Abstract Background Beyond supporting cancer cell proliferation, tumor growth relies on the ability of cancer cells to evade immune surveillance. Identifying novel molecules that promote tumor immune escape may help develop more effective immunotherapeutic strategies. The histone acetyltransferase E1A-binding protein p300 (EP300) is a key epigenetic regulator that modulates gene transcription through chromatin remodeling and acetylation of histones and transcription factors. However, its role in regulating immune evasion remains incompletely understood. This study investigates the impact of EP300 on tumor immune escape and suggests its potential as an immunotherapeutic target. Methods We analyzed tissue microarrays from patients with lung adenocarcinoma using immunohistochemistry to compare EP300 expression between cancerous tissues and benign tissues. Ep300-knockout cancer cells were generated using CRISPR-Cas9. Animal models were employed to assess the effect of Ep300 depletion on tumor progression and intratumoral CD8^+ T cell infiltration. RNA sequencing, chromatin immunoprecipitation sequencing, flow cytometry, and western blot were used to explore the mechanism by which EP300 regulates antigen-presenting gene expression. Results EP300 was significantly upregulated in cancerous tissues compared with benign tissues. Genetic ablation of Ep300 in cancer cells markedly suppressed tumor growth in vivo and enhanced CD8^+ T-cell infiltration. Mechanistically, EP300 upregulates suppressor of cytokine signaling 1 (SOCS1) expression, thereby inhibiting signal transducer and activator of transcription 1 phosphorylation. This leads to downregulation of antigen-presenting genes, enabling cancer cells to evade immune surveillance by CD8^+ T cells. Conclusions EP300 facilitates tumor immune evasion by suppressing antigen-presenting gene expression via SOCS1 upregulation. Our findings reveal a novel role for EP300 in mediating immune escape and propose a potential therapeutic strategy to enhance antitumor immunity. Keywords: Immunotherapy, JAK-STAT, Major histocompatibility complex - MHC, Tumor microenvironment - TME __________________________________________________________________ WHAT IS ALREADY KNOWN ON THIS TOPIC * Immune surveillance evasion is a hallmark of cancer. While E1A binding protein p300 (EP300) has been shown to promote tumor growth across various cancer types, its specific role and mechanisms in regulating tumor immune evasion remain unclear. WHAT THIS STUDY ADDS * This study reveals that EP300 upregulates suppressor of cytokine signaling 1, which subsequently inhibits phosphorylation of signal transducer and activator of transcription 1 (STAT1). The reduced STAT1 activation leads to downregulation of antigen presentation genes, ultimately enabling cancer cells to escape CD8^+ T cell-mediated immune surveillance. HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY * By elucidating EP300’s role in immune evasion, we demonstrate that EP300 inhibition enhances major histocompatibility complex-I expression in cancer cells and promotes CD8^+ T-cell infiltration. These findings suggest that targeting EP300 could contribute to cancer immunotherapy, offering a novel strategy for antitumor immune intervention. Introduction Cancer is fundamentally characterized by uncontrolled proliferation of cells, driven by both genetic and non-genetic alterations that support tumor growth, survival, and progression.[49]^1 Among the hallmarks of cancer, immune evasion plays a central role in enabling malignant cells to escape host immune surveillance.[50]^1 To avoid detection and elimination by immune cells, cancer cells commonly upregulate immune checkpoint molecules such as programmed death-ligand 1 (PD-L1), or downregulate antigen-presenting molecules such as major histocompatibility complex class I (MHC-I).[51]2,[52]5 These alterations are orchestrated by tumor-intrinsic regulatory mechanisms, including not only genetic mutations but also epigenetic modifications.[53]^6 E1A binding protein p300 (EP300) is a large, multidomain transcriptional coactivator that functions as a histone acetyltransferase (HAT) and is highly conserved across evolution.[54]7,[55]9 EP300 modulates chromatin accessibility by acetylating histones and transcription factors, thereby regulating gene expression programs involved in cell proliferation, differentiation, cell cycle progression, and DNA repair.[56]9,[57]12 Dysregulation of EP300 has been implicated in the development and progression of various malignancies.[58]13,[59]15 In cancer cells, EP300 has been shown to promote survival via activation of the NF-κB pathway and to contribute to immune evasion by enhancing PD-L1 expression.[60]^16 17 Several small molecules targeting EP300 have demonstrated antitumor efficacy in preclinical models. For example, JQAD1, a PROTAC degrader of EP300, reduces global H3K27 acetylation and induces apoptosis in cancer cells[61]^18; C646, a selective HAT inhibitor, also impairs tumor cell proliferation.[62]^19 20 Beyond its tumor-intrinsic roles, EP300 inhibition has been reported to impair regulatory T cell (Treg) function, thereby enhancing antitumor immunity.[63]^21 However, EP300 appears to exhibit context-dependent roles in cancer. Loss-of-function mutations have been identified in hematological malignancies and several solid tumors, including lymphoma, leukemia, bladder cancer, and non-small cell lung carcinoma.[64]22,[65]25 For instance, in diffuse large B-cell lymphoma, EP300 mutations reprogram the tumor immune landscape and promote the polarization of tumor-associated macrophages toward an M2-like, immunosuppressive phenotype.[66]^26 These observations highlight the dual and context-specific roles of EP300 in tumor biology, particularly in shaping tumor immunogenicity, which remains poorly understood. In this study, we investigated the effects of EP300 expressed on cancer cells on antitumor immunity. Targeted deletion of EP300 in cancer cells led to a remodeled tumor microenvironment and robust activation of CD8^+ T cell-mediated antitumor responses. Mechanistically, EP300 inhibited activation of the type I interferon (IFN) signaling pathway by upregulating the expression of suppressor of cytokine signaling 1 (SOCS1), thereby facilitating immune evasion. These findings uncover a novel mechanism by which cancer cells evade immune surveillance and suggest that targeting EP300 may represent a promising strategy to enhance antitumor immunity. Methods Patients’ tumor tissues and clinical data This study recruited 77 patients with lung adenocarcinoma for immunohistochemical (IHC) analysis from the Affiliated Tumor Hospital of Nantong University (patients information seen in [67]online supplemental table 1). Tumor tissues collected from surgical patients were fixed formalin and embedded with paraffin and then examined. All ethical regulations relevant to human research participants were followed. Immunohistochemical analysis Tissues were fixed with formaldehyde and embedded in paraffin, then cut into 4 µm thick slices. The paraffin-embedded tissue sections were baked at 65°C for 30 min, followed by dewaxing in xylene for 10 min three times. The sections were then subjected to graded rehydration through immersion in anhydrous ethanol for 3 min three times, 95% ethanol for 3 min two times, and 75% ethanol for 3 min three times. After rinsing with distilled water, antigen retrieval was performed using citrate buffer: the sections were boiled in a pressure cooker for 3 min and allowed to cool naturally. Subsequently, 3% hydrogen peroxide (H[2]O[2]) was applied and incubated at room temperature for 10 min to block endogenous peroxidase activity. The sections were blocked with phosphate-buffered saline (PBS) containing 10% goat serum at room temperature for 2 hours. Primary antibodies (anti-EP300, anti-phosphorylated signal transducer and activator of transcription 1 (p-STAT1)) were diluted in antibody dilution buffer (ZSbio, Cat. ZLI-9030), and 100 µL of the diluted primary antibody was added to each section and incubated at room temperature for 2 hours. Slides were washed with PBS for 3 min three times. Subsequently, 100 µL of secondary antibody (Dako, Cat. K5007) was added and incubated at room temperature for 30 min. Diaminobenzidine (DAB) chromogenic solution (Dako, Cat. K5007) was applied and incubated at room temperature for 5 min to develop staining. The slides were rinsed with tap water, counterstained with hematoxylin (nt-mevid, Cat. SL01-0500), dehydrated through graded ethanol, cleared in xylene for 15 min, and mounted with neutral resin. The antibodies used in this analysis are listed in [68]online supplemental table 2. Two associate chief pathologists independently evaluated the IHC results in a double-blind manner. According to the staining extent scoring criteria, five random fields were selected under a 400×microscope for each section, with approximately 500 cells counted per field. The average percentage of positive cells was calculated as follows: 0 points for <1% positive cells; 1 point for 1–10%; 2 points for 10–50%; 3 points for 50–75%; and 4 points for >75%. For staining intensity, 0 points were assigned for no staining; 1 point for pale yellow; 2 points for yellow or brownish yellow; and 3 points for brown or dark brown staining. The final IHC score was obtained by multiplying the extent and intensity scores. A total score of 0 was considered negative expression; 1–2 points, low expression; 3–6 points, moderate expression; and greater than 6 points, high expression. Cell culture MCA205 fibrosarcoma cell line was generated and provided by Dr S A Rosenberg (NCI, Bethesda, Maryland, USA). TC-1 lung cancer cell line was generated and provided by Dr T C Wu (Johns Hopkins University, Baltimore, Maryland, USA). 293T cell lines were purchased from the Cell Resource Center, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences (Beijing, P.R. China). HT-1080 (human fibrosarcoma cell line) was purchased from American Type Culture Collection. L929-ISRE (L929 cells expressing an Interferon-Stimulated Responsive Element) reporter cell line was a gift from Jiang Zhengfan’s laboratory at Peking University. MCA205, TC-1, HT-1080, 293T, and L929-ISRE cell lines were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) (Gibco, Cat. C11995500BT) supplemented with 10% fetal bovine serum (FBS) (Excelll, Cat. FSP500) and 1% penicillin/streptomycin (Gibco, Cat. 15 140–122) at 37°C in a 5% CO[2] incubator. Mycoplasma was tested using cell culture supernatant by Mycoplasma Detection Kit (InvivoGen, Cat. rep-mys-20) or PCR assay. Normocin (InvivoGen, Cat. ant-nr-1) and Plasmocure (InvivoGen, Cat. ant-pc) were used for the prevention and treatment of Mycoplasma contamination, respectively. All experiments were conducted without Mycoplasma contamination. Gene editing of stable knockout cell lines using the CRISPR/Cas9 system Single guide RNA oligonucleotides targeting mouse Ep300, Socs1, and Stat1 were synthesized and cloned into the LentiCRISPR v2 vector (Addgene, Cat. 52961). Three plasmids including pMD2.G (Addgene, Cat. 12259), psPAX2 (Addgene, Cat. 12260), and LentiCRISPR v2 or a control vector were co-transfected into 293T cells using Lipofectamine 3000 (Invitrogen, Cat. L3000-015) for 48 hours. The obtained lentivirus was collected and used to infect TC-1 or MCA205 cancer cells. After 48 hours of infection, cells were cultured in a complete DMEM medium containing puromycin (4 µg/mL, InvivoGen, Cat. ant-pr-1) or hygromycin B (MCE, Cat. HY-B0490) for more than 7 days. Single-cell clones were sorted into 96-well plates using an FACSAria III cell sorter (Becton Dickinson, San José, California, USA). The knockout cell lines were identified by western blot assay. The sequences synthesized in this study are listed in [69]online supplemental table 3. Obtaining of stable SOCS1 and ovalbumin overexpression cell lines Lentivirus was used to construct a stable overexpression cell line, and an empty vector was used as a control. In brief, target complementary DNA (cDNAs) such as Socs1, or ovalbumin (OVA) have been cloned into the dCAS9-VP64-GFP (Addgene, Cat. 