Prognostic value of lncRNA DARS-AS1 in colorectal cancer and its regulatory effect on tumor progression

Abstract

Background

Colorectal cancer (CRC) has high incidence and mortality with limited diagnostic and prognostic methods. This study explored the diagnostic and prognostic significance of the DARS-AS1 in CRC, and its regulatory mechanism via miR-188-5p.

Methods

The clinical significance of serum DARS-AS1 was analyzed using receiver operator characteristic (ROC) curves, Cox regression, the Kaplan–Meier method, and chi-square tests. DARS-AS1 silencing effects on CRC cell behavior were analyzed via CCK-8/Transwell assays. This study identified and validated miR-188-5p target genes using online databases and dual-luciferase reporter assays.

Results

Serum DARS-AS1 was elevated in CRC patients (P < 0.001), and distinguished them with an area under the curve (AUC) of 0.856. High DARS-AS1 was associated with adverse clinicopathological features (P < 0.05), shorter low disease-free survival (P = 0.008), and worse prognosis [hazard ratio (HR) = 2.400, P = 0.011]. DARS-AS1 was up-regulated in CRC cells (P < 0.001), and silencing it suppressed malignant behavior (P < 0.05). Serum miR-188-5p was down-regulated in CRC patients (P < 0.001), and had a target relationship with DARS-AS1 (r = − 0.733, P < 0.001). miR-188-5p target genes—including PTEN, ESR1, and FBXW7—were enriched in CRC-related pathways; FBXW7 was experimentally validated as a direct target (P < 0.05).

Conclusions

This study identifies serum DARS-AS1 as a non-invasive diagnostic and prognostic biomarker for CRC with superior performance to conventional markers, and elucidates the DARS-AS1/miR-188-5p/FBXW7 axis as a novel mechanistic framework for CRC progression, providing both a clinical tool for risk stratification and targets for molecular therapy.

Background

Colorectal cancer (CRC) is one of the most prevalent malignancies globally, characterized by high incidence and mortality. A substantial proportion of patients are diagnosed at advanced stages, facing considerable risks of postoperative recurrence and metastasis [1]. Current prognostic assessment methods, including tumor-node-metastasis (TNM) staging and conventional tumor markers, demonstrate limited sensitivity and often fail to provide timely information, particularly for patients without macroscopic disease following curative surgery [2]. Furthermore, for microsatellite-stable (MSS) metastatic CRC, which represents the majority of cases, the combination of immunotherapy and radiotherapy has emerged as a promising yet challenging strategy, highlighting the urgent need for novel biomarkers to guide personalized treatment decisions [3]. Accumulating evidence indicates that aberrant gene expression plays a pivotal role in CRC pathogenesis, and molecular profiling offers precise, individualized evidence to guide treatment decisions, evaluate therapeutic efficacy, and optimize drug regimens [4]. Given their non-invasive nature and ease of acquisition, serum biomarkers [5] have emerged as a promising avenue for dynamic monitoring and prognosis prediction in CRC.

Recent studies have further highlighted the critical roles of non-coding RNA (ncRNA) regulatory networks in CRC pathogenesis. For instance, LINC01836 promotes CRC progression by functioning as a competing endogenous RNA (ceRNA) to regulate SLC17A9 expression through sponging miR-1226-3p [6]. Similarly, circular RNA hsa_circ_0005939 enhances malignant phenotypes of CRC cells through the miR-4693-3p/UHRF1BP1L axis [7]. Additionally, investigations into novel molecular mechanisms and therapeutic strategies, such as the ERK/p65 pathway-mediated regulation of MMP9 in CRC metastasis [8] and autophagic flux modulation for enhancing chemotherapeutic sensitivity [9], and the p53/miR-34a/SIRT1 feedback loop-mediated regulation of radiosensitivity [10], have provided important insights into the molecular complexity of CRC. These findings collectively underscore the significance of exploring ncRNA-centered regulatory networks in understanding CRC progression, developing novel biomarkers, and optimizing therapeutic sensitivities.

Long non-coding RNAs (lncRNAs) play a crucial regulatory role in cancer, influencing tumor progression through diverse mechanisms. Due to their tissue-specific expression patterns and stability in body fluids, lncRNAs have emerged as promising disease biomarkers and therapeutic targets [11, 12]. DARS-AS1, a recently identified oncogenic lncRNA, has been shown to be overexpressed in gastric cancer [13], hepatocellular carcinoma [14] and triple-negative breast cancer [15], where its upregulation correlates closely with adverse clinicopathological features and poor prognosis. Furthermore, elevated DARS-AS1 serves as a predictive biomarker for osteosarcoma metastasis [16] and as an adjunct tool for the early diagnosis of cervical cancer [17]. The tissue- and body fluid-specific expression profile of DARS-AS1, combined with its functional role in regulating tumor progression, aligns well with the clinical need for novel, non-invasive biomarkers for CRC diagnosis and treatment. However, current research on DARS-AS1 has primarily focused on tissue-level analyses, and its expression patterns and prognostic value in serum from CRC patients remain unclear. Further research in this area could provide valuable non-invasive biomarkers for CRC assessment.

MicroRNAs (miRNAs) serve as crucial downstream effectors through which lncRNAs exert regulatory functions. Previous studies have demonstrated that DARS-AS1 frequently influences tumor progression by forming ceRNA networks via sponging miRNA [11, 12]. Among these, miR-188-5p is frequently dysregulated in digestive system cancers and participates in tumor progression by modulating related signaling pathways. In cholangiocarcinoma, downregulation of miR-188-5p influences cell migration and apoptosis by targeting the Wnt/β-catenin and p38/JNK pathways [18]. Aberrant miR-188-5p expression activates Wnt/β-catenin and MAPK pathways to promote gastric cancer metastasis [19, 20]; while in CRC, its downregulation promotes epithelial-mesenchymal transition (EMT), cell growth and metastasis [21, 22]. Elucidating the regulatory relationship between DARS-AS1 and downstream pathways is therefore essential for deepening our understanding of CRC mechanism and supporting the development of targeted interventions.

