Introduction
Hepatocellular carcinoma (HCC) is a significant global health concern, ranking as the sixth most common cancer and the second leading cause of cancer-related deaths worldwide.1 Early-stage HCC is often asymptomatic, resulting in late diagnoses that limit access to curative treatments and lead to poor prognoses. HCC typically progresses in stages, beginning with hepatic precancerous lesions (HPC), which develop into dysplastic nodules, then into early HCC—characterized by small tumor masses lacking invasive features such as vascular infiltration or intrahepatic metastasis—and eventually into advanced HCC.2 Identifying biomarkers for accurate early HCC diagnosis and understanding the mechanisms that drive HPC progression to invasive tumors are critical. These efforts may facilitate the prediction of HCC development from HPC and improve the standardization of histological diagnoses.
The immune system plays a dual role in both suppressing and promoting cancer. Tumors can evade immune surveillance by creating local or systemic immunosuppressive environments that hinder natural anti-tumor immunity and reduce the effectiveness of immunotherapy.3 The tumor microenvironment (TME) is a dynamic and complex network composed of malignant cells, immune cells, and other factors influencing cancer progression and therapeutic responses.4 Tumor-associated macrophages (TAMs), immune cells derived from the bone marrow, infiltrate the TME and may either inhibit or support tumor development. TAMs can enhance cancer cell proliferation, metastasis, and angiogenesis, while also suppressing anti-tumor immune responses. Depending on environmental cues, TAMs can polarize into either the anti-tumor M1 phenotype or the pro-tumor M2 phenotype.5,6 In early neoplastic tumors, TAMs often exhibit an M1-like phenotype capable of eliminating some immunogenic tumor cells. However, as tumors progress, changes in the TME and macrophage function can lead to TAM polarization toward the tumor-promoting M2-like phenotype.7 Despite these findings, the role of TAMs in regulating the transition from HPC to HCC remains unclear.
E-type cyclins, including cyclins E1 and E2, are essential regulators of the cell cycle. They promote the transition from the G1 to the S phase by activating cyclin-dependent kinases (CDKs) and regulating DNA replication and centrosome biology.8 Cyclin E1 (CCNE1) amplification or overexpression has been observed in multiple cancer types—including high-grade serous ovarian, endometrial, gastroesophageal, and breast cancers—and is often associated with poor prognosis.9–12 In normal cells, CCNE1 levels are tightly regulated, peaking at the G1/S phase transition and decreasing as cells progress through the S phase. However, this regulation is frequently disrupted in cancer cells. Mechanisms such as CCNE1 gene amplification, disruption of the retinoblastoma/E2F pathway (which increases CCNE1 transcription), or mutations in the FBXW7 ubiquitin ligase (which impairs CCNE1 degradation) can lead to CCNE1 accumulation. Elevated CCNE1 levels can cause chromosomal and genetic instability, contributing to tumorigenesis.13,14 Most HCCs reportedly overexpress E-type cyclins, promoting hepatocyte and HCC proliferation, even in a CDK2-independent manner.15 Nevertheless, the specific role of CCNE1 in HPC development and its potential utility as an early diagnostic or prognostic biomarker, or as a therapeutic target in HCC, remain unclear.
This study explores the potential role of CCNE1 in HPC progression. The findings demonstrate that CCNE1 promotes HCC cell proliferation, migration, invasion, and survival via activation of the PI3K/Akt signaling pathway and by inducing pro-tumor M2 macrophage polarization through increased secretion of CCL2 and CCL5. These findings shed light on the oncogenic mechanisms of CCNE1 and its potential as an early biomarker for HCC progression in HPC, offering new avenues for HCC prevention and treatment strategies.
Methods
Animal experiments
Male C57BL/6 mice (four weeks old) were obtained from the Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences (Beijing, China), and maintained in a pathogen-free animal facility. All mice had ad libitum access to standard rodent chow and filtered water. Thirty mice were randomly divided into two groups (15 mice per group) and treated as follows: the first group was injected intraperitoneally with 10% CCl4 (1.0 mL/kg body weight, dissolved in corn oil) twice weekly for 24 weeks. The second group served as the control and received corn oil alone. Mice were sacrificed 24 h after the final CCl4 injection, and serum and liver samples were collected for subsequent experiments. All procedures were approved by the Animal Care and Use Committee of The First Affiliated Hospital of Zhengzhou University (No. 2019-KY-21).
