NANP targeting radiosensitizes glioblastoma through TNFR1 sialylation-driven mesenchymal shift

Domain: biology
Published: 2026-03-18
Editorial outcome: major_revision

Abstract
Glioblastoma (GBM) patients have dismal survival due to resistance to initial ionizing radiation therapy (RT). Clonal evolution analysis reveals no dominant RT-resistant clones, prompting a genome-wide CRISPR screen to identify radiosensitizing targets. The screening highlights DNA damage response genes, validating the effectiveness of our approach. N-acylneuraminate-9-phosphatase (NANP), a critical enzyme in the sialic acid synthetic pathway, is top-ranked in the screening and associated with patient outcomes. After radiation, NANP-deficient cells exhibit more DNA damage, G2/M arrest and apoptosis, and impaired DNA repair by favoring non-homologous end-joining over homologous recombination. Mechanistically, NANP influences NF-κB signaling and the mesenchymal state by modulating sialylation and internalization of tumor necrosis factor receptor 1 (TNFR1), thereby affecting RT sensitivity. Intracranial orthotopic xenograft experiments validate the function of NANP in vivo. Here, we identify NANP as a radiosensitizing target dependent on TNFR1 sialylation and mesenchymal shift, providing a basis for developing RT sensitizers for GBM.

Introduction
Glioblastoma (GBM) is the most common and aggressive adult malignant brain tumor with a median survival of about 15-17 months. Current standard of care for the treatment of patients with GBM involves maximal safe surgical resection of the tumor followed by concurrent chemotherapy with temozolomide (TMZ) and radiotherapy (RT) at a dose of 60 Gy in 30 fractions daily, and then adjuvant TMZ1,2. Addition of radiation alone improved survival over surgery by 6 months in the Brain Tumor Study Group trials3-5. Subsequent addition of TMZ improved survival an additional 2 months and, recently, addition of tumor treating fields further improved survival another 2 months1,2,6. Despite the potential benefits that each of these advances has, RT continues to be the most impactful first-line treatment of GBM with respect to survival, and thus, resistance to RT serves as a major factor in disease progression. Nearly all patients succumb to tumor recurrence, hypothesized to be due to the presence of GBM stem-like cells (GSCs), a subpopulation within the tumor with self-renewal and therapy-resistant properties7,8. Given the benefit of RT in the treatment of GBM, attempts have been made to increase dose to the tumor, however, these approaches have failed to improve survival due to the resulting increased toxicity9. Therefore, there is an urgent need to develop strategies to enhance radiosensitivity of GBM, especially the GSC population, in order to improve patient outcomes.

Transcriptome analysis of TCGA (The Cancer Genome Atlas) samples have classified GBM tumors into three subtypes: Classical (CL), Proneural (PN), and Mesenchymal (MES)10. These states however exhibit plasticity and recent studies have further refined the extent of plasticity and heterogeneity at the single-cell level11. Our previous study demonstrated NF-κB activation promotes MES differentiation of GSCs and GSCs with a MES phenotype displays increased radioresistance12. Further study showed upregulation of N-cadherin, a mesenchymal marker, mediates adaptive radioresistance in GBM and protects from radiation induced apoptosis13. Thus, MES phenotype disruption has been an attractive approach for radiosensitization14,15.

Sialic acid residues attached to cell surface glycans play a crucial role in cell adhesion, migration, and interaction with the environment16,17. Aberrant sialylation is implicated in cancer progression and therapeutic resistance18. N-acylneuraminate-9-phosphatase (NANP) functions in the final step of sialic acid synthesis. In this work, we report the identification of NANP as a key regulator of radiosensitivity in GSCs using genome-wide CRISPR screening. We find that NANP regulates NF-κB pathway activation and the MES phenotype by modulating sialylation of TNFR1, ultimately impacting the radiosensitivity of GBM.

Results
Clonal evolution during radio-resistance
We previously reported that a few drug-resistant clones can dominate targeted therapy resistance through clonal evolution19, which suggesting opportunities to overcome resistance by targeting these dominant clones. We sought to undertake a similar approach with radiation to identify dominant resistant clones that could be targeted to improve radiosensitivity. To that end, we studied the clonal evolution of the patient-derived GSC line GSC20 in response to fractioned RT using our CAPTURE barcoding approach (Supplementary Fig. 1a). The clonal evolution pattern in response to RT was strikingly different to that seen in response to targeted therapy (Supplementary Fig. 1b and Supplementary Data 1). In our previous study with targeted therapy19, specifically the mutant BRAF inhibitor vemurafenib in a melanoma model, the top ten most abundant lineages contributed an impressive 85.35% to the final resistant pool (49.27-fold higher enrichment than that seen in control). However, in the RT study, this was only 7.97% (2.23-fold higher enrichment than that seen in control). The top enriched barcoded lineages in each experimental replicate were further selected based on GFOLD analysis (Supplementary Fig. 1c), and these lineages were rarely shared across experimental replicates (Supplementary Fig. 1d). Taken together, these results suggest that, unlike targeted therapy, RT resistance was not driven by a few dominant clones but instead may represent a stochastic selection, making it less likely to exploit a resistant clonal lineage.

Genome-wide CRISPR screen for radiation sensitizing targets
Since the clonal lineage approach failed to identify targetable, dominant RT resistant clones and considering the toxicity of RT dose escalation, RT sensitization may serve as a better strategy to minimize RT resistance. Hence, we sought to identify RT sensitizing targets through a genome-wide CRISPR screen. We performed a genome-wide CRISPR screen to identify genes whose gRNAs drop-off in fractioned RT treated group compared to sham radiation group (Fig. 1a and Supplementary Data 2). GSC20 was used based on its marked resistance to RT. We transduced the cells with the Brunello lentiviral CRISPR library, which targets 19114 protein-coding genes (4 gRNAs per gene), at a multiplicity of infection (MOI) < 0.3. Experiments were performed as duplicates at 300-fold library representation per biologic replicate. After fractioned RT (2 Gy × 5 fractions) or sham treatment, cells underwent prolonged culture for additional 25 days. We then amplified gRNAs from genomic DNA for next generation sequencing. Dropout of individual genes was determined by multiple gRNAs targeting the same gene (Fig. 1b-c).

Gene set enrichment analysis (GSEA) of the ranked resulting gene list (Fig. 1d and Supplementary Fig. 2) demonstrated that non-homologous end-joining (NHEJ) and the related protein complexes (e.g., DNA ligase IV-XRCC4-XLF complex) were the most negatively enriched, followed by the enrichment of many other DNA damage response (DDR) pathways. These results were aligned with the well-established importance of DDR in response to radiation and underscore the overall effectiveness of the CRISPR screen. Using a filter based on a greater than 2-fold reduction in representation with a p-value of less than 0.05, as well as requiring at least two gRNAs targeting the same genes to ensure consistent outcomes, we identified 139 potential targets for RT sensitization. (Fig. 1e). We further interrogated these candidates to identify what pathways/functions were they involved by Gene Ontology (GO) and Reactome analyses. This revealed overrepresentation for genes involved in 11 major classes of pathways (Fig. 1f). “DNA damage response and repair” relating pathways were the most significantly enriched, and 7 of 10 other major classes of pathways, including “cell cycle checkpoints”, “TP53 pathway”, “DNA replication and recombination”, “virus life cycle”, “cell proliferation and differentiation”, “post-translation protein modification”, “transcription regulation”, were not surprising to found enrichment given their related genes were highly overlapped with those involved in DDR. There were 23 genes with a direct function in key DNA double-strand break (DSB) repair pathways including 7 genes central to NHEJ (e.g., PRKDC, NHEJ1, DCLRE1C, XRCC4, LIG4, CYREN, HMGNB2), 4 genes involved in homologous recombination (HR) (RAD51D, BRCA2, RAD17, RAD9A), and 12 genes central to general DDR (e.g., ATM, RNF8, RNF168, TP53BP1, TONSL, FOXM1, TDG, ERCC6L2, RFWD3, RAD1, TRAIP, TCEA1). Collectively and not surprisingly, these findings demonstrate that the genes involved in DDR pathways, particularly NHEJ, are major targets for increasing radiosensitivity in GSCs.

In addition to the these known DDR-related pathways, we also observed enrichment of genes involved in other pathways such as "nucleotide salvage", "sterol homeostasis" and "animo sugar metabolism" pathways. Given that nucleotides serve as the building blocks for DNA synthesis, it is unsurprising to find the "nucleotide salvage" pathway among these pathways. In fact, recently studies20,21 have established its significance in regulating radiation sensitivity, further highlighting the success of the screen. The observation of the association between the "sterol homeostasis" pathway and RT sensitivity was somewhat unexpected. However, it is intriguing to note that several initial studies have indeed demonstrated its significant role in modulating RT sensitivity and DDR22-24. "Animo sugar metabolism" pathway was another unexpected RT sensitivity associated pathway, which has not been previously studied.

Identification of NANP as a potential radiosensitizing target
To identify novel targets, we focused on the pathway "animo sugar metabolism” since this had not previously been known as involved in radiation sensitivity. Among the hits implicated in this pathway, NANP was chosen because of its high rank in our screening (Fig. 1c, g) and its association with GBM patient survival and tumor aggressiveness (Fig. 2a-h). NANP catalyzes the dephosphorylation of N-acetylneuraminic acid 9-phosphate (Neu5Ac-9P) to generate N-acetylneuraminic acid (Neu5Ac), the most common sialic acid in humans17. Interestingly, other NANP related pathways showed enrichment in our screen (Supplementary Fig. 2a), such as N-glycan biosynthesis.

The analysis of multiple public patient cohorts revealed that NANP expression was significantly higher in GBM samples compared to non-tumor controls (Fig. 2a and Supplementary Fig. 3a), as well as in comparison to oligodendroglioma, oligoastrocytoma, and astrocytoma samples (Fig. 2b). There was also a notable elevation in NANP expression with increasing tumor grade (Fig. 2c-d and Supplementary Fig. 3b). Moreover, NANP expression was significantly higher in recurrent and secondary GBM when compared to the primary tumor (Fig. 2e). It was also significantly upregulated in GSCs, which are associated with RT resistance7, compared to paired matched tumor from which each GSC was derived (Fig. 2f). Importantly, NANP’s high expression was associated with poor patient survival in multiple cohorts (Fig. 2g-h and Supplementary Fig.3c).

We also analyzed genes with colinear expression to NANP in The Cancer Genome Atlas (TCGA) dataset and identified a list of genes significantly (p<0.05) correlated with NANP expression (Supplementary Data 3). Enrichment analyses were significant for the "N-glycan Synthesis" pathway (Fig. 2i and j), aligning with reported functions of NANP in sialylation. Surprisingly, several key pathways related to DNA damage repair, including "mismatch repair," "DNA replication," "base excision repair," and "homologous recombination" were also significantly enriched (Fig. 2i and k), suggesting a potential role for NANP in DDR. These findings highlight the potential involvement of NANP in glycan synthesis processes and DDR, prompting us to further investigate its functional role in radiation response.

Targeting NANP radiosensitizes GBM
To interrogate and validate the role of NANP in radiation response, we first performed clonogenic and cell viability assays after radiation treatment. GSCs (GSC20 and GSC11) were transduced with four independent NANP-targeting short hairpin RNAs (shRNAs) (shNANP-1/3/4/5) or non-targeting control (shCTL) through lentiviral transduction. Silencing efficiency ranged from 60% to 90% among these shRNAs (Supplementary Fig. 4a-b, 5a-b and 6a-b). NANP attenuation significantly improved radiation sensitivity in both GSC20 and GSC11 (Fig. 3 a and b). The RT sensitizing effect of NANP silencing was also observed in the glioma cell line U87 (Supplemental Fig. 6c).

