Abstract Background Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with poor prognosis and limited treatment options. Autophagy targeting plays a complex role in tumor resistance. The role of long noncoding RNA (LncRNA) RMST in TNBC progression and its potential involvement in autophagy regulation remain largely unexplored. Methods We performed a bioinformatics analysis using transcriptome sequencing data to identify differentially expressed genes related to autophagy and the LncRNA-miRNA-mRNA axis in TNBC. The effects of the LncRNA RMST-miR-4295-ITPR1 axis on TNBC cell proliferation and migration were investigated using CCK-8, EdU, Transwell, and wound healing assays. Additionally, a series of in vitro experiments, including flow cytometry, transmission electron microscopy, and western blotting, were performed to evaluate the role of the LncRNA RMST-miR-4295-ITPR1 axis in regulating autophagy. Results LncRNA RMST competes with ITPR1 mRNA for miR-4295 binding, thereby relieving the miR-4295-mediated suppression of ITPR1 and increasing ITPR1 expression. Overexpression of LncRNA RMST or ITPR1 significantly inhibited TNBC cell proliferation and migration, promoted apoptosis, and enhanced autophagy. Conversely, miR-4295 overexpression reversed these effects, confirming the regulatory role of the LncRNA RMST-miR-4295-ITPR1 axis in autophagy in TNBC. Conclusions Our findings indicate that the LncRNA RMST-miR-4295-ITPR1 axis plays a crucial role in regulating autophagy in TNBC cells. The modulation of this axis may represent a novel therapeutic strategy for inhibiting TNBC progression and overcoming chemoresistance. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-025-14189-7. Keywords: TNBC, LncRNA RMST, MiR-4295, ITPR1, Autophagy Background Triple-Negative Breast Cancer (TNBC) is the most aggressive subtype of breast cancer [[34]1]. Owing to the lack of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expression, TNBC is insensitive to traditional endocrine therapy and HER2-targeted treatments. Therefore, the choice of treatment options for TNBC is limited, and chemotherapy is currently the primary clinical approach [[35]2]. However, the problem of chemoresistance in TNBC cells is severe, and there is an urgent need to identify new therapeutic targets and strategies [[36]3]. Autophagy is a process of cellular self-degradation and recycling [[37]4]. Autophagy-mediated molecular pathways are crucial for maintaining cellular homeostasis and responding to external stress [[38]5]. The effects of autophagy on the promotion or inhibition of tumor cell survival are somewhat complex [[39]6]. Autophagy helps tumor cells survive by recycling nutrients from damaged cells, thereby thus increasing their chemoresistance [[40]7]. In other cases, persistent autophagy can induce tumor cell death to combat chemoresistance [[41]8]. The role of autophagy in TNBC is complex. Some studies have shown that the activation of autophagy may be associated with chemoresistance in TNBC cells and that inhibiting autophagy may help enhance the efficacy of chemotherapy [[42]9]. However, other studies have shown that inhibiting oncogene expression can promote autophagy, thereby inhibiting the growth and metastasis of TNBC [[43]10]. Therefore, a deeper understanding of the mechanisms underlying autophagy in TNBC is important for developing new therapeutic strategies. Long non-coding RNA (LncRNAs) are a class of non-coding RNA molecules exceeding 200 nucleotides in length. They play important roles in various biological processes including gene expression regulation, cell differentiation, and tumorigenesis [[44]11]. Particularly, LncRNAs interact with microRNAs (miRNAs) to form the LncRNA-miRNA-mRNA regulatory axis, which is involved in the regulation of tumor-related gene expression [[45]12]. In recent years, research on LncRNAs in TNBC has gradually increased, revealing that abnormal expression of certain LncRNAs is closely related to the malignant behavior of TNBC [[46]13]. Moreover, various types of non-coding RNAs have been shown to be involved in the regulation of autophagy in TNBC [[47]14, [48]15]. Inositol-1,4,5-trisphosphate receptor type 1 (ITPR1) is an endoplasmic reticulum calcium channel protein that regulates intracellular calcium ion concentration and affects processes such as cell proliferation, differentiation, and apoptosis. Genetic association studies have identified ITPR1 variants as an important risk factor for breast cancer development in the Chinese population [[49]16], while systematic analyses have shown that reduced expression is associated with poor prognosis and altered tumor immune microenvironment in breast cancer patients [[50]17]. Of particular note is the involvement of ITPR1 in autophagy regulation, which has been demonstrated in esophageal cancer, where ITPR1 has been identified as a key autophagy related gene [[51]18, [52]19]. The findings in thyroid papillary carcinoma further strengthen the mechanistic link between ITPR1 and autophagy, in which ITPR1-mediated autophagy is epigenetic regulated by lncRNA SLC26 A4-AS1 through ETS1 recruitment [[53]20]. TNBC is the most aggressive subtype of breast cancer with limited treatment options, and ITPR1 expression is significantly down-regulated, although its functional consequences remain unclear. Given the critical role of autophagy in TNBC progression, chemor esistance, and immune evasion, we hypothesize that ITPR1 may serve as a crucial regulator of autophagic flux in TNBC cells, potentially influencing their malignant behavior and therapeutic response. Materials and methods Transcriptome data screening related to TNBC This study first collected breast cancer clinical data files (Additional file 1) from The Cancer Genome Atlas (TCGA, [[54]https://portal.gdc.cancer.gov/]) and used the R language to read the file, examining the dimensions of the data and some column names. The “grep” function was then used in combination with column names to screen for columns containing receptor status information, and these columns were extracted. Samples with all receptor statuses as “Negative” were screened out, which are the TNBC samples. Subsequently, the breast cancer transcriptome data (Additional file 2) was read, and the “merge” function was used to match the screened TNBC samples with