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. 2024 Sep 9;24(5):158. doi: 10.1007/s10142-024-01436-6

Long non-coding RNA MAGEA4-AS1 binding to p53 enhances MK2 signaling pathway and promotes the proliferation and metastasis of oral squamous cell carcinoma

Xiaoxiao Wei 1,2,#, Zhangfu Li 2,#, Heng Zheng 1,2, Xiaolian Li 2, Yuntao Lin 2, Hongyu Yang 1,2,✉, Yuehong Shen 1,2,✉
PMCID: PMC11384635  PMID: 39249547

Abstract

Long non-coding RNAs (lncRNAs) regulate the occurrence, development and progression of oral squamous cell carcinoma (OSCC). We elucidated the expression features of MAGEA4-AS1 in patients with OSCC and its activity as an OSCC biomarker. Furthermore, the impact of up-regulation of MAGEA4-AS1 on the cellular behaviors (proliferation, migration and invasion) of OSCC cells and intrinsic signal mechanisms were evaluated. Firstly, we analyzed MAGEA4-AS1 expression data in The Cancer Genome Atlas (TCGA) OSCC using a bioinformatics approach and in 45 pairs of OSCC tissues using qPCR. Then CCK-8, ethynyl deoxyuridine, colony formation, transwell and wound healing assays were conducted to assess changes in the cell proliferation, migration and invasion protential of shMAGEA4-AS1 HSC3 and CAL27 cells. The RNA sequence of MAGEA4-AS1 was identified using the rapid amplification of cDNA ends (RACE) assay. And whole-transcriptome sequencing was used to identify MAGEA4-AS1 affected genes. Additionally, dual-luciferase reporter system, RNA-binding protein immunoprecipitation (RIP), and rescue experiments were performed to clarify the role of the MAGEA4-AS1-p53-MK2 signaling pathway. As results, we found MAGEA4-AS1 was up-regulated in OSCC tissues. We identified a 418 nucleotides length of the MAGEA4-AS1 transcript and it primarily located in the cell nucleus. MAGEA4-AS1 stable knockdown weakened the proliferation, migration and invasion abilities of OSCC cells. Mechanistically, p53 protein was capable to activate MK2 gene transcription. RIP assay revealed an interaction between p53 and MAGEA4-AS1. MK2 up-regulation in MAGEA4-AS1 down-regulated OSCC cells restored MK2 and epithelial-to-mesenchymal transition related proteins’ expression levels. In conclusion, MAGEA4-AS1-p53 complexes bind to MK2 promoter, enhancing the transcription of MK2 and activating the downstream signaling pathways, consequently promoting the proliferation and metastasis of OSCC cells. MAGEA4-AS1 may serve as a diagnostic marker and therapeutic target for OSCC patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10142-024-01436-6.

Keywords: lncRNAs, MAGEA4-AS1, MK2, p53, EMT, Transcription regulation

Introduction

Oral squamous cell carcinoma (OSCC) is a significant health concern, ranking among the top ten cancers worldwide, also a primary cause of mortality (Siegel et al. 2023). The pathogenesis of OSCC is primarily associated with genome changes caused by etiological factors such as tobacco use, smoking, betel nut chewing, and alcohol consumption (Chamoli et al. 2021). Currently, Surgery and radiotherapy are primary treatment approaches for early OSCC patients. However, the recurrence rate of OSCC patient is high. Furthermore, due to the high rate of tumor metastasis, the 5-year survival rate of OSCC patients remain less than 50% (Biau et al. 2019; Schoenfeld et al. 2020). Hence, it is necessary to improve the diagnosis of OSCC, identify effective therapeutic targets, detect and implement timely treatment measures in the early stages of the disease (Cramer et al. 2019).

Because proteins play pivotal roles in molecular biology, early research focused on protein-coding genes. However, high-throughput sequencing had revealed huge amount of non-coding RNAs, especially long non-coding RNAs (lncRNAs), in the human transcriptome (Mattick et al. 2023). Although some of non-coding RNAs are thought to be transcriptional noise (Nojima and Proudfoot 2022). LncRNAs lengths of > 200 nt, are essential regulators of genes with different expression levels (Jiang et al. 2022). And it can interact with proteins, RNA and DNA, thereby regulating gene expression through epigenetic modifications, transcriptional regulation and other mechanisms (Mattick et al. 2023; Yao et al. 2022). LncRNA subcellular location determines its biological function. Nuclear lncRNAs interact with chromatin, transcription factors and RNA processing complexes. Cytoplasmic lncRNAs participate in mRNA stability and translation modulation (Batista and Chang 2013; Schmitt and Chang 2016). LncRNAs are usually multi-exonic and highly alternatively spliced, which alters their functions (Khan et al. 2021; Mattick et al. 2023). As emerging regulatory molecules for various biological processes, lncRNAs play a crucial role in the tumorigenesis, development and progression of diverse cancers and affect biological behaviours such as proliferation, differentiation and metastasis of different human cancer cells (Jiang et al. 2019; Shao et al. 2022; Yuan et al. 2022; Zhuang et al. 2020).

Activation of the MAPK signaling pathway leads to apoptosis, invasion, and inflammatory responses (Lee et al. 1994). LncRNAs and other non-coding RNAs affect the development of OSCC by regulating the MAPK signaling pathway (Jia et al. 2020; Jiang et al. 2022). MK2 (MAPKAPK2), an upstream transcription factor, influences tumourigenesis and plays a crucial role in regulating the cell cycle, inflammation and epithelial-to-mesenchymal transition (EMT) (Soni et al. 2019). MK2 regulates the tumor microenvironment of colorectal, bladder, and skin cancers (Henriques et al. 2018; Johansen et al. 2009; Kumar et al. 2010). However, the involvement of MK2 in OSCC and its roles in OSCC cell biological behaviors modulation are unclear. We found that MAGEA4-AS1 was up-regulated in tumor tissues of patients both from TCGA-OSCC and our cohort. In addition, MAGEA4-AS1’s parent gene family members are expressed in various tumors and are highly specific to cancer cells (Griffith-Jones et al. 2024). This molecule has a significant potential for research.

Hence, to ascertain the significance of MAGEA4-AS1 in the development and advancement of OSCC, as well as to assess its potential as a prognostic biomarker and therapeutic target for OSCC patients, we investigated the biological function and mechanism of MAGEA4-AS1 in OSCC cells.

