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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">IJMM</journal-id>
<journal-title-group>
<journal-title>International Journal of Molecular Medicine</journal-title></journal-title-group>
<issn pub-type="ppub">1107-3756</issn>
<issn pub-type="epub">1791-244X</issn>
<publisher>
<publisher-name>D.A. Spandidos</publisher-name></publisher></journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3892/ijmm.2026.5856</article-id>
<article-id pub-id-type="publisher-id">ijmm-58-01-05856</article-id>
<article-categories>
<subj-group>
<subject>Review</subject></subj-group></article-categories>
<title-group>
<article-title>Spatial hepatology: Decoding liver zonation for metabolic and regenerative therapeutics (Review)</article-title></title-group>
<contrib-group>
<contrib contrib-type="author" equal-contrib="yes">
<name><surname>Chen</surname><given-names>Guiqing</given-names></name><xref rid="af1-ijmm-58-01-05856" ref-type="aff">1</xref><xref rid="af2-ijmm-58-01-05856" ref-type="aff">2</xref><xref rid="fn1-ijmm-58-01-05856" ref-type="author-notes">&#x0002A;</xref></contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name><surname>Jia</surname><given-names>Hongyan</given-names></name><xref rid="af1-ijmm-58-01-05856" ref-type="aff">1</xref><xref rid="fn1-ijmm-58-01-05856" ref-type="author-notes">&#x0002A;</xref></contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name><surname>Zhao</surname><given-names>Kai</given-names></name><xref rid="af2-ijmm-58-01-05856" ref-type="aff">2</xref><xref rid="fn1-ijmm-58-01-05856" ref-type="author-notes">&#x0002A;</xref></contrib>
<contrib contrib-type="author">
<name><surname>Gao</surname><given-names>Chang</given-names></name><xref rid="af1-ijmm-58-01-05856" ref-type="aff">1</xref></contrib>
<contrib contrib-type="author">
<name><surname>Liu</surname><given-names>Yue</given-names></name><xref rid="af1-ijmm-58-01-05856" ref-type="aff">1</xref></contrib>
<contrib contrib-type="author">
<name><surname>Zhu</surname><given-names>Hong</given-names></name><xref rid="af3-ijmm-58-01-05856" ref-type="aff">3</xref></contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Yang</surname><given-names>Dakai</given-names></name><xref rid="af1-ijmm-58-01-05856" ref-type="aff">1</xref><xref rid="af2-ijmm-58-01-05856" ref-type="aff">2</xref><xref ref-type="corresp" rid="c2-ijmm-58-01-05856"/></contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Cai</surname><given-names>Yun</given-names></name><xref rid="af2-ijmm-58-01-05856" ref-type="aff">2</xref><xref ref-type="corresp" rid="c1-ijmm-58-01-05856"/></contrib></contrib-group>
<aff id="af1-ijmm-58-01-05856">
<label>1</label>Jiangsu Key Laboratory of Medical Science and Laboratory Medicine, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu 212013, P.R. China</aff>
<aff id="af2-ijmm-58-01-05856">
<label>2</label>Department of Gastroenterology, Jintan Affiliated Hospital of Jiangsu University, Changzhou, Jiangsu 213200, P.R. China</aff>
<aff id="af3-ijmm-58-01-05856">
<label>3</label>Department of Life Sciences, Jingjiang College, Jiangsu University, Zhenjiang, Jiangsu 212013, P.R. China</aff>
<author-notes>
<corresp id="c1-ijmm-58-01-05856">Correspondence to: Professor Yun Cai, Department of Gastroenterology, Jintan Affiliated Hospital of Jiangsu University, 500 Avenue Jintan, Changzhou, Jiangsu 213200, P.R. China, E-mail: <email>caiyundyh@163.com</email></corresp>
<corresp id="c2-ijmm-58-01-05856">Professor Dakai Yang, Jiangsu Key Laboratory of Medical Science and Laboratory Medicine, School of Medicine, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu 212013, P.R. China, E-mail: <email>yangdakai@126.com</email></corresp>
<fn id="fn1-ijmm-58-01-05856" fn-type="equal">
<label>&#x0002A;</label>
<p>Contributed equally</p></fn></author-notes>
<pub-date pub-type="collection">
<month>07</month>
<year>2026</year></pub-date>
<pub-date pub-type="epub">
<day>13</day>
<month>05</month>
<year>2026</year></pub-date>
<volume>58</volume>
<issue>1</issue>
<elocation-id>185</elocation-id>
<history>
<date date-type="received">
<day>14</day>
<month>11</month>
<year>2025</year></date>
<date date-type="accepted">
<day>24</day>
<month>04</month>
<year>2026</year></date></history>
<permissions>
<copyright-statement>Copyright: &#x000A9; 2026 Chen et al.</copyright-statement>
<copyright-year>2026</copyright-year>
<license license-type="open-access">
<license-p>This is an open access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by-nc-nd/4.0/">Creative Commons Attribution-NonCommercial-NoDerivs License</ext-link>, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.</license-p></license></permissions>
<abstract>
<p>The integration of spatial omics and single-cell technologies has redefined liver zonation as a dynamic regulator of regeneration, extending beyond its traditional role in metabolic compartmentalization. This progress has given rise to the emerging field of 'spatial hepatology', which aims to integrate spatial information with molecular features. Compared with conventional bulk or single-cell approaches, spatial hepatology incorporates tissue architecture into molecular analyses, thereby revealing region-specific regulatory mechanisms during liver regeneration and disease progression. From this perspective, the present review proposes the concept of zonation-guided therapeutic strategies. It systematically summarized recent advances in the molecular mechanisms governing liver zonation, examined the role of zonal disruption in liver disease pathogenesis, clarified the dynamic functions of zonated hepatocytes during regeneration and outlined related targeted therapeutic approaches. The present review aimed to establish a framework that integrates basic research with clinical application, providing a theoretical basis for precision hepatology.</p></abstract>
<kwd-group>
<kwd>liver zonation</kwd>
<kwd>spatial reprogramming</kwd>
<kwd>regenerative niche</kwd>
<kwd>liver disease therapy</kwd></kwd-group>
<funding-group>
<award-group>
<funding-source>Key Laboratory Open Project Foundation of Jiangsu University</funding-source>
<award-id>8161280002</award-id></award-group>
<award-group>
<funding-source>Key Laboratory Open Project Foundation of Jiangsu University (Outstanding Research Project)</funding-source>
<award-id>JSKLM-Z-2024-011</award-id></award-group>
<award-group>
<funding-source>Science and Technology Plan (Apply Basic Research) of Changzhou City</funding-source>
<award-id>CJ20210006</award-id></award-group>
<award-group>
<funding-source>Science and Technology Plan (Apply Basic Research) of Changzhou City</funding-source>
<award-id>CJ20230002</award-id></award-group>
<award-group>
<funding-source>Science and Technology Plan (Apply Basic Research) of Changzhou City</funding-source>
<award-id>CJ20241041</award-id></award-group>
<award-group>
<funding-source>Natural Science Foundation of China</funding-source>
<award-id>82100666</award-id></award-group>
<award-group>
<funding-source>National Natural Science Foundation for Young Scientists of Jiangsu Province</funding-source>
<award-id>BK20200906</award-id></award-group>
<award-group>
<funding-source>Young Scientists Initiative Foundation of Jiangsu University</funding-source>
<award-id>20JDG49</award-id></award-group>
<funding-statement>The present was supported by grants from the Key Laboratory Open Project Foundation of Jiangsu University (grant no. 8161280002), the Key Laboratory Open Project Foundation of Jiangsu University (Outstanding Research Project) (grant no. JSKLM-Z-2024-011), Science and Technology Plan (Apply Basic Research) of Changzhou City (grant no. CJ20210006), Science and Technology Plan (Apply Basic Research) of Changzhou City (grant no. CJ20230002), Science and Technology Plan (Apply Basic Research) of Changzhou City (grant no. CJ20241041), Natural Science Foundation of China (grant no. 82100666), the National Natural Science Foundation for Young Scientists of Jiangsu Province (grant no. BK20200906) and the Young Scientists Initiative Foundation of Jiangsu University (grant no. 20JDG49).</funding-statement></funding-group></article-meta></front>
<body>
<sec sec-type="intro">
<label>1.</label>
<title>Introduction</title>
<p>The functional diversity of the liver arises from its spatially organized zonation architecture, where hepatocytes progressively alter their metabolic and detoxification capacities along the porto-central axis (<xref rid="b1-ijmm-58-01-05856" ref-type="bibr">1</xref>). This intricate partitioning, sustained by blood-borne molecular gradients and intercellular crosstalk, enables the liver to balance antagonistic biochemical processes while maintaining systemic homeostasis (<xref rid="b2-ijmm-58-01-05856" ref-type="bibr">2</xref>). Paradoxically, this structural stability is reconfigured during severe liver injury. Hepatocyte necrosis disrupts zonal organization, which both limits remaining liver function and triggers repair responses. Recent spatial biology studies show that the liver adopts different regenerative strategies depending on context, ranging from zonal self-renewal to whole-lobule plasticity (<xref rid="b3-ijmm-58-01-05856" ref-type="bibr">3</xref>-<xref rid="b5-ijmm-58-01-05856" ref-type="bibr">5</xref>). These processes are highly influenced by local microenvironmental signals. New technologies have begun to reveal how surviving cells use positional cues to rebuild functional structures.</p>
<p>Based on these studies and emerging technologies, the concept of 'spatial hepatology' has gradually emerged. This approach involves integrating multi-omics techniques in the context of tissue <italic>in situ</italic>, such as spatial transcriptomics, spatial proteomics and spatial metabolomics, to systematically analyze the distribution, functional states and interactions of different cell types at specific spatial locations within the liver (<xref rid="b2-ijmm-58-01-05856" ref-type="bibr">2</xref>). Compared with conventional single-cell sequencing or bulk transcriptomic analyses, spatial omics preserves tissue architecture while coupling molecular information with spatial coordinates, enabling precise mapping of functional liver regions and revealing dynamic molecular gradients in local microenvironments. This strategy offers significant advantages for investigating the remodeling of metabolic zonation, heterogeneity of injury responses and the regulation of cell fate during regeneration in liver disease, thereby providing a more refined and dynamic framework for understanding the pathogenesis and progression of liver disorders (<xref rid="b4-ijmm-58-01-05856" ref-type="bibr">4</xref>).</p></sec>
<sec sec-type="other">
<label>2.</label>
<title>Functional zonation and dynamic adaptation in hepatic metabolic architecture</title>
<p>The liver lobule exhibits a clear functionally compartmentalized structure. Traditional approaches to characterizing liver zonation and metabolic compartmentalization include quantitative PCR, immunohistochemistry and <italic>in situ</italic> hybridization (<xref rid="b6-ijmm-58-01-05856" ref-type="bibr">6</xref>). These methods reveal spatial differences in protein expression and enzymatic activity between periportal and pericentral hepatocytes, forming the basis of metabolic zonation. This spatial distribution arises from sinusoidal blood flow, which generates gradients of oxygen tension, nutrient concentrations and xenobiotics along the porto-central axis (<xref rid="b7-ijmm-58-01-05856" ref-type="bibr">7</xref>). These gradients of these substances are key determinants of liver zonation.</p>
