Targeting Aurora kinase B regulates cholesterol metabolism and enhances chemoimmunotherapy in cholangiocarcinoma

Furong Liu; Wei Chen; Ze Zhang; Weifeng Zeng; Haofan Hu; Shangwu Ning; Zhibin Liao; Yachong Liu; Hongwei Zhang; Qinggang Fu; Bixiang Zhang; Xiaoping Chen; Wanguang Zhang; Zhanguo Zhang

doi:10.1136/gutjnl-2025-335291

. 2025 Jul 31;75(2):e335291. doi: 10.1136/gutjnl-2025-335291

Targeting Aurora kinase B regulates cholesterol metabolism and enhances chemoimmunotherapy in cholangiocarcinoma

Furong Liu ^1,^2,^3,⁰, Wei Chen ^1,^2,^3,⁰, Ze Zhang ^1,^2,^3,⁰, Weifeng Zeng ^1,^2,^3,⁰, Haofan Hu ^1,^2,³, Shangwu Ning ^1,^2,³, Zhibin Liao ^1,^2,³, Yachong Liu ^1,^2,³, Hongwei Zhang ^1,^2,³, Qinggang Fu ^1,^2,³, Bixiang Zhang ^1,^2,³, Xiaoping Chen ^1,^2,^3,^*, Wanguang Zhang ^1,^2,^3,^*, Zhanguo Zhang ^1,^2,^3,^✉

PMCID: PMC12911660 PMID: 40744724

Abstract

Background

Cholangiocarcinoma (CCA) is a highly lethal malignant tumour with increasing incidence. Current therapies exhibit limited benefits, which urgently demand the identification of novel therapeutic targets.

Objective

We aimed to identify potential therapeutic targets for CCA and broaden current therapies.

Design

Potential therapeutic targets for CCA were identified by sgRNA library screening and validated in preclinical models. Multi-omics sequencing and various experimental approaches were performed to validate the mechanism by which Aurora kinase B (AURKB) regulates CCA progression and the immune microenvironment, supported by clinical samples from public data sets and Tongji Hospital cohorts. The translational therapy was comprehensively validated in CCA organoid, patient-derived xenograft and preclinical murine models.

Results

AURKB was identified as a highly expressed and targetable kinase in CCA. Knockout of AURKB significantly inhibited CCA progression, reduced CD8⁺ T cell exhaustion and enhanced antitumour response. Mechanistically, AURKB promoted the generation of histone H3 lysine 9 tri-methylation (H3K9me3)/serine 10 phosphorylation, leading to a decrease in the enrichment of H3K9me3 at the neutral cholesterol ester hydrolase 1 (NCEH1) promoter, thereby increasing NCEH1 expression and cholesterol levels in tumours. High AURKB expression in clinical samples predicted poorer outcomes in patients with CCA undergoing neoadjuvant chemoimmunotherapy and was associated with cholesterol accumulation within tumours. AURKB inhibitor or simvastatin can suppress CCA progression and significantly enhance sensitivity to chemoimmunotherapy.

Conclusions

AURKB regulates cholesterol levels and immune microenvironment in tumours, highlighting that targeting AURKB or adopting cholesterol-reducing strategy holds promise for CCA treatment, especially in conjunction with first-line chemoimmunotherapy.

Keywords: CHOLANGIOCARCINOMA, IMMUNOTHERAPY, MOLECULAR TARGETED THERAPY, LIPID METABOLISM

WHAT IS ALREADY KNOWN ON THIS TOPIC

Despite advances in molecular oncology, cholangiocarcinoma (CCA) remains an intractable hepatobiliary malignancy with dismal prognostic outcomes, which underscore an unmet need for novel therapies.

WHAT THIS STUDY ADDS

Aurora kinase B (AURKB) in tumour cells is identified as essential for the progression of CCA by sgRNA library screening. It disrupts the interaction between H3 lysine 9 tri-methylation and the HP1 complex, thereby promoting neutral cholesterol ester hydrolase 1 (NCEH1) transcription.
This metabolic shift drives intratumoral cholesterol accumulation and impairs the function of T cells.
In preclinical models, targeting AURKB or taking statins improves response to chemotherapy and immunotherapy in CCA.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

Our study highlights AURKB as a potential therapeutic target for CCA, which exerts NCEH1-driven cholesterol immunosuppression.
Targeting AURKB improves the efficacy of current chemoimmunotherapy.

Introduction

Cholangiocarcinoma (CCA) is the second most common primary liver malignancy, with the 5‐year survival being merely 5%–15%.¹ Over the past few decades, its incidence and mortality have been continuously rising worldwide. In the next 20–30 years, the incidence of CCA is expected to increase 10-fold.² Gemcitabine-based therapy is currently widely used as the first-line treatment strategy for patients with advanced CCA.³ However, gemcitabine-based combination chemotherapy or immunotherapy in patients with CCA is limited.^{4 5} As a result, there is a notable shortage of targeted therapy options for patients with CCA. In-depth insights on effective targeted strategies or enhancing the efficacy of chemotherapy and immunotherapy could be greatly beneficial for these patients.

Cholesterol is a vital lipid component of mammalian cell membranes, maintaining membrane integrity and fluidity while forming microstructures. During the progression of cancer, activation of oncogenic pathways or inactivation of tumour suppressor pathways can lead to abnormal cholesterol metabolism in tumour cells, including increased synthesis and uptake to meet heightened energy and biosynthetic demands.^{6 7} Cholesterol esters, as a reservoir of free cholesterol, can be hydrolysed by carboxylesterase, lysosomal acid lipase and neutral cholesterol ester hydrolase 1 (NCEH1) into free cholesterol and fatty acids.^{8 9} In patients with CCA, cholesterol levels in serum and tissues are significantly elevated, promoting tumour progression.^{10 11} Nonetheless, it remains unclear whether targeting cholesterol metabolism could serve as a potential therapeutic strategy for CCA and enhance the efficacy of first-line chemotherapy and immunotherapy.

In this study, we identified Aurora kinase B (AURKB), a serine/threonine protein kinase known for its critical role in mitosis,¹² as a potential target in CCA. AURKB regulates cholesterol ester hydrolysis, elevates tumour cholesterol levels and inhibits T cell function. Targeting AURKB or reducing tumour cholesterol could offer a strategy to treat CCA and enhance antitumour immunity, potentially improving the effectiveness of chemotherapy and immunotherapy. We undertook a discovery effort to identify key targetable kinases and mechanisms in CCA, and provided a potential therapeutic strategy by which blocking AURKB or lowering tumour cholesterol would suppress CCA progression and improve patient survival.

