Hyaluronan catabolism supports the peritoneal disseminated metastasis of cancer through the glucuronic acid pathway

Hyaluronan catabolism supports the peritoneal disseminated metastasis of cancer through the glucuronic acid pathway | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Hyaluronan catabolism supports the peritoneal disseminated metastasis of cancer through the glucuronic acid pathway Yi Shi, Jie Shi, Min Guo, Siyu Zuo, Jixuan Ding, Weiao Qu, Shuo Wang, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7691213/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract When disseminated into the peritoneal cavity at the very early stage, cancer cells must adapt to the glucose- and oxygen-limited environment in peritoneal fluid. To investigate the molecular mechanisms enabling this adaptation, we conducted a genome-wide CRISPR/Cas9 knockout screening in an orthotopic ovarian cancer (OC) model. We identified a series of genes involved in hyaluronic acid (HA) catabolism and glucuronic acid (GlcA) metabolism, including the HA receptor LAYN, HA catabolism enzymes (including HYAL1 and HYAL3) and key GlcA metabolic enzymes (such as AKR1A1 and XYLB). By integrating transcriptomic and metabolic analyses in multiple experimental systems, we demonstrated that HA induced the expression of key HA catabolism and GlcA pathway enzymes, which further led to the release of free GlcA from HA degradation. This GlcA is subsequently metabolized through the GlcA pathway, the pentose phosphate pathway (PPP) and glycolysis to support the maintenance and growth of disseminated OC cells. In addition, we found an atypical Rho GTPase RHOU facilitated the LAYN endosomal recycling for efficient HA uptake. Intriguingly, the rewiring of HA catabolism through GlcA pathway was regulated by its classical receptor CD44 and occurred in other peritoneal disseminating cancers such as bladder cancer and pancreatic adenocarcinoma. Importantly, pharmacological inhibition of HYAL1 with garcinol potently suppressed peritoneal disseminated metastasis in xenograft mice and synergized with cisplatin. In this study, we collectively reported a novel metabolic reprogramming feature of the early peritoneal disseminated cancer cells, which provides new diagnostic and therapeutic strategies for the cancers prone to the potential dissemination. Biological sciences/Cancer/Cancer metabolism Biological sciences/Cancer/Metastasis Biological sciences/Cell biology/Cellular imaging Metabolic Reprogramming Hyaluronan Catabolism Glucuronic Acid Pathway Peritoneal Metastasis LAYN Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Ovarian cancer (OC) represents the most lethal gynecological malignancy, with its high mortality rate largely attributed to its special transcoelomic metastatic mechanism ( 1 , 2 ). A key challenge is understanding how disseminated tumor cells survive during early metastasis, as they must overcome matrix detachment stress and adapt to the nutrient-deprived peritoneal microenvironment while maintain proliferative capacity ( 3 – 5 ). Emerging evidence highlights that metabolic adaptations, particularly through alterations in glucose metabolism, lipid utilization and mitochondrial function( 6 – 8 ), are critical for successful metastasis. The peritoneal metastatic niche has dual metabolic challenges: hypoxia enforces glycolytic dependence via HIF-1α stabilization ( 9 ), while nutrient scarcity drives alternative pathway utilization including glutaminolysis and fatty acid oxidation to meet the bioenergetic and biosynthetic demands ( 6 , 7 ). These metabolic adaptation occurs in concert with extensive extracellular matrix (ECM) remodeling, where increased deposition of collagen, fibronectin and proteoglycans creates both structural support and pro-metastatic signaling ( 10 ). The intricate interplay between nutrient scarcity, metabolic adaptation and ECM remodeling establish a permissive niche for tumor cell maintenance and dissemination. Central to this ECM reorganization is hyaluronic acid (HA), a key structural component whose role in signaling transduction and tumor promotion is well-documented ( 11 ). HA exhibit a striking molecular weight-dependent duality: high-molecular-weight HA (HMW-HA; >1000 kDa) supports tissue homeostasis and exerts tumor-suppressive effects, while low-molecular-weight fragments (LMW-HA; <500 kDa) which generated through hyaluronidase activity, potently promote tumor progression ( 12 , 13 ). This shift is orchestrated by altered expression of HA synthases (particularly HAS2) and hyaluronidases (HYAL1/2) ( 14 , 15 ), creating an autocrine loop that sustains malignant phenotypes ( 16 ). Beyond its structural and signaling roles, HA also serves as a metabolic substrate. HA catabolism generates two key metabolites: N-acetylglucosamine (GlcNAc), which can feed into the hexosamine biosynthetic pathway (HBP) to regulate critical protein modifications ( 16 ), and glucuronic acid (GlcA) that is able to enter central carbon metabolism through an evolutionarily conserved pathway. Interestingly, GlcA metabolism shows species-specific divergence. In non-primate mammals, GlcA can be converted to L-ascorbic acid (vitamin C) ( 17 ), while primates have developed a unique CRYL1-dependent route that converts GlcA to xylulose-5-phosphate, namely GlcA pathway, directly linking HA degradation to the pentose phosphate pathway ( 18 – 21 ). We hypothesized that this metabolic shift may provide crucial survival advantages when early disseminated cancer cells spread into a glucose- and oxygen-limited, yet HA-rich peritoneal microenvironment. However, its biological significance and underlying mechanisms for a successful transcoelomic metastasis remained a fundamental unanswered question. To address this question, we performed a genome-wide CRISPR/Cas9 knockout screen in the orthotopic murine model of OC to identify key genes supporting the peritoneal dissemination. We identified critical genes involved in HA uptake and catabolism, together with genes involved in the GlcA pathway. By investigating the dynamic interplay between HA-mediated extracellular signaling and intracellular metabolic reprogramming, we demonstrated that HA-derived GlcA served as a key substrate for the pentose phosphate pathway (PPP) and glycolysis in peritoneal disseminated cancer cells. This metabolic rewiring facilitated the maintenance and growth of disseminated cancer cells in the early stages of metastasis, highlighting the multiple essential roles of HA not only as a structural component of ECM but also a metabolic regulator and energy reservoir. Our findings suggest that targeting the HA -GlcA -PPP axis may offer a novel diagnostic and therapeutic strategy for preventing and treating cancers with peritoneal disseminated metastasis features. Results Genomic-wide CRISPR knockout screening reveals the potential role of LAYN-mediated HA catabolism in the early peritoneal dissemination of OC. We previously identified key genes involved in the intraperitoneal dissemination of OC to the peritoneal organs, including intestines, omentum and the peritoneum, through a genome-wide CRISPR/Cas9 knockout screening in the orthotopic xenograft mouse model of OC ( Supplementary Fig. 1A and Supplementary Table 1 ) ( 22 ). Of note, MAGeCK analyses revealed 3 genes ( LAYN, AGBL3 and GABRB1 ) showing significant negative enrichment in metastases from all three sites (Fig. 1 A and 1 B). We were especially interested in the novel HA receptor LAYN because some other key enzymes involved in HA catabolism and the recovery of its product GlcA into the PPP or glycolysis were also enriched (Fig. 1 A and 1 C), such as HYAL1 and HYAL3 (responsible for the degradation of high-molecular-mass HA polymers to HA tetrasaccharides), HEXB (the β subunit of the lysosomal enzyme β-hexosaminidase that catalyzes the degradation of N-acetyl-hexosamine-containing molecules), AKR1A1 (catalyzing the reduction of D-glucuronate to L-gulonate) and XYLB (a xylulokinase that converts L-gulonate-derived D-xylulose to PPP metabolite D-xylulose-5-phosphate). Given the disseminated OC cells at the early stage spread throughout the peritoneal cavity by normal HA-rich peritoneal fluid ( 23 ), these results suggested a potential role of the metabolic reprogramming of HA catabolism through the glucuronic pathway to PPP and glycolysis in the intraperitoneal dissemination of OC. To further investigate the reprogramming of HA metabolism in the early stage of intraperitoneal spread of OC cells, we injected GFP-transfected ID8 cells into the peritoneal cavity and isolated the GFP-positive ID8 cells from the peritoneal fluid at day 1, day 14 and day 21, when the disseminated cells adapted and survived in the peritoneal environment (Fig. 1 D) ( 24 ). The transcriptomic analyses on these cells revealed that at day 1, the HA receptor CD44, hyaluronidase Hyal2 and GlcA pathway enzymes ( Akr1a1, Dcxr, Sord and Xylb ) were highly expressed, while the HA catabolism enzymes (such as Layn, Hyal1, Hyal3, Hexa and Hexb ) and key GlcA pathway enzyme Cryl1 were upregulated through day 14 to day 21 (Fig. 1 E). The expression of major enzymes involved in the PPP, glycolysis and TCA cycles were relatively high at day 1 and declined through day 14 to day 21; however, Prps2 and Shpk in PPP and Pfkm, Gapdhs, Eno2 and Ldhb/Ldhd in glycolysis were upregulated at day 21, which were able to increase the flux of PPP metabolites into glycolysis for energy production (Fig. 1 E). The dynamic alterations in the expression of these key enzymes through day1 to day 21 were further confirmed by RT-qPCR (Fig. 1 F). In addition, the IHC analyses of paired OC tissues from the primary sites and peritoneal disseminated sites from five high-grade serous ovarian cancer (HGSOC) patients also showed the significantly increased expression of LAYN, HYAL1, AKR1A1 and CRYL1 in disseminated OC cells (Fig. 1 G). Meanwhile, the expression of above genes was positively correlated with the poor survival of OC patients according to the transcriptomic analysis of 349 OC patients from the cancer genome atlas (TCGA) database ( Fig. S1 B and Supplementary Table 2 ). And in another OC cohort (567 samples from 34 patients) from spatial profiling for studying the early dissemination ( 25 ), a significant upregulation of LAYN and HYAL3 was also observed during the transition from stage IC to stage IIA and III when OC disseminates across the abdominal cavity to abdominal organs ( Fig. S1 C ). Given that HA-rich and glucose-deficient feature of peritoneal environment also challenges the survival of other types of cancers with peritoneal disseminated metastasis trend, such as the bladder cancer (BLCA) and pancreatic adenocarcinoma (PAAD), we investigated the possible reprograming of HA catabolism in these cancer types. As shown in Fig. S2 A , within 14 days post-intraperitoneal injection of either BLCA cells MB49 or Kras-mutated PAAD cells KPC, the key HA catabolism genes (i.e., Layn, Hyal1 and Hyal3 ) and GlcA pathway genes (i.e., Akr1a1, Cryl1, Dcxr and Xylb ) were significantly upregulated. Consistently elevated expression of these genes (especially LAYN, HYAL1, AKR1A1, SORD , and XYLB ) were observed during the stages when cancer cells disseminated away from the primary site in both BLCA ( 26 ) and PAAD ( 27 ) patient cohorts ( Fig. S2 C ), and higher expression of these genes correlated with poor survival of OC, BLCA and PAAD patients ( Fig. S2 D ). These results suggested that the rewiring of HA catabolism to GlcA pathway was potentially a common feature for the peritoneal dissemination of human cancers. HA catabolism fuels OC cell survival and proliferation. To investigate whether HA catabolism and GlcA pathway are able to be induced in HA-rich and glucose-low environment, OC cell lines were cultured in high glucose (25 mM), low glucose (2.5 mM) and HA-supplemented low glucose medium. RT-qPCR results showed that HA catabolism and GlcA pathway genes were upregulated in HA-rich and glucose-low medium, as well as GAPDHS, LDHB and PRPS2 in glycolysis and nucleotide synthesis pathways (Fig. 2 A, Fig. S2 B ). Similar results were observed in patient-derived ovarian cancer organoids cultured in HA-rich and glucose-low medium (Fig. 2 B and 2 C). Notably, 100–200 kDa HA induced HA catabolism and GlcA pathway genes more efficiently within 48 hours, while 30–40 kDa and 40–100 kDa HA exhibited stronger effects at 72 hours ( Fig. S3 A ). Western blot results confirmed the significant upregulation of LAYN, HYAL1 and CRYL1 expression under HA-rich and glucose-low environment within 72 hours (Fig. 2 D). Further metabolomic analysis showed HA replenishment in low glucose environment resulted in significant increase of the key PPP metabolites 6-phosphogluconate, sedoheptulose 7-phosphate and erythrose 4-phosphate and glycolysis metabolites glucose 6-phosphate and lactate (Fig. 2 E and Supplemented Table 3 ). The elevated PPP metabolism was also confirmed by the increased synthesis of nucleotides and their derivatives (Fig. 2 E). To track the metabolic flux of HA to PPP and glycolysis, we cultured the OVCAR-8 cells in low glucose medium complemented with 13 C-labeled GlcA for 72 hours, the MS analysis showed that the GlcA-derived 13 C enriched in metabolites of glycolysis and PPP-nucleotide synthesis pathway, which were able to be attenuated by silencing CRYL1, the key enzyme in the GlcA pathway (Fig. 2 F and 2 G). Transcriptomic analysis of intraperitoneal injected ID8 cells (Fig. 1 D) also showed increased cell surface receptor-associated gene sets at day 14 and increased synthesis of nucleotide-containing compound at day 21, while the global protein metabolism was inhibited through day 14 to day 21 ( Fig. S3 B and S3C ). And interestingly, the hexosamine biosynthetic pathway was partially suppressed ( Fig. S3 D ), suggesting OC cells might redirect β-N-acetylglucosamine (NAG) from HA degradation to glycosylation, thereby conserving energy otherwise required for de novo NAG synthesis under glucose limitation. Taken together, these results highlighted a rewired HA metabolism, in which HA degradation derived GlcA was able to be converted to xylulose 5-phosphate through GlcA pathway to fuel the PPP, glycolysis and nucleotide metabolism to meet the energy and substance demand of intraperitoneal disseminated OC cells at the early stage (Fig. 2 H). To further investigate the biological significance of rewired HA catabolism for OC cells under low glucose environment, we measured cell proliferation in media supplemented with different concentrations of glucose, HA and HA metabolites. We observed that HA was able to support the slow proliferation of OC cells in low glucose medium as well (Fig. 2 I). Interestingly, the role of HA to support OC cell proliferation under low glucose condition can be largely mimicked by GlcA, but not NAG (Fig. 2 I). Notably, the degradation of endogenous HA in OC cells under low glucose condition started from the fourth day ( Fig. S3 E ), coinciding with the onset of proliferation changes, suggesting that HA catabolism was a prerequisite for sustaining cell proliferation. HA or GlcA, but not NAG, also sustained the clonal formation of ID8 and OVCAR-8 cells under low glucose environment (Fig. 2 J). These findings collectively suggested that HA catabolism serves as a compensatory energy source to sustain OC cell survival under glucose deprivation, with GlcA acting as a critical intermediate. LAYN is essential for HA-sustained early intraperitoneal dissemination of OC. As a novel HA receptor, the role of LAYN in HA catabolism keeps largely unknown. We firstly investigated its role in the uptake of HA. Overexpression of Layn (Layn-OE) in ID8 cells dramatically promoted the uptake of FITC-conjugated HA (Fig. 3 A and S4A). In addition, to investigate the role of Layn in supporting the maintenance and growth of early disseminated OC cells, we injected the same amount of Layn-OE (EGFP-labeled) and control (mCherry-labeled) ID8 cells into the peritoneal cavity of mice to compare their capacities to survive in peritoneal environment (Fig. 3 B). One day post-inoculation, Layn-OE ID8 cells and control cells remained alive at the equal ratio (Fig. 3 C and 3 D). However, through day 1 to day 7, both cells were gradually eliminated, with the number of control cells reduced much faster than Layn-OE cells, ending up with more Layn-OE cells survived. From day 7 to day 21, Layn-OE cells showed significantly accelerated proliferation within the peritoneal cavity compared to control cells (Fig. 3 C and 3 D). Consistently, knocking down LAYN in OVCAR-8 cells dramatically reduced the uptake of HA (Fig. 3 E and S4B). In low glucose medium, knocking down Layn significantly inhibited HA-sustained proliferation and colony formation of ID8 and OVCAR-8 cells (Fig. 3 F, 3 G, S4H and S4I), whereas no significant differences were observed in glucose-rich medium ( Fig. S4 C-4G ). In the orthotopic murine model of OC established by the intrabursal injection of ID8 or OVCAR-8 cells, knocking down Layn not only significantly inhibited the growth of primary tumor (Fig. 3 H and S4J), but also dramatically reduced the formation of malignant ascites (Fig. 3 I) and the number of metastatic tumor nodules in the peritoneal cavity (Fig. 3 J and S4K). Collectively, these findings identified LAYN as a key mediator of HA uptake, enabling OC cell survival and dissemination in glucose-deprived, but HA-rich environment. RHOU facilitates the endosomal recycling of LAYN for the efficient uptake of HA. To define how LAYN mediates HA uptake, we searched the BioGRID database ( https://thebiogrid.org/126823 ) and identified a potential interaction between LAYN and RHOU (Ras homolog family member U) ( 28 ), which is an atypical Rho GTPase that regulates endosomal recycling—a pathway critical for HA internalization. The human LAYN has two isoforms generated by alternative splicing, with the long isoform (LAYN-Long, LAYN-L ) carrying an additional 7-amino-acid fragment at its N-terminal compared with the short isoform (LAYN-Short, LAYN-S ) ( Fig. S5 A ), among which LAYN-L expression was able to be induced by HA in OVCAR-8 cells cultured in low glucose medium ( Fig. S5 B ). In addition, LAYN-L-substituted OVCAR-8 cells proliferated faster in HA-supplemented, glucose-low medium than LAYN-S-substituted cells ( Fig. S5 C and S5D ). Coimmunoprecipitation (Co-IP) assays showed that LAYN-L had stronger interaction with RHOU than LAYN-S (Fig. 4 A and 4 B), which could be enhanced by HA (Fig. 4 C). Proximity ligation assays (PLA) further confirmed HA-enhanced interaction between LAYN-L and RHOU (Fig. 4 D and 4 E). To investigate the whole process of LAYN-mediated endocytosis of HA, we transfected OVCAR-8 cells with mCherry-labeled LAYN (LAYN-mCherry) and BFP-labeled RHOU (RHOU-BFP). In low glucose medium, time-course imaging revealed the rapid colocalization of LAYN, RHOU, and