A novel proteolysis-targeting chimera strategy targeting multiple immune checkpoints containing ITIMs enhances antitumor immunity

Abstract

Immune checkpoint inhibitors (ICIs) have significantly advanced and revolutionized cancer treatment over the past decade; however, their clinical benefits have been limited to a subset of cancer patients. While ICI-based combinations have emerged as promising strategies, they risk broader toxicities and significant cost burdens. This highlights the critical need for the development of inhibitors that target multiple immune checkpoints. In this study, we developed a peptide that emulates the conserved sequence of the Src homology 2 domain-containing protein tyrosine phosphatase 2 (SHP2) C-terminal Src homology 2 (C-SH2) domain, which is capable of binding to immunoreceptor tyrosine-based inhibitory motifs (ITIMs) in the cytoplasmic tails of multiple immune inhibitory receptors. By utilizing this peptide as the protein of interest (POI) ligand and coupling it with the von Hippel‒Lindau (VHL) ligand via a peptide linker, a proteolytic targeting chimera (PROTAC) named PROTAC of ITIM-targeting inhibitory peptide (PITIP) was constructed. PITIP effectively induced the degradation of multiple immune inhibitory receptors in a proteasome-dependent manner, thereby attenuating immunosuppressive signaling within T cells, natural killer (NK) cells, and macrophages. In vivo investigations demonstrated that PITIP elicited a robust antitumor immune response in xenograft and allograft tumor model mice, including those resistant to αPD-1 therapy. Moreover, the encapsulation of PITIP within liposomes conjugated with anti-CD45 antibodies enhanced the targeting of immune cells by PITIP, thereby improving the therapeutic efficacy of the antibodies. This study reports, for the first time, a universal strategy targeting the common structural motifs of immunosuppressive receptors, which facilitates broader and more extensive immune activation through the ubiquitination-mediated degradation of multiple immune checkpoints.

Graphical abstract

Highlights

• •PITIP increased CD8⁺ T cell and NK cell activation and cytotoxicity.
• •PITIP reprogrammed macrophages to polarize towards an antitumor phenotype.
• •PITIP elicited antitumor immune response in various mouse xenograft tumor models.
• •PITIP induced antitumor immune responses in anti-PD-1-resistant tumor models.
• •PITIP offered a new strategy for overcoming the limitations of current ICI therapies.

1. Introduction

Ipilimumab, a monoclonal antibody targeting cytotoxic T lymphocyte-associated antigen 4 (CTLA4), was first approved for metastatic melanoma over a decade ago. Since its introduction, more than eight immune checkpoint inhibitors (ICIs) and 35 ICI-based combination therapies have been approved, demonstrating remarkable clinical efficacy across various cancer types [1]. Despite the survival advantage of ICI-based therapies, only a small percentage of patients achieve long-lasting responses owing to significant variation in ICI effectiveness among patients [2,3]. Single immune checkpoint therapies often fail to effectively control tumor growth, as tumor cells frequently exploit multiple inhibitory pathways to evade immune detection and clearance [4,5]. ICI combination therapies may enhance therapeutic efficacy; for example, the combination of tiragolumab with atezolizumab achieves a 37% objective response rate (ORR), surpassing that of either monotherapy alone (21% and 24% response rates, respectively) [6]. In another study on non-small cell lung cancer (NSCLC) treatment, a 31.3% ORR was observed in the tiragolumab plus atezolizumab group, whereas a 16.2% ORR was reported in the placebo plus atezolizumab group [7]. However, compared with monotherapy, the combined use of ICIs may lead to more pronounced side effects [8]. Moreover, the financial burden associated with combination therapies can be substantial, raising concerns about accessibility and affordability for patients. To address these challenges, researchers are investigating therapies that target multiple immune inhibitory receptors [9].

Inhibitory immune receptors are a class of molecules that play crucial roles in modulating immune responses by transmitting inhibitory signals. Over the past few decades, numerous inhibitory immune receptors, including but not limited to programmed cell death protein 1 (PD-1), T-cell immunoreceptor with Ig and ITIM domains (TIGIT), natural killer group 2A (NKG2A) and B and T lymphocyte attenuator (BTLA), have been identified and studied in the context of cancer. These receptors are referred to as “immune checkpoints”, as they function as gatekeepers of immune responses and are characterized by the presence of immunoreceptor tyrosine-based inhibitory motifs (ITIMs) in their intracellular domains [10]. After the activation of inhibitory receptors, the tyrosine residue within the ITIM becomes phosphorylated, which serves as a docking site for SH2 domain-containing phosphatases. Following the phosphorylation of phosphatases, including sequence of the phosphatase-1/2 (SHP1/2) and SH2-domain-containing inositol 5-phosphatase (SHIP), the resulting dephosphorylation of adjacent stimulatory pathway signaling intermediates, in turn, leads to the suppression of immune cell activation and proliferation [11]. Therefore, the development of ITIM-targeted degraders holds promise for degrading multiple immune inhibitory receptors containing this domain, thereby restoring phosphatase-mediated immune suppression. To achieve the simultaneous targeting and degradation of multiple immune checkpoints, we constructed an ITIM-targeting proteolytic targeting chimera (PROTAC). A PROTAC is a bifunctional molecule consisting of a ligand that binds to the protein of interest (POI), a linker, and a ligand that recruits an E3 ubiquitin ligase. This design allows PROTACs to hijack the ubiquitin-proteasome system, leading to the selective degradation of the target protein through the formation of a ternary complex. We developed a mimetic peptide comprising the TAT sequence at the N-terminus and the SH2 ITIM binding region of Src homology 2 domain-containing protein tyrosine phosphatase 2 (SHP2) at the C-terminus, which demonstrates versatility in binding to various immune checkpoint molecules. By employing this peptide as the POI ligand and coupling it with ligands for the high-efficiency von Hippel-Lindau (VHL) E3 ligases via a peptide-based linker, we constructed a PROTAC named PROTAC of ITIM-targeting inhibitory peptide (PITIP). In this study, we report that PITIP can specifically bind to various immune checkpoint molecules, promoting their ubiquitination and degradation, thereby exerting an antitumor effect on multiple immune cells and reshaping the tumor immune microenvironment. This may serve as a universal strategy to target a group of immunosuppressive receptors that contain the ITIM domain and provide a novel strategy for designing PROTAC-based drugs that target the common structural motifs of multiple targets in the future.

2. Materials and methods

2.1. Mice

C57BL/6J mice used in this study were sourced from the Animal Center of the Fourth Military Medical University, ensuring a reliable and standardized experimental model. NOD-Prkdc^em26IL2rg^em26/Gpt (NCG) mice were acquired from Jiangsu GemPharmatech (Nanjing, China), providing another genetically defined background for the experiments. All experimental mice were bred and maintained in an environment that met specific pathogen-free standards. The selected subjects for the experiments were female mice aged six to eight weeks. These mice were kept in controlled conditions featuring a 12-h light/dark cycle, with ambient temperatures maintained between 18 and 23 °C and relative humidity levels ranging from 40% to 60%. Ethical considerations were paramount throughout the study. All animal experiments conducted were thoroughly reviewed and received approval from the Animal Experiment Administration Committee of the Fourth Military Medical University (Approval number: IACUC-20220505). This approval underscores the commitment to ethical and humane treatment of the animals involved in the research. The treatment studies were carried out with randomization in the design to eliminate bias, and injections were administered by investigators who were blind to the specific experimental conditions, further ensuring the integrity of the research outcomes.

2.2. Cell lines, isolation and culture

THP-1, HCT116, Hepa1-6, MC38, Jurkat, Raji, HepG2 and NK92 cell lines were obtained from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). All cell lines were authenticated by short tandem repeat (STR) profiling and tested for mycoplasma contamination before use. Human peripheral blood mononuclear cells (PBMCs) were isolated from healthy donors' blood samples using Ficoll-Hypaque density gradient centrifugation. This study was approved by the Ethics Committee of the First Affiliated Hospital of the Air Force Medical University (Approval number: KY20212473-C-1) and was conducted in accordance with the Declaration of Helsinki. Informed consent was obtained from all the involved patients.

