SNORA49 negatively regulates self-renewal of liver cancer stem cells and hepatocarcinogenesis via suppressing SOX9 transcription

Domain: biology
Published: 2026-01-21
Editorial outcome: minor_revision

Abstract
Cancer stem cells (CSCs) play a critical role in tumor initiation, progression, and recurrence. How liver CSCs initiate their self-renewal remains elusive. Here we identify a conserved small nucleolar RNA (snoRNA), SNORA49, which is lowly expressed in liver CSCs, as a negative regulator of CSC self-renewal. SNORA49 knockout enhances the self-renewal capacity of liver CSCs and accelerates hepatocellular carcinoma (HCC) tumorigenesis, whereas overexpression of SNORA49 suppresses tumor formation. Mechanistically, in non-CSCs, SNORA49 is specifically localized in the nucleoplasm to associate with HNRNPU, blocking its interaction with ZC3H18, resulting in inhibition of SOX9 transcription. In liver CSCs, lowly expressed SNORA49 releases HNRNPU to engage with ZC3H18 and enrich on the promoter of SOX9, leading to its transcription. Of note, lipid nanoparticle (LNP)-mediated delivery of SNORA49 RNAs and antisense oligonucleotides (ASOs) targeting SOX9 exert potent synergistic anti-tumor effect on HCC tumors. Our findings define SNORA49 as a tumor suppressor in liver CSCs, and restoring SNORA49 levels and silencing SOX9 with LNP-delivered system may provide therapeutic strategy for clinical intervention to HCC patients.

Introduction
Hepatocellular carcinoma (HCC) is the sixth most common and third most deadly cancer worldwide1. Although various clinical treatments are available for HCC, including surgical resection, radiotherapy, chemotherapy, and target therapy, their overall efficacy remains limited2. The major challenge lies in the heterogeneity and high recurrence of HCC. Cancer stem cells (CSCs), a subpopulation of tumor cells that possess the ability to self-renew and differentiate, have been considered as the root cause of tumor initiation, progression, and metastasis, leading to drug resistance, treatment failure, and tumor recurrence2. Over the past two decades, extensive research has been dedicated to identifying and characterizing liver CSCs using surface markers such as CD133, CD13, CD47, EpCAM, and Lgr53–5. Based on these findings, specific therapies targeting liver CSCs have shown significant potential in animal models and preclinical trials, with even greater efficacy when combined with chemotherapy and immunotherapy. For instance, blocking CD47 with an anti-CD47 antibody sensitizes HCC cells to sorafenib, promoting cell phagocytosis and inhibiting tumor progression6. In addition, treatment with ANXA3-neutralizing antibodies reduces the expression of CD133, CD24, and EpCAM in liver CSCs, enhancing the effectiveness of sorafenib and regorafenib in HCC7,8. These studies suggested that therapeutic strategies targeting and eliminating CSCs hold great promise for the future of cancer treatment. However, to find effective biomarkers, develop more effective CSC-based therapies, and understand the biological characteristics of CSCs are urgently needed.

Similar to embryonic stem cells, CSCs rely on various stemness signaling pathways and stemness factors to maintain their self-renewal capacity9. Among these factors, the Sex determining region Y-box 9 (SOX9) plays a critical role in carcinogenesis of various malignancies, including HCC, breast cancer, gastric cancer, and lung cancer10,11. For example, in breast cancer, expression of SOX9 endows tumor cells with stem cell-like properties and enhances their tumor-initiating and metastasis-seeding abilities12. In gastric cancer, elevated SOX9 levels induce intestinal metaplasia, a pre-malignant stage in gastric carcinogenesis13, or increase β-catenin levels to accelerate tumor cell proliferation14. In HCC, SOX9 promotes the expansion of liver CSCs via tilting asymmetric division towards symmetric division by inhibiting the Notch antagonist Numb15. In addition, SOX9 functions downstream of YAP and exerts a decisive influence on HCC tumor plasticity in the context of YAP activation16. These findings indicate that SOX9 plays a pivotal role in maintaining liver CSC self-renewal, which may interact with other stemness-related pathways, such as Notch and Hippo signaling, to exert its functions. Nevertheless, the precise mechanism that regulates SOX9 expression in liver CSCs still remains elusive.

Small nucleolar RNAs (snoRNAs) are a type of non-coding RNAs with a length of 60-300 nt, which are originally discovered in the nucleolus17. They are categorized into two major classes: H/ACA box snoRNAs (snoRA) and C/D box snoRNAs (snoRD). Canonically, snoRNAs are known to guide 2’-O-methylation or pseudouridylation of ribosomal RNAs (rRNAs) through complementary base pairing. Confined by their nucleolus-only localization and limited functions, snoRNAs have not initially attracted much attention in cancer research. However, with the advent of whole-genome deep sequencing technologies, emerging studies have identified a variety of novel snoRNAs that are widely expressed in different cancer types. They have localizations beyond the nucleolus and functions beyond rRNA modifications. For example, SNORD50A and SNORD50B are specifically localized in the cytoplasm, the loss of which results in hyperactivation of Ras-ERK signaling in melanoma, ovarian cancer, and lung cancer18. In addition, SNORD27 binds to E2F7 pre-mRNAs in the nucleus, regulating the alternative splicing of E2F7, a transcriptional repressor of cell-cycle-regulated genes, which is often dysregulated in many malignancies19. In HCC, upregulation of SNORD17 promotes cell growth and tumorigenesis by inhibiting p53-mediated cell cycle arrest and apoptosis20. We recently showed that SNORD88B is highly expressed in liver CSCs. Elevated SNORD88B anchors WRN in the nucleolus to inhibit STK4 transcription via recruitment of XRCC5, leading to enhancement of self-renewal of liver CSCs21. These studies indicate that snoRNAs play a critical role in the regulation of tumor initiation and progression. However, the function and mechanisms of snoRNAs in liver CSCs still remain poorly understood. In this study, we identify a conserved snoRNA SNORA49 (originated from EP400 gene transcripts, NCBI ID: 677829) that is lowly expressed in liver CSCs and negatively regulates their self-renewal capacity. Downregulation of SNORA49 promotes enrichment of HNRNPU with ZC3H18 on SOX9 promoter to initiate SOX9 transcription, which induces the self-renewal of liver CSCs and HCC tumorigenesis. Of note, LNP-mediated delivery of SNORA49 RNAs with SOX9 ASOs exerts a potent synergistic anti-tumor effect on HCC tumors.

Results
SNORA49 is lowly expressed in liver CSCs
To explore the role of snoRNAs in liver CSCs, we sorted liver CSCs (CD13+CD133+) and non-CSCs (CD13−CD133−) from human primary HCC tumor tissues by fluorescence-activated cell sorting (FACS) as previously described22 and performed snoRNA transcriptome sequencing (Fig. 1A). We validated the top five downregulated snoRNAs in CSCs using qRT-PCR (Supplementary Fig. S1A). To determine their functions, we depleted these snoRNAs in primary HCC cells using short hairpin RNAs (shRNAs) (Supplementary Fig. S1B) and conducted sphere formation assays to evaluate the self-renewal capacity of tumor cells. Among the five snoRNAs, knockdown of SNORA49 most significantly enhanced sphere formation ability (Fig. 1B). Therefore, we selected SNORA49 to examine its function in the regulation of liver CSCs.

SNORA49 is located in the intronic region of its host gene EP400, between exons 28 and 29, with a length of 137 nt (Fig. 1C). qRT-PCR and Northern blotting revealed that SNORA49 expression was dramatically lower in HCC tumor tissues compared with peri-tumor tissues (Fig. 1D), lower in CSCs compared with non-CSCs (Fig. 1E), and lower in spheres compared with non-spheres (Supplementary Fig. S1C). When normalized to peri-tumor expression, there was also a stepwise decline from peri-tumor tissues to non-CSC tumors and further to liver CSCs (Supplementary Fig. S1D). Moreover, lower expression of SNORA49 in patient tumor tissues was further confirmed via fluorescence in situ hybridization (FISH) (Supplementary Fig. S1E). While SNORA49 was downregulated in liver CSCs compared with non-CSCs, the expression levels of its host gene EP400 remained unchanged (Supplementary Fig. S1F), suggesting that the downregulation of SNORA49 in liver CSCs was independent of its host gene.

Next, we investigated the subcellular localization of SNORA49 in liver CSCs by fractionation and qRT-PCR. We found that SNORA49 was primarily localized in the nucleoplasm, with a small amount in the cytoplasm and nucleolus (Fig. 1F). Consistently, RNA FISH also showed a nucleoplasm-specific localization of SNORA49 in both liver CSCs and non-CSCs (Fig. 1G). We also quantified copy numbers of SNORA49 in liver CSCs and non-CSCs using absolute quantification assays. We validated that SNORA49 was much lower in liver CSCs compared to non-CSCs (Supplementary Fig. S1G). Of note, Kaplan–Meier survival analysis of liver cancer patients, based on data from The Cancer Genome Atlas (TCGA), indicated that higher levels of SNORA49 were associated with better patient prognosis (Fig. 1H), suggesting that SNORA49 may serve as a tumor suppressor gene in HCC. Taken together, SNORA49 is lowly expressed in liver CSCs and correlated with improved survival of HCC patients.

SNORA49 depletion enhances self-renewal capacity of liver CSCs and promotes HCC progression
To explore the function of SNORA49 in liver CSCs, we constructed SNORA49-depleted Huh7 and primary HCC cells via lentivirus-mediated short hairpin RNA interference. Efficient depletion of SNORA49 was confirmed by qRT-PCR (Supplementary Fig. S2A) and Northern blotting (Supplementary Fig. S2B), without affecting the expression of its host gene EP400 (Supplementary Fig. S2C). After SNORA49 depletion, sphere formation of liver CSCs sorted from both Huh7 and primary HCC cells was dramatically enhanced, which could be inhibited by overexpression of SNORA49 (Fig. 2A). Serial passaging assays also demonstrated similar results (Fig. 2B), suggesting that SNORA49 depletion enhanced the self-renewal capacity of liver CSCs. Consistently, we observed an increased proportion of CSCs (CD13+CD133+) in SNORA49-depleted cells (Supplementary Fig. S2D). Furthermore, SNORA49 knockdown enhanced the proliferation capacity of tumor cells by colony formation and cell counting kit-8 (CCK-8) assays (Supplementary Fig. S2E, F). These results indicate that SNORA49 negatively regulates the stemness of CSCs in vitro.

To assess whether SNORA49 exert inhibitory effects on liver CSCs in vivo, we performed a limiting dilution assay, a well-established approach to evaluate the stemness of tumor cells in vivo. We subcutaneously injected gradient numbers of SNORA49-depleted or control cells into BALB/c nude mice and observed that SNORA49 knockdown remarkably increased tumor incidence (Fig. 2C and Supplementary Fig. S2G). In addition, we subcutaneously injected SNORA49-depleted cells into BALB/c nude mice and monitored tumor growth for approximately one month. We observed that SNORA49-depleted tumors grew much larger than those of control cells (Fig. 2D). Moreover, SNORA49 knockdown significantly increased ratios of liver CSCs (CD13+CD133+) in subcutaneously formed tumors (Supplementary Fig. S2H). To further confirm the impact of SNORA49 depletion on tumor growth, we generated luciferase-labeled SNORA49-depleted cells and injected them into the livers of BALB/c nude mice for in situ tumor monitoring. Bioluminescence imaging revealed that SNORA49 knockdown remarkably promoted orthotopic tumor growth (Fig. 2E). Collectively, SNORA49 inhibits the stemness of human liver CSCs and suppresses HCC tumor growth.

Although we validated the role of SNORA49 in liver CSCs via both in vitro and in vivo assays, these models could not fully recapitulate the complexities of HCC tumorigenesis in vivo. To address this limitation, we generated Snora49 knockout (KO) mice using CRISPR/Cas9 technology (Supplementary Fig. S2I) and subjected them to HCC induction via hydrodynamic tail vein injection (HTVI), a widely used model that closely mimics human HCC tumorigenesis23–26. In brief, a saline solution containing Sleeping Beauty transposon plasmids (HrasG12V plus shp53) in a volume of 10% of the mouse body weight was rapidly injected into the tail vein. Huge hydrodynamic pressure could force fluid into livers, cause liver expansion, and push plasmid DNAs into hepatocytes, inducing tumor formation. Given that SNORA49 was highly conserved between mouse and human, sharing similar length, intact snoRNA motifs, and a comparable genomic localization (Supplementary Fig. S2J), mouse models provide more pathogenic rationale for liver tumorigenesis. We confirmed the genotype of Snora49 KO mice by PCR (Supplementary Fig. S2K) and verified the complete absence of Snora49 in mouse hepatocytes by Northern blotting (Supplementary Fig. S2L), without effect on the expression of its host gene Ep400, at both RNA and protein levels (Supplementary Fig. S2M, N). Following tail vein injection, we euthanized mice at two time points (3 weeks and 4 weeks) to examine the role of Snora49 in both HCC initiation and progression. We noticed that Snora49 knockout mice exhibited an increased incidence of liver tumors and accelerated tumor growth compared with their wild-type (WT) littermates (Fig. 2F, G). These mice developed more and larger tumor lesions and displayed higher liver-to-body weight ratios, indicating a higher tumor burden (Fig. 2H, I). Taken together, SNORA49 plays a tumor-suppressive role in both HCC initiation and progression.

