PKMYT1 knockdown inhibits cholesterol biosynthesis and promotes the drug sensitivity of triple-negative breast cancer cells to atorvastatin

The UALCAN database

The UALCAN website provides a thorough analysis of cancer omics data and is accessible at http://ualcan.path.uab.edu. We utilized this platform to assess the mRNA expression of PKMYT1 in breast cancer. In addition, we evaluated the mutation frequency of PKMYT1 in different cancer types.

Antibodies

Anti-PKMYT1(MA5-25029) was purchased from Invitrogen. Anti-Vinculin(sc-73614) was purchased from Santa Cruz Biotechnology (Dallax, TX, USA). Anti-HMGCR(ab174830) was purchased from Abcam (Abcam, Cambridge, UK). Anti-DHCR24 (10471-1-AP), Anti-SQLE (12544-1-AP), Anti-HMGCS1 (17643-1-AP), Anti-FDFT1 (13128-1-AP), Anti-TRAF1 (45D3) and Anti-SREBF2 (28212-1-AP) were commercially obtained from Proteintech (Proteintech Group, Inc., Rosemont, IL, USA). Anti-GAPDH (#5174S) and Anti-P-AKT (Ser473) (cas#4060S) were commercially obtained from Cell Signaling Technology (CST, Danvers, MA, USA).

Cell culture

MDA-MB-453 cells were purchased from the Cell Bank of the Committee on Type Culture Collection of the Chinese Academy of Sciences (Shanghai, China). Dulbecco’s modified Eagle’s medium (DMEM, GIBCO, Carlsbad, CA, USA) dissolved with 10% FBS (Sigma-Aldrich, St. Louis, MO, USA) was used to culture the cells in a humid incubator with 5% CO₂ at the temperature of 37 °C.

Plasmids

PKMYT1 was subcloned into pBoBi expression vectors (Verma laboratory, Salk Institute La Jolla, CA, USA) and Flag-tagged expression vectors (Sigma-Aldrich, St. Louis, MO, USA). Plasmid DNA was mixed with serum-free medium and cells were transfected with Lipofectamine 2000 (Invitrogen) according to the manufacturer’s instructions. Subsequently, the cells were incubated for 4 h at 37 °C with 5% CO₂. After the transfection, the cells were observed under a fluorescence microscopy (Zeiss, Oberkochen, Germany).

Lentiviral shRNA cloning and stable cell line generation

The pLKO.1 within the AgeI/EcoRI sites at the 3′ end of the human U6 promoter was cloned with lentiviral shRNAs to target the genes of PKMYT1. The targeted sequences we as follows:

PKMYT1-sh1 5′-TGCGTTCTGTCCTTGTCATGA-3′, PKMYT1-sh2 5′-CTCCTACGGAGAGGTCTTCAA-3′, TRAF1-sh1 5′-GCCTTCTACACTGCCAAGTAT-3′. Subsequently, lentiviral particles containing these shRNAs were produced using a lentiviral packaging system. Specifically, the constructed pLKO.1-shRNA plasmid was co-transfected with packaging plasmids into HEK293T cells to collect and concentrate the viral particles for 48–72 h. The pLKO-BSD-shTRAF1 and pLKO-Puro-shPKMYT1 lentiviral particles were then used to transduce MDA-MB-453 cells, which were pre-treated with polybrene to enhance transduction efficiency. The cells were selected with antibiotic-containing medium 24 h after the transduction. The pLKO-BSD-shTRAF1-transduced cells and pLKO-Puro-shPKMYT1-transduced cells were selected with 6μg/ml Blasticidin and 2 μg/ml Puromycin, respectively. Finally, the knockdown efficiency of PKMYT1 and TRAF1 genes was verified using quantitative real-time PCR and Western blot to ensure the effectiveness of the shRNAs and the stability of shRNA-expressing cell lines for subsequent experiments.

EdU assay and plate colony formation experiments

In EdU proliferation experiments, cells were first seeded in 24-well plates at the appropriate density and treated with complete medium containing 10 μM EdU for 2–4 h after attachment. Subsequently, the cells were fixed with 4% formaldehyde, permeabilized with 0.5% Triton X-100 and then passed through the Click-iT EdU Alexa Fluor 594 Imaging Kit (Invitrogen, Life Technologies, Carlsbad, CA, USA) according to the instructions. Ultimately, the proliferative capacity of the cells was assessed by calculating the proportion of EdU-positive cells to total cells under a fluorescence microscopy.

For plate colony formation experiment, the cells were placed in a 12-well dish (with 500 cells in each well) filled with DMEM containing 10% FBS from HyClone and 1% PS from HyClone and then incubated for 14 days. Next, the colonies were washed with PBS, treated with 4% paraformaldehyde for 30 min, and stained with Giemsa stain from Leagene for another 30 min. The efficiency of the colonies was subsequently calculated by the formula: Colony formation efficiency = (number of clones/number of inoculated cells) × 100%.