Materials and methods

Clinical samples

A total of 45 pairs of cancer and paracancerous normal tissues were obtained from surgical OSCC patients who never received chemotherapy nor radiotherapy from 2022 to 2023 in our hospital. All patients had read and signed the informed consent documents. Tissues were snap-frozen and preserved in a freezer at − 80 °C. This study was approved by the Research Ethics Committee of the Peking University Shenzhen Hospital (Shenzhen, China; grant no. 2022 − 117).

Cell culture and reagents

Normal oral mucosal HOK, OSCC CAL27 and HSC3 cells were obtained from BeNa Culture Collection (Beijing, China). The cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM) (Gibco, USA) supplemented with 10% Foetal Bovine Serum (PAN, Adenbach, Germany), 100 U/mL penicillin and 100 U/mL streptomycin (Gibco, USA) at 37 °C in a moist environment with 5% CO2. The cells were digested with 0.25% trypsin-EDTA (Gibco, USA) and preserved in CELLSAVING reagent (NCM, Suzhou).

RNA extraction and quantitation

Total RNAs were collected from tissues and cells using TRIzol reagent (Catalog Number: 15596026CN, Invitrogen, USA), and the concentration and purity of RNA were assessed using Nanodrop 2000 Spectrophotometer (Thermo Scientific, USA). Reverse transcription of cDNA was performed from approximately 1 µg of total RNAs using Evo M-MLV Reverse Transcriptase (Catalog Number: AG11705, Accurate Biology, Changsha, China). Target and reference genes were quantified from the cDNA pool using a SYBR Green Pro Taq HS kit (Catalog Number: AG11701, Accurate Biology, Changsha, China) on a LightCycler 480 System (Roche Diagnostics, Basel, Switzerland). The 2−ΔΔCt method was used to calculate relative mRNA expression levels. The PCR primers were synthesised by Sangon Biotech (Shanghai, China) and the sequences were listed as follows: GAPDH forward: 5’-GAAGGTGAAGGTCGGAGTC-3’, reverse: 5’-GAAGATGGTGATGGGATTTC-3’; U6 forward: 5’-CTCGCTTCGGCAGCACA-3’, reverse: 5’- AACGCTTCACGAATTTGCGT-3’; NEAT1 forword: 5’- CAGTTAGTTTATCAGTTCTCCCATCCA-3’, reverse: 5’-GTTGTTGTCGTCACCTTTCAACTCT-3’; MAGEA4-AS1 forward: 5’-TGGCAGCTACAGATTCCCAAG-3’, reverse: 5’-GAGTTCCTCGTTCAGCTGGT-3’; MK2 forward: 5’-CGGTGAGGCCATCCAGTATC-3’, reverse: 5’-TTGTGGCTGGTGGTTTCCTT-3’.

5′- and 3′-RACE

Rapid amplification of cDNA ends (RACE) of 3′ and 5′ end of MAGEA4-AS1 were performed according to the instructions of the manufacturer of the RACE kit (Roche, Basel, Switzerland). Briefly, total RNAs extracted from CAL27 cells were converted into RACE-ready first-strand cDNA. The 5’ and 3’ RACE primers were paired respectively with the derived universal primers to amplify the 5’- and 3’-end sequences using PCR. The PCR products were separated by agarose gel electrophoresis. Target bands were purified and ligated into the pEASY-Blunt Cloning Kit (TransGen, Beijing, China), and identified using Sanger sequencing. MAGEA4-AS1 sequences were obtained by aligning the overlapped 5’- and 3’-end sequences and proofed using PCR. Primers used in RACE were listed below: 5′-RACE: cDNA synthesis primer: 5′-CCATGGGGTATACCCTGTTGGG-3’, First-round PCR primer: 5′-GTACTCTAGACCCTGTTGGC-3’, Nest PCR primer: 5′-CTGGGGTTAGACCTCTGGAGACCTC-3’; 3′-RACE: PCR primer: 5′-CCAGAGAACAGCAGCCTAAGTGTG-3’.

Isolation of nuclear and cytoplasmic RNA

NE-PER Nuclear and Cytoplasmic Extraction Reagents (Thermo Scientific) were used to separate cellular nuclear and cytoplasmic components. Nuclear and cytoplasmic component RNA purification, cDNA synthesis, and qPCR were performed as described above. The lncRNA nuclear paraspeckle assembly transcript 1 (NEAT1) served as an endogenous control for the nucleus RNA, while GAPDH was selected as an endogenous control for the cytoplasm RNA. The qPCR primers are listed above.

RNA-fluorescence in situ hybridization (RNA-FISH)

Biotin-labelled probes targeting MAGEA4-AS1 were designed and synthesised by Sangon Biotech (Shanghai, China). The probe sequence is: 5’-TCTCCTCACTGTTTTGGTCCAGCTGT-biotin-3’. The 18 S rRNA Cy3 FISH Probe (Catalog Number: R0312, Beyotime, Shanghai, China) and U6 snRNA Cy3 FISH Probe (Catalog Number: R0323, Beyotime, Shanghai, China) are used to target cell cytoplasma 18 S RNA and nucleus U6 snRNA respectively. RNA-FISH experiments were performed following instruction of the circRNA/miRNA in situ hybridisation test kit (Geneseed Biotech, Guangzhou, China). Laser scanning confocal microscope (Leica Microsystems, Germany) was used to capture fluorescence pictures for each probe hybridization group.

Lentivirus transfection

For in vivo experiments, a MAGEA4-AS1 shRNA lentiviral vector containing viruses were generated by Hanbio (Shanghai, China) and used to transfect CAL27 and HSC3 cells in accordance with the manufacturer’s instructions. MAGEA4-AS1 stable knockdown cells were screened using puromycin at 48 h after transfection. MAGEA4-AS1 expression levels were examined using qPCR to determine the knockdown efficiency.

Western blotting analysis

RIPA Lysis Buffer (Beyotime, Shanghai), with PMSF and phosphatase inhibitors addition, were used to extract proteins from cultured cells. Denatured proteins were separated by sodium dodecyl sulphate polyacrylamide gel electrophoresis. Protein bands were transferred to 0.45 μm polyvinylidene difluoride (PVDF) membranes. Then, Membranes were blocked with 5% skimmed milk and exposed to primary antibodies (anti-MAPKAPK2, 1:1000, Catalog Number: 12155, CST, Danvers, USA; anti-P53, 1:500, Catalog Number: 2527, CST; anti-vimentin 1:1000, Catalog Number: 5741, CST; anti-N-cadherin, 1:1000, Catalog Number: 13116, CST; anti-E-cadherin, 1:1000, Catalog Number: 3195, CST; anti-GAPDH, 1:1000, Catalog Number: 2118, CST) overnight at 4 °C. Subsequently membranes were treated with an HRP-labelled secondary antibody (anti-rabbit, 1:2000, Beyotime, Catalog Number: A0208) at room temperature for 1 h. Finally, the immunoblots were visualised using a ChemiDoc MP Imaging System (Bio-Rad, Hercules, USA).