Materials and methods

See supplementary methods for details.

Results

AURKB is a specific dependency in CCA and its high expression in CCA indicates a poor prognosis

Given the limitations of targeted therapies in CCA, we investigated genetic vulnerabilities using CRISPR/Cas9 knockout screening with a kinase library in 23 CCA cell lines from DepMap. Six potential kinase targets (WEE1, PLK1, CHECK1, CDK1, CDC7, AURKB) were identified based on CERES dependency scores (figure 1A). To assess therapeutic specificity, we compared kinase expression in tumours vs normal tissues, finding WEE1 similarly expressed, while others (especially AURKB, PLK1, CDK1) were significantly elevated in tumours (figure 1B). Further prognostic analysis across three CCA cohorts revealed that only high AURKB expression correlated with poorer outcomes (figure 1C, online supplemental figure S1A–D), suggesting its essential role in CCA. Subsequently, we also validated the high expression of AURKB in other CCA data sets (figure 1D). In vivo, CCA cells with a kinase-targeting sgRNA library were injected into NCG mice (figure 1E). After 28 days, deep sequencing showed reduced sgRNAs targeting AURKB in both cell lines (figure 1F), while controls remained stable (online supplemental figure S1E). PLK1 sgRNAs decreased only in QBC939 (online supplemental figure S1F). In the Tongji CCA cohort, AURKB was highly expressed in tumours but nearly absent in adjacent normal tissues (figure 1G,H). Similarly, in another cohort, high AURKB expression in tumours correlated with shorter overall survival (figure 1I,J). Mouse models (KRAS^G12D/sgp19, YAP^S127A/myr-AKT, YAP^S127A/NICD) simulating clinical CCA features^{13 14} consistently showed AURKB expression only in tumour tissues (figure 1K).

To understand the high expression of AURKB in tumours, we analysed genetic and epigenetic alterations. While AURKB’s chromosomal region showed no amplification (online supplemental figure S1G), its promoter was hypomethylated in tumours, inversely correlating with expression (online supplemental figure S1H,I), consistent with gene expression omnibus (GEO) data sets (online supplemental figure S1H-K). Bisulfite sequencing PCR confirmed AURKB promoter hypomethylation in CCA samples (figure 1L, online supplemental figure S1L,M), with protein levels inversely related to methylation (figure 1L). To investigate the direct relationship between AURKB expression and its promoter methylation, CCA cells were treated with decitabine, a DNA methyltransferase inhibitor. This treatment dose-dependently increased AURKB mRNA and protein levels (figure 1M,N, online supplemental figure S1N,O). To confirm this finding, siRNA was performed to knock down DNMT1, DNMT3A and DNMT3B, examining the effect of DNA methylation suppression on AURKB expression (online supplemental figure S1P). Similar to decitabine treatment, DNMTs knockdown also elevated AURKB mRNA and protein levels (online supplemental figure S1Q,R), demonstrating that promoter hypomethylation drives AURKB upregulation in CCA.

AURKB plays an indispensable role in the progression of CCA

To investigate AURKB’s role in CCA, we established stable knockdown models in QBC939 and HuCCT1 cells after confirming AURKB’s mRNA and protein expression across CCA cell lines (figure 2A, online supplemental figure S2A–C). The CCK-8 assay revealed that AURKB knockdown significantly restricted CCA cell proliferation, colony formation and DNA replication (figure 2B–D). Subcutaneous inoculation of AURKB-knockdown tumour cells in mice showed suppressed tumour growth (figure 2E, online supplemental figure S2D). However, it should also be noted that the CCA cells with AURKB knockdown tended to regrow after several days, accompanied by partial AURKB recovery (figure 2F). To prevent expression rebound, CRISPR/Cas9-mediated AURKB knockout achieved consistent tumour-suppressive effects (figure 2G, online supplemental figure S2E–G). To evaluate whether the indispensable role of AURKB in CCA depends on its kinase activity, we complemented the AURKB-deficient CCA cells with wild type AURKB (AURKB^WT) and a kinase‐dead mutant AURKB (AURKB^K106R) (online supplemental figure S2H). Kinase activity dependency was confirmed through rescue experiments: AURKB^WT restored growth, while AURKB^K106R failed to reverse growth restriction (online supplemental figure S2H–J). We further developed patient-derived organoid (PDO) models from CCA tissues, observing positive AURKB expression in organoids from AURKB-positive tumours (figure 2H, online supplemental figure S2K). AURKB-targeting sgRNA lentivirus significantly suppressed CCA growth in these PDOs (figure 2I), while no effect was seen in AURKB-negative PDOs (figure 2H–I, online supplemental figure S2K). In immunocompetent mice, hydrodynamic tail vein injection (HTVi)-induced CCA formation revealed that Aurkb knockdown suppressed tumour initiation and progression, knockout nearly abolished tumour formation, and humanised AURKB overexpression promoted tumour growth (figure 2J–R, online supplemental figure S3A–G). These findings underscore AURKB’s critical role in CCA survival and progression.

AURKB promotes CCA progression by enhancing cholesterol production within tumours

To investigate how AURKB regulates CCA progression, we performed RNA-seq analysis on CCA cell lines with AURKB knockdown, revealing enrichment of the cholesterol metabolism pathway in both cell lines (figure 3A, online supplemental figure S4A). Cholesterol, a key component of lipid metabolism, is vital for tumour cell proliferation and survival.⁷ We further performed targeted lipid metabolomics sequencing and found significant changes in the levels of various lipids after AURKB deletion (figure 3B), with sterol lipids notably decreasing (figure 3C). Pathway analysis highlighted cholesterol metabolism as significantly enriched (figure 3D). Further analysis of sterol lipids showed that while cholesterol esters with different chain lengths exhibited group variations, total cholesterol levels were significantly reduced following AURKB depletion (figure 3E, online supplemental figure S4B). Filipin III staining and fluorometric measurements revealed that AURKB knockdown or knockout significantly reduced cholesterol levels in CCA cells and PDOs (figure 3F,G, online supplemental figure S4C), with this effect dependent on AURKB’s kinase activity (figure 3H). This was consistent with the effect of AZD1152, an AURKB kinase inhibitor, which dose-dependently reduced tumour cholesterol (figure 3I, online supplemental figure S4D). In various CCA mouse models, AURKB knockdown decreased and overexpression increased tumour cholesterol levels (figure 3J, online supplemental figure S4E,F), while serum cholesterol remained unchanged (online supplemental figure S4G). Further analysis of clinical CCA samples revealed significantly higher cholesterol levels in tumour tissues compared with adjacent non-tumour tissue (figure 3K), strongly correlating with AURKB expression (figure 3L). However, no apparent link was found between serum cholesterol levels and tumour AURKB expression (online supplemental figure S4H), likely due to minimal AURKB expression in liver cells, which does not impact systemic cholesterol metabolism. We hypothesise AURKB influences tumour progression by regulating tumour cholesterol levels. Supporting this, cholesterol supplementation in CCA PDO culture systems alleviated the growth inhibition caused by AURKB deletion (figure 3M), suggesting AURKB promotes CCA progression by enhancing free cholesterol production within tumours.

