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Owen KL, Gearing LJ, Zanker DJ, Brockwell NK, Khoo WH, Roden DL, Cmero M, Mangiola S, Hong MK, Spurling AJ, McDonald M, Chan C, Pasam A, Lyons RJ, Duivenvoorden HM, Ryan A, Butler LM, Mariadason JM, Giang Phan T, Hayes VM, Sandhu S, Swarbrick A, Corcoran NM, Hertzog PJ, Croucher PI, Hovens C, Parker BS. Prostate cancer cell-intrinsic interferon signaling regulates dormancy and metastatic outgrowth in bone. EMBO Rep 2020; 21:e50162. [PMID: 32314873 PMCID: PMC7271653 DOI: 10.15252/embr.202050162] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Revised: 03/15/2020] [Accepted: 03/20/2020] [Indexed: 12/11/2022] Open
Abstract
The latency associated with bone metastasis emergence in castrate-resistant prostate cancer is attributed to dormancy, a state in which cancer cells persist prior to overt lesion formation. Using single-cell transcriptomics and ex vivo profiling, we have uncovered the critical role of tumor-intrinsic immune signaling in the retention of cancer cell dormancy. We demonstrate that loss of tumor-intrinsic type I IFN occurs in proliferating prostate cancer cells in bone. This loss suppresses tumor immunogenicity and therapeutic response and promotes bone cell activation to drive cancer progression. Restoration of tumor-intrinsic IFN signaling by HDAC inhibition increased tumor cell visibility, promoted long-term antitumor immunity, and blocked cancer growth in bone. Key findings were validated in patients, including loss of tumor-intrinsic IFN signaling and immunogenicity in bone metastases compared to primary tumors. Data herein provide a rationale as to why current immunotherapeutics fail in bone-metastatic prostate cancer, and provide a new therapeutic strategy to overcome the inefficacy of immune-based therapies in solid cancers.
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A Prospective Correlation of Tissue Histopathology With Nucleic Acid Yield in Metastatic Castration-Resistant Prostate Cancer Biopsy Specimens. Mayo Clin Proc Innov Qual Outcomes 2019; 3:14-22. [PMID: 30899904 PMCID: PMC6410334 DOI: 10.1016/j.mayocpiqo.2018.12.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Objective To determine histopathologic, exome, and transcriptome nucleic acid material yield from prospectively collected metastatic tissue biopsy specimens in patients with metastatic castration-resistant prostate cancer (mCRPC). Patients and Methods Patients with mCRPC initiating abiraterone acetate therapy underwent 2 serial metastatic site core needle biopsies after study activation on May 17, 2013. Multiple cores were obtained, and from each core, 1- to 2-mm segments were separated and formalin fixed for histopathologic examination. Tumor purity was determined for DNA and RNA from the rest of the biopsy specimen. RNA quality was assessed by calculation of an RNA integrity number and a DV200 score. Results A total of 89 patients underwent 172 uniformly processed core needle biopsies (89 on visit 1 and 83 on visit 2) between May 30, 2013, and September 10, 2015. Metastatic sites biopsied included bone (131), lymph nodes (31), liver (5), lung (3), and pelvic soft tissues (2). Of the 172 biopsy specimens, 85 (49%) had at least one of the multiple cores positive for tumor on histopathologic examination (53 of 88 [60%] from visit 1 and 32 of 83 [39%] from visit 2; P=.006). Metastatic carcinoma was observed in 50 of 130 bone lesion specimens (38%), compared to 35 of 41 nonbone specimens (85%) (P<.001). More than 10% tumoral DNA purity was observed in 89% and 80% of visit 1 and visit 2 biopsy specimens, respectively. Similarly, more than 10% tumor RNA purity was observed in 79% of visit 1 vs 59% for visit 2 (P=.008). In all, 134 of 172 procedures (78%) yielded tumor material either by histopathologic or nucleic acid purity analysis. Conclusion This study found that biopsy specimens from mCRPC sites yield adequate histopathologic, exome, and transcriptome material in most, but not all, cases. This finding has relevance for future genome sequencing studies on the introduction of targeted therapeutic agents. Trial Registration clinicaltrials.gov Identifier: 01953640.