SNORA49 overexpression impairs stemness of CSCs and suppresses tumor formation in mouse models
We next wanted to examine whether the self-renewal capacity of liver CSCs could be suppressed by upregulating SNORA49 expression. We overexpressed SNORA49 in Huh7 and primary HCC cells using a lentivirus-mediated approach, which was confirmed by qRT-PCR and Northern blotting (Supplementary Fig. S3A). We found that overexpression of SNORA49 remarkably reduced sphere formation (Fig. 3A, B), CSC proportion (Supplementary Fig. S3B), and cell proliferation (Fig. 3C and Supplementary Fig. S3C). Furthermore, SNORA49 overexpression obviously inhibited tumor formation in limiting dilution assays (Fig. 3D and Supplementary Fig. S3D) and inhibited tumor growth both subcutaneously (Fig. 3E) and orthotopically (Fig. 3F and Supplementary Fig. S3E).

To achieve liver-specific overexpression of Snora49 in vivo, we cloned full-length sequences of mouse Snora49 into an adeno-associated virus (AAV) plasmid and used a liver-specific TBG promoter to drive its expression (Fig. 3G). Packaged AAV was then injected into the tail veins of mice, and AAV-mediated overexpression of Snora49 in mouse hepatocytes was confirmed (Supplementary Fig. S3F). Two weeks later, when AAV-mediated Snora49 expression peaked, HCC tumors were induced in these mice using HTVI (Fig. 3G). As expected, overexpression of Snora49 dramatically suppressed tumor induction in these mice (Fig. 3H, I), with fewer and smaller tumor lesions and lower liver-to-body weight ratios compared to those of controls (Fig. 3J, K). Collectively, overexpression of SNORA49 effectively impairs the self-renewal capacity of liver CSCs and inhibits tumorigenesis.

SNORA49 binds to HNRNPU protein to abrogate its interaction with ZC3H18
We then sought to explore the mechanism by which SNORA49 regulated the self-renewal of liver CSCs. Canonically, snoRNAs containing H/ACA boxes mediate the pseudouridylation of target rRNAs via complementary base pairing in the nucleolus17. However, to date, there has been no validated rRNA site targeted by SNORA49, which was consistent with our observations that SNORA49 was localized in the nucleoplasm (Fig. 1G) rather than the nucleolus, where snoRNAs usually bind to rRNAs for modification. This led us to determine its non-canonical functions in the regulation of liver CSCs.

Recent studies have shown that snoRNAs exert non-canonical functions through interactions with various proteins18,20,21. We next performed RNA pulldown assays to identify potential binding proteins of SNORA49 in liver CSCs using biotin-labeled full-length SNORA49 probes (Fig. 4A). After silver staining and mass spectrometry (MS) analysis, we identified an RNA-binding protein, heterogeneous nuclear ribonucleoprotein U (HNRNPU) (Supplementary Fig. S4A) and confirmed their interaction by immunoblotting (Fig. 4B). To further assess whether the binding of SNORA49 and HNRNPU was specific, we conducted an RNA immunoprecipitation assay using a polyclonal HNRNPU antibody in sphere lysates from Huh7 and primary HCC cells. We found that HNRNPU specifically bound to SNORA49 but not to other snoRNAs, such as SNORD17 or SNORA74A (Fig. 4C). After incubating purified human HNRNPU protein with biotin-labeled SNORA49 probes, we observed a shift band in the migration pattern of SNORA49 on gel, indicating an interaction between HNRNPU and SNORA49 (Fig. 4D). Addition of unlabeled probes could compete with the labeled SNORA49 probes for binding to HNRNPU. However, neither SNORA74A or scramble probes with the same size and GC content as SNORA49 could compete with SNORA49 for HNRNPU binding (Supplementary Fig. S4B), further supporting the specificity of SNORA49-HNRNPU interaction. Consistently, both SNORA49 and HNRNPU exhibited nucleoplasm-specific localization by immunofluorescence staining (Fig. 4E). To test which part of SNORA49 interacted with HNRNPU, we performed a truncated RNA probe mapping assay. We found that the 31-60 nt region of SNORA49 was required for the interaction (Fig. 4F). We also generated Flag-tagged HNRNPU constructs lacking specific domains and subjected them to RNA pulldown by SNORA49. Deletion of the SPRY domain abolished the binding between HNRNPU and SNORA49 (Fig. 4G). Of note, the RGG motifs in the C terminal region of HNRNPU, previously shown to be responsible for RNA binding27, were not required for SNORA49 binding.

Next, we sought to determine how SNORA49 exerted its functions through its association with the HNRNPU protein. First, we ruled out the possibility that SNORA49 affects the expression of HNRNPU, as its depletion did not alter the RNA or protein levels of HNRNPU (Supplementary Fig. S4C). Since HNRNPU is involved in RNA splicing28,29, we hypothesized that HNRNPU might engage in the splicing of the EP400 transcript, the host gene of SNORA49, thereby modulating SNORA49 biogenesis. However, depletion of HNRNPU had no effect on SNORA49 expression, as confirmed by qRT-PCR and Northern blotting (Supplementary Fig. S4D, E). These results suggest that the interaction of SNORA49 with HNRNPU may influence the function of HNRNPU instead of its expression.

HNRNPU is implicated in promoting gene transcription in various diseases. It has been shown to bind DDX5 to activate the transcription of LMO4, thereby supporting tumor growth in triple-negative breast cancer30. HNRNPU can also drive chromatin remodeling and facilitate enhancer activation to promote target gene expression in antiviral immunity31. However, since HNRNPU itself is not a transcription factor, it may need to cooperate with other transcription factors to exert its transcriptional promotion effect. To identify the interacting proteins of HNRNPU in liver CSCs, we purified GST-tagged HNRNPU protein and performed co-immunoprecipitation (co-IP) with anti-GST beads using Huh7 sphere lysates (Fig. 4H). Through this approach, we identified zinc finger CCCH-type containing 18 (ZC3H18) as a binding partner of HNRNPU (Supplementary Fig. S4F), and verified their interaction by reciprocal co-IP using their respective polyclonal antibodies (Fig. 4I). We also performed domain-mapping to identify the binding site on HNRNPU that interacted with ZC3H18. Interestingly, HNRNPU lacking the SPRY domain lost the ability to bind to ZC3H18 (Supplementary Fig. S4G), as was the same case for SNORA49 binding to HNRNPU. We also modeled the interaction between HNRNPU and ZC3H18 by Alphafold232. As expected, we found that the second domain of HNRNPU mediated their binding, highlighted by the interactions at the Y350-D353 sites (Supplementary Fig. S4H). This overlap of binding regions prompted us to investigate whether SNORA49 binding could affect the interaction between HNRNPU and ZC3H18.

To address this issue, we conducted co-IP experiments using an anti-ZC3H18 antibody in lysates from SNORA49-depleted and rescued Huh7 spheres. We found that the interaction between HNRNPU and ZC3H18 was remarkably enhanced in SNORA49-depleted cells, while rescued SNORA49 attenuated this enhancement (Fig. 4J). Similar results were observed using an anti-HNRNPU antibody (Supplementary Fig. S4I). Conversely, overexpressed SNORA49 strongly suppressed the binding of HNRNPU to ZC3H18 (Supplementary Fig. S4J, K). In order to eliminate the interference from endogenous cellular factors, we purified GST-tagged HNRNPU and Flag-tagged ZC3H18 to test their interaction in vitro. We incubated GST-HNRNPU with increasing concentrations of SNORA49 and then added Flag-ZC3H18 for co-IP using anti-GST beads. As expected, pre-incubation with SNORA49 hindered the binding of HNRNPU to ZC3H18 in a dose-dependent manner, with high concentrations of SNORA49 completely blocking this interaction (Fig. 4K), whereas another unrelated RNA, SNORA74A, had no such effect (Fig. 4L). Taken together, these data indicate that SNORA49 specifically binds to HNRNPU and impairs its interaction with ZC3H18.

ZC3H18 associates with HNRNPU to initiate SOX9 transcription
To further explore the mechanism by which SNORA49 modulated CSC self-renewal, we performed RNA sequencing of SNORA49-depleted and control Huh7 cells. We found that SNORA49 depletion obviously upregulated several transcription factors (Fig. 5A). We confirmed these changes in SNORA49-depleted Huh7 cells (Supplementary Fig. S5A). In contrast, SNORA49-overexpressed cells showed reversed downregulation of these transcription factors (Supplementary Fig. S5B). We then depleted these transcription factors in Huh7 cells and assessed their impact on sphere formation. Among these candidates, knockdown of SOX9 most significantly impaired the stemness of Huh7 cells (Fig. 5B). We further confirmed upregulation of SOX9 in SNORA49-depleted Huh7 and primary HCC cells by qRT-PCR and immunoblotting (Fig. 5C and Supplementary Fig. S5C). Conversely, in SNORA49-overexpressed cells, both mRNA and protein levels of SOX9 were remarkably reduced (Supplementary Fig. S5D).

We then examine how SNORA49 regulated the expression of SOX9. Analysis of the TCGA database revealed a positive correlation between SOX9 expression and transcript levels of both HNRNPU and ZC3H18, with Pearson correlation coefficients (R) of 0.52 and 0.38, respectively (Supplementary Fig. S5E). Since SNORA49 could inhibit the interaction between HNRNPU and ZC3H18, we hypothesized that SNORA49 might impact target genes by interfering with this interaction. ZC3H18 is a well-characterized RNA-binding protein involved in nuclear RNA degradation33,34. Therefore, we speculated that ZC3H18 might bind to the pre-mRNA or mRNA of SOX9, thereby regulating SOX9 expression post-transcriptionally. We thus performed RNA immunoprecipitation experiments using the anti-ZC3H18 antibody but did not detect ZC3H18 binding to the pre-mRNA or mRNA of SOX9 (Supplementary Fig. S5F). They do not interact indirectly via HNRNPU, since there was no binding between HNRNPU and the SOX9 RNAs (Supplementary Fig. S5F). ZC3H18 contains a zinc finger domain, which is associated with DNA-binding activity, and interact with HNRNPU, a known transcriptional regulator. This prompted us to explore its potential role in transcriptional regulation. It has been reported to bind to the BRCA1 promoter and activate its transcription, promoting ovarian cancer progression35. We next wanted to determine whether ZC3H18 could bind to the SOX9 promoter and cooperated with HNRNPU to regulate SOX9 transcription in liver CSCs. We then performed chromatin immunoprecipitation (ChIP) with a polyclonal antibody against ZC3H18. The 4kb region upstream of the SOX9 transcription start site was divided into 10 fragments, and we found that ZC3H18 was enriched in the -600~-400 region of the SOX9 promoter (Fig. 5D). We also used biotin-labeled DNA probes of this region to enrich ZC3H18 (Fig. 5E). Moreover, depletion of either HNRNPU or ZC3H18 remarkably reduced chromatin accessibility in the SOX9 promoter (Fig. 5F). Of note, overexpression of SNORA49, blocking the interaction between HNRNPU and ZC3H18, also caused reduction in chromatin accessibility in the SOX9 promoter (Fig. 5G) and impaired the binding of ZC3H18 to this region (Fig. 5H).

To further determine the transcriptional regulation of SOX9, we performed dual-luciferase reporter assays in ZC3H18-depleted (Supplementary Fig. S5G) and SNORA49-overexpressed cells. We cloned the -600~-400 region of the SOX9 promoter into a pGL3 vector to drive luciferase expression. Luciferase activity was obviously reduced in ZC3H18-depleted cells (Fig. 5I), similar to the effect of SNORA49 overexpression (Supplementary Fig. S5H). In addition, SNORA49 overexpression also decreased levels of H3K4 trimethylation (Supplementary Fig. S5I) and H3K27 acetylation (Supplementary Fig. S5J), two histone modifications associated with transcriptional activation, at the SOX9 promoter. Consistent with changes in transcriptional activity, both mRNA and protein levels of SOX9 were remarkably decreased following knockdown of HNRNPU or ZC3H18 (Fig. 5J). Immunofluorescence staining also revealed a concomitant decrease in SOX9 expression following depletion of either HNRNPU or ZC3H18 in liver CSCs (Fig. 5K and Supplementary Fig. S5K). Consequently, proportions of liver CSCs were also remarkably reduced after HNRNPU or ZC3H18 depletion (Fig. 5L and Supplementary Fig. S5L). To explore the possibility that ZC3H18 indirectly regulated SOX9 expression via upstream regulators such as β-catenin, we performed ChIP experiments and found that there was no enrichment of ZC3H18 at the promoter of CTNNB1 (the gene encoding β-catenin) (Supplementary Fig. S5M). Collectively, these data indicate that the association and cooperation of HNRNPU with ZC3H18 are essential and sufficient for SOX9 transcription, which can be disrupted by SNORA49, leading to transcriptional suppression of SOX9 in liver CSCs.

