Cited by 12Prostate Cancer Treatment and ResearchChromatin Remodeling and CancerCancer Genomics and Diagnostics

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Structurally Oriented Classification of FOXA1 Alterations Identifies Prostate Cancers with Opposing Clinical Outcomes and Distinct Molecular and Immunologic Subtypes

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Abstract

Purpose: Around 10% to 15% of prostate cancers harbor recurrent aberrations in the Forkhead Box A1 gene, FOXA1, whereby the alteration type and the effect on the forkhead (FKH) domain affect protein function. We developed a FOXA1 classification system to inform clinical management. Experimental Design: A total of 5,014 prostate cancer samples were examined using whole-exome and -transcriptome sequencing from the Caris Life Sciences database. We denoted class 1 FOXA1 alterations as missense and in-frame insertions/deletions with subclasses oriented with respect to the FKH domain. These were in the first part of the FKH domain [class 1A: amino acids (AA) 168–246], within the Wing2 region of FKH (class 1B: AA 247–269), or outside FKH (class 1C: AA 1–167, 270+). Two hotspot missense mutations at R219 were denoted class 2. Class 3 included predicted truncating mutations with subclasses partitioned based on the FKH domain (class 3A: AA 1–269 and class 3B: AA 270+). Class 4 represented FOXA1 amplifications. Real-world overall survival and therapy outcomes were determined from insurance claims. Results: FOXA1 alterations did not influence survival when considered in aggregate but had distinct prognostic effects when stratified by class. In primary prostate samples, class 1A alterations were associated with overall improved survival (HR, 0.57; P = 0.03); a similar trend was seen in metastatic biopsies with class 1B (HR, 0.84; P = 0.09). Conversely, in primary specimens, class 1C exhibited worse survival upon second-generation androgen receptor signaling inhibitor treatment (HR, 1.93; P < 0.001). Class 2 mutations (R219C/S) were enriched in neuroendocrine prostate cancers and were associated with overall poor survival (HR, 2.05; P < 0.001) and worse outcomes to first-line androgen-deprivation therapies (HR, 2.5; P < 0.001). Class 3A alterations indicated improved survival (HR, 0.70; P = 0.01), whereas class 3B alterations portended poor outcomes (HR, 1.50; P < 0.001). Amplifications (class 4) indicated poor outcomes in metastatic samples (HR, 1.48; P = 0.02). Molecularly, different FOXA1 alteration classes harbored distinct mutational and immunologic features as well as unique transcriptional programs. Finally, relative to European Americans, African Americans had increased class 1C alterations, whereas Asian/Pacific Islander patients had increased class 1B alterations. Conclusions: FOXA1 alterations should not be interpreted in aggregate, as different classes are associated with divergent molecular features and clinical outcomes. Our revised classification schema facilitates clinical decision-making for patients with prostate cancer and uncovers important racial differences.

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Research works printed but not linked: 44

