Amino-Acid-mTORC1-Driven DDA1 Phosphorylation Promotes DNA Repair and Glioblastoma Progression

Amino-Acid-mTORC1-Driven DDA1 Phosphorylation Promotes DNA Repair and Glioblastoma Progression | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Amino-Acid-mTORC1-Driven DDA1 Phosphorylation Promotes DNA Repair and Glioblastoma Progression Xiaozhong Peng, Xing Chen, Zhixing Wang, An Yan, Yunpeng Liu, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7717041/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract The protein DDA1 is involved in protein degradation, cell cycle regulation, and DNA damage repair. Recent studies have revealed its differential expression across various tumor types. However, the manner in which how DDA1 functions as a tumorigenic factor remains to be elucidated. Through experiments in multiple glioblastoma cell models, we identified a physical association between cytoplasmic DDA1 and Raptor, a key component of lysosome-associated mTORC1. Amino acid stimulation triggers phosphorylation of DDA1 at serine 33, promoting its nuclear translocation and involvement in DNA damage repair. Integrated genomic and transcriptomic analysis revealed that the amino-acid-mTORC1-DDA1 S33 -DNA repair axis regulates the expression of a subset of metabolic genes, including ENO2, a glycolytic enzyme; CA12, which contributes to intracellular and extracellular pH homeostasis; and NMRK1, a key enzyme in nicotinamide riboside metabolism. Notably, DDA1 deficiency markedly impaired glioblastoma growth and triggered a compensatory upregulation of metabolic activity to sustain tumor cell survival. These metabolic genes supply essential nutrients required for effective DNA repair. Our findings establish DDA1 as a previously unrecognized phosphorylation target downstream of amino-acid-mTORC1, serving as both a critical mediator of mTORC1-driven DNA damage response and a key regulator of glioblastoma progression, thereby expanding our understanding of gliomagenesis. Biological sciences/Cancer/CNS cancer Biological sciences/Biochemistry/Kinases Biological sciences/Molecular biology/Proteomics/Protein–protein interaction networks Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Damage-specific DNA-binding protein 1 (DDA1) is a recently characterized component of the CRL4 CSA E3 ubiquitin ligase complex that plays a central role in transcription-coupled nucleotide excision repair (TC-NER) 1, 2, 3, 4 . The CRL4 CSA complex, which is composed of CUL4A, DDB1, RBX1, the substrate receptor CSA (ERCC8), and the regulatory subunit DDA1, ubiquitinates stalled transcription-associated factors and remodels chromatin to facilitate lesion removal 1, 2, 5, 6 . By acting as a regulatory adaptor, DDA1 helps recruit and ubiquitinate repair substrates, preserving genome integrity under genotoxic conditions 1, 2, 7 . Disruption of CRL4 CSA or DDA1 leads to defective TC-NER and persistent DNA lesions, which are drivers of genomic instability and tumor development. Elevated DDA1 expression has been reported in multiple malignancies, including breast, colorectal, and lung cancers, suggesting a conserved role in supporting tumor cell survival under stress 8, 9, 10 . Cancer cells may exploit CRL4 CSA -mediated DNA repair to tolerate therapy-induced damage, thereby contributing to therapy resistance 5, 11, 12, 13 . Despite these advances, the upstream signals linking metabolic status to DDA1 function in cancer remain poorly defined 10, 14 . The mechanistic target of rapamycin complex 1 (mTORC1) is a master kinase complex that integrates nutrient, energy, oxygen, and growth factor signals to regulate biosynthetic and catabolic pathways 15, 16 . Through phosphorylation of key effectors such as S6K1 17, 18 and 4E-BP1 19 , mTORC1 controls protein synthesis, nucleotide production, lipid metabolism, and autophagy. Its activation is orchestrated at the lysosomal membrane by Rag GTPases 20,21 , the Ragulator complex 20 , GATOR1/2 21 , and amino acid sensors including Sestrin2 22, 23 , SAMTOR 24 , and CASTOR1 25 . Dysregulated mTORC1 signaling is a hallmark of glioblastoma, where it drives unchecked proliferation and interferes with DNA damage checkpoints 26, 27, 28, 29, 30, 31 . Glioblastoma (GBM) represents the most aggressive primary brain malignancy, one that is marked by rapid progression, profound heterogeneity, and resistance to conventional therapy 32, 33 . Genomic studies have revealed frequent alterations in TP53, PTEN, EGFR, and IDH, along with dysregulation of multiple oncogenic cascades including PI3K-AKT-mTOR signaling 34, 35, 36, 37, 38 . Moreover, GBM cells display metabolic adaptability and robust DNA repair capacity, enabling them to survive radiotherapy and alkylating chemotherapy 39, 40, 41, 42 . The question of how mTORC1 signaling is functionally coupled to nuclear DNA repair programs to sustain GBM growth remains open. In this study, we identify DDA1 as a direct phosphorylation target of mTORC1 in GBM. Biochemical and transcriptomic analysis demonstrates that amino acid stimulation induces mTORC1-dependent phosphorylation of DDA1 at serine 33, which facilitates its nuclear translocation and enhances DNA repair efficiency. We further show that phosphorylated DDA1 activates the metabolic gene program-ENO2, CA12, NMRK1-that supports tumor survival under genotoxic and metabolic stress. DDA1 depletion reduces tumor burden in vivo and compromises metabolic flexibility, sensitizing tumors to nutrient limitation. Elevated DDA1 expression correlates with worse patient outcomes, suggesting clinical relevance. Together, these results reveal a nutrient-responsive amino-acid-mTORC1-DDA1-DNA repair axis that promotes GBM progression through coordinated genome maintenance and metabolic adaptation. Results DDA1 physically associates with Raptor, a key component of the lysosome-anchored mTORC1 complex. As described previously, DDA1 participates in protein degradation and DNA damage repair 7 . Recent studies have also revealed that DDA1 expression is dysregulated across several tumor types 8, 9, 10, 43 . To gain further insight into its biological function, we conducted an epitope-tagged proteomic screen that combined immunoprecipitation with mass spectrometry to define the in vivo interactome of DDA1. We generated U118-MG GBM cells that stably expressed FLAG-tagged DDA1 (FLAG-DDA1), and cell lysates were subjected to anti-FLAG affinity purification followed by mass spectrometric analysis. Proteins co-purifying with DDA1 included DDB1 and CUL4A (members of the CRL4 CSA complex), LAMTOR1/2/3/5 (Ragulator subunits), and Raptor (a core mTORC1 component). The results from these experiments indicate that DDA1 engages with critical elements of both CRL4 CSA and mTORC1 signaling machinery (Fig. 1 a; Supplementary Data 1). Consistently, a reciprocal screen using FLAG-Raptor as bait also identified DDA1, together with RagA, RagC, RagD, and Ragulator components (Fig. 1 b; Supplementary Data 1). To validate these interactions, we performed co-immunoprecipitation (co-IP) in FLAG-DDA1-expressing U118-MG cells. Anti-FLAG immunoprecipitation followed by immunoblotting revealed robust association of DDA1 with Raptor and RagA, whereas no interaction was observed with WDR24 (GATOR2 component), mTOR, RagC, RagD, or LAMTOR1/2 (Fig. 1 c). The interaction of DDA1 with DDB1 and CUL4A was also confirmed (Fig. 1 d). Reciprocal co-IP using FLAG-Raptor again yielded DDA1 as a binding partner (Fig. 1 e), and immunofluorescence analysis demonstrated partial co-localization of DDA1 and mTOR with the lysosomal marker Lamp2, suggesting that the DDA1-Raptor interaction takes place at the lysosomal surface (Fig. 1 f). Additional evidence for the DDA1, RagA, RagC, and Raptor interaction came from GST pull-down assays using bacterially purified GST-DDA1 and in vitro translated mTORC1 components (RagA, RagC, Raptor) or CSA. DDA1 directly interacted with Raptor and CSA, but not with the other tested mTORC1 components (Fig. 1 g), and reciprocal pull-downs with GST-Raptor, GST-RagA, or GST-CSA corroborated these results (Fig. 1 g). To explore the structural basis of the DDA1-Raptor interaction, we performed protein-protein interaction prediction using AlphaFold3, which has been reported to achieve near-crystallographic accuracy 44 , and this model revealed extensive binding interfaces between the two proteins (Fig. 1 h). Together, these findings demonstrate that DDA1 interacts with Raptor at the lysosomal membrane. DDA1 functions downstream of mTORC1 and is phosphorylated by amino- acid-mTORC1 To determine the functional relevance of DDA1-mTORC1 interaction, we first positioned DDA1 within the mTORC1 signaling cascade. In U118-MG cells, siRNA-mediated depletion of DDA1 neither altered phosphorylation of S6K1, a canonical mTORC1 substrate, nor changed the protein levels of mTORC1 core components (Raptor and mTOR) and the CRL4 CSA complex (CSA, DDB1, CUL4A, RBX1) (Fig. 2 a). Interestingly, DDA1 knockdown significantly reduced phosphorylation of 4E-BP1, another mTORC1 target (Fig. 2 a), but conversely, DDA1 overexpression had no detectable impact on S6K1, 4E-BP1 phosphorylation, or the abundance of mTORC1 or CRL4 components (Fig. 2 b). These results suggest that DDA1 is not an upstream regulator of mTORC1 but more likely acts downstream, potentially as a substrate of mTORC1 kinase activity. Due to the lack of commercially available phospho-specific antibodies against DDA1, we employed 4D label-free quantitative phosphoproteomics using next-generation ion mobility mass spectrometry to identify phosphorylation events regulated by mTORC1. We subjected U118-MG cells to three conditions: amino acid starvation, amino acid restimulation, and restimulation in the presence of the mTOR inhibitor Torin1. Using a cutoff of log₂ (fold change) > 2.0 and P < 0.05, amino acid stimulation increased phosphorylation in 994 phosphoproteins compared to starvation, and Torin1 reversed phosphorylation in 1,276 proteins (Fig. 2 c; Supplementary Data 1). Cross-comparison revealed 609 phosphoproteins co-regulated by amino acids and Torin1 (Fig. 2 c). Among these, phosphorylation at serine 33 of DDA1 was strongly induced by amino acid stimulation and suppressed by Torin1. GPS analysis predicted 18 potential phosphorylation sites on DDA1, including Ser33 (Fig. 2 d). To validate these findings, we generated a custom DDA1 phospho-Ser33 specific antibody (AtaGenix). Western blotting confirmed that amino acid restimulation after starvation increased Ser33 phosphorylation, an effect abolished by Torin1 (Fig. 2 e). Activation of mTORC1 is orchestrated not only by the amino acid-Rag GTPase axis but also by the PI3K-AKT-mTORC1 pathway. Thus, to define the upstream inputs, we established stable U118-MG cell lines with CRISPR mediated knockout of either RagA, a core component of the amino acid-sensing branch, or Rheb, the GTPase linking PI3K-AKT signaling to mTORC1 activation. Immunoblot analysis revealed that loss of either RagA or Rheb markedly reduced phosphorylation of the mTORC1 substrate S6K1 (Fig. 2 f), indicating effective pathway inhibition. Phosphorylation at DDA1 Ser33 was also attenuated in both RagA and Rheb deficient cells, further indicating that mTORC1 directly controls DDA1 phosphorylation modulated by both nutrient and growth factor signals in glioma cells (Fig. 2 f). DDA1 appears to have emerged early in evolution; homologs have been identified not only in vertebrates such as Mus musculus and Xenopus tropicalis but also in other established model organisms, including Danio rerio (Fig. 2 g). Potential homologs are also found in higher invertebrates such as Drosophila mojavensis (Fig. 2 g). Remarkably, all these homologs harbor conserved residues that correspond to human Ser33 within structurally analogous regions, suggesting that this phosphorylation site is functionally important and evolutionarily conserved. Together, these findings demonstrate that DDA1 functions downstream of mTORC1 and is directly phosphorylated by mTORC1 at Serine 33. Phosphorylated DDA1 undergoes nuclear translocation. To dissect the functional consequence of the physical interaction between DDA1 and mTORC1, we first analyzed the stoichiometric changes associated with this interaction. Using amino acid stimulation to modulate mTORC1 activity in U118-MG cells transfected with either FLAG-DDA1 or FLAG-Raptor, co-immunoprecipitation assays revealed that mTORC1 activation markedly reduced the interaction between DDA1 and Raptor or RagA and enhanced its association with CRL4 CSA complex components CUL4A, DDB1, and RBX1 (Fig. 3 a). These findings suggest that mTORC1 activity reshapes DDA1-binding stoichiometry, potentially through phosphorylation at serine 33. To test this directly, we generated phospho-deficient (S33A) and phospho-mimetic (S33D) mutants of DDA1 and expressed them in U118-MG cells. Co-immunoprecipitation assays showed that the DDA1 S33D mutant exhibited significantly increased binding to CRL4 CSA components compared to the DDA1 S33A mutant (Fig. 3 b), implicating S33 phosphorylation as a critical switch for CRL4 CSA complex assembly. Given that the CRL4 CSA complex primarily functions in the nucleus 45 , we hypothesized that phosphorylation of DDA1 by mTORC1 may induce its nuclear translocation. As controls to test this, we first examined the subcellular localization of DDB1 and CSA under varying mTORC1 activity states. Immunofluorescence analysis demonstrated that neither amino acid deprivation, re-stimulation, nor Torin1 treatment altered their nuclear localization (Fig. 3 c). In parallel, amino acid stimulation promoted mTOR accumulation at lysosomes, whereas amino acid withdrawal or Torin1 disrupted this lysosomal localization (Fig. 3 d). Focusing on DDA1, we observed that amino acid deprivation or Torin1 suppressed its nuclear localization and that amino acid stimulation led to nearly complete nuclear translocation of DDA1 (Fig. 3 e). To validate these observations biochemically, we performed nuclear-cytoplasmic fractionation followed by immunoblotting. Here, amino acid stimulation markedly increased nuclear DDA1 and p-DDA1 levels, with a concomitant decrease in cytoplasmic DDA1 and a modest rise in cytoplasmic p-DDA1 (Fig. 3 f). Together, these findings support a model in which amino-acid-mTORC1 activation triggers S33 phosphorylation of DDA1, promoting its nuclear translocation and potentially facilitating CRL4 CSA complex formation and function. Phosphorylation of DDA1 promotes CRL4 CSA mediated DNA repair and safeguards cellular viability under genotoxic stress. To delineate the functional consequences of amino-acid-mTORC1-mediated DDA1 phosphorylation in genotoxic signaling, we investigated the role of phosphorylated DDA1 S33 in DNA damage repair. DDA1 has previously been identified as a component of the CRL4 CSA E3 ubiquitin ligase complex, which participates in nucleotide excision repair (NER) of UV-induced DNA lesions 1 . To assess this, functionally we established U118-MG cell lines with stable depletion of DDA1 via lentiviral transduction (sgDDA1) alongside control cells (sgControl) (Fig. 4 a). Immunoblot analysis showed that DDA1 loss did not perturb the expression of core CRL4 CSA components or downstream mTORC1 effector p-S6K (Fig. 4 a). To monitor NER efficiency, we further quantified cyclobutene pyrimidine dimers (CPDs), a hallmark of UV-induced DNA lesions, using ELISA. Here, amino acid restimulation substantially reduced CPDs levels in control cells, but DDA1-deficient cells retained high CPDs burdens despite nutrient repletion, indicating compromised repair capacity (Fig. 4 b). Immunofluorescence staining with CPDs specific monoclonal antibodies corroborated these findings: amino acid stimulation mitigated UV induced CPDs accumulation in control cells, whereas DDA1 knockout cells exhibited significantly elevated CPDs signals, which were only partially alleviated upon amino acid supplementation (Fig. 4 c). These results establish DDA1 phosphorylation as a key determinant of CRL4 CSA mediated repair in response to nutrient signaling. Persistent DNA damage can precipitate apoptosis. in our experiments TUNEL staining revealed that amino acid stimulation suppressed UV induced