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TMPRSS2–ERG fusion co-opts master transcription factors and activates NOTCH signaling in primary prostate cancer

Nature Genetics volume 49, pages 1336–1345 (2017)Cite this article

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Abstract

TMPRSS2–ERG (T2E) structural rearrangements typify ∼50% of prostate tumors and result in overexpression of the ERG transcription factor. Using chromatin, genomic and expression data, we show distinct cis-regulatory landscapes between T2E-positive and non-T2E primary prostate tumors, which include clusters of regulatory elements (COREs). This difference is mediated by ERG co-option of HOXB13 and FOXA1, implementing a T2E-specific transcriptional profile. We also report a T2E-specific CORE on the structurally rearranged ERG locus arising from spreading of the TMPRSS2 locus pre-existing CORE, assisting in its overexpression. Finally, we show that the T2E-specific cis-regulatory landscape underlies a vulnerability against the NOTCH pathway. Indeed, NOTCH pathway inhibition antagonizes the growth and invasion of T2E-positive prostate cancer cells. Taken together, our work shows that overexpressed ERG co-opts master transcription factors to deploy a unique cis-regulatory landscape, inducing a druggable dependency on NOTCH signaling in T2E-positive prostate tumors.

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Figure 1: H3K27ac ChIP-seq defines active CREs proximal to functionally relevant genes in primary prostate tissue samples.
Figure 2: T2E prostate cancer has a distinct chromatin and gene expression landscape.
Figure 3: ERG remodels binding of master transcription factors to the chromatin.
Figure 4: COREs are proximal to key prostate cancer genes and are remodeled in T2E-positive prostate cancer.
Figure 5: The TMPRSS2 CORE spreads into the ERG locus and contributes to ERG expression.
Figure 6: ERG activates CREs surrounding NOTCH pathway genes.

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Gene Expression Omnibus

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Acknowledgements

R. Bristow (Princess Margaret Cancer Centre) provided 22Rv1 and LNCaP cells, and H. He (Princess Margaret Cancer Centre) provided VCaP cells. We acknowledge the Princess Margaret Genomics Centre and the Princess Margaret Bioinformatics group for providing the infrastructure to assist with analysis of the chromatin landscape of primary prostate tumor samples. This work was supported by Prostate Cancer Canada and is funded by the Movember Foundation (RS2014-04 to M.L. and RS2014-01 to P.C.B.), with additional support from the Ontario Institute for Cancer Research funded by the Government of Ontario, the Princess Margaret Cancer Foundation (M.L. and R.G.B.) and the Radiation Medicine Program Academic Enrichment Fund (R.G.B.). K.J.K. is supported by a Canadian Breast Cancer Foundation (CBCF) postdoctoral fellowship recipient. P.C.B. is supported by a Terry Fox Research Institute New Investigator Award and a Canadian Institute of Health Research (CIHR) New Investigator Award. R.G.B. is supported by a Canadian Cancer Society Research Scientist Award. M.L. is supported by an Investigator Award from the Ontario Institute for Cancer Research, a CIHR New Investigator Award and a Movember Rising Star Award from Prostate Cancer Canada. K.J.K. and A.M. are co-first authors and can be interchangeably ordered in reporting documents.

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Author notes

  1. Ken J Kron and Alexander Murison: These authors contributed equally to this work.

Authors and Affiliations

  1. Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada

    Ken J Kron, Alexander Murison, Stanley Zhou, Michael Fraser, Robert G Bristow & Mathieu Lupien

  2. Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada

    Stanley Zhou, Paul C Boutros, Robert G Bristow & Mathieu Lupien

  3. Ontario Institute for Cancer Research, Toronto, Ontario, Canada

    Vincent Huang, Takafumi N Yamaguchi, Yu-Jia Shiah, Paul C Boutros & Mathieu Lupien

  4. Department of Pathology and Laboratory Medicine, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada

    Theodorus van der Kwast

  5. Department of Pharmacology and Toxicology, University of Toronto, Toronto, Ontario, Canada

    Paul C Boutros

  6. Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada

    Robert G Bristow

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Contributions

K.J.K. designed and conducted most of the experiments. A.M. implemented most of the computational and statistical approaches. S.Z. conducted the co-IP assays and assisted in ChIP-reChIP and CRISPR experiments. V.H. and T.N.Y. analyzed the genetic data sets for single nucleotide and copy number variants. Y.-J.S. processed gene expression data sets. T.v.d.K. was responsible for histopathological assessment of the tumor samples. M.F., P.C.B., R.G.B. and M.L. supervised the research. M.L. oversaw the project. Figures were designed and prepared by K.J.K. and A.M. The manuscript was written by K.J.K., A.M. and M.L. with assistance from all authors.

Corresponding author

Correspondence to Mathieu Lupien.

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Integrated supplementary information

Supplementary Figure 1 Infiltrating immune cells do not differ between T2E and non-T2E samples and represent a small fraction of total cellularity.

