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Lutetium-177–PSMA-617 or cabazitaxel in metastatic prostate cancer: circulating tumor DNA analysis of the randomized phase 2 TheraP trial

Abstract

The prostate-specific membrane antigen (PSMA)-targeted radioligand [¹⁷⁷Lu]Lu–PSMA-617 is a new standard treatment for metastatic castration-resistant prostate cancer (mCRPC), but predictive genomic biomarkers informing its rational use are unknown. We performed detailed dissection of prostate cancer driver genes across 290 serial plasma cell-free DNA samples from 180 molecular imaging-selected patients with mCRPC from the randomized TheraP trial of [¹⁷⁷Lu]Lu–PSMA-617 (n = 97) versus cabazitaxel chemotherapy (n = 83). The primary endpoint was PSA50 biochemical response, with secondary endpoints of progression-free survival (PFS) and overall survival (OS). In this post-hoc biomarker analysis, a low pretreatment circulating tumor DNA (ctDNA) fraction predicted a superior biochemical response (100% versus 58%, P = 0.0067) and PFS (median 14.7 versus 6.0 months; hazard ratio 0.12, P = 2.5 × 10−4) on [¹⁷⁷Lu]Lu–PSMA-617 independent of predictive PSMA–positron emission tomography imaging parameters, although this benefit did not extend to OS. Deleterious PTEN alterations were associated with worse PFS and OS on cabazitaxel, whereas ATM defects were observed in select patients with favorable [¹⁷⁷Lu]Lu–PSMA-617 outcomes. Comparing pretreatment and progression ctDNA revealed population flux but no evidence that alterations in individual mCRPC genes (or FOLH1) are dominant causes of acquired [¹⁷⁷Lu]Lu–PSMA-617 or cabazitaxel resistance. Our results nominate new candidate biomarkers for [¹⁷⁷Lu]Lu–PSMA-617 selection and ultimately expand the mCRPC predictive biomarker repertoire. We anticipate our ctDNA fraction-aware analytical framework will aid future precision management strategies for [¹⁷⁷Lu]Lu–PSMA-617 and other PSMA-targeted therapeutics. ClinicalTrials.gov identifier: NCT03392428.

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Fig. 1: Study design and baseline clinical genomic correlates.
Fig. 2: Clinical outcomes by pretreatment ctDNA%.
Fig. 3: Genomic landscape of docetaxel and ARPI-treated mCRPC.
Fig. 4: Clinical outcomes by PTEN, TP53 and AR alteration status.
Fig. 5: Clinical outcomes by AR copy number and DDR defects.
Fig. 6: Resistance alterations.

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Data availability

The hg38 human reference genome was downloaded from UCSC. Germline variant population frequency is available at gnomAD v.3.0 (https://gnomad.broadinstitute.org/). ANZUP is obligated to protect the rights and privacy of trial participants, thereby necessitating restricted access to patient-level clinical and genomic sequencing data. Deidentified participant sequencing and select clinical data will be made available to researchers who are registered with an appropriate institution following publication. Methodologically sound proposals for any purpose will be considered by the trial executive committee who will have the right to review and comment on any draft manuscripts before publication. Proposals should be directed to michael.hofman@petermac.org. To gain access, data requesters will be required to sign a data access agreement. Timeframe for data access will be subject to ANZUP policy and process. Data supporting the findings of this study are available in the article in Supplementary Tables 111. Source data are provided with this paper.

Code availability

Our complete ctDNA somatic variant calling pipeline is available on GitHub (https://github.com/annalam/cfdna-wgs-manuscript-code) and is described in detail in a previous publication12. No additional custom software was utilized for any analysis performed herein.