the transcriptome data. This TNBC transcriptome data was then converted into a gene expression matrix with gene symbols as identifiers, where rows represent samples and columns represent genes (Additional file 3). Differentially expressed genes (DEGs) were screened using the criteria of p-value < 0.05 and |log[2]FC|> 1 (Additional file 4). Using Perl scripts with UCSC gene annotations, we extracted non-coding transcripts (annotated as'lncRNA'or'lincRNA') through symbol-based matching of the expression matrix, excluding potential coding sequences. The complete set of TNBC-related lncRNAs is provided in Additional file 5. From this dataset, we identified differentially expressed lncRNAs (p-value < 0.05 and |log[2]FC|> 1) that may be linked to disease pathogenesis, as shown in Additional file 6. Identification of autophagy-related DEGs Autophagy-related genes were obtained from the HADb Human Autophagy Database ([55]http://www.autophagy.lu/index.html) (Additional file 7), and the intersection was obtained with the differentially expressed genes (Additional file 8). The intersecting genes were subjected to Kyoto Encyclopedia of Genes and Genomes (KEGG) (Additional file 9) and Gene Ontology (GO) (Additional file 10) enrichment analyses to explore the main functions and biological processes of the DEGs. LncRNA-miRNA-mRNA axis prediction To further refine our screening and reduce the number of false-positive DEGs, we applied a more stringent cutoff of |log[2]FC|> 2. This identified a subset of genes with highly significant expression changes, including CX3CL1, HSPB8, ITPR1, MAP1LC3C, NRG1, TP63, and FOS. Using the gene expression matrix of 11 tumor and 11 normal breast tissue samples included in Additional file 3. To visualize the expression patterns, bar plots were generated for each gene, depicting the mean expression values (± standard error of the mean, SEM) for the tumor and normal groups (Additional file 11). Subsequently, we utilized the TargetScanHuman 7.2 database ([56]https://www.targetscan.org/vert_72/) to predict miRNAs with a context score > 95 that target these genes (Additional File 12). In parallel, we employed the miRcode database to predict miRNAs potentially regulated by differentially expressed lncRNAs (Additional File 13). By intersecting the miRNAs associated with both lncRNAs and mRNAs, we highlighted those miRNAs that were co-targeted by lncRNAs and mRNAs in yellow. Our analysis revealed that: Three genes (CX3CL1, MAP1LC3C, TP63) had predicted upstream miRNAs that did not overlap with lncRNA-targeted miRNAs. Four genes (HSPB8, ITPR1, NRG1, FOS) could form LncRNA-miRNA-mRNA regulatory axes, as their predicted miRNAs were also targeted by lncRNAs. Three genes (CX3CL1, MAP1LC3C, TP63) showed no overlap of predicted upstream mirnas with lncrNA-targeted mirnas, suggesting that their regulation may be independent of lncRNA-mediated mechanisms in our model. The other three genes (HSPB8, NRG1, FOS) can form the LncRNA-miRNA-mRNA regulatory axis, but their interaction has been reported in TNBC [[57]21–[58]23]. Given its unknown role in TNBC autophagy and the novelty of its predictive regulatory axis, we prioritize further functional validation of ITPR1 in TNBC progression and treatment response. Clinical sample This study was approved by the Ethics Committee of the Second Hospital of Hebei Medical University (2024-R510), and all procedures were performed in accordance with the ethical principles outlined in the Declaration of Helsinki. A total of 24 tissue samples were collected from July 2024 to October 2024, including 12 TNBC tissues and 12 adjacent non-cancerous tissues. After dissection, the samples were immediately snap-frozen in liquid nitrogen and stored at − 80 °C. The diagnosis of TNBC is based on the absence of ER, PR, and HER2 expressions. All tissue samples were obtained from patients who provided written informed consent prior to the surgery. Cell culture Normal human breast epithelial cell line MCF 10A (CL-0525) and five human breast cancer cell lines, MDA-MB-468 (CL-0290), MDA-MB-231 (CL-0150), BT-20 (CL-0324), HCC1937 (CL-0093), and BT- 549 (CL-0041), were purchased from Wuhan Pricella Life Technology Co., Ltd. and cultured according to the recommended protocols. The culture conditions were as follows: MCF 10 A cells were cultured in MEM/F12 supplemented with 5% horse serum (HS), 20 ng/ml epidermal growth factor (EGF), 0.5 µg/ml hydrocortisone, 10 µg/ml insulin, 1% non-essential amino acids (NEAA), and 1% penicillin/streptomycin (P/S); MDA-MB- 468 and MDA-MB- 231 cells were cultured in DMEM supplemented with 10% fetal bovine serum (FBS) and 1% P/S; BT- 20 cells were cultured in MEM (with NEAA) supplemented with 10% FBS and 1% P/S; HCC1937 cells were cultured in RPMI- 1640 supplemented with 10% FBS and 1% P/S; BT- 549 cells were cultured in RPMI- 1640 supplemented with 10% FBS, 10 µg/ml insulin, and 1% P/S. All cells were incubated in a humidified atmosphere at 37 °C with 5% CO₂ and 95% air. The cells were passaged when they reached 80% confluence, and the culture medium was changed every two days. Quantitative real-time reverse transcription PCR (qRT-PCR) Total RNA was extracted from MDA-MB-468 cells using the TRIzol reagent (15596026, Thermo Fisher Scientific Inc., USA). The concentration and purity of the RNA were determined by measuring the absorbance at 260 nm and the A260/A280 ratio. Complementary cDNA was synthesized from 1 µg of total RNA in a 10 µL reaction volume using the HiScript IV 1 st Strand cDNA Synthesis Kit (R412 - 01, Nanjing Vazyme Biotech Co., Ltd., China) according to the manufacturer's instructions, which included a gDNA eraser step. The reaction program was 37 °C for 15 min and 85 °C for 5 s. Subsequently, qRT-PCR was performed using SYBR Green qPCR Master Mix (BL698 A, Labgic Technology Co., Ltd., China). The primers for the target genes, LncRNA RMST, miR- 4295, and ITPR1 are listed in Additional file 14. GAPDH was used as an endogenous control. The total reaction volume for qRT-PCR was 20 µL, containing 10 µL of SYBR Green qPCR Master Mix, 0.4 µL of each primer, and 2 µL of cDNA template. The thermal cycling conditions were as follows: 95 °C for 10 min; 95 °C for 10 s; 60 °C for 30 s; 72 °C for 30 s; 40 cycles. The specificity of the amplification was verified using melting