Author Manuscript Published OnlineFirst on June 16, 2015; DOI: 10.1158/1541-7786.MCR-15-0146 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.
Systematic Screening of Promoter Regions Pinpoints Functional Cis-regulatory Mutations in a Cutaneous Melanoma Genome Rebecca C. Poulos1,2, Julie A. I. Thoms1,2, Anushi Shah1,2, Dominik Beck1,2, John E. Pimanda1,2,3, Jason W. H. Wong1,2,* 1
Prince of Wales Clinical School, UNSW Australia, Sydney, Australia
2
Lowy Cancer Research Centre, UNSW Australia, Sydney, Australia
3
Department of Haematology, Prince of Wales Hospital, Sydney, Australia
*Correspondence to be address to: Jason W. H. Wong, Fax: +61 2 9385 1510, E-mail: [email protected]
Running title: Functional promoter mutations in cutaneous melanoma Keywords: promoter, melanoma, somatic mutation, cis-regulation Financial support: Australian Research Council, Cancer Institute NSW Conflicts of interest: The authors declare no conflicts of interest. Word count: 4,485 Figures and tables: 4 figures, 1 table (plus supplementary figures and tables)
1
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Author Manuscript Published OnlineFirst on June 16, 2015; DOI: 10.1158/1541-7786.MCR-15-0146 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.
ABSTRACT With the recent discovery of recurrent mutations in the TERT promoter in melanoma, identification of other somatic causal promoter mutations is of considerable interest. Yet, the impact of sequence variation on the regulatory potential of gene promoters has not been systematically evaluated. This study assesses the impact of promoter mutations on promoter activity in the whole-genome sequenced malignant melanoma cell line COLO-829. Combining somatic mutation calls from COLO-829 with genome-wide chromatin accessibility and histone modification data revealed mutations within promoter elements. Interestingly, a high number of potential promoter mutations (n=23) were found, a result mirrored in subsequent analysis of TCGA whole-melanoma genomes. The impact of wildtype and mutant promoter sequences were evaluated by sub-cloning into luciferase reporter vectors and testing their transcriptional activity in COLO-829 cells. Of the 23 promoter regions tested, four mutations significantly altered reporter activity relative to wild-type sequences. These data were then subjected to multiple computational algorithms that score the cis-regulatory altering potential of mutations. These analyses identified one mutation, located within the promoter region of NDUFB9, which encodes the mitochondrial NADH dehydrogenase (ubiquinone) 1 beta subcomplex 9, to be recurrent in 4.4% (19/432) of TCGA whole-melanoma exomes. The mutation is predicted to disrupt a highly conserved SP1/KLF transcription factor binding motif and its frequent co-occurrence with mutations in the coding sequence of NF1 supports a pathological role for this mutation in melanoma. Taken together, these data show the relatively high prevalence of promoter mutations in the COLO-829 melanoma genome, and indicates that a proportion of these significantly alter the regulatory potential of gene promoters.
2
Downloaded from mcr.aacrjournals.org on August 7, 2015. © 2015 American Association for Cancer Research.
Author Manuscript Published OnlineFirst on June 16, 2015; DOI: 10.1158/1541-7786.MCR-15-0146 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.
Implications: Genomic-based screening within gene promoter regions suggests that functional cis-regulatory mutations may be common in melanoma genomes, highlighting the need to examine their role in tumorigenesis.