Biochemical parameters
Serum levels of alanine transaminase and aspartate transaminase were measured using standard autoanalyzer methods on the Chemray 240 automatic biochemistry analyzer (Rayto, USA).
Enzyme-linked immunosorbent assay (ELISA)
Serum alpha-fetoprotein (AFP) levels in mice and the concentrations of CCL2 and CCL5 secreted by HCC cells were determined using ELISA kits (Elabscience, China) according to the manufacturer’s instructions.
RNA-sequencing analysis
RNA sequencing was performed by BGI Tech Co., Ltd. (Shenzhen, China), using specific methods and procedures described previously.16
Cell cultures
THP-1, HepG2, and Huh7 cell lines were purchased from the Shanghai Institute of Cell Biology, Chinese Academy of Sciences (Shanghai, China). THP-1 cells were maintained in RPMI-1640 medium (HyClone, USA), and HepG2 and Huh7 cells were maintained in DMEM (HyClone, USA) supplemented with 10% fetal bovine serum (Gibco, USA) and 100 U/mL penicillin-streptomycin (Beyotime, China) at 37°C in a 5% CO2 incubator. The medium was changed every two to three days. THP-1 cells were treated with 100 ng/mL PMA (MedChemExpress, USA) for 24 h to generate non-polarized (M0) macrophages.
Histopathology
Liver tissue samples were fixed in 4% paraformaldehyde, embedded in paraffin, sectioned at 5 µm, and stained with hematoxylin and eosin for general histopathological evaluation. Detailed experimental methods are described previously.17
Immunohistochemistry
Paraffin-embedded tissue samples were sectioned at 5 µm, deparaffinized, and rehydrated. Sections were incubated overnight at 4°C with primary antibodies against AFP (1:100, ab46799, Abcam), vascular endothelial growth factor (VEGF) (1:100, ab27278, Abcam), and F4/80 (1:100, ab300421, Abcam). Detailed methods are described previously.17
siRNA transfection
HepG2 and Huh7 cells were seeded in 6-well plates and incubated for 24 h. At 50% confluency, cells were transfected with CCNE1-specific siRNA using Lipofectamine™ 2000 (Invitrogen, USA) in Opti-MEM. Detailed methods are described previously.18
Cell viability assay
Cell viability was assessed using the Cell Counting Kit-8 according to the manufacturer’s instructions. Briefly, 2,000 cells per well were seeded in 96-well plates and cultured for 12, 24, 48, and 72 h. Cell Counting Kit-8 solution was added, and absorbance at 450 nm was measured using a microplate reader.
Colony formation assay
HCC cells were seeded in six-well plates and cultured for 10 days. Colonies were fixed with 4% paraformaldehyde and stained with 0.1% crystal violet for 30 m. Detailed methods are described previously.19
Wound-healing assay
HCC cells were seeded in six-well plates and grown to 80% confluence. A scratch was made, and images were captured at 0 and 48 h using an inverted microscope. Detailed methods are described previously.19
Transwell invasion assay
To assess cell invasiveness, the upper chamber of the transwell insert was pre-coated with Matrigel (Corning, NY, USA). Cells were seeded in the upper chamber, and migrated cells were counted and imaged in three randomly selected fields. Detailed methods are described previously.19
Flow cytometry
HCC cells were washed with cold PBS, resuspended in binding buffer, and stained with Annexin V-FITC and propidium iodide for 20 m at room temperature. Apoptosis was analyzed using flow cytometry. Detailed methods are described previously.19
Real-time polymerase chain reaction (RT-qPCR)
Total RNA was extracted using TRIzol (Beyotime, China). cDNA was synthesized from 2 µg of total RNA using the BeyoRT™ Reagent Kit (Beyotime, China). mRNA expression levels were determined using specific primers and analyzed using the 2−ΔΔCt method, normalized to GAPDH expression. Detailed methods are described previously.19 Primer sequences are listed in Table 1.
