Biomolecules & Therapeutics 2024; 32(1): 123-135  https://doi.org/10.4062/biomolther.2023.109
Antiproliferative Activity of Piceamycin by Regulating Alpha-Actinin-4 in Gemcitabine-Resistant Pancreatic Cancer Cells
Jee-Hyung Lee1,2, Jin Ho Choi3, Kyung-Min Lee1, Min Woo Lee1, Ja-Lok Ku4, Dong-Chan Oh2, Yern-Hyerk Shin2, Dae Hyun Kim5, In Rae Cho1, Woo Hyun Paik1, Ji Kon Ryu1, Yong-Tae Kim1, Sang Hyub Lee1,* and Sang Kook Lee2,*
1Department of Internal Medicine and Liver Research Institute, Seoul National University Hospital, College of Medicine, Seoul National University, Seoul 03080,
2Natural Products Research Institute, College of Pharmacy, Seoul National University, Seoul 08826,
3Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351,
4Department of Biomedical Sciences, Korean Cell Line Bank, Laboratory of Cell Biology and Cancer Research Institute, College of Medicine, Seoul National University, Seoul 03080,
5Dxome Co. Ltd., Seongnam 13558, Republic of Korea
*E-mail: sklee61@snu.ac.kr (Lee SK), gidoctor@snu.ac.kr (Lee SH)
Tel: +82-2-880-2475 (Lee SK), +82-2-2072-4892 (Lee SH)
Fax: +82-2-762-8322 (Lee SK), +82-2-762-9662 (Lee SH)
Received: June 7, 2023; Revised: June 22, 2023; Accepted: July 5, 2023; Published online: January 1, 2024.
© The Korean Society of Applied Pharmacology. All rights reserved.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Although gemcitabine-based regimens are widely used as an effective treatment for pancreatic cancer, acquired resistance to gemcitabine has become an increasingly common problem. Therefore, a novel therapeutic strategy to treat gemcitabine-resistant pancreatic cancer is urgently required. Piceamycin has been reported to exhibit antiproliferative activity against various cancer cells; however, its underlying molecular mechanism for anticancer activity in pancreatic cancer cells remains unexplored. Therefore, the present study evaluated the antiproliferation activity of piceamycin in a gemcitabine-resistant pancreatic cancer cell line and patient-derived pancreatic cancer organoids. Piceamycin effectively inhibited the proliferation and suppressed the expression of alpha-actinin-4, a gene that plays a pivotal role in tumorigenesis and metastasis of various cancers, in gemcitabine-resistant cells. Long-term exposure to piceamycin induced cell cycle arrest at the G0/G1 phase and caused apoptosis. Piceamycin also inhibited the invasion and migration of gemcitabine-resistant cells by modulating focal adhesion and epithelial-mesenchymal transition biomarkers. Moreover, the combination of piceamycin and gemcitabine exhibited a synergistic antiproliferative activity in gemcitabine-resistant cells. Piceamycin also effectively inhibited patient-derived pancreatic cancer organoid growth and induced apoptosis in the organoids. Taken together, these findings demonstrate that piceamycin may be an effective agent for overcoming gemcitabine resistance in pancreatic cancer.
Keywords: Alpha-actinin-4 (ACTN4), Pancreatic cancer, Piceamycin, Patient-derived pancreatic cancer organoids (PDPCOs), Apoptosis
INTRODUCTION

According to the cancer statistics in 2021, pancreatic cancer accounts for approximately 8% of all cancer cases and is the fifth most common cause of cancer-related deaths (Siegel et al., 2021). Pancreatic cancer has been steadily increasing due to several factors, including environmental factors, lifestyle risk, genetic factors, and medical conditions (Zhao and Liu, 2020; Park et al., 2021). Surgical resections are considered the most effective strategy to treat early-stage pancreatic cancer (Park et al., 2021). However, in advanced pancreatic cancer, no appropriate therapeutic options have been established, except for palliative systemic chemotherapy with supportive care. Gemcitabine with paclitaxel is commonly used as the first-line chemotherapy (Siegel et al., 2021). However, the frequent occurrence of drug resistance in conventional cytotoxic agents has led to aggressive disease progression (Zhao and Liu, 2020). Therefore, novel agents for complementing conventional cytotoxic agents should be discovered for the efficient treatment of acquired drug-resistant pancreatic cancers.

Alpha-actinin-4 (ACTN4), a family of actin-binding proteins, regulates the microfilament, adherents-type junction, and cancer metastasis (Tentler et al., 2019). Accumulating evidence suggests that ACTN4 plays a pivotal role in the regulation of metastasis-associated genes that promote cancer cell invasion and metastasis (Tentler et al., 2019). Recent studies have also reported that ACTN4 inhibition can potentiate antitumor activity (Gao et al., 2015; Watanabe et al., 2015; Wang et al., 2017; Tentler et al., 2019). On this line, targeting ACTN4 signaling could be a promising approach for overcoming acquired chemoresistance in pancreatic cancer. Therefore, regulating ACTN4 signaling with ACTN4 modulators might benefit patients with pancreatic cancer who do not respond to cytotoxic chemotherapies.

Natural products have played an important role in drug discovery and development programs. In particular, >50% of anticancer drugs are developed from small-molecule compounds derived from natural products (Lichota and Gwozdzinski, 2018). Piceamycin is a macrolactam produced from a Streptomyces sp. SD53 strain isolated from the gut of the silkworm, Bombyx mori (Schulz et al., 2009; Yu and Sun, 2013; Shin et al., 2020). Previous studies revealed that piceamycin exhibits antibiotic and cytotoxic activities against several cancer cell lines including the colon, breast, liver, and lung (Schulz et al., 2009; Yu and Sun, 2013; Shin et al., 2020; Kyaw et al., 2022). However, its antiproliferative activity and underlying molecular mechanism in pancreatic cancer cells have not yet been elucidated.