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Lundon DJ, Boland A, Prencipe M, Hurley G, O'Neill A, Kay E, Aherne ST, Doolan P, Madden SF, Clynes M, Morrissey C, Fitzpatrick JM, Watson RW. The prognostic utility of the transcription factor SRF in docetaxel-resistant prostate cancer: in-vitro discovery and in-vivo validation. BMC Cancer 2017; 17:163. [PMID: 28249598 PMCID: PMC5333466 DOI: 10.1186/s12885-017-3100-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2016] [Accepted: 02/01/2017] [Indexed: 02/06/2023] Open
Abstract
Background Docetaxel based therapy is one of the first line chemotherapeutic agents for the treatment of metastatic castrate-resistant prostate cancer. However, one of the major obstacles in the treatment of these patients is docetaxel-resistance. Defining the mechanisms of resistance so as to inform subsequent treatment options and combinations represents a challenge for clinicians and scientists. Previous work by our group has shown complex changes in pro and anti-apoptotic proteins in the development of resistance to docetaxel. Targeting these changes individually does not significantly impact on the resistant phenotype but understanding the central signalling pathways and transcription factors (TFs) which control these could represent a more appropriate therapeutic targeting approach. Methods Using a number of docetaxel-resistant sublines of PC-3 cells, we have undertaken a transcriptomic analysis by expression microarray using the Affymetrix Human Gene 1.0 ST Array and in conjunction with bioinformatic analyses undertook to predict dysregulated TFs in docetaxel resistant prostate cancer. The clinical significance of this prediction was ascertained by performing immunohistochemical (IHC) analysis of an identified TF (SRF) in the metastatic sites from men who died of advanced CRPC. Investigation of the functional role of SRF was examined by manipulating SRF using SiRNA in a docetaxel-resistant PC-3 cell line model. Results The transcription factors identified include serum response factor (SRF), nuclear factor kappa-B (NFκB), heat shock factor protein 1 (HSF1), testicular receptor 2 & 4 (TR2 &4), vitamin-D and retinoid x receptor (VDR-RXR) and oestrogen-receptor 1 (ESR1), which are predicted to be responsible for the differential gene expression observed in docetaxel-resistance. IHC analysis to quantify nuclear expression of the identified TF SRF correlates with both survival from date of bone metastasis (p = 0.003), survival from androgen independence (p = 0.00002), and overall survival from prostate cancer (p = 0.0044). Functional knockdown of SRF by siRNA demonstrated a reversal of apoptotic resistance to docetaxel treatment in the docetaxel-resistant PC-3 cell line model. Conclusions Our results suggest that SRF could aid in treatment stratification of prostate cancer, and may also represent a therapeutic target in the treatment of men afflicted with advanced prostate cancer. Electronic supplementary material The online version of this article (doi:10.1186/s12885-017-3100-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- D J Lundon
- UCD School of Medicine, Conway Institute of Biomedical and Biomolecular Sciences, University College Dublin, Belfield, Dublin, Dublin 4, Ireland.
| | - A Boland
- UCD School of Mathematical Sciences and Insight, University College Dublin, Belfield, Dublin, Dublin 4, Ireland
| | - M Prencipe
- UCD School of Medicine, Conway Institute of Biomedical and Biomolecular Sciences, University College Dublin, Belfield, Dublin, Dublin 4, Ireland
| | - G Hurley
- UCD School of Biomolecular and Biomedical Science, University College Dublin, Belfield, Dublin, Dublin 4, Ireland
| | - A O'Neill
- UCD School of Medicine, Conway Institute of Biomedical and Biomolecular Sciences, University College Dublin, Belfield, Dublin, Dublin 4, Ireland
| | - E Kay
- Department of Pathology, Beaumont Hospital & Royal College of Surgeons in Ireland, Dublin, Ireland
| | - S T Aherne
- National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland Non-US/Non-Canadian, Ireland
| | - P Doolan
- National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland Non-US/Non-Canadian, Ireland
| | - S F Madden
- UCD School of Biomolecular and Biomedical Science, University College Dublin, Belfield, Dublin, Dublin 4, Ireland
| | - M Clynes
- National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland Non-US/Non-Canadian, Ireland
| | - C Morrissey
- Department of Urology, University of Washington, Seattle, WA, USA
| | - J M Fitzpatrick
- UCD School of Medicine, Conway Institute of Biomedical and Biomolecular Sciences, University College Dublin, Belfield, Dublin, Dublin 4, Ireland
| | - R W Watson