Table 1Primer sequences used for RT-qPCR
| Mouse |
| Ccne1 | Forward sequence: 5′-CTCCCACAACATCCAGACCC-3′ |
| Reverse sequence: 5′-AGCAACCTACAACACCCGAG-3′ |
| Human | |
| CD86 | Forward sequence: 5′-CAGGGACTAGCACAGACACAC-3′ |
| Reverse sequence: 5′-CAGGTTGACTGAAGTTAGCAGAG-3′ |
| iNOS | Forward sequence: 5′-CGTGGAGACGGGAAAGAAGT-3′ |
| Reverse sequence: 5′-GACCCCAGGCAAGATTTGGA-3′ |
| CD206 | Forward sequence: 5′-GGGAAAGGTTACCCTGGTGG-3′ |
| Reverse sequence: 5′-GTCAAGGAAGGGTCGGATCG-3′ |
| Arg1 | Forward sequence: 5′-TTAAAGAACAAGAGTGTGATGTGAA-3′ |
| Reverse sequence: 5′-TCCAATTGCCAAACTGTGGT-3′ |
| CCL2 | Forward sequence: 5′-AGCAGCAAGTGTCCCAAAGA-3′ |
| Reverse sequence: 5′-GGTGTCTGGGGAAAGCTAGG-3′ |
| CCL5 | Forward sequence: 5′-GACAGCAAGTCTGGCAGGAT-3′ |
| Reverse sequence: 5′-TTTTGACAAAGCAGCGCCTC-3′ |
Western blotting
Total protein was extracted using RIPA lysis buffer. Detailed methods are described previously.19 Primary antibodies included: AFP (1:1,000, ab284388, Abcam), VEGF (1:1,000, ab27278, Abcam), CCNE1 (1:1,000, ab211342, Abcam), MMP2 (1:1,000, A19080, ABclonal), MMP9 (1:1,000, A2095, ABclonal), Cleaved Caspase-3 (1:1,000, A22869, ABclonal), Bax (1:1,000, A19684, ABclonal), Bcl-2 (1:1,000, A0208, ABclonal), PI3K (1:1,000, ab302958, Abcam), p-PI3K (1:1,000, ab278545, Abcam), Akt (1:1,000, ab8805, Abcam), p-Akt (1:1,000, ab38449, Abcam), CD206 (1:1,000, ab64693, Abcam), Arg-1 (1:1,000, ab133543, Abcam), CCL2 (1:1,000, A7277, ABclonal), CCL5 (1:1,000, A5630, ABclonal), and GAPDH (1:3,000, AC001, ABclonal).
Statistical analysis
Data analysis was conducted using GraphPad Prism 8.0 (GraphPad Software, USA). Bar graphs represent the mean ± standard deviation. Statistical significance was determined using one-way ANOVA or a two-tailed unpaired Student’s t-test. A P < 0.05 was considered statistically significant.
Results
General conditions and histopathological changes in mice with hepatic precancerous lesions
Mice in the control group exhibited normal behavior, alertness, good energy, and clean fur. In contrast, mice in the model group showed signs of poor general condition, lethargy, reduced activity and appetite, and thinning hair. The model group also exhibited decreased liver weight (Fig. 1A), an increased liver-to-body weight ratio (Fig. 1B), and elevated serum alanine transaminase, aspartate transaminase, and AFP levels (Fig. 1C–E). Gross examination of liver morphology revealed a rough, firm texture and dull coloration in the model group. Hematoxylin and eosin staining showed disrupted hepatic lobular architecture, disorganized hepatocyte cords, and numerous heterocellular clusters characterized by hyperchromatic nuclei, increased nuclear-to-cytoplasmic ratios, basophilic cytoplasm, and infiltration of inflammatory cells. Masson staining revealed a marked increase in hepatic fibrotic deposition in the HPC group compared to the control group (Fig. 1F). Additionally, immunohistochemistry (Fig. 1G) and Western blotting (Fig. 1H) demonstrated significantly increased expression of AFP and VEGF in the HPC group relative to the control group.
