RFC4 Drives Temozolomide Resistance in Glioblastoma by Activating STK38-BECN1-Dependent Autophagy

RFC4 Drives Temozolomide Resistance in Glioblastoma by Activating STK38-BECN1-Dependent Autophagy | 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 RFC4 Drives Temozolomide Resistance in Glioblastoma by Activating STK38-BECN1-Dependent Autophagy Yan Wang, Min Mao, Ji Hang, Wenqian Yu, Qu-Jing Gai, Sen-lin Xu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6854944/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 Glioblastoma (GBM) remains intractable owing to treatment resistance and near-inevitable relapse. While autophagy has been demonstrated to contribute to temozolomide (TMZ) resistance, its regulatory mechanisms remain unclear. RFC4, a replication factor implicated in tumor progression, has not yet been systematically investigated in glioma for its potential role in autophagy regulation. In this work, multi-omics analyses and immunohistochemistry were used to evaluate clinical relevance of RFC4. TMZ-resistant GBM cell lines and orthotopic mouse models were used for functional studies. Autophagy was assessed via LC3B-II quantification, immunofluorescence, and electron microscopy. Structural interactions were mapped using truncation mutants, GST pull-down assays, and molecular docking. We found that RFC4 played oncogenic roles in GBM tissues, correlating with poor prognosis and TMZ resistance. TMZ treatment increased RFC4 enhancer accessibility and stabilized STK38, a kinase that regulates autophagosome formation. RFC4-STK38 interaction promoted BECN1 recruitment, thereby driving autophagy. Critically, phosphorylation of STK38 at T444 was essential for stabilizing the RFC4-STK38-BECN1 complex, whereas the phospho-deficient STK38-T444A mutation impaired BECN1 binding and autophagosome maturation. In vivo, RFC4 overexpression conferred TMZ resistance; however, this resistance was reversed by chloroquine-mediated autophagy inhibition. Co-overexpression of RFC4 and STK38 predicted the worst patient survival, and STK38 knockdown induced synthetic lethality in this context. Together, this study identified the RFC4-STK38-BECN1 axis as a master regulator of TMZ resistance via autophagy. The T444 phosphorylation could be a druggable vulnerability and its disruption reversed pro-survival autophagy. Clinically, RFC4/STK38 co-expression stratified high-risk GBM patients. Preclinically, targeting RFC4-STK38 synergized with TMZ to overcome resistance. These findings elucidated a novel GBM resistance mechanism and provided a translational roadmap for precision therapy. Biological sciences/Cancer Health sciences/Oncology Glioblastoma Temozolomide Autophagy RFC4 STK38 BECN1 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Glioblastoma (GBM) is the most prevalent and malignant primary brain tumor in adults. 1 , 2 It is characterized by rapid proliferation and diffuse infiltration into adjacent healthy brain tissue, which significantly hinders complete surgical resection. 3 Current therapeutic strategies for GBM involve maximal safe surgical resection followed by adjuvant radiation therapy and chemotherapy. Temozolomide (TMZ), an alkylating agent, remains the frontline chemotherapeutic option by inducing DNA damage and interfering with DNA replication. 4 , 5 Nevertheless, GBM treatment continues to face challenges such as TMZ resistance development, limited therapeutic sensitivity, insufficient blood-brain barrier permeability, and systemic adverse effects. 6 , 7 Consequently, GBM demonstrates a strong propensity for recurrence, even after intensive therapeutic regimens. 6 , 7 Overcoming these obstacles requires further research efforts and the development of innovative treatment approaches, including combination therapies and targeted strategies, to improve clinical outcomes for GBM patients. 8 Accumulating evidence supports the notion that pharmacological disruption of autophagic homeostasis - particularly via sustained inhibition of macroautophagy - elicits transformative therapeutic effects against GBM. 9 , 10 Autophagy is a cellular process that plays a crucial role in the degradation and recycling of impaired proteins and organelles, thereby preserving cellular homeostasis. 11 This dynamic catabolic pathway usually involves multiple steps: initiation through ULK1 kinase complex activation, elongation via ATG conjugation systems, and lysosomal degradation mediated by autophagosome-lysosome fusion. 12 Notably, the PI3K/AKT/mTOR signaling axis serves as a master regulator of nutrient-responsive autophagy, where mTORC1 suppression triggers autophagosome formation under stress conditions. Central to this process is BECN-1/Beclin-1, a key autophagy-related (ATG) protein that coordinates membrane nucleation through its interaction with class III PI3K complexes. 13 In the context of GBM, autophagy can be activated as a survival mechanism in response to chemotherapy, leading to the development of treatment resistance. 14 , 15 Advances in research have elucidated diverse signaling pathways and molecular mechanisms implicated in autophagy-mediated resistance, including the PI3K/AKT/mTOR pathway, BECN-1 expression, and lysosomal function. 16 Consequently, targeting autophagy has emerged as a promising therapeutic strategy to enhance GBM susceptibility to TMZ. 17 While preclinical studies demonstrate synergistic tumor suppression through combined autophagy inhibition and TMZ treatment, clinical translation remains limited by an incomplete mechanistic understanding of context-dependent resistance mechanisms. A comprehensive elucidation of autophagy activation in TMZ resistance, coupled with the development of targeted interventions, holds potential for overcoming therapeutic limitations and improving outcomes in GBM patients. RFC4 (Replication Factor C Subunit 4) serves as an essential component of the RFC complex, responsible for facilitating DNA replication and repair through its role in loading the PCNA sliding clamp onto DNA. Emerging evidence underscores its significant involvement in tumor progression and therapeutic resistance. RFC4 has been consistently observed to exhibit preferential upregulation in cancer tissues compared to normal counterparts, promoting carcinogenic processes across various malignancies. 18 – 21 In colorectal cancer, elevated RFC4 expression demonstrates significant correlation with inadequate tumor regression and unfavorable prognosis among locally advanced rectal cancer patients receiving neoadjuvant chemoradiotherapy, thereby emphasizing its contribution to radiotherapy resistance. 18 In lung cancer models, RFC4 potentiates tumorigenic capacity and metastatic potential through Notch signaling activation while simultaneously conferring therapeutic resistance to cancer cells. 21 These findings collectively describe the functional impacts of RFC4 on cancer biology and treatment resistance with a tumor type specificity. Regarding glioma, however, RFC4 remains insufficiently characterized, with its potential involvement in tumor proliferation and treatment responsiveness yet to be elucidated. In this study, we observed the correlation between RFC4 upregulation and TMZ resistance in GBM cells in an autophagy-dependent manner. Through coimmunoprecipitation (Co-IP) followed by mass-spectrometry (MS) analysis, we identified interaction of RFC4 with STK38. Mechanistical investigation revealed that RFC4 stabilized STK38 and facilitates BECN1 recruitment by STK38, which enhanced STK38-BECN1 complex formation to induce autophagy. Thus, our findings herein established an RFC4-STK38-BECN1 regulatory axis underlying TMZ resistance, providing a mechanistic foundation for targeting autophagy in GBM therapy. Results RFC4 upregulation in GBM is correlated with temozolomide resistance and poor prognosis. Analysis on CGGA and TCGA_GBM glioma databases revealed that RFC4 mRNA level was markedly elevated in GBM compared to non-tumor counterparts ( Fig. 1 A ) . Moreover, RFC4 mRNA level was positively correlated with glioma progression ( Fig. 1 B ) . Using other glioma databases, we consistently observed upregulation of RFC4 mRNA (Fig. S1 A) . Immunohistochemistry of a tissue microarray containing 143 GBM and 16 adjacent non-tumor tissues confirmed this oncogenic upregulation ( Fig. 1 C ) . Receiver operating characteristic (ROC) curve analysis revealed high predictive accuracy of RFC4 on GBM in clinic ( Fig. 1 D ) . Analysis on CGGA database further demonstrated increased RFC4 in recurrent glioma tissues versus primary counterparts (Fig. S1 B) . Kaplan-Meier survival analysis indicated that RFC4 predicted adverse clinical outcomes, including reduced overall survival (OS) (Fig. S1 C) and reduced recurrence-free survival (RFS) (Fig. S1 D) using TCGA_GBMLGG and/or CGGA databases. These findings indicated that RFC4 could be used as a prognostic marker and might play oncogenic roles of RFC4 in glioma. TMZ remains a major therapeutic regimen for glioma through inducing DNA alkylation damage, which promoted us to explore whether RFC4 was involved in the TMZ response of glioma cells. Using a panel of glioma cells, including one primary GBM cell line (091214) and four commercial GBM cell lines (A172, DBTRG-05MG, LN229, and U251), we surprisingly observed an upregulation of RFC4 mRNA and protein with TMZ treatment in a dose-dependent manner ( Fig. 1 E and 1 F ) , implying that RFC4 was a TMZ-responsive gene. In accordance with this notion, we found that glioma patients receiving pharmaceutical therapy harbored higher levels of RFC4 mRNA than those not receiving any intervention therapy using TCGA_GBMLGG database (Fig. S1 E) . High expression of RFC4 in patients receiving radio-chemo therapy or chemo therapy was associated with shortened overall survival of glioma patients (Fig. S1 F) . Then, we used U251 and LN18 cells to construct RFC4 overexpression and depletion stable cells to measure the IC 50 of TMZ (Fig. S1 G and S1H) . The result showed that increased or decreased RFC4 expression was associated with high or low TMZ IC 50 , respectively, in the two GBM cell lines ( Fig. 1 G and 1 H ) , which suggested that RFC4 might be related with TMZ resistance in GBM cells. To examine this assumption, we used LN229 cells to construct TMZ-resistant counterparts (LN229/RI) through treatment of TMZ with gradually increasing concentration. Compared with parental LN229, LN229/RI showed remarkably increased TMZ IC 50 and RFC4 mRNA level ( Fig. 1 I and 1 J ) . We then performed assays for transposase accessible chromatin with high-throughput sequencing (ATAC-seq) to analyze the impact of TMZ on chromatin accessibility. Consistent with TMZ-induced upregulation of RFC4, we noticed a remarkable accessibility of RFC4 enhancer ( Fig. 1 K ) . Together, these results demonstrated RFC4 as an oncogenic driver in GBM progression and responder to TMZ treatment, highlighting its involvement in TMZ resistance and dampened survival of glioma patients. RFC4 serves as a modulator for autophagy. Autophagy serves as a crucial cellular survival mechanism during various stress conditions and has been found to be critically involved in TMZ resistance of glioma cells. Indeed, geneset enrichment analysis (GSEA) 22 demonstrated that recurrent GBM dramatically enriched REACTOME_AUTOPHAGY geneset compared with primary GBM using CGGA database (Fig. S2A and S2B) , indicating the involvement of autophagy in treatment resistance of GBM. Interestingly, we also noticed significant positive correlation between RFC4 mRNA and KUMAR_AUTOPHAGY_NETWORK geneset through Pearson correlation analysis using TCGA_GBMLGG and CGGA databases ( Fig. 2 A ) . Similarly, GSEA revealed that high expression of RFC4 enriched REACTOME_AUTOPHAGY geneset compared with low expression of RFC4 using CGGA database (Fig. S2C and S2D) . In addition, analysis on TCGA_GBMLGG database revealed significant correlations between RFC4 and several key autophagy-regulated genes ( Fig. 2 B ) . Moreover, RFC4 overexpression in GBM cells leaded to an increase of LC3B-Ⅱ, indicating the activation of autophagy ( Fig. 2 C ) . Immunofluorescence (IF) and transmission electron microscope (TEM) analysis clearly indicated the increase of autophagic flux ( Fig. 2 D ) and autophagosomes with RFC4 overexpression ( Fig. 2 E ) . Then, we explored the effects of RFC4 on TMZ-induced autophagy. In LN229 cells, long time treatment of TMZ induced upregulation of autophagic markers, while in RFC4 depleted LN229 cells, the TMZ-induced autophagy was repressed ( Fig. 2 F ) . Consistently, IF and EM data demonstrated TMZ-induced autophagic flux and autophagosomes were indeed suppressed by RFC4 depletion ( Fig. 2 G and 2 H ) . Thus, TMZ-induced autophagy largely relied on RFC4 in GBM cells. Blocking autophagy sensitizes GBM cells with RFC4 overexpression to TMZ. Colony formation assay using GBM cells with forced expression of RFC4 showed that RFC4 rendered resistance of the cells to TMZ (100µM), while combined administration of autophagy inhibitor, chloroquine (CLQ, 25µM), significantly inhibited the cell proliferation of GBM cells ( Fig. 3 A ) . Then, we examined autophagy-inhibition effects in orthotopic mouse model utilizing U251 cell line with stable expression of luciferase ( Fig. 3 B ) . U251 cells with empty or RFC4 overexpression were orthotopically inoculated into NOD-SCID mice to evaluate tumorigenicity. The results showed that RFC4 could effectively promote in vivo growth of GBM cells in brain. Although TMZ (5mg/kg) treatment could inhibited the in vivo growth of U251/empty cells but barely suppressed that of U251/RFC4 cells, confirming the TMZ-resistant role of RFC4 in vivo . However, combination of TMZ and CLQ (80mg/kg) could effectively block the growth of U251/RFC4 cells ( Fig. 3 C ) . Survival analysis suggested that combination of TMZ and CLQ could improve survival of mice bearing GBM and reverse RFC4-induced TMZ resistance ( Fig. 3 D ) . Thereby, our results suggested that RFC4-related TMZ resistance was mediated by autophagy of GBM cells. STK38 interacts with RFC4 and plays oncogenic roles in GBM cells. To further investigate the downstream target pathway regulated by RFC4, we employed immunoprecipitation and mass spectrometry techniques (Co-IP-MS) to profile interactome of RFC4 ( Fig. 4 A ) . Combining Co-IP-MS data from two cell lines identified 791 proteins as potential binding partners for RFC4 ( Fig. 4 B ) . Functional enrichment assay indicated that the binding partners of RFC4 enriched ATP hydrolysis activity, which is a critical process in lysosome and closely involved in autophagy ( Fig. 4 C ) . Among 791 RFC4-binding proteins, STK38 (serine/threonine kinase 38, also known as NDR1) was found to strongly interact with RFC4 ( Fig. 4 B ) . Co-transfection of RFC4 and STK38 in 293T cells followed by Co-IP confirmed the interaction between the two proteins ( Fig. 4 D ) . Consistently, Co-IP using U251 or LN18 with RFC4 overexpression cells recombinant RFC4 protein further confirmed the interaction between RFC4 and endogenous STK38 ( Fig. 4 E ) . We also incubated recombinant RFC4-GST and STK38-His proteins in reaction buffer followed by GST pulldown assay and the result demonstrated the direct interaction between the two proteins ( Fig. 4 F ) . Notably, immunofluorescence data revealed that the interaction between RFC4 and STK38 was significantly enhanced with TMZ treatment ( Fig. 4 G ) . STK38 is a protein kinase and plays important roles in autophagy. 