Repurposing pitavastatin and atorvastatin to overcome chemoresistance of metastatic colorectal cancer under high glucose conditions

doi:10.21203/rs.3.rs-4218809/v1

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Research Article

Repurposing pitavastatin and atorvastatin to overcome chemoresistance of metastatic colorectal cancer under high glucose conditions

https://doi.org/10.21203/rs.3.rs-4218809/v1

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Background

Colorectal cancer (CRC) poses a significant clinical challenge because of drug resistance, which can adversely impact patient outcomes. Recent research has shown that abnormalities within the tumor microenvironment, especially hyperglycemia, play a crucial role in promoting metastasis and chemoresistance, and thereby determine the overall prognosis of patients with advanced CRC.

Methods

This study employs data mining and consensus molecular subtype (CMS) techniques to identify potential drugs for targeting high glucose-induced drug resistance in advanced CRC cells. CRC cells maintained in low or high glucose conditions were established and were used to evaluate the cytotoxic effects of potential drugs with or without 5-FU. CRC 3D spheroids cultured were also included to demonstrate the anti-drug resistance of these potential drugs.

Results

A bioinformatics analysis identified pitavastatin and atorvastatin as promising drug candidates. We established the CMS4 CRC cell line SW480 (SW480-HG) cultured under high glucose conditions to simulate hyperglycemia-induced drug resistance and metastasis in CRC patients. We showed that both pitavastatin and atorvastatin can effectively inhibit cell proliferation and 3D spheroid formation of CMS4 CRC cells under high glucose conditions. In addition, both pitavastatin and atorvastatin can synergistically promote the 5-FU-mediated cytotoxic effect and inhibit the growth of 5-FU-resistant CRC cells. Mechanistically, pitavastatin and atorvastatin can induce apoptosis and synergistically promote the 5-FU-mediated cytotoxic effect by activating autophagy, as well as the PERK/ATF4/CHOP signaling pathway while decreasing YAP expression.

Conclusion

This study highlights the biomarker-guided precision medicine strategy for drug repurposing. We showcase pitavastatin and atorvastatin with the moonlighting role for treating advanced CRC, particularly with CMS4 subtype CRC patients who also suffer from hyperglycemia. Pitavastatin, with an achievable dosage used for clinical interventions, is highly recommended for a novel CRC therapeutic strategy.

Colorectal cancer

hyperglycemia

drug resistance

consensus molecular subtype

pitavastatin

atorvastatin

Colorectal cancer (CRC) ranks as the fourth most common cancer and is the leading global cause of cancer-related death [1]. Despite the introduction of nationwide screening programs and higher rates of colonoscopy assessments, which have stabilized CRC incidence in developed countries, there has been a noticeable increase in CRC cases among individuals younger than 50 years, especially for rectal cancer and left-sided colon cancers [2, 3]. The standard treatment for advanced CRC involves 5-fluorouracil (5-FU) and oxaliplatin-based chemotherapy [4]. However, chemotherapy resistance remains a significant challenge for CRC treatment, with a five-year survival rate for stage IV cancer of only 12% [5]. Furthermore, the microenvironment that surrounds cancer cells plays a crucial role in shaping responses to drug treatments. Diabetes mellitus (DM) is one of the most prevalent comorbidities for CRC patients and has been identified as an independent risk factor. Approximately one in eleven adults is estimated to have DM [6], and epidemiological studies have indicated that both DM and prediabetes are linked to an increased risk of developing CRC [7–9]. DM and CRC share several common risk factors, including advanced age, obesity, physical inactivity, and smoking. Notably, hyperglycemia, a prominent biological characteristic of DM, is known to induce the upregulation of insulin and insulin-like growth factors, thereby promoting cancer cell metastasis and chemoresistance, which impacts the overall prognosis of CRC patients [10].

Currently, CRC is no longer categorized as a single disease entity due to the presence of various genetic alterations that are correlated with different responses to standard treatments. At present, it is understood that treatments should be targeted according to a sophisticated CRC classification based on molecular features [11]. The consensus molecular subtype (CMS) of CRC was proposed in 2015 to resolve inconsistencies among different gene expression-based classification systems, and this resulted in CRC cases being predominantly classified into four distinct CMS groups [12]. To capture CMS characteristics within specific settings, Sveen et al. developed a CMS classifier for CRC cells. Tests of this classifier found that its concordance ranged from 85–92%, indicating robust performance. A template, which contains distinct gene expression profiles for each CMS group, is publicly available in the R package CMScaller [13]. Among the four CMS groups, patients with CMS4 were found to exhibit the worst overall and relapse-free survival rates, as well as high levels of stromal infiltration, angiogenesis, and invasiveness [14]. Moreover, CMS4 accounts for 26% of all early-stage CRC cases at diagnosis, and the ratio increases to 40% in stage IV disease [15]. Overall, CMS4 CRC tumors exhibit a limited response to standard treatments, highlighting the urgent need to explore alternative therapeutic strategies. Given that considering both genetic and environmental factors is crucial in this endeavor, there is an unmet clinical need for new drugs capable of targeting metastatic CMS4 CRC tumors.

Statins, 3-hydroxy-3-methylglutaryl coenzyme-A (HMG-CoA) reductase inhibitors, which are commonly known as cholesterol-lowering drugs, have garnered significant recent attention due to the potential roles they may play beyond lipid regulation [16]. For example, recent evidence suggests that statins may possess anticancer properties since they influence various aspects of cancer development and progression. Although originally developed for managing cardiovascular diseases by inhibiting 3-hydroxy-3-methylglutaryl-coenzyme-A reductase (HMGCR), the key enzyme in the mevalonate pathway, statins have also been found to modulate cellular processes crucial for tumorigenesis [17]. The anticancer effects of statins are mediated by multiple mechanisms, including cell cycle blockades, the induction of apoptosis, anti-inflammatory effects, and metastasis inhibition [18]. Accumulated studies over the past decade have consistently demonstrated the beneficial impact of statins on clinical outcomes for various cancers, including colorectal, gastric, breast, lung, liver, and kidney cancers [19, 20]. However, despite promising preclinical and epidemiological data, conflicting results regarding the potential anticancer effects of statins have emerged from both clinical and observational studies, primarily due to variations in cohort diversity and follow-up study design [21–23]. Translating the anticancer properties of statins into clinical practice continues to face multiple challenges, thus underscoring the need for further elucidation of optimal dosing regimens, patient selection criteria, and the potential for adverse effects. Therefore, assessing the subtype-specific effects of statins for preventing and treating cancer within specific populations can help position them as compelling candidates for cancer treatment and prevention.