CD8⁺ T lymphocytes were further purified from PBMCs using magnetic-activated cell sorting (MACS) according to the manufacturer's instructions (CD8⁺ T lymphocytes: 130-045-201; Miltenyi Biotec, Bergisch Gladbach, Germany). Purified CD8⁺ T lymphocytes were cultured in the presence of plate-bound anti-CD3 (5 μg/mL, clone HIT3a; Biolegend, San Diego, CA, USA) with anti-CD28 (2 μg/mL, clone QA17A32; Biolegend, San Diego, CA, USA). NK cells were further purified from PBMCs using MACS according to the manufacturer's instructions (NK: 130-092-657; Miltenyi Biotec, Bergisch Gladbach, Germany). Purified NK cells were cultured in the presence of Interleukin-2 (IL2, 20 U/mL, AF-200-02; PeproTech, Cranbury, NJ, USA) and interleukin-12 (IL12, 20 ng/mL, 200-12; PeproTech, Cranbury, NJ, USA) to drive their proliferation and survival. Monocyte-derived macrophages (MDMs) were generated by culturing purified CD14⁺ monocytes (130-050-201; Miltenyi Biotec, Bergisch Gladbach, Germany) with recombinant human M-CSF (50 ng/mL; PeproTech) for 7 days.

Cells were maintained in RPMI-1640 medium or Dulbecco's modified Eagle's medium (DMEM; Gibco, Grand Island, NY, USA) supplemented with 10% heat-inactivated fetal bovine serum (FBS; Gibco, Grand Island, NY, USA) and 1% penicillin-streptomycin (100 U/mL penicillin and 100 μg/mL streptomycin; Cyagen Biosciences, Suzhou, China) at 37 °C in a humidified atmosphere containing 5% CO₂. Cell culture media were refreshed every 2–3 days.

2.3. Flow cytometry

Antibodies were from BD Biosciences (San Jose, CA, USA), eBioscience (San Diego, CA, USA), Proteintech (Rosemont, IL, USA), Biolegend (San Diego, CA, USA) or Invitrogen (Carlsbad, CA, USA). For human cells, we used anti-CD45 (clone HI30; BD Biosciences, San Jose, CA, USA), anti-CD3 (OKT3; Biolegend, San Diego, CA, USA), anti-CD56 (CMSSB; eBioscience, San Diego, CA, USA), anti-CD8 (RPA-T8; Biolegend, San Diego, CA, USA), anti-PD-1 (J110; Biolegend, San Diego, CA, USA), anti-IL10 (JES3-9D7; BD Biosciences, San Jose, CA, USA), anti-CD107a (eBIOH4A3; eBioscience, San Diego, CA, USA), anti-CD206 (15-2; eBioscience, San Diego, CA, USA), anti-CD11b (IRF44; Biolegend, San Diego, CA, USA), anti-granzyme B (GB11; eBioscience, San Diego, CA, USA), and anti-CD69 (FN50; Proteintech, Rosemont, IL, USA). Mouse cells were stained with anti-CD45 (30-F11; Biolegend, San Diego, CA, USA), anti-CD3 (17A2; Biolegend, San Diego, CA, USA), anti-F4/80 (BMg; Biolegend, San Diego, CA, USA), anti-CD86 (GL1; eBioscience, San Diego, CA, USA), anti-CD206 (MR6F3; eBioscience, San Diego, CA, USA), anti-CD8 (53-6.7; eBioscience, San Diego, CA, USA), anti-NK1.1 (PK136; Biolegend, San Diego, CA, USA), anti-perforin (eBIoOMAK-D; eBioscience, San Diego, CA, USA), and anti-Ki67 (16A8; Biolegend, San Diego, CA, USA). In order to evaluate surface staining, the cells were first incubated with specific antibodies for a duration of 30 min. Following this incubation period, the cells underwent washing to remove unbound antibodies, and subsequently, they were fixed using a Fix/Perm solution provided by BD Biosciences (San Jose, CA, USA). For the purpose of conducting intracellular staining, a permeabilization buffer from BD Biosciences (San Jose, CA, USA) was utilized to allow access for the antibodies into the cells. After this treatment, the cells were stained with appropriate antibodies designed for intracellular targets. Finally, all samples were analyzed using a CytoFLEX flow cytometer from Beckman Coulter Life Sciences (Brea, CA, USA), and the resulting data were processed with FlowJo software to facilitate comprehensive analysis.

2.4. Measurement of T cell proliferation

CD8⁺ T cells were labeled using 2 μM carboxyfluorescein succinimidyl ester (CFSE; ThermoFisher, Waltham, MA, USA) to facilitate subsequent cellular analysis. After this labeling process, the CD8⁺ T cells were then seeded into a 12-well plate and placed in an incubator at 37 °C with a 5% CO₂ atmosphere. This incubation period lasted for a duration of seven days, allowing the cells to proliferate under controlled conditions. Following this incubation phase, the cells were stained with anti-CD8 antibodies, which are essential for identifying the CD8⁺ T cells. The stained cells were subsequently analyzed using flow cytometry, a powerful technique that enables detailed examination of cellular characteristics. The proliferation of the T cells was assessed by calculating the percentage of cells that exhibited a reduction in the CFSE signal when compared to an untreated control group, thereby providing a quantitative measure of the cells' proliferative response.

2.5. Tumor models and treatments

Hepa1-6 (5 × 10⁶), MC38 (5 × 10⁶) or HepG2 (1 × 10⁶) cells were implanted into the flanks of 6- to 8-week-old female C57BL/6 mice or NCG mice. The length and width of the tumors were measured starting on day 5 or 7 and every other day thereafter. Tumor size was measured by caliper, and tumor volume was calculated with the formula (length × width²)/2. Treatment was initiated when tumors reached 100 mm³ in size. Mice in the PITIP/ITIM-targeting inhibitory peptide (ITIP) treatment group received intraperitoneal (i.p.) injections of 250 μg/kg every other day, while the positive control group received an αPD-1 monoclonal antibody (clone RMP1-14, Bio X Cell, Lebanon, NH, USA) at 6250 μg/kg i.p. every two days.

2.6. Cytokine array

Mouse cytokine array (ARY006, R&D systems, Minneapolis, MN, USA) was conducted with centrifuge clotted blood samples. Sample serum (200 μL) was prepared with appropriate buffers. Reconstituted biotinylated detection antibody cocktail (15 μL) was incubated with samples for 1 h at room temperature. Nitrocellulose membranes pre-blocked with array buffer 6 were then incubated with the sample-antibody mixture overnight at 2–8 °C with rocking. After three 10-min washes in 1 × wash buffer, membranes were incubated with streptavidin-HRP (30 min, at room temperature), washed again, and developed with freshly mixed chemiluminescent reagent (1 mL) for 1 min before X-ray film exposure. Signal intensities were quantified using densitometry after aligning spots via a transparency overlay, with background subtraction using phosphate-buffered saline (PBS) control spots.

2.7. Phagocytosis

For macrophage phagocytosis assays, green fluorescent protein (GFP)-expressing HCT116 cells were then co-cultured with the activated macrophages in the presence or absence of PITIP (100 nM) at a ratio of 3:1 (tumor cells:macrophages) for 2 h, and phagocytosis was detected by laser confocal.

2.8. Immunoblotting

Cells were subjected to lysis using cell lysis buffer (Beyotime, Shanghai, China) for Western blot assay and immunoprecipitation (IP), which included a cocktail of protease inhibitors (Roche, Basel, Switzerland) and a cocktail of phosphatase inhibitors (Roche, Basel, Switzerland). The protein concentrations were measured utilizing the enhanced BCA protein assay kit (Beyotime, Shanghai, China). Following this, the cell lysates were heated for 5 min and then underwent separation prior to Western blot analysis, where the primary antibodies utilized included anti-SHP2 (Proteintech, Rosemont, IL, USA), anti-phosphorylated-SHP2 (Invitrogen, Carlsbad, CA, USA), anti-glyceraldehyde-3-phosphate dehydrogenase (GAPDH; Proteintech, Rosemont, IL, USA), anti-ERK (CST, Danvers, MA, USA), anti-phosphorylated-ERK (CST, Danvers, MA, USA), anti-AKT (Proteintech, Rosemont, IL, USA), anti-phosphorylated-AKT (Proteintech, Rosemont, IL, USA), anti-ZAP70 (Proteintech, Rosemont, IL, USA), anti-phosphorylated-ZAP70 (R&D, Minneapolis, MN, USA), anti-SYK (R&D, Minneapolis, MN, USA), anti-phosphorylated-SYK (R&D, Minneapolis, MN, USA), anti-PD-1 (Proteintech, Rosemont, IL, USA), anti-SIRPα (Abcam, Cambridge, UK), and anti-NKG2A (Abcam, Cambridge, UK). For secondary antibodies, HRP-conjugated anti-rabbit and anti-mouse antibodies (Proteintech, Rosemont, IL, USA) were employed.