Beyond conventional chemotherapeutic agents, natural products and their derivatives have attracted considerable attention as alternative therapeutic strategies for CRC. For instance, magnolol, a natural compound derived from traditional Chinese medicine, has been shown to suppress CRC cell proliferation, migration, and invasion by targeting the FOXA2/CDK4 axis, and to overcome 5-fluorouracil resistance [23]. Similarly, extracts from various mushroom species have demonstrated selective cytotoxicity against HCT116 colorectal cancer cells while sparing healthy mesenchymal stem cells, suggesting their potential as novel sources of anticancer agents [24]. These studies reinforce the importance of identifying molecular biomarkers that can guide the application of diverse therapeutic modalities, including natural product-based interventions, in CRC management.

Building upon this background, the present study employed a combination of clinical samples, cellular experiments, and bioinformatics analysis to investigate the diagnostic and prognostic value of serum DARS-AS1 in CRC. The study aimed to validate the targeted regulatory relationship between DARS-AS1 and miR-188-5p, as well as the downstream mechanisms involved, thereby providing a novel biomarker for CRC prognosis assessment and potential targets for molecular therapy.

Patients and methods

Study population

A total of 132 patients diagnosed with CRC at Shanghai Sixth People′s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine between March 2018 and November 2024 were enrolled in this study. All patients were pathologically confirmed with CRC postoperatively, in accordance with established diagnostic criteria [25]. TNM staging was determined based on preoperative imaging and postoperative pathological examination. A control group comprising 118 patients with benign colorectal lesions treated at the same hospital during the same period was also selected. Benign lesions encompassed inflammatory bowel disease and adenomatous polyps (without high-grade intraepithelial neoplasia). This was an observational study, not a randomized controlled trial. CRC patients were enrolled using consecutive sampling, whereby all newly diagnosed CRC patients meeting the inclusion and exclusion criteria during the study period were sequentially enrolled without randomization. The control group was selected using frequency matching by age (± 5 years) and gender with the CRC group, randomly selected from patients with benign colorectal lesions treated at the same hospital during the same period, to control confounding factors and ensure baseline comparability between the two groups.

Both groups had complete clinical records and clear medical histories, and had not received any prior treatment involving hormones or immunomodulators within three months before admission. Patients with concomitant malignancies in other systems, severe hepatic or renal insufficiency, cardiovascular or cerebrovascular diseases, or active infectious diseases were excluded.

The study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Shanghai Sixth People′s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine before the study began. The written informed consent has been obtained from all the participants involved.

Serum samples collection and processing

Two groups of subjects provided 5 mL of venous blood in vacuum blood collection tubes containing a clotting agent in the early morning on an empty stomach. After standing at room temperature until layered, blood was centrifuged at 3000 rpm (4 °C, 15 min). The resulting serum was then aspirated using a sterile pipette and was divided into cryovials. Aliquots were immediately flash-frozen in liquid nitrogen and subsequently stored at − 80 °C until RNA extraction. To avoid degradation of circulating nucleic acids, repeated freeze-thaw cycles were strictly prohibited, and each aliquot was used only once. The maximum storage duration prior to analysis did not exceed 6 months.

Clinical data collection, grouping and follow-up

Basic clinical data, including demographic information and medical history, were collected for all study subjects. For patients in the CRC group, additional postoperative pathological data were collected, including tumor size (maximum diameter of the resected specimen measured macroscopically and microscopically), pathological grade [well-differentiated, moderately differentiated, poorly differentiated, and undifferentiated according to the World Health Organization (WHO) classification of digestive system tumors], depth of invasion [T1–T4 according to the 8th edition American Joint Committee on Cancer (AJCC) TNM staging system], TNM stage, lymph node metastasis (LNM) (number of positive lymph nodes and total lymph nodes examined), and nerve invasion. Nerve invasion was defined as the presence of tumor cells within the epineurium, perineurium, or endoneurium, or tumor cells surrounding at least one-third of the nerve circumference on routine hematoxylin and eosin (H&E)-stained postoperative pathological sections. All pathological parameters were evaluated independently by two experienced pathologists, and any discrepancies were resolved through joint consultation.

Based on the serum DARS-AS1 median, patients were divided into high- and low-expression groups (n = 66 in each group). This grouping was a post-hoc dichotomization based on the natural expression level of the biomarker, not a randomized grouping. The median cutoff was selected to objectively stratify prognostic risk based on the endogenous expression distribution of DARS-AS1. The median was selected as the cut-off value for the following reasons: (1) it ensures balanced sample sizes in both groups, thereby maximizing statistical power for subsequent survival comparisons; (2) it is robust against extreme values and skewed distributions, providing a more representative central tendency than the mean when the expression data may not follow a normal distribution; and (3) it represents a clinically practical dichotomization strategy widely adopted in biomarker prognostic studies, allowing straightforward risk stratification. Although ROC curve-derived thresholds optimize diagnostic accuracy, they are primarily designed for discriminating disease status rather than prognostic risk classification. Therefore, the median cut-off was deemed more appropriate for evaluating the association between DARS-AS1 expression and patient prognosis in this study.

Patients underwent a 5-year follow-up period commencing 3 months after hospital discharge, with follow-up concluding upon tumor-related death or the occurrence of severe complications (including malignant intestinal obstruction and cachexia). Follow-up was conducted through outpatient visits, telephone calls, or electronic communications at three-monthly intervals.

Cell lines and culture

The normal cell (NCM460), the CRC cells (HCT116 and RKO), were purchased from Stemrecell (Shanghai, China). The NCM460 cells were cultured in a 1640 medium (HyClone Laboratories, Logan, UT, USA). HCT116 cells were cultured in McCoy’s 5 A medium (HyClone Laboratories, Logan, UT, USA) and RKO cells in Minimum Essential Medium [MEM; containing non-essential amino acids (NEAA)] medium (HyClone Laboratories, Logan, UT, USA). All cell lines were authenticated using short tandem repeat (STR) profiling (PowerPlex 16 HS System; Promega, Madison, WI, USA) and matched against the ATCC/DSMZ databases. Mycoplasma contamination was excluded using the MycoAlert Mycoplasma Detection Kit (Lonza, Basel, Switzerland) prior to experimentation. Cells were used within 10 passages of thawing from the authenticated stock.

The cells were seeded in 75 cm² flasks (Corning, NY, USA) and cultured in a CB150 CO₂ incubator (Binder, Tuttlingen, Germany) at 37 °C with 5% CO₂ and saturated humidity.