23 – 25 Analysis on TCGA_GBMLGG and CGGA databases demonstrated that the expression level of STK38 was notably increased in glioma patients, and this elevation is further amplified as the tumor malignancy progresses (Fig. S3A) . Moreover, STK38 mRNA level was progressively elevated with the glioma histopathological grades (Fig. S3B) , significantly upregulated in IDH-wildtype versus mutant subgroups (Fig. S3C) , and differentially regulated in chemoradiation-treated versus untreated cohorts (Fig. S3D) . Notably, TMZ treatment upregulated STK48 mRNA level in multiple GBM cell lines (Fig. S3E) , which was similar to TMZ-induced RFC4 increase. Survival analyses consistently exhibit shorter overall survival in STK38-high patients across CGGA301, CGGA325, and CGGA693 cohorts (Fig. S3F) , implying STK38 as a robust prognostic biomarker in GBM. STK38 functions as a cooperative regulator of RFC4-mediated autophagy. Significantly positive correlation of RFC4 and STK38 was also observed in glioma (Fig. S4A) . Protein interaction network analysis revealed RFC4 as a central hub, directly connected to STK38, and forming a functional module with replication factors (RFC3, RFC5, PCNA) ( Fig. S4B ). Meanwhile, co-upregulation of RFC4 and STK38 produced more worse survival than downregulation of each of/both the two genes (Fig. S4C and S4D) . These data suggested a novel relationship between RFC4 and STK38 in GBM cells. To delineate the structure basis for the interaction between RFC4 and STK38, we constructed various truncated forms for RFC4 and STK38, respectively ( Fig. 5 A ) . We found that RFC4 lacking N-terminal (1-380) domains could not bind to STK38, while all three STK38 truncated forms could interact with N-terminus of RFC4 ( Fig. 5 B ) . To predict the binding pattern between the STK38 and RFC4 proteins, molecular docking analysis was conducted using protein-protein docking methods in the ClusPro server ( https://cluspro.org/help.php ). The docking results was visualized by PyMOL program and revealed that the amino acid residues T235, R211, Y299, E137, and E143 within the STK38 protein possessed the capability to form hydrogen bonds with the amino acid residues E99, F96, V105, R93, and K43 within the RFC4 protein ( Fig. 5 C ) . Notably, increased expression of RFC4 elevated the stability of STK38 protein ( Fig. 5 D ) . Suppression of STK38 considerably attenuates the RFC4-induced autophagy, featured with downregulation of LC3B-Ⅱ ( Fig. 5 E ) . Together, these results suggested that STK38 was stabilized by RFC4 and required for autophagy occurrence in GBM cells. RFC4 facilitates STK38-BECN1 interaction in a STK38-T444-dependent manner. It has been reported that STK38 activates autophagy mainly through its interaction with the autophagosome membrane-forming proteins, BECN1. 25 We performed His pull-down assay and confirmed a direct interaction between STK38 and BECN1 ( Fig. 6 A ) . Moreover, we observed that RFC4 expression significantly enhanced STK38 recruitment to BECN1 in a dose-dependent manner ( Fig. 6 B ) . Furthermore, in the TMZ-resistant GBM cells, STK38 and BECN1exhibited significantly enhanced accessibility (Fig. S5A) . As demonstrated in previous studies, phosphorylation at STK38-S281 and T444 sites represents its active state. K118 and D230 mutations eliminate STK38's kinase activity, while the S91 site is crucial for its stability. 26 In order to find the specific action site of STK38, we engineered various mutant plasmids of STK38 and co-transfected them with RFC4 and BECN1 into 293FT cells. The result indicated that only the T444A mutation in STK38 diminished its recruitment capability to BECN1 ( Fig. 6 C ) . To predict the binding pattern between the RFC4, STK38, and BECN1 proteins, molecular docking analysis was conducted using protein-protein docking methods in the Autodock server. 27 The docking result was visualized through PyMOL, revealing that the affinity of RFC4-STK38WT-BECN1 proteins was stronger than RFC4-STK38Mu-BECN1 proteins. The RFC4-STK38Mu-BECN1 protein complexes were reduced when STK38 was mutated at T444 ( Fig. 6 D ) . Additionally, STK38-T444A mutation suppressed autophagy activation, which might work through conformational changes in STK38 tertiary structure (Fig. S5B) . Thus, RFC4-STK38-BECN1 axis was functionally required for autophagy. STK38 is required for RFC4 biological functions in GBM cells with T444 as critical site. To evaluate the involvement of STK38 in RFC4 functions, we constructed RFC4 forced expression cells in combination with STK38 knockdown. Then, the STK38 expression was rescued by wild-type STK38 or STK38 T444A (Fig. S5C) . Colony formation and CCK8 assays indicated loss of STK38 attenuated RFC4-promoted growth of GBM cells ( Fig. 7 A and 7 B ) . Overexpression using STK38 wild-type in GBM cells with RFC4 and shSTK38 rescued RFC4 effects but not overexpression using STK38 T444A ( Fig. 7 A and 7 B ) . Increased TMZ IC 50 of GBM cells by RFC4 high expression could be repressed by loss of STK38. However, wild-type STK38, but not STK38 T444A mutant, could elevate the TMZ IC 50 of GBM cells with RFC4 overexpression and STK38 depletion ( Fig. 7 C ) . Similarly, orthotopical mouse model using U251 cells demonstrated depletion of STK38 leaded to growth inhibition of GBM cells with RFC4 overexpression ( Fig. 7 D ) . Rescue with wild-type STK38 consistently recovered in vivo growth of GBM cells but STK38 T444A failed to do so ( Fig. 7 D ) . Survival analysis also supported the involvement of STK38 activity in RFC4-enhance growth of GBM cells ( Fig. 7 E ) . Therefore, our data demonstrated that STK38 acted as an important mediator for RFC4 functions in GBM cells. Discussion Although autophagy has been documented to facilitate the development of TMZ resistance in GBM, how the autophagy is induced and regulated remains to be elucidated and targeting autophagy as a therapeutic regimen for GBM is challenging. In this study, we reported a novel function of RFC4 in the development of TMZ resistance through autophagy induction. Mechanistically, RFC4 stabilized STK38 and facilitated STK38 and BECN1 interaction for autophagy activation. It has been known that STK38 is required for early steps of autophagosome formation through binding with BECN1. 25 The formation of RFC4-STK38-BECN1 complexes promoted the formation of autophagosomes, leading to TMZ resistance of GBM cells ( Fig. 8 ) . Therefore, interfering with the RFC4-STK38-BECN1 complexes could be promising regimen for GBM treatment. TMZ remains a cornerstone of GBM therapy by attacking tumor cell DNA and inducing DNA alkylation damage. This mechanism provides a mechanistic basis for the observed upregulation of RFC4 enhancer accessibility and expression in both TMZ-treated GBM cell models and patients. Notably, however, RFC4 activation shows no statistical significance in radiotherapy-treated GBM patients, 21 possibly due to differential stress responses. Furthermore, elevated RFC4 expression correlates with reduced overall survival in glioma patients and specifically in TMZ-treated glioma cohorts. These findings establish RFC4-targeted interventions as a novel therapeutic avenue for glioma patients, including those developing resistance or experiencing relapse post-TMZ therapy. Strategic targeting of RFC4-associated pathways may yield innovative treatments, such as precision approaches to suppress pathological RFC4 activity or leverage synthetic lethality in RFC4-dysregulated cancer cells. Autophagy has attracted substantial research interest since its initial characterization. 12 , 14 This process exhibits dual roles in GBM cells - promoting either survival or death under metabolic and therapeutic stress conditions, with outcomes determined by stress context and intensity. 8 , 28 While autophagy modulation has demonstrated therapeutic potential in glioma management, 9 , 29 variable treatment efficacy persists due to target selection challenges and patient heterogeneity. Our investigations revealed RFC4-mediated autophagy activation across multiple GBM cell lines. Functionally, such autophagy induction suppressed cell death mechanisms while enhancing glioma cell viability. 16 , 30 Chloroquine-mediated autophagy inhibition effectively counteracted RFC4’s pro-tumorigenic effects, confirming autophagy as the principal downstream effector pathway. A critical requirement for implementing RFC4-targeted therapies in TMZ-based GBM treatment lies in fully elucidating the molecular mechanisms through which newly discovered binding partners activate RFC4 signaling. Mass spectrometry (MS) analyses systematically mapped RFC4’s primary binding partners, with our study definitively mapping the RFC4 interactome in GBM cells and revealing its essential partnership with STK38. STK38 kinase has been recognized as an upstream controller of autophagy signaling networks. 24 , 25 Emerging evidence further establishes STK38’s multifaceted involvement through direct associations with core autophagy components. 31 STK38 deficiency significantly attenuated RFC4-driven autophagy activation, while RFC4 demonstrated TMZ-responsive activation even at subtherapeutic concentrations, suggesting greater TMZ sensitivity than STK38. Integrative analysis of TCGA_GBM datasets established co-overexpression of RFC4 and STK38 as a key determinant of reduced survival and accelerated recurrence in glioma patients. We precisely determined the interaction interface between full-length STK38 and RFC4’s N-terminal region (NTR, residues 1-250). Given that STK38’s N-terminal domain (residues 1–82) contains an autoinhibitory sequence, 24 our findings suggest RFC4 binding may relieve this intrinsic inhibition. Mechanistic investigation of STK38’s role in autophagy revealed its scaffolding function, bridging RFC4 with BECN1 - a core regulator of autophagy initiation. 24 Our data further showed that RFC4-STK38 binding enhanced STK38 protein stability, thereby increasing BECN1 recruitment efficiency. Notably, kinase-dead STK38 mutants maintained full capacity to form BECN1 complexes and activate autophagy when stimulated by RFC4, demonstrating kinase-independent functionality. Collectively, these results establish that TMZ-triggered RFC4 activation propels autophagic flux via the STK38-BECN1 axis, where STK38 operates as a structural platform facilitating BECN1 interaction, ultimately amplifying cytoprotective autophagy in GBM cells. Through systematic investigation of STK38’s regulatory role in autophagy induction, we identified the T444 phosphorylation site as essential for maintaining RFC4-STK38-BECN1 complex stability. The hydrophobic motif (HM) autophosphorylation site at T444 represents a critical post-translational modification that drives STK38’s functional activation. 32 Molecular dynamics simulations demonstrated that T444 phosphorylation-deficient STK38 mutants display compromised BECN1 binding capacity, leading to defective autophagosome maturation. This molecular impairment translated to significantly reduced GBM cell viability and diminished tumorigenicity in orthotopic models. Our integrative approach establishes T444 phosphorylation as a biochemical rheostat controlling the STK38-BECN1 axis - its absence triggers structural destabilization that converts cytoprotective autophagy into a tumor-suppressive mechanism, revealing a targetable vulnerability for precision oncology. Collectively, these discoveries establish a paradigm-shifting framework for addressing TMZ resistance in GBM. Future investigations should focus on developing RFC4-STK38 axis-targeting agents, particularly small-molecule inhibitors disrupting RFC4 NTR-STK38 binding or modulating STK38 kinase activity, to synergize with TMZ and resensitize refractory tumors. Concurrently, implementing RFC4/STK38 expression-based patient stratification could optimize precision clinical trial designs, enabling personalized therapeutic approaches for recurrent or treatment-resistant cases. The identified synthetic lethality mechanism may extend beyond GBM to other malignancies sharing analogous RFC4-STK38 pathway dependencies. Furthermore, deploying cutting-edge methodologies like spatial multi-omics platforms and dynamic autophagic flux monitoring could decode spatiotemporal regulatory networks, transforming mechanistic discoveries into clinical applications. By dismantling cancer cells’ adaptive survival mechanisms, this work fundamentally repositions therapeutic strategies for glioblastoma, offering a roadmap to significantly improve patient outcomes. Materials and methods Cell culture DMEM (10,566,016), penicillin-streptomycin (15,140,122), fetal bovine serum (FBS) (10,270,106), Dulbecco’s phosphate-buffered saline (DPBS; 14,190,094) and trypsin-EDTA (25,200,056) were purchased from Gibco® (Life Technologies). The human glioma cell line U251, Ln18, LN-229, A172 and DBTRG-05MG was obtained from Institute of Pathology and Southwest Cancer Center, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China. 