<p>Studies on zonal metabolic features show that the periportal region predominantly carries out &#x003B2;-oxidation, urea synthesis and gluconeogenesis, whereas the pericentral region is primarily responsible for glycolysis, lipogenesis, and detoxification processes (<xref rid="b8-ijmm-58-01-05856" ref-type="bibr">8</xref>-<xref rid="b10-ijmm-58-01-05856" ref-type="bibr">10</xref>). Although most metabolic processes exhibit strict zonal segregation and serve as key indicators of liver function, some pathways can operate independently in different zones while remaining coordinated (<xref rid="b11-ijmm-58-01-05856" ref-type="bibr">11</xref>). A typical example is ammonia metabolism; studies have shown that periportal hepatocytes efficiently remove ammonia through glutaminase and urea cycle enzymes, whereas pericentral hepatocytes detoxify residual ammonia via glutamine synthetase (<xref rid="b12-ijmm-58-01-05856" ref-type="bibr">12</xref>,<xref rid="b13-ijmm-58-01-05856" ref-type="bibr">13</xref>). This spatial division of labor ensures high metabolic efficiency. However, this compartmentalized organization also concentrates cytochrome P450 activity in the pericentral region, making it more susceptible to toxin-induced necrosis (<xref rid="b14-ijmm-58-01-05856" ref-type="bibr">14</xref>).</p>
<p>Notably, liver zonation is not a static structure but exhibits high dynamic plasticity through coordinated transcriptional regulation and structural remodeling (<xref rid="b15-ijmm-58-01-05856" ref-type="bibr">15</xref>). Nutritional status is a key driver of this dynamic change. For example, fasting enhances lobular gluconeogenesis and promotes the extension of &#x003B2;-oxidation, typically dominant in the periportal region, toward the midlobular zone to meet systemic energy demands (<xref rid="b16-ijmm-58-01-05856" ref-type="bibr">16</xref>,<xref rid="b17-ijmm-58-01-05856" ref-type="bibr">17</xref>). During pregnancy, this adaptation is further reinforced by the expansion of periportal gluconeogenic hepatocytes, thereby maintaining maternal-fetal glucose homeostasis (<xref rid="b18-ijmm-58-01-05856" ref-type="bibr">18</xref>). Together, these regulatory mechanisms indicate that the liver can dynamically reorganize its spatial architecture in response to physiological states, enabling precise control of metabolic function.</p></sec>
<sec sec-type="other">
<label>3.</label>
<title>Molecular gradients and spatiotemporal dynamics in liver lobule compartmentalization</title>
<p>Recent advances in single-cell sequencing and multi-omics have improved the current understanding of liver zonation (<xref rid="b19-ijmm-58-01-05856" ref-type="bibr">19</xref>,<xref rid="b20-ijmm-58-01-05856" ref-type="bibr">20</xref>). These approaches define metabolic gradients, transcriptional networks and chromatin accessibility across hepatocyte populations, refining traditional models of lobular organization (<xref rid="b21-ijmm-58-01-05856" ref-type="bibr">21</xref>). Evidence shows that liver zonation is not simply binary; &gt;80% of hepatocyte genes display continuous expression gradients along the porto-central axis (<xref rid="b19-ijmm-58-01-05856" ref-type="bibr">19</xref>). Based on this, the liver lobule is commonly divided into three zones: i) Periportal (zone 1); ii) midlobular (zone 2); and iii) pericentral (zone 3) (<xref rid="b2-ijmm-58-01-05856" ref-type="bibr">2</xref>). Higher-resolution models further divide the lobule into nine layers, corresponding to these three regions. Zone-specific markers have also been identified. Periportal markers include ASS1, Cyp2f2, Sds, Asl, Gls2 and Arg1. Midlobular markers include hepcidin antimicrobial peptide 2 (Hamp2) and Insulin-like growth factor-binding protein 2 (Igfbp2). Pericentral markers include cytochrome P450 2E1 (Cyp2e1), Cyp1a2, GS and Oat (<xref rid="tI-ijmm-58-01-05856" ref-type="table">Table I</xref>) (<xref rid="b2-ijmm-58-01-05856" ref-type="bibr">2</xref>,<xref rid="b19-ijmm-58-01-05856" ref-type="bibr">19</xref>).</p>
<p>Trajectory analyses of liver development have revealed the dynamic establishment of metabolic gradients. For example, hepatocytes in neonatal mice initially exhibit pericentral metabolic features, with zonation patterns progressively maturing after birth (<xref rid="b22-ijmm-58-01-05856" ref-type="bibr">22</xref>). This developmental plasticity is closely associated with hepatocyte polyploidization. Regarding the spatial distribution of diploid hepatocytes, early studies suggested that these cells are enriched in the periportal and decline along the lobular axis, implying a higher proliferative potential in this zone (<xref rid="b23-ijmm-58-01-05856" ref-type="bibr">23</xref>,<xref rid="b24-ijmm-58-01-05856" ref-type="bibr">24</xref>). However, subsequent investigations employing alternative lineage-tracing strategies have reported a more uniform distribution, with some even indicating relative enrichment in the pericentral zone (<xref rid="b25-ijmm-58-01-05856" ref-type="bibr">25</xref>,<xref rid="b26-ijmm-58-01-05856" ref-type="bibr">26</xref>). These discrepancies may reflect differences in species, age-related shifts in polyploidization and methodological biases in nuclear isolation. Future studies integrating spatially resolved single-cell omics will be essential to clarify the interplay between ploidy status, zonation characteristics and regenerative capacity. However, spatial specialization is not unique to hepatocytes. Non-parenchymal cell populations also exhibit pronounced zonal heterogeneity, which may be a key factor in maintaining hepatic zonation (<xref rid="b27-ijmm-58-01-05856" ref-type="bibr">27</xref>-<xref rid="b29-ijmm-58-01-05856" ref-type="bibr">29</xref>). Non-parenchymal cells distributed across different lobular regions likely perform context-dependent functions, contributing to region-specific regulation during disease progression and influencing regenerative processes. By integrating single-cell atlases with spatial transcriptomics, researchers have progressively constructed high-resolution maps of both hepatocyte and non-parenchymal cell responses during injury and regeneration, providing a theoretical foundation for understanding liver repair mechanisms (<xref rid="b30-ijmm-58-01-05856" ref-type="bibr">30</xref>).</p></sec>
<sec sec-type="other">
<label>4.</label>
<title>Regulatory mechanisms governing hepatic zonation</title>
<p>Liver zonation is established through the coordinated action of systemic and local microenvironmental signals. Circulating factors, including hormonal gradients, oxygen tension and nutrient availability, activate spatially specific signaling pathways to establish metabolic compartmentalization. Among these, the Wnt/&#x003B2;-catenin pathway serves a central role, while other signaling networks, including Hedgehog (Hh) and oxygen-sensing pathways such as HIF, further coordinate epigenetic remodeling and metabolic reprogramming, thereby restricting hepatocyte functions to specific regions within the liver lobule (<xref rid="f1-ijmm-58-01-05856" ref-type="fig">Fig. 1</xref>) (<xref rid="b31-ijmm-58-01-05856" ref-type="bibr">31</xref>-<xref rid="b33-ijmm-58-01-05856" ref-type="bibr">33</xref>).</p>
<sec>
<title>Spatiotemporal regulation of metabolic zonation in hepatic architecture</title>
<p>The oxygen gradient along the porto-central axis of the hepatic lobule establishes a hypoxic microenvironment that activates hypoxia-inducible factors (HIFs) (<xref rid="b33-ijmm-58-01-05856" ref-type="bibr">33</xref>). Among these, HIF-1&#x003B1; is preferentially stabilized in pericentral hepatocytes, where it directly regulates glycolytic gene programs through binding to hypoxia-responsive elements (HREs) (<xref rid="b33-ijmm-58-01-05856" ref-type="bibr">33</xref>). This includes upregulation of glucose transporters GLUT1 (SLC2A1) and GLUT3 (SLC2A3), as well as key rate-limiting glycolytic enzymes such as HK2, PFK1, PKM2 and LDHA. Concurrently, HIF-1&#x003B1; transcriptionally activates PDK1, thereby inhibiting pyruvate entry into mitochondrial oxidative metabolism, collectively reinforcing the glycolytic phenotype characteristic of zone 3 hepatocytes (<xref rid="b34-ijmm-58-01-05856" ref-type="bibr">34</xref>,<xref rid="b35-ijmm-58-01-05856" ref-type="bibr">35</xref>). By contrast, HIF-2&#x003B1; primarily governs antioxidant defense and lipid metabolic regulation, directly inducing genes such as SOD2 and HMOX1 (<xref rid="b36-ijmm-58-01-05856" ref-type="bibr">36</xref>). However, sustained activation of HIF-2&#x003B1; can impair lipid homeostasis by transcriptionally suppressing PPAR&#x003B1;-dependent fatty acid oxidation (FAO) genes, including CPT1A and ACOX1, thereby promoting steatosis (<xref rid="b37-ijmm-58-01-05856" ref-type="bibr">37</xref>). HIF-3&#x003B1; splice variants function as dominant-negative regulators by competing with HIF-1&#x003B1; for HRE binding or forming low-activity heterodimers, ultimately attenuating HIF-1&#x003B1; signaling (<xref rid="b38-ijmm-58-01-05856" ref-type="bibr">38</xref>,<xref rid="b39-ijmm-58-01-05856" ref-type="bibr">39</xref>).</p>
<p>Beyond oxygen gradients, the spatial distribution of hormonal signals represents another key regulatory axis shaping liver zonation. Although glucagon receptors are uniformly distributed across the hepatic lobule, glucagon itself forms a functional gradient along the porto-central axis (<xref rid="b40-ijmm-58-01-05856" ref-type="bibr">40</xref>). In glucagon-deficient mice, expression of the periportal marker gene Gls2 is markedly reduced, whereas the pericentral marker Glul, which is normally restricted to 1 to 3 hepatocyte layers surrounding the central vein, expands to 5 to 6 layers (<xref rid="b41-ijmm-58-01-05856" ref-type="bibr">41</xref>). This abnormal pattern can be reversed by exogenous glucagon supplementation. Functionally, glucagon differentially regulates periportal urea cycle enzymes and pericentral xenobiotic metabolizing enzymes, such as members of the Cyp450 family. In addition, sexual dimorphisms further increases regulatory complexity. The sex-specific patterns of growth hormone (GH) secretion directly influence liver zonation by regulating the activity of transcription factors in distinct regions. In males, pulsatile GH in zone 1 activates SREBF1, promoting gluconeogenesis-related pathways, whereas in females, continuous GH in zone 3 supports TRIM24, enhancing hepatic progenitor cell-related pathways (<xref rid="b42-ijmm-58-01-05856" ref-type="bibr">42</xref>). These differential transcriptional programs restrict specific hepatocyte functions to defined zones, creating a sex-biased metabolic and regenerative landscape (<xref rid="b42-ijmm-58-01-05856" ref-type="bibr">42</xref>). Continuous GH infusion in males can abolish this zonal dimorphism, indicating that the mode of hormone secretion determines sex-specific liver zonation (<xref rid="b43-ijmm-58-01-05856" ref-type="bibr">43</xref>). These findings indicate that liver zonation functions as a dynamic interface integrating metabolic, endocrine and oxygen-dependent signals.</p></sec>
<sec>
<title>Wnt signaling regulates hepatic zonation programming</title>
<p>The Wnt/&#x003B2;-catenin pathway is a key regulator of pericentral hepatocyte identity (<xref rid="b44-ijmm-58-01-05856" ref-type="bibr">44</xref>). Its activity depends on tight regulation of the &#x003B2;-catenin destruction complex and phosphorylation events. Under basal conditions, &#x003B2;-catenin is continuously degraded by a destruction complex composed of Axin, adenomatous polyposis coli (APC), CK1 and GSK3&#x003B2;. CK1 initiates phosphorylation at Ser45, followed by sequential phosphorylation by GSK3&#x003B2; at Thr41, Ser37 and Ser33, which marks &#x003B2;-catenin for recognition by the &#x003B2;-TrCP E3 ubiquitin ligase and subsequent proteasomal degradation (<xref rid="b45-ijmm-58-01-05856" ref-type="bibr">45</xref>). Upon Wnt stimulation, including Wnt2 and Wnt9b secreted by central vein endothelial cells, the binding of these ligands to Frizzled receptors and the co-receptors LRP5/6 recruits CK1 and GSK3&#x003B2; to the membrane (<xref rid="b46-ijmm-58-01-05856" ref-type="bibr">46</xref>,<xref rid="b47-ijmm-58-01-05856" ref-type="bibr">47</xref>). This leads to phosphorylation of LRP5/6, inhibition of GSK3&#x003B2; activity and inactivation of the destruction complex (<xref rid="b44-ijmm-58-01-05856" ref-type="bibr">44</xref>). Stabilized &#x003B2;-catenin accumulates and translocates into the nucleus, where it binds T-cell factor/lymphoid enhancer-binding factor transcription factors to activate pericentral gene programs such as glutamine synthetase and Cyp2e1.</p>