curve analysis. Construction of overexpression vector ITPR1 and LncRNA RMST were amplified by PCR amplification kit (R011, takara, China) using human cDNA as template. The reaction was set at 98 °C for 3 min, (98 °C 10 s, 60 °C 15 s, 72 °C 2 min) × 30 cycles; 72 °C for 10 min. The plasmid vector pcDNA3.1(+) and the target gene cDNA were double-digested using the restriction enzymes BamHI (R0136 V, New England Biolabs [Beijing] LTD, China) and EcoRI (R0101 V, New England Biolabs [Beijing] LTD, China). Conditions: 37 °C for 4 h, 65 °C for 20 min. The plasmid and the target gene were separated by 1% agarose gel electrophoresis and the target bands were cut. DNA was recovered using Zymoclean Kit and eluted (D4001 T, Zymo Research Corporation, USA) on 30 µL ddH[2]O. The primers used are listed in Additional file 14. Subsequently, the digested vector and target gene fragments were ligated using T4 DNA ligase (EL0011, Thermo Fisher Scientific Inc., USA) to construct the recombinant plasmid. The ligation reactions were performed at 16 °C overnight. Take 5 µL of the ligation product and add it to 50 µL of DH5 α competent cells. Incubate on ice for 30 min, then heat-shock at 42 °C for 45 s, followed by cooling on ice for 2 min., The positive clones were identified by ampicillin (ST008, Beyotime Biotechnology Inc., China) selection and colony PCR. Finally, the positive bacterial culture was sent to Sangon Biotech (Shanghai) Co., Ltd. for full-length sequencing. Cell transfection The cells were seeded into 24-well plates at a density of 5 × 10^^4 cells per well and cultured until they reached 80% confluence. Lipofectamine 3000 (L3000001, Thermo Fisher Scientific Inc., USA) was used to transfect the constructed overexpression plasmid. A mixture of 25 µL Opti-MEM I medium and 0.5 µL Lipofectamine 3000 reagent was prepared, while 1 µL of P3000™ reagent and 25 µL Opti-MEM I medium were added to the plasmid. The two solutions were then combined and incubated at 25 °C for 10 min. The resulting 50 µL complex was added to the cell culture medium for a 48-h incubation. Gene knockdown The siRNA sequences (Additional file 14) used in this experiment were synthesized by GenScript Biotech Corporation and transfected into breast cancer cell lines using Lipofectamine RNAiMAX (13778100, Thermo Fisher Scientific Inc., USA). We generated three pairs of primers, si-LncRNA RMST- 1, si-LncRNA RMST- 2, si-LncRNA RMST- 3. First, siRNA and Lipofectamine RNAiMAX were each diluted in 50 µL Opti-MEM I serum-free medium, then combined and incubated at 25 °C for 15 min. The complex was then added to the cell culture medium for a 48-h incubation. Total RNA was extracted from cells using TRIzol reagent, and the relative expression level of LncRNA RMST was detected by qRT-PCR to verify the silencing effect of si-RMST. miRNA mimics and inhibitor transfection In this experiment, we used the miR-4295 mimics (HY-[59]R00975) and inhibitor (HY-RI00975) provided by MedChemExpress, as well as miRNA transfection reagent (HY-K2017, MedChemExpress, USA) for cell transfection. The transfection working concentrations were optimized to 50 nM for mimics and 100 nM for inhibitor, respectively. Prior to cell transfection, we pre-seeded cells to 5 × 10^^4 and prepared a transfection mix in serum-free medium, adding a total volume of 500 μL of the mixture per well, consisting of serum-free medium, miRNA, and transfection reagent, and incubating for 20 min at 25 ℃ after gentle mixing. After transfection, the transfected cells were incubated at 37 ℃ for 48 h, and the transfected cells were analyzed by qRT-PCR. Cell counting kit-8 (CCK-8) MDA-MB-468 cells were seeded into 96-well plates at a density of 5,000 cells per well and allowed to adhere for 24 h. At 0, 24, and 48 h, 10 μL of CCK- 8 solution (40203ES60, Yeasen Biotechnology [Shanghai] Co., Ltd., China) was added to each well. The plates were then incubated at 37 °C for 2 h. Absorbance was measured at 450 nm using a microplate reader (FlexA-200, Allsheng Instruments Co., Ltd., China). 5-Ethynyl-2'-deoxyuridine (EdU) MDA-MB- 468 cells were seeded into 96-well plates at a density of 3,000 cells/well and incubated overnight to allow cell attachment. After 24 h, the medium was replaced with a fresh medium containing 10 µM EdU. The cells were then incubated for an additional 2 h to allow EdU incorporation. The cells were fixed in PBS containing 4% paraformaldehyde (BL539 A, Labgic Technology Co., Ltd., China) at 25 °C for 15 min. After fixation, the cells were permeabilized with PBS containing 0.5% Triton X- 100 (P0096, Beyotime Biotechnology Inc., China) for 10 min. EdU detection was performed using the Cell-Light™ EdU Apollo In Vitro Kit ([60]C10310 - 1, Guangzhou RiboBio Co., Ltd., China) according to the manufacturer's instructions. The nuclei were stained with Hoechst 33,342 and the cells were incubated with 1 × Apollo staining solution for 30 min. The cells were observed under a fluorescence microscope (FM- 400, Shanghai Puda Optical Instruments Co., Ltd., Shanghai, China), and images were captured. Proliferation rate was calculated as the percentage of EdU-positive cells relative to the total number of cells. Transwell Transwell inserts with a pore size of 8 μm (FTW010 - 6Ins, Beyotime Biotechnology Inc., China) were used. Matrigel (354262, Corning Inc., USA) was thawed on ice and diluted to a concentration of 1:8 with serum-free DMEM. One hundred microliters of the diluted Matrigel was added to the upper surface of the membrane and solidified at 37 °C for 1 h to form a gel layer. Cells (5 × 10^^4) in serum-free medium were seeded into the upper chamber of the Transwell inserts. The lower chamber was filled with DMEM containing 10% FBS as a chemoattractant. After incubation for 24 h, the stained cells were washed with PBS, and images were captured for documentation. Finally, the number of invading cells was quantified using the ImageJ software (ImageJ2) [[61]24]. Cell healing experiment The cells were seeded at a density of 10^^5 per well in 6-well plates. When the cell confluence reached 80%, a wound was created in the cell monolayer by scratching with a 200-µL pipette tip. The cell debris was washed away with PBS, and the remaining cells were incubated in serum-free medium. Images of the wound area were captured at 0 and 48 h using