33 Cells were cultivated in DMEM, high glucose, 10% FBS and 100 U/mL penicillin-streptomycin at 37°C and 5% CO 2 . Cells were exposed to Temozolomide (MedChemExpress, HY17364) and Cycloheximide (MedChemExpress, HY12320), chloroquine diphosphate salt (chloroquine; Sigma-Aldrich, C6628) for the indicated time periods. Lentivirus packing in 293-FT cells For depletion and overexpression of target genes, virus particles were generated in 293-FT cells transfected with the control vector or the respective plasmid, the gag/pol plasmid pCMV-dr8.91 and the VSV-g envelope plasmid pMD2. G (Addgene, 12,259). Cells were transfected by using Lipofectamine 3000 (Thermo Fisher Scientific, L3000008) according to manufacturer’s instructions. The DNA mixture was added drop-wise to the cells and incubated for 6–8 h at 37°C and 5% CO 2 . After incubation the medium was replaced with fresh medium. 48 h and 72h after transfection the virus-containing supernatant was harvested and stored short-term at 4°C. Lentivirus were added directly in cells with polybrene (MedChemExpress, HY112735). Medium was changed after 24h and cells with stable integration of target genes were selected with puromycin or hygromycin. Immunoblot analysis For immunoblot analysis, cells were lysed with RIPA Lysis Buffer (Strong) (50 mM Tris (pH 7.4), 150 mM NaCl, 1% Triton X-100, 1% sodium deoxycholate, 0.1% SDS, and general protease and phosphatase inhibitors (cOmplete™ Protease Inhibitor, PhosSTOP) [Roche, 4693116001, 04906837001]. The protein amount was determined with a Pierce BCA protein assay kit (Thermo Fisher Scientific, 23,225). The SDS gels (8% – 15%) were loaded with 30–50 µg protein in 4x Laemmli protein sample buffer (250 mM Tris-HCl, pH 6.8, 10% SDS, 30% glycerol, 0.02% bromophenol blue (Bio-Rad, 1610747), after heating the samples for 5 min at 95°C. Proteins were separated (80 V for 30 min, then 120 V) and blotted semi-dry (15 V, 35 min) onto a PVDF membrane (Bio-Rad, 1620177). The membranes were blocked with 5% milk in TBS (150 mM NaCl [50 mM Tris, pH 7.5) + 0.05% Tween 20 (TBS-T) for 1 h at room temperature, followed by incubation with the primary antibodies overnight at 4°C:, LC3B (Abcam, ab63817), BECN-1 (Cell Signaling Technology, 4122), RFC4 (Novus biologicals, NBP2-45946), p62 (Cell Signaling Technology, 23214), Flag (Cell Signaling Technology, 14793), Myc(Cell Signaling Technology, 2276), GFP (Cell Signaling Technology, 2956), STK38 (Thermo Fisher Scientific, PA5-76351), β-actin (Cell Signaling Technology, 4970). Assessment of gene expression by quantitative real-time polymerase chain reaction (qRT-PCR) For determination of gene expression by qRT-PCR, RNA was isolated with the EXTRACTME total RNA Kit according to the manufacturer’s instructions (Bioscience, EM09.1–250). Next, 1–2 µg RNA, superscript III reverse transcriptase (Thermo Fisher Scientific, 18,080,044) and random primers were used in a total volume of 20 µL for cDNA synthesis according to the manufacturer’s protocol. cDNA was diluted with 80–180 µL DEPC-H 2 O (Carl Roth GmbH + Co. KG, T143.1). For qRT-PCR, 5µL cDNA, 1µl 1xTaqMan Gene Expression Assay primer and 10µl 1xFastStart Universal Probe Master-mix (Roche 3439 Diagnostics GmbH, 04913957001) were applied. Relative gene expression levels were calculated by using the comparative CT method. Samples were normalized to the reference gene TBP (TATA-box binding protein). The following primers were used: Forward-5’-GCAACTCAGCTCGTCAATCAACTC-3’, Reverse 5’-AGGCATTTGTCAACTTCGGCAAG-3’ (RFC4), Forward 5’-TCGTGCGGAGCGTGACATTC, Reverse 5’-CCAGGCAGGAACTCCATGATTAGG-3’ (STK38) (Thermo Fisher Scientific). Generation of shRNA KD cell lines For depletion of RFC4/STK38 virus particles were generated in HEK 293-T cells transfected with the control vector or the respective shRNA plasmid (designed and synthesized by Shanghai Sangon Biological Engineering Technology & Services Company) gag/pol plasmid pCMV-△8.91 and the VSV-g envelope plasmid pMD2. G (Addgene, 12,259). The plasmid was transfected into HEK293 cells using Lipofectamine 3000 (Thermo Fisher Scientific, L3000015). The plasmids were diluted in DMEM while blowing air bubbles through a Pasteur pipette and incubated for 15–20 min. The DNA mixture was added drop-wise to the cells and incubated for 6–8 h at 37°C and 5% CO2. After incubation the medium was replaced with fresh medium. 24 h and 48 h after transfection the virus-containing supernatant was harvested and stored short-term at 4°C. For transduction, 120,000 parental GBM cells were seeded out in 6-well plates. Next day cells were incubated for 24 h with the virus-containing supernatant diluted in culture medium and 3µg/mL polybrene. Afterward medium was changed and after additional 24h the medium was changed to selection medium containing 1 µg/mL puromycin. KD was confirmed by immunoblot analysis. Protein expression and purification The plasmid was transfected into HEK293 cells using Lipofectamine 3000 (Thermo Fisher Scientific, L3000015). After culture at 37℃ under 5% CO2 for 6 days, cells were collected and lysed by 1XPBS (pH 7.2–7.4), and the insoluble fraction was removed by centrifugation at 30,000xg for 30 min. Supernatants were incubated with protein A-agarose for 1–2 h and washed extensively. The protein was eluted by 0.1M glycine (pH 3.0) and neutralized with 1M Tris-HCl (pH8.5), and then concentrated to 1mg/ml and stored at -80℃. Immunoprecipitation The experimental procedure for immunoprecipitation commenced with cell harvesting and lysis using ice-cold RIPA buffer supplemented with protease inhibitors. After incubation on ice for 30 minutes, the lysate was centrifuged at 12,000×g for 15 minutes at 4°C to pellet cellular debris. The clarified supernatant was incubated overnight at 4°C with VHH-Sepharose® magnetic beads (Antibody Life Biotechnology) pre-coupled with specific antibodies under constant rotation. Magnetic bead complexes were isolated using a dedicated separator and washed three times with chilled Tris-buffered saline containing 0.1% Tween-20. Proteins were dissociated by boiling in Laemmli sample buffer at 95°C for 10 minutes, followed by immediate SDS-PAGE analysis. Negative controls using antibody-free beads from the same manufacturer were included to validate target-specific binding. All steps involving protein handling were performed at 4°C to preserve complex integrity, with reagents from Antibody Life Biotechnology maintained at recommended storage temperatures prior to use. The IP/MS analyses The IP/MS analyses were designed and analyzed by PTM Biological Company. Briefly, it was performed using a triple quadrupole mass spectrometer QTrap 5500 (Sciex, Darmstadt, Germany) equipped with a Turbo V Ion Source operating in positive electrospray ionization mode. The analysis was done in Multiple Reaction Monitoring (MRM) mode. Precursor to product ion transitions (m/z) for analysis and internal standards are shown in the supplementary methods. Data Acquisition was done using Analyst Software V1.6.2 and quantification was performed with MultiQuant Software 3.0.2 (both Sciex, Darmstadt, Germany), employing the internal standard method (isotope dilution mass spectrometry). Calibration curves were calculated by linear or quadratic regression with 1/x or 1/x2 weighting. Variations in accuracy of the calibration standards were less than 15% over the whole range of calibration, except for the lower limit of quantification, where a variation in accuracy of 20% was accepted. For the acceptance of the analytical run, the accuracy of the QC samples had to be between 85% and 115% of the nominal concentration for at least 67% of all QC samples. GST pull down The GST pull-down protocol was initiated by expressing GST-tagged recombinant proteins in BL21(DE3) Escherichia coli through 0.5 mM IPTG induction at 16°C for 20 hours. Bacterial pellets were lysed in ice-cold GST-binding buffer (50 mM Tris-HCl pH 8.0, 150 mM NaCl, 1% Triton X-100) supplemented with lysozyme and protease inhibitors. Following sonication and centrifugation at 15,000×g for 30 minutes at 4°C, the clarified lysate was incubated with pre-equilibrated GST-VHH nanomagnetic beads (Antibody Life Biotechnology, Cat# GST-NM102) for 2 hours at 4°C with gentle agitation. The bead-protein complexes were magnetically captured and sequentially washed with high-salt buffer (500 mM NaCl) and low-salt buffer (50 mM NaCl) to remove nonspecific binders. Competitor proteins or cell lysates containing putative interaction partners were then introduced to the immobilized GST fusion proteins and incubated for 4 hours under rotational mixing. After three stringent washes with GST elution buffer lacking reducing agents, specifically bound proteins were competitively eluted using 10 mM reduced glutathione in 50 mM Tris-HCl (pH 8.0) for downstream immunoblotting or mass spectrometry analysis. Control experiments with untagged protein lysates and GST-empty nanomagnetic beads from the same manufacturer were systematically included to exclude artifacts. All Antibody Life Biotechnology reagents were quality-controlled for batch consistency, with nanomagnetic beads stored at 4°C in glycerol-containing preservation buffer until use. Construction of shRNA-resistant STK38 plasmid​ To generate a shRNA-resistant STK38 expression plasmid, we designed a mutant construct with nucleotide substitutions in the shRNA-targeted region to disrupt base pairing while preserving the encoded protein sequence. The shRNA PLVE4507-1 targets the STK38 sequence ​CAGCAAGGGCCATGTGAAA (positions663–683 in the wild-type genomic DNA), which overlaps with the stem-loop (STEMP) and loop regions in the viral vector backbone. Two-point mutations were introduced into the STEMP sequence: ​G9A​ (position 9, G→A), T15C (position 15, T→C), converting the original sequence to ​CAGCAAGGACCATGCGAAA. This mutation disrupts the stem-loop secondary structure critical for shRNA binding while maintaining the amino acid sequence at the corresponding protein locus. The mutant fragment was synthesized via overlap extension PCR using Phusion High-Fidelity DNA Polymerase (New England Biolabs) with the following primers: Forward primer (F):​​5'- CAAGGACCATGCGAAACTTTCTGACTTTGGTCTTTGCA − 3', Reverse primer (R):​​ 5'- AGTTTCGCATGGTCCTTGCTGTCCAAAAGAAGGTT − 3'. The ligation product was transformed into Stbl3 chemically competent E. coli (Thermo Fisher Scientific), and plasmid DNA was extracted using a HiSpeed Plasmid Midi Kit (Qiagen). Site-directed mutagenesis Using a high-fidelity PCR-based approach with Phusion DNA polymerase (New England Biolabs). The plasmid template containing the wild-type STK38 gene was amplified with primers flanking the target site, designed using SnapGene software. PCR products were treated with DpnI (NEB) to digest methylated template DNA, followed by ligation using T4 DNA ligase (NEB). Competent E. coli cells (DH5α) were transformed with ligated products, and positive colonies were selected via colony PCR. Plasmid DNA was extracted (QIAGEN MinElute Kit), and mutations were confirmed by Sanger sequencing (Genewiz). ATAC-seq data visualization using IGV​ Processed ATAC-seq data were visualized using the Integrative Genomics Viewer (IGV v2.16.2) with strict adherence to the GRCh37/hg19 reference genome assembly. 