog no. 11360070, Gibco), and 0.05 mM β-mercaptoethanol (catalog no. M3148, Sigma- Aldrich), in a 24-well plate at 0.5 × 106cells per well, in the presence of plate-bound mouse anti-CD3 (5 pg / ml; catalog no. 553057, clone 145-2C11. BD Biosciences) with / without mouse anti-CD28 (1 pg / ml; catalog no. 553294, clone 37.51, BD Biosciences) as T cell stimulators for up to 4 days. At indicated time points, cells were collected for qPCR analysis of gene expression; cell culture supernatants were collected for ELISA analysis of effector cytokines. For the analysis of surface markers and cytotoxic molecule production. CD8 T cells were collected and then directly subjected to flow cytometry. For the analysis of T cell cytokine production, CD8 T cells were restimulated with phorbol-12-myristate-13-acetate (PMA) (50 ng / ml; catalog no. 524400, Sigma-Aldrich) and ionomycin (500 ng / ml; catalog no.

[0157]

[0158] I0634, Sigma-Aldrich) in the presence of GolgiStop (4 μl per 6 ml culture; catalog no.

[0159] 554724, BD Biosciences) for 4 hours at 37°C, followed by flow cytometry.

[0160] In the experiments studying the effects of SSRIs, purified Sert-WT CD8 T cells were also treated with either fluoxetine (2 mM) or citalopram (20 mM). In the experiments studying autocrine serotonin signaling, cells were cultured in T cell culture medium made of the FBS that was pretreated overnight with charcoal-dextran (1 g per 50 ml of FBS; catalog no. C6241, Sigma-Aldrich) to deplete serotonin. l-Ascorbic acid (100 mM; catalog no. A4403, Sigma-Aldrich) was also added to the medium to stabilize T cell-produced serotonin. In some experiments, purified CD8 T cells were also treated with serotonin receptor antagonist asenapine (10 mM; catalog no. A7861, Sigma-Aldrich) to block serotonin receptor signaling.

[0161] In vitro human CD8 T cell culture

[0162] Peripheral blood mononuclear cells (PBMCs) of healthy donors were purchased from the UCLA Center for AIDS Research (CFAR) Virology Core Laboratory. Naive CD8 T cells were sorted using the Human Naive CD8 T Cell Isolation Kit (catalog no. 130-093-244, Miltenyi Biotec) according to the manufacturer’s instructions. Naive CD8 T cells were cultured in vitro in a 24-well plate at 0.5 × 106cells per well in T cell culture medium in the presence of platebound human anti-CD3 (5 mg / ml; catalog no. 300314, clone HIT3a, BioLegend), soluble human anti-CD28 (1 mg / ml; catalog no. 302902, clone CD28.2, BioLegend) and soluble human IL-2 (10 ng / ml; catalog no. 200-02, PeproTech) for up to 5 days. In the experiments studying the effects of SSRIs, human naive CD8 T cells were treated with either fluoxetine (2 mM) or citalopram (20 mM). At indicated time points, cells were collected for gene and protein analysis. For T cell cytotoxicity molecule analysis, effector CD8 T cells were directly subjected to flow cytometry. For the analysis of T cell cytokine production, CD8 T cells were restimulated with PMA (50 ng / ml;) and ionomycin (500 ng / ml;) in the presence of GolgiStop (4 pl per 6 ml culture) for 4 hours at 37°C, followed by flow cytometry.

[0163]

[0164] Retro / ESO-TCR retroviral vector and human CD8 T cell transduction

[0165] The Retro / ESO-TCR vector was constructed by inserting into the parental pMSGV vector a synthetic gene encoding an HLA-A2-restricted. NY-ESO-1 tumor antigen-specific human CD8 TCR (clone 3A1). VSVG-pseudotyped Retro / ESO-TCR retroviruses were generated by transfecting 293T cells following a standard calcium precipitation protocol and an ultracentrifugation concentration protocol; the viruses were then used to transduce PG13 cells to generate a stable retroviral packaging cell line producing gibbon ape leukemia virus (GaLV) glycoprotein-pseudotyped Retro / ESO-TCR retroviruses (denoted as PG13-ESO-TCR cell line). For virus production, the PG13-ESO-TCR cells were seeded at a density of 0.8 × 106cells / ml in D10 medium and cultured in a 15-cm dish (30 ml per dish) for 2 days; virus supernatants were then harvested and stored at -80°C for future use.