CCNE1 is highly expressed in the liver tissues of mice with hepatic precancerous lesions
RNA sequencing was conducted on liver tissues from the control and HPC groups to elucidate molecular mechanisms underlying HPC development. Unsupervised hierarchical clustering and principal component analysis clearly distinguished liver samples from control and model mice into two distinct clusters, indicating significant molecular differences (Fig. 2A). A total of 2,038 differentially expressed genes (DEGs) were identified, with 1,105 upregulated and 933 downregulated genes (Fig. 2B–C). The Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis showed that the DEGs were primarily involved in the p53 signaling pathway, extracellular matrix–receptor interaction, PPAR signaling, fatty acid metabolism, PI3K/Akt signaling, and NOD-like receptor signaling pathways (Fig. 2D). The PI3K/Akt pathway, which is crucial in various cancers, regulates cancer cell survival, metastasis, metabolism, and also modulates the TME, including angiogenesis and recruitment of inflammatory mediators.20 Among 59 DEGs in this pathway, CCNE1 was among the top 10 genes with the highest fold changes, alongside THBS1, Col1a2, Col1a1, Col4a6, CDKN1A, NTRK2, Col6a2, LPAR2, and Col6a1 (Fig. 2E). RT-qPCR (Fig. 2F) and Western blotting (Fig. 2G) confirmed significant upregulation of CCNE1 mRNA and protein levels in the HPC group compared to the control group.
CCNE1 is involved in the progression from HPC to HCC
Comprehensive analysis of HCC RNA sequencing data from the TCGA database showed a significant increase in CCNE1 expression in human HCC tissues (Fig. 3A). Stratified analysis by tumor stage revealed that CCNE1 expression was significantly higher in intermediate/advanced HCC compared to early-stage HCC (Fig. 3B). In early-stage HCC (BCLC 0/A), CCNE1 levels positively correlated with tumor size and risk of vascular invasion. In advanced-stage HCC (BCLC C/D), higher CCNE1 expression was significantly associated with distant metastasis (Table 2), suggesting that CCNE1 may be involved in tumor progression. Furthermore, analysis of clinical datasets representing stages of progression from HPC to HCC (GSE6764, GSE89377) demonstrated that CCNE1 expression was significantly elevated in HPC samples compared to normal liver tissue, with a gradual increase during the transition to HCC (Fig. 3C–D). Kaplan–Meier survival analysis showed that high CCNE1 expression was significantly associated with reduced overall survival (Fig. 3E–F). These findings support a pivotal role for CCNE1 in the early malignant transformation of HCC.
Table 2Correlation between CCNE1 expression and clinical features in HCC
| Group | Clinical Feature | Sample Distribution | FPKM (Median ± IQR) | P-value |
|---|
| Early-stage HCC (BCLC 0/A) | Gender | Male: 80 | 2.5 ± 1.2 | 0.45 |
| | Female: 40 | 2.3 ± 1.0 | |
| Age (years) | ≤60: 70 | 2.4 ± 1.1 | 0.78 |
| | >60: 50 | 2.6 ± 1.3 | |
| Tumor Size | ≤5 cm: 85 | 2.1 ± 0.9 | 0.04* |
| | >5 cm: 35 | 3.0 ± 1.6 | |
| Liver cirrhosis | Yes: 90 | 2.5 ± 1.3 | 0.15 |
| | No: 30 | 2.2 ± 1.0 | |
| Vascular | Positive: 30 | 3.2 ± 1.5 | 0.02* |
| Invasion | Negative: 90 | 1.8 ± 0.9 | |
| Advanced-stage HCC (BCLC C/D) | Gender | Male: 50 | 3.8 ± 1.8 | 0.62 |
| | Female: 30 | 3.5 ± 1.6 | |
| Age (years) | ≤60: 40 | 3.6 ± 1.7 | 0.91 |
| | >60: 40 | 3.7 ± 1.9 | |
| Tumor Size | ≤5 cm: 45 | 3.2 ± 1.5 | 0.08 |
| | >5 cm: 35 | 4.0 ± 2.0 | |
| Liver cirrhosis | Yes: 70 | 3.7 ± 1.8 | 0.27 |
| | No: 10 | 3.1 ± 1.4 | |
| Distant | Positive: 25 | 4.5 ± 2.1 | 0.003** |
| Metastasis | Negative: 55 | 2.3 ± 1.2 | |
Knockdown of CCNE1 inhibits HCC cell proliferation, migration, and invasion and promotes apoptosis
To investigate the role of CCNE1 in HCC progression, its expression was analyzed in various HCC cell lines, including SMMC-7721, SNU-449, Huh7, HepG2, and Hep3B. All showed significantly higher CCNE1 expression compared to normal hepatocyte cell lines (L02) (Fig. 4A). HepG2 and Huh7 cells, which had the highest CCNE1 expression levels, were selected for further experiments. Using siRNA to knockdown CCNE1, a marked reduction in HCC cell viability (Fig. 4B–C) and colony formation (Fig. 4D) was observed in the siCCNE1 group compared to controls. Wound-healing (Fig. 4E–F) and Transwell assays (Fig. 4G–H) showed that CCNE1 knockdown significantly inhibited cell migration and invasion. Western blotting showed reduced expression of MMP2 and MMP9, which are critical mediators of tumor invasion (Fig. 4J–K). Flow cytometry analysis revealed increased apoptosis in the siCCNE1 group (Fig. 4I), corroborated by elevated levels of Cleaved Caspase-3 and Bax, and reduced Bcl-2 expression (Fig. 4J–K). These results indicate that CCNE1 can promote HCC cell proliferation, migration, invasion, and survival.
