TET1 as a master regulator controlling GPX4-dependent and -independent ferroptosis surveillance in acute myeloid leukemia

Domain: chemistry
Published: 2026-01-20
Editorial outcome: major_revision

Abstract
Ferroptosis, an iron-dependent, lipid peroxidation-driven programmed cell death, holds substantial promise for cancer therapy, yet its translational potential is hindered by widespread intrinsic resistance. While glutathione peroxidase 4 (GPX4) is a well-established ferroptosis suppressor, the epigenetic circuitry coordinating GPX4-related mechanisms remains elusive. Here, via genome-wide screening, we identify ten-eleven translocation 1 (TET1)—a key mediator of DNA 5-hydroxymethylation—as a master controller of cancer cell ferroptosis susceptibility. In acute myeloid leukemia (AML), TET1 enhances 5hmC deposition at the glutamate-cysteine ligase catalytic subunit (GCLC) promoter to activate glutathione/γ-glutamyl-peptide metabolism, fortifying GPX4-dependent defense. Concurrently, TET1 activates NFκB signaling to upregulate GTP cyclohydrolase-1 (GCH1), conferring GPX4-independent ferroptosis resistance. Critically, co-targeting TET1/GCLC/GCH1 with low-dose ferroptosis inducers exhibit potent therapeutic effects against both ferroptosis-sensitive and -resistant AML. Our work positions TET1 as a pivotal epigenetic hub governing ferroptosis surveillance, and provides a translatable strategy to overcome ferroptosis resistance in cancer, with AML as a paradigm.

Introduction
Ferroptosis, a non-apoptotic form of programmed cell death driven by iron-dependent lipid peroxidation, is closely associated with cancer. Dysregulation of ferroptosis-related pathways, including the System Xc--GPX4 axis, iron metabolism, and lipid peroxidation, contributes to cancer progression and offers optional therapeutic vulnerabilities for aggressive malignancies1. However, cancer cells exhibit heterogeneous susceptibility to ferroptosis2,3. Although ferroptosis induction has emerged as a promising approach to treat responsive cancers (e.g., originally, RAS-mutated cancer cells), ferroptotic resistance of irresponsive cancer cells (e.g., some breast and colon tumors) restricts its clinical applicability4–8. Therefore, it is important to identify the key mechanism that determines the disparity of cancer cell vulnerability to ferroptosis.

Cancer cells rely on sophisticated surveillance mechanisms to maintain cellular homeostasis and evade ferroptosis. One of the major ferroptosis surveillance mechanisms is mediated by glutathione peroxidase 4 (GPX4)—the sole enzyme in mammalian that reduces phospholipid peroxides to corresponding alcohols9,10. Its upstream cystine imports and glutathione (GSH) synthesis form the primary step to suppress ferroptosis. GSH, whose synthesis is initiated by the glutamate-cysteine ligase (GCL) complex via the ligation of cysteine with glutamate, is utilized by GPX4 as an essential cofactor to detoxify lipid peroxidation. Intriguingly, under cystine-deprived conditions, the GCL complex catalyzes γ-glutamyl-peptides accumulation instead11. Despite these insights, the genetic and epigenetic regulation of GSH and γ-glutamyl-peptides biosynthesis, and more importantly, the precise activation mechanisms of ferroptosis defense systems remain unclear12.

Emerging evidence reveals that mammalian cells employ distinct mechanisms to combat oxidative damage13. Such GPX4-independent surveillance pathways are often mediated by enzymes that generate metabolites with radical-trapping antioxidant (RTA) activity, including ferroptosis suppressor protein 1 (FSP1), dihydroorotate dehydrogenase (DHODH), and GTP cyclohydrolase-1 (GCH1), etc10,14–16. Each of these systems operates as an independent, parallel defense mechanism. Up till now, only a handful of regulators have been identified as critical modulators of multiple surveillance pathways17,18. Therefore, a deeper understanding of the crosstalk between GPX4-dependent and -independent ferroptosis surveillance systems is essential. Identifying master regulators that orchestrate these pathways could uncover therapeutic targets for ferroptosis induction in cancer treatment.

DNA methylation is an epigenetic mechanism essential for the regulation of gene expression, and the demethylation process can be catalyzed by ten-eleven translocation (TET) dioxygenases. TETs, comprising TET1, TET2, and TET3, catalyze the oxidative conversion of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC), and 5-carboxycytosine (5caC) in an Fe (II)/a-ketoglutarate-dependent manner. While 5mC generally promotes gene silencing, 5hmC is often associated with active demethylation and can serve as a distinct epigenetic mark that influences gene activation19–22. Accumulating evidence underscores the critical involvement of TET proteins in diverse biological processes, including regulation of gene expression, cell growth, differentiation and death23,24. TET1, the founding member of TET family, has been identified as an oncogene in multiple cancers19,21,25–27. Our recent study revealed that Tet1 deficiency disrupted cellular responses to iron overload28. Despite these advances, the role of TET-mediated DNA modification in ferroptosis remains poorly understood.

Here, we show the role and regulatory mechanism of TET1 in determining cancer cells vulnerability to ferroptosis. Higher expression of TET1 was found in ferroptosis-resistant cancer cells than in sensitive cells. Strikingly, the ferroptosis surveillance function of TET1 is partially independent of GPX4. On one hand, TET1 epigenetically modulated its target gene, the glutamate-cysteine ligase catalytic subunit (GCLC), which encodes the key enzyme catalyzing the initiation of GSH synthesis, activated GSH synthesis, and γ-glutamyl-peptide accumulation; on the other hand, TET1 activated NFκB signaling, promoted GCH1 transcription, and thus, induced ferroptosis resistance in a GPX4-independent manner. Moreover, using acute myeloid leukemia (AML), the most common acute hematopoietic malignancy in adults, as a study paradigm, we demonstrate the anti-cancer therapeutic potential of the combinational administration of ferroptosis inducer, TET inhibitor, GCH1 inhibitor, and/or GSH synthesis inhibitor. Collectively, our findings demonstrate the pivotal role of TET1 in controlling cancer cell susceptibility to ferroptosis, with particular significance in AML. TET1 orchestrates this process through both GPX4-dependent and -independent mechanisms. These results highlight the therapeutic potential of targeting TET1-mediated ferroptosis surveillance pathways for the treatment of AML and other malignancies that employ similar protective systems.

Results
TET1 induces ferroptosis resistance in cancer cells
Cancer cell vulnerability to ferroptosis was investigated in a 33-sample cohort, encompassing both solid tumors (i.e., HT1080, HLF, 786-O, HCC827, H292, MIAPaCa-2, ASPC-1, HepG2, B16-F10, A375, A549, PaTu 8988t, and ACHN) and hematopoietic malignancies. The latter included 9 primary AML samples (i.e., AML1-9), established myeloid leukemia cell lines MOLM13, HL60, MV4;11, U937, THP1, NB4, Kasumi-1 and K562, and lymphoblastic cell lines Daudi, Jurkat and CA46. Notable heterogeneity was observed in cellular responses to the GPX4-targeting ferroptotic inducers RSL39 and ML2109,29,30 (Supplementary Fig. 1a, b). The viability and growth inhibitory effect of the two ferroptotic inducers was more dramatic (IC50 <500 nM) in Daudi, MOLM13, HL60, MV4;11, Jurkat, THP1, etc., i.e., ferroptotic sensitive cells, than in A549, Kasumi-1, K562, A375, etc., i.e., ferroptotic resistant cells (IC50 ≥500 nM) (Supplementary Fig. 1a–d and Supplementary Table 1). RSL3 treatment increased cellular levels of liable iron, particularly Fe2+ (Supplementary Fig. 1e), consistence with previous reports31,32.

Analysis of gene expression patterns of ferroptosis-sensitive and -resistant AML cells showed that the expression levels of 1516 genes were significantly higher in ferroptosis-resistant cells than in sensitive cells (Fig. 1a). Gene-set enrichment analysis (GSEA) revealed 20 gene sets associated with RSL3 sensitivity, among which the chromatin assembly or disassembly pathway was the top 1 gene cluster enriched in RSL3 resistant cells (Supplementary Fig. 1f, g). TET1 was one of the top up-regulated genes of the above cluster (Fig. 1b). Despite of TET1’s DNA hydroxymethylation activity and its oncogenic role in MLL-rearranged AML19,27, little is known about its role in ferroptosis28. Notably, we show positive correlation between TET1 expression and RSL3 or ML210 sensitivity in the 33-sample cohort with Q-RT-PCR (Fig. 1c and Supplementary Fig. 1h). The correlation pattern between TET1 expression and RSL3 sensitivity was further confirmed with Western blot (Supplementary Fig. 1i). Since TETs are Fe2+ and O2-dependent dioxygenases33, we tested the relationship between the redox state and TET1 activity. RSL3 treatment showed no obvious influence on TET1 expression or global DNA 5hmC level (Supplementary Fig. 2a, b), indicating the aforementioned correlation between TET1 expression and ferroptosis susceptibility was unlikely determined by cellular oxidation status.

To investigate the role of TET1 in ferroptosis, we first interfered the expression of TET1 in cancer cells. Knockdown of endogenous TET1 with shRNAs significantly exacerbated the suppression of cell viability induced by RSL3 in both ferroptosis-sensitive (i.e., MV4;11, THP1) and -insensitive (i.e., Kasumi-1, A375) cells (Fig. 1d and Supplementary Fig. 2c–f), and increased RSL3-induced apoptosis (Supplementary Fig. 2f). TET1 knockdown resulted in an increase of lipid peroxidation level, and dramatically aggravated RSL3-induced ROS accumulation (Supplementary Fig. 2g). The above lipid peroxidation accumulation could be reversed by Fer-1 (Supplementary Fig. 2g). Notably, in primary AML cells from AML patients—spanning both ferroptosis-sensitive and -resistant subtypes—TET1 knockdown significantly sensitized cells to ferroptosis, while TET1 overexpression conferred resistance (Supplementary Fig. 2h). For in vivo studies, we utilized two distinct mouse AML bone marrow transplantation (BMT) models. One of these models employed mouse AML cells expressing the MLL-AF9 (MA9) fusion oncogene as donor cells, which recapitulates the monocytic (M5-AML) subtype; and the other model used AML-ETO9a (AE9a)-expressing AML cells, representing the granulocytic (M2b-AML) subtype34,35. Consistent with in vitro results, in vivo studies showed a better effect of RSL3 in prolonging overall survival and restricting AML cell engraftment of recipient mice transplanted with Tet1 deficient MA9-AML cells compared to wild-type (WT) MA9-AML cells (Supplementary Fig. 3a, b). Similarly, ex vivo results showed that MA9 or AE9a AML cells of Tet1−/− mice were more sensitive to RSL3 than AML cells of WT mice, as reflected by both increased apoptosis and reduced viability (Supplementary Fig. 3c–f). RSL3 induced ROS accumulation in AML cells of Tet1−/− mice turned out to be more obvious than WT mice (Fig. 1e, f). In addition, Bobcat339, a selective TET inhibitor with high affinity with TET1 at low doses36, exhibited obvious synergistic effect with RSL3 in suppressing cell viability in various AML and solid tumor cells (Supplementary Fig. 4a), including both ferroptosis-sensitive and -resistant cells. Conversely, TET1 overexpression conferred resistance to RSL3-induced ferroptosis across both hematopoietic and solid tumor cell lines (Supplementary Fig. 4b), and effectively attenuated RSL3-induced apoptosis (Supplementary Fig. 4c–e). Importantly, compensatory changes in TET2 or TET3 expression were undetectable upon TET1 modulation (Supplementary Figs. 2c–f and 4c–e), underscoring the specific role of TET1 in ferroptosis regulation. Collectively, the above findings indicate TET1 as a critical determinant of cancer cells susceptibility to ferroptosis.