[0166] Healthy donor PBMCs were stimulated with plate-bound anti-human CD3 (1 pg / ml) and soluble anti-human CD28 (1 pg / ml) in the presence of recombinant human IL-2 (10 ng / ml). On day 2, cells were spin-infected with frozen-thawed Retro / ESO-TCR retroviral supernatants supplemented with polybrene (10 pg / ml; catalog no. TR-1003-G, Millipore) at 660g at 30°C for 90 min after an established protocol. Transduced human CD8 T cells (denoted as ESO-T cells) were expanded for another 7 to 10 days and then cryopreserved for future use.

[0167] Flow cytometry

[0168] Flow cytometry was used to analyze the expression of surface and intracellular markers of T cells as well as to sort different subsets of T cells. Fluorochrome-conjugated monoclonal antibodies specific for mouse CD45.2 (clone 104), TCRP (clone H57-597), CD4 (clone RM4-5). CD8 (clone 53-6.7), CD69 (clone H1.2F3), CD25 (clone PC61), CD44 (clone IM7), CD62L (clone MEL-14), LAG-3 (clone C9B7W), Tim-3 (clone RMT3-23), Granzyme B (clone QA16A02), and IFN-y (clone XMG1.2) were purchased from BioLegend. Fc block (anti-mouse CD16 / 32) (clone

[0169]

[0170] 2.4G2) was purchased from BD Biosciences. Monoclonal antibodies specific for mouse PD-1 (clone RMP1-30) was purchased from Thermo Fisher Scientific. Fluorochrome-conjugated monoclonal antibodies specific for human CD45 (clone HI30), TCRa / p (clone IP26), CD4 (clone OKT4). CD8 (clone SKI), TCR Vβ13.1 (clone H131), CD62L (clone DREG-56), CD69 (clone FN50), CD25 (clone M-A251), PD-1 (clone EH12.2H7), IL-2 (clone MQ1-17H12), TNF-α (clone MAb11), Perform (clone dG9), Granzyme B (clone QA16A02), and IFN-y (clone B27) were purchased from BioLegend. Human Fc Receptor Blocking Solution (catalog no. 422302) was purchased from BioLegend. Fixable Viability Dye eFluor 506 (catalog no. 65-0866) was purchased from Thermo Fisher Scientific. OVA dextramer (catalog no. JD2163) was purchased from Immudex. Cells were stained with Fixable Viability Dye first, followed by Fc blocking and surface marker staining, using a previously described procedure. To detect intracellular molecules, cells were subjected to intracellular staining using a Cell Fixation / Permeabilization Kit (catalog no. 554714, BD Biosciences) following the manufacturer’s instructions. Stained cells were analyzed using a MACSQuant Analyzer 10 Flow Cytometer (Miltenyi Biotec). FlowJo 10 software (Tree Star) was used to analyze the data.

[0171] mRNA Quantitative RT-PCR

[0172] Total RNA was isolated using TRIzol Reagent (catalog no. 15596018, Thermo Fisher Scientific) and the miRNeasy Mini Kit (catalog no. 217004, QIAGEN) according to the manufacturers’ instructions. cDNA was prepared using the SuperScript III First-Strand Synthesis Supermix Kit (catalog no. 18080400, Thermo Fisher Scientific). Gene expression was measured using the SsoAdvanced Universal SYBR Green Supermix (catalog no. 1725271, Bio-Rad) and the 7500 Real-time PCR System (Applied Biosystems) according to the manufacturers' instructions. Ube2d2 was used as an internal control for mouse T cells, and ACTIN was used as an internal control for human T cells. The relative expression of the mRNA of interest was

[0173]

[0174] calculated using the 2−ΔΔCTmethod and is presented as the fold induction relative to the control. Primer sequences are shown in Table SI in Li et al.