AURKB impairs the antitumour immune microenvironment of CCA by increasing free cholesterol in tumours

Given the tumour-suppressive effects of AURKB knockdown in immunocompetent mice and cholesterol’s role in the tumour microenvironment, we investigated AURKB’s impact on the immune microenvironment of CCA. Since complete AURKB loss prevented HTVi-induced CCA formation, we performed single-cell RNA sequencing (scRNA-seq) on CD45⁺ cells from KRAS^G12D/sgp19-induced CCA models, comparing AURKB knockdown (shAurkb) and controls. Among 47 633 CD45⁺ cells, UMAP-based clustering identified 12 immune subtypes (online supplemental figure S5A). The shAurkb group showed reduced macrophages and monocytes but increased granulocytes and T cells (figure 4A, online supplemental figure S5B). Re-clustering 6503 T cells revealed 11 clusters, with CD8⁺ T cells being predominant (online supplemental figure S5C). The shAurkb group had a higher proportion of CD8⁺ T cells (figure 4B, online supplemental figure S5D), validated by flow cytometry in two CCA models (online supplemental figure S5E,F). AURKB overexpression produced opposite results (online supplemental figure S5G,H). Gene set enrichment analysis revealed that CD8⁺ T cells in the shAurkb group enriched immune activation and T cell function pathways (antigen presentation, proliferation, cytotoxicity), whereas controls showed metabolic pathway enrichment (ATP synthesis, glucose/fatty acid metabolism) (figure 4C, online supplemental figure S5I). CD8⁺ T cells were categorised into naïve (T_N), effector memory (T_EM), effector (T_E) and exhausted (T_Ex) subtypes (figure 4D, online supplemental figure S5J). Pseudotime analysis showed T_N cells branching into T_N-T_EM-T_E (effector lineage) and T_N-T_EM-T_EX (exhaustion lineage) trajectories (figure 4D). The shAurkb group exhibited higher cytotoxicity scores in the effector lineage, while the shNC group showed higher exhaustion scores (figure 4E, online supplemental figure S5K).

The flow cytometry from CCA mouse models aligned with scRNA-seq findings, demonstrating that shAurkb group increased proportions of Granzyme B⁺CD8⁺ and interferon gamma (IFNγ)⁺CD8⁺ T cells while reducing PD-1⁺CD8⁺ T cells (figure 4F, online supplemental figure S6A). Effector T cells (CD44⁺CD62L−CD8⁺) also increased (online supplemental figure S6D,E), whereas AURKB overexpression produced inverse effects (online supplemental figure S6B,C, F,G). In human PBMC-derived CD8⁺ T cells co-cultured with CCA cells, AURKB deletion in CCA cells elevated Granzyme B⁺CD8⁺ and IFNγ⁺CD8⁺ T populations while reducing PD-1⁺ and TIM-3⁺ exhausted subsets (online supplemental figure S7A), with overexpression reversing these trends (online supplemental figure S7B), indicating AURKB’s role in driving T cell dysfunction. Considering AURKB’s involvement in tumour cholesterol regulation, we investigated whether its effects on T cell function and exhaustion depend on cholesterol. Pharmacological treatments confirmed cholesterol pathway dependency: Cholesterol supplementation reversed AURKB deletion-induced T cell function enhancement, while methyl-β-cyclodextrin (M-β-CD), a cholesterol-depleting agent, nearly abolished AURKB’s regulatory effect on CD8⁺ T cells (figure 4G, online supplemental figure S7C). Cytotoxicity assays revealed heightened tumour-killing capacity in CD8⁺ T cells co-cultured with AURKB-knockout CCA cells, which was abolished by cholesterol/M-β-CD treatment (figure 4H, online supplemental figure S7D). Additionally, low-density lipoprotein receptor (LDLR) knockdown on T cells eliminated AURKB-mediated immunoregulation in vitro (online supplemental figure S7E,F), confirming cholesterol uptake as essential for AURKB’s immunosuppressive mechanism. These results collectively suggest that tumour AURKB suppresses CD8⁺ T cell function through cholesterol-dependent pathways.

Next, we analysed tumours from the prospective CCA cohort to evaluate AURKB expression, serum/tumour cholesterol levels and CD8⁺ T cell function (online supplemental figure S8A). High-AURKB tumours showed elevated tumour cholesterol (figure 4I,J) but comparable serum cholesterol to low-AURKB tumours (online supplemental figure S8B). High-AURKB tumours also exhibited reduced CD8⁺ T cell infiltration, fewer cytotoxic and more exhausted CD8⁺ T cells (figure 4K, online supplemental figure S8C). To determine whether AURKB’s effects rely on the cholesterol pathway, mice were fed normal diet or high-cholesterol diet (HCD) for 3 weeks, followed by KRAS^G12D/sgp19-induced CCA (figure 4L). HCD elevated serum/tumour cholesterol independently of AURKB (figure 4N). While Aurkb knockdown inhibited tumour growth, HCD reversed this effect (figure 4M,N). HCD also abrogated Aurkb knockdown’s impact on CD8⁺ T cell infiltration, cytotoxicity, exhaustion and effector T cells (figure 4O, online supplemental figure S8D), confirming AURKB’s cholesterol-dependent regulation of CCA progression and T cell function.