  1. Sung, 2021, Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries, CA Cancer J Clin, 71, 209, 10.3322/caac.21660 · DOI · Paper page
  2. Dai, 2017, Androgen signaling in prostate cancer, Cold Spring Harb Perspect Med, 7, a030452, 10.1101/cshperspect.a030452 · DOI
  3. Pomerantz, 2015, The androgen receptor cistrome is extensively reprogrammed in human prostate tumorigenesis, Nat Genet, 47, 1346, 10.1038/ng.3419 · DOI · Paper page
  4. Jozwik, 2012, Pioneer factors in hormone-dependent cancers, Nat Rev Cancer, 12, 381, 10.1038/nrc3263 · DOI
  5. Teng, 2021, Pioneer of prostate cancer: past, present and the future of FOXA1, Protein Cell, 12, 29, 10.1007/s13238-020-00786-8 · DOI
  6. Baca, 2021, Reprogramming of the FOXA1 cistrome in treatment-emergent neuroendocrine prostate cancer, Nat Commun, 12, 1979, 10.1038/s41467-021-22139-7 · DOI
  7. Pomerantz, 2020, Prostate cancer reactivates developmental epigenomic programs during metastatic progression, Nat Genet, 52, 790, 10.1038/s41588-020-0664-8 · DOI
  8. Adams, 2019, FOXA1 mutations alter pioneering activity, differentiation and prostate cancer phenotypes, Nature, 571, 408, 10.1038/s41586-019-1318-9 · DOI
  9. Imamura, 2012, FOXA1 promotes tumor progression in prostate cancer via the insulin-like growth factor binding protein 3 pathway, PLoS One, 7, e42456, 10.1371/journal.pone.0042456 · DOI
  10. Sahu, 2011, Dual role of FoxA1 in androgen receptor binding to chromatin, androgen signalling and prostate cancer, EMBO J, 30, 3962, 10.1038/emboj.2011.328 · DOI
  11. Abida, 2019, Genomic correlates of clinical outcome in advanced prostate cancer, Proc Natl Acad Sci U S A, 116, 11428, 10.1073/pnas.1902651116 · DOI · Paper page
  12. Robinson, 2015, Integrative clinical genomics of advanced prostate cancer, Cell, 162, 454, 10.1016/j.cell.2015.06.053 · DOI
  13. Barbieri, 2012, Exome sequencing identifies recurrent SPOP, FOXA1 and MED12 mutations in prostate cancer, Nat Genet, 44, 685, 10.1038/ng.2279 · DOI
  14. Cirillo, 2007, Specific interactions of the wing domains of FOXA1 transcription factor with DNA, J Mol Biol, 366, 720, 10.1016/j.jmb.2006.11.087 · DOI
  15. Dai, 2021, Toward a mechanistic understanding of DNA binding by forkhead transcription factors and its perturbation by pathogenic mutations, Nucleic Acids Res, 49, 10235, 10.1093/nar/gkab807 · DOI
  16. Avila, 2019, Next-generation sequencing for the general cancer patient, Clin Adv Hematol Oncol, 17, 447
  17. Abraham, 2021, Clinical validation of a machine-learning-derived signature predictive of outcomes from first-line oxaliplatin-based chemotherapy in advanced colorectal cancer, Clin Cancer Res, 27, 1174, 10.1158/1078-0432.CCR-20-3286 · DOI
  18. Hwang, 2023, Metastatic prostate cancers with BRCA2 versus ATM mutations exhibit divergent molecular features and clinical outcomes, Clin Cancer Res, 29, 2702, 10.1158/1078-0432.CCR-22-3394 · DOI
  19. Epstein, 2014, Proposed morphologic classification of prostate cancer with neuroendocrine differentiation, Am J Surg Pathol, 38, 756, 10.1097/PAS.0000000000000208 · DOI
  20. Silk, 2019, MTR-Viewer: identifying regions within genes under purifying selection, Nucleic Acids Res, 47, W121, 10.1093/nar/gkz457 · DOI
  21. Benjamini, 2001, Controlling the false discovery rate in behavior genetics research, Behav Brain Res, 125, 279, 10.1016/S0166-4328(01)00297-2 · DOI · Paper page
  22. Choi, 2022, FOXL2 and FOXA1 cooperatively assemble on the TP53 promoter in alternative dimer configurations, Nucleic Acids Res, 50, 8929, 10.1093/nar/gkac673 · DOI
  23. Newman, 2020, The crystal structure of human forkhead box N1 in complex with DNA reveals the structural basis for forkhead box family specificity, J Biol Chem, 295, 2948, 10.1074/jbc.RA119.010365 · DOI
  24. Schymkowitz, 2005, The FoldX web server: an online force field, Nucleic Acids Res, 33, W382, 10.1093/nar/gki387 · DOI · Paper page
  25. UniProt Consortium, 2023, UniProt: the universal protein knowledgebase in 2023, Nucleic Acids Res, 51, D523, 10.1093/nar/gkac1052 · DOI · Paper page
  26. Ayers, 2017, IFN-gamma-related mRNA profile predicts clinical response to PD-1 blockade, J Clin Invest, 127, 2930, 10.1172/JCI91190 · DOI · Paper page
  27. Bao, 2020, Molecular correlates and therapeutic targets in T cell-inflamed versus non-T cell-inflamed tumors across cancer types, Genome Med, 12, 90, 10.1186/s13073-020-00787-6 · DOI
  28. Beltran, 2016, Divergent clonal evolution of castration-resistant neuroendocrine prostate cancer, Nat Med, 22, 298, 10.1038/nm.4045 · DOI
  29. Finotello, 2019, Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data, Genome Med, 11, 34, 10.1186/s13073-019-0638-6 · DOI
  30. Abida, 2017, Prospective genomic profiling of prostate cancer across disease states reveals germline and somatic alterations that may affect clinical decision making, JCO Precis Oncol, 2017, PO.17.00029
  31. Antonarakis, 2019, Clinical features and therapeutic outcomes in men with advanced prostate cancer and DNA mismatch repair gene mutations, Eur Urol, 75, 378, 10.1016/j.eururo.2018.10.009 · DOI
  32. Anestis, 2020, Androgen receptor in breast cancer-clinical and preclinical research insights, Molecules, 25, 358, 10.3390/molecules25020358 · DOI
  33. Li, 2017, Androgen receptor signaling in bladder cancer, Cancers (Basel), 9, 20, 10.3390/cancers9020020 · DOI
  34. Xu, 2019, Androgen receptor immunohistochemistry in salivary duct carcinoma: a retrospective study of 188 cases focusing on tumoral heterogeneity and temporal concordance, Hum Pathol, 93, 30, 10.1016/j.humpath.2019.08.007 · DOI
  35. Li, 2020, A genomic and epigenomic atlas of prostate cancer in Asian populations, Nature, 580, 93, 10.1038/s41586-020-2135-x · DOI
  36. Coughlin, 2020, A review of social determinants of prostate cancer risk, stage, and survival, Prostate Int, 8, 49, 10.1016/j.prnil.2019.08.001 · DOI
  37. Kelly, 2023, Social determinants of health: does socioeconomic status affect access to staging imaging for men with prostate cancer, Prostate Cancer Prostatic Dis, 26, 429, 10.1038/s41391-022-00508-7 · DOI
  38. Key, 1997, A case-control study of diet and prostate cancer, Br J Cancer, 76, 678, 10.1038/bjc.1997.445 · DOI
  39. Matsushita, 2020, Influence of diet and nutrition on prostate cancer, Int J Mol Sci, 21, 1447, 10.3390/ijms21041447 · DOI
  40. Antonarakis, 2023, Pembrolizumab plus olaparib for patients with previously treated and biomarker-unselected metastatic castration-resistant prostate cancer: the randomized, open-label, phase III KEYLYNK-010 trial, J Clin Oncol, 41, 3839, 10.1200/JCO.23.00233 · DOI
  41. Baugh, 2018, Why are there hotspot mutations in the TP53 gene in human cancers?, Cell Death Differ, 25, 154, 10.1038/cdd.2017.180 · DOI
  42. Olivier, 2010, TP53 mutations in human cancers: origins, consequences, and clinical use, Cold Spring Harb Perspect Biol, 2, a001008, 10.1101/cshperspect.a001008 · DOI · Paper page
  43. Alvarado-Ortiz, 2020, Mutant p53 gain-of-function: role in cancer development, progression, and therapeutic approaches, Front Cell Dev Biol, 8, 607670, 10.3389/fcell.2020.607670 · DOI
  44. Kennedy, 2022, Mutant p53: it’s not all one and the same, Cell Death Differ, 29, 983, 10.1038/s41418-022-00989-y · DOI