SOX9 is highly expressed in liver CSCs and promotes self-renewal of liver CSCs
To determine the role of SOX9 in liver CSCs, we examined its expression by qRT-PCR and immunoblotting and observed that SOX9 was highly expressed in HCC tumor tissues compared with normal tissues (Fig. 6A), highly expressed in CSCs compared with non-CSCs (Fig. 6B), and highly expressed in spheres compared with non-spheres (Fig. 6C). Similar observations were validated in HCC patient samples by immunohistochemistry (Fig. 6D). High expression of SOX9 in HCC patient samples was further confirmed from the TCGA database (Fig. 6E), which was negatively correlated with survival outcomes for HCC patients (Fig. 6F). Of note, patients with higher SNORA49 expression and lower SOX9 levels had significantly better survival (Supplementary Fig. S6A). These results indicate that SOX9 plays a critical role in HCC tumorigenesis.

Next, we knocked down SOX9 in Huh7 and primary HCC cells (Supplementary Fig. S6B, C). SOX9 depletion dramatically reduced sphere formation (Fig. 6G and Supplementary Fig. S6D), cell proliferation (Fig. 6H), and CSC proportion (Supplementary Fig. S6E) in HCC cells, whereas overexpression of SOX9 could restore these oncogenic features. Moreover, SOX9 knockdown suppressed subcutaneous tumor growth in BALB/c nude mice (Fig. 6I). To further test the link between SNORA49 and SOX9, we silenced SOX9 in SNORA49-depleted cells. We found that enhanced sphere formation caused by SNORA49 knockdown was reversed by SOX9 depletion (Fig. 6J). By contrast, overexpression of SOX9 in SNORA49-overexpressed tumor cells augmented the self-renewal capacity of liver CSCs. Taken together, these results indicate that SOX9 is involved in the enhancement of self-renewal of liver CSCs as a downstream stemness factor of SNORA49.

Lipid nanoparticle delivery of SNORA49 and ASOs against SOX9 exert synergistic anti-tumor effect on HCC tumors
In order to test the in vivo role of SOX9 in HCC tumor development, we generated Alb-Cre;LSL-Cas9 mice that constitutively expressed Cas9 in the liver and deleted Sox9 upon delivery of specific sgRNAs. We injected packaged AAV-TBG-sgSox9 and/or AAV-TBG-Snora49 plasmids via mouse tail veins and detected efficient reduction of Sox9 expression (Supplementary Fig. S6F). We then established HCC tumors via HTVI and collected tumors three weeks later (Fig. 7A). We observed that deletion of Sox9 dramatically inhibited tumor formation, with more pronounced effects combining with Snora49 overexpression (Fig. 7B, C). To further evaluate their effects on CSC self-renewal, we sorted tumor cells from HTVI-induced and AAV-treated mouse HCC tumors and injected them subcutaneously into BALB/c nude mice to generate secondary tumors. Both Snora49 overexpression and Sox9 deletion dampened secondary tumor formation, and their combination exerted a synergistic anti-tumor effect (Fig. 7D).

Despite its high efficacy, AAV-mediated gene manipulation has not yet been suitable for clinical applications. Lipid nanoparticles (LNPs) have been used to deliver siRNAs and mRNAs in clinical treatment36,37. To examine the potential of LNP-mediated RNA delivery for HCC treatment, we first tested in vitro transfection and silencing efficiency of delivering human SNORA49 RNAs and SOX9 ASOs into Huh7 cells via LNPs. Full-length human SNORA49 was in vitro transcribed using T7 polymerase, yielding a high quantity of capped RNAs. SOX9-targeting ASOs were chemically modified with 2’-O-methoxyethyl groups at both ends and phosphorothioate modifications in the backbone, enhancing their stability, binding affinity, and pharmacological properties38. LNP delivery achieved obvious SNORA49 overexpression and SOX9 depletion (Supplementary Fig. S7A), which consequently dampened the stemness of liver CSCs as validated by oncosphere formation assay (Supplementary Fig. S7B). To evaluate the therapeutic potential of SNORA49 and SOX9 in mouse HCC models, we encapsulated mouse Snora49 RNAs and ASOs against Sox9 with LNPs and administered them to tumor-bearing mice (Fig. 7E). Two weeks after HTVI, mice were treated with LNPs containing Snora49 RNAs and/or Sox9 ASOs at a dose of 1 mg/kg, administered intravenously once a week (Fig. 7E). We observed efficient RNA delivery in mouse livers via LNPs, reaching ~40-fold increase in Snora49 levels and 50% reduction in Sox9 expression, which was even more prominent when Snora49 and ASOs were used together (Supplementary Fig. S7C). LNPs containing Snora49 RNAs or Sox9 ASOs remarkably suppressed tumor growth (Fig. 7F–H). A combination of Snora49 RNAs with Sox9 ASOs led to more reduction in tumor sizes and numbers, improving survival rates of tumor-bearing mice (Fig. 7I). We also assessed potential side effects of LNP-mediated RNA delivery in mice. Compared with control groups, those treated with either empty LNP vectors or LNP-RNAs displayed normal liver, kidney, and spleen morphology, comparable body weight and organ size, and only a slight but non-significant increase in hepatic expression of cytokines IFN-γ and IL-2 (Supplementary Fig. S7D, E). These results indicated that LNP-mediated RNA delivery had non-detective toxicity, minimal immunogenicity, and favorable biosafety. To further assess the translational potential of this therapy in humanized mouse models, we orthotopically injected luciferase-labeled primary HCC cells into livers of BALB/c nude mice, followed by treatment with empty LNPs or RNA-loaded LNPs (Fig. 7J). In this model, LNPs also achieved efficient RNA delivery and SOX9 silencing (Supplementary Fig. S7F). We found that combination treatment of human SNORA49 RNAs and SOX9 ASOs markedly suppressed orthotopic tumor growth, with greater effects than either agent alone (Fig. 7K). Taken together, LNP-mediated delivery of SNORA49 RNAs and SOX9 ASOs exert potent synergistic anti-tumor effect on HCC tumors, providing strong preclinical evidence for this approach as a potential therapeutic strategy.

Methods
All experiments in this study were conducted in compliance with relevant ethical regulations and approved by the Institutional Committee of the Institute of Biophysics, Chinese Academy of Sciences. Both male and female mice (6–8 weeks of age) were housed under specific pathogen-free conditions with a 12h light/dark cycle, temperature of 20 ± 2°C, and 50% relative humidity. Mice were randomly assigned to experimental groups, and no sex-dependent differences were observed in any of the analyses. All animal protocols were reviewed and approved by the Institutional Animal Care and Use Committee of the Institute of Biophysics, Chinese Academy of Sciences. Mice were euthanized before tumors exceeded 15 mm in diameter or developed skin ulceration. No biases were introduced with respect to patient sex or gender.

Cell lines and HCC samples
Human HCC cell lines Huh7 and PLC were provided by Dr. Zeguang Han (Shanghai Jiaotong University, School of Medicine, Shanghai, China), and HEK293T cells were obtained from ATCC (American Type Culture Collection, Manassas, VA, USA). HCC cell lines and HEK293T cells were cultured in DMEM medium supplemented with 10% FBS, 100 μg/ml penicillin G and 100 U/ml streptomycin. Fresh tumor tissues were minced into 1 mm3 pieces and then digested with digestion buffer (0.1% IV collagenase, 0.01% DNase, 0.05% protease dissolved in serum-free DMEM) at 37°C for 45 min. The supernatant was then filtered through a 70 μm filter, and the filtrate was centrifuged at 50 x g for 1 min to further remove clumps. The supernatant was collected and centrifuged at 150 x g for 8 min. Cells were enriched in the precipitate, and primary HCC cells were obtained after lysing the erythrocytes. All human HCC specimens were obtained from a partial hepatectomy series at Wuxi People’s Hospital (Wuxi, China) and the Department of Hepatobiliary Surgery, PLA General Hospital (Beijing, China). All tissue samples were obtained from consenting patients and approved by the Institutional Review Board of the Institute of Biophysics, Chinese Academy of Sciences, by the Ethics Committee of the Affiliated Wuxi People’s Hospital of Nanjing Medical University, and by the Ethics Committee of the PLA General Hospital. Clinical information of HCC patients in this study is listed in Supplementary Table S1. Materials used in this study are listed in Supplementary Data 1.

Sphere formation assay
2000 Huh7 or primary HCC cells were counted, seeded in low-attachment 6-well plates (Corning) and cultured in serum-free DMEM/F12 medium containing 20 ng/ml epithelial growth factor, 20 ng/ml fibroblast growth factor-2, N2 and B27 for 1-2 weeks. The number of spheres was counted under a stereomicroscope, and the percentage of sphere-initiating cells was calculated as (number of spheres formed) / (number of cells seeded per well) x 100%.

Colony formation assay
2000 Huh7 or HCC cells were seeded into 6-well plates and cultured in DMEM medium containing 10% FBS, 100 μg/ml penicillin G and 100 μ/ml streptomycin for approximately two weeks. After washing with PBS, cells were fixed in 4% PFA for 10 min and then stained with 0.1% crystal violet for 30 min. The plates were gently rinsed with running water and dried naturally.

Cell counting kit-8 (CCK-8) assay
10,000 Huh7 cells were seeded into 96-well plates and cultured in DMEM medium containing 10% FBS, 100 μg/ml penicillin G and 100 μ/ml streptomycin for 12 h to allow cell attachment. Then, 10 μl CCK-8 reagent (Zoman Bio) was added to each well, followed by incubation at 37°C for 2 h. The absorbance at 450 nm (OD450) was measured using a microplate reader. Cell proliferation rates were calculated based on the OD450 values.

Short hairpin RNA (shRNA) interference
Three shRNAs for each gene were cloned into the pSicoR-Puro lentiviral vector (Catalog No. 12084, Addgene). shRNA sequences used in this study are listed in Supplementary Table S2. The vectors were transfected into HEK293T cells with packaging plasmids pMD2.G (Catalog No. 12259, Addgene) and psPAX2 (Catalog No. 12260, Addgene). 48 h after transfection, the supernatant containing lentivirus was collected and filtered through a 0.45 μm filter, mixed with an equal volume of fresh DMEM medium and added to Huh7 or primary HCC cells for 24 h, followed by puromycin selection.

Gene overexpression
Full-length sequence of SNORA49 and coding sequence of HNRNPU, ZC3H18 and SOX9 were cloned into the pLVX-IRES-Puro or pLVX-IRES-GFP plasmid and transfected with packaging plasmids pMD2.G and psPAX2 into HEK293T cells for 48 h. Lentivirus was collected, mixed with an equal volume of DMEM medium, and transfected into target Huh7 or primary HCC cells for 24 h, followed by puromycin selection or GFP sorting.

Quantitative RT-PCR
Total RNAs were extracted from the samples using TRIzol and reverse transcribed into cDNAs by All-In-One 5X RT Master Mix (Abm). Quantitative real-time PCR analysis was conducted using the SYBR Green reaction system on the CFX Connect™ Real-Time PCR Detector (Bio-Rad, USA). All experiments were repeated three times independently and were analyzed using the 2-ΔΔCt method. U6, ACTB and 18S rRNA were used as internal references. Primers used in this study are listed in Supplementary Data 2.

Absolute quantification assay
The sequence of SNORA49 was cloned into the pcDNA3 plasmid. Plasmids were serially diluted and used as templates for qRT-PCR to generate a standard curve of CT values and copy numbers of SNORA49. Total RNAs of 2 x 10^6 CSCs or non-CSCs were extracted and reverse transcribed to cDNAs, followed by qRT-PCR with SNORA49-specific primers. The obtained CT values were then projected onto the standard curve to inversely calculate the copy number of SNORA49 in CSCs and non-CSCs.