HA within 45 minutes the addition of HA (Fig. 4 F), and in LAMP1-EYFP-cotransfected cells the LAYN/RHOU-facilitated endocytic trafficking of HA to lysosomes was clearly observed ( Fig. S5 E ). Knocking down RHOU impaired the localization of LAYN to EEA1-labeled early endosome (Fig. 4 G, S5F and 5 G) as well as RAB11-positive recycling vesicles (Fig. 4 H). This led to lysosomal degradation of LAYN, which was rescued by chloroquine (CQ), a lysosomal acidification inhibitor (Fig. 4 I and S5H), while the mRNA level of LAYN was not affected ( Fig. S5 I ). Consistently, RHOU silencing abolished the pro-survival and proliferative advantages conferred by LAYN overexpression in OVCAR-8 cells, as evidenced by diminished HA-dependent colony formation (Fig. 4 J), cell proliferation (Fig. 4 K) and BrdU incorporation (Fig. 4 L) assays. These results demonstrated that RHOU-mediated endosomal recycling of LAYN was critical for HA internalization and hence HA-fueled OC cell proliferation. GlcA pathway bridges HA-degradation-derived GlcA to PPP and glycolysis for the early peritoneal dissemination of OC. Our in vitro and ex vivo experiments have suggested that HA-catabolism-derived GlcA is able to fuel PPP and glycolysis through the GlcA pathway (Fig. 1 E and Fig. 2 E- 2 G). To determine whether GlcA is essential for HA-supported early peritoneal dissemination of OC in nutrient-deficient environment, we firstly assessed the effects of GlcA and its downstream metabolite D-xylulose (Xul) in GlcA pathway on supporting the proliferation of LAYN-depleted tumor cells in low glucose medium. Given that the complete degradation of 0.1 mg/mL of HA (40–100 kDa) would yield around 0.1–0.25 mM GlcA, a concentration as reported for HA turnover in tumor microenvironments ( 29 , 30 ), we tested wether GlcA or Xul (≥ 0.25 mM) could compensate the role of HA in supporting the proliferation of OC cells whose HA uptake were blocked by silencing LAYN. The colony formation assays and cell proliferation assay confirmed that 0.25 mM GlcA fully restored proliferation in LAYN-depleted OVCAR-8 cells (Fig. 5 A and 5 B) and ID8 cells ( Fig. S6 A and S6B ), and the same results were also observed when 0.25 mM of Xul was supplemented (Fig. 5 C, 5 D, S6C and S6D). Notably, while Xul-fueled proliferation remained unaffected, GlcA-dependent cell proliferation was entirely abolished by knocking down CRYL1 (Fig. 5 E- 5 G), consistent with the role of CRYL1 role in converting GlcA to Xul and linking the GlcA pathway to PPP and glycolysis (Fig. 1 C and Fig. 2 H). In the experimental dissemination murine model of OC (Fig. 5 H and 5 I), Cryl1 deletion completely blocked LAYN-mediated peritoneal metastasis (Fig. 5 J and 5 K), further suggesting the critical role of GlcA pathway in bridging HA catabolism to PPP and glycolysis to support OC progression. The HA-CD44 signaling axis induces the HA catabolism and GlcA pathway to support the early peritoneal disseminated metastasis of OC. To get further insights into how HA induced the expression of key HA catabolism and GlcA pathway genes (Fig. 2 A and 2 B), we investigated the canonical HA-CD44 signaling axis. While CD44 expression showed only slightly upregulation in peritoneal disseminated OC compared to primary tumors of OC patients ( Fig. S7 A ), we did not observe stage-dependent alterations of CD44 expression or its correlation with the survival rate in TCGA data ( Fig. S7 B and SC ), suggesting that the role of CD44 in tumor progression might not be regulated not at the transcriptional level. In CD44-silenced OC cells, HA-supported cell proliferation and colony formation were dramatically inhibited (Fig. 6 A- 6 C). Given the role of HA-CD44 signaling axis in the regulation of cancer stemness-related genes ( 30 , 31 ), we investigated whether HA catabolism-related genes were also targets of this signaling axis. Knocking down CD44 strongly abolished HA-induced expression of both HA catabolism genes and GlcA signaling genes as shown by RT-qPCR analyses (Fig. 6 D) and western blot analysis (Fig. 6 E). The regulation was further supported by the positive correlation between CD44 and these metabolic genes in TCGA database (Fig. 6 F). It has been reported that CD44 cleavage acts as an amplifier of oncogenic signaling to cause the phosphorylation and activation of CREB( 32 ), and increased phosphorylation of CREB was observed followed by the addition of HA in low glucose media in OC cells (Fig. 6 E). We further analyzed the promoters of LAYN and HYAL1 genes and found the predicted binding elements CRE for the transcription factor CREB, which was able to be activated by HA-CD44 signaling (Fig. 6 G). The luciferase reporter assay showed that promoters of LAYN and HYAL1 were able to be activated by HA in a CD44-dependent manner (Fig. 6 G), while deletion of the CRE element dramatically attenuated the responsiveness of these promoters to HA (Fig. 6 H). Consistently, in the experimental dissemination murine model of OC, knocking down CD44 dramatically reduced the formation of malignant ascites and the number of disseminated tumor nodules in the peritoneal cavity (Fig. 6 I-K), which was able to be partially reversed by reconstituting HA catabolism through ectopic expression of Layn, Hyal1 and Cryl1 (Fig. 6 I-K), suggesting HA-CD44 signaling as the major driver of GlcA pathway-dependent metastasis. In tumor tissues from the patients, the correlation of p-Creb (activated by HA-CD44 axis) with LAYN and HYAL1 expression were further confirmed (Fig. 6 L). Interestingly, the expression of CD44 was also induced in OC patient-derived organoids and peritoneally inoculated cancer cells ( Fig. S7 D-G ), suggesting a possibly positive feedback loop regulating HA-sourced energy metabolism. HYAL1 inhibitor garcinol suppresses the peritoneal disseminated metastasis. Given the essential role of HA catabolism and GlcA pathway in fueling the peritoneal disseminated metastasis, targeting these metabolic pathways might offer a therapeutic strategy against peritoneal metastasis. We thus focused on two key enzymes: HYAL1, which is pharmacologically inhibited by the natural compound garcinol ( 33 ), and DCXR which catalyzes the conversion of L-xylulose to xylitol, a critical step in D-xylulose generation, and has been reported to be inhibited by niacin (vitamin B3)( 34 ) and butyrate ( 35 ). Silencing HYAL1 completely abolished HA-sustained proliferation and clonogenicity in OC cells, while knocking down DCXR exerted partial inhibition ( Fig. S8A-S8F ), confirming HYAL1 as a better target. We prepared the recombinant active HYAL1 protein with K m value around 243.2 nM (Fig. 7 A), against which garcinol showed potent inhibitory activity with IC50 around 4.5 nM (Fig. 7 B). In low glucose medium, HA-supported proliferation and the colony formation of OC cell ID8, BLCA cell MB49 and PAAD cell KPC were strongly inhibited by garcinol, which could be rescued by the GlcA supplementation, confirming the anti-tumor effect of garcinol was predominantly mediated through the inhibition of HYAL1 (Fig. 7 C and 7 D). In the experimental dissemination murine model of OC, treatment with garcinol, niacin, and butyrate all reduced the formation of malignant ascites and peritoneal tumor nodules ( Fig. S8G and S8H ). However, niacin and butyrate caused slight weight loss ( Fig. S8I ), especially for niacin-treated mice with severe intestinal torsion being observed. In contrast, garcinol showed no toxicity, supported by histopathological and blood biochemistry analyses ( Fig S8J and Supplementary Table 4 ). Garcinol also strongly inhibited the peritoneal disseminated metastasis in the murine models of BLCA and PAAD (Fig. 7 E and 7 F). Given that HA catabolism-derived GlcA was able to fuel the PPP for the de novo biosynthesis of nucleotides that might contribute to DNA damage repair (Fig. 2 C and 2 E), we hypothesized that this pathway probably enhanced resistance to genotoxic agents such as cisplatin, a first-line therapy for OC. In an OC cohort ( http://www.rocplot.com/ ) ( 36 ), platinum non-responders exhibited elevated expression of HA catabolism–GlcA pathway genes (Fig. 7 G), which was able to be used to predict treatment response (AUC = 0.696; Fig. 7 H). Consistently, in the murine model of OC, combined treatment with garcinol and cisplatin showed synergistic effects on suppressing the peritoneal dissemination of cancer cells than single treatment with either one (Fig. 7 I- 7 K). Discussion Peritoneal metastasis represents one of the most common form of distant metastases in numerous cancers and is a major contributor to treatment failure and high mortality rates ( 5 ). Yet, the mechanisms through which cancer cells adapt to the unique peritoneal microenvironment remain poorly understood. In this study, we demonstrated that OC cells could utilize HA as an alternative energy source in the glucose-limited peritoneal environment and this metabolic adaptability extends beyond OC cells to BLCA and PAAD cell. We further identified a hierarchical signaling-metabolic axis initiated by the canonical HA receptor CD44. Its activation leads to upregulation of the novel HA receptor LAYN, hyaluronidases (HYAL1) and key enzyme in GlcA pathway. The degraded HA releases GlcA, which is then channeled through the GlcA pathway to fuel the PPP and glycolysis, thereby sustaining the maintenance and growth of disseminated cancer cells (Fig. 8 ). Our findings reveal a critical metabolic adaptation mechanism and point to a promising therapeutic strategy for inhibiting peritoneal metastasis. The functional role of HA is highly context-dependent, exhibiting diverse and often opposing effects across different pathological conditions. In glioblastoma multiforme, HAS2-mediated HA secretion enhances tumor cell proliferation and migration ( 37 ), while HYALs (particularly HYAL1)-catalyzed HA degradation promotes breast cancer xenograft growth and angiogenesis ( 38 ). Beyond cancer, HA serves as a critical carbon source for mycobacterial growth, highlighting its exploitation by pathogens ( 39 ). Notably, the role of HA as a metabolic substrate to support the specific pressures of peritoneal metastasis remains poorly understood. Our study directly addresses this gap by investigating how peritoneal-disseminated tumor cells metabolically exploit HA. We found that OC cells catabolize HA to GlcA, which is channeled into GlcA pathway and PPP, to fuel glycolysis, highlighting their remarkable metabolic plasticity to meet bioenergetic demands and drive metastasis. Specifically, by performing transcriptomic analyses on cancer cells isolated from the peritoneal metastatic niche we observed a dynamic upregulation of the HA-GlcA metabolic pathway. Metabolomic profiling on cancer cells supplemented with HA further confirmed that HA supplementation significantly elevated the levels of key PPP intermediates. Functional validation using 13 C-labeled GlcA tracing demonstrated that GlcA-derived carbon enters central carbon metabolism, a process dependent on CRYL1. This metabolic rewiring was further corroborated in patient-derived organoids and multiple OC cell lines, where HA stimulation robustly induced the expression of GlcA pathway genes under low glucose conditions. These findings reinforce the concept that metabolic reprogramming is a cornerstone of cancer progression, with HA emerging as a versatile substrate under nutrient stress. HA signaling is mediated through multiple receptors, including CD44, RHAMM, LYVE-1, and the more recently identified Laylin (LAYN) ( 30 , 40 ). CD44, a non-kinase transmembrane glycoprotein, frequently undergoes alternative splicing, generating variants that contribute to cancer development and progression ( 41 ). As a key marker of cancer stem cells, CD44 promotes tumor initiation, therapy resistance, and metabolic reprogramming via activation of PI3K/AKT and MAPK pathways ( 42 – 45 ). RHAMM promotes pancreatic tumor progression through EGFR signaling, while LYVE-1, which predominantly expressed in lymphatic vessels, facilitates cell proliferation and lymph angiogenesis upon HA binding ( 46 ). LAYN, identified as an HA-binding receptor in 2001, has been implicated in colorectal cancer metastasis but remained unexplored in OC( 47 ). Our CRISPR screen uniquely identified LAYN as a metastasis-specific dependency in OC. Further mechanistic studies revealed that internalization of HA is mediated by a RHOU-dependent endocytic pathway linked to LAYN, which facilitates efficient HA uptake and supports GlcA-driven glycolysis under nutrient stress. Moreover, loss of LAYN impaired both HA uptake and degradation, thereby failing to maintain OC cells in early dissemination into peritoneal. Although CD44 was not a top hit in our screen, its ablation also compromised the ability of HA to sustain cell survival, suggesting that CD44 may possess additional roles beyond functioning as an endocytic receptor for HA, especially LAYN. Previous studies have shown that CD44 activation could regulate the expression of metabolism-related genes via phosphorylation of CREB ( 48 ). We further elucidated the role of CD44 in this process and found that it primarily regulates the transcription of HA metabolic genes. Luciferase reporter assays confirmed that HA-induced activation of LAYN and HYAL1 promoters is CD44-dependent and requires intact CREB-binding sites. Importantly, reconstitution of LAYN, HYAL1, and CRYL1 in CD44-deficient cells partially restored metastatic potential in vivo, underscoring the functional hierarchy within the HA-CD44-LAYN metabolic axis. However, given its broad functional roles and the frequent discordance between its transcriptional and protein expression in our research, we prioritized HA catabolic pathway as a more specific and druggable target for inhibiting HA-dependent tumor survival, rather than CD44. By systematically mapping the HA metabolic pathway from HA biosynthesis, receptor-mediated uptake and its enzymatic degradation, we identified several potential nodes for disrupting early metastatic dissemination. Our initial approach to pharmacologically inhibit HAS2—the rate-limiting enzyme in HA synthesis, using 4-methylumbelliferone (4-MU) failed to suppress intraperitoneal HA accumulation (data not shown). Notably, emerging evidence positions 4-MU's anti-tumor effects primarily through thymidine phosphorylase inhibition rather than HAS2 blockade ( 49 ). We therefore systematically interrogated the degradation branch of HA metabolism and identified two key enzymatic targets: HYAL1, the major hyaluronidase responsible for HA breakdown, and DCXR (dicarbonyl/L-xylulose reductase), which catalyzes the conversion of L-xylulose to D-xylulose. Functional comparison via in vitro knockdown experiments revealed that genetic silencing of HYAL1 more potently abrogated HA-sustained tumor proliferation compared to DCXR depletion, establishing HYAL1 as a superior therapeutic target. We subsequently evaluated small-molecule inhibition of these targets in vivo. Although previous studies identified Garcinol, a xanthonoid natural product, as a nanomolar-range inhibitor of HYAL1 and some endogenous metabolites including butyrate and niacin (Vitamin B3) as inhibitors of DCXR ( 33 , 34 , 50 , 51 ), the in vivo efficacy of targeting this pathway remained unexplored. Distinct from in vitro results, xenograft experiments confirmed that three distinct small-molecule inhibitors targeting these enzymes potently suppressed disseminated OC metastasis. Notably, garcinol demonstrated a highly favorable biosafety profile. What’s more, consistent with report that tumors with peritoneal metastases share a metabolic microenvironment ( 52 ), garcinol potently suppressed peritoneal dissemination not only in OC but also in BLCA and PAAD, highlighting a conserved metabolic vulnerability across malignancies with peritoneal tropism. Strikingly, the synergy with cisplatin arised from dual targeting of HA-fueled metabolic adaptation (via HYAL1 blockade) and DNA integrity (via cisplatin), effectively disrupting both energy homeostasis and genomic stability in disseminated tumor cells. Our findings position HYAL1 inhibition as a complementary strategy to conventional chemotherapy to impede early metastatic colonization. Further studies should delineate whether HA catabolic rewiring modulates cisplatin sensitivity, potentially guiding rational combinations for clinical translation. In summary, our study revealed that peritoneal-metastasized tumor cells activate a CD44–LAYN-mediated metabolic pathway to generate HA into GlcA, which fuels glycolysis and PPP under glucose-limited conditions, supporting metastatic growth. This highlights the metabolic flexibility of disseminated tumor cells within the peritoneal niche. Moreover, we uncovered the conserved role of HA catabolism across multiple cancer types with peritoneal tropism, providing new insight into microenvironment-driven metabolic adaptation. Importantly, pharmacological inhibition of HYAL1 with garcinol effectively suppressed HA-driven metastasis and enhanced cisplatin response in vivo. Therefore, targeting the HA-GlcA metabolic axis represents a promising therapeutic strategy to inhibit peritoneal dissemination and improve outcomes for patients with advanced OC and other peritoneal metastases. Materials and Methods The CRISPR-Cas9 library screen in the murine model of OC A genome-wide CRISPR-Cas9 screen was performed using the GeCKO-v2 human library (Addgene) developed by Feng Zhang’s lab, which comprised 122,756 sgRNAs targeting 19,050 protein-coding genes, 1,864 miRNAs, and 1,000 non-targeting controls. For the ovarian cancer model, SK-OV-3 cells were transduced with lentiviral particles at an MOI of 0.3-0.5 to ensure single-gene perturbations, followed by puromycin (Sigma-Aldrich) selection. After 14 days of in vitro expansion, 2×10⁶ sgRNA-expressing cells were orthotopically injected into NOD-SCID mice (SPF Biotechnology, Beijing, China) (n=3) via intrabursal implantation. Tumor tissues from primary and metastatic sites (including peritoneal nodules, ascites, and abdominal wall lesions) were harvested after 30-40 days, dissociated with collagenase, and expanded in culture. This in vivo selection process was repeated for three cycles to enrich metastasis-associated clones. Following the final round, genomic DNA from both primary (first-round) and metastatic (third-round) populations was extracted using the TIANamp Genomic DNA Kit (TIANGEN) for sgRNA amplification and deep sequencing. MAGeCK-VISPR was used to identify significantly enriched sgRNAs. Analysis of OC patient samples Primary tumors and matched metastatic lesions samples were collected from patients diagnosed with high serous ovarian adenocarcinoma at Tianjin Center Hospital of Gynecology Obstetrics in 2022 (n=5). All participants provided informed consent, and the study was conducted in compliance with ethical guidelines approved by the