In this study, our results showed that pitavastatin and atorvastatin could induce apoptosis and effectively reverse 5-FU resistance under high glucose conditions in the CMS4 cells. These results hold significant promise and may serve as a guide for future clinical trials aimed at repurposing pitavastatin and atorvastatin for the treatment of CRC patients with the metastatic CMS4 group, particularly those suffering from hyperglycemia.

Dependency Map (DepMap) portal

The DepMap portal (https://depmap.org/portal/) [24] serves as a comprehensive repository for multiomics databases since it incorporates datasets from the Profiling Relative Inhibition Simultaneously in Mixtures (PRISM) and Cancer Cell Line Encyclopedia (CCLE) databases. The PRISM database contains drug sensitivity screening data for 4,686 compounds found in 750 cells. An overall PRISM score reflects the drug sensitivity of each compound in each cell in the PRISM database and is expressed as the log₂ fold change in the proliferation rates of treated and untreated cells. It is a powerful tool for exploring the potential of repurposing non-oncology drugs for cancer treatment. Overall, these publicly accessible datasets facilitate rigorous bioinformatic and statistical analysis. We conducted Mann-Whitney U tests to systematically investigate non-oncological compounds and assess their potential for targeting metastatic and CMS4 CRC cells.

Predicting the mechanism of action of statins through CLUE database

Connectivity scores and differentially expressed gene (DEG) data can be accessed from CLUE (https://clue.io/) to investigate the mechanisms of action of pitavastatin and atorvastatin. Connectivity scores quantify the degree of similarity between compound spectra or genetic perturbation spectra using pattern-matching algorithms. This information is valuable as it may offer initial insights into the biological effects of statins. The DEGs identified were then analyzed using ConsensusPathDB (CPDB, http://cpdb.molgen.mpg.de/) to further reveal which specific pathways are affected by statins.

Cell culture

The human CRC cell line SW480-vehicle (i.e., Vector alone control) and SW480-ATG5 KO (i.e., an ATG5 knockout) cells were acquired from Professor Hsiao-Sheng Liu's laboratory at Kaohsiung Medical University, Kaohsiung, Taiwan. The DLD-1 cell, with and without resistance to the chemotherapeutic drug 5-FU (referred to as DLD-1 and DLD-1R, respectively), was obtained from Professor Yi-Shiou Chiou's laboratory at Kaohsiung Medical University, Kaohsiung, Taiwan. The SW480 cells were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) under two glucose conditions: 5 mM (Gibco, cat. 12100046) and 25 mM (Gibco, cat. 31600034), resulting in low glucose-adapted SW480 (SW480-LG) and high glucose-adapted SW480 (SW480-HG) cells, respectively. The culture medium with 5 mM glucose mimics the normal physiological level of glucose in human serum (100 mg/dL), while the medium with 25 mM glucose simulates the serum of patients with severe diabetic hyperglycemia. The SW480-vehicle and SW480-ATG5 KO cells were maintained in DMEM with 5 mM glucose condition. DLD-1 and DLD-1R cells were cultured in Roswell Park Memorial Institute (RPMI) 1640 Medium. DLD-1R cells were maintained in RPMI with 20 µM of 5-FU. Before experimentation, resistant cells were rested with RPMI without adding 5-FU for at least two weeks. All media were supplemented with 10% fetal bovine serum (FBS, HyClone) and 1% antibiotic-antimycotic solution (Penicillin, streptomycin, and amphotericin B Solution) (Biological Industries). The cells were cultured in a 37°C incubator containing 5% CO₂ and passaged using 0.5% Trypsin EDTA Solution C (Biological Industries) every 3 days.

Cell viability assay

The cell viability assay refers to the previously reported method [25]. SW480-LG, SW480-HG, DLD-1, and DLD-1R cells were seeded at a density of 3,000 cells per well (96-well plate), and tested drugs were added after seeding. After 24 to 72 hours of treatment, living cells were fixed with 10% trichloroacetic acid (TCA, Sigma, cat. SI-T6399-250G) for 1 hour. The cells were then stained with 0.4% Sulforhodamine B (SRB) sodium salt dye (Sigma, cat. S1402) for 1 hour and washed with 1% acetic acid (J.T baker, cat. JT-9508-03) to remove the unstained dye. After three times wash, 10 mM Tris-base (Amresco, cat. CPT-0826) solution was added to solubilize the protein-bound dye, and the optical density was measured at 510 nm with a multimode microplate reader (Infinite 200 PRO). Pitavastatin (HY-B0144) and atorvastatin (HY-B0589) were purchased from Master of Bioactive Molecules (MedChem Express, USA).

Migration assay

The migration assay refers to the previously reported method [26]. In brief, SW480-LG and SW480-HG cells were seeded at a density of 2 × 10⁵ cells/well in the upper chambers and were incubated with serum-free medium, while medium with 10% FBS as attractants were added in the lower chambers. Tested drugs were added in both upper and lower chambers and incubated at 37°C. After 24 hours of incubation, the non-migrating cells on the upper side of the membrane were removed with a cotton bud, and the migrated cells in the lower chamber were fixed with a 4% formaldehyde solution and stained with crystal violet. The areas of stained cells were measured with Image J software.

Western blotting

CRC cells were seeded at a density of 5 × 10⁵ in a 6 cm dish. Following treatment with pitavastatin (1.25, 2.5, 5 µM) and atorvastatin (2.5, 5, 10 µM) for 48 hours, the cell lysates were analyzed by Western blotting referring to the previously reported method [27]. The primary antibodies ATG5, p62, LC3B, PERK, p-PERK (T982), ATF4, CHOP, cleaved-Caspase3, cleaved PARP, Bax, p-YAP (S127), Snail, IRS1, ZO-1, YAP-1 antibodies were used for detection, and GAPDH was used as the internal control. The signaling from secondary antibodies was detected by adding horseradish peroxidase (HRP) substrate peroxide solution/luminol reagents (ImmobilonTM Western Chemiluminescent Substrate, Millipore; mixed at a 1:1 ratio) and detected using a chemiluminescence system (Fuji LAS-4000 Fujifilm). The images were analyzed with Image J software. Additional information for antibodies is shown in Additional File 1: Table S1.

Colony formation assay

The colony formation assay was based on the previously reported method [28]. SW480-LG and SW480-HG cells were seeded at a density of 500 cells per well in a 6-well plate. The tested drugs were added the day after seeding, and the media with fresh drugs was changed every three days. After 9 days, the cells were stained with crystal violet for 1 hour to visualize single colonies. The cells were washed with phosphate-buffered saline (PBS) (Amresco, cat. K813-500ML) and fixed with 4% formaldehyde solution (Sigma, cat. 252549) for 15 minutes. The residual crystal violet dye was removed by rinsing with tap water. One colony was defined as containing more than 20 cells, and the numbers of the colonies were counted with Image J software.

