Creatine kinase mitochondrial 2 promotes the growth and progression of colorectal cancer via enhancing Warburg effect through lactate dehydrogenase B

Study population

This is a prospective study. We enrolled 220 newly diagnosed patients with CRC from June 2020 to December 2022 at the First People’s Hospital of Taizhou City, Zhejiang Province, China. None of the patients had undergone surgical, radiotherapy, or chemotherapy treatments before they enrolled, and all the patients exhibited a clear pathological diagnosis. Patients with metastatic tumors and multi-organ tumors were excluded. All participants were subjected to follow-up assessments, with the endpoint set at the patient’s death or September 2023. This study was approved by the ethical committee of the First People’s Hospital of Taizhou City, and all patients signed the informed consent form before enrollment (Ethical Application Ref: 2019-KY-009-03).

Immunohistochemistry

The expression levels of CKMT2 and LDHB in CRC tissues were tested via immunohistochemistry. Results were determined by multiplying the percentage of positive cells (0–100%) and the positive intensity (0 indicated no staining, one indicated weak staining, two indicated moderate staining, and three indicated strong staining). The results were judged by two pathologists independently, if the results were not matched, a third pathologist will make a final decision. Antibodies for CKMT2 and LDHB were obtained from Abcam, Cambridge, UK (ab227440, ab53292), and the immunohistochemistry reagent kit was purchased from Beijing Solarbio Science & Technology Co., Ltd., Beijing, China. Experiments were performed according to the instruction from the kit.

Quantitative reverse transcription polymerase chain reaction (qRT-PCR)

The expression profile of CKMT2 across human colonic epithelial cells (NCM460) and various human CRC cell lines (SW480, DLD-1, SW620, HCT116, HCT15) was evaluated by qRT-PCR. The CKMT2 expressions in SW480 and NCM460 cells after transfection with CKMT2 siRNA were also detected by qRT-PCR. Total RNA was extracted using the TRIzol method (TaKaRa Bio Inc., Shiga, Japan), and the PrimeScriptTM RT reagent kit (RR036A; TaKaRa, Shiga, Japan) was used to synthesize the first strand of cDNA. The reaction system comprised 2 ug of total RNA and five times of reverse transcription reagent. Amplification was subsequently performed with the cDNA as a template, using the TB GreenTM Premix Ex TaqTM kit (RR420A; TaKaRa, Shiga, Japan) on the ABI 7500 Real-Time PCR system. CKMT2 mRNA expressions in different samples were analyzed with the formula 2^−ΔΔCt, and normalized to glyceraldehyde 3-phosphate dehydrogenase (GAPDH) as the internal reference. All samples were measured in triplicates.

Cell culture

Human colonic epithelial cell line (NCM460) and human CRC cell lines (SW480, DLD-1, SW620, HCT116, and HCT15) were obtained from FuHeng Biology (Shanghai, China). Cells were cultured at 37 °C with 5% CO₂ in Dulbecco’s modified Eagle medium (DMEM) containing 10% fetal bovine serum (Gibco, Thermo Fisher Scientific, MA, USA) and 1% (v/v) penicillin/streptomycin (Gibco, Thermo Fisher Scientific, MA, USA). NCM460 and SW480 cells were cultured in DMEM (2317091; Viva Cell Biosciences, Shanghai, China), whereas DLD-1, SW620, HCT116, HCT15 cells were cultured in RPMI-1640 (2317095; Viva Cell Biosciences, Shanghai, China). All cells were harvested in the logarithmic growth phase. All cell experiments were repeated three times.

Cell transfection

CKMT2 siRNA (sense 5′-GCAACAAGGUGACACCCAATT-3′, antisense 5′-UUGGGUGUCACCUUGUUGCTT-3′) and its negative control (NC) siRNA (sense 5′-UUCUCCGAACGUGUCACGUTT-3′, antisense 5′-ACGUGACACGUUCGGAGAATT-3′) were purchased from Sigma (Shanghai, China). SW480 cells were transfected with siRNA using Lipofectamine 3000 (L3000001; Thermo Fisher Scientific, MA, USA) and Opti-MEM (31985070; Gibco, MA, USA). Following 48 h of transfection, the transfection efficiency was verified using qRT-PCR and western blotting.