Introduction Cancers develop when certain somatic mutations are acquired by individual cells (1). However, most tumours harbour a number of different genetic and epigenetic aberrations (2, 3). This means that identifying all driver mutations, and distinguishing them from passenger mutations, remains a major challenge (4, 5). This problem is exacerbated in the non-coding genome, as a lack of selective pressure in these regions contributes to the acquisition of higher numbers of mutations. In the past, research into cancer driver mutations has typically focused on protein-coding mutations, as the functional consequence of non-coding mutations is difficult to determine. Furthermore, availability of datasets required for analysis of noncoding mutations has been limited. However, recurrent mutations in the TERT promoter were recently identified in melanoma and other cancers (6, 7). The TERT promoter mutations were the first recurrent cis-regulatory somatic point mutations identified in cancer that alter gene expression (6). These mutations drive cancer by generating a transcription factor binding motif for E-twenty-six (ETS) transcription factors, with corresponding increases in promoter activity and expression of TERT (6). Remarkably, mutations at the promoter of TERT are found in as many as 85% of metastatic melanomas and are also found at high frequency in many other cancers including glioblastoma (62%) and bladder cancer (59%) (7). With advances in sequencing technology (8-11), whole cancer genomes are being sequenced at a rapid pace and hundreds of sequenced samples are available for analysis from
3
Downloaded from mcr.aacrjournals.org on August 7, 2015. © 2015 American Association for Cancer Research.
Author Manuscript Published OnlineFirst on June 16, 2015; DOI: 10.1158/1541-7786.MCR-15-0146 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.
The Cancer Genome Atlas (TCGA), the Wellcome Trust Sanger Institute Cancer Genome Project and the International Cancer Genome Consortium (12). This has led to a number of studies that have focused on mapping the cis-regulatory mutational landscape across cancers (13, 14) . These analyses have primarily used recurrence to determine those mutations with potential driver roles in cancer (13, 14). However, while numerous recurrent cis-regulatory mutations have been identified, thus far, only a single promoter mutation in addition to the TERT promoter mutations, in the promoter of the SDHD gene, has been linked to changes in gene expression (13). Nevertheless, from these studies, it is evident that mutations at promoters can be found in many cancers. It appears that promoter mutations may even be more prevalent in melanomas than other cancers. For example, one recent study analysing mutations within 500 bp of a transcription start site (TSS) that were recurrent in 5 or more cancer samples, found that 78% of those mutations identified were from melanomas (14). However, with relatively low numbers (A chr5:82,373,334 C>T chr6:27,777,830 A>C chr6:31,940,123 G>A chr7:66,461,664 G>A chr8:75,262,591 C>T chr8:125,551,344 C>T chr11:125,439,130 G>C chr12:41,086,186 C>T chr14:53,173,816 A>C chr14:76,618,176 G>A chr15:78,730,453 C>T chr16:1,832,640 G>A chr19:52,643,275 G>A chr20:36,156,522 G>A chr21:45,553,369 G>A chr22:30,988,178 G>A Counts 20
PSRC1 WDR3/GDAP2 RPE IFT57 XRCC4/TMEM167A HIST1H3H STK19/DOM3Z TYW1 GDAP1 NDUFB9/TATDN1 EI24 CNTN1 PSMC6 GPATCH2L IREB2 NUBP2/SPSB3 ZNF616 BLCAP C21orf33 PES1 25
0.18 0.64 0.52 0.98 0.00 0.00 0.54 0.00 0.00 0.58 0.00 0.00 0.49 0.54 0.43 0.24 0.01 0.00 0.00 0.46
0.42 0.34 0.28 0.38 0.19 0.12 0.10 0.03 0.16 0.35 0.01 0.28 0.53 0.54 0.40 0.12 0.00 0.30 0.17 0.31
Y Y Y Y Y Y Y Y Y Y 10/20
a
Transcription factor motif alterationc Motif created
Motif removed
PPARG::RXRA ELK1;FEV;ELF5… MZF1_5-13 REL;ELF5;FEV… Arnt;SPIB CREB1 PPARG::RXRA;Hoxc9 ELK1;Stat6;Stat6… NFATC2;NFKB1 ELF1 ELK1;Spz1 Hand1::Tcfe2a STAT3 SP1;ELF5;SP2 Klf4;Klf1;KLF5… Spz1 NFATC2;SPIB;Erg… SPIB;ELF1;FLI1… THAP1 ELK1;ELF5;GABPA… Klf1;THAP1;IRF1… ELK1 ELK1 TFAP2C NFATC2;FOXO3;Foxo1… Erg Nr2e3;Nr2e3 11/20 15/20
RegulomeDB 2a 2a 2b 2b 2b 4 2a 2a 4 2a 4 4 2a 4 2a 2b 3a 4 2b 2b
Scored FATHMM -MKL 0.9518 0.6864 0.8269 0.8655 0.3141 0.9504 0.7645 0.5361 0.1825 0.7400 0.0469 0.3491 0.9514 0.8413 0.9865 0.0873 0.0575 0.2862 0.3151 0.2941
FunSeq2 2.497 1.414 1.851 2.626 2.741 2.703 0.734 1.926 3.171 0.946 1.557 3.211 1.423 3.447 1.819 2.752 1.260 0.800 1.701