apoptosis, whereas DDA1 knockout markedly elevated apoptotic DNA fragmentation, which was partially reversed by amino acid re-supply (Fig. 4 d). In parallel, MTT assays demonstrated that amino acid re-stimulation enhanced cell proliferation, while DDA1 depletion impaired proliferative capacity (Fig. 4 e). Notably, treatment with the NEDD8 activating enzyme (NAE) inhibitor MLN4924 strongly inhibited cell growth. However, its suppressive effect was attenuated in DDA1 deficient cells, potentially due to compromised CRL4 CSA complex activity (Fig. 4 e). Colony formation assays further supported these observations: amino acid re-stimulation promoted clonal expansion under both basal and UV-stressed conditions, whereas DDA1 loss diminished overall colony forming potential, though responsiveness to nutrient cues was preserved (Fig. 4 f). These data collectively suggest that DDA1 promotes both DNA repair and survival, thus acting as a critical nexus between nutrient sensing and genotoxic stress response. Finally, we assessed markers of DNA damage (γ-H2A.X) and apoptosis (cleaved PARP1). Immunoblotting showed that amino acid stimulation suppressed both γ-H2A.X and cleaved PARP1 levels, and DDA1 depletion resulted in their pronounced upregulation irrespective of UV treatment (Fig. 4 g). Taken together, all of our findings converge on a model in which amino-acid-mTORC1-dependent phosphorylation of DDA1 enhances CRL4 CSA function to promote DNA repair, suppress apoptosis, and sustain tumor cell proliferation under stress conditions. DDA1 regulates DNA repair and metabolic reprogramming. To elucidate the biological relevance of the amino-acid-mTORC1-DDA1 S33 -DNA damage axis in glioma, we performed transcriptomic analysis to characterize the downstream gene expression changes associated with DDA1 phosphorylation at Ser33 in the context of DNA repair. We conducted RNA sequencing (RNA-seq) in three glioma cell lines (LN229, T98G, and U118-MG) after stable DDA1 knockdown using lentivirus delivered sgRNAs. Total RNA was then extracted and processed for cDNA synthesis, library preparation, and 50 bp-end sequencing using the BGI-seq 500 platform (APTBIO, Shanghai). Raw reads were quality-checked with FastQC, and low-quality reads (≥ 5 ambiguous bases or Phred score < 15) were removed using fastp. Under the threshold of P 1, we identified 42 consistently differentially expressed genes across the three models, including 36 upregulated and 6 downregulated genes (GSE303079) (Fig. 5 a). Gene ontology analysis indicated that many upregulated transcripts were enriched in pathways related to cellular metabolism and growth. Upregulated targets included: CA12, a carbonic anhydrase critical for regulating intracellular and extracellular pH by catalyzing the reversible hydration of CO₂ 46, 47 ; NMRK1, a member of the nucleoside kinase family that converts nicotinamide riboside to NMN in NAD⁺ biosynthesis 48, 49 ; and ENO2, also known as neuron-specific enolase, which catalyzes the final step of glycolysis converting 2-phosphoglycerate to phosphoenolpyruvate 49, 50 . Quantitative reverse transcription PCR (qRT-PCR) validation confirmed significant upregulation of CA12, NMRK1, and ENO2 following DDA1 knockout in all three glioma models (Fig. 5 b), and immunoblot analysis also corroborated these findings at the protein level (Fig. 5 e). Conversely, overexpression of FLAG-tagged DDA1 led to significant downregulation of these genes at both transcript and protein levels (Fig. 5 c, d, and f). Given prior evidence linking DNA damage repair defects to metabolic reprogramming 51 , we propose that DDA1 deficiency impairs DNA repair and induces a stress-adaptive transcriptional response involving CA12, NMRK1, and ENO2. This shift likely supports metabolic flexibility, sustains energy homeostasis, and prevents apoptosis, thereby promoting cell survival under genotoxic stress. To assess the clinical relevance of our findings, we analyzed public transcriptomic datasets from GEO ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE4290 ) that comprised astrocytoma, oligodendroglioma, and GBM specimens. Expression of CA12 was uniformly elevated across all tumor types, whereas ENO2 and NMRK1 levels were frequently lowered (Fig. 5 g). These trends may reflect loss of neuronal identity during mesenchymal or stem-like transitions in glioma, as well as metabolic rewiring that favors NAD⁺ generation via the NAMPT pathway over NMRK1 51, 52 . Hypoxic tumor cores may further drive CA12 upregulation, facilitating extracellular acidification, stromal invasion, and immune evasion 53, 54 . Analysis of the TCGA GBM cohort ( https://portal.gdc.cancer.gov/ ) revealed the same pattern. CA12 was significantly upregulated and ENO2 was downregulated; NMRK1 showed a similar downward trend that did attain our level of statistical significance but remained directionally concordant with the GEO data (Fig. 5 h). To evaluate the clinical significance of these findings, we performed survival analysis using the CGGA dataset (mRNAseq_693) ( https://www.cgga.org.cn/download.jsp ), which showed that low ENO2 expression and high CA12 expression were significantly associated with poor patient prognosis (Fig. 5 i). These results thus support a model in which amino-acid-mTORC1-dependent DDA1 phosphorylation regulates DNA damage repair and orchestrates metabolic reprogramming, revealing a previously unrecognized axis that links genome integrity to metabolic adaptation in glioma. DDA1 is overexpressed in glioma and contributes to tumorigenesis. Enhanced DNA repair capacity and dysregulated metabolism are hallmarks of malignant glioma, contributing both to intrinsic and acquired resistance to standard therapies 55, 56 . As a central regulator of both DNA repair and metabolic homeostasis, mTOR plays a pivotal role in gliomagenesisn 57, 58 . To evaluate mTORC1 activity in glioma as comprehensively as possible, we compared nine human glioma cell lines (LN18, LN229, U87-MG, U118-MG, SHG44, A172, T98G, SF126, SF763) with nonmalignant human astrocytes (HA). Immunoblotting revealed markedly elevated mTORC1 activity in glioma cells compared to HA cells, as evidenced by phosphorylation of downstream targets S6K1 and 4E-BP1 (Fig. 6 a and b). Among these, LN229, U87-MG, U118-MG, A172, and T98G exhibited pronounced mTORC1 activation. Notably, DDA1 and other components of the CRL4 CSA DNA repair complex were upregulated in glioma cells with hyperactive mTORC1 (Fig. 6 c). Amino acid re-stimulation experiments further demonstrated that DDA1 phosphorylation at Ser33 was universally induced in glioma cells in an mTORC1-dependent manner (Fig. 6 d). We also profiled phosphorylation of additional mTORC1 downstream targets, including ULK1 and AMPKα, key sensors of autophagy and energy stress respectively, which exhibited a similar pattern of upregulation, consistent with heightened mTORC1 signaling in GBM (Fig. 6 d). To probe the functional relevance of DDA1 in glioma biology, we also performed CCK-8 proliferation assays in U118-MG cells. Knockout of DDA1 suppressed proliferation, whereas its stable overexpression enhanced growth (Fig. 6 e). Consistent results were obtained in colony formation assays as well, where DDA1 loss impaired clonogenicity and its overexpression markedly increased colony numbers (Fig. 6 f). Furthermore, mTORC1 activation via amino acid supplementation promoted colony formation in control cells but failed to rescue growth in DDA1-deficient cells. Conversely, DDA1 overexpression enhanced colony formation regardless of mTORC1 activation status (Fig. 6 g). These findings indicate that mTORC1-driven DDA1 expression and phosphorylation support glioma growth. To validate these observations in vivo, we established an orthotopic intracranial glioma model. DDA1-knockout U118-MG cells (5 × 10⁵) were stereotactically implanted into the striatum of immunodeficient BALB/c nude mice. MRI performed on day 7 confirmed tumor formation and served as a baseline (Fig. 7 a). Mice were then randomized into control and amino acid-supplemented groups, the latter receiving daily oral administration of a defined amino acid mixture for four weeks. Follow up MRI on day 35 revealed significantly reduced tumor growth in DDA1-deficient mice, whereas amino acid supplementation accelerated tumor progression relative to controls (Fig. 7 b). Immunohistochemical analysis of paraffin embedded brain sections demonstrated elevated γ-H2A.X levels in DDA1 deficient tumors as well, indicative of increased DNA damage, which was moderately attenuated by amino acid supplementation (Fig. 7 c). Finally, clinical relevance was assessed via survival analysis using CGGA datasets (mRNAseq_325 and mRNAseq_693) ( https://www.cgga.org.cn/download.jsp ). High DDA1 expression was significantly associated with poorer patient prognosis (Fig. 7 d). Collectively, our findings identify DDA1 as a novel amino-acid-mTORC1 downstream effector whose phosphorylation enhances its nuclear translocation and function in DNA repair. This signaling axis promotes metabolic adaptation and glioma progression, which constitutes new insight into the crosstalk between mTORC1 signaling, DNA damage responses, and tumor metabolism (Fig. 7 e). Discussion mTORC1 has long been recognized as a central regulator of cellular metabolism, protein synthesis, and growth in response to nutrient and growth factor signals 59, 60 . However, the manner in which mTORC1 signaling directly interfaces with genome maintenance mechanisms has remained an underexplored frontier. Although previous studies have hinted at a possible link between mTORC1 and DNA damage responses, such as through indirect regulation of FANCD2 or modulation of homologous recombination repair 61 , the precise molecular mediators have remained elusive. Our identification of DDA1 as a direct phosphorylation target of amino-acid-mTORC1 that coordinates DNA repair adds a fundamentally new layer to the canonical amino-acid-mTORC1 signaling paradigm. This discovery integrates the two seemingly distinct processes of nutrient sensing and genome integrity into a unified molecular framework. The phosphorylation-dependent nuclear translocation of DDA1 highlights how lysosome associated amino-acid-mTORC1 signaling extends beyond its classical cytoplasmic functions to exert nuclear control over DNA repair fidelity. Notably, the involvement of DDA1 in modulating the CRL4 CSA complex, a key player in nucleotide excision repair (NER) 1, 62 , positions DDA1 as a pivotal nexus between nutrient-responsive signaling and chromatin-associated DNA repair machinery. Our findings also resonate with emerging concepts that DNA repair is tightly coupled to metabolic state. Recent work has shown that efficient DNA repair requires adequate nucleotide pools, redox balance, and ATP availability 63, 64 . Consistent with this, the compensatory upregulation of metabolic genes such as ENO2, CA12, and NMRK1 in DDA1-deficient glioma cells may reflect a tumor intrinsic stress response aimed at sustaining bioenergetic and biosynthetic demands under persistent genotoxic stress. However, this adaptation is ultimately insufficient, as evidenced by increased apoptosis and impaired tumor growth upon DDA1 loss. The amino-acid-mTORC1-DDA1 axis may thus represent a broader mechanism applicable beyond GBM. For example, DDA1 has been implicated in protein degradation and cell cycle control in other cancer types 4, 9, 65 , suggesting that phosphorylation-dependent functional switching of DDA1 could be a generalizable regulatory strategy in cancer biology. Whether this mechanism extends to other DNA repair pathways, such as homologous recombination or base excision repair, remains an open question worthy of further investigation. Clinically, our results suggest that DDA1 is overexpressed in glioma and that its elevated expression correlates with poor prognosis in patient datasets. In vitro and in vivo models both showed that DDA1 loss significantly impairs glioma cell proliferation and tumor growth. Notably, amino acid supplementation enhanced mTORC1 activation and DDA1 phosphorylation in glioma cells, promoting tumor progression, whereas DDA1 knockout rendered tumors less responsive to nutrient cues. These findings underscore the role of DDA1 as a critical downstream effector of mTORC1 that integrates extracellular nutrient availability with nuclear DNA repair machinery to promote gliomagenesis. Our results provide important implications for therapeutic intervention. Specifically, the amino-acid-mTORC1-DDA1 axis represents a potential vulnerability in glioma that may be exploitable using strategies that simultaneously target mTORC1 signaling and DNA repair mechanisms. Given the reliance of DDA1 function on mTORC1 activity and nutrient availability, metabolic interventions or inhibitors of mTORC1 may sensitize glioma cells to DNA damaging agents by disrupting this axis. Moreover, pharmacologic inhibition of CRL4 E3 ligase activity or specific blockade of DDA1 phosphorylation may offer additional routes for targeted therapy. In conclusion, our work establishes DDA1 phosphorylation as a key molecular event that connects nutrient responsive amino-acid-mTORC1 signaling to DNA repair and tumor growth. These findings not only redefine the functional landscape of amino-acid-mTORC1 but also provide a conceptual framework for targeting nutrient-DNA repair crosstalk in GBM. The amino-acid-mTORC1-DDA1 axis thus emerges as a promising therapeutic target that warrants further exploration in both preclinical models and clinical settings. Declarations Data availability declaration The RNA-seq data generated in this study have been deposited in the NCBI Gene Expression Omnibus (GEO) under accession code GSE303079 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE303079). 4D-Labelfree quantitative phosphoproteomics analysis data and mass spectrometry data are provided in Supplementary Data 1. Gene expression analysis of the target proteins in GBM was performed using transcriptomic data from The Cancer Genome Atlas (TCGA) GBM cohort (https://portal.gdc.cancer.gov/). Differential expression across astrocytoma, oligodendroglioma, and GBM specimens was assessed using the GEO dataset GSE4290 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE4290). Survival analysis based on target gene expression was conducted using the CGGA cohorts (mRNAseq_325 and mRNAseq_693) (https://www.cgga.org.cn/download.jsp). All data generated or analyzed during this study are included in this published article (and its supplementary information files), and the reporting summary and editorial checklist for this article are available as a Supplementary File. Source data are provided with the paper. Funding declaration This work was supported by a grant (7244374 to X.C.) from the Beijing Natural Science Foundation of China, and grants (GZC20230307 to X.C.) from the National Postdoctoral Program for Innovative Talents of China, and grants (2060204 to X.P.) from the State Key Laboratory Special Fund, and grants (2023-I2M-2-001 to X.P.) from the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences. Author contribution declaration X.C. and X.P. conceived the project and designed the experiments; Z.W. and A.Y. performed experiments; X.C. analyzed data; Y.L., R.Z., L.L., D.X., R.L., X.Z., B.Y., and W.H. provided technical assistance; X.C. and X.P. wrote the manuscript. Consent to Publish declarations We, the authors, hereby declare that this manuscript is original, has not been published elsewhere, and is not under consideration by any other journal. Upon acceptance, we agree to grant the Publisher the right to publish, reproduce, and distribute this work in all forms and media. Ethics statement All the animal studies were approved by the Institutional Animal Care Use & Welfare Committee of the Center for Experimental Animal Research (ACUC-A01-2022-059, ACUC-A02-2025-005). Competing interest declaration The authors declare no competing interests. Acknowledgments The authors thank AiMi Academic Services (www.aimieditor.com) for English language editing and review services. 