Cell lines

Two CRC cell lines, HCT116 and Hke3, were used in this study. HCT116 is a KRAS mutant cell line, harboring a G13D mutation, while Hke3 is KRAS WT. HCT116 and Hke3 are isogenic, and Hke3 was originally made by reverting the KRAS mutation in HCT116 [18]. HCT116 were purchased from the American Type Culture Collection (ATCC®). Hke3 cell lines were obtained from Dr. Takehiko Sasazuki (Medical Institute of Bioregulation, Kyushu University).

Cell culture

Cell lines were cultured in Roswell Park Memorial Institute (RPMI) 1640 media (Gibco™, Catalog #: 11875093), with 10% Fetal Bovine Serum (GemCell™, Catalog #: 100–500), 1% Non-Essential Amino Acids (Gibco™, Catalog #: 11140050), 2% HEPES buffer (Gibco™, Catalog #: 15630080), 1% Antibiotic–Antimycotic (Gibco™, Catalog #: 15240062), and 0.4% gentamicin (Gibco™, Catalog #: 15710064). The cells were maintained in an atmosphere of 5% CO2 at 37 °C and passaged according to ATCC®’s recommended protocol.

Carbamazepine (CBZ) preparation

Carbamazepine powder was purchased from (Supelco™, Catalog #: PHR1067-1G). The CBZ powder was dissolved in absolute methanol at a concentration of approximately 2 mg/ml (8.5mMol) and placed into single-use aliquots at -20 °C. At the time of treatment one aliquot of the Carbamazepine solution was diluted with media to 500uM.

Cell treatment

Cells were cultured until 70% confluency, trypsinized (Corning™, Catalog #: 25–053-CI), and spun down into cell pellets. Cells were then counted using the Countess™ II Automated Cell Counter (Invitrogen™, Catalog #: AMQAX1000) with Trypan Blue solution (Sigma-Aldrich™, Catalog #: T8154) as per the manufacturer’s protocol. Four plates of 5–7 million cells were made in a 100 mm plate (Denville™), two HCT116 and two Hke3, and allowed to remain for 24 h in 9 mL of cell culture media. After that time, one plate of each cell type was then treated with 1 mL of the 500uM Carbamazepine solution (final concentration in media = 50uM). 6 or 24 h after treatment, both the untreated and treated cell lines were trypsinized and harvested. 25% of the pellet was set aside for RNA extraction, while 75% was set aside for protein extraction.

RNA extraction and quantification

RNA was extracted from the cell pellets using the Invitrogen™ PureLink™ RNA Mini Kit (Invitrogen™, Carlsbad, CA, USA, Catalog #: 12183018A) as per the manufacturer’s protocol. The purified RNA was then placed into single-use aliquots and stored at − 80 °C. The concentration of the extracted RNA was quantified using a Thermo Scientific™ NanoDrop 1000 (Thermo Scientific™, Catalog #: 2353–30-0010). The 260/280 of the RNA was checked and the RNA was only kept if the range of 260/280 was between 1.9 and 2.1.

cDNA synthesis

A total of 1.5 μg of the extracted and quantified RNA was synthesized into cDNA using the iScript Reverse Transcription Supermix for RT-qPCR (Bio-Rad™, Catalog #: 1708841) as per the manufacturer’s protocol. A T100™ Thermal Cycler (Bio-Rad™, Catalog #: 1861096) was used to run the reaction. 100 μL of DEPC-treated water (Thermo Scientific™, Catalog #: R0601) was then added to each sample. The synthesized cDNA was then estimated using the Thermo Scientific™ NanoDrop 1000 and diluted to 25 ng/ul with DEPC-treated water and placed into single-use aliquots and stored at − 80 °C.

Quantitative polymerase chain reaction (qPCR)

Primers were purchased from Sigma-Aldrich™ (Easy Oligo) and arrived pre-diluted in deionized water at a concentration of 100 µM. The primers were made into single-use aliquots upon arrival and stored at − 20 °C. The sequences of the primers used can be seen in Table 1.

Table 1 Primer Sequences

Primers were prepared for qPCR by adding 10 µL of forward primer, 10 µL of reverse primer, and 180 µL of Thermo Scientific TM DEPC treated water (Thermo Scientific, Catalog #: FERR0601) (5 µM final concentration of forward and reverse primer). A total of 1 µL of the prepared 5 µM primer mix, 4 µL of the synthesized cDNA, and 5 µL of the Applied Biosystems™ PowerUp™ SYBR™ Green Master Mix (Applied Biosystems™, Catalog #: A25918), were added to each well of a qPCR tube set (Bio Molecular Systems™, Catalog #: 71–107) (final reaction mix contained a 500 nM concentration of each primer and 100 ng of cDNA). Quantabio™ Q cycler was used to run the qPCR (Quantabio™, Catalog #: 95900-4C). All reactions were prepared in triplicates.