Mutations with changes in promoter activity from wild-type, as determined by reporter assays (see Figure 3), are shaded in light grey. DHS = DNase I hypersensitive; Y = yes. Conservation is denoted when the PhastCons conservation score (29) for the 15 bp region (mut +/- 7 bp) is greater than that of the DHS region as a whole (~150 bp). c Transcription factor motif alterations were determined by using the OncoCis tool (15) which utilises transcription factor motifs generated by the JASPAR database (30). d Scores were obtained for each mutation from RegulomeDB (17), FATHMM-MKL (18) and FunSeq2 (16). b
20
Author Manuscript Published OnlineFirst on June 16, 2015; DOI: 10.1158/1541-7786.MCR-15-0146 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.
Downloaded from mcr.aacrjournals.org on August 7, 2015. © 2015 American Association for Cancer Research.
Table 1. Annotation of putative promoter mutations in COLO-829 according to conservation, transcription factor motif alteration and scores attributed by RegulomeDB, FATHMM-MKL and FunSeq.
Author Manuscript Published OnlineFirst on June 16, 2015; DOI: 10.1158/1541-7786.MCR-15-0146 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.
Figure Legends Figure 1. Distribution of somatic promoter mutations in the COLO-829 cell-line. (a) Flow chart detailing the methodology for identifying putative somatic promoter mutations, together with mutation and peak counts fulfilling the specified criteria. (b) Circos map of the landscape of somatic promoter mutations in COLO-829. Tracks from outside to inside are: chromosomes; regions of loss of heterozygosity (green) and complete loss of all chromosomes (grey); copy number, with 2=brown; relative number of somatic mutations per megabase, with grey bars marking centromeres; heat map indicating regions of comparatively high (red) and low (green) mutation counts; putative promoter regions (blue), identified as described in Figure 1a. Lines through the circle indicate COLO829 putative promoter mutations. Each putative promoter mutation is labelled with the associated nearest gene (bold) or genes (not bold, adjacent labels) with a transcription start site within +/- 1 kb of the mutation. Each mutation has two associated spots – the outer spot indicates if the mutation is conserved (orange) or not (black) and the inner spot indicates whether at least one transcription factor motif is created or destroyed by the mutation (green) or not (grey). Copy number and regions of loss of heterozygosity were identified from previous research (19). Figure 2. COLO-829 promoter mutations plotted against data points from MutSigCV analysis. Putative COLO-829 promoter mutations (grey bars) are plotted, along with the frequency of occurrence in the genome (per 100 kB region) of each given measurement for (a) expression level (b) DNA replication time and (c) non-coding mutation count from MutSigCV data (28). DNA replication time is expressed on a scale of 100 (early) to 1500 (late). Figure 3. Validation of the functional consequence of COLO-829 promoter mutations by reporter assays. Representative results from one luciferase reporter assay experiment for each reporter construct tested. Results from wild-type (wt) and mutant (mt) constructs are adjacent, labelled according to the gene to which the promoter region is associated. Fold change is calculated against the average of replicate wt values. Promoter regions with no activity (luciferase activity < 2 times that of the promoter-less vector pGL2 Basic) are indicated by a cross. Only statistically significant differences (by unpaired t-test) are indicated, where * denotes p
Systematic Screening of Promoter Regions Pinpoints Functional Cis-regulatory Mutations in a Cutaneous Melanoma Genome Rebecca C. Poulos1,2, Julie A. I. Thoms1,2, Anushi Shah1,2, Dominik Beck1,2, John E. Pimanda1,2,3, Jason W. H. Wong1,2,* 1
Prince of Wales Clinical School, UNSW Australia, Sydney, Australia
2
Lowy Cancer Research Centre, UNSW Australia, Sydney, Australia
3
Department of Haematology, Prince of Wales Hospital, Sydney, Australia
*Correspondence to be address to: Jason W. H. Wong, Fax: +61 2 9385 1510, E-mail: [email protected]
Running title: Functional promoter mutations in cutaneous melanoma Keywords: promoter, melanoma, somatic mutation, cis-regulation Financial support: Australian Research Council, Cancer Institute NSW Conflicts of interest: The authors declare no conflicts of interest. Word count: 4,485 Figures and tables: 4 figures, 1 table (plus supplementary figures and tables)
1
Downloaded from mcr.aacrjournals.org on August 7, 2015. © 2015 American Association for Cancer Research.