an inverted microscope (NIB900, Ningbo Yongxin Optical Co., Ltd., China). The wound healing percentage was calculated by comparing the wound area at 0 and 48 h. Flow cytometry Apoptosis was assessed via flow cytometry using an Annexin V-FITC/PI kit (CA1020, Beijing Solarbio Science & Technology Co., Ltd., Beijing, China). Cells were collected, washed with PBS, and resuspended in buffer. Annexin V-FITC and PI were added to the cell suspension, and the mixture was incubated at 25 °C in the dark for 15 min. The cells were then analyzed using a flow cytometer. The apoptotic rate was calculated as the sum of the percentages of early and late apoptotic cells. Transmission electron microscopy MDA-MB-468 cells were fixed in 2.5% glutaraldehyde (111–30 - 8, Shanghai Maokang Biotechnology Co., Ltd., China) at 4 °C for 2 h. The cells were then dehydrated using a graded series of ethanol solutions and embedded in Epon resin (E8000, HEDE BIOTECHNOLOGY Co., Ltd., China). Ultrathin sections were cut using an ultramicrotome (EM UC7, Leica, Germany) and stained with uranyl acetate (SPI- 02624, HEAD BIOTECHNOLOGY CO., LTD, China) and lead citrate (521–26 - 5, Hubei Yongkuo Technology Co., LTD, China). The sections were examined under a transmission electron microscope (Tecnai G2 F20, Thermo Fisher Scientific Inc., USA). Autophagosomes are double-membrane vesicles that contain cytoplasmic components. Autophagic vacuoles were marked with red arrows, and the nucleus was labeled “N” The number of autophagosomes per cell was calculated. Western blot MDA-MB- 468 cells were lysed in RIPA buffer (P0013C, Beyotime Biotechnology, Inc., China). The protein concentrations were determined using a BCA protein assay kit (PK10026, Proteintech, China). Equal amounts of proteins were separated via SDS-PAGE and transferred onto PVDF membranes (FFP39, Beyotime Biotechnology Inc., China). The membranes were blocked with 5% skim milk in TBST and then incubated overnight at 4 °C with primary antibodies against ITPR1, P62, LC3 II/I, Beclin1, Bcl2, and GAPDH (as a loading control). After washing, the membranes were incubated with secondary antibodies for 1 h at 25 °C. Protein bands were visualized using an ECL substrate (34,577, Thermo Fisher Scientific Inc., USA) and detected using a chemiluminescent imaging system (SH-CUTE523, Hangzhou Shenhua Technology Co., Ltd., China). Band intensities were quantified using the ImageJ software. Information on the antibodies used in the experiments is provided in Additional file 15. Statistical analysis The significance of the differences in expression between TNBC samples and controls was assessed using paired t-tests. The intersection of relevant miRNAs was determined using set-theoretic operations. Data from cell experiments were expressed as the mean ± SEM of three independent experiments (n = 3). Unpaired t-tests were used for comparisons between two groups, while one-way ANOVA was used for comparisons among four groups, indicated as * p < 0.05, ** p < 0.01, *** p < 0.001,****p < 0.0001. Result Identification of differentially expressed genes through bioinformatics analysis We collected and analyzed transcriptomic data of TNBC from TCGA database. A volcano plot (Fig. [62]1A) illustrates the differences in gene expression between TNBC and normal breast tissues, with the screening criteria set at |log[2] FC|> 1 and p-value < 0.05. Next, we generated a clustering heatmap (Fig. [63]1B) showing the top 30 DEGs, with non-tumor tissues on the left and tumor tissues on the right. Sample clustering based on gene expression profiles revealed distinct expression patterns in TNBC and normal breast tissues. To further explore the overlap between the DEGs and genes identified in the autophagy database, we constructed a Venn diagram (Fig. [64]1C). The analysis revealed that 28 genes were differentially expressed in TNBC and were significantly associated with autophagy. Through GO analysis, we identified significantly enriched biological processes, cellular components, and molecular functions among DEGs in TNBC. These included processes such as cell cycle regulation, DNA replication, and the regulation of adipocyte lipolysis, highlighting their potential roles in TNBC progression (Fig. [65]1D). KEGG pathway analysis revealed significant enrichment in pathways such as the neuroactive ligand-receptor interaction, PI3K-Akt signaling pathway, and cytokine-cytokine receptor interaction (Fig. [66]1E). Fig. 1. [67]Fig. 1 [68]Open in a new tab Identification and Analysis of DEGs in TNBC. A The volcano plot shows the differential expression and fold changes of genes. Red dots represent significantly upregulated genes, blue dots represent significantly downregulated genes, and gray dots indicate genes with no significant changes. B The heatmap displays the expression patterns of DEGs, with red clusters indicating upregulated genes in TNBC and blue clusters indicating downregulated genes. C The Venn diagram reveals the overlap between differentially expressed genes (DIFF) and autophagy-related genes (AUTOphag). D The circular plot illustrates the results of the GO enrichment analysis for gene functions. Different colors in the outer circle represent various functional categories, and the inner pie chart shows specific functional items under each category. E The bubble plot shows the results of the KEGG pathway enrichment analysis Low expression of ITPR1 in breast cancer is associated with poor prognosis We further analyzed 28 DEGs using the criterion |log[2] FC|> 2 and identified seven genes with significant differences in expression: CX3CL1, HSPB8, ITPR1, MAP1LC3 C, NRG1, TP63, and FOS. The relative expression levels of these seven genes in TNBC are shown in Additional file 5. Subsequently, using the TargetScanHuman 7.2 database ([69]https://www.targetscan.org/vert_72/), we screened for miRNAs with scores greater than 95 that were related to each of these genes. Based on gene annotations from the UCSC database, we extracted LncRNA gene expression data from the symbols and identified differentially expressed LncRNAs that may affect disease progression using the criteria |log[2]FC|> 1 and p-value < 0.05. The identified LncRNAs were C2orf48, RMST, C10orf91, C17orf77, KIAA0087, and HCG22. We then used mircode.txt provided by the miRcode website ([70]http://www.mircode.org/) to identify the miRNAs associated with these LncRNAs. By intersecting the miRNAs upstream of the mRNAs and downstream of the LncRNAs, we found that HSPB8, ITPR1, NRG1, and FOS had the potential to form LncRNA-miRNA-mRNA axes. Additionally, we discovered that LncRNA RMST and ITPR1 both target miR-4295. Using the UALCAN database ([71]https://ualcan.path.uab.edu/analysis.html), we performed a differential expression analysis of ITPR1 in tissues and found that its expression was lower in all major breast cancer subtypes than in normal breast tissue (Fig. [72]2A). Additionally, using the Kaplan–Meier Plotter database ([73]https://kmplot.com/analysis/), we discovered that recurrence-free survival (RFS) differed significantly between the low and high-expression groups of ITPR1 (log-rank P = 2.8e- 15). The hazard ratio (HR) for high ITPR1 expression was 0.66 (95% CI: 0.6–0.73), indicating that high ITPR1 expression is associated with better RFS (Fig. [74]2B). Furthermore, Fig. [75]2C shows that the overall survival (OS) differed significantly between the low and high expression groups of ITPR1 (log-rank P = 0.00013). The HR for high ITPR1 expression was 0.69 (95% CI: 0.57–0.83), indicating that high ITPR1 expression is associated with better OS. Fig. 2. [76]Fig. 2 [77]Open in a new tab Low expression of ITPR1 in breast cancer is associated with poor prognosis. A ITPR1 expression in different breast cancer subtypes. B Relationship between ITPR1 expression and recurrence-free survival (RFS). C Relationship between ITPR1 expression and overall survival (OS). Error bars represent SEM (statistical significance indicated as ****p < 0.0001) ITPR1 inhibits the proliferation, migration, and invasion of TNBC cells RT-qPCR was performed to compare the relative expression levels of ITPR1 mRNA in TNBC and normal breast tissues. Figure [78]3A shows that ITPR1 expression was significantly downregulated in tumor tissues compared to that in normal tissues (P = 0.0217), suggesting a potential role of ITPR1 in breast cancer development. To evaluate ITPR1 expression in various breast cancer cell lines, we performed qRT-PCR using the MCF- 10 A cell line as a control. ITPR1 expression decreased in five common breast cancer cell lines, with the lowest expression observed in the MDA-MB-468 cell line (Fig. [79]3B). Therefore, we overexpressed ITPR1 in MDA-MB- 468 cells and validated the overexpression efficiency using Western blot (Fig. [80]3C) and qRT-PCR (Fig. [81]3D). Next, we employed the CCK- 8 assay to evaluate the impact of ITPR1 overexpression on cell proliferation. Figure [82]3E shows that ITPR1 overexpression significantly inhibited cell proliferation at 24 and 48 h compared to the vector control. Transwell assays revealed a reduction in the number of migrating cells in the ITPR1 overexpression group (Fig. [83]3F). Wound-healing experiments were conducted to evaluate tumor cell migration. Figure [84]3G shows that the wound area was smaller in the oe-ITPR1 group than in the vector control group at 48 h, suggesting a diminished migration capacity of tumor cells. EdU assay was used to assess DNA replication in MDA-MB- 468 cells overexpressing ITPR1. Figure [85]3H shows that the number of EdU-positive cells was significantly reduced in the oe-ITPR1 group compared to that in the vector control group, indicating decreased cell proliferation. Fig. 3. [86]Fig. 3 [87]Open in a new tab ITPR1 inhibits the proliferation, migration, and invasion of triple-negative breast cancer cells. A The relative mRNA expression levels of ITPR1 in tumor and adjacent normal tissues. B The relative mRNA expression levels of ITPR1 in various cell lines. C Western blot was used to examine the expression of ITPR1 protein in overexpressing and control cells. D qRT-PCR was used to detect the relative expression levels of ITPR1 mRNA. E CCK8 assay showing the OD450 values of MDA-MB-468 cells in vector and oe-ITPR1 groups at 0, 24, and 48 h. F Transwell assay examining the invasive ability of tumor cells. G Wound healing assay indicating the migratory capacity of tumor cells. H EdU assay depicting the proliferation of tumor cells in vector and oe-ITPR1 groups. Data are presented as mean± SEM from three independent experiments (n=3) (statistical significance indicated as * p < 0.05, ** p < 0.01, ****p < 0.0001) Overexpression of ITPR1 promotes apoptosis and autophagy in TNBC cells To evaluate the effect of ITPR1 overexpression on apoptosis, flow cytometry was performed. The bar chart in Fig. [88]4A shows that the apoptosis rate was significantly increased in the oe-ITPR1 group compared to the vector control. Transmission electron microscopy was used to observe the autophagic structures in MDA-MB- 468 cells. In Fig. [89]4B, the red arrows indicate autophagic vacuoles within the cells. The oe-ITPR1 group showed a significant increase in the number of autophagosomes compared to the vector control. In MDA-MB- 468 cells overexpressing ITPR1, western blot analysis revealed a significant decrease in P62 protein levels and an increase in the LC3 II/I ratio, indicating enhanced autophagic flux. The upregulation of Beclin1 further supports the activation of autophagy. Conversely, the downregulation of Bcl2 protein levels suggests that ITPR1 overexpression promotes autophagy by relieving the inhibitory effect of Bcl2 on Beclin1 (Fig. [90]4C and D). Fig. 4. [91]Fig. 4 [92]Open in a new tab Overexpression of ITPR1 promotes apoptosis and autophagy in TNBC cells. A Flow cytometry analysis showing the apoptosis rate of MDA-MB-468 cells. B Transmission electron microscopy images depicting autophagosomes in tumor cells of the vector and oe-ITPR1 groups. C Western blot analysis of the expression levels of P62, LC3 II/I, Beclin1, and Bcl2 in the vector and oe-ITPR1 groups. D Bar charts showing the changes in protein levels of p62, LC3 II/I, Beclin1, and Bcl2 between the vector and oe-ITPR1 groups. Data are presented as mean±SEM from three independent experiments (n=3) (statistical significance indicated as * p < 0.05, ** p < 0.01) LncRNA RMST activates ITPR1 by sponging miR-4295 Firstly, we verified the expression levels of LncRNA RMST and miR-4295 in clinical tissues. Figure [93]5A shows that the expression of LncRNA RMST in tumor tissues was significantly lower compared to adjacent