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. 2025 Sep 24;77(5):178. doi: 10.1007/s10616-025-00846-z

LncRNA PSMA-AS1 affects glioma cell metastasis through mediating pyroptosis via miR-140-3p/SRSF10 axis

Zhengzheng Liu 1, Min Wang 2, Weilu Kuang 1,✉
PMCID: PMC12460221  PMID: 41018137

Abstract

Glioma is a malignant primary tumor of the brain. In recent years, numerous LncRNAs (Long non-coding RNA) have been demonstrated to be potential targets for glioma, and induction of pyroptosis is one of the important directions to inhibit the malignant process of cancer. The role of LncRNA PSMA-AS1, a novel lncRNA, on glioma remain unclear. The aim of this study was to investigate the effects and mechanisms of LncRNA PSMA-AS1 on glioma. PSMA1-AS1 and its potential targets were analyzed using bioinformatics tools and validated using a dual luciferase reporter gene system. Glioma cells were cultured to detect the expression levels of PSMA1-AS1 and its targets. The levels of PSMA1-AS1 and its targets were regulated by transfection and their effects on the viability and metastatic ability of glioma cells as well as on the level of pyroptosis were examined. PSMA1-AS1 expression was elevated in glioma, where miR-140-3p was a downstream target, and was decreased in glioma cells. Inhibition of PSMA1-AS1 promoted pyroptosis and inhibited glioma cell viability and metastatic ability. Overexpression of miR-140-3p had the same effect as inhibition of PSMA1-AS1, whereas inhibition of miR-140-3p reversed the effect of inhibition of PSMA1-AS1 on glioma cells. In addition, SRSF10 is a downstream binding target of miR-140-3p, and inhibition of SRSF10 also promoted pyroptosis and inhibited glioma cells proliferation and metastasis. In conclusion, our results confirmed that PSMA1-AS1 affects glioma cell proliferation and metastasis by regulating pyroptosis through miR-140-3p/SRSF10 axis, suggesting that LncRNA PSMA1-AS1 may be a potential target for glioma.

Keywords: Glioma, LncRNA PSMA1-AS1, miR-140-3p, SRSF10, Pyroptosis

Introduction

Glioma are the most common primary malignant tumors of the central nervous system and represent a major public safety challenge in the field of neuro-oncology (Nicholson and Fine 2021). According to the latest data from GLOBOCAN 2025, there are approximately 300,000 new cases of glioma per year globally, and the distribution shows significant geographic differences, with an annual incidence of 7–10/100,000 in developed countries in Europe and the United States, which is significantly higher than that of 5–7/100,000 in Asia (Filho et al. 2025). This difference may be related to factors such as genetic susceptibility, environmental exposures, and the prevalence of diagnostic technology (Yasinjan et al. 2023). In addition, the prognosis of glioma is generally poor, especially for high-grade subtypes, with glioblastoma, the most malignant subtype, having a median survival of only 12–15 months for its patients worldwide (Schaff and Mellinghoff 2023). The main reason for the increasing incidence and mortality of glioma is the low coverage of molecular testing, in addition to the changing living environment (Hollon et al. 2023). Currently, the missed detection of key biomarkers for glioma directly affects the accurate diagnosis and treatment of glioma.

LncRNAs are non-coding RNAs that are widely expressed in a variety of cells, and they regulate a wide range of biological processes in organisms and influence the development of many diseases (Nojima and Proudfoot 2022; Herman et al. 2022). This includes glioma, where a large number of studies have confirmed the involvement of multiple LncRNAs in regulating the malignant progression of glioma and as potential diagnostic and therapeutic markers for gliomas (Liu et al. 2023; Liang et al. 2022; Wu et al. 2022). Deng et al. found that overexpression of lncRNA PART1 significantly inhibited glioma cells proliferation, migration and epithelial mesenchymal transition (EMT) (Deng et al. 2022). Liu et al. demonstrated that the expression level of LncRNA LINC01094 was significantly increased in the tissues of glioma patients and enhanced in glioma cell lines, and that the deletion of LINC01094 inhibited the viability of glioma cells (Liu et al. 2022a). In addition, the LncRNA HOXA11-AS was shown to inhibit glioma cell proliferation, invasion, and induce apoptosis, as well as inhibit glioma xenograft tumor growth (He and Qiu 2021). It is easy to see through these studies that LncRNAs have the potential to become targets for the diagnosis and treatment of glioma. And the role and mechanism of LncRNA PSMA3-AS1, as a brand new LncRNA, for glioma is unclear.