RT primarily exerts its cytotoxic effects by inducing DNA damage, especially DSB, which often triggers G2/M cell cycle arrest to allow time for DNA repair and, if repair fails, the cells undergo apoptosis25. To further investigate how NANP effects DDR, we accessed the radiation induced cell cycle arrest and apoptosis in GSCs with and without NANP silencing. We observed a higher proportion of NANP silenced cells are still in the G2/M 24 hours after radiation compared to controls (Fig. 3c), similar to results seen with NHEJ1 silencing which was used as a positive control. We noted increased G2/M arrest with more NANP silencing across the range of shRNAs used. This observation was consistent across GSC20, GSC11, and the U87 cell lines with 2-4 different shRNAs (Supplemental Fig. 4c, 5c and 6d). Importantly, at 24 hours post-radiation, we also observed increased apoptosis in both GSC20 and GSC11 cells with NANP silencing compared to control cells (Fig. 3d-e and Supplemental Fig. 5d-e). Additionally, a time course study in GSC20 cells showed that after 8 Gy radiation, apoptosis increased over time and NANP silenced cells had higher apoptotic rates compared to control cells at 24, 48, 72, and 96 hours, (Supplemental Fig. 7). When exposed to a higher dose of 16 Gy, NANP silenced cells exhibited more apoptosis than that was induced by 8 Gy, while control cells showed similar levels of apoptosis compared to that induced by 8 Gy (Supplemental Fig. 7). Using CRISPR system, we also validated these findings in NANP knockout cells (Fig. 3f-g and Supplemental Fig. 8a-b). Moreover, re-expression of shNANP1-resistant NANP (NANPr), which expresses wild-type NANP but uses alternative codons based on wobble base pairing, rescued the radio-sensitizing phenotype of NANP silencing (Fig. 3h and Supplemental Fig. 8c). Together, these findings suggest that NANP silencing resulted in increased G2/M cell cycle arrest and subsequent apoptosis following radiation.

NANP silencing causes more DNA damage in response to radiation and impairs DNA repairs
To further explore how NANP disruption contributes to more G2/M arrest and apoptosis following radiation, we determined the level of γH2AX, a marker of DNA DSBs, whose dynamic changes reflect DNA repair capacity and efficiency26. Immunofluorescence analysis (Fig. 4a-b) of γH2AX foci revealed that 1h post radiation, nearly all cells exhibited extensive damage which was repaired over time. However, NANP deficient cells showed more γH2AX foci at 16 hours post radiation. This trend of increased γH2AX foci persisted, although to a lesser extent, at the 24-hour time point. Notably, the near-100% positivity of γH2AX at 1 hour post-radiation made it challenging to discern differences between groups at this early time point. Thus, immunoblot was performed to detect γH2AX protein levels in GSC20, GSC11 and U87. Consistent with the immunofluorescence results, higher γH2AX protein levels were observed at late time points in NANP repressed cells, and immunoblot was able to distinguish different levels of γH2AX at earlier time points of about 3 hours post-radiation when DNA damage repair is insufficient (Fig. 4c-d), indicating the possibility of more initial radiation-induced DNA damage in NANP deficient cells.

To complement these findings, we employed the alkaline comet assay, a sensitive method for assessing DNA damage. NANP suppressed cells exhibited a higher proportion of cells with elongated tails compared to control cells at 1 hour after radiation (Fig. 4e-f), validating the observation of more damage at early time point. This difference in damage level persisted as NANP silenced cells retained a higher tail moment (Fig. 4e-f) even at 24 hours when a majority of elongated comet tails were resolved in control cells as shown by the lower tail moment. This difference in damage could stem from variations in initial radiation-induced damage levels and/or DNA repair capability. To determine if more initial damage were induced in NANP silenced cells, we measured the γH2AX levels at additional time points. The results (Fig. 4g and Supplementary Fig.9 a-b) revealed that γH2AX levels peaked at ~1 h in both shCTL and shNANP cells, while it persisted higher at 1 h, 2 h, 4 h, 8 h,12 h and 24 h in NANP-deficient cells. Furthermore, in even shorter time points (<1 h), when the time is too short to complete repairs and the initial damage was still accumulating as shown by the increase level of γH2AX, NANP-silenced cells exhibited higher γH2AX levels as early as 5 minutes post-radiation (Fig. 4h). Collectively, these data suggest that NANP silencing exacerbates initial radiation-induced DNA damage.

DSB typically activates NHEJ and/or HR repair. HR is a more accurate DNA repair mechanism and happens mainly during the S and G2 phases of the cell cycle when homologues sequences are available, while NHEJ is more error prone and happens at a much higher rate than HR since it can happen at any phase of a cell cycle27. With a robust reporter system28, we were able to quantitatively compare the efficiency of HR and NHEJ. We first evaluated the system by treating cells with SCR7, a Lig4 inhibitor, to block NHEJ. With this system, we observed decreased NHEJ efficiency with no change in HR in the GSC20 treated with the Lig4 inhibitor SCR7 (Supplemental Fig. 10a-b), confirming the efficacy of this reporter system. The reporter was then used to evaluate the HR and NHEJ in NANP silenced and control cells. NANP silenced cells utilized NHEJ significantly more than control cells, while HR was significantly reduced in the same cells (Fig. 4i-k and Supplemental Fig. 10c). These data suggest NANP silenced cells favor error-prone NHEJ more over HR when repairing radiation-induced DSBs. This may partially explain the impaired repair efficacy in NANP deficient cells. Taken together, our data consistently demonstrate the prolonged presence of more substantial DNA damage and impaired DNA repair capacity in NANP silenced cells.

NANP regulates the mesenchymal state of GSCs
To investigate how targeting NANP affects GSC radiosensitivity, we performed whole transcriptome analysis (RNA-seq) and compared gene expression between non-targeting control and NANP silenced cells in both GSC20 and GSC11. Using a q-value < 0.05 and |log2FC| > 0.5 as cut-offs, we identified 614 genes that were significantly up-regulated and 916 genes were significantly down-regulated in NANP knock-down GSC20 compared with control cells (Fig. 5a, Supplementary Data 4). Similarly, in GSC11 we identified 579 up-regulated and 741 down-regulated genes (Supplementary Data 4). Evaluating the overlapping gene sets from these GSCs, we found 112 genes were commonly down-regulated and 67 genes were commonly up-regulated in both GSC20 and GSC11 upon NANP silencing (Supplementary Fig. 11a-b). Interestingly, functional annotation of these common differentially expressed genes using the Database for Annotation, Visualization and Integrated Discovery (DAVID) analysis revealed enrichment for genes associated with proteins containing N-linked glycosylation as well as functions in the extracellular matrix, membrane, and cell adhesion (Supplementary Fig. 11c-d). This suggested the disruption of glycosylation homeostasis upon NANP attenuation, which was consistent with the established role of NANP in glycosylation and suggests the reflection of NANP biology in the transcriptome analysis.

To identify additional involved pathways, we next performed gene set enrichment analysis (GSEA) and identified “epithelial mesenchymal transition (EMT)” as the most significant negatively regulated “hallmark” signature in both GSC20 and GSC11 upon NANP silencing (Fig. 5b). Prior transcriptome analysis of GBM have classified them into three molecular subtypes based on the putative function of the dominant gene expression signature for each class: proneural (PN), for enrichment of neural developmental genes; classical (CL), for genes related to oncogenic signaling; and mesenchymal (MES), for genes associated with mesenchymal functions10. The negative enrichment for the EMT pathway following NANP silencing indicated a possible role of NANP in regulating the MES subtype. This was further supported by the negative enrichment of the “Verhaak glioblastoma mesenchymal” gene set upon NANP silencing (Fig. 5c). Furthermore, we employed a classification strategy utilizing single-sample GSEA (ssGSEA) combined with equivalent distribution resampling as previously described10. This approach enabled us to assign three empirical classification p-values, facilitating the identification of significantly activated subtypes. Notably, GSC20 was classified into the mesenchymal (MES) subtype. However, following NANP knockdown, this significance diminished, and the knockdown cells exhibited a trend towards other subtypes without a significant classification (Fig. 5d), further supporting the shift from mesenchymal status following NANP silencing.

To further validate the shift towards a less mesenchymal state of GSC upon NANP attenuation, we assessed the protein levels of key markers involved in the EMT via immunoblot. We observed an increase in the epithelial marker E-cadherin and a decrease in the mesenchymal marker N-cadherin following NANP silencing (Fig. 5e), consistent with the elevated mRNA levels of CDH1 and reduced levels of CDH2 (Fig. 5f). Additionally, NANP silencing led to a decrease in the EMT-induced transcription factor SLUG, along with alterations in the β-catenin signaling pathway (Fig. 5e). These alterations were evident both at the protein and mRNA levels (Fig. 5e-f), which was validated by knock-out and rescue experiments (Supplementary Fig. 12a-c). Given the known impact of EMT on cell migration, we also investigated migration capacity through transwell migration assays and found decreased migration of GSC20 following NANP silencing (Fig. 5g-h). Collectively, these findings support the conclusion that NANP positively regulates the mesenchymal state of GSCs.

NANP regulates radiosensitivity by promoting a MES phenotype through N-linked sialylation of TNFR1, which activates the NF-κB pathway
Based on additional GSEA analysis of the RNA-seq data, we observed that NANP silencing cells were negatively enriched for genes in the NF-κB pathway (Fig. 5b and Fig. 6a). Our previous study demonstrated that NF-κB pathway activation leads to mesenchymal activation and promotes radiation resistance in GSCs12, a conclusion supported by multiple other reports14,15. Considering the regulation of MES state and the NF-κB by NANP, we hypothesized that NANP regulates MES status and RT sensitivity through the regulation of NF-κB.

We first validated this finding by accessing the expression of NF-κB regulated MES genes in GSC20, GSC11 and U87 by reverse transcription-quantitative PCR (RT-qPCR). We observed a significant decrease in expression of TNC, TNFAIP3/6, ITGB1, and ICAM1 (Fig. 6b). The primary mechanism for canonical NF-κB activation is mediated by tumor necrosis factor receptor (TNFR). Upon TNF binding, TNFRs form membrane bound receptor complexes, leading to activation and phosphorylation of the IκB kinase (IKK) complex and thereby triggering ubiquitin-dependent IκBα proteasomal degradation29. Thus, we further validated the regulation of this key signal cascade by NANP. As expected, we observed a decrease in p-IKK/ and an increased level of IκBα upon NANP silencing (Fig. 6c). Inhibition of NF-κB by overexpression of dominant-negative IκB (dnIκBα) led to significant down-regulation of MES genes (Fig. 6d, Supplementary Fig. 13a), and the regulation of these genes by NANP was largely blunted (Fig. 6d), supporting the conclusion that the regulation of MES genes by NANP occurs via the NF-κB pathway and is dependent on IκBα. Taken together, our data suggest that NANP promotes the MES phenotype of GSCs through the activation of the NF-κB signaling pathway upstream of IB.

We next explored how NANP influences NF-κB signaling. Given its role in sialylation and the known effects of sialylation on EMT30,31, we first conducted a comprehensive examination of sialylation changes through lectin screening to detect surface sialylation changes. Our analysis revealed that α2,6-linked N-sialylation detected by SNA (Sambucus nigra agglutinin) and α2,3-linked O-sialylation detected by MAL-II (Maackia amurensis lectin II) were not altered. Corresponding de-sialylation detection by PNA (Peanut agglutinin, 1,3-linked galactose) and WGA (Wheat germ agglutinin, 1,4-linked-N-Acetyglucosamine) also showed no changes, reflecting that global membrane sialylation remained unchanged (Supplementary Fig. 14). This is consistent with previous report that NANP knockout does not disrupt sialylation of cell surface glycans but decrease de novo sialic acid biosynthesis32.

However, previous studies have shown that TNFR1 activity is significantly affected by α2,6-linked N-linked sialylation, which inhibits TNFR1 internalization and thereby favors signaling towards NF-κB activation33,34. Although we did not observe a global cell surface sialyation change after NANP silencing, we hypothesized that NANP suppression might specifically affect sialylation of TNFR1, which is upstream of IκBα, thereby inhibiting the NF-κB pathway. To test this hypothesis, we performed immunoprecipitation (IP) using SNA-agarose beads to isolate α2,6-linked sialylation and followed with TNFR1 immunoblot. We observed decrease binding of TNFR1, but not another membrane sialoglycoprotein, podoplanin (PDPN)35, to SNA in NANP knock down cells compared to control cells (Fig. 6e), indicating TNFR1 in NANP silenced GSC20 had reduced α2,6-sialylation. This finding was further validated by oppositely IP of endogenous TNFR1 and blot for its SNA sialylation (Supplementary Fig. 15a-b). After PNGase F digestion, we observed down shift of TNFR1 and absent of SNA blotting, further demonstrated the purity of immunoprecipitated TNFR1 and specificity of SNA detection, respectively (Supplementary Fig. 15a-b).

Given that sialylation of TNFR1 affects its internalization, we performed an internalization assay as previously reported36 to determine the impact of NANP silencing on this process. Cells were incubated with Flag- tagged TNF for 60 min on ice, which allows TNF binding to TNFR1, but prevents the internalization of TNF-TNFR1 complexes. TNFR1 internalization was then examined by switching cells with bound TNF to 37℃ for 30 min. After this interval, cells were stained with the anti-Flag antibody to assess the levels of TNF-TNFR1 complexes remaining on the cell surface after the internalization step. We did observe significantly increased internalization of TNFR1 after TNF binding in NANP knockdown cells evidenced by greater left-shift in density plot of surface TNFR1 (Fig. 6f and Supplementary Fig. 15c). Together, these data suggest NANP promotes TNFR1 sialyation and thereby regulates its internalization.

