Abstract
Recent evidence has implicated microRNAs (miRNAs) as potentially significant players in the acquisition of cancer-drug resistance in pancreatic and other cancers. To evaluate the potential contribution of miRNAs in acquired resistance to cisplatin in pancreatic cancer, we compared levels of more than 2000 human miRNAs in a cisplatin-resistant cell line (BxPC3-R) derived from parental (BxPC3) cells by step-wise exposure to increasing concentrations of the drug over more than 20 passages. The acquired drug resistance was accompanied by significant changes in the expression of 57 miRNAs, of which 23 were downregulated and 34 were upregulated. Employing a hidden Markov model (HMM) algorithm, we identified downregulation of miR-374b as likely being directly involved in acquisition of the drug-resistant phenotype. Consistent with this prediction, ectopic overexpression of miR-374b in the resistant BxPC3-R cells restored cisplatin sensitivity to levels approaching those displayed by the BxPC3 parental cells. The results are consistent with a growing body of evidence implicating miRNAs in acquired cancer-drug resistance and with the potential therapeutic value of these small regulatory RNAs in blocking and/or reversing the process.
Similar content being viewed by others
Introduction
The ability of cancer cells to acquire resistance to chemotherapy is one of the most pressing and challenging issues in contemporary clinical oncology.1 The problem is especially acute for pancreatic cancer where tumors are unresectable in over 80% of patients making radio/chemotherapy the only viable alternatives.2 Recent studies in pancreatic3, 4, 5 and other cancers6, 7 have identified microRNAs (miRNAs) as potentially important regulatory elements underlying coordinated changes in gene expression associated with acquired drug resistance. As such, miRNAs have been proposed as a potential new class of agents for targeted treatment of acquired drug resistance.8, 9, 10
We report here evidence for the contribution of miRNAs in the acquisition of cisplatin resistance in a pancreatic cell line (BxPC3-R) developed by step-wise increasing concentrations of the drug over more than 20 passages.11 Using a hidden Markov model (HMM) algorithm to find miRNAs most likely contributing to gene expression changes associated with cisplatin resistance in BxPC3-R cells, we identified downregulation of miR-374b as putatively involved in acquisition of the drug-resistant phenotype. Consistent with this prediction, ectopic overexpression of miR-374b in the resistant BxPC3-R cells restored cisplatin sensitivity to levels approaching those displayed by the BxPC3 parental cells. Our results are consistent with the growing body of evidence indicating that changes in miRNA levels can have a significant role in the acquired resistance of cancer cells to therapeutic drugs and that therapies designed to modulate levels of these small regulatory RNAs may be of significant therapeutic value in blocking and/or reversing acquired drug resistance.
Materials and methods
Cell culture
The cisplatin-resistant pancreatic cancer cell line BxPC3-R was developed from parental human pancreatic adenocarcinoma BxPC3 cell line (ATCC CRL-1687) by step-wise treatment as previously described.11 Cells were cultured at 37 °C in a humidified atmosphere containing 5% CO2. Parental cells were maintained in RPMI-1640 (Mediatech, Manassas, VA) supplemented with 10% FBS (fetal bovine serum; Atlanta Biologicals, Lawrenceville, GA) and 1% antibiotic-antimycotic solution (Mediatech). Cisplatin-resistant cells were routinely maintained in the full RPMI medium supplemented with 0.6 μm cisplatin. Before harvesting for experiments, BxPC3-R cells were grown 1 × in cisplatin-free medium.
Growth inhibition assay
The growth inhibitory effects of cisplatin on the BxPC3 and BxPC3-R were determined by measuring cell viability using the TOX-8 reagent (Resazurin based in vitro toxicology assay kit, Sigma-Aldrich, St Louis, MO). Cells were plated in 100 μl media on 96-well plates at a density of 3000 cells per well. Subsequent to 24 h incubation, the cells were exposed to different concentrations of cisplatin in total volume of 200 μl per well at 37 °C under a 5% CO2 atmosphere for 72 h. Tox-8 (20 μl) was then added to each well; incubation continued for an additional 4 h and fluorescence was read using the Synergy 4 (Biotek, Winooski, VT) microplate reader (λex=560 nm, λem=590 nm). Blank-corrected fluorescence signals for treated cells were normalized to control wells (no drug treatment) and expressed as a percentage of the control (% cell viability). The results from three experiments were presented as mean ±s.e.m.