In general, LncRNAs can act as molecular sponges for microRNAs (miRNAs) and reduce the inhibitory effect of miRNAs on the mRNAs of their target genes by competitively binding to miRNAs (Isa 2024). There were a number of miRNAs that have been shown to regulate the malignant biological process of glioma, for example, overexpression of miR-338-3p inhibited glioma cell proliferation, migration and invasion while promoting apoptosis (Yu et al. 2022). miR-451 was shown to significantly inhibit glioma cell growth and prolong survival in tumor-bearing mice (Nan et al. 2021). In addition, the LncRNA LINC01018 was significantly down-regulated in glioma, LINC01018 directly targeted miR-182-5p, and up-regulation of miR-182-5p reversed the effects of LINC01018 on the inhibitory effect of LINC01018 on the proliferation of glioma cells (Su et al. 2022). Although one study found that miR-140-3p has the potential to serve as a biomarker to differentiate between patients with meningiomas and gliomas (Oto et al. 2020), its effect on gliomas is unknown.

SRSF10 (Serine/arginine-rich splicing factor 10] is a key RNA-binding protein and a member of the serine/arginine (SR) protein family (Xiao et al. 2016). It plays a central role in the post-transcriptional regulation of gene expression and affects a wide range of biological processes (Shkreta et al. 2021). Cai et al. found that SRSF10 is upregulated in a variety of tumors, portending a poor prognosis, and that it regulates glycolysis-related enzymes, promotes lactate production, which in turn induces M2 macrophage polarization and inhibits CD8 + T-cell activity, resulting in an immunosuppressive microenvironment (Cai et al. 2024). In hepatocellular carcinoma, SRSF10 activated the oncogenic effects of CDC25A by dephosphorylating Ser178 and played an important role both in vivo and in vitro (Liu et al. 2022b). Notably, one study, by analyzing the TCGA and CGGA_325 datasets, found that of the 12 SRSF genes, SRSF10 was a potentially independent prognostic biomarker associated with poor prognosis in glioma patients (An et al. 2024). However, it remains unclear whether SRSF10 is regulated by the LncRNAs PSMA3-AS1 and miR-140-3p to affect glioma cells.

In summary, the aim of this study was to investigate the expression of PSMA3-AS1, miR-140-3p and SRSF10 in glioma cells and to reveal the relationship between the three and their effects on glioma cells.

Method and materials

Bioinformatics tools website

To preliminarily assess the expression level of LncRNA PSMA3-AS1 in gliomas, we analyzed the expression level of PSMA3-AS1 in gliomas by UALCAN database (https://ualcan.path.uab.edu/index.html).

The downstream potential binding miRNAs of LncRNA PSMA3-AS1 were obtained from the STARBASE database (https://rnasysu.com/encori/). In addition, the potential downstream targets of miR-140-3p were obtained from the STARBASE database, miRDB database (https://mirdb.org/) and miRWalk database (http://mirwalk.umm.uni-heidelberg.de/), and the intersections were analyzed using the Venny online tool (https://bioinfogp.cnb.csic.es/tools/venny/).

Glioma-related miRNAs were obtained from the Gene Expression Omnibus (GEO) database at the National Center for Biotechnology Information (NCBI). the GSE158284 dataset (Junior et al. 2020) was used for the analysis of this study. The dataset contains 29 glioma samples and 11 non-tumorigenic white matter samples and was profiled based on the GPL13264 platform using Agilent-021827 Human miRNA Microarray, and was analyzed by GEO2R tool (https://www.ncbi.nlm.nih.gov/geo/). In addition mRNAs associated with gliomas were obtained from the Genecards database (https://www.genecards.org/).

The STARBASE database was used to analyze potential binding targets between PSMA3-AS1 and miR-140-3p as well as miR-143–0-3p and SRSF10.

Cell lines

Normal human astrocytes (NHA, CP-H122) and glioma cell lines (U251: CL-0237, T98G: CL-0583 and LN229: CL-0578) were purchased from Procell. The NHA was cultured using specialized media (CM-H122, Procell), and the glioma cell lines were cultured in DMEM (PM150210, Procell), except for T98G, which was cultured in MEM medium (PM150410, Procell). The media were supplemented with 10% FBS (164,210, Procell) and 1% penicillin–streptomycin (PB180120, Procell). The incubator was set to 37 °C with 5% CO₂.