Institutional Review Boards of Nankai University and Tianjin Center Hospital (Ethics Approval No.: NKUIRB2023168) in accordance with the Declaration of Helsinki. Fresh tissue samples, including primary ovarian tumors and peritoneal metastases were surgically resected and processed immediately. Each specimen was divided for multiple analyses—one portion fixed in 4% paraformaldehyde for immunohistochemical (IHC) evaluation, while another was preserved in TRIzol reagent for other assays. Histopathological classification and clinical staging were independently verified by experienced pathologists and oncologists. The murine models of OC All experimental protocols involving animals were reviewed and approved by the Institutional Animal Ethics Committee of Nankai University (Ethic approved number: 2023-SYDWLL-000634). To establish orthotopic ovarian tumor models, female immunodeficient (NOD-SCID) or immunocompetent (C57BL/6) mice aged 6 weeks were anesthetized for surgical implantation. Human OVCAR-8 cells (5×10 6 cells in 20 μL PBS) or murine ID8 cells (2×10 ^ 6 cells in 10 μL PBS) were microinjected into the right ovarian bursa. Tumor progression was monitored for 120 days (OVACR-8) or 60 days (ID8) post-implantation before terminal analysis. For the metastatic dissemination model, syngeneic C57BL/6 mice received intraperitoneal injections of 2×10 ^ 6 ID8 GFP cells or equal number of ID8 Vec/LAYN-OE labled with different color suspended in 100 μL PBS. The abdominal fluid was washed out with PBS for flow cytometry analysis or sorting. For in vivo therapeutic assays, syngeneic C57BL/6 mice received intraperitoneal injections of 2×10 ^ 6 luciferase-labeled ID8/KPC/MB49 cells. Mice were randomly divided into different group (n=5~6) at day 5 post injection. For the OC model, the mice were intraperitoneal injected with vehicle/ Garcinol (1 or 3 mg/kg,)/ cisplatin (5 mg/kg)/ butyrate (100 or 300 mg/kg) / niacin (50 or 150 mg/kg) every 3 days from day 7 to day 60 post-injection. For other tumor model, the mice were intraperitoneal injected with vehicle/ Garcinol (1mg/kg) from day 3 to day 30 post-injection. Cell culture SK-OV-3 cell line and HEK 293T were purchased from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). OVCAR-8 cell line was purchased from American Type Culture Collection. ID8 and MB49 cell lines were purchased from Merck (Darmstadt, Germany). KPC cell line (Cat. NO. NM-YD04) was purchased from Shanghai Model Organisms Center, Inc. KPC, ID8, MB49, KPC1199 and HEK293T were grown using Dulbecco's modified Eagle's medium (DMEM) (Servicebio) supplemented with 10% fetal bovine serum (FBS) (ViVacell) and 1% penicillin/ streptomycin (P/S) (Servicebio). SK-OV-3 cells were cultured with McCoy’s 5A Medium Modified (ViVacell). OVCAR-8 cells were cultured with RPMI-1640 Medium Modified (Servicebio). The cells were maintained in an atmosphere of 5% CO 2 at 37 °C in recommended medium and passaged using 0.05% trypsin/EDTA (Meilunbio). All cell lines were confirmed by STR analysis. Plasmid construction and stable cell line establishment Two transcript variants of LAYN and RHOU were amplified by RT-PCR using cDNA derived from SK-OV-3 cells. The sequences of Layn, Hyal1 and Cryl1 were amplified by RT-PCR using cDNA derived from mouse lung tissues. The coding sequences were subsequently cloned into the pLV-EF1α-MCS-IRES-Bsd lentiviral vector (Biosettia Inc.), incorporating a C-terminal V5/flag/mcherry epitope tag immediately upstream of the stop codon. For knockdown studies, shRNA sequences targeting indicated genes were designed using the Thermo Fisher RNAi Designer tool and inserted into the pLV-H1-EF1α-puro plasmid (Biosettia Inc.). For dual-luciferase studies, promoters of LAYN and HYAL1 were cloned from genomic DNA from HEK 293T and subsequently cloned into PGL3-Basic plasmid (Biosettia Inc.). All primers and shRNA template sequences are provided in Supplementary Table 5, and plasmid integrity was verified by Sanger sequencing (Sangon Biotech). Lentiviral particles were generated by transfecting Lenti-293T cells (Biosettia Inc.) with the constructed plasmids. Ovarian cancer cells were then transduced at an MOI of 1.0, followed by antibiotic selection—blasticidin (2.5–5.0 μg/mL) for overexpression lines or puromycin (5 μg/mL) for knockdown lines. After a 14-day selection period, polyclonal populations were assessed for target gene modulation via Western blotting and qRT-PCR prior to functional assays or in vivo experiments. Quantitative real-time PCR Total RNA was isolated from cell samples using TRIeasy™ LS reagent and subsequently reverse transcribed into cDNA with Hifair® Ⅲ 1st Strand cDNA Synthesis SuperMix for qPCR (Yeasen). qPCR amplification was carried out on a StepOnePlus system (Thermo Fisher) using SYBR Green SuperMix (Yeasen), with the following thermal cycling conditions: 95°C for 6 min, then 45 cycles of 95°C for 30 sec and 60°C for 45 sec. Gene expression levels were normalized to β-actin and analyzed via the 2 −ΔΔCt method. Primer sequences are provided in Supplementary Table 5 . Protein extraction and western blot Cells were lysed in RIPA buffer containing protease and phosphatase inhibitors. Protein concentrations were measured with the Pierce BCA Assay. Equal protein amounts (typically 20-50 μg) were resolved by 10% SDS-PAGE and electrophoretically transferred to PVDF membranes. After blocking with 5% non-fat dry milk in TBST for 1 h at room temperature, membranes were incubated with primary antibodies (listed in Supplementary Table 6 ) overnight at 4°C with gentle agitation. After washing, membranes were incubated with HRP-conjugated secondary antibodies (Proteintech, Wuhan, China) for 1 h at room temperature. Signals were detected using enhanced chemiluminescence. Hematoxylin and eosin (H&E) and immunohistochemistry (IHC) staining For histopathological examination, OC tissues were fixed in 4% paraformaldehyde (Sigma-Aldrich) and processed through graded ethanol dehydration prior to paraffin embedding. Serial sections (5 μm) were prepared and stained with hematoxylin-eosin (OriGene) for morphological evaluation. Immunohistochemical procedures involved peroxidase inactivation with 3% H₂O₂ followed by heat-mediated antigen retrieval. Sections were blocked with 5% normal goat serum before sequential incubation with primary antibodies and biotinylated secondary antibodies (Vector Laboratories). Signal amplification was achieved using streptavidin-HRP (Vector Laboratories), with DAB chromogen (Zsgb-Bio) development limited to 2 minutes. Nuclear counterstaining was performed with hematoxylin. Antibody details are provided in Supplementary Table 6 . Semiquantitative analysis employed an H-score system, calculated as the product of staining intensity (0-3 scale) and percentage of positive cells (0-4 scale), with final scores ranging from 0 to 12. Immunofluorescent (IF) staining Cells after different treatment were cultured on glass coverslips in 24-well plates. After PBS washing, samples were fixed with 4% PFA for 10 min at room temperature. Non-specific binding was blocked with 5% goat serum, followed by incubation with primary antibodies (Supplementary Table 6 ) and corresponding fluorescent secondary antibodies (Alexa Fluor-488/594, ThermoFisher). Nuclei were visualized with DAPI staining (Sigma-Aldrich). Fluorescent images were acquired using an Olympus FV1000 confocal system and quantified with ImageJ software. Organoid derivation, culture and treatment Organoids were derived from tumor samples of patients with OC and cultured according to the introduction of High-Grade Serous Ovarian Cancer Organoid Kit (Serum-free) kit (K2167-HS, biogenous technologies). Briefly, Primary biopsies are collected in cold storage solution, dissected to enrich tumor tissue, minced, and enzymatically digested. The resulting cell suspension is filtered, subjected to red blood cell lysis if needed, washed, and centrifuged. Cells are resuspended in reduced-growth-factor ECM (Matrigel) and plated as droplets. After ECM solidification, serum-free, organoid-specific complete medium (formulated from basal medium and supplements B-E, tailored to tumor heterogeneity) is added. Organoids are cultured at 37°C/5% CO₂ with medium changes every 3-4 days. To harvest bioGenous™ HGSC organoids from ECM for H&E, or RNA extraction, first aspirate medium and wash wells gently with ice-cold PBS supplemented with 1% FBS. Dissolve ECM by incubating with ice-cold Cell Recovery Solution (biogenous technologies) at 4°C for 30 min. Transfer the suspension to a chilled tube, centrifuge (200–300 × g, 5 min, 4°C), and aspirate supernatant. Wash pellets thoroughly 2–3 times with ice-cold PBS to remove ECM contaminants. For H&E, embed washed organoids in histology cassettes and fix immediately in 4% PFA for 1h. For RNA extraction, lyse the final pellet directly in TRIeasy™ LS reagent; maintain RNase-free conditions and store lysates at −80°C. Minimize handling time and maintain cold chain throughout, except during fixation. Co-Immunoprecipitation Cell lysates were immunoprecipitated with anti-Flag/mCherry antibody ( Supplementary Table 6 ) for 4 hours at 4°C, followed by incubation with protein G agarose beads (CWBIO) overnight with constant rotation. After extensive washing, bound proteins were eluted using 1× SDS loading buffer through boiling, then separated by SDS-PAGE. Western blotting was subsequently performed to detect the potential interaction between LAYN and RHOU proteins. Proximity Ligation Assay (PLA) To detect LAYN-RHOU interactions in situ, cells were fixed with 4% paraformaldehyde, permeabilized with 0.1% Triton X-100, and blocked with 5% BSA in PBS. Primary antibodies ( Supplementary Table 6 ) targeting the LAYN and RHOU proteins were incubated overnight at 4°C. After washing, species-specific PLA probes (Duolink®, Sigma-Aldrich) were applied for 1 h at 37°C. Ligation and amplification steps were performed according to the manufacturer’s protocol, using fluorescently labeled oligonucleotides to generate discrete puncta at interaction sites. Nuclei were counterstained with DAPI. Images were acquired using an Olympus FV1000 confocal system and quantified with ImageJ software. Negative controls omitted primary antibodies. Flow cytometry The abdominal fluid was washed out with PBS and processed for OC cell profiling. Red blood cells were removed using a lysis buffer (Solarbio), followed by washing in PBS supplemented with 1% FBS. The cell suspension was filtered through a 40 µm nylon mesh (BD Biosciences) to ensure a single-cell suspension. CD45-APC antibody incubation was performed for 30 minutes at 4°C in the dark, followed by two washes with 1% FBS/PBS. Flow cytometry data were acquired on an LSR Fortessa system (BD Biosciences) and analyzed using FlowJo software (BD Biosciences). Cell proliferation assay 1.5 × 10 3 ID8, MB49 and KPC1199 cells or 2 × 10 3 OVACR-8 cells were seeded in 48-well plates and incubated at 37 °C in the incubator. Cells were detached by trypsinization counted every 24 h by using a Countess 2 Automated Cell Counter (Thermo-Fisher Scientific) until the cells reached full confluency. The cell number at each time point was the average of three wells. To determine the effects of HA/GlcA/NAG, ID8, MB49, KPC and OVCAR-8 were treated with HA/GlcA/NAG (Meryer, Shanghai) in glucose-free DMEM (Pricella, Wuhan) supplemented with 2.5 mM glucose. HA with different molecular mass, GlcA and NAG were dissolved in PBS with ultrasonic solubilization. To determine the inhibitor of HYAL1, ID8, MB49, KPC were treated with Garcinol (TargetMol, Shanghai). The cell number at each time point was the average of three wells. Colony formation assay 1.5 × 10 3 ID8, MB49 and KPC cells or 2 × 10 3 OVACR-8 cells were seeded in 6-well plates and incubated at 37 °C in the incubator until colonies could be identified. The treatments were same as Cell proliferation assay. After fixed with 4% paraformaldehyde, stained with crystal violet and counted by Image J software, the numbers of colonies were presented as the average of three biological replicates. BrdU Proliferation Assay OVCAR-8 cells were cultured on glass coverslips in 24-well plates and pulsed with 10 μM BrdU (Beyotime, ST1056) for 12-hour durations. Following incubation, cells were fixed and processed for immunofluorescence staining to detect BrdU incorporation, following standard IF protocols. Nuclei were counterstained with DAPI to visualize all cells. The percentage of BrdU-positive cells was quantified to evaluate proliferative activity. Targeted metabolomics Cells (1×10 7 /sample) were quenched in liquid nitrogen and extracted with 80% methanol containing 10 μM norvaline (internal standard). Tests were performed and analyzed on an ultra-high performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS) system (Novogene, Beijing, China). The samples were centrifuged at 1000 rpm for 3 min (4°C) to remove the supernatant. Then homogenized with 250 μL of methanol (80%) which contained mixed internal standards and centrifuged at 15000 rpm for 15 min (4°C) to remove the protein. The supernatant was added to water by well vortexing as the diluted sample. Then 100 μL of them were taken respectively and homogenized with 100 μL of imino-bis (methylphosphonic acid) by well vortexing. After that, centrifuged at 15000 rpm for 15 min. Finally, the supernatant was injected into the LC-MS/MS system for analysis. Untargeted 13 C metabolic flux OVACR-8 cells were cultured in glucose-free DMEM (Procell, Wuhan, China) supplemented with 10% dialyzed FBS, 2.5 mM glucose and 5 mM 13 C-GlcA. After 72 h of labeling, cells were quenched and extracted in 80% methanol. The Tsinghua University Metabolism and Lipidomics Platform offers untargeted metabolic tracing services using 13 C-GlcA with high-resolution mass spectrometry analysis. Hyaluronic Acid staining OVCAR-8 cells were cultured on glass coverslips in 24-well plates and stained with 1% Alcian Blue (Solario) for 30 min, rinsed in 3% acetic acid and captured using optical microscope. Live imaging of tumor progression After the intraperitoneal injection of mouse tumor cells, 100μL D-luciferin (Psaitong Biotechnology, Beijing) was injected intraperitoneally at different time for monitor the dissemination progression. Metastatic burden was monitored two-weekly by bioluminescence using the Tanon 5200 multi-imaging system and the software GToC 1.3.5 for analysis. Dual-luciferase reporter assay The promoter region (−2000 to -1) of LAYN and promoter region (−2000 to −30) of HYAL genes were cloned into the plasmid pGL3(Promega) to create the firefly luciferase reporter plasmid. OVCAR-8 shLacZ/shCD44 cells were transiently transfected with renila luciferase as control reporter plasmid and PGL-3 firefly luciferase reporter plasmid. Dual-Luciferase reporter assay system (Promega) was used to measure the luciferase activity. Determination of HYAL1 Enzyme Kinetics and Inhibitor Activity Purified HYAL1 protein (MCE, HY-P70411, 50nM) were incubated with HA (0-500 nM) in 100 μL of sodium acetate buffer (0.2 M, pH=4 with 150 mM NaCl) at 37°C for catalyzation. Reactions were terminated by adding 10 µL of 1.2 M potassium tetraborate and boiling in a water bath for 5 min. NAG release was quantified by adding of 100 µL p-dimethylaminobenzaldehyde (DMAB) reagent (10% w/v in glacial acetic acid), incubating at 37°C for 30 min, and measuring absorbance at 585 nm. Enzyme activity was expressed as nmol NAG released per minute (nM/min), calculated from a standard curve of known NAG concentrations (0-500 nM). For inhibition studies, HYAL1 protein was pre-incubated with garcinol (0-200 μM in 0.1% DMSO) for 10 min at 37°C prior to addition of HA (optimal concentration determined from kinetics experiments). The reaction mixture was then processed identically to the kinetics assay. Negative controls included: (1) substrate blank (reaction mixture without enzyme), and (2) enzyme blank (reaction mixture without HA). The half-maximal inhibitory concentration ((IC 50 ) was determined by nonlinear regression analysis using GraphPad Prism 8. Each inhibitor concentration was tested in three replicates. Bioinformatic analysis The information about the HA catabolism-related genes mRNA level in OC patients were obtained from the TCGA database. The association between the survival of OC patients with HA metabolism-related genes expression was analyzed using the data from TCGA database (n=349). The correlation of CD44 and HA metabolism-related genes was analyzed using GEPIA at http://gepia.cancer-pku.cn/ . Deep RNA sequencing Total RNA of sorted ID8 cells at different time were harvested using TRIzol reagent for RNA extraction. The deep RNA sequencing was performed and analyzed on NovaSeq (Novogene, Beijing, China). Gene Set Enrichment Analysis (GSEA) was performed using the Gene Ontology (GO) database (http://geneontology.org/) as the reference gene set collection. Statistical analysis Statistical analysis was performed using Prism 8.0 software (GraphPad Software, San Diego, CA, USA). Quantitative data are presented as means ± SEM, and differences between groups were analyzed using the student’s t-test or two-way ANOVA for continuous variables, as appropriate. Survival curves were analyzed using the Kaplan–Meier method, with between-group differences assessed by the log-rank test. Co-expression of CD44 and other genes was evaluated using the Spearman or Pearson test. Statistical parameters, including definitions of n, specific tests, and exact p-values, are detailed in the figures and legends. Significance thresholds were set as follows: *p < 0.05, **p < 0.01, ***p < 0.001, "ns" indicates not significant. Declarations Competing Interest Statement: The authors declare no potential conflict of interests. CONFLICT OF INTEREST STATEMENT The authors declare that they have no conflict of interest. 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Nature Reviews Disease Primers 7 , (2021). Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryTable3Targetedmetabolomics.xlsx Supplementary Table 3 (Targeted metabolomics) SupplementaryTable2Survival.xlsx Supplementary Table 2(Survival) SupplementaryTable6antibodies.xlsx Supplementary Table 6(antibodies) SupplementaryTable5Primer.xlsx Supplementary Table 5(Primer) SupplementaryTable4BloodBiochemistryTest.xlsx Supplementary Table 4(Blood Biochemistry Test) SupplementaryFigureandFigurelegends.docx Supplementary Figure and Figure legends SupplementaryTable1screeningresults.xlsx Supplementary Table 1(screening results) Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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The genes related to HA uptake and metabolism are highlighted in yellow. \u003cstrong\u003eB \u003c/strong\u003eVenn diagram comparing the hits meeting the enrichment criteria (number of enriched sgRNAs ≥ 2, p-value \u0026lt; 0.05). \u003cstrong\u003eC\u003c/strong\u003e The diagram of the metabolic pathways that linking HA catabolism to Glycolysis through GlcA pathway. The identified genes are highlighted in red.