2.9. Co-immunoprecipitation (Co-IP) analysis

After treatments (PBS control or PITIP stimulation), collections of CD8⁺ T lymphocytes, NK cells, and MDMs were obtained. The cells were lysed using WB/IP lysis buffer (Beyotime, Shanghai, China) that was enhanced with a protease inhibitor cocktail (Roche, Basel, Switzerland) and a phosphatase inhibitor cocktail (Roche, Basel, Switzerland) for a duration of 30 min. An aliquot of the cell lysates was set aside to serve as the input control. The remaining portion of the lysates was incubated with anti-VHL antibody (MCE, Monmouth Junction, NJ, USA) overnight at 4 °C, with gentle rotation. Protein A-agarose beads (Proteintech, Rosemont, IL, USA) were pre-washed three times with WB/IP buffer before being added to the antibody-lysate mixture. Immunoprecipitation was conducted for 4 h at 4 °C with gentle rotation. Centrifugation was used to collect the immune complexes, after which the beads were washed. The elution of the immunoprecipitated proteins was achieved by boiling in 2 × loading buffer (Beyotime, Shanghai, China) for 5 min at 95 °C. Both the input and immunoprecipitated samples were subsequently analyzed using Western blotting as described.

2.10. Confocal microscopy

MDMs were directly seeded onto glass-bottom confocal dishes, while activated T lymphocytes and NK cells required dishes pre-coated with poly-L-lysine hydrobromide (PLL; 0.01%; Sigma-Aldrich, St. Louis, MO, USA) overnight at 37 °C in a humidified atmosphere containing 5% CO₂. For colocalization studies, cells were treated with fluorescein isothiocyanate (FITC)-labeled PITIP for 1 h at 37 °C, followed by fixation with 4% paraformaldehyde in PBS for 5 min and nuclear staining with 4′,6-diamidino-2-phenylindole (DAPI; 1 μg/mL) for 1 min, and blocked with 3% bovine serum albumin (BSA) in PBS for 30 min. Cells were then incubated overnight at 4 °C with primary antibodies against PD-1, BTLA, NKG2A, or SIRP-α (Abcam, Cambridge, UK), followed by 1-h incubation with corresponding secondary antibodies (goat anti-rabbit PE and goat anti-rat cy3, Proteintech, Rosemont, IL, USA). Fluorescence images were acquired using a Nikon A1HD25 confocal microscope (Nikon, Tokyo, Japan). Image processing and colocalization analysis were performed using NIS-Elements software.

2.11. Surface plasmon resonance (SPR) analysis

The analysis of the binding kinetics between PITIP and VHL protein was conducted utilizing a Biacore T200 system from Cytiva (Marlborough, MA, USA). To initiate the process, CM5 sensor chips underwent activation through 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC)/N-hydroxysuccinimide (NHS), allowing for the effective immobilization of the ligand via amine coupling in a 10 mM sodium acetate buffer solution. The binding analyses were performed employing a multi-cycle kinetics approach at a controlled temperature of 25 °C, using 4-(2-hydroxyethyl) piperazine-1-ethanesulfonic acid (HEPES) buffered saline with ethylenediaminetetraacetic acid (EDTA) and polysorbate 20 (HBS-EP⁺) as the running buffer. This buffer comprised 10 mM HEPES at pH 7.4, 150 mM sodium chloride (NaCl), 3 mM EDTA, and a 0.05% concentration of surfactant P20, facilitating optimal conditions for the experiment. During the experimental setup, the analyte concentration was methodically serially diluted at a ratio of 5-fold and subsequently injected at a flow rate of 10 μL/min. The analyses monitored both the association and dissociation phases for durations of 180 and 300 s, respectively, to capture the dynamics of the interaction thoroughly. Importantly, the sensor surface was regenerated between each cycle using a 1.5 M glycine-HCl solution at pH 2.5, ensuring that the binding measurements remained accurate across multiple iterations. To derive the binding kinetics parameters—specifically the association rate constant (K_a), dissociation rate constant (K_d), and the equilibrium dissociation constant (K_D)—a 1:1 Langmuir binding model was utilized. This fitting process was carried out using the Biacore T200 Evaluation Software, with the quality of the fits critically evaluated through chi-square values and residual plots to ensure reliable results. Notably, all experimental conditions were rigorously replicated, with each experiment performed in triplicate to bolster the statistical validity of the data obtained.

2.12. CD45 antibody conjugation

A phospholipid stock solution is prepared by dissolving 1–2 mg in 50 μL of dissolution solution. Separately, 1 mg of antibody/protein is dissolved in 1 mL of reaction buffer. The conjugation is performed by dropwise addition of 50 μL phospholipid stock into the protein solution, followed by incubation at room temperature for 2 h with gentle mixing. After the reaction, the reaction solution was transfer to an ultrafiltration tube, and centrifuged at 9500 rpm at 4 °C to remove all solvents through ultrafiltration, and washed twice with pure water to remove unreacted phospholipid. The conjugate was stored at 4 °C.

2.13. Statistical analysis

Prism software (GraphPad software Inc) was used for statistical analysis. Data are presented as scatter plots with bars (means ± standard error of the mean (SEM)). statistical significance was determined using unpaired, two-tailed Student's t-test for comparing two groups, one-way analysis of variance (ANOVA) with Dunnett's multiple comparisons test for comparing more than two groups, and two-way ANOVA for comparing more than two groups with two or more time points. ^∗P < 0.05; ^∗∗P < 0.01; ^∗∗∗P < 0.001; ^∗∗∗∗P < 0.0001 and ns, not significant.

3. Results

3.1. PITIP degrades multiple immunosuppressive receptors through the ubiquitination pathway

To develop a PROTAC that targets the ITIM present in multiple immune checkpoints, we utilized the 13-amino acid sequence (VRESQSHPGDFVL) within the C-terminal Src homology 2 (C-SH2) domain of SHP2, which is critical for binding to the ITIM, as the POI ligand. This 13-amino acid peptide, under the guidance of TAT, can enter T cells, NK cells, and macrophages and bind to programmed cell death protein 1 (PD-1), natural killer group 2A (NKG2A) and signal-regulatory protein α (SIRP-α) expressed on the cell membranes of each respective cell type (Figs. S1A and B). The seven amino acid sequence ALAP(OH)YIP corresponding to the region around Pro564 of hypoxia-inducible factor 1-alpha (HIF-1α) was exploited as the VHL E3 ligand [12]. Given that the length of the linker significantly impacts the activity of PROTACs, we designed and synthesized three peptide PROTACs with three different linker lengths: Y35 (GS linker), Y37 (GSGS linker) and Y39 (GSGSGS linker) (Figs. S1C–H). The binding of these peptides to VHL sequences was investigated using SPR. The results indicated that Y39 exhibited the strongest affinity (Figs. S1I–K). Consistent with these findings, Western blot experiments revealed that Y39 had the greatest ability to degrade three immune checkpoints, PD-1, NKG2A and SIRP-α (Figs. S1L–N). This finding suggests that six amino acids is the optimal length for the linker. Consequently, Y39 (named PITIP) was selected for further investigation, and its structural diagram and sequence are shown in Fig. 1A. The binding of PITIP to VHL and ITIM was simulated by the molecular operating environment (MOE). Molecular docking analysis revealed that PITIP can form stable complexes with the phosphorylated ITIMs of PD-1 with binding sites that are identical or similar to those between SHP2 and ITIM. Similarly, PITIP exhibits high-affinity binding with VHL, which is analogous to the binding of ALAP(OH)YIP to SHP2 (Fig. 1B). Moreover, laser confocal experiments revealed that PITIP could colocalize with PD-1 and BTLA on T cells (Fig. 1C). ITIM sequences are present in the cytoplasmic tail of multiple immune inhibitory receptors. The formation of a ternary complex by a PROTAC is a necessary step in discriminating between substrate proteins; therefore, the affinities of these interactions are highly indicative of cellular outcomes [13]. We experimentally confirmed that PITIP could form ternary complexes (Fig. 1D) with the VHL E3 ubiquitin ligase and either PD-1 or BTLA in T cells. As expected, laser confocal microscopy (Fig. 1E) and Western blot (Fig. 1F) show that PITIP reduced the protein levels in different cells. PD-1 and BTLA at different concentrations in T cells, as well as NKG2A and PD-1 in NK cells, and SIRP-α and PD-1 in macrophages were further validated through laser confocal microscopy and Western blot. Notably, the degradation of proteins was attenuated in the presence of the proteasome inhibitor MG132. These results demonstrate that PITIP increases the ubiquitination of immune inhibitory receptors while decreasing their ubiquitination in the presence of a protease inhibitor (Figs. 1F and G). In addition, PITIP can also colocalize with NKG2A and PD-1in NK cells, and colocalize with SIRP-α and PD-1 in macrophages, as shown by laser confocal microscopy (Fig. 1C). The same ternary complex patterns were experimentally confirmed with the VHL E3 ubiquitin ligase and NKG2A or PD-1 in NK cells and with SIRP-α or PD-1 in macrophages (Fig. 1D). The protein levels of NKG2A and PD-1 in NK cells and of SIRP-α and PD-1 in macrophages were reduced by PITIP (Fig. 1F). To further evaluate the broad-spectrum impact of PITIP on receptor expression, we performed flow cytometry analyses targeting a range of common ITIM-containing receptors (e.g., CD33, KIR family members, Siglecs and LAIR1). Flow cytometric analysis demonstrated a statistically significant reduction in the expression of all ITIM-containing receptors examined, compared to control groups (Fig. S2A). In contrast, receptor molecules lacking ITIM motifs, such as IGF-1R, TLR8, NKG2D, GM-CSFR, CD3, and CD16, exhibited no marked change in expression when exposed to PITIP (Fig. S2B). These findings indicate that PITIP selectively degrades ITIM-bearing receptors while sparing those lacking the ITIM motif.