Synergistic effect analysis

Synergistic effect analysis was performed as per a previously reported method [29]. Briefly, cells received coadministration of 5-FU with pitavastatin/atorvastatin and were incubated in a 96-well plate for 48 hours, after which cell viability was determined by SRB assay. Next, we used CompuSyn software (http://www.combosyn.com/) to assess the synergistic effect of 5-FU and pitavastatin/atorvastatin in inducing cytotoxic death in SW480 cells; this procedure followed a previously described method [30, 31]. The combination index (CI) defines synergism (CI < 1), an additive effect (CI = 1), and antagonism (CI > 1).

3D spheroid cultured assays

SW480-LG and SW480-HG cells were each seeded at a density of 1,000 cells per 50 µL of the kit gel mixture according to the manual instructions of the ACD 3D culture kit (GEcoll Biomedical Co., Ltd., Taiwan) [32]. Next, 50 µL of the resulting cell-gel mixture was applied to a 24-well plate. After a 5-minute reaction on ice and a subsequent 15-minute reaction with a specialized buffer that facilitates gel cross-linking, the gel becomes both stable and flexible. Finally, after a 7-day incubation period to facilitate tumor formation, pitavastatin and atorvastatin were added for an additional seven days. For DLD-1 and DLD-1R cells, cells were seeded at a density of 1,000 cells per well onto the R³CE 24-Well 3D culture Plate (Acrocyte Therapeutics Inc. Taiwan) [33]. Once again, after a 7-day incubation period to facilitate tumoroid formation, pitavastatin and atorvastatin were added for an additional 7 days.

Immunofluorescence (IF) staining and confocal microscopy

For IF staining, spheroids were first fixed with 4% formaldehyde for 1 hour and then washed twice with PBS at room temperature. Fixed spheroids were then blocked with 3% bovine serum albumin (BSA) at 4°C overnight before being stained with CD44 (i.e., Alexa Fluor™ 488), YAP1 (labeled with Alexa Fluor™ 488), Alexa Fluor™ 568 Phalloidin, and Hoechst 33342. IF staining images were then obtained using a Zeiss LSM900 confocal microscope at a magnification of 400X.

Statistical analysis

Mann-Whitney U tests were used to evaluate the statistical significance of differences in the mean sensitivity to compounds listed in the PRISM database on primary and metastatic cancer, as well as on CMS4 and other CMS cells. Subsequent statistical analyses were conducted using Student’s t-tests. All statistical analysis results are presented as mean ± standard error of the mean (SEM), and statistical significance is represented using different symbols. Specifically, the number of symbols corresponds to the significance level: one symbol indicates p < 0.05, two symbols indicate p < 0.01, and three symbols indicate p < 0.001. All experiments were repeated at least three times.

Pitavastatin and atorvastatin are identified as putative treatments for metastatic CMS4 CRC

The discordance observed among various gene expression-based classification systems can lead to inconsistent outcomes for clinical CRC trials, and we therefore postulated that a more nuanced classification of CRC based on gene expression profiles could yield valuable insight. As illustrated in the flowchart (Fig. 1A), we accelerated pharmacogenetic pairing for this study. This was achieved by making use of comprehensive gene expression and drug susceptibility data accessible through the DepMap portal [24], which functions as a repository for cellular multiomics datasets. We then used the PRISM database [34] to conduct high-throughput screening of drugs that may be suitable for repurposing. Additionally, we compared the sensitivity of primary and metastatic CRC cells. Furthermore, we subdivided these cells into four CMS groups based on the results of analysis conducted using the CMS caller R package [14]. This refined CMS classification of cells plays a crucial role in effectively stratifying drugs. This extensive screening process led to the identification of a subset of the drugs that may have specific inhibitory effects on CMS4 and metastatic CRC cells among all those found in the database. Our results demonstrate that seven compounds highlighted in the red bar at the intersection, namely SU-11274, DMNB, eltanolone, atorvastatin, cefixime, pitavastatin, and bivalirudin, exhibited effectiveness against both CMS4 and metastatic cells (Fig. 1B). However, further screening revealed that only four drugs, including atorvastatin, cefixime, pitavastatin, and bivalirudin, have been approved by the U.S. Food and Drug Administration (FDA) for safe drug repurposing (Fig. 1C). Next, we further investigated the sensitivity of other statin drugs, including lovastatin, simvastatin, and mevastatin, in both primary and metastatic cells. Additionally, we evaluated the sensitivity of these drugs in different CMS CRC groups. These results identified only two statins, i.e., pitavastatin and atorvastatin, that could affect both CMS4 and metastatic CRC cells (Fig. 1D-E and Additional File 2: Table S2). We also queried the PRISM database regarding the effects of metformin, the most used antidiabetic drug, on CMS4 and metastasis CRC cells; however, metformin failed to show any specific anti-CMS4 (Additional File 3: Figure S1A) or anti-metastasis cytotoxicity (Additional File 3: Figure S1B). Taken together, these results indicate that pitavastatin and atorvastatin are potential candidates for repurposing to treat metastatic CMS4 CRC cells.

Currently, 5-FU-based chemotherapy remains the most common treatment for patients with metastatic CRC [35]. However, the response rate of 5-FU in combination with other anticancer drugs is only 40%-50% due to chemoresistance [36]. Moreover, the presence of hyperglycemia further increases the resistance of metastatic CRC to 5-FU [37]. Therefore, the development of strategies to overcome 5-FU resistance in metastatic CRC remains urgent, especially for patients impacted by hyperglycemia. Since statins are commonly used drugs for patients with diabetes, we examined the effects of specific statins, such as pitavastatin and atorvastatin, on 5-FU resistance under different glucose conditions. Initially, sensitivity data for 5-FU (0.002 µM), pitavastatin (2.5 µM), and atorvastatin (2.5 µM) treatment of CMS4 CRC cells were extracted from the PRISM database to assess candidate cells (Fig. 1F). The results indicated that SNUC2A, SW480, and OUMS23 cells were sensitive to pitavastatin and atorvastatin, indicating these two statin drugs might have the potential to overcome 5-FU resistance. Moreover, the SW480 cells exhibited the highest sensitivity to pitavastatin and atorvastatin. Consequently, the SW480 cells were selected for subsequent experiments.