\u003cstrong\u003e D\u003c/strong\u003e Schematic diagram of the experimental OC dissemination mouse model, established by intraperitoneal (i.p.) injection of GFP-transfected ID8 cells into C57BL/6 mice, and the time points for the sorting of disseminated ID8\u003csup\u003eGFP\u003c/sup\u003e cells by flow cytometry are indicated by arrows. \u003cstrong\u003eE\u003c/strong\u003e Gene expression heatmap showing upregulated (orange)/downregulated (green) genes in HA metabolism, GlcA pathway, pentose phosphate pathway (PPP), glycolysis and Citric Acid Cycle (TCA cycle) quantified by RNA-seq. \u003cstrong\u003eF \u003c/strong\u003eRT-qPCR analysis of genes related to HA catabolism in disseminated ID8\u003csup\u003eGFP\u003c/sup\u003e cells sorted from mice at Day 14 or Day 21 after intraperitoneal (i.p.) injection of ID8\u003csup\u003eGFP\u003c/sup\u003e cells, with the values at Day 1 as the control. (n=5, ***p \u0026lt; 0.001, **p \u0026lt; 0.01, *p \u0026lt; 0.05, ns not significant, by unpaired Student’s \u003cem\u003et\u003c/em\u003e-test). \u003cstrong\u003eG \u003c/strong\u003eRepresentative images of immunohistochemistry staining for the indicated gene-encoded proteins in primary and disseminated tumor tissues from OC patients, along with H-score quantification results (n=5, **p \u0026lt; 0.01, *p \u0026lt; 0.05, by paired Student’s \u003cem\u003et\u003c/em\u003e-test).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7691213/v1/3b29b1549bb03c315179f2c0.png"},{"id":96261803,"identity":"c5a38ea7-5aa4-4821-b91f-dad63d131fda","added_by":"auto","created_at":"2025-11-19 08:00:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1346431,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e\u003cbr\u003e\n\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInduced HA catabolism and GlcA pathway genes rewire HA catabolism to PPP and glycolysis to sustain the survival and proliferation of OC cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e RT-qPCR analyses of the HA catabolism and GlcA pathway genes in ID8, OVCAR-8, and SK-OV-3 cells under HA replenishment (0.1 mg/mL) and glucose-low (2.5 mM glucose) medium. Data are presented as means ± SEM from three independent experiments (**p \u0026lt; 0.01, *p \u0026lt; 0.05, *p \u0026lt; 0.001, by unpaired Student’s t-test). \u003cstrong\u003eB\u003c/strong\u003e Bright-field images of patient-derived OC organoid\u003cstrong\u003e \u003c/strong\u003eand HE staining analysis.\u003cstrong\u003e C\u003c/strong\u003e RT-qPCR analysis of the HA catabolism and GlcA pathway genes in\u003cstrong\u003e \u003c/strong\u003eOC organoid\u003cstrong\u003e \u003c/strong\u003eunder HA replenishment and glucose-low conditions. Data are presented as means ± SEM from three independent experiments (**p \u0026lt; 0.01, *p \u0026lt; 0.05, *p \u0026lt; 0.001, by unpaired Student’s t-test). \u003cstrong\u003eD \u003c/strong\u003eWestern blot analysis of the indicated gene-encoded proteins under HA replenishment and low-glucose conditions at different time points (48, 72, and 96 h). \u003cstrong\u003eE\u003c/strong\u003e The relative abundance of metabolites of PPP, glycolysis, TCA cycle and nucleotide metabolism in ID8 cells under HA replenishment and glucose-low medium measured by metabolomics analysis. Metabolite levels were normalized to those in glucose-low medium as control. Data are represented as means ± SEM (n=3 biological replicates; ***p \u0026lt; 0.001, **p \u0026lt; 0.01, *p \u0026lt; 0.05, by unpaired Student’s t-test). \u003cstrong\u003eF\u003c/strong\u003e Western blot analysis of CRYL1 protein levels in OVCAR-8 cells transfected with specific shRNAs against\u0026nbsp;\u003cem\u003eCRYL1\u003c/em\u003e or a non-specific control shRNA against bacterial lacZ gene (shLacZ). β-actin served as a loading control. \u003cstrong\u003eG\u003c/strong\u003e Tracing the metabolic flux of GlcA, by the addition of \u003csup\u003e13\u003c/sup\u003eC-GlcA, into the PPP and glycolysis pathways in OVCAR-8 cells transfected with control shRNA or shCRYL1. \u003cstrong\u003eH\u003c/strong\u003e Schematic representation of the rewired HA catabolism to PPP and glycolysis through GlcA pathway in disseminated OC cells. Key enzymes and metabolites upregulated are highlighted in orange.\u003cstrong\u003e I \u003c/strong\u003eProliferation curves of ID8 and OVCAR-8 under different culture conditions. The concentrations of HA, GlcA and NAG are as follows: HA (40~100KD): 0.1 mg/mL, GlcA:0.25mM, NAG: 0.25mM, with detailed plots for the first four days (mean ± SEM from three replicates, **p \u0026lt; 0.001,\u0026nbsp;p \u0026lt; 0.05 by two-way ANOVA). \u003cstrong\u003eJ\u003c/strong\u003e Representative images of colony formation assays of ID8 and OVCAR-8 cells cultured in indicated conditions and quantification results (means ± SEM from three replicates, ***p \u0026lt; 0.001, **p \u0026lt; 0.01, by unpaired Student’s t-test).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7691213/v1/4ec236d9900a1dd923f91159.png"},{"id":96364194,"identity":"e923bf09-ec93-41a8-9722-42f445111e00","added_by":"auto","created_at":"2025-11-20 10:09:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1449454,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLAYN-mediated HA uptake is essential for HA-fueled early intraperitoneal dissemination.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA \u003c/strong\u003eRepresentative images of fluorescent tracking LAYN-mediated uptake FITC-conjugated HA (HA-FITC, 50 kD, 5 μM) in ID8 cells transfected with Layn or empty vector (Vec) as a control. Nuclei were counterstained with DAPI (blue). Quantification of fluorescence intensity (green panels) is shown as means ± SEM from three independent experiments (**p \u0026lt; 0.01, by unpaired Student’s t-test). \u003cstrong\u003eB \u003c/strong\u003eThe schematic of experimental dissemination murine model of OC for the competition of early dissemination capacity between Layn-overexpressed (labeled with EGFP) and Vec-transfected (labeled with mCherry) ID8 cells. The experimental timeline indicates when disseminated tumor cells were analyzed by flow cytometry. \u003cstrong\u003eC, D\u003c/strong\u003e Representative immunofluorescent images(\u003cstrong\u003eC\u003c/strong\u003e) and flow cytometry analyses (\u003cstrong\u003eD\u003c/strong\u003e) of the ID8 cells isolated from the peritoneal cavity of C57BL/6 mice at indicated timelines and quantification results. (n=6, data are shown as means ± SEM, ***p \u0026lt; 0.001, by unpaired Student’s \u003cem\u003et\u003c/em\u003e-test).\u003cstrong\u003eE\u003c/strong\u003e Representative immunofluorescent images of HA-FITC uptake in LAYN-silenced (shLAYN) and control (shLacZ) OVCAR-8 cells. Quantifications of fluorescence intensity (green signals) are shown as means ± SEM from three replicates (**p \u0026lt; 0.01, *p \u0026lt; 0.05, by unpaired Student’s \u003cem\u003et\u003c/em\u003e-test). \u003cstrong\u003eF\u003c/strong\u003e The proliferation curves of ID8 shLacZ/shLayn cells under low glucose medium supplemented with (solid lines) or without (dash lines) HA (Data are shown as means ± SEM, n=3, ***p \u0026lt; 0.001, ns not significant, by two-way ANOVA test). \u003cstrong\u003eG\u003c/strong\u003e The colony formation assays of indicated ID8 cells under indicated conditions (Data are shown as means ± SEM, n=3, ***p \u0026lt; 0.001, ns not significant, by unpaired Student’s t-test). \u003cstrong\u003eH\u003c/strong\u003e The schematic of orthotopic murine model of OC by intrabursal injection of Layn-silenced or control ID8 cells (top panel).\u003cstrong\u003e \u003c/strong\u003eAnd the\u003cstrong\u003e \u003c/strong\u003eimages of the dissected primary tumors and their weight results are shown in the bottom panels.\u003cstrong\u003e J, I\u003c/strong\u003e The peritoneal dissemination was analyzed by measure the formation of malignant ascites (\u003cstrong\u003eJ\u003c/strong\u003e) and the tumor nodules formed in the peritoneal cavity (\u003cstrong\u003eI\u003c/strong\u003e). Quantifications of tumor weight, ascites volume and the number of disseminated nodules were shown as means ± SEM. (n=5–6, ***p \u0026lt; 0.001, *p \u0026lt; 0.05, by unpaired Student’s t-test).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7691213/v1/9f8c421cd6d65261e81d2ac0.png"},{"id":96261813,"identity":"a6821685-5c2d-4c39-b1c6-4bf32e8cdf77","added_by":"auto","created_at":"2025-11-19 08:00:46","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1460248,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRHOU facilitates the endosomal recycling of LAYN for the efficient uptake of HA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA, B \u003c/strong\u003eWestern blot analysis of the lysates of OVCAR8 cells co-transfected with RHOU-Flag and the long (L) or short (S) isoforms of LAYN-mCherry immunoprecipitated (IP) with anti-mCherry (\u003cstrong\u003eA\u003c/strong\u003e) or anti-Flag antibodies(\u003cstrong\u003eB\u003c/strong\u003e). \u003cstrong\u003eC\u003c/strong\u003e Co-IP and western blot analysis of RHOU-Flag and LAYN-mCherry co-transfected OVCAR-8 cells cultured in low glucose medium supplemented with or without HA. \u003cstrong\u003eD, E\u003c/strong\u003e OVCAR-8 cells with overexpressed (OE) RHOU-Flag and LAYN-V5 (\u003cstrong\u003eD\u003c/strong\u003e) were analyzed with proximity ligation assay (PLA) under low glucose condition with or without HA (\u003cstrong\u003eE\u003c/strong\u003e). The negative control was treated without primary antibodies. The quantification data are presented as means ± SEM (n=3, **p \u0026lt; 0.01, by unpaired Student’s t-test). \u003cstrong\u003eF\u003c/strong\u003e Representative immunofluorescent images of OVCAR-8 cells transfected with mCherry-tagged LAYN, BFP-tagged RHOU and FITC-conjugated HA in low glucose medium supplemented with HA for indicated time periods.\u003cstrong\u003e G, H\u003c/strong\u003e Representative immunofluorescent images of the colocalization of mcherry-tagged LAYN with EEA1-labeled early endosome (\u003cstrong\u003eG\u003c/strong\u003e) or RAB11-labled recycling endosome (\u003cstrong\u003eH\u003c/strong\u003e) in OVCAR-8 cells transfected with shRNAs against RHOU (shRHOU) or control shLacZ in low glucose medium supplemented with HA. The nuclei were counterstained with DAPI (blue). Quantitative co-localization was analyzed by spearman rank correlation test and shown in the right panel.\u003cstrong\u003e I\u003c/strong\u003e Representative immunofluorescence images showing mCherry-tagged LAYN and lysosomal marker LAMP1 (green) in OVCAR-8 shRHOU cells under low glucose conditions with HA replenishment, with or without the treatment of 40 μM chloroquine (CQ) for 2h. Nuclei were counterstained with DAPI. The quantitative co-localization analysis by spearman rank correlation test are shown in the right panels.\u003cstrong\u003e J-L\u003c/strong\u003e The colony formation assays (\u003cstrong\u003eJ\u003c/strong\u003e), cell growth curves (\u003cstrong\u003eK\u003c/strong\u003e)and BrdU incorporation assays (\u003cstrong\u003eL\u003c/strong\u003e) in OVCAR-8 LAYN-OE cells transfected with indicated shRNAs and cultured in low glucose medium supplemented with or without HA. The quantification data are represented as means ± SEM from three independent experiments (***p \u0026lt; 0.0001, **p \u0026lt; 0.001, ns not significant, by unpaired Student's t-test for colony formation and BrdU assays, and two-way ANOVA for proliferation curve analysis).\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7691213/v1/e88ce458224a4582af2bd9c0.png"},{"id":96363409,"identity":"c6d86ff0-b09e-4659-9401-e219df13ec04","added_by":"auto","created_at":"2025-11-20 10:06:41","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1109484,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLAYN-mediated uptake of HA promotes OC proliferation and early peritoneal dissemination through GlcA pathway.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA-D\u003c/strong\u003e The colony formation assays (\u003cstrong\u003eA, C\u003c/strong\u003e) and the growth curves (\u003cstrong\u003eB, D\u003c/strong\u003e) of LAYN-silenced (shLAYN) or control (shLacZ) OVCAR-8 in low glucose medium supplemented with GlcA (\u003cstrong\u003eA, B\u003c/strong\u003e) or Xul (\u003cstrong\u003eC, D\u003c/strong\u003e) replenishment in comparison with HA. Data are shown means±SEM from three independent experiments, ***p \u0026lt; 0.001, **p \u0026lt; 0.01, nsnot significant, by unpaired Student’s t-test for colony formation assay and two-way ANOVA test for proliferation curve analysis. \u003cstrong\u003eE\u003c/strong\u003e-\u003cstrong\u003eG\u003c/strong\u003e The growth curves (\u003cstrong\u003eE, F\u003c/strong\u003e) and the colony formation assays (\u003cstrong\u003eG\u003c/strong\u003e) of \u003cem\u003eCRYL1\u003c/em\u003e-silenced (shCRYL1) or control (shLacZ) OVCAR-8 cells in low glucose medium supplemented with 0.5 mM GlcA (\u003cstrong\u003eE\u003c/strong\u003e) or Xul (\u003cstrong\u003eF\u003c/strong\u003e) supplementation. Data are shown as means ± SEM from three independent experiments (***p\u0026lt;0.001, **p\u0026lt;0.01, ns not significant, by unpaired Student’s t-test for colony formation assay and two-way ANOVA test for the proliferation curve analysis). \u003cstrong\u003eH\u003c/strong\u003eWestern blot assay of the knock-down efficiencies of shRNAs against \u003cem\u003eCryl1\u003c/em\u003ein ID8 LAYN-OE. \u003cstrong\u003eI-K \u003c/strong\u003eThe experimental OC dissemination murine model (\u003cstrong\u003eI\u003c/strong\u003e) to show the essential role of GlcA pathway enzyme CRYL1 in LAYN-promoted peritoneal dissemination analyzed by the formation of malignant ascites (\u003cstrong\u003eJ\u003c/strong\u003e) and peritoneal metastatic nodules (\u003cstrong\u003eK\u003c/strong\u003e) (n=6, *** p \u0026lt;0.001, ns not significant, by unpaired Student’s t-test).\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7691213/v1/b233ca18cb3699a3488710ef.png"},{"id":96261821,"identity":"86324a79-2d25-4a13-9218-ce20dad73996","added_by":"auto","created_at":"2025-11-19 08:00:46","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1359014,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHA induces HA catabolism and GlcA pathway genes through the CD44-CREB signaling to drive OC dissemination.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e Western blot analysis of CD44 knockdown efficiency in OVCAR-8 (top) and SK-OV-3 (bottom) cells using shRNA-mediated silencing. \u003cstrong\u003eB\u003c/strong\u003e Growth curves of OVCAR-8 and SK-OV-3 cells following CD44 depletion under HA replenishment and low-glucose conditions. Data represent mean ± SEM (n=3 independent experiments; ***p \u0026lt; 0.001, **p \u0026lt; 0.01, ns not significant; two-way ANOVA). \u003cstrong\u003eC\u003c/strong\u003e The colony formation assays of OVCAR-8 shCD44 cells under HA supplementation and low-glucose condition (Means ± SEM from three replicates, *p \u0026lt; 0.05, ns not significant, by unpair Student’s t-test). \u003cstrong\u003eD, E \u003c/strong\u003eThe RT-qPCR analyses (\u003cstrong\u003eD\u003c/strong\u003e) and western blot assays (\u003cstrong\u003eE\u003c/strong\u003e) of enzymes involved in HA metabolism in OVCAR-8 and SK-OV-3 shCD44 cells under HA replenishment and low glucose conditions. Data are shown as means ± SEM from 3 independent experiments, ***p \u0026lt; 0.001, **p \u0026lt; 0.01, *p \u0026lt; 0.05, ns not significant, by unpair Student’s t-test.\u003cstrong\u003e F \u003c/strong\u003eScatter plot showing a significant positive correlation between the expression of HA metabolism (\u003cem\u003eLAYN, HYAL1, CRYL1, AKR1A1, DCXR, SORD \u003c/em\u003eand\u003cem\u003e XYLB\u003c/em\u003e) with \u003cem\u003eCD44 \u003c/em\u003eanalyzed by GEPIA2 (Spearman R = 0.39). \u003cstrong\u003eG, H\u003c/strong\u003e Dual luciferase reporter assays assessing LAYN/HYAL1 promoter activity \u003cstrong\u003e(G)\u003c/strong\u003e and LAYN/HYAL1-depleted mutant promoteractivity \u003cstrong\u003e(H)\u003c/strong\u003e in CD44-knockdown OVCAR-8 cells under HA replenishment and low glucose conditions. Data represent mean ± SEM (n = 3 independent experiments; **p \u0026lt; 0.01, *p \u0026lt; 0.05, ns not significant, by unpaired Student's t-test). \u003cstrong\u003eI\u003c/strong\u003e The western blot of key enzymes overexpressed in ID8 shCD44 cells.\u003cstrong\u003e J, K\u003c/strong\u003e The representative images of ascites volume (\u003cstrong\u003eJ\u003c/strong\u003e) and metastatic nodules (\u003cstrong\u003eK\u003c/strong\u003e) in mice intraperitoneal injected with indicated cells. Right panels show quantitative analyses. (n=6, ***p \u0026lt; 0.001, **p \u0026lt; 0.01, *p \u0026lt; 0.05, by unpaired Student’s t-test).\u003cstrong\u003e L \u003c/strong\u003eImmunofluorescent staining of the primary and disseminated human OC tissues for the correlation analysis of P-CREB with LAYN or HYAL1 protein (n=10, by the spearman rank correlation test).\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7691213/v1/83548696077dcd9bb5db71c7.png"},{"id":96363083,"identity":"c27d4191-d387-4420-a83a-aa522df1e763","added_by":"auto","created_at":"2025-11-20 10:04:16","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1162379,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHYAL1 inhibitor garcinol p inhibits the peritoneal disseminated metastasis in multiple cancer models.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA \u003c/strong\u003eMichaelis-Menten kinetics of recombinant HYAL1 protein -mediated HA degradation. \u003cstrong\u003eB\u003c/strong\u003e Dose-response curve of garcinol inhibition on HA catabolism. \u003cstrong\u003eC, D \u003c/strong\u003eThe proliferation curves (\u003cstrong\u003eC\u003c/strong\u003e) and colony formation assays (\u003cstrong\u003eD\u003c/strong\u003e) of ID8, KPC, MB49 cells under HA replenishment and low-glucose condition with garcinol/GlcA treatment or not (means ± SEM from 3 replicates, ***p \u0026lt; 0.001, **p \u0026lt; 0.01, significances were analyzed by two-way ANOVA test in \u003cstrong\u003eC\u003c/strong\u003e and unpaired Student’s t-test in \u003cstrong\u003eD\u003c/strong\u003e).\u003cstrong\u003e E \u003c/strong\u003eThe representative image of\u003cstrong\u003e \u003c/strong\u003eliving imaging of KPC and MB49 mouse models at weeks 2 and 4 post-intraperitoneal tumor implantation and drug administration, with quantitative results shown in right panel (n=5-6, means ± SEM, ***p \u0026lt; 0.001, **p \u0026lt; 0.01, by unpaired Student’s t-test). \u003cstrong\u003eF \u003c/strong\u003eRepresentative images of immunohistochemistry staining for Ki-67 in tumor tissues of vehicle and Garcinol groups, along with H-score quantification results (n=5, ***p \u0026lt; 0.01, by paired Student’s t-test). \u003cstrong\u003eG, H \u003c/strong\u003eDifferential sensitivity to platinum-based chemotherapy in OC patients stratified by expression levels of HA metabolism (LAYN-228080_at*, HYAL1-210619_s_at, CRYL1-220753_s_at,).