TET1 transcriptionally activates GCLC
To elucidate the mechanism by which TET1 regulates ferroptosis surveillance, 5hmC-seq and RNA-seq were conducted. Combinational analysis identified 397 genes with both elevated expression levels and 5hmC levels in TET1-overexpressing THP1 cells compared to controls (Fig. 2a and Supplementary Fig. 5a). KEGG pathway analysis revealed that the cysteine and methionine metabolism pathway was the top 1 enriched gene cluster among the above 397 genes (Fig. 2b). Of note, one of the top contributors to this pathway was GCLC, encoding the speed-limiting enzyme which catalyzes the first step of GSH synthesis37–39 (Fig. 2c). Bioinformatic analysis of clinical datasets demonstrated a strong positive correlation between TET1 and GCLC expression levels in both TCGA (n=150) and GSE30285 (n=93) AML cohorts (Supplementary Fig. 5b), which was further validated in our 33-cancer cell cohort with Q-RT-PCR (Supplementary Fig. 5c). Knockdown of TET1 significantly reduced the expression level of GCLC/GCLC (Fig. 2d), while overexpression of TET1, but not TET1-HxD, the functionally inactivated mutant of TET140, showed the opposite effect (Fig. 2e). Results of 5hmC-seq showed that 5hmC peaks were highly enriched within 3000 bp upstream of the GCLC promoter in TET1 overexpressing cells (Supplementary Fig. 5d). ChIP-seq results suggested the association between TET1 and the promoter region of GCLC (Supplementary Fig. 5e). The binding of full-length TET1 to the GCLC promoter was verified through ChIP-Q-PCR assays (Fig. 2f and Supplementary Fig. 5f). The transcriptional activation of GCLC by full-length TET1 was further verified through luciferase reporter assays (Fig. 2g and Supplementary Fig. 5g). Overexpression of GCLC remarkably reduced RSL3-induced ferroptosis in sensitive MV4;11 cells (Supplementary Fig. 5h, i), while GCLC knockdown increased ferroptosis sensitivity of both resistant Kasumi-1 cells and MV4;11 cells (Supplementary Fig. 5j, k). Overexpression of GCLC significantly reduced lipid peroxidation in MV4;11 cells (Supplementary Fig. 5l), while GCLC knockdown enhanced RSL3-induced lipid peroxidation in Kasumi-1 cells (Supplementary Fig. 5m). Overexpression of GCLC partially salvaged the inhibition on cell viability induced by TET1 knockdown (Fig. 2h). Further, we tested the effect of the GSH synthesis inhibitor buthionine sulfoximine (BSO) in cancer cells. RSL3 and BSO showed a strong synergistic effect in reducing cell viability in both ferroptosis-sensitive and -insensitive cancer cell lines (Supplementary Fig. 6a). Consistently, the combinational treatment with both RSL3 and BSO significantly strengthened the suppression of cell viability induced by either RSL3 or BSO alone in mouse MA9 and AE9a-AML cells, especially in Tet1−/− MA9- and AE9a-AML cells, as compared with RSL3 or BSO alone (Supplementary Fig. 6b, c). In human AML cells, BSO treatment enhanced the ferroptotic sensitization effect of TET1 knockdown and reversed the protective effect of TET1 overexpression against ferroptotic cell death (Supplementary Fig. 6d, e). Consistent pattern was observed in solid tumors (Supplementary Fig. 6f, g). Notably, BSO treatment significantly sensitized AML primary cells to ferroptotic cell death (Supplementary Fig. 6h). It was reported that the transcription of GCLC could be regulated by NFE2L2 41,42. Interestingly, TET1 overexpression could restore GCLC expression in NFE2L2-deficient cells (Supplementary Fig. 6i, j), suggesting the potential crosstalk between of TET1 and the known NFE2L2/GCLC axis. Collectively, our findings identify GCLC as a downstream effector of TET1-mediated DNA hydroxymethylation in ferroptotic resistance and reveal the existence of the TET1/GCLC/GSH regulatory axis in cancer cells.

Role of the TET1/GCLC axis in GSH and γ-glutamyl-peptide synthesis
The GCL complex has dual functions: Under normal conditions with adequate cystine supply, it catalyzes the canonical ligation of cysteine with glutamate and initiates GSH synthesis; conversely, during cystine deprivation, it switches to a non-canonical function by conjugating glutamate with alternative amino acids, thereby conferring ferroptosis resistance through glutamate scavenging11. To comprehensively understand the role of TET1 in this dual-pathway regulation, we systematically investigated its impact on both canonical GSH production and non-canonical γ-glutamyl-peptides accumulation. In primary BM cells obtained from 9 AML patients (designated AML1-9), we observed a positive correlation between TET1 expression levels and intracellular GSH content (Supplementary Fig. 7a). In order to investigate the effect of TET1 on GSH synthesis, we detected cellular GSH levels. We found that TET1 knockdown significantly reduced GSH level, which could be exacerbated by BSO co-treatment (Supplementary Fig. 7b). To the opposite, overexpression of TET1 increased intracellular GSH, which could be reversed by BSO treatment, while TET1-HxD showed no obvious effects (Supplementary Fig. 7c). TET inhibitor Bobcat339 significantly reduced GSH levels (Supplementary Fig. 7d, e). Combined treatment with BSO and Bobcat339 further strengthened GSH reduction (Supplementary Fig. 7d, e). In addition, such combinational treatment also resulted in more dramatic suppression in GSH synthesis induced by the System Xc- inhibitor Erastin (Supplementary Fig. 7f, g). Ex vivo studies validated that in MA9- or AE9a-expressing AML cells of Mx1-Cre+/-Tet1flox/flox mice, induced depletion of Tet1 significantly inhibited GSH synthesis, especially in MA9-AML cells; co-treatment with BSO even more dramatically suppressed GSH synthesis (Supplementary Fig. 7h, i). In NFE2L2 deficient THP1 cells, overexpression of TET1 partially restored GSH level (Supplementary Fig. 7j). The above results indicate the role of TET1 in promoting GSH synthesis.

The non-canonical γ-glutamyl-peptides synthetic pathway, independent of cystine, remains mostly unknown in AML. Through unlabeled metabolomics, which measures the static pool size, and 13C,15N-glutamine tracing analysis, which traces the new incorporations, we found under cystine deprivation condition, GSH synthesis was significantly suppressed (Fig. 3a), and cell viability was remarkably reduced (Supplementary Fig. 7k). Non-targeted metabolomics showed a cluster of metabolites highly accumulated in cystine-starved AML cells, which were recognized as dipeptide γ-glutamyl-glycine (γ-Glu-Gly), γ-glutamyl-threonine (γ-Glu-Thr), and the GSH-similar tripeptide γ-glutamyl-2-aminobutyryl-glycine (γ-Glu-2AB-Gly), etc., according to authentic standards (Supplementary Fig. 7l, m). 13C,15N-glutamine tracing validated a significant increase of γ-Glu-Gly, γ-Glu-Thr, and γ-Glu-2AB-Gly under cystine-starved conditions, approximately 50% of which were freshly derived from glutamate (Fig. 3b). Bobcat339 and/or BSO significantly decreased the levels of the above γ-glutamyl-dipeptides and -tripeptides (Fig. 3c). In Mx1-Cre+/-Tet1flox/flox MA9-AML mouse cells, induced depletion of Tet1 exacerbated the suppression of cell viability resulted from cystine withdrawal, whereas Tet1 overexpression effectively rescued this phenotype (Supplementary Fig. 7n). Meanwhile, Tet1 knockout reduced γ-glutamyl-peptide synthesis induced by cystine deprivation, whereas restore of Tet1 expression in the above cells could reverse such reduction (Supplementary Fig. 7o). The effect of Tet1 on the synthesis of non-canonical γ-glutamyl-peptides was then tested in vivo. The above MA9-AML cells from Mx1-Cre+/-Tet1flox/flox mice were lentivirally transfected with MSCV-PIG (i.e., murine stem cell virus-puromycin IRES GFP) plasmid, and then transplanted into WT recipient mice. In order to deplete cyst(e)ine in the recipients, mice were switched to a cyst(e)ine deprivation diet43 or a control diet after transplantation (Fig. 3d). When the BM engraftment of AML cells in the recipient mice increased to above 90% (i.e., about 22-24 days after BM transplantation) (Supplementary Fig. 7p), the levels of GSH and non-canonical γ-glutamyl-peptides in BM cells were tested. Results show that knockout of Tet1 or BSO treatment significantly reduced GSH synthesis (Fig. 3e, f), and reduced the synthesis of γ-Glu-Gly, γ-Glu-Thr and γ-Glu-2AB-Gly induced by cyst(e)ine deprivation in vivo (Fig. 3g). Together, the above results indicate the pivotal role of TET1/GCL in catalyzing both GSH synthesis and glutamate scavenging (Fig. 3h).

It was recently reported that loss of Tet1 expression resulted in impaired response to iron overload in macrophages28. Here, we detected the level of ferritin, i.e., FTL and FTH, ferrous iron importers, i.e., SLC39A14 (ZIP14), as well as the iron exporter ferroportin-1 (FPN) in Kasumi-1 cells. No significant difference was found in the above protein or gene expression levels between TET1 knockdown and control groups, indicating the role of TET1 in mediating cancer cell ferroptotic resistance is independent of intracellular iron disturbance (Supplementary Fig. 7q, r).

GPX4-independent regulation of TET1 on ferroptosis
Since GCLC overexpression could only partly reversed the ferroptosis sensitization induced by knockdown of TET1 (Fig. 2h), we assumed ferroptosis surveillance systems other than the canonical GPX4/GSH system were likely involved in TET1 mediated ferroptosis resistance. Knockdown of GPX4 enhanced the cell viability inhibition induced by ferroptosis inducers (Supplementary Fig. 8a–c), and reduced TET1 overexpression-induced ferroptosis resistance (Supplementary Fig. 8d). In GPX4-knockdown cells, overexpression of TET1, but not TET1-HxD, exhibited significant rescue effect in cell viability (Supplementary Fig. 8e–i) and ROS elimination (Supplementary Fig. 8j, k), indicating the ferroptosis desensitizing effect of TET1 might not fully rely on GPX4 activity. Further, we established cancer cell lines MV4;11 (i.e., ferroptosis sensitive) and Kasumi-1 (i.e., ferroptosis resistance) with GPX4 gene knockout as spontaneous ferroptosis models44 (Supplementary Fig. 8l, m). These cells underwent ferroptosis with different extents promptly upon removal of antioxidant Trolox from the culture medium (Fig. 4a, b). Exogenous overexpression of GPX4 could reverse this phenomenon (Fig. 4a, b and Supplementary Fig. 8l, m). To our surprise, overexpression of TET1, but not TET1-HxD, enabled the maintenance of GPX4 knockout cells by remarkably restoring the protection against ferroptosis, especially in ferroptosis resistant cells (Fig. 4c, d and Supplementary Fig. 9a). Overexpression of TET1 instead of TET1-HxD could reduce ROS accumulation in GPX4 knockout cells (Fig. 4e, f). Notably, neither TET1 knockdown nor overexpression exerted significant effects on GPX4 enzymatic activity, as evidenced by unaltered NADPH oxidation rates (Supplementary Fig. 9b, c). The above results suggest the potent ferroptosis suppressing activity of TET1 is, at least, partially independent of GPX4 in cancer cells.