<p>A critical determinant of zonal regulation is the spatially restricted expression of APC (<xref rid="b48-ijmm-58-01-05856" ref-type="bibr">48</xref>). APC is largely absent in the pericentral zone, permitting sustained nuclear accumulation of &#x003B2;-catenin, whereas its high expression in periportal hepatocytes constrains Wnt signaling (<xref rid="b48-ijmm-58-01-05856" ref-type="bibr">48</xref>). Genetic studies demonstrate that loss of APC leads to panlobular activation of &#x003B2;-catenin, accompanied by ectopic expression of pericentral markers such as Cyp2e1 in periportal hepatocytes (<xref rid="b49-ijmm-58-01-05856" ref-type="bibr">49</xref>). In addition, oxygen gradients modulate this axis: HIF-1&#x003B1; suppresses APC transcription in the pericentral zone, thereby enhancing &#x003B2;-catenin signaling, while reactive oxygen species in the periportal region stabilize APC, establishing a redox-dependent zonal boundary (<xref rid="b50-ijmm-58-01-05856" ref-type="bibr">50</xref>,<xref rid="b51-ijmm-58-01-05856" ref-type="bibr">51</xref>). Furthermore, Wnt5a in the periportal region antagonizes &#x003B2;-catenin activity through calcium-dependent signaling, which reinforces zone 1 identity (<xref rid="b52-ijmm-58-01-05856" ref-type="bibr">52</xref>). The Ras/MAPK/ERK pathway contributes additional modulation by promoting &#x003B2;-catenin phosphorylation and proteasomal degradation in periportal hepatocytes, thereby balancing regional signaling intensity (<xref rid="b53-ijmm-58-01-05856" ref-type="bibr">53</xref>).</p>
<p>Non-canonical Wnt pathways further refine zonal patterning. Hypoxia-induced Wnt11 in zone 3 activates planar cell polarity signaling via the ROR2 receptor, regulating pericentral gene expression independently of &#x003B2;-catenin (<xref rid="b54-ijmm-58-01-05856" ref-type="bibr">54</xref>-<xref rid="b56-ijmm-58-01-05856" ref-type="bibr">56</xref>). Wnt signaling defines hepatic zonation through coordinated regulation of the &#x003B2;-catenin destruction complex, spatial control of APC expression and integration of canonical and non-canonical pathways. It also interacts with multiple signaling networks to precisely specify hepatocyte identity along the porto-central axis.</p></sec>
<sec>
<title>Spatial regulation of Hh signaling in hepatic zonation</title>
<p>The Hh signaling pathway is also a key regulator of hepatic metabolic zonation. It coordinates functional specialization along the porto-central axis through spatially restricted ligand-receptor interactions (<xref rid="b57-ijmm-58-01-05856" ref-type="bibr">57</xref>). Spatial transcriptomics analyses have shown that Indian Hh is enriched in the pericentral region, forming a morphogen gradient that is inversely correlated with Wnt/&#x003B2;-catenin signaling activity in the periportal zone (<xref rid="b31-ijmm-58-01-05856" ref-type="bibr">31</xref>). This spatial relationship is maintained through GLI-mediated inhibition of &#x003B2;-catenin transcriptional activity, establishing a dynamic balance between the two pathways (<xref rid="b58-ijmm-58-01-05856" ref-type="bibr">58</xref>). The Hh gradient can also regulate components of the insulin-like growth factor axis (IGF-I/IGFBP-1) to coordinate zonal metabolic programming (<xref rid="b59-ijmm-58-01-05856" ref-type="bibr">59</xref>). Pericentral hepatocytes exhibit GLI-dependent upregulation of gluconeogenic enzymes, whereas periportal regions show enhanced lipid oxidation (<xref rid="b32-ijmm-58-01-05856" ref-type="bibr">32</xref>). Furthermore, hepatic stellate cells (HSCs) in the space of Disse act as spatial signal integrators; they convert Hh/Wnt crosstalk into extracellular matrix (ECM) remodeling, thereby physically maintaining the structure of metabolic zonation (<xref rid="b60-ijmm-58-01-05856" ref-type="bibr">60</xref>).</p></sec>
<sec>
<title>Spatial organization of hepatic non-parenchymal cells</title>
<p>Emerging evidence indicates that the spatially restricted cellular niches of non-parenchymal cells, particularly the periportal vs. pericentral zonation patterns, establish microenvironments that directly modulate hepatocyte functional specialization via ECM regulation, metabolic exchange and immune surveillance, thereby driving the establishment of hepatic metabolic zonation (<xref rid="b61-ijmm-58-01-05856" ref-type="bibr">61</xref>). Among these, liver sinusoidal endothelial cells (LSECs) act as central regulators of zonation. Central vein associated LSECs selectively secrete Wnt2, Wnt9b and R-spondin 3, thereby activating &#x003B2;-catenin signaling in adjacent hepatocytes and maintaining pericentral cell identity (<xref rid="b47-ijmm-58-01-05856" ref-type="bibr">47</xref>,<xref rid="b62-ijmm-58-01-05856" ref-type="bibr">62</xref>). Consistently, combined deletion of Wnt2 and Wnt9b abolishes zone 3 specific gene expression. In addition, LSECs modulate sinusoidal blood flow and oxygen tension through the secretion of vascular endothelial growth factors, contributing to the establishment of the porto-central metabolic axis (<xref rid="b63-ijmm-58-01-05856" ref-type="bibr">63</xref>). Kupffer cells exhibit a preferential periportal distribution, forming an immune zonation pattern (<xref rid="b29-ijmm-58-01-05856" ref-type="bibr">29</xref>). By restricting infiltrating neutrophils to the periportal region, they spatially confine pro-inflammatory responses, thereby protecting the metabolically vulnerable pericentral hepatocytes. Disruption of Kupffer cell localization leads to bacterial dissemination and panlobular inflammatory injury (<xref rid="b64-ijmm-58-01-05856" ref-type="bibr">64</xref>-<xref rid="b65-ijmm-58-01-05856" ref-type="bibr">65</xref>). HSCs also display zonal heterogeneity, comprising functionally distinct subpopulations (<xref rid="b66-ijmm-58-01-05856" ref-type="bibr">66</xref>). Periportal-associated stellate cells express markers such as Ngfr and Tagln and are involved in rapid immune interactions, whereas pericentral-associated stellate cells specifically express Rspo3, which enhances Wnt signaling to sustain pericentral hepatocyte homeostasis (<xref rid="b67-ijmm-58-01-05856" ref-type="bibr">67</xref>,<xref rid="b68-ijmm-58-01-05856" ref-type="bibr">68</xref>).</p></sec>
<sec>
<title>Epigenetic modulation as a determinant of liver zonation</title>
<p>Beyond extrinsic cues, hepatic zonation is also governed by intrinsic epigenetic programs (<xref rid="b69-ijmm-58-01-05856" ref-type="bibr">69</xref>). DNA methylation has been shown to form a gradient along the porto-central axis, progressively decreasing from the periportal to the pericentral zone. Key transcription factors exhibit spatially restricted expression patterns; USF1 is enriched in periportal hepatocytes, where it exerts negative feedback on periportal-specific genes while modulating lipid and glucose metabolism (<xref rid="b70-ijmm-58-01-05856" ref-type="bibr">70</xref>). By contrast, Nr2f2 is progressively enriched in the pericentral zone and activates pericentral identity genes during hepatocyte maturation (<xref rid="b69-ijmm-58-01-05856" ref-type="bibr">69</xref>,<xref rid="b71-ijmm-58-01-05856" ref-type="bibr">71</xref>). Although HNF4&#x003B1; is uniformly expressed, its DNA-binding activity is gated by methylation status, and its deletion leads to ectopic expression of pericentral genes in periportal hepatocytes (<xref rid="b71-ijmm-58-01-05856" ref-type="bibr">71</xref>,<xref rid="b72-ijmm-58-01-05856" ref-type="bibr">72</xref>).</p>
<p>Histone modifications further reinforce zonal specialization. H3K27ac, a histone acetylation marker of active enhancers, is enriched at regulatory elements of Wnt/&#x003B2;-catenin-associated pericentral metabolic genes, whereas H3K4me3, a histone trimethylation marker of active promoters, predominantly labels genes involved in periportal metabolic pathways such as gluconeogenesis and the urea cycle (<xref rid="b73-ijmm-58-01-05856" ref-type="bibr">73</xref>). The SWI/SNF chromatin remodeling component ARID1A maintains hepatocyte metabolic gene programs by regulating nucleosome positioning and chromatin accessibility (<xref rid="b74-ijmm-58-01-05856" ref-type="bibr">74</xref>); hepatocyte-specific loss of ARID1A reduces accessibility at metabolic loci, impairs binding of transcription factors such as PPAR&#x003B1; and suppresses the expression of genes involved in fatty acid &#x003B2;-oxidation (<xref rid="b75-ijmm-58-01-05856" ref-type="bibr">75</xref>).</p>
<p>MicroRNAs (miRs) also provide an additional layer of fine-tuning. For example, liver-enriched miR-122 is required for the maintenance of zonation, and its deletion results in expansion of zone 3 characteristics (<xref rid="b76-ijmm-58-01-05856" ref-type="bibr">76</xref>,<xref rid="b77-ijmm-58-01-05856" ref-type="bibr">77</xref>). Collectively, DNA methylation, histone modifications, non-coding RNAs and transcription factor dynamics converge to form an integrated epigenetic-metabolic axis that spatially encodes hepatocyte identity.</p></sec></sec>
<sec sec-type="other">
<label>5.</label>
<title>Zonation homeostasis: Spatial metabolic regulation as a guardian of liver health</title>
<p>The spatial compartmentalization of hepatic function constitutes a critical defense mechanism against metabolic stress. Within this organizational framework, the Wnt/&#x003B2;-catenin pathway serves a central role, not only in maintaining pericentral hepatocyte identity but also in regulating hepatocyte turnover. Early lineage-tracing studies proposed that Axin2<sup>+</sup> hepatocytes located in the pericentral possess stem-like properties and contribute to long-term hepatocyte renewal under homeostatic conditions (<xref rid="b78-ijmm-58-01-05856" ref-type="bibr">78</xref>). However, accumulating evidence suggests that the contribution of these cells may have been overestimated due to labeling artifacts and signal-dependent activation of reporter systems in Axin2-Cre models (<xref rid="b79-ijmm-58-01-05856" ref-type="bibr">79</xref>,<xref rid="b80-ijmm-58-01-05856" ref-type="bibr">80</xref>). Multiple independent studies indicate that hepatocyte renewal occurs broadly throughout the liver lobule rather than being restricted to a discrete pericentral progenitor population (<xref rid="b81-ijmm-58-01-05856" ref-type="bibr">81</xref>-<xref rid="b83-ijmm-58-01-05856" ref-type="bibr">83</xref>). Accordingly, Axin2<sup>+</sup> hepatocytes are more likely to represent a Wnt responsive hepatocyte subset primarily responsible for maintaining zonal identity, rather than serving as a universal stem cell reservoir, although they may acquire regenerative potential under specific injury contexts (<xref rid="b80-ijmm-58-01-05856" ref-type="bibr">80</xref>). A similar paradigm applies to Leucine-rich repeat-containing G-protein-coupled receptor 5-positive (Lgr5<sup>+</sup>) hepatocytes. These cells are exceedingly rare in the healthy liver but can be induced following injury (<xref rid="b84-ijmm-58-01-05856" ref-type="bibr">84</xref>). Under physiological conditions, the nuclear receptor farnesoid X receptor (FXR) maintains Lgr5<sup>+</sup> hepatocytes in a quiescent state; by contrast, metabolic stress or tissue injury activates a PPAR&#x003B1;-dependent proliferative program, enabling their transient participation in tissue repair (<xref rid="b85-ijmm-58-01-05856" ref-type="bibr">85</xref>). Notably, aberrant activation of Lgr5 may compromise cellular identity and contribute to tumor progression.</p>