Author Manuscript Published OnlineFirst on June 16, 2015; DOI: 10.1158/1541-7786.MCR-15-0146 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.
ABSTRACT With the recent discovery of recurrent mutations in the TERT promoter in melanoma, identification of other somatic causal promoter mutations is of considerable interest. Yet, the impact of sequence variation on the regulatory potential of gene promoters has not been systematically evaluated. This study assesses the impact of promoter mutations on promoter activity in the whole-genome sequenced malignant melanoma cell line COLO-829. Combining somatic mutation calls from COLO-829 with genome-wide chromatin accessibility and histone modification data revealed mutations within promoter elements. Interestingly, a high number of potential promoter mutations (n=23) were found, a result mirrored in subsequent analysis of TCGA whole-melanoma genomes. The impact of wildtype and mutant promoter sequences were evaluated by sub-cloning into luciferase reporter vectors and testing their transcriptional activity in COLO-829 cells. Of the 23 promoter regions tested, four mutations significantly altered reporter activity relative to wild-type sequences. These data were then subjected to multiple computational algorithms that score the cis-regulatory altering potential of mutations. These analyses identified one mutation, located within the promoter region of NDUFB9, which encodes the mitochondrial NADH dehydrogenase (ubiquinone) 1 beta subcomplex 9, to be recurrent in 4.4% (19/432) of TCGA whole-melanoma exomes. The mutation is predicted to disrupt a highly conserved SP1/KLF transcription factor binding motif and its frequent co-occurrence with mutations in the coding sequence of NF1 supports a pathological role for this mutation in melanoma. Taken together, these data show the relatively high prevalence of promoter mutations in the COLO-829 melanoma genome, and indicates that a proportion of these significantly alter the regulatory potential of gene promoters.
2
Downloaded from mcr.aacrjournals.org on August 7, 2015. © 2015 American Association for Cancer Research.
Author Manuscript Published OnlineFirst on June 16, 2015; DOI: 10.1158/1541-7786.MCR-15-0146 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.
Implications: Genomic-based screening within gene promoter regions suggests that functional cis-regulatory mutations may be common in melanoma genomes, highlighting the need to examine their role in tumorigenesis.
