Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Distinct structural classes of activating FOXA1 alterations in advanced prostate cancer

Abtract

Forkhead box A1 (FOXA1) is a pioneer transcription factor that is essential for the normal development of several endoderm-derived organs, including the prostate gland1,2. FOXA1 is frequently mutated in hormone-receptor-driven prostate, breast, bladder and salivary-gland tumours3,4,5,6,7,8. However, it is unclear how FOXA1 alterations affect the development of cancer, and FOXA1 has previously been ascribed both tumour-suppressive9,10,11 and oncogenic12,13,14 roles. Here we assemble an aggregate cohort of 1,546 prostate cancers and show that FOXA1 alterations fall into three structural classes that diverge in clinical incidence and genetic co-alteration profiles, with a collective prevalence of 35%. Class-1 activating mutations originate in early prostate cancer without alterations in ETS or SPOP, selectively recur within the wing-2 region of the DNA-binding forkhead domain, enable enhanced chromatin mobility and binding frequency, and strongly transactivate a luminal androgen-receptor program of prostate oncogenesis. By contrast, class-2 activating mutations are acquired in metastatic prostate cancers, truncate the C-terminal domain of FOXA1, enable dominant chromatin binding by increasing DNA affinity and—through TLE3 inactivation—promote metastasis driven by the WNT pathway. Finally, class-3 genomic rearrangements are enriched in metastatic prostate cancers, consist of duplications and translocations within the FOXA1 locus, and structurally reposition a conserved regulatory element—herein denoted FOXA1 mastermind (FOXMIND)—to drive overexpression of FOXA1 or other oncogenes. Our study reaffirms the central role of FOXA1 in mediating oncogenesis driven by the androgen receptor, and provides mechanistic insights into how the classes of FOXA1 alteration promote the initiation and/or metastatic progression of prostate cancer. These results have direct implications for understanding the pathobiology of other hormone-receptor-driven cancers and rationalize the co-targeting of FOXA1 activity in therapeutic strategies.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Structural classes of FOXA1 alterations.
Fig. 2: Functional characterization of class-1 mutations of FOXA1.
Fig. 3: Functional characterization of class-2 mutations of FOXA1.
Fig. 4: Genomic characterization of class-3 rearrangements of the FOXA1 locus.

Similar content being viewed by others

Data availability

All raw data for the graphs, immunoblot and gel electrophoresis figures are included in the Source Data or Supplementary Information. All materials are available from the authors upon reasonable request. All the raw next-generation sequencing, ChIP and RNA-seq data generated in this study have been deposited in the Gene Expression Omnibus (GEO) repository at NCBI (accession code GSE123625).

Code availability

All custom data analysis software and bioinformatics algorithms used in this study are publically available on Github: https://github.com/mcieslik-mctp/ and https://github.com/mctp/.

References

  1. Gao, N. et al. Forkhead box A1 regulates prostate ductal morphogenesis and promotes epithelial cell maturation. Development 132, 3431–3443 (2005).

    Article  CAS  PubMed  Google Scholar 

  2. Friedman, J. R. & Kaestner, K. H. The Foxa family of transcription factors in development and metabolism. Cell. Mol. Life Sci. 63, 2317–2328 (2006).

    Article  CAS  PubMed  Google Scholar 

  3. Cancer Genome Atlas Research Network. Comprehensive molecular characterization of urothelial bladder carcinoma. Nature 507, 315–322 (2014).

    Article  ADS  CAS  Google Scholar 

  4. Robinson, D. et al. Integrative clinical genomics of advanced prostate cancer. Cell 161, 1215–1228 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Cancer Genome Atlas Research Network. The molecular taxonomy of primary prostate cancer. Cell 163, 1011–1025 (2015).

    Article  CAS  Google Scholar 

  6. Ciriello, G. et al. Comprehensive molecular portraits of invasive lobular breast cancer. Cell 163, 506–519 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Dalin, M. G. et al. Comprehensive molecular characterization of salivary duct carcinoma reveals actionable targets and similarity to apocrine breast cancer. Clin. Cancer Res. 22, 4623–4633 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Zehir, A. et al. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. Nat. Med. 23, 703–713 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Jin, H.-J., Zhao, J. C., Ogden, I., Bergan, R. C. & Yu, J. Androgen receptor-independent function of FoxA1 in prostate cancer metastasis. Cancer Res. 73, 3725–3736 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Jin, H.-J., Zhao, J. C., Wu, L., Kim, J. & Yu, J. Cooperativity and equilibrium with FOXA1 define the androgen receptor transcriptional program. Nat. Commun. 5, 3972 (2014).

    Article  ADS  CAS  PubMed  Google Scholar 

  11. Song, B. et al. Targeting FOXA1-mediated repression of TGF-β signaling suppresses castration-resistant prostate cancer progression. J. Clin. Invest. 129, 156–582 (2019).

    Google Scholar 

  12. Robinson, J. L. L. et al. Androgen receptor driven transcription in molecular apocrine breast cancer is mediated by FoxA1. EMBO J. 30, 3019–3027 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Robinson, J. L. L. et al. Elevated levels of FOXA1 facilitate androgen receptor chromatin binding resulting in a CRPC-like phenotype. Oncogene 33, 5666–5674 (2014).

    Article  CAS  PubMed  Google Scholar 

  14. Pomerantz, M. M. et al. The androgen receptor cistrome is extensively reprogrammed in human prostate tumorigenesis. Nat. Genet. 47, 1346–1351 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Cirillo, L. A. et al. Opening of compacted chromatin by early developmental transcription factors HNF3 (FoxA) and GATA-4. Mol. Cell 9, 279–289 (2002).