Pitavastatin and atorvastatin can overcome high glucose-induced drug resistance and synergistically promote 5-FU-mediated cytotoxicity

Existing evidence shows that hyperglycemia has a substantial impact on the incidence, chemotherapy resistance, and prognosis of CRC, as well as on the outcomes of both localized and metastatic CRC patients [38]. To further examine this phenomenon, we sought to replicate the hyperglycemic microenvironment in vitro. To do so, the SW480 cells were first cultured under normoglycemic conditions (i.e., low glucose medium) that mirrored the normal physiological glucose levels found in human serum to generate SW480-LG cells. In parallel, we also cultured SW480 cells under hyperglycemic conditions (i.e., high glucose medium), thereby approximating the serum glucose levels observed in patients with severe diabetic hyperglycemia, to generate SW480-HG cells (Additional File 3: Figure S2). Subsequent Western blotting analysis revealed that SW480-HG cells exhibited altered expression of the glucose metabolism-related marker IRS1 and Yes-associated protein (YAP1) (Additional File 3: Figure S3A-S3B). YAP1 has been implicated in enhancing tolerance to ER stress, thereby facilitating evasion of apoptosis [39]. Additionally, the expression of Snail was up-regulated under high-glucose conditions, indicating an increased metastatic potential in response to high glucose levels (Additional File 3: Figure S3C).

Consistent with predictions from the PRISM Database, SW480-LG cells demonstrated greater sensitivity to pitavastatin, and atorvastatin as compared to 5-FU. However, under high glucose conditions, SW480-HG cells exhibited resistance to 5-FU while retaining sensitivity to both pitavastatin and atorvastatin, even after 72 hours of treatment (Table 1 and Additional File 3: Figure S4A-S4C). This phenomenon was also evident by colony formation assays, in which SW480-HG cells showed higher resistance to 5-FU (Fig. 2A and Additional File 3: Figure S5A) but retained sensitivity to increasing doses of pitavastatin and atorvastatin (Fig. 2B-C and Additional File 3: Figure S5B-S5C). However, pitavastatin and atorvastatin were unable to inhibit the viability of HT29 cells, which were identified as CMS3 CRC cells, raising the possibility that the cytotoxic effects of pitavastatin and atorvastatin might be influenced by the genetic background of specific cells (Additional File 3: Figure S6A-S6B and Additional File 4: Table S3). Further investigation into the cytotoxicity of lovastatin, a recognized CMS4-targeting drug, we found although lovastatin could gradually inhibit the growth of SW480-LG cells, it did not impede the viability of SW480-HG cells, which further evidenced that pitavastatin and atorvastatin have the potential to overcome hyperglycemia-mediated drug resistance (Additional File 3: Figure S7A-S7C and Additional File 5: Table S4).

We further conducted SRB assays to assess whether pitavastatin and atorvastatin could enhance the cytotoxicity of chemotherapeutic agents, such as 5-FU. Co-treatment of 5-FU with either pitavastatin or atorvastatin at constant ratios (i.e., 1:1 and 1:2) was performed to analyze the drug combination effects. Additionally, we calculated the combination index (CI) to assess the synergy between the drugs. The synergistic cytotoxic effects in combinations of 5-FU and pitavastatin (Fig. 2D) or 5-FU and atorvastatin (Fig. 2E) in both SW480-LG and -HG cells, were evidenced by CI values of less than 1 (Fig. 2D-E). Further colony formation assays yielded similar results. Thus, compared to 5-FU treatment alone, combined treatment of 5-FU plus pitavastatin (Fig. 2F and Additional File 3: Figure S8A) or 5-FU plus atorvastatin (Fig. 2G and Additional File 3: Figure S8B) further decreased colony formation in both SW480-LG and -HG cells.

Although SW480-HG cells exhibited resistance to 5-FU (1.25 µM) compared to SW480-LG cells, the addition of different doses of pitavastatin (0.63 or 1.25 µM) or atorvastatin (1.25 or 2.5 µM) restored the cytotoxicity of 5-FU (Fig. 2F-G and Additional File 3: Figure S8A-S8B). These observations align with our bioinformatics predictions and further suggest that pitavastatin and atorvastatin can effectively overcome 5-FU resistance induced by high glucose conditions.

Table 1

Summary of IC₅₀ values for 5-FU, pitavastatin, and atorvastatin in SW480-LG and SW480-HG cells. Data represent the mean ± SEM (N = 3). (*** p < 0.001 vs. SW480-LG cells)
Drug		5-FU (µM)		Pitavastatin (µM)		Atorvastatin (µM)
Cell		SW480-LG	SW480-HG	SW480-LG	SW480-HG	SW480-LG	SW480-HG
Time	24 hours	> 20	> 20	6.3 ± 2.7	> 10	> 10	> 10
	48 hours	> 20	> 20	1.8 ± 0.9	3.5 ± 1.0	4.7 ± 1.5	9.1 ± 2.3
	72 hours	8.6 ± 2.0	18.1 ± 3.2^***	0.4 ± 0.2	0.6 ± 0.2	1.6 ± 0.3	3.3 ± 0.9

Pitavastatin and atorvastatin can inhibit the migration ability and spheroid formation stimulated by high glucose

To investigate the impact of pitavastatin and atorvastatin on high glucose-stimulated migration ability, we performed a Transwell assay. As anticipated, SW480-HG cells demonstrated increased migration ability compared to SW480-LG cells, indicating that SW480-HG cells exhibit metastatic behavior under high glucose conditions (Fig. 3A). However, both pitavastatin and atorvastatin could still inhibit cell migration under high glucose conditions (Fig. 3A). Interestingly, we further observed through Western blotting that both pitavastatin and atorvastatin treatment reduced ZO-1 and Snail protein levels under both low- and high-glucose conditions (Fig. 3B). Collectively, these findings underscore the potential of pitavastatin and atorvastatin to suppress potentiated metastatic regulation under high glucose conditions.

The emergence of 5-FU chemotherapy resistance induced by hyperglycemia presents a significant obstacle to treat CRC patients [40]. To better replicate the physiological conditions of tissues in vivo and gain deeper insights into cellular processes such as proliferation, differentiation, and drug response, we subsequently evaluated the potential efficacy of pitavastatin and atorvastatin using a 3D spheroid cultured assay. To do so, we treated SW480-LG and SW480-HG cells with 5-FU, pitavastatin, and atorvastatin, respectively. Our results showed that SW480-HG cells displayed a greater inclination for spheroid formation than SW480-LG cells (Fig. 3D vs. 3C, upper panel). Additionally, prolonged (i.e., 7 days) administration of pitavastatin and atorvastatin significantly reduced spheroid cell viability in both SW480-LG and SW480-HG cells when compared with 5-FU control treatment (Fig. 3E-G). Subsequently, we investigated the cytotoxic effects of 5-FU in combination with pitavastatin or atorvastatin in SW480-HG cells and observed that the combined treatment also further influenced spheroid formation (Additional File 3: Figure S9). Consequently, pitavastatin and atorvastatin were shown to restore sensitivity to 5-FU and alter spheroid formation, potentially impacting tumor growth and metastasis in vivo.