\u003cstrong\u003e I\u003c/strong\u003e In vivo imaging of OC peritoneal dissemination models at weeks 6 and 10 following monotherapy (garcinol or cisplatin) and combination treatment (n=6, means ± SEM, ***p \u0026lt; 0.001, **p \u0026lt; 0.01, by unpaired Student’s t-test). \u003cstrong\u003eJ, K\u003c/strong\u003e Representative images of ascites (\u003cstrong\u003eJ\u003c/strong\u003e) and peritoneal metastatic nodules (\u003cstrong\u003eK\u003c/strong\u003e) in OC peritoneal dissemination models following the treatment with garcinol, cisplatin, or combination therapy\u003cstrong\u003e.\u003c/strong\u003e Quantifications of ascites volume and the number of disseminated tumor nodules are shown as means ± SEM. (n=6, ***p \u0026lt; 0.001, by unpaired Student’s t-test).\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7691213/v1/a3e034ed1f4af45f043a3ce9.png"},{"id":96363516,"identity":"b665e676-6c80-4014-b33d-93b40b472762","added_by":"auto","created_at":"2025-11-20 10:07:12","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":158024,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003egraphical abstract\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7691213/v1/4852202067bb7ad58fae92d7.png"},{"id":98636660,"identity":"0fa9e4f2-3a00-47f3-b579-bd929059c251","added_by":"auto","created_at":"2025-12-19 17:28:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":11335220,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7691213/v1/2650cf68-911f-4991-9ffe-9459d3f60daa.pdf"},{"id":96261800,"identity":"31518985-278a-44ec-81fb-625508ee1ba8","added_by":"auto","created_at":"2025-11-19 08:00:45","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15717,"visible":true,"origin":"","legend":"Supplementary Table 3 (Targeted metabolomics)","description":"","filename":"SupplementaryTable3Targetedmetabolomics.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7691213/v1/d4f429ae353f07d5414787d1.xlsx"},{"id":96363183,"identity":"632bf57e-13b6-495a-8a40-5d9547bdb1ff","added_by":"auto","created_at":"2025-11-20 10:05:16","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":30445,"visible":true,"origin":"","legend":"Supplementary Table 2(Survival)","description":"","filename":"SupplementaryTable2Survival.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7691213/v1/95bc811b0d47d345d1da4898.xlsx"},{"id":96261819,"identity":"5b7ca52c-6977-4096-b4e7-677e8366b325","added_by":"auto","created_at":"2025-11-19 08:00:46","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":11137,"visible":true,"origin":"","legend":"Supplementary Table 6(antibodies)","description":"","filename":"SupplementaryTable6antibodies.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7691213/v1/f6724f10852f099728e9c160.xlsx"},{"id":96261812,"identity":"325715a3-8112-4a5b-b889-8b43554d66ef","added_by":"auto","created_at":"2025-11-19 08:00:45","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":13492,"visible":true,"origin":"","legend":"Supplementary Table 5(Primer)","description":"","filename":"SupplementaryTable5Primer.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7691213/v1/4c513087c999b1b5a0c65e5d.xlsx"},{"id":96261827,"identity":"cff778b3-7da3-481d-a503-4a73b99f25ee","added_by":"auto","created_at":"2025-11-19 08:00:46","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":10960,"visible":true,"origin":"","legend":"Supplementary Table 4(Blood Biochemistry Test)","description":"","filename":"SupplementaryTable4BloodBiochemistryTest.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7691213/v1/7acb73bc2dfb0b5f2a40a496.xlsx"},{"id":96364124,"identity":"5911a689-f69b-4fc5-9daf-eb03e7c0932b","added_by":"auto","created_at":"2025-11-20 10:08:56","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":5395165,"visible":true,"origin":"","legend":"Supplementary Figure and Figure legends","description":"","filename":"SupplementaryFigureandFigurelegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-7691213/v1/33945423c571f55576fce1f5.docx"},{"id":96261806,"identity":"dc4c4d55-f5b6-418f-9e79-3e7c5b897a00","added_by":"auto","created_at":"2025-11-19 08:00:45","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":393140,"visible":true,"origin":"","legend":"Supplementary Table 1(screening results)","description":"","filename":"SupplementaryTable1screeningresults.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7691213/v1/13eb6793b1b2881c52387cf7.xlsx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Hyaluronan catabolism supports the peritoneal disseminated metastasis of cancer through the glucuronic acid pathway","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOvarian cancer (OC) represents the most lethal gynecological malignancy, with its high mortality rate largely attributed to its special transcoelomic metastatic mechanism (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). A key challenge is understanding how disseminated tumor cells survive during early metastasis, as they must overcome matrix detachment stress and adapt to the nutrient-deprived peritoneal microenvironment while maintain proliferative capacity (\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Emerging evidence highlights that metabolic adaptations, particularly through alterations in glucose metabolism, lipid utilization and mitochondrial function(\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), are critical for successful metastasis.\u003c/p\u003e\u003cp\u003eThe peritoneal metastatic niche has dual metabolic challenges: hypoxia enforces glycolytic dependence via HIF-1α stabilization (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), while nutrient scarcity drives alternative pathway utilization including glutaminolysis and fatty acid oxidation to meet the bioenergetic and biosynthetic demands (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). These metabolic adaptation occurs in concert with extensive extracellular matrix (ECM) remodeling, where increased deposition of collagen, fibronectin and proteoglycans creates both structural support and pro-metastatic signaling (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The intricate interplay between nutrient scarcity, metabolic adaptation and ECM remodeling establish a permissive niche for tumor cell maintenance and dissemination.\u003c/p\u003e\u003cp\u003eCentral to this ECM reorganization is hyaluronic acid (HA), a key structural component whose role in signaling transduction and tumor promotion is well-documented (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). HA exhibit a striking molecular weight-dependent duality: high-molecular-weight HA (HMW-HA; \u0026gt;1000 kDa) supports tissue homeostasis and exerts tumor-suppressive effects, while low-molecular-weight fragments (LMW-HA; \u0026lt;500 kDa) which generated through hyaluronidase activity, potently promote tumor progression (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). This shift is orchestrated by altered expression of HA synthases (particularly HAS2) and hyaluronidases (HYAL1/2) (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), creating an autocrine loop that sustains malignant phenotypes (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Beyond its structural and signaling roles, HA also serves as a metabolic substrate. HA catabolism generates two key metabolites: N-acetylglucosamine (GlcNAc), which can feed into the hexosamine biosynthetic pathway (HBP) to regulate critical protein modifications (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), and glucuronic acid (GlcA) that is able to enter central carbon metabolism through an evolutionarily conserved pathway. Interestingly, GlcA metabolism shows species-specific divergence. In non-primate mammals, GlcA can be converted to L-ascorbic acid (vitamin C) (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), while primates have developed a unique CRYL1-dependent route that converts GlcA to xylulose-5-phosphate, namely GlcA pathway, directly linking HA degradation to the pentose phosphate pathway (\u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). We hypothesized that this metabolic shift may provide crucial survival advantages when early disseminated cancer cells spread into a glucose- and oxygen-limited, yet HA-rich peritoneal microenvironment. However, its biological significance and underlying mechanisms for a successful transcoelomic metastasis remained a fundamental unanswered question.\u003c/p\u003e\u003cp\u003eTo address this question, we performed a genome-wide CRISPR/Cas9 knockout screen in the orthotopic murine model of OC to identify key genes supporting the peritoneal dissemination. We identified critical genes involved in HA uptake and catabolism, together with genes involved in the GlcA pathway. By investigating the dynamic interplay between HA-mediated extracellular signaling and intracellular metabolic reprogramming, we demonstrated that HA-derived GlcA served as a key substrate for the pentose phosphate pathway (PPP) and glycolysis in peritoneal disseminated cancer cells. This metabolic rewiring facilitated the maintenance and growth of disseminated cancer cells in the early stages of metastasis, highlighting the multiple essential roles of HA not only as a structural component of ECM but also a metabolic regulator and energy reservoir. Our findings suggest that targeting the HA -GlcA -PPP axis may offer a novel diagnostic and therapeutic strategy for preventing and treating cancers with peritoneal disseminated metastasis features.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eGenomic-wide CRISPR knockout screening reveals the potential role of LAYN-mediated HA catabolism in the early peritoneal dissemination of OC.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe previously identified key genes involved in the intraperitoneal dissemination of OC to the peritoneal organs, including intestines, omentum and the peritoneum, through a genome-wide CRISPR/Cas9 knockout screening in the orthotopic xenograft mouse model of OC (\u003cb\u003eSupplementary Fig.\u0026nbsp;1A\u003c/b\u003e and \u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Of note, MAGeCK analyses revealed 3 genes (\u003cem\u003eLAYN, AGBL3\u003c/em\u003e and \u003cem\u003eGABRB1\u003c/em\u003e) showing significant negative enrichment in metastases from all three sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). We were especially interested in the novel HA receptor LAYN because some other key enzymes involved in HA catabolism and the recovery of its product GlcA into the PPP or glycolysis were also enriched (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), such as \u003cem\u003eHYAL1\u003c/em\u003e and \u003cem\u003eHYAL3\u003c/em\u003e (responsible for the degradation of high-molecular-mass HA polymers to HA tetrasaccharides), \u003cem\u003eHEXB\u003c/em\u003e (the β subunit of the lysosomal enzyme β-hexosaminidase that catalyzes the degradation of N-acetyl-hexosamine-containing molecules), \u003cem\u003eAKR1A1\u003c/em\u003e (catalyzing the reduction of D-glucuronate to L-gulonate) and \u003cem\u003eXYLB\u003c/em\u003e (a xylulokinase that converts L-gulonate-derived D-xylulose to PPP metabolite D-xylulose-5-phosphate). Given the disseminated OC cells at the early stage spread throughout the peritoneal cavity by normal HA-rich peritoneal fluid (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), these results suggested a potential role of the metabolic reprogramming of HA catabolism through the glucuronic pathway to PPP and glycolysis in the intraperitoneal dissemination of OC.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo further investigate the reprogramming of HA metabolism in the early stage of intraperitoneal spread of OC cells, we injected GFP-transfected ID8 cells into the peritoneal cavity and isolated the GFP-positive ID8 cells from the peritoneal fluid at day 1, day 14 and day 21, when the disseminated cells adapted and survived in the peritoneal environment (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD) (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). The transcriptomic analyses on these cells revealed that at day 1, the HA receptor CD44, hyaluronidase \u003cem\u003eHyal2\u003c/em\u003e and GlcA pathway enzymes (\u003cem\u003eAkr1a1, Dcxr, Sord\u003c/em\u003e and \u003cem\u003eXylb\u003c/em\u003e) were highly expressed, while the HA catabolism enzymes (such as \u003cem\u003eLayn, Hyal1, Hyal3, Hexa\u003c/em\u003e and \u003cem\u003eHexb\u003c/em\u003e) and key GlcA pathway enzyme \u003cem\u003eCryl1\u003c/em\u003e were upregulated through day 14 to day 21 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). The expression of major enzymes involved in the PPP, glycolysis and TCA cycles were relatively high at day 1 and declined through day 14 to day 21; however, \u003cem\u003ePrps2\u003c/em\u003e and \u003cem\u003eShpk\u003c/em\u003e in PPP and \u003cem\u003ePfkm, Gapdhs, Eno2\u003c/em\u003e and \u003cem\u003eLdhb/Ldhd\u003c/em\u003e in glycolysis were upregulated at day 21, which were able to increase the flux of PPP metabolites into glycolysis for energy production (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). The dynamic alterations in the expression of these key enzymes through day1 to day 21 were further confirmed by RT-qPCR (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF).\u003c/p\u003e\u003cp\u003eIn addition, the IHC analyses of paired OC tissues from the primary sites and peritoneal disseminated sites from five high-grade serous ovarian cancer (HGSOC) patients also showed the significantly increased expression of LAYN, HYAL1, AKR1A1 and CRYL1 in disseminated OC cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG). Meanwhile, the expression of above genes was positively correlated with the poor survival of OC patients according to the transcriptomic analysis of 349 OC patients from the cancer genome atlas (TCGA) database (\u003cb\u003eFig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB\u003c/b\u003e and \u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e). And in another OC cohort (567 samples from 34 patients) from spatial profiling for studying the early dissemination (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), a significant upregulation of \u003cem\u003eLAYN\u003c/em\u003e and \u003cem\u003eHYAL3\u003c/em\u003e was also observed during the transition from stage IC to stage IIA and III when OC disseminates across the abdominal cavity to abdominal organs (\u003cb\u003eFig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eC\u003c/b\u003e).\u003c/p\u003e\u003cp\u003eGiven that HA-rich and glucose-deficient feature of peritoneal environment also challenges the survival of other types of cancers with peritoneal disseminated metastasis trend, such as the bladder cancer (BLCA) and pancreatic adenocarcinoma (PAAD), we investigated the possible reprograming of HA catabolism in these cancer types. As shown in \u003cb\u003eFig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eA\u003c/b\u003e, within 14 days post-intraperitoneal injection of either BLCA cells MB49 or Kras-mutated PAAD cells KPC, the key HA catabolism genes (i.e., \u003cem\u003eLayn, Hyal1\u003c/em\u003e and \u003cem\u003eHyal3\u003c/em\u003e) and GlcA pathway genes (i.e., \u003cem\u003eAkr1a1, Cryl1, Dcxr\u003c/em\u003e and \u003cem\u003eXylb\u003c/em\u003e) were significantly upregulated. Consistently elevated expression of these genes (especially \u003cem\u003eLAYN, HYAL1, AKR1A1, SORD\u003c/em\u003e, and \u003cem\u003eXYLB\u003c/em\u003e) were observed during the stages when cancer cells disseminated away from the primary site in both BLCA (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) and PAAD (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) patient cohorts (\u003cb\u003eFig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eC\u003c/b\u003e), and higher expression of these genes correlated with poor survival of OC, BLCA and PAAD patients (\u003cb\u003eFig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eD\u003c/b\u003e). These results suggested that the rewiring of HA catabolism to GlcA pathway was potentially a common feature for the peritoneal dissemination of human cancers.\u003c/p\u003e\u003cp\u003e\u003cb\u003eHA catabolism fuels OC cell survival and proliferation.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo investigate whether HA catabolism and GlcA pathway are able to be induced in HA-rich and glucose-low environment, OC cell lines were cultured in high glucose (25 mM), low glucose (2.5 mM) and HA-supplemented low glucose medium. RT-qPCR results showed that HA catabolism and GlcA pathway genes were upregulated in HA-rich and glucose-low medium, as well as \u003cem\u003eGAPDHS, LDHB\u003c/em\u003e and \u003cem\u003ePRPS2\u003c/em\u003e in glycolysis and nucleotide synthesis pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, \u003cb\u003eFig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eB\u003c/b\u003e). Similar results were observed in patient-derived ovarian cancer organoids cultured in HA-rich and glucose-low medium (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Notably, 100\u0026ndash;200 kDa HA induced HA catabolism and GlcA pathway genes more efficiently within 48 hours, while 30\u0026ndash;40 kDa and 40\u0026ndash;100 kDa HA exhibited stronger effects at 72 hours (\u003cb\u003eFig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eA\u003c/b\u003e). Western blot results confirmed the significant upregulation of LAYN, HYAL1 and CRYL1 expression under HA-rich and glucose-low environment within 72 hours (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFurther metabolomic analysis showed HA replenishment in low glucose environment resulted in significant increase of the key PPP metabolites 6-phosphogluconate, sedoheptulose 7-phosphate and erythrose 4-phosphate and glycolysis metabolites glucose 6-phosphate and lactate (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE and \u003cb\u003eSupplemented Table\u0026nbsp;3\u003c/b\u003e). The elevated PPP metabolism was also confirmed by the increased synthesis of nucleotides and their derivatives (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). To track the metabolic flux of HA to PPP and glycolysis, we cultured the OVCAR-8 cells in low glucose medium complemented with \u003csup\u003e13\u003c/sup\u003eC-labeled GlcA for 72 hours, the MS analysis showed that the GlcA-derived \u003csup\u003e13\u003c/sup\u003eC enriched in metabolites of glycolysis and PPP-nucleotide synthesis pathway, which were able to be attenuated by silencing CRYL1, the key enzyme in the GlcA pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG). Transcriptomic analysis of intraperitoneal injected ID8 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD) also showed increased cell surface receptor-associated gene sets at day 14 and increased synthesis of nucleotide-containing compound at day 21, while the global protein metabolism was inhibited through day 14 to day 21 (\u003cb\u003eFig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eB\u003c/b\u003e and \u003cb\u003eS3C\u003c/b\u003e). And interestingly, the hexosamine biosynthetic pathway was partially suppressed (\u003cb\u003eFig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eD\u003c/b\u003e), suggesting OC cells might redirect β-N-acetylglucosamine (NAG) from HA degradation to glycosylation, thereby conserving energy otherwise required for \u003cem\u003ede novo\u003c/em\u003e NAG synthesis under glucose limitation. Taken together, these results highlighted a rewired HA metabolism, in which HA degradation derived GlcA was able to be converted to xylulose 5-phosphate through GlcA pathway to fuel the PPP, glycolysis and nucleotide metabolism to meet the energy and substance demand of intraperitoneal disseminated OC cells at the early stage (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH).\u003c/p\u003e\u003cp\u003eTo further investigate the biological significance of rewired HA catabolism for OC cells under low glucose environment, we measured cell proliferation in media supplemented with different concentrations of glucose, HA and HA metabolites. We observed that HA was able to support the slow proliferation of OC cells in low glucose medium as well (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eI). Interestingly, the role of HA to support OC cell proliferation under low glucose condition can be largely mimicked by GlcA, but not NAG (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eI). Notably, the degradation of endogenous HA in OC cells under low glucose condition started from the fourth day (\u003cb\u003eFig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eE\u003c/b\u003e), coinciding with the onset of proliferation changes, suggesting that HA catabolism was a prerequisite for sustaining cell proliferation. HA or GlcA, but not NAG, also sustained the clonal formation of ID8 and OVCAR-8 cells under low glucose environment (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eJ). These findings collectively suggested that HA catabolism serves as a compensatory energy source to sustain OC cell survival under glucose deprivation, with GlcA acting as a critical intermediate.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLAYN is essential for HA-sustained early intraperitoneal dissemination of OC.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAs a novel HA receptor, the role of LAYN in HA catabolism keeps largely unknown. We firstly investigated its role in the uptake of HA. Overexpression of Layn (Layn-OE) in ID8 cells dramatically promoted the uptake of FITC-conjugated HA (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and S4A). In addition, to investigate the role of Layn in supporting the maintenance and growth of early disseminated OC cells, we injected the same amount of Layn-OE (EGFP-labeled) and control (mCherry-labeled) ID8 cells into the peritoneal cavity of mice to compare their capacities to survive in peritoneal environment (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). One day post-inoculation, Layn-OE ID8 cells and control cells remained alive at the equal ratio (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). However, through day 1 to day 7, both cells were gradually eliminated, with the number of control cells reduced much faster than Layn-OE cells, ending up with more Layn-OE cells survived. From day 7 to day 21, Layn-OE cells showed significantly accelerated proliferation within the peritoneal cavity compared to control cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Consistently, knocking down LAYN in OVCAR-8 cells dramatically reduced the uptake of HA (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE and S4B). In low glucose medium, knocking down Layn significantly inhibited HA-sustained proliferation and colony formation of ID8 and OVCAR-8 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG, S4H and S4I), whereas no significant differences were observed in glucose-rich medium (\u003cb\u003eFig. \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003eC-4G\u003c/b\u003e). In the orthotopic murine model of OC established by the intrabursal injection of ID8 or OVCAR-8 cells, knocking down Layn not only significantly inhibited the growth of primary tumor (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH and S4J), but also dramatically reduced the formation of malignant ascites (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eI) and the number of metastatic tumor nodules in the peritoneal cavity (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eJ and S4K). Collectively, these findings identified LAYN as a key mediator of HA uptake, enabling OC cell survival and dissemination in glucose-deprived, but HA-rich environment.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eRHOU facilitates the endosomal recycling of LAYN for the efficient uptake of HA.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo define how LAYN mediates HA uptake, we searched the BioGRID database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://thebiogrid.org/126823\u003c/span\u003e\u003cspan address=\"https://thebiogrid.org/126823\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and identified a potential interaction between LAYN and RHOU (Ras homolog family member U) (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), which is an atypical Rho GTPase that regulates endosomal recycling\u0026mdash;a pathway critical for HA internalization. The human \u003cem\u003eLAYN\u003c/em\u003e has two isoforms generated by alternative splicing, with the long isoform (LAYN-Long, \u003cem\u003eLAYN-L\u003c/em\u003e) carrying an additional 7-amino-acid fragment at its N-terminal compared with the short isoform (LAYN-Short, \u003cem\u003eLAYN-S\u003c/em\u003e) (\u003cb\u003eFig. \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003eA\u003c/b\u003e), among which \u003cem\u003eLAYN-L\u003c/em\u003e expression was able to be induced by HA in OVCAR-8 cells cultured in low glucose medium (\u003cb\u003eFig. \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003eB\u003c/b\u003e). In addition, LAYN-L-substituted OVCAR-8 cells proliferated faster in HA-supplemented, glucose-low medium than LAYN-S-substituted cells (\u003cb\u003eFig. \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003eC\u003c/b\u003e and \u003cb\u003eS5D\u003c/b\u003e). Coimmunoprecipitation (Co-IP) assays showed that LAYN-L had stronger interaction with RHOU than LAYN-S (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB), which could be enhanced by HA (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Proximity ligation assays (PLA) further confirmed HA-enhanced interaction between LAYN-L and RHOU (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003eTo investigate the whole process of LAYN-mediated endocytosis of HA, we transfected OVCAR-8 cells with mCherry-labeled LAYN (LAYN-mCherry) and BFP-labeled RHOU (RHOU-BFP). In low glucose medium, time-course imaging revealed the rapid colocalization of LAYN, RHOU, and HA within 45 minutes the addition of HA (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF), and in LAMP1-EYFP-cotransfected cells the LAYN/RHOU-facilitated endocytic trafficking of HA to lysosomes was clearly observed (\u003cb\u003eFig. \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003eE\u003c/b\u003e). Knocking down RHOU impaired the localization of LAYN to EEA1-labeled early endosome (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG, S5F and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG) as well as RAB11-positive recycling vesicles (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH). This led to lysosomal degradation of LAYN, which was rescued by chloroquine (CQ), a lysosomal acidification inhibitor (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eI and S5H), while the mRNA level of \u003cem\u003eLAYN\u003c/em\u003e was not affected (\u003cb\u003eFig. \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003eI\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eConsistently, RHOU silencing abolished the pro-survival and proliferative advantages conferred by LAYN overexpression in OVCAR-8 cells, as evidenced by diminished HA-dependent colony formation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eJ), cell proliferation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eK) and BrdU incorporation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eL) assays. These results demonstrated that RHOU-mediated endosomal recycling of LAYN was critical for HA internalization and hence HA-fueled OC cell proliferation.\u003c/p\u003e\u003cp\u003e\u003cb\u003eGlcA pathway bridges HA-degradation-derived GlcA to PPP and glycolysis for the early peritoneal dissemination of OC.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOur \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003eex vivo\u003c/em\u003e experiments have suggested that HA-catabolism-derived GlcA is able to fuel PPP and glycolysis through the GlcA pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE-\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG). To determine whether GlcA is essential for HA-supported early peritoneal dissemination of OC in nutrient-deficient environment, we firstly assessed the effects of GlcA and its downstream metabolite D-xylulose (Xul) in GlcA pathway on supporting the proliferation of LAYN-depleted tumor cells in low glucose medium. Given that the complete degradation of 0.1 mg/mL of HA (40\u0026ndash;100 kDa) would yield around 0.1\u0026ndash;0.25 mM GlcA, a concentration as reported for HA turnover in tumor microenvironments (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), we tested wether GlcA or Xul (\u0026ge;\u0026thinsp;0.25 mM) could compensate the role of HA in supporting the proliferation of OC cells whose HA uptake were blocked by silencing LAYN. The colony formation assays and cell proliferation assay confirmed that 0.25 mM GlcA fully restored proliferation in LAYN-depleted OVCAR-8 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB) and ID8 cells (\u003cb\u003eFig. \u003cspan refid=\"MOESM6\" class=\"InternalRef\"\u003eS6\u003c/span\u003eA\u003c/b\u003e and \u003cb\u003eS6B\u003c/b\u003e), and the same results were also observed when 0.25 mM of Xul was supplemented (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD, S6C and S6D).\u003c/p\u003e\u003cp\u003eNotably, while Xul-fueled proliferation remained unaffected, GlcA-dependent cell proliferation was entirely abolished by knocking down CRYL1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE-\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG), consistent with the role of CRYL1 role in converting GlcA to Xul and linking the GlcA pathway to PPP and glycolysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH). In the experimental dissemination murine model of OC (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eI), Cryl1 deletion completely blocked LAYN-mediated peritoneal metastasis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eJ and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eK), further suggesting the critical role of GlcA pathway in bridging HA catabolism to PPP and glycolysis to support OC progression.\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe HA-CD44 signaling axis induces the HA catabolism and GlcA pathway to support the early peritoneal disseminated metastasis of OC.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo get further insights into how HA induced the expression of key HA catabolism and GlcA pathway genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB), we investigated the canonical HA-CD44 signaling axis. While CD44 expression showed only slightly upregulation in peritoneal disseminated OC compared to primary tumors of OC patients (\u003cb\u003eFig. \u003cspan refid=\"MOESM7\" class=\"InternalRef\"\u003eS7\u003c/span\u003eA\u003c/b\u003e), we did not observe stage-dependent alterations of CD44 expression or its correlation with the survival rate in TCGA data (\u003cb\u003eFig. \u003cspan refid=\"MOESM7\" class=\"InternalRef\"\u003eS7\u003c/span\u003eB\u003c/b\u003e and \u003cb\u003eSC\u003c/b\u003e), suggesting that the role of CD44 in tumor progression might not be regulated not at the transcriptional level. In CD44-silenced OC cells, HA-supported cell proliferation and colony formation were dramatically inhibited (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA-\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). Given the role of HA-CD44 signaling axis in the regulation of cancer stemness-related genes (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), we investigated whether HA catabolism-related genes were also targets of this signaling axis. Knocking down CD44 strongly abolished HA-induced expression of both HA catabolism genes and GlcA signaling genes as shown by RT-qPCR analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD) and western blot analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). The regulation was further supported by the positive correlation between CD44 and these metabolic genes in TCGA database (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). It has been reported that CD44 cleavage acts as an amplifier of oncogenic signaling to cause the phosphorylation and activation of CREB(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), and increased phosphorylation of CREB was observed followed by the addition of HA in low glucose media in OC cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). We further analyzed the promoters of \u003cem\u003eLAYN\u003c/em\u003e and \u003cem\u003eHYAL1\u003c/em\u003e genes and found the predicted binding elements CRE for the transcription factor CREB, which was able to be activated by HA-CD44 signaling (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG). The luciferase reporter assay showed that promoters of \u003cem\u003eLAYN\u003c/em\u003e and \u003cem\u003eHYAL1\u003c/em\u003e were able to be activated by HA in a CD44-dependent manner (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG), while deletion of the CRE element dramatically attenuated the responsiveness of these promoters to HA (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eH). Consistently, in the experimental dissemination murine model of OC, knocking down CD44 dramatically reduced the formation of malignant ascites and the number of disseminated tumor nodules in the peritoneal cavity (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI-K), which was able to be partially reversed by reconstituting HA catabolism through ectopic expression of Layn, Hyal1 and Cryl1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI-K), suggesting HA-CD44 signaling as the major driver of GlcA pathway-dependent metastasis. In tumor tissues from the patients, the correlation of p-Creb (activated by HA-CD44 axis) with LAYN and HYAL1 expression were further confirmed (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eL). Interestingly, the expression of \u003cem\u003eCD44\u003c/em\u003e was also induced in OC patient-derived organoids and peritoneally inoculated cancer cells (\u003cb\u003eFig. \u003cspan refid=\"MOESM7\" class=\"InternalRef\"\u003eS7\u003c/span\u003eD-G\u003c/b\u003e), suggesting a possibly positive feedback loop regulating HA-sourced energy metabolism.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eHYAL1 inhibitor garcinol suppresses the peritoneal disseminated metastasis.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGiven the essential role of HA catabolism and GlcA pathway in fueling the peritoneal disseminated metastasis, targeting these metabolic pathways might offer a therapeutic strategy against peritoneal metastasis. We thus focused on two key enzymes: HYAL1, which is pharmacologically inhibited by the natural compound garcinol (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e), and DCXR which catalyzes the conversion of L-xylulose to xylitol, a critical step in D-xylulose generation, and has been reported to be inhibited by niacin (vitamin B3)(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) and butyrate (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Silencing HYAL1 completely abolished HA-sustained proliferation and clonogenicity in OC cells, while knocking down DCXR exerted partial inhibition (\u003cb\u003eFig. S8A-S8F\u003c/b\u003e), confirming HYAL1 as a better target. We prepared the recombinant active HYAL1 protein with \u003cem\u003eK\u003c/em\u003em value around 243.2 nM (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA), against which garcinol showed potent inhibitory activity with IC50 around 4.5 nM (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). In low glucose medium, HA-supported proliferation and the colony formation of OC cell ID8, BLCA cell MB49 and PAAD cell KPC were strongly inhibited by garcinol, which could be rescued by the GlcA supplementation, confirming the anti-tumor effect of garcinol was predominantly mediated through the inhibition of HYAL1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn the experimental dissemination murine model of OC, treatment with garcinol, niacin, and butyrate all reduced the formation of malignant ascites and peritoneal tumor nodules (\u003cb\u003eFig. S8G\u003c/b\u003e and \u003cb\u003eS8H\u003c/b\u003e). However, niacin and butyrate caused slight weight loss (\u003cb\u003eFig. S8I\u003c/b\u003e), especially for niacin-treated mice with severe intestinal torsion being observed. In contrast, garcinol showed no toxicity, supported by histopathological and blood biochemistry analyses (\u003cb\u003eFig S8J\u003c/b\u003e and \u003cb\u003eSupplementary Table\u0026nbsp;4\u003c/b\u003e). Garcinol also strongly inhibited the peritoneal disseminated metastasis in the murine models of BLCA and PAAD (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF).\u003c/p\u003e\u003cp\u003eGiven that HA catabolism-derived GlcA was able to fuel the PPP for the \u003cem\u003ede novo\u003c/em\u003e biosynthesis of nucleotides that might contribute to DNA damage repair (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE), we hypothesized that this pathway probably enhanced resistance to genotoxic agents such as cisplatin, a first-line therapy for OC. In an OC cohort (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.rocplot.com/\u003c/span\u003e\u003cspan address=\"http://www.rocplot.