61422) vector plasmid, respectively. Then, three plasmids including pMD2.G (Addgene, Cat. 12259), psPAX2 (Addgene, Cat. 12260), and target plasmid or a control vector were co-transfected into 293T cells using Lipofectamine 3000 (Invitrogen, L3000-015) for 48 hours. The obtained lentiviruses are used to infect target cells. After 48 hours, green fluorescent protein (GFP)-positive cells were sorted using an FACSAria III cell sorter (Becton Dickinson, San José, California, USA). siRNA transfection assay For siRNA experiments, Lipofectamine 3000 (Invitrogen, L3000-015) was used to transfect siRNA into cells. After 60 hours of siRNA transfection, cells were collected for western blot analysis. The siRNA sequences synthesized in this study are listed in [70]online supplemental table 4. Animal experiments All animals were maintained in a specific pathogen-free facility. All animal studies were reviewed and approved by the Institutional Animal Care and Use Committee of the Suzhou Institute of Systems Medicine. C57BL/6N and athymic nude BALB/c (nu/nu) mice (female and male, ages between 6 and 8 weeks, weights between 18 and 20 g) were purchased from Beijing Vital River Company. C57BL/6-Tg (TcraTcrb) 1100Mjb/J (OT-I) mice were purchased from The Jackson Laboratory. Mice were randomly divided into the indicated groups (five mice/group) before inoculation. For tumor growth assay, cancer cells (2×10^6 cells in 100 µL PBS per mouse) were subcutaneously (s.c.) implanted. Tumor size was measured using a caliper every 2–3 days starting at 7 days and calculated by multiplying the length by the width and data were described as error bars of mean±SEM. Mice were euthanized by CO[2] inhalation when tumor size reached 300 mm^2. For CD8^+ T-cell depletion experiments, 10 mg/kg Anti-CD8 antibody (Bio X Cell, Cat. BE0004-1) or isotype antibody (Bio X Cell, Cat. BE0089) was administered intravenously on days −1, 1, and 3 after s.c. inoculation of cancer cells. For Anti-IFNAR1 treatment, 10 mg/kg Anti-IFNAR1 antibody (Bio X Cell, Cat. BE0241) or isotype antibody (Bio X Cell, Cat. BE0083) was administered intravenously on days 1, 3, 5, 7, 9, and 11 after s.c. inoculation of cancer cells. For JQAD1 treatment, 10 mg/kg JQAD1 (TOCRIS, Cat. 2417097-18-6) was administered intratumoral (i.t.) injection on days 6, 8, 10 and 12 after cancer cell implantation. For in vivo siEp300 treatment, 5 nM/mouse in vivo siEp300 or in vivo siNC (negative siRNA control) were i.t. injected every 2 days after 6 days of cancer cell implantations, in vivo siEp300 or in vivo siNC, which chemically modified with 5Col/2OMe was synthesized by RiboBio (Guangzhou, China), the sequences synthesized in this study are listed in [71]online supplemental table 4. For lung metastasis assay, cancer cells (1×10^6 cells in 100 µL PBS per mouse) were injected into the lateral tail vein of the mice. For pre-injection of cancer cells assay, Ep300^−/− TC-1 or MCA205 cancer cells (2×10^6 cells in 100 µL PBS per mouse) were s.c. into the left flank of each host mouse. On the 30th day after the tumor-bearing on the left side, the wild-type (WT) TC-1 or MCA205 cancer cells (2×10^6 cells in 100 µL PBS per mouse) were implanted s.c. into the right flank. Tumors were harvested on days 7–11 post-implanted for following analysis such as RNA sequencing (RNA-seq), enzyme-linked immunospot (ELISpot) assay, immunofluorescence staining and flow cytometry analysis. Immunofluorescence staining Tumors were harvested on day 10 or 11 and fixed in 4% paraformaldehyde (Solarbio, Cat. P1110) at 4°C for 24 hours. The fixed tumor tissues were then transferred to 30% (wt/vol) sucrose solution and dehydrated at 4°C for 48 hours. After dehydration, OCT was used to embed the tumor tissue. After freezing, a Leica cryostat was used to prepare sections 5 µm thick. Frozen tumor tissue sections were warmed to room temperature for 2 min, then fixed in ice-cold acetone at 4°C for 15 min. Afterward, the sections were blocked with PBS containing 10% goat serum at room temperature for 1 hour. The diluted anti-CD8a primary antibody (1:100, Abcam, Cat. ab217344) was added and incubated overnight at 4°C. The next day, after washing three times with PBS, the tumor tissue sections were incubated with Alexa Fluor Plus 568-conjugated secondary antibody (1:1000, Invitrogen, Cat. A11036) at room temperature for 1 hour. Nuclei were stained with Hoechst 33342 (1:1000, Thermo Fisher Scientific, Cat. H3570) at room temperature for 15 min. Images were acquired using a confocal microscope (Leica TCS SP8) and analyzed using ImageJ software. The number of CD8^+ cells and Hoechst 33342-stained nuclei (indicating the total number of cells) in each image was quantified using ImageJ. The percentage of CD8^+ cells was calculated as the ratio of CD8^+ cells to total nuclei. The antibodies used in this analysis are listed in [72]online supplemental table 2. Analysis of tumor-infiltrating lymphocytes by flow cytometry Mice were euthanized by CO[2] inhalation, and tumor tissues were excised and cut into small pieces in serum-free Roswell Park Memorial Institute (RPMI) 1640 medium. Then, serum-free DMEM medium containing DNase I (Sigma, Cat. 260913–10 MU) and Liberase TL (2 µg/mL, Roche, Cat. 05401020001) was used to digest the tumor tissues at 37°C for 30 min. The cell suspension was passed through a 70 µm filter (Thermo Fisher Scientific) and centrifuged at 1,500 rpm for 5 min. After discarding the supernatant, red blood cells were removed using red blood cell lysis buffer (TIANGEN, Cat. RT122-02). The cells were then washed two times with PBS and resuspended in PBS for the next experiment. For cell surface marker staining, cells were first labeled with a live/dead reagent (LIVE/DEAD Fixable Yellow Dead Cell Stain Kit, Thermo Fisher Scientific, Cat. [73]L34959), washed two times with PBS, and then Fc receptors were blocked using anti-CD16/32 antibody (BioLegend, Cat. 101320). The cells were incubated with fluorochrome-conjugated antibodies diluted in staining buffer (2% FBS in PBS) at 4°C in the dark for 30 min to stain for surface antigens (such as CD45, CD3, CD4, CD8, CD25). After staining, the cells were washed two times with PBS and then resuspended in staining buffer (2% FBS in PBS) for flow cytometry analysis. For nuclear protein staining of Foxp3, after surface marker staining, cells were washed once with PBS to remove unbound antibodies. The Foxp3/Transcription Factor Staining Buffer Set (Invitrogen, Cat. 00–5523) was used to fix and permeabilize the cells at room temperature in the dark for 30–60 min. Cells were then centrifuged at 400–500 g, the supernatant discarded, and washed two times with 1×permeabilization buffer. The cells were resuspended in anti-Foxp3 antibody diluted in Perm/Wash buffer and incubated at room temperature in the dark for 30 min. After staining, cells were washed two times with 1×permeabilization buffer and resuspended in staining buffer (2% FBS in PBS) for flow cytometry analysis. For intracellular cytokine staining (eg, IFN-γ), cells were cultured in RPMI medium containing 10% FBS, 1% penicillin/streptomycin, phorbol 12-myristate 13-acetate (PMA)/ionomycin mixture (1:250, Multi Sciences, Cat. CS1001) and brefeldin A (BFA)/monensin mixture (1:250, Multi Sciences, Cat. CS1002) in a 37°C, 5% CO[2] incubator for 4–6 hours. Cells were then stained using the Fixation/Permeabilization Buffer Set according to the manufacturer’s protocol (BD Biosciences, Cat. 554714). Briefly, surface markers were first stained, cells were washed two times with PBS, and then fixed and permeabilized with Fixation/Permeabilization solution for 20 min at 4°C, followed by two washes with 1×BD Perm/Wash buffer. Cells were then resuspended in BD Perm/Wash buffer containing anti-IFN-γ and anti-granzyme B (GZMB) fluorescent antibodies, and incubated at 4°C in the dark for 30 min to stain intracellular markers. After incubation, cells were washed two times with 1×BD Perm/Wash buffer and resuspended in staining buffer for flow cytometry analysis. Samples were analyzed using a BD LSRII Fortessa flow cytometer. Data analysis was performed using FlowJo software. The antibodies used in this analysis are listed in [74]online supplemental table 5. Detection of cell MHC-I expression For TC-1 and MCA205 cells, 3×10^5 cells were seeded per well into a 6-well plate, allowed to adhere overnight, and collected after 24–48 hours of culture. After washing the cells two times with PBS, they were resuspended in a staining solution containing anti-H2-Kb antibody (BioLegend, Cat. 116518) in PBS supplemented with 2% FBS, and incubated on ice for 30 min in the dark. After staining, the cells were washed two times with PBS, resuspended in staining buffer, and the expression of surface proteins was analyzed using a BD LSRII Fortessa or BD Symphony A1 flow cytometer. Data were analyzed using FlowJo software. The antibodies used in this analysis are listed in [75]online supplemental table 5. For experiments involving IFN-γ stimulation, 3×10^5 cells were seeded into a 6-well plate per well. After overnight adhesion, mouse IFN-γ (20 ng/mL, MCE, Cat. HY-[76]P70667) was added to the cells for 24 hours. Cells were then collected for staining and detection, following the same procedure as described above. The antibodies used in this analysis are listed in [77]online supplemental table 5. For HT-1080 cells, 2×10^5 cells were seeded per well into a 6-well plate and allowed to adhere overnight. The next day, different concentrations of JQAD1 (Tocris, Cat. 7682) were added, and cells were collected 48 hours later for analysis. After washing two times with PBS, the cells were resuspended in staining buffer (PBS containing 2% FBS) with anti-HLA-A2 antibody (BioLegend, Cat. 343306), incubated on ice for 30 min, washed two times with PBS to remove unbound antibodies, and resuspended in staining buffer. Detection was performed using a BD LSRII Fortessa or BD Symphony A1 flow cytometer, and data were analyzed using FlowJo software. The antibodies used in this analysis are listed in [78]online supplemental table 5. Detection of specific antigen peptide complexes (SIINFEKL:H2-Kb) expression OVA-expressing cancer cells were generated by infection with dCas9-VP64-OVA-GFP. 3×10^5 OVA-expressing cells were seeded per well into a 6-well plate, allowed to adhere overnight, and collected after 24–48 hours of culture. After washing the cells two times with PBS, they were resuspended in a staining solution containing anti-H2-Kb bound to SIINFEKL peptide antibody (in PBS containing 2% FBS), and incubated on ice for 30 min in the dark. After staining, the cells were washed two times with PBS, resuspended in staining buffer, and analyzed for surface expression of antigen-peptide complexes using a BD LSRII Fortessa or BD Symphony A1 flow cytometer. Data were analyzed using FlowJo software. The antibodies used in this analysis are listed in [79]online supplemental table 5. Cell apoptosis assay Cells were seeded into 24-well plates at 1×10^5 cells per well. After overnight attachment, 1 µM methotrexate (MTX) was added and the cells were incubated for 24 hours. The culture supernatant was collected, and the adherent cells were detached using EDTA-free trypsin. The cells in the supernatant were then combined with the harvested cells and washed two times with PBS. The apoptosis staining solution was prepared according to the manufacturer’s instructions for the FITC Annexin V Apoptosis Detection Kit I (BD Biosciences, Cat. 556547). Propidium iodide (PI) and Annexin V-FITC were diluted in 1×binding buffer. Then, 100 µL of the prepared staining solution was added to each sample and incubated at room temperature in the dark for 15 min. Staining was terminated by adding 400 µL of 1×binding buffer, and the samples were transferred to flow cytometry tubes and analyzed within 1 hour. Samples were analyzed using a BD LSRII Fortessa or BD Symphony A1 flow cytometer. PI was detected in the PE channel (568 nm laser), and Annexin V-FITC was detected in the Alexa Fluor 488 channel (488 nm laser). Compensation was carried out using single-stained controls, and gating was based on these controls. Data were analyzed using FlowJo software. The reagents used in this analysis are listed in [80]online supplemental table 5. Cell proliferation assay 1,000 cells were seeded into 96-well plates and cultured for 24, 48, and 72 hours. Cell proliferation was detected according to the manual of Cell Counting Kit-8 (Dojindo, Cat. CK04). Data were obtained from SpectraMax device (Molecular Devices). Experiments with co-culture of CD8^+ T and cancer cells Splenocytes were harvested from the spleen of OT-I mice and cultured in the RPMI media containing 10% FBS and 1% penicillin/streptomycin, 5 µg/mL SIINFEKL (OVA[257-264]) peptide (sigma, Cat. S7951), and 4 ng/mL mouse interleukin (IL)-2 (MCE, Cat. HY-P7077) for 3 days to expand Ag-specific CD8^+ OT-I T cells. 