[0175] ELISA ELISA for detecting mouse cytokines were performed following a standard protocol from the BD Biosciences. Capture and biotinylated antibody pairs for the detection of mouse IFN-y (coating antibody, catalog no. 554424; biotinylated detection antibody, catalog no. 554426) and IL-2 (coating antibody, catalog no.

[0176] 551216; biotinylated detection antibody, catalog no. 554410) were also purchased from BD Biosciences. The streptavidin-horseradish peroxidase (HRP) conjugate (catalog no. 18410051) was purchased from Invitrogen. Mouse IFN-y (catalog no.

[0177] 575309) and IL-2 (catalog no. 575409) standards were purchased from BioLegend. The 3,3’,5,5-tetramethylbenzidine (TMB; catalog no. 51200048) substrate was purchased from KPL. Samples were analyzed for absorbance at 450 nm using an Infinite M1000 microplate reader (Tecan).

[0178] ELISA for the analysis of T-cell produced serotonin was performed using a serotonin ultrasensitive ELISA kit (SEU39-K01, Eagle Biosciences) following the manufacturer’s instructions. The absorbance at 450 nm was measured using an Infinite M1000 microplate reader (Tecan). Titers of autoantibodies against doublestranded DNA were measured using a commercial mouse anti-dsDNA ELISA kit (637-02691, BioVendor) according to manufacturer’s instructions. The absorbance of samples at 450 nm was measured using an Infinite M1000 microplate reader (Tecan).

[0179] Western blots

[0180] CD8 T cells purified from Sert-WT mice were cultured in vitro in a 24-well plate at 0.5 x io6cells per well for 2 days, in the presence of plate-bound anti-mouse CD3 (5 mg / ml), with or without asenapine treatment (10 mM). Cells were then rested on ice for 2 hours and restimulated with plate-bound anti-mouse CD3 (5 mg / ml) for 20 min. Total protein was extracted using a RIPA lysis and extraction buffer (catalog

[0181]

[0182] no. 89900, Thermo Fisher Scientific) supplemented with protease / phosphatase inhibitor cocktail (catalog no. 5872S, Cell Signaling Technology). Nuclear protein was extracted using the Nuclear Protein Extraction Kit (catalog no. P178833, Thermo Fisher Scientific). Protein concentration was measured using the Bicinchoninic Acid (BCA) Assay Kit (catalog nos. 23228 and 1859078, Thermo Fisher Scientific). Equal amounts of protein were resolved on a 10% SDS-poly acrylamide gel electrophoresis gel and then transferred to a polyvinylidene difluoride (PVDF) membrane by electrophoresis. The following antibodies were purchased from the Cell Signaling Technology and used to blot for the proteins of interest: anti-mouse NF-KB p65 (catalog no. 8242S, clone D14E12), anti-mouse c-Jun (catalog no. 9165S, clone 60A8), anti-mouse NFAT (catalog no. 4389S), anti-mouse ERK1 / 2 (catalog no.

[0183] 9107S, clone 3A7), anti-mouse p-ERK1 / 2 (catalog no. 4370S, clone D13.14.4E), secondary anti-mouse (catalog no. 7076P2), and secondary anti-rabbit (catalog no.

[0184] 7074P2). GAPDH (catalog no. 2118S, clone 14C10, Cell Signaling Technology) was used as an internal control for cytoplasmic proteins, whereas Lamin A / C (catalog no.

[0185] 39287, clone 3A6-4C11, Active Motif) was used as an internal control for nuclear proteins. Signals were visualized with autoradiography using an enhanced chemiluminescence (ECL) prime western blotting system (catalog no. RPN2232, Cytiva). Data analysis was performed using ImageJ software (NIH).

[0186] High-performance liquid chromatography (HPLC)

[0187] HPLC was used to measure intratumoral and serum serotonin levels as previously described. Briefly, tumor and serum samples were collected from experimental mice at indicated time points and were snap-frozen using liquid nitrogen. Frozen samples were thawed and homogenized using methanol (catalog no.