Cellular fractionation
2 x 10^7 HCC cells were collected and lysed on ice for 10 min with 200 μl lysis buffer (1% NP-40, 0.25% sodium deoxycholate, 10 mM Tris pH 7.4, 140 mM NaCl, 1.5 mM MgCl2, 1x protease inhibitor cocktail). The lysates were centrifuged at 300 x g for 5 min, and the supernatant contained the cytoplasmic fraction. For further separation of the nuclear and nucleolar fractions, the pellet was resuspended in 200 μl sucrose solution (340 mM, 5 mM MgCl2) and sonicated to break up the floccules in the suspension. Then 200 μl sucrose solution (880 mM, 5 mM MgCl2) was added, and the nucleolar fraction was pelleted by centrifugation at 500 x g for 30 min, leaving the nuclear fraction in the supernatant. Finally, the nucleolar pellet was suspended in 200 μl sucrose buffer (340 mM, 5 mM MgCl2).

RNA fluorescence in situ hybridization and immunofluorescence staining
HCC cells were seeded on slides, fixed in 4% paraformaldehyde (PFA) for 15 min, and permeabilized with 1% Triton X-100 for 15 min. Biotin-labeled SNORA49 probes were diluted to a concentration of 10 ng/μl in hybridization buffer (50% formamide, 5 x SSC, 500 ng/μl yeast tRNA, 1 x Dehardt’s solution, 500 ng/μl sperm DNA, 50 ng/μl Heparin, 2.5 mM EDTA, 0.1% Tween-20) and added to the slides and incubated at 45°C for 2 h. After washing three times with 2 x SSC, TSA fluorescein (Akoya) was used to amplify the biotin signals according to the manufacturer’s instructions. For immunofluorescence staining, 10% donkey serum was used for blocking for 30 min. The primary antibodies were incubated at room temperature for 2 h or at 4°C overnight. After washing with PBS for three times, the slides were incubated with secondary antibodies at room temperature for 30 min. The slides were mounted with DAPI and observed using Nikon A1R+ confocal microscope.

Flow cytometry
Primary HCC tissues were dissociated into single cells and then were stained with CD45 antibodies to gate CD45-negative tumor cells and stained with FITC-conjugated CD13 and PE-conjugated CD133 antibodies to gate CSCs. Cells were stained with fluorescent antibodies on ice for 30 min and then sorted by flow cytometry. Data were analyzed by FlowJo V10. Flow cytometry gating strategies are listed in Supplementary Data 3.

Limiting dilution assay (LDA) and xenograft growth in nude mice
For LDA, HCC cells were serially diluted, mixed with 100 μl Matrigel and subcutaneously injected into BALB/c nude mice. The percentage of tumor-free mice was calculated 3 months later. For subcutaneous tumor growth, 1 x 10^6 HCC cells were injected into BALB/c nude mice. Tumor volume was measured every 4 days, starting from day 8 until day 28 and calculated as 1/2 * (length) * (width) * (width). All BALB/c nude mice were 6–8 weeks old and provided by Beijing Vital River Laboratory Animal Technology. Mice were sacrificed before the tumor diameter exceeded 15 mm or skin ulcers appeared. Mouse experiments were approved by the Animal Care and Use Committees of the Institute of Biophysics, Chinese Academy of Sciences.

In vivo imaging system (IVIS)
5 x 10^5 luciferase-labeled Huh7 or primary HCC cells were orthotopically injected into the livers of BALB/c nude mice. 1-2 weeks post-injection, mice were intraperitoneally injected with 3 mg D-luciferin potassium salt and then anesthetized with isoflurane. Luciferase signals were detected by IVIS Lumina 3 (PerkinElmer). Data were analyzed by Living Image V4.

Construction of knockout mice by CRISPR/Cas9 technology
Snora49 KO mice in C57BL6/J background were generated using CRISPR/Cas9 technology. Two sgRNAs (listed in Supplementary Table S3) targeting intronic sequences flanking the Snora49 locus were synthesized and injected into zygotes, which were transplanted into the uterus of pseudo-pregnant females to obtain F0 mice. To generate liver-sgSox9 mice, the U6 promoter in the AAV-sgRNA plasmid (Catalog No. 60231, Addgene) was replaced with the liver-specific TBG promoter (AAV-TBG). sgRNAs targeting the coding sequence of Sox9 were cloned into the AAV-TBG plasmid and co-transfected with pHelper and pAnc into HEK293T cells for 48 h for virus packing. Then the culture medium was collected and ultracentrifuged at 25,000 x g for 2 h. The pellet was resuspended with 0.9% NaCl solution and injected intravenously into Alb-Cre;LSL-Cas9 mice in a volume of 200 μl per mouse. The efficiency of AAV-mediated Sox9 knockout was assessed by qRT-PCR and immunoblotting. All mice were euthanized before the tumor diameter exceeded 15 mm or skin ulcers appeared. Alb-Cre mice were obtained from GemPharmatech Co., Ltd, and LSL-Cas9 mice were from Jackson Laboratory.

Hydrodynamic tail vein injection (HTVI)
8-week-old mice with C57BL/6 background were injected with 0.9% NaCl solution containing 20 μg of pBABE-c-myc T58A + HRasG12V plasmid (Catalog No. 11130, Addgene), 20 μg of pT2-shP53 plasmid (Catalog No. 124261, Addgene) and 20 μg of pT2/C-Luc//PGK-SB13 plasmid (Catalog No. 20207, Addgene). The saline was in a volume equivalent to 10% of the mouse body weight and was rapidly injected into the mouse tail vein within 7 s.

Generation of Snora49 overexpression mouse model
To achieve liver-specific overexpression of Snora49, the sequence of Snora49 was cloned into the AAV-TBG plasmid, packaged into AAV, and administered to mice via tail vein injection. Two weeks post-injection, overexpression of Snora49 was detected by qRT-PCR and Northern blotting.

RNA pulldown and mass spectrometry assay
Biotin-labeled sense and antisense probes of SNORA49 were in vitro transcribed using the T7 RNA polymerase (Roche) and biotin labeling agent (Roche). Sphere lysates of Huh7 cells were incubated with 3 mg probes at 4°C overnight. Then streptavidin magnetic beads were added to pull down RNA probes and their binding proteins. After washing with lysis buffer (RIPA), the proteins were subjected to SDS-PAGE and silver staining. Differential bands were collected for liquid chromatography-tandem mass spectrometry analysis.
For LC-MS/MS analysis, silver-stained gels were destained, reduced with DTT, alkylated with iodoacetamide, and subjected to overnight digestion with trypsin. Peptides were extracted in multiple steps using acetonitrile at different concentrations and subsequently analyzed on a nanoLC system coupled to a Q Exactive mass spectrometer (Thermo Scientific) using a reversed-phase C18 analytical column (75 μm x 20 cm, 3 μm particle size). Peptides were separated at a flow rate of 300 nL/min with mobile phase A (0.1% formic acid in H2O) and mobile phase B (0.1% formic acid in acetonitrile). The gradient was programmed as follows: 4% B at 0 min, 8% B at 8 min, 22% B at 58 min, 32% B at 70 min, 90% B at 73–80 min. The Q Exactive was operated in data-dependent acquisition mode (top 20), consisting of one full MS scan followed by MS/MS of the 20 most intense precursor ions. Full MS scans were acquired over m/z 300–1600. The spray voltage was set to 2.0 kV, and the capillary temperature was 320°C. Dynamic exclusion was set to 40 s.
Database searching was performed with the SEQUEST HT engine in Thermo Proteome Discoverer (version 1.4.0.288) against the UniProt human 2022 database. Searches were conducted with trypsin specificity, allowing up to two missed cleavages. The precursor ion mass tolerance was set to 10 ppm, and the fragment ion mass tolerance to 20 mDa. Carbamidomethylation of cysteine was specified as a fixed modification, whereas oxidation of methionine and lactylation of lysine were set as variable modifications. Spectral matches were filtered with Percolator, applying a Delta Cn threshold of < 0.1 and a false discovery rate (FDR) cutoff of 1%. Peptides were further filtered by requiring High peptide confidence. Proteins identified by mass spectrometry are listed in Supplementary Data 4.

Domain mapping
HNRNPU was divided into 4 fragments according to the distribution of functional domains. The sequence of full-length HNRNPU or HNRNPU lacking each domain was cloned into the p3xFlag-CMV10 plasmid and then transfected into HEK293T cells. 48 h later, cells were lysed with RIPA and subjected to immunoblotting to confirm the production of truncated HNRNPU proteins. Correctly truncated HNRNPU proteins were then incubated with biotin-labeled SNORA49 probes for RNA pulldown or with ZC3H18 for Co-IP assay.

Electrophoretic mobility shift assay (EMSA)
Human HNRNPU was cloned to the pGEX-6p-hDcp2 plasmid (Catalog No. 72216, Addgene) and purified by GST-tagged protein purification. Biotin-labeled SNORA49 probes were incubated with HNRNPU, with or without unlabeled probes, and then subjected to mobility shift assay using a Chemiluminescent RNA EMSA Kit (Beyotime) according to the manufacturer’s protocol. For competitive EMSA with SNORA74A and scramble probes, full-lengthen SNORA74A sequence (200 nt) was used, and the synthetic scramble RNA has the same lengthen (137 nt) and GC content (48%) as SNORA49.

Co-immunoprecipitation (Co-IP) assay
Sphere lysates of Huh7 cells were treated with RNase A at 37°C for 30 min to remove endogenous RNAs and pre-cleared with Protein A/G agarose beads for 1 h and then incubated with anti-HNRNPU or anti-ZC3H18 antibodies at 4°C for 2 h. Protein A/G agarose beads were added again to precipitate the target protein and its potential binding proteins, followed by immunoblotting.

In vitro competitive binding
GST-tagged HNRNPU and Flag-tagged ZC3H18 were purified through affinity chromatography. SNORA49 or SNORA74A was transcribed in large quantities using the T7 high yield RNA transcription kit (Vazyme). GST-HNRNPU was pre-incubated with increasing concentrations of SNORA49 or SNORA74A at 4°C for 2 h, followed by incubation with Flag-ZC3H18 at 4°C for an additional 2 h. The complexes were then captured with GST-beads. The interaction between HNRNPU and ZC3H18 was semi-quantified by immunoblotting.

Chromatin immunoprecipitation (ChIP) assay
Huh7 sphere cells were cross-linked with 1% formaldehyde at 37°C for 10 min, washed twice with PBS and lysed in SDS lysis buffer (1% SDS, 10 mM EDTA, 50 mM Tris). DNA was fragmented into 200~500-bp fragments by sonication at 300 W for 1 min 4 times. The lysate was incubated with 4 μg anti-ZC3H18 polyclonal antibodies at 4°C overnight. After incubation with Protein A/G agarose beads at 4°C for 2 h, DNA was eluted and analyzed by qPCR with specific primers listed in Supplementary Table S4.

Chromatin accessibility assay
The nuclei of Huh7 sphere cells were isolated using the NE-PER nuclear and cytoplasmic extraction kits (Thermo), suspended with 200 μl of DNase Digestion Buffer and digested with 2 μl of DNase I at 37°C for 5 min. Digestion was stopped with Digestion Stop Buffer. DNAs were extracted and analyzed by qPCR.

Dual-luciferase reporter assay
The sequence of the SOX9 promoter was cloned into the pGL3 vector and co-transfected with the pRL-TK plasmid into Huh7 cells for 36 h. After the cells were lysed, the luminescence signals were detected using a Dual Luciferase Reporter Gene Assay Kit (Beyotime) according to the manufacturer’s instructions.

Transcriptome sequencing
Total RNAs of 2 x 10^7 SNORA49-depleted and control cells were extracted by TRIzol, followed by DNBSEQ sequencing (BGI). After quality control, clean reads were aligned to the human genome (GCF_000001405.39_GRCh38.p13). Data analysis was performed by R 4.2.

Immunohistochemical staining
The tumor samples were fixed with 4% PFA for 48 h, embedded with paraffin, and sectioned into 10 µm thick slides. The slides were deparaffinized by sequential washes in xylene, 100% ethanol, 95% ethanol, and 85% ethanol, each for 10 min, and then rehydrated in PBS. Antigen retrieval was performed using an antigen retrieval buffer (Tris/EDTA pH 9.0) by heating the slides at 95°C for 15 min. Endogenous peroxidase was quenched by incubating the slides with 3% hydrogen peroxide (H2O2) for 10 min. The slides were then blocked with 10% donkey serum for 30 min, incubated with primary antibodies for 2 h, and incubated with HPR-conjugated secondary antibodies for 1 h, all at room temperature. The immunoreactivity was visualized using DAB staining, and the slides were counterstained with hematoxylin. Finally, the slides were mounted with neutral balsam for microscopic examination.