Cell migration

SW480 cells were seeded in the upper chamber of a 24-well Transwell plate. Upon reaching 30–50% confluence, they were transfected with CKMT2 siRNA or NC siRNA. After 48 h of transfection, the upper chambers were removed, and a cotton swab was used to eliminate non-migrated cells. Subsequently, the cells were fixed with 4% paraformaldehyde for 15 min, washed three times with phosphate-buffered saline (PBS), stained with 0.5% crystal violet solution for 10 min, rinsed with PBS, and then photographed under a microscope (Olympus).

Cell apoptosis

The apoptosis of SW480 cells were tested after 48 h of transfection with CKMT2 siRNA or NC siRNA. The Annexin V-FITC Apoptosis Detection Kit (CA1020, Solarbio, Beijing, China) was used. A minimum of 10⁴ cells per sample were evaluated using flow cytometry (DxFLEX; Beckman Coulter, Suzhou, Jiangsu, China).

Western blotting

SW480 cells were lysed using an appropriate volume of radioimmunoprecipitation assay buffer (Beyotime Biotechnology, Shanghai, China) and sonicated in an ice-water bath for 10 mins. After centrifugation at 12,000 rpm at 4 °C for 10 mins, the supernatant was collected. Protein concentration was measured and adjusted to 1 µg/µL. For electrophoresis, we prepared a 10% sodium dodecyl-sulfate polyacrylamide gel electrophoresis (SDS-PAGE) gel, loading each well with 20 µg of protein. The proteins were subsequently transferred to a polyvinylidene fluoride membrane, blocked with 5% skimmed milk at room temperature for 1 h. Following TBST washing, the membrane was incubated with the respective primary antibodies at 4 °C overnight. The membrane was subsequently washed three times with TBST for 5 mins each time and was then incubated at room temperature for 1 h with horseradish peroxidase-conjugated anti-rabbit (A0208; Beyotime, Shanghai, China) or anti-mouse (A0192; Beyotime, Shanghai, China) secondary antibodies. After being washed by TBST for three times, the membrane was developed using an enhanced chemiluminescence substrate (Beyotime, Shanghai, China, P0018M) and exposed for photographic documentation. Antibodies for CKMT2 and GAPDH were sourced from HUABIO (ER64987, ET1601-4), and the LDHB antibody was purchased from Proteintech (66425-1-lg).

Co-immunoprecipitation (Co-IP)

Following the designated treatments, SW480 cells were lysed with Co-IP cell lysis buffer (R0030; Solarbio, Beijing, China), supplemented with 1 mM phenylmethylsulfonyl fluoride (ST506; Beyotime, Shanghai, China) and 1% protein phosphatase inhibitor cocktail (P1260; Solarbio, Beijing, China) for 30 mins on ice. The cell lysate was then centrifuged, and the supernatant was collected for further analysis. For input examination, 20 µL of the supernatant was reserved. The remaining was mixed with 30 µL of protein A/G CoIP magnetic beads (SB-AG001; Share-Bio, Shanghai, China) and rotated at 4 °C for 30 mins. Subsequently, the supernatant was collected, incubated with rabbit anti-CKMT2 (13207-1-AP; Proteintech, Rosemont, IL, USA), or mouse anti-LDHB (Proteintech, Rosemont, IL, 66425-1-lg), and subjected to rotation at 4 °C overnight. Following this, the mixture was combined with 30 µL of protein A/G CoIP magnetic beads and rotated at 4 °C for 4 h. The beads were collated in a magnetic test-tube rack, washed three times using lysis buffer, and eluted with 1 × SDS-loading buffer. The supernatant was collected, heated, and then subjected to western blotting.