For the 293 T cells used for the dual luciferase assay, the same were purchased from Procell Wuhan (CL-0005). And they were cultured with DMEM medium containing 10% FBS and 1% penicillin–streptomycin solution.

Cell transfection

In order to interfere with the expression levels of PSMA3-AS1, miR-140-3p and SRSF10 in cells, we designed and synthesized the relevant sequences by Anhui General Biologicals, the sequences are shown in Table 1. In addition, synthetic miR-140-3p mimic and its negative control were used to overexpress the expression level of miR-140-3p in cells, the sequences are shown in Table 1. All of the above sequences were transfected into cells by lipo6000 transfection reagent (C0526, Beyotime), and subsequent experiments were performed 24 h later.

Table 1.

Sequence of interferences

Name Seqences (5′-3′)
Sh-NC F: TTCTCCGAACGTGTCACGT
R: ACGTGACACGTTCGGAGAA
Sh-PSMA3-AS1#1 F: GGAATATAGTGAAAGATAA
R: TTATCTTTCACTATATTCC
Sh-PSMA3-AS1#2 F: GATAGTTTGAAATAGTTAA
R: TTAACTATTTCAAACTATC
Sh-PSMA3-AS1#3 F: GAAAGTGTTCCTCAATTAA
R: TTAATTGAGGAACACTTTC
Sh-SRSF10#1 F: GGATGTTCGTGATGCTGAA
R: TTCAGCATCACGAACATCC
Sh-SRSF10#2 F: GACTAGATTTAATTACAAA
R: TTTGTAATTAAATCTAGTC
Sh-SRSF10#3 F: CGTAGTTTGTAAAGAAGTA
R: TACTTCTTTACAAACTACG
NC inhibitor CAGUACUUUUGUGUAGUACAA
miR-140-3p inhibitor#1 GUUACGUCAUGCUGUUCUACC
miR-140-3p inhibitor#2 GCUGUUCUACCACAGGGUAGA
miR-140-3p inhibitor#3 CCGUGGUUCUACCCUGTUGGUA
NC mimic UUCUGCCGAAUGUCACGUUU
miR-140-3p mimic UACCACAGGGUAGAACCACGG
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F: Forward; R: Reverse

Cell counting Kit-8 (CCK-8) assay

The transfected cells were then inoculated in 96-well plates, with the number of cells per well maintained at approximately 5,000. Following adhesion of the cells to the wall and incubation, the culture medium was removed and replaced with medium containing CCK-8 solution (Beyotime, C0038). The cells were then incubated under light protection for a period of 4 h, after which the optical density was determined using a microplate reader (Diatek, DR-200Bs).

Transwell assay

For migration, the transfected cells were digested and resuspended, and the number of cells was adjusted to 105 cells/ml using serum-free medium, and subsequently 500 μl was taken and added to the upper chamber (labselect, 14,141), and 1 ml of medium containing FBS was added to the lower chamber, and the small chambers were placed in an incubator for 24 h for staining and observation; for cell invasion, the transwell chambers were pre-coated with matrix gel (Beyotime, C0383), followed by the addition of 800 μl of medium containing 10% FBS to the lower chamber, and the upper chamber was inoculated with treated cells resuspended using serum-free medium and subsequently placed in a thermostat for culture. At the end of the incubation time, the chambers were removed and fixed using 4% paraformaldehyde (P0099, Beyotime) for 15 min at room temperature, then stained with crystal violet (C0121, Beyotime), and finally the untransferred cells in the upper chamber were carefully wiped off with a cotton swab before observation and counting.

ELISA

Inflammatory factors (IL-18 and IL-1β) were measured by ELISA kits. The procedure strictly follows the ELISA kit instructions. The ELISA kits were purchased from Beyotime and the product catalog information is as follows: IL-18: PI305 and IL-1β: PI305.

Relative dual-luciferase reporter gene assay

The PSMA3-AS1 or the mutative NFIX sequence, and SRSF10 also was synthesized into a pGL-U6-puromycin vector (51,133, Addgene) in a luciferase activity. Subsequently, the 293 T cells were co-transfection by WT pGL3-PSMA3-AS1 (or SRSF10) or mutative pGL3-PSMA3-AS1 (or SRSF10) with mimic control and mimic of miR-140-3p by using jetMESSENGER, according to supplier’s step (101,000,005, Polyplus). The result was counted by using a reporter system 24 h after infection (Promega, USA).