An organoid is a small organ-like three-dimensional (3D) structure that mimics human organs. Compared to two-dimensional cell cultures, the structure of organoid-type culture systems are increasingly similar to that of the human body (Nagle et al., 2018; Kim et al., 2020). Therefore, patient-derived pancreatic cancer organoids (PDPCOs) are useful tools for predicting drug responses in patients with cancer in the development of personalized medicines (Nagle et al., 2018; Kondo and Inoue, 2019; Kim et al., 2020; Vivarelli et al., 2020; Liu et al., 2021).

In the present study, we elucidated the antiproliferative activity and molecular mechanisms of piceamycin, a small molecular compound derived from natural products, in gemcitabine-resistant pancreatic cancer cells and PDPCOs. In particular, the regulation of ACTN4 signaling by piceamycin was determined to overcome acquired gemcitabine chemoresistance in pancreatic cancer cells.

MATERIALS AND METHODS

Kaplan–Meier Plotter analysis

The Kaplan–Meier Plotter (http://kmplot.com/analysis/) analysis was used to assess the overall survival (OS) and relapse-free survival (RFS) rates of patients diagnosed with pancreatic cancer. Patients were classified using the autoselect best cutoff method. Hazard ratios with 95% confidence intervals (CIs) and log-rank p-values were also calculated.

Cell culture and reagents

Pancreatic cancer cells (AsPC-1, MiaPaCa-2, and Panc-1) were obtained from the American Type Culture Collection (Manassas, VA, USA). All cells were cultured in a medium (Dulbecco’s modified Eagle medium (DMEM) for MiaPaCa-2 and Panc-1 cells; RPMI for AsPC-1 cells) supplemented with 10% fetal bovine serum (FBS) and penicillin–streptomycin (10,000 units/mL sodium penicillin G and 10,000 µg/mL streptomycin) in a humidified incubator containing 5% CO2 at 37°C. All reagents required for cell culture were purchased from Gibco® Invitrogen Corp. (Grand Island, NY, USA). Piceamycin (with a purity of >98% by HPLC analysis; Fig. 1) was isolated from a gut bacterium, Streptomyces sp. SD53, of the silkworm B. mori (Shin et al., 2020). Stock solutions (1 mg/ mL) were then prepared in sterile phosphate-buffered saline (PBS) and stored at −20°C. Gemcitabine was purchased from Sigma-Aldrich (St. Louis, MO, USA). All reagents used in the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay were purchased from Sigma-Aldrich. The AnnexinV/propidium iodide (PI) staining kit was provided by BD Biosciences (San Jose, CA, USA). The Caspase-Glo® 3/7 Assay Kit was purchased from Promega Corporation (Madison, WI, USA).

Figure 1. The chemical structure of piceamycin.

Cell proliferation assay

AsPC-1 cells (2×104 cells/mL) were seeded in 96-well plates and incubated overnight. Then, the cells were treated with the indicated piceamycin or gemcitabine concentrations and incubated at 37°C in a humidified atmosphere with 5% CO2 for the indicated times. Following incubation, the cells were incubated in MTT (0.5 mg/mL) containing the cell culture medium for an additional 4 h at 37°C. After removing the supernatant medium, dimethyl sulfoxide (DMSO) solution (200 µL) was added to each well. The formazan crystals formed by the active mitochondria were dissolved in DMSO. The absorbance in each well was measured at 570 nm, which was then used to determine cell viability. IC50 values were calculated from nonlinear regression analysis using GraphPad Prism (version 7.01; GraphPad Software, Inc., San Diego, CA, USA). The combined effect of the test compounds was calculated using the following equation of the combination index (CI): CI=D1/(Dx)1+D2/(Dx)2. D1 and D2 are the concentrations of the combined test compounds that achieve the expected effect. (Dx)1 and (Dx)2 are the concentrations of a single-concentration treatment. The Chou–Talalay method was used to determine the CI values (Chou, 2010).

RNA-seq analysis

RNA preparation, library preparation, and RNA-Seq: RNA was collected from three wells of each of the piceamycin-treated (1.25 µM) and piceamycin-untreated gemcitabine-resistant AsPC-1 cells. The total RNA was extracted from the eWAT using TRIzol reagent (Invitrogen Life Technologies, NY, USA) according to instructions provided by the manufacturer. The total RNA concentration was calculated by Quant-IT RiboGreen (#R11490, Invitrogen Life Technologies). The samples were analyzed using the TapeStation RNA screentape (#5067-5576, Agilent Technologies, Santa Clara, CA, USA) to assess the total RNA integrity. Only high-quality RNA preparations with a RIN of >7.0 were used for RNA library construction. A library was independently prepared with 1 µg of total RNA for each sample using the Illumina TruSeq Stranded mRNA Sample Prep Kit (#RS-122-2101, Illumina, Inc., San Diego, CA, USA). The poly-A-containing mRNA molecules were first purified using poly-T-attached magnetic beads. Following purification, small mRNA fragments were generated using divalent cations under a high temperature. The cleaved RNA fragments were copied into first-strand cDNA using SuperScript II reverse transcriptase (#18064014, Invitrogen Life Technologies) and random primers. This was followed by second-strand cDNA synthesis using DNA polymerase I, RNase H, and dUTP. The cDNA fragments then underwent an end-repair process, added with a single “A” base, and underwent adapter ligation. The products were then purified and enriched with polymerase chain reaction to produce the final cDNA library. The libraries were then quantified using the KAPA Library Quantification kits for Illumina Sequencing platforms based on the qPCR Quantification Protocol Guide (#KK4854, KAPA BIOSYSTEMS, Basel, Switzerland) and qualified using the TapeStation D1000 ScreenTape (#5067-5582, Agilent Technologies). The indexed libraries were submitted to Illumina NovaSeq (Illumina, Inc.). Paired-end (2×100 bp) sequencing was performed by Macrogen Incorporated.

