Altering cancer transcriptomes using epigenomic inhibitors
© Gaddis et al.; licensee BioMed Central. 2015
Received: 27 November 2014
Accepted: 8 January 2015
Published: 24 February 2015
Due to the hyper-activation of WNT signaling in a variety of cancer types, there has been a strong drive to develop pathway-specific inhibitors with the eventual goal of providing a chemotherapeutic antagonist of WNT signaling to cancer patients. A new category of drugs, called epigenetic inhibitors, are being developed that hold high promise for inhibition of the WNT pathway. The canonical WNT signaling pathway initiates when WNT ligands bind to receptors, causing the nuclear localization of the co-activator β-catenin (CTNNB1), which leads to an association of β-catenin with a member of the TCF transcription factor family at regulatory regions of WNT-responsive genes. The TCF/β-catenin complex then recruits CBP (CREBBP) or p300 (EP300), leading to histone acetylation and gene activation. A current model in the field is that CBP-driven expression of WNT target genes supports proliferation whereas p300-driven expression of WNT target genes supports differentiation. The small molecule inhibitor ICG-001 binds to CBP, but not to p300, and competitively inhibits the interaction of CBP with β-catenin. Upon treatment of cancer cells, this should reduce expression of CBP-regulated transcription, leading to reduced tumorigenicity and enhanced differentiation.
We have compared the genome-wide effects on the transcriptome after treatment with ICG-001 (the specific CBP inhibitor) versus C646, a compound that competes with acetyl-coA for the Lys-coA binding pocket of both CBP and p300. We found that both drugs cause large-scale changes in the transcriptome of HCT116 colon cancer cells and PANC1 pancreatic cancer cells and reverse some tumor-specific changes in gene expression. Interestingly, although the epigenetic inhibitors affect cell cycle pathways in both the colon and pancreatic cancer cell lines, the WNT signaling pathway was affected only in the colon cancer cells. Notably, WNT target genes were similarly downregulated after treatment of HCT116 with C646 as with ICG-001.
Our results suggest that treatment with a general HAT inhibitor causes similar effects on the transcriptome as does treatment with a CBP-specific inhibitor and that epigenetic inhibition affects the WNT pathway in HCT116 cells and the cholesterol biosynthesis pathway in PANC1 cells.
KeywordsEpigenetic inhibitor Histone acetylation WNT signaling C646 ICG-001 Colon cancer Pancreatic cancer TCF7L2 Cholesterol biosynthesis
Due to the hyper-activation of WNT signaling in a variety of cancer types [1, 2], there has been a strong drive to develop antagonists of WNT signaling for cancer treatment. Standard inhibitors of the WNT signaling pathway include biologic inhibitors, such as small interfering RNAs, antibodies, and recombinant proteins, and chemical inhibitors, such as NSAIDs, vitamins, and polyphenols, that have fairly general (or unknown) targets [1, 3, 4]. However, a new category of drugs to target the WNT pathway is being developed that holds high promise as chemotherapeutics. These drugs, called epigenetic inhibitors, function to modify chromatin structure. Chromatin is composed of nucleosomes, which are comprised of 146 bp of DNA wrapped around eight core histone proteins (two copies each of H2A, H2B, H3, and H4). The N terminal tails of the core histones that constitute the nucleosome are subject to various different types of modifications that can influence chromatin structure and either enhance or inhibit the ability of transcription factors to bind to and regulate their target genes. The pattern of histone modifications throughout the genome, in combination with the pattern of DNA methylation, is called the epigenome. Recent studies have revealed that different histone modifications are associated with active vs. silenced chromatin, that different cell types show different epigenomic patterns of silenced vs. active chromatin, and that changes in chromatin structure can have a dramatic effect on cell proliferation, differentiation, and survival. One widely studied histone modification is acetylation; histone acetylation is a critical regulatory mechanism of gene expression and plays an important role in gene expression. In fact, acetylation of histone H3 on lysine 27 is the epigenetic modification that most precisely identifies distal regulatory regions that serve as active enhancers . Because cancer genomes show changes in histone acetylation patterns, there is great interest in the use of acetylation inhibitors that inhibit signaling pathways linked to human cancers for epigenetic therapy .