- UCD School of Medicine, Conway Institute of Biomedical and Biomolecular Sciences, University College Dublin, Belfield, Dublin, Dublin 4, Ireland
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Towards Best Practice in Establishing Patient-Derived Xenografts. PATIENT-DERIVED XENOGRAFT MODELS OF HUMAN CANCER 2017. [DOI: 10.1007/978-3-319-55825-7_2] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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5
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Sapre N, Macintyre G, Clarkson M, Naeem H, Cmero M, Kowalczyk A, Anderson PD, Costello AJ, Corcoran NM, Hovens CM. A urinary microRNA signature can predict the presence of bladder urothelial carcinoma in patients undergoing surveillance. Br J Cancer 2016; 114:454-62. [PMID: 26812572 PMCID: PMC4815774 DOI: 10.1038/bjc.2015.472] [Citation(s) in RCA: 64] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2015] [Revised: 11/28/2015] [Accepted: 12/03/2015] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND The objective of this study was to determine whether microRNA (miRNA) profiling of urine could identify the presence of urothelial carcinoma of the bladder (UCB) and to compare its performance characteristics to that of cystoscopy. METHODS In the discovery cohort we screened 81 patients, which included 21 benign controls, 30 non-recurrers and 30 patients with active cancer (recurrers), using a panel of 12 miRNAs. Data analysis was performed using a machine learning approach of a Support Vector Machine classifier with a Student's t-test feature selection procedure. This was trained using a three-fold cross validation approach and performance was measured using the area under the receiver operator characteristic curve (AUC). The miRNA signature was validated in an independent cohort of a further 50 patients. RESULTS The best predictor to distinguish patients with UCB from non-recurrers was achieved using a combination of six miRNAs (AUC=0.85). This validated in an independent cohort (AUC=0.74) and detected UCB with a high sensitivity (88%) and sufficient specificity (48%) with all significant cancers identified. The performance of the classifier was best in detecting clinically significant disease such as presence of T1 Stage disease (AUC=0.92) and high-volume disease (AUC=0.81). Cystoscopy rates in the validation cohort would have been reduced by 30%. CONCLUSIONS Urinary profiling using this panel of miRNAs shows promise for detection of tumour recurrence in the surveillance of UCB. Such a panel may be useful in reducing the morbidity and costs associated with cystoscopic surveillance, and now merits prospective evaluation.
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Affiliation(s)
- Nikhil Sapre
- Department of Surgery, Division of Urology, Royal Melbourne Hospital, The University of Melbourne, Parkville, Melbourne, Victoria, Australia
| | - Geoff Macintyre
- NICTA Victoria Research Laboratory, Department of Electronic Engineering, University of Melbourne, Melbourne, Victoria, Australia.,Department of Computing and Information Systems, University of Melbourne, Melbourne, Victoria, Australia.,Centre for Neural Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - Michael Clarkson
- Department of Surgery, Division of Urology, Royal Melbourne Hospital, The University of Melbourne, Parkville, Melbourne, Victoria, Australia
| | - Haroon Naeem
- NICTA Victoria Research Laboratory, Department of Electronic Engineering, University of Melbourne, Melbourne, Victoria, Australia.,Department of Computing and Information Systems, University of Melbourne, Melbourne, Victoria, Australia.,Centre for Neural Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - Marek Cmero
- NICTA Victoria Research Laboratory, Department of Electronic Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - Adam Kowalczyk
- NICTA Victoria Research Laboratory, Department of Electronic Engineering, University of Melbourne, Melbourne, Victoria, Australia.,Department of Computing and Information Systems, University of Melbourne, Melbourne, Victoria, Australia.,Centre for Neural Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - Paul D Anderson
- Department of Surgery, Division of Urology, Royal Melbourne Hospital, The University of Melbourne, Parkville, Melbourne, Victoria, Australia
| | - Anthony J Costello
- Department of Surgery, Division of Urology, Royal Melbourne Hospital, The University of Melbourne, Parkville, Melbourne, Victoria, Australia
| | - Niall M Corcoran
- Department of Surgery, Division of Urology, Royal Melbourne Hospital, The University of Melbourne, Parkville, Melbourne, Victoria, Australia
| | - Christopher M Hovens
