GBP2 condensates promote ferroptosis to sensitize anti-PD-L1 immunotherapy in melanoma

Domain: biology
Published: 2025-12-24
Editorial outcome: major_revision

Abstract
The mechanisms underlying the limited response to immune checkpoint blockade (ICB) remain unclear. One explanation is that tumors escape cytotoxic T cell killing by disrupting interferon-gamma (IFN-γ) signaling. Here we show that guanylate-binding protein 2 (GBP2), an IFN-γ–inducible molecule, functions as a general amplifier of T cell–mediated cytotoxicity by promoting ferroptosis in melanoma. GBP2 enhances STAT1 activation and suppresses SLC7A11, thereby sensitizing tumor cells to ferroptotic death. Upon IFN-γ stimulation, GBP2 undergoes phase separation through an intrinsically disordered region, forming condensates that sequester SHP1 and sustain STAT1 activation. Disrupting GBP2 phase separation impairs ferroptosis, accelerates tumor growth, and weakens T cell–driven tumor control. GBP2 also increases HMGB1 release from ferroptotic cells, promoting cytotoxic T cell infiltration. These findings identify GBP2 as a key mediator linking IFN-γ signaling to ferroptosis and demonstrate that enhancing this pathway can improve tumor responsiveness to ICB immunotherapy.

Introduction
Immune checkpoint blockade (ICB), exemplified by inhibitors targeting programmed cell death 1 (PD-1) or programmed death ligand 1 (PD-L1), has emerged as a transformative therapeutic approach1. ICB therapy restores or enhances the function of effector CD8+T cells (cytotoxic T lymphocytes, CTL) and drives interferon-γ (IFN-γ) production to eliminate tumor cells. Despite substantial clinical success, a significant subset of melanoma patients exhibit suboptimal responses. The pre-existing immunosuppressive tumor microenvironment (TME) remains a major barrier to efficacy, driven by factors such as low expression of immune checkpoints and neoantigens, genomic instability, tumor mutational burden, limited infiltration of tumor-infiltrating lymphocytes (TILs), and attenuated IFN-γ gene signature2,3. These challenges underscore the urgent need for combinatorial strategies capable of overcoming TME‑associated resistance and broadening the benefit of ICB.

One promising approach to elicit this transformation is to induce ferroptosis in tumor cells. Ferroptosis is an iron‑dependent form of cell death driven by lethal accumulation of lipid peroxides4. Multiple strategies have been employed to trigger ferroptosis, including inhibition or degradation of ferroptosis suppressor glutathione peroxidase 4 (GPX4), development of novel sensitizers for ferroptosis suppressor protein 1 (FSP1), blockade of system X −, and therapeutic cancer nanovaccines—all of which have shown synergistic effects with ICB therapy in preclinical cancer models5. Recently, Wang et al. demonstrated that type II IFN signaling serves as an effective entry point to amplify ferroptosis6. However, the precise molecular mechanisms by which IFN-γ enhances ferroptosis remain poorly understood.

Emerging evidence suggests that many molecular assemblies form membraneless biomolecular condensates via phase separation, offering an insight into previously unexplained biological phenomena7–9. Dysregulated phase separation has been increasingly recognized as a key contributor to cancer progression, including modulation of immune responses8,10,11. Moreover, recent studies indicate that phase separation can facilitate ferroptosis, raising the possibility that this process may serve as a regulatory hub12,13. Nonetheless, the mechanisms by which phase separation selectively compartmentalizes signaling components to control ferroptotic activity remain largely elusive.

In this study, to identify candidate targets for combinatorial immunotherapy, we applied weighted correlation network analysis (WGCNA) to screen hub genes associated with IFN-γ response and CTL cytolytic activity. Guanylate binding protein 2 (GBP2) was emerged as a key gene of interest. We observed that GBP2 expression positively correlated with CTL cytotoxicity and infiltration. GBP2 overexpression enhanced, whereas GBP2 deletion attenuated, ferroptosis induced by ICB‑activated CTLs. Mechanistically, we reveal an IFN‑γ–dependent pathway in which tumor cell GBP2 undergoes phase separation, sequestering SHP1 to promote STAT1 phosphorylation. This signaling cascade drives immunogenic ferroptosis, thereby potentiating the efficacy of anti–PD‑L1 immunotherapy. Our findings establish GBP2 phase separation as a previously unrecognized molecular circuit that mediates IFN-γ-dependent ferroptosis and highlight GBP2 as a promising target for combinatorial melanoma immunotherapy.

Results
WGCNA identified GBP2 as a CTL cytolytic activity associated gene in melanoma

ICB therapy primarily eliminates tumor cells by enhancing the effector function of CTL. Activated CTLs engage multiple cytolytic pathways, including IFN-γ, perforin-granzyme, and Fas-Fas ligand signaling to eradicate tumor cells14. However, tumors frequently evade this immune pressure by impairing CTL cytolytic activity—either through inducing T cell dysfunction in CTL-high tumors or by preventing T cell infiltration in CTL-low tumors6. To identify molecular targets associated with CTL cytolytic activity, we employed WGCNA, a robust strategy for screening candidate genes linked to phenotypic traits15. Fifteen co‑expression modules were identified (Figs. 1A and S1). Among them, the yellow module exhibited the strongest correlation with 6-gene-IFN-γ signature (R=0.89, P=4e-29), cytolytic activity signature (R=0.81, P=7e-21) and two independent cytotoxic cell signatures (R=0.86, P=9e-26 and R=0.81, P=3e-20), as determined by module eigengene analysis (Fig. 1B and Supplementary Dataset 1). These signatures collectively predict CTL cytolytic activity16–19. Gene Ontology biological process (GO-BP) analysis further revealed that yellow module genes were significantly enriched in immune regulation, cell killing and IFN-γ response (Fig. 1C). These findings indicate that the yellow module represents a central network associated with CTL cytotoxicity, warranting further interrogation of its constituent genes for hub gene identification.

GO molecular function (MF) analysis showed additional enrichment of GTP binding and GTPase activity in the yellow module (Fig. 1C). GTP-binding proteins regulate a wide range of cellular processes, and elevated GTP levels have recently been linked to be associated with tumor progression, chemotherapy resistance, and ICB resistance20–22. Gene set enrichment analysis (GSEA) of the PRJEB23709 cohort demonstrated that GTPase activity and GTP binding were significantly positive enriched in ICB responders (Fig. 1D). Based on this, all yellow module genes were intersected with known GTP-binding proteins, yielding 18 candidates (Fig. 1E). Univariate Cox analysis identified guanylate binding protein 2 (GBP2) as the gene most significantly associated with overall survival (OS) in melanoma patients (Fig. 1F). This finding was validated in GSE8401, GSE59455, and GSE54467 cohorts, with consistent results (Fig. S2A–C). In the GSE65904 cohort, patients with low GBP2 expression exhibited shorter distant metastasis free survival (DMFS) and disease-specific survival (DSS) compared to those with high GBP2 expression (Fig. S2D).

We next examined the relationship between GBP2 expression and clinical features. In the GSE3189 dataset, GBP2 expression was significantly higher in normal tissues than in melanoma tissues (Fig. S2E). Spatial transcriptomic analysis of a melanoma specimen, segmented into malignant, boundary and non-malignant regions and annotated with 10 cell types, revealed that GBP2 was predominantly expressed in normal epithelial cells, with markedly lower levels in malignant regions (Fig. 1G–I). Analysis of major pathological prognostic factors demonstrated that higher GBP2 expression was associated with favorable clinical features, including reduced Breslow thickness, lower Clark level and ulceration—all indicators of better prognosis (Fig. S2F)23,24. To explore the potential biological functions of GBP2 in melanoma, we conducted GSEA and GO analyses. Across six independent cohorts, patients with high GBP2 expression showed significant enrichment in IFN-γ response, regulation of immunity and cell killing (Figs. S3 and S4). Together, these bioinformatic findings in clinical samples identify GBP2 as a potential prognostic biomarker and reveal its close association with CTL cytolytic activity in melanoma.

GBP2 deletion inhibited the CTL-induced ferroptosis to blunt the efficacy of ICB

We next investigated the relationship between GBP2 and ICB responsiveness in melanoma. GBP2 knockout (GBP2−/−) lines were generated using CRISPR/Cas9 in B16-ovalbumin (OVA). GBP2 overexpressing (GBP2oe) lines were established via lentiviral transduction in both B16-ovalbumin (OVA) and A375 cells (Fig. S5A, B and Supplementary Table 1). To investigate the role of GBP2 in antitumor immunity, we first assessed its function in immunodeficient NOD. Cg-Prkdcscid Il2rgtm1Wjl/SzJ (NSG) mice. GBP2 knockout exhibited growth kinetics comparable to control tumors, indicating that GBP2 does not influence tumor progression in the absence of adaptive immunity (Fig. S5C). This finding suggests that GBP2 may exert its antitumor function through modulating adaptive immune responses, particularly CD8⁺ T cell–mediated cytotoxicity. To assess the contribution of GBP2 to T cell–mediated tumor control, OVA‑specific CD8+ (OT‑1) T cells were adoptively transferred into mice bearing either control or GBP2−/− B16‑OVA tumors. OT‑1 transfer effectively suppressed the growth of control tumor growth; however, this effect was markedly diminished in GBP2−/− tumors (Fig. 2A, B). These findings suggest that GBP2 is essential for optimal CD8+ T‑cell–mediated tumor rejection, prompting evaluation of its role in ICB efficacy.

To this end, mice bearing GBP2−/− or sgCtrl B16-OVA tumors were treated with anti-PD-L1 blockade. GBP2 deficiency significantly reduced the antitumor efficacy of anti–PD‑L1 therapy compared to sgCtrl tumors (Fig. 2C, D). Similar results were observed in GBP2‑knockout MC38 tumors, in which GBP2 loss attenuated the response to combined OT‑1 transfer and anti–PD‑L1 treatment (Fig. S5D–H). These data indicate that GBP2 sensitizes tumor cells to CD8+ T cell-mediated cytotoxicity, thereby enhancing ICB efficacy in vivo.

Considering that CD8+ cytotoxic T lymphocytes (CTLs) eliminate tumor cells through multiple cell death pathways, we next sought to identify which CTL‑dependent cell death pathways are influenced by GBP2. OT-1 cells were co-cultured with GBP2oe B16-OVA cells in the presence of pathway‑specific inhibitors. Notably, treatment with the ferroptosis inhibitor ferrostatin‑1 (Fer‑1) significantly attenuated OT‑1-induced cytotoxicity in GBP2oe tumor cells, whereas inhibitors of pan‑caspases (emricasan), necroptosis (necrostatin‑1), or pyroptosis (disulfiram) had no effect (Fig. 2E). Consistently, GSEA revealed a strong positive correlation between GBP2 expression and ferroptosis signatures (Figs. 2F and S6A–E). These findings indicate that GBP2 facilitates CTL-mediated ferroptosis in tumor cells.

To further confirm this association, we measured lipid ROS—a hallmark of ferroptosis—in B16‑OVA tumors. GBP2 knockout tumors from both OT‑1 transfer and anti-PD-L1 treatment groups exhibited reduced lipid ROS levels relative to sgCtrl tumors (Figs. 2G, H and S6F, G). In vitro, GBP2 overexpression enhanced OT-1–induced cytotoxicity and intracellular lipid ROS, effects that were reversed by Fer-1 (Fig. 2I, J). Together, these results demonstrate that GBP2 promotes CTL‑induced ferroptosis and thereby enhances the antitumor efficacy of ICB therapy.

We next investigated the upstream signals through which GBP2 promotes ferroptosis. Given the known role of CD8⁺ T cell secreted cytokines in ICB-induced tumor cell death25, we measured IFN-γ and TNF-α levels in tumors with or without anti–PD‑L1 treatment. Under basal conditions, GBP2 loss had no effect on cytokine levels. At day 7 of anti–PD‑L1 therapy, both IFN-γ and TNF-α showed moderate increases in treated tumors, regardless of GBP2 status (Figs. 2K and S6H). Strikingly, in the late phase of treatment (Day 14), cytokine levels were markedly elevated in control tumors, whereas this increase was blunted in GBP2-deficient tumors, suggesting that GBP2 supports the sustained release of T cell–derived cytokines during late-phase ICB response (Figs. 2K and S6H).

To dissect which cytokine mediates the GBP2-dependent cell death, we co-cultured GBP2-overexpressing tumor cells with OT-1 cells lacking IFN-γ, TNF-α, or perforin. Loss of IFN-γ—but not TNF-α or perforin, abrogated OT‑1-mediated killing of GBP2oe tumor cells (Fig. 2L). These results support previous findings that IFN-γ can trigger ferroptosis in tumor cells and suggest that GBP2 may act within this pathway6,26. Thus, we performed in vivo neutralization experiments. GBP2 overexpression enhanced both anti-PD‑L1 efficacy and lipid ROS accumulation, effects that were completely abolished by anti-IFN‑γ monoclonal antibody treatment, confirming the dependence on IFN-γ signaling (Figs. 2M and S6I). Together, these data suggest that GBP2 acts as a general amplifier of CD8+ T cell–mediated cytotoxicity rather than an ICB-specific effector. GBP2 deficiency attenuated OT-1–driven tumor control even in the absence of PD-L1 blockade, highlighting its fundamental role in IFN-γ–dependent ferroptotic killing of tumor cells. Thus, GBP2 represents a core mediator of T cell cytotoxicity that potentiates the therapeutic efficacy of immune checkpoint blockade.

GBP2 promotes tumor ferroptosis through STAT1/SLC7A11

We next sought to elucidate the molecular mechanism by which GBP2 regulates IFN-γ-induced ferroptosis. Long-chain-fatty-acid-CoA ligase 4 (ACSL4) is a well-established determinant of ferroptosis27, however, GBP2 depletion did not significantly alter ACSL4 expression (Fig. S7A). The cystine/glutamate antiporter system Xc−, consisting of the light-chain subunit (SLC7A11) and the heavy-chain subunit (SLC3A2), mediates extracellular cystine uptake for antioxidant glutathione (GSH) synthesis, thereby limiting lipid peroxidation and suppressing ferroptosis28,29. To explore whether system Xc− participates in GBP2-mediated ferroptosis regulation in melanoma cells, we examined the expression of its subunits. Compared with sgCtrl cells, sgGBP2 cells displayed a marked attenuation of IFN-γ-induced downregulation of SLC7A11 (Fig. 3A), whereas SLC3A2 expression remained unaffected by GBP2 deletion (Fig. S7B). In situ multi-color immunofluorescence staining of clinical melanoma samples revealed that tumors with high GBP2 expression exhibited lower SLC7A11 levels (Fig. 3B).

To determine whether GBP2 regulates ferroptosis via SLC7A11, we silenced SLC7A11 expression in GBP2−/− cells using siRNA (Fig. S7C and Supplementary Table 2). Upon treatment with the ferroptosis inducer RSL3, SLC7A11 knockdown restored the lipid ROS levels that were reduced by GBP2 deficiency in IFN-γ–primed B16-OVA cells (Fig. 3C). Similarly, GBP2 knockout markedly increased intracellular GSH content and cell viability—effects that were reversed by SLC7A11 silencing (Fig. 3D). In vivo, SLC7A11 overexpression significantly blunted the tumor-suppressive effect of GBP2 overexpression, reduced intratumoral levels of lipid ROS, and abolished its ability to potentiate ICB efficacy (Figs. 3E, F and S7D).

We then investigated the upstream mechanism by which GBP2 represses SLC7A11. Previous studies have implicated the STAT1 signaling pathway in SLC7A11 transcriptional regulation30. We therefore assessed whether GBP2 modulates SLC7A11 expression through STAT1 activation in melanoma. As anticipated, GBP2 depletion markedly reduced phosphorylated STAT1 (p-STAT1) levels in B16-OVA and A375 cells (Fig. 3G). Immunofluorescence imaging and nuclear–cytoplasmic fractionation following IFN-γ stimulation further demonstrated impaired nuclear translocation of p-STAT1 in GBP2−/− cells (Fig. 3H). STAT1 is a central regulator of antitumor immunity, orchestrating key ICB response pathways, including MHC-I antigen presentation, checkpoint ligand expression, and cytotoxic lymphocyte (CD8+ T/NK cell) recognition25. To assess whether STAT1-dependent functions were altered by GBP2 deletion, we examined MHC-I levels in B16-OVA and MC38-OVA cells using the PresentER system, which constitutively co-overexpresses OVA and MHC-I components via peptide/MHC complexes31. As a result, these cells constitutively overexpress both OVA antigen and MHC-I molecules, eliminating the possibility that reduced immunotherapy efficacy in the GBP2-knockout context is due to altered MHC-I presentation. Flow cytometry confirmed comparable MHC-I expression between sgCtrl and sgGBP2 cells (Fig. S7E, F). We next assessed PD-L1 expression. Western blot analysis of sgGBP2 cells revealed no significant difference between sgCtrl and sgGBP2 cells under basal or IFN-γ–stimulated conditions (Fig. S7G). To evaluate potential changes in immune recognition, we employed FucoID technology, which quantifies cell-cell interactions via interaction-dependent fucosyl-biotinylation32. No significant difference in CD8+ T/NK cell–tumor cell interaction frequency was detected between sgCtrl and sgGBP2 groups (Fig. S7H). These findings support that while GBP2 modulates STAT1 activation, it does not affect MHC-I expression, PD-L1 levels, or direct lymphocyte–tumor cell interactions in these models.

Based on these findings, we hypothesize that the STAT1/SLC7A11 axis mediates GBP2-driven ferroptosis. STAT1 has been reported to bind to the SLC7A11 promoter, repressing its transcription6. Chromatin immunoprecipitation (ChIP) qPCR demonstrated that GBP2 loss abrogated IFN-γ–induced STAT1 binding to the transcription start site of SLC7A11 in B16-OVA and A375 cells (Fig. S7I). More strikingly, STAT1 knockout in GBP2oe B16-OVA cells abolished the increase in lipid ROS, leading to accelerated tumor growth (Figs. 3I–K and S7J). To exclude off-target effects, GBP2 re-expression in GBP2−/− B16-OVA cells significantly rescued SLC7A11 expression and STAT1 phosphorylation (Fig. S7K). Furthermore, enforced GBP2 expression of GBP2 in GBP2-deficient tumor cells restored lipid ROS accumulation and reinstated sensitivity to anti-PD-L1 in vivo (Fig. S7L, M). Together, these results demonstrate that GBP2 promotes ferroptosis by regulating the STAT1/SLC7A11 axis.

GBP2 undergoes phase separation to form condensates

Next, we investigated how GBP2 regulates the STAT1–SLC7A11 axis to promote ferroptosis. Recent studies have implicated phase separation as a critical mechanism triggering ferroptosis, with IFN-γ shown to induce phase separation of key proteins at high concentrations12,13,33,34. Given that GBP2 is an interferon-stimulated gene and that our results demonstrated GBP2 sensitizes tumor cells to IFN-γ-induced ferroptosis, we hypothesized that GBP2 might form biomolecular condensates via phase separation. To test this, we first analyzed the amino acid sequence of the GBP2 protein using the Predictor of Natural Disordered Regions (PONDR)35, which identified residues 436–579 (GBP2436–579) as an intrinsically disordered region (IDR) (Fig. 4A). To visualize of GBP2 condensates, we generated B16-OVA and A375 cells with a mCherry tag knocked in at the C terminus of endogenous GBP2. Upon IFN-γ stimulation, endogenous GBP2 formed prominent droplet-like condensates that exhibited fusion and aggregation over time (Figs. 4B, C and S8A, B). We also assessed the dynamic properties of these condensates using fluorescence recovery after photobleaching (FRAP), observing >60% fluorescence recovery within approximately 2 min, indicative of liquid-like mobility (Figs. 4D and S8C). To validate our FRAP methodology, glycogen condensates served as a positive control and mCherry alone as a negative control36,37. Glycogen displayed rapid fluorescence recovery, consistent with known liquid-like dynamics (Fig. S8D), whereas mCherry showed negligible recovery, confirming its non-condensing behavior (Fig. S8E). These controls substantiate the dynamic and fluid nature of GBP2 condensates.

Moreover, treatment with 1,6-hexanediol (1,6-HD), which disrupts liquid–liquid phase separation by interfering with hydrophobic interactions, effectively abolished GBP2 puncta formation (Figs. 4E and S9A). To define the role of the IDR, we generated a deletion mutant lacking residues 436–579 (ΔIDR) in the mCherry-GBP2 construct and expressed it in B16-OVA and A375 cells. Considering the potential destabilization effect of removing this segment, recombinant full-length (FL) and ΔIDR GBP2 proteins were purified from E. coli, with Coomassie staining confirming proper folding of the ΔIDR mutant (Fig. S9B). In GBP2−/− B16-OVA cells transfected with FL or ΔIDR constructs, treatments with proteasomal (MG132), autophagic (BafA1), or lysosomal (chloroquine) inhibitors did not significantly affect GBP2 expression levels (Fig. S9C). Importantly, deletion of GBP2436–579 completely abolished condensate formation (Figs. 4F and S9D). Collectively, these data demonstrate that GBP2 forms the dynamic and reversible phase-separated condensates through its intrinsically disordered region, a property likely integral to its function in regulating ferroptosis.

GBP2 condensates retains SHP1 to protect STAT1 activation to promote ferroptosis

Previous studies have reported that the biomolecular condensates formed via phase separation can spatially restrict protein functions, including nuclear regulation or protein–proteins interactions38. To further elucidate whether GBP2 phase separation facilitates ferroptosis, we performed mass spectrometry to identify GBP2-interacting proteins. As a result, SHP1, a known phosphatase involved in dephosphorylating STAT1 in the IFN-γ signaling pathway39, was detected in GBP2-immunoprecipitates (Fig. 5A). This interaction was validated at both endogenous and exogenous levels by co-immunoprecipitation assays (Figs. 5B and S9E). Functionally, SHP1 knockdown in GBP2−/− cells substantially restored STAT1 phosphorylation and further suppressed SLC7A11 expression (Figs. 5C, S9F and Supplementary Table 2). We hypothesized that GBP2 modulates SHP1 activity through phase separation. Confocal microscopy revealed that GBP2 and SHP1 co-localize within droplet-like condensates in IFN-γ–treated B16-OVA cells, supporting a spatial sequestration model (Fig. 5D).

