Aurora-A promotes lenvatinib resistance experimentally through hsa-circ-0058046/miR-424-5p/FGFR1 axis in hepatocellular carcinoma

Abstract

Objective:

This study aimed to investigate whether the dysregulation of Aurora-A is involved in lenvatinib resistance in hepatocellular carcinoma.

Methods:

Bioinformatics tools and drug sensitivity assays were used to investigate the association between Aurora-A expression level and lenvatinib resistance in hepatocellular carcinoma cell lines. Cell function experiments had performed after treatment with lenvatinib and/or a selective Aurora-A inhibitor (MLN-8237). CircRNA microarray, RIP, RNA pull-down, and dual-luciferace reporter assay were performed to identify the downstream molecular mechanism of Aurora-A dysregulation.

Results:

Aurora-A expression was positively correlated with lenvatinib resistance in hepatocellular carcinoma cells. The Aurora-A selective inhibitor MLN-8237, in combination with lenvatinib, synergistically inhibited hepatocellular carcinoma cell proliferation in vitro and vivo, suggesting the Aurora-A might be a potential therapeutic target for lenvatinib resistance. Mechanistically, Aurora-A induced FGFR1 expression through the hsa-circ-0058046/miR-424-5p/FGFR1 axis. Aurora-A promotes lenvatinib resistance through hsa-circ-0058046/miR-424-5p/FGFR1 axis in hepatocellular carcinoma cells. The simultaneous inhibition of FGFR1 by the Aurora-A inhibitor MLN-8237 and lenvatinib overcame lenvatinib resistance in hepatocellular carcinoma cells.

Conclusion:

Collectively, our findings indicate that Aurora-A promotes lenvatinib resistance through the hsa-circ-0058046/miR-424-5p/FGFR1 axis in hepatocellular carcinoma (HCC) cells. These results suggest that Aurora-A may serve as a therapeutic target for HCC patients exhibiting lenvatinib resistance. Furthermore, the combination of lenvatinib and MLN-8237 shows potential for clinical trials aimed at overcoming lenvatinib resistance.

Keywords

lenvatinib resistance Aurora-A hepatocellular carcinoma Aurora-A kinase inhibitor hsa-circ-0058046 miR-424-5p FGFR1 MLN-8237

Introduction

Hepatocellular carcinoma (HCC) is the most prevalent type of liver cancer and ranks as the fourth leading cause of cancer-related deaths worldwide.¹ HCC has been proven to be independently linked to liver disease and major risk factors include hepatitis B virus (HBV) or hepatitis C virus (HCV)^2,3 infection, cirrhosis,⁴ and genetic causes.⁵ Although recent technological advancements in the early diagnosis of hepatocellular carcinoma (HCC) have demonstrated survival benefits, a significant proportion of HCC patients present at advanced stages and are therefore not suitable for locoregional therapy.^6,7 Moreover, advanced HCC is chemo- and radio-resistant, which limiting therapeutic options for these patients.⁸ Thus, systemic therapy is a first-line option for patients with advanced, unresectable HCC.⁹ Sorafenib is the first tyrosine kinase inhibitor (TKI) approved as first-line systemic treatment for HCC. It took a decade for alternative single-agent therapies, lenvatinib.¹⁰ Lenvatinib, an oral multikinase inhibitor, suppresses the activity of fibroblast growth factor (FGF) receptors (FGFR1–4), vascular endothelial growth factor (VEGF) receptors (VEGFR 1–3), platelet-derived growth factor (PDGF) receptors, KIT, and RET.¹¹ As reported at the 2021 ASCO meeting,¹² in real-world clinical applications, lenvatinib demonstrated comparable anti-tumor efficacy to sorafenib, despite differences in patient population and pathological stage compared with the REFLECT trial. Despite the positive clinical outcomes, lenvatinib resistance is a crucial factor limiting the long-term survival of HCC patients.¹³ Therefore, there is an urgent need to investigate the mechanisms of lenvatinib resistance and identifying molecular biomarkers that represent the degree of resistance of lenvatinib or predicts patient response to lenvatinib therapy.

Aurora kinase-A (Aurora-A) belongs to serine/threonine kinase family, which shares a highly conserved catalytic domain containing auto-phosphorylation sites. Aurora-A, plays an oncogenic role in various cancers.¹⁴ Furthermore, Aurora-A is commonly overexpressed in HCC and is associated with malignant traits, such as high-grade (grade II–IV) and advanced-stage (stage IIIB–IV) tumors, p53 mutations, infrequent beta-catenin mutations, and poor outcomes.¹⁵

MLN-8237 is a well-studied selective oral small-molecule inhibitor of Aurora-A that has demonstrated promising results against advanced solid tumors in several clinical trials.¹⁶ In addition to monotherapies, trials investigating the efficacy of combination therapies have been conducted. MLN-8237 exhibited promising responses in combination with the VEGFR inhibitor pazopanib,¹⁷ estrogen receptor inhibitor fulvestrant,¹⁸ modified FOLFOX,¹⁹ and chemotherapy drugs in various malignancies. Furthermore, various trials investigating the use of MLN-8237 combined with the mTOR1/2 inhibitor MLN-0128, anti-metabolite gemcitabine, EGFR inhibitor osimertinib, proteasome inhibitor bortezomib, and CD20 type I antibody rituximab are ongoing.²⁰ Taken together, research demonstrates that MLN-8237 has substantial potential for use in clinical practice. However, little is known about the anti-cancer efficacy of MLN-8237 in HCC.

It is well known that non-coding RNAs (ncRNAs) were accumulate in common diseases, including liver cancer.²¹ ncRNAs play an important role in multiple cellular processes in HCC, such as cell proliferation, migration, apoptosis, angiogenesis, immune response, and drug resistance.²²

MicroRNAs (miRNAs) are a class of non-coding single-stranded RNA molecules that have been extensively investigated. MiRNAs regulate gene expression by degrading their target mRNAs or suppressing translation by binding to the 3′untranslated regions of mRNAs.²³ Each miRNA can repress several target genes, making them powerful regulators of gene expression.²⁴ Importantly, miRNAs can exhibit both tumor-suppressive and oncogenic functions in the progression of HCC. For instance, miR-424-5p serves as a tumor suppressor by modulating TRIM29, a protein implicated in cell proliferation and invasion within HCC.²⁵ On the contrary, serum miR-21-5p has been shown to promote NASH-related hepatocarcinogenesis,²⁶ while tumor-derived exosomal miRNA-21 contributes to tumor progression by downregulating PTEN in HCC.²⁷

Circular RNAs (circRNAs) are a circular type of ncRNAs with important biological functions. Recent research has revealed that circRNAs play pivotal roles in both pathological and physiological processes, including tumorigenesis and the progression of tumors.²⁸ Moreover, circRNAs have the capacity to influence the tumor microenvironment through intercellular communication, owing to their high abundance in exosomes.²⁹ Increasing research has demonstrated that circRNAs play either oncogenic or tumor-suppressive roles in cancers by sponging microRNAs, such as circ0030018³⁰ and circROBO1.³¹

In this study, we examined the relationship between Aurora-A overexpression in HCC and resistance to lenvatinib. Furthermore, we investigated whether the selective Aurora-A inhibitor MLN-8237 could reverse drug resistance and explored its potential molecular mechanisms. Given the growing evidence highlighting the critical role of circRNAs in tumor progression, we aimed to determine whether any specific circRNA is involved in these underlying mechanisms.

Materials and methods

Cell culture and chemicals

Human HCC lines (HepG2 and Huh-7) and human umbilical vein endothelial cells (HUVEC) were purchased from the National Collection of Authenticated Cell Cultures (Shanghai, China). All cells were maintained according to the manufacturer’s instructions. Lenvatinib, MLN-8237 (alisertib), and Maslinic acid were purchased from MedChemExpress (Shanghai, China).

