Plasma epigenomic profiling to reveal molecular correlates of response and resistance to 177Lu-PSMA-617 in metastatic castration-resistant prostate cancer (mCRPC).

J Jacob E. Berchuck P Praful Ravi (Dana-Farber Cancer Institute, Boston, MA) A Anthony D'Ippolito (Precede Biosciences, Boston, MA) A Aparna Gorthi H Hunter Savignano (Dana-Farber Cancer Institute, Boston, MA) H Hailey Stoltenberg (Dana-Farber Cancer Institute, Boston, MA) B Baovy Nguyen Tran (Precede Biosciences, Boston, MA) T Tyrone Tamakloe (Precede Biosciences, Boston, MA) C Corrie Painter (Precede Biosciences, Boston, MA) K Kristian Cibulskis N Nicole Kramer (Precede Biosciences, Boston, MA) J Jenna Wurster (Precede Biosciences, Boston, MA) C Charlene O'Brien (Precede Biosciences, Boston, MA) B Barbara Bueno Álvarez (Precede Biosciences, Boston, MA) M Mike Zhong (Precede Biosciences, Boston, MA) K Kyle Gowen (Precede Biosciences, Boston, MA) M Matthew L Eaton (Precede Biosciences, Boston, MA) J J. Carl Barrett H Heather Jacene (Dana-Farber Cancer Institute, Boston, MA)

Abstract

5074 Background: The PSMA-directed radioligand therapy, 177Lu-PSMA-617, is the most recent FDA approved therapy in mCRPC. Despite prolonging progression-free survival (PFS) and overall survival (OS) at a population level, response to therapy is heterogeneous and resistance remains poorly understood. Benchmarking molecular correlates of clinical outcomes following 177Lu-PSMA-617 could provide critical insights into predicting response and resistance to therapy. We applied a multimodal epigenomic liquid biopsy platform to plasma samples from mCRPC patients treated with 177Lu-PSMA-617 to characterize molecular features associated with treatment response. Methods: Baseline plasma samples were collected from patients with mCRPC at the time of PSMA PET imaging and initiation of 177Lu-PSMA-617 therapy. Epigenomic profiling of genome-wide signals from promoters, enhancers, and DNA methylation was performed on 1 mL of plasma (N=85, ctDNA ≥ 0.5%). Plasma epigenomic signals were analyzed to evaluate pathway activity, their association with treatment response using Cox proportional hazards model and neuroendocrine transformation. Response to 177Lu-PSMA-617 was determined by investigator-assessed clinical-radiographic (CR)-PFS. Results: We observed a significant association between predicted PSMA PET SUV mean from plasma epigenomic signals (using a previously derived model) and response to 177Lu-PSMA-617 (hazard ratio [HR] = 0.27, P<0.05). Further, unbiased analysis of plasma epigenomic signal across the genome identified FOLH1 (the gene encoding PSMA) as being significantly associated with CR-PFS (P<0.05). Low circulating tumor fraction was also independently associated with favorable CR-PFS (HR = 0.42, P<0.05). Pathway analysis identified activation of estrogen signalling and cellular plasticity to be associated with shorter CR-PFS, and immune signalling gene signatures to be associated with longer CR-PFS (all FDR<0.1). A subset of patients (n=4) exhibited increased plasma epigenomic signal at neuroendocrine genes, such as CHGA , DLL3 and SEZ6 . While too small to draw statistical conclusions, elevated neuroendocrine gene activity in plasma was associated with numerically shorter OS. Conclusions: Epigenomic profiling of plasma cfDNA enabled minimally-invasive characterization of molecular correlates of response and resistance, identifying genes and pathways associated with favorable and poor outcomes to 177Lu-PSMA-617 in mCRPC. By providing real-time insights into tumor biology and therapeutic efficacy, this platform supports precision medicine approaches for optimizing outcomes in PSMA-targeted therapies.

Article Details

Volume / Issue Vol. 43, Issue 16_suppl
Published June 01, 2025
Pages 5074-5074
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (19)

J

Jacob E. Berchuck

P

Praful Ravi

Dana-Farber Cancer Institute, Boston, MA

A

Anthony D'Ippolito

Precede Biosciences, Boston, MA

A

Aparna Gorthi

H

Hunter Savignano

Dana-Farber Cancer Institute, Boston, MA

H

Hailey Stoltenberg

Dana-Farber Cancer Institute, Boston, MA

B

Baovy Nguyen Tran

Precede Biosciences, Boston, MA

T

Tyrone Tamakloe

Precede Biosciences, Boston, MA

C

Corrie Painter

Precede Biosciences, Boston, MA

K

Kristian Cibulskis

N

Nicole Kramer

Precede Biosciences, Boston, MA

J

Jenna Wurster

Precede Biosciences, Boston, MA

C

Charlene O'Brien

Precede Biosciences, Boston, MA

B

Barbara Bueno Álvarez

Precede Biosciences, Boston, MA

M

Mike Zhong

Precede Biosciences, Boston, MA

K

Kyle Gowen

Precede Biosciences, Boston, MA

M

Matthew L Eaton

Precede Biosciences, Boston, MA

J

J. Carl Barrett

H

Heather Jacene

Dana-Farber Cancer Institute, Boston, MA