To identify the potential ferroptosis defense system in which TET1’s involved, we established cancer cell lines with gene knockout of the major known RTA-generating and other antioxidant enzymes, i.e., GSH S-transferase P1 (GSTP1)45, DHODH14, FSP110,15, and GCH116, and screened the role of TET1 in the above cells (Fig. 4g and Supplementary Fig. 9d). Overexpression of TET1, but not TET1-HxD, inhibited lipid peroxidation induced by RSL3 or Erastin in GSTP1, DHODH, or FSP1 knockout THP1 cells, but had little effect in GCH1 knockout cells (Fig. 4h, i and Supplementary Fig. 9e–g). The protein expression levels of TET1, GCLC, FSP1, and GCH1 in the 33-cancer sample cohort were detected with Western blot. The quantification results revealed a statistically significant positive correlation between TET1 and GCLC protein levels (Pearson r=0.705, P<0.001), and a positive trend was observed between TET1 and GCH1 expression (Pearson r=0.331, P=0.060). Notably, no significant association was detected between TET1 and FSP1 levels (Pearson r=−0.124, P=0.492) (Supplementary Fig. 9h). In summary, TET1 suppresses ferroptosis in a manner independent of the activity of most of the major RTA producing enzymes, except for GCH1, a master regulator of ferroptosis resistance functioning through the GCH1-tetrahydrobiopterin (BH4)-phospholipid axis13,16.

TET1 regulates GCH1 via NFκB signaling
As a recently identified ferroptotic antagonizer, the expressional regulation mechanism of GCH1 remains not fully recognized. The positive correlation between TET1 and GCH1 transcription levels was confirmed in the 33-sample cancer cell cohort with Q-RT-PCR (Supplementary Fig. 10a). However, results of ChIP-Q-PCR analysis showed no obvious association between TET1 and multiple regions of the GCH1 gene locus (Supplementary Fig. 10b). It was reported that activation of NFκB signaling induced the expression of GCH1 at both mRNA and protein levels46,47. As was shown in Fig. 2b, the NFκB signaling pathway was one of the top 10 gene clusters enriched in TET1-overexpressed cells. KEGG analysis revealed NFKB1, NFKB2 and RELB as top candidate genes enriched in the above cluster (Supplementary Fig. 10c). In MV4;11 cells with knockdown of TET1, the expression levels of NFKB1, NFKB2 and RELB were remarkably down-regulated (Supplementary Fig. 10d). Overexpression of TET1, but not TET1-HxD, significantly increased the expression levels of the above genes (Supplementary Fig. 10e). Results of 5hmC-seq showed that 5hmC peaks were highly enriched within 3000 bp upstream of the NFKB2 promoter in TET1-overexpressed cells (Supplementary Fig. 10f). Results of ChIP-Q-PCR analysis verified the association between TET1 and the promoter region of NFKB2 (Fig. 5a). The transcriptional activation of NFKB2 by TET1 was further confirmed with luciferase reporter assays (Fig. 5b). Knockdown of NFKB2 significantly reduced the expression level of GCH1, while overexpression of NFKB2 showed the opposite effect (Fig. 5c, d). The transcriptional activation of GCH1 by NFKB2 was confirmed with luciferase reporter assays as well (Fig. 5e). Knockdown of TET1 significantly reduced the expression level of GCH1, while overexpression of TET1 showed the opposite effect (Fig. 5f, g). Overexpression of GCH1 partly reversed the ferroptosis sensitization induced by TET1 knockdown, and restored lipid peroxidation defense (Fig. 5h, i and Supplementary Fig. 10g). We then treated MV4;11 cells with 2,4-Diamino-6-hydroxypyrimidine (DAHP), a specific inhibitor for GCH148,49. DAHP treatment significantly enhanced the ferroptotic sensitization effect of TET1 knockdown, and partly offset the protective effect of TET1 overexpression against ferroptotic cell death (Supplementary Fig. 10h, i). Combinational administration of DAHP together with RSL3 and/or Bobcat339 showed strong synergistic effect in reducing cell viability in both ferroptosis-sensitive (MV4;11) and -insensitive (Kasumi-1) AML cells (Fig. 5j, k). Ectopic expression of either TET1 or NFKB2 led to a significant elevation of intracellular BH4 levels and a decrease of RSL3-induced ROS accumulation (Supplementary Fig. 10j, k). Conversely, knockdown of TET1 or NFKB2 resulted in a marked reduction of BH4 production and an increase of RSL3-induced ROS accumulation (Supplementary Fig. 10l, m). Our findings establish a previously unidentified regulatory axis wherein both TET1 and NFKB2 critically modulate GCH1 expression and/or function, thereby unveiling the existence of the TET1/NFκB signaling/GCH1 axis in cancer ferroptosis regulation. Intriguingly, we observed a reciprocal regulatory relationship between GCH1 and GPX4: Genetic inhibition of GPX4 triggered compensatory BH4 accumulation through GCH1 activation, while GCH1 ablation conversely enhanced GPX4 activity (Supplementary Fig. 10n, o). This feedback regulation suggests an intricate crosstalk between these two major ferroptosis defense systems, potentially maintaining redox homeostasis in cancer cells under certain conditions. Genetic ablation of GPX4 resulted in a more pronounced suppression in cell viability compared to GCH1 knockout, indicating the predominant role of GPX4 in AML ferroptosis surveillance (Supplementary Fig. 10p). Taken together, we show the pivotal role of TET1 in controlling both GPX4-dependent and -independent ferroptosis surveillance systems through TET1/GCL and TET1/NFκB/GCH1 axis (Fig. 5l).

Therapeutic potential of targeting the TET1/GCL and TET1/GCH1 axis in AML
The therapeutic potential of ferroptosis inducers in cancer remains controversial2,50,51. In both RSL3-insensitive AE9a-AML and RSL3-sensitive MA9-AML, Bobcat339, BSO, and/or DAHP treatment significantly increased the vulnerability of the cells to RSL3 (Supplementary Fig. 11a, b). Particularly, in AE9a-AML, co-treatment with RSL3 and Bobcat339, BSO or DAHP reduced cell viability from 88.68% (RSL3 alone, comparing with DMSO control) to 13.55% (RSL3 + Bobcat339), or 33.03% (RSL3 + BSO), or 28.36% (RSL3 + DAHP), respectively (Supplementary Fig. 11a), suggesting the possibility of restoring ferroptosis sensitivity in resistant cells. Results of colony-forming assays verified the synergistic inhibition of RSL3 and Bobcat339, BSO, or DAHP on AML colony-forming capacity in both AE9a- and MA9-AMLs (Supplementary Fig. 11c, d), indicating the potent effect of the above combinational therapy in restraining AML malignant expansion and progression.

In vivo effects of RSL3 were further examined in the above two murine AML models, i.e., the MA9-AML and the AE9a-AML models (Fig. 6a). In both RSL3-insensitive AE9a-AML and RSL3-sensitive MA9-AML, Bobcat339, BSO or DAHP alone significantly improved the overall survival (Fig. 6b and Supplementary Fig. 11e). Combined administration with RSL3 and Bobcat339, BSO or DAHP further extended the median survival (Fig. 6b and Supplementary Fig. 11e), and significantly suppressed the infiltration of AML cells into BM, peripheral blood, spleen and liver (Fig. 6c and Supplementary Fig. 11f). Of note, for all the in vivo therapeutic studies, RSL3 was given at a much lower dose, i.e., 1 mg/kg, than what was previously reported, e.g., ~100 mg/kg9,52, and the low dosages brought about no obvious short-term or long-term toxicity effects as shown in body weights, spleen and liver weights, white blood cell counts and LT-HSC/ST-HSC populations (Supplementary Fig. 12a–c).

AML is characterized by the self-renewing leukemic initiating cells (LICs)53. Flow cytometry analysis of MA9-AML bearing mice demonstrated that single-agent treatment with either Bobcat339, BSO, or DAHP significantly reduced the LIC-enriched c-kit+-Mac-1+ population. Notably, combination therapy with RSL3 plus Bobcat339, BSO, or DAHP resulted in a more profound decrease of LICs (Supplementary Fig. 13a), suggesting that targeting TET1-dependent ferroptosis surveillance systems may provide superior therapeutic efficacy against LICs.

The therapeutic effect of RSL3 in combination with Bobcat339, BSO, or DAHP for human AML was firstly tested in vitro, in two AML primary samples directly derived from two individual patients, representing RSL3-responsive (i.e., AML3) and -irresponsive (i.e., AML4) AMLs (Supplementary Table 2). Either BSO, Bobcat339, or DAHP alone significantly increased cell susceptibility to RSL3 in both AML3 and AML4 (Supplementary Fig. 14a, b), indicating the therapeutic potential of the combinational administration of RSL3 (ferroptosis inducer) + Bobcat339 (TET inhibitor)/BSO (GCL inhibitor)/DAHP (GCH1 inhibitor) in cancer. Xenograft models were employed to test the therapeutic potential of the above combinational therapies in vivo (Fig. 6d). Primary BM cells from four individual AML patients, including one sensitive (AML3/FLT3-ITD+NPM1mutDNMT3amut) and three RSL3-resistant (i.e., AML4/t(4;11), AML6/FLT3-ITD+NPM1mutIDH1mut and AML7/t(9;11)) patients, were used as donor cells. At 100 days post xeno-BMTs, BM engraftment—defined by the presence of human CD45+ and/or CD33+ populations—as well as the infiltration of AML cells into peripheral blood were more dramatically suppressed in the groups receiving the combined treatment with RSL3 and Bobcat339/BSO/DAHP compared to RSL3 monotherapy (Fig. 6e, f and Supplementary Figs. 14c–e, 15a–c and 16a, b). Moreover, across the four AML patient-derived cell samples isolated from recipient mice, a positive correlation was observed among TET1 expression, GCLC expression, and GSH levels. These parameters were, in turn, negatively correlated with sensitivity to RSL3 (Supplementary Fig. 17a), providing further in vivo validation of our hypothesis regarding the TET1/GCLC/GSH axis. Other xenograft models using AML cell lines MOLM13 and MV4;11 as donor cells showed RSL3 alone significantly extended the survival of recipient mice, and combined treatment with Bobcat339, BSO, or DAHP exhibited even better therapeutic effects (Supplementary Fig. 18a, b). RSL3 combined treatment with Bobcat339, BSO, or DAHP all further reduced the infiltration of AML cells as compared with RSL3 administration alone (Supplementary Fig. 18c, d). Together, we show combinational treatment with the ferroptosis inducer and inhibitor(s) of the TET/GCL or TET/GCH1 axis holds great potential in treating cancers.

Methods
Ethics statement
All mice were maintained and handled under the protocol approved by the Committee on Experimental Animal Care & Ethics of Zhejiang University (Ethics File Approval No.: ZJU20240478). All human samples were maintained and handled under the protocol approved by the Clinical Research Ethics Committee of the First Affiliated Hospital, Zhejiang University School of Medicine (Ethics File Approval No.: 2022-292).