CCK-8 assay

MAGEA4-AS1 stable knockdown HSC3 and CAL27 cells were placed in 96-well plates with 1,000 cells in each well. CCK-8 reagent (Cell counting Kit-8, Biosharp, Hefei, China) was added to each well at time point 0–96 h in 24 h intervals and incubated for 1 h at 37 °C. The measurement of absorbance was taken at a wavelength of 450 nm using a microplate reader (Promega, Madison, WI, USA).

Ethynyl deoxyuridine (EdU) assay

HSC3 and CAL27 cells were seeded in 24-well plates at a concentration of 3 × 105 cells per well and then placed in an incubator for 24 h. Next, the cells were placed in a solution containing 0.1% EdU reagent (Uelandy, Suzhou, China) and incubated for 2 h at 37 °C. Subsequently, the cells were fixed by 4% paraformaldehyde for 10 min, rinsed with 3% bovine serum albumin (BSA) buffer, and then exposed to 0.5% Triton-100 for 5 min. Finally, the cells were stained with DAPI and examined under a fluorescence microscope. Images of stained cells were captured at 200× magnification. The positive cells in the control and MAGEA4-AS1 knockdown groups was counted and compared.

Colony formation assay

HSC3 and CAL27 cells were digested, counted and seeded in 6-well plates with 1,000 cells per well and then kept in cell incubator for 10–14 days until the formation of visible colonies containing at least 50 cells. The colonies were fixed by cold methanol and stained by 1% crystal violet solution (Beyotime, Shanghai, China).

Cell migration and invasion assays

Transwell insert chambers equipped with 8-µm porosity polycarbonate filters (Corning, New York, USA), which were either coated or uncoated with Matrigel (BD Biosciences, New York, USA), were used for invasion and migration assays. Briefly, 100 µL suspension of cells in a serum-free medium containing 5 × 104 MAGEA4-AS1 stable knockdown HSC3 and CAL27 cells were seeded in upper chamber, and the lower chambers were filled with 650 µL DMEM with 10% FBS (As a substance to attract cells). After incubation for 24 h, cells could migrate or invade to outside of the bottom of upper chamber. Cells were fixed and stained as colony formation assay. Each chamber was chosen at random, examined under a microscope and captured.

Wound healing assay

The stable knockdown of MAGEA4-AS1 cells were cultivated to 100% confluence in a 6-well plate, using a 20 µL tip to make scratches of similar width in shMAGEA4-AS1 and shNC groups of HSC3 and CAL27 cells. Cell migration through the wound was monitored at 0 h and 12 or 24 h after scraping, with random selection of fields of view for photography. The percentage of the healing cell area, which correlates with the cell migration capacity, was estimated by comparison with that at 0 h time point.

Data resources

Transcriptome data of OSCC patients were collected from TCGA, and tumors annotated as tongue or base of tongue were selected as OSCC. Next, we used the raw read counts from all tumors and adjacent normal tissues to mine the differentially expressed genes using the DESeq2 package. Genes with Benjamini-Hochberg adjusted p-values < 0.01 and at least a 2-fold change in expression between tumors and adjacent normal tissues were considered differentially expressed.

RNA-seq analysis

Total RNAs of MAGEA4-AS1 stably knockdown HSC3 cells were sent to BGI Genomics (Shenzhen, China) for whole-transcriptome sequencing. Transcripts that were differentially expressed between shMAGEA4-AS1 and shNC groups were identified and validated by qPCR and western blotting. Gene Ontology (GO) and KEGG pathway analyses were performed for differentially expressed genes using Dr. Tom’s online analysis system provided by BGI Genomics.

RNA-binding protein immunoprecipitation (RIP)

RIP experiment was performed using the PureBinding RIP kit (Geneseed Biotech, Guangzhou, China) according to the following procedure. Firstly, washing magnetic beads three times. The pre-washed magnetic beads were incubated with 2 µg of p53 antibody (CST, Danfoss, USA) and an equal mass of homologous immunoglobulin (IgG) for 2 h, respectively. Next, the antibody-coated beads were washed and incubated with cell lysates overnight. Finally, the immunoprecipitated RNA-protein complexes were resuspended in TRIzol reagent for RNA purification. Candidate RNA transcripts were validated using qPCR. The MAGEA4-AS1 RNA enrichment folds in p53 group relative to IgG group was determined using the 2−ΔCt method: △Ct = CtIP−CtIgG. Furthermore, a 10% volume of immunoprecipitated RNA-protein complexes was reserved to evaluate the immunoprecipitated efficiency by western blotting before RNA extraction.

Dual-luciferase reporter assay

The pGL3-basic-NC (control), pGL3-basic-MK2 promoter (WT), pcDNA3.1 and pcDNA3.1-TP53 plasmids were synthesised by HanBio (Shanghai, China). For the reporter assay, WT or control reporter vectors and pcDNA3.1 or pcDNA3.1-TP53 were simultaneously transfected into OSCC cells. About 48 h after transfection, Luciferase activity was examined by Luciferase Reporter Assay kit (Beyotime, Shanghai, China). The microplate reader detected the fluorescence value and calculated the luciferase ratio (firefly/Renilla) which is called the relative light unit (RLU). The promoter activity of MK2 gene among the different groups were compared based on the ratios obtained.

Overexpression plasmids transfection

HSC3 and CAL27 cells were divided into three groups: shMAGEA4-AS1 + v-NC, shMAGEA4-AS1 + v-MK2 and shNC + v-NC, and reached 60% confluence in 6-well plates. The overexpression plasmids were transfected with opti-MEM, which was changed to complete medium after 6 h, and the protein was extracted after 48 h to observe the overexpression efficiency of MK2. Simultaneously, the levels of proteins associated with EMT were assessed to evaluate recovery effects.

Statistical analysis

Statistical analyses were conducted using GraphPad Prism 9 software. All experiments were independently performed in triplicate. Data between the two groups were analysed using one-way analysis of variance (ANOVA), followed by Tukey’s post-hoc test or Student’s t-test. Multiple comparison correction was performed using Bonferroni method. Statistical significance was set at p < 0.05. All data are presented as mean ± standard error of the mean (SEM).