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Acknowledgements

The TheraP trial (ANZUP 1603) is a collaboration between the ANZUP Trials Group, the NHMRC Clinical Trials Centre, University of Sydney and the Australasian Radiopharmaceutical Trials Network (ARTnet) in partnership with the Prostate Cancer Foundation of Australia with support from ANSTO, Endocyte (a Novartis company), Movember, The Distinguished Gentleman’s Ride, It’s a Bloke Thing and CAN4CANCER. ANZUP receives infrastructure support from the Australian government through Cancer Australia (Support for Cancer Clinical Trials Program). This correlative research study was primarily supported by the Prostate Cancer Foundation via a 2023 PCF Challenge Award to A.W.W. Additional funding support was also received from a Terry Fox New Frontiers Program Project Grant and a Canadian Cancer Society Challenge Grant (grant no. 707339). E.M.K. is supported by a Prostate Cancer Foundation Young Investigator Award and an ANZUP Synchrony Fellowship. S.H.T. is supported by a Prostate Cancer Foundation Young Investigator Award and Michael Smith Health Research BC Trainee Award. J.P.B. is supported by a Prostate Cancer Foundation Young Investigator Award and PhD support through an Australian Government Research Training Program Scholarship. A.M.S. was supported by an NHMRC Investigator Fellowship (APP1177837). I.D.D. is supported by an NHMRC Practitioner Fellowship (APP1102604). M.S.H. acknowledges philanthropic and government grant support from the Prostate Cancer Foundation, the Peter MacCallum Foundation and a NHMRC Investigator Grant and Movember. S.S. is supported by the NHMRC and additionally acknowledges grant support from the Prostate Cancer Foundation and the Peter MacCallum Foundation. The NHMRC Clinical Trials Centre was supported by NHMRC Program Grants 1037786 and 1150467. 177Lu was supplied by ANSTO. Endocyte provided PSMA-11 and PSMA-617, and additional funding support. We acknowledge and thank the 200 patients for their participation in the TheraP study; and the principal investigators, coinvestigators, study coordinators, nurses, radiopharmacists and chemists and nuclear medicine technologists at the 11 centers across Australia for their dedication and enthusiasm. We also thank members and staff of the ANZUP Board, Scientific Advisory Committee, Prostate Cancer Subcommittee, Consumer Advisory Panel and Independent Data Safety and Monitoring Committee; NHMRC Clinical Trials Centre; and ARTnet.

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Contributions

Conceptualization: E.M.K., L.E., A.J.M., I.D.D., M.S.H., A.A.A. and A.W.W. Methodology: E.M.K., S.W.S.N., S.H.T., M.A., C.H. and A.W.W. Software: E.M.K., S.W.S.N., S.H.T., M.A., C.H. and A.W.W. Validation: E.M.K., S.W.S.N., S.H.T., C.H. and A.W.W. Formal analysis: E.M.K., S.W.S.N., S.H.T., M.A., C.H. and A.W.W. Investigation: E.M.K., S.W.S.N., S.H.T., G.D., C.H. and A.W.W. Resources: M.A., I.D.D., M.S.H., A.A.A. and A.W.W. Data curation: E.M.K., S.W.S.N., S.H.T., S.S., G.D., C.H. and A.W.W. Writing—original draft: E.M.K., S.W.S.N., S.H.T., C.H. and A.W.W. Writing—review and editing: E.M.K., S.W.S.N., S.H.T., L.E., S.S., J.P.B., A.I., A.M.J., R.J.F., V.S., S.-T.L., A.M.S., A.J.M., M.R.S., M.A., C.H., I.D.D., M.S.H., A.A.A. and A.W.W. Visualization: E.M.K., S.W.S.N., S.H.T., C.H. and A.W.W. Supervision: I.D.D., M.S.H., A.A.A. and A.W.W. Project administration: E.M.K. V.S., I.D.D., M.S.H., A.A.A. and A.W.W. Funding acquisition: I.D.D., M.S.H., A.A.A. and A.W.W.

Corresponding authors

Correspondence to Ian D. Davis, Michael S. Hofman, Arun A. Azad or Alexander W. Wyatt.