CCNE1 promotes HCC progression by activating the PI3K/Akt signaling pathway
Gene set enrichment analysis (GSEA) of RNA sequencing data revealed that the PI3K/Akt signaling pathway was upregulated in the HPC group (Fig. 5A). This finding was confirmed by Western blotting, which showed increased levels of p-PI3K and p-Akt in the HPC group compared to the control group (Fig. 5B), indicating activation of the PI3K/Akt pathway during HPC development. Further investigation into the role of the PI3K/Akt pathway in HCC progression showed that CCNE1 knockdown reduced the phosphorylation levels of PI3K and Akt (Fig. 5C–D). To validate the role of the PI3K/Akt pathway, LY294002 (a PI3K inhibitor) or 740Y-P (a PI3K activator) was added to the cell culture medium. Functional assays including colony formation (Fig. 5E), wound healing (Fig. 5F–H), Transwell migration/invasion (Fig. 5G–I), and flow cytometry (Fig. 5J) demonstrated that inhibition of the PI3K/Akt pathway reversed the oncogenic effects of CCNE1 on HCC cell proliferation, migration, invasion, and survival. Interestingly, activation of the PI3K/Akt pathway did not significantly rescue the phenotype of HCC cells in the siCCNE1 groups, suggesting that CCNE1 acts upstream of PI3K/Akt. These findings indicate that CCNE1 promotes the malignant phenotype of HCC cells by activating the PI3K/Akt signaling pathway, underscoring its critical role in HCC progression.
CCNE1 promotes M2 macrophage polarization in HCC
Circulating bone marrow-derived monocytes migrate to the tumor site and differentiate into TAMs under the influence of cytokines and chemokines in TME.21 TAM plays a critical role in tumorigenesis by promoting tumor cell proliferation, invasion, angiogenesis, and metastasis.22 The Gene Ontology and GSEA of RNA sequencing data identified several pathways associated with HPC development, including “cytokine receptor activity,” “inflammatory response,” and “monocyte chemotaxis” (Fig. 6A). Additionally, analysis using the Tumor Immune Estimation Resource revealed that CCNE1 expression in HCC positively correlated with immune cell infiltration, including B cells, CD8+ T cells, CD4+ T cells, and macrophages (Fig. 6B). Immunohistochemistry further confirmed increased macrophage infiltration and neovascularization in liver tissues of HPC mice compared to controls (Figs. 1G, 6C). In vitro co-culture of HCC cells with PMA-induced THP-1 monocytes showed that HCC cells elevated the mRNA and protein levels of M2 polarization markers (CD206 and Arg-1) in THP-1-derived macrophages after 48 h (Fig. 6D–G). However, CCNE1 knockdown via siRNA reduced CD206 and Arg-1 expression while increasing mRNA levels of M1 markers (CD86 and iNOS). Moreover, TAMs derived from PMA-induced THP-1 cells and co-cultured with HCC cells promoted VEGF expression in HepG2 and Huh7 cells, an effect that was reversed by CCNE1 silencing (Fig. 6H–I). These findings suggest that CCNE1 overexpression promotes TAM polarization toward the tumor-promoting M2 phenotype, thereby enhancing angiogenesis and metastasis in HCC.