Results

LncRNA MAGEA4-AS1 was upregulated in OSCC and served as an OSCC biomarker

We screened TCGA database to identify variations of lncRNAs between OSCC tissues and paracancerous normal tissues (Fig. 1A). We found a notable upregulation of lncRNA MAGEA4-AS1 expression in OSCC tissues than normal tissues (Fig. 1B). Subsequently, the ROC curve of the MAGEA4-AS1 expression pattern was generated; the area under the curve (AUC) value was 0.74 (Fig. 1C), indicating that the expression level of MAGEA4-AS1 may be a good predictive biomarker in patients with OSCC. In our cohort, we examined MAGEA4-AS1 expression in 45 pairs of OSCC patients’ surgical specimens at our hospital by qPCR. Notably, MAGEA4-AS1 expression in OSCC tissues was significantly higher than normal tissues (Fig. 1D). The AUC value under the ROC curve was 0.63 (Fig. 1E). Furthermore, the fold-changes in MAGEA4-AS1 expression levels between tumor and normal tissues were evaluated; 25/45 patients presented fold-changes in MAGEA4-AS1 levels of > 2 folds (Log2 [Tumor/Normal] > 1), and 3/45 patients presented MAGEA4-AS1 levels in tumor tissues of < 50% of that expressed in normal tissues (Log2 [Tumor/Normal] < − 1) (Fig. 1F). Additionally, MAGEA4-AS1 levels were notably elevated in the OSCC cell lines (HN6, CAL27, and HSC3) compared to normal oral epithelial HOK cells (Fig. 1G). These results demonstrated that MAGEA4-AS1 is upregulated in OSCC and can serve as a biomarker for OSCC diagnosis.

Fig. 1.

Fig. 1

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MAGEA4-AS1 was upregulated in OSCC. (A) lncRNAs differentially expressed in TCGA-OSCC cohort are presented in a volcano map. (B) The RNA levels of MAGEA4-AS1 in the tumor tissues of 342 patients and adjacent normal tissues from 31 patients were derived from TCGA database OSCC cohort. ** indicates p < 0.01 (Mann–Whitney test). (C) Receiver operating characteristic (ROC) curve for TCGA-OSCC MAGEA4-AS1 samples. (D) RNA levels of MAGEA4-AS1 were quantified in 45 pairs of OSCC tissues and adjacent normal tissues using qPCR. **** indicates p < 0.0001 (Wilcoxon matched-pairs signed rank test). (E) ROC curve for the OSCC MAGEA4-AS1 samples. (F) Fold changes in MAGEA4-AS1 expression of 45 paired OSCC tissues in figure D. Downregulated expression, blue; no difference, grey; upregulated expression, red. (G) RNA levels of MAGEA4-AS1 were quantified in immortalised OSCC cell lines and human oral keratinocytes (HOK) using qPCR. *, ** and *** indicate adjusted p < 0.05, 0.01 and 0.001 correspondingly. (Bonferroni’s multiple comparisons test in one-way ANOVA test). qPCR, quantitative reverse transcription polymerase chain reaction; TPM, transcripts per kilobase million; GAPDH, glyceraldehyde 3-phosphate dehydrogenase

Characteristics of MAGEA4-AS1 transcripts in OSCC cells

MAGEA4-AS1 has not been functionally studied. Therefore, we first identified MAGEA4-AS1 transcript sequences using the RACE method. The 5’- and 3’-end sequences of MAGEA4-AS1 were amplified using RACE and separated using agarose gel electrophoresis. Targeted DNA bands were obtained, ligated into vectors and identified using Sanger sequencing (Fig. 2A and B). Next, primers were designed according to known 5’- and 3’-end sequences to amplify full-length MAGEA4-AS1 sequences using PCR, and the full-length MAGEA4-AS1 band was identified in the same way as the 5’- and 3’-end identification (Fig. 2C). We obtained a full-length MAGEA4-AS1 sequence that contained 418 nucleotides and two exons. The junction of exons was GA nucleartides and marked as capital letter in red (Fig. 2D). Furthermore, we searched for MAGEA4-AS1 sequences in UCSC genome browser (GRch38) and found that our transcript was more similar to that in the NCBI database (Fig. 2E). Using RNA-FISH, we noticed that MAGEA4-AS1 was predominantly localized within the nucleus of OSCC cells (Fig. 2F). Additionally, we examined MAGEA4-AS1 RNA levels in the isolated nuclear and cytoplasmic components using qPCR. The results verified that MAGEA4-AS1 was predominantly localized within the nucleus of cells (Fig. 2G). Collectively, these results present a new MAGEA4-AS1 transcript that is mainly located in the nucleus of OSCC cells.

Fig. 2.

Fig. 2

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MAGEA4-AS1 transcript identification and localisation in OSCC cells. (A) The 5’-end sequence of MAGEA4-AS1 was amplified by RACE and identified using Sanger sequencing. (B) The 3’-end MAGEA4-AS1 sequence was amplified by RACE and identified using Sanger sequencing. (C) The full-length sequence of MAGEA4-AS1 was amplified using polymerase chain reaction (PCR) with primers designed according to the 5’ and 3’ end sequences identified in (A) and (B), and identified by Sanger sequencing. (D) The full-length sequence of MAGEA4-AS1 identified using Sanger sequencing in (C). Junction sites between exons are indicated in red bold capitals. (E) Location of MAGEA4-AS1 isoform (418 nt) in the human genome. (F) RNA-fluorescence in situ hybridisation (RNA-FISH) was performed to determine the cellular localisation of MAGEA4-AS1. Scale bars, 20 μm. (G) Distribution of MAGEA4-AS1 RNA in OSCC HSC3 and CAL27 cells. GAPDH was used as an endogenous cytoplasmic control. The lncRNA NEAT1 was used as an endogenous nuclear control

MAGEA4-AS1 enhanced the proliferation potential, the migration and invasion abilities of OSCC cells

To further investigate the effect of MAGEA4-AS1 on OSCC cell proliferation, HSC3 and CAL27 cells which were stably expressed short hairpin RNA (shRNA) targeting MAGEA4-AS1 were generated by lentiviral transfection. Firstly, we investigated the impact of MAGEA4-AS1 on OSCC cell growth using the CCK-8 assay and found that MAGEA4-AS1 downregulation significantly slowed the growth of HSC3 (Fig. 3A) and CAL27 cells (Fig. 3B). In addition, EdU staining which is also a method for cell proliferation rate valuation was conducted to validate the influence of MAGEA4-AS1 knockdown on OSCC cell proliferation. The results showed that the red fluorescence of shMAGEA4-AS1 group was significantly less than the control shNC group in HSC3 (Fig. 3C) and CAL27 cells (Fig. 3D). The statistical chart showed that the proliferation ability of the shMAGEA4-AS1 HSC3 cells group was decreased about 25% and 33% in shMAGEA4-AS1 CAL27 cells group comparing to their corresponding control shNC group (Fig. 3E). Furthermore, we used colony formation assays to further validate the suppression effect of MAGEA4-AS1 downregulation on OSCC proliferation. The colony formation results shown that the proliferation abilities were also weakened in the shMAGEA4-AS1 HSC3 and CAL27 cells (Fig. 3F and G). These results suggested that MAGEA4-AS1 enhanced the proliferation potential of OSCC cells.

Fig. 3.

Fig. 3

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MAGEA4-AS1 knockdown weakened the proliferation of OSCC cells. (A, B) Cell Counting Kit-8 (CCK-8) assay for HSC3 and CAL27 cells stably expressed shRNAs targeted MAGEA4-AS1 expression. (C, D) Cell proliferation assay for stable shMAGEA4-AS1 HSC3 and CAL27 cells using the EdU method. (E) Illustration of cell proliferation inhibition by shMAGEA4-AS1 in (C) and (D). (F) Cell colony formation assay using shMAGEA4-AS1 HSC3 and CAL27 cells. (G) Illustration of the cell colony formation in (F). Data are presented as the mean ± SEM of three independent experiments. * indicates p < 0.05, ** indicates p < 0.01 (two-tailed Student’s t-test). Scale bars, 200 μm

For high metastasis and invasion potentials are key features of tumors, we performed the transwell and wound healing assay to study the influence of MAGEA4-AS1 down-regulation on cell migration of OSCC cells. Our transwell assay results shown MAGEA4-AS1 down-regulation significantly weakened the migration capacity of CAL27 and HSC3 cells (Fig. 4A). And wound healing assay result also proofed the same conclusion as transwell assay (Fig. 4B). A matrix gel-coated Transwell has been used to investigate the cell invasion ability. The results revealed that MAGEA4-AS1 down-regulation decreased the invasive capacity of CAL27 and HSC3 cells (Fig. 4C). These results demonstrated that MAGEA4-AS1 promotes OSCC progression by enhancing cell proliferation, migration, and invasion.

Fig. 4.

Fig. 4

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MAGEA4-AS1 knockdown weakened the migration and invasion of OSCC cells. (A) Transwell migration assay for HSC3 and CAL27 cells stably expressing shMAGEA4-AS1. (B) Wound healing assay in HSC3 and CAL27 cells stably expressing shMAGEA4-AS1. (C) Transwell assays for the invasion of HSC3 and CAL27 cells stably expressing shMAGEA4-AS1. Data are presented as the mean ± SEM of three independent experiments. ns indicates no significance, * indicates p < 0.05, ** indicates p < 0.01 (two-tailed Student’s t-test). Scale bars, 100 μm

MAGEA4-AS1 affected MK2 involved signalling pathways in OSCC cells

The mechanism by which MAGEA4-AS1 promotes OSCC progression remains unclear. To evaluate its role, we performed whole-transcriptome sequencing for shMAGEA4-AS1 OSCC cells and identified 882 down-regulated (log2 [shMAGEA4-AS1/shNC]<-0.585, p < 0.05) and 969 up-regulated (log2 [shMAGEA4-AS1/shNC] > 0.585, p < 0.05) genes (Table S1). GO analysis results showed that these MAGEA4-AS1 affected genes mainly participated in biological processes, such as cell division, cell cycle, and MAPK cascade (Fig. 5A), located in cellular components such as the nucleus, cytoplasm, and cytosol (Fig. 5B), and exerted molecular functions such as protein binding, metal ion binding, and ATP binding (Fig. 5C). Furthermore, we investigated the KEGG pathways for these genes and found that the p53, PI3K-Akt, MAPK, and cell cycle signaling pathways were enriched (Fig. 5D). In particular, we identified significantly altered genes in pathways associated with cancer progression, such as the p53 (Fig. 6A), MAPK (Fig. 6B), and PI3K-Akt signaling pathways (Fig. 6C), and cell cycle-related genes (Fig. 6D). These results implied MAGEA4-AS1 plays an important role in gene transcription regulation of OSCC.

Fig. 5.

Fig. 5

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Bioinformatic analysis of whole-transcriptome sequencing of shMAGEA4-AS1 OSCC cells. Gene ontology (GO) analysis was performed for genes differentially expressed between shMAGEA4-AS1 and shNC cells. (A) GO term biological process, (B) GO term cellular component, and (C) GO term molecular function. (D) Bubble Chart of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways for MAGEA4-AS1 influenced genes involved. All pathways were significantly enriched (p < 0.05)

Fig. 6.

Fig. 6

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MAGEA4-AS1 knockdown affected MK involved signaling pathways in OSCC cells. (A) p53, (B) MAPK, (C) PI3K-Akt signaling pathways and (D) Cell cycle-related gene transcription levels were significantly altered in shMAGEA4-AS1 HSC3 cells. (E) Volcano map presented differentially expressed genes in shMAGEA4-AS1 HSC3 cells. (F) MK2 mRNA expression levels in shMAGEA4-AS1 HSC3 and CAL27 cells determined using qPCR. Data are presented as the mean ± SEM of three independent experiments. ** indicates p < 0.01, and *** indicates p < 0.001 (two-tailed Student’s t-test). (G) MK2 protein levels in shMAGEA4-AS1 HSC3 and CAL27 cells determined using western blotting. (H) Epithelial-mesenchymal transition (EMT) related protein evaluation in shMAGEA4-AS1 HSC3 and CAL27 cells using western blotting

Surprisingly, we found the MK2 gene which was significantly down regulated in sh-MAGEA4-AS1 groups (Fig. 6E). Deng et al. had reported that MK2 affected the cell cycle and EMT procedure by controlling the MAPK and PI3K-Akt signaling pathways (Deng et al. 2018). First, we validated MK2 mRNA and protein expression in shMAGEA4-AS1 OSCC cells and found a significant decrease in both mRNA and protein levels in shMAGEA4-AS1 OSCC cells (Fig. 6F and G). Furthermore, EMT-related proteins changed as EMT was inhibited following MAGEA4-AS1 downregulation (Fig. 6H). These results indicated MAGEA4-AS1 enhances the malignant progression of OSCC cells by promoting MK2 transcription.

MAGEA4-AS1 bound to p53 to increase MK2 transcription and resulting EMT enhancement

To clarify the molecular mechanism by which MAGEA4-AS1 controls MK2 transcription, we speculated that nucleus-localized MAGEA4-AS1 binds to transcription factors to influence MK2 transcription. Therefore, we scanned the promoter region of MK2 in the JASPAR database and several p53 binding sites were found in this region (Fig. 7A). The transcriptome sequencing results indicated that MAGEA4-AS1 influenced genes enriched in the p53, PI3K-Akt, and MAPK signaling pathways. Therefore, MAGEA4-AS1 may be associated with the p53 signaling pathway and regulate MK2 transcription. Subsequently, we constructed an MK2 promoter dual-luciferase reporter system and co-transfected the reporter system with p53 overexpressed plasmids into OSCC cells. We found that MK2 promoter luciferase activity dramatically increased in the p53 overexpression group, indicating that p53 could regulate MK2 transcription (Fig. 7B and C). Subsequently we need to solve whether MAGEA4-AS1 could interact with p53 protein. We performed RIP assay and found p53 protein could bind to MAGEA4-AS1 RNA molecule (Fig. 7D). To confirm that MAGEA4-AS1-p53 interaction is associated with increasing MK2 expression and enhancing EMT of OSCC cells, we performed rescue assays by transfecting MK2 overexpression plasmids into shMAGEA4-AS1 HSC3 and CAL27 cells. The results indicated E-cadherin did not change in the rescue groups; however, Vimentin and N-cadherin expression levels were notably upregulated after the overexpression of MK2 in the shMAGEA4-AS1 groups (Fig. 7E). These results indicate that MAGEA4-AS1-p53 complexes attach to the promoter of MK2, enhancing the transcription of MK2 and activating the downstream MAPK and PI3K-Akt signalling pathways, consequently promoting OSCC cell migration and invasion.

Fig. 7.

Fig. 7

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MAGEA4-AS1 associated with p53 promoted MK2 transcription, resulting in OSCC malignance. (A) MK2 promoter region p53 binding sites prediction by JASPAR website tool (https://jaspar.elixir.no/). (B, C) MK2 promoter dual-luciferase reporter assay performed on OSCC HSC3 and CAL27 cells. Data are presented as the mean ± SEM of three independent experiments. * indicates p < 0.05, and ** indicates p < 0.01 (Bonferroni’s multiple comparisons test in one-way ANOVA test). (D) RNA-binding protein immunoprecipitation (RIP) was performed to evaluate p53-MAGEA4-AS1 interaction. Data are presented as mean ± SEM of three independent experiments. ** indicates p < 0.01 (two-tailed Student’s t-test). (E) Evaluation of MK2 and EMT-related proteins’ expression in shMAGEA4-AS1 stably expressing HSC3 and CAL27 cells by western blotting; OE-MK2 plasmids were transfected into the same cells to rescue MK2 protein levels

Discussion

The low 5-year survival and high recurrence rate after OSCC treatment remain significant health concerns (Dai et al. 2023; Gleber-Netto et al. 2015). To develop new diagnostic and therapeutic approaches, it is critical to clarify the molecular mechanisms underlying OSCC progression. Genetically derived molecular markers, including lncRNAs, may play crucial roles in predicting disease progression (Biau et al. 2019; Cramer et al. 2019; Schoenfeld et al. 2020). The human genome encodes > 28,000 lncRNAs, many of which have not been identified or functionally studied (Bhan et al. 2017; Tragante et al. 2014). In lung, gastric, pancreatic, cervical and breast cancers, lncRNAs play crucial roles in promoting or suppressing cancer through specific regulatory ways (Gao et al. 2022; Luo et al. 2022; Xu et al. 2020; Zeng et al. 2022; Zhou et al. 2020)]. In this study, we found a novel lncRNA MAGEA4-AS1, validated its expression in OSCC surgical patient samples and evaluated its potential as an OSCC biomarker. The results indicated a significant up-regulation of MAGEA4-AS1 in tumor tissues. MAGEA4-AS1 may be a key indicator in OSCC patients.

Our whole-transcriptome sequencing revealed that MAGEA4-AS1 affects several tumor-related pathways that are closely related to MK2. MK2 can induce PI3K-Akt, c-Myc and MAPK signal transduction pathways in nasopharyngeal carcinoma, which leads to EMT and stimulates the proliferation and metastasis of nasopharyngeal carcinoma cells (Deng et al. 2018). In OSCC, lncRNA SLC16A1-AS1 was a clearly understood up-regulated non-coding RNA which played an essential role in OSCC proliferation and its biological function was related to cell-cycle regulation. SLC16A1-AS1 silencing leads to cell cycle arrest in G0/G1 phase and inhibits cyclin D1 expression (Feng et al. 2020). In our study, we found MAGEA4-AS1 was also a up-regulated non-coding RNA in OSCC tissues. MAGEA4-AS1 silencing weakened the proliferation, migration and invasion potentials of OSCC cells and might inhibit MK2 expression for the MAGEA4-AS1-P53 complex docking on MK2 promoter reduction. Of course, more experiments are needed to verify it. EMT is significantly associated with tumor stemness and metastasis (Pastushenko et al. 2021). Notably, lncRNAs modulate phenotypic changes, tumourigenesis and development by regulating EMT (Hu et al. 2020). Based on the sequencing data, MAGEA4-AS1 downregulation inhibited MK2-related pathways. However, further experiments are needed to confirm the details of these signaling pathways involved EMT procedure.

The cellular distribution of lncRNAs in the nucleus and cytoplasm involves various molecular mechanisms through which gene activity and protein function are regulated. LncRNAs modulate several activities, including transcriptional interference, RNA splicing, and miRNA quenching, and specific lncRNAs directly interact with transcription factors and RNA-binding proteins. Nuclear localisation of lncRNAs is likely to be involved in transcriptional and post-transcriptional regulation (Chen 2016; Herman et al. 2022; Wang and Chang 2011; Wapinski and Chang 2011). Additionally, lncRNAs can affect epithelial markers (such as E-cadherin) and mesenchymal markers (such as N-cadherin and Vimentin) expression, resulting in tumor invasion and metastasis (Pastushenko and Blanpain 2019). In this study, we found that MAGEA4-AS1 located in the nucleus can activate the transcription of MK2 by recruiting p53, consequently affecting cell proliferation, migration and invasion, eventually leading to malignant progression of OSCC. Therefore, MAGEA4-AS1 may be a potential biomarker for diagnosis and a candidate therapeutic target for treatment of OSCC patients.

Conclusion

We identified a new MAGEA4-AS1 transcript, which is primarily located in the nucleus and up-regulated in tumor tissues of OSCC patients. MAGEA4-AS1 influences the malignant progression of OSCC by promoting cell proliferation and metastasis. Mechanistically, MAGEA4-AS1 increased MK2 transcription by binding to the transcription factor p53 protein and subsequently activating downstream signaling pathways.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1 (333.8KB, xlsx)

Author contributions

All authors made a significant contribution to the work reported. H. Y., Y. S., Z. L. and X. W. initiated and designed the experiments. X. W., Z. L., H. Z. and X. L. performed the experiments and analyzed the data. Y. L., X. L., H. Z. and X. W. collected OSCC tissue specimens and performed clinicopathologic analyses. X. W. and Z. L. wrote the manuscript. Y. S., H. Y. and Z. L. revised the manuscript. All authors gave final approval of the version to be published.

Funding

This work was supported by Shenzhen Science and Technology Program (JCYJ20200109140208058, JCYJ20220531094216037 and SGDX20210823103200005), Shenzhen High-level Hospital Construction Fund, Peking University Shenzhen Hospital Scientific Research Fund (KYQD2023253). Shenzhen Clinical Research Center for Oral Diseases (20210617170745001), the Sanming Project of Medicine in Shenzhen (SZSM 202111012, Oral and Maxillofacial Surgery Team, Professor Yu Guangyan, Peking University Hospital of Stomatology) and Shenzhen Fund for Guangdong Provincial High-level Clinical Key Specialties (No. SZGSP008).

Data availability

No datasets were generated or analysed during the current study.

Declarations

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.

Xiaoxiao Wei and Zhangfu Li contributed equally to this work and should be considered co-first authors.

Contributor Information

Hongyu Yang, Email: yanghongyu@ahmu.edu.cn.

Yuehong Shen, Email: yhshen@pkuszh.com.

References

  1. Batista PJ, Chang HY (2013) Long noncoding RNAs: cellular address codes in development. Disease Cell 152:1298–1307. 10.1016/j.cell.2013.02.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Bhan A, Soleimani M, Mandal SS (2017) Long noncoding RNA and cancer: a new. paradigm. Cancer Res 77:3965–3981. 10.1158/0008-5472.Can-16-2634 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Biau J, Lapeyre M, Troussier I et al (2019) Selection of lymph node target volumes for definitive head and neck radiation therapy: a 2019 update radiotherapy and oncology. J Eur Soc Therapeutic Radiol Oncol 134:1–9. 10.1016/j.radonc.2019.01.018 [DOI] [PubMed] [Google Scholar]
  4. Chamoli A, Gosavi AS, Shirwadkar UP et al (2021) Overview of oral cavity squamous cell carcinoma: risk factors, mechanisms, and diagnostics. Oral Oncol 121:105451. 10.1016/j.oraloncology.2021.105451 [DOI] [PubMed]
  5. Chen LL (2016) Linking long noncoding RNA localization and function. Trends Biochem Sci 41:761–772. 10.1016/j.tibs.2016.07.003 [DOI] [PubMed] [Google Scholar]
  6. Cramer JD, Burtness B, Le QT, Ferris RL (2019) The changing therapeutic landscape of head and neck cancer. Nat Reviews Clin Oncol 16:669–683. 10.1038/s41571-019-0227-z [DOI] [PubMed] [Google Scholar]
  7. Dai Y, Wu Z, Chen Y et al (2023) OCT4’s role and mechanism underlying oral squamous cell carcinoma. J Zhejiang Univ Sci B 24:796–806. 10.1631/jzus.B2200602 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Deng X, Liu Z, Liu X et al (2018) Mir-296-3p negatively regulated by Nicotine stimulates cytoplasmic translocation of c-Myc via MK2 to suppress chemotherapy. Resist Mol Ther 26:1066–1081. 10.1016/j.ymthe.2018.01.023 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Feng H, Zhang X, Lai W, Wang J (2020) Long non-coding RNA SLC16A1-AS1: its multiple tumorigenesis features and regulatory role in cell cycle in oral squamous cell carcinoma. Cell Cycle 19:1641–1653. 10.1080/15384101.2020.1762048 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Gao Y, Zhang N, Zeng Z et al (2022) LncRNA PCAT1 activates SOX2 and suppresses radioimmune responses via regulating cGAS/STING signalling in non-small cell lung cancer. Clin Transl Med 12:e792. 10.1002/ctm2.792 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Gleber-Netto FO, Braakhuis BJ, Triantafyllou A et al (2015) Molecular events in relapsed oral squamous cell carcinoma: recurrence vs. secondary primary tumor. Oral Oncol 51:738–744. 10.1016/j.oraloncology.2015.04.016 [DOI] [PubMed] [Google Scholar]
  12. Griffith-Jones S, Álvarez L, Mukhopadhyay U et al (2024) Structural basis for RAD18 regulation by MAGEA4 and its implications for RING ubiquitin ligase binding by MAGE family proteins. EMBO J 43:1273–1300. 10.1038/s44318-024-00058-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Henriques A, Koliaraki V, Kollias G (2018) Mesenchymal MAPKAPK2/HSP27 drives intestinal carcinogenesis. Proc Natl Acad Sci USA 115:E5546–e5555. 10.1073/pnas.1805683115 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Herman AB, Tsitsipatis D, Gorospe M (2022) Integrated lncRNA function upon genomic and epigenomic regulation. Mol Cell 82:2252–2266. 10.1016/j.molcel.2022.05.027 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Hu XT, Xing W, Zhao RS et al (2020) HDAC2 inhibits EMT-mediated cancer metastasis by downregulating the long noncoding RNA H19 in colorectal cancer. J Exp Clin Cancer Res 39:270. 10.1186/s13046-020-01783-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Jia T, Ren Y, Wang F et al (2020) MiR-148a inhibits oral squamous cell carcinoma progression through ERK/MAPK pathway via targeting IGF-IR Bioscience reports 40. 10.1042/bsr20182458 [DOI] [PMC free article] [PubMed]
  17. Jiang Y, Cao W, Wu K et al (2019) LncRNA LINC00460 promotes EMT in head and neck squamous cell carcinoma by facilitating peroxiredoxin-1 into the nucleus. J Exp Clin Cancer Res 38:365. 10.1186/s13046-019-1364-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Jiang L, Zhou B, Fu D, Cheng B (2022) lncRNA TUG1 promotes the development of oral squamous cell carcinoma by regulating the MAPK signaling pathway by sponging miR-593-3. Cell Cycle 21:1856–1866. 10.1080/15384101.2022.2074624 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Johansen C, Vestergaard C, Kragballe K et al (2009) MK2 regulates the early stages of skin. Tumor Promotion Carcinog 30:2100–2108. 10.1093/carcin/bgp238 [DOI] [PubMed] [Google Scholar]
  20. Khan MR, Wellinger RJ, Laurent B (2021) Exploring the alternative splicing of long noncoding RNAs. Trends Genet 37:695–698. 10.1016/j.tig.2021.03.010 [DOI] [PubMed] [Google Scholar]
  21. Kumar B, Koul S, Petersen J et al (2010) p38 mitogen-activated protein kinase-driven MAPKAPK2 regulates invasion of bladder cancer by modulation of MMP-2 and MMP-9 activity. Cancer Res 70:832–841. 10.1158/0008-5472.Can-09-2918 [DOI] [PubMed] [Google Scholar]
  22. Lee JC, Laydon JT, McDonnell PC et al (1994) A protein kinase involved in the regulation of inflammatory. Cytokine Biosynth Nat 372:739–746. 10.1038/372739a0 [DOI] [PubMed] [Google Scholar]
  23. Luo A, Lan X, Qiu Q et al (2022) LncRNA SFTA1P promotes cervical cancer progression by interaction with PTBP1 to facilitate TPM4 mRNA. Degrad Cell Death Dis 13:936. 10.1038/s41419-022-05359-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Mattick JS, Amaral PP, Carninci P et al (2023) Long non-coding RNAs: definitions, functions, challenges and recommendations. Nat Rev Mol Cell Biol 24:430–447. 10.1038/s41580-022-00566-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Nojima T, Proudfoot NJ (2022) Mechanisms of lncRNA biogenesis as revealed by nascent transcriptomics. Nat Rev Mol Cell Biol 23:389–406. 10.1038/s41580-021-00447-6 [DOI] [PubMed] [Google Scholar]
  26. Pastushenko I, Blanpain C (2019) EMT transition states during tumor progression and metastasis. Trends Cell Biol 29:212–226. 10.1016/j.tcb.2018.12.001 [DOI] [PubMed] [Google Scholar]
  27. Pastushenko I, Mauri F, Song Y et al (2021) Fat1 deletion promotes hybrid EMT state. Tumour Stemness Metastasis Nat 589:448–455. 10.1038/s41586-020-03046-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Schmitt AM, Chang HY (2016) Long noncoding RNAs in cancer pathways. Cancer Cell 29:452–463. 10.1016/j.ccell.2016.03.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Schoenfeld JD, Hanna GJ, Jo VY et al (2020) Neoadjuvant Nivolumab or Nivolumab Plus Ipilimumab in untreated oral cavity squamous cell carcinoma: a phase 2 open-label Randomized Clinical Trial. JAMA Oncol 6:1563–1570. 10.1001/jamaoncol.2020.2955 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Shao Z, Wang X, Li Y et al (2022) The role of long noncoding RNAs as regulators of the epithelial-mesenchymal transition process in oral squamous cell carcinoma cells. Front Mol Biosci 9:942636. 10.3389/fmolb.2022.942636 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Siegel RL, Miller KD, Wagle NS, Jemal A (2023) Cancer statistics, 2023. CA Cancer J Clin 73:17–48. 10.3322/caac.21763 [DOI] [PubMed] [Google Scholar]
  32. Soni S, Anand P, Padwad YS (2019) MAPKAPK2: the master regulator of RNA-binding proteins modulates transcript stability and tumor progression. J Experimental Clin Cancer Res 38:121. 10.1186/s13046-019-1115-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Tragante V, Moore JH, Asselbergs FW (2014) The ENCODE project and perspectives on pathways. Genet Epidemiol 38:275–280. 10.1002/gepi.21802 [DOI] [PubMed] [Google Scholar]
  34. Wang KC, Chang HY (2011) Molecular mechanisms of long noncoding RNAs. Mol Cell 43:904–914. 10.1016/j.molcel.2011.08.018 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Wapinski O, Chang HY (2011) Long noncoding RNAs and human disease. Trends Cell Biol 21:354–361. 10.1016/j.tcb.2011.04.001 [DOI] [PubMed] [Google Scholar]
  36. Xu L, Chen J, Jia L et al (2020) SLC1A3 promotes gastric cancer progression via the PI3K/AKT signalling pathway. J Cell Mol Med 24:14392–14404. 10.1111/jcmm.16060 [DOI] [PMC free article] [PubMed] [Google Scholar] [Retracted]
  37. Yao ZT, Yang YM, Sun MM et al (2022) New insights into the interplay between long non-coding RNAs and RNA-binding proteins in cancer. Cancer Commun (Lond) 42:117–140. 10.1002/cac2.12254 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Yuan K, Lan J, Xu L et al (2022) Long noncoding RNA TLNC1 promotes the growth and metastasis of liver cancer via inhibition of p53. Signal Mol Cancer 21:105. 10.1186/s12943-022-01578-w [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Zeng H, Hou Y, Zhou X et al (2022) Cancer-associated fibroblasts facilitate premetastatic niche formation through lncRNA SNHG5-mediated angiogenesis and vascular permeability in breast cancer. Theranostics 12:7351–7370. 10.7150/thno.74753 [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Zhou C, Yi C, Yi Y et al (2020) LncRNA PVT1 promotes gemcitabine resistance of pancreatic cancer via activating Wnt/β-catenin and autophagy pathway through modulating the miR-619-5p/Pygo2 and miR-619-5p/ATG14 axes. Mol Cancer 19:118. 10.1186/s12943-020-01237-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Zhuang Z, Huang J, Wang W et al (2020) Down-regulation of long non-coding RNA TINCR induces cell dedifferentiation and predicts progression in oral squamous cell carcinoma. Front Oncol 10:624752. 10.3389/fonc.2020.624752 [DOI] [PMC free article] [PubMed] [Google Scholar]

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Supplementary Materials

Supplementary Material 1 (333.8KB, xlsx)

Data Availability Statement

No datasets were generated or analysed during the current study.

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