Abstract Objective To identify common and sex-specific phosphorylation dynamics during hepatocarcinogenesis in HrasG12V transgenic mice (Hras-Tg). Methods We constructed a phosphoproteomic database using male/female (M/F) tumor (T), precancerous (P), and wild-type liver tissues (W) from Hras-Tg, validated via parallel reaction monitoring (PRM). Comparative analysis and hierarchical clustering were employed to delineate shared and sex-stratified phosphorylation signatures in hepatocellular carcinoma (HCC) development. Results PRM-validated phosphoproteomic profiling quantified 5,410 phosphorylation sites across 2,427 proteins. Analysis of common features revealed nuclear-enriched phosphoprotein accumulation in tumors versus precancerous/wild-type tissues (T vs. P/W). KEGG pathway analysis identified consistently dysregulated pathways including MAPK signaling, focal adhesion, and protein digestion/absorption. Protein-protein interaction (PPI) network analysis of shared phosphoproteins pinpointed key regulators (Alb, Hspa5, Psn), with high connectivity, suggesting potential regulatory roles in the network. Sex-specific analyses demonstrated distinct phosphorylation patterns: males exhibited extensive membrane protein phosphorylation alterations, while females showed predominant cytoplasmic modifications. KEGG pathway mapping revealed male-biased dysregulation in Ras signaling, mTOR pathways, and actin cytoskeleton regulation. Functional annotation indicated greater complexity of phosphorylated proteins in males. Notably, phosphorylation events occurring on proteins with annotated kinase or phosphatase activity were more prevalent in males, suggesting enhanced phosphorylation-mediated signaling dynamics. Significance: This study establishes the first sexual dimorphism-aware phosphoproteomic resource for Ras-driven hepatocarcinogenesis, systematically characterizing conserved and sex-divergent phosphorylation networks. The findings provide preliminary molecular insights into gender disparities in HCC progression and may guide future therapeutic exploration. Supplementary Information The online version contains supplementary material available at 10.1186/s12935-025-04015-2. Keywords: Phosphoproteomics, Sexual dimorphism, Hepatocellular carcinoma, Ras oncogene, Signaling pathways Introduction Hepatocellular carcinoma (HCC), accounting for 85–90% of primary liver malignancies [[37]1], continues to impose a substantial global health burden. Ranked as the sixth most common neoplasm and the third leading cause of cancer-related mortality worldwide [[38]2], HCC affects more than 620,000 new patients each year, with a one-year survival rate of less than 50% [[39]3]. Notably, this malignancy demonstrates a striking male predominance [[40]4, [41]5]. Epidemiologic studies consistently demonstrate 2–3-fold higher incidence and mortality rates in males compared to females across most geographic regions [[42]2]. Although significant progress has been made in understanding the molecular basis of sex differences in HCC, across multiple levels, including hormonal signaling, gene expression, and metabolism, little is known about how these differences are reflected at the phosphoproteomic level. RAS mutations represent some of the most common genetic alterations across human cancers [[43]6]. The Ras/MAPK signaling pathway is frequently dysregulated in human HCC, with its aberrant activation reported in numerous studies [[44]7, [45]8]. This pathway has consequently become a major therapeutic target in clinical HCC management [[46]8, [47]9]. In mouse HCC models, Ras mutations are likewise observed at relatively high frequencies, with Hras identified as the most commonly affected isoform in both spontaneous and carcinogen-induced liver tumors [[48]10]. Interestingly, rodent HCC carcinogenesis models - including spontaneous tumorigenesis, chemical induction, and chronic viral infection systems - consistently recapitulate the male predominance observed in human HCC [[49]4, [50]11]. To investigate this sexual dimorphism, we previously developed a HrasG12V transgenic mouse model featuring hepatocyte-specific expression of the oncogenic HrasG12V variant under the control of the albumin enhancer/promoter [[51]11]. This model reliably develops male-predominant liver tumors at defined time points, providing an ideal platform for investigating sex-specific mechanisms in hepatocarcinogenesis. Protein phosphorylation, a fundamental post-translational modification regulating cellular signaling [[52]12], is frequently dysregulated in cancer pathogenesis [[53]13]. Recent phosphoproteomic studies in HCC have begun to delineate the disease landscape, identifying molecular subtypes with distinct clinical outcomes and therapeutic vulnerabilities [[54]14], as well as uncovering mechanisms of drug resistance such as sorafenib refractoriness through dysregulated kinase activities [[55]15]. However, despite these important advances, systematic analyses of sex-specific phosphorylation networks remain conspicuously absent. Considering that biological sex may differentially regulate critical signaling pathways, comparative phosphoproteomic profiling by sex could reveal molecular mechanisms contributing to gender disparities in HCC development. To address this gap, we conducted comprehensive phosphoproteomic analyses of liver tumors and adjacent non-tumor tissues from HrasG12V transgenic mice (9-month males and 15-month females) along with age- and sex-matched wild-type controls. Our differential phosphorylation analysis identified both conserved and sex-specific molecular alterations. Subsequent bioinformatic interrogation revealed distinct Ras-driven mechanisms and sex-biased molecular features in hepatocarcinogenesis. Materials & methods Animal models and tissue preparation Wild-type C57BL/6J mice (Non-Tg) served as controls, while HrasG12V transgenic mice (Hras-Tg) constituted the experimental group [[56]11]. All animal procedures including breeding, handling, and tissue sampling were performed according to established protocols from our previous publication [[57]16]. For phosphoproteomic analysis, we collected normal liver tissues (W) from Non-Tg mice and precancerous lesions (P) and HCC tissues (T) from Hras-Tg mice. Tissues were obtained from male and female mice aged 9 and 15 months, respectively (n = 9 per group; total 54 samples). All experimental protocols were approved by the Institutional Animal Care and Use Committee of Dalian Medical University. Mice were sacrificed via cervical dislocation followed by immediate tissue dissection. Excised tissues were rinsed in ice-cold PBS (0.1 M, pH 7.4) to remove blood contaminants and sectioned into 1 mm³ fragments using sterile surgical scissors. Tissue fragments were flash-frozen in liquid nitrogen and mechanically pulverized using a cryogenic grinding system. The resulting cell powder was transferred to 5 mL polypropylene centrifuge tubes. Powdered tissues were lysed in 4 volumes (w/v) of ice-cold buffer containing 8 M urea and 