    Article  CAS  PubMed  Google Scholar 

  16. Iwafuchi-Doi, M. et al. The pioneer transcription factor FoxA maintains an accessible nucleosome configuration at enhancers for tissue-specific gene activation. Mol. Cell 62, 79–91 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Lupien, M. et al. FoxA1 translates epigenetic signatures into enhancer-driven lineage-specific transcription. Cell 132, 958–970 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Barbieri, C. E. et al. Exome sequencing identifies recurrent SPOP, FOXA1 and MED12 mutations in prostate cancer. Nat. Genet. 44, 685–689 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Yang, Y. A. & Yu, J. Current perspectives on FOXA1 regulation of androgen receptor signaling and prostate cancer. Genes Dis. 2, 144–151 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Grasso, C. S. et al. The mutational landscape of lethal castration-resistant prostate cancer. Nature 487, 239–243 (2012).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  21. Gao, J. et al. 3D clusters of somatic mutations in cancer reveal numerous rare mutations as functional targets. Genome Med. 9, 4 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Clark, K. L., Halay, E. D., Lai, E. & Burley, S. K. Co-crystal structure of the HNF-3/fork head DNA-recognition motif resembles histone H5. Nature 364, 412–420 (1993).

    Article  ADS  CAS  PubMed  Google Scholar 

  23. Li, J. et al. Structure of the forkhead domain of FOXA2 bound to a complete DNA consensus site. Biochemistry 56, 3745–3753 (2017).

    Article  CAS  PubMed  Google Scholar 

  24. Sekiya, T., Muthurajan, U. M., Luger, K., Tulin, A. V. & Zaret, K. S. Nucleosome-binding affinity as a primary determinant of the nuclear mobility of the pioneer transcription factor FoxA. Genes Dev. 23, 804–809 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Wang, Z. et al. BART: a transcription factor prediction tool with query gene sets or epigenomic profiles. Bioinformatics 34, 2867–2869 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Behrens, J. et al. Functional interaction of β-catenin with the transcription factor LEF-1. Nature 382, 638–642 (1996).

    Article  ADS  CAS  PubMed  Google Scholar 

  27. Daniels, D. L. & Weis, W. I. β-catenin directly displaces Groucho/TLE repressors from Tcf/Lef in Wnt-mediated transcription activation. Nat. Struct. Mol. Biol. 12, 364–371 (2005).

    Article  CAS  PubMed  Google Scholar 

  28. Wang, W., Zhong, J., Su, B., Zhou, Y. & Wang, Y.-Q. Comparison of Pax1/9 locus reveals 500-Myr-old syntenic block and evolutionary conserved noncoding regions. Mol. Biol. Evol. 24, 784–791 (2007).

    Article  CAS  PubMed  Google Scholar 

  29. Tomlins, S. A. et al. Distinct classes of chromosomal rearrangements create oncogenic ETS gene fusions in prostate cancer. Nature 448, 595–599 (2007).

    Article  ADS  CAS  PubMed  Google Scholar 

  30. Annala, M. et al. Recurrent SKIL-activating rearrangements in ETS-negative prostate cancer. Oncotarget 6, 6235–6250 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Shalem, O. et al. Genome-scale CRISPR–Cas9 knockout screening in human cells. Science 343, 84–87 (2014).

    Article  ADS  CAS  PubMed  Google Scholar 

  32. Phair, R. D. et al. Global nature of dynamic protein–chromatin interactions in vivo: three-dimensional genome scanning and dynamic interaction networks of chromatin proteins. Mol. Cell. Biol. 24, 6393–6402 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Grimm, J. B. et al. A general method to improve fluorophores for live-cell and single-molecule microscopy. Nat. Methods 12, 244–250 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Pitchiaya, S. et al. Dynamic recruitment of single RNAs to processing bodies depends on RNA functionality. Mol. Cell 74, 521–533 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Swinstead, E. E. et al. Steroid receptors reprogram FoxA1 occupancy through dynamic chromatin transitions. Cell 165, 593–605 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Pitchiaya, S., Androsavich, J. R. & Walter, N. G. Intracellular single molecule microscopy reveals two kinetically distinct pathways for microRNA assembly. EMBO Rep. 13, 709–715 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Shah, N. B. & Duncan, T. M. Bio-layer interferometry for measuring kinetics of protein–protein interactions and allosteric ligand effects. J. Vis. Exp. 84, e51383 (2014).

    Google Scholar 

  38. Teng, Y. et al. Evaluating human cancer cell metastasis in zebrafish. BMC Cancer 13, 453 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Ramírez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 44, W160–W165 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Zhu, L. J. et al. ChIPpeakAnno: a Bioconductor package to annotate ChIP-seq and ChIP-chip data. BMC Bioinformatics 11, 237 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Bailey, T. L. et al. MEME SUITE: tools for motif discovery and searching. Nucleic Acids Res. 37, W202–W208 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Wilson, S. et al. Developing cancer informatics applications and tools using the NCI genomic data commons API. Cancer Res. 77, e15–e18 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature 490, 61–70 (2012).

    Article  ADS  CAS  Google Scholar 

  46. Cerami, E. et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2, 401–404 (2012).

    Article  PubMed  Google Scholar 

  47. Wu, Y.-M. et al. Inactivation of CDK12 delineates a distinct immunogenic class of advanced prostate cancer. Cell 173, 1770–1782 (2018).

