SPC25 as a novel therapeutic and prognostic biomarker and its association with glycolysis, ferroptosis and ceRNA in lung adenocarcinoma

Abstract

Objective: Spindle pole body component 25 (SPC25) is an important cyclin involved in chromosome segregation and spindle dynamics regulation during mitosis. However, the role of SPC25 in lung adenocarcinoma (LAUD) is unclear.

Materials and methods: The differential expression of SPC25 in tumor samples and normal samples was analyzed using TIMER, TCGA, GEO databases, and the correlation between its expression and clinicopathological features and prognosis in LUAD patients. Biological pathways that may be enriched by SPC25 were analyzed using GSEA. In vitro cell experiments were used to evaluate the effect of knocking down SPC25 expression on LUAD cells. Correlation analysis and differential analysis were used to assess the association of SPC25 expression with genes related to cell cycle, glycolysis, and ferroptosis. A ceRNA network involving SPC25 was constructed using multiple database analyses.

Results: SPC25 was highly expressed in LUAD, and its expression level could guide staging and predict prognosis. GSEA found that high expression of SPC25 involved multiple cell cycles and glycolytic pathways. Knocking down SPC25 expression significantly affected the proliferation, migration and apoptosis of LUAD cells. Abnormal SPC25 expression levels can affect cell cycle progression, glycolytic ability and ferroptosis regulation. A ceRNA network containing SPC25, SNHG15/hsa-miR-451a/SPC25, was successfully predicted and constructed.

Conclusions: Our findings reveal the association of up-regulation of SPC25 in LUAD and its expression with clinical features, prognosis prediction, proliferation migration, cell cycle, glycolysis, ferroptosis, and ceRNA networks. Our results indicate that SPC25 can be used as a biomarker in LUAD therapy and a target for therapeutic intervention.

Keywords: SPC25; ceRNA; cell cycle; ferroptosis; glycolysis; lung adenocarcinoma.

Figure 1

SPC25 expression levels in cancers and prognostic value in LUAD, as well as association with clinicopathological characteristics for LUAD patients. (A) SPC25 levels in different tumor tissues and paracancerous tissues based on the TIMER database. (B–D) SPC25 levels in LUAD samples and normal samples in the (B) GSE31210, (C) GSE116959 and (D) GSE7670. (E, F) Prognostic analysis of SPC25 expression on OS (E) and DFS (F) in LUAD based on the GEPIA database (log-rank test). (G) SPC25 expression was explored in different pathological stages based on the TCGA LUAD database. (H) SPC25 expression was explored in different pathological T stages based on the TCGA LUAD database. (I) SPC25 expression was explored in different pathological N stages based on the TCGA LUAD database. (J) SPC25 expression was explored in different pathological M stages based on the TCGA LUAD database. Abbreviations: TCGA: the Cancer Genome Atlas; LUAD: lung adenocarcinoma; OS: overall survival; DFS: disease free survival. (^***p < 0.001; ^**p < 0.01; ^*p < 0.05; Abbreviation: ns: not significant).

Figure 2

GSEA analysis reveals SPC25-related pathways. (A) REACTOME_CELL_CYCLE_CHECKPOINTS. (B) KEGG_CELL_CYCLE. (C) WP_CELL_CYCLE. (D) WP_G1_TO_S_CELL_CYCLE_CONTROL. (E) REACTOME_APC_C_MEDIATED_DEGRADATION_OF_CELL_CYCLE_PROTEINS. (F) REACTOME_TP53_REGULATES_TRANSCRIPTION_OF_GENES_INVOLVED_IN_G1_CELL_CYCLE_ARREST. (G) REACTOME_TP53_REGULATES_TRANSCRIPTION_OF_CELL_CYCLE_GENES. (H) REACTOME_DISEASES_OF_MITOTIC_CELL_CYCLE. (I) REACTOME_TP53_REGULATES_TRANSCRIPTION_OF_GENES_INVOLVED_IN_G2_CELL_CYCLE_ARREST.