Data analysis was performed by the ΔΔCT method. ΔCT was first calculated by subtracting each sample’s GAPDH CT value from its average target gene CT value. ΔΔCT was calculated by subtracting ΔCT of the untreated cell from the ΔCT of the treated cell. The ΔΔCT values were then converted to fold values using 2^(-ΔΔCT).

Protein extraction

Cell Extraction Buffer (Invitrogen™, Catalog #: FNN0011) and 10 µL of Thermo Scientific™ Halt™ Protease and Phosphatase Inhibitor Cocktail EDTA-free (100X) (Thermo Scientific™, Catalog #: 78445) was added to a microcentrifuge tube per 1 mL of cell Extraction Buffer. Each cell pellet was suspended in 250 µL of the freeze–thaw lysis buffer with protease and phosphatase inhibitor. The cell pellets were then dipped in liquid nitrogen for 10 s, allowed to thaw, and then vortexed. This was repeated three times. After the third freezing with liquid nitrogen, cells were placed on ice to thaw. The cell pellets were then placed in a microcentrifuge at max speed for 45 min at 4 °C. The supernatants were then placed into single-use aliquots at − 80 °C.

Protein estimation

Protein was estimated using a Bradford assay by combining in each 1.5 mL tube: 500uL of H2O, 495uL of Bradford, and 5uL of protein sample or BSA standard (or an additional 5uL Bradford for the plate blank). 600uL of this mixture was then plated in a 96 well plate (Corning™, Catalog #: 3598) at 200uL per well. The plate was then read using a SpectraMax Mini Multi-mode Microplate reader (Molecular Devices™, Catalog #: 76640–506) for absorbance at 595 nm. All values subtracted the plate blank, and the triplicate values were averaged together. A standard curve was made using BSA standards and protein was estimated using this curve.

Western blot

40ug of protein from each sample was used. Protein was prepped by mixing 1 part protein and 1 part 2 × laemilli sample buffer (Bio-Rad™, Catalog #: 1610737) and placed in boiling water for 10 min. Each sample was loaded in a 4–20% gel (Bio-Rad™, Catalog #: 4561094) and 2 uL of Magic marker (Invitrogen™, Catalog #: LC5602) and 10uL of protein ladder (Thermo Scientific™, Catalog #: 26616) was loaded as well. Transfer was done using a wet transfer at 80 mV for 1 h to a nitrocellulose membrane (Bio-Rad™, Catalog #: 1620215). Membranes were blocked in 1% BSA in TBS for an hour and then then allowed to sit in antibody overnight. The primary antibody for BRG1 was Invitrogen™ BRG1 Monoclonal Antibody (GT2712) at a 1:1000 dilution (Invitrogen™, Catalog #: MA5-31550). The primary antibody for ULK1 was Invitrogen™ ULK1 Recombinant Rabbit Monoclonal Antibody (JA58-36) at a 1:1000 dilution (Invitrogen™, Catalog #: MA5-32699). The primary antibody for Beta actin was Abnova ACTB monoclonal antibody (M01) clone 3G4-F9 at a 1:750 dilution (Abnova, Catalog #: H00000060-M01). The antibody detection was done using the Pierce™ Fast Western Blot Kit (Thermo Scientific™, Catalog #: 35050) and followed the manufacturer’s protocol. The ChemiDoc MP imaging system (Bio Rad™, Catalog #: 1708280) was used to detect chemiluminescence.

TCGA gene correlation analysis

The GEPIA online website was used to analyze the correlation of genes in CRC patients from The Cancer Genome Atlas (TCGA) database [19]. We assessed the correlation between gene expression of SMARCA4 and KRAS. This was done on the GEPIA website by selecting the Multiple Gene Analysis tab, selecting Correlation Analysis, and then selecting the following options: Gene A = SMARCA4, Gene B = KRAS, Normalized by gene = TUBA1A, Correlation Coefficient = Spearman, and Used Expression Datasets = COAD Tumor & READ Tumor, and then separately selected Used Expression Datasets = COAD Normal & READ Normal.

GDC gene expression and Kaplan Meier plots

The Xena online website was used to analyze the expression of genes in CRC patients from TCGA database [20]. This was done by selecting the “GDC Pan-Cancer” dataset, limiting the “cancer type” to COAD or READ, and keeping only “primary tumor” or “solid tissue normal.” Three categories were created as follows: Solid Tissue Normal: Data with “sample_type” labeled as Solid Tissue Control. KRAS-wt CRC: Data with “sample_type” labeled as primary tumor and no mutation to the KRAS gene. KRAS-mut CRC: Data with “sample_type” labeled as primary tumor and one of the following mutations to the KRAS gene: G12A, G12C, G12D, G12R, G12S, G12V, G13C, G13D. Any sample without gene expression reported was removed. Cancer samples with “Null” for KRAS-mutation status were removed. The final sample size was n = 539 consisting of 51 solid tissue, 309 KRAS-wt CRC, and 179 KRAS-mut CRC.