Western blot

Briefly, radioimmunoprecipitation assay (RIPA) buffer with phosphatase inhibitors (Roche, Sigma-Aldrich, St. Louis MO, USA) and protease inhibitors (Sigma-Aldrich, St. Louis, MO, USA) was performed to lyse the cells. After using sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) for protein separation, the proteins were moved to PVDF membrane (Bio-Rad, Hercules, CA, USA). Next, specific primary antibodies and peroxidase-conjugated secondary antibodies were used to probe the proteins. Vinculin antibody was used for monitoring equal protein-sample loading. Visualization of the bands was realized using chemiluminescence.

RNA-Seq

The SMART-RNAseq Library Prep Kit (AT4201, Hangzhou KaiTai) was employed to develop sequencing libraries based on total RNAs. Briefly, mRNA was isolated from total RNA using Sera-Mag Magnetic Oligo(dT) particles and then chemically fragmented. The fragmented RNA was reverse-transcribed into cDNA using random primers containing a tagging sequence at their 3′ ends. The cDNA libraries were amplified by the KAPA high-fidelity DNA polymerase. The quality of the libraries was assessed using the 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, United States) to confirm that they met the required standards. High-throughput sequencing was performed on the NovaSeq 6000 platform (Illumina) with a sequencing depth of 50 million reads per sample using paired-end (PE) reads of 150 base pairs (bp) each. The sequencing libraries were not stranded.

To determine gene expression, the reads for each library were mapped using hisat2 (version 4.8.2) and then transformed to fragments per kilobase of exon per million fragments mapped (FPKM) using Cuffdiff 2.1.137. For differential gene expression analysis, the DESeq2 pipeline was employed. ClusterProfiler was used to perform biological pathway analysis. Professional technical staff at Hangzhou KaiTai Bio-lab assisted in performing RNA sequencing and library construction. The statistical power of this experimental designcalculated using RNASeqPower was 0.9996503 (sequencing depth: 50 million reads; number of biological replicates: 10; coefficient of variation: 0.5; effect size: 4; alpha: 0.01).

Measure of cholesterol

After washing the cells with PBS, the cells were lysed with RIPA lysis buffer containing protease inhibitors and centrifuged at 4 °C to remove cell residue. Subsequently, the clear lysate was mixed with the enzyme reaction mixture using the Micro Total Cholestenone (TC) Content Assay Kit (Beijing Solarbio Science & Technology Co., Ltd, China) in accordance with the instructions, and the absorbance was read in a micro-enzyme labeler. Finally, the TC content in the sample was calculated from the standard curve.

IC50 of atorvastatin

Drug sensitivity test was performed to directly assess the ability of cells to respond to drug-mediated pathway alterations. By comparing the sensitivity of PKMYT1 knockdown cells and control cells to atorvastatin, we were able to indirectly assess the effect of PKMYT1 on the cholesterol synthesis pathway. The IC50 value is a commonly used pharmacological metric to characterize the concentration of a compound (usually a drug) required to inhibit half of a biological or biochemical activity. In particular, the IC50 value is used to assess the magnitude of a drug’s potency, with a lower value indicating a smaller concentration of the drug required to inhibit the target activity and a greater potency of the drug (Park et al., 2022). The IC50 of atorvastatin was detected with CCK-8 assay kit (Dojindo, Kumamoto, Japan). Specifically, 5 × 10⁴ cells were seeded into 96-well plates and cultured for 24 h before adding various concentrations of atorvastatin (0.1 to 100 μM). After the addition of the drug, the cells were incubated for another 24 h. According to the instructions of the CCK-8 assay kit, 10μL of the CCK-8 solution was added to each well, and the plates were incubated at 37 °C for 2 h. Subsequently, the absorbance of each well was measured at a wavelength of 450 nm using a microplate reader. The cell viability at each concentration was calculated based on the absorbance values, and the IC50 value of atorvastatin was determined using nonlinear regression analysis in GraphPad Prism software.

Statistical analysis

Before performing ANOVA, the data normality was assessed using Shapiro-Wilk test. ANOVA test was performed in order to compare the differences in means between three or more groups. Two-group differences were analyzed using unpaired and two-tailed Student’s t-test. Data were expressed as mean ± standard error of the mean (SEM). ImageJ (version no.: 1.8.0_112; https://imagej.net/ij/) was used to normalize all of the relative protein expressions. The SPSS 18.0 software package (SPSS, Inc., Chicago, IL, USA) was used to perform statistical analyses.