Cell transfection

Cell transfection experiments were performed using the TransIT-X2 transfection reagent (Mirus Bio LLC, Madison, WI, USA). Small interfering RNA targeting DARS-AS1 (si-DARS-AS1), miR-188-5p mimics/inhibitors and their respective negative controls (NCs) were synthesized by Saides (Shanghai, China). The si-DARS-AS1 target sequence was 5’-GCAAGUACUUGGAGAUCAATT-3’ (sense) and 5’-UUGAUCUCCAAGUACUUGCTT-3’ (antisense), targeting nucleotides 342–360 of DARS-AS1 (NR_038854.1). The si-NC sequence was 5’-UUCUCCGAACGUGUCACGUTT-3’ (sense) and 5’-ACGUGACACGUUCGGAGAATT-3’ (antisense), with no homology to human genomic sequences confirmed by BLAST analysis.

One day before transfection, log-phase HCT116/RKO cells were seeded in 6-well plates. Transfection was done when cells reached ~ 70% confluence.

Two micrograms of the transfection reagent and 5 µL of the target RNA were dissolved separately in 50 µL of basal medium, and then mixed to form the transfection complex. The complex was evenly dispensed into the cell culture wells. After transfection, cells were incubated in an incubator for 48 h.

Real-time fluorescence quantitative PCR (RT-qPCR)

Total RNA and total miRNA were extracted from serum and cell samples, respectively, using the EasyPure^® RNA Kit (TransGen Biotech, Beijing, China) and the miRNeasy Mini Kit (Qiagen, Hilden, Germany). The RNA was then reverse transcribed into complementary DNA (cDNA) using the GoScript Reverse Transcription System (Promega, Madison, WI, USA).

The relative expression levels of DARS-AS1 and miR-188-5p were detected using SsoAdvanced Universal SYBR Green Supermix Reagent (Bio-Rad Laboratories, Hercules, CA, USA) and a miRNA qPCR Assay Kit (Cwbio, Beijing, China), respectively. Both were performed on a CFX96 real-time fluorescent qPCR instrument (Bio-Rad Laboratories, Hercules, CA, USA). Reaction systems and conditions followed the manufacturers’ instructions. U6 (forward 5’-CTCGCTTCGGCAGCACA-3’, reverse 5’-AACGCTTCACGAATTTGCGT-3’; Homo sapiens, NR_004394.1) served as the internal control gene for miR-188-5p (forward 5’-CGCGTCCCACATGCAGCTATT-3’, reverse 5’-AGTGCAGGGTCCGAGGTATT-3’; Homo sapiens, MIMAT0000459), while GAPDH (forward 5’-GGAGCGAGATCCCTCCAAAAT-3’, reverse 5’- GGCTGTTGTCATACTTCTCATGG-3’; Homo sapiens, NM_002046.5) served as the internal control gene for DARS-AS1 (forward 5’-GGTCTGGTGCTGGTAGTCTTG-3’, reverse 5’-AGGAGCAGAGGTGGTGAGAG-3’; Homo sapiens, NR_038854.1). Each sample was run in triplicate (five technical replicates), and the entire experiment was independently repeated three times.

Cell proliferation

Transfected HCT116 and RKO cells were seeded in a 96-well plate. Each experiment was independently repeated three times, and five replicate wells were included per group. 10 µL of CCK-8 solution (Dojindo Molecular Technologies, Kumamoto, Japan) was added to each well. The plates were gently shaken to ensure thorough mixing, then incubated for 2.5 h. The optical density (OD) values (450 nm) were measured in each well using a SpectraMax i3x microplate reader (Molecular Devices, San Jose, CA, USA).

Cell migration and invasion

Transfected HCT116 and RKO cells were re-suspended in serum-free basal medium. A total of 200 µL of cell suspension was added to the upper chamber and 700 µL of medium with 10% fetal bovine serum (FBS) was added to the lower chamber. The chambers were incubated for 24 h. Each experiment was independently repeated three times. After incubation, non-migrated cells in the upper chamber were wiped with a sterile cotton swab. The chamber was placed in a culture dish containing 4% paraformaldehyde (Electron Microscopy Sciences, Hatfield, PA, USA) and fixed at room temperature for 30 min. Subsequently, the cells were stained with 0.1% gentian violet solution (Saint-Bio, Shanghai, China) at room temperature for 20 min, rinsed with distilled water, and air-dried. Five fields of view were randomly selected for photography and observed using an IX73 inverted microscope (Olympus, Tokyo, Japan).

For the invasion assay, Transwell chambers were pre-coated with Matrigel matrix gel (Corning, NY, USA). Matrigel was diluted 1:8 with serum-free basal medium. A total of 50 µL were evenly spread across the bottom of the upper chamber cavity and incubated at 37 °C for 4 h until the matrix gel solidified. Subsequent steps followed the migration assay protocol.

Bioinformatics analysis

The DARS-AS1 level between CRC tissues and normal colorectal tissues were analyzed using the GEPIA database, as well as its correlation with overall survival in CRC patients. The potential target genes of miR-188-5p were predicted using the TargetScan, miRDB and miRWalk databases. Candidate target genes were selected from the intersection of the predictions from all three databases and a Venn diagram was constructed. DAVID was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of candidate target genes; GO analysis included biological processes (BP), cellular components (CC) and molecular functions (MF). STRING was used to build a protein-protein interaction (PPI) network for candidate target genes. The UALCAN database was then used to analyze the level of the three core target genes (PTEN, ESR1 and FBXW7) in CRC tissue compared to normal colorectal tissue.

Dual-luciferase reporter assay

Point mutations were introduced to generate DARS-AS1/FBXW7 mutant (MUT) variants. The wild-type (WT) and MUT variants were then inserted into the psiCHECK™-2 vector (Promega, Madison, WI, USA) to create luciferase reporter vectors.

HCT116 and RKO cells were seeded in 24-well plates. Once they had reached approximately 60% confluence, the luciferase reporter vectors were co-transfected with miR-188-5p mimics/inhibitors using TransIT-X2 transfection reagent (Mirus). Each transfection condition was independently repeated three times in separate experiments. 48 h later, luciferase activity was detected with the Dual-Luciferase Reporter Assay System (Promega, Madison, WI, USA) using a Tristar LB 941 microplate reader (Berthold Technologies, Bad Wildbad, Germany). Firefly/Renilla luciferase activity ratio was calculated.

