USP22 as a key regulator of glycolysis pathway in osteosarcoma: insights from bioinformatics and experimental approaches

Ethical statement

This study obtained ethical support from the Ethics Committee of the Second Affiliated Hospital of Nanchang University (No. 2022021). All procedures performed in studies involving human participants were in accordance with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Transcriptomic datasets acquisition and preprocessing

Two transcriptomic datasets related to osteosarcoma (GSE16088 and GSE21257) were obtained from GEO database (https://www.ncbi.nlm.nih.gov/geoprofiles/). GSE16088 contains expression data of six normal and 14 tumor tissues. GSE21257 contains transcriptomic data and clinical information of 53 osteosarcoma patients. The expression profiles of GSE16088 and GSE21257 were preprocessed including gene symbol conversion, normalization and median polish. Based on The Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/), transcriptomic data and clinical information of 88 osteosarcoma patients (TCGA-OS cohort) were acquired. The transcriptomic data was also preprocessed.

Analysis of USP22 expression and prognosis in osteosarcoma

To investigate the potential role of USP22 in osteosarcoma, the expression of USP22 was firstly analyzed in tumor and normal tissues using the GSE16088 dataset. Receiver operating characteristic (ROC) analysis was then performed to assess the diagnostic value of USP22 in differentiating between osteosarcoma and normal tissues. This analysis was carried out using the R package “pROC”.

Subsequently, the relationship between USP22 expression and prognosis in osteosarcoma patients was examined using Kaplan-Meier survival curve analysis based on the GSE21257 dataset and TCGA-OS cohort. To evaluate the sensitivity and specificity of USP22 in predicting the prognosis of osteosarcoma patients, ROC analysis was performed at 1, 3, and 5-year intervals using the R package “survivalROC”.

Identification of USP22 co-expressed genes in osteosarcoma

Firstly, differentially expressed genes (DEGs) between tumor (high USP22) tissues and normal (low USP22) tissues were identified from GSE16088 dataset using limma package in R software. DEGs were filtered with criteria of absolute fold change ≥2 and p < 0.01. These DEGs were correlated with USP22 expression in GSE16088 dataset.

Then, weighted gene co-expression network analysis (WGCNA) was performed on TCGA-OS cohort to identify genes co-expressed with USP22 using R package “WGCNA”. The procedures were: firstly, a soft thresholding power was selected for network construction based on scale-free topology. It transformed the adjacency matrix to continuous values between 0 and 1 for a scale-free network close to biological network state. Secondly, blockwiseModules function was utilized to construct the unsigned co-expression network, and modules containing genes with similar expression patterns were identified using average linkage hierarchical clustering and DynamicTreeCut algorithm. Module eigengenes (MEs) were calculated as the first principal component of modules and used to evaluate association with clinical traits. Modules with p < 0.05 were considered significantly associated with the trait. Finally, gene significance (GS) and module membership (MM) were used as filtering criteria to select hub genes in the USP22 co-expression module, with the thresholds set at GS > 0.2 and MM > 0.6.

The common genes identified from both GSE16088 and TCGA datasets were considered as USP22 co-expressed genes in osteosarcoma.

PPI network analysis and functional enrichment analysis

Protein-protein interaction (PPI) analysis was performed for the USP22 co-expressed genes using STRING database (https://string-db.org/) to explore their potential interactions. The PPI network was visualized using Cytoscape software (version 3.7.2).

Then, to investigate the biological functions and signaling pathways involved with USP22 in osteosarcoma, 344 USP22 co-expressed genes (common genes) were imported into DAVID database (https://david.ncifcrf.gov/) for functional enrichment analysis, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Significantly enriched GO terms and KEGG pathways (p < 0.05) were visualized using R software. The most significant KEGG pathway is considered the key signaling pathway associated with USP22 in osteosarcoma.