To investigate the functional relevance of GBP2-SHP1 condensates, we compared full-length GBP2 (FL) with the IDR deletion mutant in GBP2−/− cells. The ΔIDR mutant exhibited diminished IFN-γ–induced phase-separated compartments, accompanied by reduced STAT1 tyrosine phosphorylation and impaired nuclear translocation (Figs. 5E, F and S9G). Correspondingly, IDR deletion led to decreased lipid ROS levels and elevated intracellular GSH upon RSL3 treatment (Fig. S9H, I). Co-immunoprecipitation experiments further demonstrated direct SHP1–STAT1 binding, which was significantly enhanced in GBP2 knockout cells (Fig. S9J). High-resolution imaging confirmed the endogenous co-localization of GBP2 and SHP1 condensates, indicating that GBP2 physically sequesters SHP1 under physiological conditions (Fig. 5G). These findings support our central hypothesis that GBP2 condensates function as spatial regulators by enriching and isolating SHP1. To dissect this mechanism in vitro, we purified recombinant GBP2, SHP1, JAK2, and STAT1 proteins from E. coli, 293T, and Sf9 systems. Pre-formed GBP2 condensates were incubated with SHP1 before assessing STAT1 phosphorylation. Without GBP2 condensates, p-STAT1 levels rapidly decreased due to SHP1-mediated dephosphorylation. In contrast, the presence of GBP2 condensates preserved STAT1 phosphorylation, indicating effective SHP1 sequestration and impaired phosphatase activity (Fig. 5H). Similar results were observed with the ΔIDR mutant, which failed to form condensates and hence could not sequester SHP1 (Fig. 5I). Furthermore, fusion of GBP2 with a hydrophilic maltose-binding protein (MBP) tag to reduce self-association disrupted condensate formation and SHP1 sequestration in vitro, resulting in decreased STAT1 phosphorylation compared to wild-type GBP2 (Fig. 5J). Collectively, these results demonstrate that GBP2 phase separation is essential for sequestering SHP1 and sustaining STAT1 signaling, robustly supporting our claims regarding the functional role of phase separation.

In vivo, introducing GBP2436-579 significantly impaired GBP2-FL-mediated lipid ROS accumulation, accelerated tumor growth, and attenuated anti–PD-L1 therapy efficacy (Fig. 5K, L). Comparable results were observed in OT-1 adoptive cell therapy models (Fig. S10K–M). Co-immunoprecipitation from PD-L1-treated tumors revealed enhanced STAT1-SHP1 binding and decreased STAT1 phosphorylation in GBP2-ΔIDR tumors (Fig. 5M). Furthermore, in vivo phase separation could observe aggregation foci under immunofluorescence36. We performed immunofluorescence staining on these tumor specimens and visualized distinct GBP2 aggregate foci in GBP2-FL tumors following anti-PD-L1 treatment, whereas such structures were absent in GBP2-ΔIDR tumors (Fig. 5N). These findings convincingly demonstrate that CTL-secreted IFN-γ promotes GBP2 phase separation, facilitating SHP1 sequestration, which sustains STAT1 activation, represses SLC7A11 transcription, and induces ferroptosis.

GBP2 promotes the intratumoral CD8+ T cell infiltration through enhancing the immunogenicity of ferroptotic cells

Next, we aimed to investigate the impact of GBP2 on the tumor immune microenvironment (TME) under ICB therapy. We first analyzed the correlation between GBP2 and TME in melanoma patients using the ssGSEA algorithm to estimate the abundance of 28 immune cell types across six cohorts. GBP2 expression was strongly associated with an inflamed immune microenvironment, showing a significant positive correlation primarily with CD8⁺ T cells (Fig. S10A). To validate these findings experimentally, we performed flow cytometry on tumor-infiltrating leukocytes from anti‑PD‑L1–treated sgGBP2 and sgCtrl tumors. Applying the established gating strategies40, we quantified the major immune subsets, including CD8⁺ T cells, CD4⁺ T cells, NK cells, B cells, neutrophils, monocytes/macrophages, and dendritic cells (DCs) (Fig. S10B). Anti-PD-L1 treatment significantly increased the proportions of CD8⁺ T cells, CD4⁺ T cells, NK cells and B cells. Critically, GBP2 deletion substantially reduced infiltration of CD8⁺ T cells regardless of PD-L1 treatment, while CD4⁺ T cells, DCs, B cells, NK cells, macrophages, and neutrophils were unaffected (Fig. 6A). Similarly, flow cytometry revealed that CD8+ OT-1 cell was markedly lower in GBP2-/- tumors compared to controls (Fig. 6B, C). Given the pivotal role of CD8+ T cells in antitumor immunity, we depleted CD8+ T cells in vivo and observed that tumor growth in the oeGBP2 group was increased (Fig. 6D), underscoring the dependence of GBP2-mediated tumor suppression on CD8⁺ T cells. Furthermore, flow cytometric analysis of CD8⁺ T cell activation markers showed that GBP2 ablation markedly attenuated IFN-γ⁺ and TNF-α⁺ CD8⁺ T cell frequencies (Fig. 6E). Analysis of a single-cell RNA sequencing data (GSE115978) from 32 melanoma patients using t-distributed stochastic neighbor embedding (t-SNE) identified 25 cell clusters into 8 major immune cell types based on canonical marker expression (Fig. S10C). Notably, the five patients with highest GBP2 expression exhibited significantly increased CD8⁺ T cell infiltration (Figs. 6F and S10D). Immunofluorescence staining of further corroborated GBP2-FL tumors following anti-PD-L1 harbored greater CD8⁺ T cell infiltration (Fig. 6G). Collectively, these data demonstrate that GBP2 shapes an immunostimulatory TME, potentiating CD8+ T cell-mediated antitumor immunity.

Recent studies have revealed that ferroptotic tumor cells release damage associated molecular patterns (DAMPs), conferring an immunogenic cell death (ICD)-like phenotype41. Importantly, ICD promotes the recruitment and activation of DCs, which facilitate tumor antigen presentation to CTL, enhancing CD8+ T cell infiltration and activation42. Since GBP2 significantly potentiates CTL-induced ferroptosis, we hypothesized that GBP2 promotes CTL-mediated killing by triggering the ICD feature in ferroptotic tumor cells. To test this, we measured levels of the DAMP high-mobility group box 1 (HMGB1) in tumor tissues from mouse models. ELISA revealed that GBP2 deficiency significantly reduced HMGB1 release under both anti-PD-L1 and OT-1 therapies (Fig. S11A). Concordantly, GBP2−/− tumors exhibited decreased expression of DC maturation markers, including the co-stimulatory molecules CD80 and CD86 (Fig. S11B). Analysis of single-cell data also showed elevated CD86 expression in patients with high GBP2 expression (Fig. S11C). Deletion of STAT1 in GBP2-overexpressing tumors significantly reduced HMGB1 levels, while SLC7A11 overexpression rescued the GBP2-induced HMGB1 upregulation (Fig. S11D, E). Furthermore, HMGB1 knockout in GBP2-overexpressing B16-OVA cells accelerated tumor growth in vivo, accompanied by diminished CD8⁺ OT-1 T cell infiltration and reduced CD80/CD86 expression (Fig. S11F–I). Together, these results suggest that GBP2 enhances the immunogenicity of ferroptotic tumor cells through HMGB1 release, thereby promoting CD8⁺ T cell infiltration in melanoma.

GBP2 facilitates ICB response in tumor patients

Next, we sought to validate the correlation between GBP2 expression and ICB response in human melanoma. We compared three established predictive signatures for ICB response: T cell inflamed expression profile (GEP), innate anti-PD-1 resistance (IPRES) and immuno-predictive score (IMPRES) signatures43–45. Higher enrichment scores of all three signatures were observed in the high GBP2 expression group across multiple melanoma cohorts (Figs. 7A and S12A–D). Using SubMap analysis to compare GBP2 expression profiles with a published melanoma immunotherapy dataset46, the high GBP2 group demonstrated significant similarity to the PD-1 responder group across five cohorts (Figs. 7B and S12E–H). Additionally, we analyzed a cohort comprising pre-treatment (PRE) biopsies taken prior to immunotherapy (n=73), and early during treatment (EDT) samples (7–14 days post-treatment initiation, n=18) (Supplementary Dataset 2). PRE samples with high GBP2 expression exhibited markedly improved clinical responses to ICB compared to low GBP2 samples. Conversely, patients with high SLC7A11 expression showed increased ICB resistance (Figs. 7C and S13A). More importantly, stratifying PRE samples by GBP2 and SLC7A11 expression yielded three groups: group 1 (high GBP2/low SLC7A11), group 2 (low GBP2/low SLC7A11 or high GBP2/high SLC7A11), and group 3 (low GBP2/high SLC7A11). Group 1 displayed the highest percentage of complete or partial responses (CR/PR), while group 3 had the lowest (Fig. 7D). Due to limited EDT samples, direct comparison revealed elevated GBP2 expression in ICB responders versus non-responders (Fig. S13B). Survival analyses indicated that among ICB-treated patients, the high GBP2 group had superior prognosis compared to the low GBP2 group, whereas high SLC7A11 predicted poorer outcomes (Figs. 7E and S13C). Moreover, group 1 exhibited the most favorable survival outcome, followed by group 2, with group 3 demonstrating the shortest OS (Fig. 7F). Similar patterns of elevated GBP2 expression in ICB responders were observed in metastatic urothelial carcinoma and non-small cell lung cancer cohorts47,48, where high GBP2 expression also predicted better prognosis (Fig. S13D, E).

To explore spatial heterogeneity, we analyzed spatial transcriptomics data from a hepatocellular carcinoma (HCC) dataset, dividing tissue slices into malignant, boundary, and non-malignant regions (Figs. 7G and S13F). Responders exhibited higher GBP2 and lower SLC7A11 expression in malignant areas, accompanied by increased CD8⁺ T cell infiltration, compared to non-responders (Figs. 7H and S13G). Finally, immunohistochemistry (IHC) of melanoma samples validated that high GBP2 expression correlated with reduced SLC7A11 levels (Fig. 7I). Together, these findings indicate that elevated GBP2 predicts improved OS and better ICB response in tumor patients.

Methods
Humans samples and animals
All melanoma cases were pathologically confirmed by two independent pathologists, and only treatment-naïve samples from patients without other malignancies were included. Only clinical samples collected in excess of those needed for diagnostic and therapeutic procedures were used for research. All participants provided written informed consent for the collection and subsequent analysis of their samples and clinical data. Twelve resected human melanoma tissues were obtained from patients at Zhongnan Hospital of Wuhan University. The information of patients is shown in Supplementary Table 3. Six-week-old female and male C57BL/6 mice and NOD. Cg-Prkdcscid Il2rgtm1Wjl/SzJ (NSG) mice were purchased from the Hubei BIONT Biological Technology Co., LTD. OT-1 mice were purchased from the Jackson Laboratory. Sex specific differences were not investigated as the study focused on general treatment efficacy rather than sex-related outcomes.

Animal model and treatment protocols
C57BL/6 mice were subcutaneously injected with sgCtrl and GBP2−/− B16-OVA or MC38-OVA cells (1×106/ml). When the tumors had grown to 125 mm3, the C57BL/6 mice were randomized into different groups. The anti-PD-L1 antibody (200 μg per mouse) and IgG isotype were administered intraperitoneally every 3 days until the end of the observation period.

For CTL killing in vivo, OT-1 cells are first isolated and enriched. In detail, after grinding the spleen to obtain a single-cell suspension, the suspension was placed in 2 ml of red blood cell lysis buffer (Sigma Aldrich) for 1 min. Then, CD8+ OT-1 cells were purified using EasySep mouse CD8+ T Cell Isolation Kit (Stemcell). The CD8+ OT-1 cells were cultured at 2×106/ml in RPMI culture medium containing 2 nM OVA 257-264 (SIINFEKL), 10 ng/mL human recombinant IL-2, and 50 μM 2-mercaptoethanol. The cells were incubated at 37°C for 5 days. Finally, C57BL/6 mice were subcutaneously injected with cells as indicated. Enriched OT-1 cells (5×106/ml per mouse, every 7 days) were resuspended into 200 μl PBS and intravenously injected into tumor-bearing mice. All the tumor volume (mm3) was measured and calculated as follows: formula: V = a × b × b / 2.

Cell culture and reagents
A human melanoma cell line (A375), mouse melanoma cell line (B16-OVA), mouse colon carcinoma cell line (MC38-OVA) and human HEK 293T cells were obtained from the Cell Resource Centre of Peking Union Medical College (Beijing, China). All cells were cultured in RPMI 1640 medium (Hyclone, USA) with 10% fetal bovine serum (Gibco, Australia) and 1% penicillin-streptomycin at 37°C with 5% CO2. All cell lines were authenticated by short tandem repeat (STR) fingerprinting and tested to confirm no mycoplasma contamination and used in the experiments were within 20 passages. Human and murine recombinant IFN-γ were purchased from PeproTech. The in vivo murine anti-PD-L1 antibody (BE0101) and IgG isotype (BE0089) were purchased from BioXCell. The ferroptosis agonizts RSL3 (S8155) and inhibitor ferrostatin-1 (Fer-1, S7243) were purchased from Selleck.

CRISPR–Cas9-mediated genome editing
The CRISPR/Cas9 based on pX459 plasmid was constructed. The guide RNA sequences were listed in Supplementary Table 1. For CRISPR/Cas9 plasmid transfection, B16-OVA and A375 cells were transfected according to instructions for the lipofectamine 2000 and sorted by puromycin to acquire a monoclonal cell line. Finally, the GBP2−/−, HMGB1−/− and STAT1−/− cells were identified via western blotting and cultured for further analysis.

Stable overexpressing cell line construction
To generate stable GBP2 overexpressing cells, Pspax2, pVSV-G and constructed Plvx-IRES-Puro or empty vector were transfected into HEK 293T cells using lipofectamine 2000. The supernatants containing viruses were added in B16-OVA with multiplicity of infection (MOI) at 5:1 and with the concentration of Polybrene at 8 μg/ml and the infection lasted for 12 h. After 48 h infection, puromycin was added to cells and the cells were treated with concentration at 1.5 μg/ml. The treatment lasted for 3 days, and the cells were kept in puromycin in half of the concentration for stable selection.

Lipid ROS detection
For the detection of lipid ROS in vivo, tumor tissues were chopped, ground, and filtered to form a single-cell suspension. Then, the density gradient centrifugation (Ficoll, Sigma-Aldrich) was used to pre-enrichment. Finally, the cell pellet was stained with anti-CD45 (30-F11) and anti-OVA 257–264 -H2Kb (25-D1.16) antibodies. Afterwards, 5 μM BODIPY-C11 (D3861, Thermo Fisher Scientific) staining were performed and incubated at 37°C for 30 min. The signal of oxidized C11 was immediately analyzed using flow cytometry.

For the detection of lipid ROS in vitro, B16-OVA cells (2×104/ml) co-cultured with activated OT-1 (B16-OVA:OT-1 ratio of 5:1) for 24 h followed by treatment with 10 μM Fer-1 for an additional 24 h. OT-1 cells were removed via gently washing several times with PBS. Then, the 5 μM C11-BODIPY 581/591 working solution was added and incubated with cells for 30 min in the incubator. Ready-to-use DAPI staining solution (C1005, Beyotime, China) was used to stain the nuclei for 5 min. After washing twice, the cells were covered with HBSS, and the images of oxidized C11 (wavelength 505–550 nm) were captured using a fluorescence microscope.

Cell viability detection
Cell viability was measured using a CellTiter-Glo Luminescent Cell Viability Assay kit (Promega), which is based on the luciferase reaction to measure the amount of ATP from viable cells. The amount of ATP in the cells correlates with cell viability.

Western blot
First, total protein fractions of melanoma cells were obtained using NP40 lysis buffer (Beyotime, China). The BCA kits (Beyotime, China) were used to determine the concentration of the protein fractions. Then, 30 μg of protein from each group was run on a 10% SDS-PAGE gel and transferred to polyvinylidene fluoride (PVDF) membranes (Millipore, USA). The PVDF membranes were blocked with 5% fat-free milk and incubated overnight at 4°C with the appropriate primary antibodies: GBP2 (11854-1-AP, Proteintech, USA), p-STAT1 (#9167, CST, USA), STAT1 (#14994, CST, USA), SLC7A11 (#98051, CST, USA), SLC3A2 (15193-1-AP, Proteintech, USA), ACSL4 (22401-1-AP, Proteintech, USA), PD-L1 (17952-1-AP, Proteintech, USA), HMGB1 (10829-1-AP, Proteintech, USA), SHP1 (24546-1-AP, Proteintech, USA), and GAPDH (10494-1-AP, Proteintech, USA). Finally, enhanced chemiluminescence reagents (Thermo, USA) were applied to detect the bands after incubation with secondary antibody (GB23303, Servicebio, China).

Flow cytometric analysis of tumor-infiltrating immune cells
B16-OVA cells were subcutaneously injected into mice, which were then treated with anti–PD-L1 antibody as described in the animal section. On day 21 after treatment, tumors were harvested, weighed, mechanically minced, and digested with collagenase IV (2 mg/mL; Sigma-Aldrich) and DNase I (50 μg/mL; Sigma-Aldrich) for 1 h. The resulting cell suspension was triturated and passed through a 70 μm cell strainer to obtain a single-cell suspension. Cells were blocked with anti-mouse CD16/32 antibody (BioLegend) and stained with the indicated antibodies on ice for 30 min. Live/Dead Aqua dye (1:1,000; Thermo Fisher Scientific) was added together with surface antibodies to exclude dead cells. After washing, cells were fixed and permeabilized using the Foxp3/transcription factor staining buffer set (eBioscience) according to the manufacturer’s instructions, blocked with mouse and rat serum, and then stained with intracellular antibodies. All stained cells were analyzed on an Attune NxT systems and the data was analyzed with FlowJo version 10 software.

ELISA assay
Cytokine production in the homogenate supernatant from tumor tissue was quantified by ELISA kits (R&D Systems) according to the manufacturer’s protocol.

Protein expression, purification, and in vitro kinase assay
To obtain recombinant wild-type (WT) proteins, their corresponding mutants, MBP-tagged, or fluorescent GBP2 proteins, E. coli BL21 (DE3) cells harboring the respective constructs (pGEX vector) were cultured in LB medium supplemented with 50 μg/mL kanamycin. Protein expression was induced overnight at 18°C with 0.1 mM IPTG once the OD600 reached 0.8. Cells were lysed in a buffer containing 20 mM Tris-HCl (pH 7.4), 150 mM NaCl, 1 mM DTT, 1 mM PMSF, and 1 mg/mL lysozyme. Fusion proteins were purified by affinity chromatography using glutathione-Sepharose resin (GE Healthcare Life Sciences, USA). The purity of the purified GBP2 was evaluated by electrophoresis on a 10% polyacrylamide gel, followed by Coomassie Blue staining and immunoblotting. Human SHP1 was expressed in E. coli BL21 (DE3) cells using an N-terminal strep-tag construct. Protein expression was induced with IPTG at 18°C overnight, and the protein was purified by Ni2+-affinity chromatography followed by size-exclusion chromatography. JAK2 was expressed in HEK293T cells by transient transfection, and the protein was isolated from cell lysates using anti-FLAG affinity resin and further purified by gel filtration. STAT1 was produced in Sf9 insect cells using the baculovirus expression system, and purified through Ni2+ affinity chromatography and size-exclusion chromatography.

For in vitro kinase assays, purified STAT1 was incubated with JAK2 in kinase buffer (50 mM HEPES pH 7.5, 10 mM MgCl₂, 1 mM DTT, 100 μM ATP) at 30°C. When indicated, GBP2 or SHP1 was added after phosphorylation to examine dephosphorylation. Reactions were terminated by adding SDS sample buffer and analyzed by SDS‑PAGE and immunoblotting with phospho-specific antibodies.

In vitro T cell killing assay
Differentially labeled, B16-OVA cells were seeded into 12-well plates in DMEM supplemented with 10% FBS. After 24 h, the medium was replaced with RPMI containing 10% FBS and preactivated OT-I T cells at the indicated effector-to-target ratios. After 24 h of co-culture, tumor cells were harvested and analyzed by flow cytometry to assess cell viability.

In vitro and cellular phase separation assay
Phase separation of recombinant wild-type or MBP-tagged mCherry‑GBP2 proteins with recombinant GFP‑tagged SHP1 was examined in LLPS buffer (40 mM Tris-HCl pH 7.4, 150 mM NaCl, and 1.25% PEG8000). Protein mixtures were gently mixed and incubated at room temperature, and 10 μL of the reaction was placed on a glass slide, covered with a coverslip, and immediately imaged using a confocal microscope.

Generation of endogenously tagged GBP2-mCherry cell line
CRISPR–Cas9 with a single guide RNA (sgRNA) targeting the endogenous GBP2 locus was used to insert a mCherry sequence immediately before the stop codon in B16-OVA. An oligonucleotide encoding this sgRNA (TGAAGCAAAACAAATCGTCT) was cloned into pX330, which also encodes Cas9 (Addgene no. 42230). Six hundred thousand B16-OVA cells were seeded and transfected with 0.5 μg pX330/sgRNA vector and 1 μg repair template, consisting of mCherry flanked by 800-base pair (bp) homology arms using lipo2000. One week later, mCherry-positive cells were collected by sorting and single-cell clones were generated. Successful targeting was verified by sequencing.

Live cell imaging
Cells were grown on poly-l-lysine-treated no. 1.5 cover glass chambers (Lab-Tek) for 24 h. Before imaging, culture medium was replaced with RPM-1640 (Thermo Fisher) supplemented with 10% FBS and 1× GlutaMAX (Thermo Fisher). Cells were imaged with a Nikon A1R+ confocal microscope with a 60× oil objective and a Nikon A1 camera equipped with a heated stage (37°C) and 5% CO2 environment.

Fluorescence recovery after photobleaching
FRAP was performed using a Nikon A1R+ microscope with a 488-nm or 561-nm laser. For FRAP experiments on GBP2 condensates in living cells, the entire punctum, typically less than 1 μm in diameter, was photobleached using 70% laser power, before time-lapse imaging. Fluorescence intensity in the photobleached region was measured using ImageJ and values were normalized to pre-bleach time points.

Coimmunoprecipitation (CoIP)
Total protein fractions were collected for CoIP with indicated antibody according to the manufacturer’s protocol using an IP/CoIP kit (Absin, China). In brief, 293T, A375, and B16-OVA cells were lysed with IP buffer (P0013J, Beyotime, China) containing protease and phosphatase inhibitors for 45 min at 4°C. The cell lysates were precleared with protein A/G-agarose beads for 1 h and then incubated with IgG, indicated antibody, overnight at 4°C with continuous inversion. The cell lysates were precipitated with protein A/G-agarose beads for 4 h and then the immunoprecipitated beads were washed five times the following day. Bound proteins were eluted and subjected to immunoblot analysis with indicated antibodies.

siRNA transfection
The human and mouse SHP1 and SLC7A11 siRNAs were purchased from Ribobio (Guangzhou, China). B16-OVA and A375 cells was transfected with siRNA using lipofectamine 2000 (Invitrogen, USA). Scramble siRNA was used as a control. Sequences of siRNAs were listed in the Supplementary Table 2.

Chromatin immunoprecipitation assay (ChIP)
A Sonication ChIP kit (Abclonal, China) was used to perform the ChIP assay according to the manufacturer’s instructions. Briefly, 1×107 cells were cross-lined with 1% formaldehyde for 8 min at room temperature. Then, fixed cells were harvested, lysed, and sonicated on ice with several pulses and incubated for 30 s on ice between pulses. The sheared chromatin fragments were immunoprecipitated with antibodies against STAT1 (5 μl per 1 mg total protein) and rabbit IgG (2 μl per 1 mg total protein). After elution and decross-linking, the enriched DNA fragments were purified by universal DNA purification kit (DP214, TIANGEN). The primer sequences used for ChIP-qPCR are listed in the Supplementary Table 4.