3 days later, the suspended cells were collected, centrifuged to remove the supernatant, and then cultured in the RPMI media containing 10% FBS and 1% penicillin/streptomycin, and 4 ng/mL IL-2 for additional 3 days. After 3 days, the suspended cells were collected, centrifuged to remove the supernatant, and then cultured in fresh RPMI medium containing 10% FBS, 1% penicillin/streptomycin, and 4 ng/mL IL-2 for an additional 3 days. CD8^+ T cells were purified using magnetic beads (Miltenyi Biotec, Cat. 130-117-044). To assess antigen-specific T cell-mediated killing of OVA-expressing cancer cells, purified CD8^+ T cells were co-cultured with WT-OVA or Ep300^−/^−-OVA TC-1 or MCA205 cells at various effector:target (E:T) ratios in 48-well plates. For example, at an E:T ratio of 3:1, 3×10^5 CD8^+ T cells were co-cultured with 1×10^5 cancer cells. After 16–24 hours, the co-cultured cells were collected, stained with 7-aminoactinomycin D (7-AAD) (BioLegend, Cat. 420404) and Annexin V-PE (BioLegend, Cat. 640947), and the apoptosis rate of GFP-positive OVA-expressing cells was determined by flow cytometry. To evaluate T-cell killing of OVA-pulsed cancer cells, target cells were pulsed with 2 ng/mL SIINFEKL peptide at 37°C for 2 hours. The cells were then washed three times to remove unbound peptide and seeded into 96-well plates at 3×10^4 cells per well. Activated CD8^+ OT-I T cells were added at different E:T ratios. After 48 hours of co-incubation, samples were analyzed by flow cytometry to determine the percentage of killing of peptide-pulsed cells under each pretreatment condition. Killing efficiency was determined by comparing the relative percentage of cancer cells remaining in wells with T cells to those without T cells. Cancer cells were identified as viable (fixable yellow negative), CD45-negative populations. As an additional control to assess MHC-I antigen specificity, the same assay was performed without peptide pulsing, to determine whether killing required peptide recognition by the OT-I T-cell receptor. Samples were analyzed using a BD LSRII Fortessa or BD Symphony A1 flow cytometer, and data were analyzed using FlowJo software. The antibodies used in this analysis are listed in [81]online supplemental table 5. Immunoblotting Cells were lysed with radio immunoprecipitation assay (RIPA) lysis buffer (Beyotime, Cat. P0013C) supplemented with phenylmethylsulfonyl fluoride (PMSF) (1:100, Beyotime, Cat. ST506) and protease and phosphatase inhibitors (1:100, NCM, Cat. P002). Protein concentrations were measured using the BCA Protein Quantification Kit (NCM, Cat. WB6501). Samples were mixed with sodium dodecyl sulfate (SDS) loading buffer (Takara, Cat. 9173) and denatured at 100°C for 10 min. Proteins were separated by sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) and transferred onto polyvinylidene fluoride (PVDF) membranes (Millipore, Cat. 195863, 159446). The membranes were blocked with 5% skim milk in Tris-buffered saline with Tween 20 (TBST) for 1 hour at room temperature, followed by incubation with primary antibodies overnight at 4°C. The next day, membranes were washed three times with TBST for 15 min each and then incubated with horseradish peroxidase (HRP)-conjugated secondary antibodies at room temperature for 1 hour. Afterward, the membranes were again washed three times with TBST (15 min each) at room temperature. Finally, signals were detected using a ChemiDoc XRS^+ System (Bio-Rad, USA) or MiniChemi 610 (Sagecreation, Beijing). Band intensity was measured using Image Lab (Bio-Rad) or ImageJ (NIH) software, and all quantifications were based on the ratio of the target protein signal to the corresponding housekeeping protein signal from the same membrane. The expression level of the control group was set to 1, and relative expression levels of the experimental groups were normalized accordingly. The antibodies used in this analysis are listed in [82]online supplemental table 2. Quantitative reverse-transcription PCR assay Total RNA was extracted using the RNA-Quick Purification Kit (uu-bio technology, Cat. [83]U10018). The extracted RNA was reverse transcribed into cDNA using the PrimeScript II first Strand cDNA Synthesis Kit (TaKaRa, Cat. 6210A). The obtained cDNA was used for real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) analysis. A total of 20–50 ng of cDNA was added per well. Gene expression levels were quantified using the SYBR Green method (Bimake, Cat. [84]B21202) on a LightCycler Real-Time PCR System (Roche) in a 384-well format. Cycle threshold values were calculated using Roche LightCycler 480 software. RT-qPCR data were normalized to β-actin or Gapdh, and results are presented as fold changes in gene expression in the test samples relative to the control. The primers used in these studies are listed in [85]online supplemental table 6. RNA sequencing Total RNA was extracted from cells or tumor tissues using the RNeasy Mini Kit (QIAGEN, Cat. 74104), and reverse transcribed to cDNA using ProtoScript II Reverse Transcriptase (New England BioLabs, Cat. E7420L). The cDNA was purified using Agencourt AMPure XP Beads (Beckman, Cat. A63881), and Multiplex Oligos were used to ligate paired-end adapters for RNA-seq. Sequencing was performed using an Illumina NovaSeq 6000. RNA sequencing (RNA-seq) data analysis was performed using CLC Genomics Workbench 12 (QIAGEN Bioinformatics). Gene Ontology (GO) analysis was performed with David website ([86]https://david.ncifcrf.gov/). Gene Set Enrichment Analysis Gene Set Enrichment Analysis (GSEA) was performed using GSEA software V.4.2.3, following the guidelines provided on the official website.[87]^27 28 The entire normalized RNA expression count matrix was used as input. Mouse ortholog hallmark gene sets and ontology gene sets from the MSigDB database were used for the analysis. The number of permutations was set to 1,000, and the permutation type was set to gene_set. The enrichment statistic used was weighted, with Signal2Noise selected as the metric for ranking genes. All other parameters were set to the default settings of the GSEA V.4.2.3 software. Chromatin immunoprecipitation Cells were seeded in 15 cm dishes, and the experiment was performed when the cells reached 70–90% confluency. In the following experiments, we used SimpleChIP Plus Enzymatic Chromatin IP Kit (Cell Signaling Technology, Cat. 9005s) and carried out the protocol according to the manufacturer’s manual. Briefly, cells were crosslinked with 1% formaldehyde for 10 min at room temperature and then treated with glycine for 5 min to terminate crosslinking. Cells were washed two times with ice-cold PBS, harvested in PBS containing protease inhibitors, and pelleted by centrifugation at 2,000×g for 5 min at 4°C. Cell nuclei were lysed in membrane extraction buffer for 10 min, followed by centrifugation at 2,000×g to collect the nuclei. Nuclei were resuspended in 100 µL of digestion buffer and digested with micrococcal nuclease at 37°C for 20 min. Digestion was stopped with 0.5 M EDTA, and nuclei were pelleted at 16,000×g for 1 min, resuspended in 100 µL chromatin immunoprecipitation (ChIP) buffer, and sonicated (three 20 s pulses at 20 W for 4×10^6 cells) to disrupt the nuclear membrane. After centrifugation at 9,400×g for 10 min, the supernatant containing digested chromatin was collected and quantified. Approximately 10 µg of digested, crosslinked chromatin was used for each immunoprecipitation. Chromatin was incubated overnight at 4°C with rotation with ChIP-grade rabbit primary antibodies (anti-EP300, Cell Signaling Technology, Cat. 57625; anti-CREBBP, Cell Signaling Technology, Cat. 7389) or an equal amount of normal rabbit IgG (Cell Signaling Technology, Cat. 2729) as a control. The next day, 30 µL of ChIP-grade protein G magnetic beads were added and incubated for 2 hours at 4°C with rotation. The beads were then sequentially washed three times with low-salt buffer and once with high-salt buffer, resuspended in 150 µL of 1×ChIP elution buffer, and incubated for 30 min with gentle vortexing. Protein-DNA crosslinks were reversed using 5 M NaCl and proteinase K. Chromatin elution from magnetic beads and DNA purification after immunoprecipitation were performed according to the operating manual of SimpleChIP Plus Enzymatic Chromatin IP Kit (Cell Signaling Technology, Cat. 9005s). The obtained chromatin was subjected to ChIP-quantitative PCR (qPCR) experiments or ChIP-sequencing (ChIP-seq) analysis. For each qPCR assay, triplicate samples were used, and data were normalized to the corresponding input sample. ChIP-qPCR primers used for the assays are listed in [88]online supplemental table 7. For ChIP-seq, the KAPA HyperPlus kit (KAPA Biosystems, Cat. KK8514) was used according to the manufacturer’s protocol. The libraries were then sequenced by 2×150 bp paired-end sequencing on an Illumina NovaSeq 6000. Data analysis was performed using CLC Genomics Workbench 12 according to the ChIP-seq analysis manual ([89]https://resources.qiagenbioinformatics.com/manuals/clcgenomicswork bench/750/index.php?manual=ChIP_Seq_Analysis.html). Enzyme-linked immunospot assay This experiment was mainly carried out according to the manufacturer’s instructions for the IFN-γ ELISpot Detection Kit (BD Biosciences, Cat.551881). Briefly, tumor tissues were harvested from mice euthanized by CO[2] inhalation and minced in serum-free RPMI 1640 medium. The tissue fragments were then digested in serum-free DMEM containing DNase I (Sigma, Cat. 260913–10 MU) and Liberase TL (2 µg/mL, Roche, Cat. 05401020001) at 37°C for 30 min. The resulting cell suspensions were filtered through a 70 µm cell strainer (Thermo Fisher Scientific) and centrifuged at 1,500 rpm for 5 min. Red blood cells were lysed using red blood cell lysis buffer (TIANGEN, Cat. RT122-02), and the remaining cells were washed two times with PBS and resuspended in RPMI 1640 complete medium supplemented with 10% FBS and 1% penicillin/streptomycin. After determining cell concentration using an automated cell counter (Thermo Fisher), an equal number of cells (5×10^5 to 2×10^6 per well) from each sample were seeded into ELISpot plates pre-coated with anti-IFN-γ capture antibody and incubated at 37°C in a CO[2] incubator for 16–18 hours. After incubation, the culture medium was discarded, and 200 µL ddH[2]O was added to each well to lyse the cells, repeated three times. Plates were then incubated with anti-IFN-γ detection antibody at room temperature for 2 hours. After three washes with phosphate-buffered saline with Tween 20 (PBST), HRP-conjugated secondary antibody was added and incubated for another 2 hours at room temperature in the dark. Following three additional PBST washes, 100 µL AEC substrate solution was added for color development. Once red spots appeared, the substrate was discarded, and the wells were washed two to three times with ddH[2]O. Plates were air-dried, and red spots were visualized using the CTL ImmunoSpot S6 Analyzer (LLC, Ohio, USA). Spot numbers were quantified using ImageJ software. ELISA IFN-β released in cell supernatant was detected with Verikine Mouse IFN-β ELISA kit (PBL, Cat. 42400) according to the manufacturer’s protocol. Data were obtained from the SpectraMax device (Molecular Devices). Dual-luciferase reporter assay The promoter fragments of Socs1 of different lengths were cloned into the luciferase reporter vector pGL4.0 (Addgene, 84924), and the EP300 coding DNA sequence was cloned into dCAS9-VP64-GFP (Addgene, 611422). 