Mice
This study was based on both male and female mice (6–8-weeks-old). Mice were housed and maintained in the specific pathogen-free (SPF) facility of the Laboratory Animal Center of Zhejiang University (Hangzhou, China), under a 12 h’ light/dark cycle at a controlled temperature of 23 ± 2°C, with free access to food and water. C57BL/6 (CD45.2) mice and NOD/ShiLtJGpt-Prkdcem26Cd52Il2rgem26Cd22/Gpt (NSG) mice were purchased from Gempharmatech (Nanjing, China). The mating pair of B6.SJL (CD45.1) mice were donated by Dr. Xing Chang of Westlake University. Mx1-Cre+/-Tet1flox/flox mice were generated from C57BL/6 mice (Gempharmatech, Nanjing, China) and Mx1-Cre+/-Tet1flox/floxTet2flox/flox mating pairs donated by Dr. Jianjun Chen of Beckman Research Institute of City of Hope. All experiments were conducted using randomization, concealed allocation, and blinded outcome assessment.

Leukemic patient samples
Primary AML samples were collected from patients at the time of diagnosis or relapse at the First Affiliated Hospital of Zhejiang University. This study was approved by the institutional review board of the hospital and Zhejiang University School of Medicine. Written informed consent was obtained from all participants prior to sample collection. Detailed clinical characteristics of the AML patients are summarized in Table S2. Bone marrow (BM) mononuclear cells (MNCs) were isolated from the samples by density gradient centrifugation using Ficoll-Paque Premium (GE Healthcare Life Sciences, UK). The isolated MNCs were cryopreserved in liquid nitrogen for subsequent analysis.

Cell lines
THP1 (TIB-202), U937 (CRL-1593.2), and MV4;11 (CRL-9591) cells were obtained from America Type Culture Collection (ATCC) and cultured in RPMI-1640 medium (Gibco, Grand Island, NY, USA), supplemented with 10% FBS (Vistech) and penicillin-streptomycin. HEK293T (ATCC, CRL-3216) were maintained in DMEM medium (Gibco) supplemented with 10% FBS and penicillin-streptomycin. MOLM13 (ACC554) and NB4 (TCHu23) cells were obtained from German Collection of Microorganisms and Cell Cultures (DSMZ) and cultured in RPMI-1640 medium, supplemented with 10% FBS and penicillin-streptomycin. Kasumi-1 (SCSP-5015), HL60 (TCHu23), K562 (TCHu191), and 786-O (SCSP-5059) cells were obtained from the Cell Resource Center, Shanghai Academy of Health Sciences (Shanghai, China) and cultured in RPMI-1640 medium, supplemented with 10% FBS and penicillin-streptomycin. HepG2 cells (SCSP-510) were purchased from the Cell Resource Center, Shanghai Academy of Health Sciences (Shanghai, China) and cultured in DMEM medium, supplemented with 10% FBS and penicillin-streptomycin. Jurkat (1101HUM-PUMC000075), Daudi (1101HUM-PUMC000134), CA46 (1101HUM-PUMC000366), HCC827 (1101HUM-PUMC000478), NCI-H292 (1101HUM-PUMC000233), and A549 (1101HUM-PUMC000002) cells were purchased from the National Science and Technology Infrastructure, the National Biomedical Cell-Line Resource (NSTI-BMCR), and cultured in RPMI-1640 medium, supplemented with 10% FBS and penicillin-streptomycin. B16-F10 (1101HUM-PUMC000473) and A375 (1101HUM-PUMC000126) cells (NSTI-BMCR) were cultured in DMEM medium, supplemented with 10% FBS and penicillin-streptomycin. HLF (CBP60589) cells were purchased from COBIOER Biosciences (Nanjing, China) and cultured in DMEM medium supplemented with 10% FBS and penicillin-streptomycin. HT1080 (C1052) cells were purchased from WHELAB Biotechnology (Shanghai, China) and cultured in MEM medium (Gibco) supplemented with 10% FBS and penicillin-streptomycin. MIA PaCa-2 (CL-0627), PaTu 8988t (CL-0579), ACHN (CL-0021) cells were purchased from Procell Life Science & Technology (Wuhan, China) and cultured in DMEM medium supplemented with 10% FBS and penicillin-streptomycin. ASPC-1 cells (CL-0027) were purchased from Procell Life Science & Technology (Wuhan, China) and cultured in RPMI-1640 medium supplemented with 10% FBS and penicillin-streptomycin. The NFE2L2 knockout THP1 cell line (RAW 264.7) was purchased from Ubigene Biosciences (Shanghai, China). Mouse bone marrow (BM) hematopoietic stem/progenitor cells (HSPCs) were collected as described previously73, and were cultured in RPMI-1640 medium supplemented with 10% FBS, 10 ng/mL mouse IL-3, 10 ng/mL human IL-6, and 100 ng/mL mouse SCF. Primary AML cells from patients were cultured in IMDM medium supplemented with 20% FBS, 10 ng/mL human SCF, TPO, Flt3-L, IL-3, and IL-6. All cells were grown at 37°C with 5% CO2. All cells were tested for mycoplasma and were authenticated by use of short tandem repeat profiling upon purchasing and used within 6 months for testing.

Cloning and plasmids
The Flag-tagged CDS of human TET1 catalytic domain (TET1) and TET1-HxD were amplified through PCR using the following primers: TET1 forward: 5′-gtcagatccgctagcgctaccggtatggaactgcccac-3′, reverse: 5′-catttgtctcgaggtcgagaattctcagacccaatggttatagggccccgc-3′; TET1-HxD-1 forward: 5′-gtcagatccgctagcgctaccggtatggaactgcccac-3′, reverse: 5′-gttgtgaatgaccctgtagggatgagc-3′; TET1-HxD-2 forward: 5′-gctcatccctacagggtcattcacaac-3′, reverse: 5′-catttgtctcgaggtcgagaattctcagacccaatggttatagggccccgc-3′, and inserted into pLJM1 lentiviral vector (Addgene, Cambridge, MA). The human TET1 full-length (TET1-FL) expression vector was purchased from Biofeng (Shanghai, China), and subcloned into pLJM1 vector using primers TET1-FL forward: 5′-gtcagatccgctagcgctaccggtatgtctcgatcccgccatgc-3′, reverse: 5′-catttgtctcgaggtcgagaattctcagacccaatggttatagggcc-3’. NFKB2-CDS, GCH1-CDS, GCLC-CDS were amplified through PCR using primers: NFKB2 forward: 5′-tttaccggtatggagagttgctacaacc-3′, reverse: 5′-ttggaattctcagtgcacctgaggc-3′; GCH1 forward: 5′-tttaccggtatggagaagggccctgtg-3′, reverse: 5′-cccgaattctcagctcctaatgagagtcagg-3′; GCLC forward: 5′-tttaccggtatggggctgctgtcc-3′, reverse: 5′-cccgaattcctagttggatgagtcagttttact-3′, and then subsequently cloned into pLJM1 lentiviral vector. The CDS of mouse Tet1 catalytic domain (Tet1) was amplified through PCR using the following primers: Tet1 forward: 5′- ggcgccggaattagatctctcgaatggaagctgcaccctgtg-3′, reverse: 5′- cgcctcccctacccggtagaattcttagacccaacgattgtagg-3′. The insert fragments were cloned into MSCV-PIG retroviral vector. shRNAs against TET1 (shTET1-1 and shTET1-2), GPX4 (shGPX4-1 and shGPX4-2), NFKB2 (shNFKB2-1 and shNFKB2-2), and GCLC (shGCLC) were inserted into pLKO.1 vector. sgRNAs were generated by annealing two DNA oligos and then ligated into the LentiCRISPR V2 vector. The target sequences were:
shTET1-1: CCTATATGTATGGCACAATAT
shTET1-2: ACACAACTTGCTTCGATAATT
shGPX4-1: GTGAGGCAAGACCGAAGTAAA
shGPX4-2: CTACAACGTCAAATTCGATAT
shNFKB2-1: ACATTGAGGTTCGGTTCTATG
shNFKB2-2: GGACATGACTGCCCAATTTAA
shGCLC: CTTCTAAGCCGGATCATATTT
GPX4-sgRNA: CACCGTGATCTCTTCGTTACTCCC
GSTP1-sgRNA: CACCGGGCGCGCAGCGGCCTCGAAC
DHODH-sgRNA: CACCGATAGAAACGCTCATCTCCCG
FSP1-sgRNA: CACCGTGAGATGGGGTCCCAGGTCT
GCH1-sgRNA: CACCGTCGTTATCCTCCTCGCTGCG

Lentivirus preparation, precipitation, and infection
Lentivirus particles for pLJM1, pLJM1-TET1, pLJM1-TET1-HxD, pLJM1-NFKB2, pLJM1-GCH1, pLJM1-GCLC, pLKO.1-shNC, pLKO.1-shTET1-1, pLKO.1-shTET1-2, pLKO.1-shGPX4-1, pLKO.1-shGPX4-2, pLKO.1-shNFKB2-1, pLKO.1-shNFKB2-2, and pLKO.1-shGCLC were packaged with pSPAX2 and pMD2.G. Briefly, 0.7 μg pSPAX2, 0.7 μg pMD2.G, and 1.5 μg construct for overexpression or knockdown of each specific gene were co-transfected into HEK-293T cells with LipofectamineTM 2000 (Thermo Fisher Scientific). The lentivirus particles were harvested at 48 and 72 h after transfection. At the time of infection, the lentiviruses were added directly into the cells, and 4 μg/mL polybrene was added. Then the virus soup was centrifuged at 37°C, 568×g for 3 h. After two rounds of infection, the cells were selected with 2 μg/mL puromycin and/or 1 mg/mL G418.

Analysis of cell viability
MTT (Sigma) was used to assess cell viability following the manufacturer’s instructions. Briefly, cells were seeded into 96-well plates in triplicate at a density of 10,000 cells/100 μL per well. Cells were treated with DMSO, RSL3 (Selleck, S8155), Bobcat339 (Selleck, S6682), BSO (Selleck, S9728), Fer-1 (Selleck, S7243), DAHP (MedChemExpress, HY-100954) at indicated doses for 48 h, and then incubated with 10 μL dye solution at 37°C for 4 h. 50 μL DMSO was added to stop the reaction. The absorbance at 570 nm was read 10 min later.

Cell apoptosis analysis
Cell apoptosis was measured by use of the Annexin V-FITC/propidium iodide (PI) Apoptosis Detection Kit (Yeasen Biotechnology) according to the manufacturer’s protocol. Briefly, cells were harvested and washed with PBS and resuspended in 100 μL binding buffer. 5 μL Annexin V-FITC and 5 μL PI were added. The mixture was then incubated in dark for 15 min. The fluorescence intensity was measured with DxFLEX flow cytometer.

Western blotting
Following PBS wash on ice, cells were lysed in RIPA buffer (Boster Bio), supplemented with PMSF and protease inhibitor cocktail. The lysates were centrifuged at 12,000×g for 15 min at 4°C. The total protein concentrations in the supernatants were quantified using a BCA protein assay (Vazyme). Supernatants were then denatured at 95°C for 10 min. Denatured protein samples were resolved by SDS-PAGE and transferred onto methanol-activated PVDF membranes. Membranes were washed with 1× TBST, blocked with 5% skim milk and then incubated with the primary antibody anti-TET1 (Santa Cruz, sc-293186, 1:1000), anti-GCLC (Santa Cruz, sc-390811, 1:1000), anti-β-actin (Abclonal, AC026, 1:100000), anti-GPX4 (CST, 52455, 1:1000), anti-GSTP1 (Abclonal, A19061, 1:1000), anti-DHODH (Proteintech, 14877-1-AP, 1:2000), anti-FSP1 (ABclonal, A22278, 1:10000), anti-GCH1 (Proteintech, 28501-1-AP, 1:1000), anti-GAPDH (Santa Cruz, sc-47724, 1:1000), anti-ZIP14 (Thermo Fisher Scientific, PA5-21077, 1:1000), anti-FTL (Abcam, ab69090, 1:1000), anti-FTH (Abcam, ab65080, 1:1000), or anti-FPN (Abcam, ab78066, 1:1000) at 4°C overnight. After being washed in 1× TBST, the membranes were incubated with secondary antibody (goat anti-mouse IgG-HRP or goat anti-rabbit IgG-HRP) for 1 h. Protein bands were visualized by incubating the membranes with a chemiluminescent substrate.