PKMYT1 expression was upregulated in TNBC and promoted cell proliferation

To clarify the biological function of PKMYT1 in TNBC, we performed bioinformatics analysis using online databases and found that PKMYT1 had the highest alteration rate in invasive breast cancer and was primarily characterized by amplification (Fig. 1A). Subsequent analysis revealed that the PKMYT1 expression was significantly higher in TNBC than in other breast cancer subtypes (Fig. 1B). Survival analysis revealed that progression-free survival of TNBC patients with high-expressed PKMYT1 was relatively shorter (Fig. 1C). Subsequently, we developed TNBC cell lines with stable knockdown of PKMYT1 in MDA-MB-453 cells. It was found that the cell proliferation and clone formation were significantly suppressed by knocking down PKMYT1 (Figs. 1D and 1E). These data suggested that PKMYT1 played an oncogenic role in TNBC, but the exact mechanism remained to be investigated.

PKMYT1 promoted cholesterol biosynthesis in TNBC

We performed transcriptome sequencing on TNBC cells with stable knockdown of PKMYT1 to clarify the specific mechanism via which PKMYT1 promoted TNBC cell proliferation. A total of 97 genes were significantly downregulated following PKMYT1 knockdown, while 59 genes were abnormally upregulated (Fig. 2A). Subsequent, GO analysis showed that these DEGs were significantly enriched in cholesterol metabolism (Fig. 2B). We observed significantly downregulated mRNA expressions of multiple enzymes involved in the cholesterol biosynthetic pathway and the expression of SREBF2 (Fig. 2C). The results of the Western blot demonstrated that PKMYT1 knockdown greatly downregulated the protein expression of SREBF2, DHCR24, SQLE, FDFT1, and HMGCS. Notably, the protein expression level of HMGCR was upregulated after the knockdown of PKMYT1 (Fig. 2D). PKMYT1 knockdown significantly reduced the content of cholesterol in MDA-MB-453 cells (Fig. 2E). To conclude, our findings supported that PKMYT1 played a functional role in the regulation of cholesterol biosynthesis in TNBC cells.

PKMYT1 promoted SREBF2-mediated cholesterol biosynthesis via the TNF/TRAF1/AKT pathway

To clarify the specific mechanism through which PKMYT1 promoted SREBF2-mediated cholesterol biosynthesis, we performed KEGG enrichment analysis based on the transcriptome data from PKMYT1 stable knockdown cell lines. It was found that the TNF signaling pathway was closely related to PKMYT1 knockdown (Fig. 3A). This relationship suggested that inhibition of PKMYT1 had potential effects on the TNF signaling pathway, which in turn may exert downstream effects on SREBF2-mediated cholesterol biosynthesis. Our study found that silencing PKMYT1 significantly downregulate TRAF1 mRNA expression and overexpression of PKMYT1 significantly upregulated TRAF1 protein expression (Figs. 3B and 3C). Additionally, under TNF treatment conditions, PKMYT1 overexpression enhanced AKT activation and the expression of proteins related to cholesterol biosynthesis such as SREBF2, SQLE, HMGCS, FDFT1 and intracellular cholesterol content (Figs. 3C and 3D). However, knockdown of TRAF1 significantly inhibited the activation of AKT and cholesterol biosynthesis mediated by PKMYT1 overexpression (Figs. 3C and 3D). These findings indicated that the TNF/TRAF1/AKT/SREBF2 signaling pathway was essential for PKMYT1-induced cholesterol biosynthesis.

PKMYT1 knockdown reversed atorvastatin-induced feedback of cholesterol biosynthesis and promoted the drug sensitivity of atorvastatin

The cholesterol biosynthesis pathway is an abundantly upregulated feedback pathway following statin treatment of TNBC cells (Cai et al., 2019; Kimbung et al., 2016; Sarkar & Chattopadhyay, 2023). As PKMYT1 knockdown inhibited SREBF2 expression and its mediated cholesterol biosynthesis, we hypothesized that PKMYT1 knockdown can suppress statin-induced feedback activation of SREBF2. Notably, atorvastatin (ATV) treatment upregulated the protein expression of SQLE, FDFT1, HMGCS, and this feedback upregulation was significantly inhibited by PKMYT1 downregulation (Fig. 4A). In addition, as shown in Fig. 4B, in the control group, the response of cancer cell lines to different concentrations of ATV showed an IC50 value of 10.83 μΜ, whereas the IC50 of ATV was significantly lower than that of the control group when PKMYT1 was silenced (IC50 = 6.25 μΜ). This indicated that TNBC cells were more sensitive to ATV after PKMYT1 knockdown. Overall, these results confirmed that PKMYT1 knockdown eliminated the feedback upregulation of cholesterol biosynthesis-related proteins caused by statins and promoted the drug sensitivity of ATV.