Statistical analysis

The normality of continuous data distribution was assessed using the Shapiro-Wilk test (n < 50) or Kolmogorov-Smirnov test (n ≥ 50). Homogeneity of variance was evaluated by Levene’s test. For cell-based assays, data from three independent biological replicates were pooled for analysis. T-tests were used for comparisons between two groups of measurement data, while analysis of variance (ANOVA) was employed for comparisons among multiple groups, with pairwise comparisons performed using Student-Newman-Keuls (SNK-q) tests. Chi-squared tests or Fisher’s exact tests were used to compare categorical data between groups.

Pearson correlation analysis was applied to assess the relationship between serum DARS-AS1 and miR-188-5p levels. Receiver operating characteristic (ROC) curve was performed to evaluate the diagnostic value of DARS-AS1 for CRC.

Cox proportional hazards regression models were constructed to identify independent prognostic factors in CRC patients. Prior to model construction, the proportional hazards (PH) assumption was assessed for each included clinical and pathological covariate using Schoenfeld residual tests (global test and individual covariate tests). The results confirmed that all variables satisfied the PH assumption (global test P > 0.05), indicating that the Cox model was appropriate for this dataset. Variables were selected for multivariate Cox regression based on clinical relevance and univariate analysis results; the Enter method (forced entry) was used to include all clinically significant variables (tumor size, pathological grade, depth of invasion, TNM stage, LNM, nerve invasion, and DARS-AS1 expression) simultaneously to control for confounding. Survival analysis was performed using the Kaplan–Meier method, with between-group comparisons conducted using the log-rank test.

All statistical analyses were performed using SPSS Statistics version 26.0 (IBM Corp., Armonk, NY, USA) and GraphPad Prism version 9.5.0 (GraphPad Software, San Diego, CA) software, and a two-tailed P value < 0.05 was considered statistically significant. No imputation was performed for missing data, and cases with missing values in survival analysis were excluded using listwise deletion.

Results

Comparison of basic information of the research subjects

The baseline demographic and clinical characteristics of the 132 CRC patients and 118 control subjects are summarized in Table 1. No significant differences were observed between the two groups in terms of age (P = 0.444), gender (P = 0.351), body mass index (BMI; P = 0.174), smoking history (P = 0.336), drinking history (P = 0.388), history of digestive system diseases (P = 0.410) or lesion location (P = 0.298). These results indicate that the two groups were well matched at baseline, rendering them suitable for subsequent comparative studies. Additionally, this study involved conducting a statistical analysis of the clinical and pathological outcomes of CRC patients.

Table 1.

Baseline characteristics of CRC patients and control subjects

Factors	CRC (N = 132)	Control (N = 118)	P value
Age (years)	56.69 ± 9.06	55.82 ± 8.75	0.444
Gender n (%)			0.351
Female	56 (42.42)	58 (48.31)
Male	76 (57.58)	61 (51.69)
BMI (kg/m2)	24.28 ± 3.73	23.63 ± 3.74	0.174
Smoking history n (%)			0.336
No	90 (68.18)	87 (73.73)
Yes	42 (31.82)	31 (26.27)
Drinking history n (%)			0.388
No	78 (59.09)	76 (64.41)
Yes	54 (40.91)	42 (35.59)
Digestive system diseases history n (%)			0.410
No	103 (78.03)	97 (82.20)
Yes	29 (21.97)	21 (17.80)
Lesion location n (%)			0.298
Colon	80 (60.61)	79 (66.95)
Rectum	52 (39.39)	39 (33.05)
Pathological pattern n (%)			-
Adenocarcinoma	117 (88.64)	-
Other	15 (11.36)	-
Tumor size (cm) n (%)			-
< 5	51 (38.64)	-
≥ 5	81 (61.36)	-
Pathological grading n (%)			-
High	65 (49.24)	-
Low-Medium	67 (50.76)	-
Infiltration depth n (%)			-
T1-T2	54 (40.91)	-
T3-T4	78 (59.09)	-
TNM stage n (%)			-
I-II	86 (65.15)	-
III-IV	46 (34.85)	-
LNM n (%)			-
Negative	93 (70.45)	-
Positive	39 (29.55)	-
Neural invasion n (%)			-
Negative	104 (78.79)	-
Positive	28 (21.21)	-
Vascular invasion n (%)			-
Negative	99 (75.00)	-
Positive	33 (25.00)	-

CRC Colorectal cancer, BMI Body mass index, TNM Tumor node metastasis, LNM Lymph node metastasis. Continuous variables are presented as mean ± standard deviation (SD), and categorical variables are presented as number (percentage). The P values for continuous variables were calculated using independent samples t-test, and those for categorical variables using chi-squared test or Fisher’s exact test. P < 0.05 means a significant difference. The control group comprised patients with benign colorectal lesions (inflammatory bowel disease and adenomatous polyps without high-grade intraepithelial neoplasia) who were frequency-matched to the CRC group by age (± 5 years) and gender

Expression level of DARS-AS1 and its diagnostic value

As shown in Fig. 1A, GEPIA analysis revealed that DARS-AS1 expression in CRC tissues was significantly higher compared to normal colorectal tissues (P < 0.01). Survival analysis showed patients with high DARS-AS1 expression had significantly shorter overall survival (Fig. 1B).

Fig. 1.

DARS-AS1 expression in CRC and its diagnostic value. A DARS-AS1 expression level in CRC and normal tissues via GEPIA database (http://gepia.cancer-pku.cn/). The analysis included 275 CRC tissue samples and 349 normal colorectal tissue samples from The Cancer Genome Atlas (TCGA) dataset. Y-axis: DARS-AS1 expression (Transcripts Per Million, TPM). Statistical significance was determined using t-test. B Overall survival curve of CRC patients with high versus low DARS-AS1 expression via GEPIA database. Patients were stratified into high- and low-expression groups based on the median DARS-AS1 expression level. X-axis: Time (months); Y-axis: Percent survival. C Relative expression of serum DARS-AS1 in 132 CRC patients and 118 control subjects with benign colorectal lesions, as determined by RT-qPCR. Y-axis: Relative DARS-AS1 expression (normalized to GAPDH, 2^−ΔΔCt method). D Diagnostic value of serum DARS-AS1 for CRC assessed by ROC curve analysis. The AUC, sensitivity, specificity, and 95% confidence interval were calculated. X-axis: 100% – Specificity%; Y-axis: Sensitivity%. Data represent mean ± standard deviation (SD). ***, P < 0.001

Quantitative RT-qPCR analysis shown in Fig. 1C demonstrated that DARS-AS1 expression was significantly higher in the serum of CRC patients compared to controls (P < 0.001). ROC curve analysis indicated that serum DARS-AS1 exhibited an area under the curve (AUC) of 0.856 [95% confidence interval (CI): 0.810–0.903] for diagnosing CRC, with a sensitivity of 79.55% and a specificity of 83.05% (P < 0.001, Fig. 1D). These results demonstrate that serum DARS-AS1 possesses good diagnostic performance for CRC.