Multiplex immunofluorescence analysis and IHC analysis
Multiplex immunofluorescence staining was obtained using PANO 3-plex IHC kit (Panovue, Beijing, China). The primary antibodies of GBP2 (27299-1-AP, Proteintech, USA), SLC7A11 (ab307601; Abcam, USA), and CD8A (A11856, ABclonal, USA) were sequentially applied, followed by horseradish peroxidase-conjugated secondary antibody incubation and tyramide signal amplification (TSA). The slides were microwave-treated after each TSA operation. Nuclei were stained with DAPI after all the human antigens had been labeled. In addition, standard immunohistochemistry protocol was also performed using the above antibodies60.

Immunofluorescence
Collected cells were spun down onto a coverslip, fixed in 4% paraformaldehyde and permeabilized with 0.2% Triton X-100. Fixed cells were blocked in 5% BSA and probed with anti-p-STAT1 (#9167, CST, USA) antibody in 5% BSA, followed by Alexa Fluor® 488 Goat anti-rabbit (ab150077, Abcam, USA) and the slides were further counterstained with DAPI and mounted for confocal analysis and the fluorescent image was observed under a fluorescent microscope.

The glutathione (GSH) assay
The reduced (GSH) assay kit (Nanjing Jiancheng) was used to quantitatively analyze the levels of intracellular GSH according to the supplier’s instructions.

Datasets collection
In this work, 7 independent melanoma cohorts were selected, including a total of 1076 melanoma patients: skin cutaneous melanoma (SKCM) from The Cancer Genome Atlas (TCGA); GSE6590461; GSE840162; GSE5945563; GSE318964; GSE11597865 and PRJEB2370966. The upper quartile fragments per kilobase of transcript per million mapped reads (FPKM-UQ) for SKCM were downloaded from the UCSC Xena browser (https://xenabrowser.net/datapages/). The PRJEB23709 cohort was obtained from the Tumor Immunotherapy Gene Expression Resource database (http://tiger.canceromics.org/#/download)67. The remaining five cohorts were all downloaded from the Gene Expression Omnibus database (http://www.ncbi.nlm.nih.gov/geo/). Detailed information of above datasets is shown in Supplementary Dataset 3.

Bioinformatic analysis
The relative abundance of 28 immune cell infiltration in each melanoma sample was quantified via ssGSEA (Supplementary Dataset 4)68,69. We used the “limma” R package to screen the differentially infiltrating cells in the tumors separated by median GBP2 expression (high versus low). An unsupervised subclass mapping method (SubMap) (GenePattern module ‘SubMap’) (https://cloud.genepattern.org) was used to identify common subgroups between independent cohorts despite their technical differences70. A melanoma dataset including anti-PD-1 and anti-CTLA4 therapy was applied to measure the similarity with high- and low-GBP2 groups in other melanoma datasets included in this study46. The spatial tumor microenvironment (SpatialTME) database was used to analyze the spatial transcriptome of one melanoma samples (https://www.spatialtme.yelab.site/#!/search/Visium/Melanoma_10x/Melanoma_IFStainedFFPE_CytAssist_10x)71. A spatial transcriptome dataset of hepatocellular carcinoma (HCC) containing ICB therapy was also used to validate our results72. For survival analysis, Kaplan–Meier survival curves and log-rank tests were used to evaluate the outcomes of melanoma patients in the with high- and low-GBP2 groups according to “survival” R package.

Gene set enrichment analysis (GSEA) and gene ontology (GO) functional annotation
GSEA was used to enrich the significant gene sets between the high- and low-GBP2 groups. The gene sets of “H.all.v7.4” were downloaded from the Molecular Signatures Database and used as the reference set to represent well-defined biological states or processes. Additionally, Gene Ontology (GO) functional enrichment analysis was performed using the DAVID database (https://david.ncifcrf.gov/)73. The GTP binding protein were collected from the GO term of GTP binding (GO: 0005525) according to the quickGO website (https://www.ebi.ac.uk/QuickGO/) (Supplementary Dataset 5).

Weighted gene coexpression network analysis (WGCNA)
First, raw data of GSE8401 were preprocessed with RMA background correction, log2 transformation, and quantile normalization, and then the median-polish probeset summarization was applied through the “Affy” R package74. The probes were annotated through the “hgu133a.db” R package. GSE8401 was assessed by sample clustering according to the distance between different samples in Pearson’s correlation matrices. Using a cutoff height of 60, no samples were removed (Fig. S1A). Genes were filtered by median absolute deviation (MAD) since low-expressed or non-varying genes usually represent noise. The “WGCNA” R package was used to construct a coexpression network according to the top 5000 genes sorted by MAD74,75. Then, we calculated the Pearson’s correlation matrices for all paired genes. A weighted adjacency matrix was further constructed using a power function a = |c |β (c = Pearson’s correlation between gene m and gene n; a = adjacency between gene m and gene n). β was a soft thresholding parameter that could emphasize strong correlations between genes and penalize weak correlations. The power of β = 6 was selected as a soft threshold to ensure a scale-free network (Fig. S1B–E). Moreover, the adjacency was transformed into a topological overlap matrix (TOM) that could measure the network connectivity of a gene and is defined as the sum of its adjacency with all other genes for network generation76. The average linkage hierarchical clustering was used to classify genes with similar expression profiles into different modules with a minimum gene group size of 3077. Finally, we used the module eigengenes (MEs) to identify gene modules of interest related to phenotype. MEs were deemed as the first principal component in the principal component analysis for each gene module, which summarizes the expression patterns of all genes into a single characteristic expression profile within a given module.

Statistical analysis and reproducibility
All experiments were performed at least three independent experiments. All results are shown as means ± SD. Comparisons between two unpaired groups were evaluated by two-tailed Student’s t test. Two-tailed unpaired Student’s t-test and ANOVA with multiple comparisons were used to calculate P values. Correlations between groups were determined by Pearson’s correlation test. The numbers of samples and independent biological experimental repeats are indicated in the figures or figure legends. The P < 0.05 was considered statistically significant. The analysis was conducted using the GraphPad 8.0 software and R 4.1.3 software.