CCNE1 induces TAM polarization by promoting CCL2 and CCL5 expressions
To further elucidate the mechanism by which CCNE1 drives TAM polarization, we focused on chemokines in the TME, which regulate immune cell migration and influence tumor immune composition and therapy resistance .23,24 RNA sequencing analysis showed that CCR1, CCL5, CCL2, and CCR2 were enriched in the “monocyte chemotaxis” pathway and were significantly upregulated in the HPC group (log2FC > 1, adjusted P < 0.05) (Fig. 7A). ELISA, RT-qPCR, and Western blotting revealed that CCNE1 silencing significantly reduced CCL2 and CCL5 expression in HCC cells (Fig. 7B–E). To test the functional relevance, neutralizing antibodies (NAbs) against CCL2 and CCL5 were added to a co-culture system of HCC cells and PMA-induced THP-1 macrophages. Both CCL2-NAb and CCL5-NAb partially attenuated TAM polarization induced by HCC cells, while the combination of both completely blocked the polarization effect (Fig. 7F–I). These findings suggest that CCNE1 promotes TAM polarization in HCC via a CCL2/CCL5-dependent mechanism.
Discussion
Precancerous lesions are tissues with a high risk of tumorigenesis due to DNA damage, genomic instability, and inflammation.25 HCC develops through a stepwise process from precancerous lesions, including low-grade and high-grade dysplastic nodules, to advanced cancer.2 Early detection of small HCC or precancerous lesions is crucial for optimal treatment; however, the molecular changes associated with HPC progression and its morphological and molecular features are not fully understood. Hence, identifying molecular markers of early HCC progression in HPC is essential for early detection and treatment. The present study not only elucidates the oncogenic mechanisms of CCNE1 in HCC but also underscores its pivotal role as a molecular bridge linking HPC to invasive HCC. Our findings reveal that CCNE1 overexpression is an early event in hepatocarcinogenesis, detectable in HPC tissues and progressively amplified during malignant transformation. This spatiotemporal expression pattern positions CCNE1 as a potential biomarker for early diagnosis (e.g., via liquid biopsy) and risk stratification to guide surveillance protocols.
E-type cyclins are key components of the cell cycle machinery that regulate various physiological and pathological processes.8 CCNE1, the first identified E-type cyclin, activates CDK2 kinase, inducing entry into the S phase.26 The normal activity of the CCNE1/CDK2 complex is essential for proper cell cycle progression and DNA replication. Its oncogenic activation has been shown to interfere with DNA replication, causing replication stress through various mechanisms and leading to genomic instability in human cancers.27 CCNE1 is overexpressed or amplified in many human cancers, contributing to resistance against standard treatments and targeted chemotherapeutic agents, and is associated with poor clinical outcomes and reduced survival.28,29 A study by Sonntag et al.30 showed that while CCNE1 and CDK2 are essential for HCC development, HCC progression is regulated by mechanisms independent of CDK2 activity, and genetic inactivation of CCNE1 prevents HCC development in mice. However, the individual contribution and mechanism of CCNE1 in HPC-to-HCC progression remain incompletely understood. In this study, CCNE1 expression was significantly upregulated in HPC mice, overexpressed in human dysplastic nodules and HCC samples, and correlated with poor survival in patients. In addition, CCNE1 was minimally expressed in normal hepatocytes but highly expressed in HCC cells. Silencing CCNE1 significantly inhibited HCC cell proliferation, migration, and invasion, and increased apoptosis. These findings suggest that CCNE1 overexpression promotes the malignant phenotype and early progression of HCC.
RNA sequencing analysis revealed that CCNE1 activates the PI3K/Akt signaling pathway in the liver tissues of HPC mice. This pathway is a critical regulator of cell proliferation, growth, metabolism, and motility. In human cancers, genetic alterations in this pathway are frequent, and its components represent important molecular targets for therapy.31,32In vitro experiments confirmed that CCNE1 promoted HCC cell proliferation, migration, invasion, and survival via PI3K/Akt activation. This mechanistic link offers actionable targets for therapeutic development in HCC. Pharmacological inhibition of the PI3K/Akt pathway effectively reversed CCNE1-driven malignant phenotypes in HCC cells, suggesting that combining CCNE1-targeted agents with existing kinase inhibitors may enhance therapeutic efficacy.