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Methods Antibodies and reagents Antibodies used included the following: αRagA (4357, 1:1000 for western blotting (WB)), αRagC (3360,1:1000 for WB), αRagD (4470,1:1000 for WB), αmTOR (2972 and 2983, 1:1000 for WB and 1:100 for Immunofluorescence (IF)), αRaptor (2280, 1:500 for WB), α4E-BP1 (9644, 1:1000 for WB), αp-4E-BP1 (2855, 1:1000 for WB), αS6K1 (9202, 1:1000 for WB), αp-S6K1 (9205, 1:500 for WB), αWDR24 (67470, 1:1000 for WB), αp18 (8975, 1:1000 for WB and 1:100 for IF), αp14 (8145, 1:1000 for WB), αFLAG (14793, 1:10000 for WB), αULK1 (8054, 1:1000 for WB), αp-ULK1 (14202, 1:1000 for WB); αAMPKα (2532, 1:1000 for WB); αp-AMPKα (2535, 1:1000 for WB); αNMRK1 (29786, 1:1000 for WB), αCA12 (5864, 1:1000 for WB), and αENO2 (24330, 1:1000 for WB) from Cell Signaling; αmTOR (ab32028, 1:100 for IF), αLamp2 (ab25631, 1:100 for IF), αDDB1 (ab109027, 1:1000 for WB and 1:100 for IF), αTubulin (ab6160, 1:1000 for WB), αLaminA/C (ab108595, 1:1000 for WB), αRBX1 (ab221548 1:1000 for WB), αRheb (ab316265, 1:1000 for WB), αCUL4A (ab92554, 1:1000 for WB), αCSA (ab137033, 1:100 for WB and 1:100 for IF), αPARP1 (ab191217, 1:1000 for WB), αCleaved PARP1 (ab32064, 1:100 for WB), αH2A.X (ab229914, 1:1000 for WB and 1:100 forimmunohistochemistry (IHC)), and αγ-H2A.X (ab81299, 1:1000 for WB and 1:100 for IHC) from Abcam; αDDA1 (YT7033, 1:1000 for WB, 1:100 for IHC, and 1:100 for IF) from Immunoway; αDDA1 (14995-1-AP, 1:1000 for WB, 1:100 for IHC, and 1:100 for IF) from Proteintech; Customized αDDA1 S33 (1:500 for WB) from AtaGenix; αβ-actin (AC004, 1:10000 for WB), HRP Goat Anti-Rabbit IgG (AS014, 1:5000 for WB), and HRP Goat Anti-Mouse IgG (AS003, 1:5000 for WB) from ABclonal. Control siRNA and siRNA for DDA1, as well as sgRNAs for DDA1, RagA, and Rheb were synthesized by Wuhan Saiweizhen Biotechnology. Torin1 (475991), Anti-FLAG M2 (A2220) affinity gel, and 3 x FLAG peptide (F3290) were sourced from Sigma-Aldrich, and MLN4924 (LKT-M4454-M001) came from ENZO. Protease inhibitor cocktail was from Roche Applied Science. RPMI 1640 Medium Modified w/o Amino acids and Glucose (R9010-01) was sourced from USBiological. Cell culture The cell lines used were obtained from the American Type Culture Collection (ATCC). U118-MG, LN18, LN229, A172, SHG44 cells were maintained in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10% fetal bovine serum (FBS) T98G, U87-MG, and SF126 cells were maintained in Minimum Essential Medium (MEM) and 10% FBS; SF762 cells were maintained in Roswell Park Memorial Institute Medium (RPMI-1640) with 20% FBS; and HA cells were maintained in Astrocyte Medium (1801, ScienCell). All cells were cultured in a humidified incubator equilibrated with 5% CO 2 at 37ºC. Transfection For transfection of cDNA expression constructs, 2-2.5 million cells were seeded in 15-cm dishes and transfected at 24 h after seeding. Experiments were done 36-48 h after transfection. siRNA Transfections were carried out using Lipofectamine® RNAiMAX Reagent (Invitrogen, Carlsbad, CA) according to the manufacturer’s instructions, and the final concentration of siRNA used for each six-well plate was 50 nM. Each experiment was performed in triplicate and repeated at least three times. For RNAi experiment, at least three independent siRNA sequences were tested for each gene, and the one with the best efficiency was chosen. The siRNA sequences were as follows: Control siRNA: UUCUCCGAACGUGUCACGU; DDA1 siRNA-1: GCGCUACCUGCAUCAGCAATT; DDA1 siRNA-2: GAAGAGAGACCAGGAGCAATT; and DDA1 siRNA-3: GGAGCAAGUGGAGCUGGAATT. Immunoprecipitation and western blotting Cellular extracts were prepared by incubating approximately 5 x 10 8 cells in lysis buffer (50 mM Tris-HCl, pH 8.0, 150 mM NaCl, 0.5% NP40, and 1 tablet of EDTA-free protease inhibitor (Roche) (per 25 ml buffer)) for 30 min at 4ºC. This was followed by centrifugation at 16,000 x g for 15 min at 4ºC. For immunoprecipitation, 500 μg of protein was incubated with specific antibodies (2-3 μg) for 12 h at 4ºC with constant rotation; 60 μl of 50% protein G agarose beads was then added and the incubation was continued for an additional 2 h. Next, beads were washed 5 times using the lysis buffer. The precipitated proteins were eluted from the beads by resuspending them in 2 x SDS-PAGE loading buffer and boiling for 10 min, and the resultant materials from immunoprecipitation or cell lysates were resolved using 8%-12% SDS-PAGE gels prior to transfer onto acetate cellulose membranes. For anti-FLAG immunoprecipitation, anti-FLAG M2 Affinity Gel (Sigma) was washed with lysis buffer three times then resuspended to a ratio of 50:50 affinity gel to lysis buffer before 25 μl of a well-mixed slurry was added to cleared lysates and incubated at 4°C in a shaker for 90-120 minutes. Immunoprecipitated proteins were denatured by the addition of 2 x SDS-PAGE loading buffer and boiled for 10 minutes. Denatured samples were resolved by 8%-12% SDS-PAGE, and analyzed by immunoblotting. For western blotting analysis, membranes were incubated with appropriate antibodies for overnight at 4ºC followed by incubation with a secondary antibody. Immunoreactive bands were visualized using Luminal reagent (Santa Cruz Biotechnology) according to the manufacturer’s recommendation. Mass spectrometry U118-MG cells that expressed FLAG-DDA1 or FLAG-Raptor were washed twice with cold PBS, scraped, and collected by centrifugation at 800 x g for 5 minutes. Cellular extracts were then prepared by incubating the cells in lysis buffer containing protease inhibitor cocktail (Roche), and anti-FLAG immunoaffinity columns were prepared using anti-FLAG M2 affinity gel (Sigma) following the manufacturer’s suggestions. Cell lysates were obtained from approximately 5 x 10 8 cells and applied to an equilibrated FLAG column of 1-mL bed volume to allow for adsorption of the protein complex to the column resin. After binding, the column was washed with cold PBS plus 0.1% Nonidet P-40 prior to application of 3x FLAG peptides to elute FLAG protein complex as described by the vendor and subjected to LC/MS-MS sequencing. The eluates were then directly entered Q-Exactive MS (Thermo Fisher Scientific, Waltham, MA, USA), set in positive ion mode and data-dependent manner with full MS scan from 350-2000 m/z, full scan resolution at 70,000, MS/MS scan resolution at 17,500. MS/MS scan with minimum signal threshold 1E+5, and isolation width at 2 Da. Peptide identification and quantification was carried out with Mascot software Revision 2.3.01 using the TAIR database search algorithm and the integrated false discovery rate (FDR) analysis function. 4D-Labelfree quantitative phosphoproteomics analysis U118-MG cells were subjected to three treatment conditions to modulate mTORC1 activity: (1) amino acid starvation 1 h, (2) amino acid stimulation 30 min, and (3) amino acid stimulation combined with the mTOR inhibitor Torin1 (250 nM) pretreated 1 h. Cells were lysed in 8 M urea lysis buffer containing protease and phosphatase inhibitors. Proteins were reduced, alkylated, and digested with trypsin overnight, and phosphopeptides were enriched using Fe-NTA affinity chromatography (Thermo Scientific) followed by LC-MS/MS analysis using a timsTOF Pro mass spectrometer (Bruker). Raw data were analyzed using MaxQuant with phosphorylation (S/T/Y) as variable modifications, from which phosphopeptides with a localization probability >0.75 were included for quantification. Differential phosphorylation was determined using P 2 as significance thresholds. Pull-down assays GST-fused constructs were expressed in BL21 Escherichia coli , and in vitro transcription and translation experiments were carried out with rabbit reticulocyte lysate (TNT systems, Promega) according to the manufacturer’s recommendations. In GST pull-down assays, about 5 mg of the appropriate GST fusion proteins with 30 ml of glutathione-Sepharose beads were incubated with 5-8 μl of in vitro transcribed/translated products in binding buffer (75 mM NaCl, 50 mM HEPES, pH 7.9) at 4°C for 2 h in the presence of the protease inhibitor mixture. The beads were then washed 5 times with binding buffer, resuspended in 30 ml of 2 x SDS-PAGE loading buffer, and subjected to western blotting. Fluorescence confocal microscopy U118-MG cells grown on 6-well chamber slides were washed with PBS, fixed in 4% paraformaldehyde, permeabilized with 0.2% Triton X-100, blocked with 0.8% BSA, and incubated with appropriate primary antibodies followed by addition of Alexa Fluor™ 488/568 donkey secondary antibodies (Invitrogen). DAPI (Sigma) was included in the final wash to stain the nuclei, and images were visualized with an Olympus inverted microscope equipped with a charge coupled camera. Immunohistochemistry (IHC) Paraffin sections (5 μm) were deparaffinized, rehydrated, and subjected to antigen retrieval in citrate buffer (pH 6.0). After blocking with 5% BSA, sections were incubated overnight at 4ºC with αγ-H2A.X, αH2A.X, or αDDA1 antibody, followed by HRP-conjugated secondary antibody and DAB chromogenic detection. Slides were counterstained with hematoxylin and imaged using a Leica DM6 microscope. RNA-seq Total RNA samples were extracted from U118-MG, T98G, or LN229 cells and subjected to deep sequencing by BGI (APTBIO, Shanghai) using a BGI500 sequencer with single-end 50-bp reads. Raw data were preprocessed through fastp to remove adaptors and low-quality reads with at the default parameters. Clean reads were aligned to GRCh38/hg38 reference genome through STAR, an ultrafast universal RNA-seq aligner. Raw read count mapped to every gene that obtained via HTSeq-Count tool was used as expression level, and the DESeq2 R Bioconductor package was used for screening differential expression genes with the threshold of P 1. Cell viability/proliferation assay For cell proliferation assays, U118-MG cells with DDA1 knockout or stable FLAG-DDA1 expression were seeded into 96-well plates with an equal volume of medium. After cell treatment, 10 μl CCK-8 solution was added according to the manufacturer’s protocol. Plates were incubated at 37ºC for 2 h and cell viability was determined by measuring the absorbance at 450 nm wavelength. Each experiment was performed in triplicate and repeated at least three times. qPCR Total cellular RNA samples were isolated with TRIzol reagent (Invitrogen) and used for the first strand cDNA synthesis with a Reverse Transcription System (Roche). Quantitation of all gene transcripts was done by real time RT-PCR (qPCR) using a Power SYBR Green PCR Master Mix and Roche LightCycler®480 II sequence detection system. The qPCR primers sequences used were: NMRK1: TCAGTGGTGTGACAAACAGTG (F), GCACATCGTACTGCAAAAATCC (R); ENO2: AGCCTCTACGGGCATCTATGA (F), TTCTCAGTCCCATCCAACTCC (R); CA12: AGTGAACGGTTCCAAGTGGAC (F), CCACACGACGGGTACTTCT (R); DDA1: TTTAGTCGATTTCACGCGGAC (F), ATCTGTTCAGACGGGTACTCG (R); and β-actin: CATGTACGTTGCTATCCAGGC (F), CTCCTTAATGTCACGCACGAT (R). Lentiviral production and infection Recombinant lentiviruses expressing FLAG-Vector and FLAG-DDA1 were constructed by Wuhan Saiweizhen Biotechnology. Concentrated amounts of these viruses were used to infect 5 x 10 5 cells in a 60-mm dish with 8 μg/ml polybrene. Infected U118-MG cells were then subjected to sorting target expression. CRISPR-Cas9-mediated gene knockout Stable knockout of DDA1, RagA, or Rheb in U118-MG cells was achieved using a two-vector lentiviral system. U118-MG cells were first transduced with lentivirus encoding Streptococcus pyogenes Cas9 in the presence of 8 μg/mL polybrene (Sigma-Aldrich), and 48 hours after infection, cells were subjected to selection with 10 μg/mL blasticidin for 5 days to establish stable Cas9-expressing populations. Subsequently, the cells were transduced with lentivirus expressing gene-specific sgRNAs targeting DDA1, RagA, or Rheb. After 48 h, transduced cells were selected with 1 μg/mL puromycin for 4 days. To isolate monoclonal knockout lines, puromycin-selected cells were subjected to limiting dilution in 96-well plates at a density of 0.5 cells/well. After 14 days, individual colonies were expanded, and genomic DNA and protein lysates were collected for Sanger sequencing and immunoblotting to confirm successful gene disruption. Control cell lines were generated using nontargeting sgRNA constructs and underwent identical procedures to those used for knockout generation. The sgRNAs sequences used were: sgDDA1-1: TTCCTGGGACTGGGAGGAATTGG; sgDDA1-2: CAACCCTCCTGCAGAACCGACGG; sgDDA1-3: CTGTTCAGACGGGTACTCGCGGG. sgRagA-1: GGAGTGTTCCACGTCAATGGTGG; sgRagA-2: GTTCCCTAGGAATCGGACGTGGG; sgRagA-3: GTGCTGAACCTGTGGGACTGTGG. sgRheb-1: CGGTTGATGTGGTTGGGCCGGGG; sgRheb-2: TCCCGGAAGATCGCGATCCTGGG; and sgRheb-3: GCTACCGGTCTGTGGGTGAGTGG. CPD quantification To evaluate NER efficiency, U118-MG cells were pretreated by amino acid starvation for 1 h, followed by re-stimulation with MEM amino acids 30 min in the presence or absence of UV-C exposure (20 J/m²). Cyclobutane-pyrimidine dimers (CPDs) were quantified using a CPD-specific ELISA kit (Cosmo Bio) following the manufacturer’s protocol, and genomic DNA was extracted (Qiagen DNeasy), denatured, and immobilized in 96-well plates for antibody-based detection. Immunofluorescence staining for CPDs Cells were grown on coverslips, UV-irradiated (20 J/m²), and treated as above. Fixation was performed with 4% paraformaldehyde (15 min), followed by DNA denaturation with 2 N HCl (30 min), neutralization (Tris-HCl pH 8.5), and blocking (5% BSA). CPDs were detected using monoclonal antibodies (Cosmo Bio) and Alexa Fluor-conjugated secondary antibodies, and Nuclei were counterstained with DAPI. Images were acquired using a Zeiss LSM980 confocal microscope. TUNEL assay Apoptotic DNA fragmentation was assessed using the In Situ Cell Death Detection Kit (Roche). Cells were UV-irradiated, fixed, permeabilized with 0.1% Triton X-100, and incubated with TUNEL reaction mixture for 1 h at 37ºC. Fluorescence was visualized using a confocal microscope and quantified with ImageJ. MTT assay Cell proliferation was measured using the MTT assay (Sigma). Cells were seeded in 96-well plates and treated as indicated. After 48 h, 0.5 mg/mL MTT solution was added (4 h), followed by solubilization in DMSO. Absorbance at 570 nm was recorded using a plate reader. Colony formation assay U118-MG cells were maintained in culture media in 6-well plate for 10 days, fixed with 4% paraformaldehyde, and then stained with crystal violet. Each experiment was performed in triplicate and repeated at least three times. Bioinformatics Transcriptomic and clinical survival data from the Chinese Glioma Genome Atlas (CGGA) cohorts (mRNAseq_325 and mRNAseq_693) were obtained from the CGGA portal (https://www.cgga.org.cn/download.jsp). Gene expression analysis in glioma was further validated using publicly available RNA-seq data from The Cancer Genome Atlas (TCGA) GBM cohort (https://portal.gdc.cancer.gov/). In addition, the GEO dataset GSE4290 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE4290), comprising astrocytoma, oligodendroglioma, and GBM specimens, was used to assess differential gene expression across glioma subtypes. Statistical analysis Data analysis was performed on the averages of biologically triplicate experimental results. Unpaired, two-tailed Student’s t -tests were used for 2-group comparisons, and ANOVA with Bonferroni’s correction was used to compare multiple groups. A P -value of less than 0.05 was considered to indicate statistically significant test results for all tests. All statistical results were determined using Prism 10 software, and variations within each group and the assumptions of the tests were checked prior to analysis. Additional Declarations There is no duality of interest Supplementary Files SupplementaryData1.xlsx Supplementary Data 1 SourceData.xlsx Source Data Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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10:14:45","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":155325,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7717041/v1/81e9421462260ac6f4b75503.html"},{"id":93924292,"identity":"6befd312-f868-4bb9-8501-7ae43b03eee6","added_by":"auto","created_at":"2025-10-20 10:14:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":604024,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDDA1 forms a physical complex with components of mTORC1 in glioma cells. (a and b)\u003c/strong\u003eImmunopurification and mass spectrometry analysis of DDA1- or Raptor-associated proteins in U118-MG cells. Cellular extracts from U118-MG cells expressing FLAG-DDA1 or FLAG-Raptor were subjected to affinity purification with an anti-FLAG affinity column and eluted with excess FLAG peptides. The eluates were retrieved and analyzed by mass spectrometry. \u003cstrong\u003e(c and d) \u003c/strong\u003eU118-MG cells were transfected with FLAG-DDA1 or FLAG-Vector. Cellular lysates were immunoprecipitated with anti-FLAG followed by immunoblotting with antibodies against the indicated proteins. Each experiment was repeated three times with similar results. \u003cstrong\u003e(e)\u003c/strong\u003e U118-MG cells were transfected with FLAG-Raptor or FLAG-Vector. Cellular lysates were immunoprecipitated with anti-FLAG followed by immunoblotting with antibodies against the indicated proteins. Each experiment was repeated three times with similar results.