AURKB increases cholesterol levels within tumours through NCEH1

We note that AURKB’s regulation of cholesterol depends on its kinase activity, which phosphorylates histone H3 at serine 10 (H3S10ph).¹⁵,¹⁷ We confirmed that AZD1152 inhibits H3S10ph (online supplemental figure S9A). Since histone modifications influence chromatin accessibility and gene expression, we performed Assay for Transposase-Accessible Chromatin sequencing (ATAC-seq) in AURKB-deleted CCA cells, revealing reduced chromatin accessibility (figure 5A, online supplemental figure S9B). By integrating differential peak-associated genes with RNA-seq and cholesterol metabolism-related genes, we identified significant changes in NCEH1 and voltage-dependent anion channel 1 in both CCA cell lines (figure 5B, online supplemental figure S9B), with NCEH1 showing consistent and pronounced alterations in chromatin accessibility and expression (figure 5C, online supplemental figure S9C). This suggests AURKB regulates cholesterol potentially through NCEH1. In AURKB knockdown and knockout cell lines, NCEH1 RNA and protein levels significantly decreased alongside reduced H3S10ph (figure 5D,E, online supplemental figure S9D,E). These changes depend on AURKB’s kinase activity (figure 5D,E), aligning with AZD1152’s dose-dependent suppression of NCEH1 (figure 5F, online supplemental figure S9F). Chromatin immunoprecipitation (ChIP)-quantitative polymerase chain reaction (qPCR) further showed reduced H3S10ph enrichment at the NCEH1 promoter after AURKB knockout or AZD1152 treatment (figure 5G, online supplemental figure S9G), validated by AURKB^WT and AURKB^K106R overexpression (online supplemental figure S9H). Functionally, NCEH1 overexpression rescued cholesterol levels suppressed by AURKB knockout (figure 5H), while NCEH1 knockdown reversed cholesterol increases induced by AURKB overexpression (online supplemental figure S9I). Clinically, NCEH1 was elevated in CCA tissues versus non-tumour tissues and correlated with AURKB expression (figure 5I, online supplemental figure S9J–L).

H3S10ph regulates gene expression through cross-regulation with adjacent histone modifications, particularly opposing the transcriptional repression mediated by H3 lysine 9 tri-methylation (H3K9me3) at lysine K9.^{18 19} Further, we investigated whether AURKB could regulate H3K9me3. Cleavage under targets and tagmentation (CUT&Tag) sequencing revealed increased H3K9me3 peak enrichment in AURKB-deficient CCA cells, suggesting stronger genomic affinity (figure 5J). Specifically, H3K9me3 enrichment rose at the NCEH1 promoter after AURKB knockout (figure 5K), confirmed by ChIP-qPCR following knockout or AZD1152 treatment (figure 5L, online supplemental figure S9M) and validated with AURKB^WT/AURKB^K106R overexpression (online supplemental figure S9N). Notably, while total H3K9me3 levels remained unchanged, the combinatorial modification H3K9me3S10ph; H3 lysine 9 tri-methylation/serine 10 phosphorylation (H3K9me3S10ph) mirrored H3S10ph dynamics (figure 5M, online supplemental figure S10A,B). Both H3K9me3S10ph and H3S10ph showed coordinated enrichment changes at the NCEH1 promoter under various AURKB conditions (figure 5N, online supplemental figure S10C,D). In vivo validation in murine CCA models recapitulated these H3K9me3S10ph and NCEH1 regulation patterns (online supplemental figure S10E,F). Clinically, CCA tumours exhibited co-elevation of AURKB, H3K9me3S10ph and NCEH1, with strong intercorrelations in two patient cohorts (figure 5O,P, online supplemental figure S10G–I). These findings collectively indicate AURKB facilitates NCEH1 expression by suppressing H3K9me3 binding at its promoter.

AURKB reduces the enrichment of H3K9me3 at the NCEH1 promoter by blocking the interaction between the HP1 complex and H3K9me3

The heterochromatin protein 1 (HP1) complex (CBX1/3/5) and H3K9me3 form heterochromatin structures that enhance genomic stability and transcriptional repression.²⁰,²² H3S10ph inhibits this heterochromatin formation.^{23 24} Therefore, we hypothesise that AURKB phosphorylates H3S10, disrupting HP1-H3K9me3 interaction and alleviating H3K9me3-mediated repression in the NCEH1 promoter. In vitro, we confirmed H3K9me3 peptide binding to HP1 complex proteins (figure 6A, online supplemental figure S11A,B). We next examined whether AURKB’s kinase activity influences the HP1 complex-H3K9me3 interaction. In vitro kinase assays showed that recombinant AURKB phosphorylated H3K9me3 peptides in the presence of ATP, generating the combined modification H3K9me3S10ph—an effect blocked by AZD1152 (figure 6B, online supplemental figure S11C). Crucially, pull-down assays revealed that H3K9me3S10ph lost HP1 binding capacity despite unchanged H3K9me3 levels (figure 6B, online supplemental figure S11C). This suggests that HP1 complex binding requires unphosphorylated H3K9me3 rather than the H3K9me3S10ph. Further microscale thermophoresis experiments measured the binding affinity of H3K9me3 or H3K9me3S10ph peptides to purified GFP-CBX1/3/5. Consistent with our findings, H3K9me3S10ph showed negligible interaction with GFP-CBX1/3/5, whereas H3K9me3 bound directly (figure 6C, online supplemental figure S11D). These findings suggest AURKB produces H3K9me3S10ph, blocking HP1-H3K9me3 binding. Thus, we propose that AURKB knockout or AZD1152 treatment suppresses NCEH1 expression by enhancing H3K9me3-mediated transcriptional repression via HP1 complex recruitment. While HP1 complex knockdown did not alter H3S10ph or H3K9me3S10ph levels under AURKB loss/inhibition (figure 6D, online supplemental figure S11E,F), it reversed H3K9me3 enrichment at the NCEH1 promoter (figure 6E, online supplemental figure S11G) and rescued the reduction in NCEH1 mRNA/protein levels (figure 6D and F, online supplemental figure S11F,H). These findings indicate that AURKB phosphorylates H3K9me3 to generate H3K9me3S10ph, disrupting HP1 complex binding and alleviating H3K9me3-driven NCEH1 repression.