[0188] 268280025, Thermo Fisher Scientific) and acetonitrile (catalog no. A998SK-1, Thermo Fisher Scientific) by vortexing. Homogenized samples were centrifuged, and supernatants were collected to new tubes and evaporated under a stream of argon. Dried sample pellets were then reconstituted in HPLC running buffer and were ready

[0189]

[0190] for analysis. Serotonin concentration was quantified using a C18 column by reversephase HPLC (System Gold 166P detector, Beckman Coulter). For tumor samples, both intracellular and interstitial serotonin were analyzed.

[0191] Single-cell RNA sequencing (scRNA-seq)

[0192] scRNA-seq was used to analyze the gene expression profiling of Tils. Day 10 B16-OVA tumors were harvested from experimental mice to prepare TII suspensions (10 tumors were combined for each group). TII suspensions were then sorted using a FACS Aria II flow cytometer to purify immune cells (gated as DAPI CD45.2+cells). Sorted Tils were immediately delivered to the Technology Center for Genomics & Bioinformatics (TCGB) facility at UCLA for library construction and sequencing. Briefly, purified Tils were quantified using a Cell Countess II automated cell counter (Invitrogen / Thermo Fisher Scientific). A total of 10,000 Tils from each experimental group were loaded on the Chromium platform (lOx Genomics), and libraries were constructed using the Chromium Single Cell 3' Library & Gel Bead Kit v2 (catalog no. PN-120237, lOx Genomics) according to the manufacturer's instructions. Libraries were sequenced on an Illumina NovaSeq using the NovaSeq 6000 S2 Reagent Kit (100 cycles; catalog no. 20012862, Illumina).

[0193] QUANTIFICATION AND STATISTICAL ANALYSIS

[0194] Sequencing data analysis

[0195] Data analysis was performed using a Cell Ranger Software Suite (lOx Genomics). Binary base call (BCL) files were extracted from the sequencer and used as inputs for the Cell Ranger pipeline to generate the digital expression matrix for each sample. Then, cell-ranger aggr command was used to aggregate the two samples into one digital expression matrix. The matrix was analyzed using Seurat (v.4.3.0), an R package designed for scRNA-seq. Specifically, cells were first filtered to have at least 300 unique molecular identifiers (UMIs), at least 100 genes, and at most 25% mitochondrial gene expression; only one cell did not pass the filter. The filtered

[0196]

[0197] matrix was normalized using the Seurat function NormalizeData through natural-log transformation. Variable genes were found using the Seurat function FindVariableGenes and ScaleData function was used to regress out the sequencing depth for each cell. Variable genes that had been previously identified were used in principal components analysis (PCA) to reduce the dimensions of the data. After this, 13 principal components (PCs) were used in Uniform Manifold Approximation and Projection (UMAP) to further reduce the dimensions to two. The same 13 PCs were also used to group the cells into different clusters by the Seurat function FindClusters. Next, marker genes were found for each cluster using the FindAllMarkers function and used to define the cell types. Cell types were manually annotated based on the cluster markers. To perform comparative scRNA-seq analysis of across experimental conditions between non-treatment, fluoxetine and anti-PD-1 groups, the Seurat object consisting of antigen-experienced tumor-infiltrating CD8 T cells (identified by coexpression of Cd8a, Cd3d, and Cd44 marker genes) were extracted using Subset function, and Seurat integration pipeline was performed following the Seurat guidelines. After integration, three clusters of cells were identified based on the signature genes (GSE122713) by calculating the module scores calculated using the AddModuleScore function for each gene list. For GSEA, escape and clusterProfiler packages were used to calculate the enrichment scores of each cluster in the signature gene list (GSE122713). For pathway analysis, the fold enrichment value was calculated as following: Fold_enrichment = (N intersect / N DEG) / (N pathway / N background), where N intersect indicates the number of genes from differentially expressed gene set that are present in the pathway gene set; N DEG indicates number of genes from differentially expressed gene set; N pathway indicates the number of genes from the pathway gene set; and N background indicates the total number of genes in this analysis.

[0198] The scRNA-seq data on tumor-infiltrating lymphocytes (TIL) from N. Borcherding's uTILity served as the human CD8 TIL atlas. The subsequent analysis of this downloaded data, consisting of 11,021 high-quality single-cell transcriptomes

[0199]

[0200] from 20 samples across seven different tumor types, was carried out using the Seurat package in R. Additionally, dot plots were created in R utilizing the scCustomize package.