normal tissues (P = 0.0092). Figure [94]5B shows that the expression of miR- 4295 in tumor tissues was significantly higher compared to adjacent normal tissues (P = 0.0183). These results suggest that LncRNA RMST and miR- 4295 may play important roles in tumors, providing a theoretical basis for further cellular experiments. Based on these expression differences observed in clinical tissues, we conducted experiments in cells to silence and overexpress LncRNA RMST to explore its effects on the expression of miR- 4295 and ITPR1. According to the RT-qPCR analysis results shown in Fig. [95]5C, we observed that the expression level of si-LncRNA RMST was significantly lower than that of the negative control group (si-LncRNA RMST-NC). This suggests that these Sirnas can effectively silence the expression of RMST. Specifically, the si-LncRNA RMST- 3 group showed the lowest RMST mRNA expression levels. Therefore, based on these results, we selected si-LncRNA RMST- 3 for subsequent knock-down experiments. RT-qPCR analysis showed that silencing of LncRNA RMST (si-LncRNA RMST) led to significantly decreased expression of LncRNA RMST and increased levels of miR- 4295, whereas overexpression of LncRNA RMST (pcDNA3.1-LncRNA RMST) had the opposite effect. Additionally, the ITPR1 mRNA level was significantly reduced in the si-LncRNA RMST group and increased in the pcDNA3.1-LncRNA RMST group, suggesting that LncRNA RMST regulates ITPR1 transcription (Fig. [96]5D). Western blot analysis confirmed these findings at the protein level, with decreased ITPR1 protein levels in the si-LncRNA RMST group and increased ITPR1 protein in the pcDNA3.1-LncRNA RMST group (Fig. [97]5E). To explore the mechanism by which LncRNA RMST affects ITPR1 expression, we assessed the effect of miR- 4295 on ITPR1 protein levels. qRT-PCR was used to evaluate the transfection efficiency of miR- 4295 mimics and inhibitors in cells. Additional file 16 showed that miR- 4295 mimics and inhibitors significantly successfully regulated the expression of miR- 4295 in MDA-MB- 468 cells. The miR- 4295 inhibitor increased ITPR1 protein levels, whereas treatment with the miR- 4295 mimic decreased ITPR1 protein levels. These results indicate that LncRNA RMST may functionally sponge miR- 4295, thereby relieving its inhibitory effect on ITPR1 (Fig. [98]5F). Fig. 5. [99]Fig. 5 [100]Open in a new tab LncRNA RMST activates ITPR1 by sponge-competing miR-4295. A The expression level of LncRNA RMST in tumor tissues and adjacent normal tissues was detected by qRT-PCR. B The expression levels of miR-4295 in tumor tissues and adjacent normal tissues were detected using qRT-PCR. C The bar chart shows the mRNA expression levels of RMST in different si-LncRNA RMST treatment groups compared with negative control groups, in which the expression of si-LncRNA RMST-3 group is most significantly reduced. D qRT-PCR analysis of the relative expression levels of LncRNA RMST, miR-4295, and ITPR1 in different treatment groups. E Western blot analysis of the impact of silencing or overexpressing LncRNA RMST on ITPR1 protein expression levels. F Western blot analysis of the effect of silencing or overexpressing miR-4295 on ITPR1 protein expression levels. Data are presented as mean±SEM from three independent experiments (n=3) (statistical significance indicated as * p < 0.05, ** p < 0.01, *** p < 0.001) LncRNA RMST inhibits TNBC cell proliferation through the miR-4295/ITPR1 axis We elucidated the effects of the LncRNA RMST/miR- 4295/ITPR1 axis on the proliferative capacity of TNBC cells through a series of cell experiments. RT-qPCR results showed (Fig. [101]6A) that compared to the control group (pcDNA3.1 + mimics NC + vector), the expression of LncRNA RMST was significantly increased in the pcDNA3.1-LncRNA RMST + mimics NC + vector group. There was also a significant upregulation of ITPR1, which was accompanied by a corresponding decrease in miR- 4295 expression, indicating that LncRNA RMST may function as a ceRNA for miR- 4295. Moreover, compared to the pcDNA3.1-LncRNA RMST + mimics NC + vector group, the downregulation of ITPR1 in the pcDNA3.1-lncRNA RMST + mimics miR- 4295 + ITPR1 group suggested that ITPR1 is a potential downstream target of miR- 4295. The CCK8 assay (Fig. [102]6B) further revealed the role of LncRNA RMST in cell proliferation. The data showed that knockdown of LncRNA RMST (pcDNA3.1-lncRNA RMST + mimics NC + vector) led to decreased cell proliferation, which was rescued by the addition of miR- 4295 mimics (pcDNA3.1-lncRNA RMST + mimics miR- 4295 + vector). EdU staining confirmed these findings (Fig. [103]6C), showing a reduction in EdU-positive cells in the pcDNA3.1-lncRNA RMST + mimics NC + vector group, which was fully restored by the addition of miR- 4295 mimics (pcDNA3.1-lncRNA RMST + mimics miR- 4295 + vector), whereas the addition of ITPR1 (pcDNA3.1-lncRNA RMST + mimics miR-4295 + ITPR1) led to a decrease in EdU-positive cells. Fig. 6. [104]Fig. 6 [105]Open in a new tab LncRNA RMST inhibits TNBC cell proliferation through the miR-4295/ITPR1 axis. A Bar charts display the relative expression levels of LncRNA RMST, miR-4295, and ITPR1 in different treatment groups. B CCK8 assay showing the OD450 values of tumor cells in various treatment groups at 0, 24, and 48 h. C EdU assay depicting the proliferation of tumor cells in different treatment groups. Data are presented as mean±SEM from three independent experiments (n=3) (statistical significance indicated as ns p > 0.05, * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001) LncRNA RMST inhibits TNBC cell migration and invasion through the miR-4295/ITPR1 axis We performed wound healing and Transwell assays to evaluate cell migration and invasion. The wound healing assay (Fig. [106]7A) showed that, compared to the control group (pcDNA3.1 + mimics NC + vector), migration capacity was significantly reduced in the pcDNA3.1-lncRNA RMST + mimics NC + vector group and significantly increased in the pcDNA3.1-lncRNA RMST + mimics miR- 4295 + vector group. Under the same conditions, the introduction of ITPR1 (pcDNA3.1-LncRNA RMST + mimics miR- 4295 + ITPR1) resulted in a wound healing capacity of tumor cells that was intermediate between the two groups, indicating that overexpression of ITPR1 can counteract the pro-migratory effects of miR- 