<p>Within this zonation dependent regulatory landscape, telomerase-positive (Tert<sup>high</sup>) hepatocytes are predominantly localized to zones 1-2, where they function as a clonogenic reservoir supporting parenchymal homeostasis and injury repair (<xref rid="b81-ijmm-58-01-05856" ref-type="bibr">81</xref>,<xref rid="b86-ijmm-58-01-05856" ref-type="bibr">86</xref>). Spatially resolved profiling has further identified Hamp2<sup>+</sup>/Igfbp2<sup>+</sup> zone 2 hepatocytes as a principal subpopulation driving homeostatic regeneration. CRISPR-based functional screening demonstrates that Igfbp2-induced cell cycle progression is essential for their proliferative capacity, mechanistically linking regional metabolic cues to regenerative potential (<xref rid="b87-ijmm-58-01-05856" ref-type="bibr">87</xref>,<xref rid="b88-ijmm-58-01-05856" ref-type="bibr">88</xref>). This hierarchical organization, where Tert<sup>high</sup> hepatocytes provide broad regenerative capacity and Igfbp2<sup>+</sup> subsets execute spatially restricted proliferation illustrates how spatial signaling networks enable precisely coordinated regeneration while preserving metabolic zonation (<xref rid="b89-ijmm-58-01-05856" ref-type="bibr">89</xref>).</p>
<sec>
<title>Gestational hepatic adaptation: zonal proliferation hierarchies for maternal-fetal metabolic coupling</title>
<p>Based on the principles of zonated hepatocyte renewal, pregnancy induces a spatiotemporally coordinated remodeling of the liver. Hepatocyte proliferation progresses in a zonal sequence, initiating in the periportal zone 1 during early pregnancy, shifting to zone 2 in mid-gestation and culminating in pericentral zone 3 expansion in late pregnancy. This dynamic pattern parallels the progressive increase in fetal metabolic demands (<xref rid="b20-ijmm-58-01-05856" ref-type="bibr">20</xref>). Lineage tracing studies indicate that estrogen coordinates this hierarchical zonal program by selectively promoting the proliferation of Ccnd1 positive hepatocytes in zone 2, whereas prolactin fine-tunes liver mass through bile acid mediated hypertrophic regulation (<xref rid="b90-ijmm-58-01-05856" ref-type="bibr">90</xref>,<xref rid="b91-ijmm-58-01-05856" ref-type="bibr">91</xref>). This spatial proliferation program is closely aligned with metabolic compartmentalization. Expansion in zones 1 and 2 supports glucose and cofactor synthesis required for fetal growth, while proliferation in zone 3 enhances detoxification capacity to counteract pregnancy associated oxidative stress (<xref rid="b90-ijmm-58-01-05856" ref-type="bibr">90</xref>,<xref rid="b91-ijmm-58-01-05856" ref-type="bibr">91</xref>). Despite these advances, critical gaps remain in understanding how maternal liver zonation adapts and synchronizes with key milestones of fetal development. This highlights the need to elucidate how the placenta liver signaling axis preserves zonation fidelity during pregnancy.</p></sec></sec>
<sec sec-type="other">
<label>6.</label>
<title>Liver zonation in liver injury: Zonation collapse as a driver of disease progression</title>
<p>The spatial erosion of metabolic zonation is a hallmark of liver pathology, where hepatocyte loss disrupts lobular signaling topography and initiates self-amplifying injury circuits (<xref rid="f2-ijmm-58-01-05856" ref-type="fig">Fig. 2</xref>). Notably, zone-specific hepatocyte necrosis, whether periportal oxidative stress or pericentral toxin accumulation, triggers localized inflammatory cascades that recruit neutrophils and monocytes (<xref rid="b92-ijmm-58-01-05856" ref-type="bibr">92</xref>,<xref rid="b93-ijmm-58-01-05856" ref-type="bibr">93</xref>). This inflammatory feed-forward loop not only exacerbates regional damage but also propagates zonation collapse.</p>
<sec>
<title>Metabolic liver diseases as pathological models of hepatic zonation disruption</title>
<p>Metabolic dysfunction associated steatotic liver disease (MASLD) is a liver disorder linked to metabolic dysfunction and is characterized by a systemic collapse of lobular metabolic zonation architecture (<xref rid="b94-ijmm-58-01-05856" ref-type="bibr">94</xref>). This pathological cascade is driven by coordinated dysregulation of the three core metabolic processes, uptake, synthesis and export, ultimately disrupting the signaling gradients required to maintain functional compartmentalization (<xref rid="b95-ijmm-58-01-05856" ref-type="bibr">95</xref>). Hepatic steatosis, a hallmark feature of MASLD, shows a developmentally and spatially patterned distribution. In adult patients, lipid accumulation typically initiates in zone 3, the primary site of fatty acid synthesis (<xref rid="b96-ijmm-58-01-05856" ref-type="bibr">96</xref>). Lipotoxicity in this region triggers zone 3-predominant hepatocyte apoptosis and pericentral fibrosis (<xref rid="b97-ijmm-58-01-05856" ref-type="bibr">97</xref>). As the disease progresses to metabolic dysfunction-associated steatohepatitis (MASH), the spatial pattern of fibrosis is remodeled, with collagen deposition shifting toward zone 1 and forming porto-central bridging fibrosis, a key precursor of cirrhosis (<xref rid="b98-ijmm-58-01-05856" ref-type="bibr">98</xref>). But prepubertal MASLD exhibits an opposite spatial pattern, characterized by zone 1-dominant steatosis and periportal fibrosis without pericentral involvement, which is associated with developmental metabolic programming and microenvironment-specific immune responses (<xref rid="b99-ijmm-58-01-05856" ref-type="bibr">99</xref>).</p>
<p>Dysregulated zonal signaling is a key determinant of disease severity. Elevated Hh ligand levels and yes-associated protein (YAP) activation are associated with steatohepatitis and fibrosis progression, while Wnt/&#x003B2;-catenin-mediated pericentral homeostasis is disrupted (<xref rid="b100-ijmm-58-01-05856" ref-type="bibr">100</xref>,<xref rid="b101-ijmm-58-01-05856" ref-type="bibr">101</xref>). Kupffer cells, traditionally localized to the periportal region, amplify zonation-restricted inflammation in early MASLD by recruiting neutrophils and releasing pro-fibrotic cytokines, thereby exacerbating zone 1 injury (<xref rid="b102-ijmm-58-01-05856" ref-type="bibr">102</xref>). Meanwhile, periportal ductular reactions characterized by hepatic progenitor cell expansion may contribute to porto-portal fibrosis, although their direct pro-fibrotic role remains to be fully validated (<xref rid="b103-ijmm-58-01-05856" ref-type="bibr">103</xref>,<xref rid="b104-ijmm-58-01-05856" ref-type="bibr">104</xref>). Mechanistically, early MASLD retains lobular zonation, with preserved regional gene expression and DNA methylation patterns, suggesting a therapeutic window for zonation restoration (<xref rid="b71-ijmm-58-01-05856" ref-type="bibr">71</xref>). This reversibility highlights the potential of targeting zone-specific drivers, including Kupffer cell-mediated spatial inflammation, HSC-derived ECM imbalance and liver sinusoidal endothelial cell-driven Wnt signaling dysregulation, to block the steatosis-fibrosis axis (<xref rid="b105-ijmm-58-01-05856" ref-type="bibr">105</xref>-<xref rid="b107-ijmm-58-01-05856" ref-type="bibr">107</xref>).</p></sec>
<sec>
<title>Hepatocellular carcinoma (HCC) as a zonation-entrenched malignancy</title>
<p>HCC arises from zonation-collapsed microenvironments in cirrhotic livers, with chronic hepatitis and metabolic dysfunction driving spatially biased oncogenesis (<xref rid="b108-ijmm-58-01-05856" ref-type="bibr">108</xref>). It is reported that &gt;50% of HCCs exhibit constitutive Wnt/&#x003B2;-catenin activation, a pathway central to pericentral zonation, alongside Hh signaling hyperactivation, constitutive YAP/TAZ activation and glycolytic reprogramming, collectively hijacking zonation-maintaining circuits to fuel tumor initiation (<xref rid="b109-ijmm-58-01-05856" ref-type="bibr">109</xref>,<xref rid="b110-ijmm-58-01-05856" ref-type="bibr">110</xref>). While HCC cellular origins remain debated, clonal tracing reveals that regeneration-competent hepatocytes within injury niches serve as dominant precursors, acquiring malignant traits through niche-derived pressures (<xref rid="b83-ijmm-58-01-05856" ref-type="bibr">83</xref>,<xref rid="b111-ijmm-58-01-05856" ref-type="bibr">111</xref>).</p>
<p>Hypoxia-mediated metabolic zonation collapse further shapes HCC evolution. Pericentral hypoxia stabilizes HIF-1&#x003B1;, synergizing with &#x003B2;-catenin to select for venous zone-adapted clones with glutamine addiction and invasive potential (<xref rid="b112-ijmm-58-01-05856" ref-type="bibr">112</xref>). Notably, HCCs retain zonation-like phenotypic diversity, as portal-like HCC with low &#x003B2;-catenin expression mirrors periportal metabolism, exhibiting indolent behavior and favorable post-resection outcomes due to preserved immune surveillance. However, central-like HCC recapitulates pericentral features with high &#x003B2;-catenin, marked by immune-cold microenvironments and resistance to checkpoint blockade, yet maintains vulnerability to Wnt/Hh-targeted therapies (<xref rid="b108-ijmm-58-01-05856" ref-type="bibr">108</xref>). This zonation-based classification system overcomes the limitations of conventional histopathological subtyping and enables prognostic stratification as well as compartment-specific therapeutic strategies (<xref rid="b113-ijmm-58-01-05856" ref-type="bibr">113</xref>). From a therapeutic perspective, restoring Wnt signaling gradients or targeting the hypoxia-HIF-&#x003B2;-catenin axis may reverse treatment resistance driven by spatial dedifferentiation. In addition, portal vein-like HCC may benefit from immunomodulatory approaches that exploit residual zonal differentiation integrity (<xref rid="b114-ijmm-58-01-05856" ref-type="bibr">114</xref>,<xref rid="b115-ijmm-58-01-05856" ref-type="bibr">115</xref>).</p></sec>
<sec>
<title>Drug-induced liver injury (DILI) as a zonation-restorative challenge</title>
<p>DILI, exemplified by acetaminophen (APAP) and carbon tetrachloride models, manifests zonation-biased damage, as demonstrated by the studies that pericentral hepatocytes (zone 3) with high cytochrome P450 activity (including Cyp2e1) metabolize toxins into reactive intermediates such as NAPQI, triggering oxidative stress and mitochondrial dysfunction that culminate in zone 3-predominant necrosis (<xref rid="b116-ijmm-58-01-05856" ref-type="bibr">116</xref>-<xref rid="b118-ijmm-58-01-05856" ref-type="bibr">118</xref>). Spatial reprogramming at the injury border initiates repair where damage-adjacent hepatocytes transiently reactivate fetal genes and upregulate ribosomes and proteasomes, enabling proteome remodeling to adopt pericentral identities (<xref rid="b82-ijmm-58-01-05856" ref-type="bibr">82</xref>). Concurrently, zonation-restricted regeneration unfolds where surviving pericentral hepatocytes initiate proliferation via mTOR signaling, followed by zone 2 hepatocyte expansion (<xref rid="b3-ijmm-58-01-05856" ref-type="bibr">3</xref>). A recent study demonstrated zone 2-derived hepatocytes as a main contributor to compartmentalized replenishment, where Igfbp2<sup>+</sup> hepatocytes migrate toward necrotic zone 3 and restore metabolic zonation (<xref rid="b89-ijmm-58-01-05856" ref-type="bibr">89</xref>).</p>
<p>In addition, annexin A2-positive (ANXA2<sup>+</sup>) hepatocyte subpopulations exhibit a migration-dominant wound closure mechanism during APAP-induced injury, sealing necrotic areas prior to mitotic expansion (<xref rid="b119-ijmm-58-01-05856" ref-type="bibr">119</xref>). This ANXA2-mediated migratory plasticity, previously implicated in cancer cell invasion, suggests a form of region-specific reparative plasticity in which spatial remodeling, rather than proliferation alone, drives functional recovery (<xref rid="b119-ijmm-58-01-05856" ref-type="bibr">119</xref>,<xref rid="b120-ijmm-58-01-05856" ref-type="bibr">120</xref>). The interplay between migration and mitosis may help maintain a dynamic balance between lobular structural integrity and metabolic demands. However, excessive migratory pressure may contribute to ductular reactions and fibrotic scar formation (<xref rid="b121-ijmm-58-01-05856" ref-type="bibr">121</xref>,<xref rid="b122-ijmm-58-01-05856" ref-type="bibr">122</xref>).</p></sec>