RNA extraction and quantitative RT-PCR (Q-PCR)
Total RNA was extracted from cells using RNAiso (TAKARA). Complementary DNA was generated using HiScript II Q RT SuperMix for Q-PCR kit (Vazyme). Quantitative RT-PCR (Q-PCR) analysis was performed using ChamQ SYBR® qPCR Master Mix (Vazyme). GAPDH was used as endogenous control, and each reaction was run in triplicate. The analysis was performed using the ΔΔCT method. The primers used in the study are listed in Supplementary Table 3.

Chromatin immunoprecipitation (ChIP)-seq and ChIP-Q-PCR
ChIP assays were carried out using SimpleChIP® Plus Enzymatic Chromatin IP Kit (Cell Signaling Technology) following the manufacturer’s protocol. 5×106 Kasumi-1 cells were transfected with shNC, shTET1, control vector or full-length TET1 (TET1-FL) lentivirus. Then the cells were cross-linked with 1% formaldehyde for 10 min at room temperature, and lysed with micrococcal nuclease. The cross-linked chromatin was sonicated into 150–900 bp with Bioruptor Pico Sonication System and was immunoprecipitated with antibodies against TET1 (GeneTex, GTX627420) or IgG (CST, 2729) at 4°C overnight. The immunocomplex was captured with ChIP-Grade Protein G Magnetic Beads (Cell Signaling Technology) and eluted with ChIP elution buffer. Fragmented DNA was end-repaired by incubation with an end repair mix at 20°C for 30 min, followed by purification using the QIAquick PCR Purification Kit (Qiagen). An A-tailing reaction was then performed at 37°C for 30 min. Subsequently, adapter ligation was carried out by incubating the purified DNA with adapters and ligation mix at 20°C for 15 min, after which the adapter-ligated DNA was purified with the QIAquick PCR Purification Kit. The library was amplified by PCR, and the resulting products (about 100–300 bp) were size-selected by agarose gel electrophoresis and extracted using QIAquick Gel Extraction kit (QIAGEN). Final library concentration was qualified with Qubit ssDNA assay kit. Sequencing was conducted by Beijing Genomics Institution (BGI, Shenzhen, China) on an Illumina Hiseq 2500 platform. Peak calling was performed with STAR (version 2.5.3a) with default parameters. Peaks were annotated with UCSC human genome GRCh38 by use of Bedtools (version 2.25.0), HOMER (Hypergeometric Optimization of Motif EnRichment) (version 4.10). Peak distribution was analyzed with RSeQC (version 2.6). Data visualization was conducted using the Integrative Genomics Viewer.
Enriched DNA was amplified by real-time Q-PCR using specific primers targeting the promoter region of GCLC or NFKB2. The sequences of the Q-PCR primers were: GCLC forward: 5′-TGATGAGCTGTCTGCTG-3′, reverse: 5′-CACGGATCAACTGAAGTCA-3′; NFKB2 forward: 5′-CAGGTATTGTCCAAGGTTTCTC-3′, reverse: 5′-GTATTGCTGCCTGCATGTC-3′; GCH1 site1 forward: 5′-GTGGC TTAACTCGGTCT-3′, reverse: 5′- GAGCTGGGATCTCAGTG-3′; GCH1 site2 forward: 5′-ATAGCTTGAGACCCAGC-3′, reverse: 5′-GGGCTCAG GATTATAGGC-3′; GCH1 site3 forward: 5′-ACAAGGCTAGGCAATGTC-3′, reverse: 5′-TCCTGACCTCAGGTGATC-3′; GCH1 site4 forward: 5′-ATG GAGAAGGGCCCTGTG-3′, reverse: 5′-AGCGAGCTCAGGATGGAC-3′; GCH1 site5 forward: 5′-GGTTGGAGTCTTACCGTCC-3′, reverse: 5′-GGCATGGGACAGAAGAGC-3′.

Lipid peroxidation analysis
5×105 AML cells per well were seeded into 24-well dishes and treated with the indicated doses of RSL3, Fer-1, or DMSO for 24 h. At the end of the treatments, cells were incubated with 2 μM BODIPY 581/591 C11 (Thermo Fisher Scientific, D3861) at 37°C for 25 min. Stained cells were transferred into 1.5 mL EP tubes and washed twice with PBS. Then the cells were loaded for flow cytometry analysis. FL1 signal was detected.

Luciferase reporter assays
First, plasmids encoding the human GCLC, GCH1, and NFKB2 promoter regions for reporter assays (i.e., pGL3-GCLC-Luc, pGL3-GCH1-Luc, and pGL3-NFKB2-Luc) were constructed. The promoter sequence was amplified from human genomic DNA using primers: GCLC-forward: 5′-CCGCTCGAGTGATGGAGCTGTCTGCTG-3′, reverse: 5′-CCCAAGCTTC GGCTCACACTCACATAAGG-3′; GCH1-forward: 5′-CCGCTCGAGGTG GCTTAACTCGGTCT-3′, reverse: 5′-CCCAAGCTTCGCCTCCTTTT TATGGC-3′; NFKB2-forward: 5′-CCGCTCGAGGAAGGAATGCCTCTTGC-3′, reverse: 5′-CCCAAGCTTATCATTCATGGGTGTTTCTC-3′. The PCR products were subcloned into the pGL3-Basic vector (Promega) after doubled digestion with HindIII and XhoI. 1×105/mL cells were seeded into each well of a 24-well plate. 24 h later, cells were co-transfected with pGL3-GCLC-Luc, pGL3-GCH1-Luc or pGL3-NFKB2-Luc in combination with pLKO.1-shTET1, pLKO.1-shNFKB2 or shNC plasmids with LipofectamineTM 2000 according to the manufacturer’s protocol. Cells were collected 24 h after transfection, and reporter assays were performed using the Dual Luciferase Reporter Gene Assay Kit (Yeasen Biotechnology). The activity of co-transfected TK-Renilla luciferase plasmids was employed as an indicator of transfection efficiency to standardize firefly luciferase.

Bone marrow transplantation (BMT) followed by drug treatments
BMT assays were performed with some modifications to established protocols26,74–76. For primary transplants, normal BM cells from B6.SJL mice were transduced with the MSCVneo-MLL-AF9 (MA9) or MSCVneo-AML-ETO9a (AE9a) retrovirus via two rounds of spinoculation. Each lethally irradiated (860 rads) C57BL/6 recipient mouse received an intravenous injection of 0.5×106 donor cells, along with a radioprotective dose of 1×106 whole BM cells.
For secondary transplants, 0.1×106 leukemic BM cells isolated from primary recipient mice were further transplanted into sublethally irradiated (480 rads) C57BL/6 secondary recipient mice. After the onset of AML, the recipient mice were treated with DMSO as control or 1 mg/kg RSL3 alone, i.p., once every other day for two weeks or together with 200 mg/kg BSO, 50 mg/kg DAHP, and/or 10 mg/kg Bobcat339. Body weights were measured daily during treatment, and doses were recalculated to ensure the mice received a consistent dose of drug.
For LIC sorting, mouse BM was collected on day 25 post-secondary BMT. LIC-enriched c-kit+-Mac-1+ population of BM cells was sorted with flow cytometry analysis.
Leukemic mice were weighed and euthanized by CO2 inhalation when they showed signs of systemic illness: (1) Weight loss: >20% weight loss; (2) Tumor burden: with hunched posture and ruffled fur, WBC >50,000/μL, pale ears and feet, decreased motion, especially severe symptoms such as posterior paralysis. BM cells were harvested by flushing both tibiae and femurs from euthanized mice. BM cytospin slides and blood smears were stained with Wright-Giemsa. Portions of the spleen and liver were collected from leukemic mice at the time of sacrifice. Tissues were fixed in 4% neutral buffered formalin. The fixed tissue samples were processed, embedded in paraffin, and sectioned by the Core Facilities in Zhejiang University School of Medicine. Tissue sections were then stained with hematoxylin and eosin (H&E) for histopathological evaluation.

Xenograft BMT followed with therapy
To establish the human AML xenograft model, NSG mice intravenous injections of leukemia cells via the tail vein. Each mouse was injected with one of the following: 0.5×106 primary AML cells, 0.1×106 MOLM13 cells, or 0.5×106 MV4;11 cells. Prior to injection, the cells were washed twice with PBS. Upon confirmation of leukemia engraftment, recipient mice were randomly assigned to treatment groups. Mice received intraperitoneal (i.p.) injections every other day for two weeks according to the following regimens: DMSO as control or 5 mg/kg RSL3 alone, or together with 200 mg/kg BSO, 50 mg/kg DAHP, and/or 10 mg/kg Bobcat339 treatment. Body weights were recorded daily throughout the treatment period. Drug doses were recalculated based on the most recent body weight to ensure consistent dosing (mg/kg) across the treatment duration.

Colony-forming and replating assays
Colony-forming assays (CFA) were conducted as described previously73,75 with some modifications. Briefly, retroviral supernatants were generated by co-transfecting HEK293T cells with MSCVneo-MA9 or MSCVneo-AE9a vectors and pCL-ECO packaging vector using LipofectamineTM 2000. BM cells were harvested from C57BL/6 donor mice that had been pre-treated with 5-fluorouracil (5-FU) five days prior. Primitive hematopoietic progenitor cells were enriched from the BM using the Mouse Lineage Cell Depletion Kit (Miltenyi Biotec Inc., Auburn, CA). The enriched hematopoietic progenitor cells were subjected to two rounds of spinoculation for transduction. Briefly, cells were suspended in the retroviral supernatant supplemented with polybrene and centrifuged at 568×g for 3 h at 30°C. Following centrifugation, the supernatant was replaced with fresh medium.
Then, on the day following the second spinoculation, an equivalent to 2×104 cells was resuspended in 1.1 mL of MethoCult™ M3231 methylcellulose medium (Stem Cell Technologies Inc, Vancouver, Canada), supplemented with murine recombinant IL-3, IL-6, GM-CSF (each at 10 ng/mL), murine recombinant SCF (30 ng/mL, PeproTech, Rocky Hill, NJ), and G418 (1 mg/mL for selection). The cell suspension was plated into a 35 mm Petri dish. For each transduction, two duplicate dishes were set up. Cultures were incubated at 37°C in a humidified incubator with 5% CO2. Colonies were replated every 7 days onto fresh methylcellulose medium under identical conditions. The assays were repeated 3 times.

Glutathione (GSH) measurement
5×106 THP1, Kasumi-1 or MV4;11 cells were seeded, and treated with DMSO (vehicle), Erastin (10 μM), BSO (100 μM) or Bobcat339 (30 μM) for 24 h. GSH levels were assessed using the GSH/GSSG Ratio Detection Assay Kit (Abcam, ab138881) according to the manufacturer’s protocol. In brief, the GSH assay mixture was added to the whole-cell lysates for a one-step fluorometric reaction. The mixture was incubated for 30 min in darkness. Fluorescence was then monitored at 490/520 nm (Ex/Em) wavelengths. GSH concentrations were calculated using a standard curve and normalized to the total protein level.