34 BAM alignment files and normalized BigWig coverage tracks were loaded following coordinate conversion using CrossMap v0.6.3 to ensure compatibility with the hg19 genomic framework. Visualization parameters were optimized through iterative adjustment of sequencing depth thresholds (1–10× in collapsed view mode) and coverage normalization (0-100 reads per million, RPM), while maintaining the diagnostic 200-bp Tn5 transposase cleavage periodicity at transcription start sites (TSSs) as critical quality control criteria. Comparative analyses incorporated ENCODE Consortium annotations (Version 3, hg19) of regulatory elements, with chromatin accessibility patterns contextualized against Roadmap Epigenomics Project ATAC-seq datasets mapped to the same genome build. Spatial relationships between differential accessibility regions and known genomic features were verified through multi-track visualization using consistent color schemes (BAM: grayscale gradient; BigWig: royal blue) and layer transparency settings (40–60%). High-resolution snapshots (300 DPI, 1600×900 pixels) of representative loci were acquired using IGV’s batch image export function with standardized chromosome coordinate ranges. Orthotopic xenograft NOD-SCID mice were injected intracranially with U251 cells (5 × 10 4 ) with pLVX-puro-linker-luciferase lentivirus via the right frontal lobe on a 4–6-week-old basis (Animal Facility of West China Fourth Hospital, China). The mice were housed in large plastic cages in groups of 10 and kept pathogen-free. An In Vivo Image System (IVIS) (PerkinElmer, USA) was used to detect and quantify growing xenograft tumors. Tumors were collected from mice with neurological signs or that were moribund. The animal experiments were approved by the Institutional Animal Care and Use Committee of West China Fourth Hospital, Sichuan University in accordance with the Guide for the Care and Use of Laboratory Animals. Ethics Statement The study was conducted in accordance with the Declaration of Helsinki. Ethical approval for this study was obtained from the Institutional Review Board of West China Fourth Hospital, Sichuan University. Statistics Analysis of proteome data was performed in Perseus. Only proteins with P < 0.01 based on a student´s t-test were considered significant. GraphPad Prism 9 (GraphPad Software, La Jolla CA, USA) was used for statistical analysis of all other data. To determine if the data set is well-modeled by a normal distribution, a Shapiro Wilk normality test was performed. In case of normally distributed data, the data set was analyzed with a one- or two-way ANOVA. For non-normally distributed data, the nonparametric Mann-Whitney U-test or Kruskal-Wallis test was used. The minimum level of statistical significance was set at P < 0.05 and significances are depicted as *P < 0.05, **P < 0.01, and ***P < 0.001, or n.s. (not significant) between control and treated cells or as indicated with brackets. Declarations Funding: This work was supported by The National Key Research and Development Program of China (2022YFA1104303 to Y.W.), The National Natural Science Foundation of China (81802508 to M.M., 82202908 to Q.-J.G., 82172854 to S.-L.X.), The Natural Science Foundation of Chongqing (CSTB2022NSCQ-MSX0206 to M.M., CSTB2022NSCQ-MSX028 to Q.-J.G.), The Natural Science Foundation of Sichuan Province (2024NSFSC1523 to M.M.), China Postdoctoral Science Foundation (GZC20231814 to M.M.), The Outstanding Youth Science Foundation of Sichuan Province (2023NSFSC1927 to X.W.), and Jinfeng Laboratory Start Funding (to Y.W.). Disclosure statement All authors declare no conflict of interest. References Alexander, B. M. & Cloughesy, T. F. Adult Glioblastoma. J Clin Oncol 35 , 2402-2409, doi:10.1200/JCO.2017.73.0119 (2017). Chen, R., Smith-Cohn, M., Cohen, A. L. & Colman, H. Glioma Subclassifications and Their Clinical Significance. 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EPHA2 mediates PDGFA activity and functions together with PDGFRA as prognostic marker and therapeutic target in glioblastoma. Signal Transduct Target Ther 7 , 33, doi:10.1038/s41392-021-00855-2 (2022). Thorvaldsdóttir, H., Robinson, J. T. & Mesirov, J. P. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Briefings in bioinformatics 14 , 178-192, doi:10.1093/bib/bbs017 (2013). Additional Declarations There is NO Competing Interest. Supplementary Files YWSupplementaryInfo.docx Supplementaty Indo 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6854944","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":473748032,"identity":"2cd03916-f073-40d2-bf97-12e26d4376f1","order_by":0,"name":"Yan Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvElEQVRIiWNgGAWjYNCCCijNQ7yWMwakamFsI0WLwY3kZw+/zvsTrTsjgfHB2zYGeXPCWtLMjWW3GeRuu5HAbDi3jcFwZwMhLbcTzKQlIVrYpHnbGBIMDhDUkv5NWnIOWAv7byK15JhJfmyA2MJMlBbJ+2/KpBmOGeduO/OwWXLOOQnDDYS08J05vk3yR41c7rbjyQc/vCmzkSdoiwJQATMkOhgbgIQEAfVAIA9Ux/iDsLpRMApGwSgYyQAAuwFDbDWck5wAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-8150-5486","institution":"Army Medical University","correspondingAuthor":true,"prefix":"","firstName":"Yan","middleName":"","lastName":"Wang","suffix":""},{"id":473748033,"identity":"f67b2c31-8e5d-4d2e-9e09-d95710ef3f49","order_by":1,"name":"Min Mao","email":"","orcid":"","institution":"West China Second University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"Mao","suffix":""},{"id":473748034,"identity":"f4369281-5597-4a83-963a-203184c04e0c","order_by":2,"name":"Ji Hang","email":"","orcid":"","institution":"sichuan university west china hospital","correspondingAuthor":false,"prefix":"","firstName":"Ji","middleName":"","lastName":"Hang","suffix":""},{"id":473748035,"identity":"634cfdb8-5e7d-4662-abd0-b8964aaf17e8","order_by":3,"name":"Wenqian Yu","email":"","orcid":"","institution":"Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Wenqian","middleName":"","lastName":"Yu","suffix":""},{"id":473748036,"identity":"591531bb-943b-4282-8ae7-e4cd89ab9edf","order_by":4,"name":"Qu-Jing Gai","email":"","orcid":"","institution":"Third Military Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qu-Jing","middleName":"","lastName":"Gai","suffix":""},{"id":473748037,"identity":"47214d38-3e54-4b10-84a9-e37412665111","order_by":5,"name":"Sen-lin Xu","email":"","orcid":"","institution":"Institute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)","correspondingAuthor":false,"prefix":"","firstName":"Sen-lin","middleName":"","lastName":"Xu","suffix":""},{"id":473748038,"identity":"00dddf74-6ef3-42e9-9b36-3a7704f1575e","order_by":6,"name":"Meng-Li Zhu","email":"","orcid":"","institution":"Jinfeng Laboratory","correspondingAuthor":false,"prefix":"","firstName":"Meng-Li","middleName":"","lastName":"Zhu","suffix":""},{"id":473748039,"identity":"259822ab-cf4a-460d-96ba-dfd83cc7b638","order_by":7,"name":"Xi He","email":"","orcid":"","institution":"Shapingba Hospital affiliated to Chongqing University","correspondingAuthor":false,"prefix":"","firstName":"Xi","middleName":"","lastName":"He","suffix":""},{"id":473748040,"identity":"5febf43c-9693-48b0-aa03-ad5f69f1ff56","order_by":8,"name":"Xin Wang","email":"","orcid":"","institution":"Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-06-09 13:36:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6854944/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6854944/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85304586,"identity":"d7d6390a-a324-4f9b-a196-350bc335266b","added_by":"auto","created_at":"2025-06-24 12:36:51","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":5318868,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRFC4 functions as oncogene in glioma.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) RFC4 expression in GBM \u003cem\u003evs.\u003c/em\u003e non-tumor brain tissues using TCGA_GBM and CGGA databases. B) RFC4 expression in different grade gliomas using CGGA databases. C) Representative IHC showing intensified RFC4 staining in GBM specimens. D) Diagnostic ROC curve demonstrating RFC4’s discriminative power (AUC=0.962, P\u0026lt;0.0001). E) and F) Dose-responsive temozolomide (TMZ) induction of RFC4 (100-800μM, 24h) in multiple GBM cell lines. G) and H) IC\u003csub\u003e50\u003c/sub\u003e values were determined via CCK-8 assays in Ln18 and U251 glioblastoma cells engineered with RFC4 overexpression or shRNA-mediated knockdown. I) TMZ-resistant LN229 cells were established via chronic TMZ exposure protocol. J) RFC4 is dynamically upregulated in TMZ-resistant glioblastoma cells. K) ATAC-seq was used to detect the chromatin accessibility of RFC4 enhancers (186,806,038-186,806,649) in LN229 TMZ-resistant cells.\u003c/p\u003e","description":"","filename":"Figure1new.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6854944/v1/ff15f90e49a8e871948b67e0.jpg"},{"id":85305853,"identity":"62aa659d-308b-44e1-b69d-76747c7c8505","added_by":"auto","created_at":"2025-06-24 12:44:51","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2203804,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRFC4 enhances autophagy in GBM cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) Pearson correlation of RFC4 and autophagy signaling pathway in TCGA-GBM and CGGA693 database. B) Correlation heatmap indicating the target autophagy genes of RFC4 according to TCGA_GBM database. C) Forced expression of RFC4 with lentivirus significantly accelerated the expression of maker gene of autophagy (LC3B-Ⅱ) examined by western blotting. D) eGFP-mRFP-LC3B plasmid was constructed to indicate the autophagy state in U251 cell. Scale Bar = 10μm. E) Transmission electron microscopy (TEM) was used to assess the autophagosomes stimulated by RFC4. Scale bar = 1μm. F) Western blotting assay was conducted to detect the autophagy when RFC4 was knockdown by shRNA-encapsulated lentivirus. G) Using transmission electron microscopy to assess the autophagosomes formation when RFC4 was at low level. Scale bar = 1μm. H) TEM analysis revealed that RFC4 knockdown significantly suppressed autophagosome biogenesis.\u003c/p\u003e","description":"","filename":"Figure2new.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6854944/v1/8ea413cc6f288189becaba9f.jpg"},{"id":85304583,"identity":"03bcfcab-18a0-4eb2-94b5-565b86e0dd23","added_by":"auto","created_at":"2025-06-24 12:36:51","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1460726,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAutophagy mediates RFC4 oncogenic roles in GBM cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) Clone formation assay of tumor cell indicated a cell growth promotion effect of RFC4. CLQ (25µM, 48h) and TMZ (100µM, 48h) combination aborted the cell growth induced by RFC4. B) Experimental flowchart (left panel) and statistic graph of tumor size using bioluminescence signal intensity (right panel). n = 8 for each group. C) Representative images of orthotopic growth of U251 cells treated with vehicle, TMZ(5mg/kg), or TMZ + CLQ (80mg/kg). D) Overall survival time of mouse exposed by individual inhibitor or combination medications.\u003c/p\u003e","description":"","filename":"Figure3new.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6854944/v1/f2e8b50138a208c76520217d.jpg"},{"id":85305855,"identity":"15d7b703-f95e-4325-8957-43282a6f91b3","added_by":"auto","created_at":"2025-06-24 12:44:51","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":10105946,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRFC4 physically interacts with STK38 in GBM cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) Diagram of RFC4 binding proteome analysis by mass spectrometry detection. B) The top-10 RFC4-binding proteins with removing IgG-binding proteins. C) GO analysis of RFC4-binding proteomes. D) STK38-myc and RFC4-flag were concurrently transfected into 293FT cells, and STK38 and RFC4 were able to bind. IP: Flag. E) U251 and LN18 were infected with lenti-RFC4-flag to construct a stable strain, and the expressions of STK38, RFC4, and Flag were detected after co-immunoprecipitation with flag magnetic beads. F) GST-pull down experiment showing direct interaction between purified GST-RFC4 and His-STK38. The expressions of GST, RFC4, and STK38 were detected after immunoprecipitation with GST magnetic beads. G) Confocal detection of the colocalization of RFC4 and STK38 in LN18 and U251 cells.\u003c/p\u003e","description":"","filename":"Figure4new.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6854944/v1/766fe8b9f4eb8e27024d17d7.jpg"},{"id":85304612,"identity":"03160655-5f4a-448a-b176-d050cf8ff7e6","added_by":"auto","created_at":"2025-06-24 12:36:52","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":4641607,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSTK38 is required for RFC4-induced autophagy in GBM cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) Diagram of truncated plasmid of STK38-flag and RFC4-myc. B) RFC4-myc and STK38-flag plasmids were co-transfected into 293FT cells, and the functional domains of RFC4 and STK38 binding were detected. C) The binding mode of STK38 protein and RFC4 protein was analyzed by molecular docking simulation method. D) STK38 protein stability under RFC4 stimulus was assessed by treating cells with cycloheximide (CHX, 100μM) for the indicated time points, followed by Western blot analysis of protein levels. E) Knockdown of STK38 weakened the autophagy activation even RFC4 was forced overexpression.\u003c/p\u003e","description":"","filename":"Figure5new.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6854944/v1/912f548751f581b0f96a009b.jpg"},{"id":85305858,"identity":"8ec78d1e-6ed6-4fa5-aef3-9d7b689d8f61","added_by":"auto","created_at":"2025-06-24 12:44:51","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3118461,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRFC4 facilitates interaction between STK38 and BECN1 to promote autophagy.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) His pull-down experiment showing direct interaction between purified GST-BECN1 and His-STK38. The expressions of STK38, His, and BECN1 were detected after immunoprecipitation with his magnetic beads. B) STK38-myc, BECN1-GFP and different concentrations of RFC4-flag-GFP plasmid were co-transfected into 293FT cells. Myc magnetic beads were used as immunoprecipitation magnetic beads, which excluded the influence of light and heavy chains. The expression of RFC4, STK38, BECN1, myc and flag was detected with western blotting assay. C) Wild type, K118R, D230N, S281A, T444A, S91A mutated type plasmid of STK38 was transfected with RFC4-GFP-flag, BECN1-GFP into 293FT cells. The expression of Myc, GFP, RFC4, and BECN1 was detected after immunoprecipitation with flag magnetic beads. D) The binding mode of RFC4, STK38WT, or STK38T444A protein and BECN1 protein was analyzed by molecular docking simulation method, which predicted destabilization of the STK38-BECN1 interface in the T444 mutant, with reduced hydrogen bonding at the critical interaction site, thereby compromising complex stability required for autophagy regulation.