<sec>
<title>Cholestatic injury and zonal repair programs: Portal niche remodeling in ductal pathobiology</title>
<p>Experimental cholestasis models, including DDC diet and bile duct ligation, precisely recapitulate human cholangiopathies while unveiling zonation-defined injury patterns (<xref rid="b123-ijmm-58-01-05856" ref-type="bibr">123</xref>). Cholestatic injury predominantly targets zone 1 hepatocytes, as bile acids first accumulate in the periportal region following impaired biliary excretion. Hydrophobic bile acids induce membrane damage through detergent-like effects, disrupt mitochondrial function, and trigger oxidative stress and endoplasmic reticulum stress. In parallel, bile acid-activated death receptor signaling, including Fas and TRAIL pathways, further amplifies hepatocyte injury. Zone 1 hepatocytes are particularly susceptible due to their high expression of bile acid uptake transporters such as NTCP and OATPs, together with limited adaptive capacity for detoxification compared with downstream zones (<xref rid="b124-ijmm-58-01-05856" ref-type="bibr">124</xref>). In addition, cholestasis induces inflammatory signaling from portal stromal and immune cells, further reinforcing periportal injury and ECM remodeling.</p>
<p>Mechanistically, periportal hepatocytes exposed to cholestatic stress can establish a self-limiting reparative microenvironment. Within this setting, a distinct subpopulation of hepatocytes with a unique phenotype has been identified in the periportal niche. These cells express multiple biliary-enriched genes, including low levels of Sox9, while retaining the canonical hepatocyte marker HNF4&#x003B1;. This population, termed hybrid hepatocytes (HybHPs), is capable of contributing to parenchymal regeneration through proliferative expansion (<xref rid="b125-ijmm-58-01-05856" ref-type="bibr">125</xref>). However, the origin of HybHPs remains controversial. In chronic injury models, HybHPs have been proposed to arise from embryonic progenitors located in the ductal plate, as these cells can upregulate biliary markers and differentiate into cholangiocytes. However, studies using partial hepatectomy models suggest that HybHPs originate from mature hepatocytes, as they appear as early as 3 h after resection without evidence of early activation of hepatic progenitor cells (<xref rid="b126-ijmm-58-01-05856" ref-type="bibr">126</xref>). Furthermore, in MASLD models, analysis of fetal liver markers indicates that these biphenotypic cells do not undergo dedifferentiation or redifferentiation (<xref rid="b127-ijmm-58-01-05856" ref-type="bibr">127</xref>). Taken together, these findings suggest that HybHPs most likely arise from mature hepatocytes undergoing microenvironment-driven transdifferentiation in response to alterations in the periportal niche during injury, rather than from stem cell populations or developmental progenitors. In addition, chronic cholestasis activates cholangiocyte progenitor cells through the FXR/TGR5 signaling pathway, which in turn induces collagen deposition from HSCs, leading to periportal fibrosis and consequently disrupting the architecture of zone 1 (<xref rid="b128-ijmm-58-01-05856" ref-type="bibr">128</xref>).</p></sec></sec>
<sec sec-type="other">
<label>7.</label>
<title>Liver regeneration: Zonal identity plasticity and hierarchical progenitor engagement</title>
<p>The regenerative capacity of the liver is deeply rooted in its metabolically zonated architecture. Early lineage-tracing studies suggested that Mfsd2a positive zone 1 hepatocytes migrate toward the pericentral region (<xref rid="b129-ijmm-58-01-05856" ref-type="bibr">129</xref>); however, more recent evidence identifies Igfbp2 positive and Hamp2 positive zone 2 hepatocytes as the primary drivers of regeneration. Their proliferative advantage is mediated by mTOR-CCND1 signaling, a mechanism conserved with pregnancy-induced liver growth (<xref rid="b30-ijmm-58-01-05856" ref-type="bibr">30</xref>). In parallel, Sox9 positive hepatocytes derived from the periportal microenvironment acquire progenitor-like features during regeneration, recapitulating biliary repair programs and underscoring the dual role of zone 1 in metabolic function and regenerative adaptation (<xref rid="b130-ijmm-58-01-05856" ref-type="bibr">130</xref>,<xref rid="b131-ijmm-58-01-05856" ref-type="bibr">131</xref>). Zone 1 mobilizes hepatic progenitor cells and biliary transdifferentiation to compensate for parenchymal loss, whereas zone 3 recruits Axin2<sup>+</sup>, Lgr5<sup>+</sup> and Cyp2e1<sup>+</sup> hepatocytes to support pericentral repair (<xref rid="b132-ijmm-58-01-05856" ref-type="bibr">132</xref>). This hierarchical strategy ensures preservation of metabolic zonation during tissue reconstruction. Importantly, this system operates through interzonal crosstalk, with zone 2 derived Igfbp2 promoting activation of zone 1 progenitor responses, while zone 3 Wnt signaling suppresses ectopic biliary reactions (<xref rid="b133-ijmm-58-01-05856" ref-type="bibr">133</xref>).</p>
<p>In addition to the hepatocyte subpopulations with regenerative potential as aforementioned, multiple liver injury models have shown that hepatocytes at the injury interface can dedifferentiate from mature hepatocytes into progenitor-like cells (<xref rid="b118-ijmm-58-01-05856" ref-type="bibr">118</xref>). Beyond the well-characterized HNF4&#x003B1;<sup>+</sup>Sox9<sup>+</sup> population, these also include AFP<sup>+</sup> reprogrammed hepatocytes. These cells retain lineage restriction while acquiring controllable proliferative capacity. Their functional state is regulated through AFP-dependent metabolic reprogramming and dynamically balanced between proliferation and stress adaptation via the PPAR&#x003B3; signaling axis (<xref rid="b5-ijmm-58-01-05856" ref-type="bibr">5</xref>). Furthermore, expansion of this cell population is driven by TNF-&#x003B1;/AP-1 signaling originating from neutrophils in the host liver, highlighting the critical role of the immune microenvironment in regulating regenerative cell states. Collectively, these findings indicate that liver regeneration does not rely on a single progenitor pool but instead involves coordinated responses from multiple hepatocyte subpopulations with distinct zonal characteristics. This coordinated response forms a dynamic and adaptive regenerative network, and such cellular plasticity is essential for effective tissue repair.</p></sec>
<sec sec-type="other">
<label>8.</label>
<title>Regenerative therapeutics: Spatial reprogramming of hepatic niche networks</title>
<p>Emerging paradigms in liver regeneration therapeutics converge on spatial orchestration of cellular plasticity and microenvironmental reprogramming (<xref rid="b1-ijmm-58-01-05856" ref-type="bibr">1</xref>). At the cellular level, strategies focus on modulating intrinsic plasticity thresholds through epigenetic and metabolic circuit editing, enabling context-dependent transdifferentiation while preserving functional zonation (<xref rid="f3-ijmm-58-01-05856" ref-type="fig">Fig. 3</xref>) (<xref rid="b134-ijmm-58-01-05856" ref-type="bibr">134</xref>,<xref rid="b135-ijmm-58-01-05856" ref-type="bibr">135</xref>). Concurrently, niche-directed approaches recalibrate stromal-immune signaling gradients to license region-specific progenitor activation (<xref rid="b136-ijmm-58-01-05856" ref-type="bibr">136</xref>).</p>
<sec>
<title>Metabolic reprogramming in liver regeneration: Therapeutic targets for compartmentalized repair</title>
<p>Liver regeneration necessitates dynamic metabolic adaptation, where zonation-defined specialization is transiently repurposed to resolve the energy-biosynthesis paradox (<xref rid="b135-ijmm-58-01-05856" ref-type="bibr">135</xref>). In the early phase of regeneration, HIF-1&#x003B1;-driven glycolytic flux predominates, while AKT/mTOR-mediated suppression of gluconeogenesis and FAO redirects substrates toward lipid droplet biogenesis, providing a strategic energy reserve to support proliferative expansion (<xref rid="b137-ijmm-58-01-05856" ref-type="bibr">137</xref>). This metabolic triage creates therapeutic opportunities through phased interventions. First, HIF stabilizers boost zone 1-2 glycolytic priming. Concurrently, PPAR&#x003B3; agonists sustain lipogenic competence, while mTOR modulators delay catabolic restoration to preserve energy reservoirs (<xref rid="b138-ijmm-58-01-05856" ref-type="bibr">138</xref>). Post-proliferative metabolic recovery, driven by PPAR&#x003B1;-dependent FAO reactivation and mitochondrial rejuvenation, is spatially coordinated to reinstate functional zonation (<xref rid="b139-ijmm-58-01-05856" ref-type="bibr">139</xref>,<xref rid="b140-ijmm-58-01-05856" ref-type="bibr">140</xref>). This phase ensures pericentral detoxification via CYP450 restoration and zonal energy flux balancing, completing the metabolic reprogramming cycle essential for functional restoration.</p></sec>
<sec>
<title>Epigenetic control of metabolic plasticity: Therapeutic anchoring to zonal memory</title>
<p>Epigenetic modifiers serve as spatial regulators of metabolic reprogramming, offering druggable nodes to enhance regenerative precision. DNA methyltransferases (DNMTs) enforce FAO gene silencing during regeneration initiation, with pharmacological DNMT inhibition extending the glycolytic proliferative window (<xref rid="b141-ijmm-58-01-05856" ref-type="bibr">141</xref>). Conversely, histone acetylase activators accelerate oxidative phosphorylation recovery by decompacting chromatin at mitochondrial genes, enabling timely metabolic restoration (<xref rid="b142-ijmm-58-01-05856" ref-type="bibr">142</xref>,<xref rid="b143-ijmm-58-01-05856" ref-type="bibr">143</xref>). Spatial multiomics have decoded zone-specific metabolite-epigenome crosstalk, identifying serine and ketone bodies as zone 2 resolved cofactors that prime chromatin accessibility for plasticity transcription factors, a mechanism that may be exploitable through dietary or metabolite supplementation strategies (<xref rid="b144-ijmm-58-01-05856" ref-type="bibr">144</xref>). For instance, zone 1 targeted HIF stabilizers amplify glycolytic flux, while zone 2 directed serine supplementation reinforces epigenetic licensing of plasticity genes. By mirroring the liver's innate spatiotemporal hierarchy where metabolic priorities shift from proliferation fuel to functional specialization, these strategies transform regenerative bottlenecks into therapeutic windows.</p></sec>
<sec>
<title>Non-parenchymal cell therapeutics: Spatial modulation of regenerative niches</title>
<p>Non-parenchymal cells have been recognized for their roles in maintaining liver zonation, and also make critical contributions to the regenerative microenvironment. Spatial transcriptomics and single-cell analyses have shown that pericentral HSC subsets enhance Wnt/&#x003B2;-catenin signaling through secretion of Rspo3, thereby supporting hepatocyte proliferation during regeneration (<xref rid="b141-ijmm-58-01-05856" ref-type="bibr">141</xref>). The loss of HSCs or Rspo3 impairs regenerative capacity, while clinical data indicate that higher Rspo3 expression is associated with improved survival and a reduced risk of hepatocellular carcinoma, supporting its potential as a therapeutic target (<xref rid="b145-ijmm-58-01-05856" ref-type="bibr">145</xref>).</p>