[0201] Tumor Immune Dysfunction and Exclusion (TIDE) analysis

[0202] Human clinical correlation studies were conducted by using TIDE computational method as previously described (http: / / tide.dfci.harvard.edu / query / ). Two functions of the TIDE computational method were used: (1) the survival correlation with gene expression, and (2) the impact of gene expression on T cell dysfunction.

[0203] The survival correlation function of TIDE was used to study the clinical data correlation between the intratumoral SERT gene expression and patient survival. For each patient cohort, tumor samples were divided into two groups: SERT-high (samples with SERT expression one standard deviation above the average) and SERT-low (remaining samples) groups. The association between the intratumoral SERT gene expression levels and patient overall survival (OS) was computed through the two-sided Wald test in the Cox-PH regression and presented in Kaplan-Meier plots, p value indicates the comparison between the SERT -low and SERT-high groups and was calculated by two-sided Wald test in a Cox-PH regression.

[0204] The second function was used to study the association between the tumorinfiltrating CD8 T cell [also known as cytotoxic T lymphocyte (CTL)] level and overall patient survival in relation to the intratumoral SERT gene expression level. For each patient cohort, tumor samples were also divided into SERT-high and SERT-low groups, followed by analyzing the association between the CTL levels and survival outcomes in each group. The CTL level was estimated as the average expression level of CD8A, CD8B, GZMA, GZMB, and PRF1 Each survival plot presented tumors in two subgroups: “CTL-high” group had above-average CTL values among all samples, whereas ‘ CTL-low” group had below-average CTL values. A T cell dysfunction score (z score) was calculated for each patient cohort, correlating the SERT expression level

[0205]

[0206] with the beneficial effect of CTL infiltration on patient survival. A positive z score indicates that the expression of SERT is negatively correlated with the beneficial effect of tumor-infiltrating CTL on patient survival. The P value indicates the comparison between the SERT-low and SERT-high groups and was calculated by two-sided Wald test in a Cox proportional hazards (Cox-PH) regression.

[0207] Statistics

[0208] A GraphPad Prism 9 software (GraphPad Software) was used for all statistical analysis. Pairwise comparisons were made using a two-tailed Student’s t test. Multiple comparisons were performed using an ordinary one-way analysis of variance (ANOVA) followed by Tukey’s multiple comparisons test or a two-way repeated measures ANOVA followed by Sidak multiple comparisons test. Data are presented as the means ± SEM, unless otherwise indicated. A P value of less than 0.05 was considered significant, ns, not significant; *P < 0.05, **P < 0.01, and ***P < 0.001. The P values of violin plots were determined by Wilcoxon rank sum test. For the Kaplan-Meier plot of the overall patient survival with different SERT levels, the p value was calculated by two-sided Wald test in a Cox-PH regression.

[0209] DISCUSSION

[0210] The nervous and immune systems possess significant overlap in their underlying molecular machinery, and many molecules traditionally thought of as “neuronal” or “immune” play important roles in communication in and between both systems49–55. The interdisciplinary field of neuroimmunology investigates the bidirectional crosstalk between these two systems, a function that is of growing interest in tumor immunology56,57. Beyond neuro-immune crosstalk, however, traditional “neurotransmitters” have been shown to play a neuron-independent role in intratumoral signaling14,54’58. Previously, our group identified MAO-A, an enzyme responsible for degradation of the neurotransmitter serotonin, as a modulator of antitumor immune reponses14,15,37,59. Here, we further characterize the influence of the

[0211]

[0212] intratumoral serotonin axis on CD8 T cell antitumor immunity and establish the serotonin transporter, SERT, as a potent negative regulator of this axis and promising molecular target for immune checkpoint blockade.