\u003c/p\u003e","description":"","filename":"Figure6new.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6854944/v1/e3ca2f2a65acc1b3d8a97bf4.jpg"},{"id":85304619,"identity":"ce5b0557-b16c-49dd-9126-d9282d9d5d45","added_by":"auto","created_at":"2025-06-24 12:36:52","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":8897702,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe functional activity of RFC4 is dependent on the effective interaction between STK38 and BECN1.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) Clone formation assay of GBM cell indicated a cell growth inhibition effect of STK38 T444A. B) CCK8 assay for cell viability in different cell lines in which RFC4 was overexpressed and STK38 knockdown was followed by restoration of expression using different mutated plasmids. C) IC\u003csub\u003e50\u003c/sub\u003e measurement of U251 cells with different expression of STK38. D) Representative images of orthotopic growth of U251 cells with luciferase in NOD-SCID mice. Statistic graph (lower panels) of tumor size using bioluminescence signal intensity. STK38-T444A mutation hindered the growth of tumors. n = 8 for each group. E) Overall survival time of mice exposed by U251 cells with different mutated genes.\u003c/p\u003e","description":"","filename":"Figure7new.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6854944/v1/363f4aef0d6023e4a18d6fab.jpg"},{"id":85304587,"identity":"814103c0-496c-4799-9e5c-f8c0ca608184","added_by":"auto","created_at":"2025-06-24 12:36:51","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":679862,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic diagram of RFC4 mediated TMZ-resistant function by induction of autophagy in GBM cells.\u003c/strong\u003e RFC4 mediates autophagy function in a STK38-dependent way to promote invasive growth and therapeutic resistance of GBM cells. Single pharmaceutical therapy with TMZ cannot effectively suppress tumorigenesis of GBM due to the existence of RFC4 pathway.\u003c/p\u003e","description":"","filename":"Figure8new.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6854944/v1/70c57248049ae2f1266f70ce.jpg"},{"id":85307439,"identity":"e9bfcefb-5cc4-4a7b-aad1-333e95edd569","added_by":"auto","created_at":"2025-06-24 13:01:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":37737306,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6854944/v1/a949e8fc-5130-4d28-8dfd-0c97dcedebb2.pdf"},{"id":85305854,"identity":"33155ed9-babf-49d0-8648-b083da0e7191","added_by":"auto","created_at":"2025-06-24 12:44:51","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1239343,"visible":true,"origin":"","legend":"Supplementaty Indo","description":"","filename":"YWSupplementaryInfo.docx","url":"https://assets-eu.researchsquare.com/files/rs-6854944/v1/96de6174dde47f7fd544dbc0.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"RFC4 Drives Temozolomide Resistance in Glioblastoma by Activating STK38-BECN1-Dependent Autophagy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGlioblastoma (GBM) is the most prevalent and malignant primary brain tumor in adults. \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e It is characterized by rapid proliferation and diffuse infiltration into adjacent healthy brain tissue, which significantly hinders complete surgical resection. \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Current therapeutic strategies for GBM involve maximal safe surgical resection followed by adjuvant radiation therapy and chemotherapy. Temozolomide (TMZ), an alkylating agent, remains the frontline chemotherapeutic option by inducing DNA damage and interfering with DNA replication. \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Nevertheless, GBM treatment continues to face challenges such as TMZ resistance development, limited therapeutic sensitivity, insufficient blood-brain barrier permeability, and systemic adverse effects. \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Consequently, GBM demonstrates a strong propensity for recurrence, even after intensive therapeutic regimens. \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Overcoming these obstacles requires further research efforts and the development of innovative treatment approaches, including combination therapies and targeted strategies, to improve clinical outcomes for GBM patients. \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAccumulating evidence supports the notion that pharmacological disruption of autophagic homeostasis - particularly via sustained inhibition of macroautophagy - elicits transformative therapeutic effects against GBM. \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e Autophagy is a cellular process that plays a crucial role in the degradation and recycling of impaired proteins and organelles, thereby preserving cellular homeostasis. \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e This dynamic catabolic pathway usually involves multiple steps: initiation through ULK1 kinase complex activation, elongation via ATG conjugation systems, and lysosomal degradation mediated by autophagosome-lysosome fusion. \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Notably, the PI3K/AKT/mTOR signaling axis serves as a master regulator of nutrient-responsive autophagy, where mTORC1 suppression triggers autophagosome formation under stress conditions. Central to this process is BECN-1/Beclin-1, a key autophagy-related (ATG) protein that coordinates membrane nucleation through its interaction with class III PI3K complexes. \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn the context of GBM, autophagy can be activated as a survival mechanism in response to chemotherapy, leading to the development of treatment resistance. \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Advances in research have elucidated diverse signaling pathways and molecular mechanisms implicated in autophagy-mediated resistance, including the PI3K/AKT/mTOR pathway, BECN-1 expression, and lysosomal function. \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Consequently, targeting autophagy has emerged as a promising therapeutic strategy to enhance GBM susceptibility to TMZ. \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e While preclinical studies demonstrate synergistic tumor suppression through combined autophagy inhibition and TMZ treatment, clinical translation remains limited by an incomplete mechanistic understanding of context-dependent resistance mechanisms. A comprehensive elucidation of autophagy activation in TMZ resistance, coupled with the development of targeted interventions, holds potential for overcoming therapeutic limitations and improving outcomes in GBM patients.\u003c/p\u003e \u003cp\u003eRFC4 (Replication Factor C Subunit 4) serves as an essential component of the RFC complex, responsible for facilitating DNA replication and repair through its role in loading the PCNA sliding clamp onto DNA. Emerging evidence underscores its significant involvement in tumor progression and therapeutic resistance. RFC4 has been consistently observed to exhibit preferential upregulation in cancer tissues compared to normal counterparts, promoting carcinogenic processes across various malignancies. \u003csup\u003e\u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e In colorectal cancer, elevated RFC4 expression demonstrates significant correlation with inadequate tumor regression and unfavorable prognosis among locally advanced rectal cancer patients receiving neoadjuvant chemoradiotherapy, thereby emphasizing its contribution to radiotherapy resistance. \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e In lung cancer models, RFC4 potentiates tumorigenic capacity and metastatic potential through Notch signaling activation while simultaneously conferring therapeutic resistance to cancer cells. \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e These findings collectively describe the functional impacts of RFC4 on cancer biology and treatment resistance with a tumor type specificity. Regarding glioma, however, RFC4 remains insufficiently characterized, with its potential involvement in tumor proliferation and treatment responsiveness yet to be elucidated.\u003c/p\u003e \u003cp\u003eIn this study, we observed the correlation between RFC4 upregulation and TMZ resistance in GBM cells in an autophagy-dependent manner. Through coimmunoprecipitation (Co-IP) followed by mass-spectrometry (MS) analysis, we identified interaction of RFC4 with STK38. Mechanistical investigation revealed that RFC4 stabilized STK38 and facilitates BECN1 recruitment by STK38, which enhanced STK38-BECN1 complex formation to induce autophagy. Thus, our findings herein established an RFC4-STK38-BECN1 regulatory axis underlying TMZ resistance, providing a mechanistic foundation for targeting autophagy in GBM therapy.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eRFC4 upregulation in GBM is correlated with temozolomide resistance and poor prognosis.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAnalysis on CGGA and TCGA_GBM glioma databases revealed that RFC4 mRNA level was markedly elevated in GBM compared to non-tumor counterparts \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. Moreover, RFC4 mRNA level was positively correlated with glioma progression \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. Using other glioma databases, we consistently observed upregulation of RFC4 mRNA \u003cb\u003e(Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA)\u003c/b\u003e. Immunohistochemistry of a tissue microarray containing 143 GBM and 16 adjacent non-tumor tissues confirmed this oncogenic upregulation \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. Receiver operating characteristic (ROC) curve analysis revealed high predictive accuracy of RFC4 on GBM in clinic \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. Analysis on CGGA database further demonstrated increased RFC4 in recurrent glioma tissues \u003cem\u003eversus\u003c/em\u003e primary counterparts \u003cb\u003e(Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB)\u003c/b\u003e. Kaplan-Meier survival analysis indicated that RFC4 predicted adverse clinical outcomes, including reduced overall survival (OS) \u003cb\u003e(Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eC)\u003c/b\u003e and reduced recurrence-free survival (RFS) \u003cb\u003e(Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eD)\u003c/b\u003e using TCGA_GBMLGG and/or CGGA databases. These findings indicated that RFC4 could be used as a prognostic marker and might play oncogenic roles of RFC4 in glioma.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTMZ remains a major therapeutic regimen for glioma through inducing DNA alkylation damage, which promoted us to explore whether RFC4 was involved in the TMZ response of glioma cells. Using a panel of glioma cells, including one primary GBM cell line (091214) and four commercial GBM cell lines (A172, DBTRG-05MG, LN229, and U251), we surprisingly observed an upregulation of RFC4 mRNA and protein with TMZ treatment in a dose-dependent manner \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF\u003cb\u003e)\u003c/b\u003e, implying that RFC4 was a TMZ-responsive gene. In accordance with this notion, we found that glioma patients receiving pharmaceutical therapy harbored higher levels of RFC4 mRNA than those not receiving any intervention therapy using TCGA_GBMLGG database \u003cb\u003e(Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eE)\u003c/b\u003e. High expression of RFC4 in patients receiving radio-chemo therapy or chemo therapy was associated with shortened overall survival of glioma patients \u003cb\u003e(Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eF)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eThen, we used U251 and LN18 cells to construct RFC4 overexpression and depletion stable cells to measure the IC\u003csub\u003e50\u003c/sub\u003e of TMZ \u003cb\u003e(Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eG and S1H)\u003c/b\u003e. The result showed that increased or decreased RFC4 expression was associated with high or low TMZ IC\u003csub\u003e50\u003c/sub\u003e, respectively, in the two GBM cell lines \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH\u003cb\u003e)\u003c/b\u003e, which suggested that RFC4 might be related with TMZ resistance in GBM cells. To examine this assumption, we used LN229 cells to construct TMZ-resistant counterparts (LN229/RI) through treatment of TMZ with gradually increasing concentration. Compared with parental LN229, LN229/RI showed remarkably increased TMZ IC\u003csub\u003e50\u003c/sub\u003e and RFC4 mRNA level \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eJ\u003cb\u003e)\u003c/b\u003e. We then performed assays for transposase accessible chromatin with high-throughput sequencing (ATAC-seq) to analyze the impact of TMZ on chromatin accessibility. Consistent with TMZ-induced upregulation of RFC4, we noticed a remarkable accessibility of RFC4 enhancer \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eK\u003cb\u003e)\u003c/b\u003e. Together, these results demonstrated RFC4 as an oncogenic driver in GBM progression and responder to TMZ treatment, highlighting its involvement in TMZ resistance and dampened survival of glioma patients.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRFC4 serves as a modulator for autophagy.