Ethical statement
The study was conducted in accordance with the principles outlined in the Declaration of Helsinki and was approved by the Ethics Committee of Zhongnan Hospital of Wuhan University (approval No. ZN2024028K). C57BL/6 mice, NOD. Cg-Prkdcscid Il2rgtm1Wjl/SzJ (NSG) mice and OT-1 mice, C57BL/6-Tg(TcraTcrb)1100Mjb/J were housed under specific pathogen free conditions. These animals were specific pathogen-free and maintained in 6 animals per group on a 12/12-h light/dark cycle at 20–26°C with around 40–70% humidity, and given ad libitum access to standard food and water. All procedures involving mice and research protocols were approved by the Experimental Animal Welfare Ethics Committee, Zhongnan Hospital of Wuhan University (approval No. ZN2024072) and the Ethics Committee of the Experimental Animal Care of Beijing Chest Hospital, Capital Medical University (approval No. XK-2025-059). The maximal tumor size permitted by the ethics committee is 1500 mm3. Throughout this study, this tumor size limit was strictly monitored and was not exceeded in any of the experimental animals.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This manuscript explores the role of GBP2 in immunogenic ferroptosis and ICB response in tumors, an intriguing and relevant topic in cancer immunotherapy. The authors provide a detailed analysis integrating bioinformatics, in vivo models, and molecular analyses to establish a link between GBP2, phase separation, and STAT1 activation in the tumor microenvironment. However, in some cases, the conclusions are based solely on correlations and require further validation to fully support the proposed model.\n1. CRISPR/Cas9 Off-Target Effects: The use of CRISPR/Cas9 technology can lead to off-target mutations. How did the authors verify that the generated cell lines do not carry unintended genetic alterations? A proper validation should be included to ensure the accuracy of the reported data.\n2. IFN-γ and Ferroptosis: The authors suggest that IFN-γ induces ferroptosis via GBP2; however, this is not supported by experimental data. To clarify this, cytokine levels should be measured in tumours derived from GBP2-/- and control cells (with or without ICB) to assess IFN-γ and other relevant cytokines in the tumour microenvironment. This would also help determine the inflammatory status in the presence or absence of GBP2 in the context of ICB. Additionally, in vivo IFN-γ blocking experiments should be performed to establish a functional link between GBP2 and IFN-γ.\n3. FRAP Analysis: The FRAP data presented are incomplete. To fully characterize GBP2 phase separation properties, appropriate controls should be included, such as a protein known to form condensates and a protein known to remain solubilized. This comparison would help determine whether GBP2 phase separation follows a typical liquid-liquid phase separation behaviour.\n4. GBP2ΔIDR and ICB Response: The authors demonstrate that GBP2ΔIDR reduces CD8+ OT-1 cytotoxicity; however, they do not assess whether GBP2 phase separation is required for ICB efficacy in vivo. A murine model with GBP2ΔIDR + anti-PD-L1 should be used to determine if GBP2 condensation is necessary for a successful ICB response.\n5. Immune Infiltration Profiling: The authors suggest that GBP2 may modulate immune responses by promoting immunogenic cell death. Since this mechanism has significant implications for immune cells, a more comprehensive analysis of tumour-infiltrating leukocytes should be performed. This should not be limited to CD8+ T cells and DCs but should include a full leukocyte profile in mice transplanted with GBP2-/- and sgGBP2 tumour cells, with or without ICB therapy. Additionally, the authors should assess whether CD8+ T cells show increased activation in sgGBP2 tumours.\n6. Manuscript Readability and Clarity: The manuscript should be carefully revised to improve clarity and readability. Lines 273-275 contain a sentence that appears incorrect and contradicts the data presented. Please revise this section for accuracy.", "reviewer_2": "Summary:\nLiu et al performed a weighted network correlation analysis of immune checkpoint blockade-treated patients and identified GBP2 as a potential driver of ICB response. They find that loss of GBP2 ablates PD-L1 response in mouse models and argue that GBP2 acts to enhance T-cell-mediated ferroptosis via modulation of SLCA11 in an IFN-dependent manner. They further argue that GBP2 forms phase-separated condensates that sequester SHP1 and thereby promote STAT1 phosphorylation and subsequent induction of SLCA11. They seek to validate this finding in patient cohorts and argue that GBP2 acts to support ferroptosis, immunogenicity cell death and HMGB1 expression.\nOverall the group presents a large body of intriguing data. The finding that GBP2 modulates and supports IFNg / STAT1 signaling via phase separated sequestration of SHP1 is interesting. They separately show that GBP2 loss impairs ferroptosis and that this impairment can be overcome by SLCA11 knockdown. Each of these findings represents a meaningful contribution to the field and, in particular, the work supporting SHP1 sequestration by GBP2 seems to me to be a strength. That said, there are also some concerns with the paper as currently constructed.\nMajor Concerns:\nThere are some logical leaps that I worry are not fully justified by the data. For example, because loss of GBP2 affects STAT1 signaling and STAT signaling affects many pathways of immunotherapy response (not least, MHC-I expression, expression of checkpoint ligands, CD8+ T cell and NK cell recognition), I am not sure that the data connecting GBP2 with ferroptosis and the data connecting GBP2 with immunotherapy response are necessarily connected. The authors could strengthen this connection by testing whether SLCA11 overexpression in tumor cells ablates the in vivo GBP2 PD-L1 response phenotype they observe. I would also recommend evaluating alternative or complementary hypotheses by testing the expression of other IFN-stimulated genes such as MHC-I in GBP2 ko cell lines. Finally, the authors rely heavily on a single mouse model for in vivo studies and could benefit from repeating core findings (e.g. GBP2 sensitization to PD-L1) in an additional model to support its robustness.\nI am additionally concerned about the potential for circular reasoning in the patient correlative studies: better clinical responses with GBP2, more immunogenic tumor cell death or more CD8+ T cells may not be all that surprising given that GBP2 is an ISG. Indeed, correlations are presented between IFN-signatures (composed of ISGs) and GBP2. In this case it seems quite possible that cause and effect may be reversed– that GBP2 expression is the effect of ISG induction rather than the cause, as is claimed. By comparison, analysis could equally be conducted simply asking if IFN signaling in tumors correlates with CD8+ T cell infiltration or whether they respond better to immunotherapy–both well established observations in the field.\nThe manuscript would benefit from editing for grammar in several places and rewriting in some others. I did not, for the most part, try to enumerate grammar or style issues. However, examples include:\n- Spelling and usage in the title: consider ‘promote’, not ‘promotes’; ‘sensitize’, not ‘sensitive’\n- Consider referring to immune checkpoint blockade as simply ‘ICB’ rather than ‘the ICB’\n- Line 79: consider ‘augments’, not ‘augment’, ‘limits’, not ‘limit’.\nSpecific Points:\n- Please add quantitative axes for flow plots\n- Fig 1: this analysis is generally correlational, which can lend to false positives. In particular, the authors ultimately correlate an ISG (GBP2) with a signatures for ISGs (e.g. IFNg signature). That said, this is probably ok in Fig 1, as the exercise is hypothesis-generating and sets up the rest of the work.\n- Why is GBP2 considered a ‘combinatorial ICB treatment biomarker’ at the end of Fig 1, rather than simply a biomarker? Also, is it thought to be prognostic or predictive?\n- Fig 2: although the statistics shown look very significant, the difference in tumor volume appears modest for Fig 2 A, C. Indeed, it appears that PD-L1 treatment was not particularly effective in this model. It is likely worth testing other models in which PD-L1 blockade is more effective to see if the phenotypes are reproducible / stronger there.\n- Fig 3A: Please quantify Western blots if reporting significance.\n- Fig 4: It would strengthen the conclusions to repeat at least some of these experiments in another cell line\n- Fig 5K: It seems important to show expression and stability of the delta IDR GBP2 protein (unless I missed this data)– otherwise it may mis-fold or be unstable and effectively just knock the protein down.\n- Is GBP2 genetically lost / selected against in tumors? The authors’ findings would predict that it should be, given that this is claimed to induce resistance to anti-tumor immunity in an immunogenic disease.\n- Fig 3: Given the purported mechanism, It would be helpful to see whether overexpression of SLC7A11 obviates the effect of GBP2 knockout to prove that this is per se the mechanism of impaired tumor growth.\n- The STAT1 ko result is already well known as a broad resistance mechanism for B16 tumors, and so may or may not be related to GBP2 biology here.\n- Fig 3B: how many samples is this representative example drawn from?\n- Fig 3E: Given that the authors argue that GBP2 limits STAT1 signaling, it should limit ISGs broadly. Do the authors therefore see lower MHC-I and PD-L1 expression in IFNg-stimulated GBP2 ko cells?\n- Fig 5: It would be helpful to see co-localization of SHP1 and STAT1 or pSTAT1 together in the same images in GBP2 KO vs GBP2-expressing cells.\n- Fig 6: HMGB1 is not particularly specific for ferroptotic death. Other IFN-dependent pathways of killing (ie most of them since IFN affects T cell recognition via MHC-I) could presumably be equally implicated here. Overexpressing SLC7A11 may provide stronger evidence than deletion of STAT1, which is a general way to suppress tumor response.\n- Fig 7: many of these analyses may be confounded by the relationship of GBP2 as an ISG— independent of any role in supporting anti-tumor immunity, GBP2 should anyhow be associated with response: because responding patients have T cells that make IFNg.\n- I did not see computational methods reported in the methods section.", "reviewer_3": "The manuscript titled “Gbp2 condensate promote ferroptosis, sensitize anti-PD-L1 ICB in melanoma” investigates the role of Gbp2 in enhancing immune checkpoint blockade (ICB) in a mouse model. The authors propose that under IFN-γ stimulation, Gbp2 undergoes phase separation to form condensates that sequester SHP1. This sequestration facilitates STAT1 phosphorylation, which then downregulates SLC7A11, leading to ferroptosis and increased immunogenicity of dying cancer cells. Gbp2 overexpression is shown to increase T-cell infiltration, with this effect being attenuated in HMGB1 knockout models. Conversely, disruption of Gbp2 phase separation appears to promote tumor growth and reduce ICB efficacy.\nWhile the authors have made a commendable effort to dissect the function and mechanism of Gbp2, several key issues remain unresolved. Most notably, it is unclear whether endogenous GBP2 condensates sequester SHP1 to a degree that facilitates STAT1 activation and ferroptosis, and whether GBP2 serves as a reliable biomarker for ICB response in patients.\nMajor Comments\n1. There is an inconsistency between the basal levels of GBP2 in the “sgCtrl” group (Figure S5, panel a) versus the “Vec” group (panel b), despite consistent GAPDH loading controls and the expectation that these represent the same cell line. The authors should provide a clear explanation for the observed differences.\n2. Data in Figures 2a and 2b indicate that GBP2 knockout cells display a growth advantage and reduced T-cell cytotoxicity regardless of ICB treatment, suggesting that GBP2 may act as a general mediator of T-cell cytotoxicity rather than being ICB-specific. The authors should provide additional data to support an ICB-specific role for GBP2 or adjust their claims to indicate that GBP2 functions as a general regulator of cell growth and T-cell toxicity.\n3. In Figure 3a, the manuscript states that “A significant increase in SLC7A11 expression was found in GBP2-/- compared to sgCtrl cells, and this effect was restored by IFN-γ stimulation.” The authors need to provide quantitative analysis to support this claim and clarify what is meant by “restored”.\n4. The in vitro co-culture experiments with ferrostatin-1 suggest that immune cell–derived factors may induce cancer cell death via ferroptosis. However, this does not establish ferroptosis as the predominant pathway underlying GBP2’s function in ICB. The authors should either present direct evidence that ferroptosis is the major mechanism (e.g., through rescue experiments with ferroptosis inhibitors or additional markers) or adjust their claims regarding the role of ferroptosis.\n5. In Figure 5d, the manuscript indicates near-complete knockdown of GBP2 and SHP1 with siRNA, yet details regarding the siRNA sequences and a dose-response curve are missing. Please provide the siRNA sequences and include a dose-response analysis to validate knockdown efficiency.\n6. In Figure 5e, it is unclear whether the data reflect endogenous GBP2 or transfected GBP2. Moreover, overexpression of GBP2 lacking its intrinsically disordered region fails to form condensates, does not sequester SHP1, and returns STAT1 phosphorylation to baseline, even though endogenous GBP2 should still be present. The authors should clarify these findings and explain the mechanism by which overexpression of a GBP2 variant without the IDR interferes with endogenous condensate formation.\n7. The claim that SHP1 sequestration within GBP2 condensates blocks its function is not directly supported by the current data. Experiments demonstrating endogenous co-localization of GBP2 and SHP1 (e.g., via high-resolution imaging) are needed. Additionally, in vitro assays (such as reconstituted phosphorylation assays) showing that GBP2 condensates sequester SHP1 and impair STAT1 phosphorylation would strengthen this claim.\n8. The authors could utilize two strategies to test the function of phase separation to strengthen their claims: (a) mutating specific amino acids to alter electrostatic and hydrophobic properties, and (b) fusing GBP2 to a hydrophilic sequence (e.g., MBP) to dampen self-association without altering the internal sequence.\n9. In the first section, the manuscript claims that “bioinformatics analysis in clinical samples suggests that GBP2 is a potential combinatorial ICB treatment biomarker and is closely associated with CTL cytolytic activity.” As the analysis does not include direct ICB data, the conclusion that GBP2 is an ICB biomarker is not well-supported. The authors need to either incorporate ICB-specific data or rephrase the claim to reflect only the observed association with cytolytic activity.\n10. It is unclear whether the clinical datasets analyzed in Figure 7 were obtained from patients before or after ICB treatment. The authors should specify the timing of these datasets to accurately interpret the correlation between GBP2 expression and ICB response.\nMinor Comments:\n1. The manuscript currently equates phase separation with biomolecular condensates by stating, “Phase separation, also known as biomolecular condensates…”.\nHowever, phase separation is the process that gives rise to condensates; it is not synonymous with the condensate itself. The authors should revise this terminology to accurately reflect that phase separation underlies the formation of biomolecular condensates.\n2. The manuscript lacks validation data for the Cas9 knockout experiments (e.g., confirming homozygous versus heterozygous knockout). Similarly, for the generation of mCherry-tagged GBP2 cells, it is unclear whether the knock-in is heterozygous or homozygous. Please provide genotyping data or additional validation to confirm the zygosity of these genetic modifications.\n3. While immunostaining data are shown in Figure 2h, similar data for Figures 2f and 2g are lacking.\n4. Some representative images are problematic. For instance, in Figure 2H, certain cells appear to be undergoing mitosis, and adjustments in image contrast (e.g., in Figure 5E) may lead to misinterpretation, such as displaying an abnormally large condensate that might be due to overexpression artifacts rather than physiological conditions.\n5. The figure legend for Figure 6H is absent and should be provided.\n6. For analyses based on published datasets, the manuscript should clearly indicate the origin of the data and include appropriate citations in the main text or figure legends.", "reviewer_4": "The authors investigated the role of guanylate binding protein 2 (GBP2) in the efficacy of immune checkpoint blockade (ICB) and its underlying mechanisms in melanoma. They discovered that GBP2 can undergo phase separation through its intrinsically disordered region (IDR), which promotes STAT1 phosphorylation and inhibits SLC7A11 expression, ultimately leading to tumor ferroptosis. This work is conceptually intriguing, and the data largely support the authors' main claims. However, the quality of the manuscript could be enhanced by addressing the following points:\nA. To better understand the immune-unrelated role of GBP2, it is recommended to test this in at least one in vivo model, such as an immune-deficient model.\nB. While the mechanistic connection between GBP2, SHP1, and pSTAT1 has been thoroughly examined in vitro, it has not yet been evaluated in vivo. Given the novelty of this aspect, including in vivo studies is essential.\nC. The data regarding HMGB1 and its participation in GBP-mediated tumor immunity are weak and somewhat tangential to the central message of the work. Omitting this section would sharpen the focus of the manuscript without compromising its significance.\nD. The immunohistochemistry (IHC) data for SLC7A11 and GBP2 (Figures 3 and 7) should be re-evaluated concerning the specificity of antibodies, cell types, and localization.\nE. The discussion could benefit from including the selectivity and involvement of other GBP family members in ICB.\nBy addressing these points, the authors could significantly enhance the clarity and impact of their findings.", "reviewer_5": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "RESPONSES TO REVIEWERS\nWe would like to express our sincere thanks to all three reviewers for their critical and\nconstructive comments. We have performed substantial additional experiments to\naddress their concerns. We respond point-by-point to each of their comments and\ncriticisms. We feel that their comments have helped us on significantly improving and\nstrengthening the manuscript and clarifying some issues. We hope that the revision\nhas addressed their major concerns.\nReviewer #1\nThis manuscript explores the role of GBP2 in immunogenic ferroptosis and ICB\nresponse in tumors, an intriguing and relevant topic in cancer immunotherapy. The\nauthors provide a detailed analysis integrating bioinformatics, in vivo models, and\nmolecular analyses to establish a link between GBP2, phase separation, and STAT1\nactivation in the tumor microenvironment. However, in some cases, the conclusions\nare based solely on correlations and require further validation to fully support the\nproposed model.\n1. CRISPR/Cas9 Off-Target Effects: The use of CRISPR/Cas9 technology can lead to\noff-target mutations. How did the authors verify that the generated cell lines do not\ncarry unintended genetic alterations? A proper validation should be included to ensure\nthe accuracy of the reported data.\nResponse:\nFollowing the reviewer’s advice, we conducted a series of experiments to rigorously\nassess potential off-target effects associated with gene editing. First, sgRNAs were\ndesigned using Benchling platform to maximize on-target efficiency while minimizing\noff-target effects. To validate the robustness and reproducibility of our findings, we\nreplicated key experiments both in vitro and in vivo across three independent tumor\nmodels: B16-OVA, MC38-OVA, and A375. This approach helped to exclude the\npossibility of cell line–specific artifacts.\nFurthermore, to rule out potential off-target effects of CRISPR/Cas9 editing, we\nadopted a rescue strategy based on the approach described by Manguso et al. (Nature.\nOVA cells. As expected, overexpression of GBP2 (oeGBP2) significantly restored the\nexpression of SLC7A11 and the phosphorylation of STAT1 (Fig. S7K). More\nimportantly, enforced GBP2 expression also restored lipid ROS accumulation and\nreinstated GBP2-/- tumor cells to anti-PD-L1 therapy in vivo (Fig. S7L-M). These\nfindings strongly suggest that the enhanced ferroptotic sensitivity and\nimmunotherapeutic response observed in GBP2-deficient models are not attributable\nto off-target effects.\nAccording to the reviewer’s suggestion, we added the new data in the revised\nmanuscript, page 22 line 489-493 and Fig. S7K-M.\nPart new figures are shown below.\nFig. S7: (K) The GBP2-/- B16-OVA cells transfected with GBP2 plasmid (oe-GBP2), then\ntreated with 10 ng/mL IFN-γ for 12 hours, and cell lysates were collected and analyzed by\nwestern blot. (L) The GBP2-/- and GBP2-/- + oeGBP2 B16-OVA (1 × 106) cells subcutaneously\ninjected into C57BL/6 mice. Mice with a tumor size of 125 mm3 were treated with anti–PD-L1\nantibody or IgG once per 3 days. (M) Relative lipid ROS of Ctrl, GBP2-/- and GBP2-/- + GBP2oe\ntumours in mice treated with anti-PD-L1 were quantified in CD45- cells by flow cytometric\nanalysis.\n2. IFN-γ and Ferroptosis: The authors suggest that IFN-γ induces ferroptosis via GBP2;\nhowever, this is not supported by experimental data. To clarify this, cytokine levels\nshould be measured in tumours derived from GBP2-/- and control cells (with or without\nICB) to assess IFN-γ and other relevant cytokines in the tumour microenvironment.\nThis would also help determine the inflammatory status in the presence or absence of\nGBP2 in the context of ICB. Additionally, in vivo IFN-γ blocking experiments should be\nperformed to establish a functional link between GBP2 and IFN-γ.\nResponse:\nWe acknowledge the reviewer's insightful comment. It will be critical to elucidate the\nprecise molecular and cellular mechanisms by which the immune system regulates\nferroptotic cell death. The seminal study by Wang et al. first demonstrated that\nimmunotherapy-activated CD8⁺ T cells enhance tumor cell-specific lipid peroxidation\nthrough released IFN-γ, thereby augmenting anti-tumor efficacy (Nature. 2019\nMay;569(7755):270-274). Recent studies have further elucidated potential\nmechanisms of IFN-γ-induced tumor ferroptosis (Nat Chem Biol. 2025 Apr 25. doi:\n10.1038/s41589-025-01887-3; Cancer Cell. 2022 Apr 11;40(4):365-378.e6; Cell Mol\nLife Sci. 2022 Jun 8;79(7):352; J Immunother Cancer. 2022 Jun;10(6):e004381). Our\nstudy aims to identify GBP2 as one potential mediator in IFN-γ-driven ferroptosis.\nHowever, it should be noted that we currently lack experimental data explicitly\ndemonstrating that IFN-γ induces ferroptosis specifically through GBP2.\nTo clarify this, we first performed ELISA to assess cytokine levels (primarily\nIFN-γ and TNF-α) in sgCtrl and sgGBP2 tumors with or without anti-PD-L1 treatment.\nThese cytokines are critically involved in CD8+T cell-mediated killing during immune\ncheckpoint blockade (ICB) (Nature. 2025 Apr;640(8060):1062-1071). Under baseline\nconditions (no anti-PD-L1), GBP2 deficiency did not alter IFN-γ or TNF-α levels versus\ncontrols. During early-phase anti-PD-L1 treatment (Day 7), we observed modest yet\nsignificant increases in IFN-γ and TNF-α relative to IgG-treated tumors. However,\nGBP2 knockout did not significantly attenuate this cytokine elevation. Strikingly, in\nlate-phase treatment (Day 14), anti-PD-L1 induced substantially heightened release\nof these cytokines (tumor weight-normalized) versus IgG controls (Fig. 2K and Fig.\nS6H). And this effect was potently suppressed by GBP2 depletion (Fig. 2K and Fig.\nS6H). We interpret this temporal divergence as potentially attributable to GBP2-\ndependent immunogenic ferroptosis in later stages. Specifically, GBP2 activation may\ntrigger DAMPs release from ferroptotic cells, subsequently recruiting dendritic cells\nand amplifying CD8+ T cell activation, thereby initiating a positive feedback loop that\naugments anti-tumor immunity.\nTo further identify the specific cytokine mediating this effect, we generated\nperforin-/-, IFNγ-/-, or TNFα-/- OT-1 cells and co-cultured them with control versus\nGBP2-overexpressing B16-OVA tumor cells. Critically, loss of IFN-γ, but not perforin\nor TNF-α, prevented OT-1-cell-mediated killing of GBP2-overexpressing tumors (Fig.\n2L). Furthermore, we performed blocking experiments as suggested by the reviewer.\nWe found that GBP2 overexpression enhanced both ICB efficacy and lipid ROS\nproduction (Fig. 2M and Fig. S6I). These effects were abrogated by anti-IFN-γ\nmonoclonal antibodies (mAbs) (Fig. 2M and Fig. S6I). Collectively, these data\ndemonstrate that GBP2 mechanistically facilitates IFN-γ-dependent tumor ferroptosis,\nthereby potentiating ICB therapeutic efficacy.\nAccording to the reviewer’s suggestion, we added the new data in the revised\nmanuscript, page19-20 line 421-439 and Fig. 2K-M and Fig. S6H-I.\nPart new figures are shown below.\nFig. 2: (K) The protein levels of IFN-γ in tumor lysates were quantified by ELISA in mice\ntreated with anti–PD-L1 antibody or control IgG. (L) Viability of vector (Vec) or GBP2-\noverexpressing (GBP2oe) B16-OVA tumor cells after 24-hours co-culture with OT-1 T cells\ntransduced with sgCtrl, sgIFNγ, sgTNFα, or sgPRF1 at an effector-to-target (E:T) ratio of 1:1\n(n = 3 per group). (M) Vec or GBP2oe B16-OVA cells (1 × 10⁶) were subcutaneously implanted\ninto C57BL/6 mice. When tumors reached ~125 mm³, mice were treated with anti-PD-L1, anti-\nIFN-γ, or control IgG antibodies every 3 days.