Dissect the impact, safety and effectiveness of gene therapy at the whole organismal level by cell-free DNA signatures

Gene therapy (GT) with integrative vectors has emerged as a revolutionary intervention for the treatment of inherited and acquired disorders.

Despite the great achievements, a major challenge pertains to the heterogeneity of responses that can be obtained in patients.

The success of these applications critically depends on the ability of engineered cells to functionally integrate within the patients’ tissues to re-establish the physiological functions.

Intrinsic features of the cellular drug product, and inter-individual factors present at the time or after cell infusion may modulate the clinical outcome. The proposed investigation aims at characterizing cell-free (cfDNA) signatures in patients who underwent GT.

Epigenetic studies on cfDNA will capture the organism-wide changes induced by disease progression and consequent to the treatment in a non-invasive fashion.

Furthermore, the retrieval of integration sites on cfDNA will provide molecular insights into the activity, clonality and persistence of engineered cells in peripheral organs.

The translational relevance of this proposal will be directly assessed in unique clinical settings represented by patients treated with hematopoietic stem cell GT for the correction of inherited metabolic disorders, and with engineered T-cells to fight hematological and solid tumors.

By correlating patient-derived cfDNA signatures with clinical variables outcomes, I will establish if these analyses can predict the impact of engineered cells at the whole organismal level potentially highlighting mechanisms of therapeutic success and failure that have not yet been explored.

The advanced knowledge gained with this project may prompt a more accurate diagnosis evaluation, assist in selecting patients who will benefit from GT, and provide early insights on the efficacy and toxicity of cellular therapies guiding for a more personalized therapeutic intervention to reduce inter-individual variability.