Pitavastatin and atorvastatin affect intrinsic 5-FU resistance in CRC cells

Next, we investigated the potential impact of pitavastatin and atorvastatin on intrinsic 5-FU-resistant DLD-1R cells. These cells differ in that DLD-1R cells exhibit greater resistance to 5-FU than DLD-1 cells (Table 2 & Additional File 1: Figure S10A). Although initial resistance to pitavastatin and atorvastatin was observed 24 hours after treatment, these cells exhibited sensitivity at 48 and 72 hours, particularly to pitavastatin (Table 2 & Additional File 1: Figure S10B-S10C). Similarly, we observed comparable results in the colony formation assay, where DLD-1R cells demonstrated greater resistance to 5-FU than DLD-1 cells (Fig. 4A & Additional File 1: Figure S11A). We found that both DLD-1 and DLD-1R cells retained sensitivity to pitavastatin and atorvastatin in a dosage-dependent manner (Fig. 4B-C & Additional File 1: Figure S11B-S11C). Since there is increasing evidence of a link between 5-FU resistance and cancer stemness, i.e., a subpopulation of cells within tumors characterized by self-renewal and tumor-initiating properties [41, 42]. We therefore also used a 3D spheroid formation assay to examine the effects of pitavastatin and atorvastatin on the intrinsic 5-FU resistance of CRC cells. In the Cyto3D™ live-death experiment, we observed that the combined treatment of 5-FU with pitavastatin or atorvastatin increased the DLD-1 spheroid death (Red signal) (Fig. 4D). We further found that DLD-1R cells exhibited greater spheroid formation than DLD-1 cells (Fig. 4E vs. 4F, upper panel). Furthermore, pitavastatin and atorvastatin had a more pronounced effect on spheroid size than the 5-FU treatment alone, which was accompanied by cell fragmentation, cell volume reduction, and irregular cell edges (Fig. 4E-F). Additionally, in the spheroid cell viability assay, it was observed that compared to treatment with 5-FU alone, pitavastatin and atorvastatin significantly reduced the survival rate of DLD-1R cells (Fig. 4G-I). Interestingly, we found both pitavastatin and atorvastatin effectively downregulated the expression of cancer stem-like cell marker, such as CD44 in DLD-1 and DLD-1R spheroid cells, with pitavastatin treatment showing particularly notable suppression (Fig. 4J-K). Taken together, these findings suggest that targeting CD44 expression in CRC cells, particularly those intrinsically resistant to 5-FU, can disrupt spheroid formation, thereby offering a promising therapeutic strategy for treating intrinsic 5-FU-resistant CRC cells.

Table 2

Summary of IC₅₀ values for doses of 5-FU, pitavastatin, and atorvastatin in DLD-1 and DLD-1R cells. Data represent the mean ± SEM (N = 3). (*** p < 0.001 vs. DLD-1R cells)
Drug		5-FU (µM)		Pitavastatin (µM)		Atorvastatin (µM)
Cell		DLD-1	DLD-1R	DLD-1	DLD-1R	DLD-1	DLD-1R
Time	24 hours	> 20	> 20	> 10	> 10	> 10	> 10
	48 hours	4.1 ± 0.8	> 20	6.3 ± 3.2	5.8 ± 3.7	8.1 ± 2.4	7.3 ± 1.5
	72 hours	1.8 ± 0.8	> 20^***	3.7 ± 0.7	3.1 ± 0.5	5.4 ± 0.5	5.5 ± 0.7

Underlying mechanisms driving the effects of pitavastatin and atorvastatin on CRC cells

To attain a comprehensive understanding of the pathway alterations involved in CRC, we extracted differentially expressed gene (DEG) signatures for pitavastatin or atorvastatin-treated CRC cells from the CLUE database. Subsequently, we utilized ConsensusPathDB (CPDB) to predict the specific pathways involved in pitavastatin or atorvastatin-triggered events. Pitavastatin and atorvastatin show similar mechanisms of action and both impact on CRC development (Fig. 5A-B). In addition, pitavastatin and atorvastatin also affect apoptosis, autophagy, the TGF-β signaling pathway, hippo signaling, epithelial-mesenchymal transition (EMT), and so on (Summarized in Additional File 6: Table S5).

Autophagy plays a pivotal role in promoting cancer cell death by inducing the degradation and recycling of cellular components, which ultimately leads to cell death [43]. Moreover, there is compelling evidence indicating that statins exert a cytotoxic effect on cancer cells by augmenting the formation of autophagosomes, which consequently triggers apoptosis [44]. Our results revealed that treatment with pitavastatin and atorvastatin significantly increased the expression of autophagy-related markers, including p62 and LC3B II, indicating the modulation of autophagy (Fig. 5C). Furthermore, the mechanism through which statins induce ER stress and activate UPR leading to cell death requires further elucidation [45]. There are differing perspectives on how YAP regulates ER stress, and the relationship between YAP and UPR is complex. YAP plays a crucial role in UPR activity and ER expansion to relieve ER stress, and the PERK kinase-eIF2α axis is associated with YAP activation during the adaptation phase of the UPR. However, prolonged ER stress-induced Hippo signaling triggers a negative feedback loop involving the assembly of the GADD34/PP1 complex, thereby inhibiting YAP, and promoting apoptosis [39]. Our results demonstrated that treatment with pitavastatin and atorvastatin significantly increased the expression of p-PERK, PERK, ATF4, and CHOP in both SW480-LG and -HG cells. In addition, YAP1 expression was reduced, whereas the phosphorylated-YAP level was increased, potentially promoting apoptosis (Fig. 5C). Again, our IF results also found that treatment with pitavastatin and atorvastatin resulted in reduced YAP1 expression in DLD-1R cells (Additional File 1: Figure S12). Moreover, the observable upregulation of apoptosis-related markers—including cleaved PARP and Bax, as well as cleaved Caspase-3—in response to pitavastatin and atorvastatin treatment, which subsequently led to apoptosis in both SW480-LG and -HG cells (Fig. 5D). Taken together, our experimental results indicated that pitavastatin or atorvastatin treatment may impair autophagy flux, trigger ER stress and activation of the PERK/ATF4/CHOP signaling pathway, as well as modulation of YAP1 expression, and therefore to the induction of apoptosis.