We selected the three dots above the box containing the 3 subgroups of samples and selected differential expression. For our first calculation of mRNA changes in cancer we set subgroup A to include both cancer groups and subgroup B to include the Solid Tissue control. Our next calculation, of mRNA change in the presence of a KRAS mutation, we set subgroup A to include the KRAS-mut data and subgroup B to include the KRAS-wt data. The advanced settings were not changed. A file including Log(2)FC, p-value, and adjp is given, and fold change of the target gene is then calculated. In order to visualize these changes, the mRNA expression of the target genes were opened. The “view as chart” symbol was selected and “compare subgroups” was then selected. “Show data from” included the target gene and “subgroup samples by” included our three groups of samples.

For the Kaplan Meier plot, three separate tabs were made, each one including only one of the subgroups. SMARCA4 mRNA expression was then opened on each tab, the three dots above the box were selected, and “Kaplan Meier Plot” was selected. The data set into quarterlies, and the cutoff was selected to 1500 days. The p-value is calculated by Xena using a log-rank test.

Molecular dynamic simulations and structural and energetic analysis

The AI AlphaFold predicted structures for human KRAS (ID: AF-P01116-F1) and human SMARCA4 (ID: AF-P51532-F1) were downloaded from the Uniprot database in Protein Data Bank (PDB) format [21, 22]., Each file was uploaded separately to PyMol to visualize the 3D structures. Each protein file contained a single protein chain (Chain A). KRAS contained 189 residues and SMARCA4 contained 1647 residues. Chain A for both SMARCA4 was renamed “Chain B” to act as a “ligand” in a complex with Chain A of KRAS, serving as a “receptor.” To create the G13D mutation in KRAS, in PyMOL the Gly13 residue was mutated to Asp13 using protein mutagenesis. This was saved as a separate pdb file.

Wildtype KRAS and G13D were each docked to each other using the ClusPro server [23,24,25,26]. Balanced structure “0” was downloaded as the complex structure for each docking. The proteins were again separated into separate chain files using PyMOL.

Using GROMACS, a topology file was created for KRAS-wt /G13D and SMARCA4. An OPLS-AA/L all atom force field was used. The SMARCA4 topology file was combined with the KRAS-wt topology to build the complex. A cubic box was generated and solvated. Ions were added to neutralize any charge in the complex if present. An energy minimization was run to reduce unfavorable sterics in the complex structure. NVT and NPT equilibrations were then used to respectively stabilize the temperature and pressure of the environment before running a 10 ns molecular dynamics simulation. Following the simulation, a trjconv command was used to correct any jumps of the protein around the box.

Root mean squared deviation (RMSD) was calculated for the carbon backbone to determine how much the complex moved from its original position, showing overall stability. Root mean square fluctuation (RMSF) was calculated for each protein in the complex in each simulation to determine the average displacement of their residues. Radius of gyration (Rg) was calculated for each protein in the complex as a measure of each of their overall structural compactness throughout the simulation while interacting.

gmx_MMPBSA software was used to calculate a per-residue decomposition analysis [27]. A MMGBSA (Generalized Born model) was used to produce energy values for the complex, the receptor KRAS /G13D), the ligand (SMARCA4), and the delta energy. The complex energy represented the bound state energy, and the receptor and ligand energies represented the unbound energies for KRAS /G13D and SMARCA4. The delta energy represented the overall binding strength. Delta energy (interaction energy) = Total Complex (bound state)—[Receptor + Ligand] (unbound states). Simulation energy values were represented in tables and graphs generated by the software.

Protein-drug docking

In-silico protein-drug dockings were accomplished using the CB-Dock2 server [28, 29]. The KRAS-wt, G13D, and SMARCA4 pdb files generated for the simulations were reused. The model structure for carbamazepine (ID: N6W) was downloaded from the RCSB database. The model structures for trans-carbamazepine diol and carbamazepine-o-quinone were created using the CB-Dock2 server ligand drawing function. KRAS-wt, G13D, and SMARCA4 were each uploaded to the server with each form of carbamazepine for cavity detection and docking. The CB-Dock2 server generated five possible binding conformations for each protein-drug pair, ranked by their energetic favorability. The highest ranked conformation was chosen for analysis.

Statistical analysis

Statistical analysis of western blot and qPCR data was performed using Microsoft™ Office Excel. For fold change, a two-tailed one-sample t-test was used. When comparing fold changes, a two-tailed two-sample t-test was used. Outliers were determined and removed using Iglewicz and Hoaglin’s outlier test with modified z-scores using the outlier criterion of a modified z-score ≥ 3.5.