A total of 532 patient clinical follow-up records and sequencing data were obtained from TARGET-ALL-P2, including 469 distinct patients diagnosed with acute lymphocytic leukemia (ALL) or precursor B-cell lymphoblastic leukemia (B-ALL). The subsequent analysis involved a comparison of overall survival (OS) between the two groups (Figure 1A). A substantial disparity in survival duration was evident between the groups (p < 0.0001), with the P2RX1 high-expression group demonstrating a reduced survival probability compared to the low-expression group. The differential expression of genes (DEGs) between these groups was subsequently analyzed and visualized. As illustrated in Figure 1B, the volcano plot of DEGs reveals that blue corresponds to downregulated genes, red indicates upregulated genes, and gray designates genes with non-significant changes. As illustrated in Figure 1C, the top 50 most significantly altered genes are displayed, with all genes circled in red indicating mitochondrial-related genes. Subsequently, KEGG and GO enrichment analyses were performed on all differential genes (Figures 1D,E). Following the filtration of the results, the most salient signaling pathway identified was the B-cell receptor signal pathway, with its primary downstream pathway being the PI3K/Akt signaling pathway. GO enrichment analysis results indicate that biological processes such as calcium ion metabolism and positive regulation of 3-phosphokinase are enriched.

Following lentiviral transduction of SUP-B15 cells, successful transduction was confirmed by RT-PCR. Analysis revealed a significant difference in mRNA expression levels between the empty vector group and the target gene construct group (p < 0.0001) (Figure 2A). This finding was further validated at the protein level by western blot analysis (Figure 2B). Using sodium-potassium ATPase (Na⁺/K⁺-ATPase) as a loading control, quantitative analysis indicated that P2RX1 protein1 protein expression was approximately threefold higher in the P2RX1-overexpressing (P2RX1-OE) group compared to the vector control group; this difference was statistically significant (p < 0.001) (Figure 2C). Subsequently, RNA sequencing (RNA-seq) was performed on both groups to identify differentially expressed genes (DEGs). A heatmap visualizing the top 25 most significantly altered genes (Figure 2D) and a volcano plot displaying all DEGs (Figure 2E) were generated. Pathway enrichment analyses using the KEGG and GO databases revealed several significantly enriched terms (Figures 2F,G). These included pathways related to calcium ion signaling, plasma membrane receptor complexes, and NF-κB signaling, which were consistent with findings from established online repositories.

The CCK-8 assay was employed to determine appropriate drug concentrations, as shown in Supplementary Figures. Supplementary Figure S1 shows the concentration screening process for KN-62, based on which 10 μM was selected as the effective inhibitory concentration. Similarly, Supplementary Figure S2 presents the screening process for imatinib, leading to the selection of 20 μM as the working concentration.

Treatment with either 20 μM or 30 μM imatinib in different cell groups, or with 10 μM KN-62 for 24 and 48 h (Figure 3), effectively suppressed cell proliferation in a time- and dose-dependent manner. Under identical drug concentrations and treatment durations, the P2RX1-OE group exhibited a significantly higher inhibition rate of cell proliferation than the Vector group (P < 0.01), indicating that P2RX1-overexpressing cells were more susceptible to proliferation inhibition. Furthermore, the strongest suppression of cell viability was observed in the combination treatment group receiving 20 μM imatinib along with 10 μM KN-62.

Using membrane protein V, Cy5/DAPI dual staining, the P2RX1-OE group demonstrated significantly increased proportions of both early and late apoptotic cells compared to the vector control group following treatment with 20 μM imatinib (P < 0.0001; Figures 4A,B). In contrast, no statistically significant pro-apoptotic effect was observed in the 10 μM KN-62 monotherapy group (ns.). When treated with the combination of 20 μM imatinib and 10 μM KN-62, a marked reduction in apoptotic cells occurred relative to 20 μM imatinib alone, indicating that inhibition of CaMKII activity during apoptosis induction can partially rescue cell death. A statistically significant difference was found both between the two monotherapy groups (P < 0.001) and between the two combination therapy groups (P < 0.001). These results suggest that differential expression levels of the P2RX1 gene influence cellular susceptibility to apoptosis induction, with the P2RX1-OE group being more readily triggered to undergo apoptosis.

