Abstract
Background
Cervical cancer (CC) remains a significant health concern for women worldwide, with poor prognosis often linked to late diagnosis. This study aimed to explore the clinical significance and molecular mechanisms of long non-coding RNA BZRAP1-AS1.
Methods
A total of 105 CC patients were enrolled, and paired tumor and normal tissues were collected. The expression levels of BZRAP1-AS1 and miR-541-3p were quantified by qRT-PCR. The direct binding between BZRAP1-AS1 and miR-541-3p was validated using a dual-luciferase reporter assay. Functional assays, including CCK-8, Transwell, and flow cytometry analysis, were performed in CC cell lines.
Results
BZRAP1-AS1 was upregulated in CC tissues and correlated with advanced FIGO stage and lymph node metastasis (P < 0.05). Kaplan–Meier analysis revealed that patients with high BZRAP1‑AS1 expression had significantly shorter overall survival (log‑rank P = 0.007). Multivariate Cox regression confirmed high BZRAP1‑AS1 expression as an independent predictor of poor prognosis (HR = 3.031, 95% CI = 1.136–8.090). Silencing of BZRAP1-AS1 inhibited cell proliferation and invasion, while promoting apoptosis. Mechanistically, BZRAP1-AS1 acted as a competing endogenous RNA (ceRNA) to sponge miR-541-3p. Rescue experiments indicated that inhibition of miR-541-3p reversed the tumor-suppressive effects resulting from BZRAP1-AS1 knockdown.
Conclusion
Our findings suggest that BZRAP1-AS1 may serve as an independent prognostic marker in cervical cancer. Mechanistically, it appears to promote tumor progression by downregulating miR‑541‑3p. The BZRAP1‑AS1/miR‑541‑3p axis thus warrants further investigation, though its translational potential requires validation through larger multi‑center studies.
Keywords: Cervical cancer, BZRAP1-AS1, miR-541-3p, Prognosis
Background
Cervical cancer (CC), a major disease posing a serious threat to women’s health worldwide, currently ranks as the fourth most common gynecological malignancy. In terms of incidence, its burden is surpassed only by breast cancer, with approximately 2.1 million new diagnoses each year, followed by colorectal cancer at 800,000 cases and lung cancer with an estimated 700,000 cases annually [1]. Globally, approximately 528,000 new cases and 266,000 deaths from CC occur annually [2]. Epidemiological studies indicate that the average age at diagnosis for CC patients is 53 years, while the average age at death is only 59 years. This suggests that the disease not only significantly reduces women’s life expectancy but also imposes a substantial socioeconomic burden on families and society [3]. Of these patients, about 50% are diagnosed with advanced cancer (FIGO stage IIB - IV). By this time, the tumor has usually undergone local invasion or distant metastasis, which makes the conventional treatment modalities less effective and dramatically reduces the five-year survival rate thereafter [4, 5]. This grim clinical reality highlights the urgent need to investigate the molecular mechanisms and progression of CC, with the aim of identifying novel diagnostic biomarkers and therapeutic targets to improve patient prognosis.
Long non-coding RNAs (lncRNAs) have emerged as crucial regulators in cancer biology, playing pivotal roles in modulating malignant behaviors such as uncontrolled proliferation, invasion, and apoptosis resistance [6, 7]. Among these, lncRNA BZRAP1-AS1 is a relatively novel lncRNA with limited reported studies. Existing research has primarily described its involvement in cancers such as non‑small cell lung cancer and hepatocellular carcinoma. Notably, bioinformatic analyses based on The Cancer Genome Atlas (TCGA) database identified BZRAP1-AS1 as a key component associated with poorer survival in CC patients [8]. Its expression correlates with immune cell infiltration and immune-related pathways in the tumor microenvironment [9]. Our preliminary experiments further confirmed that BZRAP1‑AS1 is aberrantly expressed in CC patient tissues. However, its functional role and molecular mechanisms in CC remain completely unexplored, representing a significant knowledge gap.