<p>LSECs are also key regulators of regeneration. Previous studies demonstrate that LSECs promote hepatocyte proliferation through secretion of Wnt2 and Wnt9b (<xref rid="b47-ijmm-58-01-05856" ref-type="bibr">47</xref>,<xref rid="b146-ijmm-58-01-05856" ref-type="bibr">146</xref>,<xref rid="b147-ijmm-58-01-05856" ref-type="bibr">147</xref>). Further work has identified c-Kit signaling in LSECs as essential for this pro-regenerative function. c-Kit<sup>+</sup> LSECs upregulate Wnt2 expression following injury, thereby stimulating proliferation of adjacent hepatocytes, whereas disruption of c-Kit signaling reduces Wnt production and significantly impairs liver regeneration (<xref rid="b147-ijmm-58-01-05856" ref-type="bibr">147</xref>,<xref rid="b148-ijmm-58-01-05856" ref-type="bibr">148</xref>). Recent advances have extended these findings into therapeutic strategies. Engineered exosome-based systems have been developed to target LSECs, combining CRLTRKRGLK peptide-mediated targeting with CD47 mediated evasion of mononuclear phagocyte clearance, enabling efficient delivery of Wnt2 mRNA (<xref rid="b149-ijmm-58-01-05856" ref-type="bibr">149</xref>). In APAP and dimethylnitrosamine-induced liver injury models, this approach enhances Wnt signaling, promotes hepatocyte proliferation, and improves tissue repair, demonstrating the feasibility of modulating non-parenchymal cell-derived signals to reconstruct the regenerative microenvironment (<xref rid="b149-ijmm-58-01-05856" ref-type="bibr">149</xref>).</p>
<p>In addition, a recent study has shown that injury-induced downregulation of URI1 leads to glutamate accumulation, which acts as a paracrine signal to recruit bone marrow-derived monocytes. These immune cells subsequently secrete Wnt3, activating YAP1 signaling in zone 2 hepatocytes and driving their proliferation (<xref rid="b150-ijmm-58-01-05856" ref-type="bibr">150</xref>). This metabolic immune regenerative axis follows a well-defined spatiotemporal sequence and has been validated across multiple models of acute and chronic liver injury. Clinical analyses further suggest that this pathway is dysregulated in chronic liver disease, characterized by reduced Wnt3 expression and disrupted metabolic signaling (<xref rid="b150-ijmm-58-01-05856" ref-type="bibr">150</xref>). Non-parenchymal cells thus establish a spatially organized signaling network that governs liver regeneration within the framework of liver zonation. This coordinated multicellular system indicates that liver regeneration is not driven by a single cell type but instead depends on the dynamic remodeling of zonation-defined regenerative niches. Targeting non-parenchymal cells and their spatial signaling networks therefore represents a promising strategy for enhancing liver regeneration.</p></sec>
<sec>
<title>Hepatocyte reprogramming: Spatial control of plasticity for regenerative therapy</title>
<p>Hepatocyte dedifferentiation, a spatially restricted process predominantly localized to zone 2, functions as an evolutionary safeguard mechanism for hepatic repair. This regenerative phenomenon involves surviving hepatocytes reactivating fetal transcriptional programs through conserved developmental pathways, particularly Wnt/&#x003B2;-catenin (<xref rid="b151-ijmm-58-01-05856" ref-type="bibr">151</xref>), YAP (<xref rid="b152-ijmm-58-01-05856" ref-type="bibr">152</xref>) and TGF-&#x003B2; signaling cascades (<xref rid="b153-ijmm-58-01-05856" ref-type="bibr">153</xref>). Beyond the classical Sox9<sup>+</sup>/HNF4&#x003B1;<sup>+</sup> progenitor-like transition, studies have identified multiple regenerative hepatocyte subpopulations arising from dedifferentiation or enhanced cellular plasticity of mature hepatocytes (<xref rid="b154-ijmm-58-01-05856" ref-type="bibr">154</xref>). For instance, AFP-positive reprogrammed hepatocytes represent a state of partial dedifferentiation, retaining lineage restriction while acquiring proliferative capacity. Hepatocytes driven by YAP or Wnt/&#x003B2;-catenin signaling exhibit a reversible progenitor-like phenotype (<xref rid="b152-ijmm-58-01-05856" ref-type="bibr">152</xref>). In addition, transitional hepatocyte populations with high transcriptional plasticity, as well as hepatocytes with migratory capacity involved in wound repair, have been identified at injury borders (<xref rid="b119-ijmm-58-01-05856" ref-type="bibr">119</xref>). Collectively, these distinct cellular states constitute a heterogeneous pool of regenerative sources, indicating that liver regeneration relies on multilayered cell fate reprogramming rather than a single progenitor reservoir.</p>
<p>Critically, liver regeneration extends beyond cell-autonomous reprogramming through spatially coordinated niche interactions. For example, portal vein injury models reveal that regionally activated Kupffer cells secrete IL-6, which induces STAT3 activation in adjacent hepatocytes to directly drive reprogramming-related gene re-expression (<xref rid="b154-ijmm-58-01-05856" ref-type="bibr">154</xref>). This spatial regulation is further governed by metabolic zonation dynamics that compartmentalize regenerative responses across hepatic lobules.</p></sec></sec>
<sec sec-type="other">
<label>9.</label>
<title>Zonation-based therapies for liver diseases and barriers to clinical translation</title>
<p>Therapeutic strategies for liver diseases have expanded with the development of multiple targeted agents, several of which directly exploit or modulate hepatic zonation features (<xref rid="tII-ijmm-58-01-05856" ref-type="table">Table II</xref>). In MASH, obeticholic acid, an agonist of the FXR, regulates bile acid metabolism in close association with the functional specialization of pericentral hepatocytes (<xref rid="b155-ijmm-58-01-05856" ref-type="bibr">155</xref>). Aldafermin (NGM282), a FGF19 analog, suppresses bile acid synthesis through FGFR4 signaling and similarly targets metabolic regulation in the pericentral zone (<xref rid="b156-ijmm-58-01-05856" ref-type="bibr">156</xref>). PRI-724 selectively inhibits the interaction between &#x003B2;-catenin and CBP, thereby directly modulating Wnt-dependent zonal signaling in pericentral hepatocytes (<xref rid="b157-ijmm-58-01-05856" ref-type="bibr">157</xref>).</p>
<p>However, the clinical translation of these drugs still faces considerable challenges. Cenicriviroc, by blocking the CCR2/CCR5 signaling pathway, can reduce F4/80-positive macrophages in the portal and necrotic regions, showing some anti-fibrotic effects in a phase II trial (<xref rid="b158-ijmm-58-01-05856" ref-type="bibr">158</xref>). However, its efficacy was not maintained in phase III trials (<xref rid="b158-ijmm-58-01-05856" ref-type="bibr">158</xref>). It could be considered that single pathway blockade cannot overcome the redundancy of chemotactic signals in liver fibrosis and the dual functional roles of macrophages, nor does it directly target HSCs or ECM) deposition, resulting in limited overall anti-fibrotic efficacy (<xref rid="b159-ijmm-58-01-05856" ref-type="bibr">159</xref>). However, patients exhibit heterogeneous fibrosis types; early, inflammation-dominant fibrosis responds better to intervention, whereas ECM deposition driven by sustained HSC activation is difficult to reverse. Similarly, the failure of Belapectin is largely attributable to insufficient patient stratification. Galectin-3 primarily regulates HSC differentiation and serves a key role in ECM deposition (<xref rid="b160-ijmm-58-01-05856" ref-type="bibr">160</xref>). As its inhibitor, Belapectin can theoretically attenuate fibrosis, but without accounting for the pathological heterogeneity of patients, the overall efficacy was inadequate (<xref rid="b161-ijmm-58-01-05856" ref-type="bibr">161</xref>). This indicates that whether targeting immune cells or non-parenchymal cells such as HSCs, clinical success depends critically on precise patient stratification and careful consideration of the spatial and mechanistic heterogeneity of fibrosis.</p>
<p>Not only does the type of disease progression affect treatment outcomes, but an increasing number of studies indicate that factors such as sex, age and the gut microbiome can reshape liver zonation through specific signaling pathways, thereby influencing disease development and therapeutic responses. As aforementioned, sex-dependent hormones, particularly GH can dynamically regulate liver zonation (<xref rid="b162-ijmm-58-01-05856" ref-type="bibr">162</xref>). In MASLD, male GH pulses drive STAT5 activation, exacerbating lipid metabolic disorders and inflammation, making the centrilobular zone more prone to fat accumulation and fibrosis. By contrast, estrogen promotes FAO and inhibits HSC activation, providing protection in this region, although this effect is markedly reduced after menopause (<xref rid="b163-ijmm-58-01-05856" ref-type="bibr">163</xref>). Age is also an key confounding factor, as zonal characteristics become less distinct in the aging liver, reducing the spatial precision of drug targeting (<xref rid="b164-ijmm-58-01-05856" ref-type="bibr">164</xref>). Furthermore, disruption of the gut barrier allows microbes and their metabolites, such as bile acids, to enter the portal circulation and form spatial gradients along the hepatic lobule blood flow. Bile acids regulate metabolism and inflammation through FXR and TGR5 receptors, which are differentially expressed across liver zones, thereby driving region-specific fibrotic progression (<xref rid="b165-ijmm-58-01-05856" ref-type="bibr">165</xref>). Thus, the gut microbiome modulates pathological states in different liver regions via the 'bile acid-zonation signaling axis', influencing the efficacy of zonation-targeted therapies. Taken together, future research should focus on combination therapies, precise patient stratification and spatially targeted delivery strategies based on liver zonation biology.</p></sec>
<sec sec-type="other">
<label>10.</label>
<title>Challenges and future perspectives</title>
<p>Current studies have predominately focused on engineered exosomes (<xref rid="b145-ijmm-58-01-05856" ref-type="bibr">145</xref>), lipid nanoparticles conjugated with targeting peptides (<xref rid="b166-ijmm-58-01-05856" ref-type="bibr">166</xref>) and GalNAC-based small interfering RNA systems for hepatocyte-specific delivery (<xref rid="b167-ijmm-58-01-05856" ref-type="bibr">167</xref>). With the progressive understanding of hepatic spatial organization, the paradigm of precision liver therapy is shifting from 'cell-targeted' approaches toward 'spatially targeted' strategies. However, the central challenge lies in achieving precise spatiotemporal control of zonal signaling, which requires not only targeting specific zonally distributed cells but also enabling region-restricted and dynamically adjustable modulation. Furthermore, under conditions such as injury, inflammation or metabolic stress, spatial domains can shift, leading to a mismatch between predefined target regions and the actual pathological zones. As a result, simple exogenous activation or inhibition of a single pathway is often counterbalanced by intrinsic compensatory mechanisms and might trigger region-specific signal reprogramming. This can ultimately attenuate therapeutic efficacy or lead to spatial mismatch of treatment effects.</p>
<p>With the rapid advancement of biotechnology, the accumulation of high-throughput omics data is driving the deep integration of bioinformatics and artificial intelligence (AI) in liver disease research, providing new avenues for early diagnosis, risk stratification and prognostic prediction (<xref rid="b168-ijmm-58-01-05856" ref-type="bibr">168</xref>,<xref rid="b169-ijmm-58-01-05856" ref-type="bibr">169</xref>). Traditional machine learning and deep learning approaches can extract latent patterns from complex multidimensional data and significantly outperform conventional clinical parameters, highlighting the potential of multi-source data integration as a key tool for precision hepatology. However, current AI models largely remain at the level of prediction and lack the ability to resolve spatial heterogeneity and underlying mechanisms of disease (<xref rid="b170-ijmm-58-01-05856" ref-type="bibr">170</xref>).</p>