    Article  CAS  PubMed  Google Scholar 

  48. Cieslik, M. et al. The use of exome capture RNA-seq for highly degraded RNA with application to clinical cancer sequencing. Genome Res. 25, 1372–1381 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Robinson, D. R. et al. Integrative clinical genomics of metastatic cancer. Nature 548, 297–303 (2017).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  50. Layer, R. M., Chiang, C., Quinlan, A. R. & Hall, I. M. LUMPY: a probabilistic framework for structural variant discovery. Genome Biol. 15, R84 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  51. Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2013).

    Article  PubMed  CAS  Google Scholar 

  52. Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).

    Article  CAS  PubMed  Google Scholar 

  53. Smyth, G. K., McCarthy, D. J. & Smyth, G. K. in Bioinformatics and Computational Biology Solutions Using R and Bioconductor (eds Dudoit, S. & Carey, V. J.) 397–420 (Springer, New York, 2005).

  54. Law, C. W., Chen, Y., Shi, W. & Smyth, G. K. voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 15, R29 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. Liberzon, A. et al. The molecular signatures database hallmark gene set collection. Cell Syst. 1, 417–425 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Newton, M. A., Quintana, F. A., Boon, J. A. D., Sengupta, S. & Ahlquist, P. Random-set methods identify distinct aspects of the enrichment signal in gene-set analysis. Ann. Appl. Stat. 1, 85–106 (2007).

    Article  MathSciNet  MATH  Google Scholar 

  57. Subramanian, A., Kuehn, H., Gould, J., Tamayo, P. & Mesirov, J. P. GSEA-P: a desktop application for Gene Set Enrichment Analysis. Bioinformatics 23, 3251–3253 (2007).

    Article  CAS  PubMed  Google Scholar 

  58. Searle, S. et al. The GENCODE human gene set. Genome Biol. 11, P36 (2010).

    Article  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank D. Macha, L. Wang, S. Zelenka-Wang, I. Apel, M. Tan, Y. Qiao, A. Delekta, K. Juckette and J. Tien for technical assistance, and S. Gao for assistance with the manuscript. This work was supported by the Prostate Cancer Foundation (PCF), Early Detection Research Network (UO1 CA214170), NCI Prostate SPORE (P50 CA186786) and Stand Up 2 Cancer-PCF Dream Team (SU2C-AACR-DT0712) grants to A.M.C. A.M.C. is an NCI Outstanding Investigator, Howard Hughes Medical Institute Investigator, A. Alfred Taubman Scholar and American Cancer Society Professor. A.P. is supported by a Predoctoral Department of Defense (DoD) - Early Investigator Research Award (W81XWH-17-1-0130). M.C. is supported by  a DoD - Idea Development Award (W81XWH-17-1-0224) and a PCF Young Investigator Award.

Author information

Authors and Affiliations

Authors

Contributions

A.P., M.C. and A.M.C. conceived and designed the study; A.P. performed all the experiments with assistance from L.X., T.O., X.W. and S.P. M.C. carried out bioinformatics analyses with assistance from A.P., Y.Z., R.J.L. and P.V. S.-C.C. and A.P. performed zebrafish in vivo experiments. A.P. is responsible for the following experimental figures: Figs. 2b–f, h, 3b–i, 4e, as well as Extended Data Figs. 1a–i, 3b–n, 4a–f, k–n, 5a–k, 6a–l, 7i–o, 8a–h, j, 9a, d, e, 10g. M.C. is responsible for the following computational figures: Figs. 1a–h, 2a, g, 3a, 4a–d, as well as Extended Data Figs. 1j–n, 2a–l, 3a, p, q, 4g–j, o–q, 7a–c, g, h, 9b, c, f–h, 10a–f. Y.Z. is responsible for the following computational figures: Extended Data Figs. 3o, r, s, 7d–f, 8i, k. F.S. and R.W. generated ChIP–seq and RNA-seq libraries. X.C. performed sequencing. F.Y.F. provided genomic validation data. Y.-M.W. and D.R.R. coordinated clinical sequencing. A.P., M.C. and A.M.C. wrote the manuscript and organized the figures.

Corresponding author

Correspondence to Arul M. Chinnaiyan.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature thanks Myles Brown, William Nelson, Mark A. Rubin and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Functional essentiality and recurrent alterations of FOXA1 in AR+ prostate cancer.