Introduction Cancers develop when certain somatic mutations are acquired by individual cells (1). However, most tumours harbour a number of different genetic and epigenetic aberrations (2, 3). This means that identifying all driver mutations, and distinguishing them from passenger mutations, remains a major challenge (4, 5). This problem is exacerbated in the non-coding genome, as a lack of selective pressure in these regions contributes to the acquisition of higher numbers of mutations. In the past, research into cancer driver mutations has typically focused on protein-coding mutations, as the functional consequence of non-coding mutations is difficult to determine. Furthermore, availability of datasets required for analysis of noncoding mutations has been limited. However, recurrent mutations in the TERT promoter were recently identified in melanoma and other cancers (6, 7). The TERT promoter mutations were the first recurrent cis-regulatory somatic point mutations identified in cancer that alter gene expression (6). These mutations drive cancer by generating a transcription factor binding motif for E-twenty-six (ETS) transcription factors, with corresponding increases in promoter activity and expression of TERT (6). Remarkably, mutations at the promoter of TERT are found in as many as 85% of metastatic melanomas and are also found at high frequency in many other cancers including glioblastoma (62%) and bladder cancer (59%) (7). With advances in sequencing technology (8-11), whole cancer genomes are being sequenced at a rapid pace and hundreds of sequenced samples are available for analysis from
3
Downloaded from mcr.aacrjournals.org on August 7, 2015. © 2015 American Association for Cancer Research.
Author Manuscript Published OnlineFirst on June 16, 2015; DOI: 10.1158/1541-7786.MCR-15-0146 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.
The Cancer Genome Atlas (TCGA), the Wellcome Trust Sanger Institute Cancer Genome Project and the International Cancer Genome Consortium (12). This has led to a number of studies that have focused on mapping the cis-regulatory mutational landscape across cancers (13, 14) . These analyses have primarily used recurrence to determine those mutations with potential driver roles in cancer (13, 14). However, while numerous recurrent cis-regulatory mutations have been identified, thus far, only a single promoter mutation in addition to the TERT promoter mutations, in the promoter of the SDHD gene, has been linked to changes in gene expression (13). Nevertheless, from these studies, it is evident that mutations at promoters can be found in many cancers. It appears that promoter mutations may even be more prevalent in melanomas than other cancers. For example, one recent study analysing mutations within 500 bp of a transcription start site (TSS) that were recurrent in 5 or more cancer samples, found that 78% of those mutations identified were from melanomas (14). However, with relatively low numbers (A chr5:82,373,334 C>T chr6:27,777,830 A>C chr6:31,940,123 G>A chr7:66,461,664 G>A chr8:75,262,591 C>T chr8:125,551,344 C>T chr11:125,439,130 G>C chr12:41,086,186 C>T chr14:53,173,816 A>C chr14:76,618,176 G>A chr15:78,730,453 C>T chr16:1,832,640 G>A chr19:52,643,275 G>A chr20:36,156,522 G>A chr21:45,553,369 G>A chr22:30,988,178 G>A Counts 20
PSRC1 WDR3/GDAP2 RPE IFT57 XRCC4/TMEM167A HIST1H3H STK19/DOM3Z TYW1 GDAP1 NDUFB9/TATDN1 EI24 CNTN1 PSMC6 GPATCH2L IREB2 NUBP2/SPSB3 ZNF616 BLCAP C21orf33 PES1 25
0.18 0.64 0.52 0.98 0.00 0.00 0.54 0.00 0.00 0.58 0.00 0.00 0.49 0.54 0.43 0.24 0.01 0.00 0.00 0.46
0.42 0.34 0.28 0.38 0.19 0.12 0.10 0.03 0.16 0.35 0.01 0.28 0.53 0.54 0.40 0.12 0.00 0.30 0.17 0.31
Y Y Y Y Y Y Y Y Y Y 10/20
a
Transcription factor motif alterationc Motif created
Motif removed
PPARG::RXRA ELK1;FEV;ELF5… MZF1_5-13 REL;ELF5;FEV… Arnt;SPIB CREB1 PPARG::RXRA;Hoxc9 ELK1;Stat6;Stat6… NFATC2;NFKB1 ELF1 ELK1;Spz1 Hand1::Tcfe2a STAT3 SP1;ELF5;SP2 Klf4;Klf1;KLF5… Spz1 NFATC2;SPIB;Erg… SPIB;ELF1;FLI1… THAP1 ELK1;ELF5;GABPA… Klf1;THAP1;IRF1… ELK1 ELK1 TFAP2C NFATC2;FOXO3;Foxo1… Erg Nr2e3;Nr2e3 11/20 15/20