\u003cstrong\u003e (f)\u003c/strong\u003e Confocal immunofluorescence showed that DDA1 (green) and mTOR (green) co-localize with the lysosomal marker Lamp2 (red) in U118-MG cells. Nucleus (blue). Scale bar: 10 μm. Each experiment was repeated three times with similar results. \u003cstrong\u003e(g) \u003c/strong\u003eGST pull-down assays with GST-fused DDA1, RagA, RagC, Raptor, or CSA and \u003cem\u003ein vitro\u003c/em\u003e transcribed/translated proteins as indicated. Each experiment was repeated three times with similar results. \u003cstrong\u003e(h) \u003c/strong\u003eAlphaFold3 structural prediction showed extensive contact interfaces between DDA1 and Raptor, supporting a direct physical interaction.\u003c/p\u003e","description":"","filename":"Figures1.png","url":"https://assets-eu.researchsquare.com/files/rs-7717041/v1/f4da1c86b5688bbf34c66d45.png"},{"id":93924293,"identity":"b6bdb227-dc82-4405-a2b3-ef75adcbfb99","added_by":"auto","created_at":"2025-10-20 10:14:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":942075,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDDA1 is phosphorylated by mTORC1 at Ser33 in a nutrient- and growth-factor-dependent manner. (a) \u003c/strong\u003eU118-MG cells were treated with DDA1 siRNA for western blotting analysis of the phosphorylation or expression level of the indicated proteins. Each experiment was repeated three times with similar results. \u003cstrong\u003e(b)\u003c/strong\u003e U118-MG cells were transfected with FLAG-Vector or FLAG-DDA1 for western blotting analysis of the phosphorylation or expression level of the indicated proteins. Each experiment was repeated three times with similar results. \u003cstrong\u003e(c) \u003c/strong\u003eU118-MG cells were starved of amino acids for 1 h and replenished with amino acids for 30 min in the presence or absence of the mTOR inhibitor Torin1 (250 nM) for 4D-Labelfree quantitative phosphoproteomics analysis. \u003cstrong\u003e(d) \u003c/strong\u003eGPS kinase analysis predicted 18 phosphorylation sites on DDA1, highlighting Ser33. \u003cstrong\u003e(e) \u003c/strong\u003eU118-MG cells were starved of amino acids for 1 h and replenished with amino acids for 30 min in the presence or absence of the mTOR inhibitor Torin1 (250 nM) for western blotting analysis of the level or phosphorylation of the custom phospho-specific antibody DDA1\u003csup\u003eS33\u003c/sup\u003e. Each experiment was repeated three times with similar results. \u003cstrong\u003e(f)\u003c/strong\u003e U118-MG cells were knocked out RagA or Rheb with CRISPR sgRNAs for western blotting analysis of the level or phosphorylation of the indicated proteins. Each experiment was repeated three times with similar results. \u003cstrong\u003e(g)\u003c/strong\u003e Evolutionary analysis revealed that the DDA1\u003csup\u003eS33\u003c/sup\u003e residue is conserved across vertebrates and invertebrates, suggesting functional importance.\u003c/p\u003e","description":"","filename":"Figures2.png","url":"https://assets-eu.researchsquare.com/files/rs-7717041/v1/e15a2fa1d4f892b9e7ab0aec.png"},{"id":93925371,"identity":"3a09d0da-a839-4e85-a081-225856abf323","added_by":"auto","created_at":"2025-10-20 10:30:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1129397,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhosphorylation at Ser33 controls DDA1 nuclear translocation and CRL4\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eCSA\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e binding. (a)\u003c/strong\u003e U118-MG cells were transfected with FLAG-Vector, FLAG-DDA1 or FLAG-Raptor, starved of amino acids for 1 h, and replenished with amino acids for 30 min. Cellular lysates were immunoprecipitated with anti-FLAG followed by immunoblotting with antibodies against the indicated proteins. Each experiment was repeated three times with similar results. \u003cstrong\u003e(b)\u003c/strong\u003e U118-MG cells were transfected with FLAG-Vector, FLAG-DDA1, FLAG-DDA1\u003csup\u003eS33A\u003c/sup\u003e, or FLAG-DDA1\u003csup\u003eS33D\u003c/sup\u003e. Cellular lysates were immunoprecipitated with anti-FLAG followed by immunoblotting with antibodies against the indicated proteins. Each experiment was repeated three times with similar results. \u003cstrong\u003e(c) \u003c/strong\u003eU118-MG cells were starved of amino acids for 1 h and replenished with amino acids for 30 min in the presence or absence of the mTOR inhibitor Torin1 (250 nM) by immunofluorescent staining for DDB1 (green) or CSA (green), Lamp2 (red), and nucleus (blue). Scale bar: 10 μm. \u003cstrong\u003e(d and e)\u003c/strong\u003e U118-MG cells were starved of amino acids for 1 h and replenished with amino acids for 30 min in the presence or absence of the mTOR inhibitor Torin1 (250 nM) by immunofluorescent staining for mTOR (green) or DDA1 (green), Lamp2 (red), and nucleus (blue). Scale bar: 10 μm. \u003cstrong\u003e(f) \u003c/strong\u003eU118-MG cells were starved of amino acids for 1 h and replenished with amino acids for 30 min in the presence or absence of the mTOR inhibitor Torin1 (250 nM) by Nuclear-cytoplasmic fractionation for western blotting analysis of the phosphorylation or expression level of the indicated proteins. Each experiment was repeated three times with similar results.\u003c/p\u003e","description":"","filename":"Figures3.png","url":"https://assets-eu.researchsquare.com/files/rs-7717041/v1/61ae7cf8d4c55905a652c0c8.png"},{"id":93924298,"identity":"6912e5e6-ac40-429d-aaa1-18ccfd3a3b06","added_by":"auto","created_at":"2025-10-20 10:14:45","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":612906,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDDA1 phosphorylation enhances CRL4\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eCSA\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e-mediated DNA repair and protects glioma cells from genotoxic damage. (a)\u003c/strong\u003e U118-MG cells were knocked out DDA1 with CRISPR sgRNAs for western blotting analysis of the level or phosphorylation of the indicated proteins. Each experiment was repeated three times with similar results. \u003cstrong\u003e(b)\u003c/strong\u003e U118-MG cells were knocked out DDA1 with CRISPR sgRNAs, starved of amino acids for 1 h, and replenished with amino acids for 30 min for the measurement of cyclobutane pyrimidine dimer (CPD) production by ELISA. Each bar represents the mean ± SD for biologically triplicate experiments. \u003cem\u003eP\u003c/em\u003e values were calculated using two-tailed unpaired Student’s \u003cem\u003et\u003c/em\u003e-tests (*\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05,\u003cem\u003e \u003c/em\u003e***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). \u003cstrong\u003e(c)\u003c/strong\u003e U118-MG cells were knocked out DDA1 with CRISPR sgRNAs, starved of amino acids for 1 h, and replenished with amino acids for 30 min in the presence of UV-C for the measurement of cyclobutane pyrimidine dimer (CPD) production by immunofluorescence. CPD (green). Scale bar: 10 μm. Each experiment was repeated three times with similar results. \u003cstrong\u003e(d) \u003c/strong\u003eU118-MG cells were knocked out DDA1 with CRISPR sgRNAs, starved of amino acids for 1 h, and replenished with amino acids for 30 min in the presence of UV-C for TUNEL staining. TdT (green). Scale bar: 10 μm. Each experiment was repeated three times with similar results. \u003cstrong\u003e(e)\u003c/strong\u003e U118-MG cells were knocked out DDA1 with CRISPR sgRNAs, starved of amino acids for 1 h, and replenished with amino acids for 30 min in the presence or absence of the NEDD8 inhibitor MLN4924 (500 nM) for MTT assays. Each bar represents the mean ± SD for biologically triplicate experiments. \u003cem\u003eP\u003c/em\u003e values were calculated using one-way ANOVA (*\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). \u003cstrong\u003e(f)\u003c/strong\u003e U118-MG cells were knocked out DDA1 with CRISPR sgRNAs, treated with amino acids and UV-C and cultured for 10 days before staining with crystal violet for colony formation assays. Representative images from biologically triplicate experiments are shown. \u003cstrong\u003e(g) \u003c/strong\u003eU118-MG cells were knocked out DDA1 with CRISPR sgRNAs, starved of amino acids for 1 h, and replenished with amino acids for 30 min in the presence or absence of UV-C for western blotting analysis of the level or phosphorylation of the indicated proteins. Each experiment was repeated three times with similar results.\u003c/p\u003e","description":"","filename":"Figures4.png","url":"https://assets-eu.researchsquare.com/files/rs-7717041/v1/e411bf8f81cba46ba1c232f4.png"},{"id":93924669,"identity":"01a4cb0f-5e18-463a-bf77-5949bdb5f53d","added_by":"auto","created_at":"2025-10-20 10:22:45","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":429173,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTranscriptomic profiling links DDA1 loss to metabolic gene reprogramming during DNA damage. (a) \u003c/strong\u003eU118-MG, T98G, and LN229 cells were knocked out DDA1 with CRISPR sgRNAs. The Venn diagram depicts the genes cross-analyzed from the three sets of RNA-seq experiments (GSE303079). \u003cstrong\u003e(b)\u003c/strong\u003e qPCR measurement of the expression of the indicated genes selected from RNA-seq results in U118-MG, T98G, and LN229 cells knocked out DDA1 with CRISPR sgRNAs. Each bar represents the mean ± SD for biologically triplicate experiments. \u003cem\u003eP\u003c/em\u003e values were calculated using two-tailed unpaired Student’s \u003cem\u003et\u003c/em\u003e-tests (**\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.01,\u003cem\u003e \u003c/em\u003e***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). \u003cstrong\u003e(c)\u003c/strong\u003eqPCR measurement of the expression of the indicated genes selected from RNA-seq results in U118-MG, T98G, and LN229 cells infected with lentiviruses carrying FLAG-Vector or FLAG-DDA1. Each bar represents the mean ± SD for biologically triplicate experiments. \u003cem\u003eP\u003c/em\u003e values were calculated using two-tailed unpaired Student’s \u003cem\u003et\u003c/em\u003e-tests (**\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.01,\u003cem\u003e \u003c/em\u003e***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). \u003cstrong\u003e(d)\u003c/strong\u003e U118-MG cells were infected with lentiviruses carrying FLAG-Vector or FLAG-DDA1 for western blotting analysis of the level or phosphorylation of the indicated proteins. Each experiment was repeated three times with similar results. \u003cstrong\u003e(e) \u003c/strong\u003eU118-MG, T98G, and LN229 cells were knocked out DDA1 with CRISPR sgRNAs for western blotting analysis of the level of the indicated proteins. Each experiment was repeated three times with similar results. \u003cstrong\u003e(f) \u003c/strong\u003eU118-MG, T98G, and LN229 cells were infected with lentiviruses carrying FLAG-Vector or FLAG-DDA1 for western blotting analysis of the level of the indicated proteins. Each experiment was repeated three times with similar results. \u003cstrong\u003e(g)\u003c/strong\u003e Gene expression analysis was performed using the GEO dataset (GSE4290), which includes astrocytoma, oligodendroglioma, and glioblastoma specimens. Spearman correlation coefficients and \u003cem\u003eP \u003c/em\u003evalues were calculated using two-sided permutation tests. \u003cstrong\u003e(h)\u003c/strong\u003e Independent validation was conducted using the TCGA GBM transcriptomic dataset, where Spearman correlation coefficients and \u003cem\u003eP \u003c/em\u003evalues were again calculated using two-sided permutation tests. \u003cstrong\u003e(i)\u003c/strong\u003e Survival analysis was performed based on the CGGA dataset (mRNAseq_693) to evaluate the association between gene expression and patient prognosis.\u003cem\u003e P \u003c/em\u003evalues were calculated using the log-rank test.\u003c/p\u003e","description":"","filename":"Figures5.png","url":"https://assets-eu.researchsquare.com/files/rs-7717041/v1/f9701b86c1d2c45d5bacac19.png"},{"id":93924670,"identity":"12107643-d5eb-4c8e-a56d-0e222bcc2081","added_by":"auto","created_at":"2025-10-20 10:22:45","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":900884,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDDA1 promotes glioma cell proliferation and mediates mTORC1-stimulated tumor growth. (a)\u003c/strong\u003eImmunoblotting showing the level or phosphorylation of the indicated proteins in nonmalignant astrocyte HA and different glioma cells. Each experiment was repeated three times with similar results. \u003cstrong\u003e(b) \u003c/strong\u003eNonmalignant astrocyte HA and different glioma cells were starved of amino acids for 1 h and replenished with amino acids for 30 min for western blotting analysis of the level or phosphorylation of the indicated proteins. Each experiment was repeated three times with similar results.\u003cstrong\u003e (c) \u003c/strong\u003eImmunoblotting showed the level of the indicated proteins in nonmalignant astrocyte HA and different glioma cells U118-MG, T98G, and LN229. Each experiment was repeated three times with similar results. \u003cstrong\u003e(d)\u003c/strong\u003e Nonmalignant astrocyte HA and different glioma cells U118-MG, T98G, and LN229 were starved of amino acids for 1 h and replenished with amino acids for 30 min for western blotting analysis of the level or phosphorylation of the indicated proteins. Each experiment was repeated three times with similar results. \u003cstrong\u003e(e)\u003c/strong\u003e CCK-8 assays for the proliferation of U118-MG cells were knocked out DDA1 with CRISPR sgRNAs or infected with lentiviruses carrying FLAG-Vector or FLAG-DDA1. Each bar represents the mean ± SD for biologically triplicate experiments. \u003cem\u003eP \u003c/em\u003evalues were calculated using two-way ANOVA tests (*\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05, **\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.01, ***\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001). \u003cstrong\u003e(f) \u003c/strong\u003eU118-MG cells were knocked out DDA1 with CRISPR sgRNAs or infected with lentiviruses carrying FLAG-Vector or FLAG-DDA1 and cultured for 10 days before staining with crystal violet for colony formation assays. Representative images from biologically triplicate experiments are shown. \u003cstrong\u003e(g)\u003c/strong\u003eU118-MG cells were knocked out DDA1 with CRISPR sgRNAs or infected with lentiviruses carrying FLAG-Vector or FLAG-DDA1, treated with amino acids and UV-C and cultured for 10 days before staining with crystal violet for colony formation assays. Representative images from biologically triplicate experiments are shown.