Lipid nanoparticle packaging and administration
For large-scale transcription of human and mouse SNORA49, we adopted a co-transcriptional capping reaction system, in which the standard capping reagent m7G(5’)ppp(5’)G was added together with DNA templates, NTPs, and T7 RNA polymerase, following the manufacturer’s instructions (Vazyme). ASOs targeting SOX9 were synthesized and chemically modified (Tsingke). ASOs targeting human and mouse SOX9 have identical sequences, which are listed in Supplementary Table S5. The LNP formulation was based on commercially available ionizable lipids SM-102 (Moderna) and consisted of the following components: SM-102, cholesterol, 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC), and PEG2000-DMG, with a molar ratio of 50:10:38.5:1.5. The average particle size of LNPs was approximately 100 nm, as determined by dynamic light scattering (DLS). RNAs were packaged into LNPs with a concentration of 0.35 μg/μl. For in vitro LNP administration, Huh7 cells were treated with 100 ng/ml LNP-packaged RNAs for 24 h, followed by collection for assessment of transfection and gene silencing efficiency. For in vivo LNP treatment in mouse models, 1 mg/kg RNAs (corresponding to 57 μl LNPs) were injected into the tail vein of tumor-bearing mice (20 g) once a week. For biosafety assessment, WT mice were treated with empty LNP vectors or RNA-loaded LNPs at the same dose used in HTVI-LNP model. Body and major organ weights were recorded, liver, kidney, and spleen morphology were evaluated, and expression levels of IFN-γ and IL-2 in the liver were measured by qRT-PCR 48 h after injection.