TNFR1 sialylation inhibits its internalization and promotes NF-κB activation33,34. Consistently, the basal level of NF-κB signaling was lower in NANP silenced cells as evidenced by the decrease in NF-κB target genes’ expression and increase in IκBα protein level (Fig. 6b-c). Furthermore, in the presence of TNF, NF-κB signaling induction and the nuclear p65 level was attenuated in cells where NANP was silenced (Fig. 6g-h and Supplementary Fig.13c), indicating an impaired response of TNFR to its ligand. Functionally, the increase of G2/M cell cycle arrest in response to RT by NANP suppression could be reversed by TNF mediated NF-κB activation (Fig. 6i, Supplementary Fig. 13b), consistent with our previous study that found that TNF induced EMT and rescued G2/M arrest after radiation in GSCs12. Collectively, these findings suggest that NANP regulates radiosensitivity by promoting a MES phenotype through N-linked sialylation of TNFR1 leading to activation of the NF-κB pathway (Fig. 6j).

NANP suppression radiosensitizes GBM in vivo
To validate the radiosensitizing effect of NANP attenuation observed in vitro, we investigated its impact on tumor growth following clinically relevant fractionated radiotherapy. Immunocompromised mice received intracranial injections of control (shCTL) or NANP silenced (shNANP) GSC20 or GSC11 cells to establish orthotopic xenografts (Fig. 7a). These tumors were then treated with a fractionated regimen of 2 Gy × 5 days of RT weekly for two weeks. The results (Fig. 7b) demonstrated that RT did not significantly extend the survival of mice with control GSC20 cells implantation, which was consistent with the known radioresistant nature of GSC20. However, RT significantly extended the survival of mice receiving NANP repression GSC20 cells (log-rank p-value: 0.0093). Similar results were obtained in GSC11 model (Fig. 7c). Although RT alone prolonged the survival of mice implanted with control GSC11 cells, consistent with the RT-sensitive nature of GSC11, RT extended the survival of mice receiving NANP-silenced GSC11 to a greater extent (Fig. 7c). We also performed immunohistochemical staining for TNC as an indicator of NF-κB regulation in the aforementioned xenograft models at the survival endpoint (Fig. 7d). TNC staining was significantly diminished in the shNANP group compared with the shCTL group (Fig. 7e), regardless of radiation status, validating the intrinsic suppression of the NF-κB pathway in vivo following NANP attenuation. Lastly, we explored the clinical relevance of NANP and RT by analysis of the Glioma Longitudinal Analysis consortium (GLASS) dataset37. NANP expression was significantly and negatively correlated with glioma patient survival of those receiving RT treatment in the GLASS cohort (Fig. 7f). In contrast, for the patients not receiving RT, there was no significant difference in survival between patients with high and low NANP expression (Fig. 7g). These findings highlight the promising radiosensitizing effect by NANP suppression in vivo, warranting future therapeutic development.

Methods
All experimental procedures involving animals and human-derived samples in this study were conducted in strict compliance with the relevant ethical regulations, including the National Institutes of Health (NIH) Guide for the Care and Use of Laboratory Animals and the Declaration of Helsinki. The animal study protocol was approved by the Institutional Animal Care and Use Committee (IACUC) of NYU Langone Health.

Cell culture, DNA construction, lentiviral transduction and cell line generation.
GSCs were developed in our laboratory as described previously12. GSC cells were maintained in neural basal media (NBM) containing DMEM/F12 medium (Corning, 10-090-CV), supplemented with B27 (Gibco, 17504-044), epidermal growth factor (EGF) (20ng/ml, Sigma, E9644), basic fibroblast growth factor (bFGF) (20ng/ml, Sigma, F0291) and 1% antibiotic/antimycotic supplements (Corning, 30-004-CI). For cell passaging, GSCs were dissociated into single cells with Accutase (Sigma, A6964) once large neurospheres formed. U87 (ATCC, HTB-14) and 293T (ATCC, CRL-3216) cells were grown in DMEM with 10% fetal bovine serum (FBS) (Sigma, F0926) and 1% antibiotic/antimycotic supplements (Corning, 30-004-CI). Lentiviral plasmids for targeting NANP were ordered from Sigma (TRCN0000050489 for shNANP-1 or shN1 in short; TRCN0000050488 for shNANP-3 or shN3 in short; TRCN0000050491 for shNANP-4; TRCN0000050492 for shNANP-5 and TRCN0000275632 for shNHEJ1), and empty vector was used as control. Lentiviral plasmid for expressing dominant-negative IB (dnIB) was constructed by inserting the dnIB expressing DNA amplified from pBABE-Zeo-IkB-SR48 into a lentiviral vector pHAGE-BSD with blasticidin selection marker. Lentiviral plasmid for expressing shRNA-resistant NANP was cloned by overlapping PCR to introduce wobble codons at the shN1 target region using cDNA as template, and pHAGE-BSD was used as vector. Lenti-CRIPSRv2-Blast (Addgene, # 83480) was used to generate guide RNAs (sgNANP: ACTCTCATCGACACGGCCG; sgCTL: GCGAATACGCCCACGCGAT) for knock-out. For virus production, 293T cells were transfected with lentiviral core plasmid and lentiviral packaging plasmids psPAX2 (Addgene, #12260) and pMD2.G (Addgene, #12259) at a ratio of 4:3:1. The media was changed to NBM medium 12 h after transfection in the virus was used to transduce GSCs in order to avoid introducing of FBS to GSCs. Viral supernatant was collected 72 h after transfection and filtered with a 0.45 μm filter (Millipore) and then used for cell transduction at a multiplicity of infection (MOI) of 0.3 in the presence of polybrene (Sigma, TR-1003-G). 48 hours after transduction, cells were washed and selected with 2 μg/ml puromycin or 5 g/ml blasticidin for 10 days. For CRISPR-mediated knockout, the bulk transduced cells survive the selection were first expanded to get enough cells and then used to validate the overall gene knockout by western blot. The bulk cells that showing target gene protein decreased were then seeded into multiple 96-well plates for single-cell clone isolation by limited dilution approach. Single-cell clones were then isolated and expanded to obtain enough cells for western blot validation and other experiments, such make freezing stocks, colongenic assays, cell cycle analysis etc.

Clonal evolution of RT resistance in GSCs
The clonal evolution study was performed as previous described19. Briefly, 1 million GSC20 cells were barcoded using the CAPTURE barcoding library19 at a MOI < 0.3. The founder barcoded cells were then expanded and divided into a parallel control group and 5 RT-treated replicates, each containing 108 cells (> 100× barcode diversity). The cells from the RT-treated group were subjected to fractioned radiation treatments (2 Gy × 10), which were delivered daily for two weeks (5 days/week). The control cells were cultured in parallel. After the last dose of radiation, the cells were continued in culture for another 35-40 days to allow for regrowth of the population. Cells (> 100× barcode diversity) were harvested for barcode deconvolution. TruSeq-style barcode amplicon libraries were amplified and subjected to deep sequencing using an Illumina sequencer. The sequencing reads were mapped and counted as previously described19. The GFOLD (generalized fold change)49 algorithm was employed to produce reliable statistics based on the posterior distribution of log2 fold change, which was visualized using the pheatmap R package.

CRISPR screen
The Brunello genome-wide CRISPR-Cas9 library50 was used in lentiviral pooled format to transduce GSCs. The experiment was performed in duplicate. For each screen replicate, cells were transduced at ~300-fold representation of the library (at 30% infection efficiency). 2 days after transduction, puromycin was added (2 μg/ml) for 7 days. The cells were then passaged to maintain 300-fold representation and cultured for an additional 25 days (> 8 cell doublings). Genomic DNA was extracted using Quick-DNA Midiprep Plus Kit (Zymo Research, D4075). TruSeq-style amplicon PCR was performed to amplify single guide RNAs (sgRNAs). The amount of genomic DNA used for PCR was calculated to maintain 300-fold coverage over the library. The resulting amplicon PCR products were pooled for each experimental replicate and purified using AMPure XP Bead (Beckman Coulter, A63880), followed by concentration quantification using KAPA Library Quantification Kits (Roche, 07960140001) and sequencing using a HiSeq 4000 (Illumina). The resulting reads as FASTQ files were analyzed using MAGeCK51 to generate sgRNA- and gene- level count and ranking tables, which were inputted for further analysis and visualization using MAGeCKFlute52. The top hits were subjected to Gene Ontology (GO) and Reactome pathway network analysis using Enrichr-KG53, and the result was visualized by Cytoscape 3.

Cell cycle analysis
Cells were collected by centrifugation and digested to single cells. Cells were washed with phosphate buffered saline (PBS) once then fixed with ice-cold 66% ethanol-PBS solution overnight at 4 oC. Then cells were stained using the Propidium Iodide Flow Cytometry Kit (Abcam, ab139418) according to the manufacturer’s instructions. Briefly, cells were stained with 200 µl 1× propidium iodide (PI) plus RNase staining solution at 37 oC in the dark for 30 min then analyzed using a LSRII HTS flow cytometer (BD Biosciences). Data analysis was performed using FlowJo (Becton Dickinson) or ModFit LT (Verity Software House).

Apoptosis analysis
Cells were collected by centrifugation and resuspend into single cell suspension followed by two rounds of PBS washing. Apoptosis assays were performed using the FITC Annexin V apoptosis Detection Kit I (BD pharmingen, 556547). Briefly, cells were resuspended in 1× binding buffer and stained with FITC AnnexinV and PI at room temperature in the dark for 15 min and then analyzed using a LSRII HTS flow cytometer (BD Biosciences). Data analysis was performed using FlowJo (Becton Dickinson).

Clonogenic assay and cell viability assay
Exponentially growing U87 cells were seeded in 6-well plates (3000 cells/well) overnight before treatment with radiation. Radiation was performed using a CellRad X-Ray Irradiator (Precision X-Ray) at a dose rate of approximately 1Gy/min. U87 cells were allowed to grow for 10-14 days after radiation. Media was changed every three days. Cells were then fixed with 4% paraformaldehyde (PFA) and stained with Crystal violet. For cell viability assays, 1000 cells with four replicates were seeded to 96-well plates and then given corresponding radiation treatment. Cells were allowed to grow in the incubator for 10-14 days with media changed and replaced every three days. Cell viability was measured by CellTiter-Glo (Promega, G7571). The clonogenic assay for GSCs were performed as previously described54. Survival fraction and survival curves were fitted with a Linear Quadratic model using Prism 9 (GraphPad).

Immunofluorescence H2AX staining
GSCs were seeded on Poly-D-Lysine/Laminin coated 12 mm round cover glasses (Corning BioCoat, 354087) in 24-well plates. The following day GSC cells were attached and treated with radiation. After treatment at the indicated timepoints cells were fixed with 4% PFA followed by permeabilization and blocking in blocking solution [1% bovine serum albumin (BSA), 0.1% Triton X-100 in PBS] at room temperature for 30 min. Cells were then stained with H2AX antibody (Millipore Sigma, 05-636, 1:1K in blocking solution) at 4 oC overnight. After washing with PBS-T (PBS containing 0.1% Tween-20) for three times, cells were stained with goat anti-Mouse IgG (H+L) Highly Cross-Adsorbed Secondary Antibody, Alexa Fluor™ Plus 488 (Thermo, A32723, 1:2K in blocking solution) at room temperature for 1h. After washing with PBST for three times. Stained cells were mount with ProLong™ Glass Antifade Mountant with NucBlue™ Stain (Invitrogen, P36983). Images were acquired by Zeiss Axio Observer microscope (Zeiss) and analyzed by ImageJ. Nuclei with more than 5 foci were considered as H2AX positive.

Comet assay
GSC cells were harvested and suspended as single cells at the indicated time after radiation. Alkaline comet assay was performed with CometAssay kit (Trevigen, 4250-050-K) according to the manufacturer’s instructions. Briefly, freshly harvested cells were mixed with low-melting point agarose and spread on specially treated CometSlides. Cells on the slides were then lysed at 4 oC for 1 h and then in alkaline unwinding solution for 30min at room temperature in the dark. The slides were then subjected to horizontal electrophoresis at 21V for 30 min under alkaline conditions, followed by neutralization and SYBR green staining. During electrophoresis, damaged DNA migrates away from the nucleus forming a comet-like tail, while undamaged DNA remains in the head region. Images were acquired by the EVOS® FL Auto Imaging System (Life Technologies) and tail moment were analyzed by OpenComet55.