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAutophagy serves as a crucial cellular survival mechanism during various stress conditions and has been found to be critically involved in TMZ resistance of glioma cells. Indeed, geneset enrichment analysis (GSEA) \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e demonstrated that recurrent GBM dramatically enriched REACTOME_AUTOPHAGY geneset compared with primary GBM using CGGA database \u003cb\u003e(Fig. S2A and S2B)\u003c/b\u003e, indicating the involvement of autophagy in treatment resistance of GBM. Interestingly, we also noticed significant positive correlation between RFC4 mRNA and KUMAR_AUTOPHAGY_NETWORK geneset through Pearson correlation analysis using TCGA_GBMLGG and CGGA databases \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. Similarly, GSEA revealed that high expression of RFC4 enriched REACTOME_AUTOPHAGY geneset compared with low expression of RFC4 using CGGA database \u003cb\u003e(Fig. S2C and S2D)\u003c/b\u003e. In addition, analysis on TCGA_GBMLGG database revealed significant correlations between RFC4 and several key autophagy-regulated genes \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. Moreover, RFC4 overexpression in GBM cells leaded to an increase of LC3B-Ⅱ, indicating the activation of autophagy \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. Immunofluorescence (IF) and \u003cb\u003etransmission electron microscope\u003c/b\u003e (TEM) analysis clearly indicated the increase of autophagic flux \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e and autophagosomes with RFC4 overexpression \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE\u003cb\u003e)\u003c/b\u003e. Then, we explored the effects of RFC4 on TMZ-induced autophagy. In LN229 cells, long time treatment of TMZ induced upregulation of autophagic markers, while in RFC4 depleted LN229 cells, the TMZ-induced autophagy was repressed \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF\u003cb\u003e)\u003c/b\u003e. Consistently, IF and EM data demonstrated TMZ-induced autophagic flux and autophagosomes were indeed suppressed by RFC4 depletion \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH\u003cb\u003e)\u003c/b\u003e. Thus, TMZ-induced autophagy largely relied on RFC4 in GBM cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eBlocking autophagy sensitizes GBM cells with RFC4 overexpression to TMZ.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eColony formation assay using GBM cells with forced expression of RFC4 showed that RFC4 rendered resistance of the cells to TMZ (100\u0026micro;M), while combined administration of autophagy inhibitor, chloroquine (CLQ, 25\u0026micro;M), significantly inhibited the cell proliferation of GBM cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. Then, we examined autophagy-inhibition effects in orthotopic mouse model utilizing U251 cell line with stable expression of luciferase \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. U251 cells with empty or RFC4 overexpression were orthotopically inoculated into NOD-SCID mice to evaluate tumorigenicity. The results showed that RFC4 could effectively promote \u003cem\u003ein vivo\u003c/em\u003e growth of GBM cells in brain. Although TMZ (5mg/kg) treatment could inhibited the \u003cem\u003ein vivo\u003c/em\u003e growth of U251/empty cells but barely suppressed that of U251/RFC4 cells, confirming the TMZ-resistant role of RFC4 \u003cem\u003ein vivo\u003c/em\u003e. However, combination of TMZ and CLQ (80mg/kg) could effectively block the growth of U251/RFC4 cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. Survival analysis suggested that combination of TMZ and CLQ could improve survival of mice bearing GBM and reverse RFC4-induced TMZ resistance \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. Thereby, our results suggested that RFC4-related TMZ resistance was mediated by autophagy of GBM cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSTK38 interacts with RFC4 and plays oncogenic roles in GBM cells.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo further investigate the downstream target pathway regulated by RFC4, we employed immunoprecipitation and mass spectrometry techniques (Co-IP-MS) to profile interactome of RFC4 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. Combining Co-IP-MS data from two cell lines identified 791 proteins as potential binding partners for RFC4 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. Functional enrichment assay indicated that the binding partners of RFC4 enriched ATP hydrolysis activity, which is a critical process in lysosome and closely involved in autophagy \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. Among 791 RFC4-binding proteins, STK38 (serine/threonine kinase 38, also known as NDR1) was found to strongly interact with RFC4 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. Co-transfection of RFC4 and STK38 in 293T cells followed by Co-IP confirmed the interaction between the two proteins \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. Consistently, Co-IP using U251 or LN18 with RFC4 overexpression cells recombinant RFC4 protein further confirmed the interaction between RFC4 and endogenous STK38 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE\u003cb\u003e)\u003c/b\u003e. We also incubated recombinant RFC4-GST and STK38-His proteins in reaction buffer followed by GST pulldown assay and the result demonstrated the direct interaction between the two proteins \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF\u003cb\u003e)\u003c/b\u003e. Notably, immunofluorescence data revealed that the interaction between RFC4 and STK38 was significantly enhanced with TMZ treatment \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG\u003cb\u003e)\u003c/b\u003e. STK38 is a protein kinase and plays important roles in autophagy. \u003csup\u003e\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Analysis on TCGA_GBMLGG and CGGA databases demonstrated that the expression level of STK38 was notably increased in glioma patients, and this elevation is further amplified as the tumor malignancy progresses \u003cb\u003e(Fig. S3A)\u003c/b\u003e. Moreover, STK38 mRNA level was progressively elevated with the glioma histopathological grades \u003cb\u003e(Fig. S3B)\u003c/b\u003e, significantly upregulated in IDH-wildtype \u003cem\u003eversus\u003c/em\u003e mutant subgroups \u003cb\u003e(Fig. S3C)\u003c/b\u003e, and differentially regulated in chemoradiation-treated \u003cem\u003eversus\u003c/em\u003e untreated cohorts \u003cb\u003e(Fig. S3D)\u003c/b\u003e. Notably, TMZ treatment upregulated STK48 mRNA level in multiple GBM cell lines \u003cb\u003e(Fig. S3E)\u003c/b\u003e, which was similar to TMZ-induced RFC4 increase. Survival analyses consistently exhibit shorter overall survival in STK38-high patients across CGGA301, CGGA325, and CGGA693 cohorts \u003cb\u003e(Fig. S3F)\u003c/b\u003e, implying STK38 as a robust prognostic biomarker in GBM.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSTK38 functions as a cooperative regulator of RFC4-mediated autophagy.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSignificantly positive correlation of RFC4 and STK38 was also observed in glioma \u003cb\u003e(Fig. S4A)\u003c/b\u003e. Protein interaction network analysis revealed RFC4 as a central hub, directly connected to STK38, and forming a functional module with replication factors (RFC3, RFC5, PCNA) (\u003cb\u003eFig. S4B\u003c/b\u003e). Meanwhile, co-upregulation of RFC4 and STK38 produced more worse survival than downregulation of each of/both the two genes \u003cb\u003e(Fig. S4C and S4D)\u003c/b\u003e. These data suggested a novel relationship between RFC4 and STK38 in GBM cells. To delineate the structure basis for the interaction between RFC4 and STK38, we constructed various truncated forms for RFC4 and STK38, respectively \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. We found that RFC4 lacking N-terminal (1-380) domains could not bind to STK38, while all three STK38 truncated forms could interact with N-terminus of RFC4 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. To predict the binding pattern between the STK38 and RFC4 proteins, molecular docking analysis was conducted using protein-protein docking methods in the ClusPro server (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cluspro.org/help.php\u003c/span\u003e\u003cspan address=\"https://cluspro.org/help.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The docking results was visualized by PyMOL program and revealed that the amino acid residues T235, R211, Y299, E137, and E143 within the STK38 protein possessed the capability to form hydrogen bonds with the amino acid residues E99, F96, V105, R93, and K43 within the RFC4 protein \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. Notably, increased expression of RFC4 elevated the stability of STK38 protein \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. Suppression of STK38 considerably attenuates the RFC4-induced autophagy, featured with downregulation of LC3B-Ⅱ \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE\u003cb\u003e)\u003c/b\u003e. Together, these results suggested that STK38 was stabilized by RFC4 and required for autophagy occurrence in GBM cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eRFC4 facilitates STK38-BECN1 interaction in a STK38-T444-dependent manner.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIt has been reported that STK38 activates autophagy mainly through its interaction with the autophagosome membrane-forming proteins, BECN1. \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e We performed His pull-down assay and confirmed a direct interaction between STK38 and BECN1 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. Moreover, we observed that RFC4 expression significantly enhanced STK38 recruitment to BECN1 in a dose-dependent manner \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. Furthermore, in the TMZ-resistant GBM cells, STK38 and BECN1exhibited significantly enhanced accessibility \u003cb\u003e(Fig. S5A)\u003c/b\u003e. As demonstrated in previous studies, phosphorylation at STK38-S281 and T444 sites represents its active state. K118 and D230 mutations eliminate STK38's kinase activity, while the S91 site is crucial for its stability. \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e In order to find the specific action site of STK38, we engineered various mutant plasmids of STK38 and co-transfected them with RFC4 and BECN1 into 293FT cells. The result indicated that only the T444A mutation in STK38 diminished its recruitment capability to BECN1 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. To predict the binding pattern between the RFC4, STK38, and BECN1 proteins, molecular docking analysis was conducted using protein-protein docking methods in the Autodock server. \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e The docking result was visualized through PyMOL, revealing that the affinity of RFC4-STK38WT-BECN1 proteins was stronger than RFC4-STK38Mu-BECN1 proteins. The RFC4-STK38Mu-BECN1 protein complexes were reduced when STK38 was mutated at T444 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. Additionally, STK38-T444A mutation suppressed autophagy activation, which might work through conformational changes in STK38 tertiary structure \u003cb\u003e(Fig. S5B)\u003c/b\u003e. Thus, RFC4-STK38-BECN1 axis was functionally required for autophagy.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSTK38 is required for RFC4 biological functions in GBM cells with T444 as critical site.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo evaluate the involvement of STK38 in RFC4 functions, we constructed RFC4 forced expression cells in combination with STK38 knockdown. Then, the STK38 expression was rescued by wild-type STK38 or STK38 T444A \u003cb\u003e(Fig. S5C)\u003c/b\u003e. Colony formation and CCK8 assays indicated loss of STK38 attenuated RFC4-promoted growth of GBM cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. Overexpression using STK38 wild-type in GBM cells with RFC4 and shSTK38 rescued RFC4 effects but not overexpression using STK38 T444A \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. Increased TMZ IC\u003csub\u003e50\u003c/sub\u003e of GBM cells by RFC4 high expression could be repressed by loss of STK38. However, wild-type STK38, but not STK38 T444A mutant, could elevate the TMZ IC\u003csub\u003e50\u003c/sub\u003e of GBM cells with RFC4 overexpression and STK38 depletion \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. Similarly, orthotopical mouse model using U251 cells demonstrated depletion of STK38 leaded to growth inhibition of GBM cells with RFC4 overexpression \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. Rescue with wild-type STK38 consistently recovered in vivo growth of GBM cells but STK38 T444A failed to do so \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. Survival analysis also supported the involvement of STK38 activity in RFC4-enhance growth of GBM cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE\u003cb\u003e)\u003c/b\u003e. Therefore, our data demonstrated that STK38 acted as an important mediator for RFC4 functions in GBM cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAlthough autophagy has been documented to facilitate the development of TMZ resistance in GBM, how the autophagy is induced and regulated remains to be elucidated and targeting autophagy as a therapeutic regimen for GBM is challenging. In this study, we reported a novel function of RFC4 in the development of TMZ resistance through autophagy induction. Mechanistically, RFC4 stabilized STK38 and facilitated STK38 and BECN1 interaction for autophagy activation. It has been known that STK38 is required for early steps of autophagosome formation through binding with BECN1. \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e The formation of RFC4-STK38-BECN1 complexes promoted the formation of autophagosomes, leading to TMZ resistance of GBM cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Therefore, interfering with the RFC4-STK38-BECN1 complexes could be promising regimen for GBM treatment.