Publicly available RNA sequencing data were obtained from the Gene Expression Omnibus (GEO) under accession number GSE157167 (Norkin et al., 2021). This dataset includes transcriptomic profiles of colorectal cancer organoids derived from AKP mutant mice (harboring mutations in APC, KRAS and TP53) treated with vehicle (control), atorvastatin 1 µM or lovastatin 0.5 µM for 48 h. Sequencing was performed using the Illumina NextSeq 500 platform. First, the quality of the raw sequencing reads was assessed using the FastQC toolkit (Wingett and Andrews, 2018). Low quality bases and adapter sequences were removed with Trimmomatic (Bolger et al., 2014) to ensure data integrity. The cleaned reads were then aligned to the GRCm39 mouse reference genome (Release M37) using HISAT2 (Kim et al., 2019). Gene expression quantification was performed with featureCounts (Liao et al., 2014) and to focus the analysis on reliably expressed genes, low abundance transcripts, defined as those with a count per million (CPM) ≤1 in less than two samples per group, were filtered out. The normalized count data were then analyzed for differential expression using the edgeR package (Robinson et al., 2010). Genes were considered upregulated if they exhibited a log2 fold change (log2FC) >1.0 and a false discovery rate (FDR) <0.05. Conversely, genes with a log2FC <−1.0 and FDR <0.05 were classified as downregulated.

Phosphoproteomic data (publicly available) were obtained from the study by Ouahoud et al. (2021), which analyzed the phosphorylation landscape of colorectal cancer HCT116 cells treated with 2 µM lovastatin or vehicle control for 48 h. For the analysis, we specifically focused on phosphorylation changes in kinases following statin treatment. Kinase-associated phosphopeptides were identified, and their phosphorylation intensities were statistically analyzed to assess the significance between conditions. For each peptide, average data (Σ[x₁, x₂, …, x₉]/n) and standard deviation (σ[x₁, x₂, …, x₉]) between biological replicates within each treatment group were collected. To compare phosphorylation levels between the lovastatin-treated and control groups, Welch’s t-test for independent samples was applied. The degrees of freedom were estimated using the Welch–Satterthwaite approximation, and a p-value was computed for each phosphosite. To correct for multiple hypothesis testing, FDR adjustment was performed. Kinases were considered to exhibit significant changes in phosphorylation if FDR ≤0.05.

Based on the phosphoproteomic data and the set of kinases that showed phosphorylation changes, we performed a pathway enrichment analysis to identify pathways and associated biological processes. This analysis was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (Kanehisa, 2000) with default parameters.

To investigate whether statins can directly inhibit specific kinases, we performed an initial screening using the SelectScreen™ Biochemical Profiling platform (Thermo Fisher Scientific), testing atorvastatin, cerivastatin, and simvastatin at a concentration of 1 µM. This screening covered 400 kinases, including both wild-type and cancer-associated mutants, using three fluorescence-based assay formats: LanthaScreen™, Adapta™, and Z′-LYTE™. The LanthaScreen™ assay detects kinase-mediated phosphorylation via a time-resolved fluorescence resonance energy transfer (TR-FRET) signal generated by a terbium-labeled antibody binding to a phosphorylated fluorescein-labeled substrate. The Adapta™ assay monitors ADP production by measuring the displacement of a labeled tracer from an antibody, with reduced TR-FRET signal indicating kinase activity and inhibitors preserving the signal by limiting ADP formation. The Z′-LYTE™ assay distinguishes phosphorylated from non-phosphorylated peptides based on their proteolytic susceptibility, with fluorescence changes reflecting kinase activity. Details on which assay was used for each kinase are provided in Supplementary Material S1. To validate the SelectScreen™ results with simvastatin, we used the scanMAX KINOMEscan^® platform (Eurofins Discovery), a high-throughput, site-directed competition binding assay that profiles over 500 kinase domain-containing human wild-type and mutant targets. Additionally, for a subset of kinases (ABL1, CAMK1G, CAMK2B, EGFR, ERBB2, ERK5, FLT3(ITD), MAP4K5, MET, PAK3, PIP5K1A, PIP5K2B, PRKCD, PRKD1, RIOK1, RIOK3, ROS1, SRC, SYK, TIE1, TSSK1B, and YANK3), binding affinities were further quantified using the KdELECT Binding LeadHunter Assay (Eurofins), which reports IC₅₀ concentration values.