\nFig. S6: (H) The protein levels of TNF-α in tumor lysates were quantified by ELISA in mice\ntreated with anti–PD-L1 antibody or control IgG. (I) Relative lipid ROS of B16-OVA tumors in\nmice treated with anti-IFN-γ were quantified in CD45- cells by flow cytometric analysis.\n3. FRAP Analysis: The FRAP data presented are incomplete. To fully characterize\nGBP2 phase separation properties, appropriate controls should be included, such as\na protein known to form condensates and a protein known to remain solubilized. This\ncomparison would help determine whether GBP2 phase separation follows a typical\nliquid-liquid phase separation behaviour.\nResponse:\nWe sincerely thank the reviewer for this valuable suggestion. To rigorously evaluate\nthe biophysical properties of GBP2 condensates, we have incorporated both positive\nand negative controls, as recommended. Following established protocols from Liu et\nal. (Cell, 2021, 184(22):5559–5576) and Cai et al. (Nat Cell Biol, 2019, 21(12):1578–\n1589), we used glycogen as a positive control and mCherry alone as a negative control\nin our fluorescence recovery after photobleaching (FRAP) experiments. Under\nidentical conditions, glycogen condensates displayed rapid fluorescence recovery\nafter photobleaching, consistent with liquid-like dynamics. In contrast, mCherry\nexhibited minimal recovery, validating its role as a non-phase-separating control.\nThese results confirm the robustness of our FRAP assay and demonstrate that GBP2\ncondensates possess dynamic fluidity—characteristic of biologically functional,\nphase-separated structures.\nIn accordance with the reviewer’s suggestion, we have incorporated these new data\ninto the revised manuscript (page 23 line 509-514; Fig. S8D-E.)\nPart new figures are shown below.\nFig. S8: (D) Representative images showed that FRAP assay of the droplets of glycogen\nformed in B16-OVA cells. The data are plotted as the mean ± SD on the right (n = 3). (E)\nRepresentative images showed that FRAP assay of the droplets formed in B16-OVA cells\nexpressing mCherry. The data are plotted as the mean ± SD on the right (n = 3).\n4. GBP2ΔIDR and ICB Response: The authors demonstrate that GBP2ΔIDR reduces\nCD8+ OT-1 cytotoxicity; however, they do not assess whether GBP2 phase separation\nis required for ICB efficacy in vivo. A murine model with GBP2ΔIDR + anti-PD-L1\nshould be used to determine if GBP2 condensation is necessary for a successful ICB\nresponse.\nResponse:\nWe thank the reviewer for raising this critical point and acknowledge our oversight in\naddressing GBP2 phase separation in vivo. To determine whether GBP2 phase\nseparation is essential for ICB efficacy, we established tumor-bearing mouse models\nwith GBP2ΔIDR + anti-PD-L1 treatment as suggested. As suggested, the results\nshowed that under anti–PD-L1 treatment, tumors expressing GBP2-ΔIDR exhibited a\nmarked reduction in therapeutic response compared to the GBP2-FL group, as well\nas diminished ROS production (Fig. 5K-L). Furthermore, it was reported that in vivo\nphase separation could observe aggregation foci under immunofluorescence (Cell.\nthe aforementioned tumor specimens to visualize this phenomenon. Critically, distinct\nGBP2 aggregate foci were readily detectable in GBP2-FL tumors following anti-PD-L1\ntreatment, whereas such structures were absent in GBP2-ΔIDR tumors (Fig. 5N).\nAccording to the reviewer’s suggestion, we added the new data in the revised\nmanuscript (page 26 line 564-565,568-572; Fig. 5K-L, N).\nPart new figures are shown below.\nFig. 5: (K) 1 × 106 GBP2-/- B16-OVA cells expressing GBP2-FL and GBP2 △IDR were\nsubcutaneously injected into C57BL/6 mice. (left) Mice with a tumor size of 125 mm3 were\ntreated with anti–PD-L1 antibody or IgG once per 3 days. FL, full length. (right) Tumor\ninhibition rate for GBP2 △IDR under anti-PD-L1 treatment, respectively (n = 6). (L) Relative\nlipid ROS of GBP2-FL or GBP2 △IDR tumours in mice treated with anti-PD-L1 were quantified\nin CD45− cells by flow cytometric analysis. (N) Representative images of GBP2 of\nimmunofluorescent staining in GBP2-FL or GBP2 △IDR tumours under anti-PD-L1 treatment\n(n = 3).\n5. Immune Infiltration Profiling: The authors suggest that GBP2 may modulate immune\nresponses by promoting immunogenic cell death. Since this mechanism has\nsignificant implications for immune cells, a more comprehensive analysis of tumour-\ninfiltrating leukocytes should be performed. This should not be limited to CD8+ T cells\nand DCs but should include a full leukocyte profile in mice transplanted with GBP2-/-\nand sgGBP2 tumour cells, with or without or with ICB therapy. Additionally, the authors should\nassess whether CD8+ T cells show increased activation in sgGBP2 tumours.\nResponse:\nWe thank the reviewer for raising this critical point. Following the reviewer's suggestion,\nperformed flow cytometric profiling of tumor-infiltrating leukocytes in anti‑PD‑L1–\ntreated sgGBP2 and sgCtrl tumors. Utilizing the gating strategy established by Guo et\nal. (Nature. 2023 Aug;620(7972):200-208), we quantified the major immune subsets,\nincluding CD8⁺ T cells, CD4⁺ T cells, NK cells, B cells, neutrophils,\nmonocytes/macrophages, and dendritic cells (Fig. S10B). The results showed that\nanti-PD-L1 treatment significantly increased the proportions of CD8⁺ T cells, CD4⁺ T\ncells, NK cells and B cells. Critically, regardless of PD-L1 treatment, GBP2 deletion\nsubstantially suppressed infiltration of CD8⁺ T cells, while exerting no significant effect\non CD4⁺ T cells, dendritic cells, B cells, NK cells, monocytes/macrophages, or\nneutrophils (Fig. 6A). These results demonstrate that GBP2 shapes an\nimmunostimulatory tumor microenvironment (TME) through regulating CD8+T cell\ninfiltration.\nFurthermore, we quantified the activation status of CD8⁺ T cells by assessing the\nproportions of IFN-γ⁺ and TNF-α⁺ T cell subsets (Nat Commun. 2020 Sep\n24;11(1):4835). Flow cytometric analysis of CD8⁺ T cell activation markers showed\nthat GBP2 ablation markedly attenuated IFN-γ⁺ and TNF-α⁺ CD8⁺ T cell frequencies\n(Fig. 6E). Collectively, these findings demonstrate that GBP2 potentiates CD8+T cell-\nmediated anti-tumor immunity.\nAccording to the reviewer’s suggestion, we added the new data in the revised\nmanuscript (page 26-27 line 583-589,592-595; and Fig. 6A, E and Fig. S10B).\nPart new figures are shown below.\nFig. S10B: Gating strategies for flow cytometry analysis and cell sorting.\nFig. 6A: Percentage of tumor infiltrating immune subsets between sgCtrl and GBP2-/- tumours\nwith or without anti-PD-L1 in B16-OVA-bearing mice. n = 3 mice.\nFig. 6E: Representative images and statistical quantitation of the flow cytometric analysis of\nthe percentage of IFN-γ+CD8+ and TNF-α+CD8+ TILs from sgCtrl and sgGBP2 xenografts.\n6. Manuscript Readability and Clarity: The manuscript should be carefully revised to\nimprove clarity and readability. Lines 273-275 contain a sentence that appears\nincorrect and contradicts the data presented. Please revise this section for accuracy.\nResponse:\nWe thank the reviewer for pointing out the ambiguity in Lines 273–275. The sentence\nin question has been revised to eliminate any confusion and to ensure full consistency\nwith the data presented. In addition, we have conducted a comprehensive language\nrevision throughout the manuscript to improve clarity, precision, and overall readability.\nAll changes have been highlighted in the revised version.\nReviewer #2\nSummary:\nLiu et al performed a weighted network correlation analysis of immune checkpoint\nblockade-treated patients and identified GBP2 as a potential driver of ICB response.\nThey find that loss of GBP2 ablates PD-L1 response in mouse models and argue that\nGBP2 acts to enhance T-cell-mediated ferroptosis via modulation of SLCA11 in an\nIFN-dependent manner. They further argue that GBP2 forms phase-separated\ncondensates that sequester SHP1 and thereby promote STAT1 phosphorylation and\nsubsequent induction of SLCA11. They seek to validate this finding in patient cohorts\nand argue that GBP2 acts to support ferroptosis, immunogenicity cell death and\nHMGB1 expression.\nOverall the group presents a large body of intriguing data. The finding that GBP2\nmodulates and supports IFNg / STAT1 signaling via phase separated sequestration of\nSHP1 is interesting. They separately show that GBP2 loss impairs ferroptosis and that\nthis impairment can be overcome by SLCA11 knockdown. Each of these findings\nrepresents a meaningful contribution to the field and, in particular, the work supporting\nSHP1 sequestration by GBP2 seems to me to be a strength. That said, there are also\nsome concerns with the paper as currently constructed.\nMajor Concerns:\nThere are some logical leaps that I worry are not fully justified by the data. For example,\nbecause loss of GBP2 affects STAT1 signaling and STAT signaling affects many\npathways of immunotherapy response (not least, MHC-I expression, expression of\ncheckpoint ligands, CD8+ T cell and NK cell recognition), I am not sure that the data\nconnecting GBP2 with ferroptosis and the data connecting GBP2 with immunotherapy\nresponse are necessarily connected. The authors could strengthen this connection by\ntesting whether SLCA11 overexpression in tumor cells ablates the in vivo GBP2 PD-\nL1 response phenotype they observe. I would also recommend evaluating alternative\nor complementary hypotheses by testing the expression of other IFN-stimulated genes\nsuch as MHC-I in GBP2 ko cell lines. Finally, the authors rely heavily on a single\nmouse model for in vivo studies and could benefit from repeating core findings (e.g.\nGBP2 sensitization to PD-L1) in an additional model to support its robustness.\nResponse:\nWe thank the reviewer for raising this critical and insightful point. We fully agree that\nSTAT1 plays a pivotal role in tumor immunology, including the regulation of MHC-I\nexpression, immune checkpoint ligands, and immune cell recognition (Signal\nTransduct Target Ther. 2021, 6:402). In response, we performed a series of\nexperiments to evaluate these alternative or complementary mechanisms, as\nsuggested.\nTo address the reviewer’s concern regarding MHC-I expression, we wish to clarify\nthat our B16-OVA and MC38-OVA tumor models were engineered using the\nPresentER system (Elife. 2018 Nov 30;7:e41090), which enables stable expression of\npeptide/MHC-I complexes. As a result, these cells constitutively overexpress both\nOVA antigen and MHC-I molecules, eliminating the possibility that reduced\nimmunotherapy efficacy in the GBP2-knockout context is due to altered MHC-I\npresentation. This was further confirmed by flow cytometric analysis, which revealed\nno significant differences in surface MHC-I expression between sgCtrl and sgGBP2\ntumor cells (Fig. S7E-F).\nWe next examined checkpoint ligand expression. Western blot analysis showed\nthat GBP2 knockout did not alter PD-L1 levels in tumor cells, either at baseline or\nfollowing IFN-γ stimulation (Fig. S7G). To assess CD8⁺ T and NK cell interactions with\ntumor cells, we employed the FucoID platform (Cell. 2020 Nov 12;183(4):1117–1133),\na technique that quantifies cell-cell interactions based on fucosyl-biotinylation. FucoID\nanalysis revealed no significant differences in immune cell–tumor cell interaction\nfrequencies between sgCtrl and sgGBP2 groups (Fig. S7H).\nTaken together, these results suggest that the impact of GBP2 on antitumor\nimmunity is unlikely to be mediated through canonical STAT1-driven pathways such\nas MHC-I or PD-L1 expression or changes in immune cell–tumor cell interactions.\nInstead, our data support the hypothesis that GBP2 regulates tumor ferroptosis\nthrough the STAT1/SLC7A11 axis.\nIn our initial submission, we demonstrated that silencing SLC7A11 via siRNA in\nGBP2-deficient B16-OVA cells restored lipid ROS accumulation following RSL3\ntreatment under IFN-γ priming (Fig. 3C). Moreover, GBP2 knockout significantly\nelevated intracellular GSH levels and increased cell viability—effects that were\nreversed by SLC7A11 silencing (Fig. 3D). In line with the reviewer’s suggestion, we\nhave now performed complementary in vivo experiments. Overexpression of\nSLC7A11 in tumor cells significantly diminished the tumor-suppressive effect of GBP2\noverexpression, reduced intratumoral lipid ROS levels, and abolished GBP2-mediated\nenhancement of ICB efficacy (Fig. 3E-F).\nLastly, to validate the robustness and generalizability of our findings, we extended\nour analysis to an independent tumor model using the MC38-OVA colon carcinoma\nline (Nature. 2025 Apr;640(8060):1062–1071; Nat Commun. 2022 Sep 6;13(1):4981).\nGBP2 knockout in MC38-OVA cells was confirmed by western blotting (Fig. S5D).\nIn both OT-1 adoptive transfer and anti-PD-L1 treatment settings, GBP2 deficiency\nsignificantly impaired therapeutic responses (Fig. S5E-H), recapitulating our findings\nin the B16-OVA model.\nIn accordance with the reviewer’s suggestion, we have included these new data\nin the revised manuscript (page 21 line 457-460; page 18-19, line 402-404; page 22,\nline 467-481; and Fig. 3E-F and Fig. S5D-H and Fig. S7E-H).\nPart new figures are shown below.\nFig. S7: (E-F) Representative flow cytometry plots and quantification showing H-2Kb bound\nto SIINFEKL in sgCtrl and GBP2-/- B16-OVA and MC38-OVA groups. (G) The sgCtrl and\nGBP2-/- B16-OVA and A375 cells were treated with 10 ng/mL IFN-γ for 12 hours, respectively.\nCell lysates were collected and analyzed the indicated molecules by western blot. (H)The\nsgCtrl and GBP2-/- B16-OVA cells co-cultured with CD8+T or NK cells were co-incubated in\nthe presence of biotin–LPETG for 30 min and analyzed by flow cytometry. The extent of\nlabelling of tumor cells between groups.\nFig. 3: (E) 1 × 106 vector, GBP2-overexpression (oeGBP2) and oeGBP2 transfected with\noeSLC7A11 plasmid B16-OVA cells were subcutaneously injected into C57BL/6 mice. All\nmice with a tumor size of 125 mm3 were treated with anti-PD-L1 antibody or IgG once per 3\ndays. (F) Relative lipid ROS of vector, oeGBP2 or oeGBP2 + oeSLC7A11 tumours in mice\ntreated with anti-PD-L1 were quantified in CD45− cells by flow cytometric analysis.\nFig. S5: (D) Western blot showed the transfection efficiency of sgGBP2 in MC38-OVA cells.\n(E) The sgCtrl or GBP2-/- MC38-OVA (1 × 106) cells subcutaneously injected into C57BL/6\nmice. Mice were adoptively transferred with OT-1 cells (5 × 106 per mouse) or PBS once per\n7 days. (F) Tumor inhibition rate for GBP2-/- cells relative to sgCtrl cells under OT-1 treatment,\nrespectively (n = 6). (G) The sgCtrl or GBP2-/- MC38-OVA (1 × 106) cells subcutaneously\ninjected into C57BL/6 mice. Mice with a tumor size of 125 mm3 were treated with anti–PD-L1\nantibody (200 μg per mouse) or IgG once per 3 days. (H) Tumor inhibition rate for GBP2-/-\ncells relative to sgCtrl cells under anti-PD-L1 treatment, respectively (n = 6).\nI am additionally concerned about the potential for circular reasoning in the patient\ncorrelative studies: better clinical responses with GBP2, more immunogenic tumor cell\ndeath or more CD8+ T cells may not be all that surprising given that GBP2 is an ISG.\nIndeed, correlations are presented between IFN-signatures (composed of ISGs) and\nGBP2. In this case it seems quite possible that cause and effect may be reversed–\nthat GBP2 expression is the effect of ISG induction rather than the cause, as is claimed.\nBy comparison, analysis could equally be conducted simply asking if IFN signaling in\ntumors correlates with CD8+ T cell infiltration or whether they respond better to\nimmunotherapy–both well established observations in the field.\nResponse:\nWe thank the reviewer for this expert commentary. It is well established that tumor cell\nresponsiveness to IFN-γ is a critical determinant of both ICB efficacy and anti-tumor\nimmunity (Nat Rev Cancer. 2022 Apr;22(4):195-207). CRISPR-Cas9 screens have\nrepeatedly identified IFN-γ signaling components among the top genes associated\nwith ICB responsiveness (Nature. 2017 Aug 31;548(7669):537-542; Science. 2018\nFeb 16;359(6377):770-775). Many interferon-stimulated genes (ISGs) are not merely\nmarkers but functional mediators of anti-tumor effects. For example, the lncRNA LIMIT\nactivates the GBP gene cluster to potentiate tumor immunogenicity and ICB efficacy\n(Nat Cell Biol. 2021 May;23(5):526-537), and ACSL4 links IFN-γ to ferroptosis\ninduction, improving ICB outcomes (Cancer Cell. 2022 Apr 11;40(4):365-378.e6).\nThese findings illustrate that ISGs can actively amplify IFN-γ-driven anti-tumor\nimmunity, suggesting that GBP2 might similarly function as an effector rather than a\npassive biomarker.\nOur current results indicate that sgGBP2 attenuates ICB efficacy primarily by\nreducing ICB-mediated ferroptosis. Mechanistically, as suggested by the reviewer, we\nfound that GBP2 primarily activates the STAT1 signaling pathway to influence\nferroptosis independently of STAT1-related MHC-I expression, immune checkpoint\nexpression, and CD8+ T/NK cell recognition. Regarding the concern about MHC-I\nexpression, we wish to clarify that we utilized the PresentER system (Elife. 2018 Nov\n30:7:e41090), which enables the encoding of multiple peptide/MHC complexes. Thus,\nour B16-OVA and MC38-OVA model constitutively overexpressed both OVA and\nMHC-I components and the scenario of concern to the reviewer does not exist.\nFurthermore, we performed flow cytometry analysis of MHC-I expression and\nobserved no significant changes between the sgCtrl and sgGBP2 group (Fig. S7E-F).\nAdditionally, we assessed the expression of checkpoint ligands, focusing on PD-L1.\nWestern blot analysis of sgGBP2 cells revealed no significant difference in PD-L1\nexpression levels compared to sgCtrl—both with and without IFN-γ stimulation (Fig.\nS7G). We also employed FucoID technology (Cell. 2020 Nov 12; 183(4): 1117–1133).\nIn brief, FucoID can evaluate cell-to-cell interactions based on an interaction dependent\nfucosyl-biotinylation. As a result, no significant differences were observed between\nsgCtrl and sgGBP2 group (Fig. S7H).\nWe attribute these results to significantly diminished IFN-γ signaling upon GBP2\nknockout, which consequently elevates SLC7A11 expression to inhibit ferroptosis.\nThis suppression results in reduced DAMPs release, impaired dendritic cell\nrecruitment, and subsequently diminished CD8⁺ T cell activation, culminating in\ncompromised anti-tumor immunity. However, we acknowledge that our existing data\nlack definitive experimental validation to establish a direct causal relationship between\nGBP2 and IFN-γ signaling.\nTherefore, we first performed ELISA to assess cytokine levels (primarily IFN-γ\nand TNF-α) in sgCtrl and sgGBP2 tumors with or without anti-PD-L1 treatment. These\ncytokines are critically involved in CD8+T cell-mediated killing during immune\ncheckpoint blockade (ICB) (Nature. 2025 Apr;640(8060):1062-1071). Under baseline\nconditions (no anti-PD-L1), GBP2 deficiency did not alter IFN-γ or TNF-α levels versus\ncontrols. During early-phase anti-PD-L1 treatment (Day 7), we observed modest yet\nsignificant increases in IFN-γ and TNF-αrelative to IgG-treated tumors. However,\nGBP2 knockout did not significantly attenuate this cytokine elevation. Strikingly, in\nlate-phase treatment (Day 14), anti-PD-L1 induced substantially heightened release\nof these cytokines (tumor weight-normalized) versus IgG controls (Fig. 2K and Fig.\nS6H). And this effect was potently suppressed by GBP2 depletion (Fig. 2K and Fig.\nS6H). We interpret this temporal divergence as potentially attributable to GBP2-\ndependent immunogenic ferroptosis in later stages. Specifically, GBP2 activation may\ntrigger DAMPs release from ferroptotic cells, subsequently recruiting dendritic cells\nand amplifying CD8+ T cell activation, thereby initiating a positive feedback loop that\naugments anti-tumor immunity.\nTo further identify the specific cytokine mediating this effect, we generated\nperforin-/-, IFNγ-/-, or TNFα-/- OT-1 cells and co-cultured them with control versus\nGBP2-overexpressing B16-OVA tumor cells. Critically, loss of IFN-γ, but not perforin\nor TNF, prevented OT-1-cell-mediated killing of GBP2-overexpressing tumors (Fig.\n2L). Furthermore, we performed blocking experiments as suggested by the reviewer.\nWe found that GBP2 overexpression enhanced both ICB efficacy and lipid ROS\nproduction (Fig. 2M and Fig. S6I). These effects were abrogated by anti-IFN-γ\nmonoclonal antibodies (mAbs) (Fig. 2M and Fig. S6I). To mitigate confounding effects\nfrom CD8+T cell infiltration, we intratumorally injected equal numbers of OT-1 cells.\nUnder these standardized conditions, we observed comparable levels of secreted IFN-\nγ across experimental groups. However, sgGBP2 tumors exhibited significantly\nreduced lipid ROS accumulation and accelerated tumor growth relative to controls\n(Figure for reviewer). Furthermore, rescue experiments demonstrated that GBP2\nrestoration (GBP2-/- + oeGBP2) reversed this phenotype, yielding smaller tumors with\nelevated lipid ROS levels (Fig. S7K-M). Collectively, these data establish that GBP2\nsensitizes tumor cell to IFN-γ-mediated ferroptosis, thereby potentiating ICB\ntherapeutic efficacy.\nAdditionally, we acknowledge that our study does not explore the upstream\nregulatory mechanisms controlling GBP2 expression, which may contribute to the\nobserved heterogeneity of GBP2 levels in patient tumor samples. Epigenetic\nregulation is a well-recognized mechanism of gene silencing (Nat Immunol. 2024\nOct;25(10):1858–1870; Sci Transl Med. 2023 Feb;15(681):eabq6024) and has\nrecently emerged as a conserved means of regulating GBP family gene expression in\ncancer. For instance, GBP4 promoter hypomethylation has been reported in\npancreatic ductal adenocarcinoma relative to adjacent normal tissue, and targeted\npromoter methylation suppresses GBP4 expression (Cancer Immunol Immunother.\nprognosis in gastric cancer (Clin Epigenetics. 2020 Jan 20;12(1):15), and GBP2\nmethylation levels in plasma correlate with advanced stages of breast cancer (Genet\nMol Biol. 2020 Nov 17;43(4):e20190230). In line with these findings, we observed a\nsignificant inverse correlation between GBP2 expression and DNA methylation levels\nin melanoma (Figure for reviewer), further supporting the hypothesis that DNA\nmethylation may drive GBP2 silencing in tumors. While this epigenetic regulation\nrepresents a compelling area for further research, our current study is specifically\nfocused on elucidating the functional role of GBP2 in modulating response to immune\ncheckpoint blockade. Detailed mechanistic investigation into the epigenetic regulation\nof GBP2 is ongoing and will be addressed in future studies. Accordingly, we have\nincluded this discussion in the revised manuscript's Discussion section.\nIn response to reviewers' comments and considering space constraints and overall\nmanuscript flow, we added the partial new data in the revised manuscript (page 19-20\nline 421-437; page 22 line 467-481,490-493 and Fig. 2K-M and Fig. S6H-I, Fig. S7E-\nH and Fig. S7K-M).\nPart new figures are shown below.\nFig. S7: (E-F) Representative flow cytometry plots and quantification showing H-2Kb bound\nto SIINFEKL in sgCtrl and GBP2-/- B16-OVA and MC38-OVA groups. (G) The sgCtrl and\nGBP2-/- B16-OVA and A375 cells were treated with 10 ng/mL IFN-γ for 12 hours, respectively.\nCell lysates were collected and analyzed the indicated molecules by western blot. (H)The\nsgCtrl and GBP2-/- B16-OVA cells co-cultured with CD8+T or NK cells were co-incubated in\nthe presence of biotin–LPETG for 30 min and analyzed by flow cytometry. The extent of\nlabelling of tumor cells between groups.\nFig. 2: (K) The protein levels of IFN-γ in tumor lysates were quantified by ELISA in mice\ntreated with anti–PD-L1 antibody or control IgG. (L) Viability of vector (Vec) or GBP2-\noverexpressing (GBP2oe) B16-OVA tumor cells after 24-hours co-culture with OT-1 T cells\ntransduced with sgCtrl, sgIFNγ, sgTNFα, or sgPRF1 at an effector-to-target (E:T) ratio of 1:1\n(n = 3 per group). (M) Vec or GBP2oe B16-OVA cells (1 × 10⁶) were subcutaneously implanted\ninto C57BL/6 mice. When tumors reached ~125 mm³, mice were treated with anti-PD-L1, anti-\nIFN-γ, or control IgG antibodies every 3 days.\nFig. S6: (H) The protein levels of TNF-α in tumor lysates were quantified by ELISA in mice\ntreated with anti–PD-L1 antibody or control IgG. (I) Relative lipid ROS of B16-OVA tumors in\nmice treated with anti-IFN-γ were quantified in CD45- cells by flow cytometric analysis.\nFig. S7: (K) The GBP2-/- B16-OVA cells transfected with GBP2 plasmid (oe-GBP2), then\ntreated with 10 ng/mL IFN-γ for 12 hours, and cell lysates were collected and analyzed by\nwestern blot. (L) The GBP2-/- and GBP2-/- + oeGBP2 B16-OVA (1 × 106) cells subcutaneously\ninjected into C57BL/6 mice. Mice with a tumor size of 125 mm3 were treated with anti–PD-L1\nantibody or IgG once per 3 days. (M) Relative lipid ROS of Ctrl, GBP2-/- and GBP2-/- + GBP2oe\ntumours in mice treated with anti-PD-L1 were quantified in CD45- cells by flow cytometric\nanalysis.\nFigure for reviewer only: (A) The protein levels of IFN-γ in tumor lysates were measured\nusing ELISA. (B) Comparison of tumor weight between sgCtrl + OT-1 and sgGBP2 +OT-1\ngroups. Relative lipid ROS of B16-OVA tumors in mice treated with OT-1 were quantified in\nCD45- cells by flow cytometric analysis.\nFigure for reviewer only: The relationship between GBP2 expression and beta value of\npromoter in melanoma based on the DNMIVD database.\nThe manuscript would benefit from editing for grammar in several places and rewriting\nin some others. I did not, for the most part, try to enumerate grammar or style issues.\nHowever, examples include:\n- Spelling and usage in the title: consider ‘promote’, not ‘promotes’; ‘sensitize’, not\n‘sensitive’\n- Consider referring to immune checkpoint blockade as simply ‘ICB’ rather than ‘the\nICB’\n- Line 79: consider ‘augments’, not ‘augment’, ‘limits’, not ‘limit’.