Topoisomerase I (Top1) relaxes DNA supercoiling by forming transient cleavage complexes (Top1cc) up- and downstream of transcription complexes. Top1cc can be trapped by carcinogenic and endogenous DNA lesions and by camptothecin, resulting in transcription blocks. Here, we undertook genome-wide analysis of camptothecin-treated cells at exon resolution. RNA samples from HCT116 and MCF7 cells were analyzed with the Affy Exon Array platform, allowing high-resolution mapping along 18,537 genes. Long genes that are highly expressed were the most susceptible to downregulation, whereas short genes were preferentially upregulated. Along the body of genes, downregulation was most important toward the 3′-end and increased with the number of exon–intron junctions. Ubiquitin and RNA degradation-related pathway genes were selectively downregulated. Parallel analysis of microRNA with the Agilent miRNA microarray platform revealed that miR-142-3p was highly induced by camptothecin. More than 10% of the downregulated genes were targets of this p53-dependent microRNA. Our study shows the profound impact of Top1cc on transcription elongation, especially at intron–exon junctions and on transcript stability by microRNA miR-142-3p upregulation. Cancer Res; 73(15); 4830–9. ©2013 AACR.

DNA topoisomerase I (Top1) is essential in higher eukaryotes. It is required to relax DNA supercoiling generated by transcription, replication, and chromatin remodeling (1). Topoisomerase I relaxes both positive and negative supercoiling by producing transient topoisomerase I cleavage complexes (Top1cc), which are topoisomerase I-linked DNA single-strand breaks (1). Top1cc, which are normally very transient are the target of camptothecin and its clinically used anticancer derivatives, topotecan, irinotecan, and belotecan (1, 2). The drugs bind at the enzyme–DNA interface and block DNA religation, thereby leading to the trapping of Top1cc (1, 3). The trapped Top1cc are converted into lethal DNA lesions when their slow religation interferes with the progression of transcription and replication complexes (4, 5), leading to collisions that generate irreversible DNA breaks (1, 6–8). Those breaks activate multiple responses including cell-cycle checkpoints, specific transcription factors, S and G2 arrest, and ultimately cell death (9). Trapping of Top1cc can also be generated in the absence of drug treatment when the DNA template contains endogenous and exogenous DNA damage such as abasic sites, mismatches, oxidized bases, carcinogenic adducts, and nicks (10, 11).

Beside topoisomerase I DNA untwisting activity, which is critical during transcription elongation for the dissipation of transcription-dependent supercoiling (12, 13), topoisomerase I is closely linked to transcription in at least 2 other ways: at promoters, it can act as transcription regulator and at exon–intron junctions as splicing cofactor. Indeed, topoisomerase I has been identified as a cofactor for activator-dependent transcription initiation by RNA polymerase II (Pol II; ref. 14) and for the formation of active TFIID–TFIIA complexes (15). This promoter activity is independent of topoisomerase I unwinding activity. Topoisomerase I implication in splicing stems from the discovery that it can phosphorylate serine/arginine-rich (SR)-splicing proteins (16) and that it can shift from its classical DNA untwisting activity to kinase activity after binding the SR-splicing factors (17). Moreover, trapping of Top1cc by camptothecin and topoisomerase I inactivation have been shown to impact RNA splicing (18–22) and generate alternative transcripts (23). Recently, camptothecin treatment has also been shown to preferentially alter the splicing of splicing-related factors, such as RBM8A, generating transcripts coding for inactive proteins lacking key functional domains (24), as well as to reactivate the transcription of the ubiquitin protein ligase, UBE3A, which is implicated in Angelman syndrome (25).

Here, we report the genome-wide effects of camptothecin on gene expression using the exon array platform that allowed a high-resolution mapping of transcripts for 18,537 individual genes. We used the same treatment protocol recently reported to map the impacts of camptothecin on genome-wide splicing (24).

Differential analysis using R package LIMMA

We used 2 main steps for analysis: (i) differential microarray analysis and (ii) the analysis of the probe set genome location for top differentially expressed probe sets. The microarray analysis was conducted using packages available in R Bioconductor (versions available in June 2011). We first normalized the data using the RMA package (26). We defined 3 groups (late—15 and 20 hours, early—1, 2, and 4 hours, and control—4 and 20 hours) and conducted differential analysis between groups using linear models and empirical Bayes methods provided by Linear Models for Microarray Data (LIMMA) package (27).

The mapping of the probes to the human genome (37.1) was obtained using Bowtie (28) and probe sets with all member probes uniquely mapped to the genome were kept. The distance of a probe set to 5′ end of the corresponding gene was obtained by using the genome start position of the probe set and the position of the 5′ end of the gene was obtained from Entrez Gene. The distance was normalized to a value between 0 and 1.

The distribution of the normalized distances for the top 10,000 differentially expressed (upregulated or downregulated) probe sets was obtained using density plot.