RegulomeDB 2a 2a 2b 2b 2b 4 2a 2a 4 2a 4 4 2a 4 2a 2b 3a 4 2b 2b
Scored FATHMM -MKL 0.9518 0.6864 0.8269 0.8655 0.3141 0.9504 0.7645 0.5361 0.1825 0.7400 0.0469 0.3491 0.9514 0.8413 0.9865 0.0873 0.0575 0.2862 0.3151 0.2941
FunSeq2 2.497 1.414 1.851 2.626 2.741 2.703 0.734 1.926 3.171 0.946 1.557 3.211 1.423 3.447 1.819 2.752 1.260 0.800 1.701
Mutations with changes in promoter activity from wild-type, as determined by reporter assays (see Figure 3), are shaded in light grey. DHS = DNase I hypersensitive; Y = yes. Conservation is denoted when the PhastCons conservation score (29) for the 15 bp region (mut +/- 7 bp) is greater than that of the DHS region as a whole (~150 bp). c Transcription factor motif alterations were determined by using the OncoCis tool (15) which utilises transcription factor motifs generated by the JASPAR database (30). d Scores were obtained for each mutation from RegulomeDB (17), FATHMM-MKL (18) and FunSeq2 (16). b
20
Author Manuscript Published OnlineFirst on June 16, 2015; DOI: 10.1158/1541-7786.MCR-15-0146 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.
Downloaded from mcr.aacrjournals.org on August 7, 2015. © 2015 American Association for Cancer Research.
Table 1. Annotation of putative promoter mutations in COLO-829 according to conservation, transcription factor motif alteration and scores attributed by RegulomeDB, FATHMM-MKL and FunSeq.
Author Manuscript Published OnlineFirst on June 16, 2015; DOI: 10.1158/1541-7786.MCR-15-0146 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.
Figure Legends Figure 1. Distribution of somatic promoter mutations in the COLO-829 cell-line. (a) Flow chart detailing the methodology for identifying putative somatic promoter mutations, together with mutation and peak counts fulfilling the specified criteria. (b) Circos map of the landscape of somatic promoter mutations in COLO-829. Tracks from outside to inside are: chromosomes; regions of loss of heterozygosity (green) and complete loss of all chromosomes (grey); copy number, with 2=brown; relative number of somatic mutations per megabase, with grey bars marking centromeres; heat map indicating regions of comparatively high (red) and low (green) mutation counts; putative promoter regions (blue), identified as described in Figure 1a. Lines through the circle indicate COLO829 putative promoter mutations. Each putative promoter mutation is labelled with the associated nearest gene (bold) or genes (not bold, adjacent labels) with a transcription start site within +/- 1 kb of the mutation. Each mutation has two associated spots – the outer spot indicates if the mutation is conserved (orange) or not (black) and the inner spot indicates whether at least one transcription factor motif is created or destroyed by the mutation (green) or not (grey). Copy number and regions of loss of heterozygosity were identified from previous research (19). Figure 2. COLO-829 promoter mutations plotted against data points from MutSigCV analysis. Putative COLO-829 promoter mutations (grey bars) are plotted, along with the frequency of occurrence in the genome (per 100 kB region) of each given measurement for (a) expression level (b) DNA replication time and (c) non-coding mutation count from MutSigCV data (28). DNA replication time is expressed on a scale of 100 (early) to 1500 (late). Figure 3. Validation of the functional consequence of COLO-829 promoter mutations by reporter assays. Representative results from one luciferase reporter assay experiment for each reporter construct tested. Results from wild-type (wt) and mutant (mt) constructs are adjacent, labelled according to the gene to which the promoter region is associated. Fold change is calculated against the average of replicate wt values. Promoter regions with no activity (luciferase activity < 2 times that of the promoter-less vector pGL2 Basic) are indicated by a cross. Only statistically significant differences (by unpaired t-test) are indicated, where * denotes p