The correlation between DARS-AS1 expression and the clinical characteristics of CRC patients

Serum DARS-AS1 expression in CRC patients was significantly correlated with tumor size (P = 0.020), pathological grade (P = 0.003), depth of invasion (P < 0.001), TNM stage (P < 0.001), LNM (P < 0.001) and nerve invasion (P = 0.033). Specifically, CRC patients exhibiting one or more of the following characteristics demonstrated higher serum DARS-AS1 expression: tumor size ≥ 5 cm, low-medium differentiation, T3-T4 invasion depth, stage III-IV disease, and the presence of LNM and nerve invasion (Table 2).

Table 2.

Association between serum lncRNA DARS-AS1 expression levels and clinicopathological characteristics in CRC patients

Variables	CRC (N = 132)	DARS-AS1 expression		P value
		Low (n = 66)	High (n = 66)
Age (years)				0.223
< 56	65	36 (54.55)	29 (43.94)
≥ 56	67	30 (45.45)	37 (56.06)
Gender				0.291
Female	56	31 (46.97)	25 (37.88)
Male	76	35 (53.03)	41 (62.12)
BMI (kg/m2)				0.117
< 24.2	65	37 (56.06)	28 (42.42)
≥ 24.2	67	29 (43.94)	38 (57.58)
Smoking history				0.135
No	90	49 (74.24)	41 (62.12)
Yes	42	17 (25.76)	25 (37.88)
Drinking history				0.288
No	78	42 (63.64)	36 (54.55)
Yes	54	24 (36.36)	30 (45.45)
Digestive system diseases history				0.528
No	103	53 (80.30)	50 (75.76)
Yes	29	13 (19.70)	16 (24.24)
Lesion location				0.154
Colon	80	36 (54.55)	44 (66.67)
Rectum	52	30 (45.45)	22 (33.33)
Pathological pattern				0.784
Adenocarcinoma	117	59 (89.39)	58 (87.88)
Other	15	7 (10.61)	8 (12.12)
Tumor size (cm)				0.020
< 5	51	32 (48.48)	19 (28.79)
≥ 5	81	34 (51.52)	47 (71.21)
Pathological grading				0.003
High	65	41 (62.12)	24 (36.36)
Low-Medium	67	25 (37.88)	42 (63.64)
Infiltration depth				< 0.001
T1-T2	54	37 (56.06)	17 (25.76)
T3-T4	78	29 (43.94)	49 (74.24)
TNM stage				< 0.001
I – II	86	54 (81.82)	32 (48.48)
III – IV	46	12 (18.18)	34 (51.52)
LNM				< 0.001
Negative	93	56 (84.85)	37 (56.06)
Positive	39	10 (15.15)	29 (43.94)
Neural invasion				0.033
Negative	104	57 (86.36)	47 (71.21)
Positive	28	9 (13.64)	19 (28.79)
Vascular invasion				0.547
Negative	99	51 (77.27)	48 (72.73)
Positive	33	15 (22.73)	18 (27.27)

CRC Colorectal cancer, BMI Body mass index, TNM Tumor node metastasis, LNM Lymph node metastasis. Patients were stratified into high-expression (n = 66) and low-expression (n = 66) groups based on the median serum DARS-AS1 expression level as determined by RT-qPCR. The median cutoff was selected to ensure balanced group sizes, maximize statistical power, and provide robustness against extreme values and non-normal distributions. Chi-squared test was used to compare the distribution of clinicopathological characteristics between the high- and low-DARS-AS1 expression groups. P < 0.05 means a significant difference. Bold values indicate statistically significant differences

The relationship between DARS-AS1 expression and the prognosis of CRC patients

Multivariate Cox regression analysis, presented as a forest plot in Fig. 2A, identified the following independent risk factors for poor prognosis in CRC patients: tumor size [hazard ratio (HR) = 2.193, P = 0.038], pathological grade (HR = 2.228, P = 0.020), depth of invasion (HR = 2.576, P = 0.017), TNM staging (HR = 4.274, P < 0.001), LNM (HR = 4.688, P < 0.001), and DARS-AS1 expression (HR = 2.400, P = 0.011).

Fig. 2.

Risk factors for poor prognosis and survival analysis stratified by serum DARS-AS1 in CRC patients. A Forest plot of independent risk factors for poor prognosis in CRC patients by multivariate Cox proportional hazards regression analysis. Variables were entered into the model using the forced entry (Enter) method, including tumor size, pathological grade, depth of invasion, TNM stage, lymph node metastasis (LNM), nerve invasion, and DARS-AS1 expression. X-axis: Hazard ratio (HR) with 95% confidence interval; Y-axis: Clinical and pathological variables. B Kaplan–Meier disease-free survival curve for 132 CRC patients stratified by serum DARS-AS1 expression level (high vs. low). Patients were divided into high-expression (n = 66) and low-expression (n = 66) groups based on the median serum DARS-AS1 expression level. X-axis: Time (months); Y-axis: Disease-free survival. Between-group comparisons were performed using the log-rank test

Kaplan–Meier survival analysis (Fig. 2B) further revealed that the 5-year disease-free survival rate of high DARS-AS1 expression CRC patients was significantly lower, with survival curves showing significant differences (Log-Rank P = 0.008).

The influence of DARS-AS1 on the biological behavior of CRC cells

Compared with the normal colonic epithelial cell line NCM460, DARS-AS1expression was significantly higher in CRC cell lines HCT116 and RKO (P < 0.001, Fig. 3A). After DARS-AS1 silencing, DARS-AS1 expression was significantly reduced in both cell lines (P < 0.001, Fig. 3B).

Fig. 3.