Both in vivo and in vitro experiments demonstrated that NCEH1 overexpression reversed AURKB deletion’s antitumour effects, restoring tumour proliferation and cholesterol levels (figure 6G, online supplemental figure S12A-D). Co-culture experiments revealed that while AURKB deletion enhanced T cell function, NCEH1 overexpression reversed these effects and restored CD8⁺ T cell exhaustion (figure 6H). Similar results were observed in murine primary CCA cells (KRAS^G12D/sgp19) co-cultured with CD8⁺ T cells, where Aurkb knockdown’s effects on T cell function were attenuated by Nceh1 knockdown (online supplemental figure S12E). In vivo, AAV8-shNceh1 pretreatment in mice followed by CCA induction showed that Nceh1 knockdown consistently attenuated AURKB-driven tumorigenesis (figure 6I–K, online supplemental figure S12F,G). While Nceh1 knockdown didn't affect AURKB or H3K9me3S10ph expression, it reversed AURKB-induced cholesterol accumulation and reduced tumour Ki-67 levels (figure 6K,L, online supplemental figure S12G,H). Notably, shNceh1 tumours showed increased CD8⁺ T cell infiltration, more Granzyme B⁺CD8⁺ T cells and fewer PD-1⁺CD8⁺ T cells, regardless of AURKB status, indicating NCEH1 knockdown counteracts AURKB’s immunosuppressive effects (figure 6M, online supplemental figure S12I). These findings establish NCEH1 as a key mediator of AURKB’s regulation of tumour cholesterol metabolism and immunosuppressive microenvironment in CCA progression.

Targeting AURKB or reducing tumour cholesterol can enhance the sensitivity to chemoimmunotherapy in CCA treatment

Given AURKB’s enzymatic role in cholesterol regulation and T cell function during CCA progression, we assessed the therapeutic potential of AZD1152, a validated AURKB enzymatic inhibitor in clinical phase II trials.^{25 26} In vitro, AZD1152 demonstrated dose-dependent inhibition of CCA cells, aligning with reduced H3S10ph levels (online supplemental figure S13A). RBE cells required the highest AZD1152 concentration, likely due to low AURKB expression. In addition, high AZD1152 concentrations led to increased cell size, reduced division and fewer colony formations (online supplemental figure S13B). Since gemcitabine serves as a first-line CCA treatment and AURKB is overexpressed in gemcitabine-resistant cells (online supplemental figure S13C), we hypothesised that targeting AURKB could enhance gemcitabine efficacy.

Since chemotherapy serves as first-line treatment for CCA and AURKB overexpression is observed in gemcitabine-resistant cells (online supplemental figure S13C), coupled with our finding that gemcitabine IC50 correlates with AURKB expression in CCA cell lines (online supplemental figure S13D,E), we hypothesised that AURKB inhibition could enhance gemcitabine efficacy. Initially, Combination Index (CI) analysis in HuCCT1 and QBC939 cells showed significant synergy (CI<1) and inhibition (figure 7A,B). Long-term assays revealed stronger cell viability inhibition with AZD1152-gemcitabine combination than either drug alone (figure 7C). Low-dose combinations also induced stronger apoptosis (online supplemental figure S13F). We also observed enhanced sensitivity to gemcitabine in CCA cells with AURKB knockdown (online supplemental figure S13G). However, no synthetic lethality was observed between AZD1152 and gemcitabine in HCCC-9810 and RBE cells, which are gemcitabine-sensitive but have low AURKB expression (online supplemental figure S13H). Validation in primary cells from patients with chemoresistant CCA showed that AZD1152 significantly reversed gemcitabine resistance (online supplemental figure S13I-K). Cisplatin, an essential component of first-line combination therapy with gemcitabine, was also tested alongside AZD1152. We observed synergistic antitumour activity against CCA (online supplemental figure S13L-Q). Given gemcitabine’s fundamental role in first-line treatment, it was selected as the representative chemotherapeutic agent in subsequent models.

In AURKB-positive PDO models, AZD1152 inhibited organoid growth and synergised with gemcitabine (figure 7D). In vivo, AZD1152-gemcitabine combination outperformed monotherapies in QBC939 xenografts, with AZD1152 reducing tumour cholesterol levels, while gemcitabine did not (online supplemental figure S14B). Further, patient-derived xenograft (PDX) models confirmed AURKB, H3K9me3S10ph and NCEH1 expression in primary CCA tumours (figure 7E,F). While gemcitabine monotherapy showed limited efficacy, AZD1152 alone significantly suppressed tumour growth. The combination achieved synergistic therapeutic effects (figure 7G,H, online supplemental figure S14B), with tumour cholesterol analysis replicating the QBC939 findings (figure 7I). These parallel observations across models confirm distinct mechanistic pathways underlying the drug synergy.

In clinical practice for CCA, immunotherapy and chemotherapy are often administered concurrently. First, we assessed the safety and toxicity of AZD1152 in immunocompetent mice. At therapeutic doses, AZD1152 and its solvent, compared with phosphate-buffered saline (PBS), did not affect mouse weight (online supplemental figure S14C) or cause toxicity in the liver, kidney, heart, intestines or blood systems (online supplemental figure S14D-F). Given AURKB’s role in suppressing the immune microenvironment, we combined AZD1152 with anti-PD-1 antibody for CCA model treatment. This combination demonstrated synergistic antitumour efficacy in vivo (online supplemental figure S15A-F), supporting AURKB targeting to enhance first-line chemoimmunotherapy. In a cohort of patients with CCA who underwent postsurgical chemoimmunotherapy, we analysed tumour-infiltrating CD8⁺ T cell function and exhaustion, along with the expression of AURKB, H3K9me3S10ph, NCEH1 and cholesterol levels in serum and tumour tissues. Non-recurrent patients exhibited lower intratumoral cholesterol, though serum cholesterol levels were similar (figure 7J, online supplemental figure S16A). This group also showed increased infiltration of CD8⁺ T cells and Granzyme B⁺CD8⁺ T cells, with fewer PD-1⁺CD8⁺ T cells, suggesting enhanced CD8⁺ T cell activity (figure 7K). Additionally, lower levels of AURKB, H3K9me3S10ph and NCEH1 were observed in these patients (figure 7L). In CCA models, AZD1152 was administered alongside chemoimmunotherapy (figure 7M, online supplemental figure S16D). It effectively inhibited tumour progression, alleviated tumour-induced liver damage and synergised with chemoimmunotherapy in both models (figure 7N,O, online supplemental figure S16B, E-G). AZD1152, instead of αPD-1/Gemcitabine, reduced H3K9me3S10ph and NCEH1 expression (online supplemental figure S16C, I), and combination therapy lowered Ki-67 levels (online supplemental figure S16C, I), indicating tumour suppression. Consistent with PDX model results, only AZD1152 and the triple combination reduced tumour cholesterol, while neither control nor αPD-1/Gemcitabine altered serum cholesterol (figure 7P, online supplemental figure S16H). Further analysis showed that both AZD1152 and αPD-1/Gemcitabine increased tumour CD8⁺ T cell content and function, reduced exhaustion, with maximal improvement achieved through combination therapy (figure 7Q, online supplemental figure S16H).