ac, AR (a) and FOXA1 (b) mRNA (qPCR) and (c) protein expression in a panel of prostate cancer cells (n = 3 technical replicates). Mean ± s.e.m. is shown and dots are individual data points. df, Growth curves of AR+ prostate cancer cells treated with non-targeting control (siNC), AR- or FOXA1-targeting siRNAs (25 nM at day 0 and 1; n = 6 biological replicates). Immunoblots confirm knockdown of FOXA1 protein in LNCaP and LAPC4 72 h after siRNA treatment. For all gel source data, see Supplementary Fig. 1. g, Crystal-violet stain of AR DU145 prostate cancer and LNCaP (control) cells treated with siNC, AR- or FOXA1-targeting siRNAs. Results represent 3 independent experiments (n = 2 biological replicates). h, Averaged proliferation z-scores for 6 independent FOXA1-targeting sgRNAs extracted from publically available CRISPR Project Achilles data (BROAD Institute) in prostate and breast cancer cells. HPRT1 and AR data serve as negative and positive controls, respectively. Mean ± s.e.m. is shown; dots are proliferative z-scores for independent sgRNAs. i, Ranked depletion or enrichment of sgRNA read counts from GeCKO-V2 CRISPR knockout screen in LNCaP cells (at day 30) relative to the input sample. Only a subset of genes—including essential controls, chromatin modifiers and transcription factors—is visualized. j, Recurrence of FOXA1 mutations across TCGA, MSK-IMPACT and SU2C cohorts. k, Density of break ends (RNA-seq chimeric junctions) within overlapping 1.5-Mb windows along chr14 in mCRPC tumours. l, Whole-genome sequencing (WGS) of seven mCRPC index cases with distinct patterns of FOXA1 translocations (Tlocs) and duplications (Dups), nominated by RNA-seq (WA46, WA37, WA57 and MO_1584) or whole-exome sequencing (MO_1778, SC_9221 and MO_1637). m, Concordance of RNA-seq (chimeric junctions) and whole-exome-sequencing-based FOXA1 locus rearrangements calls (mCRPC cohort). CNV, copy-number variation. n, Frequency of FOXA1 locus rearrangements in mCRPC based on RNA-seq and whole-exome sequencing.

Source Data

Extended Data Fig. 2 Genomic characteristics of the three classes of FOXA1 alterations in prostate and breast cancer.

a, b, Bi-allelic inactivation (a) and copy-number variations (b) of FOXA1 across mCRPC (n = 371). CN-LOH, copy-neutral loss of heterozygosity. c, FOXA1 expression (RNA-seq) in benign (n = 51), primary (n = 501) and metastatic (n = 535) prostate cancer. d, Distribution and functional categorization of FOXA1 mutations (all cases in the aggregate cohort) on the protein map of FOXA1. e, Aggregate and class-specific distribution of FOXA1 mutations in advanced breast cancer (MSK-IMPACT cohort). f, Structural classification of FOXA1 locus rearrangements in breast cancer (TCGA and CCLE cell lines). g, h, Variant allele frequency of FOXA1 mutations by tumour stage (g) and clonality estimates of class-1 and class-2 mutations (h) in tumour-content-corrected primary prostate cancer (n = 500) and mCRPC (n = 370) specimens. i, Mutual exclusivity or co-occurrence of FOXA1 mutations (two-sided Fisher’s exact test). Mutations in AR, WNT, and PI3K were aggregated at the pathway level. ETS, ETS gene fusions; DRD, DNA repair defects and included alterations in BRCA1, BRCA2, ATM and CDK12; MMRD, mismatch repair deficiency (total n = 371). j, Mutual exclusivity of ETS and/or SPOP (n = 26) alterations with FOXA1 (n = 46) alterations distinguished by class in mCRPC (n = 371). k, Co-occurrence of WNT (n = 58) and DRD (n = 107) pathway alterations with FOXA1 alteration classes in mCRPC (n = 371). l, Stage- and class-specific increase in FOXA1 expression levels in primary (n = 500) and metastatic prostate cancer (n = 357). Left, two-sided t-test. Right, two-way ANOVA. For all box plots, centre shows median, box marks quartiles 1–3 and whiskers span quartiles 1–3 ± 1.5 × IQR.

Source Data

Extended Data Fig. 3 Biophysical and cistromic characteristics of the class-1 FOXA1 mutants.

a, Distribution of class-1 mutations on the protein map of FOXA1. b, Three-dimensional structure of FKHD (FOXA3) with visualization of all mutated residues collectively identified as the 3D-mutational hotspot in FOXA1 across cancers. c, DNA-bound 3D structure of FKHD with visualization of all residues shown through crystallography to make direct base-specific contacts with the DNA in FOXA2 and FOXA3 proteins. d, Representative fluorescent images of nuclei expressing different variants of FOXA1 fused to GFP at the C termini. e, f, FRAP kinetic plots (left) and representative time-lapse images (right) from pre-bleaching (pre) to 100% recovery (red timestamps) for wing-2-altered class-1 mutants (e) and truncated class-2 mutants (that is, A287fs and P375fs) (f) (n = 6 nuclei per variant; quantified in Fig. 2d). White lines indicate the border between bleached and unbleached areas. g, Representative FRAP kinetics in the bleached area for indicated FOXA1 variants. t1/2 line indicates the time to 50% recovery. Coloured dots show raw data; superimposed solid curves show a hyperbolic fit with 95% confidence intervals. h, Single particle tracking quantification of chromatin-bound (slow and fast) and unbound (freely diffusing) particles of wild-type and class-1 FOXA1 variants, and average chromatin dwell times (mean ± s.d.) for the bound fractions (n ≥ 500 particles per variant). i, Diffusion constant histograms of single particles of wild-type or distinct class-1 FOXA1 mutants. Particles were categorized into chromatin-bound (slow and fast) or unbound fractions using cut-offs marked by dashed lines (n ≥ 500 particles per variant imaged in 3–5 distinct nuclei). j, Left, mRNA expression (qPCR) of labelled FOXA1 variants in stable, isogenic HEK293 cells (n = 3 technical replicates). Right, overlaps between FOXA1 wild-type and class-1 mutant cistromes from these cells (n = 2 biological replicates). k, Top de novo motifs identified from the three FOXA1 cistromes from HEK293 cells (HOMER, hypergeometric test). l, mRNA expression (qPCR) of labelled FOXA1 variants in stable, isogenic 22RV1 cells (n = 3 technical replicates). For j and l, centres show mean values and lines mark s.e.m. m, Overlap between wild-type (n = 2 biological replicates) and class-1 (n = 4 biological replicates) cistromes from stable 22RV1 overexpression models. n, Overlap between the FOXA1 wild-type and AR union cistromes generated from 22RV1 cells overexpressing wild-type (n = 2 biological replicates) or class-1 mutant (I176M or R216G; n = 2 biological replicates each) FOXA1 variants. o, De novo motif results for the wild-type or class-1 mutant FOXA1-binding sites from prostate cancer cells (HOMER, hypergeometric test). p, q, Per cent of wild-type or class-1 binding sites with perfect match to the core FOXA1 motif (5′-T[G/A]TT[T/G]AC-3′) (p) and the consensus FOXA1 motifs identified from these sites (q). r, Left, per cent of wild-type or class-1 binding sites containing known motifs of the labelled FOXA1 or AR cofactors. Right, enrichment of the cofactor motifs in the two cistromes relative to the background (n = top 5,000 peaks by score for each variant, see Methods). s, Genomic distribution of wild-type and class-1 binding sites in prostate cancer cells.