293 T cells were seeded in 24-well plates (1×10^5 cells per well), and cultured overnight in a CO[2] cell incubator at 37°C. The next day, pGL4-Socs1 promoter, Renilla luciferase plasmid, and Ep300 plasmid or empty plasmid were co-transfected into cells using Lipofectamine 3000 (Invitrogen, Cat. L3000-015). After 24 hours, firefly luciferase and Renilla luciferase activities were detected using a dual luciferase reporter system (Promega, Cat. E1910), and the ratio of firefly luciferase/Renilla luciferase activity was calculated. Type I IFN expression luciferase assay Type I IFN was detected using L929-ISRE reporter cell line (a gift from Jiang Zhengfan laboratory, Peking University).[90]^29 1×10^5 L929-ISRE cells were plated per well in a 48-well cell plate overnight. The next day, the cell culture medium was replaced with cancer cell supernatant. L929-ISRE cells were treated with the cancer cell supernatant for 4 hours in a 37°C 5% CO[2] cell culture incubator. Cell lysis and luciferase activity were then measured according to the instructions of the luciferase assay kit (Promega, Cat. E1500). TIMER V.2.0 analysis The Gene mode in the Immune Association module of the TIMER V.2.0 website ([91]http://timer.cistrome.org/) was selected to query the infiltration of immune cells, including CD8^+ T cells, CD4^+ T cells, B cells, macrophages, dendritic cells (DCs), and natural killer (NK) cells, based on the gene expression of EP300. Statistics Statistical analyses were performed with GraphPad Prism V.7 or V.9 software. Data are presented as the mean±SD or mean± SEM of at least three parallel experiments. Data with a normal distribution were analyzed by one-way analysis of variance (ANOVA) or unpaired two-tailed Student’s t-tests, and tumor growth curves were compared by the Mann-Whitney U test or two-way ANOVA. P values are indicated as *p<0.05, **p<0.01, ***p<0.001, ns means no significant difference. Data availability The raw sequence data reported in this paper have been deposited in the Genome Sequence Archive[92]^30 in National Genomics Data Center,[93]^30 31 China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences (GSA: CRA018984) that are publicly accessible at [94]https://ngdc.cncb.ac.cn/gsa. Results Immune-dependent mechanisms are responsible for the reduced tumor growth of Ep300-deficient cancer cells In the process of investigating the molecular mechanisms responsible for regulating the tumor microenvironment (TME) through aberrant gene expression in cancer cells, we collected histological samples from patients with lung adenocarcinoma (n=77), including paired cancerous and benign tissues. The staining results showed that EP300 was highly expressed in cancerous tissues compared with benign tissues ([95]figure 1A). Additionally, an independent investigation of patients with cancer by The Human Protein Atlas[96]^32 reported that EP300 is upregulated to varying degrees in the majority of human solid tumors ([97]online supplemental figure 1A). To further explore the relationship between EP300 expression levels and immune infiltration, we used TIMER V.2.0 to analyze the The Cancer Genome Atlas (TCGA) database. The results showed that in most tumors, the expression of EP300 was negatively correlated with the infiltration of various immune cells, such as CD8^+ T cells, Th1 cells, DCs, and NK cells, but it was positively correlated with Treg cells ([98]online supplemental figure 1B). These results suggest that EP300 may play a role in modulating immune cell infiltration. Figure 1. Genetic deletion of Ep300 in cancer cells inhibits tumor growth and improves survival in immunocompetent but non-immunodeficient mice. (A) Expression of EP300 determined by immunohistochemical in cancerous and benign tissue of lung adenocarcinoma. (B) Western blot analysis of EP300 in TC-1 and MCA205. (C) Tumor growth curves for C57BL/6N mice inoculated with WT or Ep300^−/− TC-1 cancer cells (n=5). (D) Tumor growth curves for C57BL/6N mice inoculated with WT or Ep300^−/− MCA205 cancer cells (n=5). (E) Kaplan-Meier survival curves for C57BL/6N mice injected with WT or Ep300^−/− TC-1 cancer cells (n=5). (F) Kaplan-Meier survival curves for C57BL/6N mice injected with WT or Ep300^−/− MCA205 cancer cells (n=5). (G) Schematic representation of the mouse tumor vaccination experiment. (H) Tumor growth curves of WT TC-1 tumors in mice pre-injected with Ep300^−/− TC-1 cells (n=5). (I) Tumor growth curves of WT MCA205 tumors in mice pre-injected with Ep300^−/− MCA205 cells (n=5). (J) Tumor growth curves for nude mice inoculated with WT or Ep300^−/− TC-1 cancer cells (n=5). (K) Kaplan-Meier survival curves for nude mice injected with WT or Ep300^−/− TC-1 cancer cells (n=5). (L) Tumor growth curves for nude mice inoculated with WT or Ep300^−/− MCA205 cancer cells (n=5). (M) Kaplan-Meier survival curves for nude mice injected with WT or Ep300^−/− MCA205 cancer cells (n=5). (N) Tumor growth for C57BL/6N mice bearing WT or Ep300^−/− TC-1 tumors, treated with 200 µg/mouse rat IgG or anti-CD8 antibodies on days −1, 1, and 3 (n=5). (O) Tumor growth for C57BL/6N mice bearing WT or Ep300^−/− MCA205 tumors, treated with 200 µg/mouse rat IgG or anti-CD8 antibodies on days −1, 1, and 3 (n=5). Data are representative of three independent experiments and presented as mean±SEM. Statistical comparisons were performed using unpaired Student’s t-test (A), Mann-Whitney U test (C, D, H, I, J, L, N and O), and log-rank test (E, F, K and M). ns, not significant, *p<0.05, **p<0.01, ***p<0.001. Ep300, E1A binding protein p300; TF, tumor-free; WT, wild-type. [99]Figure 1 [100]Open in a new tab To determine the functional effects of EP300 in cancer cells, we used CRISPR-Cas9 technology to establish Ep300-deficient (Ep300^−/−) cancer cell lines in TC-1 and MCA205 cells. WT cells transfected with an empty vector were used as controls ([101]figure 1B). Compared with WT cancer cells, Ep300 deficiency did not exert a discernible effect on cancer cell proliferation in culture ([102]onlinesupplemental figure 2A[103]B). However, under the same concentration of MTX treatment, Ep300^−/− cancer cells exhibited a higher percentage of apoptosis ([104]onlinesupplemental figure 2C[105]D), suggesting that Ep300^−/− cancer cells may be more sensitive to chemotherapeutic drugs. To assess the functional effect of Ep300 knockout on tumor phenotypes in vivo, WT and Ep300^−/− TC-1 or MCA205 cell lines were inoculated in parallel into syngeneic and immunodeficient mice. We first assessed tumor growth using s.c. inoculation. In immunocompetent (C57BL/6N) mice, tumors appeared in all mice on day 7 post s.c. inoculation. As time progressed, all mice bearing WT TC-1 or MCA205 cells developed significant tumor masses after transplantation, while tumors with Ep300^−/− TC-1 or MCA205 cells began to shrink at days 7–9 ([106]figure 1C,D). We then used tail vein injection (intravenously) to establish a lung metastasis model for survival analysis. The results showed that, compared with mice injected with WT TC-1 or MCA205 cancer cells, the survival of mice injected with Ep300^−/− TC-1 or MCA205 cancer cells was significantly extended ([107]figure 1E,F). Given that Ep300-deficient tumors were cleared in some immunocompetent mice, this clearance may induce antitumor immune memory in the host, thereby potentially triggering tumor-preventive immunity. To test this hypothesis, we re-challenged the right flank of tumor-free mice with WT cancer cells 30 days after the initial s.c. inoculation of Ep300-deficient cancer cells in the left flank ([108]figure 1G). Interestingly, mice pre-injected with Ep300^−/− TC-1 cancer cells effectively rejected tumorigenesis induced by WT TC-1 cancer cells ([109]figure 1H). Similar results were observed in MCA205 tumors ([110]figure 1I). These observations suggest that animals pre-injected with Ep300^−/− cancer cells established immunological memory that effectively protected the host against subsequent challenges with corresponding WT cancer cells. To initially explore the possibility that the immune system is involved in controlling Ep300^−/− tumor growth in vivo, we analyzed changes in tumor growth and survival rates in nude mice which have defective T-cell function. In immunodeficient (nude) mice, the results showed that both WT TC-1 and Ep300-deficient TC-1 cancer cells developed tumors of similar size in all transplanted mice ([111]figure 1J). In lung metastasis experiments, all nude mice injected with either WT TC-1 or Ep300^−/− TC-1 cancer cells died within 30 days post-inoculation ([112]figure 1K). A similar phenomenon was observed in MCA205 cancer cells ([113]figure 1L,M). To exclude sex-related differences, we also performed the experiment using male mice. WT and Ep300^−/− TC-1, as well as WT and Ep300^−/− MCA205 cancer cells, were s.c. transplanted into the backs of male C57BL/6N mice. The results showed that tumor growth of Ep300-deficient TC-1 and MCA205 cells was inhibited compared with their respective WT counterparts ([114]onlinesupplemental figure 3A[115]B). However, in male nude mice, both TC-1 and MCA205 tumors lacking EP300 were able to resume growth ([116]onlinesupplemental figure 3C[117]D). These results were consistent with those obtained in female mice. Since Ep300^−/− cancer cells can develop tumors in nude mice, which lack mature T cells, and CD8^+ T cells are the primary cell type responsible for tumor suppression, we next analyzed the role of CD8^+ T cells in controlling Ep300^−/− tumor growth in vivo. CD8 neutralizing antibody was injected via the tail vein to deplete CD8^+ T cells in mice, and flow cytometry confirmed the effective depletion of these cells ([118]online supplemental figure 3E). Following CD8^+ T-cell depletion in C57BL/6N mice, Ep300^−/− cancer cells rapidly developed tumors, suggesting that the loss of CD8^+ T-cell function significantly reversed the tumor growth-inhibitory effect caused by Ep300 deletion ([119]figure 1N,O). Collectively, these data demonstrate that tumors derived from Ep300-deficient cancer cells are strongly inhibited in immunocompetent mice but not in nude mice. Since nude mice are immunocompromised due to their lack of mature T cells, these findings suggest the involvement of the adaptive immune system. Ep300 deficiency in cancer cells triggers cellular immune responses in vivo To further evaluate the possibility that Ep300 deficiency causes tumor regression and triggers adaptive immune responses, we subjected WT and Ep300^−/− TC-1 tumor tissue samples to transcriptome analysis by RNA-seq. GSEA was used to enrich the gene sets that were upregulated after Ep300 knockout in hallmark gene sets and ontology gene sets, respectively. Ontology gene set enrichment results showed that “response to interferon beta,” “cell killing,” “adaptive immune response,” and other related gene sets were significantly upregulated in Ep300^−/− TC-1 tumor tissues ([120]figure 2A). The enrichment analysis of hallmark gene sets revealed significant upregulation of gene sets such as “interferon gamma response,” “interferon alpha response,” and “inflammatory response” in Ep300^−/− TC-1 tumors ([121]online supplemental figure 4A). Representative genes from the “adaptive immune response” gene set are shown in [122]figure 2B. According to gene function classification, RNA-seq data indicated that genes associated with the antigen presentation mechanism and CD8^+ T[eff] signaling were also significantly increased in Ep300^−/− TC-1 tumor tissues ([123]figure 2C). However, among gene sets downregulated in Ep300^−/− TC-1 tumors, we did not observe gene sets closely related to immunity ([124]onlinesupplemental figure 4B[125]C). These results indicate that EP300 expressed in cancer cells might play an important role in modulating the host’s adaptive immune response to cancer cells. Figure 2. Ep300 deficiency triggers cellular immune response in vivo. (A–G) Tumor tissue analysis of WT or Ep300^−/− TC-1 tumors at day 11 after subcutaneous implantation. (A) GSEA of the top 10 ontology gene sets enriched in Ep300^−/− TC-1 tumors. (B) Heatmap for the adaptive immune response