(P 421) CHARACTERIZATION OF INTRA-PATIENT, INTER-LESIONAL RESPONSE AND RESISTANCE DYNAMICS IN METASTATIC, FUSION-POSITIVE RHABDOMYOSARCOMA: A REPORT FROM THE NATIONAL PEDIATRIC CANCER FOUNDATION

Objective: Metastatic rhabdomyosarcoma harboring a PAX::FOXO1 fusion (aka fusion-positive rhabdomyosarcoma, FPRMS) frequently presents with a diffuse metastatic burden that dramatically responds to initial systemic therapy but is almost inevitably followed by recurrence and eventual death. The intra-patient, inter-lesional dynamics of metastatic FPRMS in response to systemic therapy has not been extensively investigated and may lead to improved understanding of resistance development and allow optimization of systemic therapy intensity and timing to maximize treatment response and extend time to recurrence.

Methods: MCC20339 (NCT04388839) is an actively accruing clinical trial for newly diagnosed, metastatic FPRMS with multiple therapeutic arms designed based on principles of evolutionary dynamics. One arm of the trial (Arm C) administers intermittent chemotherapy with vincristine, actinomycin, and cyclophosphamide (VAC), with chemotherapy timing and dose determined by frequent volumetric evaluation of radiographic response to therapy (aka adaptive therapy, Figure 1). Adaptive therapy aims to exploit competitive interactions between bulk, therapy-sensitive and minority, therapy-resistant subclones within a cancer by managing rather than eliminating the dominant therapy-sensitive subclones to prevent or delay the clinical emergence of therapy-resistant subclones.

Arm C affords the opportunity to evaluate specific tumor growth, response, and resistance dynamics of multiple sites of disease within a patient undergoing treatment. MCC20339 includes an aim to generate mathematical modeling of disease response and resistance. We have developed several models using ordinary differential equations to account for tumor growth, drug death, therapy resistance, and drug resensitization in FPRMS. Briefly, the models make different assumptions about how drug resistance arises and the dynamics of resistant tumor cells, as well as the effects of removing therapy. For each model, the parameters for these processes are fit from the patient’s data and updated upon collecting additional imaging scans.

Results: A patient with metastatic FPRMS enrolled on Arm C in July 2023. Initial disease evaluation revealed a presumed forearm primary tumor and extensive metastatic disease burden affecting multiple organs, lymph nodes, and bones. The patient received two cycles of VAC with a dramatic reduction in radiologic burden of disease. To date, the patient has received ten cycles of VAC therapy (two at full-doses and eight at reduced doses) over 11 months and remains on trial therapy at the time of this abstract with a lower disease burden than at initial presentation. A treatment summary and cumulative doses of therapy are shown in Table 1.

We prospectively selected nine lesions for volumetric monitoring over time and used these measurements to fit mathematical model parameters (Figure 2). Chemotherapy dose reductions added an extra fitting parameter, that of reduced drug effect. Of interest was the high variability in growth rates, drug efficacy, and rates of resistance seen in each lesion (Figure 3). However, some consistent trends in the data allowed the determination of which lesions were most likely to fail the adaptive therapy, which provides information that may guide future treatment decisions (e.g., which lesions to target with radiation prior to chemotherapy failure). Additional work using retrospective patient data may increase the accuracy of the model assumptions that contribute to variability.

Conclusion: Adaptive therapy in metastatic FPRMS is being evaluated on a current clinical trial. Mathematical modelling of a patient currently on trial therapy demonstrates feasibility of modelling an individual patient’s disease response in a dynamic fashion to with potential to guide adaptive therapy decisions in real time.