Statistical analyses

SPSS 22.0 software (SPSS, Inc., Chicago, IL, USA) and GraphPad Prism 8 (GraphPad Software Inc., San Diego, CA, USA) were used for the data analysis. The Student’s t-test was employed for comparing two groups of continuous variables following a normal distribution, whereas analysis of variance (ANOVA) was used for multiple group comparisons. We employed the Mann-Whitney U test for non-normally distributed variables. Kaplan-Meier survival curves were plotted, and significance was determined using the log rank test. Univariate and multivariate Cox regression analyses were conducted to identify prognostic factors for CRC patients. Statistical significance was determined when p-value < 0.05.

CKMT2 is highly expressed in CRC tissues and cell lines

A comprehensive immunohistochemical analysis was conducted on CRC tissues and their corresponding distant nontumor counterparts sourced from a cohort of 220 patients with CRC. The staining intensity of CKMT2 in cancer tissues exhibited a robust pattern, contrasting with the minimal to absent staining observed in adjacent nontumor tissues (Figs. 1A–1D). Notably, the immunohistochemical scoring indicated a marked elevation in the expression of CKMT2 in cancer tissues (1.60 ± 0.53) compared to adjacent nontumor tissues (0.45 ± 0.29), demonstrating statistical significance (t = 28.397, p < 0.001) (Fig. 1E). Using qRT-PCR, the expression profile of CKMT2 was evaluated across human colonic epithelial cells (NCM460) and various human CRC cell lines (SW480, DLD-1, SW620, HCT116, HCT15), which are widely used in vitro cancer research. The results elucidated a significant increase in CKMT2 expression in SW480 and SW620 cells when compared with NCM460 (p < 0.05) (Fig. 1F). However, a distinct decrease in the expression of CKMT2 in DLD-1 and HCT15 cells compared to NCM460 was also observed (p < 0.01) (Fig. 1F). The expression of CKMT2 in HCT116 cells showed an increasing trend, though statistically not significant. For further validation, an analysis of The Cancer Genome Atlas (TCGA) database, a widely acknowledged repository of cancer gene information, revealed a significant upregulation of CKMT2 mRNA in CRC tissues in contrast to normal controls (p < 0.001) (Fig. 1G).

CKMT2 expression is related with some clinical pathological factors in CRC patients

After collecting clinical information from 220 patients with CRC, an in-depth analysis was conducted to discern the relationship between CKMT2 expression and various clinical pathological factors (Table 1). CKMT2 expression level is higher in patients with adenocarcinoma patients compared with mucinous carcinoma (t = 2.169, p = 0.031). Furthermore, patients with a tumor size ≥5 cm exhibited enhanced CKMT2 expression compared to their counterparts with a tumor size <5 cm (t = 2.294, p = 0.023). Patients with distant metastasis showed noteworthy results, presenting higher CKMT2 expression than those without metastasis (t = 2.304, p = 0.022). Furthermore, in survival patients, the expression level of CKMT2 was lower than those who were not alive (t = 2.163, p = 0.032). There were no statistically significant correlations between CKMT2 expression and patient gender, age, smoking status, alcohol consumption, tumor differentiation degree, TNM stage, tumor infiltration depth, lymph node metastasis, or carcinoembryonic antigen (CEA) levels (p > 0.05).