Chemicals and cells

Camptothecin was obtained from Sigma-Aldrich. Human HCT116, MCF7, and MDA-MB-231 cell lines were obtained from American Type Culture Collection, grown in DMEM (Invitrogen; HCT116, MCF7) or RPMI (Invitrogen; MDA-MB-231), and supplemented with 10% FBS (Gemini Bio-products) at 37°C in 95% air and 5% CO2. p53+/+ and p53−/− HCT116 cells were kind gifts from Bert Vogelstein (Johns Hopkins Oncology Center; ref. 29).

miRNA inhibitor or miRNA mimic transfection

142-3p inhibitor, 142-3p mimic, miScript inhibitor negative control, and negative control siRNA were from Qiagen (catalogue numbers MIN0000434, MSY0000434, 1027271, and 1027310). Negative control siRNA was used as a control microRNA (miRNA) mimic. Cells were seeded at the density of 400,000 cells per well in 2.3 mL of medium containing serum, shortly before transfection. For each sample, 400 pmol of miRNA inhibitor (or 40 pmol of miRNA mimic) were mixed with 100 μL culture medium without serum (mixture A). Then 12 μL of HiPerfect (Qiagen) was added to mixture A and incubated for 10 minutes at room temperature to allow the formation of transfection complexes. Finally, the complexes were added to the cells, after 24 hours the medium was replaced with regular medium and the cells were incubated for a further 24 hours.

siRNA

For topoisomerase I downregulation, cells were transfected with siRNA duplex (Qiagen) against the sequence AAGGACTCCATCAGATACTAT from the topoisomerase I mRNA. A negative control siRNA duplex was obtained from Qiagen (target DNA sequence: AATTCTCCGAACGTGTCACGT). Cells were seeded in 6-well plates, at a density of 150,000 cells per well 16 h before transfection. For each sample, 500 pmol of siRNA were mixed with 250 μL Optimem (Invitrogen; mix A). Five μL Lipofectamine 2000 (Invitrogen) were mixed with 250 μL of Optimem and incubated for 5 minutes at room temperature (mix B). After mixing A and B and further incubation for 20 minutes at room temperature, the siRNA/lipofectamine complexes were added in 2 mL culture medium. After 5 hours, the medium was replaced with regular medium and cells were incubated for a further 72 h. BCL2L1 siRNAs were obtained from Qiagen (SI03025141) and Ambion (s1921). MAP3K7IP2 siRNAs were obtained from Qiagen (SI03107685) and Ambion (s23074). For BCL2L1 and MAP3K7IP2 siRNAs, transfections were carried out in 384-well plates. Briefly, 20 μL of serum-free media containing Lipofectamine RNAiMax (Life Technologies; 0.05 μL) was added to wells containing siRNA (0.8 pmol). Lipid and siRNA were allowed to complex for 45 minutes at ambient temperature before addition of 600 cells in RPMI-20% FBS to yield final transfection mixtures containing 20 nmol/L siRNA in RPMI-10% FBS. Camptothecin [0.1% dimethyl sulfoxide (DMSO)] was added 48 hours posttransfection and viability was assayed 72 hours later.

Reverse transcription PCR

Cells were washed in PBS. RNA extraction was carried out with the Nucleospin RNA II Kit (Macherey-Nagel). The OneStep RT-PCR Kit (Qiagen) was used as previously described (24). Primer sequences are listed in Supplementary Table S1.

Quantitative reverse transcription PCR

Cells were washed in PBS. RNA extraction was carried out with the Nucleospin RNA II Kit (Macherey-Nagel). Real-time RT-PCR was conducted with the QuantiFast SYBR Green RT-PCR Kit (Qiagen) on the ABI 7900 thermocycler (Applied Biosystems). Expression level of gene of interest was normalized by β2 microglobulin RNA level of the same sample. Reaction mixtures contained 5 μL of 2× QuantiFast SYBR Green RT-PCR Master Mix, 0.5 μL of QuantiFast RT Mix, and 50 ng of template RNA in a final volume of 10 μL containing primers (Proligo) at 1 μmol/L. Relative gene expression was expressed as |$2^{- \Delta \Delta C_{\rm t} }(\Delta \Delta C_{\rm t} =$||$\Delta C_{{\rm t}_{{\rm sample}}} - \Delta C_{\rm t} _\,{_{{\rm calibrator}}},\Delta C_{\rm t} = C_{\rm t} _{_{{\rm gene}}} - C_{\rm t} _{_{{\rm \betar 2 microglobulin}}})$|⁠. Primer sequences are listed in Supplementary Table S1.