Quantitative reverse transcription‐polymerase chain reaction (qRT-PCR)

RNA was extracted from cell samples using TRIzol reagent (Absin, abs60154), and the concentration and purity were determined using an ultra-micro spectrophotometer (Nanoone, Yooying). 500 ng of RNA were aspirated to synthesize complementary DNA (cDNA) using the Reverse Transcription Kit (Absin, abs60246) according to the recommended system, miRNA reverse transcription was performed with a miRNA-specific reverse transcription kit (Absin, abs60269), followed by quantitative polymerase chain reaction (qPCR) using the SYBR qPCR Master Mix (Absin, abs60345). The data were analyzed statistically using the 2−DDCT method. Primer information is shown in Table 2 below.

Table 2.

Primer for qPCR

Gene Primer (5′-3′)
PSMA3-AS1 F: AACAGACCATCAGAAGAGAACA
R: GAACAGAAACCAGAGCCATACA
SRSF10 F: TGAGGATGTTCGTGATGCTGA
R: CCTCCTTTCATAACTTCGGCTT
b-actin F: CCATCGCCAGTTGCCGATCC
R: GCGAGAGGAGCACAGATACCACCAA
miR-140-3p F: GCGCGACCACAGGGAGAA
R: AGTGCAGGGTCCGAGGTATT
U6 F: GCTTCGGCAGCACATATACT
R: GTGCAGGGTCCGAGGTATTC
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Western blot (WB)

Protein samples from cells were extracted using RIPA lysates (Absin, abs9229), and protein concentrations were subsequently quantified using BCA quantification (Absin, abs9232). The protein samples were denatured. This was done by adding 5 × loading buffer (Absin, abs9829) to the initial protein solution. The samples were then boiled at 100 °C for 10 min. Subsequently, SDS-PAGE electrophoresis and membrane transfer were performed, and the proteins were transferred to PVDF membranes (IPVH00010, Merck&Millipore), which were blocked using 3% skimmed milk (Absin, abs9175) and then subjected to antibody incubation, with the primary antibody being incubated overnight at 4 °C, washed by PBST, and the secondary antibody being incubated at room temperature for 2–3 h. After being washed with PBST (Absin, abs9341), the PVDF membranes were incubated in ECL chemiluminescent solution (Absin, abs9434) and then placed on an imaging system (Servicebio, SCG-W2000) to visualize the membrane. Antibody information is shown in Table 3.

Table 3.

Information of antibody

Protein Supplier Catalog
E-cadherin Absin abs171451
N-cadherin Absin abs131133
GSDMD-N Abcam ab215203
Cleaved-caspase1 CST 4199
SRSF10 CST 42,267
b-actin Absin abs132001
Goat anti-Rabbit HRP Antibody Absin abs20040
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Statistical analysis

The average and standard deviation (SD) are calculated from the triple repeat data. The Student t-test serves two cohorts. Tukey's multiple comparison test is used for multiple groups. P < 0.05 indicates a statistically significant difference.

Results

PSMA3-AS1 expression was elevated in glioma

To verify the expression level of PSMA3-AS1 in gliomas, we analyzed by Ualcan database and qPCR. The Ualcan database noted that PSMA3-AS1 expression is elevated in gliomas (Fig. 1A). RT-qCPR results confirmed that PSMA3-AS1 expression was elevated in glioma cells compared to NHA and was highest in the glioblastoma cell line LN229 (Fig. 1B). These results suggested that PSMA3-AS1 shows high expression in glioma.

Fig. 1.

Fig. 1

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Expression levels of LncRNA PSMA3-AS1 in glioma. Expression levels of PSMA3-AS1 analyzed by Ualcan database. B. Expression levels of PSMA3-AS1 in glioma cell lines and normal astrocytes. Data are exhibit as Mean ± SD. **P < 0.01, ***P < 0.001, compared to NHA

Inhibition of PSMA3-AS1 expression promoted glioma cell pyroptosis and inhibited their proliferation and metastasis