Atorvastatin (TCI, A2476), simvastatin (Sigma-Aldrich, S6196), and cerivastatin (Sigma-Aldrich, SML0005) were used in this study. Prior to each experiment, all statins were dissolved in pure ethanol to prepare a 100 mM stock solution, which was subsequently diluted in the appropriate cell culture medium to reach the desired working concentration. Mevalonolactone was obtained from BLDpharm (BD2924).

The cell lines used in this study were obtained from the American Type Culture Collection (ATCC). CaCo-2 cells (HTB-37) were maintained in Dulbecco’s Modified Eagle Medium (DMEM, Gibco, 10566016) supplemented with 20% fetal bovine serum (FBS, Sigma, F9665) and 1% penicillin-streptomycin solution (Sigma, P0781). HCT116 cells (CCL-247) were cultured in McCoy’s 5A Medium (Gibco, 16600082) supplemented with 10% FBS and 1% penicillin-streptomycin solution. All cells were incubated at 37°C in a humidified atmosphere containing 5% CO₂.

Monocultures were established by seeding 10,000 cells in 100 µL of medium per well in 96-well plates (Thermo Fisher Scientific, 167008). After a 24-h pre-incubation period, cells were treated with atorvastatin or vehicle control (ethanol) according to a predefined plate layout.

The final ethanol concentration in the cell cultures was 0.1%. The plates were then incubated for 48 h under standard culture conditions (37°C, 95% humidity, 5% CO₂). Following treatment, cell viability was assessed using the MTT assay (Sigma-Aldrich, 475989) according to the manufacturer’s instructions. A minimum of three independent biological replicates was performed for each experimental group.

A total of 200,000 cells were seeded in 2 mL of culture medium per well in 6-well plates (Thermo Fisher, 145380). After a pre-incubation period of 24 h to allow cell adhesion, treatments were applied according to a predefined arrangement of the plates. Cells were exposed to statins alone, to statins combined with 200 µM mevalonolactone or to a control vehicle (ethanol). The final ethanol concentration in all cultures, including controls, was standardized to 0.1%. After treatment, cells were incubated for an additional 48 h before further analysis. Cells were harvested by scraping with a scalpel and lysed in RIPA buffer (Thermo Fisher, R0278) supplemented with a protease inhibitor cocktail (Roche, 11836170001) to extract total protein. Protein concentrations were determined using the Lowry method, and three biological replicates were prepared for each experimental condition. For each sample, 20 µg of total protein was loaded onto a mini-PROTEAN TGX gel (Bio-Rad, 4561094), separated by SDS-PAGE, and transferred onto a PVDF membrane (Invitrogen, IB24001) using the iBlot 2 system (Invitrogen). Membranes were blocked for 1 h at room temperature with 5% nonfat milk in PBS 1X, followed by overnight incubation at 4°C with primary antibodies diluted according to the manufacturer’s instructions. After three washes with PBST buffer (PBS +0.1% Tween-20), membranes were incubated for 1 h at room temperature with a goat anti-mouse secondary antibody (Invitrogen, 31430), followed by additional PBST washes. Membrane stripping was performed by incubating the blot in stripping buffer (1.5% glycine, 0.1% SDS, 1% Tween-20; pH 2.2) for 10 min at 37°C with constant agitation, followed by three washes with PBST buffer. After washing, the membrane was reblocked with 5% nonfat milk in PBS before reprobing. Actin (BD Biosciences, 612656) was used as a loading control and processed in parallel under the same conditions. The primary antibodies used were PI3K (Abbkine, Abp52199) and phosphorylated PI3K (Thr607) (Abbkine, Abp50495). Protein detection was performed using the SuperSignal West Pico PLUS chemiluminescent substrate (Thermo Fisher, 1863096), and bands were visualized with the Azure c400 imaging system (Azure Biosystems). Band intensities were quantified using Image Studio Lite software (LI-COR Biosciences). Expression levels were calculated as the phosphorylated PI3K/total PI3K ratio, and values were normalized to the control sample.