[0213] In this report, we propose a working model in which the serotonergic transport protein SERT functions as a primary regulator of the utilization of tumor-localized serotonin, the intratumoral serotonin-5HTR-MAPK-NFKB axis, an important molecular pathway in CD8 T cell antitumor immunity (Figure 7). In this model, SERT restrains CD8 T cell antitumor immunity by inhibiting CD8 T cell-autocrine serotonin signaling pathway in the tumor (Figures 1, 3, and SI, and S3 in Li et al.). Upon recognition of tumor antigen (TA), tumor-infdtrating CD8 T cells upregulate expression of TPH1, greatly increasing intratumoral serotonin (Figures 5 and S6 in Li et al.). As negative feedback regulators of CD8 T cell activation and the serotonin axis, SERT and MAO-A are induced by TCR / TA recognition to reuptake and degrade serotonin, respectively (Figures 5 and S5 in Li et al ). Blocking SERT activity using established SSRI antidepressants depletes the peripheral serotonin; however, it increases the availability of the intratumoral T cell autocrine serotonin, which activates 5-HTR-MAPK-NF-κB signaling pathway and enhances CD8 T cells antitumor reactivities (Figure 5). This supports a SERT as a major regulator of the tumor cell-T cell immune synapse, resembling its function in the neuronal synapse (Figures 1 and 7). These discoveries provide new and fundamental insights into the molecular network that regulates T cell antitumor immunity, which could result in identification of new drug targets for the development of next-generation cancer immunotherapy.

[0214] Although serotonin has been associated with in vitro tumor cell proliferation6'163, the comprehensive influence of serotonergic signaling on tumor microenvironmental development remains ambiguous due to the multifaceted nature of serotonin as a signaling molecule. Serotonin can function as an extracellular signal through the agonism of G-protein-coupled 5-HTRs and as an intracellular signal through transglutaminase 2 (TGM2)-mediated serotonylation16,90. Both processes

[0215]

[0216] have been linked to increased ERK phosphorylation, which drives proliferation of cancer cells via the oncogenic Yes-associated protein (YAP)62,63. Serotonin-induced agonism of 5-HTR2B has also been shown to sustain liver cancer cell survival via phosphorylation of mTOR and enhance proliferation via Notch signaling64,65. However, serotonin deficiency (Tph ’~) in mice has been observed to not impact tumor cell proliferation directly, indicating a minimal role of mitogenic serotonin in tumor growth. Serotonin deficiency does diminish angiogenesis by upregulating tumor-associated macrophage (TAM) production of matrix metalloproteinase 12 (MMP-12) and lowers tumor cell PD-L1 expression, thereby compromising tumor resources and bolstering immunogenicity66, 74. Interestingly, our study revealed that SSRI treatment did not impact the growth of mouse and human melanoma in NSG mice (Figures 3 and S7 in Li et al.), which lack mature lymphocytes. We found that SSRI treatment not only directly activated CD8 T cells via a 5-HTR-dependent signaling pathway (Figures 3 and 4), but also increased production of CD8 T cell-derived serotonin in the TME (Figure 5), supporting our new model of a SERT-regulated intratumoral serotonin axis driving CD8 T cell antitumor activity.

[0217] Currently, the success of ICB therapy is restricted to a small number of responders, and a major focus of the field lies in identifying novel, nonredundant checkpoint pathways that can enhance the efficacy or range of these drugs67,68. Our analysis suggests that CD8 T cells isolated from tumors of mice treated with fluoxetine have a unique set of upregulated proliferation / effector-related pathways when compared to those in mice treated with anti-PD-1 (Figures 2 and S2 in Li et al.). Additionally, when examining human data retrieved from previous clinical trials, we found that genes relevant to serotonergic regulation were most highly expressed in CD45RA re-expressing terminally differentiated effector memory (TEMRA) CD8 T cells (Figures 6 and S6 in Li et al.). Activated TEMRA cells in the TME can be a major indicator of favorable immunogenicity69–73. and this data suggests that the serotonin axis may influence these key cells. In contrast, the targets of other approved ICB therapies were most highly expressed in exhausted CD8 T cells (Figure 6),

[0218]

[0219] indicating a unique mechanism of action that may also contribute to combination therapy synergy'. Interestingly, it was recently reported that a serotonylati on-dependent pathway in tumor cells restricted tumor immunogenicity by upregulating expression of PD-L174. This pathway was inhibited by treatment with SSRIs, suggesting an additional, tumor-intrinsic effect of SSRIs on tumor immunogenicity that could further increase the synergy' between fluoxetine and anti-PD-1 as a combination antitumor therapy. Together, these findings suggest that further investigation into the clinical combination of these drugs is a promising avenue for the advancement of ICB therapy.