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTMZ remains a cornerstone of GBM therapy by attacking tumor cell DNA and inducing DNA alkylation damage. This mechanism provides a mechanistic basis for the observed upregulation of RFC4 enhancer accessibility and expression in both TMZ-treated GBM cell models and patients. Notably, however, RFC4 activation shows no statistical significance in radiotherapy-treated GBM patients, \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e possibly due to differential stress responses. Furthermore, elevated RFC4 expression correlates with reduced overall survival in glioma patients and specifically in TMZ-treated glioma cohorts. These findings establish RFC4-targeted interventions as a novel therapeutic avenue for glioma patients, including those developing resistance or experiencing relapse post-TMZ therapy. Strategic targeting of RFC4-associated pathways may yield innovative treatments, such as precision approaches to suppress pathological RFC4 activity or leverage synthetic lethality in RFC4-dysregulated cancer cells.\u003c/p\u003e \u003cp\u003eAutophagy has attracted substantial research interest since its initial characterization. \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e This process exhibits dual roles in GBM cells - promoting either survival or death under metabolic and therapeutic stress conditions, with outcomes determined by stress context and intensity. \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e While autophagy modulation has demonstrated therapeutic potential in glioma management, \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e variable treatment efficacy persists due to target selection challenges and patient heterogeneity. Our investigations revealed RFC4-mediated autophagy activation across multiple GBM cell lines. Functionally, such autophagy induction suppressed cell death mechanisms while enhancing glioma cell viability. \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e Chloroquine-mediated autophagy inhibition effectively counteracted RFC4\u0026rsquo;s pro-tumorigenic effects, confirming autophagy as the principal downstream effector pathway.\u003c/p\u003e \u003cp\u003eA critical requirement for implementing RFC4-targeted therapies in TMZ-based GBM treatment lies in fully elucidating the molecular mechanisms through which newly discovered binding partners activate RFC4 signaling. Mass spectrometry (MS) analyses systematically mapped RFC4\u0026rsquo;s primary binding partners, with our study definitively mapping the RFC4 interactome in GBM cells and revealing its essential partnership with STK38. STK38 kinase has been recognized as an upstream controller of autophagy signaling networks. \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Emerging evidence further establishes STK38\u0026rsquo;s multifaceted involvement through direct associations with core autophagy components. \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e STK38 deficiency significantly attenuated RFC4-driven autophagy activation, while RFC4 demonstrated TMZ-responsive activation even at subtherapeutic concentrations, suggesting greater TMZ sensitivity than STK38. Integrative analysis of TCGA_GBM datasets established co-overexpression of RFC4 and STK38 as a key determinant of reduced survival and accelerated recurrence in glioma patients.\u003c/p\u003e \u003cp\u003eWe precisely determined the interaction interface between full-length STK38 and RFC4\u0026rsquo;s N-terminal region (NTR, residues 1-250). Given that STK38\u0026rsquo;s N-terminal domain (residues 1\u0026ndash;82) contains an autoinhibitory sequence, \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e our findings suggest RFC4 binding may relieve this intrinsic inhibition. Mechanistic investigation of STK38\u0026rsquo;s role in autophagy revealed its scaffolding function, bridging RFC4 with BECN1 - a core regulator of autophagy initiation. \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Our data further showed that RFC4-STK38 binding enhanced STK38 protein stability, thereby increasing BECN1 recruitment efficiency. Notably, kinase-dead STK38 mutants maintained full capacity to form BECN1 complexes and activate autophagy when stimulated by RFC4, demonstrating kinase-independent functionality. Collectively, these results establish that TMZ-triggered RFC4 activation propels autophagic flux via the STK38-BECN1 axis, where STK38 operates as a structural platform facilitating BECN1 interaction, ultimately amplifying cytoprotective autophagy in GBM cells.\u003c/p\u003e \u003cp\u003eThrough systematic investigation of STK38\u0026rsquo;s regulatory role in autophagy induction, we identified the T444 phosphorylation site as essential for maintaining RFC4-STK38-BECN1 complex stability. The hydrophobic motif (HM) autophosphorylation site at T444 represents a critical post-translational modification that drives STK38\u0026rsquo;s functional activation. \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e Molecular dynamics simulations demonstrated that T444 phosphorylation-deficient STK38 mutants display compromised BECN1 binding capacity, leading to defective autophagosome maturation. This molecular impairment translated to significantly reduced GBM cell viability and diminished tumorigenicity in orthotopic models. Our integrative approach establishes T444 phosphorylation as a biochemical rheostat controlling the STK38-BECN1 axis - its absence triggers structural destabilization that converts cytoprotective autophagy into a tumor-suppressive mechanism, revealing a targetable vulnerability for precision oncology.\u003c/p\u003e \u003cp\u003eCollectively, these discoveries establish a paradigm-shifting framework for addressing TMZ resistance in GBM. Future investigations should focus on developing RFC4-STK38 axis-targeting agents, particularly small-molecule inhibitors disrupting RFC4 NTR-STK38 binding or modulating STK38 kinase activity, to synergize with TMZ and resensitize refractory tumors. Concurrently, implementing RFC4/STK38 expression-based patient stratification could optimize precision clinical trial designs, enabling personalized therapeutic approaches for recurrent or treatment-resistant cases. The identified synthetic lethality mechanism may extend beyond GBM to other malignancies sharing analogous RFC4-STK38 pathway dependencies. Furthermore, deploying cutting-edge methodologies like spatial multi-omics platforms and dynamic autophagic flux monitoring could decode spatiotemporal regulatory networks, transforming mechanistic discoveries into clinical applications. By dismantling cancer cells\u0026rsquo; adaptive survival mechanisms, this work fundamentally repositions therapeutic strategies for glioblastoma, offering a roadmap to significantly improve patient outcomes.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCell culture\u003c/h2\u003e \u003cp\u003eDMEM (10,566,016), penicillin-streptomycin (15,140,122), fetal bovine serum (FBS) (10,270,106), Dulbecco’s phosphate-buffered saline (DPBS; 14,190,094) and trypsin-EDTA (25,200,056) were purchased from Gibco® (Life Technologies). The human glioma cell line U251, Ln18, LN-229, A172 and DBTRG-05MG was obtained from Institute of Pathology and Southwest Cancer Center, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China. \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e Cells were cultivated in DMEM, high glucose, 10% FBS and 100 U/mL penicillin-streptomycin at 37°C and 5% CO\u003csub\u003e2\u003c/sub\u003e. Cells were exposed to Temozolomide (MedChemExpress, HY17364) and Cycloheximide (MedChemExpress, HY12320), chloroquine diphosphate salt (chloroquine; Sigma-Aldrich, C6628) for the indicated time periods.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eLentivirus packing in 293-FT cells\u003c/h3\u003e\n\u003cp\u003eFor depletion and overexpression of target genes, virus particles were generated in 293-FT cells transfected with the control vector or the respective plasmid, the gag/pol plasmid pCMV-dr8.91 and the VSV-g envelope plasmid pMD2. G (Addgene, 12,259). Cells were transfected by using Lipofectamine 3000 (Thermo Fisher Scientific, L3000008) according to manufacturer’s instructions. The DNA mixture was added drop-wise to the cells and incubated for 6–8 h at 37°C and 5% CO\u003csub\u003e2\u003c/sub\u003e. After incubation the medium was replaced with fresh medium. 48 h and 72h after transfection the virus-containing supernatant was harvested and stored short-term at 4°C. Lentivirus were added directly in cells with polybrene (MedChemExpress, HY112735). Medium was changed after 24h and cells with stable integration of target genes were selected with puromycin or hygromycin.\u003c/p\u003e\n\u003ch3\u003eImmunoblot analysis\u003c/h3\u003e\n\u003cp\u003eFor immunoblot analysis, cells were lysed with RIPA Lysis Buffer (Strong) (50 mM Tris (pH 7.4), 150 mM NaCl, 1% Triton X-100, 1% sodium deoxycholate, 0.1% SDS, and general protease and phosphatase inhibitors (cOmplete™ Protease Inhibitor, PhosSTOP) [Roche, 4693116001, 04906837001]. The protein amount was determined with a Pierce BCA protein assay kit (Thermo Fisher Scientific, 23,225). The SDS gels (8% – 15%) were loaded with 30–50 µg protein in 4x Laemmli protein sample buffer (250 mM Tris-HCl, pH 6.8, 10% SDS, 30% glycerol, 0.02% bromophenol blue (Bio-Rad, 1610747), after heating the samples for 5 min at 95°C. Proteins were separated (80 V for 30 min, then 120 V) and blotted semi-dry (15 V, 35 min) onto a PVDF membrane (Bio-Rad, 1620177). The membranes were blocked with 5% milk in TBS (150 mM NaCl [50 mM Tris, pH 7.5) + 0.05% Tween 20 (TBS-T) for 1 h at room temperature, followed by incubation with the primary antibodies overnight at 4°C:, LC3B (Abcam, ab63817), BECN-1 (Cell Signaling Technology, 4122), RFC4 (Novus biologicals, NBP2-45946), p62 (Cell Signaling Technology, 23214), Flag (Cell Signaling Technology, 14793), Myc(Cell Signaling Technology, 2276), GFP (Cell Signaling Technology, 2956), STK38 (Thermo Fisher Scientific, PA5-76351), β-actin (Cell Signaling Technology, 4970).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of gene expression by quantitative real-time polymerase chain reaction (qRT-PCR)\u003c/h2\u003e \u003cp\u003eFor determination of gene expression by qRT-PCR, RNA was isolated with the EXTRACTME total RNA Kit according to the manufacturer’s instructions (Bioscience, EM09.1–250). Next, 1–2 µg RNA, superscript III reverse transcriptase (Thermo Fisher Scientific, 18,080,044) and random primers were used in a total volume of 20 µL for cDNA synthesis according to the manufacturer’s protocol. cDNA was diluted with 80–180 µL DEPC-H\u003csub\u003e2\u003c/sub\u003eO (Carl Roth GmbH + Co. KG, T143.1). For qRT-PCR, 5µL cDNA, 1µl 1xTaqMan Gene Expression Assay primer and 10µl 1xFastStart Universal Probe Master-mix (Roche 3439 Diagnostics GmbH, 04913957001) were applied. Relative gene expression levels were calculated by using the comparative CT method. Samples were normalized to the reference gene TBP (TATA-box binding protein). The following primers were used: Forward-5’-GCAACTCAGCTCGTCAATCAACTC-3’, Reverse 5’-AGGCATTTGTCAACTTCGGCAAG-3’ (RFC4), Forward 5’-TCGTGCGGAGCGTGACATTC, Reverse 5’-CCAGGCAGGAACTCCATGATTAGG-3’ (STK38) (Thermo Fisher Scientific).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGeneration of shRNA KD cell lines\u003c/h3\u003e\n\u003cp\u003eFor depletion of RFC4/STK38 virus particles were generated in HEK 293-T cells transfected with the control vector or the respective shRNA plasmid (designed and synthesized by Shanghai Sangon Biological Engineering Technology \u0026amp; Services Company) gag/pol plasmid pCMV-△8.91 and the VSV-g envelope plasmid pMD2. G (Addgene, 12,259). The plasmid was transfected into HEK293 cells using Lipofectamine 3000 (Thermo Fisher Scientific, L3000015). The plasmids were diluted in DMEM while blowing air bubbles through a Pasteur pipette and incubated for 15–20 min. The DNA mixture was added drop-wise to the cells and incubated for 6–8 h at 37°C and 5% CO2. After incubation the medium was replaced with fresh medium. 24 h and 48 h after transfection the virus-containing supernatant was harvested and stored short-term at 4°C. For transduction, 120,000 parental GBM cells were seeded out in 6-well plates. Next day cells were incubated for 24 h with the virus-containing supernatant diluted in culture medium and 3µg/mL polybrene. Afterward medium was changed and after additional 24h the medium was changed to selection medium containing 1 µg/mL puromycin. KD was confirmed by immunoblot analysis.\u003c/p\u003e\n\u003ch3\u003eProtein expression and purification\u003c/h3\u003e\n\u003cp\u003eThe plasmid was transfected into HEK293 cells using Lipofectamine 3000 (Thermo Fisher Scientific, L3000015). After culture at 37℃ under 5% CO2 for 6 days, cells were collected and lysed by 1XPBS (pH 7.2–7.4), and the insoluble fraction was removed by centrifugation at 30,000xg for 30 min. Supernatants were incubated with protein A-agarose for 1–2 h and washed extensively. The protein was eluted by 0.1M glycine (pH 3.0) and neutralized with 1M Tris-HCl (pH8.5), and then concentrated to 1mg/ml and stored at -80℃.