Figure 3

The impact of knocking down SPC25 on LUAD. (A, B) An analysis of Western blotting confirmed the success of SPC25-siRNAs transfection into H1975 cells and their ability to interfere with gene expression. (C, D) CCK-8 assay evaluated tumor cell proliferation activity. (E, F) EdU staining of H1975 cells and EdU-positive cell proportion. (G, H) The effect of SPC25 knockdown on apoptosis of the H1975 cells as detected by flow cytometry. (I–K) Representative images and quantitative analysis of wound healing measurements in LUAD cells. (^***p < 0.001; ^**p < 0.01; ^*p < 0.05; Abbreviation: ns: not significant).

Figure 4

Cell cycle regulation by SPC25 in LUAD. (A, B) Flow cytometry analysis revealed that compared to the control group, the experimental group exhibited an increase in the percentage of cells in the S and G2/M phases, accompanied by a decrease in the percentage of cells in the G0/G1 phase, leading to cell cycle arrest at the G2/M and S phases. (C–E) We utilized lollipop plots to illustrate the correlations between SPC25 and key genes including cyclins, CDKs, and CDKIs in the TCGA LUAD dataset. (^***p < 0.001; ^**p < 0.01; ^*p < 0.05; Abbreviation: ns: not significant).

Figure 5

GSEA analysis and glycolytic capacity analysis. (A) REACTOME_GLYCOLYSIS. (B) WP_GLYCOLYSIS_AND_GLUCONEOGENESIS. (C) WP_AEROBIC_GLYCOLYSIS. (D) WP_GLYCOLYSIS_IN_SENESCENCE. (E) HALLMARK_GLYCOLYSIS. (F) Interference with SPC25 expression can significantly reduce the lactate production in LUAD cells. (G, H) Inhibition of SPC25 expression can significantly reduce the uptake of 2-NBDG by LUAD cells. MFI, mean fluorescence intensity. (^***p < 0.001; ^**p < 0.01; ^*p < 0.05; Abbreviation: ns: not significant).

Figure 6

Association between SPC25 and glycolytic-related genes. (A) The correlation between SPC25 expression and 11 glycolysis-related genes was analyzed in the TCGA LUAD dataset and GSE31210 dataset. (B, C) The differential expression of 11 glycolysis-related genes between the high and low SPC25 expression groups was analyzed in the TCGA LUAD dataset and GSE31210 dataset. (D) Prognostic analysis of 11 glycolysis-related genes was conducted in the TCGA LUAD dataset. (E) The UpSet plot displays the intersection of genes with statistically significant differences in the aforementioned analyses. (F) Differences in the expression of 4 glycolysis-related genes between the experimental group and the control group in siRNA transfection experiments. (^***p < 0.001; ^**p < 0.01; ^*p < 0.05; Abbreviation: ns: not significant).

Figure 7

Association between SPC25 and ferroptosis-related genes. (A) The correlation between SPC25 expression and 25 ferroptosis-related genes was analyzed in the TCGA LUAD dataset and GSE31210 dataset. (B, C) The differential expression of 25 ferroptosis-related genes between the high and low SPC25 expression groups was analyzed in the TCGA LUAD dataset and GSE31210 dataset. (D) Prognostic analysis of 25 ferroptosis-related genes was conducted in the TCGA LUAD dataset. (E) The Veen plot displays the intersection of genes with statistically significant differences in the aforementioned analyses. (^***p < 0.001; ^**p < 0.01; ^*p < 0.05; Abbreviation: ns: not significant).

Figure 8

Prediction and construction of the ceRNA network related to SPC25 in LUAD. (A) The results of the analysis of microT-CDS and mirDIP databases are presented in a Venn diagram. (B) Differential expression analysis of 8 miRNAs in the TCGA LUAD dataset. (C) The expression of hsa-miR-451a in tumor samples from the TCGA LUAD dataset was significantly lower than in normal samples. (D) Potential binding sites between SPC25 and hsa-miR-451a were predicted using the RNAHybrid online tool. (E) The results of the analysis of miRNet and ENCORI databases are presented in a Venn diagram. (F) Differential expression analysis of 3 lncRNAs in the TCGA LUAD dataset. (G) The expression of SNHG15 in tumor samples from the TCGA LUAD dataset was significantly higher than in normal samples. (H) Potential binding sites between hsa-miR-451a and SNHG15 were predicted using the RNAHybrid online tool. (^***p < 0.001; ^**p < 0.01; ^*p < 0.05; Abbreviation: ns: not significant).