Quantitative PCR for miRNA

Cells were washed in PBS. RNA extraction was carried out with the mirVana miRNA Isolation Kit (Ambion). An aliquot of 1 μg of RNA was reverse transcribed using the miScript Reverse Transcription Kit (Qiagen). Real-time PCR was conducted with the miScript SYBR Green PCR Kit (Qiagen) on the ABI 7900 thermocycler (Applied Biosystems). The expression level of hsa-miR-142-3p was normalized by the RNU1A RNA level of the same sample. Reaction mixtures contained 10 μL of 2× QuantiTect SYBR Green PCR Master Mix and 1 μL of reverse-transcriptase–generated cDNA in a final volume of 20 μL containing miScript Universal Primer and miScript Primer Assay (Qiagen). Relative gene expression was expressed as |$2^{- \Delta \Delta C_{\rm t}} (\Delta \Delta C_{\rm t} = \Delta C_{\rm t} _{_{{\rm sample}}} -$||$\Delta C_{\rm t} _{_{{\rm calibrator}}},\Delta C_{\rm t} = C_{\rm t} _{_{{\rm miR - 142 - 3p}}} - C_{\rm t} _{_{{\rm RNU1A}}})$|⁠.

Cell viability

Cell viability was measured using CellTiter Glo (Promega). Briefly, 25 μL of reagent was added to sample wells and incubated for 15 minutes at ambient temperature before reading luminescence using a PerkinElmer Envision Plate Reader (model 2104).

Global gene expression alterations induced by Top1cc

The Affy Exon Array (GeneChip Human Exon 1.0 ST Array) allows in depth analysis of 18,537 genes with approximately 4 probes per exon and an average of 40 probes per gene. It can also be used to determine overall “gene-level” expression by averaging multiple probes on different exons. We purified total RNA from human colon carcinoma HCT116 cells treated with 10 μmol/L camptothecin for 1, 2, 4, 15, and 20 hours (Fig. 1A), and conducted exon array analysis for each sample. Controls samples treated with DMSO (0.1%; the solvent used to dissolve camptothecin) were analyzed at 4 and 20 hours (Fig. 1A). Nonresponsive probes were removed and only genes with 10 or more remaining probes were included in the analysis (all the data are in GEO; accession number GSE37352; http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc = GSE37352).

Figure 1.

Experimental protocol and global impact of Top1 poisoning. A, experimental design. Cells were treated with 10 μmol/L camptothecin (CPT) for 1, 2, 4, 15, and 20 hours. Control samples received vehicle alone (0.1% DMSO, 4 and 20 hours). B, downregulated and upregulated genes (2-fold or more) in camptothecin-treated HCT116 cells. C, downregulated and upregulated genes (2-fold or more) in camptothecin-treated MCF7 cells.

Figure 1.

Experimental protocol and global impact of Top1 poisoning. A, experimental design. Cells were treated with 10 μmol/L camptothecin (CPT) for 1, 2, 4, 15, and 20 hours. Control samples received vehicle alone (0.1% DMSO, 4 and 20 hours). B, downregulated and upregulated genes (2-fold or more) in camptothecin-treated HCT116 cells. C, downregulated and upregulated genes (2-fold or more) in camptothecin-treated MCF7 cells.

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Overall 3,808 genes (20% of all genes) were downregulated (by 2-fold or more) after camptothecin treatment, whereas 835 genes (5% of all genes) were upregulated (by 2-fold or more; Fig. 1B; see Supplementary Tables S2 and S3). At early time treatments (1, 2, and 4 hours), only few genes were differentially expressed; it was mostly at late times (15 and 20 hours) that transcripts were up- or downregulated (Fig. 1B).

Top1cc preferentially downregulate highly expressed genes and upregulate genes with low expression

First, we analyzed whether differential gene expression responses were linked to the basal expression level of the genes. Basal expression for a given gene was determined as the average between the expression values for the 2 controls (4- and 20-hours DMSO treatment). After ranking all the genes in the array in term of transcript expression under baseline untreated conditions, we divided them in 10 groups of equal size based on their basal expression level. We then looked at the number of down- (Fig. 2A) and upregulated genes (Fig. 2B) in each group. The most highly expressed genes were the most downregulated both at early times (1, 2, and 4 hours camptothecin treatment) and at late times (15- and 20-hours treatment; Fig. 2A). By contrast, the upregulated genes both at early and late times were those with lowest expression before camptothecin treatment (Fig. 2B).

Figure 2.

Effect of Top1 poisoning on gene expression is correlated with the basal gene expression level. A, downregulation of highly expressed genes by camptothecin. The basal expression level for a specific gene corresponded to the average between the log2 expression value for the controls (4 and 20 hours DMSO treatment). The genes in the array were ranked according to transcripts levels. Genes were divided in 10 groups of same size depending on their basal expression level (∼1,745 genes by group). Then we determined the proportion of downregulated genes in each group. The x-axis corresponds to the average basal expression level for each of the 10 groups of genes. The y-axis corresponds to the number of downregulated genes in each group. Top, plot for the 217 “early” downregulated genes (downregulated within 4 hours of camptothecin exposure). Bottom, plot for the 3,759 “late” downregulated genes (downregulated after camptothecin 15 and/or 20 hours). Correlation coefficients (r) are indicated. B, upregulation of low expression genes. The basal expression level for a specific gene corresponded to the average between the log2 expression values for the controls (4 and 20 hours DMSO treatment). The genes in the array were ranked according to transcripts levels. Genes were divided in 10 groups of same size depending on their basal expression level (∼1,745 genes by group). Then we determined the proportion of upregulated genes in each group. The x-axis corresponds to the average basal expression level for each of the 10 groups of genes. The y-axis corresponds to the number of upregulated genes in each group. Top, plot for the 131 “early” upregulated genes (upregulated within 4 hours of camptothecin exposure). Bottom, plot for the 810 “late” upregulated genes (upregulated after camptothecin 15 and/or 20 hours). Correlation coefficients (r) are indicated.