\u003c/p\u003e","description":"","filename":"Figures6.png","url":"https://assets-eu.researchsquare.com/files/rs-7717041/v1/211ad3e9bb3f38990d31b8df.png"},{"id":93924300,"identity":"745af663-8b94-4275-89c3-514150356f4d","added_by":"auto","created_at":"2025-10-20 10:14:45","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":928798,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDDA1 deficiency suppresses glioma growth in vivo and correlates positively with poor clinical outcomes. (a-b) \u003c/strong\u003eMRI scans were performed on day 7 and day 35 to monitor tumor growth in immunodeficient mice orthotopically implanted with DDA1-knockout U118-MG cells. During this period, the mice received daily oral supplementation of a defined amino acid mixture. MRI quantification revealed intracranial tumor volumes, demonstrating the impact of DDA1 loss and nutrient supplementation on glioma progression. Each bar represents the mean ± SD for biologically replicated experiments. \u003cem\u003eP\u003c/em\u003e values were calculated using two-tailed unpaired Student’s \u003cem\u003et\u003c/em\u003e-tests (***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). \u003cstrong\u003e(c)\u003c/strong\u003e Immunohistochemical staining for γ-H2A.X, H2A.X, and DDA1 was performed on paraffin-embedded sections from orthotopic glioma xenografts to evaluate DNA damage levels and DDA1 expression within the tumor tissues.\u003cstrong\u003e (d) \u003c/strong\u003eSurvival analysis was performed based on the CGGA dataset (mRNAseq_325 and mRNAseq_693) to evaluate the association between gene expression and patient prognosis.\u003cem\u003e P \u003c/em\u003evalues were calculated using the log-rank test.\u003cstrong\u003e (e) \u003c/strong\u003eSchematic model illustrating the mTORC1-p-DDA1-CRL4\u003csup\u003eCSA\u003c/sup\u003e axis in coordinating nutrient sensing, DNA repair, metabolic gene expression, and glioma progression.\u003c/p\u003e","description":"","filename":"Figures7.png","url":"https://assets-eu.researchsquare.com/files/rs-7717041/v1/d771201ffe586576dbefb667.png"},{"id":93926313,"identity":"f089657f-68b6-43f3-8d2f-1c1bbb5a662a","added_by":"auto","created_at":"2025-10-20 10:38:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7330279,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7717041/v1/f58570c5-9a53-41d3-b10a-88105aae94e7.pdf"},{"id":93924667,"identity":"693761f6-b5d7-472d-8117-9fabbde5a8a1","added_by":"auto","created_at":"2025-10-20 10:22:44","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1229089,"visible":true,"origin":"","legend":"Supplementary Data 1","description":"","filename":"SupplementaryData1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7717041/v1/03d3725d009b6924ba6c262c.xlsx"},{"id":93924309,"identity":"b2f5ea41-0177-4462-8098-dd50358d23a6","added_by":"auto","created_at":"2025-10-20 10:14:45","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":42223290,"visible":true,"origin":"","legend":"Source Data","description":"","filename":"SourceData.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7717041/v1/dcdea829cbb2d1bf83f05086.xlsx"}],"financialInterests":"There is no duality of interest","formattedTitle":"Amino-Acid-mTORC1-Driven DDA1 Phosphorylation Promotes DNA Repair and Glioblastoma Progression","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDamage-specific DNA-binding protein 1 (DDA1) is a recently characterized component of the CRL4\u003csup\u003eCSA\u003c/sup\u003e E3 ubiquitin ligase complex that plays a central role in transcription-coupled nucleotide excision repair (TC-NER)\u003csup\u003e1, 2, 3, 4\u003c/sup\u003e. The CRL4\u003csup\u003eCSA\u003c/sup\u003e complex, which is composed of CUL4A, DDB1, RBX1, the substrate receptor CSA (ERCC8), and the regulatory subunit DDA1, ubiquitinates stalled transcription-associated factors and remodels chromatin to facilitate lesion removal\u003csup\u003e1, 2, 5, 6\u003c/sup\u003e. By acting as a regulatory adaptor, DDA1 helps recruit and ubiquitinate repair substrates, preserving genome integrity under genotoxic conditions\u003csup\u003e1, 2, 7\u003c/sup\u003e. Disruption of CRL4\u003csup\u003eCSA\u003c/sup\u003e or DDA1 leads to defective TC-NER and persistent DNA lesions, which are drivers of genomic instability and tumor development. Elevated DDA1 expression has been reported in multiple malignancies, including breast, colorectal, and lung cancers, suggesting a conserved role in supporting tumor cell survival under stress\u003csup\u003e8, 9, 10\u003c/sup\u003e. Cancer cells may exploit CRL4\u003csup\u003eCSA\u003c/sup\u003e-mediated DNA repair to tolerate therapy-induced damage, thereby contributing to therapy resistance\u003csup\u003e5, 11, 12, 13\u003c/sup\u003e. Despite these advances, the upstream signals linking metabolic status to DDA1 function in cancer remain poorly defined\u003csup\u003e10, 14\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe mechanistic target of rapamycin complex 1 (mTORC1) is a master kinase complex that integrates nutrient, energy, oxygen, and growth factor signals to regulate biosynthetic and catabolic pathways\u003csup\u003e15, 16\u003c/sup\u003e. Through phosphorylation of key effectors such as S6K1\u003csup\u003e17, 18\u003c/sup\u003e and 4E-BP1\u003csup\u003e19\u003c/sup\u003e, mTORC1 controls protein synthesis, nucleotide production, lipid metabolism, and autophagy. Its activation is orchestrated at the lysosomal membrane by Rag GTPases\u003csup\u003e20,21\u003c/sup\u003e, the Ragulator complex\u003csup\u003e20\u003c/sup\u003e, GATOR1/2\u003csup\u003e21\u003c/sup\u003e, and amino acid sensors including Sestrin2\u003csup\u003e22, 23\u003c/sup\u003e, SAMTOR\u003csup\u003e24\u003c/sup\u003e, and CASTOR1\u003csup\u003e25\u003c/sup\u003e. Dysregulated mTORC1 signaling is a hallmark of glioblastoma, where it drives unchecked proliferation and interferes with DNA damage checkpoints\u003csup\u003e26, 27, 28, 29, 30, 31\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eGlioblastoma (GBM) represents the most aggressive primary brain malignancy, one that is marked by rapid progression, profound heterogeneity, and resistance to conventional therapy\u003csup\u003e32, 33\u003c/sup\u003e. Genomic studies have revealed frequent alterations in TP53, PTEN, EGFR, and IDH, along with dysregulation of multiple oncogenic cascades including PI3K-AKT-mTOR signaling\u003csup\u003e34, 35, 36, 37, 38\u003c/sup\u003e. Moreover, GBM cells display metabolic adaptability and robust DNA repair capacity, enabling them to survive radiotherapy and alkylating chemotherapy\u003csup\u003e39, 40, 41, 42\u003c/sup\u003e. The question of how mTORC1 signaling is functionally coupled to nuclear DNA repair programs to sustain GBM growth remains open.\u003c/p\u003e\u003cp\u003eIn this study, we identify DDA1 as a direct phosphorylation target of mTORC1 in GBM. Biochemical and transcriptomic analysis demonstrates that amino acid stimulation induces mTORC1-dependent phosphorylation of DDA1 at serine 33, which facilitates its nuclear translocation and enhances DNA repair efficiency. We further show that phosphorylated DDA1 activates the metabolic gene program-ENO2, CA12, NMRK1-that supports tumor survival under genotoxic and metabolic stress. DDA1 depletion reduces tumor burden in vivo and compromises metabolic flexibility, sensitizing tumors to nutrient limitation. Elevated DDA1 expression correlates with worse patient outcomes, suggesting clinical relevance. Together, these results reveal a nutrient-responsive amino-acid-mTORC1-DDA1-DNA repair axis that promotes GBM progression through coordinated genome maintenance and metabolic adaptation.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eDDA1 physically associates with Raptor, a key component of the lysosome-anchored mTORC1 complex.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAs described previously, DDA1 participates in protein degradation and DNA damage repair\u003csup\u003e7\u003c/sup\u003e. Recent studies have also revealed that DDA1 expression is dysregulated across several tumor types\u003csup\u003e8, 9, 10, 43\u003c/sup\u003e. To gain further insight into its biological function, we conducted an epitope-tagged proteomic screen that combined immunoprecipitation with mass spectrometry to define the \u003cem\u003ein vivo\u003c/em\u003e interactome of DDA1. We generated U118-MG GBM cells that stably expressed FLAG-tagged DDA1 (FLAG-DDA1), and cell lysates were subjected to anti-FLAG affinity purification followed by mass spectrometric analysis. Proteins co-purifying with DDA1 included DDB1 and CUL4A (members of the CRL4\u003csup\u003eCSA\u003c/sup\u003e complex), LAMTOR1/2/3/5 (Ragulator subunits), and Raptor (a core mTORC1 component). The results from these experiments indicate that DDA1 engages with critical elements of both CRL4\u003csup\u003eCSA\u003c/sup\u003e and mTORC1 signaling machinery (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea; Supplementary Data 1). Consistently, a reciprocal screen using FLAG-Raptor as bait also identified DDA1, together with RagA, RagC, RagD, and Ragulator components (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb; Supplementary Data 1).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo validate these interactions, we performed co-immunoprecipitation (co-IP) in FLAG-DDA1-expressing U118-MG cells. Anti-FLAG immunoprecipitation followed by immunoblotting revealed robust association of DDA1 with Raptor and RagA, whereas no interaction was observed with WDR24 (GATOR2 component), mTOR, RagC, RagD, or LAMTOR1/2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). The interaction of DDA1 with DDB1 and CUL4A was also confirmed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). Reciprocal co-IP using FLAG-Raptor again yielded DDA1 as a binding partner (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee), and immunofluorescence analysis demonstrated partial co-localization of DDA1 and mTOR with the lysosomal marker Lamp2, suggesting that the DDA1-Raptor interaction takes place at the lysosomal surface (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef).\u003c/p\u003e\u003cp\u003eAdditional evidence for the DDA1, RagA, RagC, and Raptor interaction came from GST pull-down assays using bacterially purified GST-DDA1 and in vitro translated mTORC1 components (RagA, RagC, Raptor) or CSA. DDA1 directly interacted with Raptor and CSA, but not with the other tested mTORC1 components (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eg), and reciprocal pull-downs with GST-Raptor, GST-RagA, or GST-CSA corroborated these results (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eg). To explore the structural basis of the DDA1-Raptor interaction, we performed protein-protein interaction prediction using AlphaFold3, which has been reported to achieve near-crystallographic accuracy\u003csup\u003e44\u003c/sup\u003e, and this model revealed extensive binding interfaces between the two proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eh). Together, these findings demonstrate that DDA1 interacts with Raptor at the lysosomal membrane.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eDDA1 functions downstream of mTORC1 and is phosphorylated by amino- acid-mTORC1\u003c/h2\u003e\u003cp\u003eTo determine the functional relevance of DDA1-mTORC1 interaction, we first positioned DDA1 within the mTORC1 signaling cascade. In U118-MG cells, siRNA-mediated depletion of DDA1 neither altered phosphorylation of S6K1, a canonical mTORC1 substrate, nor changed the protein levels of mTORC1 core components (Raptor and mTOR) and the CRL4\u003csup\u003eCSA\u003c/sup\u003e complex (CSA, DDB1, CUL4A, RBX1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Interestingly, DDA1 knockdown significantly reduced phosphorylation of 4E-BP1, another mTORC1 target (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea), but conversely, DDA1 overexpression had no detectable impact on S6K1, 4E-BP1 phosphorylation, or the abundance of mTORC1 or CRL4 components (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). These results suggest that DDA1 is not an upstream regulator of mTORC1 but more likely acts downstream, potentially as a substrate of mTORC1 kinase activity.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eDue to the lack of commercially available phospho-specific antibodies against DDA1, we employed 4D label-free quantitative phosphoproteomics using next-generation ion mobility mass spectrometry to identify phosphorylation events regulated by mTORC1. We subjected U118-MG cells to three conditions: amino acid starvation, amino acid restimulation, and restimulation in the presence of the mTOR inhibitor Torin1. Using a cutoff of log₂ (fold change)\u0026thinsp;\u0026gt;\u0026thinsp;2.0 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, amino acid stimulation increased phosphorylation in 994 phosphoproteins compared to starvation, and Torin1 reversed phosphorylation in 1,276 proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec; Supplementary Data 1). Cross-comparison revealed 609 phosphoproteins co-regulated by amino acids and Torin1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Among these, phosphorylation at serine 33 of DDA1 was strongly induced by amino acid stimulation and suppressed by Torin1. GPS analysis predicted 18 potential phosphorylation sites on DDA1, including Ser33 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed).\u003c/p\u003e\u003cp\u003eTo validate these findings, we generated a custom DDA1 phospho-Ser33 specific antibody (AtaGenix). Western blotting confirmed that amino acid restimulation after starvation increased Ser33 phosphorylation, an effect abolished by Torin1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). Activation of mTORC1 is orchestrated not only by the amino acid-Rag GTPase axis but also by the PI3K-AKT-mTORC1 pathway. Thus, to define the upstream inputs, we established stable U118-MG cell lines with CRISPR mediated knockout of either RagA, a core component of the amino acid-sensing branch, or Rheb, the GTPase linking PI3K-AKT signaling to mTORC1 activation. Immunoblot analysis revealed that loss of either RagA or Rheb markedly reduced phosphorylation of the mTORC1 substrate S6K1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef), indicating effective pathway inhibition. Phosphorylation at DDA1 Ser33 was also attenuated in both RagA and Rheb deficient cells, further indicating that mTORC1 directly controls DDA1 phosphorylation modulated by both nutrient and growth factor signals in glioma cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef).\u003c/p\u003e\u003cp\u003eDDA1 appears to have emerged early in evolution; homologs have been identified not only in vertebrates such as \u003cem\u003eMus musculus\u003c/em\u003e and \u003cem\u003eXenopus tropicalis\u003c/em\u003e but also in other established model organisms, including \u003cem\u003eDanio rerio\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg). Potential homologs are also found in higher invertebrates such as \u003cem\u003eDrosophila mojavensis\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg). Remarkably, all these homologs harbor conserved residues that correspond to human Ser33 within structurally analogous regions, suggesting that this phosphorylation site is functionally important and evolutionarily conserved. Together, these findings demonstrate that DDA1 functions downstream of mTORC1 and is directly phosphorylated by mTORC1 at Serine 33.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePhosphorylated DDA1 undergoes nuclear translocation.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo dissect the functional consequence of the physical interaction between DDA1 and mTORC1, we first analyzed the stoichiometric changes associated with this interaction. Using amino acid stimulation to modulate mTORC1 activity in U118-MG cells transfected with either FLAG-DDA1 or FLAG-Raptor, co-immunoprecipitation assays revealed that mTORC1 activation markedly reduced the interaction between DDA1 and Raptor or RagA and enhanced its association with CRL4\u003csup\u003eCSA\u003c/sup\u003e complex components CUL4A, DDB1, and RBX1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). These findings suggest that mTORC1 activity reshapes DDA1-binding stoichiometry, potentially through phosphorylation at serine 33. To test this directly, we generated phospho-deficient (S33A) and phospho-mimetic (S33D) mutants of DDA1 and expressed them in U118-MG cells. Co-immunoprecipitation assays showed that the DDA1\u003csup\u003eS33D\u003c/sup\u003e mutant exhibited significantly increased binding to CRL4\u003csup\u003eCSA\u003c/sup\u003e components compared to the DDA1\u003csup\u003eS33A\u003c/sup\u003e mutant (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb), implicating S33 phosphorylation as a critical switch for CRL4\u003csup\u003eCSA\u003c/sup\u003e complex assembly.