To investigate the effect of PSMA3-AS1 on glioma cells, we interfered with PSMA3-AS1 expression and observed changes in glioma cells. By RT-qPCR, we found that sh-PSMA3-AS1#2 was the most effective for the inhibition of PSMA3-AS1 in U251 and LN229 cells (Fig. 2A). CCK-8 results showed that inhibition of PSMA3-AS1 expression suppressed the proliferative capacity of glioma cells (Fig. 2B). Transwell results revealed that inhibition of PSMA3-AS1 suppresses the migration and invasion ability of U251 and LN229 cells (Fig. 2C). ELISA was used to detect the secretion levels of IL-1β and IL-18 in cells, and the results showed that interfering with the expression of PSMA3-AS1 promoted the secretion of IL-1β and IL-18 by glioma cells, suggesting that the secretion levels of inflammatory factors were elevated in glioma cells (Fig. 2D). WB results showed that in LN229 and U251 cells, inhibition of PSMA3-AS1 expression resulted in elevated levels of E-cadherin expression and conversely decreased abundance of N-cadherin protein expression, suggested that the phenomenon of EMT in glioma cells was suppressed, whereas the N-terminal shear body of the GSDMD was associated with an elevated expression level of Cleaved-caspase1 suggesting an elevated level of cellular pyroptosis (Fig. 2E). The above results demonstrated that interfering with PSMA3-AS1 expression can promote glioma cell pyroptosis thereby inhibiting cell proliferation and metastatic ability.

Fig. 2.

Fig. 2

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Effects of inhibiting PSMA3-AS1 expression on glioma cells. A RT-qPCR was used to detect transfection efficiency. B. CCK-8 assay for cell viability. C. Detection of cell migration and invasive capacity. D. The secretion level of IL-1β and IL-18. E. Expression abundance of EMT-associated proteins and pyroptosis-associated proteins. Data are exhibit as Mean ± SD. ***P < 0.001, compared to Sh-NC

miR-140-3p was a downstream target of LncRNA PSMA3-AS1

The potential target miRNAs of LncRNA PSMA3-AS1 were found by STARBASE database, and intersection analysis with glioma-related miRNA dataset GSE158284 in GEO database yielded five related miRNAs, among which miR-140-3p suggested decreased expression in GSE158284 dataset and had a statistical difference (Fig. 3A). And the potential binding target between PSMA3-AS1 and miR-140-3p was obtained by STARBASE database (Fig. 3B). Dual luciferase assays revealed that PSMA3-AS1 wild type with miR-140-3p mimic was able to bind and repress luciferase reporter gene expression, whereas the PSMA3-AS1 mutant was unchanged. It indicated that there is a binding site between PSMA3-AS1 and miR-140-3p (Fig. 3C). RT-qPCR results showed that miR-140-3p expression was decreased in glioma cells, while inhibition of PSMA3-AS1 was able to promote the expression level of miR-140-3p (Fig. 3D and E). The above results suggested that there is an interaction between PSMA3-AS1 and miR-140-3p, and miR-140-3p is a downstream target of PSMA3-AS1.

Fig. 3.

Fig. 3

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PSMA3-AS1 is a molecular sponge for miR-140-3p. A Bioinformatics tools to analyze downstream targets of PSMA3-AS1. B. Possible binding sites for PSMA3-AS1 and miR-140-3p. C. Validation of the binding site of PSMA3-AS1 to miR-140-3p by dual luciferase assay. D. The expression level of miR-140-3p in glioma. E. Expression level of miR-140-3p in glioma cells after inhibition of PSMA3-AS1 expression. Data are exhibit as Mean ± SD. *P < 0.05, **P < 0.01, ***P < 0.001, compared to NC mimic, NHA or Sh-NC

Overexpression of miR-140-3p triggered glioma cell pyroptosis and inhibited cell proliferation and metastasis

To elucidate the effect of miR-140-3p on glioma cells, we constructed miR-140-3p mimic and transfected it into glioma cells. RT-qPCR results showed that miR-140-3p mimic significantly elevated the expression level of miR-140-3p in U251 and LN229 cells as compared with the NC mimic group (Fig. 4A). CCK -8 results suggested that overexpression of miR-140-3p could inhibit the proliferative viability of glioma cells (Fig. 4B). Moreover, overexpression of miR-140-3p significantly inhibited the migration and invasion of glioma cells (Fig. 4C). ELISA results showed that miR-140-3p mimic significantly promoted the secretion of IL-1β and IL-18 in glioma cells (Fig. 4D). WB results showed that elevating the expression level of miR-140-3p in cells significantly promoted the expression level of the focal death-associated protein GSDMD-. N and Cleaved-caspase1 expression levels, while suppressing N-cadherin protein abundance, and E-cadherin protein expression levels in contrast to N-cadherin (Fig. 4E). The above results supported the idea that overexpression of miR-140-3p induced glioma cell pyroptosis and inhibited glioma cell proliferation and metastasis.