Both groups were subjected to intracellular calcium staining using Rhod-2 AM, which revealed significantly higher calcium levels in the P2RX1-OE group relative to the vector control group. Treatment with 20 μM imatinib markedly increased intracellular calcium in the P2RX1-OE group (P < 0.0001; Figures 5A,B), while 10 μM KN-62 alone did not induce noticeable changes. Co-administration of both drugs significantly attenuated intracellular calcium levels compared with 20 μM imatinib alone (P < 0.0001); however, these levels remained significantly elevated compared with the control group. These findings indicate that Ca²⁺ overload plays a critical role in the apoptosis induction process.

Measurement of intracellular ATP levels showed that (Figure 5C), under baseline conditions, the P2RX1-OE group exhibited significantly higher ATP levels than the vector group (P < 0.001). Upon monotherapy with either agent, ATP levels in the P2RX1-OE group decreased significantly compared with the corresponding vector-treated group (P < 0.05). Following combination therapy, the reduction in ATP levels was more pronounced in the P2RX1-OE group than in the vector group (P < 0.05), though this decrease was not statistically different from that observed with 20 μM imatinib alone. Together, these data suggest that mitochondrial function, mitochondrial function, and metabolic capacity are compromised during the process.

JC-1 staining indicated that both 10 μM KN-62 and 20 μM imatinib significantly reduced the mitochondrial membrane potential (ΔΨm) compared with the control group (P < 0.05). The most substantial decrease in ΔΨm was observed in the 20 μM imatinib monotherapy group, which differed significantly from the vector control group (P < 0.001). Notably, the combination of imatinib and KN-62 led to a less pronounced reduction in ΔΨm than imatinib alone. Moreover, under combination treatment, the loss of ΔΨm remained more prominent in the P2RX1-overexpressing group than in the vector group (P < 0.001; Figures 6A,C). Janus Green B staining revealed considerable mitochondrial swelling mitochondrial swelling in the overexpression groups (Figure 6B, arrows), further supporting the notion that mitochondrial structural integrity is compromised. Taken together with earlier data on intracellular Ca²⁺ dys⁺ dysregulation, these results strongly suggest that mitochondrial dysfunction plays a central role in the apoptotic process.

Based on our previous findings, we next sought to explore key regulatory molecules within the intrinsic apoptosis pathway. Real-time quantitative PCR analysis revealed that, under matched drug treatments, the mRNA expression levels of PI3K and Akt were significantly downregulated in the combination therapy group compared to the control group. This suppression was particularly pronounced when compared to the identically treated empty vector group (P < 0.01; Figure 7). Concurrently, transcript levels of core pro-apoptotic factors were markedly elevated (P < 0.001) relative to both the untreated control and the dose-matched vector control group.

This result was validated by Western blot (WB) analysis. Under identical treatment conditions, P2RX1-overexpressing cells showed significantly diminished phosphorylation of PI3K and AKT (P < 0.05; Figure 8) but a notable increase in P-CaMKII levels (P < 0.01) relative to the vector control group. Additionally, the P2RX1-OE group exhibited substantially upregulated expression of several pro-apoptotic proteins—BAX, Bad, cytochrome c (Cyt-C), cleaved caspase-9, and cleaved caspase-3—alongside a pronounced downregulation of the anti-apoptotic protein BCL-2. Remarkably, upon treatment with 20 µM imatinib, Cyt-C expression in P2RX1-OE cells was approximately eightfold higher than in vector controls (p < 0.001), highlighting robust engagement of the mitochondria-dependent apoptotic pathway.

Clinical follow-up information and sequencing data for patients in the TARGET-ALL-P2 dataset were retrieved using the TCGAbiolinks R package “GDCquery” (version 2.36.0) from the GDC website (https://gdc.cancer.gov). Genomic Data Commons phs000218 (2018). https://portal.gdc.cancer.gov/projects/TARGET-ALL-P2. Patients were grouped based on P2RX1 gene expression TPM values, which were calculated using the optimal intercept method. The cutoff point for P2RX1 gene expression TPM was set at 41.4635, thereby dividing patients into low-expression and high-expression groups. The generation of overall survival curves was accomplished by employing the ggsurvplot function within the survminer R package. P-values were calculated using the log-rank test. The limma package (version 3.58.1) was utilized to evaluate the disparities in gene expression between the two cohorts. The selection of differentially expressed genes (DEGs) was based on the criteria of |logFC| > 1 and an adjusted p-value < 0.05. The Benjamini-Hochberg (BH) method was employed for p-value correction. Volcano plots for differential analysis were generated using the ggplot2 package (version 3.4.4). A heatmap of the top 50 differentially expressed genes (DEGs) was generated using the R package “heatmap” (version 1.0.12). GO and KEGG enrichment analyses were performed on all DEGs using the clusterProfiler package (version) in R, with p-values calculated based on the hypergeometric distribution.