CKMT2 expression is related with the prognosis of CRC patients

A total of 220 enrolled CRC patients received follow-up, outcome information, including metastasis and mortality were collected. Utilizing patient survival as the state variable and CKMT2 expression results as the test variable, a receiver operating characteristic (ROC) curve was plotted (Fig. 2A), revealing an area under the curve of 0.602 (p = 0.025). The optimal cutoff value was determined to be 1.85. Patients were stratified based on both the cutoff value (1.85) and median (1.60), and Kaplan-Meier survival curves were generated, with the endpoint being the occurrence of distant metastasis or death. In Fig. 2B, when CKMT2 was categorized into high-expression (CKMT2 > 1.85) and low-expression (CKMT2 ≤ 1.85) groups using the cutoff value, the average survival time for the low-expression group was 34.32 months (95% confidence interval [CI] [32.72–35.92]), whereas that for the high-expression group averaged 27.59 months (95% CI [24.95–30.22]). Patients with high CKMT2 expression exhibited significantly lower average survival time and overall survival rates than the low-expression group (log rank p < 0.001). Similarly, when CKMT2 was divided using the median into high-expression (CKMT2 > 1.60) and low-expression (CKMT2 ≤ 1.60) groups, the survival time for the low-expression group averaged 34.09 months (95% CI: [32.24–35.94]), and that for the high-expression group averaged 30.40 months (95% CI [28.13–32.68]). Patients with high CKMT2 expression exhibited significantly lower average survival time and overall survival rates than the low-expression group (log rank p = 0.015) (Fig. 2C). Furthermore, the free from distant metastasis (FDM) survival rate was employed to assess the relationship between CKMT2 expression and distant metastasis in patients with CRC. Results indicated that patients with high CKMT2 expression exhibited significantly lower FDM than those exhibiting low expression (cutoff value grouping, log rank p = 0.007; median grouping, log rank p = 0.031) (Figs. 2D, 2E). Prognostic information of patients with CRC from TCGA was downloaded to analyze the relationship between CKMT2 expression and overall survival time, further confirming the effects of CKMT2 levels on patient survival (Fig. 2F). The results demonstrated that patients with high CKMT2 expression exhibited significantly lower overall survival rates than those with low expression (log rank p = 0.039).

CKMT2 is an independent prognostic factor for CRC patients

Univariate and multivariate COX regression analysis were performed to evaluate the prognostic factors for CRC patients. Age (hazard ratio (HR): 3.400, 95% CI [1.865–6.198], p < 0.001), differentiation grade (HR: 2.767, 95% CI [1.627–4.704], p < 0.001), tumor size (HR: 1.921, 95% CI [1.117–3.304], p = 0.018), TNM stage (HR: 1.867, 95% CI [1.332–2.617], p < 0.001), CEA level (HR: 2.967, 95% CI [1.664–5.290], p < 0.001), and CKMT2 level (HR: 2.925, 95% CI [1.686–5.076], p < 0.001) were found to be associated with the prognosis of patients with CRC (Table 2). Some factors, such as gender, tumor location, smoking, alcohol consumption, and pathological type showed no significant correlation with patient prognosis (p > 0.05). Factors with p < 0.01 in the univariate analysis were included in the multivariate Cox regression analysis. The results revealed that CKMT2 level (HR: 1.929, 95% CI [1.086–3.426], p = 0.025) could serve as an independent factor influencing the prognosis in CRC patients. In addition, age (HR: 3.538, 95% CI [1.848–6.773], p < 0.001), TNM stage (HR: 1.856, 95% CI [1.287–2.679], p = 0.001), CEA level (HR: 2.051, 95% CI [1.129–3.727], p = 0.018) shared the same effect.

Inhibition of CKMT2 expression affects migration and apoptosis of CRC cells

Drawing on the distinctive expression patterns of CKMT2 across various CRC cell lines (Fig. 1F), the SW480 cell line was chosen for further exploration. Initially, CKMT2 siRNA was transfected into SW480 and NCM460 cells to establish cell lines with diminished CKMT2 expression. QRT-PCR analysis demonstrated a substantial reduction in CKMT2 mRNA expression in the siCKMT2 group compared to the NC group (p < 0.001) (Figs. 3A, 3B). Subsequent western blotting validated the successful transfection, demonstrating a marked decrease in CKMT2 protein levels following siCKMT2 transfection (Fig. 3C). The effect of CKMT2 gene silencing on cell migration was evaluated using the Transwell chamber assay, revealing a noteworthy inhibition of cell migration activity in the siCKMT2 group compared to the NC group (Fig. 3D), accompanied by a significant decrease in the cell migration rate (t = 7.292, p < 0.001) (Fig. 3E). After a 48-h transfection period, flow cytometry was employed to examine cell apoptosis, revealing a significantly increased apoptosis rate in the siCKMT2 group compared to that in the NC group (t = 43.89, p < 0.001) (Figs. 3F, 3G).