On the other hand, microRNAs (miRNAs) are short non‑coding RNAs that post‑transcriptionally regulate gene expression and are deeply involved in tumor progression [10, 11]. In CC, miR-541-3p has been reported to act as a tumor suppressor, inhibiting cancer growth and enhancing radiosensitivity [12]. Notably, lncRNAs can function as competing endogenous RNAs (ceRNA) by sponging miRNAs, thereby modulating miRNA activity and affecting downstream target expression [13–15]. Bioinformatics prediction suggests that BZRAP1-AS1 contains potential binding sites for miR-541-3p indicating a possible ceRNA interaction. Given the lack of functional studies on BZRAP1‑AS1 in CC, and the established tumor‑suppressive role of miR‑541‑3p, we hypothesize that BZRAP1‑AS1 may promote CC progression by sequestering miR‑541‑3p.
Therefore, this study aims to investigate the expression, clinical relevance, and functional interplay between BZRAP1‑AS1 and miR‑541‑3p in CC, with the goal of elucidating a novel ceRNA‑dependent mechanism and identifying potential prognostic biomarkers.
Methods
Subject inclusion
105 patients diagnosed with CC and treated surgically at Nanjing Women and Children’s Healthcare Hospital were included in this study. All participants were female, aged between 40 and 65 years, and had not received any form of anti-tumor therapy prior to diagnosis. The baseline clinicopathological characteristics of the included patients are summarized in Table 1. Written informed consent was obtained from each patient, and the research protocol received approval from the Ethics Committee of Nanjing Women and Children’s Healthcare Hospital and adhere to the tenets of the Declaration of Helsinki. Paired tissue samples, including tumor tissues and paired adjacent non-tumor tissue (NT) collected from a site at least 3 cm away from the tumor margin, were obtained during surgery. All NT samples were confirmed to be free of cancer cells by pathological examination. Samples were examined independently by at least two pathologists and stored at -80 °C for subsequent experimental analysis.
Table 1.
Chi-square test evaluating the association of BZRAP1-AS1 expression with clinicopathological features
| Cases(n = 105) | Low BZRAP1-AS1 (n = 50) |
High BZRAP1-AS1 (n = 55) |
P | |
|---|---|---|---|---|
| Age | ||||
| ≤ 55 | 49 | 26 | 23 | 0.296 |
| > 55 | 56 | 24 | 32 | |
| Lesion diameter(cm) | ||||
| ≤ 4 cm | 63 | 29 | 34 | 0.690 |
| > 4 cm | 42 | 21 | 21 | |
| Differentiation | ||||
| Well-moderare | 71 | 38 | 33 | 0.080 |
| Poor | 34 | 12 | 22 | |
| FIGO stage | ||||
| I-II | 72 | 39 | 33 | 0.047 |
| III | 33 | 11 | 22 | |
| Lymph node metastasis | ||||
| No | 75 | 41 | 34 | 0.022 |
| Yes | 30 | 9 | 21 | |
| Histology type | ||||
| Adenocarcinoma | 58 | 32 | 26 | 0.085 |
| Squamous carcinoma | 47 | 18 | 29 | |
| HPV infection | ||||
| No | 56 | 30 | 26 | 0.192 |
| Yes | 49 | 20 | 29 |
Follow-up survey
Patients’ post-surgical outcomes were assessed through a retrospective review of medical records. All enrolled patients were required to have complete follow-up data. Follow-up information was obtained via hospital records, telephone interviews, or outpatient visits at regular intervals (every 3–6 months). The follow-up period ranged from 3 to 60 months, with a median follow-up time of 32 months. Survival data obtained from follow-up were analyzed.