SUP-B15 cells were obtained from Zhejiang Baidi Biotechnology Co., Ltd. The cells were cultured in Iscove's Modified Dulbecco's Medium (IMDM; Procell, China) supplemented with 20% fetal bovine serum (FBS; CellBox CellBox, USA), 100 U/mL penicillin, and 100 μg/mL streptomycin. Cultures were maintained at 37 °C in a humidified atmosphere containing 5% CO₂ (Thermo Fisher Scientific, USA).Log-phase SUP-B15 cells were seeded into 96-well plates at a density of 1 × 10⁴ cells per well. Cells were then transduced with lentiviral particles (Shanghai GK Gene) carrying either P2RX1 overexpression construct or a nonspecific control (NC) sequence at a multiplicity of infection (MOI) of 60. A transduction enhancer was added at a concentration of 4 µL/mL to improve infection efficiency. After successful transduction, stable cell lines were selected using 5 µg/mL puromycin. All experimental procedures were performed in compliance with relevant guidelines and regulations and were approved by the Institutional Review Board of the Heillongjiang Provincial Blood Cancer Laboratory.

SUP-B15 cells stably overexpressing P2RX1 (P2RX1-OE) and empty vector controls (EV) were used for RNA sequencing. Total RNA was extracted using Total RNA Extraction Reagent (Vazyme, #R711-01), and its purity and concentration were determined with a NanoDrop2000 spectrophotometer (Thermo Fisher, USA). Qualified RNA samples were subsequently subjected to sequencing on an Illumina NovaSeq6000 platform (Illumina, USA) by Berry Genomics (China). The selection of differentially expressed genes (DEGs) was based on the criteria of |logFC| > 1 and an adjusted p-value < 0.05. The Benjamini-Hochberg (BH) method was employed for p-value correction. Volcano plots for differential analysis were generated using the ggplot2 package (version 3.4.4). A heatmap of the top 50 differentially expressed genes (DEGs) was generated using the R package “heatmap” (version 1.0.12). GO and KEGG enrichment analyses were performed on all DEGs using the clusterProfiler package (version 4.0.5) in R, with p-values calculated based on the hypergeometric distribution.

Cell viability was determined using the CCK-8 assay kit (C0005, TargetMol, Shanghai, China). Cells in the logarithmic growth phase were seeded into 96-well plates at a density of 5 × 10⁴ cells per well in 100 µL of medium. At 24, 48, and 72 h after seeding, 10 µL of CCK-8 reagent was added to each well and incubated at 37 °C for 2 h. The absorbance at 450 nm was measured using a SpectraMax M5 Multifunction Microplate Reader (Molecular Devices, USA), with the absorbance at 650 nm recorded simultaneously for background correction. Cell viability was calculated according to the following formula: Cell Viability (%) = [(A treatment—A blank)/(A control—A blank)] × 100, where A represents the corrected absorbance (OD 450 nm–OD 650 nm). Here, A blank refers to wells containing only culture medium and CCK-8 reagent, and A control represents the untreated control cells.

Total RNA was isolated from cells using Trizol reagent (B610409, Sangon Biotech, Shanghai, China) according to the manufacturer's protocol. We assessed RNA concentration and purity using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, USA). Qualified RNA samples were reverse-transcribed into complementary DNA (cDNA) with a commercial reverse transcription kit (RK20429, ABclonal, Wuhan, China). Quantitative real-time PCR (qPCR) was subsequently performed using synthesized cDNA templates and gene-specific primers. The PCR reaction conditions were as follows: 95 °C for 3 min, followed by 40 cycles, each cycle consisting of 95 °C for 15 s and 56 °C for 1 min. Product specificity was subsequently verified through melt curve analysis using the instrument's default dissociation protocol. The relative expression levels of the target genes were calculated using the 2^−ΔΔCt methodCt method, with GAPDH mRNA serving as the internal reference for normalization.

The oligonucleotide primers used in this study were obtained from two sources. Primers for Bcl-2, Bax, Caspase-3, Caspase-8, and Caspase-9 were sourced from previously published literature (37), while those targeting p2rx1 (NM_002558.4), PIK3R1 (NM_181523.3), and AKT1 (NM_001014431.2) were newly designed using Primer Premier 5.0 software. All oligonucleotides were custom-synthesized by ApexBio Technology (Shanghai, China). The sequences of all primers used are provided in Supplementary Table S1.