Statistics and reproducibility
Statistical analysis was performed using GraphPad Prism 9.0 and Excel 2019. Unless otherwise stated, statistical significance was assessed by unpaired two-tailed Student’s t tests. A significance threshold of P < 0.05 was applied, with results denoted as *P < 0.05, **P < 0.01, ***P < 0.001, and ns (not significant). All assays were performed in at least three independent experiments, and representative results are presented.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The authors reported that a SNORA49/HNRNPU/ZC3H18/SOX9 axis promotes liver CSCs and targeting SNORA49 and\nSOX9 could provide synergistic effect in suppressing HCC tumorigenesis. Overall, the authors have provided robust\nevidence to demonstrate the importance of SNORA49 axis in HCC with possible improvements mentioned below.\n1. The link between SNORA49/SOX9 axis and changes in CD133+CD13+ liver CSC subset is not clear.\n2. The clinical correlation and prognostic value of SOX9 has been reported in other studies before. The combined clinical\nand prognostic values of SNORA49 and SOX9 should be investigated.\n3. In Fig. 7, verification of Snora49 and Sox9 should be performed in these mouse models.\n4. The self-renewal ability of residual tumor cells to reconstitute secondary tumor initiation should be investigated in AAV-\nTBG-Snora49-treated model as well as in combined treatment model with sgSox9.", "reviewer_2": "Comments for \"SNORA49 negatively regulates self-renewal of liver cancer stem cells and hepatocarcinogenesis via\nsuppression of SOX9 transcription\" by Yi et al.\nIn their manuscript, Yi et al. identify snoRA49 as a key factor downregulated in cancer stem cells (CSCs), which are central\nto hepatocellular carcinoma (HCC) development.\nIn summary, they propose that snoRA49 interacts with HNRNPU, thereby preventing its interaction with ZC3H18. This\ncomplex (HNRNP U/ZC3H18) can bind the SOX9 promoter and activate SOX9 expression, which is driving cancer\ndevelopment. Through this mechanism, the authors propose that downregulation of snoRA49 in CSCs enables increased\nSOX9 expression. Finally, the authors demonstrate two combinatorial treatments where increased snoRA49 expression and\nlowered SOX9 expression combined can treat HCC.\nWhile the study presents an interesting mechanistic link between snoRA49, HNRNPU, ZC3H18 and SOX9, several aspects\nof the experimental design and data interpretation require further clarification and validation. Below, I outline the major and\nminor concerns that should be addressed before considering publication.\nMajor points:\nFigure 1 and p. 5, l.128-129:\n(1) Evidence of depletion? It is shown in later figures, but why not when it is used the first time?\n(2) Why are shRNAs chosen to deplete a nuclear RNA? As far as I know, shRNAs and siRNAs mainly exert their effects in\nthe cytoplasm. In my opinion, oligonucleotides guiding RNaseH cleavage would be a more logical choice.\nFigure 4 and p. 8, l. 235-236:\n\"Recent studies show that snoRNAs may also exert functions by binding proteins to form small nucleolar ribonucleoprotein\n(snoRNP) complexes.\"\n(1) when citing \"recent studies\", there should also be some citations!\n(2) What are recent studies? It is well established since the 1990'ies that snoRNAs form snoRNPs. For box H/ACA\nsnoRNAs the core factors are Dyskerin, Gar1, Nop10 and Nhp2. Is the proposed function of snoRA49 independent of its role\nas a snoRNP? Does the RNA interact with its core protein partners? This needs to be examined in details.\n(3) Along the same lines: Map which part of snoRA49 the interacts with HNRNP U.\nFigure 4A-B:\nShow the RNAs used for these pulldowns – preferably before and after pulldown. HNRNP U inherently binds RNA, and\ntherefore it is surprising that there is not a shadow of interaction with the antisense RNA.\nFigure 4D:\nDespite the result in 4A-B, another (unrelated) RNA should be tested in this assay. As a minimum, try to compete with an\nunrelated unlabeled RNA of the same size and concentration.\nFigure 4J:\n(1) Model the proposed interaction between HNRNP U and ZC3H18 using Alphafold2.\n(2) Also try to model interaction between HNRNP U and snoRA49 using Alphafold3.\nFigure 4G-I:\n(1) Are IPs treated with RNase? If not the experiments should be repeated with and without RNase/benzonase treatment to\nassess which of the interactions are mediated through RNA. It is well known that HNRNP proteins interact with many\nproteins via RNA.\n(2) Why was ZC3H18 specifically investigated? There are multiple other proteins co-IP'ing with HNRNP U as shown in\nFigure 4G. Was the whole pool of proteins subjected to mass spectrometry? Did you test any of the other proteins from this\nIP in downstream assays, or was ZC3H18 just a fortunate pick among this array of co-precipitants?\nRegarding ZC3H18:\nThis protein has a well-established role in nuclear RNA degradation, whereas its function as a transcriptional activator is\nless studied. I wonder why the authors chose to focus on this aspect of the protein rather than its more well-established role.\nPlease clarify.\nFigure 7:\nRegarding the experiments using LNP-packaged SNORA49:\nIn the Materials and Methods, it is stated that \"Human and mouse SNORA49 was in vitro transcribed using the T7 high-yield\nRNA transcription kit (Vazyme)\" and that \"RNAs were packaged into ionizable lipids SM-102 (Moderna).\" If snoRA49 was\nproduced with regular nucleotides and without conversion of the 5'-triphosphate to a monophosphate (or capping) and taken\ndirectly from the T7 reaction, it would likely (1) be highly unstable and (2) trigger a strong innate immune response upon\ndelivery to the liver. Did the authors assess these potential issues?\nMinor:\nFigure S1B,C:\nDiscrepancy between B and C for HCC#1. Almost equal between N and S using northern\nblotting. Clear difference in RT-\nqPCR.\nFigure 1G and S1D:\nFor tumor cells in #HCC1 it looks like SNORA49 localizes in the nucleolus (Fig. S1D), whereas it is mainly found in the\nnucleoplasm of CSC cells (Fig. 1G). Discuss the discrepancy.\nFigure 4E:\nThe figure does not give detailed evidence that snoRA49 and HNRNPU co-localize, but shows that they both localize all\nover the nucleoplasm.\nFigure 6D:\nMissing information in figure text and methods description. What do they stain for, and which colors indicate SOX9?\np. 6, l. 167: Should be increased proportion instead of decreased (Fig. S2E).\np. 10, l. 274: HNUNPU should be HNRNPU\np. 10, l. 284-285: The effect appears weaker with anti-HNRNPU. Quantification of the bands should probably be shown.\np. 12-13, l. 360-361: It is unclear to us whether these effects are additive or synergistic.", "reviewer_3": "In this manuscript, the authors identify SNORA49, a conserved H/ACA box snoRNA, as a tumor suppressor that restricts\nliver cancer stem cell (CSC) self-renewal and hepatocarcinogenesis through transcriptional repression of SOX9. This study\ndemonstrates that SNORA49 is downregulated in liver CSCs and HCC tissues, and its loss enhances CSC stemness and\naccelerates tumorigenesis in vitro and in vivo, providing novel insights into non-canonical roles of snoRNAs in CSC biology,\nexpanding the functional repertoire of snoRNAs beyond rRNA modification. Mechanistically, SNORA49 binds to HNRNPU\nin the nucleoplasm, disrupting its interaction with the transcription factor ZC3H18, thereby blocking their co-recruitment to the\nSOX9 promoter and suppressing its transcription. Therapeutically, lipid nanoparticle (LNP)-mediated delivery of SNORA49\nRNA combined with SOX9 antisense oligonucleotides (ASOs) synergistically inhibits tumor growth in preclinical models,\nhighlighting translational potential. This work unveils SNORA49 as a key epigenetic regulator of liver CSCs and proposes a\ntherapeutically actionable RNA-protein interaction axis. While the mechanistic framework is innovative and the translational\nstrategy conceptually novel, incomplete specificity validation, limited exploration of HCC subtype dependencies, and\ninsufficient preclinical profiling of LNPs necessitate revision. Addressing these gaps would elevate the study’s impact,\npositioning it as a cornerstone for snoRNA biology and CSC-targeted therapy development. The following are some\nsuggestions on how to enhance the manuscript.\n1. While SNORA49 competes with ZC3H18 for HNRNPU binding in vitro, the absence of negative controls (e.g., unrelated\nsnoRNAs or mutated HNRNPU domains) weakens claims of exclusivity.\n2. ChIP-qPCR focuses solely on the -600~-400 region of SOX9. Inclusion of known SOX9 regulatory elements (e.g., Wnt/β-catenin or YAP-responsive regions) would strengthen the conclusion that ZC3H18/HNRNPU specifically drives SOX9\ntranscription in CSCs.\n3. The study links SNORA49 to H3K4me3 reduction at the SOX9 promoter but does not explore broader chromatin\nremodeling effects (e.g., histone acetyltransferase/HDAC recruitment), leaving the epigenetic landscape incompletely\nmapped.\n4. LNP treatment efficacy is shown at a single dose; escalating doses and safety assessments (e.g., cytokine release,\nliver/kidney toxicity) are needed to gauge therapeutic windows.\n5. The HTVI model (c-Myc/HrasG12V/shp53-driven) primarily recapitulates a subset of HCC with RAS pathway activation.\nSNORA49’s relevance to other HCC subtypes (e.g., Wnt/β-catenin or YAP) remains untested.\n6. SNORA49 overexpression/knockout could indirectly alter rRNA pseudouridylation via canonical snoRNA functions.\nRibosome profiling or polysome-seq data would clarify whether translational dysregulation contributes to the phenotype.", "reviewer_4": "In this research manuscript, the authors identified the lowed expression of conserved SNORA49 in liver CSCs and\ndemonstrated its negative correlation with CSC self-renewal capacity via serious logical experiments. They clarified that low\nexpressed SNORA49 could liberate HURNPU to engage with ZC3H18 to enrich to the promotor of SOX9, which would lead\nto SOX9 and followingly induced the self-renewal initiation of liver CSCs. They further reified the tumor suppressive function\nof SNORA49 by leveraging LNP-delivered system to restore SNORA49 and silence its SOX9 target on HCC tumor model,\nproviding insight into new targeting/methodology of CSC-targeted therapies for HCC patients. Overall, this research\nprovided abundant of critical and convincing evidence to elucidate the suppressive function of SNORA49 in liver CSC. After\nsome minor concerns are carefully addressed, the manuscript should be considered to publish in Nature Communications.\n1. Here, the authors mainly clarified the non-canonical function of snoRNAs (SNOA49) in the nucleolus. Could the authors\ngive some overall profile and discussion of SNOA49 in CSC, such as SNOA49 canonical target and function.\n2. The Figure 1D and Figure 1E revealed that SNORA49 expression was dramatically lower in HCC tumor tissues\ncompared with peri-tumor tissues, lower in CSCs compared with non-CSCs. Could the authors normalize SNORA49\nexpression in peri-tumor tissues, Non-CSC tumor and CSC in the qRT-PCR and Northern blotting to show the trend?\n3. Would SNORA49-depletion influence the proliferation ability of CSC? Except for colony formation assay, some\nquantitative experiment may be convincing and need, such as CCK-8 assay.\n4. Some quantitative data, such as the proportion of CSCs (CD13+CD133+) in tumor were necessary to draw the conclusion\nthat “SNORA49 inhibits the stemness of human liver CSCs and suppresses HCC tumor growth” (line 181).\n5. LNP-delivered system of mSnora49 and/or ASO-Sox9 provided an excellent platform for target verification and therapeutic\napplication. Although herein ionizable lipids SM-102 (Moderna) was employed, the formulation and preparation of LNP\nshould be detail provide. Importantly, the LNP properties should also be detailly characterized, including cryo-TEM,\nDLS size, in vitro transfection and silencing efficiency of targeting mRNA, lysosomal escape ability, in vivo distribution and in vivo\ntransfection, etc.\n6. The authors herein substantially elaborated upstream and downstream relationship between SNORA49 and SOX9 and\nillustrated them as promising therapeutic targeting. More discussion about their relationship in therapeutic application was\nnecessary in the discussion section."}, "author_response": "Point-by-point response to the reviewers\nReviewer #1:\nThe authors reported that a SNORA49/HNRNPU/ZC3H18/SOX9 axis promotes liver\nCSCs and targeting SNORA49 and SOX9 could provide synergistic effect in suppressing\nHCC tumorigenesis. Overall, the authors have provided robust evidence to demonstrate\nthe importance of SNORA49 axis in HCC with possible improvements mentioned below.\n1. The link between SNORA49/SOX9 axis and changes in CD133+CD13+ liver CSC\nsubset is not clear.\nAnswer: To further establish this link, we assessed CD133⁺CD13⁺ CSC proportions\nin HNRNPU- and ZC3H18-depleted Huh7 cells, as well as in corresponding rescue\nexperiments (new Figure 5L and S5L). We found that both HNRNPU and ZC3H18 were\nrequired for maintaining CSC populations, thereby reinforcing the regulatory role of the\nSNORA49/SOX9 axis in liver CSC dynamics.\n2. The clinical correlation and prognostic value of SOX9 has been reported in other studies\nbefore. The combined clinical and prognostic values of SNORA49 and SOX9 should be\ninvestigated.\nAnswer: This is a good suggestion. We re-analyzed the TCGA liver cancer cohort by\nstratifying patients into SNORA49Low/High and SOX9Low/High based on gene expression levels.\nWe then assessed the combined prognostic significance by comparing survival outcomes\nbetween the SNORA49LowSOX9High and SNORA49HighSOX9Low subgroups. The\nSNORA49HighSOX9Low group exhibited much better overall survival (new Figure S6A),\nhighlighting the combined prognostic value of SNORA49 and SOX9 in HCC.\n3. In Fig. 7, verification of Snora49 and Sox9 should be performed in these mouse models.\nAnswer: We provided verification of Snora49 RNA levels, as well as Sox9 RNA and\nprotein levels, across all three mouse models in new Figure S6F (AAV model), S7C (HTVI-\nLNP model), and S7F (PDC-LNP model), respectively.\n4. The self-renewal ability of residual tumor cells to reconstitute secondary tumor initiation\nshould be investigated in AAV-TBG-Snora49-treated model as well as in combined\ntreatment model with sgSox9.\nAnswer: To evaluate the self-renewal capacity of residual tumor cells, we isolated\ntumor cells from HTVI-induced, AAV-treated HCC tumors and subcutaneously injected\nthem into BALB/c nude mice. We observed that both AAV-TBG-Snora49 and AAV-TBG-\nsgSox9 treatment groups exhibited impaired secondary tumor formation, with the\ncombined treatment group showing most pronounced suppression (new Figure 7D). These\nresults indicate that AAV-mediated treatment of Snora49 and/or sgSox9 significantly\nimpairs the self-renewal potential of liver tumor cells.\nReviewer #2:\nComments for \"SNORA49 negatively regulates self-renewal of liver cancer stem cells\nand hepatocarcinogenesis via suppression of SOX9 transcription\" by Yi et al. In their\nmanuscript, Yi et al. identify snoRA49 as a key factor downregulated in cancer stem cells\n(CSCs), which are central to hepatocellular carcinoma (HCC) development.\nIn summary, they propose that snoRA49 interacts with HNRNPU, thereby preventing\nits interaction with ZC3H18. This complex (HNRNP U/ZC3H18) can bind the SOX9\npromoter and activate SOX9 expression, which is driving cancer development. Through\nthis mechanism, the authors propose that downregulation of snoRA49 in CSCs enables\nincreased SOX9 expression. Finally, the authors demonstrate two combinatorial\ntreatments where increased snoRA49 expression and lowered SOX9 expression\ncombined can treat HCC.\nWhile the study presents an interesting mechanistic link between snoRA49, HNRNPU,\nZC3H18 and SOX9, several aspects of the experimental design and data interpretation\nrequire further clarification and validation. Below, I outline the major and minor concerns\nthat should be addressed before considering publication.\nMajor points:\nFigure 1 and p. 5, l.128-129:\n(1) Evidence of depletion? It is shown in later figures, but why not when it is used the first\ntime?\nAnswer: We provided the depletion validation data (new Figure S1B) in our revised\nmanuscript.\n(2) Why are shRNAs chosen to deplete a nuclear RNA? As far as I know, shRNAs and\nsiRNAs mainly exert their effects in the cytoplasm. In my opinion, oligonucleotides guiding\nRNaseH cleavage would be a more logical choice.