Additionally, since AURKB regulates CCA progression via tumour cholesterol, we tested simvastatin, an Food and Drug Administration (FDA)-approved cholesterol-lowering drug, to verify its ability to reduce tumour cholesterol and inhibit CCA progression (figure 8A). Similar to AZD1152, simvastatin also slowed tumour progression, lowered tumour cholesterol and exhibited a synergistic effect with chemoimmunotherapy (figure 8B–E). It also reduced serum cholesterol in mice (figure 8E), likely due to its inhibition of HMG-COA reductase in hepatocytes. Furthermore, simvastatin enhanced CD8⁺ T cell infiltration and function while reducing T cell exhaustion, aligning with AZD1152 results (figure 8F). These findings indicate that AURKB/H3K9me3S10ph/NCEH1 expression and tumour cholesterol levels are linked to chemoimmunotherapy efficacy in CCA (figure 8G).

Discussion

In this study, we identified AURKB as an essential tumour-promoting target in CCA, validated in both in vitro and in vivo models. As a protein kinase, AURKB has been implicated in various cancers including CCA²⁷,³⁰ and functions as an immune checkpoint on T cells.³¹ Our findings reveal that AURKB regulates CCA through the cholesterol pathway, which is vital for cell survival and promotes tumour proliferation and drug resistance.³² Also, the observed synergistic reduction in cell proliferation following AZD1152, the AURKB inhibitor, and gemcitabine/cisplatin combination treatment suggests enhanced chemosensitivity. We hypothesise that AZD1152-mediated cholesterol depletion may potentiate gemcitabine/cisplatin efficacy by compromising cellular membrane integrity (potentially increasing gemcitabine/cisplatin uptake or reducing efflux) and impairing DNA damage repair capacity, thereby exacerbating chemotherapy-induced DNA damage and cell death. This potential dual disruption of cellular homoeostasis could underlie the synergistic interaction.

In patients with CCA, cholesterol levels in both serum and tissues are significantly upregulated, while cholesteryl esters in serum show a decrease, suggesting an increased pathway of cholesterol ester hydrolysis in CCA.^{11 33} This study shows that AURKB epigenetically upregulates NCEH1: its kinase activity reduces H3K9me3 enrichment at the NCEH1 promoter by phosphorylating adjacent H3S10, disrupting HP1 complex binding.^{23 34 35} However, under high AURKB expression, phosphorylation of H3K9me3 at adjacent amino acids (S10) disrupts the interaction between H3K9me3 and the HP1 complex, resulting in lower occupancy of H3K9me3 at the NCEH1 promoter, thus releasing the expression of NCEH1.

Based on the conclusions of the study, we propose that targeting AURKB or reducing tumour cholesterol presents a potential therapeutic strategy for CCA. Statins, cholesterol-lowering drugs, show promise in cancer prevention and therapy,^{36 37} with retrospective studies linking them to reduced CCA risk.³⁸,⁴⁰ Here, we validated statins’ efficacy in preclinical CCA models, establishing a causal relationship between statin treatment and CCA progression. Importantly, AURKB-driven cholesterol elevation is tumour-specific, as AURKB is scarcely expressed in liver but enriched in tumours, minimally affecting systemic cholesterol balance. Thus, targeting tumour cholesterol metabolism directly offers a more precise therapeutic approach than systemic cholesterol reduction.

In summary, our research reveals the roles of AURKB-H3K9me3S10ph-NCEH1-cholesterol in driving tumour growth and immune evasion in CCA, which exacerbate resistance to chemotherapy and immunotherapy. The clinical significance of this pathway has been validated through multiple clinical cohorts, indicating that high AURKB expression correlates positively with tumour cholesterol content and negatively with CD8⁺ T cell infiltration and function. Targeting AURKB or reducing tumour cholesterol offers potential therapeutic avenues for CCA and may enhance the efficacy of first-line chemotherapy and immunotherapy.

Supplementary material

online supplemental file 1

gutjnl-75-2-s001.pptx^{(1.9MB, pptx)}

DOI: 10.1136/gutjnl-2025-335291

online supplemental file 2

gutjnl-75-2-s002.pdf^{(37.7MB, pdf)}

DOI: 10.1136/gutjnl-2025-335291

Acknowledgements

We are grateful to Dr Min Pan (WHU Medical Research Institute) for technical assistance with microscale thermophoresis (MST) assays. We particularly thank Ms Zhang Meng from Vazyme for her expert guidance on CUT&Tag and ATAC-seq experimental protocols. Additionally, we acknowledge Shanghai LabEx Biotech Co, Ltd for their professional support in comprehensive scRNA-seq services including single-cell library preparation, high-throughput sequencing and upstream data filtering.

Footnotes

Provenance and peer review: Not commissioned; externally peer reviewed.

Patient consent for publication: Not applicable.

Data availability free text: The data generated in this study are available within the article, and its supplementary data files.

Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Ethics approval: Studies involving human samples were approved by the Ethics Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology (No. TJ-IRB20230396). Studies involving animal were approved by the Ethics Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology (No. TJH-202203011).

Correction notice: This article has been corrected since it published Online First. The equal contribution statement has been added.

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information.

References

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38.Wijarnpreecha K, Aby ES, Ghoz H, et al. Statins and Risk of Cholangiocarcinoma: A Systematic Review and Meta-analysis. JGLD . 2020;29:629–35. doi: 10.15403/jgld-2990. [DOI] [PubMed] [Google Scholar]
39.Marcano-Bonilla L, Schleck CD, Harmsen WS, et al. Aspirin, Statins, Non-aspirin NSAIDs, Metformin, and the Risk of Biliary Cancer: A Swedish Population-Based Cohort Study. Cancer Epidemiol Biomarkers Prev. 2022;31:804–10. doi: 10.1158/1055-9965.EPI-20-1322. [DOI] [PMC free article] [PubMed] [Google Scholar]
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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

online supplemental file 1

gutjnl-75-2-s001.pptx^{(1.9MB, pptx)}

DOI: 10.1136/gutjnl-2025-335291

online supplemental file 2

gutjnl-75-2-s002.pdf^{(37.7MB, pdf)}

DOI: 10.1136/gutjnl-2025-335291

Data Availability Statement

All data relevant to the study are included in the article or uploaded as supplementary information.

