2024 Stewart J. Rahr Foundation – PCF Challenge Award

Optimizing Patient Selection for PSMA Targeted Radiotherapy Using Individual Lesion Characteristics   

Principal Investigators: Glenn Liu, MD (University of Wisconsin – Madison), Robert Jeraj, PhD (University of Wisconsin – Madison)

Co-Investigators: Steve Cho, MD (University of Wisconsin – Madison), Jens Eickhoff, PhD (University of Wisconsin – Madison)

Young Investigator: Johnathan Floberg, MD, PhD (University of Wisconsin – Madison)

Description:

• While PSMA-targeted radioligand therapy ¹⁷⁷Lu-PSMA-617 (Pluvicto®) is approved for patients with PSMA PET-positive metastatic castration resistant prostate cancer (mCRPC), many patients do not complete planned treatment due to early disease progression.  As a result, improved tools are needed to identify patients who will most benefit from this treatment, sparing individuals unlikely to benefit from the risks of therapy.
• ¹⁷⁷Lu-PSMA-617 is prescribed for patients whose tumors express PSMA on PSMA PET scans, with higher expression levels on a patient-level associated with better treatment response.  However, PSMA levels vary in each individual metastases within patients, which contributes to variance in treatment efficacy.  Understanding impact of lesion-level PSMA expression on benefit will allow individualization of when to use ¹⁷⁷Lu-PSMA-617.
• Dr. Glenn Liu and team previously developed a software medical device (TRAWinform IQ) combining artificial intelligence (AI) with advanced image analysis methodology which received FDA clearance in 2018 for identification and quantification of all individual tumor lesions in a patient. 
• In this project, Dr. Liu and team will develop and validate lesion-level AI-based predictive models using FDG PET/CT and PSMA PET/CT to identify patients who will most likely benefit from ¹⁷⁷Lu-PSMA-617, and to evaluate treatment responses to make decisions about treatment continuation. They will also develop and validate uncertainty estimates of these predictive models for ¹⁷⁷Lu-PSMA-617.
• If successful, this project will develop first-in-field lesion-level AI-based predictive biomarkers for: (1) selection of patients that would most likely benefit from ¹⁷⁷Lu-PSMA-617, and (2) identification of patients receiving ¹⁷⁷Lu-PSMA-617 that would benefit from continuation of ¹⁷⁷Lu-PSMA-617, based on lesion-level metrics and change.

What this means to patients: ¹⁷⁷Lu-PSMA-617 (Pluvicto®) is a promising treatment option for mCRPC, however many patients do not benefit from this treatment, or only benefit for a short period of time. Dr. Liu and team are developing AI-based molecular imaging models to identify patients who should receive this treatment using both patient and lesion level information. By understanding which lesions are destined to persist (not respond), future treatment opportunities include early ablation of “resistant lesions” to extend benefit, selecting alternative radionuclide that may bane better treatment effect given the lesion-level parameters, or even pharmacologic manipulation to alter PSMA expression to improve response.