All statistical analyses and graph generation were performed using GraphPad Prism version 9 (GraphPad Software, La Jolla, CA, United States). The normality of the data was assessed using the Shapiro–Wilk test. For comparisons between multiple groups, one-way analysis of variance (ANOVA) followed by Tukey’s multiple comparisons test was applied. Differences were considered statistically significant at p ≤ 0.05.

To investigate the effects of statins on kinases, we performed analyses of RNA-seq data obtained from colorectal cancer organoids derived from AKP mice treated with atorvastatin or lovastatin. Focusing specifically on kinases, we found that only a small subset showed differential expression. Specifically, 8 kinases were differentially expressed in response to atorvastatin and 9 in response to lovastatin (Table 1). Atorvastatin resulted in upregulation of five kinases (PDK1, EGFR, ACVR1, EPHB3, MAP2K1) and downregulation of three (DCLK1, HCK, ERN2). In contrast, lovastatin downregulated all 9 differentially expressed kinases (MAP2K1, CDK6, TK1, EPHB2, AKT1, BMPR1A, EGFR, HCK, ACVR1). Interestingly, EGFR, ACVR1 and MAP2K1 were upregulated by atorvastatin but downregulated by lovastatin, highlighting that, despite sharing a common mechanism of action, these statins exert distinct transcriptional effects. HCK was the only kinase consistently downregulated by both statins.

Since kinase activity is mainly regulated through phosphorylation, we also analyzed phosphoproteomic data from HCT116 colorectal cancer cells treated with lovastatin or vehicle. Among the 90 kinases identified, 67 showed significant changes in phosphorylation (FDR ≤0.05). Among the 23 kinases that did not reach the FDR threshold of significance were PTK2B, EPHA4, TXK, FGR, VRK1, MYLK, ERBB3, SRC, MAP3K7, SGK3, CHUK, MAP3K11, MAP2K6, MAPK4, BTK, AXL, LIMK1, MAPK14 and PAK1. Consistently, 18 kinases showed increased phosphorylation at one or more sites following lovastatin treatment. These included FGFR1, BMX, EPHB1, TGFBR1, FGFR4, SGK2, MAP2K3, TBK1, PLK1, PRKAA2, DYRK1B, FES, NEK6, EIF2AK2, VAV2, SYK, PKN1, and PRKCQ. In contrast, 36 kinases exhibited significantly reduced phosphorylation levels at one or more sites after lovastatin exposure. This group included EGFR, PDPK1, RAF1, CSNK1E, CSNK2A1, AKT1, MAP2K1, ABL1, MTOR, LCK, ATM, IGF1R, PTK6, FLT3, LYN, MAPK12, STK6, GRK6, GSK3B, PHKG1, ALK, TEC, PAK2, TESK1, PRKAR2B, RPS6KA4, RPS6KA3, PDK1, PRKCA, PRKCZ, PRKCD, PRKD1, PRKDC, CDK16, CDK5, and CDK4. The remaining 13 kinases exhibited mixed phosphorylation responses to lovastatin treatment, with some phosphorylation sites showing increased phosphorylation and other sites showing decreased phosphorylation. These kinases included CHEK2, MKNK2, PDGFRB, ZAP70, AKT3, MET, MAP3K5, MAP3K11, PTK2, BRAF, CSK, TGFBR2, and KIT. Table 2 lists the kinases that showed significant phosphorylation along with detailed site information and corresponding FDR values.