Fig. 1.

Proteolytic targeting chimera (PROTAC) of immunoreceptor tyrosine-based inhibitory motif (ITIM)-targeting inhibitory peptide (PITIP) degrades multiple immunosuppressive receptors through the ubiquitination pathway. (A) Schematic representation of PITIP. C-terminal Src homology 2 domain (C-SH2) domain of Src homology 2 domain-containing protein tyrosine phosphatase 2 (SHP2) was fused to the human immunodeficiency virus trans-activator of transcription (HIV-TAT) cell-penetrating sequence, which linked von Hippel-Lindau (VHL)-ligand via GSGSGS. (B) Docking models show VHL interactions with hypoxia-inducible factor 1-alpha (HIF1α) and PITIP, SHP2 interactions with programmed cell death protein 1 (PD-1) phospho-ITIM, and PITIP interactions with PD-1 phospho-ITIM. Models were generated using molecular operating environment (MOE) software, with PITIP shown in blue stick representation and ITIM motifs in orange stick representation. (C) Confocal microscopy analysis of PITIP colocalization with immune checkpoint receptors. PITIP with PD-1 and B and T lymphocyte attenuator (BTLA) in human derived CD8⁺ T lymphocytes, with signal-regulatory protein α (SIRP-α) and PD-1 in monocyte-derived macrophages, and with natural killer group 2A (NKG2A) and PD-1 in human derived natural killer (NK) cells. PITIP was visualized in green, checkpoint receptors in red, and nuclei were counterstained with 4′,6-diamidino-2-phenylindole (DAPI; blue). (D) Coimmunoprecipitation analysis of PITIP interactions with immune checkpoint receptors and VHL in distinct immune cell populations: PD-1 and BTLA in T cells, NKG2A and PD-1 in NK cells, and SIRP-α and PD-1 in macrophages. (E) Confocal microscopy analysis of PITIP-mediated degradation of immune checkpoint receptors. Different immune cells were treated with PITIP at different time points: CD8⁺ T lymphocytes (human-derived) were tested for PD-1 and BTLA, NK cells (human-derived) for NKG2A and PD-1, and macrophages for SIRP-α and PD-1. Checkpoint receptors were visualized in red, and nuclei were counterstained with DAPI (blue). (F) Western blot (WB) analysis of the immune checkpoint receptors degradation in different immune cells treated with different doses of PITIP (with or without 5 μΜ carbobenzoxy-Leu-Leu-leucinal (MG132)) for 24 h. Expression levels normalized to the levels of glyceraldehyde-3-phosphate dehydrogenase (GAPDH). (G) PD-1, NKG2A, and SIRP-α poly ubiquitination detected by anti-ubiquitin antibody (anti-Ub) immunoblotting in different cells were treated with PITIP (with or without MG132). Data or images are representative of three independent experiments. ^∗P < 0.05; ^∗∗P < 0.01; ^∗∗∗P < 0.001; NS, not significant. IgG: immunoglobulin G; WCL: whole cell lysate.

3.2. PITIP increases the antitumor activity of multiple immune cells by inhibiting SHP2 activation

To evaluate whether PITIP can increase immune cell activity following the degradation of immune inhibitory receptors, we examined the phosphorylation of the phosphatases. The results are encouraging. PITIP led to a significant reduction in SHP2 phosphorylation in T cells, as well as SHP1 and SHIP (Figs. 2A and S3), accompanied by an increase in the expression of the activation signaling molecules extracellular signal-regulated kinase (ERK) and Ak strain transforming (AKT) (Fig. 2A). These findings provide preliminary evidence that PITIP can activate T cells. Further analysis using flow cytometry revealed that PITIP upregulated the expression of the activation marker CD69 and the proliferation marker Ki67 while decreasing the expression of the apoptosis marker cleaved caspase-3 (Fig. 2B). Consistent with these results, the CFSE assay confirmed that PITIP promotes T-cell division. Additionally, the real-time cell analysis (RTCA) results indicated that PITIP stimulation increases the cytotoxic activity of T cells against tumor cells (Fig. 2C). To evaluate the influence of PITIP on immune cell migratory capacity, transwell migration assays were performed. The results demonstrated that PITIP significantly enhanced the migration of T cells (Fig. S4). Similar phenomena were observed in NK cells, where PITIP reduced SHP2, SHP1 and SHIP phosphorylation and increased the activation of the signaling molecules SYK and ZAP70 (Figs. 2D and S5). PITIP treatment exhibited no significant effect on the proliferation of NK cells, as measured by CFSE assays (Fig. S6A). However, PITIP significantly reduced the expression of apoptosis-associated molecules within NK cells (Fig. S6B). Transwell migration assays demonstrated that PITIP also enhanced the migration of NK cells (Fig. S6C). PITIP increased the expression of the activation marker CD69 and the degranulation-associated marker CD107a, as well as the cytotoxic molecules perforin and granzyme B, in NK cells (Fig. 2E). Additionally, flow cytometry confirmed that NK cells exhibited increased cytotoxic activity in the presence of PITIP (Fig. 2F). Similarly, PITIP reduced SHP2, SHP1 and SHIP phosphorylation in macrophages and upregulated the expression of the activation signaling molecules SYK and AKT (Figs. 2G and S7). Flow cytometry analysis revealed that PITIP increased the expression of the proinflammatory macrophage-associated molecules CD86 and iNOS while decreasing the expression of the tumor-promoting macrophage-associated molecules CD206 and IL10 (Fig. 2H). Additionally, macrophages stimulated with PITIP exhibited enhanced phagocytic ability, as demonstrated by laser confocal microscopy assays (Fig. 2I). Assessment of PITIP on macrophages revealed no alteration in proliferation capacity as quantified by CFSE dilution assays (Fig. S8A). Conversely, PITIP significantly suppressed intracellular expression of key apoptosis-associated molecules cleaved caspase-3 in these cells (Fig. S8B). In the transwell migration assays, PITIP significantly enhanced the migration macrophages (Fig. S8C).

Fig. 2.