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Competing interests

E.M.K. has consulted or served in an advisory role for Astellas Pharma, Janssen and Ipsen, received travel funding from Astellas Pharma, Pfizer, Ipsen and Roche, received honoraria from Janssen, Ipsen, Astellas Pharma and Research Review, and received research funding from Astellas Pharma (institutional) and AstraZeneca (institutional). L.E. has consulted or served in an advisory role for Noxopharm and Clarity Pharmaceuticals, participated in a speakers’ bureau for Janssen Oncology, Mundipharma and Astellas Pharma, and received research funding from Noxopharm (institutional) and Novartis (institutional). S.S. has consulted or served in an advisory role for AstraZeneca, Bristol-Myers Squibb, Merck Sharp & Dohme, Novartis, Skyline Diagnostics and AbbVie, received honoraria from Bristol-Myers Squibb (institutional), Merck (institutional), AstraZeneca (institutional) and Janssen (institutional), and received research funding from Amgen (institutional), AstraZeneca (institutional), Merck (institutional), Endocyte/Advanced Accelerator Applications (institutional), Roche/Genentech (institutional), Novartis (institutional), Pfizer (institutional) and Senhwa Biosciences (institutional). A.I. has consulted or served in an advisory role for Novartis, Lantheus, Curium, ITM, Bayer, Boston Scientific, Ambrx/J&J (institutional), and received research funding from NIH (institutional), Novartis (institutional), SNMMI (institutional) and ACR (institutional). A.M.J. has consulted or served in an advisory role for Janssen Oncology, Ipsen, AstraZeneca, Sanofi, Pfizer, Novartis, Merck Serono, Eisai, IDEAYA Biosciences, IQvia, Bayer, Astellas Pharma, Grey Wolf Therapeutics, Medison and Starpharma, has a patent or received royalties with Cancer Therapeutic Methods, owns stock or holds ownership interests in Pricilium Therapeutics and Opthea, and receives research funding from Bristol-Myers Squibb (institutional), Janssen Oncology (institutional), Merck Sharpe & Dohme (institutional), Mayna Pharma (institutional), Roche/Genentech (institutional), Bayer (institutional), Lilly (institutional), Pfizer (institutional), AstraZeneca (institutional) and Corvus Pharmaceuticals (institutional). R.J.F. consulted or served in an advisory role for AIQ Solutions, receives research funding from AIQ Solutions, and has an immediate family member employed by and owns stock in AIQ Solutions. A.M.S. has consulted or served in an advisory role for ImmunOs Therapeutics and Imagion Biosystems, has an institutional patent relating to antibodies to EGFR, HER2, PDGF-CC, FN-14, GM-CSF, EphA3, owns stock or holds ownership interests in Paracrine Therapeutics and Certis Therapeutics, and received research funding from Telix Pharmaceuticals (institutional), Curis (institutional), Isotopen Technologien (institutional), Adalta (institutional), Fusion Pharmaceuticals (institutional), AstraZeneca (institutional), EMD Serono (institutional), Cyclotek (institutional), AVID/Lilly (institutional), Merck (institutional), Humanigen (institutional) and Antengene (institutional). M.R.S. has received research funding from Astellas Pharma (institutional), Bayer (institutional), Medivation (institutional), Pfizer (institutional), AstraZeneca (institutional), Bristol-Myers Squibb (institutional), Roche (institutional), Amgen (institutional), Merck Sharpe & Dohme (institutional), Tilray (institutional), BeiGene (institutional) and Novartis (institutional). M.A. is compensated for a leadership role in Fluivia and owns stock in Fluivia. S.H.T. has received honoraria from Bayer. I.D.D. is the unremunerated chair of ANZUP Cancer Trials Group, and has received research funding from Astellas Pharma (institutional), Pfizer (institutional), Roche/Genentech (institutional), MSD Oncology (institutional), AstraZeneca (institutional), Janssen Oncology (institutional), Eisai (institutional), Bayer (institutional), Amgen (institutional), Bristol-Myers Squibb (institutional), Movember Foundation (institutional), Exelixis (institutional), Ipsen (institutional), Seagen (institutional) and ESSA (institutional). M.S.H. has consulted or served in an advisory role for Janssen, MSD and Novartis, received travel funding from Novartis and Debiopharm Group, and received research funding from Bayer (institutional), Novartis (institutional), Isotopia Molecular Imaging (institutional) and Debiopharm Group (institutional). A.A.A. has consulted or served in an advisory role for Astellas Pharma, Novartis, Janssen, Sanofi, AstraZeneca, Pfizer, Bristol-Myers Squibb, Tolmar, Telix Pharmaceuticals, Merck Sharpe & Dohme, Bayer, Ipsen, Merck Serono, Amgen, Noxopharma, Aculeus Therapeutics and Daiichi Sankyo, participated in a speakers’ bureau for Astellas Pharma, Novartis, Amgen, Bayer, Janssen, Ipsen, Bristol-Myers Squibb and Merck Serono, received travel funding from Astellas Pharma, Sanofi, Merck Serono, Amgen, Janssen, Tolmar, Pfizer, Bayer and Hinova Pharmaceuticals, received honoraria from Janssen, Astellas Pharma, Novartis, Tolmar, Amgen, Pfizer, Bayer, Telix Pharmaceuticals, Bristol-Myers Squibb, Merck Serono, AstraZeneca, Sanofi, Ipsen, Merck Sharpe & Dohme, Noxopharm, Aculeus Therapeutics and Daiichi Sankyo, and received research funding Astellas Pharma (institutional), Merck Serono (institutional), Novartis (institutional), Pfizer (institutional), Bristol-Myers Squibb (institutional), Sanofi (institutional), AstraZeneca (institutional), GlaxoSmithKline (institutional), Aptevo Therapeutics (institutional), MedImmune (institutional), Bionomics (institutional), Synthorx (institutional), Astellas Pharma (institutional), Ipsen (institutional), Merck Serono (institutional), Lilly (institutional), Gilead Sciences (institutional), Exelixis (institutional), MSD (institutional) and Hinova Pharmaceuticals (institutional). A.W.W. has received honoraria from Janssen, Astellas Pharma, AstraZeneca, Merck, Bayer, Pfizer and EMD Serono, and received research funding from Promontory Therapeutics (institutional), ESSA Pharma (institutional) and Tyra Biosciences (institutional). The other authors declare no competing interests.