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eGiven that the CRL4\u003csup\u003eCSA\u003c/sup\u003e complex primarily functions in the nucleus\u003csup\u003e45\u003c/sup\u003e, we hypothesized that phosphorylation of DDA1 by mTORC1 may induce its nuclear translocation. As controls to test this, we first examined the subcellular localization of DDB1 and CSA under varying mTORC1 activity states. Immunofluorescence analysis demonstrated that neither amino acid deprivation, re-stimulation, nor Torin1 treatment altered their nuclear localization (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). In parallel, amino acid stimulation promoted mTOR accumulation at lysosomes, whereas amino acid withdrawal or Torin1 disrupted this lysosomal localization (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed). Focusing on DDA1, we observed that amino acid deprivation or Torin1 suppressed its nuclear localization and that amino acid stimulation led to nearly complete nuclear translocation of DDA1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee). To validate these observations biochemically, we performed nuclear-cytoplasmic fractionation followed by immunoblotting. Here, amino acid stimulation markedly increased nuclear DDA1 and p-DDA1 levels, with a concomitant decrease in cytoplasmic DDA1 and a modest rise in cytoplasmic p-DDA1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef). Together, these findings support a model in which amino-acid-mTORC1 activation triggers S33 phosphorylation of DDA1, promoting its nuclear translocation and potentially facilitating CRL4\u003csup\u003eCSA\u003c/sup\u003e complex formation and function.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePhosphorylation of DDA1 promotes CRL4\u003c/b\u003e\u003csup\u003e\u003cb\u003eCSA\u003c/b\u003e\u003c/sup\u003e \u003cb\u003emediated DNA repair and safeguards cellular viability under genotoxic stress.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo delineate the functional consequences of amino-acid-mTORC1-mediated DDA1 phosphorylation in genotoxic signaling, we investigated the role of phosphorylated DDA1\u003csup\u003eS33\u003c/sup\u003e in DNA damage repair. DDA1 has previously been identified as a component of the CRL4\u003csup\u003eCSA\u003c/sup\u003e E3 ubiquitin ligase complex, which participates in nucleotide excision repair (NER) of UV-induced DNA lesions\u003csup\u003e1\u003c/sup\u003e. To assess this, functionally we established U118-MG cell lines with stable depletion of DDA1 via lentiviral transduction (sgDDA1) alongside control cells (sgControl) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). Immunoblot analysis showed that DDA1 loss did not perturb the expression of core CRL4\u003csup\u003eCSA\u003c/sup\u003e components or downstream mTORC1 effector p-S6K (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). To monitor NER efficiency, we further quantified cyclobutene pyrimidine dimers (CPDs), a hallmark of UV-induced DNA lesions, using ELISA. Here, amino acid restimulation substantially reduced CPDs levels in control cells, but DDA1-deficient cells retained high CPDs burdens despite nutrient repletion, indicating compromised repair capacity (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Immunofluorescence staining with CPDs specific monoclonal antibodies corroborated these findings: amino acid stimulation mitigated UV induced CPDs accumulation in control cells, whereas DDA1 knockout cells exhibited significantly elevated CPDs signals, which were only partially alleviated upon amino acid supplementation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). These results establish DDA1 phosphorylation as a key determinant of CRL4\u003csup\u003eCSA\u003c/sup\u003e mediated repair in response to nutrient signaling.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePersistent DNA damage can precipitate apoptosis. in our experiments TUNEL staining revealed that amino acid stimulation suppressed UV induced apoptosis, whereas DDA1 knockout markedly elevated apoptotic DNA fragmentation, which was partially reversed by amino acid re-supply (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed). In parallel, MTT assays demonstrated that amino acid re-stimulation enhanced cell proliferation, while DDA1 depletion impaired proliferative capacity (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee). Notably, treatment with the NEDD8 activating enzyme (NAE) inhibitor MLN4924 strongly inhibited cell growth. However, its suppressive effect was attenuated in DDA1 deficient cells, potentially due to compromised CRL4\u003csup\u003eCSA\u003c/sup\u003e complex activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee). Colony formation assays further supported these observations: amino acid re-stimulation promoted clonal expansion under both basal and UV-stressed conditions, whereas DDA1 loss diminished overall colony forming potential, though responsiveness to nutrient cues was preserved (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ef). These data collectively suggest that DDA1 promotes both DNA repair and survival, thus acting as a critical nexus between nutrient sensing and genotoxic stress response.\u003c/p\u003e\u003cp\u003eFinally, we assessed markers of DNA damage (γ-H2A.X) and apoptosis (cleaved PARP1). Immunoblotting showed that amino acid stimulation suppressed both γ-H2A.X and cleaved PARP1 levels, and DDA1 depletion resulted in their pronounced upregulation irrespective of UV treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eg). Taken together, all of our findings converge on a model in which amino-acid-mTORC1-dependent phosphorylation of DDA1 enhances CRL4\u003csup\u003eCSA\u003c/sup\u003e function to promote DNA repair, suppress apoptosis, and sustain tumor cell proliferation under stress conditions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDDA1 regulates DNA repair and metabolic reprogramming.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo elucidate the biological relevance of the amino-acid-mTORC1-DDA1\u003csup\u003eS33\u003c/sup\u003e-DNA damage axis in glioma, we performed transcriptomic analysis to characterize the downstream gene expression changes associated with DDA1 phosphorylation at Ser33 in the context of DNA repair. We conducted RNA sequencing (RNA-seq) in three glioma cell lines (LN229, T98G, and U118-MG) after stable DDA1 knockdown using lentivirus delivered sgRNAs. Total RNA was then extracted and processed for cDNA synthesis, library preparation, and 50 bp-end sequencing using the BGI-seq 500 platform (APTBIO, Shanghai). Raw reads were quality-checked with FastQC, and low-quality reads (\u0026ge;\u0026thinsp;5 ambiguous bases or Phred score\u0026thinsp;\u0026lt;\u0026thinsp;15) were removed using fastp. Under the threshold of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and absolute log\u003csub\u003e2\u003c/sub\u003e (fold change)\u0026thinsp;\u0026gt;\u0026thinsp;1, we identified 42 consistently differentially expressed genes across the three models, including 36 upregulated and 6 downregulated genes (GSE303079) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Gene ontology analysis indicated that many upregulated transcripts were enriched in pathways related to cellular metabolism and growth. Upregulated targets included: CA12, a carbonic anhydrase critical for regulating intracellular and extracellular pH by catalyzing the reversible hydration of CO₂\u003csup\u003e46, 47\u003c/sup\u003e; NMRK1, a member of the nucleoside kinase family that converts nicotinamide riboside to NMN in NAD⁺ biosynthesis\u003csup\u003e48, 49\u003c/sup\u003e; and ENO2, also known as neuron-specific enolase, which catalyzes the final step of glycolysis converting 2-phosphoglycerate to phosphoenolpyruvate\u003csup\u003e49, 50\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eQuantitative reverse transcription PCR (qRT-PCR) validation confirmed significant upregulation of CA12, NMRK1, and ENO2 following DDA1 knockout in all three glioma models (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb), and immunoblot analysis also corroborated these findings at the protein level (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee). Conversely, overexpression of FLAG-tagged DDA1 led to significant downregulation of these genes at both transcript and protein levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec, d, and f). Given prior evidence linking DNA damage repair defects to metabolic reprogramming\u003csup\u003e51\u003c/sup\u003e, we propose that DDA1 deficiency impairs DNA repair and induces a stress-adaptive transcriptional response involving CA12, NMRK1, and ENO2. This shift likely supports metabolic flexibility, sustains energy homeostasis, and prevents apoptosis, thereby promoting cell survival under genotoxic stress.\u003c/p\u003e\u003cp\u003eTo assess the clinical relevance of our findings, we analyzed public transcriptomic datasets from GEO (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE4290\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE4290\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) that comprised astrocytoma, oligodendroglioma, and GBM specimens. Expression of CA12 was uniformly elevated across all tumor types, whereas ENO2 and NMRK1 levels were frequently lowered (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eg). These trends may reflect loss of neuronal identity during mesenchymal or stem-like transitions in glioma, as well as metabolic rewiring that favors NAD⁺ generation via the NAMPT pathway over NMRK1\u003csup\u003e51, 52\u003c/sup\u003e. Hypoxic tumor cores may further drive CA12 upregulation, facilitating extracellular acidification, stromal invasion, and immune evasion\u003csup\u003e53, 54\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAnalysis of the TCGA GBM cohort (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://portal.gdc.cancer.gov/\u003c/span\u003e\u003cspan address=\"https://portal.gdc.cancer.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) revealed the same pattern. CA12 was significantly upregulated and ENO2 was downregulated; NMRK1 showed a similar downward trend that did attain our level of statistical significance but remained directionally concordant with the GEO data (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eh). To evaluate the clinical significance of these findings, we performed survival analysis using the CGGA dataset (mRNAseq_693) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cgga.org.cn/download.jsp\u003c/span\u003e\u003cspan address=\"https://www.cgga.org.cn/download.jsp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), which showed that low ENO2 expression and high CA12 expression were significantly associated with poor patient prognosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ei). These results thus support a model in which amino-acid-mTORC1-dependent DDA1 phosphorylation regulates DNA damage repair and orchestrates metabolic reprogramming, revealing a previously unrecognized axis that links genome integrity to metabolic adaptation in glioma.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDDA1 is overexpressed in glioma and contributes to tumorigenesis.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eEnhanced DNA repair capacity and dysregulated metabolism are hallmarks of malignant glioma, contributing both to intrinsic and acquired resistance to standard therapies\u003csup\u003e55, 56\u003c/sup\u003e. As a central regulator of both DNA repair and metabolic homeostasis, mTOR plays a pivotal role in gliomagenesisn\u003csup\u003e57, 58\u003c/sup\u003e. To evaluate mTORC1 activity in glioma as comprehensively as possible, we compared nine human glioma cell lines (LN18, LN229, U87-MG, U118-MG, SHG44, A172, T98G, SF126, SF763) with nonmalignant human astrocytes (HA). Immunoblotting revealed markedly elevated mTORC1 activity in glioma cells compared to HA cells, as evidenced by phosphorylation of downstream targets S6K1 and 4E-BP1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea and b). Among these, LN229, U87-MG, U118-MG, A172, and T98G exhibited pronounced mTORC1 activation. Notably, DDA1 and other components of the CRL4\u003csup\u003eCSA\u003c/sup\u003e DNA repair complex were upregulated in glioma cells with hyperactive mTORC1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec). Amino acid re-stimulation experiments further demonstrated that DDA1 phosphorylation at Ser33 was universally induced in glioma cells in an mTORC1-dependent manner (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed). We also profiled phosphorylation of additional mTORC1 downstream targets, including ULK1 and AMPKα, key sensors of autophagy and energy stress respectively, which exhibited a similar pattern of upregulation, consistent with heightened mTORC1 signaling in GBM (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo probe the functional relevance of DDA1 in glioma biology, we also performed CCK-8 proliferation assays in U118-MG cells. Knockout of DDA1 suppressed proliferation, whereas its stable overexpression enhanced growth (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ee). Consistent results were obtained in colony formation assays as well, where DDA1 loss impaired clonogenicity and its overexpression markedly increased colony numbers (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ef). Furthermore, mTORC1 activation via amino acid supplementation promoted colony formation in control cells but failed to rescue growth in DDA1-deficient cells. Conversely, DDA1 overexpression enhanced colony formation regardless of mTORC1 activation status (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eg). These findings indicate that mTORC1-driven DDA1 expression and phosphorylation support glioma growth.\u003c/p\u003e\u003cp\u003eTo validate these observations in vivo, we established an orthotopic intracranial glioma model. DDA1-knockout U118-MG cells (5 \u0026times; 10⁵) were stereotactically implanted into the striatum of immunodeficient BALB/c nude mice. MRI performed on day 7 confirmed tumor formation and served as a baseline (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea). Mice were then randomized into control and amino acid-supplemented groups, the latter receiving daily oral administration of a defined amino acid mixture for four weeks. Follow up MRI on day 35 revealed significantly reduced tumor growth in DDA1-deficient mice, whereas amino acid supplementation accelerated tumor progression relative to controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb). Immunohistochemical analysis of paraffin embedded brain sections demonstrated elevated γ-H2A.X levels in DDA1 deficient tumors as well, indicative of increased DNA damage, which was moderately attenuated by amino acid supplementation (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ec).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFinally, clinical relevance was assessed via survival analysis using CGGA datasets (mRNAseq_325 and mRNAseq_693) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cgga.org.cn/download.jsp\u003c/span\u003e\u003cspan address=\"https://www.cgga.org.cn/download.jsp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). High DDA1 expression was significantly associated with poorer patient prognosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ed). Collectively, our findings identify DDA1 as a novel amino-acid-mTORC1 downstream effector whose phosphorylation enhances its nuclear translocation and function in DNA repair. This signaling axis promotes metabolic adaptation and glioma progression, which constitutes new insight into the crosstalk between mTORC1 signaling, DNA damage responses, and tumor metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ee).