ICG-001 and C646 have similar effects on the transcriptome of HCT116 colon cancer cells
Constitutive activation of WNT target genes via a TCF/β-catenin/CBP complex is thought to be a major driver of colorectal cancer. Therefore, it has been proposed that treatment of colon cancer cells with ICG-001 should specifically inhibit the WNT pathway (by preventing recruitment of the co-activator CBP to TCF/β-catenin target genes) and reduce the tumorigenicity of the cells. In support of this hypothesis, Emami et al. have shown that ICG-001 reduces growth of colon carcinoma cells in culture and reduces the formation of colon and small intestinal polyps in a mouse model system. As noted above, CBP is highly related to another HAT called p300 and many studies have shown similar functions for p300 and CBP . In fact, a ChIP-seq analysis of p300 and CBP in T98G glioblastoma cells immediately after release from serum starvation arrest showed that almost all of the CBP genomic binding sites were also bound by p300 . However under the tested conditions, a small set of genomic sites were preferentially bound by either CBP or p300, suggesting that there might be some specificity in their action. It is also possible that cell type plays a critical role in specifying CBP vs. p300 contributions to regulating the transcriptome. For example, approximately 50% of Rubinstein-Taybi syndrome patients have mutations in CBP but only 3% of patients have mutations in p300 . Of course, functional specificity can also occur post-DNA binding because the two HATs only share extensive, but not complete, homology. If, for example, CBP and p300 recruit different interaction partners they could have opposite effects on transcription at a given promoter. In support of this hypothesis, Ma et al. have shown that both CBP and p300 can bind to the BIRC5 promoter but they have opposite effects on transcription .
ICG-001 and C646 have similar effects on the transcriptome of PANC1 cells
Effectiveness of the epigenetic inhibitors in reverting a tumor cell phenotype
Direct targeting of a component of the transcription complex that mediates WNT signaling
Recent studies have shown large changes in the epigenomic patterns in normal vs. cancer cells, suggesting that epigenetic therapy may be commonly applicable to treatments of various cancers. Drugs that target epigenetic regulators are being developed [27–29], some of which are moving into clinical trials. However, the specificity of action of many of these drugs has not yet been thoroughly examined. In particular, genome-wide analyses of their effects have not been determined. In our study, we compare the effects of treatment with C646, which is thought to compete with acetyl-coA for the Lys-coA binding pocket of both p300 and CBP  to the effects of ICG-001, which specifically binds to CBP and prevents its interaction with the co-activator β-catenin. Theoretically, ICG-001 is expected to be of higher specificity than C646 because it should only affect β-catenin/CBP-driven transcription whereas C646 should affect all genes regulated by either CBP or p300, regardless of whether β-catenin is involved. However, it is possible that ICG-001 has broader effects than anticipated if the drug affects the ability of CBP to interact with other as-of-yet unknown co-activators. In addition, we note that CBP and p300 can acetylate non-histone proteins ; thus, both compounds could also have effects on non-chromatin bound proteins. Although we initially expected cells to respond differently to C646 and ICG-001, our results suggest that generally these two drugs have similar effects on the transcriptome of tumor cells. However, we did identify some cell-specific and drug-specific responses after epigenetic inhibition.