Data processing: The library was prepared using the Illumina TruSeq Stranded mRNA LT Sample Prep Kit. The sequence quality of paired-end sequencing reads (101 bp) generated from Illumina instruments was verified through FastQC (version 0.11.7, Babraham Bioinformatics, Cambridge, England). Before the analysis, adapter sequences and bases with a base quality of <3 from the end reads were removed using Trimmomatic (version 0.38) (Bolger et al., 2014). The sliding window trim method was used to remove bases that failed to qualify for a window size of 4 and a mean quality of 15. Reads with a minimum length of 36 bp were also removed to produce the cleaned data.

Aligning reads to the Homo sapiens reference genome: The cleaned reads were aligned to Homo sapiens (GRCh38) using HISAT v2.1.0 (Pertea et al., 2016). Transcript assembly was performed based on reference gene annotation by StringTie v2.1.3b (Pertea et al., 2015, 2016) with aligned reads. The gene/transcript level expression profiling was quantified as read count and normalized values such as fragments per kilobase of exon per million fragments mapped and transcripts per kilobase of transcript per million mapped reads, which are the normalized metrics for expression levels considering the transcript length and depth of coverage.

Differentially expressed genes (DEG) analysis: DEGs between comparable samples were analyzed using an expression profile generated from the HISAT-StringTie pipeline. The size factors and gene-wised variations were estimated from the read count data to prevent bias in the sample comparison process. The read count data were normalized through the relative log expression method in the DESeq2 R library. The statistical significance of the differential expression data was determined using DESeq2 nbinomWaldTest (Love et al., 2014) with a normalized count. The false discovery rate was controlled by adjusting the p-value using the Benjamini–Hochberg algorithm. DEGs were satisfied with |fold change| ≥2, and raw p was used.

Protein–protein interaction (PPI) network analysis

PPI network analysis (Wimalagunasekara et al., 2022) is a search tool used to retrieve interacting genes (STRING) (https://string-db.org) database, which integrates both known and predicted PPIs, and to predict functional protein interactions. The STRING tool was employed to identify and evaluate potential interactions between DEGs in different tissues. Active interaction sources, including text mining, experiments, databases, and co-expression as well as species limited to “H. sapiens” and an interaction score of >0.4 were applied to construct PPI networks. Cytoscape software (version 3.9.1; https://www.cytoscape.org) was used to visualize the PPI network.

Western blot analysis

Total cell lysates were prepared in 5× sample loading buffer (250 mM tris hydrochloride [pH 6.8], 40% glycerol [80%, v/v], 8% sodium dodecyl sulfate [SDS], 2% β-mercaptoethanol, 0.1% bromophenol blue, 100 mM dithiothreitol [1 M]. The bicinchoninic acid (BCA) method and BCA protein assay kit (Thermo Fisher Scientific, Waltham, MA, USA) were used to quantify the protein concentration of the samples. Equal amounts of protein (20-30 µg) were separated by 6-13% SDS–polyacrylamide gel electrophoresis, transferred to polyvinylidene fluoride membranes (Millipore, Bedford, MA, USA), and blocked with 5% bovine serum albumin (Sigma-Aldrich). The membranes were then probed with anti-ACTN-4, anti-α-tubulin, anti-β-Actin, anti-vinculin, anti-FAK, anti-Rac, anti-Slug, anti-Snail, anti-CDK2, anti-CDK4, anti-cyclin E, anti-cyclin D, anti-Bax, anti-Bcl-2, anti-cleaved caspase 3, anti-caspase 3, anti-MMP2, and anti-cytochrome c antibodies purchased from Cell Signaling Technology (Beverly, MA, USA) and anti-N-cadherin antibodies purchased from BD Biosciences overnight with primary antibodies at 4°C. Following the incubation, the membranes were washed three times and further incubated with peroxidase-labeled secondary antibodies for 4 h at room temperature. Protein bands were visualized using enhanced chemiluminescence (Thermo Fisher Scientific).

Cell cycle analysis

Flow cytometry was used to measure cell cycle dynamics. AsPC-1 cells (5×105 cells/dish in a 60-mm dish) were incubated with 0, 1, 2, and 5 µM piceamycin for up to 24 h. All adherent and floating cells were collected and washed twice with PBS (Invitrogen Life Technologies). Cells were fixed with 70% (v/v) ethanol at 4°C for at least 30 min. After washing with PBS, the cells were stained with 5 µL of PI (1 mg/mL) containing 50 µg/mL of RNase A (Sigma-Aldrich) for 30 min at room temperature. Fluorescence intensity was analyzed on a FACSCalibur flow cytometer (BD Biosciences). A total of 10,000 cells were counted for each analysis, and the cell distribution in each phase (G0/G1, S, G2, and M) of the cell cycle was displayed as a histogram.

Caspase 3/7 activity assay

The caspase 3/7 activity assay is a homogeneous luminescent assay used to measure caspase 3/7 activities. AsPC-1 cells were cultured on 96-well plates at a density of 10,000 cells/well with 10 µM piceamycin for 48 h. A 100 µL of Caspase-Glo® 3/7 reagent was added to each well in a white-walled 96-well plate containing 100 µL of blank, negative control or treated cells in the culture medium, which was then incubated at room temperature for 30 min to 3 h. The luminescence of each sample was measured using a plate-reading luminometer, and the resulting data were depicted as means ± standard deviations (SDs).

Colony formation assay

AsPC-1 cells were seeded into six-well plates (500 cells/well) and allowed to attach overnight. The cells were then treated with various piceamycin concentrations (0, 1, 5, and 10 µM), and the medium was changed every 3 days. The medium was removed once colony formation became apparent. After gently washing with ice-cold PBS, the colonies were fixed in 4% paraformaldehyde (PFA) for 15 min and stained with 0.5% crystal violet (20% methanol, 0.5% crystal violet, and 1% PFA in ddH2O) for 30 min. Any excess crystal violet was washed off with distilled water and allowed to dry. The colonies were photographed under a microscope (inverted microscope; CKX41, Olympus, Shibuya, Tokyo, Japan) at ×40 magnification. Each experiment was repeated three times.