\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003emTORC1 has long been recognized as a central regulator of cellular metabolism, protein synthesis, and growth in response to nutrient and growth factor signals\u003csup\u003e59, 60\u003c/sup\u003e. However, the manner in which mTORC1 signaling directly interfaces with genome maintenance mechanisms has remained an underexplored frontier. Although previous studies have hinted at a possible link between mTORC1 and DNA damage responses, such as through indirect regulation of FANCD2 or modulation of homologous recombination repair\u003csup\u003e61\u003c/sup\u003e, the precise molecular mediators have remained elusive. Our identification of DDA1 as a direct phosphorylation target of amino-acid-mTORC1 that coordinates DNA repair adds a fundamentally new layer to the canonical amino-acid-mTORC1 signaling paradigm.\u003c/p\u003e\u003cp\u003eThis discovery integrates the two seemingly distinct processes of nutrient sensing and genome integrity into a unified molecular framework. The phosphorylation-dependent nuclear translocation of DDA1 highlights how lysosome associated amino-acid-mTORC1 signaling extends beyond its classical cytoplasmic functions to exert nuclear control over DNA repair fidelity. Notably, the involvement of DDA1 in modulating the CRL4\u003csup\u003eCSA\u003c/sup\u003e complex, a key player in nucleotide excision repair (NER)\u003csup\u003e1, 62\u003c/sup\u003e, positions DDA1 as a pivotal nexus between nutrient-responsive signaling and chromatin-associated DNA repair machinery.\u003c/p\u003e\u003cp\u003eOur findings also resonate with emerging concepts that DNA repair is tightly coupled to metabolic state. Recent work has shown that efficient DNA repair requires adequate nucleotide pools, redox balance, and ATP availability\u003csup\u003e63, 64\u003c/sup\u003e. Consistent with this, the compensatory upregulation of metabolic genes such as ENO2, CA12, and NMRK1 in DDA1-deficient glioma cells may reflect a tumor intrinsic stress response aimed at sustaining bioenergetic and biosynthetic demands under persistent genotoxic stress. However, this adaptation is ultimately insufficient, as evidenced by increased apoptosis and impaired tumor growth upon DDA1 loss.\u003c/p\u003e\u003cp\u003eThe amino-acid-mTORC1-DDA1 axis may thus represent a broader mechanism applicable beyond GBM. For example, DDA1 has been implicated in protein degradation and cell cycle control in other cancer types\u003csup\u003e4, 9, 65\u003c/sup\u003e, suggesting that phosphorylation-dependent functional switching of DDA1 could be a generalizable regulatory strategy in cancer biology. Whether this mechanism extends to other DNA repair pathways, such as homologous recombination or base excision repair, remains an open question worthy of further investigation.\u003c/p\u003e\u003cp\u003eClinically, our results suggest that DDA1 is overexpressed in glioma and that its elevated expression correlates with poor prognosis in patient datasets. \u003cem\u003eIn vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e models both showed that DDA1 loss significantly impairs glioma cell proliferation and tumor growth. Notably, amino acid supplementation enhanced mTORC1 activation and DDA1 phosphorylation in glioma cells, promoting tumor progression, whereas DDA1 knockout rendered tumors less responsive to nutrient cues. These findings underscore the role of DDA1 as a critical downstream effector of mTORC1 that integrates extracellular nutrient availability with nuclear DNA repair machinery to promote gliomagenesis.\u003c/p\u003e\u003cp\u003eOur results provide important implications for therapeutic intervention. Specifically, the amino-acid-mTORC1-DDA1 axis represents a potential vulnerability in glioma that may be exploitable using strategies that simultaneously target mTORC1 signaling and DNA repair mechanisms. Given the reliance of DDA1 function on mTORC1 activity and nutrient availability, metabolic interventions or inhibitors of mTORC1 may sensitize glioma cells to DNA damaging agents by disrupting this axis. Moreover, pharmacologic inhibition of CRL4 E3 ligase activity or specific blockade of DDA1 phosphorylation may offer additional routes for targeted therapy.\u003c/p\u003e\u003cp\u003eIn conclusion, our work establishes DDA1 phosphorylation as a key molecular event that connects nutrient responsive amino-acid-mTORC1 signaling to DNA repair and tumor growth. These findings not only redefine the functional landscape of amino-acid-mTORC1 but also provide a conceptual framework for targeting nutrient-DNA repair crosstalk in GBM. The amino-acid-mTORC1-DDA1 axis thus emerges as a promising therapeutic target that warrants further exploration in both preclinical models and clinical settings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eData availability declaration\u003c/p\u003e\n\u003cp\u003eThe RNA-seq data generated in this study have been deposited in the NCBI Gene Expression Omnibus (GEO) under accession code GSE303079 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE303079). 4D-Labelfree quantitative phosphoproteomics analysis data and mass spectrometry data are provided in Supplementary Data 1. Gene expression analysis of the target proteins in GBM was performed using transcriptomic data from The Cancer Genome Atlas (TCGA) GBM cohort (https://portal.gdc.cancer.gov/). Differential expression across astrocytoma, oligodendroglioma, and GBM specimens was assessed using the GEO dataset GSE4290 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE4290). Survival analysis based on target gene expression was conducted using the CGGA cohorts (mRNAseq_325 and mRNAseq_693) (https://www.cgga.org.cn/download.jsp). All data generated or analyzed during this study are included in this published article (and its supplementary information files), and the reporting summary and editorial checklist for this article are available as a Supplementary File. Source data are provided with the paper.\u003c/p\u003e\n\u003cp\u003eFunding declaration\u003c/p\u003e\n\u003cp\u003eThis work was supported by a grant (7244374 to X.C.) from the Beijing Natural Science Foundation of China, and grants (GZC20230307 to X.C.) from the National Postdoctoral Program for Innovative Talents of China, and grants (2060204 to X.P.) from the State Key Laboratory Special Fund, and grants (2023-I2M-2-001 to X.P.) from the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences.\u003c/p\u003e\n\u003cp\u003eAuthor contribution declaration\u003c/p\u003e\n\u003cp\u003eX.C. and X.P. conceived the project and designed the experiments; Z.W. and A.Y. performed experiments; X.C. analyzed data; Y.L., R.Z., L.L., D.X., R.L., X.Z., B.Y., and W.H. provided technical assistance; X.C. and X.P. wrote the manuscript.\u003c/p\u003e\n\u003cp\u003eConsent to Publish declarations\u003c/p\u003e\n\u003cp\u003eWe, the authors, hereby declare that this manuscript is original, has not been published elsewhere, and is not under consideration by any other journal. Upon acceptance, we agree to grant the Publisher the right to publish, reproduce, and distribute this work in all forms and media.\u003c/p\u003e\n\u003cp\u003eEthics statement\u003c/p\u003e\n\u003cp\u003eAll the animal studies were approved by the Institutional Animal Care Use \u0026amp; Welfare Committee of the Center for Experimental Animal Research (ACUC-A01-2022-059, ACUC-A02-2025-005).\u003c/p\u003e\n\u003cp\u003eCompeting interest declaration\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eThe authors thank AiMi Academic Services (www.aimieditor.com) for English language editing and review services.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLlerena Schiffmacher DA, Lee SH, Kliza KW, Theil AF, Akita M, Helfricht A\u003cem\u003e, et al.\u003c/em\u003e The small CRL4(CSA) ubiquitin ligase component DDA1 regulates transcription-coupled repair dynamics. \u003cem\u003eNat Commun\u003c/em\u003e 2024, \u003cstrong\u003e15\u003c/strong\u003e(1)\u003cstrong\u003e:\u003c/strong\u003e 6374.\u003c/li\u003e\n\u003cli\u003eSchiffmacher DL, Lee SH, Kliza KW, Theil AF, Akita M, Helfricht A\u003cem\u003e, et al.\u003c/em\u003e DDA1, a novel factor in transcription-coupled repair, modulates CRL4(CSA) dynamics at DNA damage-stalled RNA polymerase II. \u003cem\u003eRes Sq\u003c/em\u003e 2023.\u003c/li\u003e\n\u003cli\u003eBurgess AE, Loughran TA, Turk LS, Nyvall HG, Dunlop JL, Jamieson SA\u003cem\u003e, et al.\u003c/em\u003e DET1 dynamics underlie cooperative ubiquitination by CRL4(DET1-COP1) complexes. \u003cem\u003eSci Adv\u003c/em\u003e 2025, \u003cstrong\u003e11\u003c/strong\u003e(9)\u003cstrong\u003e:\u003c/strong\u003e eadq4187.\u003c/li\u003e\n\u003cli\u003ePick E, Lau OS, Tsuge T, Menon S, Tong Y, Dohmae N\u003cem\u003e, et al.\u003c/em\u003e Mammalian DET1 regulates Cul4A activity and forms stable complexes with E2 ubiquitin-conjugating enzymes. \u003cem\u003eMol Cell Biol\u003c/em\u003e 2007, \u003cstrong\u003e27\u003c/strong\u003e(13)\u003cstrong\u003e:\u003c/strong\u003e 4708-4719.\u003c/li\u003e\n\u003cli\u003evan Sluis M, Yu Q, van der Woude M, Gonzalo-Hansen C, Dealy SC, Janssens RC\u003cem\u003e, et al.\u003c/em\u003e Transcription-coupled DNA-protein crosslink repair by CSB and CRL4(CSA)-mediated degradation. \u003cem\u003eNat Cell Biol\u003c/em\u003e 2024, \u003cstrong\u003e26\u003c/strong\u003e(5)\u003cstrong\u003e:\u003c/strong\u003e 770-783.\u003c/li\u003e\n\u003cli\u003eGonzalo-Hansen C, Steurer B, Janssens RC, Zhou D, van Sluis M, Lans H\u003cem\u003e, et al.\u003c/em\u003e Differential processing of RNA polymerase II at DNA damage correlates with transcription-coupled repair syndrome severity. \u003cem\u003eNucleic Acids Res\u003c/em\u003e 2024, \u003cstrong\u003e52\u003c/strong\u003e(16)\u003cstrong\u003e:\u003c/strong\u003e 9596-9612.\u003c/li\u003e\n\u003cli\u003eOlma MH, Roy M, Le Bihan T, Sumara I, Maerki S, Larsen B\u003cem\u003e, et al.\u003c/em\u003e An interaction network of the mammalian COP9 signalosome identifies Dda1 as a core subunit of multiple Cul4-based E3 ligases. \u003cem\u003eJ Cell Sci\u003c/em\u003e 2009, \u003cstrong\u003e122\u003c/strong\u003e(Pt 7)\u003cstrong\u003e:\u003c/strong\u003e 1035-1044.\u003c/li\u003e\n\u003cli\u003eZhang J, Li Y, Wang JG, Feng JY, Huang GD, Luo CG. 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NAD(+) metabolism, stemness, the immune response, and cancer. \u003cem\u003eSignal Transduct Target Ther\u003c/em\u003e 2021, \u003cstrong\u003e6\u003c/strong\u003e(1)\u003cstrong\u003e:\u003c/strong\u003e 2.\u003c/li\u003e\n\u003cli\u003eGao S, Geng C, Song T, Lin X, Liu J, Cai Z\u003cem\u003e, et al.\u003c/em\u003e Activation of c-Abl Kinase Potentiates the Anti-myeloma Drug Lenalidomide by Promoting DDA1 Protein Recruitment to the CRL4 Ubiquitin Ligase. \u003cem\u003eJ Biol Chem\u003c/em\u003e 2017, \u003cstrong\u003e292\u003c/strong\u003e(9)\u003cstrong\u003e:\u003c/strong\u003e 3683-3691.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eAntibodies and reagents\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAntibodies used included the following: αRagA (4357, 1:1000 for western blotting (WB)), αRagC (3360,1:1000 for WB), αRagD (4470,1:1000 for WB), αmTOR (2972 and 2983, 1:1000 for WB and 1:100 for Immunofluorescence (IF)), αRaptor (2280, 1:500 for WB), α4E-BP1 (9644, 1:1000 for WB), αp-4E-BP1 (2855, 1:1000 for WB), αS6K1 (9202, 1:1000 for WB), αp-S6K1 (9205, 1:500 for WB), αWDR24 (67470, 1:1000 for WB), αp18 (8975, 1:1000 for WB and 1:100 for IF), αp14 (8145, 1:1000 for WB), αFLAG (14793, 1:10000 for WB), αULK1 (8054, 1:1000 for WB), αp-ULK1 (14202, 1:1000 for WB); αAMPKα (2532, 1:1000 for WB); αp-AMPKα (2535, 1:1000 for WB); αNMRK1 (29786, 1:1000 for WB), αCA12 (5864, 1:1000 for WB), and αENO2 (24330, 1:1000 for WB) from Cell Signaling; αmTOR (ab32028, 1:100 for IF), αLamp2 (ab25631, 1:100 for IF), αDDB1 (ab109027, 1:1000 for WB and 1:100 for IF), αTubulin (ab6160, 1:1000 for WB), αLaminA/C (ab108595, 1:1000 for WB), αRBX1 (ab221548 1:1000 for WB), αRheb (ab316265, 1:1000 for WB), αCUL4A (ab92554, 1:1000 for WB), αCSA (ab137033, 1:100 for WB and 1:100 for IF), αPARP1 (ab191217, 1:1000 for WB), αCleaved PARP1 (ab32064, 1:100 for WB), αH2A.X (ab229914, 1:1000 for WB and 1:100 forimmunohistochemistry (IHC)), and αγ-H2A.X (ab81299, 1:1000 for WB and 1:100 for IHC) from Abcam; αDDA1 (YT7033, 1:1000 for WB, 1:100 for IHC, and 1:100 for IF) from Immunoway; αDDA1 (14995-1-AP, 1:1000 for WB, 1:100 for IHC, and 1:100 for IF) from Proteintech; Customized αDDA1\u003csup\u003eS33\u003c/sup\u003e (1:500 for WB) from AtaGenix; αβ-actin (AC004, 1:10000 for WB), HRP Goat Anti-Rabbit IgG (AS014, 1:5000 for WB), and HRP Goat Anti-Mouse IgG (AS003, 1:5000 for WB) from ABclonal. Control siRNA and siRNA for DDA1, as well as sgRNAs for DDA1, RagA, and Rheb were synthesized by Wuhan Saiweizhen Biotechnology. Torin1 (475991), Anti-FLAG M2 (A2220) affinity gel, and 3 x FLAG peptide (F3290) were sourced from Sigma-Aldrich, and MLN4924 (LKT-M4454-M001) came from ENZO. Protease inhibitor cocktail was from Roche Applied Science. RPMI 1640 Medium Modified w/o Amino acids and Glucose (R9010-01) was sourced from USBiological. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell culture\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe cell lines used were obtained from the American Type Culture Collection (ATCC). U118-MG, LN18, LN229, A172, SHG44 cells were maintained in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10% fetal bovine serum (FBS) T98G, U87-MG, and SF126 cells were maintained in Minimum Essential Medium (MEM) and 10% FBS; SF762 cells were maintained in Roswell Park Memorial Institute Medium (RPMI-1640) with 20% FBS; and HA cells were maintained in Astrocyte Medium (1801, ScienCell). All cells were cultured in a humidified incubator equilibrated with 5% CO\u003csub\u003e2\u003c/sub\u003e at 37ºC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTransfection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor transfection of cDNA expression constructs, 2-2.5 million cells were seeded in 15-cm dishes and transfected at 24 h after seeding. Experiments were done 36-48 h after transfection. siRNA Transfections were carried out using Lipofectamine® RNAiMAX Reagent (Invitrogen, Carlsbad, CA) according to the manufacturer’s instructions, and the final concentration of siRNA used for each six-well plate was 50 nM. Each experiment was performed in triplicate and repeated at least three times. For RNAi experiment, at least three independent siRNA sequences were tested for each gene, and the one with the best efficiency was chosen. The siRNA sequences were as follows: Control siRNA: UUCUCCGAACGUGUCACGU; DDA1 siRNA-1: GCGCUACCUGCAUCAGCAATT; DDA1 siRNA-2: GAAGAGAGACCAGGAGCAATT; and DDA1 siRNA-3: GGAGCAAGUGGAGCUGGAATT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunoprecipitation and western blotting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCellular extracts were prepared by incubating approximately 5 x 10\u003csup\u003e8\u003c/sup\u003e cells in lysis buffer (50 mM Tris-HCl, pH 8.0, 150 mM NaCl, 0.5% NP40, and 1 tablet of EDTA-free protease inhibitor (Roche) (per 25 ml buffer)) for 30 min at 4ºC. This was followed by centrifugation at 16,000 x g for 15 min at 4ºC. For immunoprecipitation, 500 μg of protein was incubated with specific antibodies (2-3 μg) for 12 h at 4ºC with constant rotation; 60 μl of 50% protein G agarose beads was then added and the incubation was continued for an additional 2 h. Next, beads were washed 5 times using the lysis buffer. The precipitated proteins were eluted from the beads by resuspending them in 2 x SDS-PAGE loading buffer and boiling for 10 min, and the resultant materials from immunoprecipitation or cell lysates were resolved using 8%-12% SDS-PAGE gels prior to transfer onto acetate cellulose membranes. For anti-FLAG immunoprecipitation, anti-FLAG M2 Affinity Gel (Sigma) was washed with lysis buffer three times then resuspended to a ratio of 50:50 affinity gel to lysis buffer before 25 μl of a well-mixed slurry was added to cleared lysates and incubated at 4°C in a shaker for 90-120 minutes. Immunoprecipitated proteins were denatured by the addition of 2 x SDS-PAGE loading buffer and boiled for 10 minutes. Denatured samples were resolved by 8%-12% SDS-PAGE, and analyzed by immunoblotting. For western blotting analysis, membranes were incubated with appropriate antibodies for overnight at 4ºC followed by incubation with a secondary antibody. Immunoreactive bands were visualized using Luminal reagent (Santa Cruz Biotechnology) according to the manufacturer’s recommendation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMass spectrometry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eU118-MG cells that expressed FLAG-DDA1 or FLAG-Raptor were washed twice with cold PBS, scraped, and collected by centrifugation at 800 x g for 5 minutes. Cellular extracts were then prepared by incubating the cells in lysis buffer containing protease inhibitor cocktail (Roche), and anti-FLAG immunoaffinity columns were prepared using anti-FLAG M2 affinity gel (Sigma) following the manufacturer’s suggestions. Cell lysates were obtained from approximately 5 x 10\u003csup\u003e8\u003c/sup\u003e cells and applied to an equilibrated FLAG column of 1-mL bed volume to allow for adsorption of the protein complex to the column resin. After binding, the column was washed with cold PBS plus 0.1% Nonidet P-40 prior to application of 3x FLAG peptides to elute FLAG protein complex as described by the vendor and subjected to LC/MS-MS sequencing. The eluates were then directly entered Q-Exactive MS (Thermo Fisher Scientific, Waltham, MA, USA), set in positive ion mode and data-dependent manner with full MS scan from 350-2000 m/z, full scan resolution at 70,000, MS/MS scan resolution at 17,500. MS/MS scan with minimum signal threshold 1E+5, and isolation width at 2 Da. Peptide identification and quantification was carried out with Mascot software Revision 2.3.01 using the TAIR database search algorithm and the integrated false discovery rate (FDR) analysis function.