Synergistic interplay of morphology and metabolic activity rule response to CAR-T cells in B-cell lymphomas

TL;DR

This study combines mechanistic modeling and imaging data analysis to understand how tumor shape and metabolic activity influence CAR T-cell therapy outcomes in B-cell lymphomas, aiming to identify biomarkers for treatment response.

Contribution

It introduces a novel mechanistic model that incorporates tumor morphology and metabolism, linking these factors to therapy efficacy and patient prognosis.

Findings

Irregular tumor shapes and high proliferation rates can impair CAR T-cell effectiveness.

Imaging features like sphericity and SUV correlate with progression-free survival.

Data-driven models can help identify patients at higher risk of disease progression.

Abstract

Cellular immunotherapies are one of the mainstream cancer treatments unveiling the power of the patient's immune system to fight tumors. CAR T-cell therapy, based on genetically engineered T cells, has demonstrated significant potential in treating hematological malignancies, including B-cell lymphomas. This treatment has complex longitudinal dynamics due to the interplay of different T-cell phenotypes (e.g. effector and memory), the expansion of the drug and the cytotoxic effect on both normal and cancerous B-cells, the exhaustion of the immune cells, the tumor immunosupressive environments, and more. Thus, the outcome of the therapy is not yet well understood leading to a variety of responses ranging from sustained complete responses, different types of partial responses, or no response at all. We developed a mechanistic model for the interaction between CAR T- and cancerous B-cells, accounting for the role of the tumor morphology and metabolic status. The simulations showed that lesions with irregular shapes and high proliferation could contribute to long term progression by potentially increasing their immunosuppressive capabilities impairing CAR T-cell efficacy. We analyzed 18F-FDG PET/CT imaging data from 63 relapsed/refractory diffuse large B-cell lymphoma receiving CAR T-cells, quantifying radiomic features including tumor sphericity and lesion aggressiveness through standardized uptake values (SUV). Statistical analyses revealed significant correlations between these metrics and progression-free survival (PFS), emphasizing that individual lesions with complex morphology and elevated metabolism play a critical role in shaping long-term treatment outcomes. We demonstrated the potential of using data-driven mathematical models in finding molecular-imaging based biomarkers to identify lymphoma patients treated with CAR T-cell therapy having higher risk of disease progression.