4295. Additionally, the Transwell assay (Fig. [107]7B) confirmed these findings, showing that the number of cells migrating through Matrigel was significantly reduced in the groups overexpressing LncRNA RMST and ITPR1. The addition of miR- 4295 mimics (pcDNA3.1-LncRNA RMST + mimics miR- 4295 + ITPR1) rescued this decrease. Fig. 7. [108]Fig. 7 [109]Open in a new tab LncRNA RMST inhibits TNBC cell migration and invasion via the miR-4295/ITPR1 axis. A Effects of different treatments of lncRNA RMST and miR-4295 on the migration ability of MDA-MB-468 cells. B Detection of the invasive behavior of MDA-MB-468 cells in different treatment groups. Data are presented as mean±SEM from three independent experiments (n=3) (statistical significance markers: * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001) LncRNA RMST promotes autophagy in TNBC cells through the miR-4295/ITPR1 axis Flow cytometry analysis (Fig. [110]8A) showed that, compared to the control group (pcDNA3.1 + mimics NC + vector), the apoptosis rate of TNBC cells transfected with pcDNA3.1-LncRNA RMST + mimics NC + vector was significantly increased, which was attenuated by the overexpression of miR- 4295 (pcDNA3.1-lncRNA RMST + mimics miR- 4295 + vector). This increase was reversed when all three factors were simultaneously overexpressed (pcDNA3.1-LncRNA RMST + mimics miR- 4295 + ITPR1). Electron microscopy provided morphological evidence of autophagy in the TNBC cells (Fig. [111]8B). By observing the effects of different treatments on the number of autophagosomes, we found that the effects of the LncRNA RMST/miR- 4295/ITPR1 axis on autophagy were consistent with those on apoptosis. Western blot analysis (Fig. [112]8C) of key autophagy-related proteins further confirmed these findings. The pcDNA3.1-lncRNA RMST + mimics NC + vector group showed an increased LC3 II/I ratio and decreased P62 levels, indicating enhanced autophagic flux. In contrast, the pcDNA3.1-lncRNA RMST + mimics miR- 4295 + vector group exhibited elevated P62 levels and decreased LC3 II/I ratio, consistent with reduced autophagy. The levels of Beclin1, another autophagy regulator, were also restored in the presence of ITPR1, further supporting the role of LncRNA RMST in regulating autophagy through the miR- 4295/ITPR1 axis (Fig. [113]9). Fig. 8. Fig. 8 [114]Open in a new tab LncRNA RMST promotes autophagy in TNBC cells via the miR-4295/ITPR1 axis. A Flow cytometry dot plots of Annexin V-FITC and PI staining in different treatment groups, with bar charts showing the percentage of apoptotic cells in each group. B Transmission electron microscopy images showing autophagosome formation in cells from different treatment groups, with red arrows indicating autophagosomes. C Western blot analysis of the expression levels of P62, LC3 II/I, Beclin1, and Bcl2 proteins in different treatment groups. Data are presented as mean±SEM from three independent experiments (n=3) (statistical significance markers: * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001) Fig. 9. Fig. 9 [115]Open in a new tab Deciphering the autophagy-related lncrna-mirna-mrna axis in TNBC. In TNBC cells, LncRNA RMST competitively binds to miR-4295, thereby up-regulating the expression of ITPR1 and significantly inhibiting autophagy in TNBC cells Discussion In recent years, significant progress has been made in the study of LncRNAs in breast cancer, revealing their important roles in regulating tumor development and treatment [[116]25]. Particularly, the role of lncRNAs in regulating autophagy has gradually attracted attention. Autophagy plays a complex role in the survival and death of breast cancer cells [[117]26]. Moreover, LncRNAs interact with miRNAs to form complex regulatory networks that affect the biological functions of tumor cells and influence the progression and drug resistance of breast cancer [[118]27]. This study also provides new perspectives and potential targets for breast cancer treatment. In this study, we predicted the LncRNA-miRNA-mRNA axis that plays a key regulatory role in the autophagy process in TNBC cells through bioinformatics analysis and verified it through a series of experiments. ITPR1 has been predicted to be a potential therapeutic target in various tumors, including breast cancer [[119]17, [120]28, [121]29], and gene expression profiling has shown that ITPR1 may be a key gene in autophagy regulation in breast cancer [[122]30]. In our study, we found that ITPR1 was significantly downregulated in TNBC tissues and inhibited the proliferation and migration of TNBC cells. ITPR1 protects renal cancer cells from natural killer cells by inducing autophagy [[123]31]. Xu et al. found that in breast cancer, the Ai-lncRNA EGOT enhanced autophagy by upregulating ITPR1, thereby inhibiting paclitaxel resistance [[124]32]. Based on the transcriptomic data, we identified the key genes, LncRNA RMST and ITPR1, in TNBC and predicted the LncRNA RMST-miR- 4295-ITPR1 axis. MiR- 4295 has been shown to play a carcinogenic role in a variety of tumors, including osteosarcoma and head and neck squamous cell carcinoma [[125]33, [126]34]. In esophageal squamous cell carcinoma, Lnc RNA PCAT5 inhibits cancer cell proliferation by spongifying miR- 4295 [[127]35]. In addition, miR- 4295 can also inhibit the apoptosis of gastric cancer cells induced by chemotherapy drugs by activating the EGFR/PI1K/Akt pathway [[128]36]. Accumulating evidence indicates that lncRNAs play important roles in regulating genes related to tumor proliferation, apoptosis, and migration [[129]37]. LncRNAs and mRNAs interact by competitively binding to miRNAs and forming ceRNA networks, and this interaction plays an important role in the regulation of breast cancer [[130]38]. The role of LncRNA RMST in tumors has not been widely studied, but existing studies have shown that it exhibits different expression patterns in tumors. LncRNA RMST is upregulated in gastric cancer and glioma, and shows significant oncogenic activity [[131]39, [132]40]. However, it may play an opposite role in other tumors. LncRNA RMST exerts a tumor-suppressive role in colorectal cancer by inactivating the Wnt signaling pathway [[133]41]. In anaplastic thyroid cancer, the downregulation of LncRNA RMST is associated with impaired epithelial-mesenchymal transition [[134]42]. In this study, LncRNA RMST