Annexin V fluorescein isothiocyanate and PI double staining

Annexin V/PI staining was performed to determine the % of apoptotic cells in the total cell population. AsPC-1 cells were cultured on a six-well plate at a density of 1×105 cells per well. The cells were incubated for >12 h to allow adhesion and treated with different piceamycin concentrations (0, 0.1, 1, 2, 5, and 10 µM) resuspended in the PBS buffer. Following a 48 h incubation, the cells were harvested using trypsin, washed with PBS, and collected using centrifugation. Then, cells were prepared for apoptosis analysis. After resuspending the cells in 300-500 µL of Annexin binding buffer, the cells were treated with 5 µL of PI (1 mg/ml) and 5 µL of Annexin V fluorescein dye for 15 min in dark setting at room temperature and filtered before a BD FACSAriaIII flowcytometer (BD Biosciences) analysis.

Wound healing assay (cell migration assay)

A scratch wound healing assay was used to measure cell migration. AsPC-1 cells were seeded into six-well plates (500 cells/well) and incubated overnight. Upon reaching an approximately 70% confluence, a wound was made to the cell monolayer by scratching gently using a 200 µL sterile pipette tip. After washing the well twice with a medium to remove any detached cells, the cells were cultured in the RPMI medium supplemented with 10% FBS and treated with 0, 1, 2, and 10 µM of piceamycin. Following a 48 h incubation, the cells were washed twice with 1× PBS and photographed under microscopy with the same configurations. Cell migration was measured at 0 and 48 h using an inverted microscope at 100× magnification.

Transwell cell invasion assay

Each 24-well transwell membrane insert (diameter, 6.5 mm; pore size, 8 µm; Corning, Tewksbury, MA, USA) was coated with 10 µL of type I collagen (0.5 mg/mL, BD Biosciences) and 20 µL of a 1:20 mixture of Matrigel (BD Biosciences) in PBS. AsPC-1 cells were treated with various piceamycin concentrations (0, 1, 2, 5, and 10 µM). Following a 48 h incubation, the cells were harvested and resuspended in a serum-free medium and plated (2×105 cells/ chamber) in the upper chambers of the Matrigel-coated transwell inserts. Roughly, 30% FBS-supplemented medium was used as a chemoattractant in the lower chambers. The cells were incubated for 48 h, and those that migrated to the outer surface of the lower chambers were fixed and stained with 0.5% crystal violet (20% methanol, 0.5% crystal violet, and 1% PFA in ddH2O) for 30 min. Any excess crystal violet was removed using distilled water and dried off. The colonies were photographed using a inverted microscope (CKX41, Olympus) at ×40 magnification. Each experiment was repeated three times. Representative images obtained from three separate experiments are shown.

Organoid culture medium and 3D culture viability assay

Pancreatic cancer organoids were provided by Korean Cell Line Bank and cultured at 37°C in 5% CO2/95% air in the stem cell media consisting of DMEM (Corning Inc, Corning, NY, USA) supplemented with 50% (v/v) with Wnt-3A, R-spending 1, and m-Noggin conditioned medium, human epidermal growth factor of 50 ng/mL, human fibroblast growth factor 10 of 100 ng/mL, nicotinamide of 10 mM, 500 nM A83-01, 1× B27 supplement, N-acetylcysteine of 1.25 mM, 10% FBS, and human Gastrin1 0.01 µM in 50% basal culture medium Recombinant Wnt-3A, Noggin, and R-spondin1 can be substituted with a conditioned medium from the L-WRN (CRL-3276TM, ATCC®, Manassas, VA, USA) cell line. Patient-derived pancreatic cancer organoid viability was assessed after 72 h of treatment using the Cell Titer-Glo® 3D reagent, Promega Corporation following the instructions provided by the manufacturer.

Data analysis

All data are presented as means ± SD from at least three independent experiments. Statistical significance (*p<0.05, **p<0.01, and ***p<0.001) was evaluated using Student’s t-test to identify between-group differences. IC50 value was calculated with nonlinear regression analysis using GraphPad Prism (version 7.01; GraphPad Software, Inc.).

RESULTS

Antiproliferation activity of piceamycin in pancreatic cancer cells and the clinical significance of ACTN4 expression in patients with pancreatic cancer

Piceamycin effectively inhibited the proliferation of all tested pancreatic cancer cell lines (AsPC-1, Panc-1, and MiaPaCa-2) (Table 1). A growing body of evidence suggests that ACTN4 expression is highly associated with cancer development and metastasis in various cancers (Gao et al., 2015; Wang et al., 2017; Tentler et al., 2019; Huang et al., 2020). To confirm the involvement of ACTN4 expression in human pancreatic cancers, the clinical significance of ACTN4 expression in patients with pancreatic cancer was analyzed using the Kaplan−Meier method for OS and RFS rates. As shown in Fig. 2A and 2B, higher ACTN4 expression levels were associated with a lower probability for OS and RFS compared with lower ACTN4 expression levels in patients with pancreatic cancer. These findings suggest that ACTN4 expression negatively correlated with OS and RFS in patients with pancreatic cancer, indicating that ACTN4 might be a therapeutic option for the management of pancreatic cancer.