1% protease inhibitor cocktail. Homogenization was achieved through three cycles of high-intensity ultrasonication (Scientz JY92-IIN) using 30-second pulses with 1-minute cooling intervals on ice. Cellular debris was removed by centrifugation at 12,000 × g (4 °C, 10 min). Supernatants were collected and protein concentrations determined using a bicinchoninic acid (BCA) assay kit (Pierce™), following manufacturer specifications. Trypsin digestion protocol Prior to enzymatic digestion, proteins were first reduced with 5 mM dithiothreitol (DTT) at 56 °C for 30 min followed by alkylation with 11 mM iodoacetamide (IAA) in dark conditions at room temperature (25 °C) for 15 min. The alkylated protein solution was subsequently diluted with 100 mM triethylammonium bicarbonate (TEAB) to reduce urea concentration below 2 M. Trypsin digestion was then performed using a two-step enzymatic cleavage protocol: initial overnight digestion at 37 °C with trypsin added at 1:50 (w/w) enzyme-to-substrate ratio, followed by a secondary 4-hour digestion supplemented with an additional aliquot of trypsin at 1:100 (w/w) ratio. TMT labeling Following trypsin digestion, peptides were desalted using Strata X C18 SPE columns (Phenomenex) and lyophilized. The lyophilized peptides were reconstituted in 0.5 M triethylammonium bicarbonate (TEAB) and labeled according to the manufacturer’s protocol for the TMT 6-plex kit (Thermo Fisher Scientific). Briefly, each TMT reagent vial was thawed and dissolved in anhydrous acetonitrile. Peptide samples were then incubated with respective TMT reagents for 2 h at 25 °C with gentle agitation. All labeled peptides were combined, acidified with 1% formic acid, and desalted again using C18 StageTips. Finally, the samples were vacuum-concentrated for subsequent analysis. HPLC fractionation Tryptic peptides were fractionated using high-pH reverse-phase HPLC on a Thermo Betasil C18 column (5 μm particle size, 10 mm internal diameter, 250 mm length). Briefly, peptides were separated with a linear gradient of 8–32% acetonitrile (pH 9.0) over 60 min, yielding 60 initial fractions. These fractions were subsequently pooled into discrete groups, concentrated via vacuum centrifugation, and stored for downstream analysis. Phosphopeptide enrichment Peptide mixtures were incubated with immobilized metal ion affinity chromatography (IMAC) microspheres in loading buffer (50% acetonitrile, 6% trifluoroacetic acid) under gentle agitation. After centrifugation, the supernatant was discarded, and the IMAC microspheres retaining phosphopeptides were subjected to sequential washes to remove nonspecifically bound peptides: first with 50% acetonitrile/6% trifluoroacetic acid, followed by 30% acetonitrile/0.1% trifluoroacetic acid. Enriched phosphopeptides were eluted using 10% NH[4]OH elution buffer under agitation. The eluate containing phosphopeptides was collected, lyophilized, and prepared for LC-MS/MS analysis. LC-MS/MS analysis Tryptic peptides were dissolved in 0.1% formic acid (Solvent A) and loaded directly onto a custom-packed reversed-phase analytical column (75 μm inner diameter × 15 cm length). Chromatographic separation was performed on an EASY-nLC 1000 UPLC system using a multi-step gradient: Solvent B (0.1% formic acid in 98% acetonitrile) was increased from 6% to 23% over 26 min, followed by a rise to 35% over 8 min, a rapid increase to 80% within 3 min, and a final 3-min hold at 80%. The flow rate was maintained at 400 nL/min throughout the gradient. Eluted peptides were ionized via a nano-electrospray ionization (NSI) source and analyzed using a Q Exactive™ Plus Hybrid Quadrupole-Orbitrap Mass Spectrometer (Thermo Scientific) coupled online to the UPLC system. Key mass spectrometry parameters included: electrospray voltage: 2.0 kV; full MS scan range: 350–1800 m/z with a resolution of 70,000 (Orbitrap); MS/MS acquisition: top 20 most intense precursors selected per cycle, fragmented via higher-energy collisional dissociation (HCD) at 28% normalized collision energy (NCE), with fragment detection at 17,500 resolution (Orbitrap); dynamic exclusion: 15.0 s; automatic gain control (AGC): 5 × 10^4; fixed first mass: 100 m/z. Data were acquired in a data-dependent acquisition (DDA) mode, alternating between one full MS scan and up to 20 subsequent MS/MS scans. Database search The resulting MS/MS data were searched using MaxQuant (v.1.5.2.8). The database was SwissProt Mouse (16,717 sequences), with a decoy reverse library included to calculate the false discovery rate (FDR), and a common contaminant library was added to minimize identification artifacts. The enzyme specificity was set to Trypsin/P, allowing up to two missed cleavages. The minimum peptide length was set to 7 amino acids, and the maximum number of modifications per peptide was set to 5. The precursor ion mass tolerance was set to 20 ppm for the first search and 4.5 ppm for the main search, while the fragment ion mass tolerance was set to 20 ppm. Carbamidomethylation of cysteine was specified as a fixed modification. Variable modifications included oxidation of methionine, N-terminal acetylation of proteins, and phosphorylation of serine, threonine, and tyrosine residues. The quantitative method was set to TMT-6plex. Protein, peptide-spectrum match (PSM), and phosphosite identifications were filtered at an FDR of 1% using a target-decoy strategy. Phosphosite localization was assessed using the MaxQuant algorithm, and only class I sites (localization probability > 0.75) were considered for downstream analysis. All statistical analyses were performed using P values corrected for multiple testing by FDR, and only FDR-adjusted results were subjected to subsequent bioinformatics interpretation. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium ([58]https://proteomecentral.proteomexchange.org) via the iProX partner repository [[59]17, [60]18] with the dataset identifier PXD064281. Bioinformatics methods Gene ontology (GO) enrichment analysis Proteins were categorized into three primary GO classes: biological process, cellular compartment, and molecular function. Enrichment analysis of differentially expressed proteins (DEPs) against the background of all identified proteins was performed using a two-tailed Fisher’s exact test for each category. GO terms with an adjusted p < 0.05 (Benjamini-Hochberg correction) were deemed statistically significant. Pathway enrichment analysis Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted to identify biologically relevant pathways associated with DEPs. A two-tailed Fisher’s exact test was applied to compare DEPs against the full set of identified proteins, with pathways achieving an adjusted p < 0.05 considered significantly enriched. Identified pathways were systematically classified into hierarchical categories based on the KEGG pathway ontology. Functional enrichment-based clustering Hierarchical clustering of proteins was performed using functional annotations (GO terms, protein domains, pathways, and complexes). Enriched categories with