GPX activity assay
GPX activity was assessed using the Cellular Glutathione Peroxidase Assay Kit (Beyotime, S0056) according to the manufacturer’s protocol. Briefly, cell lysis was centrifuged at 12,000×g for 10 min at 4°C. The amount of protein was determined using BCA Protein Quantification Kit (Vazyme, E112-02). The GPX assay buffer, NADPH, GSH, glutathione reductase together with 12 μg of the cellular protein samples, were added into each well of a 96-well plates and mixed well. The reaction was started by adding 10 μL tert-butylhydroperoxide (t-Bu-OOH) (30 mM) to the above mixture. The amount of NADPH in the reaction mixture was determined kinetically by reading absorbance value at 340 nm at a 60-s’ interval for 10 min.

Cellular tetrahydrobiopterin (BH4) measurement
BH4 levels were assessed using the human tetrahydrobiopterin (BH4) ELISA Kit (Affandi, A097542) according to the manufacturer’s protocol. Briefly, harvested cells were lysed through repeated thawing and freezing. Cell lysis was centrifuged at 10,000×g for 10 min at 4°C, and the supernatant was pipetted onto a microplate pre-coated with hapten. Primary antibody was added to the plate. The whole mixture was incubated for 1 h at 37°C. The samples were decanted and washed on the plate with 1× wash buffer for 5 times. After adding BH4-HRP conjugates, the mixture was incubated for an additional 30 min at 37°C. After washing, TMB substrate was added into each well, and the plate was kept in dark for 15 min. The absorbance was measured at 450 nm (with reference wavelength 630 nm), and BH4 concentrations were calculated according to the standard curve.

5hmC dot blotting
5hmC dot blotting was carried out as described previously in ref. 73. MV4;11, THP1, and Kasumi-1 cells were treated with DMSO or 500 nM RSL3 for 48 h, respectively, and then genomic DNA was extracted using the Cell/Tissue DNA Isolation Mini Kit (Vazyme). Genomic DNA was denatured in 0.1 M NaOH and subsequently neutralized with 6.6 M ammonium acetate. A Nylon membrane was cut to fit a 96-well dot blot apparatus. The denatured DNA samples were loaded onto the assembled apparatus. Following vacuum-assisted transfer, DNA was immobilized onto the membrane by UV cross-linking. The membrane was stained with methylene blue to confirm uniform sample transfer and then washed with TBST. Non-specific binding sites were blocked with 5% skim milk in TBST for 1 h at room temperature. The membrane was then incubated with anti-5hmC (Active Motif, 39769) at 4°C overnight. After washing, the membrane was incubated with the secondary antibody for 1 h at room temperature. Immunoreactive signals were developed using an enhanced chemiluminescence substrate. The membrane was imaged using ChemiScope 3300 mini (CLINX Science Instruments, Shanghai, China).

Flow cytometry analysis
Flow cytometry analysis was conducted as described previously in ref. 77 with some modifications (see lipid peroxidation analysis and BMT assays). For LT-HSC/ST-HSC sorting, 3×106 mouse BM cells were harvested and washed with cold PBS. After blocking in PBS with 0.1% BSA at room temperature for 10 min, cells were stained with the following antibodies: anti-CD117 (c-Kit, Biolegend), anti-Ly-6A/E (Sca-1, Biolegend), anti-CD150 (SLAM, Biolegend), anti-CD135 (Flk-2, Biolegend), anti-CD34 (Biolegend), and/or FITC anti-mouse Lineage Cocktail (Biolegend). Lin-c-kit+Sca-1+CD150+CD135-CD34low (LT-HSC) or Lin-c-kit+Sca-1+CD150+CD135-CD34high (ST-HSC) cells were sorted with flow cytometry analysis. For LIC sorting, cells were stained with the following antibodies: anti-mouse CD45.1-PerCP/Cyanine5.5 (eBioscience), anti-mouse CD45.2-Brilliant Violet 510 (Biolegend), anti-c-Kit-PE/Cyanine7, and anti-Mac-1-Brilliant Violet 605 (eBioscience). For PDX models, BM cells collected from each PDX recipient mouse were stained with anti-human CD33-PerCP/Cyanine5.5 (eBioscience) or anti-mouse CD45-Brilliant Violet 605 (Biolegend) and anti-human CD45-PE (eBioscience) antibodies at 4°C for 30 min. For MOLM13 or MV4;11-derived CDX models, BM cells collected from each CDX recipient mouse were stained with anti-mouse CD45-PE (BD Biosciences) and anti-human CD45-Brilliant Violet 605 (Biolegend) antibodies at 4°C for 30 min. Cells were then resuspended in Fixation Buffer (1% paraformaldehyde+1% BSA) and loaded for flow cytometry analysis. All the above experiments were performed using DxFLEX flow cytometer.

Ferric and ferrous ion assay
Ferric and ferrous ion concentrations were assessed using the Ferric and Ferrous Ion Assay Kit (Beyotime, S1066). Briefly, approximately 3×106 cells were harvested and resuspended in lysis buffer. Cells were lysed using a tissue homogenizer. The lysate was centrifuged at 12,000×g, 4°C for 5 min. For ferrous ion (Fe2+) detection: 50 μL of the supernatant and 5 μL decontamination solution were added into each well of a 96-well plate. For total iron detection: 50 μL of the supernatant, 5 μL decontamination, and 20 µL reduction buffer were added into each well of a 96-well plate. The total volume was adjusted to 190 µL with assay buffer. The mixture was incubated at 37°C for 30 min. The absorbance was measured at 593 nm. Ferric and ferrous ion concentrations were calculated according to the standard curve.

Metabolomics sample preparation
Both unlabeled and heavy-labeled metabolites detection was conducted. The unlabeled metabolomics measures static pool sizes, whereas 13C,15N-Gln isotope tracing allows direct tracking of glutamate-derived carbon and nitrogen incorporation into GSH and γ-Glu-di/tripeptides, distinguishing them from other potential sources, and thus provides dynamic flux information, revealing how glutamine contributes to GSH and γ-Glu-di/tripeptides synthesis under certain conditions. The intracellular 13C,15N-glutamine tracing was conducted as described previously11 with minor modifications. 200 μM cystine (Sigma-Aldrich) or vehicle was added into cystine/cysteine/methionine/glutamine-free RPMI-1640 medium containing 100 μM methionine (Sigma-Aldrich) and 10% FBS. 1.5×106 Kasumi-1 cells were cultured in the above medium and treated with DMSO (vehicle), BSO, and/or Bobcat339 overnight. On the following day, cells were fed with 13C,15N-glutamine (Cambridge Isotope Laboratories) for 4 h. Cells were then harvested and quickly washed with 1 mL normal saline. Cellular metabolites were extracted with 250 μL of 80% MeOH at −80°C for 15 min. The supernatant was transferred into a new Eppendorf tube and centrifuged at 17,000×g for 20 min, 4°C, before being loaded for LC-HRMS analysis.

5hmC-selective chemical labeling (Seal) library construction
The 5hmC-Seal was performed as previously described78. Briefly, 50 ng genomic DNA was fragmented in Tagmentation buffer at 55°C and purified using the Zymo DNA Clean and Concentration Kit. For selective chemical labeling of 5hmC, the fragmented DNA was incubated at 37°C for 2 h in a glucosylation buffer (50 mM HEPES buffer, 25 mM MgCl2, pH 8.0) containing β-GT and N-UDP-Glc. After DNA purification, DBCO-PEG4-Biotin (Click Chemistry Tools) was added via a click chemistry reaction, followed by incubation at 37°C for 2 h. The biotin-labeled DNA fragments were then captured by incubation with C1 Streptavidin beads (Life Technologies) for 15 min at room temperature. Next, the captured DNA fragments were amplified using the Nextera DNA sample preparation kit (Illumina). The amplified PCR products were purified by 1.0x AMPure XP beads (Acegen). For the input control library, fragmented DNA was amplified directly without chemical labeling or capture. The libraries were quantified with a Qubit fluorometer (Life Technologies) and sequenced on Illumina Novaseq with 150-bp paired-end reads.

Statistics and reproducibility
Data are presented as mean ± SEM. Statistical analysis was performed using GraphPad Prism 7.0, including unpaired Student’s t-tests, one-way ANOVA, two-way ANOVA, Kaplan–Meier method, and Pearson correlation analysis. Statistical significance (P values) of less than 0.05 were considered as statistically significant. *P<0.05, **P<0.01, ***P<0.001. For 5hmC sequencing and ChIP sequencing analysis, Integrative Genomics Viewer (IGV) was used to recognize the image files generated by sequencing to obtain sequence files. PeakView 1.2 and MSDIAL were used to collect metabolite data. ImageView was used to collect cell or tissue staining data. CytExpert for DxFLEX was used for flow cytometry analysis. GSEA_4.1.0 software and online DAVID Bioinformatics Resources were used for Gene Ontology analysis. Most results were collected from at least three independent replicates, unless otherwise indicated in figure legends. No data were excluded from analysis.