Figure 2. (A, B) The Kaplan-Meier survival curve represents the overall survival (OS) (the patient’s number; low=43, high=134) and relapse-free survival (RFS) (the patient’s number; low=21, high=48) of patient with pancreatic cancer according to the ACTN4 expression level. (C) Effect of piceamycin on ACTN4 mRNA expression. RNA-seq assay was performed in gemcitabine-resistant AsPC-1 cells treated with piceamycin (1.25 μM) compared with control (PBS with DMSO-treated). Heatmap shows ACTN4 mRNA expression according to z-score. The color represents z-score (yellow; positive score; upregulation, blue; negative score; downregulation). / Normalized value of ACTN4 mRNA expression. Data are presented as mean ± SD (n=3). (D) Effect of piceamycin on ACTN4 protein expression in gemcitabine-resistant AsPC-1 cells. Gemcitabine-resistant AsPC-1 cells were treated with the indicated concentrations of piceamycin for 48 h, and the protein expression level of ACTN4 was determined by western blotting. α-Tubulin was used as an internal control. (E) Protein-Protein Interaction (PPI) for ACTN4 from the search tool (STRING) database. Interacting proteins for ACTNB (Actin beta) Gene: ACTB (Actin beta)–ACTG1 (Actin gamma1), Interacting proteins for ACTN4 (Actinin alpha4) Gene: ACTN4–VCN (Vinculin) (F) Effect of piceamycin on mRNA expression of actin polymerization related genes. The heatmap was visualized from the RNA-seq data (according to z-score of actin polymerization related genes) and displayed on the column (according to z-score; –2≤z≤2, AVE; average of z-score, STD; standard deviation of z-score, n=3). / Normalized value (mRNA level) of ACTB and ACTG1 from RNA-seq analysis treated with piceamycin (1.25 μM) versus control (PBS with DMSO-treated) in gemcitabine-resistant AsPC-1 cells. Data are presented as mean ± SD (n=3) (G) Modified KEGG pathway of the genes related to actin polymerization signaling pathway. Modified KEGG pathway from Kyoto Encyclopedia of Genes and Genomes (KEGG) treated with piceamycin (1.25 μM) for 48 h compared with control (PBS with DMSO-treated) in gemcitabine-resistant AsPC-1 cells. The box colors of modified KEGG pathway represent fold change. (H) Effect of piceamycin on the proteins related to actin polymerization (VCN and ACTB). The protein expression related to actin polymerization biomarkers were analyzed by western blotting. Piceamycin was treated on the gemcitabine-resistant AsPC-1 cells with indicated concentrations. α-Tubulin was used as an internal control.

Table 1 Antiproliferative activities of piceamycin against human pancreatic cancer cell lines

Cell lineIC50 (μM)
AsPC-12.08
MiaPaCa-21.13
Panc-11.20

Results are expressed as the calculated half maximal inhibitory concentration (IC50) of piceamycin (μM) treated for 48 h.



Effects of piceamycin on the ACTN4 expression and ACTN4-associated signaling pathways in gemcitabine-resistant AsPC-1 cells

Gemcitabine is commonly used as the first-line chemotherapeutic agent for the treatment of pancreatic cancer in the clinical setting. Therefore, gemcitabine resistance in patients with pancreatic cancer is highly associated with chemotherapeutic failures (Xu et al., 2018; Koltai et al., 2022). To further establish the experimental approach with pancreatic cancer cells in vitro, a previous study assessed gemcitabine sensitivity against pancreatic cancer cell lines (AsPC-1, Panc-1, and MiaPaCa-2) (Hu et al., 2012). Since AsPC-1 cells exhibited the highest IC50 to gemcitabine among the pancreatic cancer cell lines (IC50: AsPC-1 568.354 nM, MiaPaCa-2 7.734 nM, Panc-1 136.786 nM), the AsPC-1 cell line was selected for subsequent experiments to evaluate the involvement of ACTN4 signaling in pancreatic cancers and the antiproliferative effects of piceamycin against pancreatic cancer cells. To further evaluate the effects of piceamycin on gemcitabine-resistant cells, gemcitabine resistance in AsPC-1 cells was evaluated by increasing the gemcitabine concentrations in the parent AsPC-1 cells (Supplementary Fig. 1). The gemcitabine-resistant AsPC-1 cells (IC50: >100 µM) were found to exhibit approximately >30-fold higher resistance to gemcitabine compared to the original AsPC-1 cells (IC50: 3.23 µM). However, piceamycin exerted a potent antiproliferation activity against both parent AsPC-1 cells and gemcitabine-resistant AsPC-1 cells with similar IC50 values (fold difference: 0.66) (Table 2). These data suggest that piceamycin may potentially overcome gemcitabine resistance in pancreatic cancer cells. To confirm whether the antiproliferative activity of piceamycin in gemcitabine-resistant AsPC-1 cells is associated with the expression of ACTN4-related biomolecules, gemcitabine-resistant AsPC-1 cells were treated with piceamycin (1.25 µM) for 48 h, and the corresponding mRNA and protein expressions were evaluated by RNA sequencing (Supplementary Fig. 2) and western blot analysis, respectively. Piceamycin significantly suppressed the mRNA and protein expressions of ACTN4 in gemcitabine-resistant AsPC-1 cells (Fig. 2C; heatmap and normalized values of mRNA expression, Fig. 2D; western blot analysis). In addition, the protein–protein interaction online database search tool (STRING), the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and the heatmap of RNA-seq analysis showed that ACTN4 is significantly associated with the actin polymerization signaling pathway (Fig. 2E-2G, Supplementary Fig. 3; Protein–Protein Interaction). Therefore, the RNA-seq was performed to determine gene expressions of ACTN4-associated biomolecules in piceamycin-treated gemcitabine-resistant AsPC-1 cells (Fig. 2F). The mRNA expressions of actin beta (ACTB), actin gamma1 (ACTG1), and vinculin (VCN) were downregulated by piceamycin treatment in gemcitabine-resistant AsPC-1 cells (Fig. 2F; heatmap, z-score, and normalized mRNA value). Protein expressions of ACTN4, VCN, and ACTB were also downregulated by piceamycin in gemcitabine-resistant AsPC-1 cells (Fig. 2D, 2H). These data suggest that the antiproliferation activity of piceamycin may be in part associated with the suppression of actin polymerization with the ACTN4VCNACTB axis in gemcitabine-resistant AsPC-1 cells (Fig. 2F, 2G).

Table 2 Drug resistant profiles of AsPC-1 cells with resistance to gemcitabine

IC50a (μM) AsPC-1Gemcitabine-resistant
AsPC-1
Fold differenceb
Piceamycin2.081.370.66
Gemcitabine3.23>100>30

aResults are expressed as the calculated half maximal inhibitory concentration (IC50) of piceamycin (μM) and Gemcitabine (μM).

bThe fold difference was calculated as the ratio of IC50 values between gemcitabine-resistant AsPC-1 and parent AsPC-1 cells.