Source Data

Extended Data Fig. 4 Functional effect of FOXA1 mutations on oncogenic AR signalling.

a, Immunoblot showing expression of endogenous and V5-tagged exogenous FOXA1 proteins in doxycycline (dox)-inducible 22RV1 cells transfected with distinct UTR-specific FOXA1-targeting siRNAs (no. 3–5) or a non-targeting control siRNA (siNC). These results represent two independent experiments. IncuCyte growth curves of 22RV1 cells overexpressing empty vector (control), wild-type or mutant FOXA1 variants upon treatment with UTR-specific FOXA1-targeting siRNAs (n = 5 biological replicates). Mean ± s.e.m. is shown. b, Immunoblots confirming stable overexpression of the wild-type AR protein in HEK293 and PC3 cells. c, d, Co-immunoprecipitation assay of indicated recombinant FOXA1 variants using a V5-tag antibody in HEK293 (c) and PC3 (d) cells stably overexpressing the AR protein (referred to as HEK293-AR and PC3-AR cells). eGFP is a negative control. FOXA1-FL, full-length wild-type FOXA1. del168 and del358 are truncated FOXA1 variants with only the first 168 amino acids (that is, before the FKHD) or 358 amino acids of the FOXA1 protein. H247Q and R261G are missense class-1 mutant variants. e, Immunoblots confirming comparable expression of AR and recombinant FOXA1 variants in AR reporter assay-matched HEK293 lysates. Immunoblots show representative results from 2 or 3 independent experiments and class-1 and class-2 mutants serve as biological replicates. For all gel source data (a, be), see Supplementary Fig. 1. f, AR dual-luciferase reporter assays with transient overexpression of indicated FOXA1 variants in HEK293-AR cells with or without DHT stimulation and enzalutamide treatment (n = 3 biological replicates per group). Mean ± s.e.m. is shown (two-way ANOVA and Tukey’s test). g, Genes differentially expressed in class-1 tumours from patients (n = 38) compared to FOXA1 wild-type tumours (see Methods). The most significant genes are shown in red and labelled (limma two-sided test). h, Differential expression of cancer-hallmark signature genes in class-1 mutant prostate-cancer tumours (GSEA statistical test). i, Localized, primary prostate cancer gene signature showing concordance between class-1 tumour and primary prostate cancer genes. j, BART prediction of specific transcription factors mediating observed transcriptional changes. The significant and strong (z-score) mediators of transcriptional responses in class-1 tumours are labelled (BART, Wilcoxon rank-sum test). k, mRNA expression (RNA-seq) of class-1 signature genes in LNCaP and VCaP cells either starved for androgen (no DHT) or stimulated with DHT (10 nM). RNA-seq from two distinct prostate cancer cell lines is shown. l, Representative FOXA1 and AR ChIP–seq normalized signal tracks at the WNT7B or CASP2 gene loci in LNCaP and C42B cells. ChIP–seq assays were carried out in two distinct prostate cancer cell lines with similar results. m, Growth curves (IncuCyte) of 22RV1 cells overexpressing distinct FOXA1 variants in complete, androgen-supplemented growth medium (n = 2 biological replicates). Mean ± s.e.m. is shown. n, Per cent viable 22RV1 stable cells, overexpressing either empty vector, wild-type or mutant FOXA1 variants upon treatment with enzalutamide (20 μM for 6 days; n = 4 biological replicates). Mean ± s.e.m. is shown. P values in m and n were calculated using two-way ANOVA and Tukey’s test. o, p, mRNA expression (RNA-seq) of labelled basal and luminal transcription factors or canonical markers in FOXA1 wild-type, class-1 or class-2 mutant tumours in primary prostate cancer (total n = 500; two-way ANOVA). q, Extent of AR and neuroendocrine (NE) pathway activation in FOXA1 wild-type, class-1 or class-2 mutant cases from both primary (n = 500) and metastatic (n = 370) prostate cancer. Both AR and NE scores were calculated using established gene signatures (see Methods). Left, two-sided t-test; right, two-way ANOVA. For all box plots, centre shows median, box marks quartiles 1–3 and whiskers span quartiles 1–3 ± 1.5 × IQR.