Immunoblot
Cells were harvested at indicated time points after treatment and washed with PBS once, followed by lysing with RIPA buffer (CST, 9806). Protein concentration was measured by Pierce™ BCA Protein Assay Kit (Thermo, 23225). After SDS-PAGE and transfer, membranes were blocked with 5% BSA in TBST (TBS buffer containing 0.1% Teween-20) and probed with antibodies against phospho-H2AX (Ser139) (MilliporeSigma, 05-636), NANP (SantaCruz, sc-374637), E-cadherin (CST, 3195), N-cadherin (CST, 13116), Slug (CST, 9585), -catenin(CST, 8480), pospho-IKK (Ser176/180) (CST, 2697) IKK (CST, 11930) IKK (CST, 8943) phospho-p65 (CST, 3033) p65 (CST, 8242) IB (CST, 1814) PDPN (CST, 9047) Tubulin probed by anti-tubulin (Biolegend, 801202) was used as loading control. Membranes were incubated with appropriate horse radish peroxidase (HRP)-linked anti-rabbit IgG (CST, 7074) or anti-mouse IgG (CST, 7076) secondary antibodies and protein bands were detected by Amersham ECL Prime Western Blotting Detection Reagent (Cytiva, RPN2236) or Clarity™ Western ECL Substrate (Biorad, 1705060) with ChemiDoc MP Imaging System (Biorad).

HR/NHEJ reporter assay
The lentiviral pLCN DSB Repair Reporter (DRR) was previously described28. GSC20 single clone was picked after transduced with viral particle of the DDPR at MOI < 0.1. Gene silencing was done on this single clone by lentivirus transduction. For DNA repair reporter analysis, one million cells containing the integrated reporter were transfected with 4 μg pDonor HR plasmid (Addgene, #98896, pCAGGS DRR mCherry Donor EF1a BFP) and 2.5 μg pCBASceII plasmid (Addgene, #26477) using Lipofectamine 3000 (Thermo Fisher, L3000015). 72 hours after transfection, cells were digested to single cells and resuspended in 1× PBS and directly subjected to flow cytometry analysis (BD, LSRII HTS). Green fluorescent protein (GFP) and mCherry positive cells were gated on blue fluorescent protein (BFP) positive cells to access the NHEJ and HR, respectively.

RNA-seq and data analysis
RNA-seq was performed similarly as previously described19. Briefly, total RNA was extracted using RNeasy Plus Mini Kit (Qiagen, 74134), and RNA-seq libraries were prepared using the Illumina TruSeq Stranded mRNA kit according to the manufacturer’s instructions. Paired-end reads were sequenced on an Illumina sequencer. Reads were trimmed for adapters and quality using Trimmomatic version 0.36 followed by aligning to the human reference genome (hg19) using STAR version 2.5 with standard settings. The featureCounts program was employed to generate a genes-to-samples counts matrix. Differentially expressed genes were analyzed using DESeq2. Gene set enrichment analysis (GSEA) was performed using GSEA. Transcriptome-based GSC subtyping was performed using ssgsea.GBM.classification R package10. RNA-seq data has been submitted to the Gene Expression Omnibus (GEO) repository (GSE274135).

Transwell cell migration assay
Transwells with 8.0 µM pore polycarbonate membrane Insert (Corning, 3422) was precoated with poly-l-ornithine (20 μg/mL) (Sigma, P3655) and laminin (5 µg/mL) (Sigma, L2020). GSC20 carrying control shRNA or NANP shRNA (3 × 104 cells/insert) were seeded into the upper chamber in three replicates. NBM with 10% FBS were added to the bottom chamber as a chemo attractant. Cells were allowed to migrate towards the bottom in a humidified incubator at 37 °C with 5% CO2 for 48 h. Then the cells on the membrane were fixed with 4% PFA and stained with crystal violet. Images were taken by EVOS® FL Auto Imaging System (Life Technologies) with 8-12 fields per membrane. Quantification of cells was performed using ImageJ.

Reverse transcription quantitative -polymerase chain reaction (RT-qPCR)
Total RNA was isolated from cells after treatment with RNeasy Plus Mini Kit (Qiagen, 74134) and then reverse transcribed into cDNA using Maxima H Minus First Strand cDNA Synthesis Kit (Thermo, K1652). RT-qPCR was performed on Applied Biosystems Vii7 cycler with PowerUp™ SYBR™ Green Master Mix (Thermo, A25742). Primers used are listed in Supplemental Data 5.

Cell fractionation
The cells were fractionated with NE-PER Nuclear and Cytoplasmic Extraction Reagents (Thermo Scientific, 78833) according to manufacturer’s instruction. Immunoblots were performed following nuclear extraction. CTCF (CST, 2899) was used as the indicator of nuclear fraction and Tubulin (BioRad, 12004166) was used as the indicator of cytoplasmic fraction.

Lectin screening
For detecting cell surface sialylation, 5 × 105 GSC20 cells were suspended as single cells then washed with staining buffer (1× PBS, 1mM CaCl2, 1mM MgCl2, 1% BSA) for three times. Cells were subsequently incubated with biotinylated Sambucus nigra agglutinin (SNA, 4 μg/ml, Vector Labs, B-1305-2), biotinylated Maackia amurensis Lectin II (MAL-II, 4 µg/ml, Vector Labs, B-1265-1), biotinylated peanut agglutinin (PNA, 4 µg/ml, Vector Labs, B-1075-5) or biotinylated Wheat germ agglutinin (WGA, 4 µg/ml, Vector Labs, B-1025-5) in staining buffer at 4 °C degree with rotation for 1 h. Cells stained with blank staining buffer without lectin were used as negative controls. The cells were then washed with cold staining buffer and then incubated with Streptavidin-conjugated Alexa Fluor 488 (2 µg/ml, Invitrogen, S11223) at 4 °C degree with rotation for 1 h. After washing with cold staining buffer three times, the fluorescence of the labelled cells was detected by flow cytometry (LSRII HTS, BD).

SNA-pull down assay
For lectin-IP assay, exponentially growing shCTL and shNANP GSC20 were collected and washed once with PBS. Pellets were then lysed with RIPA buffer (CST, 9806) supplemented with Halt Protease and Phosphatase inhibitor cocktail (Thermo, 78442). 1000 µg of whole cell lysate was incubated with 50 µl of SNA-conjugated agarose beads (VectorLab, AL-1303-2), which were prewashed with RIPA buffer, overnight at 4 oC with rotation. The α2-6-sialylated proteins bound to the beads were then precipitated by centrifugation, followed by washing with RIPA buffer for three times to remove nonspecific binding. The sialylated proteins were then eluted from the beads using 50 µl 1× Laemmli sample buffer by boiling at 98 oC for 5min. Parallelly, 100µg of whole cell lysate prepared using 1× Laemmli sample buffer was used as input. Proteins were resolved by SDS-PAGE and immunoblotted for TNFR1 (CST, 3736) and ß-tubulin (Biolegend, 801202).

TNFR1 glycosylation analysis
Exponentially growing shCTL and shNANP GSC20 were collected and washed once with PBS. Pellets were then lysed with RIPA buffer (CST, 9806) supplemented with Halt Protease and Phosphatase inhibitor cocktail (Thermo, 78442) for 1h on ice. After centrifugation at 16,000 rpm at 4 °C, the supernatants were collected. 5% of the supernatants were prepared using 1× Laemmli sample buffer as input while remaining supernatant were incubated with TNFR1 primary antibody conjugated agarose beads (SantaCruz, sc-8436 AC) at 4 °C overnight. The beads were washed three times with extensive wash buffer (50mM Tris-HCl, pH 7.4, 500 mM NaCl, 1mM EDTA and 1% Triton X-100) at 4 °C and one more time with modified RIPA buffer (50mM Tris-HCl, pH 7.4, 150 mM NaCl, 1mM EDTA. Washed beads were divided equally to two aliquots, one aliquot was used to directly elute the protein with 2× SDS sampling buffer (80mM Tris-HCl, pH 6.8, 2% SDS, 10% glycerol) by boiling at 98 °C for 5 min. The other aliquot was digested with PNGase F (NEB, P0704) according to manufacturer’s instructions. Briefly, proteins were first eluted with 1x denaturing buffer (0.4% SDS, 40mM DTT) at 100°C for 10min. After cooling to room temperature, SDS was neutralized with 10% Nonidet P-40 (NP-40). Glycans were digested at 37 ̊C for 4h using 1 U PNGase F per 10 μg proteins. For immunoblot analysis, the membranes were blocked with use carbon free blocking solution (VectorLab, SP-5040-125) at room temperature for 1h. Then the membranes were incubated with fluorescein (FITC) conjugated Sambucus Nigra Lectin (Thermo, L32479) and Rhodamine conjugated Ricinus Communis Agglutinin I (RCA I, RCA120) (VectorLab, RL-1082-1) at same time at room temperature for 3hr in PBS-T (PBS containing 0.05% Tween-20). After washed three times wash of PBS-T, bands were detected with ChemiDoc MP Imaging System (BioRad). Silver staining was performed with Pierce™ Silver Stain Kit (Thermo, #24612) according to manufacturer’s instructions.

TNFR1 internalization assay
Exponentially growing shCTL and shNANP GSC20 were treated with 200ng/ml TNF with Flag tag (Enzo Life Sciences, ALX-522–008) at 4 °C for 1h. Unbound TNF-Flag was washed off with ice-cold PBS twice. Cells were then incubated with prewarmed 37 °C serum-free medium for 30 min to induce the internalization of TNF-TNFR1 complexes. Control cells were maintained at 4 °C. The internalization step was then terminated by placing cells back on ice. To measure the levels of surface TNF-TNFR1 complexes, cells were collected and washed with ice cold PBS once and then stained with anti-Flag-Alexa 647 (1:200, Invitrogen, 701629RP647) for 30 min on ice. Propidium Iodide (PI) (Sigma Aldrich, P4170, 2 μg/ml) was used to exclude dead cells. Data were acquired on a BD FACSymphony™ A5 flow cytometer and analyzed by the FlowJo (Becton Dickinson). The relative amount of internalization was calculated by subtracting MFI values obtained after the 37 ° C internalization step from MFI values obtained at 4 °C prior to the internalization step.

Animal experiments
All animal studies were performed in accordance with protocols approved by IACUC of NYU Langone Health. Mice were housed under specific pathogen-free (SPF) conditions in a temperature-controlled room maintained at 22 ± 2°C with a relative humidity of 50 ± 10%. A 12-hour light/12-hour dark cycle was implemented (lights on at 07:00 AM, lights off at 07:00 PM), and mice had ad libitum access to standard laboratory chow and filtered water. 6-8 weeks old BALB/c Nude (nu/nu) were used in this study. All mice were randomly assigned to appropriate treatment groups. For intracranial orthotopic implantation, 5 × 105 cells of dissociated GSCs were stereotactically injected into the left striatum of nude mice using a guide-screw technique56. Female mice were used for GSC20 experiments, and equal numbers of male and female mice were initially used for GSC11 experiments (a small number were lost during guide-screw placement/implantation). Moreover, GSC20 and GSC11 were derived from male and female patients, respectively, therefore sex was not considered a biological variable. The GSCs were transduced by pLenti-PGK-V5-LUC Neo (Addgene, #21471) viral particles to express luciferase for monitoring tumor growth using an in vivo imaging system (IVIS) bioluminescence imaging system. Fractionated radiation (2 Gy for 5 consecutive days) to the whole brains of mice with a small field biological irradiator, the SARRP Irradiator from Xstrahl with image-guided radiation capability was performed and the treatment was delivered with the small 1.5 mm cylinder. Moribund state, inability to rise or ambulate were used as humane endpoints, and spontaneous death was also recorded for mouse survival. The endpoints were monitored daily by trained staff working in the animal facility, who would attach identification tags to mice that met the endpoint criteria and promptly notify the laboratory technicians for subsequent handling, in strict accordance with the guidelines of the IACUC at NYU Langone Health. Brain tissues were harvested at the endpoint for immunohistochemistry (IHC) analysis.

Immunohistochemistry (IHC)
For IHC, brains were fixed in 4% PFA followed by paraffin-embedding. Five-micron thick sections were immune-stained using a Leica BondRX automated stainer according to the manufacturer’s manual. Briefly, tissues underwent deparaffinization online, followed by epitope retrieval for 20 minutes at 100oC with Leica Biosystems ER2 solution (pH9, AR9640) and endogenous peroxidase activity blocking with H2O2 (provided in the Leica BOND Polymer Refine Detection System, DS9800). Sections were then incubated with primary antibodies against TNC (CST, 93029) at 1:600 for 30 minutes at room temperature. Primary antibodies were detected with anti-rabbit HRP-conjugated polymer and 3,3’-diaminobenzidine substrate that are provided in the Leica BOND Polymer Refine Detection System. Following counter-staining with hematoxylin, slides were scanned at 40× on a Hamamatzu Nanozoomer (2.0HT) and the image files uploaded to the NYUGSoM’s OMERO Plus image data management system (Glencoe Software). TNC positive areas and intensity were quantified with IHC image analysis Toolbox57.