Proteolytic targeting chimera (PROTAC) of immunoreceptor tyrosine-based inhibitory motif (ITIM)-targeting inhibitory peptide (PITIP) suppresses Src homology 2 domain-containing phosphatase 2 (SHP2)-mediated inhibitory signaling pathways and increases the cytotoxicity of T cells and natural killer (NK) cells as well as the phagocytosis and antitumor phenotype of macrophages via the activation signaling pathways. (A) Immunoblot analysis of signaling molecules in PITIP-treated T cells (50 nM, 24 h). Blots show phosphorylation levels of SHP2 (Tyr542 and Tyr580 residues) and key downstream molecules ak strain transforming (AKT) and extracellular signal-regulated kinase (ERK), with corresponding total protein levels as controls. (B) Flow cytometric analysis of T-cell functional activation was performed, quantifying surface expression of intracellular Ki67 (proliferation marker), CD69 (activation marker), cleaved caspase-3 (apoptosis indicator), and granzyme B secretion (cytotoxic effector molecule) following PITIP treatment. (C) Up: Flow cytometric assessment of T cell proliferation via carboxyfluorescein succinimidyl ester (CFSE); representative histograms of CFSE fluorescence intensity and quantification of proliferating T cells are shown. Down: Real-time cytotoxicity of CD8⁺ T cells against human colorectal tumor cell line (HCT)116 cells. CD8⁺ T cells were treated with or without PITIP (50 nM) prior to coculture with HCT116 cells; target cell viability was monitored continuously using the xCELLigence real-time cell analysis (RTCA) system, and the cell index at 96 h is presented as a bar graph. (D) Immunoblot analysis of signaling molecules in PITIP-treated NK cells (50 nM, 24 h). Blots show phosphorylation levels of SHP2 (Tyr542 and Tyr580 residues) and key downstream molecules spleen tyrosine kinase (SYK) and zeta-chain-associated protein kinase 70 kDa (ZAP70), with corresponding total protein levels as controls. (E) NK cell cytotoxic activity was assessed via flow cytometry through measurement of CD107a surface mobilization (degranulation marker), along with intracellular perforin and granzyme B expression (cytolytic mediators) in PITIP-treated cells. (F) Cytotoxicity of PITIP-treated NK cells against human hepatocellular carcinoma cell line G2 (HepG2) cells, which were labeled with CFSE. NK cells were stimulated with PITIP (50 nM) for 3 days before coculture with labeled tumor cells (effector-to-target ratio = 1:1) for 4 h. Representative flow cytometric assessment histograms were shown. (G) Immunoblot analysis of signaling molecules in PITIP-treated macrophages (50 nM, 24 h). Blots show phosphorylation levels of SHP2 (Tyr542 and Tyr580 residues) and key downstream molecules SYK and AKT, with corresponding total protein levels as controls. (H) Macrophage polarization status was evaluated by flow cytometric quantification of M2-like protumoral markers (CD206 surface density and interleukin-10 (IL-10) secretion) versus M1-like antitumoral markers (CD86 surface expression and inducible nitric oxide synthase (iNOS) production) in PITIP-exposed macrophage populations. (I) Representative fluorescence microscopy images showing phagocytosis of green fluorescent protein (GFP)-expressing HCT116 cells by PITIP-treated macrophages. Images were captured after 2 h coculture of macrophages with tumor cells. Data or images are representative of three independent experiments. Statistical analysis was performed using Student's t-test or one-way analysis of variance (ANOVA). ^∗P < 0.05; ^∗∗P < 0.01; ^∗∗∗P < 0.001; NS, not significant. β-actin: beta-actin; PHA: phytohemagglutinin; PMA: phorbol 12-myristate 13-acetate; 7AAD: 7-aminoactinomycin D.

3.3. PITIP exhibits antitumor effects in different mouse tumor models

To investigate the in vivo antitumor efficacy of PITIP, we utilized mouse xenograft and allograft tumor models (Fig. 3A). In Hepa1-6 tumor-bearing mice, PITIP treatment significantly suppressed tumor growth in a dose-dependent manner. Notably, at a dose of 5 μg, the antitumor effects of PITIP were superior to those of αPD-1 antibodies (Figs. 3B and C). By dissociating tumor tissues and analyzing the expression of molecules using flow cytometry, we observed a significant increase in the expression of the proliferation marker Ki67 and the activation marker CD69 in CD8⁺ T cells (Fig. 3D). Similarly, in NK cells, there was a notable increase in the expression of CD69 and the degranulation marker CD107a (Fig. 3E). In macrophages, we confirmed a decrease in the expression of the tumor-promoting macrophage-associated markers CD206 and interleukin-10 (IL-10) to varying degrees, whereas the expression of the proinflammatory macrophage-associated markers CD86 and iNOS increased significantly (Fig. 3F). Additionally, survival analysis in the Hepa 1–6 syngeneic model confirmed sustained therapeutic efficacy. PITIP-treated mice achieved median survival exceeding 50 days, whereas untreated controls survived approximately 30 days (Fig. 3B). These findings indicate that PITIP elicits a comprehensive and sustained antitumor immune response. Preliminary in vivo toxicity assessment of PITIP revealed a favorable safety profile. Histopathological evaluation of major organs from PITIP treated mice demonstrated no significant pathological alterations (Figs. S9A and B). Concurrent analysis of hepatic/renal function biomarkers and hematological parameters showed no evidence of treatment-related toxicity (Figs. S9C and D). Furthermore, PITIP treatment elicited elevated levels of specific chemokines (e.g., intercellular adhesion molecule 1 (ICAM-1), granulocyte colony-stimulating factor (G-CSF), interleukin-16 (IL-16), and interleukin-1 receptor antagonist (IL-1ra)). Modest elevations in systemic inflammatory cytokines indicated expected immune activation post-checkpoint modulation, while serum levels of immune-related adverse event (irAE)-associated cytokines (interleukin-6 (IL-6), interferon-gamma (IFN-γ), and tumor necrosis factor-alpha (TNF-α)) showed no statistically significant increase (Fig. S9E). Quantification of the median lethal dose (LD₅₀) following intravenous administration demonstrated that PITIP possesses an LD₅₀ value 1064-fold higher than therapeutic dose, exhibits a favorable toxicity profile and a safety margin with a wide therapeutic window (Table S1).

Fig. 3.

Proteolytic targeting chimera (PROTAC) of immunoreceptor tyrosine-based inhibitory motif (ITIM)-targeting inhibitory peptide (PITIP) revives antitumor immunity in different types of tumors in humans and mice. (A) Schematic depicting the treatment regimen of tumor-bearing mice. (B, C) PITIP treatment suppresses hepatocellular carcinoma growth in vivo. Mice bearing hepatoma 1–6 (Hepa1-6) tumors were randomized to receive vehicle, PITIP (i.p., every other day; PITIP-L, 125 μg/kg; PITIP-M, 250 μg/kg; PITIP-H, 500 μg/kg), ITIM-targeting inhibitory peptide (ITIP) (i.p., every other day; 250 μg/kg), or anti-programmed cell death protein 1 (αPD-1) antibody (i.p., every two days; 6250 μg/kg) when tumor volumes reached ∼100 mm³ (n = 6 per group). (B) Tumor photographs and weights at the study endpoint (left), and the survival curves of mice in each group (right). (C) Tumor growth curves were monitored by caliper measurements every three days. (D) Flow cytometric analysis of tumor-infiltrating CD8⁺ T cells to evaluate PITIP-induced antitumor immunity: percentages and relative mean fluorescence intensity (MFI) are shown. Quantification of Ki67 (proliferation marker) and CD69 (activation marker) expression via relative MFI values and representative plots in tumor-infiltrating CD8⁺ T cells. (E) Flow cytometric analysis of tumor-infiltrating natural killer (NK) cells: percentages and MFI are shown. Comparative analysis of CD69 (activation marker) and CD107a (degranulation marker) expression levels in tumor-infiltrating NK cells, presented as normalized MFI with corresponding flow cytometry plots. (F) Flow cytometric analysis of tumor-infiltrating macrophages: percentages and MFI are shown. Relative MFI quantification and representative flow plots demonstrating M2-like (CD206, interleukin-10 (IL-10)) and M1-like (CD86, inducible nitric oxide synthase (iNOS)) macrophage polarization markers in tumor-associated macrophages from tumor-bearing mice. (G) Schematic of the treatment regimen for tumor-bearing humanized mice. Human peripheral blood mononuclear cells (PBMCs) were injected on day −14, and human hepatocellular carcinoma cell line G2 (HepG2) cells were inoculated on day 0. When tumors reached 100 mm³, mice were randomly assigned to 4 groups (n = 5 per group): vehicle, PITIP (i.p., every other day; 250 μg/kg), ITIP (i.p., every other day; 250 μg/kg), or αPD-1 antibody (i.p., every two days; 6250 μg/kg). (H) Tumor photographs and weights at the study endpoint. (I) Tumor growth curves were monitored by caliper measurements at day 5, 7, 11, 15, 19 and 23. The color codes for each group are as follows: gray, vehicle control; red, PITIP; yellow, ITIP; blue, αPD-1. (J–M) Flow cytometric analysis of tumor-infiltrating CD8⁺ T cells to assess PITIP-induced activation: relative MFI and representative plots of proliferation (Ki67) (J), activation (CD69) (K), and cytotoxicity (perforin (L), granzyme B (M)) markers are shown. Statistical analysis was performed using one-way analysis of variance (ANOVA). ^∗P < 0.05; ^∗∗P < 0.01; ^∗∗∗P < 0.001; ^∗∗∗∗P < 0.0001; NS, not significant.