Pitavastatin and atorvastatin induce apoptosis partly by stimulating autophagy and inducing ER stress

To further elucidate the underlying mechanism responsible for pitavastatin and atorvastatin-induced apoptosis, we employed the PI3K inhibitor 3-MA (an early autophagy inhibitor) (Fig. 6A), ATG5 KO SW480 cells (autophagy-deficient cells) (Fig. 6B), and the selective PERK inhibitor GSK2606414 (Fig. 6C). We observed that co-treatment with 3-MA could reduce pitavastatin- and atorvastatin-induced LC3B II expression and PERK/ATF4/CHOP protein levels, indicating these statins can induce autophagy and further affect ER stress/UPR signaling (Fig. 6A). Pitavastatin and atorvastatin treatment also induced the expression of PERK/ATF4/CHOP in parental SW480 cells, while it was slightly decreased in ATG5 KO SW480 cells, again indicating these statins can induce an autophagy-dependent ER stress/UPR signaling (Fig. 6B). Although the co-treatment with 3-MA did not inhibit pitavastatin or atorvastatin-induced cleaved PARP and cleaved caspase 3, their slightly decrease in ATG5 KO cells may indicate the partial role of autophagy in pitavastatin- or atorvastatin-induced apoptosis. Next, we found that co-treatment with GSK2606414 slightly affected pitavastatin- and atorvastatin-induced LC3B II expression in SW480-LG and SW480-HG cells, while significantly inhibiting the expression of ER stress/UPR markers such as ATF4 and CHOP (Fig. 6C). Downregulation of ATF4 and CHOP appeared to slightly inhibit the apoptosis of SW480-LG cells, while significantly inhibiting the apoptosis of SW480-HG cells, as evidenced by the reduction of cleaved PARP. Additionally, we observed upregulation of YAP1 in GSK2606414 co-treated cells (Fig. 6C), thereby endowing the cells with anti-apoptotic potential. Taken together, these results indicated that ER stress/UPR signaling plays a role in pitavastatin and atorvastatin-induced apoptosis, particularly under high glucose conditions.

By using data mining techniques and CMS classification, this study identified pitavastatin and atorvastatin as potential anti-CMS4 as well as anti-metastasis CRC drugs. As expected, pitavastatin and atorvastatin not only can inhibit the survival and metastatic potential of CMS4 cells but also can influence 5-FU-resistant cells and spheroid formation, particularly under high glucose conditions. Pitavastatin and atorvastatin treatment modulated autophagy and followed ER stress/UPR signaling, which may ultimately lead to apoptosis or other forms of cell death in CRC cells. Additionally, both pitavastatin and atorvastatin decreased the expression of YAP1, contributing to cell apoptosis. Consequently, we provide evidence to repurpose pitavastatin and atorvastatin, which originally served as primary lipid-lowering drugs, for treating patients with metastatic CRC, which may also benefit patients suffering from hyperglycemia.

Examining gene expression data sourced from large drug sensitivity databases can be used to provide information on drug repurposing strategies to combat specific forms of cancer. These databases have been widely used to explore how genetic alterations in cancer cells affect their response to drugs. However, varying degrees of genomic heterogeneity exist among cells, even among those of the same cancer type. It is therefore difficult to identify possible drug candidates that depend only on single mutant genes. However, by incorporating a more comprehensive classification of molecular paradigms for each cancer type in the search phase (e.g., CMS in CRC), we may be able to predict which drugs efficiently and precisely can be repurposed for target-based cancer treatment.

The CMS procedure helps to integrate gene expression-based classifications of CRC to facilitate clinical translation [12]. CMS has been proven to be a prognostic factor and has been gradually applied in numerous clinical trials [15]. In this study, we focused on CMS4 CRC since it is a common form of advanced-stage disease and exhibits the worst prognosis. In general, CMS4 CRC is resistant to the current anti-EGFR agent cetuximab in both chemo-refractory and chemo-naïve settings [46, 47]. Moreover, no benefit of oxaliplatin treatment against CMS4 CRC has yet been reported [48]. The limited affected treatment for CMS4 CRC encouraged us to identify candidate drugs that are also capable of being repurposed for treating metastatic CMS4 CRC.

In addition to genetic heterogeneity, differences in the CRC microenvironment, including hyperglycemia, also play a pivotal role in influencing responses to drug treatments. For example, Ma et al. reported that a high glucose environment attenuated 5-FU-mediated growth inhibition in CRC cells by decreasing cell death and increasing DNA replication [49]. In another study, Ikemura et al. revealed that the efficacies of 5-FU and oxaliplatin were limited in a CRC mouse model with induced hyperglycemia, the decreased overall survival was the result of chemoresistance [50]. DM also has been found to have a negative impact on CRC prognosis. Several meta-analyses have identified an association between DM and increased all-cause mortality and worse disease-free survival in patients with advanced CRC [51–56]. In Taiwan, Yang et al. further reported that high blood glucose levels could affect both overall and disease-free survival in patients with stage III CRC who were also receiving adjuvant 5-FU and oxaliplatin-based chemotherapy [37]. Similar observations can be found in the present study. For example, we found that SW480-HG cells were more resistant to 5-FU than SW480-LG cells. It is therefore critical to develop novel strategies to overcome chemoresistance in advanced CRC by considering both genetic and environmental factors.

One of the main findings of the present study is that pitavastatin and atorvastatin, but not other statins, have the potential to treat metastatic CMS4 CRC in patients with comorbid hyperglycemia. However, based on genetic heterogeneity, the results of preclinical and clinical trials have shown that treatments involving statins combined with chemotherapy drugs may not always be effective for treating CRC. Therefore, prospective studies stratified by biomarkers are required to evaluate the efficacy of statins when combined with conventional chemotherapy (Additional File 7: Table S6). Moreover, we also note that a systematic review of randomized controlled trials did not confirm the efficacy of statins in treating patients with solid malignant tumors, including CRC [57]. Our analysis also indicated that inappropriate selection of statin drugs may result in no significant efficacy in CRC patients. (Additional File 3: Figure S13). The data from this study suggest that statins were specifically effective against CMS4 cancers. Moreover, other studies have observed that statin use is associated with a lower incidence of left-sided colon cancers and rectal cancers, which are common sites of CMS4 cancers [58–61].

Although lipid-lowering effects may be similar among statins, their potential to treat cancer may differ significantly. Statins can be classified as hydrophilic or lipophilic, with each group having a different overall tissue distribution. For example, hydrophilic statins (e.g., pravastatin, rosuvastatin, and fluvastatin) are mainly located in the liver. In contrast, lipophilic statins (e.g., simvastatin, mevastatin, lovastatin, pitavastatin, and atorvastatin) readily diffuse across cell membranes and are distributed throughout many body tissues [62, 63]. Thus, another meta-analysis found that lipophilic, but not hydrophilic, statins could significantly reduce the risk of CRC [59]. Moreover, rosuvastatin, pitavastatin, and atorvastatin can be chemically synthesized to possess a fluorophenyl group that can form an additional linkage to HMG-CoA reductase, which exhibits a more potent inhibition [64, 65]. In addition to the different pharmacokinetics of different statins, their mechanisms on CRC cells may also vary significantly. For example, a subgroup analysis of the TOHO lipid intervention trial using pitavastatin (TOHO-LIP) showed that the anticancer effect of pitavastatin may be drug-specific [66].