Fig. 4.

Fig. 4

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Effects of overexoression of miR-140-3p on glioma cells. A Transfection efficiency of MiR-140-3p mimic. B. Cell viability of U251 and LN229 cells. C. Transwell for cell migration capacity and invasive capacity. D. ELISA for secretion level of IL-1β and IL-18. E. Protein expression abundance of E-cadherin, N-cadherin, GSDMD-N and Cleaved-caspase1 in glioma cells. Data are exhibit as Mean ± SD. **P < 0.01, ***P < 0.001, compared to NC mimic

MiR-140-3p directly targeted SRSF10

To identify downstream targets directly bound by miR-140-3p and associated with glioma, we analyzed and intersected the miRDB, miRWalk, and STARBASE databases to obtain potential ligand targets for miR-140-3p. We identified a total of 249 potential downstream targets of miR-140-3p, termed “Intersection”, and then intersected these genes with glioma-associated genes analyzed in the Genecards database. The results revealed 160 genes, among which SRSF10 exhibited the highest glioma association score (Fig. 5A). STARBASE database suggested a hypothetical binding site between miR-140-3p and SRSF10 (Fig. 5B). The results of dual-luciferase assay suggested that wild-type SRSF10 could bind to miR-140-3p and inhibit luciferase reporter gene expression, whereas mutant SRSF10 was unable to bind to miR-140-3p then there was no notable difference in luciferase reporter gene expression (Fig. 5C). WB and RT-qPCR results suggested that SRSF10 expression was remarkably elevated in glioma cells compared with NHA, especially in U251 and LN229 cells (Fig. 5D and E). Furthermore, overexpression of miR-140-3p was able to dramatically inhibit the expression level of SRSF10 in cells (Fig. 5F). These results suggested that miR-140-3p directly targets binding to SRSF10.

Fig. 5.

Fig. 5

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SRSF10 is a downstream binding target of miR-140-3p. A Analysis of mRNAs associated with gliomas and with binding sites for miR-140-3p using bioinformatics databases. B. Predicted binding targets of SRSF10 to miR-140-3p. C. Dual luciferase reporter gene technology to study the binding site between miR-140-3p and SRSF10. D. The mRNA level of SRSF10 in glioma cells. E. The protein level of SRSF10 in glioma cells. F. Protein abundance of SRSF10 in glioma cells after overexpression of miR-140-3p. Data are exhibit as Mean ± SD. **P < 0.01, ***P < 0.001, compared to NC mimic or NHA

LncRNA PSMA3-AS1 modulated glioma cell proliferation and metastasis at the level of cellular pyroptosis mediated through the miR-140-3p/SRSF10 axis.

To deeply investigate whether PSMA3-AS1 regulates the malignant progression of glioma cells through the miR-140-3p/SRSF10 axis, we interfered with the expression levels of miR-140-3p and SRSF10 in cells. The results showed that miR-140-3p inhibitor#1 had the most obvious inhibitory effect on miR-140-3p, while Sh-SRSF10#3 had the best inhibitory effect on SRSF10 (Fig. 6A and B). In Fig. 6C, we learned that inhibition of PSMA3-AS1 inhibited LN229 cell proliferation, whereas inhibition of miR-140-3p expression promoted LN229 cell proliferation but was reversed by Sh-SRSF10 (Fig. 6C). Transwell results suggested that interfering with PSMA3-AS1 expression was able to inhibit the ability of LN229 cells to migrate and invade, and miR-140-3p inhibitor co-transfection was able to reverse the inhibitory effect of Sh-PSMA3-AS1, whereas Sh-SRSF10 inhibited the metastatic ability of LN229 cells again (Fig. 6D). ELISA results proved that inhibition of PSMA3-AS1 promoted the secretion levels of IL-1β and IL-18 in LN229 cells, whereas co-transfection with miR-140-3p inhibitor promoted the secretion levels of IL-1β and IL-18, but Sh-SRSF10 transfection reversed the effect of miR-140-3p inhibitor (Fig. 6E). WB results confirmed that inhibition of PSMA3-AS1 expression promoted the expression levels of E-cadherin, GSDMD-N, and Cleaved-caspase1 in LN229 cells, while inhibiting the abundance of protein expression of N-cadherin, whereas disruption of miR-140-3p expression reversed the above results, and co-transfection with Sh-SRSF10 again reversed the the effect of miR-140-3p inhibitor (Fig. 6F). The above results pointed to the fact that LncRNA PSMA3-AS1 mediates the malignant progression of glioma cells by regulating cellular pyroptosis through the miR-140-3p/SRSF10 axis.