- Department of Surgery, Division of Urology, Royal Melbourne Hospital, The University of Melbourne, Parkville, Melbourne, Victoria, Australia
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Hong MK, Macintyre G, Wedge DC, Van Loo P, Patel K, Lunke S, Alexandrov LB, Sloggett C, Cmero M, Marass F, Tsui D, Mangiola S, Lonie A, Naeem H, Sapre N, Phal PM, Kurganovs N, Chin X, Kerger M, Warren AY, Neal D, Gnanapragasam V, Rosenfeld N, Pedersen JS, Ryan A, Haviv I, Costello AJ, Corcoran NM, Hovens CM. Tracking the origins and drivers of subclonal metastatic expansion in prostate cancer. Nat Commun 2015; 6:6605. [PMID: 25827447 PMCID: PMC4396364 DOI: 10.1038/ncomms7605] [Citation(s) in RCA: 272] [Impact Index Per Article: 30.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2014] [Accepted: 02/11/2015] [Indexed: 12/29/2022] Open
Abstract
Tumour heterogeneity in primary prostate cancer is a well-established phenomenon. However, how the subclonal diversity of tumours changes during metastasis and progression to lethality is poorly understood. Here we reveal the precise direction of metastatic spread across four lethal prostate cancer patients using whole-genome and ultra-deep targeted sequencing of longitudinally collected primary and metastatic tumours. We find one case of metastatic spread to the surgical bed causing local recurrence, and another case of cross-metastatic site seeding combining with dynamic remoulding of subclonal mixtures in response to therapy. By ultra-deep sequencing end-stage blood, we detect both metastatic and primary tumour clones, even years after removal of the prostate. Analysis of mutations associated with metastasis reveals an enrichment of TP53 mutations, and additional sequencing of metastases from 19 patients demonstrates that acquisition of TP53 mutations is linked with the expansion of subclones with metastatic potential which we can detect in the blood.
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Affiliation(s)
- Matthew K.H. Hong
- Department of Surgery, Division of Urology, Royal Melbourne Hospital and University of Melbourne, Parkville 3050, Victoria, Australia
- The Epworth Prostate Centre, Epworth Hospital, Richmond 3121, Victoria, Australia
| | - Geoff Macintyre
- Centre for Neural Engineering, Department of Computing and Information Systems, University of Melbourne, Parkville, Victoria 3010, Australia
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK
- Diagnostic Genomics, NICTA, Victoria Research Laboratory, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - David C. Wedge
- Cancer Genome Project, Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK
| | - Peter Van Loo
- Cancer Genome Project, Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK
- Department of Human Genetics, KU Leuven, Herestraat 49 Box 602, B-3000 Leuven, Belgium
- Cancer Research UK London Research Institute, London WC2A 3LY, UK
| | - Keval Patel
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK
- Academic Urology Group, Addenbrookes Hospital, Cambridge University, Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, UK
| | - Sebastian Lunke
- Centre for Translational Pathology, University of Melbourne, Parkville 3050, Victoria, Australia
| | - Ludmil B. Alexandrov
- Cancer Genome Project, Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK
- Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, USA
| | - Clare Sloggett
- Victorian Life Sciences Computation Initiative, The University of Melbourne, Parkville 3050, Victoria, Australia
| | - Marek Cmero
- Department of Surgery, Division of Urology, Royal Melbourne Hospital and University of Melbourne, Parkville 3050, Victoria, Australia
- The Epworth Prostate Centre, Epworth Hospital, Richmond 3121, Victoria, Australia
- Centre for Neural Engineering, Department of Computing and Information Systems, University of Melbourne, Parkville, Victoria 3010, Australia
- Diagnostic Genomics, NICTA, Victoria Research Laboratory, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Francesco Marass
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK
| | - Dana Tsui
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK
| | - Stefano Mangiola
- Centre for Neural Engineering, Department of Computing and Information Systems, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Andrew Lonie
- Victorian Life Sciences Computation Initiative, The University of Melbourne, Parkville 3050, Victoria, Australia
| | - Haroon Naeem
- Centre for Neural Engineering, Department of Computing and Information Systems, University of Melbourne, Parkville, Victoria 3010, Australia
- Diagnostic Genomics, NICTA, Victoria Research Laboratory, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Nikhil Sapre