[0220] The popularity of antidepressant drug (AD) prescription and the co-occurrence of major depressive disorder (MDD) in patients with cancer provides the opportunity' for correlative clinical studies investigating the association between AD consumption and cancer patient survival75,76. A nationwide cohort study of 42,075 Israeli patients with cancer reported that adherence to a prescribed AD at a rate above 50% was associated with one quarter less mortality' over 4 years than adherence below 20%77. Similarly, a large-cohort clinical study from Taiwan reported a dose-dependent relationship between AD use and overall survival in patients with gastric cancer after surgery and adjuvant chemotherapy78. Although these studies did not separate out AD class, we can postulate that SSRIs were the primary' influence on these results as they made up over 60% of all AD prescriptions in 201532. Our clinical correlation studies identified SERT as a possible negative regulator of clinical outcomes and CD8 T cell antitumor function in a broad range of cancer (Figures 6 and S7 in Li et al.). Continued investigation into possible correlations between SSRI treatments and clinical outcomes therefore could provide valuable insights to further support SSRI repurposing for cancer therapy.

[0221] Studies estimate the "‘bench to bedside" pipeline for novel cancer therapeutics costs an average of $1.56 billion compared to an estimated $300 million for repurposing studies80,81, due in part to the lack of required fundamental R& D and already -established safety' profiles82 84The repurposing of existing drugs provides a

[0222]

[0223] cost-effective and rapid route to developing more cancer therapies. Currently, SSRIs are the most popular clinical AD class due to their high efficacy and favorable safety profile36’85’86. Our studies demonstrated antitumor efficacy of SSRIs in a broad range of cancer and showed comparable tumor suppression between SSRIs and anti-PD-1 (Figure 1), one of the most effective ICB therapies on the market9,87. The mechanism of action for SSRIs uniquely restricts increased serotonin to the TME (Figure 5), without impacting the catabolism of other monoamines88. SSRIs did not induce any observable adverse tissue inflammation and autoimmunity (Figure SI in Li et al.) as well as aggressive behaviors in mice, supporting them as a favorable candidate for ICB repurposing. Additionally, the repurposing of SSRIs as an antitumor therapy is especially appealing because of the dual benefit provided to patients suffering from depression, which often accompanies cancer diagnosis76,77. These studies support expansions of clinical trials that investigate the effects of SSRIs on antitumor responses and clinical outcomes in an array of tumor types and cotherapies77,78.

[0224] In conclusion, we identified SERT as a new immune checkpoint negatively regulating CD8 T cell antitumor immunity through modulating intratumoral T cell autocrine serotonin and demonstrated potential of targeting the intratumoral serotonin axis in solid tumors using SSRI antidepressants for T-cell based cancer immunotherapy. Our findings provide a rational mechanistic basis to investigate clinical effect of SSRIs on CD8 T cell antitumor immunity and to examine the benefits of SSRIs when administered in concert with existing ICBs in cancer patients. Given the widespread clinical use of SSRIs, these strategies can be readily translated to clinical trials. Additionally, the serotonergic pathway is one of several neuronal regulatory pathways that are only beginning to be understood in the context of tumor immunity. Future studies are encouraged to elucidate new roles of other neuronal regulatory genes and neurotransmitters in tumor immunology, which could contribute to a deeper understanding of the regulatory network controlling antitumor immunity.