We further categorized pitavastatin, atorvastatin, lovastatin, simvastatin, mevastatin, and pravastatin into three classes based on their sensitivity for treating CRC cells. Class I statins (i.e., pitavastatin and atorvastatin) were sensitive against metastatic CRC cells, whereas class II statins (i.e., lovastatin, simvastatin, and mevastatin) were sensitive only to primary CRC cells. The one class III statin (pravastatin) identified was not effective in treating CRC cells. By comparing the gene signatures of six different statins in the CLUE database, we found class I and II statins show some degrees of similarities of DEGs, while little similarity can be found as compared to class III statins (Data not shown). Taken together, these results show that the significant cytotoxicity of pitavastatin and atorvastatin against CRC is related not only to their specific pharmacokinetics but also that these statins generate unique changes in gene expression relative to other statins.

Since hypercholesteremia is one of the most common comorbidities in DM patients, statins are frequently prescribed for this patient population [67]. Despite the similar potency of all statins in reducing serum cholesterol levels, they may show significant differences in their ability to treat CMS4 CRC cells and overcome 5-FU drug resistance. This may be related to dosage as well as their mechanisms of action against CRC. For example, in this study, we found that the dosage of pitavastatin to inhibit SW480 was significantly lower than that of atorvastatin. However, the equivalent dosage between pitavastatin and atorvastatin when used to reduce CRC cell viability was similar to that used to generate a cholesterol-lowering effect. Although strict control of serum glucose levels in patients with CRC and DM may improve their prognosis, elevated postprandial serum glucose levels may exist even with normal fasting glucose and glycated hemoglobin (HbA1c) levels. Moreover, direct administration of the blood-glucose-lowering agent metformin is unable to kill CMS4 CRC cells [68]. Therefore, the proper selection of specific statins (i.e., pitavastatin or atorvastatin) to treat hypercholesteremia in patients with both metastatic CRC and DM may help reduce the potential resistance to chemotherapy and improve cancer-specific survival.

Next, we extracted pitavastatin and atorvastatin-treated CRC gene signatures from CLUE database and utilized CPDB analysis to predict the specific pathways involved in their triggering events. Our findings confirm that these statins impact CRC development via similar pathways (Fig. 5A-5B). Prior research indicates that statins induce cancer cell death by triggering autophagy and apoptosis [44]. Intriguingly, our results demonstrate that pitavastatin and atorvastatin indeed stimulate autophagy, as evidenced by elevated levels of p62 and LC3B II, along with increased apoptosis-related markers such as cleaved PARP, Bax, and cleaved Caspase-3 (Fig. 5C-5D). However, co-treatment with 3-MA, which affects autophagy, did not apparently inhibit pitavastatin and atorvastatin-induced apoptosis-related markers, such as cleaved PARP and cleaved caspase 3 (Fig. 6A). Since these statin drugs-induced apoptosis-related markers slightly decreased in ATG5 KO SW480 cells, indicating modulating autophagy may still partly result in statin drugs-induced apoptosis (Fig. 6B). The robust upregulation of PERK/ATF4/CHOP expression under pitavastatin or atorvastatin treatment, indicating the induction of ER stress/UPR signaling. The administration of GSK2606414 (PERKi) decreased the cleavage of PARP, especially under high glucose conditions, indicating ER stress/UPR signaling played a crucial role in pitavastatin or atorvastatin-induced apoptosis (Fig. 6C). Additionally, since YAP serves as a critical regulator promoting cell survival under endoplasmic reticulum stress [39], pitavastatin or atorvastatin-induced increase of phosphorylated YAP, which promote its cytosolic retention and degradation by ubiquitin-proteasome system, may at least, partly, confer pitavastatin or atorvastatin-induced apoptosis (Fig. 5C). Interestingly, administration of GSK2606414 reversed pitavastatin and atorvastatin-induced ATF4/CHOP signaling as well as the decrease of YAP (Fig. 6C). The increase of YAP expression under PERK inhibition may partly result from the decrease of phosphorylated YAP. Recently, YAP also has been demonstrated to degrade via ER stress-mediated ER-associated degradation (ERAD) [69], it will be of interest to investigate whether YAP or its interplay with ER stress signaling plays a crucial role in pitavastatin or atorvastatin-induced apoptosis. The upregulation of YAP has been found to possess an anti-apoptotic effect in many cells, however, it also has been found to promote apoptosis and other forms of cell death, such as ferroptosis and pyroptosis, in some cell types [70]. Other ER stress inhibitors will be included to validate the role of ER stress/UPR signaling and YAP expression in pitavastatin and atorvastatin-mediated cell death. Whether other forms of cell death mechanisms were involved in pitavastatin, and atorvastatin-induced cell death still needs further investigation.

From a clinical standpoint, it's worth noting that the doses of pitavastatin and atorvastatin utilized in our cell culture experiments greatly exceeded typical clinical standards. This could potentially impede the translation of our research findings into practical clinical applications. For instance, the minimum dose of atorvastatin employed in our cell culture experiments was 2.5 µM, equivalent to a clinical dose of 1396 µg/L. This dosage is approximately 70 times higher than the current clinical standard of 20 µg/L [71]. Similarly, we observed that the lowest dose of pitavastatin used in our cell culture experiments was 1.25 µM, translating to a clinical dose of 1101 µg/L. This is approximately 5 times higher than the current clinical dose of 200 µg/L [72]. This discriminates the utilities of pitavastatin from atorvastatin in clinical practice. To enhance the feasibility of clinical therapeutic interventions for CRC, it may be beneficial to reduce the need for administering a single high dose by extending the duration of treatment. This approach could potentially maintain efficacy while minimizing the risk of adverse effects associated with high doses.

Our study underscores the detrimental effects of high glucose conditions on the metastasis and chemoresistance of CMS4 CRC cells. By integrating gene expression-based cancer classification with extensive drug sensitivity data under varying glucose conditions, we repurpose pitavastatin and atorvastatin as anti-CMS4 CRC drugs, particularly effective under high glucose conditions. Pitavastatin and atorvastatin exhibited significant efficacy in inhibiting cell migration and spheroid formation in highly metastatic CMS4 CRC under high glucose conditions, achieved through induction of autophagy and activation of ER stress/UPR, coupled with inhibition of YAP expression, leading to apoptosis (Fig. 7). Overall, this study highlights the utility of a gene expression-based cancer cell classification system for high-throughput prediction of cancer therapeutic drug repurposing. These findings may inform future clinical trials aimed at repurposing pitavastatin, which dosage might be achievable in clinical settings, to treat patients with metastatic CMS4 CRC, particularly under hyperglycemic conditions.

CRC	Colorectal cancer
5-FU	5-fluorouracil
BSA	Bovine serum albumin
CCLE	Cancer Cell Line Encyclopedia
CI	Combination index
CMAP	Connectivity Map
CMS	Consensus molecular subtype
CPDB	ConsensusPathDB
CSC	Cancer stem-like cell
DEGs	Differential expression genes
DepMap	Dependency Map
DM	Diabetes mellitus
DMEM	Dulbecco’s Modified Eagle’s Medium
ERAD	ER-associated degradation
EMT	Epithelial-mesenchymal transition
ER	Endoplasmic reticulum
FBS	Fetal bovine serum
FDA	Food and Drug Administration
HbA1c	Glycated hemoglobin
HG	High glucose
HMG-CoA	3-hydroxy-3-methylglutaryl coenzyme-A
HMGCR	3-hydroxy-3-methylglutaryl-coenzyme-A reductase
HRP	Horseradish peroxidase
IF	Immunofluorescence
KO	Knockout
LG	Low glucose
PBS	Phosphate-buffered saline
PRISM	Profiling Relative Inhibition Simultaneously in Mixtures
R³CE	Rapid, Reproducible, Rare Cell 3D Expansion
RPMI	Roswell Park Memorial Institute
SEM	Standard error of the mean
SRB	Sulforhodamine B
TCA	Trichloroacetic acid
TGF-β	Transforming growth factor-β
TOHO-LIP	TOHO lipid intervention trial using pitavastatin
UPR	Unfolded protein response
YAP	Yes-related protein

Ethics approval and consent to participate

Not applicable.

Consent for publication

All authors have participated in the study and consented to publication.

Availability of data and materials

The data generated or analyzed from this study are included in the published article.

Competing interests

The authors declare that no competing interests or personal relationships could have influenced the work reported in this paper.

Funding

This work was supported by grants from the Integrated Research Plan of the National Science and Technology Council (MOST111-2320-B-A49-036) to Chi-Ying F Huang, MOST 111-2320-B-030-008 and MOST 109-2320-B-030-MY3 to Jin-Mei Lai. This work was also supported by grants from the Department of Health, Taipei City Government (11201-62-016) and Taipei City Hospital (TPCH-113-45) to Wei-Ming Cheng. MOST111-2320-B-039-019-MY3 and grant from China Medical University, Taiwan (CMU109-S-61 & CMU111-MF-44) to Ming-Fen Lee.

Authors’ contributions

Research Supervision: T-S.C., J-M.L., W-M.C., and C-Y. F. H.; Conceptualization and Study Design: P-C.L., M.T-B.N., S-Y.C., T-S.C., J-M.L., and C-Y. F. H.; Experimental Work: P-C.L., Y-T.L., Y-T.H., S-Y.C., T-Y.H., Y-C.C., and C-W.W.; Intellectual Contributions: T-H.N., T-H.T., H-T.H., M-F.L., and W-M.C.; Manuscript Writing: P-C.L., M.T-B.N.,T-S.C., W-M.C., J-M.L and C-Y. F. H..
All authors have read and approved the final manuscript.

Acknowledgments

We acknowledge the generous gift of SW480-vehicle and SW480-ATG5 KO cells from Professor Hsiao-Sheng Liu at Kaohsiung Medical University, Kaohsiung, Taiwan. Additionally, we gratefully acknowledge the generous gift of DLD-1 and DLD-1R cells from Professor Yi-Shiou Chiou, also at Kaohsiung Medical University, Kaohsiung, Taiwan. We extend our gratitude to Yu-Chieh Chu and Chih-Wei Wu from Taipei First Girls High School, Taipei, Taiwan, for their assistance with the experiments.

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No competing interests reported.

Additionalfile1Table.S1.xlsx
Additional File 1: Table S1. Antibody information sheet.
Additionalfile2Table.S2.xlsx
Additional File 2: Table S2. Summary of all statinspresent in the DepMap database.
Additionalfile3FigureS1S13.docx
Additional File 3: Figure S1. Effective role of metformin for treating specific CMS or metastatic CRC cells. Figure S2. A flowchart illustrating the establishment of SW480-LG and SW480-HG cells. Figure S3. IRS-1, YAP1, and Snail expression in SW480-LG and SW480-HG cells. Figure S4. Drug effects of 5-FU, pitavastatin, and atorvastatin on the CMS4 cell line SW480. Figure S5. Colony formation assays for SW480-LG and SW480-HG cells. Figure S6. The effects of pitavastatin and atorvastatin on the CMS3 cell line HT29. Figure S7. The effects of lovastatin on SW480-LG and SW480-HG cells. Figure S8. The effect of 5-FU in combination with pitavastatin or atorvastatin in SW480-LG and SW480-HG cells. Figure S9. The inhibition of 3D spheroid formation under high glucose conditions by pitavastatin and atorvastatin. Figure S10. The effects of pitavastatin and atorvastatin on DLD-1 and DLD-1R cells. Figure S11. Colony formation assays for DLD-1 and DLD-1R cells. Figure S12. Expression of YAP1 in DLD-1R spheroids following treatment with 5-FU pitavastatin and atorvastatin. Figure S13. Effects of statins on primary and metastatic colorectal cancer cells.
Additionalfile4TableS3.xlsx
Additional File 4: Table S3. Summary of IC₅₀ values for pitavastatin and atorvastatin in HT29 cells.
Additionalfile5TableS4.xlsx
Additional File 5: Table S4. Summary of IC₅₀ values for lovastatin in SW480-LG and SW480-HG cells.
Additionalfile6TableS5.xlsx
Additional File 6: Table S5. CPDB analysis predicts which pathways may be related to pitavastatin and atorvastatin sensitivity.
Additionalfile7TableS6.xlsx
Additional File 7: Table S6. Studies of a combination treatment including atorvastatin, simvastatin, and lovastatin with CRC chemotherapeutic drugs.

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Repurposing pitavastatin and atorvastatin to overcome chemoresistance of metastatic colorectal cancer under high glucose conditions

Status:

Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

Background

Methods

Dependency Map (DepMap) portal

Predicting the mechanism of action of statins through CLUE database

Cell culture

Cell viability assay

Migration assay

Western blotting

Colony formation assay

Synergistic effect analysis

3D spheroid cultured assays

Immunofluorescence (IF) staining and confocal microscopy

Statistical analysis

Results

Pitavastatin and atorvastatin are identified as putative treatments for metastatic CMS4 CRC

Pitavastatin and atorvastatin can overcome high glucose-induced drug resistance and synergistically promote 5-FU-mediated cytotoxicity

Pitavastatin and atorvastatin can inhibit the migration ability and spheroid formation stimulated by high glucose

Pitavastatin and atorvastatin affect intrinsic 5-FU resistance in CRC cells

Underlying mechanisms driving the effects of pitavastatin and atorvastatin on CRC cells

Pitavastatin and atorvastatin induce apoptosis partly by stimulating autophagy and inducing ER stress

Discussion

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1