Functional enrichment analysis of kinases with decreased phosphorylation following lovastatin treatment revealed significant involvement in several key signaling pathways, including insulin signaling (p adjusted [adj] = 4.396 × 10⁻⁸), EGFR signaling (p adj = 1.395 × 10⁻⁸), ERBB signaling (p adj = 2.303 × 10⁻⁸), FOXO signaling (p adj = 2.940 × 10⁻⁸), mTOR signaling (p adj = 4.396 × 10⁻⁸), PI3K/AKT signaling (p adj = 2.296 × 10⁻⁶), and PD-L1 expression and the PD-1 checkpoint pathway in cancer (p adj = 8.690 × 10⁻¹⁰) (Figure 1A). In contrast, kinases with increased phosphorylation did not show enrichment in any specific biological process.

Given previous reports indicating that simvastatin can inhibit kinases such as EGFR, ERBB2, MET, and SRC, we sought to investigate whether other kinases might also be directly inhibited by statins (Li et al., 2020). To address this, we solicited a kinome profiling assay using atorvastatin, simvastatin, and cerivastatin across a panel of 400 kinases, including those previously reported to be statin-sensitive. A starting concentration of 1 µM was selected, as it was considered sufficiently high to detect potential inhibitory effects on susceptible kinases. However, the results from this initial screen were negative for all tested kinases, with none showing more than 20% inhibition, including EGFR, HER2, MET, and SRC (Supplementary Material S1). To confirm these findings, a second kinome profiling assay for simvastatin was performed by a different provider under identical conditions. This second screen included an expanded panel of 500 kinases and yielded similar results, confirming the lack of inhibition for most kinases. Notably, two kinases, CAMK1G and TSSK1B, showed greater than 95% inhibition by simvastatin in this second assay. To further investigate, concentration-response curves were generated to determine the IC₅₀ values for these two kinases, along with a selected group of additional kinases (ABL1, CAMK1G, CAMK2B, EGFR, ERBB2, ERK5, FLT3(ITD), MAP4K5, MET, PAK3, PIP5K2B, PRKCD, PRKD1, RIOK1, ROS1, SRC, SYK, TIE1, TSSK1B, and YANK3). The IC₅₀ for CAMK1G was determined to be 8.9 µM (Figure 1B), while that for TSSK1B was 3.3 µM (Figure 1C). Concentration curves were also generated for EGFR (Figure 1D), ERBB2 (Figure 1E), MET (Figure 1F), and SRC (Figure 1G) to reconcile our findings with previously published data. However, no inhibition was observed for these kinases at any tested concentration, and thus, IC₅₀ values could not be determined, further supporting our conclusion that these kinases are not directly inhibited by simvastatin under the tested conditions.

Given that phosphoproteomic analysis revealed a decrease in PI3K phosphorylation following lovastatin treatment, we investigated whether a similar effect could be observed with atorvastatin, one of the most widely used statins globally and actively explored for cancer therapy. To begin, the citotoxic half-maximal inhibitory concentration (IC₅₀) of atorvastatin was determined in two colorectal cancer cell lines, HCT116 and CaCo2 (Figure 2A). The calculated IC₅₀ was 80.89 µM for HCT116 cells and 28.97 µM for CaCo2 cells. These concentrations were subsequently used for all downstream experiments. Atorvastatin treatment led to a significant reduction in PI3K phosphorylation in both cell lines (Figures 2B,C), confirming results previously observed with lovastatin. Since statins inhibit HMGCR, thereby blocking the conversion of HMG-CoA to mevalonate, we hypothesized that the observed reduction in PI3K phosphorylation could be attributed to mevalonate depletion. To test this, rescue experiments were performed by supplementing atorvastatin-treated cells with 200 µM mevalonolactone. This intervention restored PI3K phosphorylation to near-control levels in HCT116 cells and to approximately 60% in CaCo2 cells (Figures 2B,C). These results suggest that the decrease in PI3K phosphorylation is largely driven by mevalonate depletion resulting from atorvastatin-mediated HMGCR inhibition, although other mechanisms may be involved.