Figure 2.

Effect of Top1 poisoning on gene expression is correlated with the basal gene expression level. A, downregulation of highly expressed genes by camptothecin. The basal expression level for a specific gene corresponded to the average between the log2 expression value for the controls (4 and 20 hours DMSO treatment). The genes in the array were ranked according to transcripts levels. Genes were divided in 10 groups of same size depending on their basal expression level (∼1,745 genes by group). Then we determined the proportion of downregulated genes in each group. The x-axis corresponds to the average basal expression level for each of the 10 groups of genes. The y-axis corresponds to the number of downregulated genes in each group. Top, plot for the 217 “early” downregulated genes (downregulated within 4 hours of camptothecin exposure). Bottom, plot for the 3,759 “late” downregulated genes (downregulated after camptothecin 15 and/or 20 hours). Correlation coefficients (r) are indicated. B, upregulation of low expression genes. The basal expression level for a specific gene corresponded to the average between the log2 expression values for the controls (4 and 20 hours DMSO treatment). The genes in the array were ranked according to transcripts levels. Genes were divided in 10 groups of same size depending on their basal expression level (∼1,745 genes by group). Then we determined the proportion of upregulated genes in each group. The x-axis corresponds to the average basal expression level for each of the 10 groups of genes. The y-axis corresponds to the number of upregulated genes in each group. Top, plot for the 131 “early” upregulated genes (upregulated within 4 hours of camptothecin exposure). Bottom, plot for the 810 “late” upregulated genes (upregulated after camptothecin 15 and/or 20 hours). Correlation coefficients (r) are indicated.

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Impact of gene length on transcriptional down- and upregulation

Next, we analyzed the impact of gene length on Top1cc-induced up- and downregulation. Figure 3A shows that the gene density curve for the downregulated genes is shifted to the right compared with the gene density curve for all the genes, meaning that the downregulated genes were the longest genes. On the other hand, the gene density curve for the upregulated genes was shifted to the left, meaning that the upregulated genes were the shortest (Fig. 3A). The median gene length for the overall genome (∼24 kb) increased to approximately 66 kb for the downregulated genes and decreased to approximately 7 kb for the upregulated genes (Fig. 3B). These results show that the long genes are selectively downregulated, whereas the short genes are selectively upregulated.

Figure 3.

Effect of Top1 poisoning on gene expression is correlated with gene length. A, distribution of the downregulated, upregulated genes, and all the genes of the array depending on their gene length. The downregulated genes (3,808), the upregulated genes (835), and all the genes of the array (18,537 genes) are represented in green, red, and black, respectively. B, median and average of gene length (in bases) for the downregulated genes, the upregulated genes, and all the genes of the array.

Figure 3.

Effect of Top1 poisoning on gene expression is correlated with gene length. A, distribution of the downregulated, upregulated genes, and all the genes of the array depending on their gene length. The downregulated genes (3,808), the upregulated genes (835), and all the genes of the array (18,537 genes) are represented in green, red, and black, respectively. B, median and average of gene length (in bases) for the downregulated genes, the upregulated genes, and all the genes of the array.

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Downregulation is predominant at the 3′-end of genes

The exon array platform allowed us to test whether the genes were downregulated or upregulated differentially along their length. For this purpose, we plotted the density of the 10,000 top differentially expressed probes (up- and downregulated) and 10,000 random probes, depending on their distance from the 5′-end of the gene. Our analysis showed that the downregulated probes were preferentially located at the 3′-end of genes compared with random probes, and this effect was accentuated at late time treatments (Fig. 4A and B, left).

Figure 4.

Transcripts are differentially affected along the length of genes. A, distribution of the top 10,000 differentially expressed probes (5,770 downregulated probes in green and 4,230 upregulated probes in red) at early times of treatment with camptothecin depending on their distance from the 5′ end of the gene. The distribution of the 10,000 random probes is represented in black. The differential analysis was done with R package LIMMA (see Materials and Methods). B, distribution of the top 10,000 differentially expressed probes (9,233 downregulated probes in green and 767 upregulated probes in red) at late times of treatment with camptothecin depending on their distance from the 5′ end of the gene. The distribution of 10,000 random probes is represented in black. The differential analysis was done with R package LIMMA (see Materials and Methods).

Figure 4.

Transcripts are differentially affected along the length of genes. A, distribution of the top 10,000 differentially expressed probes (5,770 downregulated probes in green and 4,230 upregulated probes in red) at early times of treatment with camptothecin depending on their distance from the 5′ end of the gene. The distribution of the 10,000 random probes is represented in black. The differential analysis was done with R package LIMMA (see Materials and Methods). B, distribution of the top 10,000 differentially expressed probes (9,233 downregulated probes in green and 767 upregulated probes in red) at late times of treatment with camptothecin depending on their distance from the 5′ end of the gene. The distribution of 10,000 random probes is represented in black. The differential analysis was done with R package LIMMA (see Materials and Methods).