Metadata

Authors
Hwang, J., Likasitwatanakul, P., Deshmukh, S. K., Wu, S., Kwon, J. J., Toye, E., Moline, D., Evans, M. G., Elliott, A., Passow, R., Luo, C., John, E., Gandhi, N., McKay, R. R., Heath, E. I., Nabhan, C., Reizine, N., Orme, J. J., Domingo Domenech, J. M., Sartor, O., Baca, S. C., Dehm, S. M., & Antonarakis, E. S.
Affiliations
  • University of Minnesota (US)
  • Caris Life Sciences (United States) (US)
  • Broad Institute (US)
  • University of California San Diego (US)
  • Wayne State University (US)
  • University of Illinois Chicago (US)
  • Mayo Clinic (US)
  • 11Mayo Clinic, Rochester, Minnesota.
  • Dana-Farber Cancer Institute (US)
Corresponding author
Antonarakis, Emmanuel S.
Venue
Clinical Cancer Research
Published
2025-01-02
Volume
31
Issue
5
Pages
936-948
ISSN
  • 1078-0432 (ISSN-L)
  • 1557-3265
OpenAlex
W4405990508
Cited by
12
References
4
Citations by year
2026: 3 · 2025: 9
FWCI
7.83
Type
journal article
Language
en
Open access
Locations
  • Clinical Cancer Research (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • Masonic Cancer Center, University of Minnesota (CRTI TWG)
  • Division of Cancer Prevention, National Cancer Institute (1R37CA288972-01, P30 CA077598, 1K99CA270290)
  • U.S. Department of Defense (W81XWH-22-2-0025, W81XWH-21-1-0358)
  • Damon Runyon Cancer Research Foundation (Innovation in Cancer Informatics)
  • Prostate Cancer Foundation (Young Investigator Award)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Prostate Cancer Treatment and Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
Keywords
prostate cancer, forkhead domain, missense mutations, truncating mutations, neuroendocrine prostate cancer, androgen receptor pathway inhibitors, androgen deprivation therapy, overall survival, prognostic stratification, molecular subtypes, metastatic prostate cancer
MeSH terms
Exome Sequencing, Humans, Male, Mutation, Prognosis, Prostatic Neoplasms, Biomarkers, Tumor, Gene Expression Regulation, Neoplastic, Hepatocyte Nuclear Factor 3-alpha

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