miRNA transfection
Transfection of the miR-374b mimetic and the negative control miRNA (both from Applied Biosystems, ThermoFisher Scientific, Grand Island, NY) at final concentrations of 30 nm was carried out using the Lipofectamine 2000 Reagent (Invitrogen, Carlsbad, CA) following the manufacturer’s instructions. Cells were harvested for subsequent analyses 48 h after the transfection. All transfection experiments were carried out in triplicate.
RNA extraction, miRNA microarray analysis
Gene expression profiling of BxPC3 and BxPC3-R cells was performed using GeneChip miRNA 3.0 Array (Affymetrix, Santa Clara, CA). Cellular RNA enriched for small RNAs (<200 nt) was isolated using the mirVana miRNA isolation kit according to the manufacturer's instructions (ThermoFisher Scientific). The concentration and quality of miRNA were determined using the Small RNA Assay in the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA). In all, 400 ng of cellular RNA enriched for small RNAs was labeled using the FlashTag Biotin HSR Labeling Kit, hybridized for 18 h at 48 °C (rotation 60 r.p.m.) on the GeneChip miRNA 3.0 Array, washed in the Affymetrix Fluidics Station 450 and scanned using the Affymetrix GeneChip Scanner 3000 7G (all from Affymetrix) as previously described.12 Microarray experiments were performed in two replicates per each cell type. The data were analyzed with Expression Console software Build 1.2.1.20 (Affymetrix) using the default analysis setting for RMA+DAGB workflow and submitted to the Gene Expression Omnibus repository (GEO, available under the series accession number GSE79506).
Computational analysis
MiRNAs differentially expressed between parental BxPC3 and cisplatin-resistant BxPC3-R cells were identified by differential expression analysis of the normalized miRNA 3.0 Array data using the absolute fold change (FC) ⩾2 and ANOVA P-value <0.05 as a threshold.
The 561 annotated genes previously reported as upregulated in BxPC3-R cells relative to BxPC3 cells11 (data are publicly available under Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/; series accession number GSE73978) were uploaded to miRvestigator (http://mirvestigator.systemsbiology.net)13 and analyzed for overrepresented sequence motifs to identify miRNAs most likely involved in the regulation of these genes through their complementary seeds. miRvestigator was employed using the following parameters: Weeder Parameters: Motif Sizes: 8 bp; Weeder Model: Default; Seed Models: 6mer, 7mer, 8mer; Wobble Base-Pairing: No. The top 10 miRNAs complementary to the overrepresented sequence motif were identified and compared with the list of miRNAs found to be differentially expressed between BxPC3 and BxPC3-R cells by miRNA microarray profiling.
Results
Significant changes in the expression of miRNAs are associated with the acquisition of cisplatin resistance in BxPC3-R cells
Unsupervised hierarchical clustering of the expression profiles of miRNAs was carried out on two biological replicates each of the parental cisplatin-sensitive BxPC3 cells and derived resistant BxPC3-R cells (Figure 1). Using a threshold of ⩾2-FC, 57 miRNAs were identified as being significantly differentially expressed (P<0.05) between the BxPC3 and BxPC3-R cells. Of these, 23 miRNAs were downregulated and 34 were upregulated (Table 1).
Computational analysis of gene expression changes between BcPC3 and BcPC3-R cells implicates miR-374b in the acquisition of cisplatin resistance
We previously developed a pancreatic cancer cell line BxPC3-R with ~15-fold increase in resistance to cisplatin by exposing the well-characterized pancreatic adenocarcinoma cell line BxPC3 to step-wise increasing concentrations of the drug over more than 20 passages.11 Comparative gene expression analysis determined that 1565 genes were differentially expressed between the cisplatin-resistant BxPC3-R cells relative to the pre-selected BxPC3 cells (Gene Expression Omnibus series accession number GSE73978).11 Of these, 561 genes were significantly upregulated in the resistant BxPC3-R cells and many of these upregulated genes were found to have been previously associated with acquired drug resistance.11
In the current study, the 561 upregulated genes were uploaded to miRvestigator13 to detect overrepresented sequence motifs within the genes' untranslated leader regions and to putatively identify those miRNAs most likely associated with their regulation. The miRvestigator algorithm identified a significantly overrepresented consensus sequence present among 31% of the upregulated gene sequences (5’-UAUUGUAA-3’) (Figure 2).