DARS-AS1 expression in CRC cell lines and the effect of its silencing on malignant biological behavior. A Relative DARS-AS1 expression in normal human colonic epithelial cell line (NCM460) and CRC cell lines (HCT116, RKO), as determined by RT-qPCR. Y-axis: Relative DARS-AS1 expression (normalized to GAPDH). B Relative DARS-AS1 expression in HCT116 and RKO cells 48 h after transfection with small interfering RNA targeting DARS-AS1 (si-DARS-AS1) or negative control siRNA (si-NC). Y-axis: Relative DARS-AS1 expression. C, D Cell proliferation activity of HCT116 (C) and RKO (D) measured by CCK-8 assay at indicated time points (0, 24, 48, 72 h and 96 h). Five replicate wells per group and three independent biological replicates. X-axis: Time (hours); Y-axis: Optical density (OD) value at 450 nm. E, F Migration (E) and invasion (F) abilities of HCT116 and RKO cells assessed by Transwell assay 24 h after transfection (scale bar = 100 μm). Y-axis: Number of migrated or invaded cells per field. Data represent mean ± SD from three independent biological replicates with five technical replicates per group. *, P < 0.05; **, P < 0.01; ***, P < 0.001 vs. NCM460 or Control (si-NC) group

CCK-8 proliferation assays (Fig. 3C and D) showed that DARS-AS1 silencing significantly inhibited the proliferative activity of HCT116 cells after 24 h of culture (Fig. 3C) and of RKO cells after 48 h (Fig. 3D) (P < 0.01). Transwell migration and invasion assays (Fig. 3E and F) demonstrated that silencing DARS-AS1 significantly reduced the number of migrating and invasive cells of both HCT116 and RKO cells (P < 0.05, Fig. 3E and F).

The expression correlation and targeting relationship between miR-188-5p and DARS-AS1

Serum miR-188-5p levels was significantly lower in CRC patients compared to controls (P < 0.001, Fig. 4A). Scatter plot analysis revealed a significant negative correlation between serum DARS-AS1 and miR-188-5p expression levels (r = -0.733, P < 0.001, Fig. 4B). Bioinformatics prediction revealed a potential binding site between DARS-AS1 and miR-188-5p (Fig. 4C).

Fig. 4.

Serum miR-188-5p expression in CRC patients and its direct targeting relationship with DARS-AS1. A Relative serum miR-188-5p expression in 132 CRC patients and 118 control subjects, as determined by RT-qPCR. Y-axis: Relative miR-188-5p expression (normalized to U6, 2^−ΔΔCt method). B Pearson correlation analysis between serum DARS-AS1 and miR-188-5p expression levels in 132 CRC patients. X-axis: Serum DARS-AS1 relative expression; Y-axis: Serum miR-188-5p relative expression. C Potential binding sites between DARS-AS1 and miR-188-5p predicted by bioinformatics analysis. D, E Dual-luciferase reporter assay verifying the targeting relationship between DARS-AS1 and miR-188-5p in HCT116 (D) and RKO (E) cells. Wild-type (WT) DARS-AS1 sequence containing the predicted miR-188-5p binding site and mutant (MUT) variant with point mutations in the seed region were cloned into the psiCHECK™-2 vector. Co-transfected with reporter vectors (WT or MUT) and miR-188-5p mimics, miR-188-5p inhibitors, or negative controls (NC) using TransIT-X2 reagent. Y-axis: Relative luciferase activity (Firefly/Renilla). Data are presented as mean ± SD from three independent biological replicates. **, P < 0.01; ***, P < 0.001

In HCT116 and RKO cells, miR-188-5p mimic significantly reduced the luciferase activity of the DARS-AS1-WT reporter vector (P < 0.01), while inhibitor significantly increased this activity (P < 0.001). No significant changes in luciferase activity were observed with the DARS-AS1-MUT reporter vector in either group (Fig. 4D and E). These results confirm a direct targeting relationship between DARS-AS1 and miR-188-5p.

Prediction and enrichment analysis of the target genes of miR-188-5p

The potential target genes of miR-188-5p were predicted using TargetScan, miRDB, and miRWalk databases. The intersection of predictions from all three databases identified 88 core candidate target genes (Fig. 5A).

Fig. 5.

Bioinformatics prediction and functional enrichment of miR-188-5p target genes. A Venn diagram showing the intersection of miR-188-5p potential target genes predicted from three databases: TargetScan (http://www.targetscan.org/), miRDB (http://mirdb.org/), and miRWalk (http://zmf.umm.uni-heidelberg.de/apps/zmf/mirwalk/). The overlapping 88 genes were selected as core candidate target genes. B GO enrichment analysis for 88 candidate target genes performed using DAVID Bioinformatics Resources (https://david.ncifcrf.gov/), including biological process (BP), cellular component (CC), and molecular function (MF). The top 10 enriched terms in each category are displayed. C KEGG pathway enrichment analysis for 88 candidate target genes performed using DAVID. The top 10 enriched pathways are displayed. Y-axis: Enriched pathways; X-axis: enrichment score

GO analysis revealed that the candidate target genes were primarily enriched in BP including ‘synapse assembly’, ‘B cell apoptotic process’, and ‘regulation of hemopoiesis’’, among others. In CC, they were enriched in the ‘histone methyltransferase complex’, ‘methyltransferase complex’, and ‘PcG protein complex’, among others. In MF, they were enriched in “transcription coregulator binding”, “miRNA binding”, “regulatory RNA binding”, and “protein phosphorylated amino acid binding”, among others (Fig. 5B).

KEGG pathway analysis revealed that the candidate target genes were primarily enriched in the ‘mTOR signaling pathway’, the ‘p53 signaling pathway’, ‘autophagy - animal’, ‘tight junctions’, and ‘microRNAs in cancer’ (Fig. 5C). These pathways are all closely associated with tumorigenesis and cancer progression.

As visualized in the PPI network (Fig. 6), the analysis revealed a regulatory network comprising 88 gene/protein nodes and 254 edges (PPI enrichment P < 0.01). The core target genes with node degrees of at least 15 included PTEN, ESR1, FBXW7, KMT2C, JARID2, RASA1, HNRNPA2B1, SUMO2 and UBE2I. Notably, PTEN, ESR1 and FBXW7 exhibited the highest degree values of 33, 27 and 20, respectively, identifying them as the top three hub genes in the network.

Fig. 6.