<p>Future efforts should shift from purely data-driven prediction toward a new paradigm that integrates mechanistic insights with spatial information. Incorporating spatial transcriptomics and single-cell sequencing into AI models would enable the modeling of zonation-specific signals within the hepatic lobule, thereby revealing region-specific contributions to disease initiation and progression. Overall, the convergence of AI and spatial hepatology is poised to reshape liver disease research and clinical management, providing a new theoretical and technological foundation for precision therapy.</p></sec>
<sec sec-type="discussion">
<label>11.</label>
<title>Discussion</title>
<p>Liver zonation is not merely a manifestation of metabolic compartmentalization but represents a dynamic regulatory framework that integrates physiological function with disease pathogenesis. Along the porto-central axis, a continuous metabolic gradient is established through coordinated signaling interactions between zonation-specific hepatocyte subpopulations and non-parenchymal cells, thereby shaping region-specific metabolic programs and functional specialization. This highly ordered spatial organization supports efficient hepatic metabolism under homeostatic conditions, while simultaneously conferring region-specific vulnerability under pathological states. Spatial multi-omics studies further demonstrate that different hepatic zones exhibit distinct responses to injury, indicating that liver disease fundamentally arises from disruption of zonal architecture and imbalance of spatial signaling networks.</p>
<p>Building on this concept, the integration of spatial biology and regenerative medicine is driving a paradigm shift in therapeutic strategies from 'cell-targeted' to 'zonation-targeted' approaches. Emerging evidence shows that adeno-associated virus-mediated expression of R-spondin3 can restore Wnt/&#x003B2;-catenin signaling gradients, thereby re-establishing pericentral metabolic identity and ameliorating fibrosis in preclinical models. However, clinical translation of such strategies remains challenged by the difficulty of achieving precise spatial control of zonal signaling and by substantial inter-individual variability. Recently developed organoid and bioengineered systems incorporate physiologically relevant oxygen and nutrient gradients, enabling reconstruction of liver lobule-like spatial architecture <italic>in vitro</italic> and providing powerful platforms for dissecting zonal regulatory mechanisms and screening compartment-specific interventions. In the future, the integration of spatial omics, AI, controllable delivery systems and personalized models are expected to bridge mechanistic insights with therapeutic development, thereby advancing zonation-based precision interventions toward clinical application.</p></sec></body>
<back>
<sec sec-type="data-availability">
<title>Availability of data and materials</title>
<p>Not applicable.</p></sec>
<sec sec-type="other">
<title>Authors' contributions</title>
<p>DY conceived the idea and supervised the project. DY and GC wrote the manuscript. HJ, YL, CG and HZ helped with figure preparation. DY, GC and KZ revised the manuscript. HJ and YL participated in editing the manuscript. CG, HZ and YC contributed to revision of the manuscript. KZ, YC and DY finalized the manuscript and made the conceptual evaluation of the manuscript. Data authentication is not applicable. All authors read and approved the final version of the manuscript.</p></sec>
<sec sec-type="other">
<title>Ethics approval and consent to participate</title>
<p>Not applicable.</p></sec>
<sec sec-type="other">
<title>Patient consent for publication</title>
<p>Not applicable.</p></sec>
<sec sec-type="COI-statement">
<title>Competing interests</title>
<p>The authors declare that they have no competing interests.</p></sec>
<glossary>
<title>Abbreviations</title>
<def-list>
<def-item>
<term>HIF</term>
<def>
<p>hypoxia-inducible factor</p></def></def-item>
<def-item>
<term>GH</term>
<def>
<p>growth hormone</p></def></def-item>
<def-item>
<term>mTOR</term>
<def>
<p>mechanistic target of rapamycin</p></def></def-item>
<def-item>
<term>ECM</term>
<def>
<p>extracellular matrix</p></def></def-item>
<def-item>
<term>MASLD</term>
<def>
<p>metabolic dysfunction-associated steatotic liver disease</p></def></def-item>
<def-item>
<term>MASH</term>
<def>
<p>metabolic dysfunction-associated steatohepatitis</p></def></def-item>
<def-item>
<term>YAP</term>
<def>
<p>Yes-associated protein</p></def></def-item>
<def-item>
<term>APAP</term>
<def>
<p>acetaminophen</p></def></def-item>
<def-item>
<term>NAPQI</term>
<def>
<p>N-acetyl-p-benzoquinone imine</p></def></def-item>
<def-item>
<term>HybHPs</term>
<def>
<p>hybrid hepatocytes</p></def></def-item>
<def-item>
<term>PHx</term>
<def>
<p>partial hepatectomy</p></def></def-item>
<def-item>
<term>FAO</term>
<def>
<p>fatty acid oxidation</p></def></def-item></def-list></glossary>
<ack>
<title>Acknowledgements</title>
<p>Not applicable.</p></ack>
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<floats-group>
<fig id="f1-ijmm-58-01-05856" position="float">
<label>Figure 1</label>
<caption>
<p>Spatial metabolic zonation of the liver. (A) The structural organization of liver lobules. Functionally distinct zones are defined by their position relative to the portal triad and central vein: the periportal zone (zone 1), intermediate zone (zone 2) and pericentral zone (zone 3). (B) Metabolic specialization along the portal-central axis. Zone 3 hepatocytes operate under hypoxic conditions that stabilize HIFs, promoting glycolytic metabolism. Paracrine signaling from pericentral endothelial cells and hepatic stellate cells via Wnt ligands such as Wnt2, Wnt9b and Rspo3 activates the canonical Wnt/&#x003B2;-catenin pathway through LRP5/6 and LGR4/5 receptors. By contrast, zone 1 hepatocytes exposed to oxygen-rich blood and glucagon signaling maintain &#x003B2;-catenin degradation through APC-mediated proteasomal targeting, while Hh ligand signaling further suppresses Wnt activity to preserve periportal identity. CV, central vein; HA, hepatic artery; PV, portal vein; BD, bile duct; HIFs, hypoxia-inducible factors; Rspo3, R-spondin 3; APC, adenomatous polyposis coli; LRP5/6, low-density lipoprotein receptor-related protein 5/6; LGR4/5, leucine-rich repeat-containing G-protein coupled receptor 4/5; TCF/LEF, T cell factor/lymphoid enhancer-binding factor; GSK-3&#x003B2;, glycogen synthase kinase 3 b; Axin, axis inhibition protein 1; FA, fatty acid; FAO, FA oxidation; Hh, Hedgehog; HSCs, hepatic stellate cells.</p></caption>
<graphic xlink:href="ijmm-58-01-05856-g00.tif"/></fig>
<fig id="f2-ijmm-58-01-05856" position="float">
<label>Figure 2</label>
<caption>
<p>Liver zonation in liver injury. (A) Metabolic injury: In MASLD, centrilobular (zone 3) hepatocytes demonstrate enhanced <italic>de novo</italic> lipogenesis. Lipotoxicity drives pericentral hepatocyte apoptosis via JNK1 activation, initiating centrilobular fibrosis. Chronic injury activates HSCs and Kupffer cells, generating pro-inflammatory (such as TNF-&#x003B1; and IL-6) and pro-fibrotic (such as TGF-&#x003B2;) mediators that drive porto-central bridging fibrosis. (B) Neoplastic transformation: HCC subtypes show distinct zonation patterns: zonation-independent (stem-like phenotype), centrilobular-pattern (&#x003B2;-catenin/Wnt-activated) and periportal-pattern (Hedgehog-activated). Zonation collapse correlates with constitutive YAP/TAZ activation and metabolic reprogramming. (C) Toxic injury: Zone 3-selective cytochrome P450 such as Cyp2e1 bioactivates xenobiotics, for example, APAP into reactive NAPQI, depleting glutathione reserves and inducing mPTP opening, culminating in centrilobular coagulative necrosis. (D) Cholestatic injury: Bile acid overload disrupts zone 1 hepatocyte bile acid transporters, inducing ER stress and ROS production. Chronic cholestasis activates ductular progenitor cells through FXR/TGR5 signaling, driving periportal fibrosis via HSC-derived collagen deposition. MASLD, metabolic dysfunction-associated steatotic liver disease; NAPQI, N-acetyl-p-benzoquinone imine; GSH, glutathione; ER, endoplasmic reticulum; BA, bile acid; HSC, hepatic stellate cells; HCC, hepatocellular carcinoma; ROS, reactive oxygen species; mPTP, mitochondrial permeability transition pore; FXR, farnesoid X receptor; ECM, extracellular matrix; APAP, acetaminophen; YAP, Yes-associated protein; Cyp2e1, cytochrome P450 2E1; PP Hep, periportal hepatocytes; PC Hep, pericentral hepatocytes; BD, bile duct.</p></caption>
<graphic xlink:href="ijmm-58-01-05856-g01.tif"/></fig>
<fig id="f3-ijmm-58-01-05856" position="float">
<label>Figure 3</label>
<caption>
<p>Precision therapeutic strategies for liver regeneration. (A) Targeting regenerative hepatocyte subpopulations: Igfbp2<sup>+</sup>/Hamp2<sup>+</sup> hepatocytes demonstrate enhanced proliferative capacity during injury, while migratory ANXA2<sup>+</sup> hepatocytes restore lobular zonation through wound closure mediated architectural reorganization. (B) Metabolic modulation via PPAR&#x003B1; agonist-driven fatty acid oxidation clears cytotoxic lipid droplets, concurrent with LSEC cycle activation to fuel ATP-dependent regeneration. (C) Niche engineering targets LSEC-derived Wnt ligands, immune modulation or ECM remodeling, to establish a pro-regenerative microenvironment. (D) Cellular reprogramming through Wnt/&#x003B2;-catenin, YAP/TAZ, IL-6/STAT3 and TGF-&#x003B2; signaling mediated expansion of SOX9+ progenitor-like hepatocytes, followed by Wnt-guided redifferentiation into functional HNF4&#x003B1;+ hepatocytes, enables structural and metabolic restitution. Igfbp2, Insulin-like growth factor-binding protein 2; Hamp2, hepcidin antimicrobial peptide 2; ANXA2, annexin A2; ECM, extracellular matrix; PPAR, peroxisome proliferator-activated receptors; LSEC, liver sinusoidal endothelial cells; FXR, farnesoid X receptor; DNMT, DNA methyltransferases; Hep, hepatocytes; TCA, tricarboxylic acid cycle; LPC, liver progenitor cell.</p></caption>
<graphic xlink:href="ijmm-58-01-05856-g02.tif"/></fig>
<table-wrap id="tI-ijmm-58-01-05856" position="float">
<label>Table I</label>
<caption>
<p>Metabolic zonation in the liver.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th colspan="4" valign="top" align="left">A, Periportal (zone 1)
<hr/></th></tr>
<tr>
<th valign="bottom" align="left">Metabolic function</th>
<th valign="bottom" align="left">Metabolic markers</th>
<th valign="bottom" align="center">Key signaling pathways</th>
<th valign="bottom" align="center">(Refs.)</th></tr></thead>
<tbody>
<tr>
<td valign="top" align="left">Fatty acid oxidation</td>
<td valign="top" align="left">CPT1</td>
<td rowspan="4" valign="top" align="left">Low Wnt/&#x003B2;-catenin; high glucagon signaling; high mTORC1 (fed state); low HIF</td>
<td rowspan="4" valign="top" align="center">(<xref rid="b1-ijmm-58-01-05856" ref-type="bibr">1</xref>,<xref rid="b2-ijmm-58-01-05856" ref-type="bibr">2</xref>,<xref rid="b17-ijmm-58-01-05856" ref-type="bibr">17</xref>,<xref rid="b33-ijmm-58-01-05856" ref-type="bibr">33</xref>)</td></tr>
<tr>
<td valign="top" align="left">Urea cycle</td>
<td valign="top" align="left">ASS1, Asl, Arg1</td></tr>
<tr>
<td valign="top" align="left">Gluconeogenesis</td>
<td valign="top" align="left">PCK1, Sds</td></tr>
<tr>
<td valign="top" align="left">Glutamine synthesis</td>
<td valign="top" align="left">Gls2</td></tr>
<tr>
<td colspan="4" valign="top" align="left">
<hr/></td></tr>
<tr>
<td colspan="4" valign="top" align="left">B, Midlobular (zone 2)</td></tr>
<tr>
<td colspan="4" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Metabolic function</td>