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4D-Labelfree quantitative phosphoproteomics analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eU118-MG cells were subjected to three treatment conditions to modulate mTORC1 activity: (1) amino acid starvation 1 h, (2) amino acid stimulation 30 min, and (3) amino acid stimulation combined with the mTOR inhibitor Torin1 (250 nM) pretreated 1 h. Cells were lysed in 8 M urea lysis buffer containing protease and phosphatase inhibitors. Proteins were reduced, alkylated, and digested with trypsin overnight, and phosphopeptides were enriched using Fe-NTA affinity chromatography (Thermo Scientific) followed by LC-MS/MS analysis using a timsTOF Pro mass spectrometer (Bruker). Raw data were analyzed using MaxQuant with phosphorylation (S/T/Y) as variable modifications, from which phosphopeptides with a localization probability \u0026gt;0.75 were included for quantification. Differential phosphorylation was determined using \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 and absolute log\u003csub\u003e2 \u003c/sub\u003e(fold change) \u0026gt; 2 as significance thresholds.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePull-down assays\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGST-fused constructs were expressed in BL21 \u003cem\u003eEscherichia coli\u003c/em\u003e, and \u003cem\u003ein vitro \u003c/em\u003etranscription and translation experiments were carried out with rabbit reticulocyte lysate (TNT systems, Promega) according to the manufacturer’s recommendations. In GST pull-down assays, about 5 mg of the appropriate GST fusion proteins with 30 ml of glutathione-Sepharose beads were incubated with 5-8 μl of \u003cem\u003ein vitro \u003c/em\u003etranscribed/translated products in binding buffer (75 mM NaCl, 50 mM HEPES, pH 7.9) at 4°C for 2 h in the presence of the protease inhibitor mixture. The beads were then washed 5 times with binding buffer, resuspended in 30 ml of 2 x SDS-PAGE loading buffer, and subjected to western blotting.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFluorescence confocal microscopy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eU118-MG cells grown on 6-well chamber slides were washed with PBS, fixed in 4% paraformaldehyde, permeabilized with 0.2% Triton X-100, blocked with 0.8% BSA, and incubated with appropriate primary antibodies followed by addition of Alexa Fluor™ 488/568 donkey secondary antibodies (Invitrogen). DAPI (Sigma) was included in the final wash to stain the nuclei, and images were visualized with an Olympus inverted microscope equipped with a charge coupled camera.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunohistochemistry (IHC)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParaffin sections (5 μm) were deparaffinized, rehydrated, and subjected to antigen retrieval in citrate buffer (pH 6.0). After blocking with 5% BSA, sections were incubated overnight at 4ºC with αγ-H2A.X, αH2A.X, or αDDA1 antibody, followed by HRP-conjugated secondary antibody and DAB chromogenic detection. Slides were counterstained with hematoxylin and imaged using a Leica DM6 microscope.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA-seq\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA samples were extracted from U118-MG, T98G, or LN229 cells and subjected to deep sequencing by BGI (APTBIO, Shanghai) using a BGI500 sequencer with single-end 50-bp reads. Raw data were preprocessed through fastp to remove adaptors and low-quality reads with at the default parameters. Clean reads were aligned to GRCh38/hg38 reference genome through STAR, an ultrafast universal RNA-seq aligner. Raw read count mapped to every gene that obtained via HTSeq-Count tool was used as expression level, and the DESeq2 R Bioconductor package was used for screening differential expression genes with the threshold of \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 and absolute log\u003csub\u003e2 \u003c/sub\u003e(fold change) \u0026gt; 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell viability/proliferation assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor cell proliferation assays, U118-MG cells with DDA1 knockout or stable FLAG-DDA1 expression were seeded into 96-well plates with an equal volume of medium. After cell treatment, 10 μl CCK-8 solution was added according to the manufacturer’s protocol. Plates were incubated at 37ºC for 2 h and cell viability was determined by measuring the absorbance at 450 nm wavelength. Each experiment was performed in triplicate and repeated at least three times.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eqPCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal cellular RNA samples were isolated with TRIzol reagent (Invitrogen) and used for the first strand cDNA synthesis with a Reverse Transcription System (Roche). Quantitation of all gene transcripts was done by real time RT-PCR (qPCR) using a Power SYBR Green PCR Master Mix and Roche LightCycler®480 II sequence detection system. The qPCR primers sequences used were: NMRK1: TCAGTGGTGTGACAAACAGTG (F), GCACATCGTACTGCAAAAATCC (R); ENO2: AGCCTCTACGGGCATCTATGA (F), TTCTCAGTCCCATCCAACTCC (R); CA12: AGTGAACGGTTCCAAGTGGAC (F), CCACACGACGGGTACTTCT (R); DDA1: TTTAGTCGATTTCACGCGGAC (F), ATCTGTTCAGACGGGTACTCG (R); and β-actin: CATGTACGTTGCTATCCAGGC (F), CTCCTTAATGTCACGCACGAT (R).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLentiviral production and infection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRecombinant lentiviruses expressing FLAG-Vector and FLAG-DDA1 were constructed by Wuhan Saiweizhen Biotechnology. Concentrated amounts of these viruses were used to infect 5 x 10\u003csup\u003e5\u003c/sup\u003e cells in a 60-mm dish with 8 μg/ml polybrene. Infected U118-MG cells were then subjected to sorting target expression. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRISPR-Cas9-mediated gene knockout\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStable knockout of DDA1, RagA, or Rheb in U118-MG cells was achieved using a two-vector lentiviral system. U118-MG cells were first transduced with lentivirus encoding Streptococcus pyogenes Cas9 in the presence of 8 μg/mL polybrene (Sigma-Aldrich), and 48 hours after infection, cells were subjected to selection with 10 μg/mL blasticidin for 5 days to establish stable Cas9-expressing populations. Subsequently, the cells were transduced with lentivirus expressing gene-specific sgRNAs targeting DDA1, RagA, or Rheb. After 48 h, transduced cells were selected with 1 μg/mL puromycin for 4 days. To isolate monoclonal knockout lines, puromycin-selected cells were subjected to limiting dilution in 96-well plates at a density of 0.5 cells/well. After 14 days, individual colonies were expanded, and genomic DNA and protein lysates were collected for Sanger sequencing and immunoblotting to confirm successful gene disruption. Control cell lines were generated using nontargeting sgRNA constructs and underwent identical procedures to those used for knockout generation. The sgRNAs sequences used were: sgDDA1-1: TTCCTGGGACTGGGAGGAATTGG; sgDDA1-2: CAACCCTCCTGCAGAACCGACGG; sgDDA1-3: CTGTTCAGACGGGTACTCGCGGG. sgRagA-1: GGAGTGTTCCACGTCAATGGTGG; sgRagA-2: GTTCCCTAGGAATCGGACGTGGG; sgRagA-3: GTGCTGAACCTGTGGGACTGTGG. sgRheb-1: CGGTTGATGTGGTTGGGCCGGGG; sgRheb-2: TCCCGGAAGATCGCGATCCTGGG; and sgRheb-3: GCTACCGGTCTGTGGGTGAGTGG. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCPD quantification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate NER efficiency, U118-MG cells were pretreated by amino acid starvation for 1 h, followed by re-stimulation with MEM amino acids 30 min in the presence or absence of UV-C exposure (20 J/m²). Cyclobutane-pyrimidine dimers (CPDs) were quantified using a CPD-specific ELISA kit (Cosmo Bio) following the manufacturer’s protocol, and genomic DNA was extracted (Qiagen DNeasy), denatured, and immobilized in 96-well plates for antibody-based detection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunofluorescence staining for CPDs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells were grown on coverslips, UV-irradiated (20 J/m²), and treated as above. Fixation was performed with 4% paraformaldehyde (15 min), followed by DNA denaturation with 2 N HCl (30 min), neutralization (Tris-HCl pH 8.5), and blocking (5% BSA). CPDs were detected using monoclonal antibodies (Cosmo Bio) and Alexa Fluor-conjugated secondary antibodies, and Nuclei were counterstained with DAPI. Images were acquired using a Zeiss LSM980 confocal microscope.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTUNEL assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApoptotic DNA fragmentation was assessed using the In Situ Cell Death Detection Kit (Roche). Cells were UV-irradiated, fixed, permeabilized with 0.1% Triton X-100, and incubated with TUNEL reaction mixture for 1 h at 37ºC. Fluorescence was visualized using a confocal microscope and quantified with ImageJ.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMTT assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCell proliferation was measured using the MTT assay (Sigma). Cells were seeded in 96-well plates and treated as indicated. After 48 h, 0.5 mg/mL MTT solution was added (4 h), followed by solubilization in DMSO. Absorbance at 570 nm was recorded using a plate reader.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eColony formation assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eU118-MG cells were maintained in culture media in 6-well plate for 10 days, fixed with 4% paraformaldehyde, and then stained with crystal violet. Each experiment was performed in triplicate and repeated at least three times.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBioinformatics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTranscriptomic and clinical survival data from the Chinese Glioma Genome Atlas (CGGA) cohorts (mRNAseq_325 and mRNAseq_693) were obtained from the CGGA portal (https://www.cgga.org.cn/download.jsp). Gene expression analysis in glioma was further validated using publicly available RNA-seq data from The Cancer Genome Atlas (TCGA) GBM cohort (https://portal.gdc.cancer.gov/). In addition, the GEO dataset GSE4290 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE4290), comprising astrocytoma, oligodendroglioma, and GBM specimens, was used to assess differential gene expression across glioma subtypes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData analysis was performed on the averages of biologically triplicate experimental results. Unpaired, two-tailed Student’s \u003cem\u003et\u003c/em\u003e-tests were used for 2-group comparisons, and ANOVA with Bonferroni’s correction was used to compare multiple groups. A\u003cem\u003e P\u003c/em\u003e-value of less than 0.05 was considered to indicate statistically significant test results for all tests. All statistical results were determined using Prism 10 software, and variations within each group and the assumptions of the tests were checked prior to analysis. \u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cell-death-and-disease","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddis","sideBox":"Learn more about [Cell Death \u0026 Disease](http://www.nature.com/cddis/)","snPcode":"41419","submissionUrl":"https://mts-cddis.nature.com/cgi-bin/main.plex","title":"Cell Death \u0026 Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7717041/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7717041/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe protein DDA1 is involved in protein degradation, cell cycle regulation, and DNA damage repair. Recent studies have revealed its differential expression across various tumor types. However, the manner in which how DDA1 functions as a tumorigenic factor remains to be elucidated. Through experiments in multiple glioblastoma cell models, we identified a physical association between cytoplasmic DDA1 and Raptor, a key component of lysosome-associated mTORC1. Amino acid stimulation triggers phosphorylation of DDA1 at serine 33, promoting its nuclear translocation and involvement in DNA damage repair. Integrated genomic and transcriptomic analysis revealed that the amino-acid-mTORC1-DDA1\u003csup\u003eS33\u003c/sup\u003e-DNA repair axis regulates the expression of a subset of metabolic genes, including ENO2, a glycolytic enzyme; CA12, which contributes to intracellular and extracellular pH homeostasis; and NMRK1, a key enzyme in nicotinamide riboside metabolism. Notably, DDA1 deficiency markedly impaired glioblastoma growth and triggered a compensatory upregulation of metabolic activity to sustain tumor cell survival. These metabolic genes supply essential nutrients required for effective DNA repair. Our findings establish DDA1 as a previously unrecognized phosphorylation target downstream of amino-acid-mTORC1, serving as both a critical mediator of mTORC1-driven DNA damage response and a key regulator of glioblastoma progression, thereby expanding our understanding of gliomagenesis.\u003c/p\u003e","manuscriptTitle":"Amino-Acid-mTORC1-Driven DDA1 Phosphorylation Promotes DNA Repair and Glioblastoma Progression","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-20 10:14:40","doi":"10.21203/rs.3.rs-7717041/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cell-death-and-disease","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddis","sideBox":"Learn more about [Cell Death \u0026 Disease](http://www.nature.com/cddis/)","snPcode":"41419","submissionUrl":"https://mts-cddis.nature.com/cgi-bin/main.plex","title":"Cell Death \u0026 Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b9c952bc-8aa2-4a95-b86e-fe4979fe41e1","owner":[],"postedDate":"October 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":55583650,"name":"Biological sciences/Cancer/CNS cancer"},{"id":55583651,"name":"Biological sciences/Biochemistry/Kinases"},{"id":55583652,"name":"Biological sciences/Molecular biology/Proteomics/Protein\u0026#x2013;protein interaction networks"}],"tags":[],"updatedAt":"2025-10-20T10:14:40+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-20 10:14:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7717041","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7717041","identity":"rs-7717041","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}