gene set in WT and Ep300^−/− TC-1 cells. (C) Heatmap for core biological pathways in WT and Ep300^−/− TC-1 cells. (D) ELISpot assay of IFN-γ secretion in WT and Ep300^−/− TC-1 tumors (n=3). (E) Representative immunofluorescence (IF) images and quantification of CD8 T cells in primary s.c. tumors formed by WT and Ep300^−/− TC-1 cells (n=3). The percentage of CD8 T cells in each image was statistically analyzed using ImageJ. Each mouse was randomly photographed in at least three fields of view for analysis. Scale bar, 50 µm. (F) Flow cytometric analysis of the frequency of CD45^+ cells, CD45^+CD3^+ T cells, CD45^+CD3^+CD4^+ T cells, and CD45^+CD3^+CD8^+ T cells infiltrating WT and Ep300^−/− TC-1 tumors from C57BL/6N mice. n=4 mice for WT groups, n=5 mice for Ep300^−/− groups. (G) Flow cytometric analysis of the frequency of IFN^+, GZMB^+ expressing CD8 T cells infiltrating WT and Ep300^−/− TC-1 tumors from C57BL/6N mice. n=4 mice for WT groups, n=5 mice for Ep300^−/− groups. The gating strategy used to analyze immune cells in tumor tissue in (F) and (G) is shown in [126]online supplemental figure 11A. (H and I) Tumor tissue analysis of WT or Ep300^−/− MCA205 tumors at day 10 after subcutaneous (s.c.) implantation. (H) Representative IF images and quantification of CD8 T cells in primary s.c. tumors formed by WT and Ep300^−/− MCA205 cells (n=3). The percentage of CD8 T cells in each image was statistically analyzed using ImageJ. Each mouse was randomly photographed in at least three fields of view for analysis. Scale bar, 50 µm. (I) ELISpot assay of IFN-γ secretion in WT and Ep300^−/− MCA205 tumors (n=3). Data are representative of three independent experiments and presented as mean±SD. Statistical comparisons were performed using unpaired Student’s t-test (D–I). ns, not significant, *p<0.05, **p<0.01, ***p<0.001. Ep300, E1A binding protein p300; ELISpot, enzyme-linked immunospot; GSEA, Gene Set Enrichment Analysis; GZMB, granzyme B; IFN, interferon; Treg, regulatory T cell; WT, wild-type. [127]Figure 2 [128]Open in a new tab ELISpot experiments revealed that Ep300^−/− TC-1 tumor tissues had more IFN-γ-secreting cells ([129]figure 2D). Immunofluorescence analysis showed that Ep300^−/− TC-1 tumors exhibited greater CD8^+ T-cell infiltration compared with WT TC-1 tumors ([130]figure 2E). The proportion of T cells in tumor tissues was further analyzed by flow cytometry. The percentages of infiltrating CD45^+ and CD3^+ cells were similar between WT TC-1 and Ep300^−/− TC-1 tumors, whereas Ep300^−/− tumors displayed a higher proportion of CD8^+ T-cell infiltration and a lower proportion of CD4^+ T-cell infiltration ([131]figure 2F). Notably, a greater fraction of CD8^+ T cells in Ep300^−/− TC-1 tumors expressed activation markers such as IFN-γ and GZMB ([132]figure 2G), suggesting enhanced infiltration of cytotoxic CD8^+ T cells. Conversely, the percentage of CD4^+ T cells was relatively reduced in Ep300^−/− TC-1 tumors ([133]figure 2F). Further characterization of CD4^+ T cells revealed increased expression of IFN-γ and decreased expression of CD25 and Foxp3 in Ep300^−/− TC-1 tumor tissues ([134]figure 2G), indicating an increased proportion of Th1 cells and a significant reduction in immunosuppressive Treg cells. Similarly, in Ep300-deficient MCA205 tumor tissues, increased CD8^+ T-cell infiltration ([135]figure 2H) and elevated numbers of IFN-γ-secreting cells ([136]figure 2I) were observed. Collectively, these data indicate that increased infiltration and activation of CD8^+ T cells in the TME may underlie the enhanced antitumor immunity associated with Ep300-deficient cancer cells. Ep300 deficiency leads to the activation of type I interferon response Although we observed that specifically deleting Ep300 in cancer cells reshaped the tumor immune microenvironment and increased the infiltration and activation of CD8^+ T cells in tumor tissues, the underlying mechanism at the cellular level remained unclear. To further explore this mechanism, we performed RNA-seq analysis on WT TC-1 and Ep300^−/− TC-1 cancer cells. GO analysis of the genes upregulated in Ep300^−/− TC-1 cells revealed enrichment of pathways such as “cellular response to interferon-beta” and “immune system process” ([137]figure 3A). GSEA pathway enrichment analysis identified the “response to type I interferon” pathway as significantly upregulated ([138]figure 3B), and multiple interferon-stimulated genes (ISGs), including Stat1, Stat2 and Isg15, were upregulated in Ep300^−/− TC-1 cells compared with WT TC-1 cells ([139]figure 3C). We then performed RT-qPCR to measure messenger RNA (mRNA) levels of representative ISGs, such as Ifnb1, Stat1, Stat2, Isg15, Ifi204, Mx1, Mx2, Irf7 and Irf9, in Ep300^−/− and WT TC-1 cells. The results showed significant upregulation of these ISGs in Ep300^−/− TC-1 cells relative to WT TC-1 cells ([140]figure 3D). Similarly, in MCA205 cells, the expression levels of these ISGs in Ep300^−/− MCA205 cells were also significantly higher than those in WT MCA205 cells ([141]figure 3E). Figure 3. Ep300 deficiency activates type I interferon pathway. (A) GO analysis reveals pathway alterations in Ep300^−/− TC-1 cancer cells. (B) Ep300^−/− TC-1 cancer cells upregulated response to type I interferon gene set in Gene Set Enrichment Analysis. (C) Heatmap for the response to type I interferon gene set in WT and Ep300^−/− TC-1 cells. (D) RT-qPCR analysis of the mRNA expression levels of Ifnb1, Stat1, Stat2, Isg15, Ifi204, Mx1, Mx2, Irf7, and Irf9 in WT and Ep300^−/− TC-1 cancer cells (n=3). β-actin was used as a loading control. (E) RT-qPCR analysis of the mRNA expression levels of Ifnb1, Stat1, Stat2, Isg15, Ifi204, Mx1, Mx2, Irf7, and Irf9 in WT and Ep300^−/− MCA205 cells (n=3). β-actin was used as a loading control. (F) L929-ISRE reporter cells were used to detect type I interferon in the supernatants of WT TC-1, Ep300^−/− TC-1, WT MCA205 and Ep300^−/− MCA205 cancer cells (n=3). The concentration of type I interferon is proportional to the luciferase activity. (G) ELISA experiment was used to detect the secretion of IFN-β in the supernatant of WT TC-1, Ep300^−/− TC-1, WT MCA205 and Ep300^−/− MCA205 cancer cells (n=3). (H) Western blot analysis of total and phosphorylated STAT1 in WT, Ep300^−/− TC-1 cancer cells (left) and in WT, Ep300^−/− MCA205 cancer cells (right). β-actin was used as a loading control. (I) Expression of phosphorylated STAT1 determined by immunohistochemical in cancerous and benign tissue of lung adenocarcinoma. Data are representative of three independent experiments and presented as mean±SD. Statistical comparisons were performed using unpaired Student’s t-test (D–G, and I). *p<0.05, **p<0.01, ***p<0.001. Ep300, E1A binding protein p300; FDR, false discovery rate; GO, Gene Ontology; IFN, interferon; IHC, immunohistochemical; ISG, interferon-stimulated gene; mRNA, messenger RNA; NES, normalized enrichment score; p-STAT1, phosphorylated STAT1; RT-qPCR, real-time quantitative reverse transcription polymerase chain reaction; STAT1, signal transducer and activator of transcription 1; WT, wild-type. [142]Figure 3 [143]Open in a new tab Importantly, we measured type I IFN levels in the supernatants of WT TC-1 and Ep300^−/− TC-1 cells using L929-ISRE reporter cells. L929-ISRE cells, which are L929 cells stably transfected with the interferon-stimulated response element (ISRE), can detect type I IFN in cell culture supernatants.[144]^29 The results indicated that the concentration of type I IFN in the supernatant of Ep300^−/− TC-1 cells was significantly higher than that of WT TC-1 cells ([145]figure 3F). A similar trend was observed in MCA205 cells ([146]figure 3F). ELISA assays further confirmed that IFN-β concentrations were higher in the supernatants of Ep300^−/− TC-1 and MCA205 cells compared with their WT counterparts ([147]figure 3G). In addition, western blot analysis demonstrated increased levels of total signal transducer and activator of transcription 1 (STAT1) and p-STAT1 in Ep300^−/− TC-1 and MCA205 cells relative to WT cells ([148]figure 3H). Since phosphorylation of STAT1 is a critical step in type I IFN signaling activation, these results collectively demonstrate that the type I IFN pathway is activated following Ep300 loss. Furthermore, we assessed p-STAT1 levels in cancerous and benign lung adenocarcinoma tissues from the samples used in [149]figure 1A. The results revealed that p-STAT1 expression was lower in cancerous tissues compared with benign tissues ([150]figure 3I). Together, these results also suggest that EP300 may affect the phosphorylation level of STAT1. MHC-I expression levels are upregulated in Ep300-deficient cancer cells The results above demonstrate that the type I IFN pathway is activated in cells following Ep300 deletion. Since type I IFN stimulates cells by binding to its receptors and transmitting signals through the JAK-STAT pathway, it induces the expression of a series of downstream molecules, including genes related to the MHC-I antigen presentation pathway.[151]^4 33 RNA-seq analysis revealed that the antigen presentation pathway was upregulated in Ep300^−/^− TC-1 cells ([152]figure 4A). The expression of multiple genes associated with MHC-I antigen presentation, such as H2-K1, H2-D1, Tap1, Tap2, and B2m, was significantly increased in Ep300^−/− TC-1 cells ([153]figure 4B). Western blot analysis showed that, compared with WT TC-1 and MCA205 cells, protein levels of B2M and TPN were elevated in Ep300^−/− TC-1 and MCA205 cells ([154]figure 4C–F). Flow cytometry results demonstrated that the surface of Ep300^−/− cells expressed higher levels of MHC-I molecules than WT cells ([155]figure 4G,H). IFN-γ is a cytokine known to effectively induce MHC class I expression. Therefore, we treated Ep300^−/− and WT cells in vitro with or without IFN-γ for 24 hours. MHC class I surface expression was elevated at baseline and further increased on IFN-γ stimulation in Ep300^−/− TC-1 and MCA205 cells, as measured by flow cytometry ([156]figure 4I,J). Figure 4. Upregulation of MHC class I in Ep300-deficient cancer cells. (A) KEGG analysis reveals pathway alterations in Ep300^−/− TC-1 cancer cells. (B) The heatmap showing differentially expressed genes related to the MHC-I pathway in WT TC-1 and Ep300^−/− TC-1 cancer cells. (C) Western blot analysis of B2M in WT TC-1 and Ep300^−/− TC-1 cancer cells. β-actin was used as a loading control. (D) Western blot analysis of TPN (TAPBP) in WT TC-1 and Ep300^−/− TC-1 cancer cells. β-actin was used as a loading control. (E) Western blot analysis of B2M in WT MCA205 and Ep300^−/− MCA205 cancer cells. GAPDH was used as a loading control. (F) Western blot analysis of TPN (TAPBP) in WT MCA205 and Ep300^−/− MCA205 cancer cells. β-actin was used as a loading control. (G) Cell-surface H2-Kb expression on WT TC-1 and Ep300^−/− TC-1 cancer cells (n=3). The quantified MFI is shown. (H) Cell-surface H2-Kb expression on WT MCA205 and Ep300^−/− MCA205 cancer cells (n=3). The quantified MFI is shown. (I) Cell-surface H2-Kb expression in WT TC-1 or Ep300^−/− TC-1 cancer cells with or without IFN-γ (20 ng/mL) treatment (n=3). The quantified MFI is shown. (J) Cell-surface H2-Kb expression in WT MCA205 or Ep300^−/− MCA205 cancer cells with or without IFN-γ (20 ng/mL) treatment (n=3). The quantified MFI is shown. (K) Cell-surface SIINFEKL:H2-Kb expression on WT-OVA TC-1 and Ep300^−/−-OVA TC-1 cancer cells (n=3). The quantified MFI is shown. (L) Cell-surface SIINFEKL:H2-Kb expression on WT-OVA MCA205 and Ep300^−/−-OVA MCA205 cancer cells (n=3). The quantified MFI is shown. (M) Flow cytometric analysis of apoptosis in WT-OVA MCA205 and Ep300^−/−-OVA MCA205 cancer cells (n=3). Co-culturing of OT-I CD8 T cells with WT-OVA MCA205 or Ep300^−/−-OVA MCA205 cancer cells. The effector-to-target (E:T) ratio is shown in the figure. (N) Flow cytometric analysis of apoptosis in WT-OVA TC-1 and Ep300^−/−-OVA TC-1 cancer cells (n=4). Co-culturing of OT-I CD8 T cells with WT-OVA TC-1 or Ep300^−/−-OVA TC-1 cancer cells. The E:T ratio is shown in the figure. The gating strategy adopted for (M) and (N) is shown in [157]online supplemental figure 11B. (O) Peptide pulsing assay schematic (Created in BioRender. Na, L. (2025) [158]https://BioRender.com/hl5ya0i). (P) Per cent remaining live target tumor cells following 48 hours incubation with OT-I T cells at the indicated E:T ratios. Data are representative of three independent experiments and presented as mean±SD. Statistical comparisons were performed using unpaired Student’s t-test. ns, not significant, *p<0.05, **p<0.01, ***p<0.001. Ep300, E1A binding protein p300; IFN, interferon; KEGG, Kyoto Encyclopedia of Genes and Genomes; MFI, mean fluorescence intensity; MHC, major histocompatibility complex class; OVA, ovalbumin; TCR, T-cell receptor; WT, wild-type. [159]Figure 4 [160]Open in a new tab Given the important role of PD-L1 expressed by cancer cells in tumor immune escape, we also examined changes in PD-L1 expression following Ep300 deletion. compared with WT TC-1 and MCA205 cells, PD-L1 expression was downregulated in Ep300-deficient cells ([161]onlinesupplemental figure 5A[162]C), consistent with previous reports.