\nAnswer: This is a good point. Indeed, ASOs have advantages for targeting nuclear\nRNAs due to their ability to guide RNase H–mediated cleavage. However, their effects are\nusually transient, lasting only hours to days. In contrast, shRNAs integrate into the genome\nof target cells, enabling stable and long-term knockdown. Since our functional assays,\nincluding oncosphere and colony formation, subcutaneous tumor growth, and limiting\ndilution assays, span weeks to months, shRNAs were chosen to achieve sustained RNA\ninterference consistent with the experimental timeline.\nFigure 4 and p. 8, l. 235-236:\n\"Recent studies show that snoRNAs may also exert functions by binding proteins to form\nsmall nucleolar ribonucleoprotein (snoRNP) complexes.\"\n(1) when citing \"recent studies\", there should also be some citations!\n(2) What are recent studies? It is well established since the 1990'ies that snoRNAs form\nsnoRNPs. For box H/ACA snoRNAs the core factors are Dyskerin, Gar1, Nop10 and Nhp2.\nIs the proposed function of snoRA49 independent of its role as a snoRNP? Does the RNA\ninteract with its core protein partners? This needs to be examined in details.\nAnswer: We sincerely apologize for the inaccurate and overly generalized statement\nin the original version. Indeed, the formation of snoRNP complexes by snoRNAs and core\nproteins such as Dyskerin, Gar1, Nop10, and Nhp2 has been well established since the\n1990s. We revised this wording in our revised text.\nWe re-examined our mass spectrometry data from the SNORA49 pulldown assay and\nfound no interactions with the canonical snoRNP core proteins Dyskerin, Gar1, Nop10, or\nNhp2, which further supported our conclusion that SNORA49 functions in a non-canonical\nmanner distinct from the traditional role of snoRNAs as part of a snoRNP complex.\n(3) Along the same lines: Map which part of snoRA49 the interacts with HNRNP U.\nAnswer: We designed truncated SNORA49 probes, each lacking specific fragments,\nand performed RNA pulldown assays to identify the region responsible for binding\nHNRNPU. Our results demonstrated that the 31–60 nt segment of SNORA49 was\nindispensable for its interaction with HNRNPU (new Figure 4F).\nFigure 4A-B:\nShow the RNAs used for these pulldowns – preferably before and after pulldown. HNRNP\nU inherently binds RNA, and therefore it is surprising that there is not a shadow of\ninteraction with the antisense RNA.\nAnswer: This is a valuable suggestion. We added images showing the RNA probes\nbefore pulldown (new Figure 4B). After pulldown, the RNAs were bound to proteins, which\nprevented their clear separation by gel electrophoresis. Regarding the lack of interaction\nwith the antisense RNA, we previously found that other snoRNAs, including SNORD17\nand SNORA74A similarly did not bind to HNRNPU (Figure 4C, RIP assays). These results\nindicate that although HNRNPU possesses inherent RNA-binding ability, this interaction is\nat least partially dependent on specific RNA sequences or structures rather than\nnonspecific binding.\nFigure 4D:\nDespite the result in 4A-B, another (unrelated) RNA should be tested in this assay. As a\nminimum, try to compete with an unrelated unlabeled RNA of the same size and\nconcentration.\nAnswer: This is a good point. To test binding specificity, we performed competitive\nEMSA assay adding two unrelated and unlabeled RNAs: SNORA74A (a 200-nt snoRNA)\nand a synthetic scramble RNA (137 nt, 48% GC content, matching SNORA49 in length\nand GC ratio). Neither was able to compete with SNORA49 for HNRNPU binding (new\nFigure S4B). These results further support the sequence and/or structure-specific\ninteraction between SNORA49 and HNRNPU.\nFigure 4J:\n(1) Model the proposed interaction between HNRNP U and ZC3H18 using Alphafold2.\n(2) Also try to model interaction between HNRNP U and snoRA49 using Alphafold3.\nAnswer: We successfully modeled the interaction between HNRNPU and ZC3H18\nusing Alphafold2 (new Figure S4H). The predicted complex structure and electrostatic\npotential map (new Figure S4H, left) illustrated a stable protein-protein interaction. Notably,\nthe SPRY domain (S267-K464) of HNRNPU appeared to mediate this interaction, with key\ncontact residues identified as Y350–D353 (new Figure S4H, right), consistent with our\nprevious domain mapping results (Figure S4G), thereby supporting the structural basis of\nthe HNRNPU–ZC3H18 interaction.\nWe also attempted to model the interaction between HNRNPU and SNORA49 using\nAlphafold3. However, RNA structure prediction remains considerably more challenging\nthan that of proteins. Despite this, our modeling revealed potential interactions, such as\ncontacts between C56 of SNORA49 and residues E314, H348, and L349 of HNRNPU\n(Attached Figure 1). These findings were consistent with our domain mapping results,\nwhich identified the 31-60 nt region of SNORA49 (new Figure 4F) and the SPRY domain\nof HNRNPU (Figure 4G) as mediators of the RNA-protein interaction. Nevertheless, we\nremain cautious, as the predictive accuracy and structural details of the RNA component\nare not fully reliable.\nFigure 4G-I:\n(1) Are IPs treated with RNase? If not, the experiments should be repeated with and without\nRNase/benzonase treatment to assess which of the interactions are mediated through\nRNA. It is well known that HNRNP proteins interact with many proteins via RNA.\nAnswer: In our initial co-IP experiments, endogenous RNAs were not removed. To\naddress this, we repeated the reciprocal co-IP experiments with RNase A treatment and\nfound that the interaction between HNRNPU and ZC3H18 persisted (new Figure 4I),\nindicating a direct protein–protein interaction without involvement of RNA mediators. We\nupdated Figure 4I with the new RNase-treated results. At the same time, we updated the\nMethods section to include RNase treatment in the description of the co-IP procedure.\n(2) Why was ZC3H18 specifically investigated? There are multiple other proteins co-IP'ing\nwith HNRNP U as shown in Figure 4G. Was the whole pool of proteins subjected to mass\nspectrometry? Did you test any of the other proteins from this IP in downstream assays, or\nwas ZC3H18 just a fortunate pick among this array of co-precipitants?\nAnswer: This is a good point. ZC3H18 was not an arbitrary choice but a carefully\nselected HNRNPU-interacting protein identified through rigorous screening and validation.\nThe entire pool of co-immunoprecipitated proteins was subjected to mass spectrometry\nanalysis. We then conducted literature and database research on the top-scoring\ncandidates to assess their relevance to liver cancer, which allowed us to preliminarily\nnarrow down the list, including potential candidates such as ZC3H18, FUBP1, ILF3, and\nPABPC1.\nFor proteins with potential roles in HCC, we further validated their interaction with\nHNRNPU by immunoblotting. In addition, we performed knockdown experiments to assess\ntheir impact on liver cancer stem cell (CSC) self-renewal using sphere formation assays.\nThrough this stepwise screening approach, ZC3H18 emerged as the sole candidate that\nboth interacted with HNRNPU and significantly affected oncosphere formation. Therefore,\nwe selected ZC3H18 as an interactor for further investigation.\nRegarding ZC3H18:\nThis protein has a well-established role in nuclear RNA degradation, whereas its function\nas a transcriptional activator is less studied. I wonder why the authors chose to focus on\nthis aspect of the protein rather than its more well-established role. Please clarify.\nAnswer: After identifying ZC3H18 as an HNRNPU-interacting protein in liver CSCs,\nwe first explored its well-established role in RNA binding and degradation. Given our\nfindings that both SNORA49 and HNRNPU influenced the stemness factor SOX9, and the\nobserved positive correlation between HNRNPU/ZC3H18 expression and SOX9 levels\n(Figure S5E), we hypothesized that ZC3H18 might be involved in RNA processing of SOX9\nby binding to its mRNA or pre-mRNA, which were localized in the cytoplasm and\nnucleoplasm, respectively.\nTo test this, we performed RNA immunoprecipitation (RIP) assays using a polyclonal\nantibody against ZC3H18. However, we did not detect binding between ZC3H18 and either\nthe mRNA or pre-mRNA of SOX9, even indirectly via HNRNPU (new Figure S5F). These\nresults led us to rule out the canonical RNA processing function of ZC3H18 in this context.\nZC3H18 contains a zinc finger domain, which is associated with DNA-binding activity,\nand interacts with HNRNPU, a known transcriptional regulator. This prompted us to explore\nits potential role in transcriptional regulation. We also took note of a prior study\ndemonstrating that ZC3H18 can bind the BRCA1 promoter and act as a transcriptional\nactivator in ovarian cancer (Kanakkanthara, Nat Commun, 2019). As such, we investigated\nwhether ZC3H18 could bind to the SOX9 promoter and regulate its transcription. In fact,\nour data confirmed that ZC3H18 bound to the SOX9 promoter and enhanced its\ntranscription, supporting a previously underappreciated role of ZC3H18 as a transcriptional\nactivator.\nFigure 7:\nRegarding the experiments using LNP-packaged SNORA49:\nIn the Materials and Methods, it is stated that \"Human and mouse SNORA49 was in vitro\ntranscribed using the T7 high-yield RNA transcription kit (Vazyme)\" and that \"RNAs were\npackaged into ionizable lipids SM-102 (Moderna).\" If snoRA49 was produced with regular\nnucleotides and without conversion of the 5'-triphosphate to a monophosphate (or capping)\nand taken directly from the T7 reaction, it would likely (1) be highly unstable and (2) trigger\na strong innate immune response upon delivery to the liver. Did the authors assess these\npotential issues?\nAnswer: Thank you for this important comment regarding the stability and\nimmunogenicity of in vitro transcribed RNAs delivered via LNPs. We acknowledge that our\n that our\noriginal description in the Materials and Methods was too concise. In fact, for large-scale\ntranscription of SNORA49, we adopted a co-transcriptional capping reaction system, in\nwhich the standard capping reagent m7G(5')ppp(5')G was added together with DNA\ntemplates, NTPs, and T7 RNA polymerase, following the manufacturer’s instructions. We\nrevised the Methods section to clarify this procedure in detail.\nTo assess potential immunogenicity, we evaluated body weight, organ size and\nmorphology, and measured expression levels of cytokines IFN-γ and IL-2 following LNP-\nmediated RNA delivery (new Figure S7D, E). No overt signs of toxicity or systemic\ninflammation were observed in treated mice. The results indicate that the in vitro\ntranscribed RNAs did not induce obvious innate immune response in vivo.\nMinor:\nFigure S1B, C:\nDiscrepancy between B and C for HCC#1. Almost equal between N and S using northern\nblotting. Clear difference in RT-qPCR.\nAnswer: Northern blotting results are highly sensitive to experimental conditions,\nparticularly the amount of RNA loaded (reflected by the internal reference signal) and the\nexposure time. In our earlier experiments, sphere sample (S) from HCC#1 showed a\nrelatively higher 18S rRNA signal, which might have masked actual difference in SNORA49\nexpression between the non-sphere (N) and sphere (S) samples. To address this, we\nrepeated both qRT-PCR and Northern blotting experiments using freshly extracted RNAs.\nThe revised Northern blotting results were included in new Figure S1C.\nFigure 1G and S1D:\nFor tumor cells in #HCC1 it looks like SNORA49 localizes in the nucleolus (Fig. S1D),\nwhereas it is mainly found in the nucleoplasm of CSC cells (Fig. 1G). Discuss the\ndiscrepancy.\nAnswer: Higher-resolution images (new Figure S1E) confirmed that SNORA49 was\nmainly localized in the nucleoplasm rather than the nucleolus in HCC tumor cells.\nFigure 4E:\nThe figure does not give detailed evidence that snoRA49 and HNRNPU co-localize, but\nshows that they both localize all over the nucleoplasm.\nAnswer: We revised the description to state that “both SNORA49 and HNRNPU exhibit\nnucleoplasm-specific localization”.\nFigure 6D:\nMissing information in figure text and methods description. What do they stain for, and\nwhich colors indicate SOX9?\nAnswer: We used DAB staining for immunohistochemistry, where SOX9-positive\nstaining was shown in brown. We labeled it in new Figure 6D, and corresponding\ndescriptions was provided.\np. 6, l. 167: Should be increased proportion instead of decreased (Fig. S2E).\np. 10, l. 274: HNUNPU should be HNRNPU\nAnswer: We revised these errors accordingly.\np. 10, l. 284-285: The effect appears weaker with anti-HNRNPU. Quantification of the\nbands should probably be shown.\nAnswer: We added band quantification in new Figure S4I.\np. 12-13, l. 360-361: It is unclear to us whether these effects are additive or synergistic.\nAnswer: We included evaluation of the effects of combined SNORA49 and SOX9\nASO treatment on SOX9 expression in various mouse models (new Figures S6F, S7A,\nS7C, S7F). Based on our mechanistic studies, SNORA49 repressed SOX9 at the\ntranscriptional level, whereas the SOX9 ASOs promoted degradation of SOX9 mRNA.\nThese two interventions acted at distinct regulatory levels, transcriptional and post-\ntranscriptional, converging to reduce SOX9 expression and suppressed HCC\ntumorigenesis. Therefore, we conclude that the effects are synergistic rather than simply\nadditive.\nReviewer #3:\nIn this manuscript, the authors identify SNORA49, a conserved H/ACA box snoRNA,\nas a tumor suppressor that restricts liver cancer stem cell (CSC) self-renewal and\nhepatocarcinogenesis through transcriptional repression of SOX9. This study\ndemonstrates that SNORA49 is downregulated in liver CSCs and HCC tissues, and its loss\nenhances CSC stemness and accelerates tumorigenesis in vitro and in vivo, providing\nnovel insights into non-canonical roles of snoRNAs in CSC biology, expanding the\nfunctional repertoire of snoRNAs beyond rRNA modification. Mechanistically, SNORA49\nbinds to HNRNPU in the nucleoplasm, disrupting its interaction with the transcription factor\nZC3H18, thereby blocking their co-recruitment to the SOX9 promoter and suppressing its\ntranscription. Therapeutically, lipid nanoparticle (LNP)-mediated delivery of SNORA49\nRNA combined with SOX9 antisense oligonucleotides (ASOs) synergistically inhibits tumor\ngrowth in preclinical models, highlighting translational potential. This work unveils\nSNORA49 as a key epigenetic regulator of liver CSCs and proposes a therapeutically\nactionable RNA-protein interaction axis. While the mechanistic framework is innovative and\nthe translational strategy conceptually novel, incomplete specificity validation, limited\nexploration of HCC subtype dependencies, and insufficient preclinical profiling of LNPs\nnecessitate revision. Addressing these gaps would elevate the study’s impact, positioning\nit as a cornerstone for snoRNA biology and CSC-targeted therapy development. The\nfollowing are some suggestions on how to enhance the manuscript.\n1. While SNORA49 competes with ZC3H18 for HNRNPU binding in vitro, the absence of\nnegative controls (e.g., unrelated snoRNAs or mutated HNRNPU domains) weakens\nclaims of exclusivity.\nAnswer: This is a good point. We performed additional in vitro binding assays using\nan unrelated snoRNA, SNORA74A (new Figure 4L), which did not affect the interaction\nbetween HNRNPU and ZC3H18. This result supports the specificity of SNORA49 in\ncompetitively blocking their binding.\n2. ChIP-qPCR focuses solely on the -600~-400 region of SOX9. Inclusion of known SOX9\nregulatory elements (e.g., Wnt/β-catenin or YAP-responsive regions) would strengthen the\nconclusion that ZC3H18/HNRNPU specifically drives SOX9 transcription in CSCs.\nAnswer: This is a valuable suggestion. To test whether ZC3H18 might indirectly\nregulate SOX9 via upstream regulators, such as Wnt/β-catenin, we performed ChIP-qPCR\non the promoter of CTNNB1 (encoding β-catenin). No enrichment of ZC3H18 was detected\n(new Figure S5M), supporting a direct transcriptional regulation of SOX9 by\nZC3H18/HNRNPU in liver CSCs.\n3. The study links SNORA49 to H3K4me3 reduction at the SOX9 promoter but does not\nexplore broader chromatin remodeling effects (e.g., histone acetyltransferase/HDAC\nrecruitment), leaving the epigenetic landscape incompletely mapped.\nAnswer: To further explore the epigenetic regulation of SOX9 by SNORA49, we\nadditionally assessed H3K27 acetylation (new Figure S5J), a well-established marker of\nactive transcription, at the SOX9 promotor. These results extended our initial observation\nand suggested that SNORA49 modulated a broader epigenetic landscape at the SOX9\nlocus, potentially through influencing both histone methylation and acetylation.