To evaluate PITIP's antitumor efficacy across diverse malignancies, we established a murine MC38 colon carcinoma model. Treatment with PITIP significantly enhanced functional activation of both T lymphocytes and NK cells. Concurrently, macrophages underwent pro-inflammatory polarization (Fig. S10), demonstrating PITIP's capacity to elicit comprehensive antitumor immunity through synergistic lymphocyte activation and myeloid cell reprogramming. These findings indicate that PITIP elicits a comprehensive antitumor immune response, which includes the activation of T cells and NK cells, as well as the reprogramming of macrophages into an antitumoral phenotype.

To examine the influence of PITIP on human immune cells, a mouse model with a humanized immune system was established by injecting human peripheral blood lymphocytes into immunodeficient NCG mice via the tail vein. A tumor-bearing model was subsequently created via the subcutaneous inoculation of HepG2 cells (Fig. 3G). Compared with αPD-1 antibody treatment and ITIP treatment, PITIP treatment significantly inhibited tumor growth, resulting in superior antitumor effects (Figs. 3H and I). PITIP treatment also significantly increased the number of tumor-infiltrating T cells and upregulated the expression of Ki67, CD69, and cytotoxic molecules such as perforin and granzyme B in T cells (Figs. 3J–M). These findings indicate that PITIP effectively controls tumor growth and enhances the activity of human CD8⁺ T cells in a humanized immune system tumor-bearing mouse model. These results are consistent with the conclusions obtained from in vitro experiments and allograft tumor models.

3.4. PITIP induces robust antitumor immune responses in αPD-1-resistant tumors

To further validate the applicability of PITIP as a universal ICI in tumors resistant to ICI treatment, we examined its effect on αPD-1-resistant tumors. MC38 colon adenocarcinoma tumors were transplanted into C57BL/6 mice, and with ongoing administration of αPD-1 antibodies, a mouse model exhibiting resistance to αPD-1 therapy was subsequently developed through in vivo passages (Fig. 4A). Using this model, we assessed the effects of PITIP on the immune landscape within αPD-1-resistant tumors. As expected, αPD-1 therapy failed to elicit a therapeutic response, whereas PITIP exhibited substantial antitumor efficacy (Figs. 4B–D). In alignment with the aforementioned findings, treatment with PITIP led to significant upregulation of Ki67 and CD69 in T cells, as well as CD69 and CD107a in NK cells. In macrophages, there was pronounced downregulation of CD206 and IL-10, accompanied by significant upregulation of CD86 and iNOS (Figs. 4E-L). These results imply that PITIP may mediate immune microenvironment remodeling via pathways independent of the PD-1/PD-L1 axis, thereby potentiating antitumor immunity within αPD-1-resistant tumors and presenting a promising approach for overcoming resistance to ICI therapy.

Fig. 4.

Proteolytic targeting chimera (PROTAC) of immunoreceptor tyrosine-based inhibitory motif (ITIM)-targeting inhibitory peptide (PITIP) induces robust anti-tumor immune responses in anti-programmed cell death protein 1 (αPD-1)-resistant tumor. (A) Schematic depicting the treatment regimen of tumor-bearing mice. αPD-1-resistant mouse colon 38 (MC38) tumor model was established by serially passaging MC38 tumors under continuous αPD-1 treatment. Mice were inoculated with αPD-1-resistant MC38 cells. When tumors reached 100 mm³, mice were randomly assigned to receive vehicle, PITIP (i.p., every other day; 250 μg/kg), ITIM-targeting inhibitory peptide (ITIP) (i.p., every other day; 250 μg/kg) or αPD-1 antibody (i.p., every two days; 6250 μg/kg) treatment (n = 6 per group). (B–D) Antitumor efficacy of PITIP in αPD-1-resistant MC38 tumors: Representative tumor images (B), tumor weights at the endpoint (C), and tumor growth curves (D) (measured at day 5, 7, 11, 15, 19 and 23) are shown. . (E, F) Flow cytometric quantification of Ki67⁺ (proliferative) (E) and CD69⁺ (activated) (F) subpopulations in tumor-infiltrating CD8⁺ T cells, with representative density plots and percentage distributions. (G, H) Representative plots and percentages of CD69 (G) and CD107a (H) expression in tumor-infiltrating natural killer (NK) cells analyzed by flow cytometry. (I–L) Multiparametric flow analysis of macrophage polarization in tumor lesions to evaluate PITIP-induced tumor microenvironment (TME) remodeling: CD206⁺ (M2-like) macrophages (I), interleukin-10 (IL-10)⁺ (M2-like) macrophages (J), CD86⁺ (M1-like) macrophages (K), and inducible nitric oxide synthase (iNOS)⁺ (M1-like) macrophages (L). Percentage distributions and gating strategies are shown, with PITIP promoting M1-like polarization and inhibiting M2-like polarization. Statistical significance was determined by one-way analysis of variance (ANOVA). ^∗P < 0.05; ^∗∗P < 0.01; ^∗∗∗P < 0.001; ^∗∗∗∗P < 0.0001; NS, not significant.

3.5. Anti-CD45 antibody-conjugated liposomes enhance the immune cell targeting ability of PITIP

To increase the specific uptake of PITIP by immune cells, we conjugated anti-CD45 antibodies to the surface of liposomes for the delivery of PITIP, thereby specifically targeting immune cells that express CD45. To characterize the liposomes before and after conjugation with anti-CD45 antibodies, the liposomes were observed via transmission electron microscopy (TEM), and the particle size and zeta potential of the liposomes were determined. The morphology of the liposomes remained largely unchanged following anti-CD45 antibody conjugation, with only a slight increase in particle size (Figs. 5A and B). The zeta potential of the liposomes decreased slightly after antibody conjugation, shifting from −35.70 to −17.80 mV (Fig. 5C). Continuous monitoring over 7 days showed no significant changes in particle size distribution and zeta potential, indicating that antibody conjugation does not affect the stability of liposomes (Fig. S11). These findings suggest that the stability of the liposomes was marginally affected by the antibody conjugation, although it remained within an acceptable range. Confocal microscopy analysis revealed that PITIP encapsulated within liposomes could successfully escape from lysosomes (Fig. 5D). Furthermore, the flow cytometry results indicated that the delivery of PITIP via anti-CD45 antibody-conjugated liposomes significantly increased its ability to target immune cells, with increased and rapid internalization by lymphocytes (Fig. 5E). These findings demonstrate that conjugating anti-CD45 antibodies to the surface of liposomes is an effective strategy for enhancing the immune cell targeting ability of PITIP.

Fig. 5.

CD45 antibody-conjugated liposomes enhance the immune cell targeting of proteolytic targeting chimera (PROTAC) of immunoreceptor tyrosine-based inhibitory motif (ITIM)-targeting inhibitory peptide (PITIP). (A) Morphological characterization by transmission electron microscopy (TEM) revealed spherical nanostructures of both PITIP encapsulated within liposomes (lipoPITIP) and CD45 antibody-conjugated liposomes (CD45-lipoPITIP), with surface topology variations between unmodified and antibody-functionalized formulations observed through uranyl acetate negative staining. (B) Hydrodynamic profiling via dynamic light scattering (DLS) demonstrated monodisperse size distributions for both systems, with CD45-conjugated liposomes exhibiting a diameter increase versus lipoPITIP. (C) Colloidal stability assessment through electrophoretic light scattering quantified surface charge alterations, showing CD45 conjugation increased zeta potential from −35.70 ± 7.09 mV to −17.80 ± 7.23 mV. (D) Immunofluorescence images showing CD45-lipoPITIP (green) uptake into immune cells escaping from lysosomes (red). (E) Percentages of CD45-lipoPITIP uptaken by CD45⁺ cells analyzed through flow cytometry. Data or images are representative of three independent experiments. Statistical significance was determined by Student's t-test. ^∗∗∗∗P < 0.0001; NS, not significant. PDI: polydispersity index; CY5.5: cyanine5.5.