To further evaluate whether piceamycin enhances the sensitivity of gemcitabine-resistant AsPC-1 cells, various piceamycin and gemcitabine concentrations were combined and treated with gemcitabine-resistant AsPC-1 cells for 48 h. Cell proliferation was then measured using the MTT assay, and the CI value was calculated using the Chou–Talalay method (Chou, 2010). Treatment with gemcitabine and piceamycin induced higher antiproliferative activity levels compared to treatment with either drug alone, and the synergistic effects were confirmed by a CI value of <1 (Table 3). These data indicate that the combination of gemcitabine and piceamycin synergistically enhances gemcitabine sensitivity and, therefore, may be effective for the treatment of gemcitabine-resistant AsPC-1 cells.

Table 3 The effect of drug combination on gemcitabine-resistant AsPC-1 cells

Concentration (μM)Combination index (CI values)
PiceamycinGemcitabine
1.2512.50.53138804Synergism
2.5250.54395158Synergism
5501.093662394Nearly additive
101002.283837682Antagonism

Combination index: antagonism (CI >1), additivity (CI=1) and synergism (CI<1).

Cell viability was measured after combined piceamycin and gemcitabine treatment for 48 h in gemcitabine-resistant AsPC-1 cells. Based on cell viability results, CI values were calculated to demonstrate the effect of drug combination on gemcitabine-resistant AsPC-1 cells.



Effects of piceamycin on the expressions of epithelial-mesenchymal transition (EMT) biomarkers in gemcitabine-resistant AsPC-1 cells

As ACTN4-associated genes are involved in the critical steps of cancer cell metastasis (Honda, 2015), the effects of piceamycin on the expressions of focal adhesion and EMT biomarkers were analyzed in gemcitabine-resistant AsPC-1 cells. Focal adhesion-related mRNA expressions (ACTN4, vinculin, ACTB, ACTG, and Rac) were downregulated by the piceamycin treatment in gemcitabine-resistant AsPC-1 cells (Fig. 3A; heatmap, z-score, and normalized mRNA value). Modified KEGG pathway analysis also exhibited the downregulation of focal adhesion-associated mRNA expressions after the piceamycin treatment in gemcitabine-resistant AsPC-1 cells (Fig. 3B). These effects were further confirmed by suppressing focal adhesion-associated protein expressions (ACTN4, VCN, FAK, Rac, and ACTB) following the piceamycin treatment in gemcitabine-resistant AsPC-1 cells (Fig. 2D, 2H, 3C). In addition, piceamycin downregulated the expression of mesenchymal biomarkers (N-cadherin, Slug, and Snail) in gemcitabine-resistant AsPC-1 cells (Fig. 3D). To further investigate the effects of piceamycin on cancer cell metastasis, migration (wound healing) and invasion (transwell) assays were performed by treating gemcitabine-resistant AsPC-1 cells with piceamycin for 48 h. The results revealed that piceamycin effectively inhibited cancer cell migration (Fig. 3E) and invasion (Fig. 3F) in a concentration-dependent manner. Taken together, these data indicate that piceamycin exhibits anti-invasion and antimigration activities by regulating focal adhesion and EMT biomarkers in gemcitabine-resistant AsPC-1 cells.

Figure 3. (A) Heatmap of mRNA expression related to the focal adhesion signaling pathway in gemcitabine-resistant AsPC-1 cells. Gemcitabine-resistant AsPC-1 cells were treated with piceamycin (PCM) (1.25 μM) versus control (PBS with DMSO-treated) for 48 h. The color represents mRNA level using z-score (yellow; positive score; upregulation, blue; negative score; downregulation) and displayed on the column (according to z-score; –2≤z≤2, AVE; average of z-score, STD; standard deviation of z-score, n=3). Normalized value (mRNA level) of Rac2, Rac3, and VAV3. (B) Modified KEGG pathway from Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway of the genes related to focal adhesion signaling pathway from RNA-sequencing data. Gemcitabine-resistant AsPC-1 cells were treated with piceamycin (1.25 μM) for 48 h compared with control (PBS with DMSO-treated). The box colors of the Modified KEGG pathway indicate fold change of mRNA expression. (C) The protein expressions of focal adhesion-related biomarkers (FAK and Rac) were analyzed by western blotting in gemcitabine-resistant AsPC-1 cells. Piceamycin (PCM) was treated in the gemcitabine-resistant AsPC-1 cells with indicated concentrations. α-Tubulin was used as an internal control. (D) The protein expression levels of epithelial-mesenchymal transition (EMT)-related biomarkers (N-cadherin, Slug, and Snail) were analyzed by western blotting in gemcitabine-resistant AsPC-1 cells. Piceamycin was treated on the gemcitabine-resistant AsPC-1 cells with indicated concentrations. α-Tubulin was used as an internal control. (E) Effect of piceamycin on gemcitabine-resistant AsPC-1 cells migration. Monolayers of gemcitabine-resistant AsPC-1 cells were scratched mechanically and treated with piceamycin (indicated concentrations) for 48 h. Representative images of wound closure obtained under a light microscope. All data are presented as mean ± SD (n=3, *p<0.05, **p<0.01). (F) Effect of piceamycin on gemcitabine-resistant AsPC-1 cells invasion. The cells (treated with piceamycin) (at 0, 1, 2, and 5 μM concentration) that invaded to lower chambers were fixed, stained, imaged, and counted. All data are presented as mean ± SD (n=3, *p<0.05) (Scale bars, 50 μm).

Effects of piceamycin on cell cycle regulation and apoptosis in gemcitabine-resistant AsPC-1 cells

To further confirm whether the antiproliferation activity of piceamycin is associated with cell cycle regulation, gemcitabine-resistant AsPC-1 cells were treated with piceamycin for 24 h, and the cell cycle distribution was analyzed by flow cytometry. As shown in Fig. 4A and 4B, the cell population in the G0/G1 phase increased from 58.4% (control) to 74.5% (1 µM, piceamycin) after the piceamycin treatment. Heatmap analysis of RNA sequencing data also indicated that piceamycin suppressed G0/G1 phase-related mRNA expressions (cyclin E, cyclin A, cyclin D, and CDK2) in gemcitabine-resistant AsPC-1 cells (Fig. 4C; heatmap, z-score of cell cycle-related genes, and normalized mRNA value). In addition, the induction of the G0/G1 cell cycle arrest was confirmed by suppressing cell cycle regulators, such as cyclins (cyclin E and D1) and CDKs (CDK2 and CDK4) in gemcitabine-resistant AsPC-1 cells (Fig. 4D; western blot analysis). These findings indicate that the antiproliferation activity of piceamycin is partly correlated with the induction of G0/G1 cell cycle arrest in gemcitabine-resistant AsPC-1 cells.