Protein–protein interaction (PPI) network of 88 candidate target genes of miR-188-5p constructed using the STRING database (https://string-db.org/). Nodes represent proteins; edges represent protein–protein associations (confidence score > 0.2). Node size and color intensity are proportional to the degree of connectivity. The top three hub genes with the highest degrees (PTEN, degree = 33; ESR1, degree = 27; and FBXW7, degree = 20) are shown. PPI enrichment P < 0.01

Core target gene expression and targeted relationship verification

UALCAN database analysis of transcript levels (Fig. 7A–C) revealed that, compared to normal colorectal tissue, PTEN and ESR1 expression was significantly down-regulated in CRC tissue (P < 0.001, Fig. 7A and B), whereas FBXW7 expression was significantly up-regulated (P < 0.001, Fig. 7C). Since the expression trends of PTEN and ESR1 were inconsistent with the typical pattern of miRNA-mRNA target regulation (i.e., miRNA downregulation should correspond to target gene upregulation), and instead aligned with the downregulation of miR-188-5p, FBXW7 was selected for further analysis in this study.

Fig. 7.

Expression of core target genes and verification of the direct targeting relationship between miR-188-5p and FBXW7. A-C Relative expression of PTEN (A), ESR1 (B), and FBXW7 (C) in CRC and normal colorectal tissues via UALCAN database (http://ualcan.path.uab.edu/), based on TCGA transcriptome data. Y-axis: Relative expression (TPM). D Potential binding sites between miR-188-5p and FBXW7 predicted by the ENCORI database (http://starbase.sysu.edu.cn/). E, F Dual-luciferase reporter assay verifying the direct targeting relationship between miR-188-5p and FBXW7 in HCT116 (E) and RKO (F) cells. Wild-type (WT) FBXW7 3’-UTR sequence containing the predicted miR-188-5p binding site and mutant (MUT) variant with point mutations were cloned into the psiCHECK™-2 vector. Cells were co-transfected with reporter vectors and miR-188-5p mimics, inhibitors, or negative controls (NC) using TransIT-X2 reagent. Y-axis: Relative luciferase activity (Firefly/Renilla). Data are presented as mean ± SD from three independent biological replicates. *, P < 0.05; **, P < 0.01; ***, P < 0.001

ENCORI database prediction identified a potential binding site between miR-188-5p and FBXW7 (Fig. 7D). In HCT116 and RKO cells, miR-188-5p mimic significantly reduced FBXW7-WT vector luciferase activity (P < 0.05), while inhibitor significantly increased it (P < 0.001). No significant changes in FBXW7-MUT vector luciferase activity in either group (Fig. 7E and F). These results confirm a direct targeting relationship between miR-188-5p and FBXW7.

Discussion

Postoperative recurrence and metastasis remain significant challenge in clinical management of CRC. Even among patients with stage I–II disease, the five-year recurrence rate ranges from 10% to 25% [26]. However, existing clinical monitoring methods exhibit substantial limitations. TNM staging struggles to identify occult high-risk patients [27], while conventional tumor markers such as carbohydrate antigen 19 − 9 (CA19-9) demonstrate high false-positive rates when monitoring disease-free status after surgery and fail to accurately predict recurrence risk [28]. This ‘assessment lag’ means that some patients miss the optimal window for postoperative intervention. Therefore, the development of novel molecular biomarkers capable of predicting early recurrence and correlating with disease aggressiveness has become crucial for overcoming current bottlenecks in CRC diagnosis and treatment. Notably, recent advances in the combination of immunotherapy and radiotherapy for MSS metastatic CRC underscore the necessity of robust biomarkers for patient stratification and treatment optimization [3].

In recent years, numerous lncRNAs associated with disease progression have been identified. Due to their stability in body fluids, tissue specificity, and close association with disease progression, lncRNAs have become a focal area of biomarker research. For example, SNHG15 is highly expressed in CRC and represents a potential therapeutic target [29]. RUNDC3A-AS1, which is associated with glycolysis, holds significant predictive value for CRC progression and prognosis [30]. Downregulation of PCAT19 serves as a potential diagnostic marker and therapeutic target [31]. DARS-AS1, located on chromosome 2q21.3, is a confirmed oncogenic factor in multiple cancer types [11, 12]. Its association with LNM, advanced TNM staging and poor survival in gastric and liver cancers suggests it may play a common oncogenic role in cancers of the digestive system [13, 14]. It is also considered a potential diagnostic adjunct in osteosarcoma and cervical cancer [16, 17]. The present study found that DARS-AS1 was highly expressed in both tissue and serum samples from CRC patients, effectively distinguishing CRC from benign lesions. Its diagnostic performance (AUC = 0.856) was superior to that of traditional tumor markers such as carcinoembryonic antigen (CEA), CA19-9 and cytokeratin fragment antigen 21 − 1 (CYFRA 21 − 1) (AUC = 0.6–0.7) [32]. Notably, patients with high DARS-AS1 expression exhibited significantly reduced overall and disease-free survival. Multivariate Cox regression analysis confirmed its role as an independent risk factor for poor prognosis. These findings suggest that DARS-AS1 could advance two key areas of CRC clinical practice: the development of early-stage diagnostic serum biomarkers and the refinement of postoperative recurrence prediction indicators.

Tumor size, TNM staging, LNM and nerve invasion are key factors in the clinical assessment of CRC malignancy. Patients with stage III–IV disease exhibit significantly higher malignancy due to deeper tumor progression compared to stage I–II, with a reduction in 5-year survival rate of approximately 40% [33]. Tumors measuring ≥ 5 cm in diameter often exhibit broader local invasion, while LNM indicates enhanced tumor dissemination capacity, both signify increased CRC malignancy [34]. Nerve invasion reflects increased tumor aggressiveness and correlates with a higher risk of postoperative recurrence and reduced survival [35]. This study found that high DARS-AS1 expression was significantly associated with these adverse clinical features, specifically, correlating with tumor diameter of at least 5 cm, low-medium differentiation, invasion depth of T3-T4, stage III-IV disease, and the presence of LNM and nerve invasion. These findings suggest that DARS-AS1 may serve as a “molecular complement” to traditional clinical indicators, providing additional information for reflecting the degree of malignant progression in CRC.