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e), platinum non-responders exhibited elevated expression of HA catabolism\u0026ndash;GlcA pathway genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eG), which was able to be used to predict treatment response (AUC\u0026thinsp;=\u0026thinsp;0.696; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eH). Consistently, in the murine model of OC, combined treatment with garcinol and cisplatin showed synergistic effects on suppressing the peritoneal dissemination of cancer cells than single treatment with either one (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eI-\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eK).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePeritoneal metastasis represents one of the most common form of distant metastases in numerous cancers and is a major contributor to treatment failure and high mortality rates (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Yet, the mechanisms through which cancer cells adapt to the unique peritoneal microenvironment remain poorly understood. In this study, we demonstrated that OC cells could utilize HA as an alternative energy source in the glucose-limited peritoneal environment and this metabolic adaptability extends beyond OC cells to BLCA and PAAD cell. We further identified a hierarchical signaling-metabolic axis initiated by the canonical HA receptor CD44. Its activation leads to upregulation of the novel HA receptor LAYN, hyaluronidases (HYAL1) and key enzyme in GlcA pathway. The degraded HA releases GlcA, which is then channeled through the GlcA pathway to fuel the PPP and glycolysis, thereby sustaining the maintenance and growth of disseminated cancer cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Our findings reveal a critical metabolic adaptation mechanism and point to a promising therapeutic strategy for inhibiting peritoneal metastasis.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe functional role of HA is highly context-dependent, exhibiting diverse and often opposing effects across different pathological conditions. In glioblastoma multiforme, HAS2-mediated HA secretion enhances tumor cell proliferation and migration (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e), while HYALs (particularly HYAL1)-catalyzed HA degradation promotes breast cancer xenograft growth and angiogenesis (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Beyond cancer, HA serves as a critical carbon source for mycobacterial growth, highlighting its exploitation by pathogens (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Notably, the role of HA as a metabolic substrate to support the specific pressures of peritoneal metastasis remains poorly understood. Our study directly addresses this gap by investigating how peritoneal-disseminated tumor cells metabolically exploit HA. We found that OC cells catabolize HA to GlcA, which is channeled into GlcA pathway and PPP, to fuel glycolysis, highlighting their remarkable metabolic plasticity to meet bioenergetic demands and drive metastasis. Specifically, by performing transcriptomic analyses on cancer cells isolated from the peritoneal metastatic niche we observed a dynamic upregulation of the HA-GlcA metabolic pathway. Metabolomic profiling on cancer cells supplemented with HA further confirmed that HA supplementation significantly elevated the levels of key PPP intermediates. Functional validation using \u003csup\u003e13\u003c/sup\u003eC-labeled GlcA tracing demonstrated that GlcA-derived carbon enters central carbon metabolism, a process dependent on CRYL1. This metabolic rewiring was further corroborated in patient-derived organoids and multiple OC cell lines, where HA stimulation robustly induced the expression of GlcA pathway genes under low glucose conditions. These findings reinforce the concept that metabolic reprogramming is a cornerstone of cancer progression, with HA emerging as a versatile substrate under nutrient stress.\u003c/p\u003e\u003cp\u003eHA signaling is mediated through multiple receptors, including CD44, RHAMM, LYVE-1, and the more recently identified Laylin (LAYN) (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). CD44, a non-kinase transmembrane glycoprotein, frequently undergoes alternative splicing, generating variants that contribute to cancer development and progression (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). As a key marker of cancer stem cells, CD44 promotes tumor initiation, therapy resistance, and metabolic reprogramming via activation of PI3K/AKT and MAPK pathways (\u003cspan additionalcitationids=\"CR43 CR44\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). RHAMM promotes pancreatic tumor progression through EGFR signaling, while LYVE-1, which predominantly expressed in lymphatic vessels, facilitates cell proliferation and lymph angiogenesis upon HA binding (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). LAYN, identified as an HA-binding receptor in 2001, has been implicated in colorectal cancer metastasis but remained unexplored in OC(\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Our CRISPR screen uniquely identified LAYN as a metastasis-specific dependency in OC. Further mechanistic studies revealed that internalization of HA is mediated by a RHOU-dependent endocytic pathway linked to LAYN, which facilitates efficient HA uptake and supports GlcA-driven glycolysis under nutrient stress. Moreover, loss of LAYN impaired both HA uptake and degradation, thereby failing to maintain OC cells in early dissemination into peritoneal. Although CD44 was not a top hit in our screen, its ablation also compromised the ability of HA to sustain cell survival, suggesting that CD44 may possess additional roles beyond functioning as an endocytic receptor for HA, especially LAYN. Previous studies have shown that CD44 activation could regulate the expression of metabolism-related genes via phosphorylation of CREB (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). We further elucidated the role of CD44 in this process and found that it primarily regulates the transcription of HA metabolic genes. Luciferase reporter assays confirmed that HA-induced activation of \u003cem\u003eLAYN\u003c/em\u003e and \u003cem\u003eHYAL1\u003c/em\u003e promoters is CD44-dependent and requires intact CREB-binding sites. Importantly, reconstitution of LAYN, HYAL1, and CRYL1 in CD44-deficient cells partially restored metastatic potential in vivo, underscoring the functional hierarchy within the HA-CD44-LAYN metabolic axis. However, given its broad functional roles and the frequent discordance between its transcriptional and protein expression in our research, we prioritized HA catabolic pathway as a more specific and druggable target for inhibiting HA-dependent tumor survival, rather than CD44.\u003c/p\u003e\u003cp\u003eBy systematically mapping the HA metabolic pathway from HA biosynthesis, receptor-mediated uptake and its enzymatic degradation, we identified several potential nodes for disrupting early metastatic dissemination. Our initial approach to pharmacologically inhibit HAS2\u0026mdash;the rate-limiting enzyme in HA synthesis, using 4-methylumbelliferone (4-MU) failed to suppress intraperitoneal HA accumulation (data not shown). Notably, emerging evidence positions 4-MU's anti-tumor effects primarily through thymidine phosphorylase inhibition rather than HAS2 blockade (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). We therefore systematically interrogated the degradation branch of HA metabolism and identified two key enzymatic targets: HYAL1, the major hyaluronidase responsible for HA breakdown, and DCXR (dicarbonyl/L-xylulose reductase), which catalyzes the conversion of L-xylulose to D-xylulose. Functional comparison via in vitro knockdown experiments revealed that genetic silencing of \u003cem\u003eHYAL1\u003c/em\u003e more potently abrogated HA-sustained tumor proliferation compared to \u003cem\u003eDCXR\u003c/em\u003e depletion, establishing HYAL1 as a superior therapeutic target. We subsequently evaluated small-molecule inhibition of these targets in vivo. Although previous studies identified Garcinol, a xanthonoid natural product, as a nanomolar-range inhibitor of HYAL1 and some endogenous metabolites including butyrate and niacin (Vitamin B3) as inhibitors of DCXR (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e), the in vivo efficacy of targeting this pathway remained unexplored. Distinct from in vitro results, xenograft experiments confirmed that three distinct small-molecule inhibitors targeting these enzymes potently suppressed disseminated OC metastasis. Notably, garcinol demonstrated a highly favorable biosafety profile. What\u0026rsquo;s more, consistent with report that tumors with peritoneal metastases share a metabolic microenvironment (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e), garcinol potently suppressed peritoneal dissemination not only in OC but also in BLCA and PAAD, highlighting a conserved metabolic vulnerability across malignancies with peritoneal tropism. Strikingly, the synergy with cisplatin arised from dual targeting of HA-fueled metabolic adaptation (via HYAL1 blockade) and DNA integrity (via cisplatin), effectively disrupting both energy homeostasis and genomic stability in disseminated tumor cells. Our findings position HYAL1 inhibition as a complementary strategy to conventional chemotherapy to impede early metastatic colonization. Further studies should delineate whether HA catabolic rewiring modulates cisplatin sensitivity, potentially guiding rational combinations for clinical translation.\u003c/p\u003e\u003cp\u003eIn summary, our study revealed that peritoneal-metastasized tumor cells activate a CD44\u0026ndash;LAYN-mediated metabolic pathway to generate HA into GlcA, which fuels glycolysis and PPP under glucose-limited conditions, supporting metastatic growth. This highlights the metabolic flexibility of disseminated tumor cells within the peritoneal niche. Moreover, we uncovered the conserved role of HA catabolism across multiple cancer types with peritoneal tropism, providing new insight into microenvironment-driven metabolic adaptation. Importantly, pharmacological inhibition of HYAL1 with garcinol effectively suppressed HA-driven metastasis and enhanced cisplatin response in vivo. Therefore, targeting the HA-GlcA metabolic axis represents a promising therapeutic strategy to inhibit peritoneal dissemination and improve outcomes for patients with advanced OC and other peritoneal metastases.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eThe CRISPR-Cas9 library screen in the murine model of OC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA genome-wide CRISPR-Cas9 screen was performed using the GeCKO-v2 human library (Addgene) developed by Feng Zhang\u0026rsquo;s lab, which comprised 122,756 sgRNAs targeting 19,050 protein-coding genes, 1,864 miRNAs, and 1,000 non-targeting controls. For the ovarian cancer model, SK-OV-3 cells were transduced with lentiviral particles at an MOI of 0.3-0.5 to ensure single-gene perturbations, followed by puromycin (Sigma-Aldrich) selection. After 14 days of in \u003cem\u003evitro\u003c/em\u003e expansion, 2\u0026times;10⁶ sgRNA-expressing cells were orthotopically injected into NOD-SCID mice (SPF Biotechnology, Beijing, China) (n=3) via intrabursal implantation. Tumor tissues from primary and metastatic sites (including peritoneal nodules, ascites, and abdominal wall lesions) were harvested after 30-40 days, dissociated with collagenase, and expanded in culture. This \u003cem\u003ein vivo\u003c/em\u003e selection process was repeated for three cycles to enrich metastasis-associated clones. Following the final round, genomic DNA from both primary (first-round) and metastatic (third-round) populations was extracted using the TIANamp Genomic DNA Kit (TIANGEN) for sgRNA amplification and deep sequencing. MAGeCK-VISPR was used to identify significantly enriched sgRNAs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of OC patient samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrimary tumors and matched metastatic lesions samples were collected from patients diagnosed with high serous ovarian adenocarcinoma at Tianjin Center Hospital of Gynecology Obstetrics in 2022 (n=5). All participants provided informed consent, and the study was conducted in compliance with ethical guidelines approved by the Institutional Review Boards of Nankai University and Tianjin Center Hospital (Ethics Approval No.: NKUIRB2023168) in accordance with the Declaration of Helsinki. Fresh tissue samples, including primary ovarian tumors and peritoneal metastases were surgically resected and processed immediately. Each specimen was divided for multiple analyses\u0026mdash;one portion fixed in 4% paraformaldehyde for immunohistochemical (IHC) evaluation, while another was preserved in TRIzol reagent for other assays. Histopathological classification and clinical staging were independently verified by experienced pathologists and oncologists.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe murine models of OC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll experimental protocols involving animals were reviewed and approved by the Institutional Animal Ethics Committee of Nankai University (Ethic approved number: 2023-SYDWLL-000634). To establish orthotopic ovarian tumor models, female immunodeficient (NOD-SCID) or immunocompetent (C57BL/6) mice aged 6 weeks were anesthetized for surgical implantation. Human OVCAR-8 cells (5\u0026times;10\u003csup\u003e6\u003c/sup\u003e cells in 20 \u0026mu;L PBS) or murine ID8 cells (2\u0026times;10\u003csup\u003e^\u003c/sup\u003e6 cells in 10 \u0026mu;L PBS) were microinjected into the right ovarian bursa. Tumor progression was monitored for 120 days (OVACR-8) or 60 days (ID8) post-implantation before terminal analysis.\u003c/p\u003e\n\u003cp\u003eFor the metastatic dissemination model, syngeneic C57BL/6 mice received intraperitoneal injections of 2\u0026times;10\u003csup\u003e^\u003c/sup\u003e6 ID8 GFP cells or equal number of ID8 Vec/LAYN-OE labled with different color suspended in 100 \u0026mu;L PBS. The abdominal fluid was washed out with PBS for flow cytometry analysis or sorting.\u003c/p\u003e\n\u003cp\u003eFor \u003cem\u003ein vivo\u003c/em\u003e therapeutic assays, syngeneic C57BL/6 mice received intraperitoneal injections of 2\u0026times;10\u003csup\u003e^\u003c/sup\u003e6 luciferase-labeled ID8/KPC/MB49 cells. Mice were randomly divided into different group (n=5~6) at day 5 post injection. For the OC model, the mice were intraperitoneal injected with vehicle/ Garcinol (1 or 3 mg/kg,)/ cisplatin (5 mg/kg)/ butyrate (100 or 300 mg/kg) / niacin (50 or 150 mg/kg) every 3 days from day 7 to day 60 post-injection. For other tumor model, the mice were intraperitoneal injected with vehicle/ Garcinol (1mg/kg) from day 3 to day 30 post-injection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell culture\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSK-OV-3 cell line and HEK 293T were purchased from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). OVCAR-8 cell line was purchased from American Type Culture Collection. ID8 and MB49 cell lines were purchased from Merck (Darmstadt, Germany). KPC cell line (Cat. NO. NM-YD04) was purchased from Shanghai Model Organisms Center, Inc. KPC, ID8, MB49, KPC1199 and HEK293T were grown using Dulbecco\u0026apos;s modified Eagle\u0026apos;s medium (DMEM) (Servicebio) supplemented with 10% fetal bovine serum (FBS) (ViVacell) and 1% penicillin/ streptomycin (P/S) (Servicebio).\u0026nbsp;SK-OV-3 cells were cultured with McCoy\u0026rsquo;s 5A Medium Modified (ViVacell). OVCAR-8 cells were cultured with RPMI-1640 Medium Modified (Servicebio). The cells were maintained in an atmosphere of 5% CO\u003csub\u003e2\u003c/sub\u003e at 37 \u0026deg;C in recommended medium and passaged using 0.05% trypsin/EDTA (Meilunbio). All cell lines were confirmed by STR analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePlasmid construction and stable cell line establishment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo transcript variants of LAYN and RHOU were amplified by RT-PCR using cDNA derived from SK-OV-3 cells. The sequences of Layn, Hyal1 and Cryl1 were amplified by RT-PCR using cDNA derived from mouse lung tissues. The coding sequences were subsequently cloned into the pLV-EF1\u0026alpha;-MCS-IRES-Bsd lentiviral vector (Biosettia Inc.), incorporating a C-terminal V5/flag/mcherry epitope tag immediately upstream of the stop codon. For knockdown studies, shRNA sequences targeting indicated genes were designed using the Thermo Fisher RNAi Designer tool and inserted into the pLV-H1-EF1\u0026alpha;-puro plasmid (Biosettia Inc.). For dual-luciferase studies, promoters of LAYN and HYAL1 were cloned from genomic DNA from HEK 293T and subsequently cloned into PGL3-Basic plasmid (Biosettia Inc.). All primers and shRNA template sequences are provided in Supplementary Table 5, and plasmid integrity was verified by Sanger sequencing (Sangon Biotech).\u003c/p\u003e\n\u003cp\u003eLentiviral particles were generated by transfecting Lenti-293T cells (Biosettia Inc.) with the constructed plasmids. Ovarian cancer cells were then transduced at an MOI of 1.0, followed by antibiotic selection\u0026mdash;blasticidin (2.5\u0026ndash;5.0 \u0026mu;g/mL) for overexpression lines or puromycin (5 \u0026mu;g/mL) for knockdown lines. After a 14-day selection period, polyclonal populations were assessed for target gene modulation via Western blotting and qRT-PCR prior to functional assays or in vivo experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantitative real-time PCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA was isolated from cell samples using TRIeasy\u0026trade; LS reagent and subsequently reverse transcribed into cDNA with Hifair\u0026reg;\u0026nbsp;Ⅲ\u0026nbsp;1st Strand cDNA Synthesis SuperMix for qPCR (Yeasen). qPCR amplification was carried out on a StepOnePlus system (Thermo Fisher) using SYBR Green SuperMix (Yeasen), with the following thermal cycling conditions: 95\u0026deg;C for 6 min, then 45 cycles of 95\u0026deg;C for 30 sec and 60\u0026deg;C for 45 sec. Gene expression levels were normalized to \u0026beta;-actin and analyzed via the 2\u003csup\u003e\u0026minus;\u0026Delta;\u0026Delta;Ct\u003c/sup\u003e method. Primer sequences are provided in \u003cstrong\u003eSupplementary Table 5\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtein extraction and western blot\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells were lysed in RIPA buffer containing protease and phosphatase inhibitors. Protein concentrations were measured with the Pierce BCA Assay. Equal protein amounts (typically 20-50 \u0026mu;g) were resolved by 10% SDS-PAGE and electrophoretically transferred to PVDF membranes. After blocking with 5% non-fat dry milk in TBST for 1 h at room temperature, membranes were incubated with primary antibodies (listed in \u003cstrong\u003eSupplementary Table 6\u003c/strong\u003e) overnight at 4\u0026deg;C with gentle agitation. After washing, membranes were incubated with HRP-conjugated secondary antibodies (Proteintech, Wuhan, China) for 1 h at room temperature. Signals were detected using enhanced chemiluminescence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHematoxylin and eosin (H\u0026amp;E) and immunohistochemistry (IHC) staining\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor histopathological examination, OC tissues were fixed in 4% paraformaldehyde (Sigma-Aldrich) and processed through graded ethanol dehydration prior to paraffin embedding. Serial sections (5 \u0026mu;m) were prepared and stained with hematoxylin-eosin (OriGene) for morphological evaluation.