In vivo, the drugs were prepared as a stock solution at a concentration of 20.8 mg/mL in dimethyl sulfoxide (DMSO). DMSO stock solution was diluted in a ratio of 1:9 with 20% SBE-β-CD in saline to achieve a uniform suspension at a final concentration of 2.08 mg/mL.

Cell viability and drug sensitivity assay

Drug sensitivity was determined based on IC₅₀ value (50% decrease in absorbance normalized to that of the control) measured using the CCK-8 assay (MCE, USA). Briefly, cells were seeded in 96-well plates (3,000 cells/well) and incubated overnight. They were then treated with lenvatinib or MLN-8237 at various concentrations for 48 h. To evaluate cell proliferation, 10 μL of CCK-8 reagent was added to each well and incubated for 2 h at 37°C. Absorption was evaluated at 450 nm using a microplate reader (Tecan, Switzerland). The synergistic effect of the two drugs were determined based on combination index (CI) values, calculated using CompuSyn software.³² CI values of <0.8, 0.8, and >0.8 indicated synergistic, additive, and antagonistic effects, respectively.

RNA extraction and quantitative real-time PCR

Total RNA from HCC cell lines was extracted using TRIzol reagent (Takara, Japan), and nuclear and cytoplasmic fractions were extracted using a PARIS Kit (Thermo Scientific, USA). Genomic DNA (gDNA) was isolated using the FastPure DNA Isolation kit (Vazyme, China) according to the manufacturer’s instructions. The concentration and purity of the RNA samples were measured using a Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific, USA). For mRNA and circRNA, reverse transcription was performed using the PrimeScript RT Master Mix kit (Takara) with random primers. For the miRNA, reverse transcriptions was performed using the miRNA 1st Strand cDNA Synthesis Kit (Vazyme) with specific stem-loop primers. Complementary DNA (cDNA) amplification was performed using TB Green Premix Ex Taq II (Takara) with a Roche LightCycler^® 480II PCR instrument (Basel, Switzerland). Divergent primers were used to detect back-splice junction of circRNAs, and convergent primers were used to detect linear mRNA. GAPDH and U6 were used as internal controls. The relative RNA expression levels were calculated using the 2–ΔΔCT method, with all samples analyzed in triplicate.

CircRNAs microarray and data analysis

The circRNAs microarray was performed by Shanghai Biotechnology Corporation (Shanghai, China). The “fold change” between the groups for each circRNA was used to compute the circRNA differences between the Aurora-A-overexpressing or Aurora-A-knockdown HepG2 cells compared to control HepG2 cells. The statistical significance of the difference was estimated by t-test. The differentially expressed circRNAs (|fold changes| ≥ 1.5 and p-values ≤ 0.05) were subjected to further analysis.

RNase R treatment

Total RNA (10 μg) was incubated with or without 3 U/ug of RNase R (JISAI Biology, China) at 37°C for 10 min. Following RNase R treatment, reverse transcription (RT) of total RNA into cDNA was performed using the PrimeScript RT Master Mix kit (Takara). Subsequently, nucleic acid electrophoresis was employed to evaluate the expression levels of circRNA and GAPDH mRNA.

Sanger sequencing

Sanger sequencing was conducted by Tsingke Biotech (Nanjing, China) to confirm the amplification products of circRNAs.

Cell transfection

shRNAs targeting Aurora-A and Aurora-A-overexpressing lentivirus were synthesized by GENECHEM (Shanghai, China). Small interfering RNA (siRNA) targeting the junction region of the hsa-circ-0058046 sequence, hsa-circ-0058046-overexpressing plasmids, and FGFR1-overexpressing plasmids were purchased from RIBOBio (Guangzhou, China). The siRNAs targeting FGFR1 were synthesized by GenScript (Nanjing, China). The hsa-miR-424-5p mimic was designed and synthesized by Realgene (Nanjing, China). For transient transfection, cells were transfected with Lipofectamine 2000 reagent (Invitrogen), according to the manufacturer’s instructions. To establish a stable cell line, a lentiviral vector was introduced into the HCC cells via transient transfection. After 6 h, the cell culture medium was replaced, and viral supernatants were collected after 48 h. The supernatant was then collected and filtered through a 0.22-mm filter. Cells were infected at approximately 70% confluence in complete medium supplemented with 8 mg/mL polybrene (Sigma), followed by selection with 0.5 mg/mL puromycin (Sigma). The overexpression efficiency was determined using quantitative real-time PCR. The sequences of the siRNAs used were as follows:

siFGFR1-1:CGGUCAUCGUCUACAAGAUdTdT;

siFGFR1-2 :GAUGGUCCCUUGUAUGUCAdTdT;

si-h-hsa_circ_0058046_001: CCACTGCTCAGTACATGAA;

si-h-hsa_circ_0058046_002: GCTCAGTACATGAAGCTTG; and

si-h-hsa_circ_0058046_003: CAGTACATGAAGCTTGCAA.

Western blot assay

The Cells were lysed using RIPA buffers (Beyotime Biotechnology, Shanghai, China). Proteins were prepared and quantified using bicinchoninic acid (BCA) analysis (Beyotime, China). Equal amounts of protein were separated by 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis and transferred onto polyvinylidene fluoride (PVDF) membranes (Millipore, USA). The protein was blocked with 5% skim milk powder and incubated with primary antibody at 4°C overnight. The prepared membranes were incubated with secondary antibodies for 2 h. Finally, the blots were visualized using ECL chemiluminescent reagent (Millipore, USA). The primary antibodies used were anti-Aurora-A (1:1000, ab13824, Abcam) and anti-GAPDH (1:10000, 60004-1-Ig, Proteintech).

Cell apoptosis assay

Apoptosis in HepG2 and Huh-7 cells was determined using an FITC/Annexin V apoptosis detection kit (KeyGEN Biotech, China). Briefly, cells were seeded in a 6-well plate (1 × 10⁶ cells/well) for 24 h and then treated with lenvatinib, MLN-8237, or a combination of the two for a further 24 h. The cells were then harvested and resuspended in binding buffer. Next, 100 μL of cell solution was transferred to a 1.5 mL centrifuge tube, and 5 μL of FITC Annexin V and 5 μL of PI were added to each tube. Finally, the tubes were incubated in the dark for 15 min at room temperature, and 400 μL of binding buffer was added to each tube before analysis via flow cytometry. The data were analyzed using FlowJo 7.6.1 software.

5-ethynyl-20-deoxyuridine (EdU) incorporation assay

The EdU assay was performed to assess cell proliferation using the Cell-Light EdU DNA Cell Proliferation Kit (KeyGEN Biotech) according to the manufacturer’s protocol. HCC cells were treated with lenvatinib, MLN-8237, or a combination of the two for 48 h in 96-well plates. The cells were incubated with 50 mM EdU solution for 2 h and fixed using 4% paraformaldehyde. Hoechst 33342 was used to stain the nucleic acids within the cells. EdU cell lines were photographed and counted using an Olympus FSX100 microscope (Olympus, Tokyo, Japan).

Cell migration assays

The migratory ability of HCC cells was assessed using wound healing and Transwell migration assays. For the wound healing assay, HCC cells were treated with lenvatinib, MLN-8237, or their combination in 6-well plates for 24 h. When the cells reached 100% confluency, a yellow pipette tip was used to create a clear wound in the cell layer. Images were captured using an optical microscope system at 0, 24, 48, and 72 h after injury.

For Transwell assays, HCC cells were treated with lenvatinib, MLN-8237, or their combination in 6-well plates for 24 h, according to the manufacturer’s protocol. The drug-treated cells were then seeded in the upper chambers with 200 µL of serum-free medium, and the bottom chamber was filled with medium containing 10% FBS. After a 24 h incubation, the remaining cells on the bottom of the upper chamber were fixed with 4% paraformaldehyde for 25 min, stained with 0.1% crystal violet for 25 min, and counted under a microscope at 40× magnification (Nikon).