\nResponse:\nWe thank the reviewer for highlighting these grammar or style issues. We have revised\nthe sentence mentioned above as suggested by the reviewer. In addition, we have\nconducted a comprehensive language revision throughout the manuscript to improve\nclarity, precision, and overall readability. All changes have been highlighted in the\nrevised version.\nSpecific Points:\n- Please add quantitative axes for flow plots\nResponse:\nFollowing the reviewer’s advice, we added all the quantitative axes for flow plots in the\nrevised manuscript.\n- Fig 1: this analysis is generally correlational, which can lend to false positives. In\nparticular, the authors ultimately correlate an ISG (GBP2) with a signatures for ISGs\n(e.g. IFNg signature). That said, this is probably ok in Fig 1, as the exercise is\nhypothesis-generating and sets up the rest of the work.\nResponse:\nWe appreciate the reviewer’s thoughtful comments and understanding of our research\nrationale. In our initial bioinformatic analysis aimed at identifying potential targets\ninvolved in T cell–mediated cytotoxicity, GBP2 emerged as a promising candidate.\nAcknowledging that such computational findings are inherently correlational, we\nsubsequently performed a series of in vivo and in vitro experiments to functionally\nvalidate the role of GBP2 in modulating the efficacy of immune checkpoint blockade\n(ICB) and to uncover the underlying mechanisms.\nOur experimental data revealed that GBP2 enhances tumor cell sensitivity to IFN-\nγ-induced ferroptosis, thereby amplifying the therapeutic response to ICB. Notably,\nrescue experiments in GBP2-deficient cells (GBP2-/- + oeGBP2) demonstrated that\nGBP2 restoration reversed SLC7A11 expression, increased STAT1 phosphorylation,\nand resulted in smaller tumors with elevated lipid ROS levels following anti–PD-L1\ntreatment (Fig. S7K-M). These findings underscore the essential role of GBP2 in\nmediating ICB efficacy.\nMechanistically, we found that GBP2 promotes STAT1 phosphorylation through\nphase separation, leading to suppression of SLC7A11 expression and induction of\nferroptosis. Therefore, as the reviewer appropriately noted, the correlative findings in\nFigure 1 serve as a hypothesis-generating foundation that guided the subsequent\nmechanistic and functional investigations presented in our study.\nIn response to reviewers' comments and considering space constraints and\noverall manuscript flow, we added the partial new data in the revised manuscript (page\n22 line 490-493 and Fig. S7K-M).\nFig. S7: (K) The GBP2-/- B16-OVA cells transfected with GBP2 plasmid (oe-GBP2), then\ntreated with 10 ng/mL IFN-γ for 12 hours, and cell lysates were collected and analyzed by\nwestern blot. (L) The GBP2-/- and GBP2-/- + oeGBP2 B16-OVA (1 × 106) cells subcutaneously\ninjected into C57BL/6 mice. Mice with a tumor size of 125 mm3 were treated with anti–PD-L1\nantibody or IgG once per 3 days. (M) Relative lipid ROS of Ctrl, GBP2-/- and GBP2-/- + GBP2oe\ntumours in mice treated with anti-PD-L1 were quantified in CD45- cells by flow cytometric\nanalysis.\n- Why is GBP2 considered a ‘combinatorial ICB treatment biomarker’ at the end of Fig\n1, rather than simply a biomarker? Also, is it thought to be prognostic or predictive?\nResponse:\nWe sincerely appreciate the reviewer’s constructive critique and acknowledge the\nneed to revise our initial conclusion in the first section. As correctly noted, the data\npresented there demonstrated a correlation with cytolytic activity rather than a\ndefinitive association with ICB response. The latter was more rigorously supported by\nour analysis of ICB-specific datasets in Fig. 7, which established a link between GBP2\nexpression and ICB responsiveness.\nRegarding prognostic significance, Univariate Cox regression analysis identified\nGBP2 as the most significant prognostic factor in SKCM. This finding was consistently\nvalidated across multiple independent melanoma cohorts, where high GBP2\nexpression correlated with improved overall survival (Fig. 1F, Fig. S2A-D and Fig. 7E).\nIn response to the reviewer’s suggestion, we have revised the conclusion in the first\nsection to read: “Together, these bioinformatic findings in clinical samples identify\nGBP2 as a potential prognostic biomarker and reveal its close association with CTL\ncytolytic activity in melanoma.” in the revised manuscript, page 18 line 383-384.\n- Fig 2: although the statistics shown look very significant, the difference in tumor\nvolume appears modest for Fig 2 A, C. Indeed, it appears that PD-L1 treatment was\nnot particularly effective in this model. It is likely worth testing other models in which\nPD-L1 blockade is more effective to see if the phenotypes are reproducible / stronger\nthere.\nResponse:\nFollowing the reviewer’s suggestion, we validated our findings in an additional in vivo\nmodel using the MC38-OVA colon carcinoma cell line (Nature. 2025 Apr;\n640(8060):1062–1071; Nat Commun. 2022 Sep 6;13(1):4981). MC38-OVA is a widely\nused murine model of colorectal cancer characterized by a high mutational burden\nand sensitivity to immune checkpoint blockade (Front Immunol. 2023 Mar\n8;14:1102282). GBP2 knockout in MC38-OVA cells was generated using\nCRISPR/Cas9 and confirmed via western blotting (Fig. S5D). Subcutaneous tumors\nderived from sgCtrl and sgGBP2 MC38-OVA cells were subsequently treated with\nadoptive OT-1 cell transfer or anti-PD-L1 antibody. Notably, GBP2 deficiency\nsignificantly impaired tumor suppression induced by either OT-1 cell transfer or PD-\nL1 blockade (Fig. S5E-H).\nIn accordance with the reviewer’s advice, these new data have been incorporated into\nthe revised manuscript (page 18 line 402-404; Fig. S5D-H).\nPart new figures are shown below.\nFig. S5: (D) Western blot showed the transfection efficiency of sgGBP2 in MC38-OVA cells.\n(E) The sgCtrl or GBP2-/- MC38-OVA (1 × 106) cells subcutaneously injected into C57BL/6\nmice. Mice were adoptively transferred with OT-1 cells (5 × 106 per mouse) or PBS once per\n7 days. (F) Tumor inhibition rate for GBP2-/- cells relative to sgCtrl cells under OT-1 treatment,\nrespectively (n = 6). (G) The sgCtrl or GBP2-/- MC38-OVA (1 × 106) cells subcutaneously\ninjected into C57BL/6 mice. Mice with a tumor size of 125 mm3 were treated with anti–PD-L1\nantibody (200 μg per mouse) or IgG once per 3 days. (H) Tumor inhibition rate for GBP2-/-\ncells relative to sgCtrl cells under anti-PD-L1 treatment, respectively (n = 6).\n- Fig 3A: Please quantify Western blots if reporting significance.\nResponse:\nFollowing the reviewer’s advice, we quantified the western blots of Fig. 3A. The grey\nvalues including the GAPDH were quantified by Image J, and the relative expression\nwas calculated by comparing to the control groups and GAPDH (See the figure below).\nIn addition, we also quantified other WB bands in the manuscript.\n- Fig 4: It would strengthen the conclusions to repeat at least some of these\nexperiments in another cell line\nResponse:\nIn response to the reviewer’s suggestion, we repeated key experiments from Fig. 4\nusing A375 melanoma cells. Consistent with our previous observations, endogenous\nGBP2 formed droplet-like condensates upon IFN-γ stimulation in A375 cells. These\ncondensates exhibited hallmark features of liquid–liquid phase separation (LLPS),\nincluding dynamic fusion events and rapid fluorescence recovery after photobleaching\n(FRAP), with recovery exceeding 60% within approximately 120 seconds (Fig. S8A-\nC). Treatment with 1,6-hexanediol, a reagent known to disrupt hydrophobic\ninteractions critical for LLPS, effectively abolished condensate formation (Fig. S9A).\nMoreover, deletion of the intrinsically disordered region (IDR) completely abrogated\ncondensate assembly (Fig. S9D).\nIn accordance with the reviewer’s recommendation, these new data have been\nincorporated into the revised manuscript (page 23 line 504-509,515-517; page 24 line\n524-525, Fig. S8A-C and S9A, D).\nPart new figures are shown below.\nFig. S8: (A) Representative images from live GBP2-mCherry A375 cells stimulated with 10\nng/ml IFN-γ for 6 hours. (B) Representative images from live cell images of A375 cells\nexpressing GBP2-mCherry stimulated with 10 ng/ml IFN-γ for 6 hours. The arrows point to the\nrepresentative condensates formed by GBP2 that fused over time. (C) Representative images\nshowed that FRAP assay of the droplets formed in A375 cells expressing GBP2-mCherry\nstimulated with 10 ng/ml IFN-γ for 6 hours. The data are plotted as the mean ± SD on the right\n(n = 3).\nFig. S9: (A) Representative images showed that GBP2-mCherry B16-OVA cells were treated\nwith 5% 1,6-hexanediol (1,6-HD) for 5 min stimulated with 10 ng/ml IFN-γ for 6 hours. (D)\nRepresentative images from A375 cells expressing GBP2-mCherry and GBP2-mCherry IDR\ndeletion (△IDR) stimulated with 10 ng/ml IFN-γ for 6 hours.\n- Fig 5K: It seems important to show expression and stability of the delta IDR GBP2\nprotein (unless I missed this data)– otherwise it may mis-fold or be unstable and\neffectively just knock the protein down.\nResponse:\nThank you for this valuable comment. To address the concern regarding the protein\nexpression and stability of ΔIDR GBP2, we performed the following experiments. First,\nwe purified recombinant GBP2-FL and GBP2-ΔIDR proteins from E. coli. Coomassie\nblue staining revealed bands of the expected molecular weights, indicating that the\nIDR deletion does not impair GBP2 folding (Fig. S9B). Next, we transfected GBP2⁻/⁻\nB16-OVA cells with either GBP2-FL or ΔIDR plasmids, followed by treatment with\nMG132 (proteasome inhibitor), BafA1 (autophagy inhibitor), or CQ (lysosomal\ninhibitor). In both the FL and ΔIDR groups, GBP2 expression levels remained largely\nunchanged regardless of the inhibitor applied (Fig. S9C).\nCollectively, these results demonstrate that deletion of the IDR region does not\nsubstantially affect GBP2 protein expression or stability. In accordance with the\nreviewer’s suggestion, we have incorporated these new data into the revised\nmanuscript (page 24 line 519-524; Fig. S9B-C).\nPart new figures are shown below.\nFig. S9: (B) Purified recombinant GBP2-FL and GBP2 ΔIDR were shown by coomassie\nstaining. (C) Western blot analysis of WCL derived from GBP2-/- + FL or GBP2-/- + ΔIDR cells\ntreated with MG132 (10 μM), bafilomycin A1 (BafA1, 100 nM), or chloroquine (CQ, 5 μM) for\n12 h.\n- Is GBP2 genetically lost / selected against in tumors? The authors’ findings would\npredict that it should be, given that this is claimed to induce resistance to anti-tumor\nimmunity in an immunogenic disease.\nResponse:\nWe thank the reviewer for raising this critical point. The genetic status of tumors is\nindeed a major determinant of response to ICB therapy (Cell. 2021 Oct\n14;184(21):5309–5337). Accordingly, it is essential to investigate whether GBP2 is\ngenetically lost or selectively downregulated in tumors.\nFirst, integrative analyses using spatial transcriptomics (Fig. 1I) and newly\nacquired clinical melanoma specimens (Figure for reviewer. A) consistently revealed\nreduced GBP2 expression in melanoma tissues compared to adjacent normal tissues.\nTo explore potential genetic mechanisms underlying this downregulation, we analyzed\nsomatic mutation rates in melanoma using data from The Cancer Genome Atlas\n(TCGA). A waterfall plot illustrating the top 20 most frequently mutated genes, along\nwith GBP2, showed that the somatic mutation rate of GBP2 is very low (~2%) (Figure\nfor reviewer. B), suggesting that genetic mutation is unlikely to be the major\nmechanism underlying GBP2 loss.\nBeyond genetic alterations, epigenetic regulation represents a well-established\nalternative mechanism for gene silencing (Nat Immunol. 2024 Oct;25(10):1858–1870;\nSci Transl Med. 2023 Feb;15(681):eabq6024). Recent studies have demonstrated that\nepigenetic dysregulation is a conserved mechanism modulating GBP family gene\nexpression across various cancers. For instance, GBP4 promoter hypomethylation\nhas been observed in pancreatic ductal adenocarcinoma relative to adjacent normal\ntissue, and targeted promoter methylation suppresses GBP4 expression (Cancer\nImmunol Immunother. 2024 Aug 7;73(10):208). Similarly, GBP6 hypermethylation\npredicts poor prognosis in gastric cancer (Clin Epigenetics. 2020 Jan 20;12(1):15),\nwhile plasma GBP2 methylation levels correlate with advanced stages of breast\ncancer (Genet Mol Biol. 2020 Nov 17;43(4):e20190230). Consistent with these\nfindings, we observed a strong negative correlation between GBP2 expression and\nDNA methylation in melanoma samples (Figure for reviewer. C). These results\ncollectively suggest that DNA methylation-mediated silencing may represent a\nplausible mechanism for GBP2 downregulation in tumors. While this epigenetic axis\nis of significant interest, our current study focuses primarily on the functional and\nmechanistic role of GBP2 in modulating ICB responses. Investigation of upstream\nepigenetic regulation remains an important component of our ongoing work and is\ntherefore discussed in the revised manuscript's Discussion and Limitations sections\nSecond, regarding the question of whether GBP2 is under negative selective\npressure in tumors: the concept of \"selected against\" implies that tumor cells lose\nGBP2 expression to gain a survival advantage. To address this, we analyzed publicly\navailable screening data and found that GBP2 expression was positively correlated\nwith OT-1-mediated cytotoxicity (Figure for reviewer. D), akin to known components\nof the IFN-γ signaling pathway such as STAT1, B2M, and TAP1. This supports a role\nfor GBP2 in promoting anti-tumor immune responses. These findings suggest that\ntumors may actively suppress GBP2 expression as an immune evasion strategy.\nConsistently, GBP2 knockout rendered tumor cells resistant to immune-mediated\nkilling.\nIn response to reviewers' comments and considering space constraints and\noverall manuscript flow, the relevant results are presented in the corresponding figure\npanels below (Figure for reviewer. A-D). Given that the primary aim of this study is to\nelucidate the mechanisms by which GBP2 enhances ICB efficacy, we have discussed\nthese insights in the revised Discussion and Limitations section. Future studies are\nwarranted to further dissect the upstream regulatory mechanisms governing GBP2\nexpression.\nPart new figures are shown below.\nFigure for reviewer only: (A) Representative image of GBP2 immunohistochemical staining\nof melanoma samples (including normal skin) (n = 3). (B) The waterfall plots showed the\nsomatic mutation rate of top 20 gene and GBP2 based on the TCGA-SKCM cohort. (C) The\nrelationship between GBP2 expression and beta value of promoter in melanoma based on the\nDNMIVD database. (D) CRISPR screen data from J. Kearney, 2018. The positive score and\np value of Gbp2, Stat1, Jak1, B2m, Tap1 sgRNA (OT-1 treatment versus T0) in MC38-OVA\ncells were shown.\n- Fig 3: Given the purported mechanism, It would be helpful to see whether\noverexpression of SLC7A11 obviates the effect of GBP2 knockout to prove that this is\nper se the mechanism of impaired tumor growth.\nResponse:\nAs suggested by the reviewer, we further conducted in vivo experiments, which\ndemonstrated that SLC7A11 overexpression significantly attenuated the tumor-\nsuppressive effect of GBP2 overexpression. It also led to a reduction in intratumoral\nlipid ROS levels and abrogated the ability of GBP2 to enhance immune checkpoint\nblockade (ICB) efficacy (Fig. 3E-F).\nIn accordance with the reviewer’s recommendation, we have included these new data\nin the revised manuscript (page 21 line 457-460; Fig. 3E-F).\nPart new figures are shown below.\nFig. 3: (E) 1 × 106 vector, GBP2-overexpression (oeGBP2) and oeGBP2 transfected with\noeSLC7A11 plasmid B16-OVA cells were subcutaneously injected into C57BL/6 mice. All\nmice with a tumor size of 125 mm3 were treated with anti-PD-L1 antibody or IgG once per 3\ndays. (F) Relative lipid ROS of vector, oeGBP2 or oeGBP2 + oeSLC7A11 tumours in mice\ntreated with anti-PD-L1 were quantified in CD45− cells by flow cytometric analysis.\n- The STAT1 ko result is already well known as a broad resistance mechanism for B16\ntumors, and so may or may not be related to GBP2 biology here.\nResponse:\nWe thank the reviewer for raising this important point. We understand the concern that\nSTAT1 might influence immunotherapy not only by inducing ferroptosis in B16 cells\nbut also via other mechanisms. To clarify, in our study using B16-OVA cells, STAT1\nknockout does not affect MHC-I expression. This is because our B16-OVA cells were\nengineered (Elife. 2018 Nov 30:7:e41090) to constitutively overexpress both OVA and\nMHC-I components, ensuring stable antigen presentation independent of STAT1\nstatus. Flow cytometry analysis confirmed no significant differences in MHC-I surface\nexpression between sgCtrl and sgGBP2 (or STAT1 KO) cells (Fig. S7E-F). Thus, the\nobserved effects are unlikely to be confounded by altered MHC-I expression due to\nSTAT1 knockout. Additionally, we assessed the expression of checkpoint ligands,\nfocusing on PD-L1. Western blot analysis of sgGBP2 cells revealed no significant\ndifference in PD-L1 expression levels compared to sgCtrl—both with and without IFN-\nγ stimulation (Fig. S7G). We also employed FucoID technology (Cell, 2020 Nov\n12;183(4):1117–1133) to assess CD8⁺ T and NK cell interactions with tumor cells. As\na result, no significant differences were observed between sgCtrl and sgGBP2 group\n(Fig. S7H).\nThese results indicate that GBP2's effects are independent of STAT1 pathway-\nmediated alterations in MHC-I expression, PD-L1 expression, or recognition by CD8+\nT cells/NK cells. Meanwhile, our findings in Fig. 2 demonstrate that GBP2 modulates\nferroptosis, and given that Wang et al. reported STAT1 suppresses SLC7A11 to\npromote ferroptosis (Nature. 2019 May;569(7755):270-274), we hypothesize that the\nSTAT1/SLC7A11 axis contributes to GBP2-mediated cell death. As suggested by the\nreviewer, we further performed in vivo experiments and the result demonstrated that\nSLC7A11 overexpression SLC7A11 overexpression significantly diminished the\ntumor-suppressive effect of GBP2 overexpression, reduced intratumoral levels of lipid\nROS, and abolished its ability to enhance ICB efficacy (Fig. 3E-F).\nAs response to reviewer, we have included these new data in the revised manuscript\n(page 21-22 line 457-460,467-481; Fig. 3E-F and Fig. S7E-H).\nPart new figures are shown below.\nFig. S7: (E-F) Representative flow cytometry plots and quantification showing H-2Kb bound\nto SIINFEKL in sgCtrl and GBP2-/- B16-OVA and MC38-OVA groups. (G) The sgCtrl and\nGBP2-/- B16-OVA and A375 cells were treated with 10 ng/mL IFN-γ for 12 hours, respectively.\nCell lysates were collected and analyzed the indicated molecules by western blot. (H)The\nsgCtrl and GBP2-/- B16-OVA cells co-cultured with CD8+T or NK cells were co-incubated in\nthe presence of biotin–LPETG for 30 min and analyzed by flow cytometry. The extent of\nlabelling of tumor cells between groups.\nFig. 3: (E) 1 × 106 vector, GBP2-overexpression (oeGBP2) and oeGBP2 transfected with\noeSLC7A11 plasmid B16-OVA cells were subcutaneously injected into C57BL/6 mice. All\nmice with a tumor size of 125 mm3 were treated with anti-PD-L1 antibody or IgG once per 3\ndays. (F) Relative lipid ROS of vector, oeGBP2 or oeGBP2 + oeSLC7A11 tumours in mice\ntreated with anti-PD-L1 were quantified in CD45− cells by flow cytometric analysis.\n- Fig 3B: how many samples is this representative example drawn from?\nResponse:\nWe have added representative example images from three samples in the figure\nlegend. According to the reviewer’s suggestion, we revised the description in the figure\nlegend of revised manuscript, page 41 line 1014.\n- Fig 3E: Given that the authors argue that GBP2 limits STAT1 signaling, it should\nlimit ISGs broadly. Do the authors therefore see lower MHC-I and PD-L1 expression\nin IFNg-stimulated GBP2 ko cells?\nResponse:\nWe thank the reviewer for raising this important point. We agree that STAT1 plays a\npivotal role in tumor immunology (Signal Transduct Target Ther. 2021; 6:402). In\nresponse to the reviewer’s suggestion, we conducted comparative analyses of MHC-\nI expression and checkpoint ligand expression.\nOur experimental model utilized B16-OVA cells, where MHC-I is essential for OT-\nderived from lysosomal and proteasomal degradation. To rule out confounding effects\nrelated to antigen presentation, we followed the approach described by Gejman et al.\n(Elife. 2018 Nov 30;7:e41090) and engineered B16-OVA cells to constitutively\noverexpress both OVA and MHC-I components. Therefore, the scenario raised by the\nreviewer does not apply in our system.\nTo further address this concern directly, we performed flow cytometric analysis of\nMHC-I expression and observed no significant differences between sgCtrl and\nsgGBP2 groups (Fig. S7E-F). We also examined checkpoint ligand expression,\nspecifically focusing on PD-L1. Western blot analysis showed that PD-L1 levels were\ncomparable between sgCtrl and sgGBP2 cells, both under basal conditions and\nfollowing IFN-γ stimulation (Fig. S7G).\nIn accordance with the reviewer’s suggestion, these new data have been\nincorporated into the revised manuscript (page 22, line 467-478) and are presented in\nFig. S7E-G.\nPart new figures are shown below.\nFig. S7: (E-F) Representative flow cytometry plots and quantification showing H-2Kb bound\nto SIINFEKL in sgCtrl and GBP2-/- B16-OVA and MC38-OVA groups. (G) The sgCtrl and\nGBP2-/- B16-OVA and A375 cells were treated with 10 ng/mL IFN-γ for 12 hours, respectively.\nCell lysates were collected and analyzed the indicated molecules by western blot.\n- Fig 5: It would be helpful to see co-localization of SHP1 and STAT1 or pSTAT1\ntogether in the same images in GBP2 KO vs GBP2-expressing cells.\nResponse:\nAs suggested by the reviewer, we performed Co-IP experiment and the result\ndemonstrated that SHP1 directly binds to STAT1, and this binding was increased\nfollowing GBP2 knockout (Fig. S9J).\nAccording to the reviewer’s suggestion, we added the new data in the revised\nmanuscript, page 25 line 546-547 and Fig. S9J.\nPart new figures are shown below.\nFig. S9J: The sgCtrl and GBP2-/- cells treated with IFN-γ were used for immunoprecipitation\nwith anti-SHP1 antibody and analyzed by western blot with the indicated antibodies.\n- Fig 6: HMGB1 is not particularly specific for ferroptotic death. Other IFN-dependent\npathways of killing (ie most of them since IFN affects T cell recognition via MHC-I)\ncould presumably be equally implicated here. Overexpressing SLC7A11 may provide\nstronger evidence than deletion of STAT1, which is a general way to suppress tumor\nresponse.\nResponse:\nWe appreciate the reviewer’s comment regarding HMGB1. We acknowledge that\nHMGB1 release is not exclusively specific to ferroptosis. As a prototypical damage-\nassociated molecular pattern (DAMP), HMGB1 is known to translocate and be\nreleased in response to elevated levels of reactive oxygen species (ROS). During\nferroptosis, HMGB1 is frequently secreted and serves as an immunogenic signal,\ncontributing to the activation and recruitment of CD8⁺ T cells.\nTo more robustly support our hypothesis that GBP2 suppresses tumor\nprogression by promoting ferroptosis, as suggested by the reviewer, we performed\nadditional in vivo experiments. Our experiments demonstrated that overexpression of\nSLC7A11 significantly reversed the tumor-suppressive effects induced by GBP2\noverexpression (Fig. 3E-F). Consistently, ELISA analysis of tumor tissues revealed a\nmarked reduction in HMGB1 levels in the SLC7A11 overexpression group (Fig. S11E).\nMoreover, we appreciate reviewer #4's assessment that the data linking HMGB1\nto GBP2-mediated tumor immunity may be redundant, along with their\nrecommendation to deemphasize this aspect. In line with our proposed mechanism—\nnamely, that GBP2 enhances immune checkpoint blockade (ICB) efficacy by\npromoting immunogenic ferroptosis—HMGB1 was used as an auxiliary indicator of\nimmunogenic cell death. Accordingly, we have relocated all HMGB1-related data to\nthe Supplementary Materials, in alignment with the feedback from both reviewers.\nAccording to the reviewer’s suggestion, we added the new data in the revised\nmanuscript (page 21 line 457-460; page 28 line 614-615 and Fig. 3E-F and Fig. S11).\nPart new figures are shown below.\nFig. 3: (E) 1 × 106 vector, GBP2-overexpression (oeGBP2) and oeGBP2 transfected with\noeSLC7A11 plasmid B16-OVA cells were subcutaneously injected into C57BL/6 mice. All\nmice with a tumor size of 125 mm3 were treated with anti-PD-L1 antibody or IgG once per 3\ndays. (F) Relative lipid ROS of vector, oeGBP2 or oeGBP2 + oeSLC7A11 tumours in mice\ntreated with anti-PD-L1 were quantified in CD45− cells by flow cytometric analysis.\nFig. S11: (A) The level of HMGB1 was assessed between sgCtrl and GBP2-/- tumours under\nanti-PD-L1 and OT-1 treatment through ELISA. (B) Dendritic cells were isolated by positive\nselection from tumor tissues (sgCtrl + OT-1 or GBP2-/-+ OT-1) using magnetic-activated cell\nsorting and total RNA was extracted from these cells. CD80 and CD86 were analyzed by\nqPCR. (C) Violin plot of CD86 expression in GBP2 lowest and GBP2 highest patients based\non the GSE115978 dataset. (D) The level of HMGB1 was assessed between sgCtrl and\nSTAT1-/- tumours under OT-1 treatment through ELISA. (E) The level of HMGB1 was\nassessed between Vec, oeGBP2 and oeGBP2 + oeSLC7A11 tumours under anti-PD-L1\ntreatment through ELISA. (F) Western blot showed the transfection efficiency of sgHMGB1 in\nGBP2oe B16-OVA cells. (G) GBP2 vector, GBP2oe and GBP2oe + HMGB1-/- B16-OVA (1 × 106)\ncells subcutaneously injected into C57BL/6 mice. Mice were adoptively transferred with OT-1\ncells (5 × 106 per mouse) or PBS once per 7 days. Tumor growth curves were monitored. (H)\nThe quantitative percentage of CD45+CD8+OT-1 cells between Vec and HMGB1 knockout\ntumors were shown. (I) Dendritic cells were isolated by positive selection from GBP2oe tumor\ntissues (sgCtrl + OT-1 or HMGB1-/-+ OT-1) using magnetic-activated cell sorting and total RNA\nwas extracted from these cells. CD80 and CD86 were analyzed by qPCR.