Database analysis
The NANP expression level in GBM patients and expression of correlated genes and the relation to patient survival data from clinical cohorts were obtained from GlioVis58. The analysis of NANP expression in RT-related patient survival from the GLASS cohort was performed using cBioPortal59. Overrepresenting pathway analysis of NANP correlated genes was performed using DAVID60.

Statistics
Unless otherwise noted, all tests were carried out in three biological replicates. All results were presented as mean ± SD unless otherwise stated with statistical significance determined by tests as indicated in figure legends. The analysis was performed with Prism 9 software (GraphPad) or R (version 4.1) unless otherwise noted in the methods.

Data availability: All RNA-seq data were deposited in the NCBI GEO repository under accession GSE274135 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE274135). Raw data for the genome-wide CRISPR screen and clonal evolution analysis have been deposited in the NCBI Sequence Read Archive (SRA) repository under accession number PRJNA1432116 (https://www.ncbi.nlm.nih.gov/sra). Other data that support the findings of this research are available within the paper and its Supplementary Information. Source Data are provided with this paper.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Ding et al present data supporting a model whereby NANP supports the mesenchymal phenotype of GBM cells, including a more radioresistant phenotype, and hence targeting NANP can serve to radiosensitize GBM. The CRISPR screen is well-described with clear rationale for the pipeline leading to hits to focus on with strong bioinformatic support for the ultimate focus on NANP. Overall, the data provided are supportive for the relevance of NANP to the response to radiotherapy as well as for the model proposed linking NANP to the NF-kB pathway. There are some minor concerns to be addressed to further support the impact of this work on the brain tumor field.\n1. The authors cannot claim anything regarding mitotic failure as this was not evaluated, “Together, these findings suggest that NANP silencing resulted in increased mitotic failure and subsequent apoptosis following radiation.” This conclusion should be revised to reflect what the data demonstrate.\n2. The authors report decreased migration upon NANP depletion but also report an increase in G2/M arrested cells and an increase in apoptosis following NANP depletion. As arrested cells and dying cells will not migrate, how did the authors control for this when evaluating a decrease in migration? That is, is there a direct decrease in migration or just more cells dying/arrested in the cell cycle that aren’t migrating?\n3. As U87 is well known in the field to no longer represent GBM, it is unclear why these data were included and what they will contribute to the field versus the data with the GSC lines. The limitation of this model should at least be acknowledged in the Discussion.\n4. The authors should go through the work and make sure all conclusions are supported by more than one shRNA (e.g., clonogenic assay in 6G/H is only with shNANP-1).\nAdditional\n1. The intro highlights the TCGA/Verhaak subtypes but more recent single cell studies have further refined the extent of plasticity and heterogeneity and should be noted (i.e. Neftel et al., Cell, 2019).\n2. Main text states fractionated regimen was 2 Gy x 5 days but Methods states 2.5 Gy x 4 days.\n3. Methods only mention U87 for the clonogenic assay but this was done in the other cells as well so details should be added.", "reviewer_2": "Ding et al present a potentially very interesting hypothesis that NANP downregulation may sensitize gliobastoma for radiation therapy. Additionally, they claim that this effect is mechanistically explained by a role of NANP in TNFR1 specific sialylation resulting in an effect on NFKB signaling.\nMany of the experiments that are shown and discussed indeed indicate a link between NANP and RT sensitization. Causality could/should be increased by studying the effect in NANP knockout GSC20 cells and its NANP corrected lines. Mechanistically, in my view no evidence is presented for a defect in sialylation of TNFR1. The SNA agarose IP is not a quantitative test that can be used to assess percentage of sialylation of an individual protein. As alternative, IP of TNFR1 (with proof of purity) should be performed followed by western blotting with a sialic acid specific lectin (showing a decrease in staining) as well as a lectin against the underlying galactose residue (showing elevated staining). Therefore, the claim of a TNFR1 specific sialylation defect as mechanistic explanation for increased radiosensitization is in my view not supported by experimental evidence.\nMinor points:\nSummary\nNANP (N-acylneuraminate-9-phosphatase): NANP (N-acetylneuraminate 9-phosphatase) and consistent naming throughout the manuscript\nMany abbreviations, some unexplained (TNFR1), complicates readability\nIntroduction:\nDespite the potential benefits that each of these advances (has)\nTCGA: explain abbreviation\nResults:\nto identify dominate resistant clones\nTo identify novel (targets?), we\na global surface sialyation change\nFigure 5D: why does shNANP-3 results in much higher residual NANP expression in GSC11 as compared to GSC20?", "reviewer_3": "In this manuscript, the authors identify a novel radiation sensitizing target, NANP, utilizing a genome-wide CRISPR screen. They demonstrate that silencing of NANP reduces NF-kB signaling, potentially through impaired TNFR1 sialylation, leading to a decline in mesenchymal markers. Given that mesenchymal phenotype has been associated with radioresistance, this suggests a mechanism underlying the radiosensitization seen with NANP silencing. Their results correlate well with patient tumor expression profiles and endpoints, and they validate NANP suppression mediated radiosensitization in one in vivo xenograft model. They also demonstrate effects of NANP on modulation of DNA repair, though these findings are less convincing. Overall, most of the results and methods are presented clearly and the manuscript is well-written. A novel radiation sensitizing target, if fully validated, would be highly significant given the great clinical need for addressing radioresistance in GBM. However, there are some points to be addressed as detailed below.\nMajor points:\n1. The data in Fig. 5 are not fully consistent with the authors’ conclusion that NANP silenced cells display a DSB repair defect, favoring NHEJ over HR. Specifically, Fig. 5C and 5F demonstrate increased DNA damage as measured by gamma-H2AX and alkaline comet assay at 1 and 2.5 hours. This cannot be explained by the decrease in HR observed in the reporter assay in Fig. 5H, given that HR requires 4-6+ hours to complete and almost all repair at these early timepoints is NHEJ mediated. This could be interpreted as either a decrease in NHEJ activity (inconsistent with Fig. 5I) or potentially an increase in DNA damage, which has not been ruled out. Of note, Fig. 5B shows no difference in gH2AX foci at 1 hour; however 100% of cells are positive making the cut off used incapable of detecting a difference. In addition, it is not clear why the alkaline comet assay, rather than the neutral comet assay was chosen given the focus on DSB repair.\n2. There is not a clear mechanistic explanation for how NANP silencing specifically effects TNFR1 (while not impacting global sialylation), making it important to validate this finding more fully. Given the extensive use of NANP silencing, a rescue experiment with NANP re-expression should be performed. Experiments investigating TNFR1 localization upon NANP suppression and determining the dependence of radiosensitization on the sialyltransferase ST6Gal-I would significantly improve the validity of the findings, again given that it is not clear mechanistically how NANP is having this specific effect.\nMinor points:\n1. RT doses shown in Figs. 1 and 8 are different than those described in the methods.\n2. In Supplemental Fig. 3 and 4, NANP protein levels via western blotting should be shown upon shRNA knockdown in GSC20 and GSC11.\n3. In Fig. 5D, there is minimal NANP knockdown with shNANP3 despite similar effects on RT sensitivity (Fig. 4b). This should be addressed. As per major point 2 above, the specificity of NANP knockdown should be confirmed via rescue experiment.\n4. The conclusion in lines 187-189 is confusing and doesn’t seem to agree with data in Supplemental Fig. 6.\n5. In Fig. 7E, are there other sialyation target proteins that could be probed as controls to show the specificity of the decrease in TNFR1 pulldown?\n6. Most of the experiments are performed in GSC20 with some reproduced in GSC11. It is noted that GSC20 resembles the mesenchymal subtype. What about GSC11? Will these results be limited to mesenchymal type tumors? Overall, the findings would benefit from reproduction in a wider array of models.", "reviewer_4": "In this manuscript, the authors conducted a CRISPR knockout screen to identify radiosensitizing targets in glioblastoma (GBM). They further investigated the molecular mechanism of one target gene, NANP. Overall, this is an interesting study; however, I have the following comments:\nMajor comments:\nThe authors used CRISPR knockout screening to identify radiosensitizing targets but validated NANP using only shRNAs. At least some key experiments should be confirmed using NANP sgRNA knockout.\nFor the in vivo radiotherapy (RT) treatment experiments, at least two different glioma stem cell (GSC) lines should be used.\nThe levels of P65 protein, its phosphorylation, and its nuclear localization should be assessed in the NANP knockdown cells.\nMinor comments:\nScale bars should be included in Figures 5A and 6G.\nThe cutoff for high versus low NANP expression should be indicated in Figures 8E and 8F.\nCan NANP be targeted by any small molecule inhibitors?"}, "author_response": "We sincerely thank all four reviewers for their careful evalua4on and construc4ve comments which we have addressed point by point as detailed below. We have also revised the manuscript to comply with editorial forma:ng requirements (e.g., abstract word count reduced to 149). All changes are yellow highlighted, and new figures are underlined when referred in rebuEal leEer. In addi4on, please note changes to figures and supplementary figures as follows:\nRenamed:\nFigure 1 -> Supplementary Figure 1\nFigure 2 -> Figure 1\nFigure 3 -> Figure 2\nFigure 4 -> Figure 3\nFigure 5 -> Figure 4\nFigure 6 -> Figure 5\nFigure 7 -> Figure 6\nFigure 8 -> Figure 7\nSupplementary Figure 1 -> Supplementary Figure 2\nSupplementary Figure 2 -> Supplementary Figure 3\nSupplementary Figure 3 -> Supplementary Figure 4\nSupplementary Figure 4 -> Supplementary Figure 5\nSupplementary Figure 5 -> Supplementary Figure 6\nSupplementary Figure 6 -> Supplementary Figure 7\nSupplementary Figure 7 -> Supplementary Figure 10\nSupplementary Figure 8 -> Supplementary Figure 11\nSupplementary Figure 9 -> Supplementary Figure 13\nSupplementary Figure 10 -> Supplementary Figure 14\nAdded:\nFigure 3: f, g and h\nFigure 4: g and h\nFigure 6: f\nFigure 7: c\nSupplementary Figure 4: b\nSupplementary Figure 5: b\nSupplementary Figure 8: a, b and c\nSupplementary Figure 9: a and b\nSupplementary Figure 12: a, b and c\nSupplementary Figure 13: c\nSupplementary Figure 15: a and b\nUpdated:\nFigure 2: d\nFigure 5: g and h\nFigure 6: e\nFigure 7: a\nAll the figures referred below in the responses are new figure names, the new data referred were underlined.\nREVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nDing et al present data supporting a model whereby NANP supports the mesenchymal phenotype of GBM cells, including a more radioresistant phenotype, and hence targeting NANP can serve to radiosensitize GBM. The CRISPR screen is well-described with clear rationale for the pipeline leading to hits to focus on with strong bioinformatic support for the ultimate focus on NANP. Overall, the data provided are supportive for the relevance of NANP to the response to radiotherapy as well as for the model proposed linking NANP to the NF-kB pathway. There are some minor concerns to be addressed to further support the impact of this work on the brain tumor field.\n1. The authors cannot claim anything regarding mitotic failure as this was not evaluated, “Together, these findings suggest that NANP silencing resulted in increased mitotic failure and subsequent apoptosis following radiation.” This conclusion should be revised to reflect what the data demonstrate.\nRESPONSE: We appreciate your sugges/on. As suggested by the reviewer, we revised the text to remove references to mito/c failure and instead conclude: \"Together, these findings suggest that NANP silencing resulted in increased G2/M cell cycle arrest and subsequent apoptosis following radia/on. \" This aligns with our observed G2/M arrest and apoptosis induc/on.\n2. The authors report decreased migration upon NANP depletion but also report an increase in G2/M arrested cells and an increase in apoptosis following NANP depletion. As arrested cells and dying cells will not migrate, how did the authors control for this when evaluating a decrease in migration? That is, is there a direct decrease in migration or just more cells dying/arrested in the cell cycle that aren’t migrating?