\n4. LNP treatment efficacy is shown at a single dose; escalating doses and safety\nassessments (e.g., cytokine release, liver/kidney toxicity) are needed to gauge therapeutic\nwindows.\nAnswer: For LNP treatment dose, in our preliminary studies, we tested a range of\nLNP and RNA doses (from 0.1 mg/kg to 10 mg/kg) and identified 1 mg/kg as the optimal\ndose that achieved efficient hepatic RNA delivery without causing notable liver or kidney\ntoxicity, nor affecting overall body weight.\nFor safety assessments, we included additional data comparing liver/kidney/spleen\nmorphology (new Figure S7D), body weight and organ size (new Figure S7E), as well as\nIFN-γ and IL-2 expression levels (new Figure S7E) among LNP-treated and control mice.\nThese results collectively indicate that LNP-mediated RNA delivery is well tolerated and\nexhibits a favorable safety in vivo.\n5. The HTVI model (c-Myc/HrasG12V/shp53-driven) primarily recapitulates a subset of\nHCC with RAS pathway activation. SNORA49’s relevance to other HCC subtypes (e.g.,\nWnt/β-catenin or YAP) remains untested.\nAnswer: We appreciate this insightful point. Indeed, this remains a valuable direction\nfor further exploration. Mutation of CTNNB1 alone is insufficient to drive robust HCC\nformation in mice (Nejak-Bowen et al., Hepatology, 2010). Hydrodynamic tail vein injection\n(HTVI) of Sleeping Beauty transposons combined with pT3-EF1αH-myr-Akt and pT3-N90-\nβ-catenin plasmids can induce Wnt/β-catenin-driven HCC (Stauffer et al., Cancer Res,\n2011) (Scarzello et al., Gut, 2016). Although early tumorigenic changes characterized by\nhepatic steatosis can be observed at week 4 post-induction in this model, it is time-\nconsuming and requires multiple rounds of tumor passaging to generate bona fide tumors.\nDespite these limitations, we conducted a preliminary evaluation of SNORA49 in this\nmodel. We found that knockout of Snora49 dramatically accelerated steatosis progression\n(Attached Figure 2), whereas AAV-mediated Snora49 overexpression or Sox9 knockout\ninhibited malignant transformation. These results suggest a tumor-suppressive role for\nSNORA49 during early hepatocarcinogenesis in this subtype. However, definitive\nconclusion will require more solid models of Wnt/β-catenin-driven HCC for validation.\n6. SNORA49 overexpression/knockout could indirectly alter rRNA pseudouridylation via\ncanonical snoRNA functions. Ribosome profiling or polysome-seq data would clarify\nwhether translational dysregulation contributes to the phenotype.\nAnswer: We appreciate your thoughtful suggestion regarding the potential\ncontribution of translational dysregulation and agree that ribosome profiling or polysome-\nseq could provide valuable information. However, based on our current data, such as the\nabsence of predicted rRNA target sites for SNORA49, its specific nucleoplasmic (rather\nthan nucleolar) localization, and the lack of core snoRNP components in our mass\nspectrometry results, theoretically, SNORA49 was unlikely to perform canonical snoRNA\nfunctions, including rRNA modification. These findings collectively support a non-canonical\nrole for SNORA49 in regulating liver CSC self-renewal. Thus, we conclude that SNORA49\nregulates the liver CSCs in an rRNA pseudouridylation-independent manner.\nReviewer #4:\nIn this research manuscript, the authors identified the lowed expression of conserved\nSNORA49 in liver CSCs and demonstrated its negative correlation with CSC self-renewal\ncapacity via serious logical experiments. They clarified that low expressed SNORA49 could\nliberate HURNPU to engage with ZC3H18 to enrich to the promotor of SOX9, which would\nlead to SOX9 and followingly induced the self-renewal initiation of liver CSCs. They further\nreified the tumor suppressive function of SNORA49 by leveraging LNP-delivered system\nto restore SNORA49 and silence its SOX9 target on HCC tumor model, providing insight\ninto new targeting/methodology of CSC-targeted therapies for HCC patients. Overall, this\nresearch provided abundant of critical and convincing evidence to elucidate the\nsuppressive function of SNORA49 in liver CSC. After some minor concerns are carefully\naddressed, the manuscript should be considered to publish in Nature Communications.\n1. Here, the authors mainly clarified the non-canonical function of snoRNAs (SNOA49) in\nthe nucleolus. Could the authors give some overall profile and discussion of SNOA49 in\nCSC, such as SNOA49 canonical target and function.\nAnswer: This is a good comment. To our knowledge, SNORA49 lacks any predicted\ncanonical rRNA targets, and no experimental evidence to date supports its involvement in\nconventional snoRNA-guided rRNA modification. Consistent with this, SNORA49 was\nlocalized in the nucleoplasm (Figure 1G, 4E) rather than the nucleolus, and our mass\nspectrometry data revealed no association with core snoRNP proteins. These findings\nstrongly suggest that SNORA49 lacks canonical functions. Instead, our study focuses on\nits non-canonical, nucleoplasmic role in liver CSCs, where it regulates stemness through\ntranscriptional modulation of SOX9. We addressed this issue in our revised discussion\nsection.\n2. The Figure 1D and Figure 1E revealed that SNORA49 expression was dramatically\nlower in HCC tumor tissues compared with peri-tumor tissues, lower in CSCs compared\nwith non-CSCs. Could the authors normalize SNORA49 expression in peri-tumor tissues,\nnon-CSC tumor and CSC in the qRT-PCR and Northern blotting to show the trend?\nAnswer: This is a good suggestion. To address it, we performed additional qRT-PCR\nand Northern blotting analyses with normalization to peri-tumor tissues. These results\nrevealed a clear, stepwise decline in SNORA49 expression from peri-tumor tissues to non-\nCSC tumor cells and further to CSCs (new Figure S1D). This normalization enhanced the\nclarity and intuitiveness of SNORA49’s expression pattern, providing stronger support for\nits potential role in liver cancer progression.\n3. Would SNORA49-depletion influence the proliferation ability of CSC? Except for colony\nformation assay, some quantitative experiment may be convincing and need, such as CCK-\n8 assay.\nAnswer: We found that SNORA49 depletion indeed promoted CSC proliferation. To\nquantitatively validate this, we performed CCK-8 assays in SNORA49-depleted Huh7 cells\n(new Figure S2F) as well as in SNORA49-overexpressed cells (new Figure S3C).\n4. Some quantitative data, such as the proportion of CSCs (CD13+CD133+) in tumor were\nnecessary to draw the conclusion that “SNORA49 inhibits the stemness of human liver\nCSCs and suppresses HCC tumor growth” (line 181).\nAnswer: To address this gap, we re-established subcutaneous tumors using\nSNORA49-depleted and control Huh7 cells, and analyzed the proportion of CD13⁺CD133⁺\nCSCs by flow cytometry at week 4. As expected, SNORA49-depleted tumors exhibited a\nsignificantly higher CSC frequency (new Figure S2H), supporting our conclusion that\nSNORA49 inhibits liver CSC stemness and suppresses HCC tumor growth.\n5. LNP-delivered system of mSnora49 and/or ASO-Sox9 provided an excellent platform for\ntarget verification and therapeutic application. Although herein ionizable lipids SM-102\n(Moderna) was employed, the formulation and preparation of LNP should be detail provide.\nImportantly, the LNP properties should also be detailly characterized, including cryo-TEM,\nDLS size, in vitro transfection and silencing efficiency of targeting mRNA, lysosomal\nescape ability, in vivo distribution and in vivo transfection, etc.\nAnswer: We included additional information and experimental validations in the revised\nmanuscript. The LNP formulation used in our study was based on commercially available\nionizable lipids SM-102 and consisted of the following components: SM-102, cholesterol,\n1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC), and PEG2000-DMG, with a molar\nratio of 50:10:38.5:1.5. The average particle size of LNPs was approximately 100 nm, as\ndetermined by dynamic light scattering (DLS). These formulation and characterization\ndetails have been incorporated into the revised Methods section.\nTo assess in vitro transfection and silencing efficiency, we treated Huh7 cells with LNP-\nSNORA49 and/or LNP-ASO and measured both target RNA and protein levels (new Figure\nS7A). The results confirmed efficient RNA delivery and robust target gene knockdown.\nFurthermore, oncosphere formation assays showed that LNP treatment significantly\nimpaired CSC stemness in vitro (new Figure S7B).\nWe also evaluated in vivo transfection efficiency in both hydrodynamic tail vein\ninjection (HTVI) models (new Figure S7C) and PDC models (new Figure S7F), where we\nobserved effective RNA delivery and target gene suppression.\nRegarding lysosomal escape and in vivo biodistribution, while we acknowledge the\nimportance of these analyses, performing these assays would require packaging\nfluorescence-labeled RNAs into LNPs, which was technically unavailable to us at this time.\nNonetheless, the consistent phenotypic outcomes across models strongly suggest\neffective delivery and intracellular activity.\n6. The authors herein substantially elaborated upstream and downstream relationship\nbetween SNORA49 and SOX9 and illustrated them as promising therapeutic targeting.\nMore discussion about their relationship in therapeutic application was necessary in the\ndiscussion section.\nAnswer: We expanded the discussion on the therapeutic relevance of SNORA49 and\nSOX9 in our revised manuscript. Notably, SNORA49 expression progressively declined\nfrom peri-tumor tissues to tumor tissues and further to CSCs, whereas SOX9 displayed the\nopposite trend, being markedly upregulated in tumors and CSCs but minimally expressed\nin normal hepatocytes. This inverse and causally linked expression pattern offered a\nvaluable therapeutic window, allowing for specific targeting of liver CSCs and tumor cells\nwhile minimizing potential toxicity to normal tissues.\nTo support the clinical significance of this axis, we added a combined survival analysis\nusing TCGA liver cancer datasets (new Figure S6A), which revealed that patients with a\nSNORA49HighSOX9Low profile had significantly better overall survival compared to those\nwith a SNORA49LowSOX9High profile. This finding underscored the prognostic value and\ntherapeutic potential of this inverse regulatory relationship.\nFurthermore, in both our hydrodynamic tail vein injection (HTVI) and patient-derived\ncell (PDC) models, LNP-mediated combinatorial delivery of SNORA49 RNAs and SOX9\nASOs exhibited potent synergistic anti-tumor effects. These results further support the\nfeasibility and translational potential of this dual-targeting strategy for future liver cancer\ntherapies. Taken together, our findings not only elucidate a mechanistic link between\nSNORA49 and SOX9 in liver tumorigenesis but also establish a rationale for a clinically\ntranslatable dual-targeting strategy that could effectively eliminate CSCs and suppress\ntumor progression with minimal toxicity.\nAttached Figures\nAttached Figure 1. Modeling of the SNORA49-HNRNPU interaction by Alphafold3. (A)\nOverall complex structure of SNORA49 and HNRNPU predicted by AlphaFold3. The\ndashed box represents interactive region. (B) Close-up view of representative interacting\nresidues between SNORA49 and HNRNPU. C56 base of SNORA49 is flipped out of the\ndouble-stranded pairing region to form interactions with E314, H348 and L349 of HNRNPU.\nIt should be noted that the predicted RNA structure may not be very credible.\nAttached Figure 2. Snora49 suppresses early malignant transformation of AKT/CAT-\ndriven HCC. (A) Representative images of liver steatosis induced by HTVI-AKT/CAT in\nSnora49+/+ and Snora49-/- mice. Livers were harvested 4 weeks post-injection. Scale bars:\nupper, 5 mm; lower, 100 μm. (B) Liver-to-body weight ratios of Snora49+/+ and Snora49-/-\nmice shown in (A). n = 6 for each group. Data are presented as means ± SD. (C)\nRepresentative images of liver steatosis in mice treated with AAV-Snora49 and/or AAV-\nsgSox9. Livers were collected at 4 weeks after tumor induction. Scale bars: upper, 5 mm;\nlower, 100 μm. (D) Liver-to-body weight ratios of mice shown in (C). n = 6 for each group.\nData are presented as means ± SD. * P < 0.05; ** P < 0.01; *** P < 0.001 by two-tailed\nStudent’s t-test."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have responded all concerns.", "reviewer_2": "The authors have addressed all my concerns.\nA few additional comments:\nProvide the complete list of targets identified in the different mass spectrometry experiments.\nLines 233–234: “However, there was no reported rRNA site targeted by SNORA49, either in terms of experimental evidence\nor bioinformatics analysis.”\nThis statement is not entirely accurate. Without delving into detail, snoDB, one of the most prominent snoRNA databases,\nlists predicted target sites for SNORA49 in 28S rRNA (https://bioinfo-\nscottgroup.med.usherbrooke.ca/snoDB/detailed_view/snoDB0554 and http://snoatlas.bioinf.uni-\nleipzig.de/snoRNAAtlas_single.php?sno=snoID_0473). So, at the very least, bioinformatic predictions of target sites do\nexist.\nLines 238–239: “Recent studies have shown that snoRNAs exert their functions by binding to various proteins.”\nThis phrasing remains unclear. If you are referring to non-canonical (non-snoRNA) functions, please rephrase accordingly.\nFor example:\n“Recent studies have shown that some snoRNAs exert non-canonical functions through interactions with various proteins.”\nAlternatively, omit the “Recent studies” phrase altogether and revise to:\n“snoRNAs exert their functions through interactions with various proteins.”\nLine 575: Please specify the lysing component in the lysis buffer (10 mM Tris pH 7.4, 140 mM NaCl, 1.5 mM MgCl₂, 1×\nprotease inhibitor cocktail). Is there a detergent or mechanical lysis involved?", "reviewer_3": "All my concerns have been addressed and suggested for publication.", "reviewer_4": "The authors have resolved all of my concerns. It should be accepted without any revision."}, "author_response": "Point-by-point response to Reviewer #2\nReviewer #2:\nThe authors have addressed all my concerns.\nA few additional comments:\n1.Provide the complete list of targets identified in the different mass spectrometry\nexperiments.\nAnswer: We have provided full lists of proteins identified by mass spectrometry in\nSupplementary data 4.\n2.Lines 233–234: “However, there was no reported rRNA site targeted by SNORA49,\neither in terms of experimental evidence or bioinformatics analysis.”This statement is not\nentirely accurate. Without delving into detail, snoDB, one of the most prominent snoRNA\ndatabases, lists predicted target sites for SNORA49 in 28S rRNA\n(https://bioinfoscottgroup.med.usherbrooke.ca/snoDB/detailed_view/snoDB0554 and http\n://snoatlas.bioinf.uni-leipzig.de/snoRNAAtlas_single.php?sno=snoID_0473). So, at the\nvery least, bioinformatic predictions of target sites do exist.\nAnswer: Thank you for pointing this out. In our initial search using the snoPY database,\nno potential rRNA targets were reported for SNORA49 (http://snoopy.med.miyazaki-\nu.ac.jp/snorna_db.cgi?mode=sno_info&id=Homo_sapiens300697). However, we\nacknowledge that other databases such as snoDB and snoRNA Atlas indeed list\nbioinformatically predicted target sites for SNORA49 in 28S rRNA. We have therefore\nrevised our statement to: “However, to date, there has been no validated target rRNA sites\nby SNORA49, which was consistent with our observations…”.\n3.Lines 238–239: “Recent studies have shown that snoRNAs exert their functions by\nbinding to various proteins.”This phrasing remains unclear. If you are referring to non-\ncanonical (non-snoRNA) functions, please rephrase accordingly. For example:“Recent\nstudies have shown that some snoRNAs exert non-canonical functions through\ninteractions with various proteins.”Alternatively, omit the “Recent studies” phrase\naltogether and revise to:“snoRNAs exert their functions through interactions with various\nproteins.”\nAnswer: This is a good point. We have revised it to “Recent studies have shown that\nsome snoRNAs exert non-canonical functions through interactions with various proteins.”\n4.Line 575: Please specify the lysing component in the lysis buffer (10 mM Tris pH 7.4, 140\nmM NaCl, 1.5 mM MgCl₂, 1× protease inhibitor cocktail). Is there a detergent or\nmechanical lysis involved?\nAnswer: The lysing components are 1% NP-40 and 0.25% sodium deoxycholate.\nNo additional detergents were added and no mechanical lysis was performed. We stated\nit in the Methods section."}]

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