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Conversely, for the upregulated genes, the probes that were upregulated had a preference for the 5′-end of the genes at early times. However, they had the same location than random probes at late times (Fig. 4A and B, right). To test whether the observed increase at 5′ ends of genes (Fig. 4A, right) may influence the tendency of short genes to be upregulated by camptothecin, we took the 131 early upregulated genes, separated them in 2 groups based on their length (short genes: less than 24,566 bases; long genes: 24,566 bases or more), and looked at the upregulation mean of their 5′ probes (probes located in the first 1,000 bases of the gene) compared with the upregulation mean of the other probes (probes located after the first 1,000 bases of the gene). For the early short upregulated genes, we obtained the same upregulation for both the 5′ probes and the other probes: 1.63 and 1.64, respectively, indicating that camptothecin -induced gene upregulation is not solely based on accumulation of 5′ probes for short genes.

Both gene length and exon–intron junctions are related to transcripts downregulation

Figure 5A shows that the probability for a gene to be downregulated increased with the number of exons. Conversely, intronless genes or genes with few exons had a higher probability to be upregulated (Fig. 5A and B). The median number of exons is 9 for the overall genome of HCT116 cells, while it was 14 for the downregulated genes and 4 for the upregulated genes. Thus, downregulated transcripts originated from long genes with a high number of exons.

Figure 5.

Preferential downregulation of genes with numerous exon–intron junctions. A, The x-axis corresponds to the number of exons. The y-axis corresponds to the proportion of downregulated genes (green) or upregulated genes (red) and unchanged genes (black) among the genes with a determined number of exons. B, intronless genes have a higher probability to be upregulated than downregulated. Proportion of downregulated genes, upregulated genes, and unchanged genes in intronless genes or in intron-containing genes are represented in green, red, and black, respectively. C, same length genes have a higher probability to be downregulated when they have large number of exons. The number of downregulated genes for 2 groups of same size genes that differ only by the number of exons (a group with lower number of exons, a second group with a larger number of exons) is plotted in green. D, same exon number genes have a higher probability to be downregulated if they are long. The number of downregulated genes for 2 groups of genes with the same exon number, but differing by gene length (a group with short genes, a second group with long genes) is plotted in green.

Figure 5.

Preferential downregulation of genes with numerous exon–intron junctions. A, The x-axis corresponds to the number of exons. The y-axis corresponds to the proportion of downregulated genes (green) or upregulated genes (red) and unchanged genes (black) among the genes with a determined number of exons. B, intronless genes have a higher probability to be upregulated than downregulated. Proportion of downregulated genes, upregulated genes, and unchanged genes in intronless genes or in intron-containing genes are represented in green, red, and black, respectively. C, same length genes have a higher probability to be downregulated when they have large number of exons. The number of downregulated genes for 2 groups of same size genes that differ only by the number of exons (a group with lower number of exons, a second group with a larger number of exons) is plotted in green. D, same exon number genes have a higher probability to be downregulated if they are long. The number of downregulated genes for 2 groups of genes with the same exon number, but differing by gene length (a group with short genes, a second group with long genes) is plotted in green.

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Because long genes also contain high number of exons, we analyzed the importance of exon–intron junctions. To eliminate the gene length parameter, we divided genes in groups of same size that differed only by the number of exons (Fig. 5C). By applying this correction, we observed that downregulation increases when genes have more exons. This finding is not limited to the 2 specific groups shown in Fig. 5C; it is general for different groups of genes with matched lengths (Supplementary Fig. S1).

In addition, to examine gene length and eliminate the exons number parameter, we compared genes with same exons number but different length (Fig. 5D). The proportion of downregulated genes was higher in long genes. Together these data show that both the length of a gene and the frequency of exon–intron junctions per gene are linked to its downregulation.

Preferential downregulation of the RNA degradation and ubiquitin-mediated proteolysis genes

Gene ontology analyses of the 3,808 genes upregulated by camptothecin in HCT116 cells showed significant correlations for the oxidative phosphorylation, ribosome and p53 signaling pathways (Supplementary Fig. S2A). We also analyzed by Affy Exon Array the response of the breast carcinoma MCF7 cells treated with camptothecin (Fig. 1C; all the data are in GEO; accession number GSE37352; http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc = GSE37352). One hundred genes were upregulated in MCF7 cells. They correspond to the p53 signaling pathway, MAPK signaling pathway and cell-cycle–related genes. These results confirm that the p53 signaling pathway is transcriptionally upregulated in both HCT116 and MCF7 cells (Supplementary Fig. S2), which is consistent with the p53 status of those 2 cell lines (30).