The 10 miRNAs identified by miRvestigator as containing sequences most significantly complementary to this consensus sequence are presented in Table 2. Of these, miR-374b was among the miRNAs most significantly downregulated in the BxPC3-R-resistant cells (FC=−3.16, Table 1). Moreover, miR-374b was found to have highly significant overall complementarity with the consensus sequence (P<7.3e−04). Indeed, the consensus sequence is an exact compliment to the miR-374b 7-mer seed sequence (Table 2). Combined, these findings strongly implicated the downregulation of miR-374b in BxPC3-R cells with acquired cisplatin resistance.
Ectopic overexpression of miR-374b in cisplatin-resistant BxPC3-R cells decreases drug resistance to levels approaching those in pre-selected BxPC3 cells
To experimentally test the hypothesis that downregulation of miR-374b has contributed to acquired cisplatin resistance in BxPC3-R cells, we ectopically overexpressed an miR-374b mimetic in BxPC3-R cells and subsequently tested the sensitivity of the cells to increasing concentrations of cisplatin relative to controls.
The results presented in Figure 3 demonstrate that sensitivity to cisplatin was significantly increased in BxPC3-R cells in which miR-374b was ectopically overexpressed. The sensitivity of the miR-374b-transfected cells to cisplatin was not significantly different from the parental BxPC3 cells at the highest level of drug tested (4.5 μm) (P=0.25). In contrast, cells transfected with the mock miRNA (negative control) maintained a level of cisplatin resistance statistically indistinguishable from the BxPC3-R-resistant cells. These results are consistent with the hypothesis that downregulation of miR-374b is a significant factor in the acquired cisplatin resistance of BxPC3-R cells.
Discussion
Recent evidence has implicated miRNAs as potentially significant players in the acquisition of cancer-drug resistance in pancreatic3, 4, 5 and many other cancer types.6, 7 In an effort to further evaluate the potential contribution of miRNAs in acquired drug resistance in pancreatic cancer, we compared levels of over 2000 human miRNAs in a well-characterized pancreatic cell line, BxPC3, and a cisplatin-resistant cell line (BxPC3-R) derived from BxPC3 cells by step-wise exposure to increasing concentrations of the drug over more than 20 passages.11 We found that the acquired resistance of BxPC3 cells to cisplatin was accompanied by significant (P<0.01) changes in the expression of 57 miRNAs, of which 23 were downregulated and 34 were upregulated. It is possible that many, if not all of these differentially expressed miRNAs, may have contributed either directly or indirectly to the acquisition of drug resistance in BxPC3-R cells. Indeed, several of the miRNAs differentially expressed between BxPC3-R and BxPC3 cells have been previously implicated in acquired drug resistance in pancreatic (for example, miR-7,5 miR-21 (refs. 14, 15) and miR-196a5) and other cancers (for example, miR-21,16 miR-30c,17 miR-122 (ref. 18) and miR-326 (ref. 19)).
Because experimental validation of the functional significance of each of the 57 differentially expressed miRNAs associated with acquired cisplatin resistance in BxPC3-R cells would be a monumental task beyond the scope of the present study, we sought a computational approach that could narrow focus to those most likely implicated in the regulation of the majority of genes differentially expressed between BxPC3 and BxPC3-R cells. miRvestigator is a HMM algorithm that systematically computes a similarity P-value for each unique miRNA seed sequence from the miRNA database to an overrepresented sequence motif identified within the 3′-UTR of the query genes.13 In our case, the query genes applied to the algorithm were the 561 genes significantly upregulated in the BxPC3-R-resistant cells.
The miRvestigator algorithm identified the consensus sequence 5′-UAUUGUAA-3′ as being present within the untranslated leader regions of 31% of upregulated genes. This motif was identified as pairing significantly with the seed regions of a number of miRNAs including miR-374b, one of the most significantly downregulated miRNAs in BxPC3-R-resistant cells (Table 1).
The computational prediction that downregulation of miR-374b likely contributed to the acquisition of resistance to cisplatin in BxPC3-R cells was experimentally tested by transfection of miR-374b into BxPC3-R cells and subsequently measuring cisplatin sensitivity of these cells relative to controls. The results demonstrated that miR-374b transfection significantly reduced drug resistance in BxPC3-R cells to levels approaching those of the parental BxPC3 cells.
Mir-374b is predicted to directly target >7000 genes (http://www.microrna.org/) and downregulation of miR-374b, like most miRNAs, is predicted to result in upregulation of directly targeted genes.20, 21 Of the 561 genes upregulated in BxPC3-R cells, 201 are predicted to be directly targeted by miR-374b (Supplementary Table S1). Among these are genes previously implicated in cisplatin resistance including ATP7A (ATPase, Cu++ Transporting, Alpha Polypeptide)22 and CLU (Clusterin).23 This is not to say that these are the only genes likely involved in miR-374b-mediated acquisition of drug resistance nor that miR-374b is the only miRNA contributing to the process. Rather, emerging evidence indicates that drug resistance, like cancer onset and progression, is a system-wide process and not necessarily attributable to changes in the expression of one or a few genes.24 Just as there are multiple molecular pathways involved in acquired drug resistance, there are likely to be multiple pathways by which drug sensitivity can be restored. The growing body of evidence for the involvement of miRNAs in acquired drug resistance6, 7, 8, 10, 21 supports the systems view and identifies miRNAs as regulatory elements of potentially significant therapeutic value.
References
Dizon DS, Krilov L, Cohen E, Gangadhart T, Ganz PA, Hensing TA et al. Clinical cancer advances 2016: annual report on progress against cancer from the American Society of Clinical Oncology. J Clin Oncol 2016; 34: 987–1011.
Evans DB, Abbruzzese JL, Willett CG . Cancer of the pancreas. In: Devita VT, Hellman S, Rosenberg SA (eds). Cancer: Principles and Practice of Oncology. Lippincott-Raven: Philadelphia, PA, USA, 2014, pp 1126–1161.
Hasegawa S, Eguchi H, Nagano H, Konno M, Tomimaru M, Wada H et al. MicroRNA-1246 expression associated with CCNG2-mediated chemoresistance and stemness in pancreatic cancer. Brit J Cancer 2014; 111: 1572–1580.
Xia J, Sarkar FH, Wang Z . Emerging role of microRNA in pancreatic cancer. Pancreat Disord Ther 2012; 2: e114.
Singh S, Chitkara D, Kumar V, Behrman SW, Mahato RI . miRNA profiling in pancreatic cancer and restoration of chemosensitivity. Can Lett 2013; 334: 211–220.
Li H, Yang BB . MicroRNA in drug resistance. Oncoscience 2014; 1: 3–4.
Ma J, Dong C, Ji C . MicroRNA and drug resistance. Can Gene Ther 2010; 17: 523–531.
Mishra PJ . The miRNA–drug resistance connection: a new era of personalized medicine using noncoding RNA begins. Pharmacogenomics 2012; 13: 1321–1324.
Hong L, Han Y, Zhang H, Zhao Q, Wu K, Fan D . MicroRNA-21: a therapeutic target for reversing drug resistance in cancer. Expert Opin Ther Targets 2013; 17: 1073–1080.
To KKW . MicroRNA: a prognostic biomarker and a possible druggable target for circumventing multidrug resistance in cancer chemotherapy. J Biomed Sci 2013; 20: 99.
Mezencev R, McDonald J . Resistance of pancreatic cancer cells to cisplatin displays cell context dependent variety of mechanisms (submitted).
Shahab SW, Matyunina LV, Hill CG, Wang L, Mezencev R, Walker LD et al. The effects of microRNA transfections on global patterns of gene expression in ovarian cancer cells are functionally coordinated. BMC Med Genomics 2012; 5: 33.
Plaisier CL, Bare JC, Baliga NS . miRvestigator: web application to identify miRNAs responsible for co-regulated gene expression patterns discovered through transcriptome profiling. Nucleic Acids Res 2011; 39: W125–W131.
Hwang JH, Voortman J, Giovannetti E . Identification of microRNA-21 as a biomarker for chemoresistance and clinical outcome following adjuvant therapy in resectable pancreatic cancer. PLoS One 2010; 5: e10630.
Giovannetti E, Funel N, Peters GJ . MicroRNA-21 in pancreatic cancer: correlation with clinical outcome and pharmacologic aspects underlying its role in the modulation of gemcitabine activity. Cancer Res 2010; 70: 4528–4538.
Gao W, Lu X, Liu L, Xu J, Feng D, Shu Y . MiRNA-21: a biomarker predictive of platinum-based adjuvant chemotherapy response in patients with non-small cell lung cancer. Cancer Biol Ther 2012; 13: 330–340.
Ma J, Dong C, Ji C . MicroRNA and drug resistance. Can Gen Ther 2010; 17: 523–531.
Xu Y, Xia F, Ma L . MicroRNA-122 sensitizes HCC cancer cells to adriamycin and vincristine through modulating expression of MDR and inducing cell cycle arrest. Cancer Lett 2011; 310: 160–169.
Liang Z, Wu H, Xia J . Involvement of miR-326 in chemotherapy resistance of breast cancer through modulating expression of multidrug resistance-associated protein 1. Biochem Pharmacol 2010; 79: 817–824.
Bartel DP . MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 2004; 116: 281–297.
Ling H, Fabbri M, Carlin GA . MicroRNAs and other non-coding RNAs as targets of anticancer drug development. Nat Rev Drug Dis 2013; 12: 847–865.
Inoue Y, Matsumoto H, Yamada S, Kawai K, Suemizu H, Gika M et al. Association of ATP7A expression and in vitro sensitivity to cisplatin in non-small cell lung cancer. Oncol Lett 2010; 1: 837–840.
Hara I, Miyake H, Gleave ME, Kamidono S . Introduction of clusterin gene into human renal cell carcinoma cells enhances their resistance to cytotoxic chemotherapy through inhibition of apoptosis both in vitro and in vivo. Jpn J Cancer Res 2001; 92: 1220–1224.
Du W, Elemento O . Cancer systems biology: embracing complexity to develop better anticancer therapeutic strategies. Oncogene 2014; 34: 3215–3225.
Acknowledgements
This work was supported by funds from the Deborah Nash Endowment and the Mark Light Fellowship.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing interests
The authors declare no conflict of interest.
Additional information
Supplementary Information accompanies the paper on Cancer Gene Therapy website
Supplementary information
Rights and permissions
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/
About this article
Cite this article
Schreiber, R., Mezencev, R., Matyunina, L. et al. Evidence for the role of microRNA 374b in acquired cisplatin resistance in pancreatic cancer cells. Cancer Gene Ther 23, 241–245 (2016). https://doi.org/10.1038/cgt.2016.23
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/cgt.2016.23
This article is cited by
-
Small RNA sequencing analysis of peptide-affinity isolated plasma extracellular vesicles distinguishes pancreatic cancer patients from non-affected individuals
Scientific Reports (2023)
-
The role of miR-153 and related upstream/downstream pathways in cancers: from a potential biomarker to treatment of tumor resistance and a therapeutic target
Medical Oncology (2022)
-
A Systematic Review of Applications of Machine Learning in Cancer Prediction and Diagnosis
Archives of Computational Methods in Engineering (2021)
-
Effect of miR-26b-5p on cis-diamine dichloroplatinum–induced ovarian granulosa cell injury by targeting MAP3K9
In Vitro Cellular & Developmental Biology - Animal (2020)
-
MiR-629 promotes human pancreatic cancer progression by targeting FOXO3
Cell Death & Disease (2017)