<td valign="top" align="left">Metabolic markers</td>
<td valign="top" align="center">Key signaling pathways</td>
<td valign="top" align="center">(Refs.)</td></tr>
<tr>
<td colspan="4" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Iron metabolism</td>
<td valign="top" align="left">Hamp2</td>
<td rowspan="2" valign="top" align="left">Intermediate Wnt signaling</td>
<td rowspan="2" valign="top" align="center">(<xref rid="b88-ijmm-58-01-05856" ref-type="bibr">88</xref>,<xref rid="b89-ijmm-58-01-05856" ref-type="bibr">89</xref>)</td></tr>
<tr>
<td valign="top" align="left">Growth regulation</td>
<td valign="top" align="left">Igfbp2</td></tr>
<tr>
<td colspan="4" valign="top" align="left">
<hr/></td></tr>
<tr>
<td colspan="4" valign="top" align="left">C, Pericentral (zone 3)</td></tr>
<tr>
<td colspan="4" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Metabolic function</td>
<td valign="top" align="left">Metabolic markers</td>
<td valign="top" align="center">Key signaling pathways</td>
<td valign="top" align="center">(Refs.)</td></tr>
<tr>
<td colspan="4" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Lipogenesis</td>
<td valign="top" align="left">ACC, ACL</td>
<td rowspan="5" valign="top" align="left">High Wnt/&#x003B2;-catenin; low mTORC1 (fasting); high HIF-1&#x003B1;</td>
<td rowspan="5" valign="top" align="center">(<xref rid="b17-ijmm-58-01-05856" ref-type="bibr">17</xref>,<xref rid="b33-ijmm-58-01-05856" ref-type="bibr">33</xref>,<xref rid="b171-ijmm-58-01-05856" ref-type="bibr">171</xref>)</td></tr>
<tr>
<td valign="top" align="left">Glycolysis</td>
<td valign="top" align="left">LDH, HK2</td></tr>
<tr>
<td valign="top" align="left">Glutamine synthesis</td>
<td valign="top" align="left">GS</td></tr>
<tr>
<td valign="top" align="left">Xenobiotic metabolism</td>
<td valign="top" align="left">Cyp2e1, Cyp1a2</td></tr>
<tr>
<td valign="top" align="left">Bile synthesis</td>
<td valign="top" align="left">Cyp7a1, HSD3B7</td></tr></tbody></table>
<table-wrap-foot>
<fn id="tfn1-ijmm-58-01-05856">
<p>CPT1, Carnitine palmitoyltransferase 1; ASS1, argininosuccinate synthase 1; Asl, argininosuccinate lyase; Arg1, arginase 1; PCK1, phosphoenolpyruvate carboxykinase 1; Sds, serine dehydratase; Gls2, glutaminase 2; Hamp2, hepcidin antimicrobial peptide 2; ACC, acetyl-CoA carboxylase; ACL, ATP citrate lyase; LDH, lactate dehydrogenase; HIF, hypoxia-inducible factors; HK2, hexokinase 2; GS, glutamine synthetase; Cyp2e1, cytochrome P450 family 2 subfamily E member 1; Cyp1a2, cytochrome P450 family 1 subfamily A member 2;Cyp7A1, Cytochrome P450 family 7 subfamily A member 1; HSD3B7, hydroxysteroid 17-&#x003B2; dehydrogenase 7.</p></fn></table-wrap-foot></table-wrap>
<table-wrap id="tII-ijmm-58-01-05856" position="float">
<label>Table II</label>
<caption>
<p>Completed and ongoing clinical trials targeting zonal hepatic pathology.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th colspan="8" valign="top" align="left">A, Metabolic regulation
<hr/></th></tr>
<tr>
<th valign="bottom" align="left">Target/mechanism</th>
<th valign="bottom" align="center">Drug</th>
<th valign="bottom" align="center">Phase</th>
<th valign="bottom" align="center">Indication</th>
<th valign="bottom" align="center">Outcome</th>
<th valign="bottom" align="center">Trial no.</th>
<th valign="bottom" align="center">Unmet clinical needs</th>
<th valign="bottom" align="center">(Refs.)</th></tr></thead>
<tbody>
<tr>
<td valign="top" align="left">FXR agonist</td>
<td valign="top" align="left">Obeticholic acid</td>
<td valign="top" align="center">III</td>
<td valign="top" align="left">NASH</td>
<td valign="top" align="left">Improved histology with acceptable safety</td>
<td valign="top" align="center">NCT02548351</td>
<td valign="top" align="left">Pruritus and lipid imbalance limit clinical; utility systemic activation lacks zonal specificity</td>
<td valign="top" align="center">(<xref rid="b172-ijmm-58-01-05856" ref-type="bibr">172</xref>)</td></tr>
<tr>
<td valign="top" align="left">FGF19 receptor agonist</td>
<td valign="top" align="left">Aldafermin</td>
<td valign="top" align="center">II</td>
<td valign="top" align="left">NASH/PSC</td>
<td valign="top" align="left">Reduced liver fat; trend toward fibrosis improvement</td>
<td valign="top" align="center">NCT02443116</td>
<td valign="top" align="left">Anti-fibrotic effect modest; requires long-term validation</td>
<td valign="top" align="center">(<xref rid="b156-ijmm-58-01-05856" ref-type="bibr">156</xref>)</td></tr>
<tr>
<td valign="top" align="left">IBAT inhibitor</td>
<td valign="top" align="left">Elobixibat</td>
<td valign="top" align="center">II</td>
<td valign="top" align="left">NAFLD/NASH</td>
<td valign="top" align="left">No results posted</td>
<td valign="top" align="center">NCT04006145</td>
<td valign="top" align="left">Bile acid modulation alone insufficient for fibrosis reversal</td>
<td valign="top" align="center">(<xref rid="b173-ijmm-58-01-05856" ref-type="bibr">173</xref>)</td></tr>
<tr>
<td valign="top" align="left">Thyroid hormone receptor-&#x003B2; agonist</td>
<td valign="top" align="left">Resmetirom</td>
<td valign="top" align="center">III</td>
<td valign="top" align="left">NASH</td>
<td valign="top" align="left">No results posted</td>
<td valign="top" align="center">NCT03900429</td>
<td valign="top" align="left">Metabolic improvement may not directly translate to fibrosis benefit</td>
<td valign="top" align="center">(<xref rid="b174-ijmm-58-01-05856" ref-type="bibr">174</xref>)</td></tr>
<tr>
<td valign="top" align="left">PPAR&#x003B1; modulator</td>
<td valign="top" align="left">Pemafibrate</td>
<td valign="top" align="center">II</td>
<td valign="top" align="left">NAFLD/NASH</td>
<td valign="top" align="left">Reduced liver stiffness (via magnetic resonance elastography)</td>
<td valign="top" align="center">NCT03350165</td>
<td valign="top" align="left">Imaging improvement needs histological confirmation</td>
<td valign="top" align="center">(<xref rid="b175-ijmm-58-01-05856" ref-type="bibr">175</xref>)</td></tr>
<tr>
<td valign="top" align="left">Pan-PPAR agonist</td>
<td valign="top" align="left">Lanifibranor</td>
<td valign="top" align="center">IIb</td>
<td valign="top" align="left">NASH</td>
<td valign="top" align="left">Improved fibrosis</td>
<td valign="top" align="center">NCT03008070</td>
<td valign="top" align="left">Multi-target approach more effective than single pathway</td>
<td valign="top" align="center">(<xref rid="b176-ijmm-58-01-05856" ref-type="bibr">176</xref>)</td></tr>
<tr>
<td valign="top" align="left">Pan-PPAR agonist</td>
<td valign="top" align="left">Chiglitazar</td>
<td valign="top" align="center">II</td>
<td valign="top" align="left">NASH</td>
<td valign="top" align="left">No results posted</td>
<td valign="top" align="center">NCT05193916</td>
<td valign="top" align="left">Patient heterogeneity may mask efficacy</td>
<td valign="top" align="center">(<xref rid="b177-ijmm-58-01-05856" ref-type="bibr">177</xref>)</td></tr>
<tr>
<td colspan="8" valign="top" align="left">
<hr/></td></tr>
<tr>
<td colspan="8" valign="top" align="left">B, Inflammation/immune modulation</td></tr>
<tr>
<td colspan="8" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Target/mechanism</td>
<td valign="top" align="center">Drug</td>
<td valign="top" align="center">Phase</td>
<td valign="top" align="center">Indication</td>
<td valign="top" align="center">Outcome</td>
<td valign="top" align="center">Trial no.</td>
<td valign="top" align="center">Unmet clinical needs</td>
<td valign="top" align="center">(Refs.)</td></tr>
<tr>
<td colspan="8" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">CCR2/5 inhibitor</td>
<td valign="top" align="left">Cenicriviroc</td>
<td valign="top" align="center">IIb</td>
<td valign="top" align="left">NASH</td>
<td valign="top" align="left">Improved results in advanced fibrosis</td>
<td valign="top" align="center">NCT03028740</td>
<td valign="top" align="left">Redundant inflammatory pathways limit efficacy</td>
<td valign="top" align="center">(<xref rid="b158-ijmm-58-01-05856" ref-type="bibr">158</xref>)</td></tr>
<tr>
<td valign="top" align="left">TLR4 antagonist</td>
<td valign="top" align="left">JKB-121</td>
<td valign="top" align="center">II</td>
<td valign="top" align="left">NASH</td>
<td valign="top" align="left">No results posted</td>
<td valign="top" align="center">NCT02442687</td>
<td valign="top" align="left">Single immune axis blockade insufficient</td>
<td valign="top" align="center">(<xref rid="b178-ijmm-58-01-05856" ref-type="bibr">178</xref>)</td></tr>
<tr>
<td valign="top" align="left">TLR7 agonist</td>
<td valign="top" align="left">RO7119929</td>
<td valign="top" align="center">I</td>
<td valign="top" align="left">HCC</td>
<td valign="top" align="left">No results posted</td>
<td valign="top" align="center">NCT04338685</td>
<td valign="top" align="left">Immune activation may be context-dependent</td>
<td valign="top" align="center">(<xref rid="b179-ijmm-58-01-05856" ref-type="bibr">179</xref>)</td></tr>
<tr>
<td colspan="8" valign="top" align="left">
<hr/></td></tr>
<tr>
<td colspan="8" valign="top" align="left">C, Fibrosis/ECM targeting</td></tr>
<tr>
<td colspan="8" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Target/mechanism</td>
<td valign="top" align="center">Drug</td>
<td valign="top" align="center">Phase</td>
<td valign="top" align="center">Indication</td>
<td valign="top" align="center">Outcome</td>
<td valign="top" align="center">Trial no.</td>
<td valign="top" align="center">Unmet clinical needs</td>
<td valign="top" align="center">(Refs.)</td></tr>
<tr>
<td colspan="8" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Galectin-3 inhibitor</td>
<td valign="top" align="left">Belapectin</td>
<td valign="top" align="center">IIb/III</td>
<td valign="top" align="left">NASH</td>
<td valign="top" align="left">No results posted</td>
<td valign="top" align="center">NCT04365868</td>
<td valign="top" align="left">ECM remodeling too advanced to reverse in late-stage patients</td>
<td valign="top" align="center">(<xref rid="b161-ijmm-58-01-05856" ref-type="bibr">161</xref>)</td></tr>
<tr>
<td colspan="8" valign="top" align="left">
<hr/></td></tr>
<tr>
<td colspan="8" valign="top" align="left">D, Wnt/regeneration signalling</td></tr>
<tr>
<td colspan="8" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Target/mechanism</td>
<td valign="top" align="center">Drug</td>
<td valign="top" align="center">Phase</td>
<td valign="top" align="center">Indication</td>
<td valign="top" align="center">Outcome</td>
<td valign="top" align="center">Trial no.</td>
<td valign="top" align="center">Unmet clinical needs</td>
<td valign="top" align="center">(Refs.)</td></tr>
<tr>
<td colspan="8" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">CBP/&#x003B2;-catenin inhibitor</td>
<td valign="top" align="left">PRI-724</td>
<td valign="top" align="center">I</td>
<td valign="top" align="left">HCV cirrhosis</td>
<td valign="top" align="left">Improved histology and CP score</td>
<td valign="top" align="center">NCT02195440</td>
<td valign="top" align="left">Safety acceptable, but long-term oncogenic risk needs monitoring</td>
<td valign="top" align="center">(<xref rid="b157-ijmm-58-01-05856" ref-type="bibr">157</xref>)</td></tr></tbody></table>
<table-wrap-foot>
<fn id="tfn2-ijmm-58-01-05856">
<p>FGF19, fibroblast growth factor 19; IBAT, ileal bile acid transporter; TLR4, Toll-like receptor 4; CCR2/5, C-C chemokine receptor 2/5; FXR, farnesoid X receptor; ECM, extracellular matrix; PPAR, peroxisome proliferator-activated receptor; CBP, CREB-binding protein; TLR7, Toll-like receptor 7; NASH, non-alcoholic steatohepatitis; PSC, primary sclerosing cholangitis; NAFLD, non-alcoholic fatty liver disease; HCC, hepatocellular carcinoma; HCV, hepatitis C virus.</p></fn></table-wrap-foot></table-wrap></floats-group></article>