[163]^16 17 To further confirm the relationship between the upregulation of MHC-I expression caused by Ep300 deficiency and STAT1, we generated Ep300 and Stat1 double knockout cells by knocking out Stat1 in Ep300-deficient cells, resulting in Ep300^−/− Stat1^−/− TC-1 and MCA205 cells ([164]online supplemental figure 6A). Flow cytometry analysis of surface H2-Kb expression showed that, compared with WT cells, only Ep300 deficiency induced upregulation of MHC-I expression; however, the knockout of Stat1 in Ep300-deficient cells significantly reduced MHC-I expression, indicating that Stat1 deficiency reversed the upregulation of MHC-I expression caused by Ep300 loss ([165]onlinesupplemental figure 6B[166]C). Western blot analysis of B2M expression revealed similar results: B2M levels were increased only after Ep300 deletion, while additional Stat1 knockout reversed this upregulation ([167]online supplemental figure 6D). These findings indicate that the upregulation of MHC-I expression induced by Ep300 deficiency is closely dependent on STAT1. Downregulation of MHC-I expression is one of the primary mechanisms by which cancer cells evade recognition and killing by CD8^+ T cells.[168]^4 Therefore, following Ep300 deletion, the upregulation of MHC-I and related molecules on cancer cells may enhance recognition and killing by CD8^+ T cells. To test this hypothesis, we constructed OVA-overexpressing cells in both WT and Ep300^−/− backgrounds, namely WT-OVA TC-1, Ep300^−/−-OVA TC-1, WT-OVA MCA205, and Ep300^−/−-OVA MCA205 cells. In cells ectopically expressing OVA protein as an antigen, OVA is processed intracellularly into OVA[257-264] (SIINFEKL) peptides, which form specific MHC-I:peptide complexes (SIINFEKL: H2-Kb) via the MHC-I antigen processing and presentation pathway, and are presented on the cell surface. Accordingly, we detected these specific antigen peptide complexes (SIINFEKL:H2-Kb) on the cell surface. Flow cytometry analysis revealed that Ep300^−/−-OVA TC-1 cells exhibited higher levels of MHC-I antigen peptide complexes compared with WT-OVA TC-1 cells ([169]figure 4K), with a similar pattern observed in MCA205 cells ([170]figure 4L). Subsequently, in vitro killing assays were performed to evaluate the cytotoxic activity of effector CD8^+ T cells against cancer cells. OVA-overexpressing WT and Ep300^−/− cancer cells were co-cultured with OVA antigen-specific OT-I CD8^+ T cells after antigen stimulation, and apoptosis of cancer cells was assessed 16 hours later. Flow cytometry results demonstrated that, on co-culture with varying ratios of OT-I CD8^+ T cells, Ep300^−/−-OVA cells exhibited a significantly higher apoptosis rate than WT-OVA cells ([171]figure 4M,N). To further verify the functional impact of MHC-I expression levels, cells were pulsed with OVA peptide (SIINFEKL), which binds to MHC-I (H2-Kb) on the cell surface; unbound peptide was washed away, and pulsed cells were co-cultured with TCR transgenic OT-I T cells that specifically recognize H-2Kb-bound SIINFEKL peptide ([172]figure 4O). The results showed that pulsed WT MCA205 cells were more resistant to killing by antigen-specific T cells than pulsed Ep300^−/− MCA205 cells, as indicated by a higher number of viable cells remaining after 48 hours of co-incubation ([173]figure 4P). Collectively, these results indicate that loss of Ep300 leads to upregulation of MHC-I molecules in cancer cells, thereby enhancing their susceptibility to CD8^+ T cell-mediated killing. EP300 indirectly inhibits JAK-STAT pathway activation and MHC-I expression by promoting SOCS1 expression Since EP300 is a histone acetyltransferase, which is closely related to opening chromatin and promoting gene transcription,[174]^11 the upregulation of MHC-I and type I IFN pathways observed in Ep300^−/− cells may be indirectly regulated. EP300 may promote the expression of inhibitory molecules, thereby indirectly affecting the activation of the type I IFN pathway and MHC-I expression. RNA-seq analysis was performed to examine transcript level changes of major molecules potentially involved in negatively regulating type I IFN pathway activation, including Usp18, Pias family, and Socs family. The results showed that the expression of most Socs family members was decreased in Ep300^−/− TC-1 cells compared with WT TC-1 cells ([175]figure 5A). Among the SOCS family, SOCS1 primarily inhibits signaling stimulated by type I IFNs and IFN-γ by competitively binding to JAK in place of STAT1, thereby inhibiting downstream STAT1 phosphorylation and blocking signaling induced by type I IFN and IFN-γ.[176]^34 35 This suggests that SOCS1 may play a role in tumor growth regulation mediated by EP300. The mRNA levels of Socs1 in TC-1 and MCA205 cells were verified using RT-qPCR. The results showed that the mRNA levels of Socs1 were slightly downregulated in both Ep300^−/− TC-1 and MCA205 cells compared with WT TC-1 and MCA205 cells ([177]figure 5B). Western blot analysis further confirmed that SOCS1 protein expression was lower in Ep300^−/− TC-1 and MCA205 cells than in WT TC-1 and MCA205 cells ([178]figure 5C). Figure 5. EP300 indirectly inhibits JAK-STAT pathway activation and MHC-I expression by promoting SOCS1 expression. (A) The heatmap displays the mRNA levels of SOCS family, PIAS family, and Usp18 in WT TC-1 and Ep300^−/− TC-1 cancer cells. (B) RT-qPCR analysis of the mRNA expression levels of Socs1 in TC-1 (left) and MCA205 (right) cancer cells with or without Ep300 knockout (n=3). β-actin was used as a loading control. (C) Western blot analysis of SOCS1 in TC-1 (left) and MCA205 (right) cancer cells with or without Ep300 knockout. GAPDH was used as a loading control. (D) Western blot analysis of total and phosphorylated STAT1 in WT+vector, Ep300^−/−+vector, and Ep300^−/−-Socs1 OE TC-1 cancer cells. β-actin was used as a loading control. (E) Cell-surface H2-Kb expression on TC-1 cancer cells (n=3). The quantified MFI is shown. (F) Tumor growth for C57BL/6N mice bearing TC-1 cancer cells (n=5). (G) Enzyme-linked immunospot assay detection of IFN-γ secretion in tumor tissues 7 days after implantation of TC-1 tumors (n=5). (H) Western blot analysis of total and phosphorylated STAT1 in WT+vector, Ep300^−/−+vector, and Ep300^−/−-Socs1 OE MCA205 cancer cells. β-actin was used as a loading control. (I) Cell-surface H2-Kb expression on MCA205 cancer cells (n=3). The quantified MFI is shown. (J) Tumor growth for C57BL/6N mice bearing MCA205 cancer cells (n=5). (K and L) ChIP sequencing tracks EP300 signals at the genomic loci of the Socs1 gene. (M and N) ChIP-quantitative PCR analysis of EP300 signal in the Socs1 promoter region of TC-1(M) and MCA205 (N) cancer cells (n=3). The distance from the transcription start site is shown in the figure. (O) Effect of EP300 on PGL4.0-Socs1 promoter. The results are expressed as relative luciferase activity (ratio of the luciferase activities vs the corresponding Renilla activity, n=3). Data are representative of three independent experiments and presented as mean±SD (B, E, G, I, M, N, and O) or mean±SEM (F and J). Statistical comparisons were performed using unpaired Student’s t-test (B, E, G, I, M, N, and O) and Mann-Whitney U test (F and J). ns, not significant, *p<0.05, **p<0.01, ***p<0.001. ChIP, chromatin immunoprecipitation; Ep300, E1A binding protein p300; IFN, interferon; mRNA, messenger RNA; MFI, mean fluorescence intensity; OE, overexpress; p-STAT1, phosphorylated STAT1; RT-qPCR, real-time quantitative reverse transcription polymerase chain reaction; SOCS1, suppressor of cytokine signaling 1; STAT1, signal transducer and activator of transcription 1; WT, wild-type. [179]Figure 5 [180]Open in a new tab To further verify EP300’s regulatory effect on SOCS1, experiments were conducted in the human fibrosarcoma cell line HT-1080. Treatment with JQAD1 (a PROTAC that selectively targets EP300 for degradation via CRBN) resulted in decreased SOCS1 and PD-L1 expression, while the levels of B2M, HLA-A/B/C, and p-STAT1 were increased ([181]onlinesupplemental figure 7A[182]C). JQAD1 treatment also elevated HLA-A2 surface expression on HT-1080 cells ([183]online supplemental figure 7D). Similar results were observed in HT-1080 cells following Ep300 knockdown by siRNA, with a reduction in SOCS1 expression and increased levels of B2M and p-STAT1 ([184]onlinesupplemental figure 7E[185]G). To follow-up on these observations, Ep300^−/− TC-1 and MCA205 cancer cell lines were engineered to overexpress (OE) SOCS1 protein, generating Ep300^−/−-Socs1 OE TC-1 cells and Ep300^−/−-Socs1 OE MCA205 cells. Western blot analysis showed that, compared with Ep300^−/−+vector TC-1 cells, total STAT1 and p-STAT1 protein levels were reduced in Ep300^−/−-Socs1 OE TC-1 cells ([186]figure 5D). Additionally, flow cytometry analysis revealed that the expression level of MHC class I on the surface of Ep300^−/−-Socs1 OE TC-1 cells was significantly decreased compared with Ep300^−/−+vector TC-1 cells ([187]figure 5E). After transplantation into syngeneic immunocompetent mice, tumor growth was monitored and characterized. Compared with Ep300^−/−+vector TC-1 tumors, Ep300^−/−-Socs1 OE TC-1 tumors exhibited increased tumor size ([188]figure 5F) and a significant decrease in IFN-γ-secreting cells within the tumor tissues ([189]figure 5G). Similar results were observed following SOCS1 overexpression in Ep300^−/− MCA205 cells ([190]figure 5H–J). These results indicate that SOCS1 participates in tumor growth regulation mediated by EP300. Since SOCS1 is significantly downregulated at the mRNA level, not only at the protein level, this suggests that the reduction of SOCS1 in Ep300-deficient cells is not due to increased degradation but may be caused by changes at the transcriptional level. Therefore, we performed ChIP-seq experiments to investigate whether EP300 directly binds to the promoter region of Socs1 and promotes its transcription. ChIP-seq analysis showed that the signal of EP300 was enriched in the Socs1 promoter region ([191]figure 5K,L), and ChIP-qPCR further confirmed this result ([192]figure 5M,N). Subsequently, we constructed luciferase reporter plasmids containing the Socs1 promoter fragments spanning −1000 bp to +200 bp, −500 bp to +200 bp, and −300 bp to +200 bp, respectively, and performed dual-luciferase reporter assays in 293T cells to evaluate promoter activity. The results showed that EP300 significantly increased the activity of the Socs1 promoter plasmids in a dose-dependent manner, with relative luciferase activity increasing alongside EP300 plasmid concentrations ([193]figure 5O). Collectively, these results indicate that EP300 enhances Socs1 transcription by binding to its promoter region. Overall, these findings suggest that EP300 indirectly inhibits the JAK-STAT signaling pathway by promoting SOCS1 expression, thereby suppressing type I IFN pathway activation and MHC class I expression. CREBBP and EP300 share highly similar structures. Although both possess histone acetyltransferase activity and partially overlap in function, EP300 and CREBBP may play distinct roles in regulating certain molecules.