\n- Fig 7: many of these analyses may be confounded by the relationship of GBP2 as\nan ISG— independent of any role in supporting anti-tumor immunity, GBP2 should\nanyhow be associated with response: because responding patients have T cells that\nmake IFNg.\nResponse:\nWe appreciate the reviewer's comment. Based on bioinformatic analysis screening for\npotential targets associated with T cell cytotoxicity, we identified GBP2 as a candidate.\nHowever, recognizing that bioinformatic findings are inherently correlative, we\nsubsequently conducted comprehensive in vivo and in vitro experiments to\ndemonstrate GBP2's impact on ICB efficacy and elucidate its underlying mechanism.\nOur results revealed that GBP2 sensitizes tumor cells to IFN-γ-induced ferroptosis,\nthereby enhancing the therapeutic effectiveness of immune checkpoint blockade (ICB).\nFurthermore, rescue experiments demonstrated that GBP2 restoration in GBP2-/- cells\n(GBP2-/- + oeGBP2) reversed the expression of SLC7A11, promoted STAT1\nphosphorylation, and consequently generated smaller tumors exhibiting elevated\nlevels of lipid ROS. These findings demonstrate that ICB efficacy is dependent on\nGBP2 expression. Mechanistically, GBP2 inhibited SLC7A11 expression by promoting\nSTAT1 phosphorylation through phase separation, leading to ferroptosis. Finally,\nprompted by these mechanistic findings, we analyzed the relationship between GBP2\nexpression and response to ICB in patients, revealing a strong positive association\nbetween GBP2 levels and ICB responsiveness.\n- I did not see computational methods reported in the methods section.\nResponse:\nWe previously included the computational methods in the supplementary materials in\norder to reduce the length of the manuscript. According to the reviewer’s suggestion,\nwe have now re-adjusted these essential methodological descriptions to the revised\nmanuscript (Methods section, page 13-15 line 287-332) to enhance accessibility and\nfacilitate direct citation.\nReviewer #3\nThe manuscript titled “Gbp2 condensate promote ferroptosis, sensitize anti-PD-L1 ICB\nin melanoma” investigates the role of Gbp2 in enhancing immune checkpoint blockade\n(ICB) in a mouse model. The authors propose that under IFN-γ stimulation, Gbp2\nundergoes phase separation to form condensates that sequester SHP1. This\nsequestration facilitates STAT1 phosphorylation, which then downregulates SLC7A11,\nleading to ferroptosis and increased immunogenicity of dying cancer cells. Gbp2\noverexpression is shown to increase T-cell infiltration, with this effect being attenuated\nin HMGB1 knockout models. Conversely, disruption of Gbp2 phase separation\nappears to promote tumor growth and reduce ICB efficacy.\nWhile the authors have made a commendable effort to dissect the function and\nmechanism of Gbp2, several key issues remain unresolved. Most notably, it is unclear\nwhether endogenous GBP2 condensates sequester SHP1 to a degree that facilitates\nSTAT1 activation and ferroptosis, and whether GBP2 serves as a reliable biomarker\nfor ICB response in patients.\nMajor Comments\n1. There is an inconsistency between the basal levels of GBP2 in the “sgCtrl” group\n(Figure S5, panel a) versus the “Vec” group (panel b), despite consistent GAPDH\nloading controls and the expectation that these represent the same cell line. The\nauthors should provide a clear explanation for the observed differences.\nResponse:\nWe appreciate the reviewer’s comment and sincerely regret this oversight. The\ndiscrepancy primarily resulted from the fact that Western blot validation was not\nconducted simultaneously upon generation of the respective cell lines. This temporal\nvariation likely introduced inconsistencies in protein loading and exposure time, which\nmay have contributed to the apparent differences in expression levels between the\ntwo control groups derived from the same cell line.\nTo resolve this issue, we ensured rigorous control over protein loading and exposure\nconditions, and conducted detection on a single membrane to minimize technical\nvariability. The updated results confirm that sgCtrl and vector control (vec) display\ncomparable expression levels.\nIn accordance with the reviewer’s suggestion, we have included this new data in the\nrevised manuscript (Fig. S5A).\nPart new figures are shown below.\nFig. S5A: Western blot showed the transfection efficiency of sgGBP2 and GBP2\noverexpression lentiviral in B16-OVA cells.\n2. Data in Figures 2a and 2b indicate that GBP2 knockout cells display a growth\nadvantage and reduced T-cell cytotoxicity regardless of ICB treatment, suggesting that\nGBP2 may act as a general mediator of T-cell cytotoxicity rather than being ICB-\nspecific. The authors should provide additional data to support an ICB-specific role for\nGBP2 or adjust their claims to indicate that GBP2 functions as a general regulator of\ncell growth and T-cell toxicity.\nResponse:\nWe appreciate the reviewer’s insightful comment. In the tumor microenvironment,\nexcessive activation of immune checkpoint pathways suppresses T cell cytotoxicity,\nfacilitating immune evasion. The therapeutic efficacy of ICB is primarily attributed to\nthe reinvigoration of tumor-specific CD8⁺ T cells (Cell. 2021 Oct 14;184(21):5309-5337;\nScience. 2018 Mar 23;359(6382):1350-1355). These reinvigorated T cells recognize\nMHC-I–peptide complexes on tumor cells via their specific TCRs, triggering the\nrelease of cytolytic granules and IFN-γ, which mediate tumor cell killing (Nature. 2023\nJun;618(7967):1033-1040).\nDespite its clinical benefits, ICB is effective in only a subset of patients, prompting\nintensive efforts to identify novel targets that enhance CTL-mediated killing and\npotentiate ICB efficacy. For example, VDAC2 has been reported as an\nimmunoregulatory checkpoint that attenuates T cell–derived IFN-γ–mediated tumor\ndestruction and suppresses inflammatory reprogramming of the tumor\nmicroenvironment. Inhibiting VDAC2 sensitizes tumor cells to IFN-γ–induced cell\ndeath, thereby significantly enhancing antitumor immunity and ICB responsiveness\n(Nature. 2025 Apr;640(8060):1062-1071). Similarly, Liao et al. demonstrated that\nCTL-derived IFN-γ and tumor microenvironmental arachidonic acid synergistically\ninduce ACSL4-dependent ferroptosis, and targeting ACSL4 increases tumor\nsusceptibility to ICB therapy (Cancer Cell. 2022 Apr 11;40(4):365-378.e6).\nIn this study, bioinformatic screening identified GBP2 as a key regulator positively\ncorrelated with T cell cytotoxicity. We performed comprehensive in vivo and in vitro\nanalyses to validate GBP2’s impact on T cell–mediated tumor elimination. First,\nsgGBP2 tumors implanted in immunodeficient NSG mice exhibited comparable growth\nbetween sgCtrl and sgGBP2 groups (Fig. S5C), indicating that GBP2 primarily\nmediates tumor suppression through immune regulation. Given the pivotal role of\nCD8⁺ T cells in antitumor immunity, we next depleted CD8⁺ T cells and found that\ntumor growth in the oeGBP2 group was markedly increased (Fig. 6D), underscoring\nthe CD8⁺ T cell dependency of GBP2-mediated effects.\nTo assess whether GBP2 specifically influences ICB-mediated killing, we\ncompared PD-L1 expression after sgGBP2 knockout and observed no significant\nchanges (Fig. S7G). To eliminate potential confounding from MHC-I modulation, we\nengineered B16-OVA cells (following Gejman et al., Elife. 2018 Nov 30;7:e41090) to\nconstitutively express both OVA and MHC-I components. Flow cytometry confirmed\nno significant differences in MHC-I levels between sgCtrl and sgGBP2 cells (Fig. S7E-\nF).\nCD8⁺ T cells activated by cancer immunotherapy primarily clear tumors via\nperforin–granzyme and Fas–FasL pathways (Nat Rev Immunol. 2018 Aug;18(8):527-\n535). To identify the specific effector molecule involved, we generated perforin⁻/⁻,\nIFNγ⁻/⁻, or TNFα⁻/⁻ OT-1 cells and co-cultured them with control or GBP2-\noverexpressing B16-OVA tumor cells. Loss of IFN-γ, but not perforin or TNF, \nabrogated OT-1–mediated killing of GBP2-overexpressing tumors (Fig. 2L).\nFurthermore, as suggested by the reviewer, we performed blocking experiments,\nshowing that GBP2 overexpression enhanced both ICB efficacy and lipid ROS\naccumulation (Fig. 2M and Fig. S6I), effects that were completely abolished by anti–\nIFN-γ monoclonal antibodies (Fig. 2M and Fig. S6I). Consistent with Wang et al.\n(Nature. 2019 May;569(7755):270-274). who demonstrated that ICB-activated CD8⁺\nT cells can directly sensitize tumors to ferroptosis via IFN-γ secretion, our in vivo\nresults indicate that GBP2 knockout reduces both CTL-mediated ferroptosis and anti–\nPD-L1 efficacy (Fig. 2A-B).\nWhile our current data cannot fully resolve whether GBP2 acts primarily as a\ngeneral enhancer of T cell cytotoxicity or as an ICB-specific regulator, they clearly\nestablish that GBP2 both augments T cell–mediated killing and amplifies ICB-induced\ntumor elimination through CD8⁺ T cell–driven ferroptosis. We acknowledge that the\noriginal manuscript provided suboptimal mechanistic resolution; therefore, we have\nsubstantially revised the text to clarify GBP2’s dual role. Notably, given its ability to\nenhance CTL-mediated cytotoxicity, future studies should explore whether GBP2\nmodulation can be harnessed to improve CAR-T cell efficacy.\nIn accordance with the reviewer’s suggestion, these new data have been incorporated\ninto the revised manuscript (page 20, line 430-437; page 18, line 389-393; page 22,\nline 470-478, Fig. 2L-M; Fig. 6D; Fig. S5C; Fig. S6I; Fig. S7E-G).\nPart new figures are shown below.\nFig. S5C: Tumor volume of sgCtrl, or GBP2-/- B16-OVA tumors in NSG mice. Fig. 6D: Tumor\nvolume of vector, GBP2oe, anti-CD8α or GBP2oe + anti-CD8α B16-OVA tumors in C57BL/6\nmice.\nFig. S7: (E-F) Representative flow cytometry plots and quantification showing H-2Kb bound\nto SIINFEKL in sgCtrl and GBP2-/- B16-OVA and MC38-OVA groups. (G) The sgCtrl and\nGBP2-/- B16-OVA and A375 cells were treated with 10 ng/mL IFN-γ for 12 hours, respectively.\nCell lysates were collected and analyzed the indicated molecules by western blot.\nFig. 2: (L) Control or GBP2-overexpression tumor cell viability after co-culture with sgCtrl-,\nsgIFNγ-, sgTNFα- or sgPRF1-transduced OT-1 cells at E:T ratio of 1:1 for 24 h (n = 3 per\ngroup) (M) The control and GBP2-overexpression B16-OVA (1 × 106) cells subcutaneously\ninjected into C57BL/6 mice. Mice with a tumor size of 125 mm3 were treated with anti-PD-L1\nantibody, anti-IFN-γ antibody or IgG once per 3 days.\nFig. S6I: Relative lipid ROS of vector, GBP2oe, anti-IFNγ, GBP2oe + anti-IFNγ tumours in mice\ntreated with anti-PD-L1 were quantified in CD45- cells by flow cytometric analysis.\n3. In Figure 3a, the manuscript states that “A significant increase in SLC7A11\nexpression was found in GBP2-/- compared to sgCtrl cells, and this effect was restored\nby IFN-γ stimulation.” The authors need to provide quantitative analysis to support this\nclaim and clarify what is meant by “restored”.\nResponse:\nWe apologize for the inaccurate characterization of our results in the original\nmanuscript. As the reviewer's suggestion, we have now quantified all Western blot\nbands. The grey values including the GAPDH were quantified by ImageJ software,\nand the relative expression was calculated by comparing to the control groups and\nGAPDH. We have corrected the erroneous description regarding 'rescue' effects - our\nintended conclusion was that “Compared with sgCtrl cells, sgGBP2 cells displayed a\nmarked attenuation of IFN-γ-induced downregulation of SLC7A11” in the revised\nmanuscript, page 20 line 448-449.\n4. The in vitro co-culture experiments with ferrostatin-1 suggest that immune cell–\nderived factors may induce cancer cell death via ferroptosis. However, this does not\nestablish ferroptosis as the predominant pathway underlying GBP2’s function in ICB.\nThe authors should either present direct evidence that ferroptosis is the major\nmechanism (e.g., through rescue experiments with ferroptosis inhibitors or additional\nmarkers) or adjust their claims regarding the role of ferroptosis.\nResponse:\nWe sincerely thank the reviewer for this critical insight. We acknowledge that our study\nhas not yet definitively established ferroptosis as the primary mechanism through\nwhich GBP2 potentiates ICB efficacy. First, to further identify the specific cytokine\nmediating this effect, we generated perforin-/-, IFNγ-/-, or TNFα-/- OT-1 cells and co-\ncultured them with control versus GBP2-overexpressing B16-OVA tumor cells.\nCritically, loss of IFN-γ, but not perforin or TNF, prevented OT-1-cell-mediated killing\nof GBP2-overexpressing tumors (Fig. 2L). Furthermore, we performed blocking\nexperiments as suggested by the reviewer. We found that GBP2 overexpression\nenhanced both ICB efficacy and lipid ROS production (Fig. 2M and Fig. S6I). These\neffects were abrogated by anti-IFN-γ monoclonal antibodies (mAbs) (Fig. 2M and Fig.\nS6I).\nFurthermore, to distinguish ferroptosis from alternative CD8+T cell-induced death\npathways (e.g., pyroptosis, necroptosis, apoptosis) (J Hematol Oncol. 2020 Aug\n10;13(1):110), we conducted rescue experiments with inhibitors of CD8+T cell-induced\ndeath. Treatment with the ferroptosis-specific inhibitor ferrostatin-1 significantly\nattenuated IFN-γ-induced cell death in GBP2-overexpressing tumor cells, whereas\ninhibitors targeting pan-caspase (emricasan), necroptosis (necrostatin-1), and\npyroptosis (disulfiram) showed no such effects (Fig. 2E). These results demonstrate\nthat GBP2 potentiates CD8⁺ T cell-derived IFNγ to predominantly execute tumor cell\nelimination through ferroptosis.\nAccording to the reviewer’s suggestion, we added the new data in the revised\nmanuscript, page 19 line 409-412; page 20 line 430-437 and Fig. 2E, L-M and Fig. S6I.\nPart new figures are shown below.\nFig. 2: (L) Control or GBP2-overexpression tumor cell viability after co-culture with sgCtrl-,\nsgIFNγ-, sgTNFα- or sgPRF1-transduced OT-1 cells at E:T ratio of 1:1 for 24 h (n = 3 per\ngroup) (M) The control and GBP2-overexpression B16-OVA (1 × 106) cells subcutaneously\ninjected into C57BL/6 mice. Mice with a tumor size of 125 mm3 were treated with anti-PD-L1\nantibody, anti-IFN-γ antibody or IgG once per 3 days.\nFig. S6I: Relative lipid ROS of vector, GBP2oe, anti-IFNγ, GBP2oe + anti-IFNγ tumours in mice\ntreated with anti-PD-L1 were quantified in CD45- cells by flow cytometric analysis.\nFig. 2E: Control or GBP2-overexpression tumor cell before or after co-cultured with OT-1 cells\nat E:T ratio of 1:1 for 24 hours (n = 3 per group) plus pan-caspase inhibitor emricasan,\nferroptosis inhibitor ferrostatin-1 (Fer-1), necroptosis inhibitor necrostatin-1 (Nec-1) or\nGSDMD- mediated pyroptosis inhibitor disulfiram for 24 hours (n = 3 per group).\n5. In Figure 5d, the manuscript indicates near-complete knockdown of GBP2 and\nSHP1 with siRNA, yet details regarding the siRNA sequences and a dose-response\ncurve are missing. Please provide the siRNA sequences and include a dose-response\nanalysis to validate knockdown efficiency.\nResponse:\nWe appreciate the reviewer’s insightful comment. To clarify, GBP2 knockout in this\nstudy was accomplished using CRISPR/Cas9 technology. For mus-SHP1,\nhum-SHP1, and mus-SLC7A11 knockdown, all siRNAs were commercially obtained\nfrom RiboBio. Following the manufacturer’s protocol, we transfected A375 and B16-OVA\ncells with a range of siRNA concentrations and assessed knockdown efficiency by qPCR.\nWestern blot validation was subsequently performed at the optimal concentration\ndetermined by transfection efficiency (Fig. S7C and Fig. S9F). Importantly, both\nSLC7A11 and SHP1 protein levels were efficiently silenced (≥90% reduction), as\nconfirmed by western blot analysis. The corresponding siRNA sequences are provided\nin Supplementary Table 3.\nIn response to the reviewers’ comments, and to balance space limitations with\nmanuscript flow, we have incorporated part of these new data into the revised\nmanuscript (page 21 line 452-454; page 24 line 536-537; and Fig. S7C and Fig. S9F).\nPart new figures are shown below.\nFigure for reviewer only: (A-B) Real-time PCR used to analyze the mRNA expression levels\nof SHP1 in B16-OVA and A375 cells transfected with siCtrl and different concentrations of\nhuman and murine si-SHP1 (si-#1, si-#2). (C) Real-time PCR used to analyze the mRNA\nexpression levels of SLC7A11 in B16-OVA cells transfected with siCtrl and different\nconcentrations of SLC7A11 siRNA (si-#1, si-#2).\nFig. S7C: Western blot showed the transfection efficiency of si-SLC7A11-#1 and si-SLC7A11-\n#2 and siCtrl at the optimal concentration in B16-OVA cells. Fig. S9F: Western blot showed\nthe transfection efficiency of human and murine si-SHP1-#1 and si-SHP1-#2 and siCtrl at the\noptimal concentration in B16-OVA and A375 cells.\n6. In Figure 5e, it is unclear whether the data reflect endogenous GBP2 or transfected\nGBP2. Moreover, overexpression of GBP2 lacking its intrinsically disordered region\nfails to form condensates, does not sequester SHP1, and returns STAT1\nphosphorylation to baseline, even though endogenous GBP2 should still be present.\nThe authors should clarify these findings and explain the mechanism by which\noverexpression of a GBP2 variant without the IDR interferes with endogenous\ncondensate formation.\nResponse:\nTo clarify, in the first version of the manuscript, Figure 5e represents endogenous\nGBP2 condensates, as these were assessed in live B16-OVA cells following knock-in\nof GBP2-mCherry. Additionally, we sincerely apologize for insufficient clarification\nregarding the cell models in Figure 5F-J. All data presented in these panels were\ngenerated using identical GBP2-deficient cell lines (B16-OVA or A375) to those in\nFigure 5K, as now explicitly stated in the revised manuscript. Furthermore, as the\nreviewer’s suggestion, we repeated the experiment by transfecting GBP2-/- cells with\nexogenous GBP2-FL or GBP2-ΔIDR. WB analysis confirmed reduced STAT1\nphosphorylation in the ΔIDR group (Figure for reviewer). We further established GBP2-\n/- tumor models reconstituted with either GBP2-FL or GBP2-ΔIDR, treated them with\nPD-L1 blockade, and performed in vivo co-IP (Fig. 5K, M). This confirmed an increase\nof STAT1-SHP1 binding in the ΔIDR group, leading to diminished STAT1\nphosphorylation (Fig. 5M). Together, these data demonstrate that overexpression of\na GBP2 variant without the IDR interferes with endogenous condensate formation,\nthereby impairing SHP1 retention. This ultimately reduces STAT1 phosphorylation and\nattenuates ICB efficacy.\nIn response to reviewers' comments and considering space constraints and overall\nmanuscript flow, we added the partial new data in the revised manuscript, page 26\nline 564-568 and Fig. 5K-M.\nPart new figures are shown below.\nFigure for reviewer only: B16-OVA GBP2-/- and A375 GBP2-/- cells were treated with 10\nng/ml IFN-γ for 12 hours, then transfected with vector, GBP2-FL and GBP2 △IDR plasmids\nfor 24 hours. Cell lysates were collected and analyzed the indicated molecules by western\nblot.\nFig. 5: (K) 1 × 106 GBP2-/- B16-OVA cells expressing GBP2-FL and GBP2 △IDR were\nsubcutaneously injected into C57BL/6 mice. Mice with a tumor size of 125 mm3 were treated\nwith anti–PD-L1 antibody or IgG once per 3 days. FL, full length. (M) The GBP2-FL and GBP2\n△IDR tumours were used for in vivo immunoprecipitation with anti-SHP1 antibody and\nanalyzed by western blot with the indicated antibodies.\n7. The claim that SHP1 sequestration within GBP2 condensates blocks its function is\nnot directly supported by the current data. Experiments demonstrating endogenous\nco-localization of GBP2 and SHP1 (e.g., via high-resolution imaging) are needed.\nAdditionally, in vitro assays (such as reconstituted phosphorylation assays) showing\nthat GBP2 condensates sequester SHP1 and impair STAT1 phosphorylation would\nstrengthen this claim.\nResponse:\nWe thank the reviewer’ s constructive suggestion. Following the reviewer’s\nsuggestions, we conducted super-resolution imaging and in vitro reconstituted\nphosphorylation assays to substantiate the claim that SHP1 sequestration within\nGBP2 condensates inhibits its ability to dephosphorylate STAT1. First, high-resolution\nimaging (e.g., super-resolution microscopy) demonstrated endogenous co-localization\nof GBP2 and SHP1 in cells, confirming that GBP2 condensates physically sequester\nSHP1 under physiological conditions (Fig. 5G). These results revealed a clear spatial\nassociation, with SHP1 enriched within GBP2 condensates, supporting our core\nhypothesis of sequestration.\nSubsequently, we purified recombinant GBP2, SHP1, JAK2, and STAT1 using E. coli,\n293T, and Sf9 expression systems to obtain high-purity proteins. Following\nestablished protocols (J Biol Chem. 1995 Sep 1;270(35):20775-80), we established\nan in vitro phase separation system by pre-incubating GBP2 to form condensates,\nfollowed by the addition of SHP1 to allow potential sequestration. In parallel, we\nperformed in vitro kinase reactions by incubating STAT1, JAK2, and ATP at 25°C for\n30 minutes. The phase separation system was then combined with the kinase reaction\nsystem in a HEPES reaction buffer (25 mM HEPES, pH 6.5, 50 mM NaCl, 10 mM 2-\nmercaptoethanol) for 10 minutes at room temperature to allow STAT1\ndephosphorylation. Reactions were terminated by boiling in SDS sample buffer for 5\nminutes. STAT1 phosphorylation was analyzed by Western blot using anti-phospho-\nSTAT1 (Tyr701) antibodies, comparing conditions with and without GBP2\ncondensates. In the absence of GBP2 condensates, phospho-STAT1 levels were\nreduced, indicating active dephosphorylation by SHP1. In contrast, sustained STAT1\nphosphorylation was observed in the presence of GBP2 condensates, demonstrating\nthat SHP1 sequestration within GBP2 condensates impairs its ability to\ndephosphorylate STAT1 (Fig. 5H). These findings provide robust evidence supporting\nthe functional inhibition of SHP1 by GBP2 condensate sequestration.\nAccording to the reviewer’s suggestion, we added the new data in the revised\nmanuscript, page 25 line 547-556 and Fig. 5G-H.\nPart new figures are shown below.\nFig. 5: (G) Representative high-resolution images from live B16-OVA cells expressing GBP2-\nmCherry stimulated with 10 ng/ml IFN-γ for 6 hours, and transfected with SHP1-mEGFP\nplasmid for 36 hours. The line plots show GBP2-mCherry and SHP1-mEGFP colocalization\nof areas. (H) In vitro kinase reactions were performed in the absence or presence of GBP2\ncondensates and immunoblotting of STAT1 phosphorylation and Coomassie blue staining of\ntotal protein of samples as indicated.\n8. The authors could utilize two strategies to test the function of phase separation to\nstrengthen their claims: (a) mutating specific amino acids to alter electrostatic and\nhydrophobic properties, and (b) fusing GBP2 to a hydrophilic sequence (e.g., MBP)\nto dampen self-association without altering the internal sequence.\nResponse:\nWe thank the reviewer’s constructive suggestion. To address the reviewer’s\nsuggestions for testing the role of phase separation in GBP2 function, we considered\nmutating specific amino acids in GBP2 to alter its electrostatic and hydrophobic\nproperties. However, due to concerns based on prior literature indicating that such\nmutations could disrupt protein’s overall structure and\nfunction(https://www.biorxiv.org/content/10.1101/2021.12.16.472976v1), we opted\nnot to pursue this approach to avoid confounding effects on protein integrity. Instead,\nwe fused GBP2 to a hydrophilic MBP sequence to dampen self-association while\npreserving the internal sequence. This fusion protein was tested in vitro, revealing\nreduced condensate formation and impaired SHP1 sequestration, which led to\nsustained STAT1 phosphorylation compared to wild-type GBP2 (Fig. 5J). Moreover,\nsimilar effects were observed in the IDR-deletion group (Fig. 5I). These results\ndemonstrate that GBP2’s phase separation is critical for its ability to sequester SHP1\nand modulate STAT1 signaling, robustly supporting our claims regarding the functional\nrole of phase separation.\nAccording to the reviewer’s suggestion, we added the new data in the revised\nmanuscript, page 25 line 556-560 and Fig. 5I-J.\nPart new figures are shown below.\nFig. 5: (I) In vitro phase separation compared the formation of condensates in GBP2 wild-type\n(WT) and GBP2 IDR groups. (J) In vitro phase separation compared the formation of\ncondensates in GBP2 WT and GBP2 MBP groups. Immunoblotting of STAT1 phosphorylation\nwith samples as indicated.\n9. In the first section, the manuscript claims that “bioinformatics analysis in clinical\nsamples suggests that GBP2 is a potential combinatorial ICB treatment biomarker and\nis closely associated with CTL cytolytic activity.” As the analysis does not include direct\nICB data, the conclusion that GBP2 is an ICB biomarker is not well-supported. The\nauthors need to either incorporate ICB-specific data or rephrase the claim to reflect\nonly the observed association with cytolytic activity.\nResponse:\nWe sincerely appreciate the reviewer’s constructive critique and acknowledge the\nneed to revise our initial interpretation. We apologize for the overstatement in the first\nsection. As noted, the data presented there demonstrated only a correlation between\nGBP2 expression and cytolytic activity, whereas our subsequent analysis of immune\ncheckpoint blockade (ICB)-specific datasets in Fig. 7 more directly established an\nassociation between GBP2 and ICB response.