Uncontrolled cell proliferation is the core mechanism driving tumor growth, while enhanced migration and invasion capabilities are key prerequisites for metastasis. HCT116 cells exhibit robust proliferative activity and a high degree of invasiveness, aligning with the biological characteristics of advanced CRC. In contrast, RKO cells demonstrate relatively lower malignancy, more closely resembling the behavior of early-to-mid-stage CRC lesions [36]. Therefore, this study selected these two cell lines to comprehensively investigate the effects of DARS-AS1 on CRC cell behavior. The results showed that DARS-AS1 was up-regulated in both cell lines and that silencing its expression effectively inhibited cell proliferation, migration, and invasion. These findings suggest that DARS-AS1 may facilitate the progression of CRC from localized lesions to malignant invasive metastasis by regulating these critical biological behaviors.

miRNA serves as the core downstream effectors through which lncRNAs exert regulatory functions, often forming ceRNA networks to modulate disease progression [37]. miR-188-5p has been demonstrated to suppress tumor growth in multiple cancers of the digestive system. In cholangiocarcinoma, it inhibits cell migration by targeting PSMD10 and the Wnt/β-catenin pathway [18, 38]. In gastric cancer, it impedes MAPK pathway-mediated metastasis [19, 20]. In oral squamous cell carcinoma, it inhibits cell growth, and its downregulation promotes malignant progression [39]. In CRC, it has also been shown to regulate cell growth and metastasis [21, 22]. The present study found that serum miR-188-5p expression was significantly reduced in CRC patients and was strongly negatively correlated with DARS-AS1 expression. Dual-luciferase reporter assays further confirmed that miR-188-5p binds directly to specific sequences within DARS-AS1, thereby inhibiting its luciferase activity. These results suggest that DARS-AS1 can function as a sponge for miR-188-5p, releasing its suppression of downstream target genes and thereby maintaining the malignant phenotype of CRC cells. Intriguingly, the involvement of ncRNA-mediated regulatory loops in modulating therapeutic sensitivity has been increasingly recognized. For example, the p53/miR-34a/SIRT1 feedback loop serves as a critical modulator of metformin-induced radiosensitivity in colorectal cancer cells, wherein miR-34a upregulation suppresses SIRT1 to stabilize p53 and promote apoptosis [10]. Although the present study focused on the DARS-AS1/miR-188-5p/FBXW7 axis in regulating basal malignant behaviors, the potential interplay between this axis and treatment sensitivity—particularly radiotherapy and chemotherapy resistance—represents a compelling avenue for future investigation.

In-depth analysis of miRNA downstream target genes is crucial for identifying core nodes in lncRNA regulatory networks and elucidating the molecular mechanisms underlying CRC progression [40]. This study identified 88 candidate target genes of miR-188-5p. GO analysis revealed enrichment in CRC-related biological processes such as cell adhesion regulation and B-cell apoptosis, while KEGG analysis pointed to classic oncogenic pathways including the mTOR and p53 signaling pathways. These findings suggest that these genes may serve as key regulators of CRC cell malignancy. Further screening via the PPI network identified three core target genes: PTEN, ESR1 and FBXW7. PTEN expression negatively correlates with tumor size and metastasis; its downregulation activates the PI3K/AKT signaling pathway, accelerating CRC progression [41]. Abnormal ESR1 expression affects CRC cell apoptosis and invasion [42]. FBXW7 participates in cell cycle regulation by modulating oncoprotein degradation [43]. This study found that the expression trends of PTEN and ESR1 in CRC tissues deviated from the conventional miRNA target regulation patterns (where miRNA downregulation should theoretically lead to target gene upregulation), instead aligning with the downregulation of miR-188-5p. This suggests that their regulation may be indirect or subject to additional regulatory mechanisms. In contrast, FBXW7 was highly expressed in CRC tissues and possessed a predicted binding site for miR-188-5p. Dual-luciferase reporter assay confirmed their direct interaction. Consequently, this study speculated that DARS-AS1 may sponge miR-188-5p, thereby relieving its inhibitory effect on FBXW7 and subsequently promoting malignant cell behavior and disease progression in CRC.

Moreover, the identification of the DARS-AS1/miR-188-5p/FBXW7 axis aligns with the broader paradigm of multi-targeted therapeutic strategies in CRC. Recent studies have demonstrated that natural compounds such as magnolol can inhibit CRC progression and overcome 5-fluorouracil resistance through the FOXA2/CDK4 pathway [23], while mushroom-derived extracts exhibit selective antiproliferative effects against CRC cells [24]. These findings suggest that the DARS-AS1/miR-188-5p/FBXW7 axis may not only serve as a prognostic biomarker but also as a potential target for natural product-based combination therapies, warranting further investigation into synergistic treatment modalities.

However, this study has certain limitations. Samples from a single center may introduce selection bias, and although the proportional hazards assumption was satisfied in the Cox regression, the stability of hazard ratios over extended follow-up requires validation in larger, multicenter cohorts. The regulatory effect of DARS-AS1 on CRC cell growth and metastasis has not been validated through animal experiments. Therefore, it is necessary to expand the sample size to multiple centers and construct a CRC animal model in future studies to further verify the role of the DARS-AS1/miR-188-5p/FBXW7 regulatory axis. The use of the median serum DARS-AS1 expression level as the cut-off points for prognostic stratification, while ensuring balanced group sizes and statistical power, may not represent the optimal threshold for predicting clinical outcomes. Alternative approaches, such as ROC curve analysis for prognostic endpoints or the minimum P-value method (e.g., X-tile software), might identify cut-off values with superior predictive accuracy; however, these methods can introduce bias when applied to small sample sizes and were therefore not adopted here. Future large-scale multicenter studies should validate whether the median remains the most appropriate cut-off or whether a data-driven optimal threshold improves risk stratification.

Conclusion

To summarize, this study found demonstrates that DARS-AS1 is highly expressed in CRC patients and serves as a serum biomarker with potential utility for diagnosing CRC, assessing malignant progression, and monitoring prognosis. Mechanistically, DARS-AS1 regulates CRC malignant progression via the DARS-AS1/miR-188-5p/FBXW7 axis. These findings provide a novel molecular tool for the precise diagnosis and treatment of CRC, while offering new insights into the molecular mechanisms underlying CRC progression.

Authors’ contributions

Qiaoyu Chen: Conceptualization, Data curation, Resources, Project administration, Validation, Writing - original draft. Qijin Xu: Formal analysis, Investigation, Software, Visualization, Writing - original draft. Li Zhang: Data curation, Methodology, Supervision, Visualization, Writing - review & editing.

Funding

The funding source had no role in the design, practice or analysis of this study.

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

The study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Shanghai Sixth People′s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine before the study began. The written informed consent has been obtained from all the participants involved.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.