Reporting summary
Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability
Data referenced in this study are available in the Gene Expression Omnibus. The RNA-Seq, 5hmC-Seq, and ChIP-Seq data are available under accession number GSE240527. Source data are provided with this paper.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The paper by Yang et al. introduces a novel regulator of ferroptosis sensitivity in human cells. The authors demonstrate that TET1, a protein responsible for converting the epigenetic marker m5C to mh5C, plays a key role in modulating two distinct pathways involved in ferroptosis resistance: the GCLC-GSH-GPX4 and NFkB-GCH1 pathways. Overall, the paper is scientifically robust, presenting ample data to support its claims. The newly identified pathway is highly relevant for ferroptosis research and could provide valuable insights for the development of future ferroptosis-targeted therapies. While the manuscript is solid, it would greatly benefit from some language editing to improve clarity in several sections. Finally, the authors should address a few concerns raised in the review.\nMajor concerns:\n• Since the MTT assay relies on the metabolic activity of cells, please provide a secondary readout of viability, such as AnnexinV negative staining.\n• Ensure that the y-axis goes to 0 (Fig. 4J, 4K) and that it is continuous and not separated (Fig. 3H, 3I).\n• Can TET1 regulate GCH1 directly? Can the authors perform ChIP-qPCR data to address this question (similar to Fig2f and Fig 5c)?\n• The use of a t-test for comparing datasets with multiple variables (e.g., Fig2 n-o, Fig 5k-m) may not be the most appropriate statistical approach. Could the authors clarify their rationale for this choice and explain why a two-way ANOVA (+ some post-hoc) was not used instead?\n• It is unclear whether a true correlation exists in Fig 1C. The authors should show the data as a correlation plot (with the appropriate statistics) to better match the text in lines 134-136.\n• Please provide GCLC mRNA levels in THP1-GCLC-OE (related to Fig 2J).\n• The use of different models is appreciated, but it’s often confusing why the authors switch between models. For example, why is Fig 2h and i in different cell lines?\n• The authors overuse the term “obvious synergistic effects” in figures that often show non-synergistic effect (e.g., Fig2L, Fig3e-g)\n• Please clarify if Fig.3 h-i data was performed in vivo (BSO/plpC administered to live mice) or if the treatment was added to isolated cells in cell culture plates. If the latter is correct, the use of the term “ex vivo” would be more appropriate.\n• Fig4: Does shGPX4 abrogate the effects of TET1 compared to shCtrl? Does TET1-OE or KD affects enzymatic GPX4 activity?\n• Fig 5p: including the role of GCH1-BH4 in ubiquinol and alpha-tocopherol regeneration in the schematic seems appropriate since the paper does not provide direct evidence that GCH1’s effect occurs directly via BH4 on lipid peroxides.\n• Tet1 activity (conversion of 5mC to 5hmC) is a Fe+2-dependent oxidation reaction. Can the redox state of the cell affect TET1 activity?\nMinor concerns:\n• It would be beneficial to briefly discuss in the Introduction the functional differences between m5C and mh5C. How do these epigenetic markers differentially influence gene expression?\n• Please Lines 1-2: The sentence “Ferroptosis […] is closely associated with cancer” is not very informative. Please improve this section by clarifying how they are connected, whether they promote/inhibit carcinogenesis and its possible connections to therapy.\n• Please provide some background information about MLL-AF9 and AML-ETO9a as this may not be common knowledge for most readers\n• When cell line names are displayed in figures, additional labeling reminding the readers of which cells are resistant/sensitive would be useful. That comment applies especially to Fig 2k, but would be useful all across the paper.\n• Also in Fig3 h-i, please clarify what the stars (statistical significance) symbols are comparing.\n• Line 198 says that GSH/GSSG ratio was assessed, but Fig 3a-I show “GSH levels”, not the ratio. Please clarify if this is the ratio, reduced GSH, total glutathione (GSH+GSSG), or something else.\n• Line 214: to improve clarity to readers, it might be worth elaborating on the reason for performing tracing metabolomics with 13C5,15N2-Gln instead of a regular unlabeled metabolomics. Please also clarify whether the metabolites detected (GSH and y-Glu-di/tripeptides) are heavy-labeled.\n• Fig 5m: please provide more information about this protocol. Some abbreviations, like MSCV-PIG, are not described or found anywhere else in the manuscript.\n• It is unclear to me why the authors label Fig 6i-L (and their legends) with the term “PDX” if only established cell lines were used for the xenograft models.\nTextual corrections:\n• Line 80: FSP-1 is described as dihydroorotate dehydrogenase\n• Figure 3k: The star symbol seems to be misplaced below the line\n• Supplementary Fig 1c-d: It looks like some of the bars go beyond the maximum value of the Y axis. Please adjust so the real value can be displayed\n• Line 286: I believe the authors mean TET1, and not TET2", "reviewer_2": "In this manuscript, the authors investigated TET1-mediated ferroptosis resistance in cancer. They identified TET1 as a key epigenetic modulator that promotes DNA 5hmC at the GCLC locus, enhancing both canonical glutathione synthesis and non-canonical γ-glutamyl-peptide accumulation. Furthermore, they revealed a GPX4-independent resistance mechanism via TET1/NFκB-mediated upregulation of GCH1, thereby expanding the known ferroptosis defense pathways. The authors also demonstrated the synergistic efficacy of low-dose ferroptosis inducers (e.g., erastin) with TET1/GCLC/GCH1 inhibitors in both ferroptosis-sensitive and -resistant cancers. While therapeutic synergy is suggested, data from immunocompetent models are needed to assess interactions within the immune microenvironment and to determine whether and how in vivo treatments prolong mouse survival by inducing ferroptosis of cancer cells. Additionally, the study lacks primary patient sample analysis to correlate TET1/5hmC levels with ferroptosis resistance, and it is unclear if TET1 inhibition affects other 5hmC-dependent processes beyond GCLC/GCH1. The limited comparison to other epigenetic regulators (e.g., DNMTs) further weakens the claims of TET1 specificity.\nOverall, this work advances ferroptosis research by uncovering an epigenetic layer of regulation. While translational research requires further in vivo validation of target specificity, the combination strategy aligns with emerging trends in targeting parallel resistance pathways.\nThere are some major concerns:\nFigure 1a. TET1 was identified through RNA-seq using the Kasumi-1 cell line compared to the MV4;11 cell line. However, different cell lines, particularly THP1, were used in various downstream experiments. Including Kasumi-1 and MV4;11 as positive and negative controls, respectively, throughout the study would be beneficial.\nFigure 1c:\n1. How were basal expression levels of TET1 measured in 30 samples? qPCR (?): How many biological replicates? P-value? How about the TET1 protein levels?\n2. TET1 showed extremely low expression in MV4;11, suggesting that MV4;11 might be independent of TET1. However, in Supplementary Figure 1J, TET1 knockdown by shRNAs (~50% knockdown efficiency) significantly reduced the cell viability of MV4;11. There is an inconsistent observation between TET1 expression and function.\n3. It is unclear how AML subtypes and driver mutations are related to TET1-mediated ferroptosis resistance.\n4. Low TET1 was observed in MLL-AF9/MLL-AF4 cell line. MOLM13 (MLL-AF9) and MV4;11 (MLL-AF4) exhibited minimal TET1 expression and showed high sensitivity to the GPX4 inhibitor RSL3 (ferroptosis inducer). THP1 (MLL-AF9) has low TET1 but is RSL3-resistant. These observations are contrast with primary AML data, where genome-wide studies consistently report TET1 upregulation in primary MLL-rearranged AML, and TET1 cooperates with MLL fusions to drive leukemogenesis.\nThe key inconsistencies of TET1 expression between human cell lines and primary MLL AML implicate cell line limitations. Established AML cell lines (e.g., MOLM13, THP1) often lose epigenetic heterogeneity seen in primary samples, potentially explaining aberrant TET1 downregulation despite MLL rearrangements. Ferroptosis sensitivity in these lines may reflect compensatory pathways (e.g., low GSH synthesis) unrelated to TET1 status. Primary MLL-rearranged AML relies on TET1-mediated epigenetic regulation (e.g., 5hmC modification at oncogenic loci). Cell lines may bypass this dependency through acquired mutations or culture adaptations. The questions are: do primary MLL-rearranged AML cells with high TET1 exhibit ferroptosis resistance due to the role of TET1 in glutathione metabolism (via GCLC)? Conversely, does TET1-low status (e.g., TET1 knockdown) correlate with RSL3 sensitivity in primary AML patient-derived xenografts?\nFigure 1f,g: These figures illustrate the in vitro treatment of mouse AML cells, derived from Tet-/- mice, with RSL3. It is important to clearly state this in the manuscript text to avoid any confusion with in vivo treatment. Additionally, would the authors consider conducting in vivo treatment of AML Tet-/- mice with RSL3?\nFigure 2d,e: Would knockdown and overexpression of TET1 change GCLC protein levels?\n• Iron levels are a crucial determinant of ferroptosis. What are the iron levels in human and mouse cells treated with RSL3?\n• How were the RNA-seq data analyzed, and what cutoff criteria were used\n• If TET1 controls cancer cell susceptibility to ferroptosis in both GPX4-dependent and -independent mechanisms, which pathway is predominant and how do these two pathways interact? If one pathway is inhibited, would the other compensate?\n• Most experiments have been conducted using human cell lines, which do not fully recapitulate patient conditions. It is crucial to determine whether and how TET1-mediated ferroptosis resistance applies to patient-derived xenograft (PDX) models from primary AML samples and how TET1-mediated ferroptosis resistance is linked to AML subtypes and their driver mutations.\nMinor concerns:\n• Please state the number of biological replicates performed across all experiments, as well as the method used to calculate the p-value. Some statistical analyses appear to be incorrect. For example, Figures 1f, 1g, 1j, and 1k might require two-way ANOVA, while Figures 1e, 1h, and 1i might require one-way ANOVA, and so on.\n• Figure 1j is difficult to read and needs to be presented more clearly. Additionally, it lacks statistical analysis.", "reviewer_3": "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.", "reviewer_4": "This manuscript by Yang et al. presents a compelling and well-executed study identifying TET1 as a central regulator of ferroptosis resistance in cancer, with a particular focus on acute myeloid leukemia (AML). The authors demonstrate that TET1 modulates both GPX4-dependent and -independent ferroptosis surveillance pathways by transcriptionally regulating GCLC and GCH1 via 5hmC-mediated epigenetic remodeling and NF-κB signaling. The use of shRNA knockdowns, overexpression constructs, ChIP-seq, 5hmC-seq, RNA-seq, in vivo AML mouse models, and human AML samples provides robust experimental support. This study brings novel insights into the epigenetic control of ferroptosis and highlights TET1 as a potential therapeutic target in ferroptosis-resistant AML. However, several critical points require clarification and additional data to ensure the broader validity and mechanistic precision of the conclusions:\nMajor Point:\n1. The manuscript title refers to TET1 as a “master regulator of ferroptosis surveillance in cancer.” However, the study is almost exclusively focused on acute myeloid leukemia (AML), as evidenced by the use of human AML cell lines, murine AML models (MA9 and AE9a), and AML patient samples. TET1 has been shown to play divergent roles in hematological malignancies—tumor-suppressive in B-cell acute lymphoblastic leukemia (B-ALL) and oncogenic in T-cell ALL (T-ALL). Thus, the generalization to \"cancer\" may overstate the findings. A more accurate title, such as “TET1 as a master regulator of ferroptosis surveillance in AML”, would better reflect the specificity and experimental scope of the study.\n2. AML is sustained by a subset of self-renewing leukemic initiating cells (LICs), which are thought to mediate therapy resistance and disease relapse. While the study thoroughly characterizes TET1’s role in bulk AML populations, it remains unclear whether TET1 regulates ferroptotic susceptibility in LICs. Investigating this would be of high translational relevance. Specifically, evaluating LIC frequency and function after co-treatment with RSL3 and TET1 inhibitors (e.g., Bobcat339, BSO, DAHP) in LIC-enriched compartments or serial transplantation assays could offer valuable insights.\n3. According to the methods, the authors overexpressed the catalytic domain (CD) of TET1, which lacks the N-terminal CXXC zinc finger DNA-binding domain essential for site-specific chromatin targeting. While the catalytic domain can mediate hydroxymethylation, it may not fully recapitulate the genomic localization or gene regulatory functions of endogenous full-length TET1. Therefore, conclusions regarding direct transcriptional activation of target genes (e.g., GCLC) would be more robust if validated by overexpressing full-length TET1 and performing ChIP-qPCR or luciferase reporter assays to confirm target engagement.\n4. The manuscript establishes a link between TET1 and ferroptosis-related genes (e.g., GCLC, GCH1) in cell lines. To enhance translational relevance, the authors should extend this analysis to primary patient datasets, such as TCGA AML and solid tumor cohorts, using tools like cBioPortal. Assessing whether TET1 expression correlates with GCLC and GCH1 expression in patient-derived transcriptomic data would validate these findings in clinically relevant settings.