Figure 4. Piceamycin (PCM) induced G0/G1 cell cycle arrest in gemcitabine-resistant AsPC-1 cells. (A, B) Gemcitabine-resistant AsPC-1 cells were treated with piceamycin (at 0, 1, 2, and 5 μM concentration) for 24 h, stained with PI, and cell cycle arrest was detected by flow cytometry. All data are presented as mean ± SD (n=3, *p<0.05, **p<0.01, ***p<0.001). (C) Heatmap of the genes related to the cell cycle signaling pathway. Z-score comes from RNA-sequencing data treated with piceamycin (1.25 μM) for 48 h in gemcitabine-resistant AsPC-1 cells. The color represents z-score (yellow; positive score; upregulation, blue; negative score; downregulation). The column indicates z-score (–2≤z≤2) related with cell cycle signaling pathway. Normalized value (mRNA level) of CDK2 and Cyclin D1. All data are presented as mean ± SD (n=3). (D) The effect of piceamycin on the G0/G1 phase cell cycle arrest was confirmed by observing the cell cycle regulatory proteins by western blotting. Piceamycin was treated with indicated concentrations in the gemcitabine-resistant AsPC-1 cells. α-Tubulin was used as an internal control.

Recent studies suggest that ACTN4-mediated signaling is also associated with the control of apoptosis in cancer cells (Lomert et al., 2018; Zhao et al., 2019). Based on ACTN4 regulation by piceamycin, we further investigated whether piceamycin can induce apoptosis through long-term treatment in gemcitabine-resistant AsPC-1 cells. Gemcitabine-resistant AsPC-1 cells were treated with piceamycin for 48 h, and flow cytometric analysis was performed after double staining with Annexin V-FITC and PI. Piceamycin (10 µM) effectively increased the apoptotic cell deaths including those during the early and late apoptosis by 35.5% in gemcitabine-resistant AsPC-1 cells (Fig. 5A, 5B). To further confirm the molecular mechanism of piceamycin-induced apoptosis in gemcitabine-resistant AsPC-1 cells, the effects of piceamycin on caspases were determined using enzymatic activity and western blot analysis. As depicted in Fig. 5C, the piceamycin (10 µM) treatment significantly enhanced the caspase 3 and 7 activities. Western blot analysis also exhibited the increased expression of cleaved caspase 3 after the piceamycin treatment; the subsequent suppression of Bcl-2, a cell-survival protein, and MMP2 expressions; and the upregulation of Bax expression. Cytochrome c accumulation also increased after the piceamycin treatment, which suggests that the apoptotic cell death by piceamycin is partly associated with mitochondrial-dependent apoptosis in gemcitabine-resistant AsPC-1 cells (Fig. 5D). Taken together, these data indicate that the induction of apoptosis by long-term exposure of piceamycin may be correlated with caspase and Bax activation and Bcl-2 suppression in gemcitabine-resistant AsPC-1 cells. In addition, piceamycin effectively inhibited the colony formation of gemcitabine-resistant AsPC-1 cells in a concentration-dependent manner (Fig. 5E).

Figure 5. Induction of apoptosis by piceamycin (PCM) in gemcitabine-resistant AsPC-1 cells. Gemcitabine-resistant AsPC-1 cells were treated with piceamycin at different concentrations (0, 0.1, 1, 2, 5, and 10 μM) for 48 h. (A) Cell apoptosis was measured by flow cytometry using Annexin V-FITC/PI staining. Representative images of Annexin V-FITC/PI staining. (B) Statistical analysis of the cell apoptosis rate at 48 h. All data are presented as mean ± SD (n=3, *p<0.05, **p<0.01). (C) Effect of piceamycin on caspase activity in gemcitabine-resistant AsPC-1 cells. Gemcitabine-resistant AsPC-1 cells (80% confluent) were treated with piceamycin (10 μM) for 48 h and treated with caspase 3/7 reagents. The enzymatic activity of piceamycin-treated AsPC-1 cells was evaluated. All data are presented as mean ± SD (n=3, **p<0.01). (D) The effect of piceamycin on the expression of apoptotic biomarkers in gemcitabine-resistant AsPC-1 cells. The cells were treated with piceamycin versus control (PBS with DMSO-treated) for 48 h and the expression levels of the mitochondrial apoptosis regulatory proteins were detected by western blotting. α-Tubulin was used as an internal control. (E) The effect of piceamycin on colony formation in gemcitabine-resistant AsPC-1 cells. Gemcitabine-resistant AsPC-1 cells were treated with various concentrations of piceamycin (0, 1, 5, and 10 μM) for 48 h. When colony formation was visible, the medium was removed, stained, and imaged. All data are presented as mean ± SD (n=3, *p<0.05) (Scale bars, 50 μm).

Antiproliferation activity of piceamycin in PDPCOs

To further evaluate the in vivo mimic antiproliferation activity of piceamycin, PDPCO models were employed. PDPCOs were established as previously described (Lee et al., 2022) and provided by the cell line bank of Seoul National University (Seoul, Korea). Primarily, the effects of gemcitabine on PDPCO proliferation were investigated. Among the tested PDPCOs, the organoid SNU-4340-TO was found to be relatively resistant to gemcitabine-based on the drug response (area under curve [AUC], red; resistant, blue; sensitive) (Fig. 6A). However, piceamycin exhibited an effective growth-inhibitory activity on all PDPCOs (Fig. 6B). In addition, the effects of piceamycin on inducing apoptosis were determined in the organoid SNU-4340-TO, the most gemcitabine-resistant organoid, among the tested organoids. Various piceamycin concentrations were administered for 72 h in the organoid SNU-4340-TO, and the apoptotic cell death was detected by flow cytometry with Annexin V−FITC and PI double staining. Piceamycin significantly increased the total cell death (Annexin V-positive and/or PI-positive cells) in a concentration-dependent manner (Fig. 6C). These data suggest that piceamycin may effectively inhibit the growth of gemcitabine-resistant PDPCOs.