[194]^9 Western blot results showed that following Ep300 knockout, CREBBP was upregulated in MCA205 cells, while no significant changes were observed in TC-1 cells ([195]online supplemental figure 8A). To investigate the effect of CREBBP on SOCS1, we knocked down CREBBP in MCA205 and TC-1 cells using siRNA ([196]online supplemental figure 8B). The results indicated that CREBBP knockdown did not reduce SOCS1 expression, nor did it lead to increased B2M expression ([197]online supplemental figure 8C), which contrasts with the effects observed after Ep300 deletion. Furthermore, we examined CREBBP binding to the Socs1 promoter in the presence or absence of EP300. The results demonstrated that when EP300 was present, CREBBP was significantly enriched at the region approximately −1.1 kb to the transcription start site of Socs1 ([198]onlinesupplemental figure 8D[199]E). CREBBP signals at +0.1 kb, −0.2 kb, and −0.3 kb were relatively weak, showing only onefold to twofold enrichment compared with IgG controls ([200]onlinesupplemental figure 8D[201]E). Although CREBBP signal at −1.1 kb was significantly increased after EP300 loss, there was no notable increase at +0.1 kb, −0.2 kb, or −0.3 kb ([202]onlinesupplemental figure 8D[203]E). In contrast, EP300 signals were significantly enriched at +0.1 kb, −0.2 kb, and −0.3 kb ([204]figure 5M,N), where CREBBP signals remained weak ([205]onlinesupplemental figure 8D[206]E). These results suggest distinct binding sites of EP300 and CREBBP on the Socs1 promoter, and that Ep300 loss does not alter CREBBP binding at these sites. Collectively, these findings indicate that EP300 and CREBBP differ in their regulation of SOCS1 expression, with EP300 potentially playing a more critical role. Reduced tumor growth of Socs1-deficient cancer cells in vivo in an immune-dependent manner Studies have shown that SOCS1 plays a crucial role in regulating DC antigen presentation and adaptive immunity, and silencing SOCS1 in antigen-presenting DCs can enhance antigen-specific antitumor immunity.[207]^36 In addition, sensory neurons fail to effectively express MHC-I in response to IFN-γ stimulation due to their constitutive high expression of SOCS1, and overexpression of SOCS1 in glial cells also suppresses IFN-γ-induced expression of MHC-I.[208]^37 These reports suggest that SOCS1 may directly or indirectly affect the expression of MHC-I. In the above results, we observed that the expression of MHC-I was upregulated in Ep300-deficient cancer cells, but overexpression of SOCS1 suppressed the expression of MHC-I. To further explore the regulatory role of SOCS1 on MHC-I, we constructed Socs1 knockout TC-1 and MCA205 cancer cells using CRISPR-Cas9 technology. WT TC-1 and Socs1^−/− TC-1 cells were subjected to transcriptome sequencing analysis, and gene sets upregulated in Socs1^−/− TC-1 cells were enriched by GSEA. The enrichment results of GSEA ontology gene sets showed that Socs1^−/− TC-1 cells mainly upregulated gene sets related to antigen presentation in the MHC-I pathway ([209]figure 6A). The top 10 upregulated GSEA ontology gene sets in Socs1^−/− TC-1 cells are shown ([210]figure 6A). The expression of several genes related to the MHC-I pathway, such as H2-K1, H2-D1, Tap1, and Tap2, was also increased ([211]figure 6B). Flow cytometry analysis showed that Socs1 deletion significantly upregulated the expression of MHC-I molecules on the cell surface ([212]figure 6C,D), and western blot analysis further showed that TPN and B2M protein levels were higher in Socs1-deficient cells than in WT cells ([213]figure 6E). Figure 6. SOCS1 regulates MHC-I expression in cancer cells and affects tumor growth. (A) Gene Set Enrichment Analysis revealed altered pathways following Socs1 deletion in TC-1 cancer cells. (B) The heatmap displays these MHC class I-related differentially expressed genes in WT TC-1 and Socs1^−/− TC-1 cancer cells. (C) Cell-surface H2-Kb expression on WT TC-1 and Socs1^−/− TC-1 cancer cells (n=3). The quantified MFI is shown. (D) Cell-surface H2-Kb expression on WT MCA205 and Socs1^−/− MCA205 cancer cells (n=3). The quantified MFI is shown. (E) Western blot analysis of TPN (TAPBP) and B2M in TC-1 (left) and MCA205 (right) cancer cells with or without Socs1 knockout. GAPDH was used as a loading control. (F) Tumor growth for C57BL/6N mice bearing WT TC-1 and Socs1^−/− TC-1 cancer cells (n=5). (G) Tumor growth for C57BL/6N mice bearing WT MCA205 and Socs1^−/− MCA205 cancer cells (n=5). (H) Tumor growth for nude mice bearing WT TC-1 and Socs1^−/− TC-1 cancer cells (n=5). (I) Flow cytometric analysis of the frequency of CD45^+CD3^+CD8^+ T-cell infiltration in WT and Socs1^−/− TC-1 tumors in C57BL/6N mice (n=5). The gating strategy used to analyze immune cells in tumor tissue in (I) is shown in [214]online supplemental figure 11A. (J) Enzyme-linked immunospot assay of IFN-γ secretion in WT and Socs1^−/− TC-1 tumors (n=5). Data are representative of three independent experiments and presented as mean±SD (C, D, I, and J) or mean±SEM (F–H). Statistical comparisons were performed using unpaired Student’s t-test (C, D, I, and J) and Mann-Whitney U test (F–H). *p<0.05, **p<0.01, ***p<0.001. Ep300, E1A binding protein p300; FDR, false discovery rate; IFN, interferon; MFI, mean fluorescence intensity; MHC, major histocompatibility complex class; SOCS1, suppressor of cytokine signaling 1; STAT1, signal transducer and activator of transcription 1; WT, wild-type. [215]Figure 6 [216]Open in a new tab We then s.c. implanted WT TC-1 and Socs1^−/− TC-1 cells into immunocompetent C57BL/6N mice and immunodeficient nude mice. Interestingly, tumor growth of Socs1^−/− TC-1 cells was significantly suppressed in C57BL/6N mice ([217]figure 6F). Similarly, the growth of Socs1-deficient MCA205 tumors was markedly inhibited in C57BL/6N mice ([218]figure 6G). In contrast, Socs1^−/− TC-1 cells rapidly formed tumors in nude mice lacking functional T cells ([219]figure 6H). Tumors from WT TC-1 and Socs1^−/− TC-1 cells implanted in C57BL/6N mice were harvested for flow cytometric analysis on day 7 post-implantation due to the rapid inhibition observed in Socs1^−/− tumors. Flow cytometry revealed a significant increase in CD8^+ T-cell infiltration in Socs1^−/− TC-1 tumor tissues compared with WT TC-1 tumor tissues ([220]figure 6I). Consistently, the ELISpot experiment confirmed that there were more IFN-γ-secreting cells in Socs1^−/− TC-1 tumor tissues ([221]figure 6J). To further investigate the role of SOCS1, we reintroduced SOCS1 expression into Socs1 knockout cells ([222]onlinesupplemental figure 9A[223]B). Restoration of SOCS1 led to decreased B2M expression ([224]onlinesupplemental figure 9C[225]D) and reduced cell surface H2-Kb levels ([226]onlinesupplemental figure 9E[227]F), as well as a rescue of tumor growth in vivo ([228]onlinesupplemental figure 9G[229]H). These data indicate that cancer cell-specific Socs1 deletion suppresses tumor growth in an immune system-dependent manner. Increased antitumor immunity induced by Ep300-deficient cancer cells is partially dependent on the type I interferon pathway To explore the impact of SOCS1 in cancer cells, we performed GSEA analysis of the upregulated and downregulated hallmark gene sets following Socs1 loss. The results showed that only the “interferon alpha response” and “interferon gamma response” gene sets were significantly upregulated after Socs1 deletion ([230]figure 7A). We then compared the upregulated GSEA hallmark gene sets in Ep300^−/− TC-1 cells and Socs1^−/− TC-1 cells. The analysis revealed that the “interferon alpha response” and “interferon gamma response” gene sets upregulated in Socs1^−/− TC-1 cells were also enriched in Ep300^−/− TC-1 cells ([231]figure 7B). Here we show some of the upregulated genes in the IFN alpha response and interferon gamma response gene sets in Socs1^−/− TC-1 cells ([232]figure 7C,D). RNA-seq analysis indicated that Stat1 expression was increased in Socs1^−/− TC-1 cells ([233]figure 7D). Consistently, western blot confirmed that both total and p-STAT1 levels were elevated in Socs1^−/− TC-1 and MCA205 cells compared with their respective WT TC-1 and MCA205 cells ([234]figure 7E). On reintroduction of SOCS1 expression into Socs1 knockout cells, total and p-STAT1 levels were reduced ([235]online supplemental figure 9I). These results indicate activation of the type I IFN pathway in Socs1-deficient cancer cells. Figure 7. Antitumor immunity induced by Ep300 deletion is partially dependent on activation of the type I interferon pathway. (A) GSEA analysis revealed altered hallmark gene sets following Socs1 deletion in TC-1 cancer cells. (B) GSEA analysis of upregulated hallmark gene sets in Ep300^−/− and Socs1^−/− TC-1 cancer cells. (C) Heatmap for the “interferon alpha response” gene set in WT and Socs1^−/− TC-1 cells. (D) Heatmap for the “interferon gamma response” gene set in WT and Socs1^−/− TC-1 cells. (E) Western blot analysis of total and phosphorylated STAT1 in WT, Socs1^−/− TC-1 (left) and MCA205 (right) cancer cells. β-actin was used as a loading control. (F) Tumor growth for C57BL/6N mice bearing WT, Ep300^−/− or Socs1^−/− TC-1 tumors, treated with 200 µg/mouse isotype or anti-IFNAR1 antibodies on days 1, 3, 5, 7, 9, and 11. n=5 mice for WT TC-1 and Socs1^−/− TC-1 group, n=8 mice for Ep300^−/− TC-1 group. Data are presented as the mean±SEM. (G) Comparison of WT, Ep300^−/− or Socs1^−/− TC-1 tumor sizes on day 16 after tumor bearing in mice treated with isotype or IFNAR1 antibodies. n=5 mice for WT TC-1 and Socs1^−/− TC-1 group, n=8 mice for Ep300^−/− TC-1 group. Data are presented as the mean±SD. (H) Tumor growth for C57BL/6N mice bearing TC-1 tumors, treated with JQAD1 (10 mg/kg) on days 6, 8, 10 and 12 (n=5). (I) Tumor growth for C57BL/6N mice bearing TC-1 tumors, treated with in vivo siEp300 or in vivo siNC (5 nM) on days 6, 8, 10, 12, 14 and 16 (n=5). (J) Proposed model of SOCS1 regulated by EP300 to affect antitumor immune response (Created in BioRender. Na, L. (2025) [236]https://BioRender.com/rc41gdw). Data are presented as mean±SD (G) or mean±SEM (F, H and I). Statistical comparisons were performed using unpaired Student’s t-test (G) and Mann-Whitney U test (H and I). ns, not significant, *p<0.05, **p<0.01, ***p<0.001. Ep300, E1A binding protein p300; GSEA, Gene Set Enrichment Analysis; IFN, interferon; MHC, major histocompatibility complex; SOCS1, suppressor of cytokine signaling 1; STAT1, signal transducer and activator of transcription 1; TCR, T-cell receptor; WT, wild-type. [237]Figure 7 [238]Open in a new tab To investigate the relationship between antitumor immunity related to the type I IFN pathway in Ep300^−/− and Socs1^−/− cancer cells, we implanted WT TC-1, Ep300^−/− TC-1, and Socs1^−/− TC-1 cancer cells into C57 mice, followed by treatment with either anti-IFNAR1 or isotype control antibodies. RNA-seq analysis showed that treatment with IFNAR1 antibodies effectively blocked the type I interferon pathway in Ep300^−/− TC-1 tumors ([239]onlinesupplemental figure 10A[240]C). After administration of IFNAR1 antibodies, the “response to interferon beta” and “interferon alpha response” pathways in tumor tissues were significantly downregulated ([241]onlinesupplemental figure 10A[242]B). The heatmap shows representative genes related to the significantly downregulated “response to interferon beta” pathway ([243]online supplemental figure 10C). We observed that IFNAR1 antibody blockade treatment significantly reversed the tumor growth inhibition induced by Ep300 or Socs1 deletion and rescued tumor growth ([244]figure 7F,G). Additionally, treatment with IFNAR1 antibody blockade rapidly restored the growth of Socs1^−/− TC-1 tumors, which was not significantly different from WT TC-1 tumors treated with IFNAR1 antibodies ([245]figure 7F,G). However, in Ep300^−/− TC-1 tumors, although IFNAR1 antibody treatment restored tumor growth, the tumor size remained significantly smaller than that of WT TC-1 tumors receiving the same treatment at the corresponding time point ([246]figure 7F,G). Since intravenous injection of anti-IFNAR1 also suppresses DCs and induces immunodeficiency, to further clarify the direct effect of blocking the type I IFN pathway on tumors, we administered anti-IFNAR1 i.t. After i.t. injection of anti-IFNAR1, the tumor size of Ep300^−/− TC-1 tumors was not significantly different from WT tumors, although their growth rate remained slightly slower than WT tumors ([247]online supplemental figure 10D). On euthanasia, tumors from each group were collected and weighed, revealing that Ep300^−/− TC-1 tumors treated with anti-IFNAR1 were significantly lighter than WT tumors ([248]online supplemental figure 10E). These results suggest that the antitumor immunity induced by Ep300 deletion in cancer cells is partially dependent on the type I IFN pathway. Targeted inhibition of EP300 in vivo suppresses tumor growth Our results indicate that inhibiting EP300 expression in cancer cells can effectively enhance antitumor immunity. These findings are primarily based on the targeted knockout of Ep300 in cancer cells; however, this strategy is difficult to implement in practice. Therefore, we further explored the effects of using inhibitors or other methods to treat tumor-bearing mice in vivo. Due to the high homology between EP300 and CREBBP, currently, no inhibitors specifically targeting EP300 are available. Through literature review, we found that JQAD1, developed by Durbin et al,[249]^18 is a CRBN-dependent PROTAC that can selectively degrade EP300 without affecting CREBBP. To investigate the feasibility of using drugs to target and inhibit or degrade EP300 for tumor treatment, we administered JQAD1 to tumor-bearing mice. The results showed that JQAD1 treatment significantly inhibited TC-1 tumor growth in immunocompetent C57BL/6N mice ([250]figure 7H). siRNA therapy is one of the potential approaches for targeted tumor therapy, enabling specific interference with target genes.