Source Data

Extended Data Fig. 5 DNA-binding dominance of the class-2 FOXA1 mutants.

a, FOXA1 protein maps showing the recombinant proteins used to validate the N-terminal (N-term) and C-terminal (C-term) FOXA1 antibodies. b, Immunoblots depicting detection of all variants by the N-terminal antibody (left), and of only the full-length wild-type FOXA1 protein by the C-terminal antibody (right). These results were reproducible in two independent experiments. Antibody details are included in the Methods. c, Sanger sequencing chromatograms showing the heterozygous class-2 mutation in LAPC4 cells after the P358 codon in exon 2 (n = 2 technical replicates). All other tested prostate cancer cell lines were wild type for FOXA1. d, Immunoblots confirming the expression of the truncated FOXA1 variant in LAPC4 at the expected approximately 40-kDa size (top, red arrow). The short band is detectable only with the N-terminal (top) FOXA1 antibody and not the C-terminal (bottom) antibody. These results were reproducible in two independent experiments. e, Co-immunoprecipitation and immunoblotting of FOXA1 using N-terminal and C-terminal antibodies from LAPC4 nuclei with species-matched IgG used as control. f, Nuclear co-immunoprecipitation of FOXA1 from LAPC4 or LNCaP cells stimulated with DHT (10 nM for 16 h) using N-terminal and C-terminal antibodies. Species-matched IgG are controls. Immunoprecipitations and immunoblots in df were reproducible in two and three independent experiments, respectively. For gel source data (b, d, e, f), see Supplementary Fig. 1. g, FOXA1 N-terminal and C-terminal ChIP–seq normalized signal tracks from FOXA1 wild-type or class-2 mutant prostate cancer cells at canonical AR target KLK3. h, Left, overlap between global N-terminal and C-terminal FOXA1 cistromes in untreated C42B cells. Right, overlap between global N-terminal and C-terminal FOXA1 cistromes in LAPC4 cells treated with DHT (10 nM for 3 h). i, FOXA1 ChIP–seq normalized signal tracks from N-terminal and C-terminal antibodies in LAPC4 cells with or without DHT stimulation (10 nM for 3 h) at KLK3 and ZBTB10 loci. ChIP–seq assays in g and i were carried out in two distinct FOXA1 wild-type prostate cancer cells. For LAPC4 ChIP–seq experiments, results were reproducible in two independent experiments. j, mRNA (qPCR) expression of FOXA1 in LAPC4 cells with exogenous overexpression of wild-type FOXA1 (left), and in LNCaP cells with exogenous overexpression of the P358fs mutant (right) (n = 3 technical replicates). Mean ± s.e.m. is shown and dots are individual data values. k, FOXA1 ChIP–seq normalized signal tracks from N-terminal and C-terminal antibodies in parental LAPC4 cells and LAPC4 cells overexpressing wild-type FOXA1 at the KLK3 locus. This experiment was independently repeated twice with similar results. The 60-bp AR- and FOXA1-bound KLK3 enhancer element used for electrophoretic mobility shift assay (EMSA) is shown.

Source Data

Extended Data Fig. 6 DNA-binding affinity and functional essentiality of the class-2 FOXA1 mutants.

a, Immunoblot showing comparable expression of recombinant FOXA1 variants in equal volume of nuclear HEK293 lysates used to perform EMSAs. b, Higher exposure of EMSA with recombinant wild-type or P358fs mutant and KLK3 enhancer element, showing the super-shifted band with addition of the V5 antibody (red asterisks; matched to Fig. 3f). c, d, EMSA with recombinant wild-type or different class-2 mutants (truncated at 268, 287, 358, 375 and 453 amino acids) and KLK3 enhancer element. Class-2 mutants display higher affinity than wild-type FOXA1. Each class-2 mutant serves as a biological replicate and these results were reproducible in two independent experiments. e, DNA association and dissociation kinetics at varying concentrations of purified wild-type or P358fs class-2 FOXA1 mutants from the biolayer-interferometry assay performed using OctetRED system. Overall binding curves and equilibrium dissociation constants (mean ± s.d.) are shown. These results were reproducible in two independent experiments. f, Sanger sequencing chromatograms from a set of 22RV1 CRISPR clones confirming the introduction of distinct indels in the endogenous FOXA1 allele, resulting in a premature stop codon (n = 2 technical replicates). Protein mutations are identified on the right. g, Immunoblots showing the expression of endogenous wild-type or class-2 mutant FOXA1 variants in parental and distinct CRISPR-engineered 22RV1 clones. h, Immunoblots showing expression of FOXA1 (N-terminal antibody) in parental and CRISPR-engineered LNCaP clones expressing distinct class-2 mutants with truncations closer to the FKHD domain. For gel source data (ad, g, h), see Supplementary Fig. 1. i, Growth curves of wild-type or mutant clones upon treatment with the non-targeting or FOXA1-targeting sgRNAs and CRISPR–Cas9 protein (see Methods). For i, distinct class-2 clones and distinct sgRNAs serve as biological replicates. j, k, Overlap between union FOXA1 (j) and AR (k) cistromes from wild-type (n = 3 biological replicates) and class-2-mutant (n = 4 biological replicates) 22RV1 clones. l, Overlap between union FOXA1 and AR cistromes from class-2 mutant 22RV1 cells.