adjusted p < 0.05 in at least one cluster were retained for analysis. P-values were log-transformed (x = − log[10](P value)) and subsequently standardized (z-score normalization) within each functional category. Clustering was executed using one-way hierarchical clustering (Euclidean distance metric, average linkage method) in the Genesis software package. Resulting clusters were visualized as a heatmap generated with the heatmap. function from the gplots R package. Subcellular localization prediction Subcellular localization predictions were performed using WoLF PSORT ([61]https://wolfpsort.hgc.jp/), a bioinformatics tool for protein subcellular localization forecasting. Parallel reaction monitoring (PRM) of phosphorylated proteins Phosphopeptides for PRM validation were enriched using the same IMAC-based protocol as described above for global phosphoproteomic analysis. Tryptic peptides were reconstituted in 0.1% formic acid (solvent A) and subjected to chromatographic separation using an EASY-nLC 1000 UPLC system (Thermo Fisher Scientific). The elution gradient was programmed as follows: 1–18% solvent B (0.1% formic acid in 90% acetonitrile) over 38 min, 18–32% over 4 min, followed by a ramp to 80% over 4 min, and equilibration at 80% for 4 min. A constant flow rate of 450 nL/min was maintained throughout the separation. Phosphorylated peptides were subsequently analyzed using a Q Exactive™ HF-X mass spectrometer (Thermo Fisher Scientific) equipped with a NanoSpray Ionization (NSI) source. Key mass spectrometry parameters included: electrospray voltage: 2.2 kV; scan range: 510–1,120 m/z; full MS resolution: 120,000 (Orbitrap); MS/MS resolution: 30,000 (Orbitrap); Automatic Gain Control (AGC) targets: 3 × 10^6 (MS), 1 × 10^5 (MS/MS); maximum injection time: 140 ms; isolation window: 1.4 m/z. Data acquisition employed data-independent acquisition (DIA) methodology. Technical reproducibility between PRM results and initial phosphoproteomics datasets was quantified using Pearson correlation analysis. Protein–Protein interaction (PPI) network construction The PPI network was constructed using Cytoscape software with interaction data retrieved from the STRING database. Subnetworks were subsequently identified through topology-driven module analysis using the MCODE plugin. Functional enrichment analysis of phosphoproteins within these subnetworks was performed for KEGG pathways and GO terms using the ClueGO plugin. Identification of kinases and phosphatases with differentially phosphorylated sites identification of novel phosphorylation sites A comprehensive dataset of human kinases and phosphatases was curated from the UniProt Knowledgebase ([62]www.uniprot.org), restricted to manually reviewed Swiss-Prot entries. To prioritize biologically relevant targets, the dataset was further filtered to retain proteins harboring differentially phosphorylated sites (|fold change| ≥ 1.5, adjusted p < 0.05) identified in the study. Identification of novel phosphorylation sites To identify potential novel phosphorylation events, we utilized our pre-processed phosphoproteomic dataset of Mus musculus. All experimentally detected phosphosites from this dataset were systematically compared against annotated phosphorylation sites documented in the UniProt Knowledgebase (UniProtKB/Swiss-Prot, accessed on 2025-08-15) (Table [63]S1, sheet 2). Phosphosites matching existing UniProt annotations were classified as “known sites”, whereas those absent from the UniProt database were defined as “novel sites” (Table [64]S1, sheet 3). Results Phosphoproteomics experimental design The Hras-Tg mice, previously characterized in detail [[65]11, [66]19], exhibits sexually dimorphic hepatocarcinogenesis. Male Hras-Tg mice demonstrated near-complete penetrance of HCC by 8–9 months of age, while female counterparts showed delayed tumor development with only 30% incidence after 15 months. To ensure equivalent tumor progression stages, we selected 9-month-old males and 15-month-old females bearing hepatic tumors for comparative analysis. Three biological conditions were established for phosphoproteomic profiling: (1) precancerous hepatic tissue (P) from Hras-Tg mice, (2) HCC lesions (T) from Hras-Tg mice, and (3) normal liver tissue (W) from age-matched wild-type controls (Non-Tg). Following individual protein extraction, we generated three pooled biological replicates per group through randomized equal-mass combination of triplicate samples. The pooled samples underwent sequential processing: lysis buffer extraction, tryptic digestion, TMT 6-plex labeling, and reversed-phase HPLC fractionation. Phosphopeptides were subsequently enriched using TiO2 affinity chromatography before LC-MS/MS analysis on a Q Exactive HF-X mass spectrometer. Differential phosphorylation was defined by thresholds of fold change >1.5 and adjusted p-value < 0.05 (Benjamini-Hochberg correction). To validate phosphoproteomic findings, we implemented PRM for targeted quantification of candidate phosphopeptides. Bioinformatics integration of significantly altered phosphoproteins and phosphorylation sites enabled systematic comparison of sex-specific regulatory patterns in hepatocarcinogenesis. A comprehensive workflow schematic is provided in Fig. [67]1. Fig. 1. [68]Fig. 1 [69]Open in a new tab Workflow for TMT-based quantitative phosphoproteomics using IMAC enrichment. Liver tissues from age-matched mice were grouped as follows: W (wild-type, non-transgenic mice; n = 9/sex), P (precancerous tissues of HrasG12V transgenic mice; n = 9/sex), and T (HCC tissues of HrasG12V transgenic mice; n = 9/sex). The experimental pipeline includes tissue lysis, protein digestion, TMT 6-plex labeling, pooled sample fractionation, immobilized metal affinity chromatography (IMAC) phosphopeptide enrichment, and LC-MS/MS analysis. Sex-balanced biological replicates (F: female; M: male) were processed independently to ensure statistical robustness. Key comparisons include tumor vs. peri-tumor (T vs. P), tumor vs. wild-type liver (T vs. W) and peri-tumor vs. wild-type liver (T vs. P) Identification of phosphorylated peptides and distribution of phosphorylation sites Our phosphoproteomic analysis identified 6,517 phosphopeptides corresponding to 2,805 phosphoproteins, with 5,410 phosphopeptides (from 2,427 phosphoproteins) successfully quantified (Table S1). Rigorous quality control measures confirmed data reliability, as evidenced by mass error distributions centered near zero (median < 5 ppm) and peptide length distributions characteristic of tryptic digestion products (Fig. S1). Biological replicates demonstrated strong intra-group correlations (Fig. S2), though P samples showed reduced correlation coefficients (r = 0.56–0.70) compared to W and T groups, suggesting enhanced phosphorylation heterogeneity in Hras-activated hepatic tissues. Both hierarchical clustering and principal component analysis revealed distinct phosphoproteomic profiles across experimental groups (Fig. [70]2A, B), with heatmap visualization demonstrating substantial phosphorylation remodeling in MT and FT tissues. Phosphorylation site analysis revealed a characteristic residue distribution: 88.6% serine, 10.3% threonine, and 1.1% tyrosine phosphorylation (Fig. [71]2C). Phosphopeptide complexity analysis showed 53.0% (n = 1,487) contained single phosphorylation sites, while 20.7% (n = 580) and 26.3% (n = 738) exhibited two or ≥ three sites, respectively (Fig. [72]2D). Fig. 2. [73]Fig. 2 [74]Open in a new tab Quality assessment of phosphoproteomics data. (A) Hierarchical clustering analysis and (B) principal component analysis (PCA) demonstrated strong intra-group reproducibility and distinct inter-group separation. (C) Classification of detected phosphorylation sites by residue type: phosphoserine (pS), phosphothreonine (pT), and phosphotyrosine (pY). (D) Frequency distribution of proteins containing specific numbers of phosphorylation sites. Abbreviations and experimental details are consistent with those provided in Fig. [75]1’s caption Validation of phosphoproteomics findings through parallel reaction monitoring (PRM) To independently verify our phosphoproteomics results, we performed orthogonal validation using parallel reaction monitoring (PRM)-MS on the same sample set. Through systematic selection based on peptide detectability and protein abundance considerations, we successfully quantified 30 significantly altered phosphopeptides corresponding to 29 phosphoproteins (Table S3). Pearson correlation analysis demonstrated strong concordance between PRM quantification and initial phosphoproteomics data (Fig. [76]3). Notably, 23 phosphorylation sites exhibited high correlation coefficients (r > 0.79), while 5 sites showed moderate correlations (0.4 ≤ r ≤ 0.7). This validation confirms the technical reproducibility of our phosphoproteomic profiling, with the majority of identified phosphorylation events showing consistent quantification patterns across different mass spectrometry platforms. Fig. 3. [77]Fig. 3 [78]Open in a new tab PRM-based validation of candidate phosphorylation sites. Row labels denote protein gene symbols followed by their corresponding modified peptide sequences. Abbreviations correspond to those described in Fig. [79]1. Detailed validation metrics, including retention time, precursor charge states, and transition peak areas, are provided in Supplementary Table S3 Identification of differentially expressed phosphoproteins and phosphopeptides in hepatocarcinogenesis Differentially expressed phosphopeptides were identified in female and male cohorts using stringent criteria (adjusted p < 0.05, fold change > 1.5; Table S2). Comparative analyses revealed distinct patterns of phosphopeptide abundance and their corresponding phosphoproteins across experimental groups (Fig. [80]4A, S3). Notably, the T/P(W) comparisons exhibited significantly higher numbers of differential phosphorylation sites and proteins compared to the P/W comparison in both sexes. A consistent predominance of up-regulated phosphorylation events over down-regulated ones was observed across all group comparisons (Fig. [81]4A), indicating widespread alterations in phosphorylation-associated pathways during hepatocarcinogenesis. Sex-specific disparities emerged in phosphorylation dynamics, with male cohorts demonstrating greater quantities of differentially expressed phosphorylation sites/proteins across intergroup comparisons, particularly in up-regulated events within the P/W comparison. Fig. 4. [82]Fig. 4 [83]Open in a new tab Quantitative profiling and subcellular mapping of phosphoprotein regulation. (A) Comparative analysis of differentially regulated phosphoproteins and phosphorylation sites across experimental groups. Histograms display quantitative changes in phosphoprotein counts and corresponding phosphorylation sites identified through pairwise comparisons between groups. The forward slash ("/") denotes comparative relationships (equivalent to "versus"). Abbreviations and experimental group descriptions follow the conventions established in Figure [84]1. (B) Systematic mapping of subcellular localization patterns for regulated phosphoproteins. The pie chart distribution reveals compartment-specific phosphorylation dynamics, with proportional representations indicating predominant localization to distinct cellular organelles Subcellular localization profiling provided functional insights into regulated phosphoproteins (Fig. [85]4B). Both sexes exhibited nuclear enrichment of differentially phosphorylated proteins in T/P(W) comparisons (Fig. [86]4B), implicating nuclear phosphorylation dysregulation as a potentially important contributor to HCC pathogenesis. Striking sex differences emerged in cytoplasmic localization patterns during P/W comparisons, with male specimens showing 20.65% of regulated phosphoproteins in cytoplasmic compartments versus 27.69% in females. Membrane-associated phosphorylation events demonstrated significant sexual dimorphism, with males exhibiting nearly double the proportion of plasma membrane-localized phosphoproteins compared to females (14.17% vs. 7.69%, P/W comparison). However, T/P(W) comparisons revealed attenuated sex disparities in subcellular localization patterns, particularly for plasma membrane and cytoplasmic phosphoproteins. KEGG pathway enrichment analysis in sex-specific hepatocarcinogenesis KEGG pathway enrichment analysis of differentially expressed phosphoproteins from longitudinal comparisons of W, P, and T tissues revealed distinct metabolic alterations and cellular activities during hepatocarcinogenesis progression (Fig. [87]5). Mirroring the quantitative differences in regulated phosphoproteins, the T/P (W) comparisons exhibited significantly more enriched pathways than the P/W comparison (Table S4), demonstrating substantial phosphorylation dysregulation in HCC tissues. Fig. 5. [88]Fig. 5 [89]Open in a new tab KEGG pathway enrichment analysis of differentially phosphorylated proteins in males. Males (A) and females (B). The forward slash ("/") denotes comparative groups (vs.). Abbreviations and detailed descriptions follow the conventions established in Figure [90]1 Shared pathway enrichments between sexes across all stages suggested fundamental regulatory mechanisms independent of sexual dimorphism. The P/W comparison highlighted phosphorylation in precancerous tissues, potentially linked to Hras oncogene activation. T/P comparisons identified hepatocarcinogenesis-associated pathways including: Core signaling pathways (MAPK, focal adhesion); Mechanical stress responses (fluid shear stress, atherosclerosis); Nutrient processing pathways (protein digestion/absorption); Comprehensive metabolic networks (amino acids, cytochrome P450, nitrogen, nicotinate/nicotinamide, butanoate, glycerophospholipid, glutathione, phosphonate/phosphinate metabolism). T/W comparisons revealed additional HCC-related mechanisms: Oncogenic processes (Ras-mediated effects, amyotrophic lateral sclerosis); Metabolic reprogramming (fatty acids, steroid hormones, pyruvate, nitrogen, amino acids); Conserved pathways across comparisons (bile secretion, proximal tubule bicarbonate reclamation). Sex-specific enrichment patterns emerged as potential determinants of sexual dimorphism in HCC pathogenesis. Male-specific findings included: P/W comparisons: ErbB, Prolactin, Fc epsilon RI, Ras, and cAMP signaling; T/P comparisons: mTOR, Rap1, T cell receptor, AGE-RAGE, Jak-STAT, and AMPK signaling. This male-predominant signaling dysregulation, particularly in Hras oncogene-driven pathways, may partly help explain the observed sexual dimorphism. T/W comparisons revealed sex-divergent enrichment in both metabolic and signaling pathways, requiring further investigation considering the multifactorial regulation of Hras expression and hepatocarcinogenesis. Interestingly, no significant enrichment of the MAPK signaling pathway was observed in the T/W comparison, despite its well-established role as a downstream effector of Ras oncogene activation. Examination of MAPK-associated phosphosites revealed heterogeneous regulation in our dataset: while some sites showed elevated phosphorylation in tumors, others remained comparable between tumor and wild-type tissues but displayed partial reduction in precancerous tissues (Table S1, 4). Such stage-dependent variation may reduce the net differences between tumors and wild-type groups, thereby attenuating MAPK pathway enrichment in this comparison. Complementary GO analysis confirmed both shared and sex-specific regulatory patterns in phosphorylation dynamics (Fig S4, Table S4). Systematic cross-tabulation analysis between sexes will be essential to elucidate the complex interplay of phosphorylation regulation and sexual dimorphism in HCC development. Common and unique regulated phosphorylation sites involved in hepatocarcinogenesis between males and females Changes in phosphosite abundance alone cannot reliably reflect the functional state of the corresponding proteins or the activation status of signaling pathways. During the development and progression of HCC, phosphosites that exhibit consistent, stage-dependent regulation in both sexes may be closely linked to core oncogenic mechanisms. In contrast, phosphosites with sex-specific expression patterns are more likely to underlie the molecular basis of sex differences observed in HCC. Therefore, systematically identifying phosphosites that are commonly or differentially regulated in males and females during HCC progression, followed by functional enrichment analysis, represents a critical step toward elucidating the molecular mechanisms underlying sex-based disparities in hepatocarcinogenesis. To investigate shared and sex-specific phosphorylation regulation during hepatocarcinogenesis, we conducted Venn analyses of regulated phosphorylation sites across intergroup comparisons in male and female cohorts separately (Fig. [91]6A). Phosphorylation sites exhibiting abundance differences in at least two intergroup comparison pairs were systematically identified (Table S5). Using our previously established classification framework [[92]16], these phosphorylation sites were categorized into 12 distinct expression patterns based on their abundance trends across non-tumor (W), precancerous (P), and tumor (T) tissues. A cross-tabulation analysis further delineated sex-specific and shared regulatory patterns (Fig. [93]6B). Fig. 6. Fig. 6 [94]Open in a new tab Sex-dependent common and unique phosphorylation dynamics during hepatocarcinogenesis. (A) Venn diagrams comparing sex-specific regulated phosphosites across experimental groups (W: wild-type; P: precancerous; T: tumor). The "/" symbol denotes pairwise comparisons. (B) Temporal phosphorylation patterns during hepatocarcinogenesis in both sexes (detailed data in Table S5). Phosphosites were categorized as: HCC-associated: (a) Positively correlated: significantly elevated in T vs. P and/or W; (c) Negatively correlated: significantly reduced in T vs. P and/or W. HrasG12V oncogene-associated: (b) Positively correlated: progressively increased in P and T vs. W; (d) Negatively correlated: progressively decreased in P and T vs. W. Expression patterns (denoted by graded levels 1-3) are color-coded: Deep red: sex-shared phosphosites with identical regulation patterns; Light red: sex-shared phosphosites with analogous regulation trends; Green: sex-unique phosphosites. Abbreviations and experimental details follow Figure [95]1 conventions These patterns were consolidated into four functional categories (a–d): Category (a) pattern: phosphorylation sites exhibiting tumor-promoting effects in HCC. The majority followed the “⤴” model, suggesting attenuated responsiveness to Ras oncogenic signaling. The remaining sites conformed to the “⤻” model, indicative of Ras-suppressive responses potentially counteracted by cancer-preventive mechanisms in precancerous hepatocytes. Category (c) pattern: phosphorylation sites displaying tumor-suppressive roles in HCC. Most adhered to the “⤸” model, reflecting weak Ras pathway engagement. Sites corresponding to the “⤼” model demonstrated Ras-activating responses, likely potentiated by cancer-preventive systems in precancerous cells. Categories (b) and (d): represented phosphorylation sites with opposing Ras pathway activation states between precancerous hepatocytes (category d: Ras-suppressive) and malignant cells (category b: Ras-activating). The red-shaded regions in Fig. [96]6B (including both dark and light tones) represent phosphosites that follow defined longitudinal expression patterns across the W, P, and T stages. Notably, the dark red diagonal blocks highlight phosphosites exhibiting consistent dynamic trends in both sexes. These sites were not classified merely based on differential expression in individual pairwise comparisons, but were instead selected according to their temporal regulation patterns and potential functional relevance to HCC progression. In contrast, the green-colored cells in the matrix indicate phosphosites that showed significant changes in only one sex and in only a single pairwise comparison, or exhibited inconsistent trends across stages. These sites were excluded from the trend-based classification, as they are less likely to reflect robust or biologically meaningful phosphorylation dynamics relevant to tumor development. This filtering step was crucial to focus the downstream functional enrichment and mechanistic analyses on phosphosites with temporally coherent regulation patterns that are more likely to contribute to HCC pathogenesis and sex-specific molecular features. Functional enrichment analysis of sex-common and sex-Specific phosphoregulation in hepatocarcinogenesis To investigate how phosphorylation sites exhibiting shared regulatory patterns in both sexes (deep red region, Fig. [97]6B) contribute to Ras-driven hepatocarcinogenesis, we performed protein-protein interaction (PPI) network analysis and functional enrichment of core subnetworks. The PPI network was constructed in Cytoscape using STRING database interactions, with the five most significant subnetworks identified through MCODE module analysis (Fig. [98]7A). Notably, albumin (Alb) emerged as the central hub protein, a molecule previously implicated in HCC initiation and progression [[99]20]. Our phosphoproteomic data revealed significant upregulation (male: 7.61-fold, female: 12.09-fold in T/W comparisons) of phosphorylation at threonine-444 (T444) in Alb, given Alb’s central position in the PPI network and its fundamental roles in liver physiology as well as its emerging links to liver disease, this phosphorylation event may represent a previously unrecognized layer of Alb regulation during hepatocarcinogenesis. Fig. 7. [100]Fig. 7 [101]Open in a new tab Integrated PPI network analysis and functional enrichment of phosphorylation sites exhibiting conserved variation patterns across both sexes. (A) MCODE analysis identified five core protein interaction modules (MCODE score > 3 threshold), color-coded to distinguish functional clusters. (B) KEGG pathway enrichment analysis revealed module-specific involvement in signal transduction pathways. (C) GO term analysis demonstrated significant biological process associations ClueGO-based KEGG/GO analysis of subnetwork phosphoproteins (Fig. [102]7B, C; Table S6) identified conserved pathway activation in both sexes. For sex-specific regulatory patterns (green regions, Fig. [103]6B), functional enrichment revealed distinct mechanistic divergences. Male-specific phosphoregulation demonstrated greater complexity with more enriched terms (Fig. [104]8A, B; Table S6), particularly in intermembrane lipid transfer processes that dominated the male profile (Fig. [105]8A). This suggests enhanced male-specific engagement of energy metabolism, membrane dynamics, signal transduction, and lipid homeostasis during HCC development. These sex-dimorphic phosphorylation patterns likely reflect metabolic adaptation mechanisms that differentially promote hepatocarcinogenesis, providing mechanistic insights into sexual dimorphism in HCC pathogenesis. Fig. 8. [106]Fig. 8 [107]Open in a new tab Functional enrichment of phosphorylation sites through gender-specific variation pattern analysis in male (A) and female (B) cohorts. (C) Demonstrates a comparative analysis of phosphorylation site quantification between tumor and adjacent precancerous tissues across both genders. Abbreviations and experimental descriptors maintain consistency with those established in Fig. [108]1 legend Analysis of differentially phosphorylated protein kinases and phosphatases Utilizing validated protein data from the UniProt Knowledgebase, we systematically identified 371 proteins with kinase or phosphatase functionality, including multidomain proteins harboring kinase/phosphatase activity (Table S7). Subsequent analysis revealed 437 distinct phosphorylation sites exhibiting differential regulation across these proteins (Table S8). Detailed characterization demonstrated significant sex-specific disparities, with male samples showing elevated numbers of regulated phosphorylation sites compared to females. This trend was most pronounced in kinase-active proteins and paralleled in phosphatase-active counterparts (Fig. [109]8C). These findings indicate a greater number of differentially regulated phosphorylation sites in males compared to females, especially in kinase- and phosphatase-related proteins. Discussion Studies analyzing human HCC samples have identified substantial overlap in molecular alterations between sexes, with 76.5% of differentially expressed genes and 75.7% of expression quantitative trait loci (eQTLs) shared between males and females [[110]21]. This observation aligns with our previous proteomic and transcriptomic findings demonstrating convergent molecular profiles in male and female mice during hepatocarcinogenesis [[111]10, [112]22]. Extending these observations to post-translational regulation, our current phosphoproteomic analysis revealed sex-independent convergence at the phosphorylation level. KEGG pathway analysis further identified broadly conserved regulatory mechanisms across sexes, as evidenced by the consistent enrichment of pathways including MAPK signaling, mTOR signaling, focal adhesion, and bile secretion (Fig. [113]5; Table S4). These shared pathways likely represent common molecular processes in hepatocarcinogenesis that are not strictly sex-dependent. Importantly, several of these pathways are pharmacologically tractable: MAPK and mTOR signaling can be targeted by clinically available kinase inhibitors [[114]23, [115]24]; focal adhesion signaling can be modulated by focal adhesion kinase (FAK) inhibitors [[116]25]; and bile secretion and related bile acid metabolism can be regulated by farnesoid X receptor (FXR) agonists [[117]26, [118]27]. While our study does not establish these pathways as causal drivers, their consistent dysregulation across sexes highlights them as potential universal therapeutic targets. Nevertheless, we also recognize that sex-specific regulatory features remain, as approximately one-quarter of molecular traits exhibit sexual dimorphism in previous studies [[119]10, [120]21, [121]22]. Sex hormone regulation is considered one of the key mechanisms underlying the male predominance of HCC [[122]28]. Epidemiological studies have shown that, before menopause, the incidence of HCC in men is significantly higher than in women, whereas this difference is markedly reduced after menopause [[123]1, [124]29, [125]30]. Consistently, in the HrasG12V mouse model, female mice typically begin to show marked HCC tumorigenesis around 12 months of age, with little to no tumor formation observed in the liver before this time; in contrast, male mice exhibit tumorigenesis as early as 2 months of age [[126]11]. Notably, by around 12 months of age, female mice enter a physiological state similar to postmenopausal women, characterized by ovarian reserve depletion and a decline in hormone levels [[127]31]. One important mechanism through which sex hormones contribute to this disparity is their regulation of chronic inflammation, a well-established driver of hepatocarcinogenesis. High androgen receptor (AR) density promotes hepatic lipid accumulation and persistent inflammatory responses, thereby facilitating HCC initiation and progression [[128]32]. By contrast, estrogen receptor (ER) signaling suppresses NF-κB–mediated inflammation, attenuating oxidative stress and slowing tumor development [[129]33]. In line with this, our previous work showed that in HrasG12V HCC mice at the same age (3 months), males exhibited significantly higher ROS levels within hepatocytes and more severe hepatic steatosis than females [[130]34], further supporting the role of hormone-driven inflammatory regulation in shaping sex disparities in HCC susceptibility. Interestingly, in our HrasG12V model, Ras signaling showed a clear male bias, with KEGG enrichment detected only in male but not in female cohorts (Table [131]S4). Male mice displayed pronounced dysregulation of Ras pathway–related phosphoproteins, a pattern consistent with their earlier tumor onset compared with females [[132]11]. This sex disparity aligns with established roles of sex hormones in modulating hepatocarcinogenesis. Mechanistically, this preferential activation of Ras in males may reflect the combined influence of AR–driven inflammatory signaling, elevated oxidative stress, and a pro-inflammatory microenvironment, all of which can potentiate Ras activity [[133]32, [134]35]. By contrast, in females, ER signaling is known to suppress inflammation and oxidative stress, which could restrain Ras-driven oncogenic signaling and thereby delay tumor development [[135]33]. Of note, our study used 15-month-old females, a stage physiologically resembling peri-/postmenopause when declining estrogen levels would be expected to attenuate this protective effect [[136]31]. Yet, the absence of Ras pathway enrichment in these females suggests that additional phosphorylation-dependent regulatory mechanisms continue to buffer against Ras hyperactivation even under reduced estrogen conditions. Collectively, these findings imply that Ras pathway hyperactivation constitutes a male-specific vulnerability in hepatocarcinogenesis, and that delineating the phospho-regulatory mechanisms restraining Ras activity in females may uncover new strategies to selectively block Ras signaling in high-risk male populations. In our current experimental design, 15-month-old females were selected because, at this age, they consistently develop sizable and histologically confirmed tumors, whereas females younger than 12 months rarely present with detectable tumorigenesis, making phosphoproteomic profiling infeasible. Although this necessarily resulted in a comparison between 9 month old males and 15 month old females, and thus introduced differences in reproductive stage, it allowed us to capture robust, biologically relevant phosphorylation signatures that distinguish HCC in males and females. Therefore, although some of the observed sex-related phosphorylation patterns may be influenced by reproductive stage rather than sex per se, the findings still provide valuable molecular insights into the mechanisms underlying sex disparities in HCC. To address this potential limitation, future studies could employ transgenic models with controlled hormone levels to more precisely delineate the respective contributions of sex and reproductive status to HCC tumorigenesis. Despite comparable tumor characteristics and underlying hepatic pathology, a 17-year longitudinal analysis of 1,138 HCC patients demonstrated superior survival outcomes in female patients relative to males [[137]36], highlighting persistent sexual dimorphism in HCC progression. While sex hormones have been proposed as key mediators in sexual dimorphism [[138]37], the limited clinical efficacy of conventional hormone-targeted interventions [[139]37, [140]38] implies the involvement of additional regulatory mechanisms. Nevertheless, estrogen receptor β (ERβ) has emerged as a tumor suppressor whose expression is progressively downregulated in HCC tissues, particularly in advanced stages [[141]39]. This loss likely weakens endogenous estrogen signaling during disease progression. Importantly, exogenous activation of ERβ (e.g., by E2) can restore its protective function, underscoring its potential as a therapeutic target [[142]39]. Consistently, epidemiological studies report that postmenopausal estrogen replacement not only lowers HCC incidence but also prolongs survival, highlighting estrogen as a clinically relevant protective factor in HCC [[143]40]. While these findings underscore the importance of estrogen signaling, they also suggest that it cannot fully explain the pronounced sex disparities in HCC. To address this gap, we turned to phosphoproteomic profiling, which revealed sexually dimorphic phosphorylation signatures despite partial pathway overlap, indicating fundamentally divergent regulatory mechanisms between sexes. Quantitative analysis demonstrated greater phosphoproteomic dysregulation in male murine models, with both elevated and reduced phosphorylation intensities observed across significantly more proteins and phosphorylation sites compared to females (Figs. [144]4 A, S3). Striking sex-specific disparities emerged in kinase/phosphatase regulatory networks: male specimens demonstrated particular enrichment of upregulated phosphorylation sites in kinase (Fig, [145]8C), while functional annotation revealed greater regulatory complexity in male-specific phosphosites, particularly within cancer-relevant signaling pathways (Fig. [146]8A and B). These collective findings propose that heightened phosphorylation complexity in males may drive both increased hepatocarcinogenesis susceptibility and reduced survival capacity. This sexual stratification of phosphoregulatory networks underscores the necessity for sex-specific therapeutic development in HCC precision medicine, and future studies dissecting these dimorphic signaling architectures may reveal novel biomarkers and kinase targets for gender-tailored treatment. Hepatocarcinogenesis is characterized by profound metabolic reprogramming [[147]41], and targeting metabolic dysregulation has emerged as a promising therapeutic strategy in oncology [[148]42]. Given that phosphorylation serves as a critical molecular switch governing metabolic networks [[149]43], our phosphoproteomic profiling revealed striking enrichment of metabolism-related pathways in HCC (Fig. [150]5; Table S4), thereby highlighting the complexity of metabolic regulation in liver carcinogenesis. Notably, we identified 4,552 previously unannotated phosphorylation sites (Table S1, sheet 3), which may represent novel regulatory mechanisms underlying tumor-specific metabolic adaptations. Of particular interest is carbamoyl-phosphate synthase 1 (Cps1), the urea cycle rate-limiting enzyme and established HCC prognostic biomarker [[151]44], which exhibited four significantly downregulated phosphorylation sites shared between males and females (Table S8). To our knowledge, these sites have not been previously reported in mouse, nor are they listed in the human PhosphoNET database for Cps1. While this absence does not preclude their existence in humans, it highlights a currently unrecognized layer of post-translational regulation in the mouse system. While the functional implications of these phosphorylation events require further investigation, our findings establish a framework for understanding how phospho-regulation of metabolic enzymes drives tumor progression and potentially reveals new therapeutic targets for disrupting metabolic reprogramming in HCC. Future validation of these sites, for example by mutagenesis-based functional assays, will be essential to fully clarify their mechanistic roles. Albumin (Alb), a pivotal secretory protein predominantly synthesized in the liver, serves as a central regulator of physiological homeostasis [[152]45]. Emerging evidence indicates that phosphorylation-mediated