\nRESPONSE: We appreciate your feedback. Here, we would like to clarify that: (a) decreased migra/on upon NANP deple/on was due to transcrip/onal subtype shiL, which does not result in G2/M arrest or apoptosis without radia/on; (b) G2/M arrest and apoptosis in NANP silencing cells were induced aLer radia/on. The increased G2/M arrest and apoptosis of NANP silencing cells only happened when cells were treated with radia/on. The cell migra/on was evaluated without radia/on, thus not affected by radia/on-induced arrest/apoptosis.\n3. As U87 is well known in the field to no longer represent GBM, it is unclear why these data were included and what they will contribute to the field versus the data with the GSC lines. The limitation of this model should at least be acknowledged in the Discussion.\nRESPONSE: We appreciate your feedback. We acknowledge U87’s limita/ons due to its mis-iden/fica/on. Although its pa/ent of origin is unknown, U87 is of CNS origin and is likely to be a bona fide human glioblastoma cell line based on transcrip/onal similarity analysis (PMID: 27582061). Thus, we included it to validate some of the findings in addi/on to the results obtained from GSCs. As suggested, we have highlighted the model’s u/lity while no/ng caveats in discussion (line 409).\n4. The authors should go through the work and make sure all conclusions are supported by more than one shRNA (e.g., clonogenic assay in 6G/H is only with shNANP-1).\nRESPONSE: Thank you for the sugges/on. We understand the reviewer’s concern about off-target effects of shRNA. To address this concern, we included more than one shRNA for this men/oned experiment (Fig.5 g-h in the revised manuscript). Moreover, we performed knockout and rescue experiments for key conclusions (Fig. 3 f-h; Supplementary Fig. 8 a-c; Supplementary Fig. 12 a-c).\nAdditional\n1. The intro highlights the TCGA/Verhaak subtypes but more recent single cell studies have further refined the extent of plasticity and heterogeneity and should be noted (i.e. Neftel et al., Cell, 2019).\nRESPONSE: Thank you for the sugges/on. We have now revised the intro to include the suggested statement (see line 57-58 of the revised MS).\n2. Main text states fractionated regimen was 2 Gy x 5 days but Methods states 2.5 Gy x 4 days.\nRESPONSE: Our apologies for the typo while wri/ng using an old method template. The correct regimen is 2 Gy × 5 days (total 10 Gy), which was revised (line 679).\n3. Methods only mention U87 for the clonogenic assay but this was done in the other cells as well so details should be added.\nRESPONSE: Thank you for the sugges/on. The details of clonogenic assay for GSCs were added to the methods sec/on.\nReviewer #2 (Remarks to the Author):\nDing et al present a potentially very interesting hypothesis that NANP downregulation may sensitize gliobastoma for radiation therapy. Additionally, they claim that this effect is mechanistically explained by a role of NANP in TNFR1 specific sialylation resulting in an effect on NFKB signaling.\nMany of the experiments that are shown and discussed indeed indicate a link between NANP and RT sensitization. Causality could/should be increased by studying the effect in NANP knockout GSC20 cells and its NANP corrected lines.\nMechanistically, in my view no evidence is presented for a defect in sialylation of TNFR1. The SNA agarose IP is not a quantitative test that can be used to assess percentage of sialylation of an individual protein. As alternative, IP of TNFR1 (with proof of purity) should be performed followed by western blotting with a sialic acid specific lectin (showing a decrease in staining) as well as a lectin against the underlying galactose residue (showing elevated staining). Therefore, the claim of a TNFR1 specific sialylation defect as mechanistic explanation for increased radiosensitization is in my view not supported by experimental evidence.\nRESPONSE: We sincerely appreciate the reviewer’s insigh_ul comments and valuable sugges/ons, which have significantly strengthened the rigor of our study.\nRegarding the causality of NANP in radiosensi/za/on, we agree that knockout and rescue experiments are cri/cal to validate this rela/onship. We have generated NANP knockout GSC20 cells using CRISPR-Cas9 and established NANP-corrected lines by reintroducing wild-type NANP into these knockout cells. The results show that NANP knockout recapitulates the radiosensi/za/on phenotype observed in NANP-silenced cells (Fig. 4f-g; Supplementary Fig. 8a-b, 12a), while NANP re-expression reverses this effect (Fig. 4h; Supplementary Fig.8c, 12b-c), directly confirming that NANP deficiency is causally linked to enhanced radiosensi/vity in GBM.\nTo address the mechanis/c evidence for TNFR1-specific sialyla/on defects, we have performed endogenous TNFR1 IP with strict valida/on of IP purity (Supplemental Fig. 15a) by silver staining, confirmed the specific enrichment of TNFR1. As suggested, we further analyzed these IP samples using both sialic acid-specific lec/n (SNA) and galactose residue-specific lec/n (RCA). In addi/on, the specificity of lec/n binding was validated by PNGase F diges/on. The data confirmed a decrease in SNA staining (Supplemental Fig. 15a), indica/ng reduced sialyla/on of TNFR1. However, we did not observe a concurrent increase in RCA staining of TNFR1 in NANP-silenced cells (Supplemental Fig. 15a). This may be adributed to the complex intracellular glycosyla/on modifica/on network in our experimental system. It is possible that other glycosyltransferases or deglycosylases are ac/vated when sialic acid is absent, modifying the exposed galactose residues and thus not necessarily resulted in an increase of RCA staining. Despite the lack of increased RCA staining, the decrease in SNA staining strongly supports the reduc/on in TNFR1 sialyla/on upon NANP silencing.\nMoreover, since sialyla/on regulates TNFR1 internaliza/on and downstream NF-kB signaling—a key mediator of radia/on resistance—we performed TNFR1 internaliza/on assays. The results (Fig. 6f and Supplementary Fig. 15b) show increased TNFR1 internaliza/on in NANP-silenced cells (evidenced by a leL shiL in surface TNFR1 density plots), which is associated with impaired NF-kB ac/va/on (Fig. 6a-d, 6h; Supplemental Fig. 13a, 13c). Reduced NF-κB ac/va/on weakens the cell's ability to resist radia/on-induced damage (PMID: 29232556; PMID:23993863), thereby enhancing radiosensi/vity. These findings link NANP-mediated TNFR1 sialyla/on to altered receptor trafficking, signaling, and ul/mately, radia/on response.\nTogether, these addi/onal experiments address the reviewer’s concerns and provide robust evidence for the proposed mechanism.\nMinor points:\nSummary\nNANP (N-acylneuraminate-9-phosphatase): NANP (N-acetylneuraminate 9-phosphatase) and consistent naming throughout the manuscript\nMany abbreviations, some unexplained (TNFR1), complicates readability\nRESPONSE: Thank you. We have corrected these abbrevia/ons and carefully checked other abbrevia/ons throughout the manuscript.\nIntroduction:\nDespite the potential benefits that each of these advances (has)\nTCGA: explain abbreviation\nRESPONSE: Thank you. We have amended as suggested.\nResults:\nto identify dominate resistant clones\nTo identify novel (targets?), we\na global surface sialyation change\nRESPONSE: Thank you. We have corrected all these gramma/cal errors.\nFigure 5D: why does shNANP-3 results in much higher residual NANP expression in GSC11 as compared to GSC20?\nRESPONSE: We appreciate the reviewer’s careful observa/on. We have rechecked the knockdown efficiency of all NANP-targe/ng shRNAs using both qPCR and immunoblot (Supplementary Figs. 4a-b; Supplementary Fig. 5a-b), and the results from both methods are consistent: shNANP-3 indeed results in higher residual NANP expression in GSC11 than in GSC20.\nSuch cell line-specific differences in shRNA efficiency are commonly observed in RNAi experiments, and mul/ple factors may contribute to this phenomenon. These include cell-type-specific epigene/c modifica/ons (e.g., mRNA methyla/on), cell-type-specific binding of regulatory proteins (e.g., RNA-binding proteins that can mask the shRNA target site), divergence in RNAi machinery ac/vity, and/or sequence polymorphisms in the target region.\nWhile inves/ga/ng the precise mechanism underlying this cell line-specific difference would be of interest, it lies beyond the primary focus of the current study, which centers on the func/onal role of NANP in radiosensi/za/on. However, we have confirmed that even with the higher residual NANP expression in GSC11, shNANP-3 s/ll induces the expected radiosensi/za/on phenotype in this cell line (Fig. 3b, 4d; Supplementary 5; 9b), suppor/ng the func/onal relevance of NANP knockdown in both models.\nReviewer #3 (Remarks to the Author):\nIn this manuscript, the authors identify a novel radiation sensitizing target, NANP, utilizing a genome-wide CRISPR screen. They demonstrate that silencing of NANP reduces NF-kB signaling, potentially through impaired TNFR1 sialylation, leading to a decline in mesenchymal markers. Given that mesenchymal phenotype has been associated with radioresistance, this suggests a mechanism underlying the radiosensitization seen with NANP silencing. Their results correlate well with patient tumor expression profiles and endpoints, and they validate NANP suppression mediated radiosensitization in one in vivo xenograft model. They also demonstrate effects of NANP on modulation of DNA repair, though these findings are less convincing. Overall, most of the results and methods are presented clearly and the manuscript is well-written. A novel radiation sensitizing target, if fully validated, would be highly significant given the great clinical need for addressing radioresistance in GBM. However, there are some points to be addressed as detailed below.\nMajor points:\n1. The data in Fig. 5 are not fully consistent with the authors’ conclusion that NANP silenced cells display a DSB repair defect, favoring NHEJ over HR. Specifically, Fig. 5C and 5F demonstrate increased DNA damage as measured by gamma-H2AX and alkaline comet assay at 1 and 2.5 hours. This cannot be explained by the decrease in HR observed in the reporter assay in Fig. 5H, given that HR requires 4-6+ hours to complete and almost all repair at these early timepoints is NHEJ mediated. This could be interpreted as either a decrease in NHEJ activity (inconsistent with Fig. 5I) or potentially an increase in DNA damage, which has not been ruled out. Of note, Fig. 5B shows no difference in gH2AX foci at 1 hour; however 100% of cells are positive making the cut off used incapable of detecting a difference. In addition, it is not clear why the alkaline comet assay, rather than the neutral comet assay was chosen given the focus on DSB repair.\nRESPONSE: We appreciate your astute observa/on regarding the interpreta/on of DNA damage repair phenotypes. We share your interpreta/on of the men/oned data and would like to clarify that we did not conclude a sole cause-effect rela/onship between the HR-NHEJ shiL and the DNA damage outcome. In fact, we agree with the reviewer that the damage outcome could stem from varia/ons in ini/al radia/on-induced damage levels and/or DNA repair capability.\nAs noted, the 100% posi/vity of gH2AX foci at 1 hour limits the ability to detect differences at this /me point. To address this, we performed further /me-course gH2AX immunoblot experiments in GSC20 and GSC11 (using two shRNAs per cell line) to assess damage at 1 hour, a /me point when repair is minimally complete. The results (Fig. 4g and Supplementary Fig. 9) showed increased DNA damage in NANP-silenced cells as early as 1 hour post-radia/on. In addi/on, we observed that DNA damage accumulated shortly aLer radia/on in GSCs, peaked at ~1 hour (Fig. 4g-h). Notably, NANP-silenced cells exhibited increased damage as early as 5 minutes post-radia/on (Fig. 4h), a /me that is too short to complete repairs and the ini/al damage was s/ll accumula/ng as shown by the increase level of gH2AX (Fig. 4h). Therefore, NANP silencing independently affects both the ini/al induc/on of radia/on-induced damage and repair capability, which explains the inconsistency men/oned by the reviewer (i.e., more damage despite incomplete HR)—a contradic/on that would only hold if there were a sole cause-effect rela/onship between repair ac/vity and damage outcome. We have included these new data in the revised manuscript and rephrased the relevant statements to more accurately reflect our conclusion.\nRegarding the use of the alkaline comet assay: although our focus includes DSB repair, ionizing radia/on induces both DSBs and SSBs. The alkaline comet assay was chosen to capture the full spectrum of radia/on-induced DNA breaks (both SSBs and DSBs), which is relevant to understand the overall damage burden contribu/ng to radiosensi/vity, the primary focus of the study. For DSB examina/on, gH2AX related assays were used.\n2. There is not a clear mechanistic explanation for how NANP silencing specifically effects TNFR1 (while not impacting global sialylation), making it important to validate this finding more fully. Given the extensive use of NANP silencing, a rescue experiment with NANP re-expression should be performed. Experiments investigating TNFR1 localization upon NANP suppression and determining the dependence of radiosensitization on the sialyltransferase ST6Gal-I would significantly improve the validity of the findings, again given that it is not clear mechanistically how NANP is having this specific effect.