Among the most significant GO categories for the genes downregulated after camptothecin treatment in HCT116 cells are the RNA degradation and ubiquitin-mediated proteolysis categories, two categories that are also present for the genes that are downregulated in MCF7 cells (Supplementary Table S4). Supplementary Fig. S3A shows the large number of genes implicated in RNA decay, and Supplementary Fig. S3B shows that the CNOT genes are mainly downregulated at late time treatments. We confirmed the Affy Exon Array data by reverse transcription (RT)-PCR experiments (Supplementary Fig. S3C). It is noteworthy that downregulation was detectable at 2 hours by quantitative (q)RT-PCR (Supplementary Fig. S3D). Similarly, the downregulation of ubiquitin-mediated proteolysis genes observed with the Affy Exon Array (Supplementary Fig. S4A and S4B) was confirmed by RT-PCR and qRT-PCR (Supplementary Fig. S4C and S4D).

To differentiate whether the transcriptional effects of camptothecin were related to Top1cc or to topoisomerase I inactivation, we compared the effects of topoisomerase I downregulation by siRNA versus camptothecin treatment with whole-genome transcript analyses by Affy Exon Array (the data are in GEO; accession number GSE37352). By contrast to camptothecin, downregulation of topoisomerase I had only limited impact on gene expression. Only few genes were up (DDIT4L) or downregulated (SLC16A6, CPA4) following topoisomerase I downregulation, indicating that the generation of Top1cc rather than topoisomerase I inactivation is responsible for inducing differential gene expression. Moreover, contrary to camptothecin treatment, topoisomerase I silencing did not downregulate the ubiquitin-related genes, CUL5 and UBE2W (see Supplementary Fig. S5). These results indicate the importance of Top1cc for the transcriptional effects of camptothecin.

p53-dependent miR-142-3p upregulation as a novel mechanism of genomic downregulation and camptothecin-induced cell death

In parallel to the Affy Exon Array, we conducted Agilent miRNA microarray (8 × 15K version 3) analyses in human colon carcinoma HCT116 cells treated with camptothecin for 1, 2, 4, 15, and 20 hours (see Fig. 1; the data are in GEO; accession number GSE37358; http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc = GSE37358). Only few miRNA were affected by camptothecin treatment. miR-142-3p was among the most significantly upregulated miRNAs (Fig. 6A and B). This miRNA has 1,329 predicted target genes including the ubiquitin-mediated proteolysis gene family. Moreover, 415 of these predicted target genes were downregulated by camptothecin treatment (χ2 with Yates correction, P value < 0.0001). We confirmed by PCR that CUL5 and UBE2W, 2 of the predicted target genes from ubiquitin-mediated proteolysis gene family, were effectively downregulated by miR-142-3p mimic (Fig. 6C) and camptothecin treatment (Supplementary Fig. S4C and Fig. 6D). To confirm that the downregulation of CUL5 and UBE2W after camptothecin treatment was due to the upregulation of miR-142-3p, we used an inhibitor of miR-142-3p in our experiments. As expected, the miR-142-3p inhibitor strongly counteracted the downregulation of CUL5 and UBE2W (Fig. 6D). Because the 5′ flanking region of miR-142-3p contains a p53 binding sequence (Fig. 6E; ref. 31), we tested whether p53 was functionally related to miR-142-3p upregulation. For this purpose, we compared p53+/+ or p53−/− HCT116 cells. The upregulation of mir-142-3p was delayed in p53−/− cells compared with p53+/+ cells (Fig. 6F). Altogether, these results showed that p53-dependent miR-142-3p upregulation could be involved in the downregulation of 10% of the downregulated genes after camptothecin treatment.

Figure 6.

miR-142-3p upregulation is responsible for gene downregulation in response to camptothecin treatment. A, Agilent miRNA microarray data for hsa-miR-142-3p expression after camptothecin treatment. The log2 difference for hsa-miR-142-3p expression depending on camptothecin treatment was normalized to the untreated controls. B, hsa-miR-142-3p upregulation after camptothecin treatment (10 μmol/L). hsa-miR-142-3p was analyzed by qPCR. C, hsa-miR-142-3p mimic downregulates CUL5 and UBE2W transcripts. HCT116 cells were transfected with hsa-miR-142-3p mimic or negative control. CUL5 and UBE2W transcripts were analyzed by qRT-PCR. The y-axis corresponds to the fold decrease of CUL5 (black bar) or UBE2W (gray bar) after mimic transfection compared with control. D, the hsa-miR-142-3p inhibitor counteracts the downregulation of CUL5 and UBE2W transcripts. HCT116 cells transfected with the hsa-miR-142-3p inhibitor or miScript inhibitor negative control were treated with camptothecin (10 μmol/L, 15 or 20 hours). CUL5 and UBE2W transcripts were analyzed by qRT-PCR. The y-axis corresponds to the fold decrease of CUL5 (left) or UBE2W (right) after camptothecin treatment (15 or 20 hours). The black bars correspond to inhibitor-negative control, and the gray bars correspond to hsa-miR-142-3p inhibitor. E, schematic representation of hsa-miR-142 and its flanking region, showing its p53 binding site. F, miR-142-3p upregulation after camptothecin treatment is p53 dependent. p53+/+ and p53−/− HCT116 cells were treated with camptothecin (10 μmol/L, 1, 2, 4, 15, or 20 hours). hsa-miR-142-3p was analyzed by qPCR. p53+/+ HCT116 cells are in black and p53−/− HCT116 cells are in gray.