Figure 6. Antiproliferative activity of piceamycin in PDPCOs.(A) Drug response (AUC) heatmap based on gemcitabine treatment. PDPCOs (SNU-4206, SNU-4305-TO, SNU-4425-TO, and SNU-4340-TO) were treated with gemcitabine (0.01 μM-100 μM) for 72 h and the drug sensitivity was measured using cell-titer glow, 3D reagent. Drug response heatmap (red; resistant, blue; sensitive). (B) PDPCOs (SNU-4206, SNU-4305-TO, SNU-4425-TO, and SNU-4340-TO) were treated with various concentrations of piceamycin (PCM) and detected by 3D cell titer-glow assay after 72 h. All data are presented as mean ± SD (n=3, *p<0.05, **p<0.01). (C) The level of cell apoptosis was determined by flow cytometry using Annexin V-FITC/ propidium iodide (PI) staining in PDPCO (SNU-4340-TO).
DISCUSSION

Pancreatic cancer is considered one of the most intractable cancers (Park et al., 2021). Despite recent advances in therapeutic approaches to treat pancreatic cancer, the survival rate of patients with pancreatic cancer remains significantly low (Zhao and Liu, 2020; Park et al., 2021). The limitation in the early cancer diagnosis is one of contributing factors, making it difficult to perform surgical resection.

Gemcitabine, an agent for DNA damage, is widely used as standard first-line chemotherapy for patients with unresectable locally advanced or metastatic pancreatic cancer (Pereira and Corrêa, 2018). However, long-term exposure to gemcitabine results in the emergence of acquired gemcitabine resistance in patients with pancreatic cancer. Therefore, searching for novel agents in gemcitabine-resistant pancreatic cancer cells has become an important strategy in improving the therapeutic outcomes for patients with pancreatic cancer. Thus, the present study was designed to evaluate the effects of piceamycin on inhibiting the growth of gemcitabine-resistant pancreatic AsPC-1 cells.

Previous studies reported that piceamycin exhibits antiproliferative activity against a panel of human cancer cell lines. However, only a few studies have been conducted to elucidate the growth-inhibitory activity of piceamycin against pancreatic cancer cells and its underlying molecular mechanisms (Schulz et al., 2009; Shin et al., 2020). We found that piceamycin effectively inhibited the proliferation of both AsPC-1 cells and gemcitabine-resistant AsPC-1 cells in vitro. Furthermore, the Gene Ontology functional analysis (extracellular matrix organization, microtubule, cell leading edge, and collagen-containing extracellular matrix) and western blot analysis exhibited that focal adhesion and metastasis pathways were suppressed by piceamycin in gemcitabine-resistant AsPC-1 cells. In addition, piceamycin effectively inhibited the invasion and migration of gemcitabine-resistant AsPC-1 cells by modulating focal adhesion and EMT biomarkers (mRNA and protein). These findings suggest that piceamycin may be effective in suppressing the growth of gemcitabine-resistant pancreatic cancer cells.

Cell migration and invasion are major processes in cancer cell metastasis from the primary site to distant organs (Bravo-Cordero et al., 2012). Recent studies suggest that ACTN4 is also involved in cancer metastasis and invasion (Peng et al., 2019; Huang et al., 2020; Tozuka et al., 2022). Higher ACTN4 expression in patients with pancreatic cancer was associated with lower survival rates, indicating that ACTN4 suppression may help overcome metastatic pancreatic cancer. In the present study, ACTN4 expression in gemcitabine-resistant AsPC-1 cells was downregulated by piceamycin. Therefore, ACTN4 inhibition by piceamycin may be a promising approach for treating metastatic pancreatic cancers. Since ACTN4 plays a role in the actin polymerization process, the present study further evaluated whether piceamycin affects the actin polymerization axis. As a result, piceamycin was found to effectively downregulate the expression of the ACTN4VCNACTB axis in gemcitabine-resistant AsPC-1 cells. These findings suggest that piceamycin may be effective in suppressing the metastasis of gemcitabine-resistant pancreatic cancer cells.

PDPCOs mimic the 3D organ-type structures that are considered useful tools in evaluating biological events. Piceamycin exerted strong growth-inhibitory activity against various PDPCOs, including gemcitabine-resistant organoids. Based on these findings, piceamycin is assumed to effectively exert an antitumor activity against gemcitabine-resistant pancreatic cancers. To the best of our knowledge, this is the first study to confirm the antiproliferation activity of piceamycin in PDPCOs.

In summary, piceamycin effectively suppressed the ACTN4 expression and subsequently inhibited metastatic potential in gemcitabine-resistant AsPC-1 cells. Its antiproliferative activity was also associated with the induction of G0/G1 cell cycle arrest and mitochondrial apoptotic cell death in gemcitabine-resistant AsPC-1 cells. The combination of piceamycin and gemcitabine exhibited synergistic antiproliferation activity against gemcitabine-resistant AsPC-1 cells. Piceamycin also effectively inhibited the growth of PDPCOs and a gemcitabine-resistant PDPCO. Therefore, piceamycin has a strong potential as an antitumor agent to effectively inhibit gemcitabine-resistant cancer cells and an alternative candidate for the development of combined targeted therapy for patients with gemcitabine-resistant pancreatic cancer.

ACKNOWLEDGMENTS

This research was supported by the Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (0720213063) and by the MSIT (2021R1A4A2001251).

CONFLICT OF INTEREST

The authors declare there is no conflict of interest.

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