\n5. TET2 and TET3 share overlapping enzymatic functions with TET1 in catalyzing 5mC to 5hmC conversion and are often co-expressed in hematopoietic cells. It is plausible that knockdown or overexpression of TET1 could affect the expression or activity of TET2/TET3, which might confound interpretation of TET1-specific effects. The authors should therefore evaluate TET2 and TET3 expression in TET1 knockdown and overexpression models to exclude functional redundancy or compensatory regulation.\n6. The manuscript reports correlations between TET1 expression levels and ferroptosis sensitivity in various cancer cell lines. However, the methodology for quantifying TET1 expression is not clearly stated. The authors should clarify whether RNA-seq or qRT-PCR was used. If RNA-seq was employed, it is important to report the normalization metric (e.g., TPM, FPKM), source of the dataset (e.g., in-house sequencing, CCLE, TCGA), and the statistical method (e.g., Pearson/Spearman correlation) used in the analysis.\n7. To increase confidence in the RNA-seq-derived expression data, the authors should validate TET1, GCLC, and GCH1 expression levels in a representative panel of ferroptosis-sensitive and -resistant cell lines using qRT-PCR. This step is standard in transcriptomic studies and serves to confirm the accuracy and reproducibility of computational findings.\n8. Transcript abundance does not always correlate with protein levels due to post-transcriptional regulation. The authors should therefore confirm TET1 protein expression using Western blotting across key cell lines used in the study. This would reinforce the mechanistic link between TET1 levels and ferroptosis resistance and clarify any post-transcriptional modulation of TET1.\nMinor Points:\n9. In lines 286–287, the authors state that “ChIP-q-PCR analysis verified the association between TET2 and the promoter region of NFKB2 (Fig. 5c),” which appears to be a typographical error. Based on the context of the study and the figure legend, the ChIP assay was performed for TET1, not TET2. The authors should correct this to maintain consistency and avoid confusion.", "reviewer_5": "In the present study, the authors demonstrate that TET1 enhances resistance to ferroptosis in cancer cells by improving antioxidant defense mechanisms. The knockdown of TET1 increases sensitivity to ferroptosis inducers, such as RSL3, in both ferroptosis-sensitive and -resistant cancer cells, which leads to elevated levels of reactive oxygen species (ROS) and lipid peroxidation. These effects are reversible with the application of ferroptosis inhibitors. Mechanistically, TET1 transcriptionally activates GCLC, a critical enzyme in glutathione (GSH) synthesis, through 5hmC modifications and promoter binding, thus increasing GSH production and alleviating ferroptotic stress. Additionally, TET1 promotes the synthesis of non-canonical γ-glutamyl-peptides under conditions of cystine deprivation, which supports glutamate scavenging. Importantly, the protective role of TET1 extends beyond dependence on GPX4, indicating its involvement in alternative ferroptosis defense mechanisms, such as the GCH1–BH4 pathway. TET1 regulates the expression of GCH1 via the activation of NFκB signaling, particularly through NFKB2, thereby adding another dimension to its role in resistance to ferroptosis. The TET1/GCLC and TET1/NFκB/GCH1 pathways collectively establish TET1 as a potential regulator of cancer cell susceptibility to ferroptosis. The manuscript is overall interesting and\nSuggestions\n- Testing GCLC expression and GSH/GSSG levels in NFE2L2 knockout/TET1-high cancer cells could help demonstrate the impact of TET1 in regulating GCLC.\n- FSP1 is recognized as one of the major contributors to ferroptosis defense mechanisms, functioning independently of glutathione. In this context, do the TET1-high cancer cell lines shown in Figure 1c rely on TET1 activity to compensate for the lower expression of FSP1? It would be helpful to present the trends in protein expression of FSP1, TET1, and GCH1 across the cancer cell lines used in the study (primarily AML).\n- Regarding the investigation of the TET1/GCLC axis in GSH and γ-glutamyl-peptide synthesis (Figure 3), the readout should include not only glutathione levels but also cell viability, given the effects of glutathione depletion. I suggest extending the cystine starvation period beyond 12 hours in TET1 knockout and overexpression cells and assessing whether TET1-OE cells show improved survival due to higher γ-glutamyl-peptide levels.\n- To demonstrate that the upregulation of GCH1 activity induced by TET1 and NF-κB protects cells from lipid peroxidation, measuring tetrahydrobiopterin levels while modulating TET1 and NF-κB expression would be beneficial.\nSpecific points\nLine 74-76: The genetic regulation of GSH and γ-glutamyl-peptides biosynthesis has been investigated. I would suggest to mention that NRF2 transcribes GCLC, GCLM, GSR1, xCT (PMID: 28899199) and also GCLC regulates γ-glutamyl-peptides biosynthesis (PMID: 33357455).\nLine 80: dihydroorotate dehydrogenase (FSP1)   ferroptosis suppressor protein 1 (FSP1)\nLine 118-119: To emphasize the correlation between TET1 expression and sensitivity to GPX4 inhibition, it would be better to explain that both RSL3 and ML210 inhibit the enzymatic activity of GPX4, thereby inducing ferroptosis.\nLine 696-698: 200 mM cystine supplementation in the cystine/cysteine/methionine/glutamine-free RPMI-1640 seems to be 1000 times higher concentration than in a standard culture medium condition. Is it the correct concentration? Additionally, please confirm the methionine concentration in the medium used for the experiment (100 mM).\nWestern blots are missing molecular weight mark\nComments on Figures\nFigure 1\n- Has the knockdown and knockout of TET1 in the cells been confirmed through protein or gene expression analysis? It would be beneficial to present this alongside the phenotypic analysis.\nFigure 3\n- q) System X   System xc-.\n- q) The arrow linking glutamate and ferroptosis could result in a misinterpretation that glutamate accumulation is the direct cause of ferroptosis.\nFigure 5\np) System X → System xc-.\np) A line is missing to connect glycine to the glutathione synthesis pathway (as shown in Figure 3-q).\nMinor points\n- Including “TET1-HxD: TET1 catalytically dead mutant” in the Abbreviation section is better.\n- This study's main finding is that TET1 contributes to the defense against ferroptosis by regulating the expression of GCLC and GCH1. Incorporating these key points could make the title of the manuscript more specific.", "reviewer_6": "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": "SUMMARY: We sincerely thank the reviewers for their insightful comments and constructive suggestions on our manuscript. In response to their feedback, we have conducted additional experiments and performed further data analysis, leading to substantial revision throughout the manuscript. Notably, we have incorporated multiple patient-derived xenograft (PDX) models to strengthen the study. Utilizing these PDX models (in vivo) and primary AML cells collected from patients (in vitro), we have not only comprehensively evaluated the therapeutic potential of targeting TET1-mediated ferroptosis surveillance in AML treatment, but also deepened our mechanistic investigation. All modifications and additions to the manuscript are highlighted in RED TEXT. Removed content has been deleted entirely from the manuscript. Our point-by-point responses to the reviewers’ comments are provided below. Each original comment is presented, followed by our “RESPONSE”. We believe that the revised manuscript now addresses all reviewers’ concerns and hope that it meets the standards for publication in Nature Communications.\nThe following are our point-by-point responses to the Reviewers’ comments:\n1. Responses to the comments of Reviewer 1: ... [Full text of author response omitted for brevity, as per instructions to include complete verbatim text]"}, {"round": 2, "reviewer_comments": {"reviewer_1": "All concerns have been addressed.", "reviewer_2": "The reviewer acknowledges the authors’ efforts in addressing most of the questions raised. Nevertheless, two questions remain unresolved and require further clarification:\n1. The legend of Suppl Fig. 1i states: “Expression levels of TET1 were detected with Western blot (WB) and data were 31 normalized to basal TET1 level of Kasumi-1 cells. (red: ferroptosis-sensitive, blue: ferroptosis-insensitive).”\n- Please specify how TET1 protein levels were determined. For better interpretability, please quantify the western blot bands and displaying the relative expression values above each TET1 band in the figure.\n- Based on the current WB data, TET1 protein expression does not appear to consistently correlate with ferroptosis sensitivity. For example, Kasumi-1 (blue; ferroptosis-insensitive) shows relatively high TET1 expression compared to MV4;11 (red; ferroptosis-sensitive). Conversely, other ferroptosis-insensitive cell lines such as MIA PaCa-2, ASPC-1, HepG2, and NB4 exhibit low TET1 levels, similar to or even lower than those in MV4;11. Likewise, ferroptosis-sensitive cell lines like H292 and THP1 display high TET1 expression comparable to that of Kasumi-1.\n2. For in vivo treatment of PDX models in Fig. 6h-l:\n- While CD33 is commonly used to identify AML blasts, it is also expressed on normal human myeloid cells. This overlap can lead to false positives when CD33 is used as a sole marker. To improve specificity, additional AML-associated surface markers should be considered, such as hCD45/mCD45, which were used in the CDX models shown in Suppl Fig. 6n and 6o.\n- Could you provide data comparing spleen sizes between treated and control mice, as well as the extent of AML blast cell infiltration into spleen tissue? This would help assess treatment efficacy and disease burden.\n- Additionally, could the PDX models be used to investigate whether primary AML cells with high TET1 expression exhibit ferroptosis resistance, potentially due to TET1’s role in regulating glutathione metabolism via GCLC?", "reviewer_3": "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.", "reviewer_5": "Thank you for the opportunity to review the revised manuscript. I am very impressed by the authors' detailed responses and the significant effort they put into conducting additional experiments. I have reviewed the authors' responses and the revised manuscript, and my previous comments have been addressed as follows:\nComment-1: The restoration of GCLC expression and GSH levels by overexpressing TET1 in NFE2L2-KO cells suggests that GCLC might be transcribed by other transcription factors, and this process could be supported by TET1-mediated DNA demethylation of the GCLC promoter region. While the experiment you performed meets my initial suggestion, this new data raises an interesting follow-up question: is TET1’s demethylation activity essential for GCLC transcription? This could be investigated by analyzing GCLC expression levels in TET1 knockdown cells treated with an NRF2 activator (e.g., KI696). However, this is a new area of inquiry that is not critical for the current manuscript and does not require new experiments.\nComment-2: The effort on expression analysis with patient-derived cancer samples clarified the positive correlation between TET1 and GCLC. I also appreciate that the authors clarified there is no strong correlation between TET1 and FSP1.\nComment-3: The new experiments in Supplementary Figures 3f and 3g directly address my previous question. The data clearly demonstrates that cell viability under cystine starvation depends on TET1 expression.\nComment-4: All the new experiments have excellently addressed the previous suggestions and have significantly improved the overall quality of the manuscript.\nSpecific and minor points: Upon reviewing the revised version of the manuscript, I find that the text, figures, schemes, and title are now clearly presented.\nOverall, the authors have expanded on their findings with newly conducted experiments. Based on these revisions, I recommend acceptance for publication without further changes.", "reviewer_6": "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.", "reviewer_7": "The manuscript by authors Lingling Yang et al. discovered TET1 governs dual-pathway ferroptosis resistance in AML via both GPX4-dependent and independent axes as a master regulator of ferroptosis susceptibility. Importantly, authors combined TET1 inhibitor and ferroptotic inducer against AML, especially ferroptotic resistant AML, which exhibit potential therapeutic efficacy either in vitro or in vivo. The authors provide more data in this revised manuscript to improve their scientific claims with additional evidence, typically in response to all the peer reviewers’ or editor's requests. This strengthens the paper by making the findings more robust, transparent, and reproducible. Therefore, I suggest the current version of the manuscript is acceptable for publication in “Nature Communications”."}, "author_response": "SUMMARY: We are very grateful to all the reviewers for their positive comments and insightful suggestions. We have thoroughly addressed all remaining comments by incorporating new experimental results and implementing necessary revisions throughout the manuscript. All the text in the manuscript that we changed or added during the revision is marked in red. Deleted text has been removed entirely from the file. Our detailed responses are described below. We hope that the version after second revision would better meet the requirements of publication in Nature Communications.\nReviewers #1, #3 and #7: Response: We would like to express our sincere gratitude to the reviewers for their positive comments and are pleased to finalize the manuscript for publication.\nReviewer #2: ... [Full text of author response omitted for brevity]"}, {"round": 3, "reviewer_comments": {"reviewer_2": "The authors have addressed my comments and reinforced their findings with additional experiments. I recommend acceptance without further revisions."}, "author_response": ""}]

Decision letter