[251]^38 Studies have shown that using siRNA to target various immunoregulatory ligands can promote tumor immunity.[252]^39 However, the susceptibility of siRNA to degradation in vivo limits its application. We designed siRNA targeting Ep300 and modified it to create an in vivo-optimized siRNA (siEp300) suitable for use in mice, using modified NC siRNA (siNC) as a control. Tumor-bearing mice were treated with both in vivo siNC and siEp300. The results indicated that, compared with in vivo siNC, treatment with in vivo siEp300 significantly inhibited TC-1 tumor growth ([253]figure 7I). These results suggest that targeting and inhibiting EP300 in vivo can also suppress tumor growth, highlighting the therapeutic potential of EP300-targeted strategies for tumors. Discussion The types of infiltrating immune cells in the TME have a significant impact on the treatment and prognosis of solid tumors.[254]^40 41 Numerous studies have confirmed that certain molecules expressed by cancer cells themselves can modulate the tumor immune microenvironment.[255]^4 6 42 43 Elucidating the specific functions of these molecules in antitumor immune processes is crucial for the development of effective immunotherapeutic strategies. In this study, we report a novel role of EP300 in cancer cells in suppressing antitumor immune responses. We demonstrated that EP300 in cancer cells inhibits STAT1 phosphorylation by promoting SOCS1 expression, thereby impairing the expression of antigen presentation-related genes and facilitating tumor immune escape ([256]figure 7J). These findings provide important evidence that EP300 expression in cancer cells can reshape the tumor immune microenvironment and attenuate host antitumor immunity. The role of EP300 in tumorigenesis is likely multifaceted. Some studies have shown that EP300 can enhance the functions of tumor suppressor proteins such as p53 and Rb1,[257]^9 44 supporting its function as a tumor suppressor gene. However, many other studies have shown that inhibiting or reducing the expression of EP300 can suppress tumor growth.[258]1821 45,[259]47 Despite the extensive research on EP300, few studies have explored its impact on antitumor immunity within TME. Our investigation revealed that Ep300-deficient cancer cells developed tumors only in immunodeficient mice but not in immunocompetent mice. This is similar to the phenomenon observed by Liu et al using the EP300 inhibitor C646.[260]^21 The extent of T-cell infiltration within the TME is closely associated with treatment outcomes and prognosis. High levels of CD8^+ T-cell infiltration are generally considered beneficial for tumor immunotherapy.[261]^5 48 49 In our study, Ep300 deletion in cancer cells significantly increased the infiltration of effector CD8^+ T cells into tumor tissues. Furthermore, depletion of CD8^+ T cells restored the growth of Ep300^−/− tumors in immunocompetent mice. These results suggest that the deletion of Ep300 in cancer cells can effectively enhance the host’s antitumor immune response, mainly through the adaptive immune response pathway. Although type I IFNs are well-known for their key role in antiviral immunity, numerous studies have also demonstrated that they play a critical role in antitumor immunity.[262]50,[263]52 For instance, type I IFNs enhance the antigen-presenting capacity of cancer cells and augment the antitumor functions of immune cells.[264]^51 In our study, we observed that the type I IFN signaling pathway was activated in Ep300-deficient cancer cells, resulting in the upregulation of multiple ISGs and increased phosphorylation levels of STAT1. Furthermore, we noted that total STAT1 protein levels were also upregulated in Ep300-deficient cancer cells, which might be attributed to the auto-regulatory feedback of STAT1, as STAT1 expression is known to increase in the context of its activation and phosphorylation.[265]53,[266]55 Dysregulation of MHC class I molecules is often associated with impaired immune surveillance and resistance to immunotherapy.[267]56,[268]58 STAT1 activation has been shown to effectively induce MHC-I gene expression in cancer cells.[269]59,[270]62 Cancer cells may evade CD8^+ T cell-mediated cytotoxicity by downregulating tumor-associated antigens.[271]^4 57 In subsequent experiments, we found that Ep300-deficient cancer cells exhibited elevated expression of MHC-I-related genes such as H2-Kb and B2M. Blocking the type I IFN pathway using an IFNAR1-neutralizing antibody significantly restored tumor growth in Ep300-deficient tumors. However, compared with WT and Socs1-deficient tumors, this inhibition did not fully rescue tumor growth, suggesting that the immune response enhancement caused by Ep300 loss is partially dependent on the type I IFN pathway. RNA-seq analysis further revealed that multiple immune-related signaling pathways were upregulated following Ep300 deletion. Moreover, EP300 has been reported to bind the PD-L1 promoter to promote its transcription and expression, thereby contributing to immune evasion.[272]^17 These results suggest that EP300 may regulate antitumor immunity not only via modulation of the type I IFN pathway but also through additional mechanisms that warrant further investigation. EP300 is a member of the histone acetyltransferase family and is closely associated with chromatin accessibility and the activation of gene transcription.[273]^11 Therefore, we investigated several potential molecules that may negatively regulate STAT1 phosphorylation. SOCS1 can competitively bind to JAK alongside STAT1, thereby inhibiting the phosphorylation of STAT1 and attenuating the signaling cascades activated by type I IFNs and IFN-γ.[274]^34 We found that EP300 can bind to the promoter region of Socs1, thereby enhancing its transcription and subsequent SOCS1 expression. CREBBP, a structural homolog of EP300, exhibits partially overlapping functions.[275]^9 Notably, inhibition of CREBBP did not significantly reduce SOCS1 expression, suggesting that EP300 may play a more dominant role in regulating Socs1 transcription compared with CREBBP. Overexpression of SOCS1 in Ep300-deficient cancer cells not only diminished STAT1 phosphorylation and MHC-I expression but also significantly reversed the in vivo tumor suppression induced by Ep300 loss. Conversely, genetic ablation of Socs1 in cancer cells resulted in immune-dependent tumor growth inhibition. At the cellular level, Socs1 knockout led to marked upregulation of genes involved in the MHC-I antigen presentation pathway, increased expression of type I IFN response-related genes, and increased expression of p-STAT1. Taken together, these findings suggest that EP300 facilitates the transcriptional activation of Socs1, thereby indirectly suppressing STAT1 phosphorylation and the expression of downstream genes associated with antigen presentation. Strategies such as PROTAC-mediated degradation and siRNA-mediated silencing have demonstrated significant therapeutic potential. In our study, we found that in vivo administration of both the EP300-targeting PROTAC JQAD1 and EP300-specific in vivo siRNA effectively inhibited tumor growth, underscoring the potential of EP300-targeted approaches in cancer therapy. Although our investigation primarily focused on the role of EP300 within cancer cells, it is noteworthy that EP300 is also expressed in various immune cell populations within the TME, where it may exert diverse, cell type-specific functions. EP300 has been shown to play multiple and context-dependent roles across distinct immune subsets in the TME, including Tregs, myeloid-derived suppressor cells (MDSCs), CD8^+ cytotoxic T lymphocytes, and tumor-associated macrophages. For instance, EP300 promotes the acetylation of FOXP3 in Tregs, thereby enhancing their immunosuppressive activity within the TME.[276]^21 In MDSCs, inhibition of the bromodomain activity of EP300 has been reported to reprogram these cells toward a pro-inflammatory phenotype, thus strengthening antitumor immunity.[277]^63 In contrast, in CD8^+ T cells, EP300 supports metabolic reprogramming by upregulating bromodomain PHD finger transcription factor (BPTF) and sustaining glycolytic activity, both of which are essential for their cytotoxic function.[278]^64 These findings suggest that systemic inhibition of EP300 may yield cell type-specific outcomes, potentially enhancing antitumor immunity by impairing immunosuppressive populations such as Tregs and MDSCs, while posing a risk of dampening effector T-cell function under certain conditions. Therefore, future therapeutic strategies targeting EP300 may benefit from approaches that enable cell type-specific modulation of EP300 activity, thereby maximizing therapeutic efficacy while minimizing unintended immunological consequences. In summary, our findings demonstrate that EP300 suppresses type I IFN and IFN-γ signaling pathways by promoting SOCS1 expression, thereby facilitating immune evasion in cancer. Ep300 deletion enhances CD8^+ T-cell infiltration into the TME and suppresses tumor growth. This work suggests that targeted inhibition of EP300 in cancer cells may represent a promising therapeutic strategy to boost antitumor immunity. Supplementary material online supplemental table 1 [279]jitc-13-10-s001.docx^ (29.8KB, docx) DOI: 10.1136/jitc-2025-011488 online supplemental figure [280]jitc-13-10-s002.docx^ (26.3KB, docx) DOI: 10.1136/jitc-2025-011488 online supplemental file 2 [281]jitc-13-10-s003.pdf^ (583.8KB, pdf) DOI: 10.1136/jitc-2025-011488 online supplemental file 3 [282]jitc-13-10-s004.pdf^ (840.3KB, pdf) DOI: 10.1136/jitc-2025-011488 online supplemental file 4 [283]jitc-13-10-s005.pdf^ (491.1KB, pdf) DOI: 10.1136/jitc-2025-011488 online supplemental file 5 [284]jitc-13-10-s006.pdf^ (471.2KB, pdf) DOI: 10.1136/jitc-2025-011488 online supplemental file 6 [285]jitc-13-10-s007.pdf^ (607.2KB, pdf) DOI: 10.1136/jitc-2025-011488 online supplemental file 7 [286]jitc-13-10-s008.pdf^ (1MB, pdf) DOI: 10.1136/jitc-2025-011488 online supplemental file 8 [287]jitc-13-10-s009.pdf^ (768.2KB, pdf) DOI: 10.1136/jitc-2025-011488 online supplemental file 9 [288]jitc-13-10-s010.pdf^ (1.1MB, pdf) DOI: 10.1136/jitc-2025-011488 online supplemental file 10 [289]jitc-13-10-s011.pdf^ (688KB, pdf) DOI: 10.1136/jitc-2025-011488 online supplemental file 11 [290]jitc-13-10-s012.pdf^ (564.8KB, pdf) DOI: 10.1136/jitc-2025-011488 online supplemental file 12 [291]jitc-13-10-s013.pdf^ (1MB, pdf) DOI: 10.1136/jitc-2025-011488 Acknowledgements