\nRESPONSE: We agree that clarifying the specific effect of NANP silencing on TNFR1 while sparing global sialya/on requires much more future inves/ga/on, which has been discussed (line 425). As suggested, we have performed a rescue experiment by NANP re-expression in NANP-silenced cells, and the results demonstrate that reintroducing NANP reverses the changes in RT sensi/vity, NF-kB signaling, mesenchymal state (Fig. 3h; Supplementary Fig. 8c; 12b-c). These data confirm that the observed effects are indeed NANP-dependent.\nRegarding TNFR1 localiza/on, mul/ple studies reported sialyla/on of TNFR1 affects its internaliza/on thus promotes NF-κB ac/va/on (PMID: 39615678; PMID: 29233887). Given that NANP affects TNFR1 sialyla/on, we performed an internaliza/on assay to inves/gate TNFR1 localiza/on upon NANP suppression. The results (Fig. 6f and Supplementary Fig. 15b) revealed increased TNFR1 internaliza/on in NANP-silenced cells, as indicated by the greater leL-shiL in density plot of surface TNFR1, measured by the surface ligand binding, upon temperature shiL to induce internaliza/on. Moreover, in the presence of TNFα, NF-kB signaling induc/on and the nuclear p65 level was adenuated in NANP deficient cells (Fig. 6g-h and Supplementary Fig.13c), indica/ng an impaired NF-κB signaling. Together, these data suggest NANP promotes TNFR1 sialya/on and thereby regulates its internaliza/on, and finally affects NF-kB ac/va/on.\nRegarding ST6Gal-I, we note that its TPM/RPKM values in GSCs are extremely low (TPM₍GSC20₎=0.071, RPKM₍GSC20₎=0.028; TPM₍GSC11₎=0.089, RPKM₍GSC11₎=0.033), well below the thresholds for ac/ve transcrip/on (TPM≥2 or RPKM≥1; PMID: 23615947, PMID: 21654674). Consistent with this, ST6Gal-I protein is undetectable in these cells (data not shown), making it unlikely to mediate NANP’s effects in GSCs. While inves/ga/ng the precise mechanism that what sialyltransferase, neuraminidase or something else mediated NANP’s specific impact on TNFR1 sialya/on would be of interest, it lies beyond the primary focus of the current study. In fact, although a series of studies has been published (PMID: 29233887; PMID: 39615678; PMID: 21930713; PMID: 29191829), the mechanism of how ST6GAL1 has specific effects on TNFR1 sialyla/on remains unclear.\nMinor points:\n1. RT doses shown in Figs. 1 and 8 are different than those described in the methods.\nRESPONSE: Our sincere apologies for the typos introduced while using old method templates. We have corrected the RT doses in the methods as shown in line 679 of the revised manuscript.\n2. In Supplemental Fig. 3 and 4, NANP protein levels via western blotting should be shown upon shRNA knockdown in GSC20 and GSC11.\nRESPONSE: Thank you. Western blotting results showing NANP protein levels upon knockdown in GSC20 and GSC11 have been included as Supplemental Figure 4b and Supplemental Figure 5b, respectively.\n3. In Fig. 5D, there is minimal NANP knockdown with shNANP3 despite similar effects on RT sensitivity (Fig. 4b). This should be addressed. As per major point 2 above, the specificity of NANP knockdown should be confirmed via rescue experiment.\nRESPONSE: The specificity of NANP knockdown has been confirmed via both knockout and rescue experiments (Fig. 3 f-h; Supplementary Fig. 8 a-c; Supplementary Fig. 12 a-c).\n4. The conclusion in lines 187-189 is confusing and doesn’t seem to agree with data in Supplemental Fig. 6.\nRESPONSE: Our apologies for the confusion caused by the inclusion of two factors (time and dosage); we have now rephrased the statement to separate the comparisons between time and dosage. Please refer to lines 189-191.\n5. In Fig. 7E, are there other sialyation target proteins that could be probed as controls to show the specificity of the decrease in TNFR1 pulldown?\nRESPONSE: Thank you for the sugges/on. We have probed another sialyla/on target protein, PDPN, as a control to show the specificity of the decrease in TNFR1 pulldown (Fig. 6e).\n6. Most of the experiments are performed in GSC20 with some reproduced in GSC11. It is noted that GSC20 resembles the mesenchymal subtype. What about GSC11? Will these results be limited to mesenchymal type tumors? Overall, the findings would benefit from reproduction in a wider array of models.\nRESPONSE: We appreciate the reviewer’s valuable sugges/on regarding the generalizability of our findings across GBM subtypes.\nGBM subtypes were determined by single-sample gene set enrichment analysis (ssGSEA) using subtype signatures derived from TCGA data and our previous studies (PMID: 20129251; PMID: 28697342). Thus, a GBM classified as one subtype means that the subtype signature expression is dominant, but can retain rela/vely lower ac/vi/es of other subtypes’ signature expression. GSC11 is classified as the classical (CL) subtype. While the CL subtype is defined by dominant enrichment of classical signatures, it may retain par/al expression of other subtype signatures due to intrinsic subtype plas/city—a phenomenon supported by studies highligh/ng the heterogeneity and dynamic transi/ons between GBM subtypes (PMID: 34087162).\nNotably, our key findings, including NANP silencing-induced radiosensi/za/on and the underlying mechanism involving TNFR1-NF-kB signaling, were consistently reproduced in GSC11 (Fig. 4d-g, 5b, 6b, 7c and Supplementary Fig. 5a-e, 9b). These results confirm that NANP targe/ng can radiosensi/ze both mesenchymal (GSC20) and classical (GSC11) subtypes.\nWe agree that expanding the models would further strengthen generalizability. However, the conserva/on of the NANP-TNFR1 axis across GSC11 (CL) and GSC20 (mesenchymal) supports that our findings are not restricted to the mesenchymal subtype. We have clarified and discussed this point in the manuscript (lines 405-409).\nReviewer #4 (Remarks to the Author):\nIn this manuscript, the authors conducted a CRISPR knockout screen to identify radiosensitizing targets in glioblastoma (GBM). They further investigated the molecular mechanism of one target gene, NANP. Overall, this is an interesting study; however, I have the following comments:\nMajor comments:\nThe authors used CRISPR knockout screening to identify radiosensitizing targets but validated NANP using only shRNAs. At least some key experiments should be confirmed using NANP sgRNA knockout.\nFor the in vivo radiotherapy (RT) treatment experiments, at least two different glioma stem cell (GSC) lines should be used.\nThe levels of P65 protein, its phosphorylation, and its nuclear localization should be assessed in the NANP knockdown cells.\nRESPONSE: Thank you for sugges/ng areas to strengthen our manuscript. Suggested experiments to address your concerns were performed as described below.\n1. Some key experiments were validated using NANP sgRNA knockout (Fig. 3f-g; Supplementary Fig. 8a-b, 12a). Moreover, rescue experiments (Fig. 3h; Supplementary Fig. 8c, 12b-c) was additionally carried out to confirm the findings.\n2. We have performed in vivo RT treatment experiments using an additional GSC, the results were included as Fig. 7c.\n3. The levels of P65 protein and its phosphoryla/on in the NANP knockdown cells was shown in Supplementary Fig. 13a, and validated in Supplementary Figure 12c. P65 nuclear localiza/on results has been included as Supplementary Fig. 13c.\nMinor comments:\nScale bars should be included in Figures 5A and 6G.\nThe cutoff for high versus low NANP expression should be indicated in Figures 8E and 8F.\nCan NANP be targeted by any small molecule inhibitors?\nRESPONSE: Scale bars have been added to the revised figures. The cutoff for high versus low NANP expression was its median expression, which has been described in the figure legend of the revised manuscript. A NANP inhibitor was published by a group from Bristol-Myers Squibb (BMS) in 2013 (PMID: 23747226); however, this compound is not commercially available nor available from BMS."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have adequately addressed all prior concerns from this reviewer.", "reviewer_2": "The authors have expanded the number of experiments to confirm and respond to the questions of the reviewers, which is highly appreciated. Knockout of NANP in the GSC20 cell line was performed and 2 clones were selected (1 and 5) with clear NANP protein decrease on western blot (supplemental Figure 8a). Experimental details are very limited on their generation. Clone 1 was used to confirm the effect on RT, while the rescue by wildtype transfection was done again on the shRNA line. It is unclear why clone 5 was shown but not tested for effect on RT and why the wildtype rescue was not performed on the knockout clones (as a more convincing model).\nThe causal link of the claimed effect of TNFR1 specific desiaylation on RT has been addressed by an IP of TNFR1, followed by SNA lectin staining and the results section has been adapted on page 8. In panel 1 of supplemental Figure 15a, I don’t see convincing evidence of a single band that was stained with SNA in lanes 3-4, or even a band with lower intensity in the shN1 lane (4) as compared to the shC lane (3). For RCA (second panel) , 2 bands are specifically stained that disappear after PNGaseF, which is as expected. This may indicate that a significant portion of TNFR1 is already desialylated in normal conditions, but at least should increase in intenstity upon NANP knock-down. What is worrying is that the band of IB TNFR1 (panel 3) shows increased migration in the gel (lower MW) upon PNGaseF treatment (lanes 3-4 versus lanes 5-6; as expected because entire N-glycans are removed), but the silver stained bands (panel 4) in lanes 3-6 move at exactly the same height, suggesting the same MW. In my view, you would also expect a lower MW in the silver stained bands upon PNGaseF treatment. Another question is why these experiments were done in the shRNA model, which is more complicated than the now available KO model.\nAll in all, the added data (especially knockouts) increase evidence of the effect of NANP on RT, but in my view these data are not convincing to support a role of NANP in TNFR1-specific siaylation and this claim should in my view be omitted from title and paper. Possibly, NANP has additional functions or otherwise results in the clear effect of NANP on RT, which may be discussed.", "reviewer_3": "The authors have addressed the comments thoroughly, and overall the additional data supports their conclusions. There is one minor concern with the new data shown in Supplementary Fig. 12b, as two of the three MES/NF-kB genes show minimal restoration of expression with NANP rescue. Analyzing a larger panel of genes (such as that done initially in Fig. 5f and 6g) would better indicate whether NANP rescue restores this expression phenotype as the authors conclude. There also seem to be some incorrect figure references in lines 215-226.", "reviewer_4": "The authors have addressed all my concern!"}, "author_response": "POINT-BY-POINT RESPONSE\nWe sincerely thank all reviewers for their careful evaluation, and please see our responses below.\nREVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nThe authors have adequately addressed all prior concerns from this reviewer.\nRESPONSE: Thank you for helping us to improve our manuscript.\nReviewer #2 (Remarks to the Author):\nThe authors have expanded the number of experiments to confirm and respond to the questions of the reviewers, which is highly appreciated. Knockout of NANP in the GSC20 cell line was performed and 2 clones were selected (1 and 5) with clear NANP protein decrease on western blot (supplemental Figure 8a). Experimental details are very limited on their generation. Clone 1 was used to confirm the effect on RT, while the rescue by wildtype transfection was done again on the shRNA line. It is unclear why clone 5 was shown but not tested for effect on RT and why the wildtype rescue was not performed on the knockout clones (as a more convincing model).\nThe causal link of the claimed effect of TNFR1 specific desiaylation on RT has been addressed by an IP of TNFR1, followed by SNA lectin staining and the results section has been adapted on page 8. In panel 1 of supplemental Figure 15a, I don’t see convincing evidence of a single band that was stained with SNA in lanes 3-4, or even a band with lower intensity in the shN1 lane (4) as compared to the shC lane (3). For RCA (second panel), 2 bands are specifically stained that disappear after PNGaseF, which is as expected. This may indicate that a significant portion of TNFR1 is already desialylated in normal conditions, but at least should increase in intenstity upon NANP knock-down. What is worrying is that the band of IB TNFR1 (panel 3) shows increased migration in the gel (lower MW) upon PNGaseF treatment (lanes 3-4 versus lanes 5-6; as expected because entire N-glycans are removed), but the silver stained bands (panel 4) in lanes 3-6 move at exactly the same height, suggesting the same MW. In my view, you would also expect a lower MW in the silver stained bands upon PNGaseF treatment. Another question is why these experiments were done in the shRNA model, which is more complicated than the now available KO model.\nAll in all, the added data (especially knockouts) increase evidence of the effect of NANP on RT, but in my view these data are not convincing to support a role of NANP in TNFR1-specific siaylation and this claim should in my view be omitted from title and paper. Possibly, NANP has additional functions or otherwise results in the clear effect of NANP on RT, which may be discussed.