\u003c/p\u003e\n\u003cp\u003eImmunohistochemical procedures involved peroxidase inactivation with 3% H₂O₂ followed by heat-mediated antigen retrieval. Sections were blocked with 5% normal goat serum before sequential incubation with primary antibodies and biotinylated secondary antibodies (Vector Laboratories). Signal amplification was achieved using streptavidin-HRP (Vector Laboratories), with DAB chromogen (Zsgb-Bio) development limited to 2 minutes. Nuclear counterstaining was performed with hematoxylin. Antibody details are provided in \u003cstrong\u003eSupplementary Table 6\u003c/strong\u003e. Semiquantitative analysis employed an H-score system, calculated as the product of staining intensity (0-3 scale) and percentage of positive cells (0-4 scale), with final scores ranging from 0 to 12.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunofluorescent (IF) staining\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells after different treatment were cultured on glass coverslips in 24-well plates. After PBS washing, samples were fixed with 4% PFA for 10 min at room temperature. Non-specific binding was blocked with 5% goat serum, followed by incubation with primary antibodies \u003cstrong\u003e(Supplementary Table 6\u003c/strong\u003e) and corresponding fluorescent secondary antibodies (Alexa Fluor-488/594, ThermoFisher). Nuclei were visualized with DAPI staining (Sigma-Aldrich). Fluorescent images were acquired using an Olympus FV1000 confocal system and quantified with ImageJ software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOrganoid derivation, culture and treatment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOrganoids were derived from tumor samples of patients with OC and cultured according to the introduction of High-Grade Serous Ovarian Cancer Organoid Kit (Serum-free) kit (K2167-HS, biogenous technologies). Briefly, Primary biopsies are collected in cold storage solution, dissected to enrich tumor tissue, minced, and enzymatically digested. The resulting cell suspension is filtered, subjected to red blood cell lysis if needed, washed, and centrifuged. Cells are resuspended in reduced-growth-factor ECM (Matrigel) and plated as droplets. After ECM solidification, serum-free, organoid-specific complete medium (formulated from basal medium and supplements B-E, tailored to tumor heterogeneity) is added. Organoids are cultured at 37\u0026deg;C/5% CO₂ with medium changes every 3-4 days.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo harvest bioGenous\u0026trade; HGSC organoids from ECM for H\u0026amp;E, or RNA extraction, first aspirate medium and wash wells gently with ice-cold PBS supplemented with 1% FBS. Dissolve ECM by incubating with ice-cold Cell Recovery Solution (biogenous technologies) at 4\u0026deg;C for 30 min. Transfer the suspension to a chilled tube, centrifuge (200\u0026ndash;300 \u0026times; g, 5 min, 4\u0026deg;C), and aspirate supernatant. Wash pellets thoroughly 2\u0026ndash;3 times with ice-cold PBS to remove ECM contaminants. For H\u0026amp;E, embed washed organoids in histology cassettes and fix immediately in 4% PFA for 1h. For RNA extraction, lyse the final pellet directly in TRIeasy\u0026trade; LS reagent; maintain RNase-free conditions and store lysates at \u0026minus;80\u0026deg;C. Minimize handling time and maintain cold chain throughout, except during fixation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCo-Immunoprecipitation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCell lysates were immunoprecipitated with anti-Flag/mCherry antibody (\u003cstrong\u003eSupplementary Table 6\u003c/strong\u003e) for 4 hours at 4\u0026deg;C, followed by incubation with protein G agarose beads (CWBIO) overnight with constant rotation. After extensive washing, bound proteins were eluted using 1\u0026times; SDS loading buffer through boiling, then separated by SDS-PAGE. Western blotting was subsequently performed to detect the potential interaction between LAYN and RHOU proteins.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProximity Ligation Assay (PLA)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo detect LAYN-RHOU interactions in situ, cells were fixed with 4% paraformaldehyde, permeabilized with 0.1% Triton X-100, and blocked with 5% BSA in PBS. Primary antibodies (\u003cstrong\u003eSupplementary Table 6\u003c/strong\u003e) targeting the LAYN and RHOU proteins were incubated overnight at 4\u0026deg;C. After washing, species-specific PLA probes (Duolink\u0026reg;, Sigma-Aldrich) were applied for 1 h at 37\u0026deg;C. Ligation and amplification steps were performed according to the manufacturer\u0026rsquo;s protocol, using fluorescently labeled oligonucleotides to generate discrete puncta at interaction sites. Nuclei were counterstained with DAPI. Images were acquired using an Olympus FV1000 confocal system and quantified with ImageJ software. Negative controls omitted primary antibodies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFlow cytometry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe abdominal fluid was washed out with PBS and processed for OC cell profiling. Red blood cells were removed using a lysis buffer (Solarbio), followed by washing in PBS supplemented with 1% FBS. The cell suspension was filtered through a 40 \u0026micro;m nylon mesh (BD Biosciences) to ensure a single-cell suspension. CD45-APC antibody incubation was performed for 30 minutes at 4\u0026deg;C in the dark, followed by two washes with 1% FBS/PBS. Flow cytometry data were acquired on an LSR Fortessa system (BD Biosciences) and analyzed using FlowJo software (BD Biosciences).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell proliferation assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1.5 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e ID8, MB49 and KPC1199 cells or 2 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e OVACR-8 cells were seeded in 48-well plates and incubated at 37 \u0026deg;C in the incubator. Cells were detached by trypsinization counted every 24 h by using a Countess 2 Automated Cell Counter (Thermo-Fisher Scientific) until the cells reached full confluency. The cell number at each time point was the average of three wells. To determine the effects of HA/GlcA/NAG, ID8, MB49, KPC and OVCAR-8 were treated with HA/GlcA/NAG (Meryer, Shanghai) in glucose-free DMEM (Pricella, Wuhan) supplemented with 2.5 mM glucose. HA with different molecular mass, GlcA and NAG were dissolved in PBS with ultrasonic solubilization. To determine the inhibitor of HYAL1, ID8, MB49, KPC were treated with Garcinol (TargetMol, Shanghai). The cell number at each time point was the average of three wells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eColony formation assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1.5 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e ID8, MB49 and KPC cells or 2 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e OVACR-8 cells were seeded in 6-well plates and incubated at 37 \u0026deg;C in the incubator until colonies could be identified. The treatments were same as Cell proliferation assay. After fixed with 4% paraformaldehyde, stained with crystal violet and counted by Image J software, the numbers of colonies were presented as the average of three biological replicates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBrdU Proliferation Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOVCAR-8 cells were cultured on glass coverslips in 24-well plates and pulsed with 10 \u0026mu;M BrdU (Beyotime, ST1056) for 12-hour durations. Following incubation, cells were fixed and processed for immunofluorescence staining to detect BrdU incorporation, following standard IF protocols. Nuclei were counterstained with DAPI to visualize all cells. The percentage of BrdU-positive cells was quantified to evaluate proliferative activity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTargeted metabolomics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells (1\u0026times;10\u003csup\u003e7\u003c/sup\u003e/sample) were quenched in liquid nitrogen and extracted with 80% methanol containing 10 \u0026mu;M norvaline (internal standard). Tests were performed and analyzed on an ultra-high performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS) system (Novogene, Beijing, China). The samples were centrifuged at 1000 rpm for 3 min (4\u0026deg;C) to remove the supernatant. Then homogenized with 250 \u0026mu;L of methanol (80%) which contained mixed internal standards and centrifuged at 15000 rpm for 15 min (4\u0026deg;C) to remove the protein. The supernatant was added to water by well vortexing as the diluted sample. Then 100 \u0026mu;L of them were taken respectively and homogenized with 100 \u0026mu;L of imino-bis (methylphosphonic acid) by well vortexing. After that, centrifuged at 15000 rpm for 15 min. Finally, the supernatant was injected into the LC-MS/MS system for analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUntargeted \u003csup\u003e13\u003c/sup\u003eC metabolic flux\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOVACR-8 cells were cultured in glucose-free DMEM (Procell, Wuhan, China) supplemented with 10% dialyzed FBS, 2.5 mM glucose and 5 mM \u003csup\u003e13\u003c/sup\u003eC-GlcA. After 72 h of labeling, cells were quenched and extracted in 80% methanol. The Tsinghua University Metabolism and Lipidomics Platform offers untargeted metabolic tracing services using \u003csup\u003e13\u003c/sup\u003eC-GlcA with high-resolution mass spectrometry analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHyaluronic Acid staining\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOVCAR-8 cells were cultured on glass coverslips in 24-well plates and stained with 1% Alcian Blue (Solario) for 30 min, rinsed in 3% acetic acid and captured using optical microscope.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLive imaging of tumor progression\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter the intraperitoneal injection of mouse tumor cells, 100\u0026mu;L D-luciferin (Psaitong Biotechnology, Beijing) was injected intraperitoneally at different time for monitor the dissemination progression. Metastatic burden was monitored two-weekly by bioluminescence using the Tanon 5200 multi-imaging system and the software GToC 1.3.5 for analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDual-luciferase reporter assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe promoter region (\u0026minus;2000 to -1) of \u003cem\u003eLAYN\u003c/em\u003e and promoter region (\u0026minus;2000 to \u0026minus;30) of \u003cem\u003eHYAL\u003c/em\u003e genes were cloned into the plasmid pGL3(Promega) to create the firefly luciferase reporter plasmid. OVCAR-8 shLacZ/shCD44 cells were transiently transfected with renila luciferase as control reporter plasmid and PGL-3 firefly luciferase reporter plasmid. Dual-Luciferase reporter assay system (Promega) was used to measure the luciferase activity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermination of HYAL1 Enzyme Kinetics and Inhibitor Activity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePurified HYAL1 protein (MCE, HY-P70411, 50nM) were incubated with HA (0-500 nM) in 100 \u0026mu;L of sodium acetate buffer (0.2 M, pH=4 with 150 mM NaCl) at 37\u0026deg;C for catalyzation. Reactions were terminated by adding 10 \u0026micro;L of 1.2 M potassium tetraborate and boiling in a water bath for 5 min. NAG release was quantified by adding of 100 \u0026micro;L p-dimethylaminobenzaldehyde (DMAB) reagent (10% w/v in glacial acetic acid), incubating at 37\u0026deg;C for 30 min, and measuring absorbance at 585 nm. Enzyme activity was expressed as nmol NAG released per minute (nM/min), calculated from a standard curve of known NAG concentrations (0-500 nM).\u003c/p\u003e\n\u003cp\u003eFor inhibition studies, HYAL1 protein was pre-incubated with garcinol (0-200 \u0026mu;M in 0.1% DMSO) for 10 min at 37\u0026deg;C prior to addition of HA (optimal concentration determined from kinetics experiments). The reaction mixture was then processed identically to the kinetics assay. Negative controls included: (1) substrate blank (reaction mixture without enzyme), and (2) enzyme blank (reaction mixture without HA). The half-maximal inhibitory concentration ((IC\u003csub\u003e50\u003c/sub\u003e) was determined by nonlinear regression analysis using GraphPad Prism 8. Each inhibitor concentration was tested in three replicates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBioinformatic analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe information about the HA catabolism-related genes mRNA level in OC patients were obtained from the TCGA database. The association between the survival of OC patients with HA metabolism-related genes expression was analyzed using the data from TCGA database (n=349). The correlation of CD44 and HA metabolism-related genes was analyzed using GEPIA at http://gepia.cancer-pku.cn/ .\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeep RNA sequencing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA of sorted ID8 cells at different time were harvested using TRIzol reagent for RNA extraction. The deep RNA sequencing was performed and analyzed on NovaSeq (Novogene, Beijing, China). Gene Set Enrichment Analysis (GSEA) was performed using the Gene Ontology (GO) database (http://geneontology.org/) as the reference gene set collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis was performed using Prism 8.0 software (GraphPad Software, San Diego, CA, USA). Quantitative data are presented as means \u0026plusmn; SEM, and differences between groups were analyzed using the student\u0026rsquo;s t-test or two-way ANOVA for continuous variables, as appropriate. Survival curves were analyzed using the Kaplan\u0026ndash;Meier method, with between-group differences assessed by the log-rank test. Co-expression of CD44 and other genes was evaluated using the Spearman or Pearson test. Statistical parameters, including definitions of n, specific tests, and exact p-values, are detailed in the figures and legends. Significance thresholds were set as follows: *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, \u0026quot;ns\u0026quot; indicates not significant.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eCompeting Interest Statement:\u003c/h2\u003e\u003cp\u003eThe authors declare no potential conflict of interests.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCONFLICT OF INTEREST STATEMENT\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eACKNOWLEDGMENTS\u003c/h2\u003e\u003cp\u003eThis work was supported by the grants from the National Natural Science Foundation of China (82573055, 32570916, 32200641, 323B2025, 32271350, 82172801, 82472870). We thank ChiPlot (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.chiplot.online/\u003c/span\u003e\u003cspan address=\"https://www.chiplot.online/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for drawing Fig.\u0026nbsp;1E and home-for-researchers (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.home-for-researchers.com/#/\u003c/span\u003e\u003cspan address=\"https://www.home-for-researchers.com/#/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003ch2\u003eDATA AVAILABILITY STATEMENT\u003c/h2\u003e\u003cp\u003eThe research data underlying these findings may be requested from the corresponding author with reasonable rationale.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eL. A. 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To investigate the molecular mechanisms enabling this adaptation, we conducted a genome-wide CRISPR/Cas9 knockout screening in an orthotopic ovarian cancer (OC) model. We identified a series of genes involved in hyaluronic acid (HA) catabolism and glucuronic acid (GlcA) metabolism, including the HA receptor LAYN, HA catabolism enzymes (including HYAL1 and HYAL3) and key GlcA metabolic enzymes (such as AKR1A1 and XYLB). By integrating transcriptomic and metabolic analyses in multiple experimental systems, we demonstrated that HA induced the expression of key HA catabolism and GlcA pathway enzymes, which further led to the release of free GlcA from HA degradation. This GlcA is subsequently metabolized through the GlcA pathway, the pentose phosphate pathway (PPP) and glycolysis to support the maintenance and growth of disseminated OC cells. In addition, we found an atypical Rho GTPase RHOU facilitated the LAYN endosomal recycling for efficient HA uptake. Intriguingly, the rewiring of HA catabolism through GlcA pathway was regulated by its classical receptor CD44 and occurred in other peritoneal disseminating cancers such as bladder cancer and pancreatic adenocarcinoma. Importantly, pharmacological inhibition of HYAL1 with garcinol potently suppressed peritoneal disseminated metastasis in xenograft mice and synergized with cisplatin. In this study, we collectively reported a novel metabolic reprogramming feature of the early peritoneal disseminated cancer cells, which provides new diagnostic and therapeutic strategies for the cancers prone to the potential dissemination.\u003c/p\u003e","manuscriptTitle":"Hyaluronan catabolism supports the peritoneal disseminated metastasis of cancer through the glucuronic acid pathway","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-19 08:00:40","doi":"10.21203/rs.3.rs-7691213/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b7aa9a89-a3cd-4442-8ea0-a0ce7504dbf6","owner":[],"postedDate":"November 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":58069922,"name":"Biological sciences/Cancer/Cancer metabolism"},{"id":58069923,"name":"Biological sciences/Cancer/Metastasis"},{"id":58069924,"name":"Biological sciences/Cell biology/Cellular imaging"}],"tags":[],"updatedAt":"2025-12-19T17:27:45+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-19 08:00:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7691213","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7691213","identity":"rs-7691213","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}