(a) ESTIMATE immune score from mRNA expression array data for non-T2E and T2E samples. (b) Estimated percentage of tumor infiltrating lymphocytes within each tumor sample as assessed by H&E staining.

Supplementary Figure 2 ChIP-seq signal distribution across the genome of primary prostate tissue samples.

(a) Distribution of H3K27ac enriched cis-regulatory elements across promoters, introns, exons, downstream/3′ UTR, and promoter/5′UTR elements in each of the 19 samples profiled by ChIP-seq. Snapshot of H3K27ac levels surrounding (b) the housekeeping ACTB gene and (c) prostate-specific KLK3 gene.

Supplementary Figure 3 Classification of samples into T2E and non-T2E on the basis of ERG expression.

(a) Complete linkage hierarchical clustering of HOXB13, AR, ERG, and FOXA1 mRNA expression values in 17 CPCG tumor samples. (b) Immunohistochemical staining of ERG in 6 T2E and 5 non-T2E CPCG samples.

Supplementary Figure 4 T2E-up and T2E-down elements are proximal to known ERG targets and genomic regions previously not classified as T2E specific.

Snapshots of H3K27ac levels in proximity to (a) LAMC2, (b) LINC00898, (c) POTEB, and (b) HTR7 genes.

Supplementary Figure 5 Promoter and enhancer acetylation changes between T2E and non-T2E primary prostate tumors are significantly predictive of one another and of associated gene expression changes.

Volcano plots of log2 fold change vs -log2 FDR-corrected q-value for statistical significance of differential H3K27ac ChIP-seq signal between T2E and non-T2E tumors at enhancer regions linked to (a) T2E-up promoters or (b) T2E-down promoters. Volcano plots of log fold change vs -log FDR corrected q-value for statistical significance of matched differential mRNA expression between T2E and non-T2E tumors for mRNA associated with genes whose promoters (c) or predicted enhancers (d) show differential H3K27ac ChIP-seq signal between T2E and non-T2E tumors.

Supplementary Figure 6 ERG recruits prostate master transcription factors to T2E-up elements.

(a) Motif enrichment for selected motifs in cis-regulatory elements that were not significantly different between T2E and non-T2E tumors. (FKH: Forkhead; ARE: androgen response element; ETS: E26 transformation specific; HBOX: homebox). (b) Western blot of ERG, FOXA1, and HOXB13 following depletion of ERG with siRNA in VCaP cells. Vinculin was blotted as a loading control. (siCtl: non-targeting siRNA; siERG: ERG targeting siRNA). (c) ChIP-seq signal plots of average HOXB13 tag density in VCaP cells treated with control non-targeting siRNA or ERG targeting siRNA at HOXB13/ERG co-bound T2E-up elements, (d) HOXB13 bound T2E-up elements not ERG bound, (e) HOXB13 bound T2E-down elements, and (f) HOXB13 peaks that are not T2E-up, T2E down, and not bound by ERG. (g) ChIP-seq plots of average FOXA1 tag density in VCaP cells treated with control non-targeting siRNA or ERG targeting siRNA at FOXA1/ERG co-bound T2E-up elements, (h) FOXA1 bound T2E-up elements not ERG bound, (i) FOXA1 bound T2E-down elements, and (j) FOXA1 peaks that are not T2E-up, T2E down, and not bound by ERG. (k). Co-immunoprecipitation of FOXA1, ERG, and HOXB13 transcription factors in VCaP cells. Arrows indicate expected size of protein on blot. (IP: immunoprecipitation; WB: western blot).

Supplementary Figure 7 ERG colocalizes with FOXA1, HOXB13 and AR at T2E-up elements.

Snapshot depicting H3K27ac ChIP-seq signal in primary tumors and VCaP cells as well as FOXA1, HOXB13, AR and ERG binding in VCaP cells at seven loci tested (Fig. 3g) by ChIP-reChIP-qPCR.

Supplementary Figure 8 COREs surround prostate master transcription factors, and CORE deregulation in T2E prostate cancer corresponds to T2E-specific gene expression changes.

Snapshot depicting H3K27ac ChIP-seq signal in T2E and non-T2E primary prostate cancer for (a) FOXA1 and (b) HOXB13. (c) Volcano plot of log2 fold change vs -log2 FDR-corrected q-value for statistical significance of differential expression from MSKCC dataset of all genes that were overlapping a T2E-up or T2E-down CORE.

Supplementary Figure 9 CRISPR-mediated deletions of the TMPRSS2–ERG CORE.

(a) Snapshot depicting H3K27ac ChIP-seq signal in primary tumors, VCaP cells, and HUVEC cells as well as master transcription factor binding in VCaP cells across the control AAVS1 locus in the PPP1R12C gene. (b) PCR blots to verify deletions of EC1, EC2, EC3, and control loci. PCR products running below expected size products represent deletion fragments. (*: non-specific PCR product).

Supplementary Figure 10 Cis-regulatory elements affected by ERG enrich for genes involved in NOTCH and developmental signaling pathways.