\nRESPONSE: We sincerely appreciate your valuable feedback, which has helped us strengthen the rigor of our study. Below are our responses addressing your concerns, with a focus on key evidence and scientific rationale:\n(1) Regarding the knockout clones:\nThe detailed protocol for generating NANP knockout clones has been added to the revised manuscript (Lines 461–467). Similar to Clone 1, Clone 5 was also used to confirm NANP’s effect on radiosensitivity via clonogenic assays (in original Figure 3f) and new added cell cycle analyses (Supplementary Figure S8).\nThe decision to perform rescue experiments in knockdown cells rather than knockout clones was based on two considerations. First, CRISPR-mediated gene knockout relies on frameshift mutations introduced through non-homologous end joining (NHEJ)-mediated repair of DNA double-strand breaks. Consequently, only a subset of cells in a population will harbor such mutations, making single-cell clone isolation a necessary and standard practice (Nature Protocol, PMID: 35197604; STAR Protocol, PMID: 38972040). In our experiments, five independent single clones were selected, but only two (Clones 1 and 5) showed complete NANP knockout as validated by western blot. Given the inherent heterogeneity of tumors and the prolonged culture period (approximately four months from single cell isolation to clonal expansion), clonal variability in the generated knockout lines is unavoidable. Rescue experiments in individual clones might therefore be inherently biased toward the specific genetic background of each clone, limiting generalizability. In contrast, single-clone selection and expansion is not necessary for gene knockdown using shRNA, which avoids clone-specific variability. Second, as detailed in the Methods section, establishing knockout clones is extremely time-intensive, particularly for patient-derived glioblastoma spheroid cells. Generating these clones required almost half year (encompassing sgRNA construction, viral transduction, blasticidin selection, knock out validation at bulk cell level, single-clone isolation, clone expansion, and western blot validation for each clonal line). To avoid delaying the revision, we performed parallel rescue experiments in knockdown cells instead of waiting for knockout clone-based rescues.\nWe fully acknowledge the importance of excluding off-target effects, as emphasized by all the four reviewers. Our findings originated from a CRISPR knockout screen with four different sgRNAs and have been validated using 4 distinct shRNAs in some experiments and 2 shRNAs in numerous others across GSCs and cell lines. In previous revision, we have added further validation using an sgRNA distinct from those in the original CRISPR library, alongside rescue experiments. These data, we believe, adequately address concerns about off-target effects—an assessment supported by the other three reviewers who initially raised this issue.\n(2) Regarding TNFR1 bands migration upon PNGase F treatment (supplemental Figure 15a):\nWe agree with the reviewer that the TNFR1 bands should expect a lower MW upon PNGaseF treatment, which was exactly the case in our data. As shown in Figure A below (bottom panels with alignment lines added for clarity), the bands in lanes 5–6 are clearly lower than those in lanes 3–4. As a control, the light chain bands in the same experiment align perfectly. We have marked this band shift with an asterisk (*) in previous revision. To show this more clearly, we have now replaced this data with a stronger exposed version (Figure A left panel) as new supplemental Figure 15a. The reason that the migration difference of proteins appears more pronounced in the western blot than in the silver staining was that different gel gradients were used. For Western blot (WB) analysis, proteins were resolved on 4–15% gradient gels to optimize the resolution of the target band (25-75 kDa). For silver staining, broader gradient (4–20%) gel was used to separate a wider range of proteins for evaluating the purity and success of immunoprecipitation. In Summary, treatment with PNGase F resulted in increased migration (i.e., a lower apparent molecular weight) of the TNFR band in both images, consistent with the expected reduction in molecular weight following deglycosylation.\nFigure A Supplemental Figure 15a of our previous revision with dashed lines to clarify the points raised by Reviewer 2. * Indicates the molecular weight for TNFR1 with or without PNGase F digestion.\n(3) Regarding TNFR1 sialylation (supplemental Figure 15a):\nThank you for your thoughtful suggestion to perform target protein immunoprecipitation (IP) followed by SNA blotting as a complementary approach to validate TNFR1 glycosylation. We fully appreciate the intent to strengthen our analysis and agree that multiple orthogonal methods add rigor to glycosylation studies, however, this is technically challenging. Nevertheless, we tried our best to obtain results by this workflow by testing four distinct SNA reagents from two suppliers (Figures B). Two reagents—SNA-Fluorescein (Vector Laboratories, Cat: FL-1301-2) and SNA-Biotin (Vector Laboratories, Cat: B-1305-2)—failed to detect specific bands (Figure B panels I–III). In contrast, the other two lectins—SNA-FITC (Thermo Fisher Scientific, Cat: L32479, Figure A) and SNA-Cy5 (Vector Laboratories, Cat: CL-1305-1, Figure B panel IV)—successfully detected glycosylated TNFR1 at the same molecular weight identified by the TNFR1 antibody. Both positive reagents showed reduced signals in NANP knockdown samples, supporting our conclusion. Although the signal intensity is weak, a single band stained with SNA is visible in lane 3, with an even fainter band in lane 4 (marked with an asterisk in the previous figure and boxed here for emphasis). As expected, these bands were absent following PNGase F digestion —confirming their glycosylation dependence. To show this more clearly, we have now replaced the figure with a stronger exposed version (Figure A left panel, new Supplemental Figure 15a). In the original supplemental Figure 15a, we presented SNA-FITC (Thermo Fisher Scientific, Cat: L32479) because, despite weaker TNFR1 bands, this reagent produced fewer non-specific signals; a stronger exposure (with enhanced contrast) is shown here (Figure A). SNA-Cy5 (Vector Laboratories, Cat: CL-1305-1) yielded stronger specific bands (Figure B panel IV, top panel); these bands (unlike non-specific bands at ~37 kDa or ~75 kDa) were eliminated by PNGase treatment, further confirming that the bands at the TNFR1 molecular weight represent immunoprecipitated glycosylated TNFR1. We have now also included SNA-Cy5 data in the revised manuscript (Supplementary Figure S15b). Given the technical difficulty of SNA blotting, many recent high-impact studies in glycosylation research only present results from SNA pull-down followed by target protein blotting, rather than target protein immunoprecipitation followed by SNA blotting (Cancer Discovery PMIDs: 37272843 [Figure 5C]; Gastroenterology 33022277 [Figure 1E]; JCI Insight 36345944 [Figure 4G]; J Biol Chem 39615678 [Figure 7E]). Through extensive efforts, we have demonstrated TNFR1 sialylation regulation using both approaches, supplemented with TNFR1 endocytosis data as indirect evidence of sialylation-dependent outcomes. We believe our data provided sufficient evidence of sialylation regulation that meets, if not exceeds, the standards of current studies in this field.\nSNA-Cy5\n(VectorLab, Cat: B-1305-1)\nI II III IV\nInput IP:TNFR1\nPNGaseF - - - - + +\nSNA-biotin SNA-biotin SNA-Fluorescein sh\nC shN\nsh\nC shN\nsh\nC\nsh\nN\n(VectorLab, Cat: B-1305-2) (VectorLab, Cat: B-1305-2) (VectorLab, Cat: FL-1301-2) 250KD-\nMs In h C p s u h t N Msh C IP sh N Ms In h C p s u h N t sh C I s P h N sh C I s P h N -s M Ms In h C p s u h N t sh C I s P h N sh C I s P h N -s M 1 1 7 5 5 0 5 0 0 0 K K K K D D D D - - - - * * B S l N o A t: -Cy5\n250KD- 250KD- 250KD- 37KD-\n1 1 7 5 0 5 0 0 K K K D D D - - - 1 1 7 5 0 5 0 0 K K K D D D - - - 1 1 7 5 0 5 0 0 K K K D D D - - - 2 2 5 0 K K D D - -\n50KD- 50KD- 50KD-\n3 2 7 5 K K D D - - 3 2 7 5 K K D D - - 3 2 7 5 K K D D - - 2 1 1 5 5 0 0 0 0 K K K D D D - - - B R l C o A t: -I-Rhodamine\n75KD-\n1#: SNA-Biotin,1:1000 1#: SNA-Biotin,1:100 SNA-Fluorescein,1:200 50KD- * *\n2#:Strep,1:5000 2#:Strep,1:2000 37KD-\n25KD-\n50KD- *\n*\n37KD-\nBlot:TNFR1\n25KD-\nFigure B TNFR1 sialyation analysis through TNFR1 immunoprecipitation (IP) followed by SNA blotting. (I-\nIII) SNA blotting results of TNFR1 IP with two reagents that did not detect specific bands in IP samples. M\nstands for marker, IP-s stands for IP supernatant. (IV) SNA blotting with SNA-Cy5. * Indicates the\nmolecular weight for TNFR1 with or without PNGase F digestion.\nThank you for acknowledging that our RCA blotting results showed the expected bands. RCA\nstaining did not increase following NANP knock down. As explained in our point-by-point response, the\nintracellular glycosylation network is complex and incompletely understood. It is plausible that other\nglycosyltransferases or deglycosylases are activated when sialic acid is depleted, modifying exposed\ngalactose residues and thus preventing a predictable increase in RCA staining. Notably, none of the\naforementioned SNA-focused studies (PMIDs: 37272843; 33022277; 36345944; 39615678) nor more\nrecent studies (J Clin Invest, PMID: 40371640; Nat Cell Biol, PMID: 39984654) demonstrated reciprocal\nregulation of SNA and RCA signals. We maintain that the data should be interpreted as observed (per\nyour confirmation of RCA band identity).\nCollectively, we have demonstrated that TNFR1 sialylation is decreased using both SNA pull-down\nand TNFR1 IP approaches, with PNGase F digestion to confirm specificity and silver staining to verify IP\npurity. Our results are consistent across two independent SNA reagents (SNA-FITC, Thermo Fisher; SNA-\nCy5, Vector Labs) from different suppliers, ensuring reproducibility. Moreover, NANP’s effect on TNFR1\nsialylation—and the consequent impact on TNFR1 function—was further confirmed by the internalization\nassay shown in Figure 6f. We believe our data—with its rigorous validation, cross-reagent consistency,\nand clarity—provides sufficient, field-standard evidence for NANP-dependent TNFR1 sialylation, and we\ntherefore retain this claim in the title and manuscript.\nReviewer #3 (Remarks to the Author):\nThe authors have addressed the comments thoroughly, and overall, the additional\ndata supports their conclusions. There is one minor concern with the new data shown in\nSupplementary Fig. 12b, as two of the three MES/NF-kB genes show minimal restoration of\nexpression with NANP rescue. Analyzing a larger panel of genes (such as that done initially\nin Fig. 5f and 6g) would better indicate whether NANP rescue restores this expression\nphenotype as the authors conclude. There also seem to be some incorrect figure references\nin lines 215-226.\nRESPONSE: Thank you for your recognition of our improvement. Per your suggestion, we have analyzed a\nlarger panel of genes for NANP rescue experiments and the new added data is in new Supplementary Fig.\n12b. There were no incorrect figure references in lines 215-216, we referenced this panel twice to describe\nresults at two different time points (1 and 24 hours, respectively).\nReviewer #4 (Remarks to the Author):\nThe authors have addressed all my concern!\nRESPONSE: Thank you for helping us to improve our manuscript."}, {"round": 3, "reviewer_comments": {"reviewer_2": "I would like to thank the authors for clarifying the use of different gradient gels to explain the difference in PNGaseF treated mobility of TNFR1. The use of the additional SNA-Cy5 reagent produces much cleared bands with convincing bands of IP TNFR1 stained with SNA-Cy5. This indicates that TNFR1 is partly sialylated in this model in the control situation.\nIf I am correct, lanes 3-4 should show a lower intensity SNA staining for the shN versus shC in Figure S15b. This may seem the case. In combination with the lower capturing (IP) of TNFR1 after SNA staining, I feel that the combined results at least suggest a slight reduction in sialylation of TNFR1 and can agree with the conclusions drawn in the paper."}, "author_response": "POINT-BY-POINT RESPONSE\nREVIEWERS' COMMENTS\nReviewer #2 (Remarks to the Author):\nI would like to thank the authors for clarifying the use of different gradient gels to explain the difference in PNGaseF treated mobility of TNFR1. The use of the additional SNA-Cy5 reagent produces much cleared bands with convincing bands of IP TNFR1 stained with SNA-Cy5. This indicates that TNFR1 is partly sialylated in this model in the control situation.\nIf I am correct, lanes 3-4 should show a lower intensity SNA staining for the shN versus shC in Figure S15b. This may seem the case. In combination with the lower capturing (IP) of TNFR1 after SNA staining, I feel that the combined results at least suggest a slight reduction in sialylation of TNFR1 and can agree with the conclusions drawn in the paper.\nRESPONSE: Thank you for your careful evaluation and constructive feedback, which are very helpful for improving our manuscript. We are grateful for your positive recognition of our TNFR1 sialylation analysis and its agreement with our conclusions."}]

Decision letter