Dual-luciferase reporter assay

The sequences of the hsa-circ-0058046 promoter and its corresponding mutant were designed, synthesized, and inserted into the luciferase reporter vector by RiboBio (Guangzhou, China). Luciferase activity in the transfected 293T cells was measured using a Dual-Luciferase Reporter Assay System (Promega, USA) after 48 h, according to the manufacturer’s instructions.

RNA immunoprecipitation (RIP) and RNA pull down assay

The RIP assay was performed using a Magna RIP RNA-Binding Protein Immunoprecipitation Kit (Millipore), according to the manufacturer’s instructions. Antibodies against AGO2 (ab186733, USA) and IgG (ab172730, USA) for the RIP assays were purchased from Abcam.

For the RNA pull-down assay, in vitro biotin-labeled hsa-circ-0058046 and control probes were synthesized by RiboBio (Guangzhou, China). RNA pull-down assays were performed using the Pure Binding™ RNA Protein Pull-down Kit (Guangzhou Geneseed Biotech Co., Ltd.; cat. no. P0201) according to the manufacturer’s instructions.

Tube formation assay

HCC cells were seeded in 6-well plates and treated with hsa-circ-0058046 plasmids. After 48 h, the cell culture media was collected and concentrated 10-fold using ultrafiltration spin columns (Millipore, Billerica, MA, USA). For the tube formation assay, HUVEC cells were seeded in 96-well plates pre-coated with Matrigel. The concentrated cell culture medium was added to the wells. After a 12 h incubation, the lymphatic tubes were photographed using an inverted microscope, and the number and area of the completed tubule structures were measured and quantified by Image J software.

Mouse xenografts

The in vivo assay was approved by the Animal Management Committee of Nanjing University Affiliated Jinling Hospital. All experimental procedures and animal care were performed in accordance with the institutional ethics guidelines for animal experiments. For the in vivo study, approximately 6 × 10⁶ HepG2 cells were injected subcutaneously into the right flank of BALB/c nude mice (5 weeks old, female). When the tumor volume reached approximately 50 mm³, the tumor-bearing mice were randomized into four groups: control group (saline solution, administered daily, intragastrically), lenvatinib group (30 mg/kg, administered daily, intragastrically), MLN-8237 group (30 mg/kg, administered daily, intragastrically), and lenvatinib combined with MLN-8237 group. The tumor volume was measured using a caliper and calculated using the following formula: tumor volume = 1/2(length × width²). Three weeks after injection, the mice were sacrificed, and subcutaneous tumor tissues were analyzed for tumor weight and immunohistochemical staining.

Bioinformatics analysis

The drug sensitivity profiles obtained from the depmap portal of the Cancer Cell Line Encyclopedia (https://depmap.org/portal/). The circRNA sequence obtained from circBank databse (http://www.circbank.cn/#/home). Starbase (ENCORI) (https://rnasysu.com/encori/), RNAhybrid (https://bibiserv.cebitec.uni-bielefeld.de/rnahybrid), and miRanda. (http://www.microrna.org/microrna/home.do) databases were used to predict microRNAs that might bound to has_circ_0058046. JASPAR database (https://jaspar.elixir.no/) was applied to predic potential transcript factor.

Statistical analysis

The experimental data were analyzed using GraphPad Prism 7 and SPSS 20.0 (IBM, SPSS, Chicago, IL, USA). Differences between groups were analyzed using the Student’s t-test or ANOVA. Pearson’s correlation analysis was used to analyze the correlations between groups. Statistical significance was set at p < 0.05. All in vitro experiments had triplicated.

Results

Aurora-A inhibitor MLN-8237 combined with lenvatinib synergistically inhibits HCC cell proliferation

The area under the dose response curve (AUC) of lenvatinib in HCC cell lines was positively correlated with the gene copy number and expression level of AURKA, based on drug sensitivity profiles from the Cancer Cell Line Encyclopedia (CCLE) (Figure 1(a)). Pearson’s correlation analysis showed a positive correlation between Aurora-A protein expression levels and IC₅₀ values across four HCC cell lines (Figure S1(a–d)), suggesting that in HCC cells, higher basal expression levels of Aurora-A correspond with greater resistance to lenvatinib.

Figure 1.

MLN-8237 combined with lenvatinib synergistically inhibits hepatocellular carcinoma (HCC) cell proliferation. (a) Pearson’s regression analysis was conducted to examine the correlation between the area under the dose response curve (AUC) of lenvatinib and the AURKA gene copy number in the CCLE cell line panel. (b) EDU assays measured the proliferation of Huh-7 and HepG2 cells after treatment with lenvatinib, MLN-8237, or a combination of both for 48 (200× magnification). (c–d) Wound healing (c) and Transwell migration assays (d) were used to evaluate Huh-7 and HepG2 cell migration in various treatment groups (40× magnification). (e) An annexin V-FITC apoptosis detection assay was used to measure apoptosis in Huh-7 and HepG2 cells after treatment with lenvatinib and/or MLN-8237 for 48 h. (f) Six-week-old nude mice were transplanted with HepG2 cells and administered lenvatinib and/or MLN-8237 via oral gavage for 14 days. Tumor volumes were measured using an electronic vernier caliper. Red arrows: EDU-positive cells. Blue arrows: Hoechst 33342 staining indicating cell nuclei (200× magnification).

Drug combination index (CI) values suggested a synergistic effect in HepG2 cells (CI = 0.45; lenvatinib: MLN-8237 = 3:4) and a mild synergistic effect in Huh-7 cells (CI = 0.75; lenvatinib: MLN-8237 = 1:3), as calculated using the CompuSyn software (Figure S1(e and f)).

Therefore, we assessed the anti-proliferative efficacy of combined drug stimulation using EDU and CCk-8 assays (Figure 1(b); Figure S2(a)). The results showed that the viability of HepG2 and Huh-7 cells in the combination drug group was significantly reduced compared with that in the single-drug groups. Wound healing and Transwell migration assays showed a remarkable decrease in migration activity in the combination drug group, whereas a modest reduction was observed in the lenvatinib- and MLN-8237-alone groups (Figure 1(c and d); Figure S2(b)). Furthermore, the combination drug group exhibited elevated apoptosis, as determined by flow cytometry (Figure 1(e), Figure S2(c)).

Next, we examined whether MLN-8237 enhances the anti-tumor efficacy of lenvatinib in vivo. The results showed that combination therapy with MLN-8237 and lenvatinib inhibited tumor growth more potently than treatment with MLN-8237 or lenvatinib alone (Figure 1(f)). Furthermore, IHC staining revealed that the combination therapy decreased Ki67 expression, while the TUNEL assay revealed an increased apoptotic rate (Figure S2(d and e)). Collectively, these results indicated that inhibiting Aurora-A with MLN-8237 in combination with lenvatinib synergistically inhibited HCC cell proliferation.

Aurora-A induces lenvatinib resistance by positively regulating hsa-circ-0058046

To investigate the influence of Aurora-A on lenvatinib resistance, we used a circRNA expression microarray to screen HepG2 cells after altering Aurora-A expression levels (Figure S3(a and b)). A total of 2627 circRNAs were identified that were differentially expressed in Aurora-A-overexpressing or Aurora-A-knockdown HepG2 cells compared to control HepG2 cells (1354 differentially expressed circRNAs in the Aurora-A-overexpressing group and 1273 in the Aurora-A-knockdown group; fold change >2) (Figure 2(a); Figure S3(c and d)). qRT-PCR analysis revealed that hsa-circ-0058046 expression was markedly upregulated in the Aurora-A-overexpressing group, whereas it was decreased in the Aurora-A-knockdown group (Figure 2(b)). Furthermore, hsa-circ-0058046 was highly expressed in HCC cell lines compared to that in the normal hepatocyte cell line L-02 (Figure S3(e)).

Figure 2.

Aurora-A positively regulates hsa-circ-0058046 expression. (a) Heatmap showing significant differentially expressed circRNA in Aurora-A-overexpressing and Aurora-A-knockdown HepG2 cells. (b) qRT-PCR assay confirmed hsa-circ-0058046 expression levels in Aurora-A-overexpressing and Aurora-A-knockdown HCC cells. (c) Schematic representation of the genetic position of hsa-circ-0058046. (d) Gel electrophoresis confirmed the presence of hsa-circ-0058046 in HCC cells. (e) Gel electrophoresis and RT-PCR assay revealed changes in hsa-circ-0058046 expression after RNase R treatment. (f–g) Dual-Luciferase reporter assay performed in 293T cells after co-transfection with negative control or NF-κB plasmids and wild-type (WT) or mutant (MUT) luciferase reporter vectors. The relative luciferase activity is presented as the relative hRluc/hluc ratio. (h) A CCK-8 assay was used to measure the IC₅₀ of lenvatinib in Huh-7 and HepG2 cells after hsa-circ-0058046 plasmid transfection for 24 h. (i) A CCK-8 assay was used to measure the IC₅₀ of lenvatinib in Aurora-A-overexpressing Huh-7 and HepG2 cells after hsa-circ-0058046-si transfection for 24 h.

We further examined the characteristics of the hsa-circ-0058046 as a circRNA. The hsa-circ-0058046 formed a 282 nt circular transcript derived from exons 6 and 7 of the BARD1 gene (human reference genome (GRCh37/hg19) database). Sanger sequencing confirmed that the divergent primers targeting the back-spliced junction site could amplify hsa-circ-0058046 (Figure 2(c)). Moreover, nucleic acid electrophoresis results showed that divergent primers could amplify hsa-circ-0058046 only in cDNA but not in gDNA (Figure 2(d)). RNase R treatment, used to measure the circRNA stability, demonstrated that linear-circ-0058046 was significantly degraded after RNase R treatment, whereas hsa-circ-0058046 remained resistant (Figure 2(e)). These results confirm that hsa-circ-0058046 is a circRNA. The specific primers were listed in Table 1.

Table 1.

The sequences of specific primers.

Primer	Sequence
AURKA forward	GGAATATGCACCACTTGGAACA
AURKA reverse	TAAGACAGGGCATTTGCCAAT
hsa_circ_0058046 forward	TCGCTATTGCTGCTACCAGAG
hsa_circ_00580464 reverse	GCTTCATGTACTGAGCAGTGG
linear_0058046 forward	AAGCTTGCAATCATGGGCAC
linear_0058046 reverse	ATAATCGACAGGCCGCAGAC
BARD1 forward	GGAAGAGCTTGGCCGGTTTC
BARD1 reverse	TTCGGATGAAAGGCTCCTCG
pre-BARD1 forward	CACTTCACGATGCAGCCAAG
pre-BARD1 reverse	AGTCTGCTTTATCACACACCTTGA
U6 forward	ATTGGAACGATACAGAGAAGATT
U6 reverse	GGAACGCTTCACGAATTTG
GAPDH forward	CCAGGGCTGCTTTTAACTCTGGTAAAGTGG
GAPDH reverse	ATTTCCATTGATGACAAGCTTCCCGTTCTC

We then performed promoter region analysis using JASPAR database to identify potential transcription factors promoted hsa-circ-0058046 expression at the transcriptional level. The results suggested that the transcription factor NF-κB may be a candidate because it has two binding sites within the 2kb promoter region. NF-κB is a well-established novel transcription factor that plays an essential role in HCC progression.^33,34 Notably, it had been reported that Aurora-A promotes NF-κB activation by inhibiting IκBα phosphorylation.³⁵

To verify these result, we initially perforemed a qRT-PCR assay to determine whether NF- κB alters hsa-circ-0058046 expression levels. NF-κB (RelA/p65) overexpression increased hsa-circ-0058046 expression levels, while treating HCC cells with Maslinic acid, a selective inhibitor of p65 DNA binding, decrease hsa-circ-0058046 expression levels (Figure S4(a–c)). Notably, the mRNA levels of the host gene BARD1 remained unchanged (Figure S4(d)). Following this, we constructed a BARD1 gene promoter luciferase reporter by inserting a 2 kb 5′ promoter region of BARD1 containing an NF-κB binding site into a pGL3 luciferase backbone, along with another version with a mutated NF-κB binding site (Figure 2(f)). As anticipated, the luciferase assay revealed that NF-κB significantly increased luciferase activity in 293T cells transfected with the wild-type (WT) promoter but not in cells transfected with the mutant (MUT) hsa-circ-0058046 promoter (Figure 2(g)).

A drug sensitivity assay showed that hsa-circ-0058046 overexpression in HCC cells significantly increased the lenvatinib IC₅₀ value (Figure 2(h)). A rescue assay revealed that the decrease in HCC cell viability induced by lenvatinib stimulation was partially reversed by hsa-circ-0058046 overexpression (Figure S4(e)). Knocking down hsa-circ-0058046 in Aurora-A-overexpressing HCC cells partially reversed its Aurora-A proliferation-promoting effect (Figure S4(f and g)) and suppressed its capacity to induce lenvatinib drug resistance (Figure 2(i)).

Taken together, these results suggest that Aurora-A induces lenvatinib resistance by positively regulating hsa-circ-0058046 expression.

Hsa-circ-0058046 promotes HCC cell viability, migration and tube formation

Functional assays revealed that hsa-circ-0058046 over-expression in Huh-7 and HepG2 cells increased cell viability (Figure 3(a and b); Figure S5(a)). Furthermore, wound healing and Transwell migration assays revealed that the migration ability of Huh-7 and HepG2 cells was significantly increased by hsa-circ-0058046 overexpression (Figure 3(c and d)). We hypothesized that hsa-circ-0058046 may effect angiogenesis based on the observation that hsa-circ-0058046 induced lenvatinib resistance. As expected, HUVEC tube formation significantly increased in the hsa-circ-0058046 overexpression group (Figure 3(e)).

Figure 3.

hsa-circ-0058046 promotes HCC proliferation, migration, and angiogenesis. (a) Representative images of Huh-7 and HepG2 cells obtained by fluorescence microscopy showing the effects of transfection with hsa-circ-0058046 or NC plasmids for 24 h on cell growth. Red arrows: EDU-positive cells. Blue arrows: Hoechst 33342 staining indicating cell nuclei (200× magnification). (b) A CCK-8 assay was used to measure cell viability 4 days after hsa-circ-0058046 plasmid transfection. (c) Representative optical microscopy images of Huh-7 and HepG2 cells showing wound healing 48 h after transfection with hsa-circ-0058046 or NC plasmid (40× magnification). (d) A Transwell migration assay was used to evaluate Huh-7 and HepG2 cell migration following hsa-circ-0058046 plasmid transfection for 48 h. The percentage of the migrated cell area was calculated based on microscopy images (40× magnification). (e) HUVEC cells treated with cell supernatant from hsa-circ-0058046 overexpressing or negative control cells. Tube formation was evaluated using optical microscopy after 48 h of treatment with cell supernatant (200× magnification).

Hsa-circ-0058046 regulates FGFR1 by sponging miR-424-5p

Given that the subcellular localization of molecules can indicate their biological functions, we performed subcellular fractionation location analysis, which showed that hsa-circ-0058046 was primarily localized in the cytoplasm (Figure 4(a)) rather than in the nucleus. This suggests that hsa-circ-0058046 may potentially function as a competing endogenous RNA (ceRNA) that regulates other RNA transcripts by competing for shared miRNAs. Therefore, we utilized multiple databases to identify the potential candidate miRNAs whose functions might be linked to the HCC lenvatinib resistance and hsa-circ-0058046 expression in HCC. MiR-424-5p was selected for further validation (Figure 4(b)) based on the overlap of predictions from three miRNA target prediction tools (ENCORI, RNAhybrid, and miRanda)^36–38 (Figure S5(b)). In addition, TCGA and GEO databases showed that the expression level of miR-424-5p in HCC was significantly lower than that in normal liver tissue (Figure S5(c)), suggesting that miR-424-5p might be involved in the HCC progression.

Figure 4.

hsa-circ-0058046 sponges miR-424-5p. (a) Nuclear and cytoplasmic fractions from Huh-7 and HepG2 cells were extracted using a PARIS Kit assay. The abundance of hsa-circ-0058046 was evaluated by qRT-PCR. GAPDH RNA and U6 RNA were used as positive controls for RNA distributed in the cytoplasm and nucleus, respectively. (b) Venn diagram showing the predicted target miRNAs retrieved from the miRANDA, RNAhytrid, and ENCORI databases. (c) qRT-PCR was used to measure miR-424-5p following hsa-circ-0058046 overexpression in Huh-7 and HepG2 cells. (d) Ago2-RIP assay and qRT-PCR were used to measure the enrichment of hsa-circ-0058046 and miR-424-5p in the Ago2-RNA complex after transfection with the miR-424-5p mimic. (e) RNA pull-down assay was performed in Huh-7 and HepG2 cells, followed by qRT-PCR to assess the enrichment of hsa-circ-0058046 and miR-424-5p pull down by hsa-circ-0058046 probe. (f) qRT-PCR was used to measure the expression of lenvatinib drug targets (KDR, RET, PDFGRA, FGFR1, FGFR2, FGFR3, and FGFR4) expression in Huh-7 and HepG2 cells following miR-424-5p mimic transfection. (g) Scheme of WT and MUT miR-424-5p binding sites on FGFR1. (h) Dual-Luciferase reporter assay performed in 293T cells after co-transfection with miR-424-5p mimic (or NC mimic) and luciferase reporter vectors (WT or MUT). The relative luciferase activity is presented as the relative hRluc/hluc ratio.

qRT-PCR assay verified that hsa-circ-0058046 overexpression decreased miR-424-5p expression in Huh-7 and HepG2 cells (Figure 4(c)). We examined the potential regulation of miR-424-5p by hsa-circ-0058046 by detecting the miR-424-5p in the Argonaute 2 (Ago2) complex using RNA interaction precipitation (RIP) assays. As anticipated, both Argonaute 2 and hsa-circ-0058046 were pulled down by the Argonaute 2 antibody (Figure S5(d)); however, miR-424-5p overexpression increased hsa-circ-0058046 levels in the Argonaute 2 complex (Figure 4(d); Figure S5(e)). We then designed a biotinylated probe specific to hsa-circ-0058046, which pulled down both hsa-circ-0058046 and the miR-424-5p in a RNA pull-down assay (Figure 4(e)). The specific probe sequences were listed in Table 2. These results indicated that hsa-circ-0058046 functions as a sponge for miR-424-5p.

Table 2.

The sequences of specific probes.

Probe	Sequence
Ribo™ hsa_circ_0058046(3bio)_ChIRP_Probe_1	AAGCTTCATGTACTGAGCAG-/3bio/
Ribo™ hsa_circ_0058046(3bio)_ChIRP_Probe_2	GCAAGCTTCATGTACTGAGC-/3bio/
Ribo™ hsa_circ_0058046(3bio)_ChIRP_Probe_3	TTGCAAGCTTCATGTACTGA-/3bio/

Given that hsa-circ-0058046 promoted lenvatinib resistance in HCC cells and functioned as a sponge for miR-424-5p, we hypothesized that miR-424-5p targets the drug targets of lenvatinib (KDR, FLT1, FLT4, KIT, RET, PDFGRA, and FGFR1-4). Using the Starbase database, seven targets (KDR, RET, PDFGRA, FGFR1, FGFR2, FGFR3, and FGFR4) were predicted to be downstream of miR-424-5p (Figure S5(f)). RT-PCR was used to assess changes in the expression levels of target genes following miR-424-5p overexpression. The results showed that FGFR1 expression levels were significantly decreased in both Huh-7 and HepG2 cells after transfection with miR-424-5p mimic (Figure 4(f)). To investigate the relationship between miR-424-5p and FGFR1, we constructed two luciferase reporter vectors containing FGFR1 with wild-type (WT) or mutated (MUT) miR-424-5p binding sites (Figure 4(g)). The luciferase reporter assay demonstrated that co-transfecting miR-424-5p mimics with WT FGFR1 significantly altered the luciferase activity (Figure 4(h)); however, this was no observed when co-transfecting miR-424-5p mimics with Mut FGFR1. These results indicated that FGFR1 is a target of miR-424-5p.

Hsa-circ-0058046 promotes lenvatinib resistance by regulating FGFR1 expression

Next, we investigated the roles of FGFR1 in HCC cell phenotypes. CCK-8 and EDU assays showed that FGFR1 significantly enhanced HepG2 and Huh-7 cells viability (Figure 5(a); Figure S6(a–c)). The drug sensitivity assay showed the lenvatinib IC₅₀ value was substantially increased after FGFR1 overexpression (Figure 5(b)). The tube formation assay illustrated that the tube formation capacity of HUVEC cells was significantly increased following treatment with supernatant from FGFR1-overexpressing HCC cells (Figure 5(c)).

Figure 5.

FGFR1 promotes HCC cells proliferation, lenvatinib resistance, and angiogenesis in HCC. (a) Representative fluorescence microscopy images of Huh-7 and HepG2 cells showing the effect of FGFR1 or NC plasmid transfection for 48 h on cell growth. Red arrows: EDU positive cells. Blue arrows: Hoechst 33342 staining indicating cell nuclei (200× magnification). (b) A CCK-8 assay was used to determine the IC₅₀ of lenvatinib in Huh-7 and HepG2 cells following transfection with the FGFR1 plasmid for 48 h. (c) HUVEC cells treated with cell supernatant from FGFR1-overexpressing or negative control cells. Tube formation was assessed using optical microscopy 48 h after treatment with cell supernatant (200× magnification). (d) An EDU viability assay was used to measure Huh-7 and HepG2 cell viability following the co-transfection of the hsa-circ-0058046 plasmid with FGFR1 siRNA for 24 h. (e) HUVEC cells treated with HCC cell supernatant were co-transfected with the hsa-circ-0058046 plasmid and FGFR1 siRNA. Tube formation was assessed following 48 h of treatment with cell supernatant by optical microscopy (200× magnification). (f) A CCK-8 assay was used to determine the IC₅₀ of lenvatinib in Huh-7 and HepG2 cells after co-transfection with the hsa-circ-0058046 plasmid and FGFR1.

To explore whether hsa-circ-0058046 exerted its biological activity by regulating FGFR1 expression, we performed a rescue assay. We synthesized small interfering RNA (si-RNA) specifically targeting FGFR1 (FGFR1-si) and confirmed that it effectively inhibited FGFR1 expression using qRT-PCR (Figure S6(d)). We then measured cell viability, tube formation, and lenvatinib resistance after co-transfection with FGFR1-si and hsa-circ-0058046 plasmids in HCC cells. The results demonstrated that FGFR1 inhibition blocked the effects of hsa-circ-0058046 on cell viability (Figure 5(d); Figure S6(e)) and tube formation capacity (Figure 5(e)). In addition, FGFR1 inhibition partially reversed the effects of hsa-circ-0058046 on lenvatinib resistance in HCC cells (Figure 5(f)). Taken together, hsa-circ-0058046 promoted HCC cells proliferation, tube formation, and lenvatinib resistance through FGFR1.

Discussion

Lenvatinib is the latest first-line tyrosine kinase inhibitor (TKI) with potent antiangiogenic activity for HCC therapy. It has demonstrated promising therapeutic efficacy in unresectable HCC.³⁹ However, the clinical effectiveness of lenvatinib is primarily limited by drug resistance.⁴⁰ Currently, there is limited understanding on the molecular mechanisms and targets involved in lenvatinib resistance; However, two primary mechanisms are being explored: the activation of alternative pathways and upregulation of receptors on tumor cells.^41,42 Several signaling pathways have been identified whose inhibition could partially reverse lenvatinib resistance, including EGFR,^43,44 c-MET, RAS/MEK/ERK,⁴⁵ and AKT⁴⁶ signaling pathways. These molecular could be a therapeutic target repurposing drugs like various vitamins as E and D as prophylactic with tumor-resistance modulatory effect.^47,48

Aurora-A is overexpressed in a variety of cancers, especially HCC. Increasing research has describe the characteristics of Aurora-A activation in drug resistance. For instance, aberrant activation of Aurora-A kinase in EGFR-TKI-resistant NSCLC cells has been reported, and inhibiting Aurora-A using MLN-8237 restored the sensitivity of resistant cells to EGFR-TKIs.⁴⁹ Moreover, MLN-8237 treatment has been demonstrated to overcome cisplatin (CDDP) resistance in gastric cancer⁵⁰ and bevacizumab resistance in glioblastoma (GBM).⁵¹ In addition to preclinical studies, MLN-8237 has shown promising anti-tumor efficacy and a favorable safety profile in combination with targeted drugs in various Phase I trials. For example, the clinical activity of MLN-8237 in combination with fulvestrant was verified in estrogen receptor-positive (ER+) breast cancer models.¹⁸ Additionally, MLN-8237 combined with pazopanib demonstrated manageable safety and early clinical evidence of antitumor activity in patients with advanced malignancies (NCT01639911).¹⁷ In summary, the combination of Aurora-A inhibitors with targeted therapies has substantial potential for overcoming drug resistance, because the simultaneous inhibition of different oncogenes may produce synergistic effects.¹⁴

Our study demonstrated that MLN-8237 in combination with lenvatinib synergistically inhibited HCC cell proliferation and induced apoptosis. MLN-8237 further sensitized HCC cells to lenvatinib treatment and reversed lenvatinib resistance by inhibiting Aurora-A expression. This is because, on one hand, Aurora-A act as an oncogene in HCC, activating several tumorigenic molecules and signaling pathways in HCC, like PI3K/Akt pathway,^52,53 NF-κB,³³ and c-Myc.⁵⁴ On the other hand, simultanious inhibition of oncogenic molecules by MLN-8237 might synergize with the anti-tumor efficacy of lenvatinib in HCC cells. On the other hand, we found that Aurora-A promotes FGFR1 expression through the hsa-circ-0058046/miR-424-5p/FGFR1 axis. FGFR1, a specific target of lenvatinib, is generally overexpressed in HCC cells, reflecting the degree of resistance to lenvatinib.⁵⁵ As expexted, the present study showed that overexpression of FGFR1 in HCC cells remarkably increased lenvatinib IC₅₀. Therefore, simultaneous inhibition of FGFR1 by lenvatinib and MLN-8237 partially overcome lenvatinib resistance in HCC cells.

Accumulating evidences highlighted the critical role of non-coding RNAs (ncRNAs) in drug resistance in HCC.^56,57 Most ncRNAs involved in drug resistance are miRNAs and long ncRNAs (lncRNAs).⁵⁸ However, little is known about the role of circRNAs in drug resistance. Recent studies have demonstrated that circRNAs contain miRNA response elements (MREs), enabling them to competitively bind miRNAs.⁵⁹ Several studies have shown that circRNAs plays a role in biological processes by sponging miRNAs.⁶⁰ Oncogenic circRNAs induces HCC progression by sponging tumor-suppressive miRNAs.⁶¹ In contrast, tumor-suppressor circRNAs inhibit HCC tumorigenesis by sponging onco-miRNAs.⁶²

In this present study, we describe for the first time hsa-circ-0058046, a 282 nt circular transcript derived from exons 6 and 7 of the BARD1 gene. We found that hsa-circ-0058046 was overexpressed in HCC cell lines, and its expression level was positively correlated with Aurora-A. Additionally, functional assays demonstrated that hsa-circ-0058046 promotes cell viability, angiogenesis, and lenvatinib resistance. These findings indicated that hsa-circ-0058046 may play an oncogenic role in hepatocellular carcinoma (HCC) and prompt us to investigate its downstream target microRNAs.

Database predictions and in vitro validation revealed miR-424-5p as a target of hsa-circ-0058046. Recently, it has been reported that serum miR-424-5p could be a diagnostic biomarker for HCC.⁶³ miR-424-5p is remarkably downregulated in HCC tissues and the serum of patients and correlated with poor clinical outcome, suggesting that miR-424-5p act as a tumor suppressor miRNA in HCC.²⁵ Several circRNAs have been reported to regulate miR-424-5p through sponging, including Circ-RNF13,⁶⁴ circCBFB,⁶⁵ and circular RNA_LARP4,⁶⁶ Other studies have reported that miR-424-5p targets FGFR1 in infantile skin hemangiomas⁶⁷ and Microvascular endothelial cells (ECs).⁶⁸ Therefore, we selected miR-424-5p as a candidate microRNA. As anticipated, our results indicated that hsa-circ-0058046 positively regulated the expression level of FGFR1 by sponging miR-424-5p.

It is important to note that this study has certain limitations. First, our research lacks human tissue samples that would allow for the measurement of hsa-circ-0058046 expression levels in cancer tissues and the analysis of correlations with clinical signatures, particularly regarding lenvatinib resistance. This limitation arises because lenvatinib is approved only for advanced HCC patients who are not candidates for surgery. Second, through database predictions, we found that hsa-circ-0058046 may also sponge other miRNAs. It is plausible that the hsa-circ-0058046/miR-424-5p/FGFR1 axis is not a unique mechanism by which hsa-circ-0058046 exerts its oncogenic role. Further exploration of additional miRNAs and downstream target genes is warranted. Third, it is essential to recognize that sponging miRNA represents only one of the mechanisms through which circRNAs exert their biological functions. According to predictions derived from the circular RNA interactome database, hsa-circ-0058046 has the potential to interact with the novel RNA-binding protein EIF4A3. This finding indicates that the biological role of hsa-circ-0058046 merits further investigation in future studies.

Conclusion

In conclusion, our study highlights that Aurora-A might be a potential therapeutic target of HCC drug resistance to lenvatinib. We firstly validated the hsa-circ-0058046 circular structure and illustrated its biological function. Present study indicated that Aurora-A induce lenvatinib resistance through hsa-circ-0058046/miR-424-5p/FGFR1 axis. Importantly, combination treatment with Aurora-A selective inhibitor MLN-8237 and lenvatinb partially reversed lenvatinib resistance in vitro and vivo study. These results have provided a theoretical foundation for further clinical trials.

Recommendation and future perspectives

This study suggests that Aurora-A may serve as a therapeutic target for hepatocellular carcinoma (HCC). The simultaneous inhibition of Aurora-A using the inhibitor MLN-8237, in combination with lenvatinib, demonstrated synergistic anti-tumor efficacy in HCC. Given the recent positive outcomes from phase I and II clinical trials indicating that the Aurora-A inhibitor MLN-8237 possesses favorable tolerability and anti-tumor efficacy. This treatment strategy holds significant potential for application in future clinical trials and could benefit a larger population of cancer patients moving forward.

Supplemental Material

sj-docx-1-iji-10.1177_03946320251316692 – Supplemental material for Aurora-A promotes lenvatinib resistance experimentally through hsa-circ-0058046/miR-424-5p/FGFR1 axis in hepatocellular carcinoma

Supplemental material, sj-docx-1-iji-10.1177_03946320251316692 for Aurora-A promotes lenvatinib resistance experimentally through hsa-circ-0058046/miR-424-5p/FGFR1 axis in hepatocellular carcinoma by Mubalake Abudoureyimu, Ni Sun, Weiwei Chen, Xinrong Lin, Fan Pan and Rui Wang in International Journal of Immunopathology and Pharmacology

Footnotes

Acknowledgements

The authors wish to express their gratitude to all staffs in the Department of Oncology, Jinling Hospital, Nanjing, China.