structural alterations in Alb impair its lipid-binding domain, substantially diminishing its affinity for free fatty acids (FFA) [[153]46, [154]47]. This post-translational modification not only initiates lipid metabolism dysregulation but also promotes hepatic steatosis - a well-established precursor accelerating HCC pathogenesis [[155]34]. Our phosphoproteomic analyses align with recent reports demonstrating tumor-specific multi-site phosphorylation patterns of Alb across multiple malignancies [[156]48–[157]50], with quantitative validation provided in this investigation (Table S1). PPI network mapping further establishes Alb as a critical nodal protein (Fig. [158]7A), suggesting its multifaceted regulatory roles in disease progression. This finding gains particular relevance when interpreted alongside our previous experimental data from identical animal models, which documented significantly increased hepatic steatosis incidence [[159]34]. The elevated Alb phosphorylation levels observed in the current study, combined with established mechanisms of phosphorylation-induced FFA binding impairment, collectively suggest a potential pathogenic cascade: Alb phosphorylation may drive lipid metabolic dysfunction through compromised FFA sequestration, thereby exacerbating hepatic steatosis. This mechanism could represent a critical molecular bridge connecting post-translational protein modification to microenvironmental metabolic reprogramming in HCC development. While this study provides valuable insights, several limitations merit thoughtful consideration. First, achieving a comprehensive understanding of the molecular mechanisms underlying Ras-induced male-biased hepatocarcinogenesis would benefit from integrated multi-omics approaches that synergize proteomic, transcriptomic, and epigenomic analyses. Second, the experimental design necessitated the use of younger male mice (9 months) and older female counterparts (15 months) to accommodate the pronounced male predominance observed in the HrasG12V HCC model. This age disparity introduces potential confounding effects that should be carefully accounted for in future investigations. Finally, while our phosphoproteomic analysis revealed numerous previously uncharacterized phosphorylation sites with PRM-validated reliability, these findings demand rigorous functional characterization through systematic validation studies to establish their biological relevance and mechanistic contributions to hepatic carcinogenesis. Conclusion This investigation comprehensively delineated Ras-driven phosphoproteomic alterations and sexual dimorphism in HCC, constructing a novel sex-stratified phosphoproteomic repository. Our findings elucidate both conserved and gender-distinct phosphorylation signatures, establishing pathological hyperphosphorylation as a critical molecular mechanism driving hepatic oncogenesis. The identified sexual dichotomy in phosphorylation networks provides a mechanistic framework for understanding gender disparities in HCC progression and therapeutic responses. Supplementary Information [160]Supplementary Material 1.^ (2.2MB, xlsx) [161]Supplementary Material 2.^ (21.7KB, xlsx) [162]Supplementary Material 3.^ (82.6KB, xlsx) [163]Supplementary Material 4.^ (21.5KB, xlsx) [164]Supplementary Material 5.^ (125.8KB, xlsx) [165]Supplementary Material 6.^ (345.6KB, xlsx) [166]Supplementary Material 7.^ (3.1MB, xlsx) [167]Supplementary Material 8.^ (386KB, xlsx) [168]Supplementary Material 9.^ (534.2KB, tif) [169]Supplementary Material 10.^ (182KB, tif) [170]Supplementary Material 11.^ (1.3MB, tif) [171]Supplementary Material 12.^ (1.2MB, tif) [172]Supplementary Material 13.^ (1.2MB, tif) [173]Supplementary Material 14.^ (1.3MB, tif) [174]Supplementary Material 15.^ (1.2MB, tif) [175]Supplementary Material 16.^ (1.3MB, tif) [176]Supplementary Material 17.^ (1.3MB, tif) Abbreviations Non-Tg Wild-type C57BL/6J mice Hras-Tg HrasG12V transgenic mice MT Male tumor MP Male precancerous MW Male wild-type liver tissues PRM Parallel reaction monitoring FT Female tumor FP Female precancerous FW Female wild-type liver tissues PRM Parallel reaction monitoring HCC Hepatocellular carcinoma PPI Protein-protein interaction KEGG Kyoto encyclopedia of genes and genomes Alb Albumin BCA Bicinchoninic acid DTT Dithiothreitol IAA Iodoacetamide TEAB Triethylammonium bicarbonate IMAC Immobilized metal ion affinity chromatography NSI Nano-electrospray ionization HCD Higher-energy collisional dissociation NCE Normalized collision energy AGC Automatic gain control DDA Data-dependent acquisition FDR False positive rate PSM Peptide spectrum match GO Gene ontology DEPs Differentially expressed proteins DIA Data-independent acquisition HPLC High performance liquid chromatography TiO2 Titanium dioxide pS Phosphoserine pT Phosphothreonine pY Phosphotyrosine T444 Threonine-444 MCODE Molecular complex detection eQTLs Expression quantitative trait loci FFA Free fatty acid Author contributions To design and study conception: AGW, HLL. To acquisition of data: CCY, JFH, LY, YY, XYD, JC, HLL. To analysis and interpretation: CCY, JFH, YY, HLL, AGW. Participation in drafting: CCY, JFH, HLL, AGW. Participation in revising: AGW, HLL. All authors approved the final version. Funding This work was supported by the National Natural Science Foundation of China (30872950). Data availability The authors state that all data necessary for confirming the conclusions presented in the article are represented fully within the article. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (https://proteomecentral.proteomexchange.org) via the iProX partner repository with the dataset identifier PXD064281. The parallel reaction monitoring (PRM) data have been deposited to the ProteomeXchange Consortium (https://proteomecentral.proteomexchange.org) via the iProX partner repository with the dataset identifier PXD067725. The mass spectrometry proteomics dataset can be accessed via ProteomeXchange ([https://proteomecentral.proteomexchange.org/cgi/GetDataset? ID=PXD064281](https:/proteomecentral.proteomexchange.org/cgi/GetDataset ? ID=PXD064281)) or the iProX partner repository ([https://www.iprox.cn/page/project.html? id=IPX0012060000](https:/www.iprox.cn/page/project.html? id=IPX0012060000)). The PRM validated dataset can be accessed via ProteomeXchange ([https://proteomecentral.proteomexchange.org/cgi/GetDataset? ID=PXD067725](https:/proteomecentral.proteomexchange.org/cgi/GetDataset ? ID=PXD067725)) or the iProX partner repository (https://www.iprox.cn/page/project.html? id=IPX0013171000). Declarations Ethics approval Experiments and procedures for animal handling and tissue sampling were approved by the Animal Care and Use Committee of Dalian Medical University. Competing interests The authors declare no conflicts of interest. Footnotes Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Changcheng Yang and Juefu Hu contributed equally to this work. Contributor Information Aiguo Wang, Email: wangaiguo@dmu.edu.cn. Huiling Li, Email: lhl@dmu.edu.cn. References