Figure 6.

miR-142-3p upregulation is responsible for gene downregulation in response to camptothecin treatment. A, Agilent miRNA microarray data for hsa-miR-142-3p expression after camptothecin treatment. The log2 difference for hsa-miR-142-3p expression depending on camptothecin treatment was normalized to the untreated controls. B, hsa-miR-142-3p upregulation after camptothecin treatment (10 μmol/L). hsa-miR-142-3p was analyzed by qPCR. C, hsa-miR-142-3p mimic downregulates CUL5 and UBE2W transcripts. HCT116 cells were transfected with hsa-miR-142-3p mimic or negative control. CUL5 and UBE2W transcripts were analyzed by qRT-PCR. The y-axis corresponds to the fold decrease of CUL5 (black bar) or UBE2W (gray bar) after mimic transfection compared with control. D, the hsa-miR-142-3p inhibitor counteracts the downregulation of CUL5 and UBE2W transcripts. HCT116 cells transfected with the hsa-miR-142-3p inhibitor or miScript inhibitor negative control were treated with camptothecin (10 μmol/L, 15 or 20 hours). CUL5 and UBE2W transcripts were analyzed by qRT-PCR. The y-axis corresponds to the fold decrease of CUL5 (left) or UBE2W (right) after camptothecin treatment (15 or 20 hours). The black bars correspond to inhibitor-negative control, and the gray bars correspond to hsa-miR-142-3p inhibitor. E, schematic representation of hsa-miR-142 and its flanking region, showing its p53 binding site. F, miR-142-3p upregulation after camptothecin treatment is p53 dependent. p53+/+ and p53−/− HCT116 cells were treated with camptothecin (10 μmol/L, 1, 2, 4, 15, or 20 hours). hsa-miR-142-3p was analyzed by qPCR. p53+/+ HCT116 cells are in black and p53−/− HCT116 cells are in gray.

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As for camptothecin, the surexpression of miR-142-3p was cytotoxic (Supplementary Fig. S6A). Moreover, downregulation by siRNA of BCL2L1 and MAP3K7IP2, 2 genes that are downregulated after camptothecin treatment and are targeted by miR142-3p, increased camptothecin sensitivity by 25-fold (Supplementary Fig. S6B and S6C). Altogether, our data show the functional impact of miR-142-3p on cell toxicity and downregulation of critical survival genes.

Our study shows the profound impact of Top1cc on transcription. Using a combination of high-resolution genome-wide analyses and targeted gene experiments, we show that the specific Top1cc poison camptothecin downregulates (by at least 2-fold) more than one-fifth of the genome. We show that this inhibition can be explained by the combination of 3 mechanisms: (i) Top1cc-mediated transcription arrest along the body of genes with incremental effect toward the 3′-end of long genes, (ii) presence of high number of exon–intron junctions that tend to arrest transcript elongation, and (iii) upregulation of at least one specific miRNA, miR-142-3p that downregulates a large number of survival genes.

miRNAs target the 3′ untranslated region (3′UTR) of genes (32). Perfect or near-perfect base pairing with the target RNA promotes cleavage of the RNA (33). miRNA that are partially complementary to their target genes can also promote their deadenylation, causing mRNA destabilization and degradation possibly starting at the 3′-end of the transcripts (34). Upregulation of miR-142-3p can be invoked for the downregulation of more than 400 of the total 3,800 genes downregulated by camptothecin, including genes coding for ubiquitin pathways, and which respond in a coordinated manner to camptothecin treatment. Although other miRNA were known to be upregulated by DNA damage responses [miR-34a (35, 36), miR-34c (37), miR-192, miR-215 (38, 39), miR-16-1, miR-143, and miR-145 (40)], in our analysis, only miR-142-3p was overexpressed significantly after camptothecin treatment. On the basis of the presence of a p53 binding sequence, upstream from the miR-142-3p, and the impact of p53 knockout on miR-142-3p induction after camptothecin treatment, we conclude that miR-142-3p is a novel p53-dependent miRNA. It is also likely that miR-142-3p is upregulated by DNA damage independently of p53 as it has been recently reported to be upregulated by ionizing radiation in M059K glioblastoma cells, TK6 human B lymphoblast cells, and Jurkat lymphoblast acute T-cell leukemia cells (41, 42), which are p53 defective.