Fig. 6.

Fig. 6

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Role of PSMA3-AS1 on glioma cells via miR-140-3p/SRSF10. A Transfection efficiency of MiR-140-3p inhibitor. B. Transfection efficiency of Sh-SRSF10. C. Cell viability after transfection. D. Metastatic capacity of LN229 cells. E. The concentration of IL-IL-1β and IL-18. F. The protein level of E-cadherin, N-cadherin, GSDMD-N and Cleaved-caspase1. Data are exhibit as Mean ± SD. *P < 0.05, **P < 0.01, ***P < 0.001, compared to NC inhibitor, Sh-NC or Control; ###P < 0.001, compared to Sh-PSMA3-AS1#2 + NC inhibitor + Sh-NC; $$P < 0.01, $$$P < 0.001, compared to Sh-PSMA3-AS1#2 + miR-140-3p inhibitor#1 + Sh-NC

Discussion

At present, the epidemiology of glioma in China presents a unique situation of “one rise and one high”, i.e., the incidence rate continues to rise and the mortality rate remains high (Li et al. 2022). The main reason for this phenomenon is due to the delayed diagnosis of glioma disease. Currently, in China, the proportion of rural glioma patients diagnosed with intermediate and advanced stages is as high as 60%, while only 35% in urban areas (Zhao et al. 2022). Currently, mutations in IDH1/2, TERT promoter mutations and CDKN2A/B pure deletions are key biomarkers for gliomas (Zhang et al. 2013; Eckel-Passow et al. 2015; Ippen et al. 2025). However, these markers are difficult to generalize to economically disadvantaged areas due to the testing methods. Therefore, the development of new and easily detectable novel biomarkers is important for glioma diagnosis and treatment.

In recent years, more and more studies have confirmed that a variety of LncRNAs regulate the malignant progression of glioma cells and have the potential to become biomarkers for the diagnosis and treatment of glioma. LncRNA H19 had been reported to regulate glioma cell proliferation, migration, and angiogenesis and is a novel target for glioma treatment and diagnosis (Zhou et al. 2022). Knockdown of NEAT1 inhibited the proliferation of glioma cells both in vivo and ex vivo, suggested that NEAT1 may be a new target for glioma therapy (Li et al. 2021). LncRNA ANCR was up-regulated in glioma cells, bound to enhancer homologous protein 2 (EZH2) and inhibited phosphatase and tension homolog (PTEN) expression, promoted cell invasion, migration, and proliferation, while inhibited apoptosis (Cheng et al. 2021). These studies have confirmed the potential of LncRNAs as biomarkers for gliomas. And our study found that LncRNA PSMA3-AS1 expression was elevated in gliomas, and inhibition of PSMA3-AS1 expression significantly promoted glioma cell scotoma and suppressed glioma cell proliferation and metastasis. In addition, in previous studies, LncRNAs had often been shown to exert regulatory effects on gliomas by targeting binding to miRNAs, and in the same way as previous studies, we also found that the LncRNA PSMA3-AS1 acts by directly targeting binding to miR-140-3p.

MiR-140-3p is a classical miRNA, and its role has been demonstrated in a variety of tumor diseases. It had been found that LncRNA AC005224.4 promotes ovarian cancer cell invasion and metastasis by regulating miR-140-3p and SNAI2 axis (Xiong et al. 2023). In addition, LncRNA CCAT1 was shown to regulate its expression by adsorbing miR-140-3p, which in turn affected the expression of ATG5 and promoted the growth of gastric cancer cells in nude mice (Yang et al. 2022). In nasopharyngeal carcinoma, LINC01385 had been confirmed to act as a molecular sponge for miR-140-3p, directly regulating Twist1 mRNA expression and thereby modulating the malignant characteristics of nasopharyngeal carcinoma cells (Li and Zhang 2020). Through these studies, it was easy to see that miR-140-3p is involved in regulating the progression of a variety of tumor diseases and is regulated by a variety of LncRNAs as well as targeting downstream mRNAs.