Gene set enrichment analysis (GSEA) was performed using GSEA software version 4.0.1 to identify differentially expressed signaling pathways between USP22 low expression and high expression groups in GSE16088 dataset and TCGA-OS cohort, with KEGG gene sets as reference. The normalized enrichment score (NES) >0 and p < 0.05 represent significantly upregulated signaling pathways, while NES < 0 and p < 0.05 represent significantly downregulated signaling pathways.

Cell culture and transfection

The human osteosarcoma cell line Sao-2 was obtained from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China) and cultured in DMEM medium (Gibco, CA, USA) supplemented with 10% fetal bovine serum (FBS) (Gibco, Waltham, MA, USA) and 1% penicillin/streptomycin (Solarbio, Beijing, China) at 37 °C in a humidified atmosphere containing 5% CO₂.

USP22 expression was silenced by transfecting Sao-2 cells with USP22-specific small interfering RNA (siUSP22) using Lipofectamine 3000 (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s protocol. The sequences of siRNA were as follows: 5′-GAAGCAUAUUCACGAGCAUTT-3′ (forward) and 5′-AUGCUCGUGAAUAUGCUUCTT-3′ (reverse). Non-targeting siRNA (siNC) was used as control. At 24 h post-transfection, Western blot analysis was conducted to assess USP22 protein levels in normal Sao-2 cells, siNC-transfected Sao-2 cells, and siUSP22-transfected Sao-2 cells to evaluate the knockdown efficiency of siUSP22.

Cell proliferation assay

The effect of USP22 knockdown on cell proliferation was evaluated using the Cell Counting Kit-8 (CCK-8) (NCM Biotech, Suzhou, China) assay. Briefly, transfected cells were seeded into 96-well plates at a density of 2,000 cells per well and incubated for 24, 48, and 72 h. At each time point, 10 µl of CCK-8 solution was added to each well, and the cells were incubated for 30 min at 37 °C. The absorbance at 450 nm was measured using a microplate reader (BioTek, Winooski, VT, USA).

Colony formation assay

Suspended Sao-2 cells were seeded at a density of 500 cells per well in a 6-well plate and cultured for 14 days to allow for colony formation. After 14 days, the cells were then fixed with 4% paraformaldehyde and stained with 0.1% crystal violet. The number of colonies with more than 50 cells was counted under a microscope (Nikon, Tokyo, Japan).

Scratch assay

Transfected cells were seeded into 6-well plates and grown to confluence. A scratch was made in the cell monolayer using a 200-µl pipette tip, and the cells were washed with PBS to remove the debris. The cells were then incubated in serum-free medium for 24 h, and the migrated cells were photographed under a microscope (Nikon, Tokyo, Japan) and quantified using ImageJ software.

Transwell invasion assay

Single-cell suspensions from the USP22 knockdown group and the siNC group were seeded into the upper chamber of Transwell inserts (Corning, NY, USA) coated with Matrigel (BD Biosciences, Franklin Lakes, NJ, USA), while the lower chamber was filled with 10% FBS-containing medium. After 24 h of incubation, the invaded cells were fixed with 4% paraformaldehyde and stained with 0.1% crystal violet. The number of invaded cells was counted under a microscope (Nikon, Tokyo, Japan).

Cell apoptosis assay

Single-cell suspensions were harvested and washed with cold PBS. The cells were then stained with Annexin V-FITC and propidium iodide (PI) using the Annexin V-FITC Apoptosis Detection Kit (Solarbio, Beijing, China) according to the manufacturer’s instructions. The stained cells were analyzed using a flow cytometer (Beckman Coulter, Brea, CA, USA).

Glucose consumption, lactate production, and ATP level assays

Transfected cells were seeded into 12-well plates and cultured for 48 h. The supernatant was collected, and the glucose and lactate levels were measured using the Glucose Assay Kit (Solarbio, Beijing, China) and Lactate Assay Kit (Solarbio, Beijing, China), respectively. The intracellular ATP level was measured using the ATP Assay Kit (Solarbio, Beijing, China) according to the manufacturer’s instructions.