3.6. CD45-lipoPITIP outperforms PITIP in tumor microenvironment (TME) remodeling and anticancer effects

To investigate the in vivo antitumor efficacy of PITIP, we established orthotopic transplantation tumor models. Hepa1-6 tumor-bearing mice were used to compare the anticancer effects of CD45-lipoPITIP with those of PITIP. Compared with those treated with saline, the bioluminescence signal intensities of the mice treated with the anti-CD45 antibody-conjugated empty liposomes did not differ. In contrast, the CD45-lipoPITIP treatment group demonstrated significantly enhanced tumor suppression, with a notable decrease in bioluminescence signal intensity (Figs. 6A and B). Compared with the PITIP-treated mice, the mice in the CD45-lipoPITIP group had significantly smaller tumor volumes (Fig. 6C).

Fig. 6.

CD45 (proteolytic targeting chimera (PROTAC) of immunoreceptor tyrosine-based inhibitory motif (ITIM)-targeting inhibitory peptide (PITIP)) encapsulated within liposomes (lipoPITIP) outperformed PITIP in tumor microenvironment (TME) remodeling and anti-cancer effects. (A) Images displaying luminescence in orthotopic hepatoma 1–6 (Hepa1-6) -luciferase (Luc) tumor-bearing C57BL/6 mice following indicated treatments. Mice were randomly assigned to receive vehicle (i.p., every other day), CD45-lipid nanoparticle (LNP) (i.v., every three days), PITIP (i.p., every other day), lipoPITIP (i.v., every three days), CD45-lipoPITIP (i.v., every three days) treatment (n = 5 per group). (B) Quantification of luminescence levels in mice utilizing the in vivo imaging system spectrum (IVIS) after indicated treatments. (C) Photos of excised liver tumors from mice following indicated treatments. (D) Heatmap displays the expression levels of 41 markers of CD45⁺ clusters within the tumor-infiltrating immune cells of CD45-LNP or CD45-lipoPITIP treatment (n = 3). (E) t-distributed stochastic neighbor embedding (t-SNE) plot of CD45⁺ tumor-infiltrating leukocytes of total 6 samples (pooled data) by the cytometry by time-of-flight (CyTOF) assay divided the immune cells into 10 clusters. (F) Proportions of the indicated immune cell subsets within the CD45⁺ population are shown. (G–I) Violin plots showing the expression levels of proliferation (Ki67) and cytotoxicity (granzyme B, perforin) markers in CD8⁺ T cells (G) and the expression levels of activation (CD25) and cytotoxicity (CD107a, perforin) markers in natural killer (NK) cells (H). Violin plots depicting the expression of antitumoral (CD86, inducible nitric oxide synthase (iNOS)) and protumoral (CD172a) markers in macrophages (I). Statistical significance was determined by one-way analysis of variance (ANOVA) or log-rank test. ^∗P < 0.05; ^∗∗P < 0.01; NS, not significant. DC: dendritic cell; MDSC: myeloid-derived suppressor cell.∖

To further investigate the reshaping of the tumor immune microenvironment by CD45-lipoPITIP, we utilized cytometry by time of flight (CyTOF) to assess the immune cell composition of Hepa1-6 orthotopic hepatocellular carcinoma xenografts. At the single-cell level, CyTOF employs 41 monoclonal antibodies (mAbs) to detect immune cells and functional molecules. The evaluated population of CD45⁺ cells was categorized into 10 distinct clusters (Figs. 6D and E). Notably, subsequent analyses demonstrated that in mice treated with CD45-lipoPITIP, there was a significant increase in the numbers of CD8⁺ T cells, antitumor macrophages, and CD4⁺ T cells, with the numbers of NK cells and dendritic cells (DCs) showing increasing trends. Conversely, the numbers of protumor macrophages, monocytes, and myeloid-derived suppressor cells (MDSCs) decreased, and the number of tumor-associated neutrophils (TANs) tended to decrease (Fig. 6F). We further analyzed the expression of key immune cell markers across the groups. The CyTOF results revealed significant upregulation of Ki67, granzyme B and perforin in CD8⁺ T cells post-CD45-lipoPITIP treatment (Fig. 6G), which was consistent with previous flow cytometry data. Furthermore, CD45-lipoPITIP treatment notably increased the expression of NK cell activation and cytotoxicity markers (Fig. 6H). In macrophages, CD45-lipoPITIP treatment significantly increased the expression of CD86 and iNOS, markers of antitumor macrophages, while SIRP-α expression decreased (Fig. 6I), corroborating earlier flow cytometry findings. In summary, the findings presented herein substantiate that the administration of CD45-lipoPITIP markedly modulates the tumor immune microenvironment, thereby promoting a shift toward a predominantly antitumor phenotype.

4. Discussion

Monotherapy with a single ICI has been demonstrated to be insufficient for effectively controlling tumor growth. Similarly, combination therapies involving ICIs have also shown limited efficacy [14]. This limitation is largely attributed to the substantial variability of the TME across different tumor types, as well as the complex and intricately regulated network of immune cells within tumors [14]. The diverse immune cell populations within the TME collectively impact tumor initiation and progression, and intricate regulation of each immune cell type is mediated by various immune inhibitory receptors, such as PD-1, CTLA-4, BTLA, NKG2A, TIGIT, and SIRP-α. These immune checkpoint molecules play crucial roles in facilitating tumor immune evasion [[15], [16], [17]]. Acquired resistance to ICIs is prevalent, often due to compensatory upregulation of immune checkpoints after treatment [18]. The development of multitarget PROTACs theoretically overcomes the limitations of single ICI therapies by addressing TME heterogeneity through the targeted degradation of various immune checkpoint molecules. Additionally, the direct degradation of immune checkpoint molecules can mitigate the risk of drug resistance caused by their overexpression. As a crucial avenue for novel drug discovery, PROTAC-based therapeutic strategies have been effectively employed to conditionally degrade numerous POIs both in vitro and in vivo and are widely utilized in a broad spectrum of diseases, including cancer, viral infections, immune disorders, and neurodegenerative diseases [19]. In 2019, the initial clinical trials on PROTACs commenced. By 2020, clinical trials on the PROTACs ARV-110 and ARV-471, which target the androgen receptor (AR) and estrogen receptor (ER), respectively, demonstrated the first clinical proof-of-concept [20]. Currently, ARV-471 is being evaluated in phase III trials to obtain US Food and Drug Administration (US FDA) approval, while a minimum of 20 additional degraders are being evaluated in phase I/II clinical trials [[21], [22], [23]]. In light of the initial favorable clinical study data concerning safety, efficacy, and pharmacokinetics, PROTACs exhibit considerable potential for development as cancer therapies [24].

ITIMs are prevalent in the intracellular domains of various immune checkpoint molecules. Upon phosphorylation, ITIMs recruit phosphatases such as SHP1/2 or SHIP, which are responsible for transmitting inhibitory signals to immune effector cells [25]. We have developed a peptide that mimics the conserved sequence of SHP2 and is capable of binding to various immune inhibitory receptors. A PROTAC, designated PITIP, was constructed by utilizing this peptide as a ligand for the POI and coupling it to the VHL ligand via a peptide-based linker. Consistent with our hypothesis, PITIP significantly reduced expression of ITIM-containing receptors PD-1, BTLA, NKG2A, SIRP-α, CD33, KIR2DL3, Siglec-7, Siglec-9, and LAIR-1 across multiple cell types through ubiquitin-mediated degradation. Conversely, PITIP induced no significant alteration in surface expression of non-ITIM receptors including IGF-1R, TLR8, NKG2D, GM-CSFR, CD3, and CD16. This finding substantiates our design concept that PITIP is capable of specifically recognizing and degrading a spectrum of immune checkpoint molecules containing ITIMs, achieving simultaneous intervention in multiple pathological proteins by targeting conserved protein structures, despite their expression on various immune cell types.