−log10 FDR values for top ten GO biological processes terms in (a) VCaP siERG H3K27ac down cis-regulatory elements, (b) primary tissue defined T2E-up cis-regulatory elements, and (c) primary tissue defined T2E-up COREs.

Supplementary Figure 11 Key NOTCH pathway genes associated with T2E-up cis-regulatory elements and COREs are overexpressed in T2E prostate cancer.

Log2 mRNA array expression values for T2E and non-T2E samples within the entire CPCG cohort for (a) HES1, (b) JAG1, and (c) DLL1.

Supplementary Figure 12 BMP and Nodal signaling genes do not show essentiality in a T2E-specific manner.

Average gene level Z-score in the Achilles project dataset from (a) BMP and (b) Nodal signaling pathway genes in 22Rv1and VCaP cells. Distributions were obtained from 1,000 random gene sets.

Supplementary Figure 13 Saturation analysis of called H3K27ac peaks stratified by T2E status suggests we have identified at least 95% of potential peaks.

A non-linear regression model was fit to the number of new peaks obtained sequentially over all samples for 1,000 permutations of sample orders and stratified according to (a) T2E and (b) nonT2E status. Individual points show mean new peaks per sample added and associated standard error of the mean fitted blue line shows fitted model with saturation line (red) marked as well as estimated number of samples needed to identify 95, 97 and 99% of peaks (grey lines).

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Life Sciences Reproducibility Summary (PDF 190 kb)

Supplementary Tables 1–10

H3K27ac cis-regulatory elements in CPCG0233 (XLSX 19715 kb)

H3K27ac cis-regulatory elements in CPCG0236

H3K27ac cis-regulatory elements in CPCG0242

H3K27ac cis-regulatory elements in CPCG0246

H3K27ac cis-regulatory elements in CPCG0248

H3K27ac cis-regulatory elements in CPCG0258

H3K27ac cis-regulatory elements in CPCG0259

H3K27ac cis-regulatory elements in CPCG0262

H3K27ac cis-regulatory elements in CPCG0265

H3K27ac cis-regulatory elements in CPCG0266

Supplementary Tables 11–19

H3K27ac cis-regulatory elements in CPCG0267 (XLSX 18329 kb)

H3K27ac cis-regulatory elements in CPCG0269

H3K27ac cis-regulatory elements in CPCG0339

H3K27ac cis-regulatory elements in CPCG0340

H3K27ac cis-regulatory elements in CPCG0341

H3K27ac cis-regulatory elements in CPCG0342

H3K27ac cis-regulatory elements in CPCG0348

H3K27ac cis-regulatory elements in CPCG0365

H3K27ac cis-regulatory elements in CPCG0366

Supplementary Table 20

GREAT analysis of cis-regulatory elements found in all 19 tumors (XLSX 465 kb)

Supplementary Table 21

T2E-up cis-regulatory elements (XLSX 160 kb)

Supplementary Table 22

T2E-down cis-regulatory elements (XLSX 203 kb)

Supplementary Tables 23–32

Cis-regulatory elements with increased H3K27ac in T2E samples with PTEN deletion (XLSX 33 kb)

Cis-regulatory elements with decreased H3K27ac in T2E samples with PTEN deletion

Cis-regulatory elements with increased H3K27ac in non-T2E samples with NKX3-1 deletion

Cis-regulatory elements with decreased H3K27ac in non-T2E samples with NKX3-1 deletion

Cis-regulatory elements with increased H3K27ac in T2E samples with RB1 deletion

Cis-regulatory elements with decreased H3K27ac in T2E samples with RB1 deletion

Cis-regulatory elements with increased H3K27ac in T2E samples with CDKN1B deletion

Cis-regulatory elements with decreased H3K27ac in T2E samples with CDKN1B deletion

Cis-regulatory elements with increased H3K27ac in non-T2E samples with CDKN1B deletion

Cis-regulatory elements with decreased H3K27ac in non-T2E samples with CDKN1B deletion

Supplementary Table 33

Catalog of COREs defined across 19 tumors (XLSX 97 kb)

Supplementary Table 34

T2E-up COREs (XLSX 18 kb)

Supplementary Table 35

T2E-down COREs (XLSX 18 kb)

Supplementary Table 36

GREAT analysis from VCaP siERG H3K27ac down cis-regulatory elements (XLSX 1100 kb)

Supplementary Table 37

GREAT analysis from T2E-up cis-regulatory elements (XLSX 467 kb)

Supplementary Table 38

GREAT analysis from T2E-up COREs (XLSX 193 kb)

Supplementary Table 39

Oligos used in this study (XLSX 11 kb)

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Kron, K., Murison, A., Zhou, S. et al. TMPRSS2–ERG fusion co-opts master transcription factors and activates NOTCH signaling in primary prostate cancer. Nat Genet 49, 1336–1345 (2017). https://doi.org/10.1038/ng.3930

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