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Extended data

Extended Data Fig. 1 CONSORT diagram for sequencing and enrolment.

CONSORT diagram of participant and sample flow culminating in the formation of the biomarker participant population.

Extended Data Fig. 2 ctDNA% versus baseline PET imaging variables.

Correlation between ctDNA% and four quantitative PET imaging variables. Spearman’s rho (two-sided) is reported for each comparison, with p-values adjusted using Bonferroni correction (α = 0.05, m = 3; correcting for three pairwise comparisons within each imaging modality). A grey line represents the linear regression to illustrate the bivariate relationships. FDG, 2-[18F]fluoro-2-deoxy-D-glucose; MTV, metabolic tumour volume; PSMA, prostate-specific membrane antigen; SUV, standardised uptake value.

Extended Data Fig. 3 PTEN, TP53, and BRCA2 structural variants.

Examples of structural variants and associated focal copy number alterations in (a) PTEN, (b) TP53, and (c) BRCA2. SNP, single nucleotide polymorphism.

Extended Data Fig. 4 Relationship between ctDNA% and molecular imaging variables by PTEN and TP53 status.

Correlation between ctDNA% and two quantitative PET imaging variables (PSMA SUVmean - top, FDG MTV - bottom), stratified by genomic alteration status (PTEN - left, TP53 - right).

Extended Data Fig. 5 PFS and OS by TP53 and PTEN alteration status in all-comers.

Kaplan-Meier estimates of progression-free survival and overall survival stratified by (a) TP53 alteration status and (b) PTEN alteration status. Each survival curve includes estimates for three-levels: ctDNA <2%, intact status, and altered status. In-set summary bar plots in the progression-free survival curves represent the proportion of patients that experienced a PSA50 and PSA90 response. An alteration is defined as any mutation(s) or structural variant(s), deep deletion, or expected null gene status. Monoallelic deletions in isolation were not considered altered. In-set tables show univariable hazard ratios from a Cox proportional hazards model. CI, confidence interval; HR, hazard ratio; mPFS, median progression-free survival; NR, not reached; OS, overall survival; PFS, progression-free survival; PSA, prostate-specific antigen; Ref, reference.

Extended Data Fig. 6 PFS and OS by AR alteration status in all-comers.

Kaplan-Meier estimates of progression-free survival and overall survival stratified by (a) AR gain (defined as ≥4 absolute AR copies) status, (b) presence of AR LBD GSRs, and (c) AR LBD mutation status. Each survival curve includes estimates for three-levels: ctDNA <2%, intact status, and altered status. In-set summary bar plots in the progression-free survival curves represent the proportion of patients that experienced a PSA50 and PSA90 response. In-set tables show univariable hazard ratios from a Cox proportional hazards model. CI, confidence interval; HR, hazard ratio; GSR, gene structural rearrangement; LBD, ligand binding domain; mPFS, median progression-free survival; NR, not reached; OS, overall survival; PFS, progression-free survival; PSA, prostate-specific antigen; Ref, reference.

Extended Data Fig. 7 Clinical outcomes by baseline clinical variables in all-comers.

Forest plots show post-hoc sensitivity analyses for (a) PSA50 response, (b) progression-free survival, and (c) overall survival endpoints according to baseline clinical variables. The ‘All patients’ category includes those in the all-comers biomarker population (n = 178). ALP, alkaline phosphatase; ECOG PS, Eastern Cooperative Oncology Group performance status; FDG, 2-[18F]fluoro-2-deoxy-D-glucose; HR, hazard ratio; MTV, metabolic tumour volume; PSA, prostate-specific antigen; PSMA, prostate-specific membrane antigen; Ref, reference; SUV, standardised uptake value.

Extended Data Fig. 8 PSA response by DDR alterations.

Best PSA response in the four most commonly altered DNA damage repair-related gene categories: ATM, BRCA1/2, CDK12, and mismatch repair. PSA response for each gene category is expressed at a per-treatment arm level, and further stratified by either (a) PSMA SUVmean (<10 and ≥10) or (b) ctDNA% level (medium [2–30%] and high [>30%]). MMR, mismatch repair; PSA, prostate-specific antigen; PSMA, prostate-specific membrane antigen; SUV, standardised uptake value.

Extended Data Fig. 9 Copy number status in tumour suppressor genes across consecutive samples.

Correlation of the copy number status of tumour suppressor genes TP53, PTEN and RB1 between consecutive ctDNA samples from the same patient. Each dot represents a consecutive sample pair (baseline and progression). Pearson’s correlation coefficient (two-sided) is reported for each comparison.

Source data

Supplementary information

Supplementary Information

Consortia authorship, collaborators, list of key sponsors and personnel, and supplementary tables.

Reporting Summary

Supplementary Tables

List of all mutations and copy number alterations.

Source data

Source Data Fig. 3

Statistical source data (genomics).

Source Data Fig. 6

Statistical source data (genomics).

Source Data Extended Data Fig. 9

Statistical source data (genomics).

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Kwan, E.M., Ng, S.W.S., Tolmeijer, S.H. et al. Lutetium-177–PSMA-617 or cabazitaxel in metastatic prostate cancer: circulating tumor DNA analysis of the randomized phase 2 TheraP trial. Nat Med 31, 2722–2736 (2025). https://doi.org/10.1038/s41591-025-03704-9

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