CKMT2 impacts the glycolytic metabolism in CRC Cells

We identified the proteins have interactions with CKMT2 from the STRING database (https://cn.string-db.org/) (Fig. 4A), functional enrichment analysis of these associated genes was performed via Database for Annotation, Visualization and Integrated Discovery (DAVID) (https://david.ncifcrf.gov/). Gene Ontology (GO) enrichment analysis revealed that CKMT2 and its interacting factors play a pivotal role in pathways related to sugar metabolism, including “lactate metabolic process,” “pyruvate metabolic process,” “ATP biosynthetic process,” and “L-lactate dehydrogenase activity” (Fig. 4B). Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis highlighted “glycolysis/gluconeogenesis” and “pyruvate metabolism” as key pathways potentially regulated by CKMT2 interacting factors in CRC (Fig. 4C). We performed further experiments to investigate whether CKMT2 regulates sugar metabolism in CRC cells. Notably, CKMT2 inhibition in NCM460 cells did not significantly alter lactate concentration (Fig. 4D) and glucose uptake (Fig. 4E) levels (p > 0.05). However, in SW480 cells with low CKMT2 expression, we observed a significant decrease in lactate concentration (t = 5.096, p = 0.007) (Fig. 4F) and glucose uptake (t = 6.197, p = 0.003) (Fig. 4G).

CKMT2 promotes the Warburg effect by upregulating LDHB in CRC cells

To evaluate the mechanism underlying the regulation of the Warburg effect by CKMT2, we analyzed the correlation between CKMT2 and glycolysis-related gene expression in colon adenocarcinoma and rectum adenocarcinoma from the Gene Expression Profiling Interactive Analysis (GEPIA) database (http://gepia.cancer-pku.cn/index.html) (Figs. 5A–5M). The results revealed a negative correlation between CKMT2 mRNA expression and HK2 mRNA (p = 0.029, R = −0.11) and PKM mRNA (p = 0.009, R = −0.14) expression. Conversely, a positive correlation was noted with LDHB mRNA (p = 0.0016, R = 0.16) and PFKM mRNA (p = 3.8e−5, R = 0.21). No significant correlations were noted with the expression of glycolysis-related genes, including ALDOA, ALDOB, ENO1, G6PC, LDHA, PGAM1, PGK1, SLC2A1, and SLC2A4 (p > 0.05). Subsequently, qRT-PCR was employed to examine expression changes of HK2, LDHB, PFKM, and PKM genes in SW480 cells after CKMT2 gene silencing. The results demonstrated a significant decrease in LDHB expression (t = 5.966, p = 0.004) and a modest reduction in HK2 expression (t = 4.061, p = 0.015) following CKMT2 inhibition. However, the expression of PFKM and PKM did not significantly change (p > 0.05) (Fig. 5N). The results of qRT-PCR showed distinct decreases both in LDHB and HK2 expressions. However, the GEPIA database revealed a negative correlation between LDHB and HK2 expression. So, HK2 was not employed for subsequent research. Furthermore, western blotting confirmed that CKMT2 silencing led to the significant downregulation of LDHB expression in SW480 cells (Fig. 5O). Combining the correlation analysis from the GEPIA database and the relative expression changes of glycolysis-related enzymes in SW480 cells, we propose that CKMT2 promotes the Warburg effect by upregulating LDHB expression in CRC cells.

Additionally, we substantiated the correlation between CKMT2 and LDHB in CRC tissues. Immunohistochemical staining of CKMT2 and LDHB in CRC tissues and distal para-cancerous tissues is presented in Figs. 6A–6H. The assessment of LDHB expression in 30 CRC tissue samples revealed a significantly higher expression in CRC tissues compared to adjacent normal tissues, demonstrating a statistically significant difference (t = 10.77, p < 0.001) (Fig. 6I). Correlation analysis unveiled a positive correlation between CKMT2 and LDHB expression in CRC tissues (r = 0.374, p = 0.042) (Fig. 6J). To further confirm the association between CKMT2 and LDHB, Co-IP was performed. The results showed that in SW480 cells, LDHB protein was detectable in the immunoprecipitated products of CKMT2, and vice versa. Notably, both CKMT2 and LDHB proteins were not detected in the immunoprecipitated products with IgG, as depicted in Fig. 6K. Thus, the interaction between CKMT2 and LDHB was detected.