[R1] 1.Benson AB, D’Angelica MI, Abrams T, et al. NCCN Guidelines® Insights: Biliary Tract Cancers, Version 2.2023. J Natl Compr Canc Netw. 2023;21:694–704. doi: 10.6004/jnccn.2023.0035. [DOI] [PubMed] [Google Scholar]

[R2] 2.Ilyas SI, Affo S, Goyal L, et al. Cholangiocarcinoma - novel biological insights and therapeutic strategies. Nat Rev Clin Oncol. 2023;20:470–86. doi: 10.1038/s41571-023-00770-1. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R3] 3.Bowlus CL, Arrivé L, Bergquist A, et al. AASLD practice guidance on primary sclerosing cholangitis and cholangiocarcinoma. Hepatology. 2023;77:659–702. doi: 10.1002/hep.32771. [DOI] [PubMed] [Google Scholar]

[R4] 4.Harding JJ, Khalil DN, Fabris L, et al. Rational development of combination therapies for biliary tract cancers. J Hepatol. 2023;78:217–28. doi: 10.1016/j.jhep.2022.09.004. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R5] 5.Ma T, Chen Z, Chai Y, et al. Research progress on immunotherapy targeting the tumor immune microenvironment for cholangiocarcinoma*. Oncology and Translational Medicine. 2023;9:49–55. doi: 10.1007/s10330-023-0642-2. [DOI] [Google Scholar]

[R6] 6.Huang B, Song BL, Xu C. Cholesterol metabolism in cancer: mechanisms and therapeutic opportunities. Nat Metab . 2020;2:132–41. doi: 10.1038/s42255-020-0174-0. [DOI] [PubMed] [Google Scholar]

[R7] 7.Liu X, Lv M, Zhang W, et al. Dysregulation of cholesterol metabolism in cancer progression. Oncogene. 2023;42:3289–302. doi: 10.1038/s41388-023-02836-x. [DOI] [PubMed] [Google Scholar]

[R8] 8.Luo J, Yang H, Song BL. Mechanisms and regulation of cholesterol homeostasis. Nat Rev Mol Cell Biol. 2020;21:225–45. doi: 10.1038/s41580-019-0190-7. [DOI] [PubMed] [Google Scholar]

[R9] 9.Igarashi M, Osuga J, Uozaki H, et al. The critical role of neutral cholesterol ester hydrolase 1 in cholesterol removal from human macrophages. Circ Res. 2010;107:1387–95. doi: 10.1161/CIRCRESAHA.110.226613. [DOI] [PubMed] [Google Scholar]

[R10] 10.Manieri E, Folgueira C, Rodríguez ME, et al. JNK-mediated disruption of bile acid homeostasis promotes intrahepatic cholangiocarcinoma. Proc Natl Acad Sci U S A. 2020;117:16492–9. doi: 10.1073/pnas.2002672117. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R11] 11.Banales JM, Iñarrairaegui M, Arbelaiz A, et al. Serum Metabolites as Diagnostic Biomarkers for Cholangiocarcinoma, Hepatocellular Carcinoma, and Primary Sclerosing Cholangitis. Hepatology. 2019;70:547–62. doi: 10.1002/hep.30319. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R12] 12.Vader G, Medema RH, Lens SMA. The chromosomal passenger complex: guiding Aurora-B through mitosis. J Cell Biol. 2006;173:833–7. doi: 10.1083/jcb.200604032. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R13] 13.Chen X, Calvisi DF. Hydrodynamic transfection for generation of novel mouse models for liver cancer research. Am J Pathol. 2014;184:912–23. doi: 10.1016/j.ajpath.2013.12.002. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R14] 14.Tang M, Zhao Y, Zhao J, et al. Liver cancer heterogeneity modeled by in situ genome editing of hepatocytes. Sci Adv. 2022;8:eabn5683. doi: 10.1126/sciadv.abn5683. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R15] 15.Hsu JY, Sun ZW, Li X, et al. Mitotic phosphorylation of histone H3 is governed by Ipl1/aurora kinase and Glc7/PP1 phosphatase in budding yeast and nematodes. Cell. 2000;102:279–91. doi: 10.1016/s0092-8674(00)00034-9. [DOI] [PubMed] [Google Scholar]

[R16] 16.Komar D, Juszczynski P. Rebelled epigenome: histone H3S10 phosphorylation and H3S10 kinases in cancer biology and therapy. Clin Epigenetics. 2020;12:147. doi: 10.1186/s13148-020-00941-2. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R17] 17.Nigg EA. Mitotic kinases as regulators of cell division and its checkpoints. Nat Rev Mol Cell Biol. 2001;2:21–32. doi: 10.1038/35048096. [DOI] [PubMed] [Google Scholar]

[R18] 18.Djeghloul D, Dimond A, Cheriyamkunnel S, et al. Loss of H3K9 trimethylation alters chromosome compaction and transcription factor retention during mitosis. Nat Struct Mol Biol. 2023;30:489–501. doi: 10.1038/s41594-023-00943-7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R19] 19.Hirota T, Lipp JJ, Toh B-H, et al. Histone H3 serine 10 phosphorylation by Aurora B causes HP1 dissociation from heterochromatin. Nature New Biol. 2005;438:1176–80. doi: 10.1038/nature04254. [DOI] [Google Scholar]

[R20] 20.Watanabe S, Mishima Y, Shimizu M, et al. Interactions of HP1 Bound to H3K9me3 Dinucleosome by Molecular Simulations and Biochemical Assays. Biophys J. 2018;114:2336–51. doi: 10.1016/j.bpj.2018.03.025. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R21] 21.Zhang J, Donahue G, Gilbert MB, et al. Distinct H3K9me3 heterochromatin maintenance dynamics govern different gene programmes and repeats in pluripotent cells. Nat Cell Biol. 2024;26:2115–28. doi: 10.1038/s41556-024-01547-z. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R22] 22.Hiragami-Hamada K, Soeroes S, Nikolov M, et al. Dynamic and flexible H3K9me3 bridging via HP1β dimerization establishes a plastic state of condensed chromatin. Nat Commun. 2016;7:11310. doi: 10.1038/ncomms11310. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R23] 23.Fischle W, Tseng BS, Dormann HL, et al. Regulation of HP1-chromatin binding by histone H3 methylation and phosphorylation. Nature New Biol. 2005;438:1116–22. doi: 10.1038/nature04219. [DOI] [Google Scholar]