[0225] There are several limitations to our study. Our study has discovered a negative correlation between SERT expression and patient survival, and has uncovered SSRIs

[0226]

[0227] to be sufficient to activate human CD8 T cell and promote antitumor immunity in vivo and in vitro,- however, our study lacks clinical correlation data between SSRI adherence and overall survival / ICB response among cancer patients. Given that many cancer patients suffer from major depression / anxiety and may be receiving ICB and SSRI treatments, a retrospective analysis of existing clinical data regarding SSRIs' use in cancer patients receiving immunotherapy is required in follow-up studies. Additionally, there is a possibility that SERT also regulates other immune cells in cancer immunity. Several types of immune cells (e.g.. macrophages, dendritic cells, and regulatory T cells) have been shown to display the expression of serotonergic machinery and receptors88,89; and we have observed the hyperresponsiveness of macrophages upon SSRI treatments. The mechanisms of how SERT exclusively regulates macrophage-mediated antitumor immunity remain incompletely addressed and should be the focus of future studies. Similarly, serotonin is an important signaling molecule in many systems, particularly in the brain22,90. While this study focused on the impact of SSRIs on immune-intrinsic serotonergic regulation, it is undefined whether these drugs may also influence intratumoral neurogenesis and key aspects of neuroimmune crosstalk that can influence disease outcome42,91,92. Further investigation into the cross-system complexities of serotonin signaling and the impact of SERT inhibition on these dynamics will increase the applicability of SSRIs in new contexts and enhance our understanding of the TME.

[0228]

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[0379] All publications mentioned herein (e.g. the references numerically listed above) are incorporated herein by reference to disclose and describe aspects, methods and / or materials in connection with the cited publications.

[0380]

Claims

CLAIMS:

1. A method of modulating a physiology of a tumor-infiltrating CD8 T cell comprising introducing a SSRI into the environment in which the tumor-infiltrating CD8 T cell is disposed: wherein amounts of the SSRI introduced into the environment are selected to be sufficient to enhance the tumor-infiltrating CD8 T cell antitumor immunity, thereby modulating the physiology of the tumor-infiltrating CD8 T cell.

2. The method of claim 1, wherein the tumor-infiltrating CD8 T cell is disposed in an individual diagnosed with cancer.

3. The method of claim 2, wherein the individual is undergoing a therapeutic regimen comprising the administration of a therapeutic agent.

4. The method of claim 3, wherein the cancer is a lymphoma or a skin, breast, ovarian, prostate, colorectal or lung cancer.

5. The method of claim 1, wherein modulation of the physiology of the tumorinfiltrating CD8 T cell comprises at least one of: enhanced tumor immunoreactivity; enhanced secretion of serotonin; increased expression of IFN-y; increased expression of Granzyme B; or decreased expression of PD-1.

6. The method of claim 1, wherein the SSRI comprises at least one of: citalopram, escitalopram, fluoxetine, paroxetine, and sertraline7. The method of claim 6, wherein the SSRI is disposed within a nanoparticle; optionally a nanoparticle comprising a lipid.

8. The method of claim 3, wherein the therapeutic agent comprises:a targeted antibody;carboplatin;paclitaxel; orat least one immune checkpoint inhibitor selected to affect CTLA-4 or a PD-1 / PD-L1 blockade.

9. The method of claim 1, wherein the SSRI is combined with anti-PD-l / anti-PD-L1 in amounts sufficient to induce an accumulation of tumor-infiltrating CD8 T cells at the effector / proliferating stage.

10. A method of treating a cancer in an individual comprising administering to the individual a SSRI; wherein amounts of the SSRI administered to the individual are selected to be sufficient to modulate the physiology of tumor-infiltrating CD8 T cells in the individual.

11. The method of claim 10, wherein modulation of the physiology of the tumorinfiltrating CD8 T cells comprises at least one of: enhanced tumor immunoreactivity; enhanced secretion of serotonin; increased expression of IFN-y; increased expression of Granzyme B; or decreased expression of PD- 1.

12. The method of claim 10, wherein the individual is undergoing a therapeutic regimen comprising the administration of at least one therapeutic agent.

13. The method of claim 10, wherein the cancer is a lymphoma or a skin, breast, ovarian, prostate, colorectal or lung cancer.

14. The method of claim 10, wherein the SSRI is disposed within a nanoparticle; optionally a nanoparticle comprising a lipid.

15. The method of claim 10, wherein the SSRI comprises at least one of: citalopram, escitalopram, fluoxetine, paroxetine, and sertraline

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