\nMoreover, Reviewer #2 considered that whether GBP2 is a prognostic or\npredictive biomarker. Our Univariate Cox regression analysis identified GBP2 as the\nmost significant prognostic factor in SKCM. This finding was further validated across\nmultiple independent melanoma cohorts, where elevated GBP2 expression\nconsistently correlated with improved overall survival (Fig. 1F, S2A-D, Fig. 7E).\nAccordingly, we have revised the conclusion in the first section to reflect the data\nmore accurately: “Together, these bioinformatic findings in clinical samples identify\nGBP2 as a potential prognostic biomarker and reveal its close association with CTL\ncytolytic activity in melanoma.” in the revised manuscript, page 18 line 383-384.\n10. It is unclear whether the clinical datasets analyzed in Figure 7 were obtained from\npatients before or after ICB treatment. The authors should specify the timing of these\ndatasets to accurately interpret the correlation between GBP2 expression and ICB\nResponse:\nWe thank the reviewer’s pertinent comment. Upon thorough re-examination of Figure\n7 datasets, the PRJEB23709 cohort comprises biopsies categorized as pre-treatment\n(PRE) and early during treatment (EDT) in ICB therapy. PRE biopsies (n=73) taken\nprior to immunotherapy, and EDT samples (n=18), taken 7-14 days following the\ncommencement of immunotherapy (Cancer Cell. 2019 Feb 11;35(2):238-255.e6).\nDetailed clinical metadata are now provided in Supplementary Table S9.\nWe reanalyzed and observed the significant therapeutic advantages and clinical\nresponse to ICB immunotherapy in patients with higher GBP2 expression compared\nto those with lower GBP2 expression in PRE samples (Fig. 7C). Conversely, high-\nSLC7A11 group showed a higher proportion of ICB resistance in PRE samples (Fig.\nS13A). We also stratified PRE samples from PRJEB23709 according to GBP2 and\nSLC7A11 expression into three groups (group 1: high GBP2/low SLC7A11; group 2:\nlow GBP2/low SLC7A11 or high GBP2/high SLC7A11; and group 3: low GBP2/low\nSLC7A11). The highest percentage of CR/PR were found in group 3, while lowest\npercentage of CR/PR were found in group 1 (Fig. 7D). Due to limited sample size\n(n=18), we performed direct comparison of GBP2 expression between\nresponders/non-responders. Consistent with PRE data, responders exhibited\nelevated GBP2 levels (Fig. S13B). In addition, the ICB response of figure 7A-B was\ncomputationally predicted (bioinformatics pipeline) as raw clinical annotations were\nunavailable. And the Figure 7G (from an HCC cohort) lacks information before/after\nICB treatment (J Hepatol. 2023 Apr;78(4):770-782).\nAccording to the reviewer’s suggestion, we added the new data in the revised\nmanuscript, page 28-29 line 629-639 and Fig. 7C-D and Fig. S13A-B.\nPart new figures are shown below.\nFig. 7: (C) The proportion of pre-treatment (PRE) patients with response to anti-PD-1 (left)\nor anti-PD-1 + anti-CTLA4 blockade immunotherapy (right) in high or low GBP2 expression\ngroups. SD, stable disease; PD, progressive disease; CR, complete response; PR, partial\nresponse. (D) Pre-treatment (PRE) patients were divided into group 1 (low SLC7A11/high\nGBP2), group 2 (low SLC7A11/low GBP2 or high SLC7A11/high GBP2) and group 3 (high\nSLC7A11/low GBP2). The proportion of patients with response to anti-PD-1 (left) or anti-PD-\n1 + anti-CTLA4 blockade immunotherapy (right) was shown between groups.\nFig. S13: (A) The proportion of pre-treatment (PRE) patients with response to anti-PD-1 (left)\nor anti-PD-1 + anti-CTLA4 blockade immunotherapy (right) in high or low SLC7A11 expression\ngroups. SD, stable disease; PD, progressive disease; CR, complete response; PR, partial\nresponse. (B) Box plots showing expression of GBP2 (left) and SLC7A11 (right) between\nCR/PR and PD/SD group in early during treatment (EDT) patients.\nMinor Comments:\n1. The manuscript currently equates phase separation with biomolecular condensates\nby stating, “Phase separation, also known as biomolecular condensates…”.\nHowever, phase separation is the process that gives rise to condensates; it is not\nsynonymous with the condensate itself. The authors should revise this terminology to\naccurately reflect that phase separation underlies the formation of biomolecular\ncondensates.\nResponse:\nWe sincerely apologize for the terminological conflation between phase separation\nand biomolecular condensates. Following the reviewer's guidance and consistent with\ncurrent literature (Nat Cancer. 2023 Mar;4(3):382-400; Nat Cell Biol. 2024\nJan;26(1):86-99), we revised the description to ' Emerging evidence suggests that\nmany molecular assemblies form membraneless biomolecular condensates via phase\nseparation.' in the revised manuscript, page 3 line 66-67.\n2. The manuscript lacks validation data for the Cas9 knockout experiments (e.g.,\nconfirming homozygous versus heterozygous knockout). Similarly, for the generation\nof mCherry-tagged GBP2 cells, it is unclear whether the knock-in is heterozygous or\nhomozygous. Please provide genotyping data or additional validation to confirm the\nzygosity of these genetic modifications.\nResponse:\nTo address the reviewer’s concerns regarding the validation of Cas9 knockout\nexperiments and mCherry-tagged GBP2 knock-in cells, we performed genotyping to\nconfirm the zygosity of these genetic modifications. For both the Cas9-mediated\nknockout and the mCherry-GBP2 knock-in, we designed specific primers targeting the\nmodified loci and conducted PCR followed by agarose gel electrophoresis. The\nresulting DNA gel analysis clearly demonstrated distinct band patterns consistent with\nhomozygous modifications for both the knockout and knock-in cell lines, with no\nevidence of heterozygous or wild-type alleles. These genotyping results confirm that\nthe Cas9 knockout and mCherry-GBP2 knock-in are homozygous.\nIn response to reviewers' comments and considering space constraints and overall\nmanuscript flow, new figures are shown below.\nFigures for reviewer only: (A-C) Schematic of mCherry knock-in strategy for the GBP2 exon\nregion. Product size validation by 1.5% agarose gel electrophoresis. (D-E) CRISPR/Cas9-\nmediated knockout strategy targeting the GBP2 exon region. Validation of deletion fragment\nsizes by 1.5% agarose gel electrophoresis.\n3. While immunostaining data are shown in Figure 2h, similar data for Figures 2f and\n2g are lacking.\nResponse:\nFollowing the reviewer’s advice, we repeated the immunofluorescence experiment for\nFig. 2F and Fig. 2G. According to the reviewer’s suggestion, we added the new data\nin the revised manuscript, page 19 line 415-417and Fig. S6F-G.\nPart new figures are shown below.\nFig. S6: (F-G) Representative images of lipid ROS in B16-OVA tumours in mice treated with\nanti-PD-L1 or OT-1.\n4. Some representative images are problematic. For instance, in Figure 2H, certain\ncells appear to be undergoing mitosis, and adjustments in image contrast (e.g., in\nFigure 5E) may lead to misinterpretation, such as displaying an abnormally large\ncondensate that might be due to overexpression artifacts rather than physiological\nconditions.\nResponse:\nWe sincerely apologize for the suboptimal image selection in the original submission.\nAs the reviewer's suggestion, regarding Figure 2H, we have repeated the experiments\nfor Fig. 2H and Fig. 5E and selected new representative images that more accurately\nreflect our findings.\nAccording to the reviewer’s suggestion, we added the new data in the revised\nmanuscript (page 19 line 418-419; page 24 line 538-540 and Fig. 2I and Fig. 5D).\nPart new figures are shown below.\nFig. 2I: Representative images of lipid ROS in Vector (Vec) or GBP2-overexpressing\n(GBP2oe) B16-OVA tumor cell co-cultured with activated OT-1 (B16-OVA: OT-1 ratio of 5:1)\nfor 24 hours followed by treatment with ferrostatin-1 (Fer1; 10 μM) for an additional 24 hours.\nFig. 5D: Representative images from live B16-OVA cells expressing GBP2-mCherry\nstimulated with 10 ng/ml IFN-γ for 6 hours, and transfected with SHP1-mEGFP plasmid for 36\nhours. The line plots show GBP2-mCherry and SHP1-mEGFP colocalization of areas.\n5. The figure legend for Figure 6H is absent and should be provided.\nResponse:\nWe are very sorry for the missing legend, and we have carefully checked and modified\nall the legends. According to the reviewer’s suggestion, we revised the figure legend\nof figure 6 in the manuscript-R1, page 44-45 line 1084-1099.\n6. For analyses based on published datasets, the manuscript should clearly indicate\nthe origin of the data and include appropriate citations in the main text or figure legends.\nResponse:\nFollowing the reviewer’s advice, we re-adjusted the supplementary methods section\nto the main manuscript to facilitate direct referencing. All methodological descriptions\nare now appropriately cited throughout the text in the manuscript-R1, page 13-15 line\n277-332. Meanwhile, we consolidated all referenced datasets into Tables S5 and\nTables S9 for reviewing.\nReviewer #4\nThe authors investigated the role of guanylate binding protein 2 (GBP2) in the efficacy\nof immune checkpoint blockade (ICB) and its underlying mechanisms in melanoma.\nThey discovered that GBP2 can undergo phase separation through its intrinsically\ndisordered region (IDR), which promotes STAT1 phosphorylation and inhibits\nSLC7A11 expression, ultimately leading to tumor ferroptosis. This work is conceptually\nintriguing, and the data largely support the authors' main claims. However, the quality\nof the manuscript could be enhanced by addressing the following points:\nA. To better understand the immune-unrelated role of GBP2, it is recommended to test\nthis in at least one in vivo model, such as an immune-deficient model.\nResponse:\nFollowing the reviewer’s advice, we evaluated the effect of GBP2 on tumor growth in\nimmunodeficient NSG mice. Following Ishizuka et al.'s methodology (Nature. 2019\nJan;565(7737):43-48), we established subcutaneous tumor models using B16-OVA\nsgCtrl and sgGBP2 cells. The results showed that comparable tumor growth between\nsgCtrl and sgGBP2 groups (Fig. S5C).\nAccording to the reviewer’s suggestion, we added the new data in the revised\nmanuscript, page 18 line 389-393 and Fig. S5C.\nPart new figures are shown below.\nFig. S5C: Tumor volume of sgCtrl, or GBP2-/- B16-OVA tumors in NSG mice.\nB. While the mechanistic connection between GBP2, SHP1, and pSTAT1 has been\nthoroughly examined in vitro, it has not yet been evaluated in vivo. Given the novelty\nof this aspect, including in vivo studies is essential.\nResponse:\nTo determine whether GBP2 phase separation is essential for ICB efficacy, we\nestablished tumor-bearing mouse models with GBP2ΔIDR + anti-PD-L1 treatment as\nsuggested. As suggested, the results showed that under anti–PD-L1 treatment,\ntumors expressing GBP2-ΔIDR exhibited a marked reduction in therapeutic response\ncompared to the GBP2-FL group, as well as diminished ROS production (Fig. 5K-L).\nCo-immunoprecipitation from PD-L1-treated tumors revealed enhanced STAT1-SHP1\nbinding and decreased STAT1 phosphorylation in GBP2-ΔIDR tumors (Fig. 5M).\nFurthermore, it was reported that in vivo phase separation could observe aggregation\nfoci under immunofluorescence (Cell. 2021 Oct 28;184(22):5559-5576.e19). We\nperformed immunofluorescence staining on the aforementioned tumor specimens to\nvisualize this phenomenon. Critically, distinct GBP2 aggregate foci were readily\ndetectable in GBP2-FL tumors following anti-PD-L1 treatment, whereas such\nstructures were absent in GBP2-ΔIDR tumors (Fig. 5N). According to the reviewer’s\nsuggestion, we added the new data in the revised manuscript, page 26 line 564-572\nand Fig. 5K-N.\nPart new figures are shown below.\nFig. 5: (K) 1 × 106 GBP2-/- B16-OVA cells expressing GBP2-FL and GBP2 △IDR were\nsubcutaneously injected into C57BL/6 mice. (left) Mice with a tumor size of 125 mm3 were\ntreated with anti–PD-L1 antibody or IgG once per 3 days. FL, full length. (right) Tumor\ninhibition rate for GBP2 △IDR under anti-PD-L1 treatment, respectively (n = 6). (L) Relative\nlipid ROS of GBP2-FL or GBP2 △IDR tumours in mice treated with anti-PD-L1 were quantified\nin CD45− cells by flow cytometric analysis. (M) The GBP2-FL and GBP2 △IDR tumours were\nused for in vivo immunoprecipitation with anti-SHP1 antibody and analyzed by western blot\nwith the indicated antibodies. (N) Representative images of GBP2 of immunofluorescent\nstaining in GBP2-FL or GBP2 △IDR tumours under anti-PD-L1 treatment.\nC. The data regarding HMGB1 and its participation in GBP-mediated tumor immunity\nare weak and somewhat tangential to the central message of the work. Omitting this\nsection would sharpen the focus of the manuscript without compromising its\nsignificance.\nResponse:\nWe appreciate reviewer’s assessment that the data linking HMGB1 to GBP2-mediated\ntumor immunity may be redundant, along with the recommendation to deemphasize\nthis aspect. In line with our proposed mechanism—namely, that GBP2 enhances\nimmune checkpoint blockade (ICB) efficacy by promoting immunogenic ferroptosis—\nHMGB1 was used as an auxiliary indicator of immunogenic cell death.\nIn addition, Reviewer #2 also considered that HMGB1 is not particularly specific\nfor ferroptotic death. We acknowledge that HMGB1 release is not exclusively specific\nto ferroptosis. As a prototypical damage-associated molecular pattern (DAMP),\nHMGB1 is known to translocate and be released in response to elevated levels of\nreactive oxygen species (ROS). During ferroptosis, HMGB1 is frequently secreted and\nserves as an immunogenic signal, contributing to the activation and recruitment of\nCD8⁺ T cells.\nTherefore, we have relocated all HMGB1-related data to the Supplementary\nMaterials, in alignment with the feedback from both reviewers.\nAccording to the reviewer’s suggestion, we added the new data in the revised\nmanuscript, page 27-28 line 608-618 and Fig. S11.\nPart new figures are shown below.\nFig. S11: (A) The level of HMGB1 was assessed between sgCtrl and GBP2-/- tumours under\nanti-PD-L1 and OT-1 treatment through ELISA. (B) Dendritic cells were isolated by positive\nselection from tumor tissues (sgCtrl + OT-1 or GBP2-/-+ OT-1) using magnetic-activated cell\nsorting and total RNA was extracted from these cells. CD80 and CD86 were analyzed by\nqPCR. (C) Violin plot of CD86 expression in GBP2 lowest and GBP2 highest patients based\non the GSE115978 dataset. (D) The level of HMGB1 was assessed between sgCtrl and\nSTAT1-/- tumours under OT-1 treatment through ELISA. (E) The level of HMGB1 was\nassessed between Vec, oeGBP2 and oeGBP2 + oeSLC7A11 tumours under anti-PD-L1\ntreatment through ELISA. (F) Western blot showed the transfection efficiency of sgHMGB1 in\nGBP2oe B16-OVA cells. (G) GBP2 vector, GBP2oe and GBP2oe + HMGB1-/- B16-OVA (1 × 106)\ncells subcutaneously injected into C57BL/6 mice. Mice were adoptively transferred with OT-1\ncells (5 × 106 per mouse) or PBS once per 7 days. Tumor growth curves were monitored. (H)\nThe quantitative percentage of CD45+CD8+OT-1 cells between Vec and HMGB1 knockout\ntumors were shown. (I) Dendritic cells were isolated by positive selection from GBP2oe tumor\ntissues (sgCtrl + OT-1 or HMGB1-/-+ OT-1) using magnetic-activated cell sorting and total RNA\nwas extracted from these cells. CD80 and CD86 were analyzed by qPCR.\nD. The immunohistochemistry (IHC) data for SLC7A11 and GBP2 (Figures 3 and 7)\nshould be re-evaluated concerning the specificity of antibodies, cell types, and\nlocalization.\nResponse:\nWe thank the reviewer’s pertinent comment. To further validate antibody specificity\nand cellular localization, we substituted the originally used antibodies against GBP2\nand SLC7A11 with: GBP2 (Proteintech, 27299-1-AP) and SLC7A11 (Abcam,\nab307601). The results showed that immunostaining confirmed predominant\ncytoplasmic localization of GBP2 in melanoma cells, whereas SLC7A11 exhibited\ndistinct membrane-associated expression.\nAccording to the reviewer’s suggestion, we added the new data in the revised\nmanuscript (Fig. 3B and Fig. 7I).\nPart new figures are shown below.\nFig. 7I: The representative images of GBP2, SLC7A11 immunohistochemical staining from\nmelanoma patients (n = 12).\nFig. 3B: The representative images of GBP2, SLC7A11 in situ immunofluorescent staining\nfrom melanoma patients (n = 3).\nE. The discussion could benefit from including the selectivity and involvement of other\nGBP family members in ICB.\nBy addressing these points, the authors could significantly enhance the clarity and\nimpact of their findings.\nResponse:\nWe thank the reviewer’s pertinent comment. Our literature review reveals that\nresearch on GBP family members beyond GBP2 in immune checkpoint blockade (ICB)\nremains limited, with current evidence predominantly derived from bioinformatic\nanalyses of clinical databases. For example, GBP5 expression is a potential biomarker\nfor predicting the outcomes of ICB treatment in patients with non-small cell lung cancer\n(NSCLS) and melanoma (Int J Gen Med. 2023 May 10:16:1757-1769; Clin Immunol.\ninvolvement in immunotherapeutic efficacy across malignancies.\nImmunohistochemical validation confirming GBP6 expression elevation in responsive\nSCLC patients (J Inflamm Res. 2023 Sep 20:16:4153-4164). Pancreatic cancer\norganoids with high GBP4 expression exhibit enhanced sensitivity to PD-1 blockade,\ncorrelating with increased IFN-γ⁺CD8⁺ T cell infiltration and tumor cell death (Cancer\nImmunol Immunother. 2024 Aug 7;73(10):208). An exploratory analysis of\nneoadjuvant PD-L1 inhibition with chemotherapy in early triple-negative breast cancer\nidentified GBP1 among seven genes differentially upregulated in durvalumab\nresponders compared to the placebo (Clin Cancer Res. 2021 May 1;27(9):2584-2591).\nCollectively, these findings underscore the GBP family's potential as key\nimmunotherapeutic regulators. Li et al. further demonstrated that IFN-γ-inducible\nlncRNA LIMIT cis-activates GBP clusters, thereby amplifying tumor immunogenicity\nand potentiating checkpoint therapy efficacy (Nat Cell Biol. 2021 May;23(5):526-537).\nAccording to the reviewer’s suggestion, we added the new description about other\nGBP family members in the Discussion section in the revised manuscript, page 31 line\n678-686.\nReviewer #5\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports.\nThis is part of the Nature Communications initiative to facilitate training in peer review\nand to provide appropriate recognition for Early Career Researchers who co-review\nmanuscripts.\nResponse:\nWe express our sincere gratitude to the reviewer for the time and expertise in\nevaluating our work. These perceptive critiques have prompted essential\nimprovements to this study.\nRESPONSES TO REVIEWERS\nReviewer #3\nThe authors have added new experiments that address a substantial portion of the\nearlier concerns. However, several issues remain unresolved:\n1. Related to raw Western blot images in Fig. S5A\nWhile the newly provided figure does not show the problem noted previously, the\nauthors have not adequately explained why the issue existed in the original figure. To\nensure transparency, the authors should submit all uncropped raw Western blot\nimages, including both the old and new data.\nResponse:\nWe appreciate the reviewer’s comment. We submitted all uncropped raw WB images\n(both the old and new data) in the source data.\n2. Regarding the role of GBP2, whether it is a general T-cell cytotoxicity versus ICB-\nspecific function\nThe response did not directly address whether GBP2 functions as a general mediator\nof T-cell cytotoxicity or has an ICB-specific role. Based on both the new and prior data,\nit seems more consistent with GBP2 being a general mediator of T-cell cytotoxicity.\nIf this is the case, the authors should describe their results more clearly to avoid\nmisleading readers into thinking that GBP2 has an ICB-specific function.\nResponse:\nWe appreciate the reviewer’s comment. We thank the reviewer for this critical insight.\nWe agree that our data support the conclusion that GBP2 acts primarily as a general\nmediator of T-cell cytotoxicity, rather than possessing a function exclusive to Immune\nCheckpoint Blockade (ICB). We have therefore revised the manuscript text throughout,\nparticularly in the Results and Discussion sections (Page 8, lines 172-177 and Page\n23, lines 505-514), to avoid any unintended implication of ICB-specificity and to clearly\nframe GBP2's role as a general amplifier of T-cell mediated anti-tumor immunity. Once\nagain, we are grateful to the reviewer for prompting this important clarification, which\nhas undoubtedly strengthened the precision and impact of our manuscript.\n3. The relation between GBP2 and ferroptosis in Fig. 2E:\nThe mechanism by which GBP2 regulates ferroptosis remains unclear. In the newly\nprovided Fig. 2E, the concentrations of each inhibitor are not indicated. It is critical to\nclarify whether the concentrations used were appropriate. For example, the reported\nIC50 of ferrostatin-1 is approximately 60 - 90 nM based on prior literature and vendor\ninformation, whereas the authors used 10 µM, nearly 50 - 100 times higher. It is\ntherefore unclear whether the differences observed in Fig. 2E are due to the biological\npathways or to overdosing with inhibitors at different levels. The authors should clarify\nthe rationale for the chosen concentrations.\nResponse:\nWe thank the reviewer for this astute observation and for highlighting the need to\nclarify this critical methodological detail. We agree that justifying the concentration of\ninhibitors is essential for interpreting the results correctly. The reviewer is correct that\nthe reported IC50 for Ferrostatin-1 is in the nanomolar range for some specific models.\nAs suggested by the reviewer, we provided the concentrations of each inhibitor in the\nfigure legend: “pan-caspase inhibitor emricasan (20μM), ferroptosis inhibitor\nferrostatin-1 (Fer-1, 10μM), necroptosis inhibitor necrostatin-1 (Nec-1, 20μM) or\nGSDMD- mediated pyroptosis inhibitor disulfiram (20μM)”.\nIn this study, the concentrations of each inhibitor were chosen to align with the\nmethodological standards set by prior literature, ensuring robust inhibition of cell death.\nThis decision is supported by its application in relevant cancer biology models: Yuan\net al. (Nature. 2025 Apr;640(8060):1062-1071) selected pan-caspase inhibitor\nemricasan (20μM), ferroptosis inhibitor ferrostatin-1 (Fer-1, 10μM), necroptosis\ninhibitor necrostatin-1 (Nec-1, 20μM) or GSDMD- mediated pyroptosis inhibitor\ndisulfiram (20μM) to perform cell death inhibition assays; Wang et al. (Nature. 2019\nMay;569(7755):270-274) used 10 µM in a B16-OVA/OT-I co-culture system. Similar,\nLiao et al. and Lang et al. (Cancer Cell. 2022 Apr 11;40(4):365-378.e6; Cancer Discov.\nµM with demonstrated efficacy. Therefore, our use of concentrations are firmly\nsupported by precedent and is appropriate for our experimental context.\n4. SHP1 Western blot in the original Fig. 5D, now Fig. 5C:\nThe blot shows a complete absence of SHP1 signal, resembling a knockout rather\nthan a transient knockdown/reduction. Considering the expected transfection\nefficiency, it is unclear how transient transfection could fully eliminate SHP1 protein.\nThe authors should provide uncropped original blots corresponding to the original Fig.\n5D and the new Fig. 5C.\nResponse:\nWe thank the reviewer for this critical observation and the opportunity to clarify this\nresult. The reviewer indicated that a complete absence of signal is unusual for a\ntransient knockdown. First, we have consulted other high-quality publications and\nconfirmed that transfection with siRNA can indeed result in the apparent absence of\nbands in Western blot analyses under conditions of highly efficient knockdown (J Clin\nInvest. 2023 Dec 15;133(24):e170753; Methods Mol Biol. 2021:2267:159-163; STAR\nProtoc. 2024 Mar 15;5(1):102867).\nFurthermore, the combination of reduced protein expression from gene knockdown,\nlimited sample loading, and short exposure times may have resulted in the residual\ntarget protein signals falling below the detection threshold in some blots (N Am J Med\nSci. 2012 Sep;4(9):429-34; Methods Mol Biol. 2015:1312:17-30).\nFinally, we have already provided the full uncropped original Western blot\nmembranes corresponding to the original Fig. 5D (now Fig. 5C) in the source data.\nMinor points:\n1. In Fig. 2M, the figure legend is unclear. It is not obvious which groups received anti–\nPD-L1 antibody.\nResponse:\nWe revised the figure legend of Fig. 2M in the manuscript-R2.\n2. In Fig. 3A, the authors state that quantification is provided, but no quantification\nresults with error bars are provided.\nResponse:\nWe sincerely thank the reviewer for highlighting this oversight. In response, we have\nnow included the quantification with error bars for Figure 3A as suggested. Due to\nspace limitations in the main text, the quantified results, expressed as mean ± SD from\nthree independent experiments, are provided below. The results clearly show that\ncompared with sgCtrl cells, sgGBP2 cells displayed a marked attenuation of IFN-γ-\ninduced downregulation of SLC7A11.\nFigure for reviewer only: (A, C) The western blot images from the experiment shown in\nFigure 3A in the manuscript. (B, D) Western blot results from two additional independent\nexperiments (left panels) and the corresponding quantitative data from all three replicates\n(right panels, mean ± SD).\n3. In the siRNA dose–response experiment, the x-axis units, e.g. nM, uM are not\nlabeled.\nResponse:\nWe labeled the x-axis unit of nM in the revised figure shown below.\nFigure for reviewer only: (A-B) Real-time PCR used to analyze the mRNA expression levels\nof SHP1 in B16-OVA and A375 cells transfected with siCtrl and different concentrations of\nhuman and murine si-SHP1 (si-#1, si-#2). (C) Real-time PCR used to analyze the mRNA\nexpression levels of SLC7A11 in B16-OVA cells transfected with siCtrl and different\nconcentrations of SLC7A11 siRNA (si-#1, si-#2)."}]

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