Source Data

Extended Data Fig. 7 Cistromic and WNT-driven phenotypic characteristics of the class-2 FOXA1 mutants.

a, De novo motif analyses of the wild-type-specific, common and class-2-specific FOXA1-binding site subsets defined from either sequencing-read fold changes (left) or peak-calling scores (right) of ChIP–seq data. Wild-type and class-2 cistromes were generated from n = 3 and n = 2 independent biological replicates, respectively. Only the top 5,000 or 10,000 peaks from each subset were used as inputs for motif discovery (see Methods) (HOMER, hypergeometric test). b, c, Per cent of wild-type or class-2 binding sites with perfect match to the core FOXA1 motif (5′-T[G/A]TT[T/G]AC-3′) (b) and the consensus FOXA1 motifs identified from these sites (c). d, e, Per cent of binding sites in the three FOXA1-binding-site subsets containing known motifs of the labelled FOXA1 or AR cofactors (d), and enrichment of the cofactor motifs in the three binding site subsets relative to the background (e). f, Genomic distribution of wild-type-specific, common and class-2-specific binding sites in prostate cancer cells. g, Differential expression of genes in FOXA1 class-2 mutant CRISPR clones relative to FOXA1 wild-type clones (n = 2 biological replicates (limma two-sided test)). h, Distinct transcription factor motifs within the promoter (2-kb upstream) of differentially expressed genes. Transcription factors with the highest enrichment (fold change, per cent of upregulated genes with the motif and significance) are highlighted and labelled (two-tailed Fisher’s exact test). i, Immunoblots showing the expression of β-catenin and vimentin in a panel of wild-type and heterozygous or homozygous class-2 mutant 22RV1 CRISPR clones. j, Immunoblots showing the phosphorylation status of β-catenin and expression of direct WNT target genes in select class-2 mutant 22RV1 clones. Immunoblots in i and j are representative of two independent experiments; every individual clone serves as a biological replicate. For gel source data, see Supplementary Fig. 1. k, Representative images of Boyden chambers showing invaded cells stained with calcein AM dye. l, Quantified fluorescence signal from invaded cells (n = 2 biological replicates per group; two-way ANOVA and Tukey’s test). Mean ± s.e.m. is shown and dots are individual data points. m, Absolute counts of disseminated cell foci in individual zebrafish embryos as a measure of metastatic burden. n, Per cent metastasis at day 2 and day 3 in zebrafish embryos injected with either the normal HEK293 cells (negative controls) or 22RV1 prostate cancer cells virally overexpressing wild-type, class-1 or class-2 mutant FOXA1 variants (n > 20 for each group). o, Fluorescent signal from the invaded wild-type or class-2-mutant 22RV1 cells after androgen starvation (5% charcoal-stripped serum medium for 72 h) or treatment with the WNT inhibitor XAV939 (20 μM for 24 h; n = 2 biological replicates per group; two-way ANOVA and Tukey’s test). Mean ± s.e.m. and individual data points are shown.

Source Data

Extended Data Fig. 8 Functional association of FOXA1 and TLE3 in prostate cancer.

a, mRNA (qPCR) and protein (immunoblot) expression of TLE3 in a panel of prostate cancer cells. Mean ± s.e.m. and individual data points are shown. b, Left, mRNA expression of FOXA1 and TLE3 in LNCaP and VCaP cells treated with siRNAs targeting either FOXA1 or AR (n = 3 technical replicates). Two FOXA1 wild-type prostate cancer cells serve as biological replicates. Mean ± s.e.m. and individual data points are shown. Right, protein expression of FOXA1 and TLE3 in matched LNCaP lysates. c, FOXA1 N-terminal ChIP–seq normalized signal tracks from LNCaP, C42B and LAPC4 prostate cancer cells at the TLE3 locus. Each cell line serves as a biological replicate. d, Overlap of the union wild-type FOXA1- and TLE3-binding sites from LNCaP and C42B prostate cancer cells (n = 1 for each), and top de novo motifs discovered (HOMER, hypergeometric test) in the TLE3 cistrome. e, Co-immunoprecipitation assays of labelled recombinant FOXA1 wild-type, class-1 or class-2 variants using a V5-tag antibody in HEK293 cells overexpressing the TLE3 protein. V5-tagged GFP protein was used as a negative control. These results were reproducible in two independent experiments and distinct class-1 and class-2 mutants serve as biological replicates. f, Overlap of union TLE3 cistromes from isogenic wild-type (n = 2 biological replicates) or heterozygous class-2-mutant (n = 2 biological replicates) 22RV1 CRISPR clones. g, ChIP peak profile plots from TLE3 ChIP–seq in isogenic FOXA1 wild-type or class-2-mutant 22RV1 clones (n = 2 biological replicates each). h, Representative TLE3 and FOXA1 ChIP–seq read signal tracks from independent 22RV1 CRISPR clones with or without endogenous FOXA1 class-2 mutation (n = 2 biological replicates each). i, GSEA showing significant enrichment of WNT (left) and EMT (right) pathway genes in 22RV1 cells treated with TLE3-targeting siRNAs (n = 2 biological replicates for each treatment; GSEA enrichment test). j, Left, mRNA (RNA-seq) expression of direct WNT target genes in 22RV1 upon siRNA-mediated knockdown of TLE3 (n = 2 biological replicates). Right, Immunoblot showing LEF1 upregulation upon TLE3 knockdown in 22RV1 prostate cancer cells with and without androgen starvation (representative of two independent experiments). For gel source data (a, b, e, j), see Supplementary Fig. 1. k, Gene enrichment plots showing significant enrichment of class-2 upregulated genes upon TLE3 knockdown in 22RV1 cells (n = 2 biological replicates for each treatment; GSEA enrichment test).