We observed dramatic effects on the transcriptome upon treatment of HCT116 colon cancer cells with either ICG-001 or C646, with thousands of genes showing differential expression. Interestingly, the responses to the two drugs were quite similar overall, with both drugs causing a reduction in certain genes involved in the WNT pathway. Because ICG-001 affects only CBP-driven transcription and not p300-driven transcription, these results suggest that perhaps the majority of the WNT-related active regulatory elements in HCT116 cells are bound by β-catenin/CBP complexes. We did identify a set of approximately 500 genes whose expression was downregulated by ICG-001 and not by C646 (these are potential CBP-specific target genes) and a set of approximately 500 genes whose expression was downregulated by C646 but not by ICG-001 (these are potential p300-specific target genes). These results are similar to a previous study of CBP and p300 in T98G glioblastoma cells that found that the two factors bound mainly to the same sites but that some specific binding sites could be identified . Interestingly, the genes specifically responsive to ICG-001 but not to C646 in HCT116 cells showed enrichment for cell proliferation-related gene ontology categories. Taken together, these results suggest that thousands of genes are regulated both by p300 and CBP (many of which are involved in cell proliferation) and that CBP-specific genes may also include additional genes that regulate cell proliferation whereas p300-specific genes are involved in other processes. In general, our results in HCT116 cells support the current model implicating WNT-mediated cell signaling as a critical regulator of cancer cell proliferation.
Although the WNT pathway has been implicated in the development of pancreatic cancer, the studies are not as extensive as those related to WNT’s role in colon cancer [20–25]. We show that, in general, the effects of ICG-001 and C646 on the transcriptome of PANC1 cells are similar to those observed upon treatment of HCT116 cells. For example, a set of genes involved in cell proliferation show reduced expression upon treatment of PANC1 with either ICG-001 or C646. However, we did observe several differences in the response of PANC1 cells to the epigenetic inhibitors, as compared to HCT116 cells. First, we found that many of the enriched gene categories that responded specifically to ICG-001 treatment of PANC1 cells are involved in cholesterol biosynthesis. Interestingly, many cancers have a high dependency on accelerated biogenesis and uptake of lipids and cholesterol and inhibition of these pathways has been proposed to be a therapeutic opportunity for metabolic targeting of cancer growth [31, 32]. Cholesterol homeostasis in mammalian cells is maintained in part by a basic-helix-loop-helix family of transcription factors called the sterol regulatory element binding proteins (SREBPs) [33, 34]. The SREBP family members activate a number of target genes involved in cholesterol and fatty acid metabolism through binding to sterol regulatory elements in the promoters of target genes. In fact, SREBP transcription factors have been suggested to be novel therapeutic targets . Interestingly, SREBP proteins require interaction with CBP to mediate transcriptional activation . Thus, the treatment of PANC1 cells with ICG-001 likely disrupts a functional interaction between CBP and a SREBP family member, causing downregulation of genes involved in the cholesterol biosynthetic pathway (Additional file 10). Second, in PANC1 cells the WNT pathway was not enriched in downregulated genes after treatment with either drug and several critical WNT target genes showed unexpected transcriptional responses. Notably, expression of JUN (which promotes differentiation) was predicted to be increased upon treatment but in PANC1 cells JUN expression was decreased (JUN did show the expected response in HCT116 cells). Similarly, expression of MYC (which promotes proliferation) was predicted to be decreased upon treatment but in PANC1 cells MYC expression was increased (MYC did show the expected response in HCT116 cells). The transcriptional response of the MYC gene was particularly surprising because it is considered to be a critical mediator of WNT signaling. Upregulation of MYC in PANC1 suggests that the drugs do not inhibit the WNT pathway in these cells. This hypothesis is supported by our finding that in PANC1 cells knockdown of TCF7L2, the transcription factor that brings β-catenin and CBP to regulatory elements to regulate WNT-responsive genes, does not affect expression of the same genes as are affected by treatment with ICG-001. While our work was in progress, another group reported treatment of pancreatic cancer cells with ICG-001 . They showed that treatment of PANC1 cells with 10 uM ICG-001 was effective at reducing cell proliferation in culture and reducing colony formation in soft agar. Although global effects on the PANC1 transcriptome were not examined in that study, the noted effects on proliferation are consistent with our finding that cell cycle-related genes are downregulated in response to ICG-001 and C646. That study did, however, perform microarray expression analysis after treatment of a different pancreatic cancer cell line (AsPC-1) with ICG-001 and found that 569 transcripts were upregulated and 150 transcripts were downregulated. Because only 117 of the 719 drug-responsive genes were altered in β-catenin knockdown cells, they concluded that ICG-001 had a broader effect than simply as a disrupter of WNT/β-catenin signaling in AsPC-1 cells.
As noted above, epigenetic inhibitors are considered promising new drugs for cancer treatment. One current clinical trial employs PRI-724, a derivative of ICG-001, in combination with gemcitabine in patients with advanced or metastatic pancreatic adenocarcinoma (NCT01764477). Gemcitabine is considered a first-line treatment for pancreatic adenocarcinoma but has poor overall efficacy because pancreatic cancer cells develop resistance to the drug . While investigating the pathways that lead to drug resistance, the transcriptional regulator NUPR1 (also known as anti-apoptotic protein p8 or Candidate of Metastasis-1) was identified as being involved in the acquisition of gemcitabine resistance by pancreatic cancer cells . NUPR1 normally functions as a stress response gene in the pancreas, but it has been shown to contribute to metastasis, anti-apoptotic activity and pancreatic cancer development [40, 41]. Interestingly, our genome-wide analyses identified NUPR1 as one of the top upregulated genes after treatment of PANC1 cells with ICG-001. The upregulation of NUPR1 by ICG-001 may explain why ICG-001 plus gemcitabine did not increase overall lifespan in an in vivo pancreatic cancer cell xenograft model . Although the mechanism by which NUPR1 promotes oncogenesis and/or drug resistance in pancreatic cells is not yet known, NUPR1 has been shown to form a complex with p300 and TP53 to upregulate and promote cytoplasmic translocation of CDKN1A (p21) in breast cancer cells . Although nuclear p21 is a negative regulator of cell cycle progression, studies have associated cytoplasmic p21 with drug resistance and oncogenic activity in breast and testicular cancer [43–45]. Vincent et al. showed that treatment of NUPR1-expressing cells with PI3K-AKT inhibitors could reverse cytoplasmic p21 localization and re-sensitize cells to doxorubicin. Importantly, studies have also shown that inhibition of the PI3K-AKT pathway in pancreatic cancer helps re-sensitize cells to gemcitabine [46, 47]. Thus, adding a PI3K-AKT inhibitor to the combined usage of ICG-001 plus gemcitabine may be the most effective treatment combination. However, it should also be noted that C646 caused only a modest increase in NUPR1 in PANC1 cells and that C646, but not ICG-001, specifically inhibited the PI3K-AKT pathway (see Figure 4). Taken together, these results suggest that perhaps C646 plus gemcitabine would be more effective than ICG-001 plus gemcitabine in the treatment of pancreatic cancer.
We have compared the genome-wide effects on the transcriptome of ICG-001 (a specific CBP inhibitor) versus C646 (a compound that competes with acetyl-coA for the Lys-coA binding pocket of both CBP and p300). We found that ICG-001 has a similar broad specificity as C646 in HCT116 colon cancer, with both drugs decreasing the expression of cell cycle-related and WNT pathway genes. In contrast, ICG-001 and C646 affect cell cycle-related genes but do not result in appropriate responses of critical WNT target genes in PANC1 cancer cells. The effects of ICG-001 on PANC1 cells and comparison to gene expression patterns in TCF7L2 knockdown cells suggests that ICG-001 inhibits proliferation of pancreatic cancer cells via a mechanism different than the WNT pathway. Gene ontology analyses point toward disruption of SREBP-CBP functional interactions as a possible cause of the anti-proliferative function of ICG-001 in pancreatic cancer cells. Importantly, both epigenetic inhibitors are effective at reversing some tumor-specific changes in gene expression that are observed in colon or pancreatic tumor cells.
Cell growth conditions
The human cell lines HCT116 (ATCC #CCL-247) and PANC1 (ATCC #CRL-1469) were obtained from the American Type Culture Collection. HCT116 and PANC1 cells were grown in Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum and 1% penicillin/streptomycin. Michael Kahn (University of Southern California) provided ICG-001 and C646 was obtained from VWR (catalog # 102516–240). Cells were treated with 10 uM ICG-001, 10 uM C646, or 0.05% DMSO and collected after 12 or 96 h. Cells for the 12-h treatments were grown to 70% confluency before addition of the drugs or DMSO. Cells for the 96-h treatments were grown at 40% to 50% confluency before addition of the drugs or DMSO and were passaged before they could reach 90% confluency. New media and drugs were added every 24 h. After treatment, gene expression was analyzed using Illumina BeadChips.
Microarray RNA expression
Total RNA was collected using Trizol according to the manufacturer’s instructions (Life Technologies). To confirm RNA samples were not degraded, RNA quality was checked with the Experion StdSens kit (Bio-Rad) prior to amplification and labeling. The Illumina TotalPrep RNA Amplification Kit (Life Technologies catalog # AMIL1791) was used according to the manufacturer’s instructions to amplify and label RNA samples for Illumina array hybridization. Labeled RNAs were analyzed with Illumina HT-12 v4 Expression BeadChips (Catalog #: BD-103-0204) with the Direct Hybridization Assay and then scanned on an Illumina HiScan (catalog # BD-103-0604). The data were analyzed and exported from Illumina’s GenomeStudio software using quantile normalization without background subtraction. Each drug/DMSO treatment and time point was performed using two independent biological replicates. The correlation between replicates was calculated to ensure that the data were reproducible, replicate samples were averaged together and genes with a detection P value <0.01 were considered for further analysis. Differential expression analysis was performed using Illumina’s custom differential expression error model, which assumes a normal distribution of the target signal intensity and takes into account biological variation, non-specific biological variation, and technical error. For more detail on Illumina’s custom error model, see GenomeStudio Gene Expression Module v1.0 User Guide (pages 103 and 104). Genes with a differential expression P value <0.05 were considered to be significantly differentially expressed.
TCF7L2 knockdown was performed in triplicate by siRNA transfection. Transfections were performed using Lipofectamine RNAiMax (Life Technologies) according to manufacturer’s instructions. A final concentration of 40nM siRNAs targeting either TCF7L2 (catalog # 4392420, Life Technologies) or a non-specific negative control siRNA (catalog # AM4611, Life Technologies) were used using reduced serum OptiMEM media (Life Technologies). Media was changed 12 h post transfection and total RNA was collected 48 h post transfection using Trizol according to manufacturer’s instructions (Life Technologies). Knockdown efficiency was detected using RT-qPCR and then samples were analyzed by RNA-seq.
Total RNA was used for polyA+ RNA selection using oligo-dT beads and subjected to library construction by True-Seq library preparation kits (Illumina), followed by Illumina HiSeq2000 sequencing. The RNA-seq reads were aligned to the human genome hg19 using Bowtie2 with ultrasensitive parameters. The RNA-seq reads were counted over gene exons using HTSeq . EdgeR was used for statistical analyses of siControl and siTCF7L2 samples, and a fold change of 2 was used to call the differentially expressed genes .
Ingenuity pathway analysis
Gene network diagrams in Additional file 10 were created through use of IPA. The expression data were analyzed through the use of QIAGEN’s Ingenuity® Pathway Analysis (IPA®, QIAGEN Redwood City, http://www.qiagen.com/ingenuity). For each subset of genes a core analysis was run with parameters set to consider only direct relationships and relationships between molecules that have been experimentally observed. The reference gene set used for P value calculations was the Ingenuity Knowledge Base (genes only).
Expression array analyses for control and treated cells and RNA-seq datasets for TCF7L2 knockdown experiments have been deposited in GEO (GSE64039 and GSE63776). The TCGA RNA-seq can be downloaded at https://tcga-data.nci.nih.gov/tcga/tcgaDownload.jsp.
Normal human pancreatic ductal cells immortalized with TERT
Sterol regulatory element binding protein.
The study was supported in part by award number P30CA014089 from the National Cancer Institute and 5T32GM067587 for MG. We thank Michael Kahn (University of Southern California) for providing the initial aliquots of ICG-001 used in this study and the USC/Norris Next Generation Sequencing Facility for services rendered with respect to the gene expression microarrays and RNA-seq samples.
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