Our results confirmed that miR-140-3p expression was decreased in glioma and that overexpression of miR-140-3p heightened levels of cellular pyroptosis thereby inhibiting glioma cell proliferation and metastasis. Notably, although one study had already found that LncRNA MIAT acts as a molecular sponge for miR-140-3p and enhances the expression of ZAK, which in turn promotes the antitumor drug doxorubicin to cross the blood-tumor barrier (BTB) and induce apoptosis in glioma cells through the downregulation of tight junction-associated proteins (He et al. 2020). In contrast to our results, we confirmed that miR-140-3p is regulated by the LncRNA PSMA3-AS1 and targets the downstream target SRSF10 to regulate glioma cell proliferation and metastasis.

As a multifunctional splicing factor, SRSF10 is deeply involved in shaping the developmental, metabolic, and immune microenvironments by precisely regulating variable splicing and RNA stability (Zhong et al. 2023). SRSF10 mediated upregulation through E6E7, regulated selective splicing of interleukin-1 receptor accessory protein, which in turn promotes cervical carcinogenesis and inhibits macrophage phagocytosis (Liu et al. 2018). SRSF10 drove colorectal cancer development by generating aberrantly spliced RFC5 exon2-AS1(S) transcript variants, suggested that SRSF10 may become an important target for clinical diagnosis and treatment of colorectal cancer (Xu et al. 2024). Interestingly, Cai et al. found that removal of SRSF10 in oligodendrocyte lineage cells (OLCs) resulted in attenuated myelin production and a reduced number of OLCs, this study that provides important insights into understanding OLCs development and exploring potential therapeutic strategies for diseases associated with demyelination (Mu et al. 2025). These studies had confirmed the important role of SRSF10 in tumor diseases and neurological disorders, and our study also confirmed that SRSF10 expression was elevated in glioma cells, and that inhibition of SRSF10 was able to reverse the promotional effect of miR-140-3p inhibitor on glioma cells.

In conclusion, our results confirmed that LncRNA PSMA3-AS1 affects the malignant proliferation and metastasis of glioma cells by regulating cellular pyroptosis through the miR-140-3p/SRSF10 axis. It is suggested that LncRNA PSMA3-AS1 possesses the potential to be a powerful target for glioma diagnosis and treatment in the future.

Conclusion

In the present study, we found that LncRNA PSMA3-AS1 expression was elevated in glioma cells, and SRSF10 expression level was also elevated, while miR-140-3p expression was decreased in glioma cells. The present study also demonstrated that inhibition of LncRNA PSMA3-AS1 or overexpression of miR-140-3p could inhibit the proliferation and metastasis of glioma cells by enhancing the level of cellular pyroptosis, and that inhibition of SRSF10 expression had the same effect. However, there are still some limitations in this study, such as the lack of in vivo studies, and subsequent in vivo studies will be conducted using tumor-bearing mice to improve the study of the effects of LncRNA PSMA3-AS1 on glioma, and to provide stronger evidence that LncRNA PSMA3-AS1 is a potential target for the diagnosis and treatment of glioma.

Author Contributions

Zhengzheng Liu: Conceptualization, Funding acquisition, Writing—Original Draft, Data Curation, Visualization. Min Wang: Investigation, Resources. Weilu Kuang: Funding acquisition, Supervision, Project administration, Writing—Review & Editing.

Funding

This study was supported by the Natural Science Foundation of Hunan Province (No. 2022JJ40795 and No. 2024JJ5620).

Data Availability

The dataset used in this work was retrieved from the publicly available NCBI’s Gene Expression Omnibus database (GEO, https://www.ncbi.nlm.nih.gov/geo/). Dataset GSE158284 was generated by Junior LGD et al. and is available at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc = gse158284 The data that support the findings of this study are available from the coresponding author, Weilu Kuang, upon reasonable request.

Declarations

Conflict of Interest

The authors declare no competing interests.

Ethical approval

Not applicable.

Consent for publication

Not applicable.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The dataset used in this work was retrieved from the publicly available NCBI’s Gene Expression Omnibus database (GEO, https://www.ncbi.nlm.nih.gov/geo/). Dataset GSE158284 was generated by Junior LGD et al. and is available at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc = gse158284 The data that support the findings of this study are available from the coresponding author, Weilu Kuang, upon reasonable request.

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