Source Data

Extended Data Fig. 9 Topological, physical and transcriptional characteristics of the FOXA1 locus in normal tissues and prostate cancer.

a, HI-C data (from: http://promoter.bx.psu.edu/hi-c/view.php) depicting conserved topological domains within the PAX9 and FOXA1 syntenic block in normal and FOXA1+ cancer cell lines. DHSs, DNase I hypersensitive sites. b, Highly tissue-specific patterns of gene expression within the PAX9 and FOXA1 syntenic block. Tissues were dichotomized into FOXA1+ and FOXA1 on the basis of FOXA1 expression levels; genes were subject to unsupervised clustering. z-score normalization was performed for each gene across all tissues. c, Correlation of RP11-356O9.1 (Methods) and FOXA1 or TTC6 expression levels across metastatic tissues (n = 370; Spearman's rank correlation coefficient). The 95% confidence interval is shown. d, Representative ATAC-seq (n = 1) read signal tracks from normal basal epithelial prostate (RWPE1 and PNT2 cells) or prostate cancer cells. Cells are grouped on the basis of expression of FOXA1, and differentially pioneered loci are marked with red boxes. CRISPR sgRNA pairs used for genomic deletion of the labelled elements are shown at the bottom. Distinct FOXA1+ and FOXA1 cell lines serve as biological replicates for ATAC-seq. e, mRNA (qPCR) expression of housekeeping control genes, genes located within the FOXA1 topologically associated domain, and MIPOL1 in VCaP cells treated with CRISPR sgRNA pairs targeting a control site (sgCTRL), FOXMIND or the MIPOL1 UTR regulatory element (see Extended Data Fig. 2c for sgRNA binding sites). Distinct sgRNA pairs cutting at FOXMIND serve as biological replicates. Mean ± s.e.m. is shown (n = 3 technical replicates; two-way ANOVA and Tukey’s test). f, Distribution of tandem duplication and translocation break ends (chimeric junctions or copy-number segment boundaries) focused at the FOXMIND-FOXA1 regulatory domain. g, Outlier expression of genes involved in translocations with the FOXA1 locus. Translocations positioning a gene between FOXMIND and FOXA1 (hijacking) are shown on top (red). Translocations positioning a gene upstream of the FOXA1 promoter (swapping) are shown on the bottom (blue). h, Inferred duplications within the FOXA1 locus on the basis of RNA-seq (tandem break ends) and whole-exome sequencing (copy-gains), zoomed-in at the FOXA1 topologically associating domain.

Source Data

Extended Data Fig. 10 Transcriptional and genomic characteristics of class-3 FOXA1 rearrangements in prostate cancer.

a, Dosage sensitivity of the FOXA1 gene. Expression of FOXA1 (RNA-seq) across mCRPC tumours (n = 370) as a function of gene ploidy (as determined by absolute copy number at the FOXA1 locus (two-way ANOVA)). b, Relative expression of FOXA1 (within the minimally amplified region) to TTC6 (outside the amplified region) in rearranged (n = 50) (duplication or translocation) versus wild-type (n = 320) FOXA1 loci (two-sided t-test). For all box plots, centre shows median, box marks quartiles 1–3 and whiskers span quartiles 1–3 ± 1.5 × IQR. c, Association plot visualizing the relative enrichment of cases with both translocation and duplications within the FOXA1 locus (n = 370). Overabundance of cases with both events is quantified using Pearson residuals. Significance of this association is based on the χ2 test without continuity correction. Inv, inversion; del, deletion. d, FOXA1 locus visualization of linked-read (10X platform) whole-genome sequencing of the MDA-PCA-2b cell line. Alignments on the haplotype-resolved genome are shown in green and purple. Translocation and tandem-duplication calls are indicated in blue and red, respectively. e, Monoallelic expression of FOXA1 cell lines with FOXMIND-ETV1 translocations in MDA-PCA-2b (n = 6 biological replicates) and LNCaP (n = 15 biological replicates). Phasing of FOXA1 SNPs to structural variants is based on linked-read sequencing (Methods). f, Biallelic expression of the RP11-356O9.1 transcript assessed using three distinct SNPs in MDA-PCA-2b cells that contain ETV1 translocation into the FOXA1 locus (n = 7 biological replicates). g, mRNA (qPCR) expression of ETV1 and TTC6 upon sgRNA-mediated disruption of the FOXMIND or the MIPOL1 UTR enhancer in LNCaP cells, which also contain ETV1 translocation into the FOXA1 locus (see Extended Data Fig. 9d for sgRNA binding sites). Distinct sgRNA pairs cutting at FOXMIND serve as biological replicates. Mean ± s.e.m. are shown (n = 3 technical replicates; two-way ANOVA and Tukey’s test).

Source Data

Supplementary information

Supplementary Information

Supplementary Discussion, Supplementary Figure 1 and Supplementary Tables 2, 3 and 5.

Life Sciences Reporting Summary.

Supplementary Table 1

Summary of FOXA1 locus rearrangements form RNA-seq data in primary and metastatic tumors.

Supplementary Table 4

Genomic details of the de-novo assembly of FOXMIND fusions involving known oncogenes.

Source data

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Parolia, A., Cieslik, M., Chu, SC. et al. Distinct structural classes of activating FOXA1 alterations in advanced prostate cancer. Nature 571, 413–418 (2019). https://doi.org/10.1038/s41586-019-1347-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41586-019-1347-4

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer