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Crumbaker M, Goldstein LD, Murray DH, Tao J, Pathmanandavel S, Boulter N, Ratnayake L, Joshua AM, Kummerfeld S, Emmett L. Circulating Tumour DNA Biomarkers Associated with Outcomes in Metastatic Prostate Cancer Treated with Lutetium-177-PSMA-617. EUR UROL SUPPL 2023; 57:30-36. [PMID: 38020530 PMCID: PMC10658415 DOI: 10.1016/j.euros.2023.08.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/09/2023] [Indexed: 12/01/2023] Open
Abstract
Background Lutetium-177-prostate-specific membrane antigen- 617 (Lu-PSMA) is an effective therapy for metastatic castration-resistant prostate cancer (mCRPC). However, treatment responses are heterogeneous despite stringent positron emission tomography (PET)-based imaging selection criteria. Molecularly based biomarkers have potential to refine patient selection and optimise outcomes. Objective To identify circulating tumour DNA (ctDNA) features associated with treatment outcomes for men treated with Lu-PSMA. Design setting and participants ctDNA from men treated with Lu-PSMA in combination with idronoxil for progressive mCRPC were analysed using an 85-gene customised sequencing assay. ctDNA fractions, molecular profiles, and the presence of alterations in aggressive-variant prostate cancer (AVPC) genes were analysed at baseline, cycle 3 and at disease progression. Intervention Men received Lu-PSMA with idronoxil every 6 wk for up to six cycles. Outcome measurements and statistical analysis Baseline and exit PSMA and fluorodeoxyglucose PET/computed tomography (CT) imaging was conducted at baseline and study exit. Single-photon emission CT (SPECT) scans were performed 24 h after Lu-PSMA. Blood samples were collected at baseline,cycle 3 and at disease progression. Cox proportional-hazards models were used to assess associations and derive hazard ratios (HRs) and confidence intervals (CIs) for associations between molecular factors, imaging features, and clinical outcomes. Results and limitations Sixty samples from 32 men were sequenced (32 at baseline, 24 at cycle 3, four from patients with disease progression); two samples (baseline, on-treatment) from one individual were excluded from analysis owing to poor quality of the baseline sequencing data. Alterations in AVPC genes were associated with shorter prostate-specific antigen (PSA) progression-free survival (PFS) and overall survival (OS) in univariate (HR 3.4, 95% CI 1.5-7.7; p = 0.0036; and HR 3.3, 95% CI 1.4-7.7; p = 0.0063, respectively) and multivariate analyses (HR 4.8, 95% CI 1.8-13; p = 0.0014; and HR 4.1, 95% CI 1.6-11; p = 0.004). Conclusions ctDNA alterations in AVPC genes were associated with shorter PSA PFS and OS among men treated with Lu-PSMA and intermittent idronoxil. These candidate molecular biomarkers warrant further study to determine whether they have predictive value and potential to guide synergistic combination strategies to enhance outcomes for men treated with Lu-PSMA for mCRPC. Patient summary Certain DNA/gene changes detected in the blood of men with advanced prostate cancer were associated with shorter benefit from lutetium PSMA, a targeted radioactive therapy. This information may be useful in determining which men may benefit most from this treatment, but additional research is needed.
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Affiliation(s)
- Megan Crumbaker
- The Kinghorn Cancer Centre, St. Vincent’s Hospital Sydney, Darlinghurst, Australia
- St. Vincent’s Clinical School, University of New South Wales, Kensington, Australia
- Garvan Institute of Medical Research, Darlinghurst, Australia
- Department of Theranostics and Nuclear Medicine, St. Vincent’s Hospital Sydney, Darlinghurst, Australia
| | - Leonard D. Goldstein
- St. Vincent’s Clinical School, University of New South Wales, Kensington, Australia
- Garvan Institute of Medical Research, Darlinghurst, Australia
| | - David H. Murray
- Garvan Institute of Medical Research, Darlinghurst, Australia
| | - Jiang Tao
- Garvan Institute of Medical Research, Darlinghurst, Australia
| | - Sarennya Pathmanandavel
- St. Vincent’s Clinical School, University of New South Wales, Kensington, Australia
- Department of Theranostics and Nuclear Medicine, St. Vincent’s Hospital Sydney, Darlinghurst, Australia
| | - Nicky Boulter
- Garvan Institute of Medical Research, Darlinghurst, Australia
| | - Lalith Ratnayake
- The Kinghorn Cancer Centre, St. Vincent’s Hospital Sydney, Darlinghurst, Australia
| | - Anthony M. Joshua
- The Kinghorn Cancer Centre, St. Vincent’s Hospital Sydney, Darlinghurst, Australia
- St. Vincent’s Clinical School, University of New South Wales, Kensington, Australia
- Garvan Institute of Medical Research, Darlinghurst, Australia
| | - Sarah Kummerfeld
- St. Vincent’s Clinical School, University of New South Wales, Kensington, Australia
- Garvan Institute of Medical Research, Darlinghurst, Australia
| | - Louise Emmett
- St. Vincent’s Clinical School, University of New South Wales, Kensington, Australia
- Garvan Institute of Medical Research, Darlinghurst, Australia
- Department of Theranostics and Nuclear Medicine, St. Vincent’s Hospital Sydney, Darlinghurst, Australia
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Nevedomskaya E, Sugawara T, Baumgart SJ, Lesche R, Hahne H, Mumberg D, Haendler B. Comparative Proteomic and Transcriptomic Analysis of the Impact of Androgen Stimulation and Darolutamide Inhibition. Cancers (Basel) 2022; 15. [PMID: 36611998 DOI: 10.3390/cancers15010002] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 11/22/2022] [Accepted: 12/14/2022] [Indexed: 12/24/2022] Open
Abstract
Several inhibitors of androgen receptor (AR) function are approved for prostate cancer treatment, and their impact on gene transcription has been described. However, the ensuing effects at the protein level are far less well understood. We focused on the AR signaling inhibitor darolutamide and confirmed its strong AR binding and antagonistic activity using the high throughput cellular thermal shift assay (CETSA HT). Then, we generated comprehensive, quantitative proteomic data from the androgen-sensitive prostate cancer cell line VCaP and compared them to transcriptomic data. Following treatment with the synthetic androgen R1881 and darolutamide, global mass spectrometry-based proteomics and label-free quantification were performed. We found a generally good agreement between proteomic and transcriptomic data upon androgen stimulation and darolutamide inhibition. Similar effects were found both for the detected expressed genes and their protein products as well as for the corresponding biological programs. However, in a few instances there was a discrepancy in the magnitude of changes induced on gene expression levels compared to the corresponding protein levels, indicating post-transcriptional regulation of protein abundance. Chromatin immunoprecipitation DNA sequencing (ChIP-seq) and Hi-C chromatin immunoprecipitation (HiChIP) revealed the presence of androgen-activated AR-binding regions and long-distance AR-mediated loops at these genes.
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Marzec J, Ross-Adams H, Pirrò S, Wang J, Zhu Y, Mao X, Gadaleta E, Ahmad AS, North BV, Kammerer-Jacquet SF, Stankiewicz E, Kudahetti SC, Beltran L, Ren G, Berney DM, Lu YJ, Chelala C. The Transcriptomic Landscape of Prostate Cancer Development and Progression: An Integrative Analysis. Cancers (Basel) 2021; 13:345. [PMID: 33477882 PMCID: PMC7838904 DOI: 10.3390/cancers13020345] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 01/07/2021] [Accepted: 01/12/2021] [Indexed: 11/16/2022] Open
Abstract
Next-generation sequencing of primary tumors is now standard for transcriptomic studies, but microarray-based data still constitute the majority of available information on other clinically valuable samples, including archive material. Using prostate cancer (PC) as a model, we developed a robust analytical framework to integrate data across different technical platforms and disease subtypes to connect distinct disease stages and reveal potentially relevant genes not identifiable from single studies alone. We reconstructed the molecular profile of PC to yield the first comprehensive insight into its development, by tracking changes in mRNA levels from normal prostate to high-grade prostatic intraepithelial neoplasia, and metastatic disease. A total of nine previously unreported stage-specific candidate genes with prognostic significance were also found. Here, we integrate gene expression data from disparate sample types, disease stages and technical platforms into one coherent whole, to give a global view of the expression changes associated with the development and progression of PC from normal tissue through to metastatic disease. Summary and individual data are available online at the Prostate Integrative Expression Database (PIXdb), a user-friendly interface designed for clinicians and laboratory researchers to facilitate translational research.
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Affiliation(s)
- Jacek Marzec
- Bioinformatics Unit, Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; (J.M.); (S.P.); (J.W.); (E.G.)
| | - Helen Ross-Adams
- Bioinformatics Unit, Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; (J.M.); (S.P.); (J.W.); (E.G.)
| | - Stefano Pirrò
- Bioinformatics Unit, Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; (J.M.); (S.P.); (J.W.); (E.G.)
| | - Jun Wang
- Bioinformatics Unit, Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; (J.M.); (S.P.); (J.W.); (E.G.)
| | - Yanan Zhu
- Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; (Y.Z.); (X.M.); (S.-F.K.-J.); (E.S.); (S.C.K.); (D.M.B.); (Y.-J.L.)
| | - Xueying Mao
- Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; (Y.Z.); (X.M.); (S.-F.K.-J.); (E.S.); (S.C.K.); (D.M.B.); (Y.-J.L.)
| | - Emanuela Gadaleta
- Bioinformatics Unit, Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; (J.M.); (S.P.); (J.W.); (E.G.)
| | - Amar S. Ahmad
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine, Queen Mary University of London, London EC1M 6BQ, UK; (A.S.A.); (B.V.N.)
| | - Bernard V. North
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine, Queen Mary University of London, London EC1M 6BQ, UK; (A.S.A.); (B.V.N.)
| | - Solène-Florence Kammerer-Jacquet
- Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; (Y.Z.); (X.M.); (S.-F.K.-J.); (E.S.); (S.C.K.); (D.M.B.); (Y.-J.L.)
| | - Elzbieta Stankiewicz
- Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; (Y.Z.); (X.M.); (S.-F.K.-J.); (E.S.); (S.C.K.); (D.M.B.); (Y.-J.L.)
| | - Sakunthala C. Kudahetti
- Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; (Y.Z.); (X.M.); (S.-F.K.-J.); (E.S.); (S.C.K.); (D.M.B.); (Y.-J.L.)
| | - Luis Beltran
- Department of Pathology, Barts Health NHS, London E1 F1R, UK;
| | - Guoping Ren
- Department of Pathology, The First Affiliated Hospital, Zhejiang University Medical College, Hangzhou 310058, China;
| | - Daniel M. Berney
- Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; (Y.Z.); (X.M.); (S.-F.K.-J.); (E.S.); (S.C.K.); (D.M.B.); (Y.-J.L.)
- Department of Pathology, Barts Health NHS, London E1 F1R, UK;
| | - Yong-Jie Lu
- Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; (Y.Z.); (X.M.); (S.-F.K.-J.); (E.S.); (S.C.K.); (D.M.B.); (Y.-J.L.)
| | - Claude Chelala
- Bioinformatics Unit, Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; (J.M.); (S.P.); (J.W.); (E.G.)
- Centre for Computational Biology, Life Sciences Initiative, Queen Mary University London, London EC1M 6BQ, UK
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