Seahorse analysis of glycolysis

The extracellular acidification rate (ECAR) was measured in siNC and siUSP22 transfected Sao-2 cells using a Seahorse XF96 Extracellular Flux Analyzer (Agilent Technologies, Santa Clara, CA, USA) to assess glycolysis. Briefly, 2 × 10⁴ cells per well were seeded into XF96 cell culture microplates and incubated overnight. Before measurements, cells were washed and incubated in XF base medium containing 1 mM pyruvate, 2 mM glutamine and 10 mM glucose. The ECAR was monitored under basal conditions and in response to the sequential addition of glucose (10 mM), oligomycin (1 μM) and 2-deoxyglucose (50 mM). The glycolysis and glycolytic capacity were calculated based on the ECAR values.

Quantitative real-time PCR

Total RNA was extracted from siNC and siUSP22 transfected Sao-2 cells using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s protocol. The concentration and purity of extracted RNA were determined using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). Complementary DNA was generated from 1 microgram of total RNA through reverse transcription according to the manufacturer’s protocol of a cDNA synthesis kit (Takara, Dalian, China). Polymerase chain reaction was performed on a real-time amplification system (Applied Biosystems, CA, USA) employing a premix reagent (Takara, Dalian, China). The PCR procedure involved initial denaturation at 95 °C for 30 s, followed by 40 cycles consisting of denaturation at 95 °C for 5 s and annealing/extension at 60 °C for 34 s. The primer sequences were:

USP22 forward, 5′-GGAAAATGCAAGGCGTTGGAG-3′, reverse, 5′-GTGCAGTTCGAGGTGATCTTT-3′; HK2 forward, 5′-GAGCCACCACTCACCCTACT-3′, reverse, 5′-CCAGGCATTCGGCAATGTG-3′; PKM2 forward, 5′-ATGTCGAAGCCCCATAGTGAA-3′, reverse, 5′-TGGGTGGTGAATCAATGTCCA-3′; GLUT1 forward, 5′-GGCCAAGAGTGTGCTAAAGAA-3′, reverse, 5′-ACAGCGTTGATGCCAGACAG-3′; β-actin forward, 5′-AGATTACTGCCCTGGCTCCTAG-3′, reverse, 5′-CATCGTACTCCTGCTTGCTGAT-3′. The relative expression levels were calculated using the 2^−ΔΔCt method. β-actin was used as an internal control.

Western blot analysis

The expression levels of USP22, HK2, PKM2, and GLUT1 in cells were evaluated using Western blot analysis. Briefly, transfected cells were harvested and lysed in RIPA buffer (NCM Biotech, Suzhou, China) containing protease inhibitor cocktail (NCM Biotech, Suzhou, China). The protein concentration was determined using the BCA Protein Assay Kit (NCM Biotech, Suzhou, China). Equal amounts of protein were separated by SDS-PAGE and transferred to PVDF membranes (Millipore, Bedford, MA, USA). The membranes were then blocked with 5% non-fat milk in TBS-T buffer and incubated with primary antibodies against USP22, HK2, PKM2, GLUT1, and β-actin (Abcam, Cambridge, UK) at 4 °C overnight. After washing with TBS-T buffer, the membranes were incubated with HRP-conjugated secondary antibodies (Abcam, Cambridge, UK) for 1 h at room temperature. The protein bands were visualized using ECL reagent (NCM Biotech, Suzhou, China) and quantified using ImageJ software.

Statistical analysis

All experimental data were shown from at least three independent experiments and presented as the mean ± standard deviation (SD). Differences between groups were analyzed using the Student’s t-test in GraphPad Prism 7.0. A p value less than 0.05 was considered statistically significant.

USP22 is highly expressed in osteosarcoma and associated with poor prognosis

In GSE16088 dataset, USP22 expression was significantly higher in tumor tissues than normal tissues (p < 0.05) (Fig. 1A). ROC curve analysis showed the area under curve (AUC) of USP22 was 1.00, indicating its high diagnostic value (Fig. 1B).