Our findings demonstrate that PITIP effectively reduces SHP1/2 and SHIP phosphorylation induced by ITIMs in T cells, NK cells, and macrophages, thereby concurrently attenuating the downstream inhibitory signals of multiple immune checkpoints. In T cells, SHP1/2 and SHIP negatively modulates the PI3K-AKT and MEK-ERK signaling pathways, which are vital for T-cell proliferation, growth, and survival, through dephosphorylation [1,26,27]. PITIP effectively inhibits apoptosis, promotes T-cell proliferation, and enhances T-cell activation and cytotoxicity. In NK cells, NKG2A recruits SHP1/2 or SHIP, resulting7 in the dephosphorylation of key activation molecules such as Zap70, Syk, and Vav1, thereby suppressing NK cell activation and degranulation [[28], [29], [30]]. PITIP mitigates the suppression of Zap70, Syk, and Vav1 phosphorylation, thus enhancing the activation and cytotoxic function of NK cells by inhibiting different phosphatases phosphorylation. Similarly, in macrophages, PITIP restores the ‘eat-me’ signal and promotes the phagocytosis of tumor cells by disrupting SIRP-α signal transduction [31]. These findings further support the efficacy of the PITIP design strategy in initiating a comprehensive antitumor immune response through the ubiquitination and degradation of multiple immune checkpoints across various immune cells. Given that PITIP activates diverse immune cells, including T cells, NK cells, and macrophages, in vitro, its potential therapeutic applications may be extended to augment the antitumor effects of CAR-T, CAR-NK, and CAR-M therapies. PITIP operates analogously to ICI combination therapies, which could reduce the economic burden associated with treatment. Moreover, another advantage of PITIP is that PROTACs do not degrade with the POI and can be reused, increasing both their cost-effectiveness and efficiency.

The TME across different tumor types exhibits considerable heterogeneity and dynamic plasticity. For example, early lung adenocarcinoma is characterized by the aggregation of lymphocytes and the expansion of T cells, whereas hepatocellular carcinoma (HCC) and colorectal cancer (CRC) present a greater proportion of monocytes than T cells and NK cells [32,33]. This variability highlights the limitations of relying solely on the blockade of a limited number of checkpoints or the activation of a single immune cell type, suggesting that combination checkpoint therapies may only demonstrate significant efficacy in certain tumor types. PITIP demonstrated broad-spectrum antitumor efficacy across multiple mouse models (CRC, HCC subcutaneous/orthotopic, and humanized HCC), consistently inhibiting tumor growth. Mechanistically, it enhanced the infiltration of CD8⁺ T cell, and improved the activation and cytotoxicity of CD8⁺ T cell and NK cell within tumors, aligning with in vitro results. Furthermore, PITIP was observed to transform the tumor-promoting phenotype of macrophages into a tumor-suppressive phenotype. CyTOF analysis further corroborated the aforementioned findings, demonstrating a decrease in the number of immunosuppressive cells following PITIP treatment, concomitant with an increase in the number of tumor-suppressive cells and a significant increase in the levels of cytotoxic molecules such as perforin and granzyme B. These findings indicate that PITIP significantly promotes the reshaping of the antitumor immune microenvironment. Additionally, the results demonstrated that the antitumor efficacy of PITIP exceeded that of PD-1 monoclonal antibodies, likely due to its ability to target a broader range of immune checkpoints, thereby enhancing the activation of various immune cells. ITIP also exhibited a certain degree of antitumor activity by binding to phosphorylated ITIMs on various immune checkpoint molecules, potentially competing with SHP1/2 and SHIP for binding. In contrast, PITIP is superior because of its degradation of immune checkpoint molecules, which results in a more pronounced modulation of SHP1/2 and SHIP activity than the competitive binding of ITIP. To further validate the clinical applicability of PITIP as a universal ICI in tumors resistant to ICI treatment, we examined its effect on αPD-1-resistant tumors. The results were highly encouraging, as PITIP elicited a robust antitumor immune response and effectively addressed resistance to PD-1 inhibitors. Consequently, PITIP represents a promising strategy for overcoming clinical resistance to ICI therapy.

Optimizing delivery systems is critical for advancing peptide PROTAC therapeutics, with nano-engineered coordination polymers (NCPs) and immunoliposomes emerging as highly promising platforms in preclinical development [[32], [33], [34]]. Antibody-targeted liposomes, engineered by conjugating antibodies to the liposomal surface, facilitate targeted drug delivery. Surface-bound antibodies significantly increase the rate and magnitude of liposome endocytosis by cells, thereby facilitating increased drug uptake and improving therapeutic outcomes [35,36]. In this study, we encapsulated PITIP within nanoparticles to optimize its bioavailability and innovatively conjugated anti-CD45 antibodies to liposome surfaces to augment immune cell targeting. The experimental findings corroborated our hypotheses, demonstrating that anti-CD45 antibody-conjugated liposomes for PITIP delivery substantially enhance the immune cell targeting efficiency of PITIP both in vivo and in vitro, thereby significantly improving the therapeutic efficacy of PITIP in liver cancer treatment.

Compared with those of inhibitors and antibodies, the therapeutic effects of PROTACs are more persistent, as they eliminate target proteins catalytically and effectively [37]. PROTAC also offers advantages in targeting drug-resistant mutations and difficult-to-drug proteins and has high specificity for target proteins [[38], [39], [40], [41], [42]]. The distinct mechanism by which PITIP inhibits immune checkpoints, as opposed to antibody-mediated blockade, allows it to bypass the side effects typically associated with antibody therapy. For example, monoclonal antibodies targeting CD47, while exhibiting antitumor activity, can lead to complications such as anemia due to the high expression of CD47 on the red blood cell membrane [43]. In contrast, the specificity of PITIP for immune cells fundamentally addresses this concern. However, a limitation of this study is that PITIP is effective only against immune checkpoints containing ITIMs. Some immune checkpoints lack these intracellular segments, necessitating the potential combination of PITIP with inhibitors targeting those checkpoints to achieve optimal clinical outcomes. Moreover, the capacity of PITIP to interact with various immune cell types and maintain efficacy regardless of the heterogeneity of the TME indicates its potential for broad therapeutic application across diverse cancer types. Nonetheless, our research to date has been limited to assessing the antitumor efficacy of PITIP in colon and liver cancers, underscoring the necessity for further validation across a wider range of cancer types. Substantial evidence confirms that synergistic integration of immune checkpoint inhibitors with cancer vaccines enhances antitumor efficacy while minimizing adverse effects [34,[44], [45], [46]]. Thus, future investigations will evaluate synergistic combinations of PITIP with complementary therapeutic modalities such as cancer vaccines to minimize dosing requirements while enhancing antitumor efficacy. Concurrently, efforts are underway to develop PITIP into small-molecule drugs, with the objective of creating universal ICI that offer improved tissue penetration and oral bioavailability.

In conclusion, PITIP reshaped the TME by specifically targeting ITIMs and degrading multiple immune checkpoint molecules across diverse immune cell populations, thereby stimulating robust antitumor immunity in various tumor types. PITIP not only broadens and increases the efficacy of immune checkpoint inhibition but also mitigates the compensatory upregulation of immune checkpoints that can lead to drug resistance, presenting significant advantages over traditional single ICI or combination therapies. Additionally, this PROTAC construction strategy represents a paradigm shift, enabling in the degradation of multiple pathological proteins by targeting the common domains they share.

CRediT authorship contribution statement

Yue-Yuan Qiu: Writing – original draft, Formal analysis, Data curation. Zhao-Wei Wang: Software, Funding acquisition, Formal analysis. Lei He: Validation, Resources. Ge-Ge Shi: Validation, Investigation. Zhao-Zhao Li: Validation, Methodology. Shuang-Xin Ma: Validation. Duo Yu: Validation. Hai-Chen Du: Validation. Fei Xie: Validation. Cun Zhang: Funding acquisition. Ying-Qi Zhang: Supervision, Resources, Project administration. Meng Li: Resources, Funding acquisition, Formal analysis. Wei-Na Li: Writing – review & editing, Project administration, Conceptualization.

Data availability

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Declaration of interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary data

The following is the Supplementary data to this article.