- Department of Surgery, Division of Urology, Royal Melbourne Hospital and University of Melbourne, Parkville 3050, Victoria, Australia
- The Epworth Prostate Centre, Epworth Hospital, Richmond 3121, Victoria, Australia
| | - Pramit M. Phal
- Department of Radiology, Royal Melbourne Hospital, Parkville 3050, Victoria, Australia
| | - Natalie Kurganovs
- Department of Surgery, Division of Urology, Royal Melbourne Hospital and University of Melbourne, Parkville 3050, Victoria, Australia
- The Epworth Prostate Centre, Epworth Hospital, Richmond 3121, Victoria, Australia
| | - Xiaowen Chin
- Department of Surgery, Division of Urology, Royal Melbourne Hospital and University of Melbourne, Parkville 3050, Victoria, Australia
- The Epworth Prostate Centre, Epworth Hospital, Richmond 3121, Victoria, Australia
| | - Michael Kerger
- Department of Surgery, Division of Urology, Royal Melbourne Hospital and University of Melbourne, Parkville 3050, Victoria, Australia
- The Epworth Prostate Centre, Epworth Hospital, Richmond 3121, Victoria, Australia
| | - Anne Y. Warren
- Department of Histopathology, University Cambridge Hospitals, Addenbrookes Hospital, Hills Road, Cambridge CB2 0QQ, UK
| | - David Neal
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK
- Academic Urology Group, Addenbrookes Hospital, Cambridge University, Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, UK
| | - Vincent Gnanapragasam
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK
- Academic Urology Group, Addenbrookes Hospital, Cambridge University, Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, UK
| | - Nitzan Rosenfeld
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK
| | - John S. Pedersen
- TissuPath Specialist Pathology, Mount Waverley 3149, Victoria, Australia
- Monash University Faculty of Medicine, Clayton 3168, Victoria, Australia
| | - Andrew Ryan
- TissuPath Specialist Pathology, Mount Waverley 3149, Victoria, Australia
| | - Izhak Haviv
- Bar-Ilan University Medical School, Safad 1311502, Israel
| | - Anthony J. Costello
- Department of Surgery, Division of Urology, Royal Melbourne Hospital and University of Melbourne, Parkville 3050, Victoria, Australia
- The Epworth Prostate Centre, Epworth Hospital, Richmond 3121, Victoria, Australia
| | - Niall M. Corcoran
- Department of Surgery, Division of Urology, Royal Melbourne Hospital and University of Melbourne, Parkville 3050, Victoria, Australia
- The Epworth Prostate Centre, Epworth Hospital, Richmond 3121, Victoria, Australia
| | - Christopher M. Hovens
- Department of Surgery, Division of Urology, Royal Melbourne Hospital and University of Melbourne, Parkville 3050, Victoria, Australia
- The Epworth Prostate Centre, Epworth Hospital, Richmond 3121, Victoria, Australia
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Reimers MS, Engels CC, Kuppen PJK, van de Velde CJH, Liefers GJ. How does genome sequencing impact surgery? Nat Rev Clin Oncol 2014; 11:610-8. [PMID: 24958181 DOI: 10.1038/nrclinonc.2014.101] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Cancer is a leading cause of death worldwide. Great efforts are dedicated to the development of prognostic and predictive biomarkers to improve diagnosis and achieve optimal treatment selection, thereby, introducing precision medicine in the multimodality treatment of cancer. Genomic aberrations are the basis of tumour development, representing excellent candidates for the development of promising clinical biomarkers. Over the past decade, single-gene mutations and genomic profiling have been increasingly used in multidisciplinary consultations for risk-assessment and treatment planning for patients with cancer. We discuss the impact of such genetic-based information on surgical decision-making. Single-gene mutations have already influenced surgical decision-making in breast, colorectal and thyroid cancer. However, the direct impact of genomic profiling on surgical care has not yet been fully established. We discuss the direct and indirect influences of genomic profiling on surgery, and analyse the limitations and unresolved issues of a genotypic-approach to the surgical management of cancer.
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Affiliation(s)
- Marlies S Reimers
- Department of Surgery, Leiden University Medical Centre, PO Box 9600, 2300 RC Leiden, Netherlands
| | - Charla C Engels
- Department of Surgery, Leiden University Medical Centre, PO Box 9600, 2300 RC Leiden, Netherlands
| | - Peter J K Kuppen
- Department of Surgery, Leiden University Medical Centre, PO Box 9600, 2300 RC Leiden, Netherlands
| | | | - Gerrit J Liefers
- Department of Surgery, Leiden University Medical Centre, PO Box 9600, 2300 RC Leiden, Netherlands
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