Gene expression assessment
Total RNA was extracted from tissues and cultured cells using Trizol® reagent (Invitrogen, USA) according to the manufacturer’s protocol. Potential genomic DNA contamination was removed by treatment with RNase-free DNase I (Thermo Fisher Scientific, USA). RNA concentration and purity were determined using a Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific, USA), with an A260/280 ratio between 1.8 and 2.0 considered acceptable. For reverse transcription, 1 µg of total RNA was converted into cDNA using the PrimeScript RT reagent Kit (Takara, Japan) for BZRAP1-AS1, and the miScript II RT Kit (Qiagen, Germany) for miR-541-3p, according to the respective protocols. Quantitative real-time PCR (qRT-PCR) was performed using TB Green Premix Ex Taq II (Takara, Japan) on a QuantStudio 5 Real-Time PCR System (Applied Biosystems, USA). The 20 µL reaction mixture contained 10 µL of TB Green Premix, 0.8 µL each of forward and reverse primers (10 µM), 2 µL of cDNA template, and 6.4 µL of nuclease-free water. The thermal cycling conditions were: 95 °C for 30 s, followed by 40 cycles of 95 °C for 5 s and 60 °C for 30 s. Expression levels were normalized to GAPDH (for BZRAP1-AS1) or U6 snRNA (for miR-541-3p) and calculated using the 2 − ΔΔCt method.
Cell culture and transfection
CC cells (SiHa, HeLa, CaSki, and C33A) and normal cell End1/E6E7 were cultured in DMEM containing 10% FBS and 0.1% penicillin-streptomycin. Cells were transfected with plasmids to silence BZRAP1-AS1 and miR-541-3p inhibitors to regulate miR-541-3p expression. Transfections were performed using Lipofectamine 2000 (Invitrogen, USA) according to the manufacturer’s instructions at room temperature. After 48 h, the expression levels of BZRAP1-AS1 and miR-541-3p were measured to assess the transfection efficiency.
Cell Counting Kit-8 (CCK-8) assay
CCK‑8 assay was performed to assess cell proliferation. CaSki and HeLa cells subjected to the indicated transfections (si‑BZRAP1‑AS1, miR‑541‑3p inhibitor, or corresponding controls) were trypsinized, resuspended, and seeded into 96-well plates at a density of 3 × 10³ cells per well. Wells containing culture medium only served as the blank control (CK). After incubation for 0, 24, 48, or 72 h,10 µL CCK-8 reagent was added to each well and incubated at 37 °C for 2 h. Absorbance at 450 nm absorbance (OD450) was then measured using a microplate reader.
Transwell assay
Cells were plated into the upper compartment of a 24-well Transwell insert, which was pre-coated with Matrigel for invasion assays. After 24 h of incubation, non-migrated or non-invaded cells on the upper side of the membrane were gently removed using a cotton swab. The cells that had traversed to the underside of the membrane were then fixed, stained, and visualized. Cell invasion was assessed by counting stained cells in five randomly chosen fields under a light microscope.
Cell apoptosis
Apoptosis was assessed using flow cytometry with Annexin V-FITC/PI dual staining. After transfection, cells from each group were harvested and fixed with 3.7% formaldehyde at room temperature for 15 min. Cells were permeabilized with 0.1% Triton X-100 for 5 min, and resuspended in 1X binding buffer. Cell apoptosis was quantified using a FACScan flow cytometer.
Dual-luciferase reporter assay
The relevant BZRAP1-AS1 sequences, including both wild-type and mutated binding sites, were inserted into the pGL3 luciferase reporter plasmid (Promega, USA) to generate reporter constructs. These plasmids were then co-transfected with miR-541-3p inhibitors into CC cells using Lipofectamine 2000 reagent (Invitrogen, USA). Firefly luciferase signals were normalized to Renilla luciferase activity to account for transfection efficiency.
RNA immunoprecipitation (RIP) assay
RNA immunoprecipitation was performed using the Magna RIP Kit (Millipore, USA) following the manufacturer’s instructions. Briefly, CaSki and HeLa cells were lysed in RIP lysis buffer. Cell lysates were incubated with magnetic beads conjugated with anti-Ago2 antibody (Abcam, ab32381) or normal mouse IgG (negative control) overnight at 4 °C. Beads were washed extensively, and co-precipitated RNA was extracted. Enrichment of BZRAP1-AS1 and miR-541-3p was detected by qRT‑PCR and normalized to input controls.
Statistical analysis
Statistical analyses were conducted using SPSS version 26.0 (IBM, USA) and GraphPad Prism version 7.0 (GraphPad Software, USA). Data from at least three independent experiments are presented as the mean ± standard deviation (SD). The normality of continuous variables was assessed using the Shapiro–Wilk test. Differences between two groups were compared using the Student’s t‑test (for normally distributed data) or the Mann–Whitney U test (for non‑normally distributed data). For comparisons among multiple groups, one‑way ANOVA (followed by Tukey’s post‑hoc test) or the Kruskal–Wallis test was applied as appropriate. Survival analysis was performed using the Kaplan-Meier method, and differences in survival curves were assessed by the log-rank test. To evaluate the prognostic factors, multivariate Cox proportional hazards regression analyses were performed. Clinico-pathological variables with a P-value < 0.1 in the univariate analysis were incorporated into the subsequent multivariate model. The results are presented as hazard ratios (HR) with 95% confidence intervals (CI). A P-value of less than 0.05 was considered statistically significant.
Results
Expression levels of BZRAP1-AS1 and miR-541-3p in CC tissues
As shown in Fig. 1A, BZRAP1-AS1 expression was markedly upregulated in CC tissues compared to NT tissues. In contrast, miR-541-3p expression was significantly downregulated in tumor samples, as illustrated in Fig. 1B. Both differences were statistically significant (P < 0.001).
Fig. 1.
Expression of BZRAP1-AS1 (A) and miR-541-3p (B) in cervical cancer (CC) tumor tissues and paired adjacent non-tumor tissues (NT). Data are presented as mean ± SD (n = 105 patient pairs). (***P < 0.001, compared with NT group)
Association of BZRAP1-AS1 with clinical pathological features and prognosis in patients
Based on the average level of BZRAP1-AS1 in CC tumor tissues, patients were divided into a low BZRAP1-AS1 group (50 patients) and a high BZRAP1-AS1 group (55 patients). There was a significant correlation between BZRAP1-AS1 levels and FIGO stage (P = 0.047), and Lymph node metastasis (P = 0.022) in CC patients (Table 1). Follow-up data indicated that lower BZRAP1-AS1 levels were associated with higher survival rates (log rank P = 0.007, Fig. 2). Additionally, BZRAP1-AS1 (HR = 3.031, 95% CI = 1.136–8.090) was identified as prognostic factor, along with lymph node metastasis (HR = 2.400, 95% CI = 1.049–5.492) and FIGO stage (HR = 2.691, 95% CI = 1.037–6.982) (Table 2).
Fig. 2.
Kaplan-Meier survival curve showing the overall survival of CC patients over a 60-month follow-up period
Table 2.
Cox regression analysis to assess clinicopathologic features and prognostic value of BZRAP1-AS1
| P | HR | 95%CI | |
|---|---|---|---|
| BZRAP1-AS1 | 0.027 | 3.031 | 1.136 ~ 8.090 |
| Age | 0.351 | 0.627 | 0.235 ~ 1.674 |
| Menopause | 0.073 | 0.414 | 0.158 ~ 1.084 |
| Lesion diameter | 0.192 | 0.480 | 0.159 ~ 1.448 |
| Differentiation | 0.260 | 0.575 | 0.220 ~ 1.505 |
| FIGO stage | 0.042 | 2.691 | 1.037 ~ 6.982 |
| Lymph node metastasis | 0.038 | 2.400 | 1.049 ~ 5.492 |
| Histology type | 0.074 | 2.274 | 0.922 ~ 5.611 |
| HPV | 0.381 | 1.466 | 0.623 ~ 3.451 |
Regulatory role of BZRAP1-AS1 on miR-541-3p
Consistent with the expression patterns observed in tumor tissues, BZRAP1-AS1 levels were significantly elevated in CC cell lines compared to normal cervical epithelial cells (Fig. 3A), while miR-541-3p expression was markedly reduced (Fig. 3B) (P < 0.001). To further explore their interaction, functional analyses were performed in HeLa and CaSki cells, both of which exhibit sensitivity to alterations in BZRAP1-AS1 and miR-541-3p expression. To validate the direct binding between BZRAP1-AS1 and miR-541-3p as predicted by bioinformatics analysis (Fig. 4A), a dual-luciferase reporter assay was performed. The results showed that co-transfection with miR-541-3p mimics significantly suppressed the luciferase activity of the wild-type BZRAP1-AS1 reporter vector in both CaSki (Fig. 4B) and HeLa (Fig. 4C) cells. In contrast, the luciferase activity of the mutant reporter remained unchanged. To further substantiate their intracellular interaction, RIP assays were conducted using an antibody against Ago2, a core component of the RNA‑induced silencing complex. The results demonstrated that both BZRAP1‑AS1 and miR‑541‑3p were significantly enriched in Ago2 immunoprecipitates compared to the IgG control (Fig. 4D‑E), supporting a direct physical association within the cellular context. Silencing BZRAP1-AS1 expression resulted in a significant decline in its expression levels (P < 0.001, Fig. 5A-B). Moreover, knockdown of BZRAP1-AS1 significantly increased miR-541-3p expression, an effect that was reversed upon co-transfection with miR-541-3p inhibitors (P < 0.001, Fig. 5C-D).
Fig. 3.
Expression of BZRAP1-AS1 (A) and miR-541-3p (B) in CC cells and normal cells. Data are presented as mean ± SD of five independent experiments. (***P < 0.001, compared with normal cells)
Fig. 4.
Validation of the competing endogenous RNA (ceRNA) mechanism between BZRAP1-AS1 and miR-541-3p. A Schematic of the putative miR-541-3p binding site in BZRAP1-AS1 and the corresponding wild‑type (WT)/mutant (MUT) luciferase reporter constructs. B, C The luciferase activity of these reporters was measured after transfection with miR-541-3p mimic or inhibitor in (B) CaSki and (C) HeLa cells, confirming the specific binding that underpins the ceRNA model. D, E RNA immunoprecipitation (RIP) assays using anti‑Ago2 antibody in (D) CaSki and (E) HeLa cells. Data are presented as mean ± SD (n = 5 independent experiments). (***P < 0.001, compared with miR-NC or anti-IgG group). CK, Blank Control; miR-NC, microRNA negative control
Fig. 5.
The effect of BZRAP1-AS1 on miR-541-3p expression in Caksi cell and Hela cell. A‑B Relative expression levels of BZRAP1-AS1 under indicated treatments in Caksi cell (A) and Hela cell (B). C‑D Relative expression of miR‑541‑3p under indicated treatments in Caksi cell (C) and Hela cell (D). Data are presented as mean ± SD (n = 5). (***P < 0.001, compared with si-NC group; ###P < 0.001, compared with the si-BZRAP1-AS1 + miR-NC group). CK, Blank Control; si-BZRAP1-AS1, BZRAP1-AS1-targeting small interfering RNA; si-NC, scrambled small interfering RNA negative control; miR-NC, microRNA negative control; miR-inhibitor, miR-541-3p inhibitor
Impact of BZRAP1-AS1 and miR-541-3p on CC Cell Proliferation
In HeLa and CaSki cells, silencing BZRAP1-AS1 significantly suppressed cell proliferation compared to the control group (P < 0.01). However, this suppressive effect was notably attenuated when miR-541-3p expression was concurrently inhibited (P < 0.01, Fig. 6A-B). Additionally, BZRAP1-AS1 knockdown reduced invasive capabilities (P < 0.001, Fig. 6C) and enhanced apoptosis capabilities (P < 0.001, Fig. 6D) in both cell lines. These effects were reversed by miR-541-3p downregulation, indicating a regulatory interaction between the two molecules.
Fig. 6.
The function of BZRAP1-AS1 and miR-541-3p in the proliferation (A-B), invasion (C), and apoptosis (D) of CC cells. Data are presented as mean ± SD (n = 5). (** P < 0.01, ***P < 0.001, compared with si-NC group; ## P < 0.01, ###P < 0.001, compared with the si-BZRAP1-AS1 + miR-NC group). CK, Blank Control; si-BZRAP1-AS1, BZRAP1-AS1-targeting small interfering RNA; si-NC, scrambled small interfering RNA negative control; miR-NC, microRNA negative control; miR-inhibitor, miR-541-3p inhibitor
Discussion
Since CC typically lacks obvious symptoms in its early stages, approximately half of the patients are diagnosed at advanced stages, significantly increasing the difficulty of treatment and leading to poor prognosis [16, 17]. Therefore, a comprehensive understanding of the pathological mechanisms of CC can help identify new biomarkers improving women’s health. This study suggests that elevated levels of BZRAP1-AS1 may indicate poor prognosis and malignant progression in CC patients, while miR-541-3p mediates the tumor-promoting effects of BZRAP1-AS1 on CC cells.
In line with earlier findings [9], our study confirmed that BZRAP1‑AS1 expression is significantly upregulated in CC tissues compared with adjacent normal tissues. Yao et al. previously reported that high BZRAP1‑AS1 levels are associated with poor prognosis in CC [8]. Similarly, we observed that elevated BZRAP1‑AS1 expression correlates with advanced FIGO stage, lymph node metastasis, and serves as an independent prognostic indicator for reduced overall survival. These results strengthen the evidence that BZRAP1‑AS1 may function as a clinically relevant biomarker with potential utility in risk stratification and outcome prediction in CC patients.
Emerging evidence indicates that BZRAP1-AS1 plays a critical role in cancer progression. For instance, Hao et al. reported that BZRAP1-AS1 could serve as a prognostic factor in non-small cell lung cancer, where its knockdown significantly suppressed cancer cell proliferation and metastasis [18]. It also has been reported to be involved in regulating the malignant development of liver cancer [19]. Similarly, in the present study, in vitro experiments confirmed that silencing BZRAP1‑AS1 significantly inhibited invasion and promoted apoptosis in CC cells, further supporting its oncogenic role across different cancer types. Mechanistically, lncRNAs often function as ceRNAs by sponging miRNAs, thereby modulating their activity. For example, the oncogenic lncRNA DLG1-AS1 was reported to negatively regulate miR-16-5p through a similar sponge mechanism in CC [20]. Mechanistically, lncRNAs often function as ceRNAs by sponging miRNAs, thereby regulating their activity. In this study, dual‑luciferase reporter and RIP assays confirmed the direct binding between BZRAP1‑AS1 and miR‑541‑3p. Notably, miR‑541‑3p has also been reported to be targeted by other lncRNAs in different cancers. For instance, LINC00638 was shown to promote non‑small cell lung cancer progression by regulating the miR‑541‑3p/IRS1/PI3K/Akt axis [21], and LOXL1‑AS1 was found to modulate prostate cancer cell proliferation and cell cycle progression via miR‑541‑3p and CCND1 [22]. These reports suggest that miR‑541‑3p may represent a common regulatory node targeted by multiple lncRNAs. In CC, miR‑541‑3p has been identified as a tumor‑suppressive miRNA. For example, Circ_0085616 was reported to contribute to radio‑resistance and progression in CC by targeting the miR‑541‑3p/ARL2 signaling pathway [12]. Our rescue experiments further indicated that inhibition of miR‑541‑3p could reverse the tumor‑suppressive effects induced by BZRAP1‑AS1 knockdown, supporting the notion that the oncogenic function of BZRAP1‑AS1 in CC may be mediated, at least in part, through downregulation of miR‑541‑3p.
This study provides mechanistic evidence that BZRAP1‑AS1 may exert its effects by sponging miR‑541‑3p, highlighting this axis as a possible target for further investigation.
Nonetheless, several limitations should be acknowledged and addressed in future investigations. Firstly, the clinical correlations are derived from a single-center cohort with a limited sample size, which may constrain the statistical power and generalizability of the findings. Consequently, future research should prioritize multi-center studies with larger cohorts. Secondly, while we elucidated a ceRNA mechanism involving miR-541-3p, other potential functions of BZRAP1-AS1 remain unexplored. For instance, its potential roles in extracellular vesicles or in modulating the tumor immune microenvironment—as suggested by prior bioinformatic analyses—require experimental validation [23, 24]. Further mechanistic investigations are warranted to explore its potential secretion via extracellular vesicles and its interaction with the tumor immune landscape. Lastly, the functional conclusions drawn in this study are derived exclusively from in vitro models. To establish the in vivo relevance and translational potential of the BZRAP1‑AS1/miR‑541‑3p axis, validation in appropriate animal models is essential [25, 26]. Furthermore, prospective clinical studies are ultimately required to assess the prognostic utility and therapeutic relevance of targeting this axis in cervical cancer patients.
In summary, this study identifies BZRAP1-AS1 as an independent prognostic biomarker in cervical cancer and demonstrates its functional role in promoting tumor progression through the miR-541-3p pathway. These findings provide new insights into cervical cancer pathogenesis while highlighting potential therapeutic targets; however, further validation in larger clinical cohorts and animal models is required to assess their translational potential.
Acknowledgements
Not applicable.
Authors’ contributions
Conceptualization: KY, YL, MYT; Data curation: MYT; Formal analysis: ZXZ, LNH; Funding acquisition: ZXZ; Investigation: LNH; Methodology: ZXZ, LNH, CH; Project administration: CH; Resources: MYT; Software: ZXZ, LNH; Supervision: CH; Validation: ZXZ, LNH, KY, YL; Visualization: KY, YL, CH ; Writing - original draft: KY, YL; Writing - review & editing: ZXZ, LNH, CH.
Funding
This work was supported by Hunan Provincial Health Commission Research Project, Grant numbers [20256802]; Hunan Provincial Natural Science Foundation University Joint Fund, Grant numbers [2025JJ90091]; Central Government Subsidy for Traditional Chinese Medicine Special Projects Hunan University of Chinese Medicine Institutional Research Project, Grant numbers [000100200609]; Hunan Provincial Department of Education Grant Project Hunan University of Chinese Medicine Institutional Research Project, Grant numbers[020000203220].
Data availability
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
Written informed consent was obtained from each patient, and the research protocol received approval from the Ethics Committee of Nanjing Women and Children’s Healthcare Hospital and adhere to the tenets of the Declaration of Helsinki.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Zhixiang Zou and Lina Huang should be considered joint first authors.
References
- 1.Johnson CA, James D, Marzan A, Armaos M. Cervical Cancer: An Overview of Pathophysiology and Management. Semin Oncol Nurs. 2019;35(2):166–74. [DOI] [PubMed] [Google Scholar]
- 2.Buskwofie A, David-West G, Clare CA. A Review of Cervical Cancer: Incidence and Disparities. J Natl Med Assoc. 2020;112(2):229–32. [DOI] [PubMed] [Google Scholar]
- 3.Vu M, Yu J, Awolude OA, Chuang L. Cervical cancer worldwide. Curr Probl Cancer. 2018;42(5):457–65. [DOI] [PubMed] [Google Scholar]
- 4.Abu-Rustum NR, Yashar CM, Arend R, Barber E, Bradley K, Brooks R, et al. NCCN Guidelines® Insights: Cervical Cancer, Version 1.2024. J Natl Compr Cancer Network: JNCCN. 2023;21(12):1224–33. [DOI] [PubMed] [Google Scholar]
- 5.Li M, Tian X, Guo H, Xu X, Liu Y, Hao X, et al. A novel lncRNA-mRNA-miRNA signature predicts recurrence and disease-free survival in cervical cancer. Brazilian J Med Biol Res = Revista brasileira de pesquisas medicas e biologica. 2021;54(11):e11592. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Lin W, Zhou Q, Wang CQ, Zhu L, Bi C, Zhang S, et al. LncRNAs regulate metabolism in cancer. Int J Biol Sci. 2020;16(7):1194–206. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Iaccarino I, Klapper W. LncRNA as Cancer Biomarkers. Methods in molecular biology. (Clifton NJ). 2021;2348:27–41. [DOI] [PubMed] [Google Scholar]
- 8.Yao H, Jiang X, Fu H, Yang Y, Jin Q, Zhang W, et al. Exploration of the Immune-Related Long Noncoding RNA Prognostic Signature and Inflammatory Microenvironment for Cervical Cancer. Front Pharmacol. 2022;13:870221. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Zheng J, Cao B, Zhang X, Niu Z, Tong J. Immune-Related Four-lncRNA Signature for Patients with Cervical Cancer. Biomed Res Int. 2020;2020:3641231. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Pan G, Liu Y, Shang L, Zhou F, Yang S. EMT-associated microRNAs and their roles in cancer stemness and drug resistance. Cancer Commun (London England). 2021;41(3):199–217. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Wang J, Zhang C. Identification and validation of potential mRNA- microRNA- long-noncoding RNA (mRNA-miRNA-lncRNA) prognostic signature for cervical cancer. Bioengineered. 2021;12(1):898–913. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Tang Y, Zhou L, Liu L. Circ_0085616 contributes to the radio-resistance and progression of cervical cancer by targeting miR-541-3p/ARL2 signaling. Histol Histopathol. 2023;38(5):571–84. [DOI] [PubMed] [Google Scholar]
- 13.Zhu SF, Yuan W, Du YL, Wang BL. Research progress of lncRNA and miRNA in hepatic ischemia-reperfusion injury. Hepatobiliary & Pancreatic Diseases International: HBPD INT. 2023;22(1):45–53. [DOI] [PubMed]
- 14.Panda AC. Circular RNAs Act as miRNA Sponges. Adv Exp Med Biol. 2018;1087:67–79. [DOI] [PubMed] [Google Scholar]
- 15.Panni S, Lovering RC, Porras P, Orchard S. Non-coding RNA regulatory networks. Biochimica et biophysica acta gene regulatory mechanisms. 2020;1863(6):194417. [DOI] [PubMed]
- 16.Basen-Engquist K, Paskett ED, Buzaglo J, Miller SM, Schover L, Wenzel LB, et al. Cerv cancer Cancer. 2003;98(9 Suppl):2009–14. [DOI] [PubMed] [Google Scholar]
- 17.Sharma S, Deep A, Sharma AK. Current Treatment for Cervical Cancer: An Update. Anti-cancer Agents Med Chem. 2020;20(15):1768–79. [DOI] [PubMed] [Google Scholar]
- 18.Hao X, Zhang M, Gu M, Wang Z, Zhou S, Li W, et al. Long non-coding RNA BZRAP1-AS1 functions in malignancy and prognosis for non-small-cell lung cancer. PeerJ. 2022;10:e13871. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Wang W, Chen G, Wang B, Yuan Z, Liu G, Niu B, et al. Long non-coding RNA BZRAP1-AS1 silencing suppresses tumor angiogenesis in hepatocellular carcinoma by mediating THBS1 methylation. J translational Med. 2019;17(1):421. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Zou MJ, Cheng XR, Liu RF. lncRNA DLG1-AS1 promotes cervical cancer cell gemcitabine resistance by regulating miR-16-5p/HDGF. J Obstet Gynaecol Res. 2022;48(7):1836–47. [DOI] [PubMed] [Google Scholar]
- 21.Zhang J, Mou Y, Li H, Shen H, Song J, Li Q. LINC00638 promotes the progression of non-small cell lung cancer by regulating the miR-541-3p/IRS1/PI3K/Akt axis. Heliyon. 2023;9(6):e16999. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Long B, Li N, Xu XX, Li XX, Xu XJ, Liu JY, et al. Long noncoding RNA LOXL1-AS1 regulates prostate cancer cell proliferation and cell cycle progression through miR-541-3p and CCND1. Biochem Biophys Res Commun. 2018;505(2):561–8. [DOI] [PubMed] [Google Scholar]
- 23.Zheng Y, Wen S, Jiang S, He S, Qiao W, Liu Y, et al. CircRNA/lncRNA-miRNA-mRNA network and gene landscape in calcific aortic valve disease. BMC Genomics. 2023;24(1):419. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Wen JL, Ruan ZB, Wang F, Chen GC, Zhu JG, Ren Y, et al. Construction of atrial fibrillation-related circRNA/lncRNA-miRNA-mRNA regulatory network and analysis of potential biomarkers. J Clin Lab Anal. 2023;37(2):e24833. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Robinson NB, Krieger K, Khan FM, Huffman W, Chang M, Naik A, et al. The current state of animal models in research: A review. Int J Surg (London England). 2019;72:9–13. [DOI] [PubMed] [Google Scholar]
- 26.Planchez B, Surget A, Belzung C. Animal models of major depression: drawbacks and challenges. J neural transmission (Vienna Austria: 1996). 2019;126(11):1383–408. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.