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eImmunoprecipitation\u003c/h2\u003e \u003cp\u003eThe experimental procedure for immunoprecipitation commenced with cell harvesting and lysis using ice-cold RIPA buffer supplemented with protease inhibitors. After incubation on ice for 30 minutes, the lysate was centrifuged at 12,000×g for 15 minutes at 4°C to pellet cellular debris. The clarified supernatant was incubated overnight at 4°C with VHH-Sepharose® magnetic beads (Antibody Life Biotechnology) pre-coupled with specific antibodies under constant rotation. Magnetic bead complexes were isolated using a dedicated separator and washed three times with chilled Tris-buffered saline containing 0.1% Tween-20. Proteins were dissociated by boiling in Laemmli sample buffer at 95°C for 10 minutes, followed by immediate SDS-PAGE analysis. Negative controls using antibody-free beads from the same manufacturer were included to validate target-specific binding. All steps involving protein handling were performed at 4°C to preserve complex integrity, with reagents from Antibody Life Biotechnology maintained at recommended storage temperatures prior to use.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eThe IP/MS analyses\u003c/h2\u003e \u003cp\u003eThe IP/MS analyses were designed and analyzed by PTM Biological Company. Briefly, it was performed using a triple quadrupole mass spectrometer QTrap 5500 (Sciex, Darmstadt, Germany) equipped with a Turbo V Ion Source operating in positive electrospray ionization mode. The analysis was done in Multiple Reaction Monitoring (MRM) mode. Precursor to product ion transitions (m/z) for analysis and internal standards are shown in the supplementary methods. Data Acquisition was done using Analyst Software V1.6.2 and quantification was performed with MultiQuant Software 3.0.2 (both Sciex, Darmstadt, Germany), employing the internal standard method (isotope dilution mass spectrometry). Calibration curves were calculated by linear or quadratic regression with 1/x or 1/x2 weighting. Variations in accuracy of the calibration standards were less than 15% over the whole range of calibration, except for the lower limit of quantification, where a variation in accuracy of 20% was accepted. For the acceptance of the analytical run, the accuracy of the QC samples had to be between 85% and 115% of the nominal concentration for at least 67% of all QC samples.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eGST pull down\u003c/h2\u003e \u003cp\u003eThe GST pull-down protocol was initiated by expressing GST-tagged recombinant proteins in BL21(DE3) Escherichia coli through 0.5 mM IPTG induction at 16°C for 20 hours. Bacterial pellets were lysed in ice-cold GST-binding buffer (50 mM Tris-HCl pH 8.0, 150 mM NaCl, 1% Triton X-100) supplemented with lysozyme and protease inhibitors. Following sonication and centrifugation at 15,000×g for 30 minutes at 4°C, the clarified lysate was incubated with pre-equilibrated GST-VHH nanomagnetic beads (Antibody Life Biotechnology, Cat# GST-NM102) for 2 hours at 4°C with gentle agitation. The bead-protein complexes were magnetically captured and sequentially washed with high-salt buffer (500 mM NaCl) and low-salt buffer (50 mM NaCl) to remove nonspecific binders. Competitor proteins or cell lysates containing putative interaction partners were then introduced to the immobilized GST fusion proteins and incubated for 4 hours under rotational mixing. After three stringent washes with GST elution buffer lacking reducing agents, specifically bound proteins were competitively eluted using 10 mM reduced glutathione in 50 mM Tris-HCl (pH 8.0) for downstream immunoblotting or mass spectrometry analysis. Control experiments with untagged protein lysates and GST-empty nanomagnetic beads from the same manufacturer were systematically included to exclude artifacts. All Antibody Life Biotechnology reagents were quality-controlled for batch consistency, with nanomagnetic beads stored at 4°C in glycerol-containing preservation buffer until use.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eConstruction of shRNA-resistant STK38 plasmid​\u003c/h2\u003e \u003cp\u003eTo generate a shRNA-resistant STK38 expression plasmid, we designed a mutant construct with nucleotide substitutions in the shRNA-targeted region to disrupt base pairing while preserving the encoded protein sequence. The shRNA PLVE4507-1 targets the STK38 sequence ​CAGCAAGGGCCATGTGAAA (positions663–683 in the wild-type genomic DNA), which overlaps with the stem-loop (STEMP) and loop regions in the viral vector backbone. Two-point mutations were introduced into the STEMP sequence: ​G9A​ (position 9, G→A), T15C (position 15, T→C), converting the original sequence to ​CAGCAAGGACCATGCGAAA. This mutation disrupts the stem-loop secondary structure critical for shRNA binding while maintaining the amino acid sequence at the corresponding protein locus. The mutant fragment was synthesized via overlap extension PCR using Phusion High-Fidelity DNA Polymerase (New England Biolabs) with the following primers: Forward primer (F):​​5'- CAAGGACCATGCGAAACTTTCTGACTTTGGTCTTTGCA − 3', Reverse primer (R):​​ 5'- AGTTTCGCATGGTCCTTGCTGTCCAAAAGAAGGTT − 3'. The ligation product was transformed into Stbl3 chemically competent E. coli (Thermo Fisher Scientific), and plasmid DNA was extracted using a HiSpeed Plasmid Midi Kit (Qiagen).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eSite-directed mutagenesis\u003c/h2\u003e \u003cp\u003eUsing a high-fidelity PCR-based approach with Phusion DNA polymerase (New England Biolabs). The plasmid template containing the wild-type STK38 gene was amplified with primers flanking the target site, designed using SnapGene software. PCR products were treated with DpnI (NEB) to digest methylated template DNA, followed by ligation using T4 DNA ligase (NEB). Competent E. coli cells (DH5α) were transformed with ligated products, and positive colonies were selected via colony PCR. Plasmid DNA was extracted (QIAGEN MinElute Kit), and mutations were confirmed by Sanger sequencing (Genewiz).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eATAC-seq data visualization using IGV​\u003c/h2\u003e \u003cp\u003eProcessed ATAC-seq data were visualized using the Integrative Genomics Viewer (IGV v2.16.2) with strict adherence to the GRCh37/hg19 reference genome assembly. \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e BAM alignment files and normalized BigWig coverage tracks were loaded following coordinate conversion using CrossMap v0.6.3 to ensure compatibility with the hg19 genomic framework. Visualization parameters were optimized through iterative adjustment of sequencing depth thresholds (1–10× in collapsed view mode) and coverage normalization (0-100 reads per million, RPM), while maintaining the diagnostic 200-bp Tn5 transposase cleavage periodicity at transcription start sites (TSSs) as critical quality control criteria. Comparative analyses incorporated ENCODE Consortium annotations (Version 3, hg19) of regulatory elements, with chromatin accessibility patterns contextualized against Roadmap Epigenomics Project ATAC-seq datasets mapped to the same genome build. Spatial relationships between differential accessibility regions and known genomic features were verified through multi-track visualization using consistent color schemes (BAM: grayscale gradient; BigWig: royal blue) and layer transparency settings (40–60%). High-resolution snapshots (300 DPI, 1600×900 pixels) of representative loci were acquired using IGV’s batch image export function with standardized chromosome coordinate ranges.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eOrthotopic xenograft\u003c/h2\u003e \u003cp\u003eNOD-SCID mice were injected intracranially with U251 cells (5\u003cb\u003e×\u003c/b\u003e10\u003csup\u003e4\u003c/sup\u003e) with pLVX-puro-linker-luciferase lentivirus via the right frontal lobe on a 4–6-week-old basis (Animal Facility of West China Fourth Hospital, China). The mice were housed in large plastic cages in groups of 10 and kept pathogen-free. An In Vivo Image System (IVIS) (PerkinElmer, USA) was used to detect and quantify growing xenograft tumors. Tumors were collected from mice with neurological signs or that were moribund. The animal experiments were approved by the Institutional Animal Care and Use Committee of West China Fourth Hospital, Sichuan University in accordance with the Guide for the Care and Use of Laboratory Animals.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eEthics Statement\u003c/h2\u003e \u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki. Ethical approval for this study was obtained from the Institutional Review Board of West China Fourth Hospital, Sichuan University.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eStatistics\u003c/h2\u003e \u003cp\u003eAnalysis of proteome data was performed in Perseus. Only proteins with P \u0026lt; 0.01 based on a student´s t-test were considered significant. GraphPad Prism 9 (GraphPad Software, La Jolla CA, USA) was used for statistical analysis of all other data. To determine if the data set is well-modeled by a normal distribution, a Shapiro Wilk normality test was performed. In case of normally distributed data, the data set was analyzed with a one- or two-way ANOVA. For non-normally distributed data, the nonparametric Mann-Whitney U-test or Kruskal-Wallis test was used. The minimum level of statistical significance was set at P \u0026lt; 0.05 and significances are depicted as *P \u0026lt; 0.05, **P \u0026lt; 0.01, and ***P \u0026lt; 0.001, or n.s. (not significant) between control and treated cells or as indicated with brackets.\u003c/p\u003e \u003c/div\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by The National Key Research and Development Program of China (2022YFA1104303 to Y.W.), The National Natural Science Foundation of China (81802508 to M.M., 82202908 to Q.-J.G., 82172854 to S.-L.X.), The Natural Science Foundation of Chongqing (CSTB2022NSCQ-MSX0206 to M.M., CSTB2022NSCQ-MSX028 to Q.-J.G.), The Natural Science Foundation of Sichuan Province (2024NSFSC1523 to M.M.), China Postdoctoral Science Foundation (GZC20231814 to M.M.), The Outstanding Youth Science Foundation of Sichuan Province (2023NSFSC1927 to X.W.), and Jinfeng Laboratory Start Funding (to Y.W.).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare no conflict of interest.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlexander, B. 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Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. \u003cem\u003eBriefings in bioinformatics\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 178-192, doi:10.1093/bib/bbs017 (2013).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Glioblastoma, Temozolomide, Autophagy, RFC4, STK38, BECN1","lastPublishedDoi":"10.21203/rs.3.rs-6854944/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6854944/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGlioblastoma (GBM) remains intractable owing to treatment resistance and near-inevitable relapse. While autophagy has been demonstrated to contribute to temozolomide (TMZ) resistance, its regulatory mechanisms remain unclear. RFC4, a replication factor implicated in tumor progression, has not yet been systematically investigated in glioma for its potential role in autophagy regulation. In this work, multi-omics analyses and immunohistochemistry were used to evaluate clinical relevance of RFC4. TMZ-resistant GBM cell lines and orthotopic mouse models were used for functional studies. Autophagy was assessed via LC3B-II quantification, immunofluorescence, and electron microscopy. Structural interactions were mapped using truncation mutants, GST pull-down assays, and molecular docking. We found that RFC4 played oncogenic roles in GBM tissues, correlating with poor prognosis and TMZ resistance. TMZ treatment increased RFC4 enhancer accessibility and stabilized STK38, a kinase that regulates autophagosome formation. RFC4-STK38 interaction promoted BECN1 recruitment, thereby driving autophagy. Critically, phosphorylation of STK38 at T444 was essential for stabilizing the RFC4-STK38-BECN1 complex, whereas the phospho-deficient STK38-T444A mutation impaired BECN1 binding and autophagosome maturation. In vivo, RFC4 overexpression conferred TMZ resistance; however, this resistance was reversed by chloroquine-mediated autophagy inhibition. Co-overexpression of RFC4 and STK38 predicted the worst patient survival, and STK38 knockdown induced synthetic lethality in this context. Together, this study identified the RFC4-STK38-BECN1 axis as a master regulator of TMZ resistance via autophagy. The T444 phosphorylation could be a druggable vulnerability and its disruption reversed pro-survival autophagy. Clinically, RFC4/STK38 co-expression stratified high-risk GBM patients. Preclinically, targeting RFC4-STK38 synergized with TMZ to overcome resistance. These findings elucidated a novel GBM resistance mechanism and provided a translational roadmap for precision therapy.\u003c/p\u003e","manuscriptTitle":"RFC4 Drives Temozolomide Resistance in Glioblastoma by Activating STK38-BECN1-Dependent Autophagy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-24 12:36:46","doi":"10.21203/rs.3.rs-6854944/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6bd4746b-2371-48d5-b6b9-fe99ded64a97","owner":[],"postedDate":"June 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":50314502,"name":"Biological sciences/Cancer"},{"id":50314503,"name":"Health sciences/Oncology"}],"tags":[],"updatedAt":"2026-03-04T16:56:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-24 12:36:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6854944","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6854944","identity":"rs-6854944","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}