was downregulated in TNBC, which is consistent with the survival prediction results of Yang et al. [[135]43]. However, there is still a lack of studies on the role of LncRNA RMST in breast cancer. Mutual regulatory relationships exist between LncRNAs and autophagy. Some LncRNAs affect autophagy by regulating the expression of autophagy-related genes or proteins, thereby affecting drug resistance in tumor cells. Studies have shown that targeting and inhibiting LncRNA DDIT4-AS1 or lncRNA DARS-AS1 may exert anticancer activity in TNBC cells by inhibiting autophagy [[136]15, [137]44]. We also demonstrated that LncRNA RMST promotes autophagy in TNBC through transmission electron microscopy combined with the expression of autophagy-related proteins. In TNBC, we demonstrated through overexpression and knockdown experiments that the LncRNA RMST-miR- 4295-ITPR1 axis exerts tumor-suppressive effects by regulating autophagy. Specifically, LncRNA RMST may competitively bind to miR- 4295, thereby relieving its inhibitory effect on ITPR1 and activating ITPR1-mediated autophagy. This activation of autophagy helps clear damaged organelles and metabolic waste within the cells, maintaining cellular homeostasis, and thereby inhibiting the proliferation and survival of TNBC cells. This finding not only deepens our understanding of the molecular landscape of TNBC but also provides a theoretical basis for developing TNBC therapeutic strategies based on autophagy regulation. Future research is needed to further explore the role of this axis in other tumor types and assess its feasibility as a clinical therapeutic target. However, the role of this axis in other tumor types and its feasibility as a clinical therapeutic target have not been fully validated. Future studies are needed to further explore the function of this axis in different tumors and validate its therapeutic potential through in vivo models and clinical trials to advance its clinical application. Conclusions In summary, this study has uncovered a novel mechanism by which the LncRNA RMST-miR-4295-ITPR1 axis exerts tumor-suppressive effects in TNBC through the regulation of autophagy. Through in vitro experiments, we demonstrated that LncRNA RMST competitively binds to miR-4295, thereby upregulating ITPR1 expression, which significantly inhibits the proliferation, migration, and invasion of TNBC cells while promoting apoptosis and autophagy. These findings not only provide a potential new therapeutic target for TNBC but also offer important insights into the molecular mechanisms underlying TNBC progression. Supplementary Information [138]12885_2025_14189_MOESM1_ESM.zip^ (7.7MB, zip) Additional file 1. Clinical data from breast cancer samples downloaded from the TCGA database. [139]12885_2025_14189_MOESM2_ESM.txt^ (299.6MB, txt) Additional file 2. Transcriptome data of breast cancer samples downloaded from the TCGA database. [140]12885_2025_14189_MOESM3_ESM.txt^ (2.9MB, txt) Additional file 3. Transcriptome data from TNBC samples. [141]12885_2025_14189_MOESM4_ESM.txt^ (290.7KB, txt) Additional file 4. DEGs between TNBC samples and control samples. [142]12885_2025_14189_MOESM5_ESM.txt^ (21.5KB, txt) Additional file 5. LncRNAs in transcriptome samples. [143]12885_2025_14189_MOESM6_ESM.xlsx^ (9.9KB, xlsx) Additional file 6. Differentially expressed LncRNA between TNBC samples and control samples. [144]12885_2025_14189_MOESM7_ESM.txt^ (1.6KB, txt) Additional file 7. Autophagy related genes downloaded from the HADB database. [145]12885_2025_14189_MOESM8_ESM.txt^ (2KB, txt) Additional file 8. Intersection of autophagy related genes and DEGs. [146]12885_2025_14189_MOESM9_ESM.txt^ (21.6KB, txt) Additional file 9. KEGG pathway enrichment analysis of key autophagy genes. [147]12885_2025_14189_MOESM10_ESM.txt^ (638.8KB, txt) Additional file 10. GO pathway enrichment analysis of key autophagy genes. [148]12885_2025_14189_MOESM11_ESM.pdf^ (24.1KB, pdf) Additional file 11. Transcriptome expression analysis of 7 key genes. [149]12885_2025_14189_MOESM12_ESM.xlsx^ (315.8KB, xlsx) Additional file 12. The upstream miRNAs of 7 key genes were predicted using TargetScanHuman 7.2 database. [150]12885_2025_14189_MOESM13_ESM.txt^ (19.5KB, txt) Additional file 13. The miRNA targeted by LncRNA was predicted using miRcode database. [151]12885_2025_14189_MOESM14_ESM.docx^ (16.1KB, docx) Additional file 14. Primers sequence information needed in the experiment. [152]12885_2025_14189_MOESM15_ESM.docx^ (15.2KB, docx) Additional file 15. The antibodies information for western blot. [153]12885_2025_14189_MOESM16_ESM.tif^ (433.8KB, tif) Additional file 16. qRT-PCR was used to evaluate the transfection efficiency of miR-4295 mimics and inhibitors in cells. [154]Additional file 17.^ (211.8MB, ppt) Abbreviations TNBC Triple-Negative Breast Cancer ER Estrogen receptor PR Progesterone receptor HER2 Human epidermal growth factor receptor 2 LncRNAs Long Non-Coding RNA miRNAs MicroRNAs ITPR1 Inositol-1,4,5-trisphosphate receptor type 1 TCGA The Cancer Genome Atlas HS Horse serum EGF Epidermal growth factor NEAA Non-essential amino acids P/S Penicillin/streptomycin FBS Fetal bovine serum DEGs Differentially expressed genes GO Gene Ontology RFS Recurrence-free survival HR Hazard ratio OS Overall survival Authors’ contributions Linlei Zhang: Conception of the manuscript and drafting of the initial manuscript; Sainan Li: Investigation and visualization; Jiajie Shi: Investigation and data management; Hao Guo: Data management and validation; Bo Wang: Data management and validation; Cuizhi Geng: Conception of the manuscript, project management, and manuscript review. Funding This study was supported by the Hebei Provincial Department of Finance, 2025 Government-funded Clinical Medicine Talent Training Project (Grant No. ZF2025187). Data availability The materials used in this study are available from the corresponding author upon request. Declarations Ethics approval and consent to participate This study was conducted in accordance with the principles of the Declaration of Helsinki. This study was approved by the Ethics Committee of the Second Hospital of Hebei Medical University (Approval Number: [2024-R510]). Written informed consent was obtained from all participants. 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. References