At least 2 other mechanisms (besides miR-142-3p discussed above) are involved in the Top1cc-induced transcription inactivation. First, our exon array analyses show an overall presence of aborted transcripts in camptothecin-treated cells. This result is consistent with earlier studies by Kann and Kohn who reported that camptothecin shifts pulse-labeled RNA to lower molecular weight (43). More recently, using 3H-uridine pulse-labeling, Ljungman and Hanawalt also showed that camptothecin inhibits elongation by Pol II in the dihydrofolate reductase gene (4). Our genome-wide analyses generalize these earlier results by showing preferential truncation of long transcripts. In addition, we show that gene upregulation was confined to short transcripts. Aborted transcripts produced by premature chain termination may have profound cellular effects. The simplest mechanism for the formation of abortive transcripts in camptothecin-treated cells is Pol II arrest at trapped Top1cc. Pol II is rapidly arrested by Top1cc (4, 44) with reduction of Pol II density at promoter pausing sites (45), activation of low abundance antisense RNA (23), and rapid hyperphosphorylation of Pol II (46). The role of Top1cc rather than topoisomerase I inactivation by sequestration at Top1cc is supported by the fact that topoisomerase I siRNA had a much weaker effect than camptothecin treatment (see Supplemental Fig. S5).

Our study reveals another mechanism related to exon–intron junctions for the generation of aborted transcript. Indeed, transcript downregulation was significantly correlated to the number of exon–intron junctions in camptothecin-treated cells (see Fig. 5C and Supplementary Fig. S1). Thus, it seems that the trapping of Top1cc might be particularly deleterious on exon–intron junctions, which is plausibly based on the known involvement of topoisomerase I in RNA splicing. The splicing alterations generated by camptothecin could produce premature stops and generate instable transcripts subjected to nonsense-mediated mRNA decay (NMD; refs. 21, 24, 47). Recently, an ExonHit Array on the RNA samples used in the present study (see protocol in Fig. 1A) showed that camptothecin preferentially affected the splicing of splicing-related factors. The preferential effect of camptothecin on genes encoding splicing factors may explain the abnormal splicing of a large number of genes in response to Top1cc (24), and raises the question as to whether transcript defects identified in the present study are related to splice defects. The alternatively spliced genes represent 9% of the downregulated genes, 2% of the upregulated genes, and 5% of the unchanged genes. These percentages indicate that the downregulated genes have a higher probability to be spliced than the unchanged genes and the upregulated genes (Fisher exact test; P value < 2.2e-16). Together, our results suggest the importance of camptothecin-induced Top1cc at or near intron–exon junctions for camptothecin-induced transcription stalling and splicing alterations.

We found several pathways significantly downregulated in camptothecin-treated cells: ubiquitin-mediated proteolysis, cell cycle, RNA degradation, basal transcription factors, TGFβ, and immune response signaling (see Supplementary Table S4). Downregulation of cell-cycle–related genes leading to growth arrest is a well-known effect of Top1cc (48). The sensitivity of RNA-related genes has recently been noted by Lotito and colleagues (49). Unexpectedly, the most significantly enriched gene category in our study is ubiquitin-mediated proteolysis. Downregulation of ubiquitin pathways is unexpected as ubiquitylation is a major component of the DNA damage response and a prerequisite to Top1cc repair (11). Overexpression of CUL3, a component of an SCF (Skip1-Cul-F-Box) E3 ligase, has been shown to increase topoisomerase I ubiquitylation and subsequent degradation resulting in camptothecin resistance (50). However, in our study, CUL3 and many other ubiquitin genes are downregulated, consequently the DNA breaks are not repaired, contributing to the cytotoxicity of Top1cc.

In summary, our exon-specific gene expression study of the whole-human genome in response to Top1cc provides novel insights in the transcriptional effects of Top1cc. At least 3 mechanisms seem to coexist to inactivate gene expression in camptothecin-treated cancer cells: miRNA upregulation by DNA damage responses, transcript elongation arrests by trapped Top1cc, and exon–intron junction interference by Top1cc. Moreover, cells that are targeted by camptothecin seem to selectively inactivate several key pathways involved at least in ubiquitin metabolism, cell cycle, and RNA stability and to upregulate miR-142-3p, which downregulates survival genes. These findings are relevant not only for basic cell biology as Top1cc form in response to endogenous and exogenous DNA lesions but also for cancer therapeutics as Top1cc-targeted drugs are routinely used for various human cancers.

No potential conflicts of interest were disclosed.

Conception and design: S. Solier, K.W. Kohn, Y. Pommier

Development of methodology: S. Solier, H. Liu, Y. Pommier

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): S. Solier, S.E. Martin, Y. Pommier

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): S. Solier, M.C. Ryan, S. Varma, K.W. Kohn, H. Liu, B.R. Zeeberg, Y. Pommier

Writing, review, and/or revision of the manuscript: S. Solier, Y. Pommier

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): Y. Pommier

Study supervision: Y. Pommier

The authors thank Dr. Bert Vogelstein (Johns Hopkins University) for providing the HCT116 p53 +/+ and −/− cell lines. The authors also thank Dr. Natasha Caplen, Center for Cancer Research, NCI, for insightful discussion regarding our miRNA analyses.

This study was supported by the Center for Cancer Research, the Intramural program of the National Cancer Institute, NIH.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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