The apoptotic rate of cells was detected using an Annexin V-Cy5/DAPI apoptosis assay kit (APExBIO, No. K2255). Cells were collected by centrifugation at 300 × g for 5 min at 4 °C. After being washed twice with pre-cooled PBS, the cells were resuspended in 100 μL of 1× Binding Buffer. Subsequently, 2.5 μL of DAPI staining solution and 2.5 μL of Annexin V-Cy5 staining solution were added, and the mixture was gently mixed. The reaction was carried out at room temperature in the dark for 20 min. Then, 400 μL of 1× binding buffer was added to each tube, and the mixture was gently mixed prior to flow cytometry analysis. Samples were analyzed using a BD FACSLyric™ flow cytometer (USA), and data were processed with FlowJo software.

Mitochondrial membrane potential was assessed using the Enhanced Mitochondrial Membrane Potential Assay Kit (C2003S, Beyotime Biotechnology, Shanghai, China). Treated cells were resuspended in 4 μM JC-1 staining working solution and incubated at 37 °C for 30 min. Following two washes with JC-1 staining buffer, the cells were resuspended in the same buffer and analyzed on a BD FACSLyric™ flow cytometer (USA). Data were processed using FlowJo software.

Intracellular calcium levels were measured using Rhod-2, AM probe (MX4507-250UG, Maokangbio, Shanghai, China). Cells were loaded with 5 μM Rhod-2, AM working solution and incubated at 37 °C for 30 min. Fluorescence imaging was performed using an EVOS FL cell imaging system (Thermo Fisher, USA). Parallel fluorescence intensity measurements were conducted with a SpectraMax M5 multifunction microplate reader (Molecular Devices, USA) set at excitation/emission wavelengths of 549/578 nm. Images were analyzed using ImageJ software.

Mitochondria were stained with Janus Green B (HY-D1122, MCE, USA). USA). A staining working solution was prepared by dissolving 5 μg of Janus Green B in 1.96 mL of mL of PBS to yield a final concentration of 5 μM. Cells were incubated with the working solution for 5 min. Mitochondrial morphology was observed and mitochondria were counted within cells using a standard light microscope.

Intracellular ATP levels were quantified using an ATP Assay Kit (S0026, Beyotime Biotechnology, Shanghai, China). Cells were collected by centrifugation at 1,500 rpm for 5 min, followed by the addition of 100 μL ATP lysis buffer. The lysates were centrifuged at 12,000 rpm and 4 °C for 5 min, and the resulting supernatant was collected for ATP determination. Both the supernatants and ATP standard solutions were diluted to appropriate concentrations with ATP dilution buffer. Subsequently, 20 μL of each diluted sample or standard was mixed with 100 μL of reaction working solution, and the mixtures were transferred to a black 96-well plate. Luminescence intensity was measured using a SpectraMax M5 Multifunction Microplate Reader (Molecular Devices, USA).

Total protein was extracted from cells using RIPA lysis buffer (P0013B, BiYunTian, Shanghai, China) supplemented with protease and phosphatase inhibitors (K1007, K1015, APExBIO, Houston, USA). Protein concentration was determined with a BCA assay kit (ZJ102, YaEnzyme, Shanghai, China). Then, 20 μg of protein per sample was separated by SDS-PAGE and transferred onto PVDF membranes (IPVH00010, Millipore, Germany). The membranes were incubated with primary antibodies overnight at 4 °C, followed by incubation with corresponding secondary antibodies for 1 h at room temperature. Protein bands were detected using the Omni-ECL™ Ultra-Sensitive Chemiluminescent Detection Kit (SQ201, Yasei, Shanghai, China) and visualized with a Tanon-5200 gel imaging system (Shanghai, China). GAPDH protein was utilized as the internal reference protein. The list of antibodies used can be found in the Supplementary Material (Supplementary Table S2). The grayscale analysis was performed using the ImageJ software.

The results were analyzed using GraphPad Prism 9.5.0 and R 4.5.0. Both datasets exhibited normal distribution. When variances were equal, two-tailed paired or unpaired Student's t-tests were used to calculate p-values between groups. Non-normally distributed data underwent nonparametric analysis. Differences in intergroup variance were analyzed using Welch's correction. Multi-group comparisons were performed using a two-way ANOVA. Survival analysis p-values were calculated using the log-rank test. P-values were corrected using the Benjamini-Hochberg method, and no data were excluded during the analysis.