List of abbreviations

AUC: Area Under the Curve; ASCO: American Society of Clinical Oncology; CCLE: Cancer cell line encyclopedia; circRNAs: Circular RNAs; FGFR: fibroblast growth factor (FGF) receptors; ncRNAs: non-coding RNAs; NASH: non-alcoholic steatohepatitis; PDGFR: platelet-derived growth factor (PDGF) receptor; ROC curves: Receiver Operating Characteristic curves; TCGA: The cancer genome atlas; TKI: tyrosine kinase inhibitor; VEGFR: vascular endothelial growth factor (VEGF) receptors

Author contributions statement

Rui Wang was involved in the conception and design of the study. Mubalake Abudoureyimu performed in vitro experiments, bioinformatics analysis and drafting of the manuscript. Xinrong Lin and Fan Pan assisted the data analyses. Weiwei Chen were manuscript revisions. All authors listed approved the final version of the manuscript.

Data availability

All data used to support the findings of this study are available from the corresponding author at wangrui218@163.com upon request.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical considerations

This study was conducted in accordance with the recommendations of the Guide for the Care and Use of Laboratory Animals from the National Institute of Health. The Animal Care Committee at our institution approved the protocol for the animal experiments described in this manuscript (No. 2020JLHGKJDWLS-98).

ORCID iD

Rui Wang

Supplemental material

Supplemental material for this article is available online.

References

Singal

Lampertico

Nahon

(2020) Epidemiology and surveillance for hepatocellular carcinoma: New trends. Journal of Hepatology 72(2): 250–261.

El-Mesallamy

Hamdy

Rizk

, et al (2011) Apelin serum level in Egyptian patients with chronic hepatitis C. Mediators of Inflammation 2011: 703031.

Ali

Hamdy

Gibriel

, et al (2021) Investigation of the relationship between CTLA4 and the tumor suppressor RASSF1A and the possible mediating role of STAT4 in a cohort of Egyptian patients infected with hepatitis C virus with and without hepatocellular carcinoma. Archives of Virology 166(6): 1643–1651.

Youssef

Hamdy

(2017) SOCS1 and pattern recognition receptors: TLR9 and RIG-I; novel haplotype associations in Egyptian fibrotic/cirrhotic patients with HCV genotype 4. Archives of Virology 162(11): 3347–3354.

Wen

Cai

, et al (2022) The clinical management of hepatocellular carcinoma worldwide: A concise review and comparison of current guidelines: 2022 update. BioScience Trends 16(1): 20–30.

Wang

Wei

(2020) Advances in the early diagnosis of hepatocellular carcinoma. Genes & Diseases 7(3): 308–319.

Eldosoky

Hammad

Elmadbouly

, et al (2023) Diagnostic significance of hsa-miR-21-5p, hsa-miR-192-5p, hsa-miR-155-5p, hsa-miR-199a-5p panel and ratios in hepatocellular carcinoma on top of liver cirrhosis in HCV-infected patients. International Journal of Molecular Sciences 24(4): 3157.

Villanueva

(2019) Hepatocellular carcinoma. The New England Journal of Medicine 380(15): 1450–1462.

Lazzaro

Hartshorn

(2023) A comprehensive narrative review on the history, current landscape, and future directions of hepatocellular carcinoma (HCC) systemic therapy. Cancers (Basel) 15(9): 2506.

10.

Llovet

Pinyol

Kelley

, et al (2022) Molecular pathogenesis and systemic therapies for hepatocellular carcinoma. Nature Cancer 3(4): 386–401.

11.

Hao

Wang

(2020) Lenvatinib in management of solid tumors. Oncologist 25(2): e302–e310.

12.

Dipasquale

Marinello

Santoro

(2021) A comparison of lenvatinib versus sorafenib in the first-line treatment of unresectable hepatocellular carcinoma: Selection criteria to guide physician's choice in a new therapeutic scenario. Journal of Hepatocellular Carcinoma 8: 241–251.

13.

Capozzi

De Divitiis

Ottaiano

, et al (2019) Lenvatinib, a molecule with versatile application: From preclinical evidence to future development in anti-cancer treatment. Cancer Management and Research 11: 3847–3860.

14.

Huang

Liu

, et al (2021) Targeting AURKA in Cancer: Molecular mechanisms and opportunities for Cancer therapy. Molecular Cancer 20(1): 15.

15.

Jeng

Peng

Lin

, et al (2004) Overexpression and amplification of Aurora-A in hepatocellular carcinoma. Clinical Cancer Research 10(6): 2065–2071.

16.

Liewer

Huddleston

(2018) Alisertib: A review of pharmacokinetics, efficacy and toxicity in patients with hematologic malignancies and solid tumors. Expert Opinion on Investigational Drugs 27(1): 105–112.

17.

Shah

Fischer

Venepalli

, et al (2019). Phase I study of Aurora A kinase inhibitor alisertib (MLN8237) in combination with selective VEGFR inhibitor pazopanib for therapy of advanced solid tumors. American Journal of Clinical Oncology 42(5): 413–420.

18.

Haddad

D’Assoro

Suman

, et al (2018) Phase I trial to evaluate the addition of alisertib to fulvestrant in women with endocrine-resistant, ER+ metastatic breast cancer. Breast Cancer Research and Treatment 168(3): 639–647.

19.

Goff

Azad

Stein

, et al (2019) Phase I study combining the aurora kinase a inhibitor alisertib with mFOLFOX in gastrointestinal cancer. Investigational New Drugs 37(2): 315–322.

20.

Jing

Chen

(2021) Aurora kinase inhibitors: A patent review (2014–2020). Expert Opinion on Therapeutic Patents 31(7): 625–644.

21.

El-Aziz

MKA

Dawoud

Kiriacos

, et al (2023) Decoding hepatocarcinogenesis from a noncoding RNAs perspective. Journal of Cellular Physiology 238(9): 1982–2009.

22.

Tang

Ren

Guo

, et al (2021) Review on circular RNAs and new insights into their roles in cancer. Computational and Structural Biotechnology Journal 19: 910–928.

23.

Xue

Bao

, et al (2022) The mechanism underlying the ncRNA dysregulation pattern in hepatocellular carcinoma and its tumor microenvironment. Frontiers in Immunology 13: 847728.

24.

Oura

Morishita

Masaki

(2020) Molecular and functional roles of microRNAs in the progression of hepatocellular carcinoma-a review. International Journal of Molecular Sciences 21(21): 8362.

25.

Xiao

, et al (2019) MicroRNA-424-5p acts as a potential biomarker and inhibits proliferation and invasion in hepatocellular carcinoma by targeting TRIM29. Life Sciences 224: 1–11.

26.

Rodrigues

Afonso

Simao

, et al (2023) MiR-21-5p promotes NASH-related hepatocarcinogenesis. Liver International 43(10): 2256–2274.

27.

Zhou

Ren

Dai

, et al (2018) Hepatocellular carcinoma-derived exosomal miRNA-21 contributes to tumor progression by converting hepatocyte stellate cells to cancer-associated fibroblasts. Journal of Experimental & Clinical Cancer Research 37(1): 324.

28.

Zhou

Mao

Peng

, et al (2022) CircRNAs in hepatocellular carcinoma: Characteristic, functions and clinical significance. International Journal of Medical Sciences 19(14): 2033–2043.

29.

Abaza

El-Aziz

MKA

Daniel

, et al (2023) Emerging role of circular RNAs in hepatocellular carcinoma immunotherapy. International Journal of Molecular Sciences 24(22): 16484.

30.

Liu

Jiang

Song

, et al (2023) Isoliquiritigenin inhibits circ0030018 to suppress glioma tumorigenesis via the miR-1236/HER2 signaling pathway. MedComm 4(3): e282.