[R24] 24.Noh K-M, Maze I, Zhao D, et al. ATRX tolerates activity-dependent histone H3 methyl/phos switching to maintain repetitive element silencing in neurons. Proc Natl Acad Sci U S A. 2015;112:6820–7. doi: 10.1073/pnas.1411258112. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R25] 25.Collins GP, Eyre TA, Linton KM, et al. A phase II trial of AZD1152 in relapsed/refractory diffuse large b-cell lymphoma. Br J Haematol. 2015;170:886–90. doi: 10.1111/bjh.13333. [DOI] [PubMed] [Google Scholar]

[R26] 26.Löwenberg B, Muus P, Ossenkoppele G, et al. Phase 1/2 study to assess the safety, efficacy, and pharmacokinetics of barasertib (AZD1152) in patients with advanced acute myeloid leukemia. Blood. 2011;118:6030–6. doi: 10.1182/blood-2011-07-366930. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R27] 27.Jiang J, Wang J, Yue M, et al. Direct Phosphorylation and Stabilization of MYC by Aurora B Kinase Promote T-cell Leukemogenesis. Cancer Cell. 2020;37:200–15. doi: 10.1016/j.ccell.2020.01.001. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R28] 28.Ramkumar K, Tanimoto A, Della Corte CM, et al. Targeting BCL2 Overcomes Resistance and Augments Response to Aurora Kinase B Inhibition by AZD2811 in Small Cell Lung Cancer. Clin Cancer Res. 2023;29:3237–49. doi: 10.1158/1078-0432.CCR-23-0375. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R29] 29.Liu K, Zhou X, Huang F, et al. Aurora B facilitates cholangiocarcinoma progression by stabilizing c‐Myc. Anim Models and Exp Med. 2024;7:626–40. doi: 10.1002/ame2.12370. [DOI] [Google Scholar]

[R30] 30.Ma P, Hao Y, Wang W, et al. AURKB activates EMT through PI3K/AKT signaling axis to promote ICC progression. Discov Oncol . 2023;14:102. doi: 10.1007/s12672-023-00707-1. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R31] 31.Wang Q, Liu W, Zhou H, et al. Tozasertib activates anti-tumor immunity through decreasing regulatory T cells in melanoma. Neoplasia. 2024;48:100966. doi: 10.1016/j.neo.2024.100966. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R32] 32.Miller T, Yang F, Wise CE, et al. Simvastatin stimulates apoptosis in cholangiocarcinoma by inhibition of Rac1 activity. Dig Liver Dis. 2011;43:395–403. doi: 10.1016/j.dld.2011.01.010. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R33] 33.Paul B, Lewinska M, Andersen JB. Lipid alterations in chronic liver disease and liver cancer. JHEP Rep . 2022;4:100479. doi: 10.1016/j.jhepr.2022.100479. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R34] 34.Padeken J, Methot SP, Gasser SM. Establishment of H3K9-methylated heterochromatin and its functions in tissue differentiation and maintenance. Nat Rev Mol Cell Biol. 2022;23:623–40. doi: 10.1038/s41580-022-00483-w. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R35] 35.Wakim JG, Spakowitz AJ. Physical modeling of nucleosome clustering in euchromatin resulting from interactions between epigenetic reader proteins. Proc Natl Acad Sci U S A. 2024;121:e2317911121. doi: 10.1073/pnas.2317911121. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R36] 36.Murto MO, Simolin N, Arponen O, et al. Statin Use, Cholesterol Level, and Mortality Among Females With Breast Cancer. JAMA Netw Open . 2023;6:e2343861. doi: 10.1001/jamanetworkopen.2023.43861. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R37] 37.Guo C, Wan R, He Y, et al. Therapeutic targeting of the mevalonate-geranylgeranyl diphosphate pathway with statins overcomes chemotherapy resistance in small cell lung cancer. Nat Cancer . 2022;3:614–28. doi: 10.1038/s43018-022-00358-1. [DOI] [PubMed] [Google Scholar]

[R38] 38.Wijarnpreecha K, Aby ES, Ghoz H, et al. Statins and Risk of Cholangiocarcinoma: A Systematic Review and Meta-analysis. JGLD . 2020;29:629–35. doi: 10.15403/jgld-2990. [DOI] [PubMed] [Google Scholar]

[R39] 39.Marcano-Bonilla L, Schleck CD, Harmsen WS, et al. Aspirin, Statins, Non-aspirin NSAIDs, Metformin, and the Risk of Biliary Cancer: A Swedish Population-Based Cohort Study. Cancer Epidemiol Biomarkers Prev. 2022;31:804–10. doi: 10.1158/1055-9965.EPI-20-1322. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R40] 40.Lavu S, Therneau TM, Harmsen WS, et al. Effect of Statins on the Risk of Extrahepatic Cholangiocarcinoma. Hepatology. 2020;72:1298–309. doi: 10.1002/hep.31146. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Targeting Aurora kinase B regulates cholesterol metabolism and enhances chemoimmunotherapy in cholangiocarcinoma

Furong Liu

Wei Chen

Ze Zhang

Weifeng Zeng

Haofan Hu

Shangwu Ning

Zhibin Liao

Yachong Liu

Hongwei Zhang

Qinggang Fu

Bixiang Zhang

Xiaoping Chen

Wanguang Zhang

Zhanguo Zhang

Abstract

Background

Objective

Design

Results

Conclusions

WHAT IS ALREADY KNOWN ON THIS TOPIC

WHAT THIS STUDY ADDS

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

Introduction

Materials and methods

Results

AURKB is a specific dependency in CCA and its high expression in CCA indicates a poor prognosis

AURKB plays an indispensable role in the progression of CCA

AURKB promotes CCA progression by enhancing cholesterol production within tumours

AURKB impairs the antitumour immune microenvironment of CCA by increasing free cholesterol in tumours

AURKB increases cholesterol levels within tumours through NCEH1

AURKB reduces the enrichment of H3K9me3 at the NCEH1 promoter by blocking the interaction between the HP1 complex and H3K9me3

Targeting AURKB or reducing tumour cholesterol can enhance the sensitivity to chemoimmunotherapy in CCA treatment

Discussion

Supplementary material

Acknowledgements

Footnotes

Data availability statement

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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