In recent years, immune cell therapy has shown remarkable efficacy in cancer treatment. However, immunosuppressive cells in the TME limit its clinical benefits. In particular, the crosstalk between cancer cells and TAMs allows cancer cells to evade immune defenses and facilitates cancer progression.33 Li and colleagues showed that NLRP7 promotes colorectal cancer progression by inducing TAM recruitment and pro-tumor M2-like macrophage polarization.34 A study by Xu et al.35 proved that abundant M2 TAMs in HER2/neu+ breast tumors represent a barrier to anti-HER2/neu antibody therapy. In the present study, immunohistochemical analysis showed increased macrophage infiltration and VEGF expression in the liver tissues of HPC mice. Furthermore, in vitro co-culture experiments revealed that CCNE1 overexpression in HCC cells promotes macrophage polarization toward the M2 phenotype, partially enhancing its carcinogenic effect. TAMs exhibit plasticity, and their functional roles are regulated by molecules in the TME.36 Chemokines are central mediators of the crosstalk between tumor cells and TAMs, coordinating TAM recruitment and polarization.37 Colony-stimulating factor-1 (CSF1) and CSF1 receptor are critical ligand–receptor pairs involved in macrophage differentiation and survival. Several studies have shown that blocking CSF1 or its receptor can repolarize TAMs from the M2 to the M1 phenotype and increase cancer cell sensitivity to immunotherapies, such as PD-L1 blockade.38,39 Our data revealed that CCNE1 induces M2 polarization of TAMs via CCL2/CCL5 secretion, thereby fostering an immunosuppressive TME. This suggests that neutralizing CCL2/CCL5 with monoclonal antibodies or CCR5 antagonists could reverse TAM polarization and work synergistically with immune checkpoint inhibitors (ICIs) such as anti–PD-1/PD-L1 antibodies. This combination strategy could enhance T-cell infiltration and help overcome ICI resistance in HCC.
In this study, the in vitro experiments primarily utilized HepG2 and Huh7 cell lines. It is important to note that the origin of HepG2 remains controversial, as it has been suggested to derive from hepatoblastoma rather than HCC.40 However, HepG2 remains widely employed in HCC research due to its established utility in modeling hepatocellular carcinogenesis.41,42 Importantly, the experimental results from Huh7 cells confirmed the functional role of CCNE1 in HCC progression. Future studies will incorporate additional validated HCC cell lines to further corroborate these findings.
Conclusions
This study identifies CCNE1 as a pivotal driver of HPC-to-HCC progression, playing multifaceted roles in tumor cell survival, invasion, and immune evasion. Its expression is positively correlated with early vascular invasion and late distant metastasis in HCC. Mechanistically, CCNE1 promotes tumorigenesis via PI3K/Akt pathway activation and fosters an immunosuppressive microenvironment through CCL2/CCL5-mediated TAM infiltration and M2 polarization. These findings highlight CCNE1 as a promising biomarker for early HCC diagnosis and a potential therapeutic target for disrupting both tumor-intrinsic signaling and the immunosuppressive microenvironment. However, several limitations must be acknowledged. First, although our bioinformatic analyses of TCGA and GEO datasets validate CCNE1’s clinical relevance, prospective studies with longitudinal HPC-to-HCC cohorts are needed to confirm its predictive value. Second, the functional crosstalk between CCNE1 and other signaling pathways or molecules remains unexplored. Finally, preclinical models (e.g., CCNE1-transgenic mice) are essential to validate its causal role in HPC progression and to evaluate targeted therapies in vivo. Future studies should confirm these findings in longitudinal cohorts and preclinical models to translate CCNE1’s diagnostic and therapeutic potential into clinical practice. By bridging mechanistic insights with clinical needs, this work lays the foundation for precision medicine strategies to intercept HCC at its precancerous stage.
Declarations
Ethical statement
All animal experiments were approved by the Animal Care and Use Committee of The First Affiliated Hospital of Zhengzhou University (No. 2019-KY-21). All animals received human care.
Data sharing statement
The datasets generated for this study are available from the corresponding author upon reasonable request.
Funding
None to declare.
Conflict of interest
The authors have no conflict of interests related to this publication.
Authors’ contributions
Study concept (WG), study design (WG, KZ, XH, LY), experiment performance, data acquisition, data analysis (KZ, XH, LY), drafting of the manuscript (KZ), and revision of the manuscript (WG). All authors contributed to the article and approved the final version.