31.

Zhou

Qin

Song

, et al (2023) CircROBO1 promotes prostate cancer growth and enzalutamide resistance via accelerating glycolysis. Journal of Cancer 14(13): 2574–2584.

32.

Chou

(2010) Drug combination studies and their synergy quantification using the Chou-Talalay method. Cancer Research 70(2): 440–446.

33.

Shen

Chen

Huang

, et al (2019) Aurora-a confers radioresistance in human hepatocellular carcinoma by activating NF-kappaB signaling pathway. BMC Cancer 19(1): 1075.

34.

Zhang

Chen

, et al (2014) Aurora-A promotes chemoresistance in hepatocelluar carcinoma by targeting NF-kappaB/microRNA-21/PTEN signaling pathway. Oncotarget 5(24): 12916–12935.

35.

Briassouli

Chan

Savage

, et al (2007) Aurora-A regulation of nuclear factor-kappaB signaling by phosphorylation of IkappaBalpha. Cancer Research 67(4): 1689–1695.

36.

Kruger

Rehmsmeier

(2006) RNAhybrid: microRNA target prediction easy, fast and flexible. Nucleic Acids Research 34: W451–454.

37.

Enright

John

Gaul

, et al (2003) MicroRNA targets in drosophila. Genome Biology 5(1): R1.

38.

Nakahara

Kim

Sciulli

, et al (2005) Targets of microRNA regulation in the Drosophila oocyte proteome. Proceedings of the National Academy of Sciences of the United States of America 102(34): 12023–12028.

39.

Huang

Yang

Chung

, et al (2020) Targeted therapy for hepatocellular carcinoma. Signal Transduction and Targeted Therapy 5(1): 146.

40.

Shen

Huang

, et al. (2021) Genome-scale CRISPR-Cas9 knockout screening in hepatocellular carcinoma with lenvatinib resistance. Cell Death Discov 7(1): 359.

41.

Rexer

Engelman

Arteaga

(2009) Overcoming resistance to tyrosine kinase inhibitors: Lessons learned from cancer cells treated with EGFR antagonists. Cell Cycle 8(1): 18–22.

42.

Sennino

McDonald

(2012) Controlling escape from angiogenesis inhibitors. Nature Reviews Cancer 12(10): 699–709.

43.

Hikiba

Suzuki

, et al (2022) EGFR inhibition reverses resistance to lenvatinib in hepatocellular carcinoma cells. Scientific Reports 12(1): 8007.

44.

Jin

Shi

, et al (2021) EGFR activation limits the response of liver cancer to lenvatinib. Nature 595(7869): 730–734.

45.

Zhao

Zhang

, et al (2021) Sophoridine suppresses lenvatinib-resistant hepatocellular carcinoma growth by inhibiting RAS/MEK/ERK axis via decreasing VEGFR2 expression. Journal of Cellular and Molecular Medicine 25(1): 549–560.

46.

Hou

Bridgeman

Malnassy

, et al (2022) Integrin subunit beta 8 contributes to lenvatinib resistance in HCC. Hepatology Communications 6(7): 1786–1802.

47.

El-Derany

Hamdy

Al-Ansari

, et al (2016) Integrative role of vitamin D related and Interleukin-28B genes polymorphism in predicting treatment outcomes of Chronic Hepatitis C. BMC Gastroenterology 16: 19.

48.

Hamdy

Suwailem

El-Mesallamy

(2009) Influence of vitamin E supplementation on endothelial complications in type 2 diabetes mellitus patients who underwent coronary artery bypass graft. Journal of Diabetes and its Complications 23(3): 167–173.

49.

Wang

Lee

Kao

, et al (2021) Alisertib inhibits migration and invasion of EGFR-TKI resistant cells by partially reversing the epithelial-mesenchymal transition. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research 1868(6): 119016.

50.

Wang

Arras

Katsha

, et al. (2017) Cisplatin-resistant cancer cells are sensitive to Aurora kinase A inhibition by alisertib. Mol Oncol 11(8): 981-995.

51.

Kurokawa

Geekiyanage

Allen

, et al (2017) Alisertib demonstrates significant antitumor activity in bevacizumab resistant, patient derived orthotopic models of glioblastoma. Journal of Neuro-Oncology 131(1): 41–48.

52.

Zhu

Zhou

, et al (2017) Inhibition of Aurora A kinase by alisertib induces autophagy and cell cycle arrest and increases chemosensitivity in human hepatocellular carcinoma HepG2 cells. Current Cancer Drug Targets 17(4): 386–401.

53.

Chen

Song

Xiang

, et al (2017) AURKA promotes cancer metastasis by regulating epithelial-mesenchymal transition and cancer stem cell properties in hepatocellular carcinoma. Biochemical and Biophysical Research Communications 486(2): 514–520.

54.

Han

Tian

, et al (2015) Aurora kinase A mediates c-Myc's oncogenic effects in hepatocellular carcinoma. Molecular Carcinogenesis 54(11): 1467–1479.

55.

Zhao

Song

Zhang

, et al (2021) Oxysophocarpine suppresses FGFR1-overexpressed hepatocellular carcinoma growth and sensitizes the therapeutic effect of lenvatinib. Life Sciences 264: 118642.

56.

Wang

Chen

, et al (2020) The underlying mechanisms of noncoding RNAs in the chemoresistance of hepatocellular carcinoma. Molecular Therapy Nucleic Acids 21: 13–27.

57.

Ding

Lou

, et al (2018) Non-coding RNA in drug resistance of hepatocellular carcinoma. Bioscience Reports 38(5): BSR20180915.

58.

Ayers

Vandesompele

(2017) Influence of microRNAs and long non-coding RNAs in cancer chemoresistance. Genes (Basel) 8(3): 95.

59.

Bezzi

Guarnerio

Pandolfi

(2017) A circular twist on microRNA regulation. Cell Research 27(12): 1401–1402.

60.

Han

Hur

Cho

, et al (2020) Epigenetic associations between lncRNA/circRNA and miRNA in hepatocellular carcinoma. Cancers (Basel) 12(9): 2622.

61.

Shi

Yuan

, et al (2020) Downregulation of circular RNA circPVT1 restricts cell growth of hepatocellular carcinoma through downregulation of Sirtuin 7 via microRNA-3666. Clinical and Experimental Pharmacology and Physiology 47(7): 1291–1300.

62.

Han

Wang

, et al (2017) Circular RNA circMTO1 acts as the sponge of microRNA-9 to suppress hepatocellular carcinoma progression. Hepatology 66(4): 1151–1164.

63.

Yang

(2023) MiR-424 acts as a novel biomarker in the diagnosis of patients with hepatocellular carcinoma. Cancer Biotherapy and Radiopharmaceuticals 38(10): 670–673.

64.

Chen

Wei

, et al (2021) Circ-RNF13, as an oncogene, regulates malignant progression of HBV-associated hepatocellular carcinoma cells and HBV infection through ceRNA pathway of circ-RNF13/miR-424-5p/TGIF2. Bosnian Journal of Basic Medical Sciences 21(5): 555–568.

65.

Zhao

Feng

(2022) CircCBFB is a mediator of hepatocellular carcinoma cell autophagy and proliferation through miR-424-5p/ATG14 axis. Immunologic Research 70(3): 341–353.

66.

Zhang

Liu

Hou

, et al (2017) Circular RNA_LARP4 inhibits cell proliferation and invasion of gastric cancer by sponging miR-424-5p and regulating LATS1 expression. Molecular Cancer 16(1): 151.

67.

Yang

Dai

, et al (2017) The expression and function of miR-424 in infantile skin hemangioma and its mechanism. Scientific Reports 7(1): 11846.

68.

Sahni

Narra

Patel

, et al (2018) MicroRNA-regulated rickettsial invasion into host endothelium via fibroblast growth factor 2 and its receptor FGFR1. Cells 7(12): 240.

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